01e_text_embeddings_spacy_wikitext103.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "from fastai.learner import *\n",
    "from fastai.data.all import *\n",
    "from fastai.callback.tracker import SaveModelCallback\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from pathlib2 import Path\n",
    "import numpy as np\n",
    "import random\n",
    "from torch.nn import MSELoss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can download the ebooks [here](https://www.openslr.org/resources/12/original-books.tar.gz).\n",
    "\n",
    "We will need the pretrained embeddings from https://github.com/iamyuanchung/speech2vec-pretrained-vectors. We will use them to compare our results and also to figure out what vocab the authors of the speech2vec paper used for training. Let us start with the latter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv('data/wikitext-103/train.csv', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29539, 1)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "texts = df_train[0].tolist()\n",
    "texts = texts[:2000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/sklearn/utils/deprecation.py:143: FutureWarning: The sklearn.datasets.base module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.datasets. Anything that cannot be imported from sklearn.datasets is now part of the private API.\n",
      "  warnings.warn(message, FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "import logging\n",
    "from six import iteritems\n",
    "from web.datasets.similarity import fetch_MEN, fetch_WS353, fetch_SimLex999\n",
    "from web.embeddings import fetch_GloVe\n",
    "from web.evaluate import evaluate_similarity\n",
    "from web.embedding import Embedding, Vocabulary\n",
    "from gensim.models import Word2Vec\n",
    "from gensim.models import KeyedVectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37622"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "speech2vec = KeyedVectors.load_word2vec_format('../speech2vec-pretrained-vectors/speech2vec/50.vec', binary=False) \n",
    "\n",
    "vocab = set(speech2vec.vocab.keys())\n",
    "len(vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from joblib import Parallel, delayed\n",
    "from functools import partial\n",
    "from spacy.util import minibatch\n",
    "import spacy\n",
    "\n",
    "nlp = spacy.load(\"en_core_web_sm\")\n",
    "\n",
    "batch_size= 200\n",
    "partitions = minibatch(texts, size=batch_size)\n",
    "\n",
    "executor = Parallel(n_jobs=10, backend=\"multiprocessing\", prefer=\"threads\")\n",
    "\n",
    "def transform_texts(nlp, vocab, text):\n",
    "    docs = nlp.tokenizer.pipe(texts)\n",
    "    word_pairs = []\n",
    "    \n",
    "    for doc in docs:\n",
    "        words = [token.text.lower() for token in doc if token.is_alpha]\n",
    "        words = [w if w in vocab else '<UNK>' for w in words]\n",
    "        \n",
    "        for i, word in enumerate(words):\n",
    "            if word == '<UNK>': continue\n",
    "            for offset in [-2, -1, 1, 2]:\n",
    "                if i + offset < 0 or i + offset >= len(words): continue\n",
    "                target_word = words[i+offset]\n",
    "                if target_word == '<UNK>': continue\n",
    "                word_pairs.append([word, target_word])\n",
    "                 \n",
    "    return word_pairs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for doc in docs:\n",
    "#     words = [token.text.lower() for token in doc if token.is_alpha]\n",
    "#     words = [w if w in vocab else '<UNK>' for w in words]\n",
    "    \n",
    "#     for i, word in enumerate(words):\n",
    "#         if word == '<UNK>': continue\n",
    "#         for offset in [-2, -1, 1, 2]:\n",
    "#             if i + offset < 0 or i + offset >= len(words): continue\n",
    "#             target_word = words[i+offset]\n",
    "#             if target_word == '<UNK>': continue\n",
    "#             word_pairs.append([word, target_word])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 55s, sys: 17.7 s, total: 2min 12s\n",
      "Wall time: 4min\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "do = delayed(partial(transform_texts, nlp, vocab))\n",
    "tasks = (do(batch) for batch in partitions)\n",
    "word_pairs_hierarchical = executor(tasks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_pairs = []\n",
    "\n",
    "for pairs in word_pairs_hierarchical: word_pairs += pairs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['is', 'a'],\n",
       " ['a', 'is'],\n",
       " ['a', 'genus'],\n",
       " ['genus', 'a'],\n",
       " ['genus', 'in'],\n",
       " ['genus', 'the'],\n",
       " ['in', 'genus'],\n",
       " ['in', 'the'],\n",
       " ['in', 'family'],\n",
       " ['the', 'genus']]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_pairs[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# np.random.shuffle(word_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183690620"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(word_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['is', 'a'],\n",
       " ['a', 'is'],\n",
       " ['a', 'genus'],\n",
       " ['genus', 'a'],\n",
       " ['genus', 'in'],\n",
       " ['genus', 'the'],\n",
       " ['in', 'genus'],\n",
       " ['in', 'the'],\n",
       " ['in', 'family'],\n",
       " ['the', 'genus'],\n",
       " ['the', 'in'],\n",
       " ['the', 'family'],\n",
       " ['family', 'in'],\n",
       " ['family', 'the'],\n",
       " ['family', 'a'],\n",
       " ['a', 'family'],\n",
       " ['a', 'grouping'],\n",
       " ['a', 'of'],\n",
       " ['grouping', 'a'],\n",
       " ['grouping', 'of']]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_pairs[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab = list(vocab)\n",
    "word2index = {w: i for i, w in enumerate(vocab)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Dataset():\n",
    "    def __init__(self, pairs, length=10_000_000):\n",
    "        self.pairs = pairs\n",
    "        self.len = length\n",
    "    def __len__(self):\n",
    "        return self.len\n",
    "    def __getitem__(self, idx):\n",
    "        source_word, target_word = self.pairs[np.random.randint(len(self.pairs))]\n",
    "        return word2index[source_word], word2index[target_word]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 14 mln -> 180 mln"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183690620"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(word_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_ds = Dataset(word_pairs)\n",
    "valid_ds = Dataset(word_pairs, 200_000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000000, 200000)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_ds), len(valid_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "BS = 2048\n",
    "NUM_WORKERS = 4\n",
    "\n",
    "train_dl = DataLoader(train_ds, BS, NUM_WORKERS, shuffle=True)\n",
    "valid_dl = DataLoader(valid_ds, BS, NUM_WORKERS)\n",
    "\n",
    "dls = DataLoaders(train_dl, valid_dl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Model(Module):\n",
    "    def __init__(self, hidden_size=50):\n",
    "        self.embeddings =nn.Embedding(len(vocab), hidden_size)\n",
    "        self.linear = nn.Linear(hidden_size, len(vocab))\n",
    "            \n",
    "    def forward(self, x):\n",
    "        x = self.embeddings(x)\n",
    "        return self.linear(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = Learner(\n",
    "    dls.cuda(),\n",
    "    Model().cuda(),\n",
    "    loss_func=CrossEntropyLossFlat(),\n",
    "    opt_func=Adam,\n",
    "    metrics=[accuracy]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>6.911878</td>\n",
       "      <td>6.903167</td>\n",
       "      <td>0.094245</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>6.826917</td>\n",
       "      <td>6.809525</td>\n",
       "      <td>0.096670</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>6.772814</td>\n",
       "      <td>6.776364</td>\n",
       "      <td>0.098515</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>6.748465</td>\n",
       "      <td>6.748441</td>\n",
       "      <td>0.098995</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>6.708656</td>\n",
       "      <td>6.715177</td>\n",
       "      <td>0.099920</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>6.700110</td>\n",
       "      <td>6.692660</td>\n",
       "      <td>0.101150</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>6.670153</td>\n",
       "      <td>6.671999</td>\n",
       "      <td>0.100795</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>6.677501</td>\n",
       "      <td>6.669620</td>\n",
       "      <td>0.100570</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>6.644104</td>\n",
       "      <td>6.657688</td>\n",
       "      <td>0.100420</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>6.638129</td>\n",
       "      <td>6.638594</td>\n",
       "      <td>0.101415</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>6.633169</td>\n",
       "      <td>6.638857</td>\n",
       "      <td>0.101560</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>6.628120</td>\n",
       "      <td>6.623160</td>\n",
       "      <td>0.101665</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>6.615932</td>\n",
       "      <td>6.630966</td>\n",
       "      <td>0.101230</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>6.617925</td>\n",
       "      <td>6.608466</td>\n",
       "      <td>0.102895</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>6.597972</td>\n",
       "      <td>6.598041</td>\n",
       "      <td>0.103445</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>6.602977</td>\n",
       "      <td>6.603446</td>\n",
       "      <td>0.102935</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>6.600562</td>\n",
       "      <td>6.599042</td>\n",
       "      <td>0.102660</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>6.585884</td>\n",
       "      <td>6.589365</td>\n",
       "      <td>0.102575</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>6.590660</td>\n",
       "      <td>6.588049</td>\n",
       "      <td>0.102355</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>6.572023</td>\n",
       "      <td>6.583738</td>\n",
       "      <td>0.102185</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>6.588515</td>\n",
       "      <td>6.584647</td>\n",
       "      <td>0.103320</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>6.566707</td>\n",
       "      <td>6.578616</td>\n",
       "      <td>0.103265</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>6.575782</td>\n",
       "      <td>6.571418</td>\n",
       "      <td>0.103115</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>6.578994</td>\n",
       "      <td>6.557122</td>\n",
       "      <td>0.103590</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>6.573166</td>\n",
       "      <td>6.564962</td>\n",
       "      <td>0.104810</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>6.558394</td>\n",
       "      <td>6.561156</td>\n",
       "      <td>0.103540</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>6.555405</td>\n",
       "      <td>6.559977</td>\n",
       "      <td>0.103415</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>6.564699</td>\n",
       "      <td>6.566343</td>\n",
       "      <td>0.103590</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>6.557091</td>\n",
       "      <td>6.559979</td>\n",
       "      <td>0.103750</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>6.569430</td>\n",
       "      <td>6.549287</td>\n",
       "      <td>0.103815</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>6.551260</td>\n",
       "      <td>6.550628</td>\n",
       "      <td>0.102870</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>6.570599</td>\n",
       "      <td>6.556447</td>\n",
       "      <td>0.104600</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>6.556633</td>\n",
       "      <td>6.541326</td>\n",
       "      <td>0.105130</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>6.549679</td>\n",
       "      <td>6.549599</td>\n",
       "      <td>0.104110</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>6.546754</td>\n",
       "      <td>6.540114</td>\n",
       "      <td>0.104785</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>6.547807</td>\n",
       "      <td>6.544338</td>\n",
       "      <td>0.104805</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>6.556248</td>\n",
       "      <td>6.548569</td>\n",
       "      <td>0.103150</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>6.548527</td>\n",
       "      <td>6.537141</td>\n",
       "      <td>0.103585</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>6.540543</td>\n",
       "      <td>6.544613</td>\n",
       "      <td>0.103330</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>6.543300</td>\n",
       "      <td>6.549151</td>\n",
       "      <td>0.103255</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>6.540937</td>\n",
       "      <td>6.542977</td>\n",
       "      <td>0.103845</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>6.550108</td>\n",
       "      <td>6.543509</td>\n",
       "      <td>0.104495</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>6.536345</td>\n",
       "      <td>6.538901</td>\n",
       "      <td>0.102900</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>6.528562</td>\n",
       "      <td>6.540480</td>\n",
       "      <td>0.104045</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>6.532227</td>\n",
       "      <td>6.548687</td>\n",
       "      <td>0.103420</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>6.545248</td>\n",
       "      <td>6.527055</td>\n",
       "      <td>0.104995</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>6.533469</td>\n",
