georgehc/UDA Clustering on Text - Longer Version with Clustering Metrics and HDBSCAN.ipynb Secret

## UDA Clustering on Text - Longer Version with Clustering Metrics and HDBSCAN.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# UDA Clustering on Text (Includes Clustering Metrics and HDBSCAN)\n",
    "\n",
    "Author: George H. Chen (georgechen [at symbol] cmu.edu)\n",
    "\n",
    "We begin with some boilerplate imports."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "np.set_printoptions(precision=5, suppress=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading in Data\n",
    "\n",
    "Let's load a preprocessed version of the 20 Newsgroups dataset: [download here](https://www.andrew.cmu.edu/user/georgech/95-865/Lectures/lemmatized_text.xz).\n",
    "\n",
    "The code notebook that produces the above preprocessed dataset is available here: [GitHub gist](https://gist.github.com/georgehc/3a0781dcedb6bbdc159c0fc17409b5d4)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('lemmatized_text.xz', 'rb') as f:\n",
    "    docs = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      " Koberg , \n",
      "\n",
      "\t just a couple of minor correction here ... \n",
      "\n",
      "\t 1 )   the church of Christ do not usually believe in speak in \n",
      " tongue , in fact many of they be know for be strongly oppose to \n",
      " pentecostal teaching .   you be probably think of Church of God in \n",
      " Christ , the large african - american Pentecostal denomination . \n",
      "\n",
      "\t 2 )   I be not sure what you mean by \" signify believer \"   but it \n",
      " should be point out that the assembly of God do not now , nor have it \n",
      " ever , hold that speak in tongue be the sign that one be a Christian . \n",
      " the doctrine that traditional pentecostal ( include the A / g ) maintain be \n",
      " that speak in tongue be the sign of a second experience after become \n",
      " a Christian in which one be \" baptize in the Holy Spirit \"   that may be \n",
      " what you be refer to , but I point this out because pentecostal be \n",
      " frequently label as believe that you have to speak in tongue in order \n",
      " to be a Christian .   such a position be only hold by some group and not the \n",
      " majority of Pentecostals .    many Pentecostals will quote the passage in \n",
      " Mark 16 about \" these sign follow they that believe \" but they generally \n",
      " do not interpret this as mean if you do not pactice the sign you be not \n",
      " \" save \" . \n",
      "\n",
      "\t 3 )   I know it be hard to summarize the belief of a movement that \n",
      " have such diversity , but I think you have make some pretty big \n",
      " generalization here .   do \" Neo - Pentecostals \" only believe in tongue as a \n",
      " sign and tongue as prayer but not tongue as revelatory with a message ? \n",
      " I have never hear of that before .   in fact I would have characterize they \n",
      " as believe the same as pentecostal except less likely to see tongue as \n",
      " a sign of Spirit Baptism .   also , while neo - Pentecostals may not be \n",
      " incline to speak in tongue in the non - pentecostal church they attend , \n",
      " they do have their own meeting and , in many case , a whole church will be \n",
      " charismatic .\n"
     ]
    }
   ],
   "source": [
    "print(docs[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Computing term frequencies for every document\n",
    "\n",
    "We now fit a `CountVectorizer` model that will compute, for each post, what its raw word count histograms are (the \"term frequencies\" we saw in week 1).\n",
    "\n",
    "The output of the following cell is the term-frequencies matrix, where rows index different posts/text documents, and columns index different vocabulary words. A note about the arguments to `CountVectorizer`:\n",
    "\n",
    "- `max_df`: we only keep words that appear in at most this fraction of the documents\n",
    "- `min_df`: we only keep words that appear in at least this many documents\n",
    "- `stop_words`: whether to remove stop words\n",
    "- `max_features`: among words that don't get removed due to the above 3 arguments, we keep the top `max_features` number of most frequently occuring words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab_size = 30000\n",
    "\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "# CountVectorizer does tokenization and can remove terms that occur too frequently, not frequently enough, or that are stop words\n",
    "\n",
    "# document frequency (df) means number of documents a word appears in\n",
    "tf_vectorizer = CountVectorizer(max_df=0.8,\n",
    "                                min_df=2,\n",
    "                                stop_words='english',\n",
    "                                max_features=vocab_size)\n",
    "tf = tf_vectorizer.fit_transform(docs)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can verify that there are 10,000 rows (corresponding to posts), and 30,000 columns (corresponding to words)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 30000)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A note about the `tf` matrix: this actually is stored as what's called a sparse matrix (rather than a 2D NumPy array that you're more familiar with). The reason is that often these matrices are really large and the vast majority of entries are 0, so it's possible to save space by not storing where the 0's are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "scipy.sparse._csr.csr_matrix"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(tf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " To convert `tf` to a 2D NumPy table, you can run `tf.toarray()` (this does not modify the original `tf` variable)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(tf.toarray())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf = tf.toarray()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can figure out what words the different columns correspond to by using the `get_feature_names_out()` function; the output is in the same order as the column indices. In particular, we can index into the following list (i.e., so given a column index, we can figure out which word it corresponds to)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "vocab = tf_vectorizer.get_feature_names_out()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['00', '000', '0000', ..., 'zy', 'zyxel', 'zz'],\n",
       "      shape=(30000,), dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vocab"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also go in reverse: given a word, we can figure out which column index it corresponds to. To do this, we use the `vocabulary_` attribute. (This converts a word into a \"word index\".)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(26313)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_vectorizer.vocabulary_['technology']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We write a few helper functions that cover concepts we've seen in previous lecture demos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_top_words(tf_1d_table, vocab, num_top_words=20):\n",
    "    return sorted(zip(tf_1d_table, vocab), reverse=True)[:num_top_words]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_top_words(tf_1d_table, vocab, num_top_words=20):\n",
    "    sorted_tuples = get_top_words(tf_1d_table, vocab, num_top_words)\n",
    "\n",
    "    for _, word in sorted_tuples:\n",
    "        print(word, end=' ')\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_top_words(tf_1d_table, vocab, num_top_words=20, divide_by_sum=False):\n",
    "    if divide_by_sum:\n",
    "        tf_1d_table = tf_1d_table / tf_1d_table.sum()\n",
    "    sorted_tuples = get_top_words(tf_1d_table, vocab, num_top_words)\n",
    "    top_counts, top_words = zip(*sorted_tuples)\n",
    "\n",
    "    plt.bar(range(num_top_words), top_counts)\n",
    "    plt.xticks(range(num_top_words), top_words, rotation=90)\n",
    "    plt.xlabel('Word')\n",
    "    plt.ylabel('Frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from wordcloud import WordCloud\n",
    "\n",
    "def plot_word_cloud(tf_1d_table, vocab, num_top_words=20):\n",
    "    wc = WordCloud(max_words=num_top_words, random_state=0)\n",
    "    wc.generate_from_frequencies(dict(zip(vocab, tf_1d_table)))\n",
    "    plt.imshow(wc)\n",
    "    plt.gca().set_axis_off()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize a row of `tf`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0], shape=(30000,))"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_words(tf[0], vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_word_cloud(tf[0], vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tongue sign speak believe pentecostals church christian think spirit point neo mean know hold god fact christ usually traditional teaching \n"
     ]
    }
   ],
   "source": [
    "print_top_words(tf[0], vocab)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also visualize the term frequencies across all 10,000 documents by summing across the documents' different feature vectors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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pY1+s1FQU763Ou/4WVo3/AD7X3/ftP/iq19B8S2XiLz/skU6fZ9u7zVAzuzjGCfQ143XffC//AJin/bL/ANnp18NThTco7iw+KqVKijLY3/8AhOfDf/QR/wDIEn/xNH/Cc+G/+gj/AOQJP/ia8iorT6jT7sy+v1OyPbrDWdO1KykvbS5V7eIkPIwKBcAE53Adj1pv9v6N/wBBex/8CU/xrkfCn/JO9a/7b/8Aopa4GsIYSM5SV9mdE8ZKEYu26PbP7f0b/oL2P/gSn+NXo5EljWSN1dHAZWU5DA9CDXgtem61/wAktj/69Lb+aVNXCqDik93Yqji3UUm1srnX0V4HRWn1D+9+Bl/aH938T3yiuW+IN5dWWgwSWlzLbubpVLROVJG1uMj6V53/AG/rP/QXvv8AwJf/ABrClhZVY8yZ0VsXGlPlaPbaK8g0TW9Wl17T45NUvHR7qNWVrhyGBYZBGa7jxL4y/wCEd1GO0+wfaN8Ik3edsxkkYxtPpSnhZxkorVsdPFQlBzeiR09FcD/wtD/qDf8Akz/9hV/Q/Hn9taxBp/8AZvk+du/eefuxhSem0elS8NVirtFRxVGTsmdfRXIa548/sXWJ9P8A7N87ydv7zz9ucqD02n1qh/wtD/qDf+TP/wBhQsNVkrpBLFUYuzZ31FYHhfxR/wAJJ9q/0P7N9n2f8td+7du9hj7tY9/8RvsOo3Np/ZO/7PM8e77RjdtJGcbeOlSqFRycUtUU8RTUVJvRnb0VwP8AwtD/AKg3/kz/APYV03hrXv8AhItOku/s32fZMY9vmb84AOc4HrROhUguaS0CGIp1HyxepsUVyH/CytG/59r7/v2n/wAVR/wsrRv+fa+/79p/8VT+r1f5Q+s0f5kdfRWfY61aX2ijV18yK22O58xfmUKSCSBn0PSqH/Cc+G/+gj/5Ak/+JrNU5u6S2LdWCSba1N+isD/hOfDf/QR/8gSf/E1fu9c02x06HULm52W1xt8uTYx3bhkcAZHAodOa3TBVYPVNGhRWB/wnPhv/AKCP/kCT/wCJo/4Tnw3/ANBH/wAgSf8AxNV7Gp/K/uF7an/MvvN+is/VNc03RfK/tC58nzs7PkZs4xnoD6iqH/Cc+G/+gj/5Ak/+JqVTnJXSY3VhF2bRv0Vj2PivRNSvEtLS98yeTO1fKcZwCTyRjoDUmp+I9J0e4W3v7vyZWQOF8t2yMkZ4B9DR7Od7W1H7SFua6salFYH/AAnPhv8A6CP/AJAk/wDiat6Z4j0nWLhrewu/OlVC5Xy3XAyBnkD1FN0ppXaYlVpt2UkalFFFZmhhXf8AyPmlf9g28/8ARltW7WFd/wDI+aV/2Dbz/wBGW1btABRRRQAUUUUAFFFFABRRRQBVvtT0/TER9Qvra0VztRriVYwx9Bk81ZVgyhlIIIyCO9ctcfY/+Fhz/wBp+T5f9kL9n8/G3HmP52M8dPLz7YqfwMZR4HsCq7sRv5AckAx728vnnA2bfwoAmu/+R80r/sG3n/oy2rdrlJoPFsuvWuqf2VpA+z200Hl/2nJ83mNG2c+Rxjy+mO/tV77X4t/6Aukf+DWT/wCMUAbteReOf+Rwvv8Atn/6LWvQPtfi3/oC6R/4NZP/AIxXI654O8Wa1rE+ofZ9Ih87b8n26RsYUDr5I9K6sLUjTm3J9DkxdOVSCUV1OOrvvhf/AMxT/tl/7PXMx+C/E0urXGmLHpnnW8Ec7E3cm0q7OBj911zG2fwrqfC+heLPDf2rFjpFz9o2f8xCRNu3P/TE5+9XViMRTnTcYvU5MPhqsKqlJaHG6/8A8jFqX/X3L/6GaoV1V/4E8WX2o3N35WkJ58rybftsh27iTjPle9Ztn4L8TXtzfW8UemBrGcQSFruTBYxpJx+66YcfjmtY4qkopXMpYSs5N2O1+Gv/ACLtx/19t/6AleZV6R4a0zxZ4e06S0GnaRcb5TJu/tGRcZAGMeQfSuZ/4V14s/u6T/4GSf8AxqsaVenGpOTejN6uHqSpwilqjna9N0X/AJJbJ/16XP8AN64rTvBfibVLZ7iCPTFVJ5YCHu5Ad0cjRt0i6ZU49q7Cy0zxZZ+F20P+ztIfdFJH539oyD75bnHkdt3r2oxFenNJRfVBhsPUhJuS6M83oroj8O/FYBO3SeP+nyT/AONVV0zwV4m1bSrTUrePS1hu4UmjD3cgYKwBGcRHnmuj63R7nN9UrdvyOm8V/wDJO9F/7Yf+imrga9B1XQvFmqeHrLSPsOkRfZPL/e/2hId21CvTyeM5z1rltR8F+JtLtkuJ49MZXnigAS7kJ3SSLGvWLplhn2rChiKcItN9Wb4jDVZzTiui/Ix6774of8wv/tr/AOyVh/8ACuvFn93Sf/AyT/41W/4o0LxZ4k+y5sdItvs+/wD5iEj7t2P+mIx92ieIpupGSeiuFPDVVSnFrV2PPq3/AAN/yOFj/wBtP/RbVBeeC/E1lc2NvLHpha+nMEZW7kwGEbyc/uumEP44rZ0Pwd4s0XWINQ+z6RN5O75Pt0i5ypHXyT61pUxNKUGk+hnSwtaM02uoz4lf8jFb/wDXov8A6G9cjXc+JfDHizxDqMd2bTSLfZEI9v2+Rs4JOc+SPWuek8F+JotWt9MaPTPOuIJJ1Iu5NoVGQHP7rrmRcfjU0cTSjTUW9Sq+GqyqSkloa3w1/wCRiuP+vRv/AENKoeOf+Rwvv+2f/ota2vDXhjxZ4e1GS7FppFxviMe37fIuMkHOfJPpVfXPB3izWtYn1D7PpEPnbfk+3SNjCgdfJHpUKvT9u530saPD1Pq6hbW5x1d98L/+Yp/2y/8AZ65mPwX4ml1a40xY9M863gjnYm7k2lXZwMfuuuY2z+FdT4X0LxZ4b+1YsdIuftGz/mISJt25/wCmJz96niMRTnTcYvUnD4arCqpSWh59RXRf8K68Wf3dJ/8AAyT/AONVV07wX4m1S2e4gj0xVSeWAh7uQHdHI0bdIumVOPat/rdHuYfVK3b8jpvCn/JO9a/7b/8Aopa4GvQdK0LxZpfh690j7DpEv2vzP3v9oSDbuQL08nnGM9awD8O/FYBO3SeP+nyT/wCNVhSxFOMptvdm9XDVZQgktl+pztem61/yS2P/AK9Lb+aVxWmeCvE2raVaalbx6WsN3Ck0Ye7kDBWAIziI8812F7pniy88Lrof9naQm2KOPzv7RkP3CvOPI77fXvSr16cnBp7Mqhh6kIzTW6PN6K2NT8FeJtJ0q71K4j0tobSF5pAl3IWKqCTjMQ54q0Ph34rIB26Tz/0+Sf8Axquj63R7nN9UrdvyOr+JX/Iu2/8A19r/AOgPXmVekeJdM8WeIdOjtDp2kW+yUSbv7RkbOARjHkD1rj9R8F+JtLtkuJ49MZXnigAS7kJ3SSLGvWLplhn2rnw1enCnyyep04rD1KlTmitCtoH/ACMWm/8AX3F/6GK3/iV/yMVv/wBei/8Aob1HYeBPFljqNtd+VpD+RKkm37bIN20g4z5XtV/xL4Y8WeIdRjuzaaRb7IhHt+3yNnBJznyR605Yim60ZX0syY4aqqMo21ujhq3/AAN/yOFj/wBtP/RbVBeeC/E1lc2NvLHpha+nMEZW7kwGEbyc/uumEP44rZ0Pwd4s0XWINQ+z6RN5O75Pt0i5ypHXyT61pUxNKUGk+hnSwtaM02upm+Of+Rwvv+2f/otawK7HXPB3izWtYn1D7PpEPnbfk+3SNjCgdfJHpWNH4L8TS6tcaYsemedbwRzsTdybSrs4GP3XXMbZ/CiniaUYJN9Aq4WtKbaXU6b4X/8AMU/7Zf8As9chr/8AyMWpf9fcv/oZrsvC+heLPDf2rFjpFz9o2f8AMQkTbtz/ANMTn71ZF/4E8WX2o3N35WkJ58rybftsh27iTjPle9ZQr01WlJvR2Np4eo6EYpaq5ytem/DX/kXbj/r7b/0BK4qz8F+Jr25vreKPTA1jOIJC13JgsY0k4/ddMOPxzXYeGtM8WeHtOktBp2kXG+Uybv7RkXGQBjHkH0oxNenOnyxeoYXD1KdTmktDzeiui/4V14s/u6T/AOBkn/xqquneC/E2qWz3EEemKqTywEPdyA7o5GjbpF0ypx7V0fW6Pc5vqlbt+R2ui/8AJLZP+vS5/m9eZV6RZaZ4ss/C7aH/AGdpD7opI/O/tGQffLc48jtu9e1cyfh34rAJ26Tx/wBPkn/xquehXpxc23uzpr4epOMElsjna77xX/yTvRf+2H/opq5nTPBXibVtKtNSt49LWG7hSaMPdyBgrAEZxEeea6nVdC8Wap4estI+w6RF9k8v97/aEh3bUK9PJ4znPWnVxFOUoNPZk0sNVjCaa3X6nn1FbGo+C/E2l2yXE8emMrzxQAJdyE7pJFjXrF0ywz7Va/4V14s/u6T/AOBkn/xqt/rdHuYfVK3b8jc+KH/ML/7a/wDslcDXoPijQvFniT7Lmx0i2+z7/wDmISPu3Y/6YjH3a5a88F+JrK5sbeWPTC19OYIyt3JgMI3k5/ddMIfxxWGHxFOFNRk9TfEYarOq5RWhP4G/5HCx/wC2n/otqv8AxK/5GK3/AOvRf/Q3p+h+DvFmi6xBqH2fSJvJ3fJ9ukXOVI6+SfWrHiXwx4s8Q6jHdm00i32RCPb9vkbOCTnPkj1pOvT9up30sUsPU+ruFtbnDV13w1/5GK4/69G/9DSsmTwX4mi1a30xo9M864gknUi7k2hUZAc/uuuZFx+NdD4a8MeLPD2oyXYtNIuN8Rj2/b5Fxkg5z5J9KutiaUqbinqZ0MNVjUjJrQ9DorC+1+Lf+gLpH/g1k/8AjFH2vxb/ANAXSP8Awayf/GK8k9gLv/kfNK/7Bt5/6Mtq3a560tNdufE1tqWpWdjaw21pPABb3bzMzSPEe8a4A8s+vWuhoAKKKKACiiigAooooAKKKKAKt9pmn6miJqFjbXiodyLcQrIFPqMjirKqFUKoAAGAB2paKACiiigApKWqupJHJpd2kts91G0DhrdPvSjacqORyenUdaAJFtoEu5LsRqJ5UWN5O7KpYqPwLN+dTV57Y6drFrqen/25O2oWSTr5Fil4Hexcv8jSHgz7eOSflxnDda9CoAKhhtYLeWeWKJUe4cSSkfxttC5P4Ko/Cs/xPdXdl4eubizdo5V2AyIm9okLqHcDnJVCzdO1cz4Y8QfbrvTbCy1htSaO9vRct5glP2ZWkETOR0yRHjpkHjigDvKazqpUMwBY4UE9T1wPyNOrH8TQW1zpiw3GiSaxvlAjgjCgo+Dh9zEbMc/NnPPvQBpW1rBZxGK3iWNGd5CF7szFmP4kk/jU1cVZaX4z0mCe8t72KSJF3Q6PPI1ySB/CLhtrAnoM5ANdrQAhGRio7W1gsrSG0to1iggQRxovRVAwAPwrmvHF4bJLJ0TWRIS4WfTnKxxfd5lOGXHplT0PSn+Cr3U722uZNQ1vTtUUMvlfZHV3iHORIyqoJ6fwjoaAOnqG5tYLyIRXESyIrpIA3ZlYMp/AgH8KmrlfEuqazYa1CmgRvqV00GZdOdAsSplsSebxsYkEYJO7HQYzQB1VFYfhO7kvtKknuL6W6ujMftCSw+SbeTC5iCdVAGOpOc5yc1uUAQzWsFxLBLLErvbuZIif4G2lcj8GYfjU1eeS+KTZeKLoarrxtVEd6hs2ZVEIR4xAyrjLM6szA85yQOldtosl3LodhJqClbx7aNrhSMESFRuGPrmgC7ULWsD3cd20SmeJGjSTuqsVLD8Sq/lU1eVW99fQtqenl9WbXL2xhTawmOLzzJdzKfurGAUOQQu3HvQB6rRRVTVmvF0e9bTlDXgt5Dbg95Np2/rigCVbWBLuS7WJRPKixvJ3ZVLFR+BZvzqavNdE1gy3Uul6dqGp3V0dWtpFFwZS6wiOIz+Zu+6ufNG04G7AA6V6VQAhYAgEgEnAz3qG3gtrNfs9uiRB2eXYD1LNudv++myfrXPeJjqt6WtLXw/dy+Q6y2t/BdwoUkC8MFZgeMlSCMEZHQ1F4Tg1x9Smv/EelSRX8sRX7SZo2ijXIxFGisSoPUk9SOT0AAOtqMTQtO9uJUMyoHaMMNwUkgEjrglWwfY+lSVwuradbWOv6tqEviLXInSyjnkjtzH8qGSXYikrzyWCrjjuTngA7GxSzt7cWViYliswsHlRsD5WFBCn0+UqcHsRVmuf8Hi2Gn3YjW+W5+1N9sF+6tN5uxfvFflPybMY4xiugoAiurWC9tJrS5jWWCdDHIjdGUjBB/CpAMDFcFr88uneNra/vodRkjjvFNu8EUssQt/s7qy7UBG7zSM5GSCvYHHT+F47uLw/AL1JI5WeVxHKcvGjSMyK3uEKg/SgDXqG5tYLyIRXESyIrpIA3ZlYMp/AgH8KW4gjuraW3mBMcyFHCsVJBGDyOR9RXnt1oWg6Vrl/Fq1nrS2zBPsLW0t3MjLtG7mMkh9+7huMbcd6APR6KxPB1tPZ+FrOC4imidfMISdi0gQuxTeST820gkdjkcVt0AVVWy1OO0vUMdwiHzraVTuGSpXcpHqrEfjVqvMYdWsNFX+zrfx9qnlwttVYtJWVFyxACsISMbgQADjjA6V6dQAhIAyTgCohbW8d3JeCNVnlRInk7sqklR+bt+dZviO9a1sHibRrjUraeKRbjypIkVExg7i7rwQT09D0rltLTxHdapZw6zpGpzaZaTIbUvJBknOVknIlJcpxjA5xuIJxgA9BoorK8SzLb+H7qV49RkCBTt03P2g/MPu4I/H2znigC/DawW8s8sUSo9w4klI/jbaFyfwVR+FTVwnhLVtYv9ZRP7ctZrBQ2+0u5o3vhwccRqu3BxnOeM13dABUNtawWcRit4ljRneQhe7MxZj+JJP41yXxIS6bSsqL1rQWtzkWm/P2jYPILbOdud3tnbmtHw3dy6lqWoahEtyunyRwRwGdGTe6hvMZVbBA5QZxyVNAHRUySSOMDzHVAx2jccZJ7U+uH8b6ZdyarBqCaTNqUcf2byPJCu1s6XAkkYKSPvoAMj+7g4BoA7K0toLO0itbWNY4IEEcaL0VQMAfgKmrE8M290kN/d3Vq1ob+8a4jtnILRIVRRuwSASVLEAnG6tugCG5tYLyIRXESyIrpIA3ZlYMp/AgH8Kmrzua61Lw9q2oJfeNtKhuLuVZ2jGlvI2PLRASok+T7nTnOM55wOt8LJbp4fgNtem+SR5ZDcGMp5jtIzOdp6DcWwKANeoZrWC4lglliV3t3MkRP8DbSuR+DMPxqavP9a0nQby4v4z4E1O4uZXkH2iONEEjkn5w5kGATzn9KAPQKKo6LbTWehafa3Kos0FrHHIsf3QwUAge2RS6pqaaVbLO9rd3IZwmy0gaZhwTkheccdfpQBO1rA93HdtEpniRo0k7qrFSw/Eqv5VNXmp1fVZP+JJJZ69/Yy8m6Gnzfanj7QE4495M5K4HXJr0qgAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACqesQXN1ot9b2UnlXUttIkL5xtcqQpz7HFXKKAPOk8E/Ydfgay8M2qr9strqO+Bj/0ZUVBKhB+ZidjEEA/M+7IIzXotFFAGX4ju7ux0SW5sg5kjkiLeXHvYR+YvmELg5ITcenasHSr3U5ddtb6N5E0/UrqaNLM2wjCwpGxWY/KHDM69z0ccV0OvLaPotwt9a3N1bnbvitVcyN8wxgJ83XB47A1ymkadYnxTp1zo2i6xaJD5n2mS+85I9pQgYEjctuI6DoT7UAd5WP4jtLm/isbWJp1tpbtReeRIY3MW1uNwIIG7ZnBzjNbFY/iGwvryOxn05IJbixuxcCGdyiS/I6YLAHH38jg8gUAct4CsHs9aCfZtQSa3sPI1B7qWRkNwHXBj3MQdwDEkccLjGTXoNcv4f8Ly6NqltdkQeY1lIt9NHw1zcPIr7jxkgYfBPOGxXUUAc34sfdLY2kR1Wa5n8wpaafcCDzVG3czuSCqrkDhhy3fseEo9Mt5L62ttGl0q/QxtdxzOJHkB3bG8zc28cNg54INN8XtapNp7rNqUWqAyfZDpsQklK4XzMqwKlPuZ3d9tO8JR/Pe3E8Orm8l2edc6nEkbSAbtqoE+UBeeAB97vmgDpK47xhrOr2l3LDp9/Hp8NrBBPNKYVkZlkn8tz83ACKCx47jpXY1x3izU4rbXIbLU/Ecmi2E1ruj8gR75pNxDhi6thQu3HAzk88UAX/Bt9c3tlfi61RNUa3vXiW7jjREkUIhGNvBxnB68g1s39/baZZSXl5J5cEeNzbS2MkAcAE9SKy/CJ046Qy6XrEmqW6TEebJs+Q4B2DYqjHOen8RrdoA81vvGcMeoPa2tzDdC4kZ7bU57VybBSSWUrty2M/Jj6Hpk+gaaYzpdoYriS5jMCbJpfvyDaMM3A5PU8Vwura9rrag7jxHbaNatJeQx+ZboVR4GUIGZ+7jc3GOAMA122h3Ml7oOn3cxcyT2sUjl1AYkqCcgcA89qAF1TT5NRtlhi1K709lcN5toUDHgjad6sMc56dhXDfb4tv2n/hIfGH9nbsf2j5Nv9nxnG7Plbtuf4tuO+cV6NXlu0fYP+Ec/4TuH7Fv+z4/sZvJxnHledu24/hxuz2zQB6lWTr+pW9laG2uLfU5Vu43Tdp9rJKyDGCcoDtPPB9varOl2+oW1syalfx30xclZI7fyQFwOMbj3zznvVLxA2qJ5f9m2d1deZDLE/kXUcPlltuH+ccsMHHYc5ByKAOY03XdX1TVLSw1O21eK0tZk23CaZPGb1tw2NISgEajgsM4JB6LwfQa4TTrHxMmpWrXEevCFZkMnm6naum3IzuUJkjHUDmu7oA5zxtHLJploBZ3t7B9sQ3NtZZ3yx7WyCQRwDtPXnAHeoPC9ro0OpSNp3hrUNLlMJBmuYiqsuV+XJY85wfwNWfE4t7ayBln1cyXd2ohh0+crK77CNi8gBcKWIJAyCareF4LiLUpGms/EUK+SQG1O9SaMnI4AV2O73x0zQB1Vcr4l06S41m2uovD11qPlIhZ4r9YUcq5ZUdCw3BWAYZ45+tdVXIa/b+I7y5tprODUoQ1svmx2upQxKj5JIO6NiSOOQcHjigDR8KXAu4NRnbT5rC4e+f7RDNKsjbwiDPy8AbQuB6AHvW9XKeG3vtJnSwu9CvIReyu73sl4tyXl25zIQBt+VMA4xwBXTzzxW0ElxPKkUMSl5JHYBUUDJJJ6ACgDiNa1KzXxRfWmreItTs1jWNraDT92FQqMl9ikht2773bbjvXVaC9tJosD2l3c3kB3bZrrd5jfMc53AHg5HToBXL6lqT6N4m1J7XxT4ashdNG8lrfk+YrCNRuOJF6gD2xj3J6rRLx7/SILqS9sr1n3Znsc+S+GI+XJPTGDz1BoAv1w+t3loviK+j8QazqemwIE+wLayyQxyJsBZtyD5337htOcADjmu4ritX1OFvEV/a6v4ql0CG2CG0jSSOETKUBaTc6nf82V2jpt6c0Ab3haa+n8O2smoGUznfhpk2SMm8hGZeMMU2kj1JrXrJ8LXt3qHh21ur1i8z7/AN4Y9hlQOQj7e25QrY961qAPNnstOmsriw03xHClvZ6fHY6jI9m7fuQ7hHRgQNwO8FhuGeeMV6TXlWm2lxe3M2grqVja289lFp7RXcckN75CNIeI2ADMVk27gxHGe+K9VoAqarbJe6Re2kkiRpPbyRs8i5VQVIJIyMjn1FcboOsXEl5ZWQ8bRXillVfN0d4hcgdVWUsFYkA8jPrzXX63bJeaDqFrIsrJNayRsIRmQgqQdo7nnj3rirPVp9WutN0nV9T06yW3uYZFje2mtri4eNgUULIAFyQM7S2eg60Aeh1l+I7hLXQriV7i6tx8ih7ML5xYuAqruBGWJC8+vUda1Kx/FTWqeHLn7ZFPLGTGqLbkCQyF1Ee0ngNvK4J4FAGDoEWji903UZ9OvDqc9xc2iT3t0biSGSPeGGSxAyEf7vFdtXB+FtE1y01qGXVrO8khSWeWJ5rqDbA8m5nfZGoLMSxHXADHArvKAOF1GaH7T5sOt+KJWuZ7lVt7FY38vypNjgLsJChiAOvatjwozN9r3Ta9J9z/AJC8QTH3vuYUZ9/wqK68C2FxrI1KG/1KzJEpaK2u3Rd0jKzMMH5clckDgk57VraTo0ekebsvb+683Gftl0823Gfu7jx15+goA0a4rxS9o/imG21CHVdQgNkHS004y/uW3tmRwhGQwwBk/wAB45rta47xS/2LxBDd22u3Nldy2vlG1tNO+1vKisTuIAJABbg8d/U0AbHheOxi02RbCwv7KLziTHfeZvLYHI3knHT24NbNY/hi6a90oztq/wDam6Vh5ptxA0eMAoydQQc9RnmtigDkNQOr6Jr9/eWt5oMFtqDRuFv53SQsqKhPAxj5Rx7Z7mui0i5mvNLhnuJbOWV9257Ny8RwxHyk9ff3zXEeIbbTH8TXUkz6VeahHewzR2d5Ksbyw+RsMQLjGMuXGMjJ5wa6zwrp8+l+HLWzuI4onTewiibcsas7MqA99qkDPfFAF+/so9RspLSWSeJJMZeCZonGCDwykEdO1ecS22nWf9p2mp614ntb8TyLawxXd05ZM4jMeMh9wwTyeSRxivUK83uJLjTPF0897pmq3VxNHexFoYZJElR3jMCqw+VQEDA9MEEnrkgHdaItymg6et4jJcraxiZXcuVfaNwLEkk5zySSavVS0WC6tdDsLe9ffdRW0aTNnO5woDHPfnNXaAPMP7Rf+z/N/trWf+Etz/yD90nl+dn7nlY2eX/tf3ec16fXmf8Ab8v9k/2l/wAJZN/wkO7/AJAv7vHm5x5Hk7d+O27Of4s16ZQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAcv4rimOraPNDqculENLELtbdJE3PsxG+7oGxx2JA74qbwteXt3PqAm1N9TtYmWOK6+zpEjON28Jt+8B8oz0zkDoaTU/BsWrC5jutb1cwXRbfbi4XywCfugFenpV7QtBj0G3a3hvr25i2qqJcyKyxBc4CgAY6/oKANWud1TTdeXxKNV0YaYVe0W3lF4X3Ha7MMbRwPmP1z7CuiooApaWdUNs39rraLPvO37IzFduBjO4A5zn9Ku0UUAedahqWm3mpahaeIPGM1hNb3TKllCsPlpGD+7PzRsSxXBPPBJGBiu80545NNtXhuWuo2hQpcPjdKMDDHAAyevAHWudtdO8V6XcXyWC6K1pPdy3EYlaUSDexY7iBgnJ/Dp2rprfz/s0X2kRifYPN8snbuxzjPOM9M0AS15zGks2jXnhWPXNHfSbFBBc3Kq5njiLFQCPub+Cu7PBBOM16NXkMc3l3NxoC32n/YJ7SLSm1H99tCJJJk58vZ5hEmPv43DOecUAevUUUUAFFFFAHAeOLqC11ywgu/FN5ZCe4WRYYoosWwEb4kVjGWOWTaRn+M9uKv8AhnVHu/EHkW3iG81u1Fq7yvLBHGkTh0CDKxqSSC/fsePTrXjjkZGdFYxtuQkZ2nBGR6HBI/Gn0AFFFFABSMoZSrAEEYIPelooA4210/xmt9qE89voUn2idXTzZJWCgRIuF44GVJwe5PrXQ6FYXOm6THbXk6zT75JJGQEKC7s+1c87RuwPYCtGigArz/W5LB/FOpR654pvdGjjEZtIfPSNHXYMuhdTn5sjA6EE9xXoFNZFfG5Q2DkZGcUAcd4Ln1cT26Xd7e3trd2ks267jwUZJQqMDgECRDu2nJGK7OiigDmJ/CD64EPijUG1FFYOtpCnkW6n6Al2/Fse1a2j6SNGgmto7mWa3aYvAkrFjAhVRsDEkkZDEem7HatGigCrqe3+yrvdPNbr5D5mgUtJGNp+ZQASWHUDB57VwGiafqS61aSLokusW6yqW1HV4mimhGfvr5sjMSOoARfwr0migAqlrGlxa1pc+nTyzRRzABnhYK4wQeCQcdKu0UAYuneHG0+7juP7d1e6Eef3VzcB0bII5G0E9c9eoraoooAKKKKACuZ1GK+bxdJJolzbpeiwjFzFdws0Rj8yTyyGUghs+Z2II+grpqyNV8PjUL2O/ttRu9NvEj8ozWxQ70znayurA4JJHGRk0AQeFYjEmqLPcCe+N+xvGWLy0EhjjwEGT8uzZ1OT1Nb1UNI0iDRrRoIZJpnlkMs087bpJXPVmPAzgAcAAACr9AHnXjS6kk1meyuNUh1C02r/AMSW3BFwuVHXZFIxz1H3OD+NdZ4SgtrbwxZRWelXGlQKrbbO5JMkXzEnOSTycnr37dK1wqqSQoBY5JA606gAooooAKpappx1O2WEX13ZbXDeZaSBGPBGCSDxz+gq7RQBzX/CGDzfN/4SLXPMxjf9pTOPrsrpaKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK4L/hG/GP/CL/APCO79C+x+X5Ocy7/K/u5xjOON2PfrXe0UAUtLOqG2b+11tFn3nb9kZiu3AxncAc5z+lXaKKACiiigAooooAKKKwL3xE+ma3qFteLGLW30z7fC4BDEIWEgJzg4+TGB/FQBv0VxI8a31t4bs7rUorWDUDfm2vFCsY4kTdJIwGc8RLu69SK2bPxXbXMphnsL+xkNu1zCt1GqmeNcbiuGPIyODg8jigDdormoPG9pcaZb6gml6l5d4Y1s1MSB7lmBO1Bv7AEktgYGQSOaf4a1u51jV9cSVZoorSeKOKCaNVeLMSlgcdfmJOckc8HFAHRUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFcz4u8MXWv3Omy2k0UQhkMd2JCR5ls5UyKMA5J2L146101FAHFaz4En1rxFfTy3Ucem3VpIFRcmRLl41iL4xjARR3zkmrq6Lrmo30d3rD2CNaWc0EC2ruwkeQAF23KNowv3Rnqea6iigDmD4c1CDQfDsdpJbHUdDSPAkZhDKRCYnXIGQCGJBx2HFWfD2k6nZalq9/qj2pk1GaORUtyxCBY1TbyBnp179eOlb1FABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB//9k=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_words(tf.sum(axis=0), vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_word_cloud(tf.sum(axis=0), vocab)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What happens when we try PCA?\n",
    "\n",
    "Let's directly apply PCA to the raw count (term frequency) feature vectors and see what happens."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(n_components=2, random_state=0)  # for large datasets, by default PCA actually does random fitting\n",
    "tf_pca = pca.fit_transform(tf)  # sklearn's PCA class can actually directly work on the sparse matrix format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.98537, 0.0014 ])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(np.float64(-564.5599054971477),\n",
       " np.float64(11730.550170363256),\n",
       " np.float64(-285.09911145648186),\n",
       " np.float64(590.225435810774))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/jpeg": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(tf_pca[:, 0], tf_pca[:, 1], alpha=.5)\n",
    "plt.axis('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are a few exercises you can try for yourself (the answers to these are for you to figure out and not included in this demo notebook):\n",
    "\n",
    "- Verify for yourself that the single word that has the highest weight for the first principal component (or in Python indexing, since we start counting from 0, the \"0-th\" principal component) is \"ax\".\n",
    "- Verify for yourself that in the PCA plot above, nearly all documents map approximately to (0, 0).\n",
    "- For each document that mentions the word \"ax\", plot what the top words are for each of these documents. What do you notice?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filtering the documents and then building a new vectorizer\n",
    "\n",
    "It turns out that many of the documents don't really consist of valid English text. Let's only keep documents where at least 50% of the top 10 words in the document are valid English words.\n",
    "\n",
    "Note that the code below uses a set of English words from NLTK. For the code to work, you need to first download the listing of valid words:\n",
    "\n",
    "```\n",
    "import nltk\n",
    "nltk.download('words')\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import words\n",
    "\n",
    "valid_english_words = set(words.words())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10000/10000 [00:26<00:00, 371.00it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "\n",
    "docs_to_keep = []\n",
    "\n",
    "num_top_words_to_check = 10\n",
    "for doc_idx, row in enumerate(tqdm(tf)):\n",
    "    sorted_tuples = get_top_words(row, vocab)\n",
    "\n",
    "    num_valid_english_words = 0\n",
    "    for count, word in sorted_tuples[:num_top_words_to_check]:\n",
    "        if word in valid_english_words:\n",
    "            num_valid_english_words += 1\n",
    "\n",
    "    if num_valid_english_words / num_top_words_to_check >= .5:\n",
    "        docs_to_keep.append(doc_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8947"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(docs_to_keep)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_docs = [docs[doc_idx] for doc_idx in docs_to_keep]\n",
    "\n",
    "filtered_tf_vectorizer = CountVectorizer(max_df=0.06,\n",
    "                                         min_df=0.0005,\n",
    "                                         stop_words='english',\n",
    "                                         max_features=vocab_size)\n",
    "filtered_tf = filtered_tf_vectorizer.fit_transform(filtered_docs).toarray()\n",
    "\n",
    "filtered_vocab = filtered_tf_vectorizer.get_feature_names_out()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11707"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(filtered_vocab)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Normalization\n",
    "\n",
    "Even with the above filtering steps, the different text documents vary wildly in the number of words they contain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of documents')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([row.sum() for row in filtered_tf], 20, log=True)\n",
    "plt.xlabel('Number of words in document (after filtering)')\n",
    "plt.ylabel('Number of documents')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Many machine learning models crucially rely on the feature vectors being \"normalized\". In fact, the problem with the word \"ax\" from earlier is that it rarely shows up, but the few times that it shows up, it shows up so often that its raw counts completely swamp out the raw counts for all the other words. As a result, the presence of \"ax\" explains most of the variance in the original raw counts feature vectors. What we did was apply some aggressive filtering that ultimately eliminated the word \"ax\" and lots of other words.\n",
    "\n",
    "However, we have not dealt with actually making sure that the feature vectors after filtering are normalized. A simple way to do this is to convert each raw counts feature vector into a probability vector (which we talked about in week 1 of the course!)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "prob_vectors = np.array([row / row.sum() for row in filtered_tf])\n",
    "# warning: sometimes there could be a row that is all zeros in which case you'd get a divide by 0 issue,\n",
    "# (in this case, it does not happen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8947, 11707)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prob_vectors.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "num_PCA_dimensions = 100\n",
    "pca = PCA(n_components=num_PCA_dimensions, random_state=0)\n",