       "      <td>6.537072</td>\n",
       "      <td>0.104640</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>6.545434</td>\n",
       "      <td>6.526211</td>\n",
       "      <td>0.104980</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>6.528752</td>\n",
       "      <td>6.544187</td>\n",
       "      <td>0.103170</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>6.532738</td>\n",
       "      <td>6.532998</td>\n",
       "      <td>0.104295</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50</td>\n",
       "      <td>6.531579</td>\n",
       "      <td>6.538992</td>\n",
       "      <td>0.104060</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>51</td>\n",
       "      <td>6.537718</td>\n",
       "      <td>6.532350</td>\n",
       "      <td>0.104070</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>52</td>\n",
       "      <td>6.534180</td>\n",
       "      <td>6.524691</td>\n",
       "      <td>0.104710</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>53</td>\n",
       "      <td>6.551740</td>\n",
       "      <td>6.530454</td>\n",
       "      <td>0.103270</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>54</td>\n",
       "      <td>6.526588</td>\n",
       "      <td>6.534687</td>\n",
       "      <td>0.103920</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55</td>\n",
       "      <td>6.541762</td>\n",
       "      <td>6.539319</td>\n",
       "      <td>0.104235</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>56</td>\n",
       "      <td>6.545687</td>\n",
       "      <td>6.533277</td>\n",
       "      <td>0.104275</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>57</td>\n",
       "      <td>6.535060</td>\n",
       "      <td>6.533923</td>\n",
       "      <td>0.103480</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>58</td>\n",
       "      <td>6.529228</td>\n",
       "      <td>6.530119</td>\n",
       "      <td>0.104270</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>59</td>\n",
       "      <td>6.525106</td>\n",
       "      <td>6.535258</td>\n",
       "      <td>0.102945</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>60</td>\n",
       "      <td>6.526790</td>\n",
       "      <td>6.539114</td>\n",
       "      <td>0.103100</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>61</td>\n",
       "      <td>6.542925</td>\n",
       "      <td>6.547224</td>\n",
       "      <td>0.103630</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>62</td>\n",
       "      <td>6.539646</td>\n",
       "      <td>6.538191</td>\n",
       "      <td>0.104885</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>63</td>\n",
       "      <td>6.531807</td>\n",
       "      <td>6.540354</td>\n",
       "      <td>0.102675</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>64</td>\n",
       "      <td>6.532178</td>\n",
       "      <td>6.531079</td>\n",
       "      <td>0.102780</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>65</td>\n",
       "      <td>6.526546</td>\n",
       "      <td>6.535516</td>\n",
       "      <td>0.103410</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>66</td>\n",
       "      <td>6.548122</td>\n",
       "      <td>6.524737</td>\n",
       "      <td>0.103755</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>67</td>\n",
       "      <td>6.533246</td>\n",
       "      <td>6.531131</td>\n",
       "      <td>0.104370</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>68</td>\n",
       "      <td>6.542005</td>\n",
       "      <td>6.529123</td>\n",
       "      <td>0.104395</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>69</td>\n",
       "      <td>6.541124</td>\n",
       "      <td>6.520865</td>\n",
       "      <td>0.104180</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>70</td>\n",
       "      <td>6.530611</td>\n",
       "      <td>6.547929</td>\n",
       "      <td>0.102685</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>71</td>\n",
       "      <td>6.526997</td>\n",
       "      <td>6.539859</td>\n",
       "      <td>0.104360</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>72</td>\n",
       "      <td>6.539635</td>\n",
       "      <td>6.537766</td>\n",
       "      <td>0.104025</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>73</td>\n",
       "      <td>6.532441</td>\n",
       "      <td>6.522226</td>\n",
       "      <td>0.104200</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>74</td>\n",
       "      <td>6.535347</td>\n",
       "      <td>6.523766</td>\n",
       "      <td>0.103845</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75</td>\n",
       "      <td>6.535052</td>\n",
       "      <td>6.541876</td>\n",
       "      <td>0.102890</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>76</td>\n",
       "      <td>6.528634</td>\n",
       "      <td>6.525242</td>\n",
       "      <td>0.105875</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>77</td>\n",
       "      <td>6.529060</td>\n",
       "      <td>6.517869</td>\n",
       "      <td>0.105615</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>78</td>\n",
       "      <td>6.529747</td>\n",
       "      <td>6.537069</td>\n",
       "      <td>0.104100</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>79</td>\n",
       "      <td>6.536887</td>\n",
       "      <td>6.538928</td>\n",
       "      <td>0.104290</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>80</td>\n",
       "      <td>6.538122</td>\n",
       "      <td>6.526726</td>\n",
       "      <td>0.104260</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>81</td>\n",
       "      <td>6.526128</td>\n",
       "      <td>6.538083</td>\n",
       "      <td>0.103540</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>82</td>\n",
       "      <td>6.530730</td>\n",
       "      <td>6.542341</td>\n",
       "      <td>0.104470</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>83</td>\n",
       "      <td>6.525475</td>\n",
       "      <td>6.533046</td>\n",
       "      <td>0.104495</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>84</td>\n",
       "      <td>6.533831</td>\n",
       "      <td>6.533871</td>\n",
       "      <td>0.104540</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>85</td>\n",
       "      <td>6.529655</td>\n",
       "      <td>6.533091</td>\n",
       "      <td>0.104340</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>86</td>\n",
       "      <td>6.520028</td>\n",
       "      <td>6.527242</td>\n",
       "      <td>0.104835</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>87</td>\n",
       "      <td>6.536116</td>\n",
       "      <td>6.532333</td>\n",
       "      <td>0.103000</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>88</td>\n",
       "      <td>6.523502</td>\n",
       "      <td>6.528395</td>\n",
       "      <td>0.104775</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>89</td>\n",
       "      <td>6.522158</td>\n",
       "      <td>6.521588</td>\n",
       "      <td>0.104545</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>90</td>\n",
       "      <td>6.538376</td>\n",
       "      <td>6.525882</td>\n",
       "      <td>0.104470</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>91</td>\n",
       "      <td>6.530544</td>\n",
       "      <td>6.527175</td>\n",
       "      <td>0.104445</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>92</td>\n",
       "      <td>6.522489</td>\n",
       "      <td>6.539092</td>\n",
       "      <td>0.103840</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>93</td>\n",
       "      <td>6.535452</td>\n",
       "      <td>6.532729</td>\n",
       "      <td>0.103935</td>\n",
       "      <td>01:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>94</td>\n",
       "      <td>6.528687</td>\n",
       "      <td>6.525846</td>\n",
       "      <td>0.104460</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>95</td>\n",
       "      <td>6.527965</td>\n",
       "      <td>6.526542</td>\n",
       "      <td>0.104340</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>96</td>\n",
       "      <td>6.536592</td>\n",
       "      <td>6.522127</td>\n",
       "      <td>0.104585</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>97</td>\n",
       "      <td>6.534569</td>\n",
       "      <td>6.537545</td>\n",
       "      <td>0.104355</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>98</td>\n",
       "      <td>6.536701</td>\n",
       "      <td>6.524371</td>\n",
       "      <td>0.103255</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>99</td>\n",
       "      <td>6.539051</td>\n",
       "      <td>6.540404</td>\n",
       "      <td>0.103670</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>100</td>\n",
       "      <td>6.525282</td>\n",
       "      <td>6.545290</td>\n",
       "      <td>0.103285</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>101</td>\n",
       "      <td>6.522091</td>\n",
       "      <td>6.534271</td>\n",
       "      <td>0.103655</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>102</td>\n",
       "      <td>6.529117</td>\n",
       "      <td>6.533379</td>\n",
       "      <td>0.104310</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>103</td>\n",
       "      <td>6.525003</td>\n",
       "      <td>6.524312</td>\n",
       "      <td>0.104400</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>104</td>\n",
       "      <td>6.528829</td>\n",
       "      <td>6.541362</td>\n",
       "      <td>0.104355</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>105</td>\n",
       "      <td>6.533306</td>\n",
       "      <td>6.535370</td>\n",
       "      <td>0.104045</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>106</td>\n",
       "      <td>6.523956</td>\n",
       "      <td>6.521349</td>\n",
       "      <td>0.104300</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>107</td>\n",
       "      <td>6.537216</td>\n",
       "      <td>6.527814</td>\n",
       "      <td>0.103470</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>108</td>\n",
       "      <td>6.534691</td>\n",
       "      <td>6.530685</td>\n",
       "      <td>0.103975</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>109</td>\n",
       "      <td>6.531523</td>\n",
       "      <td>6.520197</td>\n",
       "      <td>0.104305</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>110</td>\n",
       "      <td>6.512198</td>\n",
       "      <td>6.518575</td>\n",
       "      <td>0.105690</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>111</td>\n",
       "      <td>6.524975</td>\n",
       "      <td>6.533186</td>\n",
       "      <td>0.104460</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>112</td>\n",
       "      <td>6.534156</td>\n",
       "      <td>6.525473</td>\n",
       "      <td>0.103695</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>113</td>\n",
       "      <td>6.527490</td>\n",
       "      <td>6.531316</td>\n",
       "      <td>0.103895</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>114</td>\n",
       "      <td>6.525311</td>\n",
       "      <td>6.523046</td>\n",
       "      <td>0.105210</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>115</td>\n",
       "      <td>6.524971</td>\n",
       "      <td>6.530903</td>\n",
       "      <td>0.103790</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>116</td>\n",
       "      <td>6.527875</td>\n",
       "      <td>6.534530</td>\n",
       "      <td>0.103660</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>117</td>\n",
       "      <td>6.529708</td>\n",
       "      <td>6.527980</td>\n",
       "      <td>0.105750</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>118</td>\n",
       "      <td>6.530342</td>\n",
       "      <td>6.531455</td>\n",
       "      <td>0.104870</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>119</td>\n",
       "      <td>6.527744</td>\n",
       "      <td>6.536857</td>\n",
       "      <td>0.104195</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>120</td>\n",
       "      <td>6.532185</td>\n",
       "      <td>6.535984</td>\n",
       "      <td>0.103730</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>121</td>\n",
       "      <td>6.522152</td>\n",
       "      <td>6.539434</td>\n",
       "      <td>0.104525</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>122</td>\n",
       "      <td>6.526580</td>\n",
       "      <td>6.537572</td>\n",
       "      <td>0.103900</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>123</td>\n",
       "      <td>6.538841</td>\n",
       "      <td>6.533760</td>\n",
       "      <td>0.103365</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>124</td>\n",
       "      <td>6.537343</td>\n",
       "      <td>6.535103</td>\n",
       "      <td>0.102995</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>125</td>\n",
       "      <td>6.534271</td>\n",
       "      <td>6.529286</td>\n",
       "      <td>0.104250</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>126</td>\n",
       "      <td>6.521006</td>\n",
       "      <td>6.524336</td>\n",
       "      <td>0.104425</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>127</td>\n",
       "      <td>6.520037</td>\n",
       "      <td>6.533742</td>\n",
       "      <td>0.104320</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>128</td>\n",
       "      <td>6.527222</td>\n",
       "      <td>6.524680</td>\n",
       "      <td>0.104155</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>129</td>\n",
       "      <td>6.519101</td>\n",
       "      <td>6.519608</td>\n",
       "      <td>0.105335</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>130</td>\n",
       "      <td>6.525943</td>\n",
       "      <td>6.535764</td>\n",
       "      <td>0.104095</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>131</td>\n",
       "      <td>6.531152</td>\n",
       "      <td>6.527410</td>\n",
       "      <td>0.104685</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>132</td>\n",
       "      <td>6.536532</td>\n",
       "      <td>6.527863</td>\n",
       "      <td>0.104265</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>133</td>\n",
       "      <td>6.520077</td>\n",
       "      <td>6.527856</td>\n",
       "      <td>0.104345</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>134</td>\n",
       "      <td>6.532059</td>\n",
       "      <td>6.524684</td>\n",
       "      <td>0.104230</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>135</td>\n",
       "      <td>6.520425</td>\n",
       "      <td>6.533329</td>\n",
       "      <td>0.104145</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>136</td>\n",
       "      <td>6.532412</td>\n",
       "      <td>6.533044</td>\n",
       "      <td>0.102595</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>137</td>\n",
       "      <td>6.529062</td>\n",
       "      <td>6.513135</td>\n",
       "      <td>0.104955</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>138</td>\n",
       "      <td>6.534882</td>\n",
       "      <td>6.521183</td>\n",
       "      <td>0.104375</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>139</td>\n",
       "      <td>6.524769</td>\n",
       "      <td>6.539518</td>\n",
       "      <td>0.102780</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>140</td>\n",
       "      <td>6.523107</td>\n",
       "      <td>6.538612</td>\n",
       "      <td>0.103995</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>141</td>\n",
       "      <td>6.531524</td>\n",
       "      <td>6.536498</td>\n",
       "      <td>0.103290</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>142</td>\n",
       "      <td>6.533463</td>\n",
       "      <td>6.530128</td>\n",
       "      <td>0.104325</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>143</td>\n",
       "      <td>6.532843</td>\n",
       "      <td>6.522478</td>\n",
       "      <td>0.104440</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>144</td>\n",
       "      <td>6.543056</td>\n",
       "      <td>6.522872</td>\n",
       "      <td>0.103570</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>145</td>\n",
       "      <td>6.522005</td>\n",
       "      <td>6.521644</td>\n",
       "      <td>0.104500</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>146</td>\n",
       "      <td>6.532049</td>\n",
       "      <td>6.546933</td>\n",
       "      <td>0.103625</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>147</td>\n",
       "      <td>6.536515</td>\n",
       "      <td>6.530170</td>\n",
       "      <td>0.103970</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>148</td>\n",
       "      <td>6.536002</td>\n",
       "      <td>6.528411</td>\n",
       "      <td>0.104220</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>149</td>\n",
       "      <td>6.523236</td>\n",
       "      <td>6.532349</td>\n",
       "      <td>0.104565</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>150</td>\n",
       "      <td>6.529987</td>\n",
       "      <td>6.527133</td>\n",
       "      <td>0.104300</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>151</td>\n",
       "      <td>6.533625</td>\n",
       "      <td>6.526356</td>\n",
       "      <td>0.104145</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>152</td>\n",
       "      <td>6.524390</td>\n",
       "      <td>6.529723</td>\n",
       "      <td>0.105200</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>153</td>\n",
       "      <td>6.533356</td>\n",
       "      <td>6.527324</td>\n",
       "      <td>0.104680</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>154</td>\n",
       "      <td>6.521967</td>\n",
       "      <td>6.534850</td>\n",
       "      <td>0.104020</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>155</td>\n",
       "      <td>6.527893</td>\n",
       "      <td>6.515623</td>\n",
       "      <td>0.104475</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>156</td>\n",
       "      <td>6.526127</td>\n",
       "      <td>6.526074</td>\n",
       "      <td>0.103765</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>157</td>\n",
       "      <td>6.537031</td>\n",
       "      <td>6.525145</td>\n",
       "      <td>0.105030</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>158</td>\n",
       "      <td>6.532842</td>\n",
       "      <td>6.521492</td>\n",
       "      <td>0.104175</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>159</td>\n",
       "      <td>6.534027</td>\n",
       "      <td>6.525052</td>\n",
       "      <td>0.104070</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>160</td>\n",
       "      <td>6.530282</td>\n",
       "      <td>6.526868</td>\n",
       "      <td>0.104595</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>161</td>\n",
       "      <td>6.520338</td>\n",
       "      <td>6.530581</td>\n",
       "      <td>0.103985</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>162</td>\n",
       "      <td>6.526151</td>\n",
       "      <td>6.523325</td>\n",
       "      <td>0.104010</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>163</td>\n",
       "      <td>6.536770</td>\n",
       "      <td>6.527268</td>\n",
       "      <td>0.105250</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>164</td>\n",
       "      <td>6.531813</td>\n",
       "      <td>6.523315</td>\n",
       "      <td>0.104865</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>165</td>\n",
       "      <td>6.523051</td>\n",
       "      <td>6.517580</td>\n",
       "      <td>0.104040</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>166</td>\n",
       "      <td>6.536177</td>\n",
       "      <td>6.523537</td>\n",
       "      <td>0.103585</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>167</td>\n",
       "      <td>6.540723</td>\n",
       "      <td>6.542291</td>\n",
       "      <td>0.103250</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>168</td>\n",
       "      <td>6.534904</td>\n",
       "      <td>6.536456</td>\n",
       "      <td>0.104540</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>169</td>\n",
       "      <td>6.524323</td>\n",
       "      <td>6.526419</td>\n",
       "      <td>0.105460</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>170</td>\n",
       "      <td>6.531293</td>\n",
       "      <td>6.527373</td>\n",
       "      <td>0.103995</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>171</td>\n",
       "      <td>6.531351</td>\n",
       "      <td>6.518658</td>\n",
       "      <td>0.105015</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>172</td>\n",
       "      <td>6.535889</td>\n",
       "      <td>6.525622</td>\n",
       "      <td>0.104050</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>173</td>\n",
       "      <td>6.531853</td>\n",
       "      <td>6.540788</td>\n",
       "      <td>0.103695</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>174</td>\n",
       "      <td>6.531829</td>\n",
       "      <td>6.524208</td>\n",
       "      <td>0.104820</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>175</td>\n",
       "      <td>6.521962</td>\n",
       "      <td>6.533048</td>\n",
       "      <td>0.104820</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>176</td>\n",
       "      <td>6.526564</td>\n",
       "      <td>6.525026</td>\n",
       "      <td>0.103680</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>177</td>\n",
       "      <td>6.523790</td>\n",
       "      <td>6.532899</td>\n",
       "      <td>0.104225</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>178</td>\n",
       "      <td>6.535333</td>\n",
       "      <td>6.527302</td>\n",
       "      <td>0.104365</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>179</td>\n",
       "      <td>6.534350</td>\n",
       "      <td>6.532518</td>\n",
       "      <td>0.104275</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>180</td>\n",
       "      <td>6.528660</td>\n",
       "      <td>6.528836</td>\n",
       "      <td>0.103685</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>181</td>\n",
       "      <td>6.531311</td>\n",
       "      <td>6.531162</td>\n",
       "      <td>0.103580</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>182</td>\n",
       "      <td>6.515179</td>\n",
       "      <td>6.526597</td>\n",
       "      <td>0.103845</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>183</td>\n",
       "      <td>6.531155</td>\n",
       "      <td>6.526833</td>\n",
       "      <td>0.103840</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>184</td>\n",
       "      <td>6.532020</td>\n",
       "      <td>6.524667</td>\n",
       "      <td>0.104510</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>185</td>\n",
       "      <td>6.532925</td>\n",
       "      <td>6.530567</td>\n",
       "      <td>0.104135</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>186</td>\n",
       "      <td>6.537433</td>\n",
       "      <td>6.523486</td>\n",
       "      <td>0.105175</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>187</td>\n",
       "      <td>6.535101</td>\n",
       "      <td>6.531290</td>\n",
       "      <td>0.103390</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>188</td>\n",
       "      <td>6.538947</td>\n",
       "      <td>6.529778</td>\n",
       "      <td>0.104455</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>189</td>\n",
       "      <td>6.530065</td>\n",
       "      <td>6.533669</td>\n",
       "      <td>0.104155</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>190</td>\n",
       "      <td>6.530328</td>\n",
       "      <td>6.532512</td>\n",
       "      <td>0.104145</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>191</td>\n",
       "      <td>6.539903</td>\n",
       "      <td>6.530592</td>\n",
       "      <td>0.104785</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>192</td>\n",
       "      <td>6.526731</td>\n",
       "      <td>6.535331</td>\n",
       "      <td>0.103770</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>193</td>\n",
       "      <td>6.530719</td>\n",
       "      <td>6.523856</td>\n",
       "      <td>0.103585</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>194</td>\n",
       "      <td>6.525577</td>\n",
       "      <td>6.530161</td>\n",
       "      <td>0.103365</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>195</td>\n",
       "      <td>6.514955</td>\n",
       "      <td>6.519270</td>\n",
       "      <td>0.105015</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>196</td>\n",
       "      <td>6.529655</td>\n",
       "      <td>6.520774</td>\n",
       "      <td>0.103865</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>197</td>\n",
       "      <td>6.533305</td>\n",
       "      <td>6.531521</td>\n",
       "      <td>0.104145</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>198</td>\n",
       "      <td>6.532205</td>\n",
       "      <td>6.532505</td>\n",
       "      <td>0.104375</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>199</td>\n",
       "      <td>6.533462</td>\n",
       "      <td>6.536796</td>\n",
       "      <td>0.103800</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>200</td>\n",
       "      <td>6.528585</td>\n",
       "      <td>6.524628</td>\n",
       "      <td>0.104020</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>201</td>\n",
       "      <td>6.537583</td>\n",
       "      <td>6.526807</td>\n",
       "      <td>0.104665</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>202</td>\n",
       "      <td>6.540192</td>\n",
       "      <td>6.527159</td>\n",
       "      <td>0.104260</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>203</td>\n",
       "      <td>6.520133</td>\n",
       "      <td>6.535759</td>\n",
       "      <td>0.104345</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>204</td>\n",
       "      <td>6.535662</td>\n",
       "      <td>6.527654</td>\n",
       "      <td>0.104295</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>205</td>\n",
       "      <td>6.531634</td>\n",
       "      <td>6.526591</td>\n",
       "      <td>0.104425</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>206</td>\n",
       "      <td>6.537027</td>\n",
       "      <td>6.536685</td>\n",
       "      <td>0.102705</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>207</td>\n",
       "      <td>6.533144</td>\n",
       "      <td>6.530952</td>\n",
       "      <td>0.104595</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>208</td>\n",
       "      <td>6.525766</td>\n",
       "      <td>6.539598</td>\n",
       "      <td>0.103955</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>209</td>\n",
       "      <td>6.541143</td>\n",
       "      <td>6.537145</td>\n",
       "      <td>0.102995</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>210</td>\n",
       "      <td>6.538584</td>\n",
       "      <td>6.523304</td>\n",
       "      <td>0.105075</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>211</td>\n",
       "      <td>6.533528</td>\n",
       "      <td>6.543345</td>\n",
       "      <td>0.103705</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>212</td>\n",
       "      <td>6.527736</td>\n",
       "      <td>6.542420</td>\n",
       "      <td>0.103970</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>213</td>\n",
       "      <td>6.530678</td>\n",
       "      <td>6.534394</td>\n",
       "      <td>0.104580</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>214</td>\n",
       "      <td>6.526175</td>\n",
       "      <td>6.536333</td>\n",