    "prob_vectors_pca = pca.fit_transform(prob_vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.00617, 0.00486, 0.00473, 0.00418, 0.00389, 0.00385, 0.00372,\n",
       "       0.00356, 0.00312, 0.00308, 0.00307, 0.00284, 0.00282, 0.0028 ,\n",
       "       0.00265, 0.00261, 0.0026 , 0.00252, 0.00248, 0.00247, 0.00238,\n",
       "       0.00236, 0.00234, 0.0023 , 0.00228, 0.00225, 0.00223, 0.00218,\n",
       "       0.00217, 0.00211, 0.00209, 0.00208, 0.00204, 0.00202, 0.002  ,\n",
       "       0.00196, 0.00193, 0.00192, 0.00191, 0.00191, 0.00188, 0.00187,\n",
       "       0.00186, 0.00185, 0.00184, 0.00182, 0.00181, 0.00179, 0.00179,\n",
       "       0.00178, 0.00175, 0.00172, 0.00171, 0.0017 , 0.00169, 0.00169,\n",
       "       0.00166, 0.00165, 0.00164, 0.00163, 0.00162, 0.00159, 0.00159,\n",
       "       0.00158, 0.00157, 0.00155, 0.00155, 0.00154, 0.00154, 0.00153,\n",
       "       0.00152, 0.0015 , 0.0015 , 0.00149, 0.00148, 0.00147, 0.00146,\n",
       "       0.00146, 0.00145, 0.00144, 0.00142, 0.00142, 0.00141, 0.00141,\n",
       "       0.0014 , 0.00139, 0.00138, 0.00137, 0.00137, 0.00135, 0.00134,\n",
       "       0.00134, 0.00133, 0.00132, 0.00131, 0.00129, 0.00128, 0.00128,\n",
       "       0.00126, 0.00125])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Fraction of variance explained')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/jpeg": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(range(1, num_PCA_dimensions + 1), np.cumsum(pca.explained_variance_ratio_))\n",
    "plt.xlabel('Number of principal components used')\n",
    "plt.ylabel('Fraction of variance explained')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x143da56d0>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/jpeg": 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/+P0fZPFv/Qa0j/wVSf8Ax+gDdorC+yeLf+g1pH/gqk/+P0fZPFv/AEGtI/8ABVJ/8foA3aKwvsni3/oNaR/4KpP/AI/VHT5/Ft9ealb/ANq6Qn2C5EG7+zJDvzFHJn/X8f6zGOelAHV0VhfZPFv/AEGtI/8ABVJ/8fo+yeLf+g1pH/gqk/8Aj9AG7RWF9k8W/wDQa0j/AMFUn/x+j7J4t/6DWkf+CqT/AOP0AbtFYX2Txb/0GtI/8FUn/wAfo+yeLf8AoNaR/wCCqT/4/QBu0VhfZPFv/Qa0j/wVSf8Ax+j7J4t/6DWkf+CqT/4/QBu1heL/APkDQf8AYSsf/SqKj7J4t/6DWkf+CqT/AOP1Bd6L4i1JYYb3WdNa3juYZ3WHTnRm8uRZAATMQMlQOhoA6SiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKq6gl+9qRps9vDcZGHuIWkTHf5VZT+tZZtPFUkciXGpaU8bxuuILGSN8lSBhjKwHOOxoAsWPijRdSvhZWl6JJm3bMxuqS7fvbHICvjvtJq1fX9holgJ7qRbe3QqihVJ5PCqqgZJ7AAVxGl3trqFl4O0iyyNQ0yWNryAKQ1qI4HR9/8AdyxAGeua1/Eeo2kz6RqiS+ZYaZqzJeOFOIiqSRljx0VyMnp3oA1v+En0c6PPq32s/ZLd9kx8l98bZA2lMbgckcYzyKs6bq1rqqSNbLdKIyA32i0lgPPoJFXP4VySNo+q/wDCS6hfXOzQ7ya2RbpXKLIyKuWVh23bV3dPlPNaHhS8E2s6lBp2oXGpaNHFE0VxNKZQsxLb0SQ8uMBD1OCaAOqooooAKKKKACkZlRSzMFVRkknAApay/E9rcXvhXVrS0BNxPZTRxAdSxQgD86AE0zxNo+s3Bt7C78yTZ5ihonTzEzjchYAOuSOVyORT9W1rStJeD+0JcSOWaFEheV+B8zBUBOADycYGfeuXh1nTdT1fw/Pp8oMWlWs8t7tU/wCip5QXY4xw27Hy9fkPHFW7vV9P0/xhba3e3Kw6de6SEt7qQEJu37yuT0LKVIB67fagDcufEWk2unW+oSXitb3WBbtErSGYkZAVVBLHAJ4HarWn6jaarZpeWM6zQPkBgCOQcEEHkEEYIPIrgtMYaPH4a1XUla009ZL875VKi3E0m+Et/d+QEc9N2K6PwafOg1a+jUi1vdTlntiRjfHtRdwHoWViPXOe9AHR0UUUAFFFFABRRRQBR1PWLDR4o5L6Yp5r7I0SNpHkbGcKqgseATwKlsNQtNUso7yynWaCTO1xkdDggg8ggggg8isHxFcw6Z4q0TVb9xFYRRXMLzvwkUj+WVLHtkIwyfXHeo/CV/bRm6LOY11jU7iewVkI82MAZYccA7WbnGQc96ANO38SaG+pf2Zb3SicyvGAImEbSDJZQ+NpbqSAc9aUeKNKbUpNOja7knimEEnl2M7ojnBwXCFRwwOScDPNcbZXEL+H9E8NIT/bVpqkTT2+074vLnLySH0UqCQ3Q7h61a1q40qxvrmXw/q9wdelvkZrCK4ZhK+5VcPD0C7Ry2BgDOaAO/ooooAKKKKACiiigArJtvFGjXepf2fBeh5y7Iv7twjsv3lVyNrEYOQCTwa1WBKkA4OODXm+l3MM+heF/D0Of7XsL2E3Vvg74PKLeY7egPOD33jGc0AdzrWrabo9kLnVH2QbuCIWk5HzZwoJ4xnPbFPudXsLPSxqdxcrHaMqsshB+bdjaAMZJORgYzzWR4k1/SW8D318b+FLe6t5oYJJDsEkm1xtGcc5U8e1ZNzqVleeFfDmpWtzHdWWm3tu148J3iICIqS2P7rOhPpjNAHW6Zq9jrELy2MxkEb7JFZGjeNuuGVgGU4IPI71drmPDdxFqXiXXdVsnEthOttFFOv3JXRW3lT3HzKMj09q6egAooooAKKKKACquo6lZ6TZtd304hhUgbiCSSTgAAckk9AOatVzfjFhbjRtQmB+yWWpJLcsBkIhjdQ59gzKT6de1AGvpmrWOsW7z2MxkWNzG6sjI6MOzKwBU8jgjvUCa7pK66dHSXbfyZYoIHAYhQT8+NpIGO+elYui6tYt4g1jVkuB9g1C4trW1mVSUnmCEHaQORyFz0+XrxUXiHxDotl470SK61S0he1S4E6vKAYy6IV3eme1AG5e+KNLsNQksJWu3uYkV3S3sZ59gbO0kohAzg/lWvXEeK5dCtLzUbqLWrmz17yFEcNtcMHkZQTGPKHEnLdwep6V19i9xJp9s92gjuGiUyoOivgZH55oAsUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH//Z",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(prob_vectors_pca[:, 0], prob_vectors_pca[:, 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Is the 11,707-dimensional probability vector space capturing semantic information?\n",
    "\n",
    "Here's an example: \"learn\" and \"study\" are English words that we would expect are related, whereas \"learn\" and \"car\" are not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(6269)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn_idx = filtered_tf_vectorizer.vocabulary_['learn']\n",
    "learn_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(10117)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "study_idx = filtered_tf_vectorizer.vocabulary_['study']\n",
    "study_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(2134)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_idx = filtered_tf_vectorizer.vocabulary_['car']\n",
    "car_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn_one_hot = np.zeros(len(filtered_vocab))\n",
    "learn_one_hot[learn_idx] = 1\n",
    "\n",
    "study_one_hot = np.zeros(len(filtered_vocab))\n",
    "study_one_hot[study_idx] = 1\n",
    "\n",
    "car_one_hot = np.zeros(len(filtered_vocab))\n",
    "car_one_hot[car_idx] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 0, 0], shape=(11707,))"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_tf_vectorizer.transform(['learn']).toarray()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dist(x, y):\n",
    "    return np.linalg.norm(x - y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(1.4142135623730951)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist(learn_one_hot, study_one_hot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(1.4142135623730951)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist(learn_one_hot, car_one_hot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(1.4142135623730951)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Euclidean distance between any two documents corresponding to two different words is always:\n",
    "\n",
    "$\\|(1,0,\\dots,0) - (0,1,0,\\dots,0)\\| = \\sqrt{ (1 - 0)^2 + (0 - 1)^2 + (0 - 0)^2 + \\cdots + (0 - 0)^2} = \\sqrt{2}$.\n",
    "\n",
    "**In particular, Euclidean distance in the 11,707-dimensional probability vector space is not useful at telling us anything about semantics.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Is the PCA low-dimensional representation capturing any semantic information?\n",
    "\n",
    "Let's look at the distance of \"learn\" and \"study\" in PCA space.\n",
    "\n",
    "We can separately look at the distance of \"learn\" and \"car\" in PCA space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn_one_hot_pca = pca.transform([learn_one_hot])[0]\n",
    "study_one_hot_pca = pca.transform([study_one_hot])[0]\n",
    "car_one_hot_pca = pca.transform([car_one_hot])[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.1412023473132542)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist(learn_one_hot_pca, study_one_hot_pca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.9745345524464784)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist(learn_one_hot_pca, car_one_hot_pca)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing PCA space using t-SNE\n",
    "\n",
    "T-SNE can be used to try to visualize any representation of data. Here, we are going to use t-SNE to visualize the PCA space that we have come up with above (since we noticed that the 100-dimensional PCA space appears to be capturing some sort of useful semantic information when we use Euclidean distance in this space). Importantly, t-SNE does use Euclidean distance for calculations!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[t-SNE] Computing 91 nearest neighbors...\n",
      "[t-SNE] Indexed 8947 samples in 0.001s...\n",
      "[t-SNE] Computed neighbors for 8947 samples in 0.571s...\n",
      "[t-SNE] Computed conditional probabilities for sample 1000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 2000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 3000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 4000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 5000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 6000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 7000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 8000 / 8947\n",
      "[t-SNE] Computed conditional probabilities for sample 8947 / 8947\n",
      "[t-SNE] Mean sigma: 0.015432\n",
      "[t-SNE] KL divergence after 250 iterations with early exaggeration: 90.113907\n",
      "[t-SNE] KL divergence after 1000 iterations: 2.007293\n"
     ]
    }
   ],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "tsne = TSNE(n_components=2, perplexity=30, learning_rate=200, max_iter=1000, random_state=0, verbose=1)\n",
    "prob_vectors_tsne = tsne.fit_transform(prob_vectors_pca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x143f211d0>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/jpeg": 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AdFG0sqooJJPQV7rbRpDawxRqFREVVA7ACvNfh9Z2t7qNwlwCxjRXRex57/pXp9eVjZ3ko9j18DTtFz7hRRRXAegFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQBheEP8AkDT/APYSvv8A0qlrdrC8If8AIGn/AOwlff8ApVLW7QAUUUUAFFFFABRRRQBheEP+QNP/ANhK+/8ASqWt2sLwh/yBp/8AsJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFZ2v3ZsdDu51JDCMhSPU8CtGuY8b6mLbTPsCRCSW7U8t0QDv9c1pSjzTSM6suWDZ5bNI0khL9asaXfvpt/DdJnMcitwecA8/pVQ5zz1or32k1Y+dTad0d7e+OjJL5ttcmKPPyRqgJ+rZrqNF1W28R6OWO0kgxzJ6f8A668arf8ACeuyaLqIcoHgmwkg9Oeoriq4WPJ7m6O6ji5c/v7Mr6vor2Go3FvIShVzsBX7y54Iqium3jgFbdzkZ6V7gyRzKCyqwxwSK5l/C92sxjimi8gnh2zuUfTvUU8ZdWZpUwVneJyFl4WvEEc91ZyNDIuVKfNn8uld74asP7J0qTzUECs5k2n+EY7/AJVrW0CW1tHAn3Y1CjPtXE+KvGa7bzSrSDcNrRPMXxz0OBWLnUxD5UbKnTwy5myTWviJDCGh0qPzJOnmyD5R9BXnss8s8zTSyM8jnczE8k0yivSpUYU17p5lWtOq7yZ6F4B1KW4nNvk7RDlgTwSCACPeu6rg/h0LTEpNypuQCFhxghTjJ967yvIxNvaux7GFv7JXCmRmNstGVPPJWuW8f6r9i02K2SUq07/OqnDFAD+ma4jRPElxo2pLcogMJ4kiBwGH+NVTw0qkOZE1MVGnU5Gex01mVBlmCj1Jqjpet2OrRhraX5sZKMMEVwHxAv7k601ozMI0UFRnjBH/AOuopUXOfI9DSrXjThzrU9G/tKx84Q/bIPMPRfMGas14LHI0bhlJBHpXc6/rUt74GtGtboSElUuyh+YcdD7E1vUwfK4pPc56eNUlJtbGt4ov7J/JlS+t3EJZXQSqSCcc4zz0rgdVnkuH+0I37vJVSDWZRuJGM130qCpq1zz6td1He1gopQpIJHakBwQeD9a3OcciFsDnJOBU0FhPcyeXFsLem8cUxJ/LjdQvzMMbs9B3pBMVYOo2uDwRUu/QpW6npXgbQBYWpv5GBklBUAemev6V11eN6X4n1XTLlHS7kaMH5onO5SPoa9S0fW7fV4Q0atHKFDNG3oe49RXk4qlUUuaWp7GFrU3HkjpY0qKKK4ztCisXWtalsZ1trZEMhXczOMhR24rIvvGtxa2gjEEf2sk/Mc7Avrj19q1jRnK1jGVaEW7nY0V5MfGmpNKZnldpc5Uo5VR7belaln8S7lZh9sso3iPXyzhh+dbPB1VsYxxtJvXQ9Foqrp2o22qWSXdq+6N/UYIPoatVytNOzOtNNXQUUUUhhRRRQAUUUUAFFFFABRRRQBheEP8AkDT/APYSvv8A0qlrdrC8If8AIGn/AOwlff8ApVLW7QAUUUUAFFFYkfizS5NVv7DMqjT4DPNcMo8rapw2DnJKkEHjGQR1BoA26KxdL8UW2p3kVq1le2UlxCZ7b7XGFE8YxkrgnpuXg4PPStqgDC8If8gaf/sJX3/pVLW7WF4Q/wCQNP8A9hK+/wDSqWt2gAooooAKKKKACiiigAorA1Txpo+lTtbvK80ynDJEudp9z0p+leLtL1V/LWQwSHospAz9DmtPZVOXmtoZe2p83LfU3KRjhSQMkDpTWljRSzSKoUZJJ6CoLXU7G+dktbuGZl6qjgkVFnuaXWxx76lfSyG6N3Kj5JADYVfbHSuzspnuLGCaRdryRhiPcisy9t/D0F8GvHgimc52NJgE+pGcVW1rxpp2jSeQEe4kA+7HgKPxroknUsoROaLVK7nI6Oiua8P+NLbXLv7I0JgmYEoC2Q2O1dLWM4Sg7SRvCcZq8WFZGv6BHrkMf70wzQk7JAMjnqCPSteilGTi7ocoqSszyLxN4dl0W6iWSUSCZNwkVcKCDyP5VgHg8HNe4alpltqkAiuAflOVZeq1xlz8OJmuCILqPyieHfO4fgK9Oji4uNpvU8qvg5KV4LQ4IAsQB1NdX4P8OR6nfP8AapSEttrmNR9/PYnt0rnJbV4p3hZSGjYqfqDiuw8O+LdG0Sxjga3nM8n/AB8SjBGRwO/TFb13Pk9zcww8Yc/v7HoYGBgUEgDJ4ArGtfF2iXbhIrzk/wB5CMfXiqnjq4nh0JTEzCKSULKyHnbg4H0JxXkRpSclF6XPZlVioOS1sUtR8fwxecltbsyAFVm3dT6gV51cyLLcSSKWIdi3zdaY/BwOlNr2aVGNP4Tw6tadX4goHWihRkgAZJ6CtjE6Xw1/oGqW2pXe+2towSHKnMnGMKO/WvQD4o0n+znvlud0aEKVCnfuPQYNcdeaLqC6PptwqtdIkG1xF8/lnJPb61zF+0iylWBTB+6wwSfcVwSpRru9z0I1Z0I2SLXifVhrOsyXSK6pgKqvjIA+lZFHU0V2xiopJHDKTlJyZ3fgqWO7u7fy3CNACXDMASSDwB3/APrUfEy1bz7K6EfylGRnA75yAfzNYnhmNpmdYAxuCyhAo5HvXpGr6hpNtbi31Z4mWQcxuu7PvivOqN066ktfI9KklUoOL08zxeus8A2klzqUgMW+324lDLlSuDwfxxXRQeB/Dd+VvLV5Ht35CJLlfp61M/iLRfD0p020tJGWI4kMIGFP1J5NaVMR7SLhBO5nSw3s5KdRq35mhJ4W0Y200UOnwRtKpG8JkgmuH/4V7qr3vlDYkWf9azZAH869Gj1K0k00agsoNuV3b/b/ABrmdX+IEFhiO3spJJTz+8YKAPwzXNRnXu1HU6q9OhZOenoYepeDLnSxIsRkuI3Th1jzzjpx0rkHUo5Vhgg4IrvLf4msbhRcaaqwn7xSTLD35HNcdqE1tNqNw9urNC8rMhfg4JzzXfRdXVVEefXVLR02U6Kvy2cC2u+OcMwUEqQRkn0/l+FUK6E7nM1YB1rtPBN7NbXUck43QMfJQ55GSPzGa4urmnX1zZ3cM0MjExuCEJyDg+lZ1Yc8GjSjPkmme4Vn6nrFtpYUShndhkIg5x6n0FXkYtGrFdpIBIPauN8dNHbZmEqmSSLYY8/MOuD9K8WlBTmos92tNwg5IxfFPiqG+uomsI5InVMO7gc+gx/X3rmLm9nuyDM+4j2xULMWOTyaSvbhTjBJI8GpVlNtsKKK6bwb4eg1e+3XhIjjG7Z/z0pzmoRcmKnB1JKKOu+H1pNbeHt8oIE0hdAfTAGf0rqKaiLGioihVUYAHYU6vBqT55OXc+hpw5IKPYKKKKgsKKKKACiiigAooooAKKKKAMLwh/yBp/8AsJX3/pVLW7WF4Q/5A0//AGEr7/0qlrdoAKKKKAKupQXNzptzBZXP2W5kjZYp9u7y2I4bHfFef3PhTxC95e6Wj2Rt30B7VHhtJI0YkvtXc0jfNuIJJzkE8d69KooA5K0nudd8RaNcrpl7ZR6bBK1ybqAxASOqqI1z9/8AiORkcDnmug1LSrfVY0S4kukCHI+zXcsB/ExsCfxq7RQBz/gmFbfw+8KFyseoXqgu5diBcyjljkk+55NdBWF4Q/5A0/8A2Er7/wBKpa3aACiiigAooooAKbIGMbBfvYOPrTqKAPCr2GaC8ljuARKGO7PXNQAkHIOK9E+IelRNHBexxqJHfy3bH1IOf0rzx0aNyrDBFe9RqKpBM+erUnSm4k3264MJi807T1qaw1GWxvobmBvKeNgdw5478d6pUVo4pqxmpNO5oXGqST3c08pMzSsSWbv/AJ9KjaN7qEMrLvTgozgHGSRjPXrVPoaUOwJIPJ60ctth819yzaLPBeoUdopUbIKnkV3+j+Lro2Jimh+0TROVMjNtBHb8a848xjjJPHSp4r+4i4jlZVByADWVWiqi1NaVZ03oep3HjLTLSzSafeJXJHkqMsCP6Vo6RrVnrVsZ7RyQpw6sMMp968eub43Eqy7SW2AMSep9vTtXb/D+wka0vruRjHHOBGoB54Byf1rhrYaEKfN1O6jiZ1KnL0LWo/ESwtLs29tA9wEOGlzhfw9a2NH8S6drKqIJNsp/5ZsMHPse9eQXlu1rdPCxztPDDow7Gls7yeyuY5oJWRkYMMHuK3lg6bj7u5hHG1FP3tj0Lxfo2kW0U2oPcPb3EoJESEYkb1xjj3rzY9a7PxqLqcWWozIRDPboM9kbkkfjXGHqcVrhk1T1dzLFNOporDo5HibcjFW9RXR6LqklzJHptxcyNbXA2MJDuVGHRhnpyB+Fc1V/SS/2kojrGXGNxxxWtSKcTGlJqQ3VoRb6jNCoULG5X5enBxVKum1vRZpzDfwAYut25fRgecfzrnzZzD+H9elFOacUOpBqT0IadG7RSLIpwynIq+mmeTEkl0cGUfIi9fqaz3Xa5X0OKpNMhxa3PSfCc1zf6JfS2/yF12qP+mmDnH6VxniGPZcx/IUIXBBGDn3q94c8X/8ACPWD262vnmSXecvtAGAPT2rrppbLxz4cmW1CpcKQdj43Iw9/Q8jNcPvUajk17rZ3+7WpKKfvJbHllFXrrSp7TUJLS4UQvGeQzA/y61Cpt40kjeJpJMkBg2AK7uZPY4HFp6lvQNZm0XUo548lCwEij+Je4q941aWXxA87EtBMivCexUgVnR6eghS6+0p5ZPAwd2fTFaXizWo797WysyfsltCoGVwS3fPf0rFpe1Uorvc2TapOMn2sa3w2muEurqMsRalQTk8Bvb8KxdYuoLfW7uK3kWeMzMQ4PHJ6Z9j3rHW7nWAwiQ7M5A9PpUNNUv3jm+onW/dqC6Hq+l6Z5/guO2hlDSODID23bs4+navL715ZLqRpgQ4YqwPYiuq8PeJJdN063RrtNiEjyXxyM/mKqeLrO3fXbh7NdoYCRv8AaYjOR+dY0U4VJKXU6KzjUpxcehzNOiiknlWKJC7ucKqjJJpuMVueEJ2tfEVq6qHZ32bcZ4PX6V1zlyxbRxQjzSSZoN4euW02NHtJVNuN0zFduB1PXrWI+my5aQQOYl5yRt4r2S+WF7GdbhtkJjbe3oMcmvNrfVbG4vltZ5HS1Z9pnKdR7jtmuGjXnNN2PQr0IQaVzKh0CVgHlbYg5PQk/SvRdN8GaJYSR3EcDyyKAVaVicH1x0rOvoNP03URFDFLceVhjG8mEXuB0ya6G21m1n05r2RhAkZxIHP3T/Wsa9WpJK2xtQo04N81rmhXB+N9OuN09x5bvHIVKOozjjG0+ldLaeKNGvHZI7xVZRn94CmR7Zq5Ktpq9jJEsqyRPxujbODWFNypTu0dFRRrQsmeIPG0ZwwwabXoGv8AhYwiKWaUzQgkFkTBU9iawV8MyNFPPEd1vGADIe2SK9aFeElc8eeHnF2MFIWaNpD91a3tDv7vSbyG5R9w4Voj0KnqPrV7TNIih1C2EoWdDIqeWV+8DxXW2/g3Sra8FwokYKcrGzZUVjWrwSszajh5t3ibyncoYdxmlpCQoJPQVxF/4/NrdkJEjID/AKvB3Y9z2NeZTpSqP3T1alWNNXkzuKK4iy+JVrLcFbyzaCI9HRt5H1GK66w1G01O2FxZzLLGeMjsfQjtTnSnT+JCp1qdT4WWaKKKyNQooooAKKKKACiiigDC8If8gaf/ALCV9/6VS1u1heEP+QNP/wBhK+/9Kpa3aACiiigAooooAKKKKAMLwh/yBp/+wlff+lUtbtYXhD/kDT/9hK+/9Kpa3aACiiigAooooAKKKKAIbu0t763a3uollifqrV5j4w0W30/VRBYxMi+SHO5ixY5PQn6V6pWZrenade2bTahDvEClgykhh9CK6KFV05eRz4iiqkPM8WIIOCOaK1dZvLea4WC3hjit4xwseSST1JY8k1mOm08HK+te1F3V2eFJWdkNoooqiQooooAUZwSK09L1O7sJo/s95IgZgGQOdpHTpWWCR+NPVowhBUliOD6VMkmrMqMnF3RsapBb3lzF9nu45HMYGxQcg/3fc/Sq1po1xM65XqwAHqfpWeuSQEB3dsVrnWGtVLW5VbnGBLGMH3zUNSirRNE4yd5HU/EGCc29iygtaxAq4XkI3GM/hXEJYTTI88UTNCpClwOMnt71Z0jXLrT9TiuGmd4y481Sch1PUflXReLPENlexW40uUhI1fICFBzjpWMFOlaCV/M2m4Vb1G7eRyElnLCuZBs5xzVmysTOxRd2Tj2GPWqDOztudixPcmtXQtT/ALNlaWW3iuYQMGOUdfp71vLmUdDnhyuWux2FrfQQ6MthNa/aVDkxbm27V9c9euaybx9JmmKRwC3CLmVPNLb2z61Jq3iTTdTKvZq9vJ5Wwq6gL7YI6da5p4l8kljmUnjHUGuWnT6vQ66lRbKzQt/cCSdkV3RY/wDV7jzj61QZizEsck96fO++Ukrg8d6jrsirI4pO7Cut8AWt2dX8+HcIwh8xv4cY4H51yVdLonjbUdLhW0YRTQKNq7hgp+I6/jWddSlBqKNaDhGonJlvUbe2Qv8A2jHiZSd27O4n+tczKsRuzHbOHVyNpPygE9ua2/EurzX8Cbr5Z8EhlGBjPpjtxXNUqMXy3Y60lzWR0mr6RJoVjaIwV7gAvNjkLuI2jPfoa5+eZp33OACOOBXSXmsW2saFDb7JI76CNY2J5DoO/wBR/WuZkQxuVPWnSvb3txVrX93YbRRQOTWxgOVlUcrk1vTXNi3he3kMj/2hHIYiFOMJyRn19qxPLIj3n1xg0GTMZVsgkg/l/wDrqJR5rGkZctyMsSTnvW34Tik/t+zlhwzrKOPbv+maxCuBkGrWmajPpl/FdQOVaNgfYjvRNNxaQqbUZps77xj4ojjFzosEHmu0e2WQvgISOg9TXJ6NoOoa6wW3hCxBtskrMMJ/WtjxHo/223PiWymi+z3KK8kbE5DdOPXmqmj+JZfD1g9rFbRme4feZnYkLxjp/wDXrjprlpWp7/r1O2o+arert+nQ6vWtHFsTeJcwxQ7VD+e+3BAxnP4dK5fXNTtRozWFncpM3miSSRWwGOMYA9BWbrvie71wQx3ATbBuxsGAxPcisSro0JJJzepFbERbagtGLubOcnNehfD03c3mTMG8kKVLHoxyMf1rzwYyM9K9U8D6l9ssJLdf9VAF2gj7mc8fpTxbap6IWDSdXVnTkZGDWR4kne30wRxAKsz+Wxx0BB/nVfUPGOn2F61r5U07RnEjRgYU+nJ5Na0b2esaesgCzW8y5GR1/wDr15ajKDUpLQ9ZyjNOMXqcl4eiS21qEIpcOGGGO7bxnIz0rr5r60tpFjnuYo3borOATXI3XifQ9AmnSxtZJZwColzkZ9Mk5xXA3l9c393JdXErPJI2SSa7Fh5Vpcz0RxPERoR5Vqz2y+eRdPneDmQRsU+uK8PuRi4kwSw3HBPeus8H+I7+O7isZ5mntnwux+SuTjg/jWnf+AJri6byJoUiY/fYHIH09aqlbDycZvcmtfExUoLY88r0v4dWNzb6XNdTZWO4YGNT3A71jj4c3cV0BNeW4gz/AKwsQcfT1/GvQ7W2js7SK2iGEiQKv0FLFV4yhyxd7hhMPOM+aatYmoqG4u7a1ANxPHFu6b2AzUiurqGRgynkEHINedZnp3Q6iiikMKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/5A0//YSvv/SqWt2gAooooAKKjuPO+zyfZghn2HyxISF3Y4zjnGawrPVtVtfEKaTqz2M/m2j3QltI3j8kKyjDqzNkHdwcj7p4oA6GiuQ0/wAT6vLHpOqXkFmul6xMscMcYbzoA4JiZmJw2cAEADG7vXXEgdSBQBh+EP8AkDT/APYSvv8A0qlrdrC8H/8AIGn/AOwlff8ApVLW7QAUUUUAFFFFABRRTJpUgheaRtqIpZj6AUAPqrqMH2uwuLQOFeaJlGT6iuLuPiYUuGWDTQ0Q4UvJgn36Vy9x4hvJ5WuPMdZ2bO7+79DXZTwlRu70OKpjKSVlqR3Gg6pBdm2ewuC+7A2xk7voa0dc06XTNLsbG4hVJRG0rEDklj0z7DFV7fxdrVuSUvpCW+8XO7+ddBp/iDT9dsZrfxKIz5C7knUFWOeMcd67purGza0XY4IRpSuouzfc4SipbpIUuJBA5aMMdhYYOM8fpUVdS1ORqwUUUUAFFFFAFhbopbNGowx/jHXHOf51XoopWsNu4VKJnaLyjhlBzz2qLPGMfjTsAKGDe2KGCNG20yOVFnlkCQ43Mfas+YoZX8sER7jtB7CrMuoM1itmmfL3bjnHJHT+Z/OqdTFPdlSa2QVcsbzyCQ6KwHIJ7VToz+tU1dEp2dwJySaKKKYgoAzwOSegFFSQFlcsvUChghjUlSySKVKhQSTndimDZg9cikMt2NwllOJpoDNlTtXft9s5q2sEGqrLMhELp95XIAA7HIFZTSMxDE5wMVdb7NbWGDJ5l1I4LIudqKAeCe5zj8qiS6rc0i9LPYqTwiEgCRXz/dNJBEZp0iHBcgZNRsSxJPU1e0m5gt76N7m2NyinhRIUP51TukQrOQ7ULkqgs2hQNC3L9/pWeSScmtXxJLYz6p5+noUhkjUlD/C2MEVlUofCmOp8TQUAEnAGaKntp1tZ1lMaS4B+VwSORVMlHU2D3C+FxptwVELHzM4O6PnIP9ce5rm9RK/aHQTxzBDgNHnafcZFa2n341ZW06eQwySqUhYDhmI+UE9gTxWJNaXMVw1tJCySIdrKR0NYU1aTub1HeKsQUVM9pKkRkZflU7Tz3qJRk1vcwtYStzRvEk2gxTC0TMkqBTu6KR39z1rJMOLcTZ6+tQ1MoxmrMqMpQd1uSy3c80ryvKxZ2LE57muy8C69OJRpMh8yJwxQY+ZT161xFdL4BtJLnxJHKjBRbqXfnkjGMfrWdeMXSdzXDykqqsY+o2dxFcMzqSpOQR/KqVd/40l06G5jgtXiW4kYmbY/I+o6A1yoW3+1kSEOHU7snJU+tFKq5QTaCrSUZtJmdbXEtpcx3EDlJI2DKR2Ir2ax17Tb22SVb2AEoGcFwNvHPWvGZ0VJCqMrD1U5FNWRkBAY4PUdjU1qCrWew6GIdFtWudT4o1WO91qd2uFmhjwsIVsrjHUfjmsWTW9QkiWAX1wsEf3EEhGBVGWZpX3N1phOTWkKcYpIznVlKTfc2rPxA6hvtzy3LAAIzHcQPTJq4PF18lqLTT5Wto9xYnALc9h6Dv8AjXM06Mqsilt23PO3rQ6UH0BVprS56h4K8QXmrLcWt83myQBWWXGCQexx34rqqwPB9tpUWkCfS2dxMf3ry/f3DsfTGf1rfrxa1vaPlVj3KHN7NczuFFFFZGwUUUUAYXhD/kDT/wDYSvv/AEqlrdrC8If8gaf/ALCV9/6VS1u0AFFFFAEV0bgWkxtBEbny28kSkhC+Pl3Ec4zjOK53wzpOtWMk7axa2Es12C11exXjySSt2UKYlCoBkAA8e5JNdPRQByGn+GNXij0nS7yezbS9HmWSGSMt504QERqykYXGQSQTnb2ro9R0jTNXjSPU9Ptb1IzlFuIVkCn1GRxVyigDn/BMMVt4fkggjSKKLUL1EjRcKqi5lAAA6ACugrC8If8AIGn/AOwlff8ApVLW7QAUUUUAFFFFABUN3brd2k1u/wB2VCp/EVNRQtAaueJajo15p0zxyxn5Tg4/wqgQQcEYr3iaCKeN45UDK6lTx2Ncpd+Aormbf9rUKvQGLJI9Cc/rXqU8bF/HoeTUwMl8Gp5lWhp+m3l7HK1rA83lYZlQZOPp+NegR/D7SI4cyvIX6s4OAB7A9K09FGg6fFJb6bcQEoC0hEgZjjqSaqeMjb3FcUMFK/vux5lBaxR3KtqcEsUOxuqEMTjjGfQ1ly+X5jeVnZnjNdP4z1G21PUDNaOXXywhz7E/pzXPWen3V/cJBbws7ucDjA/OuinK8eaWhy1I2lyx1K9Fbus6G2j3QhuGzHsUo4GQ3HOD9c1k/ZmLEYKE8qrAjI9quM1JXREoOLsyCitC70ieytIpbhHikk/gddvHY81nnrj0qk09iXFx3CigDNFMQUE0ZooAKKUnpgY9aSgAooooAKKKKAClVsA9eRSUDPQGgAoopUClwG6Z5xQAqL+8UHuRRIpSRlPUGnFURupBzjBHSp5IJILNJ2AKTE4z3qblWKlPhfy5Q3H40gfEZTavJznHIpyRoRnduJB+VRyDimxISRgehJ7knuabxkcUlFMQ5gQoORhucU2iigA6VoaTbXV/cyRQF2cRM5xz90ZrPrqvDOtQ+GoJ3msxJLMvyyBuQeyn2rOq2o+6rs1pJOXvOyMOUQxQrtYM4OTnv9afe29s++W0yFChmXtnPb2qvf3r3t1JMyRoXcsdi45Jp2myH7fErIJVZtpRicEH6UWaVxXTdiqWOMZOKSt3UtKsQxlsrmGNXy3kyMcxnuucYPtzWda26ySKFZd4OFXpvPsaammrg4NOxWihknYrGu5gM4rf0G0u7JmvklaB9hCEH+ftS3bpozPIlmolz5Y3tuAbucdDisibV72dnMk3LnJwAP5VD5qi02LSjTeu4ydmBdZlbzsktu65quxHG305qRrmZwQ8jMDn7xzUVapGLYUUdale1mjiWV42VX+6SOtO4rEVFGCDiigAoopVVnO1QST2AoA9U8AWaW3hxZVmWQ3DlyFPC9sfXiunrl/h/ZzWnh9mmyPNlLKh/h7f0rqK8Gv/ABZH0ND+FHToFFFFYmwUUUUAYXhD/kDT/wDYSvv/AEqlrdrC8If8gaf/ALCV9/6VS1u0AFFFFABRRRQAUUUUAYXhD/kDT/8AYSvv/SqWt2sLwh/yBp/+wlff+lUtbtABRRRQAUUUUAFFFRT3ENrCZriVIo16s7YFAEtcz4w1650mOCC1cRPMGZpSM7QMdM9+a37W9tb6LzLW4jmQcEo2cV5d43v7q81ho5mIihLLGnZecfnwK6sNS56ln0OXFVeSnddRl74w1O606SwkuDIjkZkwAxH93I7ViG6lxhWKjGODzj61DRXrxhGOiR4sqkpatiliT1p8UzxMMOwXIJAOM1HR1qyLnY6EZdXja1ilVin7xY3bAY9PzwT+Va6282kMupX0GxICdiEgs7YP5DvXK+G3kkna3jQ+dwY9o6EHrXYeM9X0z+yFgadZrgt8qxEHnGDn25rzqqaqKK2Z6VJp03N7o891LUptTu3uJiSznJyc1TqRIXk3FFJ2jJA7D1pGhkQZZePXtXoKy0R57u3djACegp/lkjIOSe1SRB44WY42McY9TT7e7SB/miDjGOT096Tb6AkupVIwcUVLcvHJNuiQqpA4PPNMQAt8wOPQU+grag+c89en0ptOYY5zTaYmFFFFABRRRQAUUUUAFFFKrFWDDqKAEp7ys8aIzEhAQAT05plOYl+cAAegoAbUkEvkSeZjOOMetCoh6v2zjFRkEHBpbj2HMQ7M2MZ5AFJkbcAc+tPKGOMl1wT90EfrUdAClWBwQQfShULZx2pASOaUMQcg0xCqoYgZwSe9dc/hjzrSZTqVpLKsW6KOKTJc4yMVx+aXe2Qdx+Xpz0rOcZS2djSE4xvdXAowYrg5BxinxO0JEsZIdT1HataONZrBL6aRYTyGYjJc5rLaXepjj+VD2P8AjTUricbakRdj1YnPqaVMs6g+uKcttK+diFsDPFXNN0+ae5iYRE/MMBl4Pt7020kJRbZoy6ReXHh578Mpt4ZSql2wccdPUZrnq7Tx5qLh002ILDDCAPKQYycA5x6VxY61nRblHmfU1rqMZ8q6D44XlYKikk9BTCCpIIwRwRXo1tpWnjTra2hvLSHUQCWjMgOc/wAJPtxXB6naTWV/LBcDbKrfMPeinVU20FSi6aTK8UjRSB1PIrq/DdpD4l82wuZXR403xMoGFI45H9K5Kp7O+utPnE9pO8Mg7qcZqqkHKOm5FOajL3tUb/ibQzopt43uBNNLlgQm1VA/mTmsiz0u71SdoYEDzLGXCDqwHX8a6Gz1JvGLwafqhVJgSIbmNcENjOCO4OK1INPTwndFbZxcXkkfzyyLwi56Ae+K5vayhHlfxHV7KM5cy+E5nTfCOp6jP5YgkhA+80qFVHtk963ofDWneHgJ9XvzHJJwkcAJJHftmnah8Q7iCEQQW8X2jOGlOSmPYetc1f8AiKfVLsXN4FZ1jCAoMDqT0/Gi1ep8WiC9Cn8OrPVdIu9PurBP7NkVoY/lwMgr7EHnNXq8asvEl/prymykEIlxu4znH/66sXvjPVrxVb7Q8Ug7xttA+grnlgpuWj0OmOOgo6rU9dorgvBfi+7u7/8As7U5/N8wfupGAB3ehPfNd7XJVpSpy5ZHXSqxqx5ohRRRWZqYXhD/AJA0/wD2Er7/ANKpa3awvCH/ACBp/wDsJX3/AKVS1u0AFFFFABRRSEhVJPQDNAC0Vw+n61rf2HRPEFzfiW21e5jjex8lAsKS5EZVgNxYfLnJIOTwK6vUtVt9KjR7iO6cOcD7NaSzn8RGpI/GgDP8If8AIGn/AOwlff8ApVLW7XP+CZluPD7zIHCyahesA6FGANzKeVOCD7HkV0FABRRRQAUUUUART3MFsm+eVIl9XbFcl4433MFlcwt5tmpbcyHKhuME/rVnxQkq38UsgJg8vCHsrZ5/pVjwtFJ5dy5Ui3cjaCOGPOSP0rpglTSqHLUbqN0zE8DRTtqs08QItvK2yNj5WbIwPr1rqNR8OaVqsnmXdqHfuwYqT+VaDNFbQlmKRRoMknCgCshPF+hPc+Qt8pOcb9p25+vSlKc6k+eC+4qMIU4ck2vmch4m8HR2N3G9ntS3lJADE/KfSuevtLW2kEUUvmuF3MMYxXsSTWWoxMiSQ3KfxKCGFc94h8Jm6kS603yYSqbXjb5VIHOc+vNdNLFNWjM5a2ETvKB5jHA8oO3GQcbe5rVtvD8rbkuN8U/RYwMtn6V0Fja6XYWV0y31nc6m2MCIg+Wuedp7nGeRVjTWaLU7ZrY/vGkA4P3l75/Cuidd62OaFBaXM28e18KWclmhM2ozoomOcBAcErXMXl7LeyK8gUbRhQowAKveKLa6t/EF2btW3SSswYjhhngj2xWTgitaUVZS3bMasnzOOyQ5JHiJKMVJGDg9RV7TtXnsvMhYCW1mGJoWHDD+h96oKjOcAV1A8E3TaDLqEbu0gAZIdnLjjJ/n+VOpKC0l1FTjN6w6HO3c4mmby9whBOxWOSB71BSlHBIKkEdeOlWrXTJ7qdYlKLlSxZmACgdye1XdRRFnJi6aLPzy1+ZBAqk4j+8TjgD8aqu+5yVG0dhnNac+mRC3T7NdRXDgneI8nHvyOlVDpt0to900RESEAsfU1Kkm73KcZJWsQLtAO4ckcUwjFFKhwwwM+1aGYlFPKKVL7lH+z3plABRRRQAUUUUAFFFFABRRRQAUpZmOSxJ+tJSqMsBnGfWgB+55UCsxIXpk9Ka0bIMkcZxxU+wQ4V2Vlxn5efzqHeoJwoIIxzUryKa7iwuiOd6Bgwxk/wAPvTHG1yoOcHGaSiqJCilCkqWA4HWgcckfnQArOSuwMdgOQpPFNoooA2dNuIoZreZRHuj5IfGOPWt+1vAlwL+3mWSYHJIwQ3tiuKErBdvGK0/Dupxabq0U9xAZo1bJA6j8Olc9SndNnTSq2aRc8dRTp4mmlmUhZVUpn0wK50HBrs/GmoW2pLFdW6+dG8QGWGDEcniuMqqDbpq5OISVR2Y/zpMAByNvTFT3ctxfk3c8hkfAUs3U4GKqgE9Bmu7+H2nThp7iZAIWTCJIPvn1we3HWnVmqceYVGDqS5DhMH0qzb6fPcxySxgGOJd0jk4CD3qzrdxHJe/u0CuMmRgMZbNUxcv5Uil2+dQDg8HkHn8qq7auiGknZm94a1DStJuhPKZZrhc+UGUJGCRgknJP6V1u+HxM5ZD9nuo4+Np3rIv6dK8urc8K6xNp2rxIDmOb903cru4yPcVz1qN7zW500a9rQktDKvUMdyylw5HcfyqCrF6jxzFHTaR0P973qvXUtjkluFFKEYnAU59MUFSDgimIEkeJw8bFWByCDgivRfAfiO81GaWwvZDKUTejt1Azgg/nXFaZoOo6u7pZwbygBbLAYB+td94O8Lz6NNJdXI2yMmwDIz+n0rjxUqfI09ztwkaimmtjraKKK8c9owvCH/IGn/7CV9/6VS1u1heEP+QNP/2Er7/0qlrdoAKKKKACiiigDmLLwfLavY20mqGbStOn8+0tPICspGdgaTPzKueBgdBknFdPRRQBheEP+QNP/wBhK+/9Kpa3awvCH/IGn/7CV9/6VS1u0AFFFFABRRRQAhAYYIBHoaAMDApaKAOB+ImuLhNIgJ3AiSYjp04H9fyrgckdDXo/izwXdarqBv8AT3jLuAJI3OOR3BrnLnwDr0G3bDHPkf8ALOQcfnivYw9SlGmlc8bE060qjdjP0zX9RsLyOaK4wUGMFQQR6H1r0LV7yXXfBM0+nZMskal406joWWuUTwPfWkcc97GzhuqQ/MV+uP6VsNc3vh7Snnii8l7p1iiDr90AElsfoKzrck5Jw3uXR9pCMlUvZo4O1gnnu4obVHadmAQKOc13/i3V28OR29vp8MMN5cJulmWMZA6cfU5/KovDOu3Z1tILkrMLrIL+WocHGeoHI4rV8ZeGpNdhgltiBPBkY/vA/wD6qVSonViqi0HSptUZOm9TE8Ka7J4hujpWtKl0CheGQrhlI6jI9v5VB400i20m7hnSIGCVNoGckMOvX6ijTLF/BkovryLzbqZSkEIYDA4yxPOO3503Xr2XxVal44PKubONneMPkPHkZK+4x0ppWq80PhE3ejyz+I5a3vpLWUvEAoJB24yOOlbI8da6XBa6+UdQEXn9K59o3UbmQgepFSW1rJcyqiqTuPbrXZKEJayRxRnUjpFnrGg6hFrujyStDDLICVYFBhzjIyPxryW5Lm4k3rsbccqBjBz0xXofhhf7K0W/kjkUyJEWEQYFsgE5x/npXnUkjSyNI5yzHJJ71zYaKU522OrFSbhC+46C4mtplmhkZJEOVYdRT2vJX5YgsTkseS31qCiuyyOK7JA0ZDErg9h2pgYryOtOQDJRsDPc9qRoyGwDuHYjvQA2inFCjbXGDjNNpiCiiigAooooAKKKKACiiigApQfWkooAKKCcnJqU27CETZBWgLDG24GM571K9lOlol0yjypCQp3A5I68dqjaJ1UMVO09DikJYJt3Hae2eDS9B+o32ozQACcZwKswwwyIQ7bSp5bsRQ3YErldVLsFUZJOAK2b/QBp+gQajLPmaeYp5Y6KBn8+RUNg2m2l9HLcSSsiZJEQ5P4npWp4i1qy1PT7RLeNYVgyI0DbuPcetYylLmSS0NoQjySbepy9AJUgg4IqxBZS3m8wKp29V3AGtTRNBF5ewret5EJf5mdguR7ZrSU4xV2ZxhKTsjodF8Ox6t4SFxJK0cjly2VyCAeP5VwR6mu713XZrC0ltLGYWsMeYoYkAyQDgkmuErHD8zvJ7PY3xHIuWK3W5s+G0ie4uhMwVRbsyksACw6DPvTWuPKj+0rKwlHRw3OazYJRDICcle4qd7qJ43RYFBLBlY9eM5H45/StHH3rmSl7tivPK00m9yS2OSajpzgg5IxkZptaIzYVseFJYYfEVo80SyLvAAbsTwD+FY9dBolhA1usxVnmckKgHP4VFVrkaZpST5010HeMNMNhrkiHcIGUNESO3p+BzXPfdNe0NpMGoaXBBqUQkkWMBmzgg455rzfxfo1po1+kUFz5jMuWQryo7ZNc2HxCl7j3OnE4dxvNbGh4WsrHxG8sd5vS5jUYaMgAqPaumn8B6NJEixLLC6dHV8k/UHivNdN1OXTJWlgZlkIwCrEV6L4W8YrrDJZ3SCO528MG4fH8jWeIhVi+aD0NMNOjNcs1qbWkaLa6LbtFbbmZzl5HOWY1oVBezPb2M80a7njjLAe4FcYmpX0Uguhdyu+QSC2Vb2x0rijCVS8mzvlONK0UjuqKRTlQSMEjpS1ibGF4Q/5A0/8A2Er7/wBKpa3awvCH/IGn/wCwlff+lUtbtABRRRQAUUUUAFFFFAGF4Q/5A0//AGEr7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUVBcXtraY+0XEUW7pvYDNCV9hNpbk9FU73V9P06BZ7q7ijRvuktnd9B3rEl+IGho4CPLIO5VMY/OtI0py2REqsI/Ezp6KwNM8Z6Tql4trE0kbucRmRcBz6Vv1MoSg7SViozjNXi7hRRRUlBVTUtNttVs2tbpSUJyCpwVPqKt1l+I9Q/szQbq5BO8JtTH948CqhdyVtyZtKLctjJtLHQPDck149+Jp4UOPMkXK+wA79q5q5+IWqS3heIJFAD8qKATj3J61zFzeTXbZlfIHRRwBUNexDDLeerPFniZbU9Een3dk/jDRbPUbZ0juUDAhs7W55Ht0qbw14Ym024e7vnjaRkKLGnIAPXJ79K534danNFqL2DMTBKuQOyt1/XBrqdQ8Y6fYXrWvlTTtGcSNGBhT6cnk1xVI1It0o7fodtKVKSVWW/wCpxXi23sbXVWNlbYgXKnk7d/fFcwCQcg811/jFY1tobuzlEltesZFOOV9R+ZrkK9Gg7wR52IVqjNPSdZmsL6CVyzxow3KTnI7/AKV2H/CvdOv5UvLS9kS0mAdYwoJAPOAa88rfi8W3kVtDCC4EKBEEchUAD27moq053vTdmVRqQSaqK6Ny4+G0m9ltrldv8LyHkexAFcbeWUlnNJExV/LbaXQ5BNdbF8SrgWyxS2CSPjDP5mM++MVx09w0zHk4JzjNKj7a79oOu6Fl7MiOM8Uq9aSpYmUAryCwweM8V0s5kRl2bqc/WnbGkcYXBboKaEYnAHSpJmYFVI2sigYFAepEeOO9FFFMQUUUUAFFFFABRRRQAUZoooAKlSdgvlvloz/DUYIB5GaswQowaVTkIM4Yd6TGiIXMysrByNhBX0GPamyyGV97AAnrtGB+VSmESxvPuVTnlQP5Us4tlRFgkZyVBfcMDPtSuh2ZWopWADYBB+lGB3qiQKtgEg4PQ0lXTHJb2KXAbcHYqhI4HHP41T3Etk9TSTuNqw+BmWUFWKn1BrqNMumuLYtdHMjHAJH3x7VgR/Ykst+S9xu+63AA/rTIbxo5Fcucg5BHBX6VnOPOawlyE+tTI94UQMCi7X3euT/9b8qzq6Y+F7vWrdNS02aK580ZmTdho37gg+9Rf8IffQ5W5jkjcc8Jlceu7pUxqwStccqVRu9jCht5bhgkUbOzHACjOTW5Z+DdWkcPeRrY26nLyzsAAPpXWeGNJ0OzuI/KuXnugMjeMLnuV45ql8SLyUNbWqE+WFLPjpk8D+RrF4iU6nJDQ3WHjCn7SevkilfnwlDEsCSXF8yDaiqdi57ndisCP+zTdFWDpFngdePc1mU+KVoWLKAcjGDXRGnyrdnPKrzPZI6xfCEzWMmpQ+WsGC6iQHdtA6itDSr660i3iVJA8cfLIVGDk5OD1o8LeLDNHBpl2sRjwIR64PA+tQ61Pb6ZrDW1lGZVgILLK2VB6445Ncb55ScJo7FyRipwZ6DvHl7+cYzXjfiaeW71qW6lAHnYZQOw6AfpXqWgayutaeZ/L8uRG2SJnofb2rm/FHgqW6uBd6Yu7d9+EtjB9R7e1Y4aSpVGp6G+Ki6tNOGp53To5HhkWSNirKcgit2TwZq8PyyW7Bz91VBYH8R0rQ074e388qfbD9nQHL5wfwGDXouvTSu2eZGhVbskdr4WvJdR8O2txOdzspBJ74JFWI9D06K5E6WwDA5AydoPqB0qxY2cOn2cVrAMRxjAqxXiSl7zcdEz3Yw91KWrQUUUVBoYXhD/AJA0/wD2Er7/ANKpa3awvCH/ACBp/wDsJX3/AKVS1u0AFFFUtS1a10mNJLoXJWQ4XyLWWc/iI1Yj8aALtFY0GtWGvCWwtZNRgkeMnzDZT25Ueod0Azz9ax7CeTT9W1Z9Nu7y90yxsm803Vw0y/alOdqMxJ4XO4A4BI75oA7GiuG043unL4X1NtUvLuTWHWO8jmmLxuXheTciHhNrKMbccHnNdZqV9cWMaNb6XdagWOCts0QK+58x1H5ZoAz/AAh/yBp/+wlff+lUtbtc/wCCZGl8PvI8Tws+oXrGNyCyE3MvBwSMj2JFdBQBzXjPxJJoNnHFaqDc3GdrN0QDqfrzXltxd3F3O01xO8sjHJZmya9c8TeGovEVoiGXyZ4STHJjI56g+1cO/wAPdZibnynX1jbP6HFenhalKMNXZnlYunWnPRXRyxJPUk0AEnAGTXdwfDSRrdGmvlSU/fTZkAfXNbtt4E0SG3SN4XkkXrLvIJ/I1tLF0o7amMcHVlvocL4Y0e+1HUrcxQyLFFMrPMRgJg56+tevVDaWlvY2629rEsUSdFWpq82vW9rK56dCiqMbXCiiisDoCqupafDqmny2dxnZIMZHUHsRVqimm07oTSaszx/UvC11YXcsG9W2k7cgguOxFS6f4M1O9ZQYmj7t5ilQB9TXrRUEgkAkdMioL68jsLKW6lPyxjP1PYV2/XKjVktTh+pU07t6HN6N4etPC6tf6jdxBlHAHCr2+pNcpcrHc6pOLKVZUkkLoXYRkAnPO7H51R1bWW1Ahny0u/cz7s/hWb9plEnmBsNyM/WuunRnrKT1Zx1K0NIxWiNxtbiXSY9Ont4p4Y2LcMQ5JPOD2qHSxpN3dC1ltpIGn+SKUyhgrHoCCPXuKxK0dINtBeQXd65MEMgYxpyzEcgfStXBRi7GMajlJXLuo+GLq0jd1hmBQgFTHwO3XpWCetekDx5pGqh7C5tpoI512eY+CAT3OOlef3djcWV7JaTRlZY2wRipozm7qorMuvCCs6buivSujRth1KnGcGuz8KeErPVtOnnuPMEyPsQ5+XOAenfFYfiiwutP1mSK6AyVBRl6MuO361Ua0ZTcFuiJUZRgpvZmPQCVOQcUVYs7N7tzjiNeXb0H+NatpLUySbeh1fh7w5c32km7RoVFwSgRyQRjjINcrqVpPY6jPbXAxJG5U+/v9KWfUbmXYvmMkcYxGinAUV0Xh7xDDdXKQa7bwXUaL8txKgLoPc9x9a5/fheW/kdH7upaGz7nK+WVK7wVDDIJHUUmM5I6CpbuYT3Uki52FjsB7L2H5UyJS77M43V0dLnP1sMoBwc1ObXa4QzRBzjgn19+gpt1bS2dw0EygOuM4YEcjI5FF0FmhhHG7PWm1cht4Ps3myE4PAbtn0+tVAM/KBkk8UJg0KwKMA2D3pUCNuDBs4+Xb601+uM5xxmkBIORQA4RuxwFNSNZ3CkL5L7iOm3mniae3j3glTMMgj0HFLFqd3ENvnO6f3WYkUry6DtHqVelX9MtJriZhEwAWNnfjICgZ5qtdMjXDNGhRTjCnqK2tDv/ALPoWp25j4cKyyBR26gnrg1M21G6KpxTlZmFIVHyozEe9MoONxx0zxRWhmFOVtnzAA004zxRQBK1zK0AgLkxhy4XsD0zUVKEJBPYd6SkgdwoXO4YGT6UVoaFbRXOsW0c8ohiLZMh6DAzRJ2VxxV2kbnhzV28NaddXMkTNJPtEcR4AxnlvSqupeN9W1CFrdmiSJjyETGfbrW54j8PkaZLPYEXFqED71YEqQOc+tcCQR1rmpRp1G521OqrKpSSp30N6z8TvDNA88O7y5FYshweDXY3lvY+OdMe40+cxzouxlcfiA3+NeYV6H8NrGaKG8u3JVZCqKnrjnP61GJhGEfaR0aLw05Tl7OWqZxGpaTe6TcGC8gMbDnqCCPUGqfWvbdV0ez1iER3ce7byrDqtUrHw1o+hxy3Ii3lVJZ5ecDvgdKiONXLqtS5YB82j0PIY5HikV4yQykEEdjXSX1/a6nH/aRuI4ryQhJrbBO5gMbl9j71iapPDcancTQRCKN5GKoOwzVSuxx5rPY4lPkut0eneENT0mz0yWJ7nyZlbzJjOQuc8cc8iujsdUsNSVmsruKfb94I2SPqK8OJLHJJP1roPA32j/hKbbyCQMN5noVwc5/SuOthVaU7ndQxbvGFtD1yimu6xoXdgqqMkk4ArOt/Eek3Vz9nhvUd84GM4J+teYot7I9NyS3Zp0UUUigooooAwvCH/IGn/wCwlff+lUtbtYXhD/kDT/8AYSvv/SqWt2gAooooAr39p9vsJ7T7RNbechTzoGCyJnupIOD71m6H4cGhwLax6pe3VokXlJbTpAEUevyRqSevUnOTnmtqigDB03wjZabd20y3d7PHYhls7eeUNHbAjHy4AJ+XIG4nAOBW9RRQBheEP+QNP/2Er7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAFFFFABXFePvtEqGHLeWIgyKOjHPP44rtaintoLqPy54UlX0dc1pSnySUjOrD2kHE8IowT0r1698GaLeIQLcwt1DRnG38OlZz+DfD1pEIJbto7hzkSNIob6Y6Yr01jKb6M8p4GouqPMq1dL0G91aKQ2MfmsiZYZwOvQE963dY8HNo1rLdR3CSwcAFh8xycAY6Va8N+IpdOkt7CS3gFq7BN0akMpJ6k9+audZyhzU9SIUFGfLU0MC38H6w04F1bfZIQRvmmYBVH5811fjFtJXSILmGOO5nJEMcqueAB3I61kfEHW5LjVRpsLlYbYDfg/ecjP6DH61Q8Lad/bklzaXEpjgSLzDL2RgcA/qazfNKMas3a3Q0TjCUqUFe/Vmr4V8VyWM6WN55a2ZDEMqYKEDPbrnFV/E/i7T9ZxBHpwkRM4mkOGH0wf51o2Xgi1mtrho9Ujup9pWPZwqH1PP4Vxt7o17YXTW06IJFOMCRT/WnTjRnUclv9wqkq8Kai9vvLdnp1pLp326VwY0lEZiUnzGPXHoBjvW5D4w0612wxaDapInCsG4A9+OtUdO0ljpslnL+7upnDRMGyAwBAU/XPWsO4065t2KyxlWU4IIPFXywqNqTM+adNJxQupvZy3Bls43hViSYmbcF+h9KtabbWEml3s0t0UuolBSJl+VxkZ5rNmjSPASVZD3wDx+damkaGdStp3+1wQuBiNJJAC5rWVlHcyjdz2Mdsbjtzjtmt/wAL2NlerfGUv9qggaSFBjDYH9OKozeH9TtpxDPbeWxGeWBGPXjtUsE50Pe8NwGupV2BouiL35Pft+dE3zRtFjgnCV5LQymVlcqwIYHnNTXdvJbvGJOroGxnkdsH8q0NL1C3ivg0sO7erKC/zbGI4YfjWjqlpb3VumAwmHCADnn1oc2pJNAqacW0zmTJJ5XlbjsDbtueM+tSWlrJdziKIc9Sewq3cm3s/Nt9m+YYG/qBVWG48tgeQe+3iqu2tCLJPUY0LjojcdeKjrW89rmJYINqJHySfvZPWqzWy7GVFZnU/Mc8fyoUu4OPYsw6VNe6LJdQlZDbjcyZ+YDvgdxWSASQAMk9AK1bnVDHFBHZFrcIuCQeQe/NVYLmOMkOik5yJAOR7UouWtypKOiRp3unrZMLW4RHkCqzSHPUqCVH0zWat9Mlu1rEqCItk8cmoPOd5dzSEEnrmpjCrx+akgUAZbd60KNl7wOV37pCtuWUNuUAnHJp0MDOzKpGcd6Yzrxjtxin20ywl2IySMAZwKp3sQrXGSQsiBzjBOMZ5z9KjpXdnYsxyx6muk8P+FP7UnVbicxkx71XbnuOvPvSlNQV5FRg5ytEzdL02XUEukQMWigMoA9ARnP4Zqo32XzEVd6gH5mIzx9K7vXNFXw14WuPsZZnnYLPL3284HsM155WdKftLyWxpWh7K0XudJZaHpFwFJ1e3VWOD5rbGX/gP/16r6wdP0nUPK0a488KgBmbnB747ViDhST36UmapQd7t3IdRctlGzNvTPFOoWKywFkmgnGHSRePTIxVqLT9JvrJ7gSlJg2DFtPr2PTpXNVoafqpsoGhMQZWbO7PIpSp21hoxwqX0nqjSj8ORm6jC3XyMwzkfw9yfbFdzp2qaHpFiYUu+FyxZkILn24rMOs6HqemSxWYjt7p1BIaPbvwckbunOK4m+1eW6mUlAsan5V74rl5JV9JXVjr540NYWdz0S38Z288uTBtgBwXLfMo9SK2pJ7HUbOaJbmJ43UoxVxxmvGGvpWbg4U8EeoqS91BryVW+4AoG0dBRLBq+jsOONdnzK5Lr2jXGi6i8E2GUndHIOjr2NZtXIppWhkhcvIhU7e+CBVMgjqMV3RvazOCdr3QVLbXEttMssLFHU5DA4IrU8M6FPrepBEUeVFhpWPQCuzvvAFvNetPZ3C26Ocshi3bfXHNY1K9OEuWRtSw9SceaJyOs+L9T1i1S3kZYocDcsfVyO5P9Kw4pXhkEkbFWU5BFdzqHw2mVWNherIqjKxyLhifTPSuYi8M61NefZRp06yZwSy4Ue+emKKVSjy2i1YKtOtzXmnc9R8M6q+r6Ss8uDIp2sw/i4Bz+ta9Z2g6UujaRDZggsoy5HcmtGvGqcvM+XY9unzci5twoooqCzC8If8AIGn/AOwlff8ApVLW7WF4Q/5A0/8A2Er7/wBKpa3aACiiigAooooAKKKKAMLwh/yBp/8AsJX3/pVLW7WF4Q/5A0//AGEr7/0qlrdoAKKKKACiiigAooooAKKKKACiiigAoorjPFPi5LcLb2jyAZO5043EdgfT3rSnTlUdkZ1KkacbyOk1LV7bTNqyhnkcZCIOcevtXn97r9o15PJJvdnkOeAeM8D8q5+91e8vpC0s74xgDcTgVSJJOScmvUo4VQWu55NbFub02O9HiCzv/DiaU2WlkyAXP3ADkH6jik8N6NHJq6m9n3CAebGoXAYg9/pxXDRSmNsgZrXttbUHN1lyqYUDpn3pyouKah1FGupNOfQ2vHHhuWPUH1WB0MNwwyC2CGx/LjNZ9hdrp2ltYxxCSWWUSTOr5BUDhfw61n3evXNxEluSDBG+9FOcA1R+1S+cZQxUn+6cVcKcuRRl0InUhzuUOp0f/CRvYTRz2YVJdpDFhkAenvXOS3Uk24yEszHJOep9aJ5zPgszEgdz3qIKTjjqcVpCCjqZTqSloW7S/lhuI5TIVaNgytjOSOma9O1qCTXvDcVxaKHaRRIVXndwR+OCa8mZWU4YEGt3SvEmpaJpbW0DlVkfemRnHrjNY16Tk1KO6N6FZRTjPZmPdW01pcNDcRPE4/hdcGrug3HlX3lHlZRgjGa0HurjxlJFazCNdRjB8qT7omXrtPofQ/Wtnwr4PvdO1NdS1MJBHbgkAsOTjGfYU51VGDU9+wqdJymnDbuF3bXWnWf2u8ik8pkBDYyVHQKfTtXCyv5khbGB2Fewan9i8SaXcWNnfQyS8EbXBwQc8+1eU6lpd5pl69tcwsjg8dwR6is8LNSunozTF03GzjqitCrPMiqcMzAAmvV9bhsrLw7ElxcxxSW8YMZYjLkDp75rz7RdDvrq4jlFnMyZyDsOG/GneK5nOrfZzcCcQRJGCpyAQOR+dVViqlSKT2JpSdKnKTW5jzuZJ5JD1ZieDmmUUV1nGXLLYpLSTiHK/eIzn8PWtApB9lkms7hGZSAyPkFieNw4/MVhntzWx4atPtuoCGUhbY4MzMcAKPf1/wAaymrLmNabu+Wxn3COkh847ieciq9bXiW2tLHVfJtLhrmAICrFgcE9RkVi1UHzRTJnHlk0FKzlgAe1JQAScAZNWQFFGKKALloYVVCELTl/lJ+6B9K2l8R3Nlay28KhbqUgG5VsEJ6Adj05FVfDPh+bXJ3COIo4huaUjIHtiodYhisL2SGK5W54AZwpCk+g/SueXJKfK9TojzwhzLRG74c1Ce8v10+4lluLW8Vo5opXLY4J3DPSrM3w5t45TM2rKloDnLJzj0znFcbbajLahvKABbqfUen0pW1S8I2i4kC5zt3cZ+lS6U+a8HYtVqfLaaudz4hsLB9HstP08xGJN22YYY5HbPvkmvPp4ZLeZopV2sp5rd8N6xDHqHkapmW1mGCT1Vuxru77wnpOp2KrCqq33lmHzE/UntWaqfV3yy18zV0/rK5oaNdDySgggAkcHpXoi/DiCPc73Zk4J2hMfgOa8+kR0cq4IKnGD2rpp1oVL8py1KM6duYdDcywjahHXIyO9MkOXJwBnnA7VN9jkEEcxICyEgfhUDqVYg9q0Vr6GTvbUSgUUUxGrYXrQtGsdvCc5Hfc2e3JrZk8IXs8aaha2QaKRciION31x/SuSRijhlOCDkV6z4N1wavpflPGsctsFRgvQjHBrjxEpU1zR+Z24aMKr5J/Ij8H6Dc6Sk890giefaFiBB2gZ6478101FFeVObnLmZ68IKEeVBRRRUFhRRRQAUUUUAYXhD/kDT/9hK+/9Kpa3awvCH/IGn/7CV9/6VS1u0AFFFUtSv5rCNHh0u81AscFbXy8r7ne6/pmgC7RXPz+J7uCxurl/DGrxeRCXUSLE3mNwAoEcjtk59OgNcroGpJb+JdclhkurjUJ9KjmeSWymiDzKZicB1G1QNqrnqBjkg0AelUV59pljaaZH4O1PT8/bdTdUvJQxLXavbvI7Of4sMoIJ6V2mpS6pFGh0u0tblyfnFzctCAPYhHz+lAGf4Q/5A0//YSvv/SqWt2uf8EmVvD7tOiJMdQvTIqMWVW+0y5AJAyM98D6V0FABRRRQAUUUUAFFFFABRRRQAUUUUAIw3KVPcYrx7xTpd3pmrOlwpMZA8qQdGX/ABr2Kori3huoGhnjWSNxghhmt6Fb2Ur2OfEUFWja54RRXU+LvCcmjsLy2zLaucMQvKHtn/GuWr2oTjOPNE8OpTlTlyyFxSUVdS1tolVrqXcWAbZEwOAfU+vtVN2JSuUqKdKUMjGIFUz8oJ5xTaYgrcsLW2s9MTVZpY7hll2xWnqeuX9uOnesMetaMLW9wYo5BIFA+dowCV49+tZzV0aU3Zm3a+MFVGtb/TLOaEglBHCBsbtx3qHULWPVrRLiGcF0HGeB9MdqoXeiS26w3UMn2m3mzsdFwQR1BHY1peHLeCc3VnIyrLPCwhLkgK/b25zisGoRXPA6E5yfJMk8JWdhZa2k95fxGSPIiRA21mxj7xGKo694jutQLRmaTDHLAOQMemKsx6Lqc9wLIWEySZAJZCFX3z0xWFq9v9k1e6t8k+XKy5PsacFGVTmbuyZylGnypWRFb3MsM6Oszpg/eViCBXo/hO6Gr2U66kEu47UgpNKAxA7jP4V5oiF3Ar0LwXp8smm6inzRWs6BEY9C2Dkj9KWKS5LlYRy57G4viOwbMCJLDGRtSUKAo9OO1eUXsM8cn75GHoccEfWvQY9B1GaQQtEqoThpQwK49R3rWn8K6bM5MhkEJ5aLcNv+Irmp1adF6dTqqUqlda9Dx+prWGSebbGm8gZI9q7m9+HCSyNLp18giJyqOM49siqUcUPhi/Mc9tDfXSoBtzhIh19OTXX9YhJe5qzi+rTi/f0Rmywafp+jLHOrNqMpLkL0jTtn37/jWX9tEYRYFEYTncByx96m1i8+1XcsvllGlcsQTnGe1ZtaQjpdmc5a2RYubx7idpWVcsOeOD71XopShBAOMkZrRJIzbbEoqT7NPtLGJwo7kYFNjQs3TIHJouFmP2HYjdA3BrX8PaSNW1dLZFUptJcsu4KPWl13V7a5s7azsbWO3iVQX2cs/HG44rN03VLzSrnz7OZomxg47isnzSg7aM1XJGavqj1y20SKw0WawtCFaRGy+MZYiuC1jw9f3Dgw2U/mKMOoQkD3BrqPB3il9a8y0vCv2mMblYcb178eoror95o7C4eAZlWNig98V5iqVKM2nueq6dOvTTWx4lc2V1ZttuIJIj23qRn86grS1Odp0EksjPI5ySTzWbXrxba1PGkknoFdfpOrywC3TTpWQuhWXI6ADrjpmuQAz0q1bNLDh45WRs8YNTUgpKzLpTcHdHZXvjGaCwubRrrfOygJIB8y88jj2rjWuYjOsvlbiGy2853fWmXKNG+xlYOPvZ9agqadKMFoOpVlN69DXGpx30iQXMSIhON4GMVlzEeawGcA8Z60yvSbf4eadPbwTXE9wJGQGQKwwTjtxSnUhR36lU6c697dDzbnFGCRnBwK9Pi+H+k2shneW4ljTLeWxGP5c1xtxK88kkkKxQwuxYQBAVUUoYiM/hHPDypr3jDVWdgqglicADvXrPgvRG0jRg0ylbi4O9weqjsP8+tP8OaHpEVla6hbWSrLJErbn5KkjnFb9cOJxPOuRI78LhvZvnb1CiiiuE7wooooAKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/5A0//YSvv/SqWt2gAooooAKrJYWseoy6gsWLmaJInk3HlFLFRjpwWb86s0UAZNh4X0bS70XlnZeXKoYJmR2WIMcsEUkqmf8AZArWoooAwvCH/IGn/wCwlff+lUtbtYXhD/kDT/8AYSvv/SqWt2gAooooAKKKKACiiigAooooAKKKKACiivPfiFrd/BqMenQTSQQiIO2wlS5JPf04rWlSdWXKjKtVVKHMzpPGOqLpegSkbDLN+7RWAOc9Tg+gryFsbjjpT5LiaUASTO4XoGYnFMr2KFH2UbHi4iv7aV7BRRRW5zhQDg5oooAVTjjPBqUuE+VQfxqGgknqc0rDudZoWq6emhXGn6hKp80M8Z2ksr9B0pIZIBbhbOFmdzjvwR3JPpXKqcGuj0CSKeRg0pilbaqFx8jeuT27VzzpqN5I6adRytFnoej60uoMYJI/LmRc/eyGHqKx/EXgWPWb9r62uRbyyY8xWTIY+v1qW3W28Nyfa9VuUWWRSsUUYLHHc1vafqVpqlv59nMJEzg9iD6Edq8xuVOXPT2PUSjUjyVNzK0zRdM8JaTNJNIHBG6aaRfvegA9Pb3rhNW8Z6hqEpWNhFbA/LCBxjtn1ro/iNqOyzhsUByWDufTrivOq7sNT5l7SerZw4qryP2cNEjrvDPiye1vWSYILdh8yZxjnqPet3x3PP5VlGrEWku4sQeGbjAP61x+laS21Z7oNGrjKKVPzr6ivTdKsvN0KG2v4VkUg/u5VzgZ4Bz7VnX5KdRTRph+epTcGcv4GlnXVZoIiTbGLdIuflVsjB+vWtHxF4Vub+/N7YyR7pABJHISOR3Bqn4j8RJ4bLafpFrBAf4mC98en496xdE8ZXkepQ/aZHZHcCTLkgg+x/pS5Kkn7WGgc9KK9jN3JPEfhddJ0FLq4l33bSgfJ9wAjpXIV7jqOnW2rWL2l0m+J/Q8j0IrynVPDsmnX81qyy8MfKbbkOvY1rha/MmpPUyxWH5WnFaGJSqCzgAEknGB3rpYfAestbJcmFCG58rfhsVoaZa6V4VuRcau3mX2QY4EO7yh6k9M1vKvC3u6vyOeOHnf3tF5nUeGtISDw7DDe2qGSVcyrIuSR2Bz7Viaj4ACJcPZXW2LaXWIx5bPXGc1Z1XxirIn2GVo1K5Y7QWJ9B2x71e8LeIv7XEsE0gM0WCCcAsD9K8799C9Q9P9xO1M8turOa2Pzodo/iA4NV69wn0jT7hZVktIj5ylXOwZIPvXKQ/Da2S9Dy3he2DZ2bcMR6E5rqhjYNe9oclTAzT93U5bwta3Eur2r2obzRKpyP4VB5J9sZr2Co4YIbdAkMSRqBjCrinblyRuGRyeelcFet7WV7HoUKPsY2ucl4l8Hx3twbqzthlx86oQCG/vAdK5a58Ba3CqPHAswb+FWG5fqK9Hi17TJrn7PHdKXztBwcE+melaAYEkAgkdcGtI4mrTSX5mcsNRqNv8jjvDfgSGzjFxqqrNOf8AllnKqPf1rWi8HaFFdfaFs/mByFLkqD9M1uUVlKvUk22zaNCnFJJHkHjGEWniO7iQ/IWDAemRnFYVem+KfB8mq3D3lrIgdh8yvxyPSvPp9LureIStGSnqO1erQqxlBK+p4+IpSjNu2hUQKZFDHC55PpXsfhm8lu9L/eP5gjbYkn94YFePi3mLqgics3KjacmvXvCVlcWHhu1guV2yAFip6qCSQKxxtuRG+Avzs2q5ybwRpkt2ZhJOkTHc0KsNv4cZAro6K82M5R+FnqShGfxK42ONIo1jjUKiAKqjoAKdRRUFhRRRQAUUUUAFFFFABRRRQBheEP8AkDT/APYSvv8A0qlrdrC8If8AIGn/AOwlff8ApVLW7QAUUUUAFFFFABRRRQBheEP+QNP/ANhK+/8ASqWt2sLwh/yBp/8AsJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAFFFFABXNeNPD39s6cJoEBu7fJX1Ze610tFXCbhJSRE4KcXFngjoY3KMMEHBFJWvr+n3Ftrl2lwjK7zMwO3hwTkEVpv4atNK8ORanqJmF1McRwZAA9M8Z6c17jqxST7ngKjJtrscqQVOCMGrmmabNqdz5MSM2FJO0ZPAzUV3cfaZd+xVwMZUdasaNqk2k3wnhkZMqVbAByD9aqXNy6bkx5ebXYpSp5UrR5B2nGR3ptWr2ZbuUSpGFO35iD196q8Y96pPQlrUKKDRTEFT293JbnKY3HuagqzY2Ut7KVQYVeWbGdopO1tRxvfQ1X1a+1y+D3ERllSIKPKQn5QeuPxrs/BOm3dqt1dXETwpNtCI4wTjPzY/GsDQYH0O7kureSK4cjYHZSAR3xzx9a9A069XULKO5Vdu7IK+hHBFeZiZ2jyxWh6uFheXNJ6mf4g8NQa8g3SGKQDG7GcjtXDN4C1eK98lYRKmfllDAIR6nnI+lep0Vz08RUpqy2OiphqdR3e5V0+yWx062tSQ5gjC7iO4FV9b1i30ewkmlmRJSp8pW6s2OOK0q80+IsVwNdilkDGBoQIz2Bycj60qMFVqWkx15ulTvFHJXNxNd3ElxPI0kshyzMckmltADeQ5BI3jOPTNdB4X8KnXkuZJCYokwquVPJ74/wA9663S/h/pun3SXEk0tyyHKq2AufpXp1MTThePU8qnhqlS0uh0NzdxWVi1zJkRoowB1PoK5+58XiKJmltFjJ4iYvkA+9aPiK6tUsjaTFzJKMoEGSMHg/TNeY6zeCaZRu3KoxgetcWHoqe6O/E13T2ZvT+NL+O4CLeFoj99wi8f7vFcnqFzLeX0txK5dnYnce9V6K9OFKMNkeXOrKejY9ZGChSTtHYU+G6eCXzI2IPr3qGirsjO7PQ/CfjY3DxabqPMjEJHNnr6A/413NeH6TaXF5qcEVsjNJvBG0dOete3rnaNxycc15GLpxhJcvU9nB1Zzg+boQXzSpYztAMyiNin1xXlmr6k8aukLsHYYeXcdxz1r1l2KxswXcQCQB3rxjVWkvZJL+QjzJGyygYA9sVeDSbdyMa2krGfHPJC4eNijeoNalj4ivrO8S5jn2sp5XHysO4PrWRQBkgDmvTlGMt0eVGco7M9s0vWrTVYkML4kKBmjIII/wAa0K4XwbbXc88MzIyx2xKmQjGeMbf1/Su6rwq0FCdke/Rm5wuwrGl8MWEs7OTIsbHLRAjaf64rZoqIycdmaSjGW6K9vY2loMW9tFEP9lQKsUUUm29xpJbBRRRSGFFFFABRRRQAUUUUAFFFFABRRRQBheEP+QNP/wBhK+/9Kpa3awvCH/IGn/7CV9/6VS1u0AFFFUtSm1OGNDpljbXbk/Os90YQo9QQjZ/SgC7VO11fTL66ktbTUbS4uIf9ZFFOrunbkA5Fc94hvPE7+FdZ8zS7W0ZbCUxyW1+0z7tvZTEvbPOfSs/TprzT2s9P0+/t79b3SZpYlggRPszKq7ChQZ2Etj5snIHPWgDsrfVdOvLqW0tr+1nuIP8AWwxzKzx/7wByPxq3Xn2m/wBn/Y/Af9l+V9pyN3l43eV9nfzt3/A9uc/xY712mpRapLGg0u7tbZwfnNzbNMCPYB0x+tAGf4Q/5A0//YSvv/SqWt2uf8EiVfD7rO6PMNQvRIyKVVm+0y5IBJwM9sn610FABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFADWRGILKpK9CR0rj/AB6BcC3gVWkdVZiq/wAOcYP6GuyrA8R6RPdK15ZsPOSMgo38WORj3rajJRmmzGvFyptI8jdGRirAgjqDSVb1KBoLr52DM43HFVK91O6ufPtWdgoqSC3lup1hhRnkY4CqMk1p6v4dutDtLeW8IEtwThBzsA9T680nKKaTerGoSabS0RkUVLAnmSrEejH8qjddjsvXBxVE2EAJ6Cr1iLm3HnROUBxxn734VSRijBh2r0TwfYaRdLFJLaYu1XzVBYlMZ6ge1Y1qnJG7RvQp+0lZM05PDCCNZIbkwR7AXRk3FeOcVgweL7yzCR2dvD9kj+6jgl3HqT6mvQSAQQRkHqK5CXwErXR8q+Mdsxzs2ZZR6A5rzKVSDuqh6lWlNWdI6myukvrKG6jyEmQOAe2aj1G+TT7OSdhuZR8qZ5YngVLDAlpapBAuEiQKg+g4ryjX7u4lvCs8jh8bnJPO7PT8PSoo0lVl5F1qzpQXc6a+8XahAVRzDGJOrqvKD2z1rJufGk81ubWeOG4RjlXkVSy/hjFcrNcSzYWWRn29Cxyair044aC3R5csVUezO203x5JaRfZRbRygfcOQgH5Dmus0bxNZatFhmW3nB2mJ3Gc+3rXjtdBoLQ+W8RbfPIeEA5P0rKthoWujWhiql7PY7vxBpVzcXAu7dPMHl7XTIBGM8jP1ryq7DC4bcOM8fSvbrJJVsIEuDmURgPn1xXkPiDTpNO1S5ilBQmVigK8Fc8EH0xUYOerizTG09FJdTJopWBXgjBpK9E8wKVHKNuH5HvSUDgg4zQB2PhzUZNGtDcrLGEd90kZAAx6Z65r0O0vrW/h821njmTuUYHH1rw4ysWz2ByBXdeABcTahLcxqy2/lFZTj5S2RgfXrXnYmguVzvqelha75lC2h39Yl54R0a9mkme2KvJknYxAz646Vt0V50ZSjqmenKEZaSVzgNS+HU0jNJZ3MRJ6KwK/41T0fwBqDaih1FFjt42y2HB347DFel0V0LF1eW1zmeDpOV7EcFvFawrDBGI416KKkoorlOsKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/wCQNP8A9hK+/wDSqWt2gAooooAKqWeladpzyPY6fa2rSnMhghVC598DmrdFAFS30rTrO6lu7XT7WC4n/wBbNHCqvJ/vEDJ/GrdFFAGF4Q/5A0//AGEr7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAcp4p8GLrUi3Nk0cE4GGBGA/wCXeo/DngSDTRLLqbRXUsqbPLC5RBnnk9TwOeMc119Fbe3qcnJfQw+r0+fntqZ+naFpmlOz2dokbt1bqcemTRrGi2et2n2e8UkA5VlOCp9q0KKz55X5r6mvJHl5baHL23w/0e3idWM0kjdJGbBX6YrkvFvhNtDK3Vu7S2shwS3VG969VqC8s7e/tXtbqMSRSDDKa3p4mcZXbujnqYWnKFoqzPDYIXuJ44YhueRgqj1JOK9c8P6BJpZEk7oXWPy0VOQB3OfXim6Z4M0nSr0XcSSPIpynmNkLW/WmJxKqaR2M8NhXT1nuFFFFcR3BXI/ECGwi0f7RJaobl5AscgGCO5zjrwK66uc8b6TPquhbbZS8kD+YEHVhgg4/OtqDSqK7Ma6bpSsjyY8nNFKysjFWBBHUGkr3j54K0dKMzXtubXd56SKVI6g5rOrs/hvYyS6pPelf3MMezJHVj6fgKyrSUIORrRi51FFHpC52jcMHHNY3iPQf7bgj8t1SaEkqW6HNbVFeFGTi7o+glFSXKzxS+06eK6njJUmJypA9qz9jYJxwOteu6n4RsNSuzdGSWCR/v+WRhvzHWsXxP4X0XTtGe4R5IHUBUGd3mt6Eep5r1aeLi7LqeRUwc1eXRHndFTzbZMCOLYVHI7moK7EziasFekfDjUJZrCexcAx25DIwH97ORXm9ek/Du4txYTWypslLb+f4hgD/AD9a5cZ/CZ14L+KtTs6KKK8Y9sKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAMLwh/yBp/+wlff+lUtbtYXhD/AJA0/wD2Er7/ANKpa3aACiiigAooooAKKKKAMLwh/wAgaf8A7CV9/wClUtbtYXhD/kDT/wDYSvv/AEqlrdoAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPKfHOlz22vTXPkkQzYZWVeOg/WuZr3mSNJozHIoZWGCCK8i8Q+Fr3R790jglmtmOYpUQkYPY46GvWwuIUlyS3R4+Lwzi+eOqZJ4V8OHXp5AZPLjQfM23OK9Q0vTLbSLFLO1XCLySerHuTWD4B0m70zSJnvI2ia4k3LE4wVAGMkds/0rqq48VVcpuN9DtwtJQgpNasKKKK5TrCsDxfolxrWlotpgzwSb1QnAcYwR9a36KqEnCSkiZwU4uLPNdG8EX95eB9Rie0gQHnI3Me2BWbqnhO/sr6WEQTzZY+VIkZIk9OnQ165RXUsZUUrnI8FTcbHgjRujlGUqynBBGCDXqfgzQZdOs47y5P72WMbU/ug46+/Arbk0bTJrsXclhA84Od5jGc+v1q7Tr4r2keVKwqGE9lLmbuFFFFcR3BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQBheEP+QNP/ANhK+/8ASqWt2sLwh/yBp/8AsJX3/pVLW7QAUUVS1KPVZI0GlXNnA4Pzm6t2lBHsFdcfrQBZmmitoJJ55FjiiUu7scBVAyST6YrP03xJpOr3Bt7O5dpfL81UkgkiLpnG5d6jcvI5GRyKy9Xi8RR+HtWOoHTtUiNjKBaW1nLE0pK9MmVuMZ4Az6GsDTP9N1aKDT9cbX3Okzw+eyBfsJITaMqAAWIAw2W+Tr1oA7Gw8UaNql6LOzvRJKwYpmN1WUKcMUYgK+O+0mtavPtMvrTU4/B2maf/AMfumOr3kQUhrRUt3jdXH8OWYDB612mpWNxfRotvql1p5U5LWyxEt7HzEYfligDP8If8gaf/ALCV9/6VS1u1y+m6D4k0i1e0tdesJIjPLKHudNZpCZJGc7isqqTlj0UD2q39k8W/9BrSP/BVJ/8AH6AN2isL7J4t/wCg1pH/AIKpP/j9H2Txb/0GtI/8FUn/AMfoA3aK5TSJ/Fuq2clx/aukRbLmeDb/AGZI2fLlaPP+v77c47Zq99k8W/8AQa0j/wAFUn/x+gDdorC+yeLf+g1pH/gqk/8Aj9H2Txb/ANBrSP8AwVSf/H6AN2isL7J4t/6DWkf+CqT/AOP0fZPFv/Qa0j/wVSf/AB+gDdorCNr4tCk/21pHA/6Bcn/x+qWizeLdY0Ow1P8AtXSIftlvHP5f9mSNs3KGxnzxnGaAOqorC+yeLf8AoNaR/wCCqT/4/R9k8W/9BrSP/BVJ/wDH6AN2isL7J4t/6DWkf+CqT/4/R9k8W/8AQa0j/wAFUn/x+gDdorC+yeLf+g1pH/gqk/8Aj9Utam8W6Pod/qf9q6RN9jt5J/L/ALMkXftUtjPnnGcUAdVRWELXxaVB/trSOR/0C5P/AI/R9k8W/wDQa0j/AMFUn/x+gDdorC+yeLf+g1pH/gqk/wDj9H2Txb/0GtI/8FUn/wAfoA3aKwvsni3/AKDWkf8Agqk/+P0fZPFv/Qa0j/wVSf8Ax+gDdorldam8W6Pod/qf9q6RN9jt5J/L/syRd+1S2M+ecZxV0Wvi0qD/AG1pHI/6Bcn/AMfoA3aKwvsni3/oNaR/4KpP/j9H2Txb/wBBrSP/AAVSf/H6AN2isL7J4t/6DWkf+CqT/wCP0fZPFv8A0GtI/wDBVJ/8foA3aKwvsni3/oNaR/4KpP8A4/VHV5/FulWcdx/aukS77mCDb/Zki48yVY8/6/tuzjvigDq6Kwvsni3/AKDWkf8Agqk/+P0fZPFv/Qa0j/wVSf8Ax+gDdorC+yeLf+g1pH/gqk/+P0fZPFv/AEGtI/8ABVJ/8foA3aKwvsni3/oNaR/4KpP/AI/R9k8W/wDQa0j/AMFUn/x+gDdorlNQn8W2N5ptv/aukP8Ab7kwbv7MkGzEUkmf9fz/AKvGOOtXvsni3/oNaR/4KpP/AI/QBu0VhfZPFv8A0GtI/wDBVJ/8fo+yeLf+g1pH/gqk/wDj9AG7RWF9k8W/9BrSP/BVJ/8AH6Psni3/AKDWkf8Agqk/+P0AbtFYX2Txb/0GtI/8FUn/AMfqjqE/i2xvNNt/7V0h/t9yYN39mSDZiKSTP+v5/wBXjHHWgDq6Kwvsni3/AKDWkf8Agqk/+P0fZPFv/Qa0j/wVSf8Ax+gDdorC+yeLf+g1pH/gqk/+P0fZPFv/AEGtI/8ABVJ/8foA3aKwvsni3/oNaR/4KpP/AI/R9k8W/wDQa0j/AMFUn/x+gDdorlJZ/FsWvWul/wBq6QftNtNP5n9mSfL5bRrjHn858zrnt71e+yeLf+g1pH/gqk/+P0AbtFYX2Txb/wBBrSP/AAVSf/H6Psni3/oNaR/4KpP/AI/QBu0VhfZPFv8A0GtI/wDBVJ/8fo+yeLf+g1pH/gqk/wDj9AG7RWF9k8W/9BrSP/BVJ/8AH6oyz+LYtetdL/tXSD9ptpp/M/syT5fLaNcY8/nPmdc9vegDq6Kwvsni3/oNaR/4KpP/AI/R9k8W/wDQa0j/AMFUn/x+gA8If8gaf/sJX3/pVLW7WboGlzaRpf2W4uUuJmnmneSOMxqTJI0hwpJwAWx1NaVABRRRQAUUUUAFFFFABRRRQAVXvr610yykvL2ZYbeIZd26DnA+pJIGPeq2pRa3JIh0q8sIEA+cXVq8pJ9isi4/Wuf8Tx61H4Xuhq09lcxtLBiS0tJIzbDzVJmI8xi2zhgBj7vORQBuafr2j3cN01tOIltB5lws0LQNGDltzK4BAOCc4weadpXiLStakeKwuS8iIHKPE8bFD0YBwCVPqMiuEuI5dUtPE6affP4h8zTov9OCruYqzE242AI3GT8ozl8HPFdDaanZeIPG2n3mjzLcQWdhOtzLGDtUu0WyMn+98jHb1GKAOtooooAKKKztSi1uSRDpV5YQIB84urV5ST7FZFx+tAFy6uYLK1kubqVIYIlLSSOcKoHcmqOn63pd1ZyyWzvDb2iAuZraSBUTB5G9V+XAPI44rnPF1l4il8K3H229tZljuLeU/YLN0dUWVWc4Z33YAzjH8J61m3pl1PSvEVjoV9daxpn9no6s8zT5m3MXjRzy2UAyuTgkdM4oA7XSvEWla1I8Vhcl5EQOUeJ42KHowDgEqfUZFadclaanZeIPG2n3mjzLcQWdhOtzLGDtUu0WyMn+98jHb1GK62gAooooAKjn8kW8huNnk7T5nmY27cc5z2xWdqEPiF7onTb/AE2G3wMJcWckj57/ADLKo/SsvV9P8UXllBbTf2ZqEZn3XMSF7RZIwPlQk+ZkFuT0yBjuaANS38S6Pc6G2txXq/2ehYGZkZMENtIwQDndx057VPpetWGspK1jMzmFtsqSRtG6EjI3IwDDI6ZHNcDZNft4R+03lkkdvZeImuJhDKZTsW6cyEjaOEPPfIXOB0rpNDurfV/GOqarpsizWH2K3tzPHyksqtIxweh2q6gn3xQB1FFFFABRRWVqEPiF7onTb/TYbfAwlxZySPnv8yyqP0oAm1XU7DTbdf7QLFJyYxGkDzF+ORtUEnj2pieIdJfR5NWF6gsoiRJIwK7CDgqVIyGzxjGc9qzNV8RT+FNH+0a9d2M9zPKIrVYIzbIzEcBi7sABySxOAO2euJKlr/wi0WpW+o2+qhNahvtTmsyJIwQ6lsAZ4QbDjrhcmgDstL1qw1lJWsZmcwttlSSNo3QkZG5GAYZHTI5q9XL6HdW+r+MdU1XTZFmsPsVvbmePlJZVaRjg9DtV1BPviuooAKKKKACsvWNc0nSjFFqUvzSZkSNYXlbCkEttUEgA4+Y8CtSuT1DUbPQfHUt/q0y21rc6ZHFBPJwu9JHLpn+8QykDqce1AHT29xDd20dzbyrLDKoeORDkMpGQQalrB8EW81r4QsI54mhYh3EbjBRWdmUEdsKQMdq3qACiiigAqvfX1vptm93dyGOGPG5gpY8kAAAAkkkgcVYqjrGr2eg6TcapqEnl21uu52AyeTgAe5JA/GgCKx1vSdWErwTAtZkNIs8TRPDkHDFXAKgjPOOmabpfiXSNZnMFhdmSQJ5gVonj3pnG9dwG5c91yORXJo6eJ9B8SX1pqFndavqGnGFbOzuFl+zxBX2RkqeWJZsnpk4HA5vWmp2OveJtAfR3EqWFtM1ztUj7OGVVWNvRiR93r8poA7OiiigAooooAKyE8R6FcrfTC9iZNJci5kZSFhbBBwxGDxkcZ7ipPEMWqT6NNDo5jW7kwoZ5DHhSfmwwBw23ODg4ODXnr2+oxNr9u2j29va2c+nSzQWtw0xEcRjYqBsG4bAzE9eMYOc0Aei6Xrmnaz5osZ2d4ceZHJE8TpnoSrgHB7HGDWhXK6Te2uteOLjU9LmW5sotNS3kuI+UaQyFgoPcqM59N1dVQAUUUUAFVNS1Sy0m3E99P5SMwRAFLM7HoqqoJY8HgA9Kt1xvjaFRrvh+9vL2ay0yFrhLm4ikMexmQbMuOUB2kbuOuM80Ab0mu6THpy6vNI0UIPlq8tu6SZJA2hCu/JIHAHOBVjTNVstYtmuLGbzERzG4ZGRkYdVZWAKnkcEd64hLub7Dpmp3c89zpOn645jupgWY25idEkY4yVDvjce2D71u+GJo9Q13X9Vs28ywuZYVhmX7szJGAzL6joue+2gDpqKKKACiiigCjqesWGjpE17MyGZtkSJG0jyHGcKigsePQVXPiHRDpg1k3cZt1YwiTy23hiwBTbjduyB8uM8dKyPGkqQ6pokkt6dLiSSYnUwAfIO0AJ8wKDfk8sCPl9cVhWcgt9N07U5i0+n2evyyzXxQj7QjRuouGHYB3AyPl4yMCgDvtM1Wy1i2a4sZvMRHMbhkZGRh1VlYAqeRwR3q5XM+GJo9Q13X9Vs28ywuZYVhmX7szJGAzL6joue+2umoAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA//Z",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(prob_vectors_tsne[:, 0], prob_vectors_tsne[:, 1], alpha=.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clustering in the 100-dimensional PCA space and cluster interpretation\n",
    "\n",
    "We'll start with k-means.\n",
    "\n",
    "The code to run k-means clustering is fairly straightforward. In fact, running numerous off-the-shelf clustering methods is usually straightforward. Often, the difficulty is in figuring out what data to provide to the clustering method (which means figuring out what preprocessing you're going to do), thinking about to what extent the clustering method makes sense for the data you're giving it, and interpreting what the resulting clusters mean.\n",
    "\n",
    "Also there often could be another question to think about of what the goal of clustering is (what are we going to use the estimated cluster assignments for). At least for this demo, the goal is largely just to cluster as to get a rough sense of what are some key topics are that are being discussed in the 20 Newsgroups dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "num_clusters = 10\n",
    "kmeans = KMeans(n_clusters=num_clusters, n_init=100, random_state=0)\n",
    "kmeans.fit(prob_vectors_pca)\n",
    "kmeans_cluster_assignments = kmeans.predict(prob_vectors_pca)\n",
    "# the above 2 lines can be abbreviated as: kmeans_cluster_assignments = kmeans.fit_predict(prob_vectors_pca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, ..., 1, 1, 1], shape=(8947,), dtype=int32)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans_cluster_assignments"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code cell above does the clustering. Now we move onto interpreting the clusters found."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(201)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(kmeans_cluster_assignments == 2).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster 0 has 474 points\n",
      "Cluster 1 has 7185 points\n",
      "Cluster 2 has 201 points\n",
      "Cluster 3 has 63 points\n",
      "Cluster 4 has 134 points\n",
      "Cluster 5 has 324 points\n",
      "Cluster 6 has 1 points\n",
      "Cluster 7 has 244 points\n",
      "Cluster 8 has 198 points\n",
      "Cluster 9 has 123 points\n"
     ]
    }
   ],
   "source": [
    "for cluster_idx in range(num_clusters):\n",
    "    cluster_size = (kmeans_cluster_assignments == cluster_idx).sum()\n",
    "    print(f'Cluster {cluster_idx} has {cluster_size} points')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x11669a3c0>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter = plt.scatter(prob_vectors_tsne[:, 0], prob_vectors_tsne[:, 1],\n",
    "                      c=kmeans_cluster_assignments, cmap='Spectral', alpha=.5)\n",
    "plt.legend(*scatter.legend_elements())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8947, 11707)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prob_vectors.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.00013, 0.     , 0.     , ..., 0.     , 0.00018, 0.     ],\n",
       "      shape=(11707,))"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prob_vectors[kmeans_cluster_assignments == 0].mean(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_words(prob_vectors[kmeans_cluster_assignments == 0].mean(axis=0),\n",
    "               filtered_vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Cluster 0]\n",
      "appreciate advance hi list email info anybody address reply interested windows book source greatly software code pc wonder graphic response \n",
      "\n",
      "[Cluster 1]\n",
      "car law com government sell sound article yes claim computer gun wrong ago big space answer book stuff maybe available \n",
      "\n",
      "[Cluster 2]\n",
      "file windows format dos directory ftp convert image create anybody hi window advance bmp gif site available zip floppy utility \n",
      "\n",
      "[Cluster 3]\n",
      "soon pitt gordon geb banks surrender skepticism shameful n3jxp intellect dsl chastity cadre lyme blood patient disease migraine usually t560i \n",
      "\n",
      "[Cluster 4]\n",
      "key chip encryption clipper phone public algorithm escrow secret encrypt maybe secure message pgp 80 government serial sell 128 answer \n",
      "\n",
      "[Cluster 5]\n",
      "game team play player win season baseball hockey fan score playoff league nhl tigers espn spring detroit lose tie night \n",
      "\n",
      "[Cluster 6]\n",
      "speculation zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "\n",
      "[Cluster 7]\n",
      "card driver video windows monitor color mouse pc version bus vga slot hi mode anybody graphic window printer mb ftp \n",
      "\n",
      "[Cluster 8]\n",
      "god jesus bible sin love christ faith christian exist christians man son belief hell life atheism word lord existence eternal \n",
      "\n",
      "[Cluster 9]\n",
      "window manager version application display appreciate hi driver dos xterm server app pointer motif icon position windows fine advance default \n",
      "\n"
     ]
    }
   ],
   "source": [
    "for cluster_idx in range(num_clusters):\n",
    "    print(f'[Cluster {cluster_idx}]')\n",
    "    print_top_words(prob_vectors[kmeans_cluster_assignments == cluster_idx].mean(axis=0), filtered_vocab)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for cluster_idx in range(num_clusters):\n",
    "    plt.figure()\n",
    "    plot_word_cloud(prob_vectors[kmeans_cluster_assignments == cluster_idx].mean(axis=0), filtered_vocab)\n",
    "    plt.title(f'Cluster {cluster_idx}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1], dtype=int32)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.predict(np.array([prob_vectors_pca[0]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      " Koberg , \n",
      "\n",
      "\t just a couple of minor correction here ... \n",
      "\n",
      "\t 1 )   the church of Christ do not usually believe in speak in \n",
      " tongue , in fact many of they be know for be strongly oppose to \n",
      " pentecostal teaching .   you be probably think of Church of God in \n",
      " Christ , the large african - american Pentecostal denomination . \n",
      "\n",
      "\t 2 )   I be not sure what you mean by \" signify believer \"   but it \n",
      " should be point out that the assembly of God do not now , nor have it \n",
      " ever , hold that speak in tongue be the sign that one be a Christian . \n",
      " the doctrine that traditional pentecostal ( include the A / g ) maintain be \n",
      " that speak in tongue be the sign of a second experience after become \n",
      " a Christian in which one be \" baptize in the Holy Spirit \"   that may be \n",
      " what you be refer to , but I point this out because pentecostal be \n",
      " frequently label as believe that you have to speak in tongue in order \n",
      " to be a Christian .   such a position be only hold by some group and not the \n",
      " majority of Pentecostals .    many Pentecostals will quote the passage in \n",
      " Mark 16 about \" these sign follow they that believe \" but they generally \n",
      " do not interpret this as mean if you do not pactice the sign you be not \n",
      " \" save \" . \n",
      "\n",
      "\t 3 )   I know it be hard to summarize the belief of a movement that \n",
      " have such diversity , but I think you have make some pretty big \n",
      " generalization here .   do \" Neo - Pentecostals \" only believe in tongue as a \n",
      " sign and tongue as prayer but not tongue as revelatory with a message ? \n",
      " I have never hear of that before .   in fact I would have characterize they \n",
      " as believe the same as pentecostal except less likely to see tongue as \n",
      " a sign of Spirit Baptism .   also , while neo - Pentecostals may not be \n",
      " incline to speak in tongue in the non - pentecostal church they attend , \n",
      " they do have their own meeting and , in many case , a whole church will be \n",
      " charismatic .\n"
     ]
    }
   ],
   "source": [
    "print(docs[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Illustration of computing a score function for different numbers of clusters\n",
    "\n",
    "Let's first fit k-means to various choices for the number of clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_clusters_to_try = [2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 100]\n",
    "candidate_models = []\n",
    "\n",
    "for candidate_num_clusters in num_clusters_to_try:\n",
    "    candidate_model = KMeans(n_clusters=candidate_num_clusters, n_init=10, random_state=0)\n",
    "    candidate_model.fit(prob_vectors_pca)\n",
    "    candidate_models.append(candidate_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Per k-means model in `candidate_models`, we can print out what the different clusters' top words are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Number of clusters 2]\n",
      "Cluster 0: file card window windows driver dos video version anybody hi color advance ftp pc monitor info format appreciate ms graphic \n",
      "Cluster 1: game god car key team law com sell list appreciate book play government chip email article sound yes answer interested \n",
      "\n",
      "[Number of clusters 3]\n",
      "Cluster 0: card window driver windows appreciate advance hi video monitor color dos anybody info version pc software mode graphic email display \n",
      "Cluster 1: god game car key law team com sell list play government sound chip book article answer yes maybe claim ago \n",
      "Cluster 2: file windows format dos directory ftp convert create window image hi anybody gif bmp advance zip site floppy manager copy \n",
      "\n",
      "[Number of clusters 4]\n",