       "      <td>0.103725</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>215</td>\n",
       "      <td>6.527203</td>\n",
       "      <td>6.523649</td>\n",
       "      <td>0.104515</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>216</td>\n",
       "      <td>6.527004</td>\n",
       "      <td>6.535695</td>\n",
       "      <td>0.103785</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>217</td>\n",
       "      <td>6.524115</td>\n",
       "      <td>6.535877</td>\n",
       "      <td>0.102890</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>218</td>\n",
       "      <td>6.526873</td>\n",
       "      <td>6.538383</td>\n",
       "      <td>0.104255</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>219</td>\n",
       "      <td>6.528769</td>\n",
       "      <td>6.539924</td>\n",
       "      <td>0.104385</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>220</td>\n",
       "      <td>6.516497</td>\n",
       "      <td>6.523701</td>\n",
       "      <td>0.104110</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>221</td>\n",
       "      <td>6.548932</td>\n",
       "      <td>6.536510</td>\n",
       "      <td>0.104200</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>222</td>\n",
       "      <td>6.529961</td>\n",
       "      <td>6.528201</td>\n",
       "      <td>0.103900</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>223</td>\n",
       "      <td>6.538307</td>\n",
       "      <td>6.529501</td>\n",
       "      <td>0.103430</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>224</td>\n",
       "      <td>6.525852</td>\n",
       "      <td>6.533941</td>\n",
       "      <td>0.103200</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>225</td>\n",
       "      <td>6.526545</td>\n",
       "      <td>6.523190</td>\n",
       "      <td>0.103910</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>226</td>\n",
       "      <td>6.530758</td>\n",
       "      <td>6.532929</td>\n",
       "      <td>0.103900</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>227</td>\n",
       "      <td>6.521533</td>\n",
       "      <td>6.530906</td>\n",
       "      <td>0.104175</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>228</td>\n",
       "      <td>6.538794</td>\n",
       "      <td>6.527173</td>\n",
       "      <td>0.104855</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>229</td>\n",
       "      <td>6.520840</td>\n",
       "      <td>6.522890</td>\n",
       "      <td>0.103730</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>230</td>\n",
       "      <td>6.528120</td>\n",
       "      <td>6.535723</td>\n",
       "      <td>0.105210</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>231</td>\n",
       "      <td>6.531610</td>\n",
       "      <td>6.523017</td>\n",
       "      <td>0.103860</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>232</td>\n",
       "      <td>6.528649</td>\n",
       "      <td>6.528587</td>\n",
       "      <td>0.103160</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>233</td>\n",
       "      <td>6.526502</td>\n",
       "      <td>6.532371</td>\n",
       "      <td>0.104465</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>234</td>\n",
       "      <td>6.527818</td>\n",
       "      <td>6.530345</td>\n",
       "      <td>0.103585</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>235</td>\n",
       "      <td>6.537458</td>\n",
       "      <td>6.522540</td>\n",
       "      <td>0.104430</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>236</td>\n",
       "      <td>6.514893</td>\n",
       "      <td>6.527052</td>\n",
       "      <td>0.103590</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>237</td>\n",
       "      <td>6.528698</td>\n",
       "      <td>6.532133</td>\n",
       "      <td>0.103145</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>238</td>\n",
       "      <td>6.527530</td>\n",
       "      <td>6.519622</td>\n",
       "      <td>0.104450</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>239</td>\n",
       "      <td>6.526812</td>\n",
       "      <td>6.522693</td>\n",
       "      <td>0.104630</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>240</td>\n",
       "      <td>6.529862</td>\n",
       "      <td>6.529683</td>\n",
       "      <td>0.104065</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>241</td>\n",
       "      <td>6.527708</td>\n",
       "      <td>6.523052</td>\n",
       "      <td>0.104120</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>242</td>\n",
       "      <td>6.531031</td>\n",
       "      <td>6.513736</td>\n",
       "      <td>0.104890</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>243</td>\n",
       "      <td>6.527788</td>\n",
       "      <td>6.521733</td>\n",
       "      <td>0.105060</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>244</td>\n",
       "      <td>6.534762</td>\n",
       "      <td>6.526750</td>\n",
       "      <td>0.104080</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>245</td>\n",
       "      <td>6.529214</td>\n",
       "      <td>6.529071</td>\n",
       "      <td>0.103880</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>246</td>\n",
       "      <td>6.542085</td>\n",
       "      <td>6.538125</td>\n",
       "      <td>0.103250</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>247</td>\n",
       "      <td>6.527364</td>\n",
       "      <td>6.513730</td>\n",
       "      <td>0.104385</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>248</td>\n",
       "      <td>6.530690</td>\n",
       "      <td>6.520815</td>\n",
       "      <td>0.104705</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>249</td>\n",
       "      <td>6.531660</td>\n",
       "      <td>6.532805</td>\n",
       "      <td>0.103405</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>250</td>\n",
       "      <td>6.526919</td>\n",
       "      <td>6.537993</td>\n",
       "      <td>0.103550</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>251</td>\n",
       "      <td>6.527624</td>\n",
       "      <td>6.526400</td>\n",
       "      <td>0.104385</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>252</td>\n",
       "      <td>6.533648</td>\n",
       "      <td>6.526894</td>\n",
       "      <td>0.104530</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>253</td>\n",
       "      <td>6.528475</td>\n",
       "      <td>6.528255</td>\n",
       "      <td>0.104690</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>254</td>\n",
       "      <td>6.532430</td>\n",
       "      <td>6.535430</td>\n",
       "      <td>0.103920</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>255</td>\n",
       "      <td>6.529804</td>\n",
       "      <td>6.530538</td>\n",
       "      <td>0.104125</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>256</td>\n",
       "      <td>6.533230</td>\n",
       "      <td>6.525773</td>\n",
       "      <td>0.104725</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>257</td>\n",
       "      <td>6.526979</td>\n",
       "      <td>6.523259</td>\n",
       "      <td>0.104120</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>258</td>\n",
       "      <td>6.529524</td>\n",
       "      <td>6.528519</td>\n",
       "      <td>0.103770</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>259</td>\n",
       "      <td>6.530081</td>\n",
       "      <td>6.528796</td>\n",
       "      <td>0.104420</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>260</td>\n",
       "      <td>6.527995</td>\n",
       "      <td>6.535524</td>\n",
       "      <td>0.103495</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>261</td>\n",
       "      <td>6.525990</td>\n",
       "      <td>6.534597</td>\n",
       "      <td>0.103785</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>262</td>\n",
       "      <td>6.526299</td>\n",
       "      <td>6.531813</td>\n",
       "      <td>0.103585</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>263</td>\n",
       "      <td>6.533526</td>\n",
       "      <td>6.531399</td>\n",
       "      <td>0.103750</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>264</td>\n",
       "      <td>6.521169</td>\n",
       "      <td>6.531689</td>\n",
       "      <td>0.104170</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>265</td>\n",
       "      <td>6.525878</td>\n",
       "      <td>6.533255</td>\n",
       "      <td>0.103730</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>266</td>\n",
       "      <td>6.521080</td>\n",
       "      <td>6.521979</td>\n",
       "      <td>0.104960</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>267</td>\n",
       "      <td>6.521299</td>\n",
       "      <td>6.526073</td>\n",
       "      <td>0.104845</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>268</td>\n",
       "      <td>6.530637</td>\n",
       "      <td>6.526131</td>\n",
       "      <td>0.103810</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>269</td>\n",
       "      <td>6.537061</td>\n",
       "      <td>6.528196</td>\n",
       "      <td>0.104305</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>270</td>\n",
       "      <td>6.531601</td>\n",
       "      <td>6.527938</td>\n",
       "      <td>0.104220</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>271</td>\n",
       "      <td>6.529831</td>\n",
       "      <td>6.529654</td>\n",
       "      <td>0.104135</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>272</td>\n",
       "      <td>6.528193</td>\n",
       "      <td>6.538549</td>\n",
       "      <td>0.103700</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>273</td>\n",
       "      <td>6.533643</td>\n",
       "      <td>6.530906</td>\n",
       "      <td>0.104165</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>274</td>\n",
       "      <td>6.532382</td>\n",
       "      <td>6.526570</td>\n",
       "      <td>0.102770</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>275</td>\n",
       "      <td>6.533419</td>\n",
       "      <td>6.529104</td>\n",
       "      <td>0.104090</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>276</td>\n",
       "      <td>6.538997</td>\n",
       "      <td>6.524387</td>\n",
       "      <td>0.104745</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>277</td>\n",
       "      <td>6.518568</td>\n",
       "      <td>6.543656</td>\n",
       "      <td>0.102890</td>\n",
       "      <td>01:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>278</td>\n",
       "      <td>6.532130</td>\n",
       "      <td>6.526467</td>\n",
       "      <td>0.104285</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>279</td>\n",
       "      <td>6.548047</td>\n",
       "      <td>6.526092</td>\n",
       "      <td>0.103675</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>280</td>\n",
       "      <td>6.522285</td>\n",
       "      <td>6.527276</td>\n",
       "      <td>0.103865</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>281</td>\n",
       "      <td>6.532184</td>\n",
       "      <td>6.530408</td>\n",
       "      <td>0.103635</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>282</td>\n",
       "      <td>6.529398</td>\n",
       "      <td>6.537572</td>\n",
       "      <td>0.102270</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>283</td>\n",
       "      <td>6.534352</td>\n",
       "      <td>6.522018</td>\n",
       "      <td>0.104530</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>284</td>\n",
       "      <td>6.520448</td>\n",
       "      <td>6.531837</td>\n",
       "      <td>0.103345</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>285</td>\n",
       "      <td>6.531035</td>\n",
       "      <td>6.539327</td>\n",
       "      <td>0.104040</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>286</td>\n",
       "      <td>6.528076</td>\n",
       "      <td>6.544642</td>\n",
       "      <td>0.103875</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>287</td>\n",
       "      <td>6.531813</td>\n",
       "      <td>6.530777</td>\n",
       "      <td>0.103665</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>288</td>\n",
       "      <td>6.530039</td>\n",
       "      <td>6.531709</td>\n",
       "      <td>0.103310</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>289</td>\n",
       "      <td>6.526526</td>\n",
       "      <td>6.529444</td>\n",
       "      <td>0.104535</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>290</td>\n",
       "      <td>6.514051</td>\n",
       "      <td>6.527929</td>\n",
       "      <td>0.104455</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>291</td>\n",
       "      <td>6.522651</td>\n",
       "      <td>6.528549</td>\n",
       "      <td>0.103845</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>292</td>\n",
       "      <td>6.528440</td>\n",
       "      <td>6.523817</td>\n",
       "      <td>0.105110</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>293</td>\n",
       "      <td>6.534213</td>\n",
       "      <td>6.537367</td>\n",
       "      <td>0.103280</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>294</td>\n",
       "      <td>6.535436</td>\n",
       "      <td>6.526841</td>\n",
       "      <td>0.104625</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>295</td>\n",
       "      <td>6.522667</td>\n",
       "      <td>6.545990</td>\n",
       "      <td>0.103115</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>296</td>\n",
       "      <td>6.531548</td>\n",
       "      <td>6.528219</td>\n",
       "      <td>0.103560</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>297</td>\n",
       "      <td>6.517323</td>\n",
       "      <td>6.531179</td>\n",
       "      <td>0.104425</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>298</td>\n",
       "      <td>6.522221</td>\n",
       "      <td>6.522420</td>\n",
       "      <td>0.103800</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>299</td>\n",
       "      <td>6.531369</td>\n",
       "      <td>6.540129</td>\n",
       "      <td>0.102850</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>300</td>\n",
       "      <td>6.532459</td>\n",
       "      <td>6.539116</td>\n",
       "      <td>0.104220</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>301</td>\n",
       "      <td>6.529193</td>\n",
       "      <td>6.523264</td>\n",
       "      <td>0.105330</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>302</td>\n",
       "      <td>6.537840</td>\n",
       "      <td>6.518047</td>\n",
       "      <td>0.104165</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>303</td>\n",
       "      <td>6.521718</td>\n",
       "      <td>6.535148</td>\n",
       "      <td>0.104325</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>304</td>\n",
       "      <td>6.530335</td>\n",
       "      <td>6.526026</td>\n",
       "      <td>0.103795</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>305</td>\n",
       "      <td>6.534539</td>\n",
       "      <td>6.531658</td>\n",
       "      <td>0.105155</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>306</td>\n",
       "      <td>6.520128</td>\n",
       "      <td>6.533978</td>\n",
       "      <td>0.104200</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>307</td>\n",
       "      <td>6.532573</td>\n",
       "      <td>6.526487</td>\n",
       "      <td>0.103945</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>308</td>\n",
       "      <td>6.538625</td>\n",
       "      <td>6.525061</td>\n",
       "      <td>0.104190</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>309</td>\n",
       "      <td>6.525799</td>\n",
       "      <td>6.527965</td>\n",
       "      <td>0.104280</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>310</td>\n",
       "      <td>6.522458</td>\n",
       "      <td>6.520654</td>\n",
       "      <td>0.104015</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>311</td>\n",
       "      <td>6.532169</td>\n",
       "      <td>6.529164</td>\n",
       "      <td>0.103755</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>312</td>\n",
       "      <td>6.516337</td>\n",
       "      <td>6.526877</td>\n",
       "      <td>0.103915</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>313</td>\n",
       "      <td>6.528310</td>\n",
       "      <td>6.528016</td>\n",
       "      <td>0.104645</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>314</td>\n",
       "      <td>6.520015</td>\n",
       "      <td>6.527230</td>\n",
       "      <td>0.104590</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>315</td>\n",
       "      <td>6.533518</td>\n",
       "      <td>6.525825</td>\n",
       "      <td>0.104320</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>316</td>\n",
       "      <td>6.536824</td>\n",
       "      <td>6.532016</td>\n",
       "      <td>0.104065</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>317</td>\n",
       "      <td>6.531187</td>\n",
       "      <td>6.534854</td>\n",
       "      <td>0.104235</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>318</td>\n",
       "      <td>6.532421</td>\n",
       "      <td>6.534971</td>\n",
       "      <td>0.103885</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>319</td>\n",
       "      <td>6.525725</td>\n",
       "      <td>6.537426</td>\n",
       "      <td>0.103510</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>320</td>\n",
       "      <td>6.529040</td>\n",
       "      <td>6.536706</td>\n",
       "      <td>0.104105</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>321</td>\n",
       "      <td>6.525560</td>\n",
       "      <td>6.529685</td>\n",
       "      <td>0.105195</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>322</td>\n",
       "      <td>6.525182</td>\n",
       "      <td>6.524971</td>\n",
       "      <td>0.104100</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>323</td>\n",
       "      <td>6.529812</td>\n",
       "      <td>6.525903</td>\n",
       "      <td>0.105020</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>324</td>\n",
       "      <td>6.531052</td>\n",
       "      <td>6.530882</td>\n",
       "      <td>0.104435</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>325</td>\n",
       "      <td>6.536712</td>\n",
       "      <td>6.514231</td>\n",
       "      <td>0.105150</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>326</td>\n",
       "      <td>6.531802</td>\n",
       "      <td>6.530469</td>\n",
       "      <td>0.103890</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>327</td>\n",
       "      <td>6.537776</td>\n",
       "      <td>6.535261</td>\n",
       "      <td>0.104055</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>328</td>\n",
       "      <td>6.535728</td>\n",
       "      <td>6.529324</td>\n",
       "      <td>0.104080</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>329</td>\n",
       "      <td>6.530786</td>\n",
       "      <td>6.539026</td>\n",
       "      <td>0.103185</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>330</td>\n",
       "      <td>6.546797</td>\n",
       "      <td>6.520338</td>\n",
       "      <td>0.104790</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>331</td>\n",
       "      <td>6.520671</td>\n",
       "      <td>6.532984</td>\n",
       "      <td>0.103910</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>332</td>\n",
       "      <td>6.529831</td>\n",
       "      <td>6.526007</td>\n",
       "      <td>0.104705</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>333</td>\n",
       "      <td>6.524833</td>\n",
       "      <td>6.523973</td>\n",
       "      <td>0.105025</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>334</td>\n",
       "      <td>6.511316</td>\n",
       "      <td>6.526090</td>\n",
       "      <td>0.104395</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>335</td>\n",
       "      <td>6.535954</td>\n",
       "      <td>6.525968</td>\n",
       "      <td>0.104380</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>336</td>\n",
       "      <td>6.531915</td>\n",
       "      <td>6.522027</td>\n",
       "      <td>0.104205</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>337</td>\n",
       "      <td>6.524121</td>\n",
       "      <td>6.538034</td>\n",
       "      <td>0.103765</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>338</td>\n",
       "      <td>6.533602</td>\n",
       "      <td>6.530215</td>\n",
       "      <td>0.103895</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>339</td>\n",
       "      <td>6.535203</td>\n",
       "      <td>6.530564</td>\n",
       "      <td>0.104595</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>340</td>\n",
       "      <td>6.530635</td>\n",
       "      <td>6.531345</td>\n",
       "      <td>0.103800</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>341</td>\n",
       "      <td>6.519986</td>\n",
       "      <td>6.517667</td>\n",
       "      <td>0.104145</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>342</td>\n",
       "      <td>6.528482</td>\n",
       "      <td>6.527255</td>\n",
       "      <td>0.103910</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>343</td>\n",
       "      <td>6.535128</td>\n",
       "      <td>6.528916</td>\n",
       "      <td>0.104180</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>344</td>\n",
       "      <td>6.537328</td>\n",
       "      <td>6.523778</td>\n",
       "      <td>0.103675</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>345</td>\n",
       "      <td>6.522332</td>\n",
       "      <td>6.531202</td>\n",
       "      <td>0.103490</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>346</td>\n",
       "      <td>6.532437</td>\n",
       "      <td>6.526612</td>\n",
       "      <td>0.105020</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>347</td>\n",
       "      <td>6.526893</td>\n",
       "      <td>6.535695</td>\n",
       "      <td>0.103955</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>348</td>\n",
       "      <td>6.518684</td>\n",
       "      <td>6.536061</td>\n",
       "      <td>0.102740</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>349</td>\n",
       "      <td>6.526363</td>\n",
       "      <td>6.530999</td>\n",
       "      <td>0.102975</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>350</td>\n",
       "      <td>6.525348</td>\n",
       "      <td>6.526605</td>\n",
       "      <td>0.104425</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>351</td>\n",
       "      <td>6.525568</td>\n",
       "      <td>6.530396</td>\n",
       "      <td>0.104205</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>352</td>\n",
       "      <td>6.545446</td>\n",
       "      <td>6.532774</td>\n",
       "      <td>0.104055</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>353</td>\n",
       "      <td>6.524969</td>\n",
       "      <td>6.530309</td>\n",
       "      <td>0.103645</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>354</td>\n",
       "      <td>6.519111</td>\n",
       "      <td>6.533668</td>\n",
       "      <td>0.104280</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>355</td>\n",
       "      <td>6.524108</td>\n",
       "      <td>6.525862</td>\n",
       "      <td>0.104040</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>356</td>\n",
       "      <td>6.530723</td>\n",
       "      <td>6.533962</td>\n",
       "      <td>0.103770</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>357</td>\n",
       "      <td>6.526614</td>\n",
       "      <td>6.538831</td>\n",
       "      <td>0.104640</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>358</td>\n",
       "      <td>6.526708</td>\n",
       "      <td>6.516531</td>\n",
       "      <td>0.104685</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>359</td>\n",
       "      <td>6.526706</td>\n",
       "      <td>6.535230</td>\n",
       "      <td>0.103745</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>360</td>\n",
       "      <td>6.531102</td>\n",
       "      <td>6.519198</td>\n",
       "      <td>0.104630</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>361</td>\n",
       "      <td>6.528438</td>\n",
       "      <td>6.529023</td>\n",
       "      <td>0.104015</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>362</td>\n",
       "      <td>6.527283</td>\n",
       "      <td>6.534185</td>\n",
       "      <td>0.102880</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>363</td>\n",
       "      <td>6.540285</td>\n",
       "      <td>6.538822</td>\n",
       "      <td>0.104395</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>364</td>\n",
       "      <td>6.527953</td>\n",
       "      <td>6.538975</td>\n",
       "      <td>0.103145</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>365</td>\n",
       "      <td>6.529635</td>\n",
       "      <td>6.535688</td>\n",
       "      <td>0.104060</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>366</td>\n",
       "      <td>6.521909</td>\n",
       "      <td>6.525049</td>\n",
       "      <td>0.103890</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>367</td>\n",
       "      <td>6.536799</td>\n",
       "      <td>6.530971</td>\n",
       "      <td>0.104235</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>368</td>\n",
       "      <td>6.530937</td>\n",
       "      <td>6.533306</td>\n",
       "      <td>0.103400</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>369</td>\n",
       "      <td>6.531309</td>\n",
       "      <td>6.532254</td>\n",
       "      <td>0.102845</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>370</td>\n",
       "      <td>6.518056</td>\n",
       "      <td>6.529799</td>\n",
       "      <td>0.105020</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>371</td>\n",
       "      <td>6.531700</td>\n",
       "      <td>6.531386</td>\n",
       "      <td>0.104200</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>372</td>\n",
       "      <td>6.528551</td>\n",
       "      <td>6.533344</td>\n",
       "      <td>0.104145</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>373</td>\n",
       "      <td>6.526236</td>\n",
       "      <td>6.522289</td>\n",
       "      <td>0.104330</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>374</td>\n",
       "      <td>6.528157</td>\n",
       "      <td>6.530908</td>\n",
       "      <td>0.103415</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>375</td>\n",
       "      <td>6.527071</td>\n",
       "      <td>6.533673</td>\n",
       "      <td>0.104560</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>376</td>\n",
       "      <td>6.525280</td>\n",
       "      <td>6.526300</td>\n",
       "      <td>0.104505</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>377</td>\n",
       "      <td>6.536101</td>\n",
       "      <td>6.527721</td>\n",
       "      <td>0.105340</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>378</td>\n",
       "      <td>6.527701</td>\n",
       "      <td>6.524209</td>\n",
       "      <td>0.104405</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>379</td>\n",
       "      <td>6.527445</td>\n",
       "      <td>6.541893</td>\n",
       "      <td>0.104520</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>380</td>\n",
       "      <td>6.527907</td>\n",
       "      <td>6.522082</td>\n",
       "      <td>0.104685</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>381</td>\n",
       "      <td>6.535927</td>\n",
       "      <td>6.534543</td>\n",
       "      <td>0.104370</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>382</td>\n",
       "      <td>6.523967</td>\n",
       "      <td>6.530112</td>\n",
       "      <td>0.104675</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>383</td>\n",
       "      <td>6.537230</td>\n",
       "      <td>6.527096</td>\n",
       "      <td>0.105045</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>384</td>\n",
       "      <td>6.537417</td>\n",
       "      <td>6.525343</td>\n",
       "      <td>0.103610</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>385</td>\n",
       "      <td>6.541878</td>\n",
       "      <td>6.529009</td>\n",
       "      <td>0.104050</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>386</td>\n",
       "      <td>6.529520</td>\n",
       "      <td>6.537721</td>\n",
       "      <td>0.104005</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>387</td>\n",
       "      <td>6.531899</td>\n",
       "      <td>6.533643</td>\n",
       "      <td>0.104110</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>388</td>\n",
       "      <td>6.539425</td>\n",
       "      <td>6.534653</td>\n",
       "      <td>0.103970</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>389</td>\n",
       "      <td>6.531428</td>\n",
       "      <td>6.530452</td>\n",
       "      <td>0.105095</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>390</td>\n",
       "      <td>6.535826</td>\n",
       "      <td>6.535790</td>\n",
       "      <td>0.103160</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>391</td>\n",
       "      <td>6.530810</td>\n",
       "      <td>6.527583</td>\n",
       "      <td>0.105450</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>392</td>\n",
       "      <td>6.533134</td>\n",
       "      <td>6.523067</td>\n",
       "      <td>0.105250</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>393</td>\n",
       "      <td>6.525270</td>\n",
       "      <td>6.525219</td>\n",
       "      <td>0.104050</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>394</td>\n",
       "      <td>6.527457</td>\n",
       "      <td>6.532942</td>\n",
       "      <td>0.104060</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>395</td>\n",
       "      <td>6.531130</td>\n",
       "      <td>6.526981</td>\n",
       "      <td>0.103770</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>396</td>\n",
       "      <td>6.542171</td>\n",
       "      <td>6.526690</td>\n",
       "      <td>0.105250</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>397</td>\n",
       "      <td>6.535034</td>\n",
       "      <td>6.537123</td>\n",
       "      <td>0.102685</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>398</td>\n",
       "      <td>6.537934</td>\n",
       "      <td>6.526694</td>\n",
       "      <td>0.103335</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>399</td>\n",
       "      <td>6.528060</td>\n",
       "      <td>6.534278</td>\n",
       "      <td>0.102575</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>400</td>\n",
       "      <td>6.528463</td>\n",
       "      <td>6.532446</td>\n",
       "      <td>0.103945</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>401</td>\n",
       "      <td>6.528105</td>\n",
       "      <td>6.535577</td>\n",
       "      <td>0.103750</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>402</td>\n",
       "      <td>6.532111</td>\n",
       "      <td>6.523574</td>\n",
       "      <td>0.104570</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>403</td>\n",
       "      <td>6.525070</td>\n",
       "      <td>6.520875</td>\n",
       "      <td>0.104665</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>404</td>\n",
       "      <td>6.531607</td>\n",
       "      <td>6.515448</td>\n",
       "      <td>0.104940</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>405</td>\n",
       "      <td>6.533643</td>\n",
       "      <td>6.524109</td>\n",
       "      <td>0.103535</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>406</td>\n",
       "      <td>6.523037</td>\n",
       "      <td>6.522676</td>\n",
       "      <td>0.104720</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>407</td>\n",
       "      <td>6.534359</td>\n",
       "      <td>6.524793</td>\n",
       "      <td>0.103990</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>408</td>\n",
       "      <td>6.524415</td>\n",
       "      <td>6.541050</td>\n",
       "      <td>0.103690</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>409</td>\n",
       "      <td>6.526043</td>\n",
       "      <td>6.529848</td>\n",
       "      <td>0.103235</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>410</td>\n",
       "      <td>6.522673</td>\n",
       "      <td>6.516146</td>\n",
       "      <td>0.105885</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>411</td>\n",
       "      <td>6.530394</td>\n",
       "      <td>6.534877</td>\n",
       "      <td>0.103825</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>412</td>\n",
       "      <td>6.529451</td>\n",
       "      <td>6.522156</td>\n",
       "      <td>0.105475</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>413</td>\n",
       "      <td>6.537150</td>\n",
       "      <td>6.529490</td>\n",
       "      <td>0.104860</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>414</td>\n",
       "      <td>6.528372</td>\n",
       "      <td>6.536789</td>\n",
       "      <td>0.103700</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>415</td>\n",
       "      <td>6.523251</td>\n",
       "      <td>6.537650</td>\n",
       "      <td>0.104115</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>416</td>\n",
       "      <td>6.531978</td>\n",
       "      <td>6.534368</td>\n",
       "      <td>0.103215</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>417</td>\n",
       "      <td>6.532186</td>\n",
       "      <td>6.526120</td>\n",
       "      <td>0.104050</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>418</td>\n",
       "      <td>6.524971</td>\n",
       "      <td>6.531872</td>\n",
       "      <td>0.103440</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>419</td>\n",
       "      <td>6.524782</td>\n",
       "      <td>6.526900</td>\n",
       "      <td>0.103765</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>420</td>\n",
       "      <td>6.525961</td>\n",
       "      <td>6.522711</td>\n",
       "      <td>0.104525</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>421</td>\n",
       "      <td>6.525999</td>\n",
       "      <td>6.524594</td>\n",
       "      <td>0.104140</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>422</td>\n",
       "      <td>6.539255</td>\n",
       "      <td>6.542420</td>\n",
       "      <td>0.103395</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>423</td>\n",
       "      <td>6.537805</td>\n",
       "      <td>6.526492</td>\n",
       "      <td>0.104390</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>424</td>\n",
       "      <td>6.534119</td>\n",
       "      <td>6.537027</td>\n",
       "      <td>0.104975</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>425</td>\n",
       "      <td>6.534631</td>\n",
       "      <td>6.529415</td>\n",
       "      <td>0.104955</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>426</td>\n",
       "      <td>6.531525</td>\n",
       "      <td>6.535199</td>\n",
       "      <td>0.103500</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>427</td>\n",
       "      <td>6.538919</td>\n",
       "      <td>6.524053</td>\n",
       "      <td>0.103370</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>428</td>\n",
       "      <td>6.529049</td>\n",
       "      <td>6.526838</td>\n",
       "      <td>0.104200</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>429</td>\n",
       "      <td>6.531208</td>\n",
       "      <td>6.528158</td>\n",
       "      <td>0.103615</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>430</td>\n",
       "      <td>6.533822</td>\n",
       "      <td>6.529346</td>\n",
       "      <td>0.103815</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>431</td>\n",
       "      <td>6.526391</td>\n",
       "      <td>6.535392</td>\n",
       "      <td>0.104175</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>432</td>\n",
       "      <td>6.521654</td>\n",
       "      <td>6.535430</td>\n",
       "      <td>0.103385</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>433</td>\n",
       "      <td>6.518010</td>\n",
       "      <td>6.531950</td>\n",
       "      <td>0.103510</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>434</td>\n",
       "      <td>6.517995</td>\n",
       "      <td>6.533158</td>\n",
       "      <td>0.103410</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>435</td>\n",
       "      <td>6.531656</td>\n",
       "      <td>6.528660</td>\n",
       "      <td>0.104445</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>436</td>\n",
       "      <td>6.531504</td>\n",
       "      <td>6.527131</td>\n",
       "      <td>0.104115</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>437</td>\n",
       "      <td>6.539174</td>\n",
       "      <td>6.540590</td>\n",
       "      <td>0.103230</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>438</td>\n",
       "      <td>6.538927</td>\n",
       "      <td>6.530081</td>\n",
       "      <td>0.103515</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>439</td>\n",
       "      <td>6.522986</td>\n",
       "      <td>6.528391</td>\n",
       "      <td>0.105390</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>440</td>\n",
       "      <td>6.529039</td>\n",
       "      <td>6.534008</td>\n",
       "      <td>0.102565</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>441</td>\n",
       "      <td>6.530641</td>\n",
       "      <td>6.536734</td>\n",
       "      <td>0.104365</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>442</td>\n",
       "      <td>6.532414</td>\n",
       "      <td>6.533297</td>\n",
       "      <td>0.103620</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>443</td>\n",
       "      <td>6.528535</td>\n",
       "      <td>6.527986</td>\n",
       "      <td>0.103890</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>444</td>\n",
       "      <td>6.528260</td>\n",
       "      <td>6.536913</td>\n",
       "      <td>0.104450</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>445</td>\n",
       "      <td>6.526257</td>\n",
       "      <td>6.539980</td>\n",
       "      <td>0.104320</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>446</td>\n",
       "      <td>6.538662</td>\n",
       "      <td>6.524854</td>\n",
       "      <td>0.103565</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>447</td>\n",
       "      <td>6.533907</td>\n",
       "      <td>6.533114</td>\n",
       "      <td>0.103775</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>448</td>\n",
       "      <td>6.541430</td>\n",
       "      <td>6.530642</td>\n",
       "      <td>0.103505</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>449</td>\n",
       "      <td>6.526890</td>\n",
       "      <td>6.527396</td>\n",
       "      <td>0.104545</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>450</td>\n",
       "      <td>6.535476</td>\n",
       "      <td>6.525311</td>\n",
       "      <td>0.104375</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>451</td>\n",
       "      <td>6.534541</td>\n",
       "      <td>6.532917</td>\n",
       "      <td>0.102550</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>452</td>\n",
       "      <td>6.525293</td>\n",
       "      <td>6.530263</td>\n",
       "      <td>0.103905</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>453</td>\n",
       "      <td>6.528394</td>\n",
       "      <td>6.528207</td>\n",
       "      <td>0.104160</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>454</td>\n",
       "      <td>6.530740</td>\n",
       "      <td>6.526169</td>\n",
       "      <td>0.104425</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>455</td>\n",
       "      <td>6.519974</td>\n",
       "      <td>6.530317</td>\n",
       "      <td>0.103150</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>456</td>\n",
       "      <td>6.533288</td>\n",
       "      <td>6.521842</td>\n",
       "      <td>0.104250</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>457</td>\n",
       "      <td>6.527867</td>\n",
       "      <td>6.539558</td>\n",
       "      <td>0.104555</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>458</td>\n",
       "      <td>6.526958</td>\n",
       "      <td>6.535852</td>\n",
       "      <td>0.104105</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>459</td>\n",
       "      <td>6.523536</td>\n",
       "      <td>6.525081</td>\n",
       "      <td>0.103610</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>460</td>\n",
       "      <td>6.531389</td>\n",
       "      <td>6.522042</td>\n",
       "      <td>0.103615</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>461</td>\n",
       "      <td>6.536500</td>\n",
       "      <td>6.521406</td>\n",
       "      <td>0.104900</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>462</td>\n",
       "      <td>6.534000</td>\n",
       "      <td>6.532969</td>\n",
       "      <td>0.104145</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>463</td>\n",
       "      <td>6.523739</td>\n",
       "      <td>6.536882</td>\n",
       "      <td>0.104105</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>464</td>\n",
       "      <td>6.522480</td>\n",
       "      <td>6.534496</td>\n",
       "      <td>0.104540</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>465</td>\n",
       "      <td>6.527157</td>\n",
       "      <td>6.531318</td>\n",
       "      <td>0.105600</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>466</td>\n",
       "      <td>6.529359</td>\n",
       "      <td>6.534561</td>\n",