      "Cluster 0: god car key law com government sell list article book yes answer claim sound ago man wrong maybe gun quite \n",
      "Cluster 1: file windows format dos directory ftp convert create window image anybody hi gif bmp advance site zip manager application version \n",
      "Cluster 2: game team play player win season baseball fan score hockey playoff league nhl espn detroit lose series tie night hit \n",
      "Cluster 3: card window driver windows hi appreciate advance monitor video color pc disk anybody info software scsi address dos version mac \n",
      "\n",
      "[Number of clusters 5]\n",
      "Cluster 0: card driver window video windows version monitor color mouse hi mode pc vga bus memory display dos slot ftp software \n",
      "Cluster 1: god car key law com government sell yes list article chip sound claim book answer maybe wrong computer man remember \n",
      "Cluster 2: game team play player win season baseball fan score hockey playoff league nhl espn detroit lose tie night hit watch \n",
      "Cluster 3: appreciate hi advance email info anybody address interested windows greatly list reply software book source wonder pc response mac code \n",
      "Cluster 4: file windows format dos directory ftp window convert create image anybody hi gif bmp advance zip site application floppy manager \n",
      "\n",
      "[Number of clusters 6]\n",
      "Cluster 0: file window windows dos format version manager server ftp advance create directory anybody hi convert image application ms pc appreciate \n",
      "Cluster 1: card driver video windows monitor color window hi mouse pc version bus vga mode slot graphic anybody ftp fast printer \n",
      "Cluster 2: car key appreciate com law sell list chip book government hi email sound article computer answer interested yes advance maybe \n",
      "Cluster 3: action zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 4: god jesus bible sin love christ faith christian exist christians man son belief hell life atheism word lord existence eternal \n",
      "Cluster 5: game team play player win season baseball fan hockey score playoff league nhl espn detroit series lose tie night hit \n",
      "\n",
      "[Number of clusters 7]\n",
      "Cluster 0: god jesus bible sin love christ action faith christian exist christians man son belief hell life atheism word lord existence \n",
      "Cluster 1: car key law government com yes article list book answer gun ago claim maybe wrong bike remember quite space kill \n",
      "Cluster 2: card driver hi windows appreciate advance disk software monitor mac pc video email anybody color address scsi info memory mb \n",
      "Cluster 3: window manager version driver application display appreciate hi card dos xterm server app windows pointer video position advance default option \n",
      "Cluster 4: file windows format dos directory ftp image convert create window anybody hi advance bmp gif site zip available version floppy \n",
      "Cluster 5: lead motto zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 6: game team play player win season baseball score hockey fan playoff league nhl espn detroit lose series tie night hit \n",
      "\n",
      "[Number of clusters 8]\n",
      "Cluster 0: window appreciate hi advance windows software email version disk mac anybody driver pc info memory scsi color monitor address dos \n",
      "Cluster 1: god jesus lead law bible sin love christ faith christian exist christians man son belief hell life atheism word motto \n",
      "Cluster 2: key chip encryption clipper phone public algorithm escrow secret encrypt maybe secure message pgp 80 government serial sell 128 answer \n",
      "Cluster 3: car price dealer sell driver model mile owner small bike convertible engine window light volvo pay door ford oil insurance \n",
      "Cluster 4: card driver video monitor color slot bus pc vga graphic window mb mode hi fast windows anybody software controller cache \n",
      "Cluster 5: law government com book list gun claim article yes wrong ago sound big sell kill man remember answer bike space \n",
      "Cluster 6: file windows format dos directory ftp convert create window image anybody hi gif bmp advance site manager zip floppy utility \n",
      "Cluster 7: game team play player win season baseball fan score hockey playoff league nhl espn spring detroit lose series tie night \n",
      "\n",
      "[Number of clusters 9]\n",
      "Cluster 0: card driver video monitor color window slot bus vga pc graphic mouse mb mode hi anybody fast diamond windows software \n",
      "Cluster 1: law government gun claim man wrong kill yes article bike maybe life space remember word big ago cause agree book \n",
      "Cluster 2: god jesus sin bible love faith exist christ son christian man hell christians atheism belief word existence life lord eternal \n",
      "Cluster 3: window key chip software email sell disk computer sale address mac phone list version offer hi available memory price machine \n",
      "Cluster 4: file windows format convert dos directory ftp window create image anybody gif bmp site hi postscript copy zip utility server \n",
      "Cluster 5: game team play player win season baseball score hockey fan playoff league nhl espn detroit lose tie night hit toronto \n",
      "Cluster 6: windows dos version driver ms window file advance font os pc 386 printer anybody microsoft hi screen software server disk \n",
      "Cluster 7: car price dealer sell driver model mile owner small bike convertible engine window light volvo pay door ford oil insurance \n",
      "Cluster 8: appreciate advance info hi greatly anybody window email wonder pointer reply ftp book code site address list graphic source hello \n",
      "\n",
      "[Number of clusters 10]\n",
      "Cluster 0: card driver video monitor color window slot bus vga pc graphic mouse mb mode hi anybody fast diamond windows software \n",
      "Cluster 1: law government gun claim man wrong kill yes article bike maybe life space remember cause word ago big agree sound \n",
      "Cluster 2: god jesus sin bible love faith exist christ son christian man hell christians atheism belief word existence life lord eternal \n",
      "Cluster 3: window key chip hi email software advance sell disk computer address list mac sale version memory phone offer machine available \n",
      "Cluster 4: file windows format dos convert directory ftp window create image anybody gif bmp site hi postscript copy utility ini zip \n",
      "Cluster 5: game team play player win season baseball score hockey fan playoff league nhl espn detroit lose tie night hit toronto \n",
      "Cluster 6: windows dos font version advance ms driver window file anybody printer pc 386 microsoft os application hi package software screen \n",
      "Cluster 7: car price dealer sell driver model mile owner small bike convertible engine window light volvo pay door ford oil insurance \n",
      "Cluster 8: appreciate info greatly hi window pointer advance anybody wonder code email hint assume list site server reply ftp motif contact \n",
      "Cluster 9: soon pitt gordon geb banks surrender skepticism shameful n3jxp intellect dsl chastity cadre lyme blood patient disease migraine usually t560i \n",
      "\n",
      "[Number of clusters 20]\n",
      "Cluster 0: monitor color version image screen display font video window type apple vga value mode print 16 mac price 17 256 \n",
      "Cluster 1: bike ride motorcycle dod mile honda turn sell road cost fast rider sound class sport helmet advice stupid eat learn \n",
      "Cluster 2: car price dealer sell model small owner mile driver convertible window light engine volvo door ford oil insurance saturn pay \n",
      "Cluster 3: law government gun claim man wrong yes kill life space remember maybe word com big answer agree book cause ago \n",
      "Cluster 4: file windows format convert directory dos create ftp window anybody image bmp hi gif copy zip site available postscript floppy \n",
      "Cluster 5: key chip encryption clipper public escrow algorithm phone secret maybe encrypt message pgp 80 secure serial 128 answer rsa government \n",
      "Cluster 6: window manager application display xterm appreciate app pointer motif icon position hi default server create size screen font reply memory \n",
      "Cluster 7: spring zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 8: address article email phone com advance book list interested response lose copy title news hi incredibly ftp bored chip offer \n",
      "Cluster 9: speculation zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 10: card video slot bus monitor pc graphic vga color mb fast driver controller software cache nubus mode hi pds ati \n",
      "Cluster 11: driver card windows ftp video printer version site window hi anybody diamond mouse late advance info ati available appreciate update \n",
      "Cluster 12: windows dos ms file advance package anybody pc window os font server microsoft 386 nt screen mouse disk hi application \n",
      "Cluster 13: software sell hi advance disk sale computer mac machine memory pc scsi offer available chip price reply code board interested \n",
      "Cluster 14: stuff delete usually window registration omit unit nice glad wow smoking guy dan realistic matter eat confess ambition university professional \n",
      "Cluster 15: appreciate info greatly hi tigers advance anybody assume list hint bring effect email hello contact monitor disk pointer computer project \n",
      "Cluster 16: law zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 17: game team play player win season baseball score hockey fan playoff nhl league espn detroit lose tie night hit toronto \n",
      "Cluster 18: god jesus bible sin love faith christ exist christian christians son man belief hell atheism word life existence lord eternal \n",
      "Cluster 19: pitt gordon geb banks soon surrender skepticism shameful n3jxp intellect dsl chastity cadre lyme blood patient disease migraine usually pressure \n",
      "\n",
      "[Number of clusters 30]\n",
      "Cluster 0: sale offer sell price condition 00 email trade brand shipping interested contact excellent manual pay model box original pair sound \n",
      "Cluster 1: bike ride motorcycle dod mile usually honda turn stuff sell road cost fast sound class helmet advice stupid eat learn \n",
      "Cluster 2: government space gun com big remember maybe ago guy cause sound stuff control cost area week phone hope leave pretty \n",
      "Cluster 3: yes matter knowledge value norton non freedom adobe oh win wheelie type shaft motorcycle morality manager ca blah coast ago \n",
      "Cluster 4: window version manager display dos position pointer server size application app appreciate hi xterm object default advance ms reply icon \n",
      "Cluster 5: game hockey espn detroit toronto wings score playoff team copy pens roster pick baseball schedule home octopus play tv season \n",
      "Cluster 6: spring zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 7: article com news reader generate buggy joke section sound delete newspaper relate print ago sun hp col sq net paper \n",
      "Cluster 8: game win team play season player hit fan score baseball playoff lose series division goal throw league hockey watch night \n",
      "Cluster 9: action zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 10: speculation zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 11: anybody wonder advance hi appreciate windows info interested exactly board font regard source surface wasp format client archie color function \n",
      "Cluster 12: address email lose phone advance corporation reconsider monthly eric uk white house snail postal competitor weitek ticket texas ranger printer \n",
      "Cluster 13: car dealer price driver model small sell owner mile convertible light volvo engine ford month ago fun door fast particularly \n",
      "Cluster 14: law claim kill book man wrong religion word god jesus answer life christian bible agree church statement evidence understand child \n",
      "Cluster 15: driver card windows video printer ftp version window mouse site hi anybody diamond late available info ati appreciate mode update \n",
      "Cluster 16: law zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 17: card video monitor slot vga bus graphic pc color fast mb driver nubus software mode cache pds port ati controller \n",
      "Cluster 18: key chip encryption clipper public escrow phone algorithm secret maybe pgp message 80 encrypt serial answer secure rsa keyboard attack \n",
      "Cluster 19: team player nhl game win fan league play hockey record stat baseball score lose toronto season coach trade compare cubs \n",
      "Cluster 20: file windows format dos directory create ftp convert hi window image gif advance manager floppy site utility available anybody zip \n",
      "Cluster 21: soon pitt gordon geb banks surrender skepticism shameful n3jxp intellect dsl chastity cadre lyme blood patient disease migraine usually t560i \n",
      "Cluster 22: tigers zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 23: god jesus lead faith bible exist love sin christ man hell son christians motto atheism belief christian word life existence \n",
      "Cluster 24: play player game team hockey season puck playoff draft yes pittsburgh traffic ralph baseball answer left league pick cup man \n",
      "Cluster 25: list mailing add com address software interested faq motif stuff wonder appreciate info instruction newsgroup advance chicago nickname fourth edition \n",
      "Cluster 26: memory server display terminal client screen error mb mode window pixmap mit simm chip sun meg appreciate message size cursor \n",
      "Cluster 27: info assume appreciate hi equivalent effect peer fall direction available 93 zx zoom zoo zone zip zionist zionism zinc zimmerman \n",
      "Cluster 28: appreciate windows advance software mac hi computer color version machine monitor pc image code available window reply screen email port \n",
      "Cluster 29: disk scsi controller ide bus mb floppy isa boot pc format device dma card mac transfer interface tape dos cable \n",