       "      <td>0.103315</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>467</td>\n",
       "      <td>6.524093</td>\n",
       "      <td>6.541412</td>\n",
       "      <td>0.104390</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>468</td>\n",
       "      <td>6.525823</td>\n",
       "      <td>6.526370</td>\n",
       "      <td>0.104060</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>469</td>\n",
       "      <td>6.515088</td>\n",
       "      <td>6.522309</td>\n",
       "      <td>0.104380</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>470</td>\n",
       "      <td>6.526257</td>\n",
       "      <td>6.528058</td>\n",
       "      <td>0.103865</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>471</td>\n",
       "      <td>6.536575</td>\n",
       "      <td>6.526790</td>\n",
       "      <td>0.104780</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>472</td>\n",
       "      <td>6.532519</td>\n",
       "      <td>6.532609</td>\n",
       "      <td>0.104160</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>473</td>\n",
       "      <td>6.529144</td>\n",
       "      <td>6.518861</td>\n",
       "      <td>0.104935</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>474</td>\n",
       "      <td>6.531743</td>\n",
       "      <td>6.527239</td>\n",
       "      <td>0.105275</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>475</td>\n",
       "      <td>6.525650</td>\n",
       "      <td>6.528985</td>\n",
       "      <td>0.104540</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>476</td>\n",
       "      <td>6.520637</td>\n",
       "      <td>6.519682</td>\n",
       "      <td>0.104025</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>477</td>\n",
       "      <td>6.530632</td>\n",
       "      <td>6.532765</td>\n",
       "      <td>0.103125</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>478</td>\n",
       "      <td>6.532729</td>\n",
       "      <td>6.532982</td>\n",
       "      <td>0.104390</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>479</td>\n",
       "      <td>6.537281</td>\n",
       "      <td>6.525083</td>\n",
       "      <td>0.104665</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>480</td>\n",
       "      <td>6.521245</td>\n",
       "      <td>6.534062</td>\n",
       "      <td>0.104890</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>481</td>\n",
       "      <td>6.531978</td>\n",
       "      <td>6.537467</td>\n",
       "      <td>0.103025</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>482</td>\n",
       "      <td>6.529412</td>\n",
       "      <td>6.530780</td>\n",
       "      <td>0.103810</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>483</td>\n",
       "      <td>6.524909</td>\n",
       "      <td>6.531938</td>\n",
       "      <td>0.103705</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>484</td>\n",
       "      <td>6.532334</td>\n",
       "      <td>6.527710</td>\n",
       "      <td>0.104075</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>485</td>\n",
       "      <td>6.527244</td>\n",
       "      <td>6.521181</td>\n",
       "      <td>0.104355</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>486</td>\n",
       "      <td>6.536951</td>\n",
       "      <td>6.537518</td>\n",
       "      <td>0.104540</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>487</td>\n",
       "      <td>6.530561</td>\n",
       "      <td>6.520513</td>\n",
       "      <td>0.104865</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>488</td>\n",
       "      <td>6.523617</td>\n",
       "      <td>6.524523</td>\n",
       "      <td>0.104395</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>489</td>\n",
       "      <td>6.525620</td>\n",
       "      <td>6.526902</td>\n",
       "      <td>0.104800</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>490</td>\n",
       "      <td>6.522083</td>\n",
       "      <td>6.536208</td>\n",
       "      <td>0.103245</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>491</td>\n",
       "      <td>6.533437</td>\n",
       "      <td>6.518033</td>\n",
       "      <td>0.105010</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>492</td>\n",
       "      <td>6.540241</td>\n",
       "      <td>6.528422</td>\n",
       "      <td>0.104360</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>493</td>\n",
       "      <td>6.522419</td>\n",
       "      <td>6.536194</td>\n",
       "      <td>0.103535</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>494</td>\n",
       "      <td>6.525544</td>\n",
       "      <td>6.521790</td>\n",
       "      <td>0.104680</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>495</td>\n",
       "      <td>6.524005</td>\n",
       "      <td>6.523792</td>\n",
       "      <td>0.104350</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>496</td>\n",
       "      <td>6.527014</td>\n",
       "      <td>6.531223</td>\n",
       "      <td>0.104135</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>497</td>\n",
       "      <td>6.536088</td>\n",
       "      <td>6.535356</td>\n",
       "      <td>0.103665</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>498</td>\n",
       "      <td>6.529639</td>\n",
       "      <td>6.534391</td>\n",
       "      <td>0.103625</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>499</td>\n",
       "      <td>6.519527</td>\n",
       "      <td>6.536194</td>\n",
       "      <td>0.103090</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>500</td>\n",
       "      <td>6.521369</td>\n",
       "      <td>6.539025</td>\n",
       "      <td>0.103695</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>501</td>\n",
       "      <td>6.529431</td>\n",
       "      <td>6.539706</td>\n",
       "      <td>0.103130</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>502</td>\n",
       "      <td>6.524120</td>\n",
       "      <td>6.515844</td>\n",
       "      <td>0.105000</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>503</td>\n",
       "      <td>6.520655</td>\n",
       "      <td>6.524033</td>\n",
       "      <td>0.105045</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>504</td>\n",
       "      <td>6.538678</td>\n",
       "      <td>6.532117</td>\n",
       "      <td>0.103880</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>505</td>\n",
       "      <td>6.531943</td>\n",
       "      <td>6.523864</td>\n",
       "      <td>0.105100</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>506</td>\n",
       "      <td>6.520369</td>\n",
       "      <td>6.518298</td>\n",
       "      <td>0.105455</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>507</td>\n",
       "      <td>6.528934</td>\n",
       "      <td>6.536464</td>\n",
       "      <td>0.104115</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>508</td>\n",
       "      <td>6.521956</td>\n",
       "      <td>6.521888</td>\n",
       "      <td>0.106540</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>509</td>\n",
       "      <td>6.523351</td>\n",
       "      <td>6.517278</td>\n",
       "      <td>0.105245</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>510</td>\n",
       "      <td>6.532385</td>\n",
       "      <td>6.543293</td>\n",
       "      <td>0.103160</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>511</td>\n",
       "      <td>6.525801</td>\n",
       "      <td>6.527959</td>\n",
       "      <td>0.103720</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>512</td>\n",
       "      <td>6.521687</td>\n",
       "      <td>6.534050</td>\n",
       "      <td>0.103750</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>513</td>\n",
       "      <td>6.525527</td>\n",
       "      <td>6.544471</td>\n",
       "      <td>0.103685</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>514</td>\n",
       "      <td>6.526650</td>\n",
       "      <td>6.518999</td>\n",
       "      <td>0.104345</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>515</td>\n",
       "      <td>6.534153</td>\n",
       "      <td>6.526691</td>\n",
       "      <td>0.105450</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>516</td>\n",
       "      <td>6.526698</td>\n",
       "      <td>6.525022</td>\n",
       "      <td>0.104305</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>517</td>\n",
       "      <td>6.528681</td>\n",
       "      <td>6.527928</td>\n",
       "      <td>0.104520</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>518</td>\n",
       "      <td>6.522098</td>\n",
       "      <td>6.526503</td>\n",
       "      <td>0.104770</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>519</td>\n",
       "      <td>6.539927</td>\n",
       "      <td>6.521769</td>\n",
       "      <td>0.105430</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>520</td>\n",
       "      <td>6.537958</td>\n",
       "      <td>6.517988</td>\n",
       "      <td>0.104875</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>521</td>\n",
       "      <td>6.531106</td>\n",
       "      <td>6.526042</td>\n",
       "      <td>0.104600</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>522</td>\n",
       "      <td>6.523558</td>\n",
       "      <td>6.531513</td>\n",
       "      <td>0.103020</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>523</td>\n",
       "      <td>6.526651</td>\n",
       "      <td>6.519314</td>\n",
       "      <td>0.104250</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>524</td>\n",
       "      <td>6.511649</td>\n",
       "      <td>6.530027</td>\n",
       "      <td>0.105115</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>525</td>\n",
       "      <td>6.535858</td>\n",
       "      <td>6.532441</td>\n",
       "      <td>0.104340</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>526</td>\n",
       "      <td>6.521970</td>\n",
       "      <td>6.518223</td>\n",
       "      <td>0.105245</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>527</td>\n",
       "      <td>6.532468</td>\n",
       "      <td>6.527277</td>\n",
       "      <td>0.104300</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>528</td>\n",
       "      <td>6.526601</td>\n",
       "      <td>6.531707</td>\n",
       "      <td>0.103485</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>529</td>\n",
       "      <td>6.523571</td>\n",
       "      <td>6.529358</td>\n",
       "      <td>0.104155</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>530</td>\n",
       "      <td>6.520521</td>\n",
       "      <td>6.519491</td>\n",
       "      <td>0.105130</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>531</td>\n",
       "      <td>6.521124</td>\n",
       "      <td>6.522607</td>\n",
       "      <td>0.104280</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>532</td>\n",
       "      <td>6.528876</td>\n",
       "      <td>6.539262</td>\n",
       "      <td>0.103710</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>533</td>\n",
       "      <td>6.546336</td>\n",
       "      <td>6.542011</td>\n",
       "      <td>0.103150</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>534</td>\n",
       "      <td>6.530123</td>\n",
       "      <td>6.543643</td>\n",
       "      <td>0.102715</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>535</td>\n",
       "      <td>6.525665</td>\n",
       "      <td>6.535830</td>\n",
       "      <td>0.103510</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>536</td>\n",
       "      <td>6.531126</td>\n",
       "      <td>6.534921</td>\n",
       "      <td>0.104065</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>537</td>\n",
       "      <td>6.534035</td>\n",
       "      <td>6.514917</td>\n",
       "      <td>0.103615</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>538</td>\n",
       "      <td>6.522390</td>\n",
       "      <td>6.530608</td>\n",
       "      <td>0.104925</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>539</td>\n",
       "      <td>6.520551</td>\n",
       "      <td>6.525939</td>\n",
       "      <td>0.105080</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>540</td>\n",
       "      <td>6.526837</td>\n",
       "      <td>6.528681</td>\n",
       "      <td>0.104045</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>541</td>\n",
       "      <td>6.537760</td>\n",
       "      <td>6.525632</td>\n",
       "      <td>0.104715</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>542</td>\n",
       "      <td>6.526385</td>\n",
       "      <td>6.514343</td>\n",
       "      <td>0.104270</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>543</td>\n",
       "      <td>6.521788</td>\n",
       "      <td>6.532785</td>\n",
       "      <td>0.104050</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>544</td>\n",
       "      <td>6.529193</td>\n",
       "      <td>6.543674</td>\n",
       "      <td>0.104060</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>545</td>\n",
       "      <td>6.529762</td>\n",
       "      <td>6.531007</td>\n",
       "      <td>0.103900</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>546</td>\n",
       "      <td>6.525501</td>\n",
       "      <td>6.524037</td>\n",
       "      <td>0.105045</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>547</td>\n",
       "      <td>6.522887</td>\n",
       "      <td>6.531171</td>\n",
       "      <td>0.104250</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>548</td>\n",
       "      <td>6.531322</td>\n",
       "      <td>6.527844</td>\n",
       "      <td>0.104180</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>549</td>\n",
       "      <td>6.537862</td>\n",
       "      <td>6.535613</td>\n",
       "      <td>0.103705</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>550</td>\n",
       "      <td>6.537239</td>\n",
       "      <td>6.526794</td>\n",
       "      <td>0.103775</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>551</td>\n",
       "      <td>6.530943</td>\n",
       "      <td>6.515001</td>\n",
       "      <td>0.104790</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>552</td>\n",
       "      <td>6.541019</td>\n",
       "      <td>6.545216</td>\n",
       "      <td>0.103445</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>553</td>\n",
       "      <td>6.524992</td>\n",
       "      <td>6.525232</td>\n",
       "      <td>0.104150</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>554</td>\n",
       "      <td>6.526134</td>\n",
       "      <td>6.526543</td>\n",
       "      <td>0.105555</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>555</td>\n",
       "      <td>6.535842</td>\n",
       "      <td>6.520853</td>\n",
       "      <td>0.104330</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>556</td>\n",
       "      <td>6.520172</td>\n",
       "      <td>6.530223</td>\n",
       "      <td>0.104020</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>557</td>\n",
       "      <td>6.530609</td>\n",
       "      <td>6.529512</td>\n",
       "      <td>0.103465</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>558</td>\n",
       "      <td>6.529701</td>\n",
       "      <td>6.522386</td>\n",
       "      <td>0.104900</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>559</td>\n",
       "      <td>6.527463</td>\n",
       "      <td>6.529561</td>\n",
       "      <td>0.103250</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>560</td>\n",
       "      <td>6.531844</td>\n",
       "      <td>6.526873</td>\n",
       "      <td>0.103715</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>561</td>\n",
       "      <td>6.530390</td>\n",
       "      <td>6.512636</td>\n",
       "      <td>0.105075</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>562</td>\n",
       "      <td>6.537054</td>\n",
       "      <td>6.531092</td>\n",
       "      <td>0.103705</td>\n",
       "      <td>01:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>563</td>\n",
       "      <td>6.524353</td>\n",
       "      <td>6.521358</td>\n",
       "      <td>0.105050</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>564</td>\n",
       "      <td>6.523197</td>\n",
       "      <td>6.527453</td>\n",
       "      <td>0.104355</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>565</td>\n",
       "      <td>6.526045</td>\n",
       "      <td>6.544784</td>\n",
       "      <td>0.103035</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>566</td>\n",
       "      <td>6.531272</td>\n",
       "      <td>6.534656</td>\n",
       "      <td>0.102550</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>567</td>\n",
       "      <td>6.520452</td>\n",
       "      <td>6.542916</td>\n",
       "      <td>0.103060</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>568</td>\n",
       "      <td>6.536772</td>\n",
       "      <td>6.528536</td>\n",
       "      <td>0.103790</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>569</td>\n",
       "      <td>6.538841</td>\n",
       "      <td>6.530069</td>\n",
       "      <td>0.104300</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>570</td>\n",
       "      <td>6.530787</td>\n",
       "      <td>6.532086</td>\n",
       "      <td>0.103920</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>571</td>\n",
       "      <td>6.518633</td>\n",
       "      <td>6.534463</td>\n",
       "      <td>0.103225</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>572</td>\n",
       "      <td>6.530864</td>\n",
       "      <td>6.523216</td>\n",
       "      <td>0.103750</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>573</td>\n",
       "      <td>6.525391</td>\n",
       "      <td>6.539399</td>\n",
       "      <td>0.103670</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>574</td>\n",
       "      <td>6.520053</td>\n",
       "      <td>6.525680</td>\n",
       "      <td>0.104610</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>575</td>\n",
       "      <td>6.529966</td>\n",
       "      <td>6.540234</td>\n",
       "      <td>0.103440</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>576</td>\n",
       "      <td>6.528468</td>\n",
       "      <td>6.528887</td>\n",
       "      <td>0.104465</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>577</td>\n",
       "      <td>6.525586</td>\n",
       "      <td>6.537187</td>\n",
       "      <td>0.104520</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>578</td>\n",
       "      <td>6.529277</td>\n",
       "      <td>6.522458</td>\n",
       "      <td>0.104440</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>579</td>\n",
       "      <td>6.535731</td>\n",
       "      <td>6.536839</td>\n",
       "      <td>0.102055</td>\n",
       "      <td>01:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>580</td>\n",
       "      <td>6.520123</td>\n",
       "      <td>6.541935</td>\n",
       "      <td>0.102995</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>581</td>\n",
       "      <td>6.530318</td>\n",
       "      <td>6.517693</td>\n",
       "      <td>0.104320</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>582</td>\n",
       "      <td>6.524686</td>\n",
       "      <td>6.529826</td>\n",
       "      <td>0.104495</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>583</td>\n",
       "      <td>6.527271</td>\n",
       "      <td>6.519566</td>\n",
       "      <td>0.105340</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>584</td>\n",
       "      <td>6.531824</td>\n",
       "      <td>6.526417</td>\n",
       "      <td>0.103655</td>\n",
       "      <td>01:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>585</td>\n",
       "      <td>6.516602</td>\n",
       "      <td>6.521539</td>\n",
       "      <td>0.103715</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>586</td>\n",
       "      <td>6.526930</td>\n",
       "      <td>6.539391</td>\n",
       "      <td>0.102645</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>587</td>\n",
       "      <td>6.537572</td>\n",
       "      <td>6.534668</td>\n",
       "      <td>0.103275</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>588</td>\n",
       "      <td>6.527786</td>\n",
       "      <td>6.526002</td>\n",
       "      <td>0.104125</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>589</td>\n",
       "      <td>6.530625</td>\n",
       "      <td>6.526585</td>\n",
       "      <td>0.104870</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>590</td>\n",
       "      <td>6.530534</td>\n",
       "      <td>6.525718</td>\n",
       "      <td>0.104550</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>591</td>\n",
       "      <td>6.536829</td>\n",
       "      <td>6.535070</td>\n",
       "      <td>0.104870</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>592</td>\n",
       "      <td>6.546130</td>\n",
       "      <td>6.526529</td>\n",
       "      <td>0.105180</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>593</td>\n",
       "      <td>6.519838</td>\n",
       "      <td>6.538762</td>\n",
       "      <td>0.103710</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>594</td>\n",
       "      <td>6.533573</td>\n",
       "      <td>6.531194</td>\n",
       "      <td>0.104005</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>595</td>\n",
       "      <td>6.525714</td>\n",
       "      <td>6.528217</td>\n",
       "      <td>0.104810</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>596</td>\n",
       "      <td>6.527365</td>\n",
       "      <td>6.533042</td>\n",
       "      <td>0.103640</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>597</td>\n",
       "      <td>6.529465</td>\n",
       "      <td>6.525684</td>\n",
       "      <td>0.104100</td>\n",
       "      <td>01:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>598</td>\n",
       "      <td>6.530456</td>\n",
       "      <td>6.521050</td>\n",
       "      <td>0.105045</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>599</td>\n",
       "      <td>6.525094</td>\n",
       "      <td>6.520670</td>\n",
       "      <td>0.104615</td>\n",
       "      <td>01:14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_EPOCHS = 600\n",
    "learn.fit(NUM_EPOCHS, lr=1e-3, cbs=SaveModelCallback(fname='text_embeddings', every_epoch=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "NUM_EPOCHS = 200\n",
    "learn.fit(NUM_EPOCHS, lr=1e-4, cbs=SaveModelCallback(fname='text_embeddings_2', every_epoch=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evalute embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils import Embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "embeddings = learn.model.embeddings.weight.cpu().detach().numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "e = Embeddings(\n",
    "    embeddings,\n",
    "    vocab\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fast: ['fast', 'paced', 'slow', 'clumsily', 'forwarding']\n",
      "lost: ['lost', 'losing', 'missed', 'regained', 'scored']\n",
      "small: ['small', 'large', 'smaller', 'remote', 'miniature']\n",
      "true: ['true', 'surprising', 'symbolic', 'bridegroom', 'believer']\n",
      "crazy: ['crazy', 'hopeful', 'dangerously', 'horribly', 'immaculately']\n",
      "slow: ['slow', 'tame', 'tough', 'fast', 'mood']\n"
     ]
    }
   ],
   "source": [
    "for w in ['fast', 'lost', 'small', 'true', 'crazy', 'slow']:\n",
    "    print(f'{w}: {e.nn_words_to(e[w])}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluating embeddings using [word-embeddings-benchmarks](https://github.com/kudkudak/word-embeddings-benchmarks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "from six import iteritems\n",
    "from web.datasets.similarity import fetch_MEN, fetch_WS353, fetch_SimLex999\n",
    "from web.embeddings import fetch_GloVe\n",
    "from web.evaluate import evaluate_similarity\n",
    "from web.embedding import Embedding, Vocabulary\n",
    "from gensim.models import Word2Vec\n",
    "from gensim.models import KeyedVectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "tasks = {\n",
    "    \"MEN\": fetch_MEN(),\n",
    "    \"WS353\": fetch_WS353(),\n",
    "    \"SIMLEX999\": fetch_SimLex999()\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "our_embeddings = Embedding(\n",
    "    Vocabulary(vocab),\n",
    "    embeddings\n",
    ")\n",
    "\n",
    "speech2vec = KeyedVectors.load_word2vec_format('../speech2vec-pretrained-vectors/word2vec/50.vec', binary=False) \n",
    "speech2vec_embeddings = Embedding(Vocabulary(list(speech2vec.vocab.keys())), speech2vec.vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Missing 392 words. Will replace them with mean vector\n",
      "/opt/conda/lib/python3.7/site-packages/web-0.0.1-py3.7.egg/web/evaluate.py:336: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
      "  A = np.vstack(w.get(word, mean_vector) for word in X[:, 0])\n",
      "/opt/conda/lib/python3.7/site-packages/web-0.0.1-py3.7.egg/web/evaluate.py:337: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
      "  B = np.vstack(w.get(word, mean_vector) for word in X[:, 1])\n",
      "Missing 61 words. Will replace them with mean vector\n",
      "Missing 24 words. Will replace them with mean vector\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spearman correlation of scores on MEN 0.38720472306719\n",
      "Spearman correlation of scores on WS353 0.42593220452566005\n",
      "Spearman correlation of scores on SIMLEX999 0.1798777763845928\n"
     ]
    }
   ],
   "source": [
    "for name, data in iteritems(tasks):\n",
    "    print(\"Spearman correlation of scores on {} {}\".format(name, evaluate_similarity(our_embeddings, data.X, data.y)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Missing 392 words. Will replace them with mean vector\n",
      "Missing 61 words. Will replace them with mean vector\n",
      "Missing 24 words. Will replace them with mean vector\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spearman correlation of scores on MEN 0.6056592803599269\n",
      "Spearman correlation of scores on WS353 0.43349390636024643\n",
      "Spearman correlation of scores on SIMLEX999 0.25938770901422736\n"
     ]
    }
   ],
   "source": [
    "for name, data in iteritems(tasks):\n",
    "    print(\"Spearman correlation of scores on {} {}\".format(name, evaluate_similarity(speech2vec_embeddings, data.X, data.y)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loss decrease and improvements on semantic tasks as training progresses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "\n",
    "val_losses, accuracies, task_perf = [], [], []\n",
    "for i in range(NUM_EPOCHS):\n",
    "    learn.load(f'text_embeddings_{i}')\n",
    "    loss, accuracy = learn.validate()\n",
    "    val_losses.append(loss)\n",
    "    accuracies.append(accuracy)\n",
    "    \n",
    "    embeddings = learn.model.embeddings.weight.cpu().detach().numpy()\n",
    "    our_embeddings = Embedding(\n",
    "        Vocabulary([w.lower() for w in vocab]),\n",
    "        embeddings\n",
    "    )\n",
    "\n",
    "    task_perf.append([evaluate_similarity(our_embeddings, data.X, data.y) for name, data in iteritems(tasks)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "men, ws353, simlex999 = list(zip(*task_perf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "ax1.plot(val_losses, label='val loss')\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(men, label='MEN', c='g')\n",
    "ax2.plot(ws353, label='WS353', c='m')\n",
    "ax2.plot(simlex999, label='SIMLEX999', c='y')\n",
    "\n",
    "ax1.legend(loc=[0.07, 0.9])\n",
    "ax2.legend(loc=[0.7, 0.15])\n",
    "\n",
    "ax1.set_xlabel('epochs');"
   ]
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}