      "\n",
      "[Number of clusters 40]\n",
      "Cluster 0: advance hi appreciate software version image color anybody mac available source reply email code interested machine file graphic package application \n",
      "Cluster 1: wonder advance exactly warning comparison jesus hi dream ok appreciate win nyc manager heh box chance feeling mistake local file \n",
      "Cluster 2: team play player win game hockey nhl league season fan baseball score watch stat goal record toronto trade playoff lose \n",
      "Cluster 3: game play playoff team win espn score season hockey baseball fan night detroit hit toronto tv series pens wings tonight \n",
      "Cluster 4: monitor video color vga card apple screen connect soon display lc mac spec switch 17 font 1280x1024 t560i kind box \n",
      "Cluster 5: law government encryption clipper phone chip hope legal federal clinton key gun country citizen public issue court force company protect \n",
      "Cluster 6: pitt gordon geb banks soon surrender skepticism shameful n3jxp intellect dsl chastity cadre lyme blood patient disease migraine usually pressure \n",
      "Cluster 7: driver card printer windows video version anybody window diamond mouse hi color info ftp available load mode appreciate cica panasonic \n",
      "Cluster 8: window manager application display position appreciate pointer app default xterm hi size create reply font icon event dos object screen \n",
      "Cluster 9: book reference hi subject copy phone incredibly bored graphic email guide recommend history advance title appreciate answer vga example publish \n",
      "Cluster 10: god jesus bible christian word man christ sin life faith christians belief love church religion truth claim understand child christianity \n",
      "Cluster 11: speculation zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 12: scsi chip bus board port controller mb motherboard mouse ide memory pc pin simm speed ram card serial mode fast \n",
      "Cluster 13: article com news reader generate buggy joke section sound delete newspaper relate print ago sun hp col sq net paper \n",
      "Cluster 14: disk floppy boot able format switch dos scsi supply controller copy original computer software offer ide box appreciate model 25 \n",
      "Cluster 15: sell sale offer price 00 condition brand email shipping interested trade excellent manual model contact pay box original 50 pair \n",
      "Cluster 16: list mailing add com address interested software motif appreciate instruction advance chicago nickname fourth edition faq email anybody delete 000 \n",
      "Cluster 17: version dos window refer recently satisfied quite plain ghostscript 386 zx zoom zoo zone zip zionist zionism zinc zimmerman zeus \n",
      "Cluster 18: lead motto zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 19: card video slot color pc bus graphic fast driver vga mb nubus software mode cache hi pds ati port controller \n",
      "Cluster 20: ftp site code zip driver advance available win3 pub pc cica source font email appreciate indiana hi ok hello windows \n",
      "Cluster 21: answer 800 maybe key simple twice soundblaster sound share quality pose past nope multiple cheer business 9000 playing geo simply \n",
      "Cluster 22: gun wrong space yes kill com claim cause big remember maybe ago guy week man pretty life leave control feel \n",
      "Cluster 23: law zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 24: windows dos file ms window advance pc font os microsoft 386 anybody package hi mouse screen nt memory application appreciate \n",
      "Cluster 25: action zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 26: file windows format directory dos create convert ftp anybody window bmp image hi postscript yo available advance zip gif application \n",
      "Cluster 27: info appreciate assume bring hi anybody effect offer equivalent contact greatly club campbell monitor interested manufacturer computer car remember modern \n",
      "Cluster 28: god son exist hell atheism receive love jesus definition eternal faith bible existence agree father belief pro trash readable paint \n",
      "Cluster 29: stuff delete usually window registration omit electronic application maybe serve unit nice glad wow smoking guy dan interesting stop doctor \n",
      "Cluster 30: bike ride motorcycle mile turn honda dod sell road cost fast rider sound class sport advice helmet eat learn insurance \n",
      "Cluster 31: tigers zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 32: server memory display client terminal screen pixmap sun size mit window message cursor character mask limit copy ncd neglect gxxor \n",
      "Cluster 33: car dealer driver price model small mile owner sell convertible light volvo engine fun door fast particularly oil road insurance \n",
      "Cluster 34: quite understand remember feeling expand cica ago week unofficial trick simple manufacture formal flood expect designation code agree 1993 sufficient \n",
      "Cluster 35: key chip encryption public escrow clipper algorithm secret phone pgp 80 serial message rsa secure encrypt keyboard attack 128 scheme \n",
      "Cluster 36: sound mac sale price pro tea file driver nice card exe drv technical audio blaster noise oil projector cheap theory \n",
      "Cluster 37: spring zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 38: matter knowledge zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 39: address email lose advance corporation reconsider monthly eric uk white house phone snail postal competitor weitek ticket texas ranger printer \n",
      "\n",
      "[Number of clusters 50]\n",
      "Cluster 0: chip computer mac software machine memory board port apple speed hardware pc modem motherboard mb switch pin upgrade fast video \n",
      "Cluster 1: card video slot bus pc graphic driver vga mb fast nubus software mode cache pds controller ati port hi sound \n",
      "Cluster 2: car dealer driver price model small owner mile sell convertible light volvo engine ford fun door fast particularly oil road \n",
      "Cluster 3: team play player nhl trade game hockey league season win fan captain stat baseball watch toronto score goal record pittsburgh \n",
      "Cluster 4: disk floppy boot format able switch supply controller dos offer original model 25 box scsi sale machine external appreciate access \n",
      "Cluster 5: spring zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 6: windows dos ms file advance pc window mouse package 386 microsoft hi nt screen os memory driver software version anybody \n",
      "Cluster 7: gun control carry firearm likely law crime weapon safety criminal police kill suppose away bullet unless movie shoot safe conceal \n",
      "Cluster 8: government big remember cause maybe sound yes ago pretty leave issue cost hand area control kind turn week feel effect \n",
      "Cluster 9: speculation zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 10: book hi email phone incredibly bored advance copy reference graphic subject guide recommend list title motorcycle offer vga appreciate learn \n",
      "Cluster 11: key chip encryption clipper public escrow algorithm phone secret maybe encrypt pgp message 80 secure serial answer rsa keyboard attack \n",
      "Cluster 12: scsi controller ide bus isa mb device dma pc mac transfer interface motherboard seagate 16 vlb floppy card ram performance \n",
      "Cluster 13: pitt gordon geb banks soon surrender skepticism shameful n3jxp intellect dsl chastity cadre blood patient lyme migraine usually disease pressure \n",
      "Cluster 14: god jesus bible exist faith christians son hell love atheism man sin word existence christ belief eternal christian life lord \n",
      "Cluster 15: tigers zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 16: advance source hi code server application mouse window display font widget motif type available mode screen sun package client graphic \n",
      "Cluster 17: game hockey espn detroit baseball toronto copy wings score playoff team fan play pens roster pick schedule home season octopus \n",
      "Cluster 18: file windows create directory dos download hi format convert ini utility add window print cview exe win bmp nt zip \n",
      "Cluster 19: bike ride motorcycle mile honda turn dod sell road cost fast rider sound class sport helmet advice eat learn insurance \n",
      "Cluster 20: game win play team season fan hit score player playoff baseball series throw lose tie watch night hockey goal league \n",
      "Cluster 21: article news reader generate buggy joke section sound delete newspaper ca print ago net paper month subject file notice clinton \n",
      "Cluster 22: version guess driver text late dos sell resolution model vms useful rom pgp peter patch os unix hi winbench window \n",
      "Cluster 23: action zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 24: window manager display position pointer appreciate size application app hi event xterm object default reply create icon child server option \n",
      "Cluster 25: address email lose advance corporation reconsider monthly eric uk white house phone snail postal competitor weitek ticket texas ranger moscow \n",
      "Cluster 26: appreciate info greatly assume hi effect bring hint contact pointer computer hello site reply anybody public offer equivalent bitmap icon \n",
      "Cluster 27: dos server ms irq w4wg sorry neglect message terminal fancy character cell device 386 available simply share os port microsoft \n",
      "Cluster 28: driver card video ftp window site windows diamond anybody mouse hi late info ati appreciate available speaker mode sound load \n",
      "Cluster 29: kill cruel jews die net sleep war chop death neutral messenger israel israeli wording israelis soldier koresh maybe shoot missile \n",
      "Cluster 30: file format convert ftp dos windows window image gif available directory create site graphic copy version pcx zip disk access \n",
      "Cluster 31: law zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 32: matter knowledge zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 33: sell sale price offer 00 condition email interested shipping manual excellent model contact pay box brand pair 50 sound list \n",
      "Cluster 34: com hp netcom reply sun article tek email feustel away bob blow vice ico stay bobbe paul jmd handheld sea \n",
      "Cluster 35: guy hold maybe david faq team hey gal hell technology feel temporary orbit player joke jason throw curious total begin \n",
      "Cluster 36: answer message test 800 phone quite interesting pose suck roger kindly simple advance faq email mac obviously comp past 30 \n",
      "Cluster 37: lead motto zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 38: law god man claim jesus wrong word religion christian bible life church christ christians belief live evidence understand truth faith \n",
      "Cluster 39: stuff delete usually application posting holiday andi warrant electronic wrong maybe serve clock unit nice glad comment wow waffle smoking \n",
      "Cluster 40: wonder exactly warning advance comparison jesus dream ok win nyc manager heh box chance feeling mistake local chip yes hi \n",
      "Cluster 41: space nasa area sci launch station orbit gov shuttle moon cost city news available option ago fund beacon office larc \n",
      "Cluster 42: list mailing add interested address software motif appreciate instruction advance chicago nickname fourth edition faq com newsgroup count 000 option \n",
      "Cluster 43: printer driver print windows laser panasonic version pc anybody page 200 printing bj screen font pin network deskjet non advance \n",
      "Cluster 44: hope week ago quite goal cica clinton check remember modem simply horn couple lose target stop simple president marriage manufacture \n",
      "Cluster 45: value objective agree morality brand freedom science subjective yes word totally amen example exist patch assistance absolute application claim quite \n",
      "Cluster 46: color card screen 256 monitor display 16 image picture vram mono anybody price cell foreground xterm mode 24bit liver hope \n",
      "Cluster 47: cheer statement kent meaningless define wrongly spite spell robert movement hello cheap advantage understand recommend owner manual rule objective morality \n",
      "Cluster 48: monitor vga card video color connect apple soon lc mac screen spec switch 17 display t560i kind box nanao font \n",
      "Cluster 49: anybody advance info interested hi wasp format client archie tobacco surface compile scanner monitor manufacturer function source algorithm board windows \n",
      "\n",
      "[Number of clusters 100]\n",
      "Cluster 0: appreciate greatly bring hint contact offer hello reply 94 xlib shading public label example domain correct colormap bitmap allocate pointer \n",
      "Cluster 1: law zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 2: space nasa sci launch shuttle orbit station gov cost news address option moon beacon larc cain egalon cause area navigation \n",
      "Cluster 3: software hardware package copy apple pc hi windows pirate level tape price unix backup advance duo computer large instal sale \n",
      "Cluster 4: hi appreciate type anybody info reply animation surface fix gif display sun source recently interested ticket picture replace package hint \n",
      "Cluster 5: jesus god christian bible church christians religion christ life word belief faith live christianity love understand man sin child exist \n",
      "Cluster 6: guy net chop bmw involve david somebody curious company hell technology temporary orbit hit admit feel jason hold throw money \n",
      "Cluster 7: email offer interested title address book response sell 16 contact appreciate xlib com price intel copy receive player cheap cheer \n",
      "Cluster 8: file windows download ini utility sound print exe dos convert info add hi application window drv create edit yo forward \n",
      "Cluster 9: gun control carry firearm likely crime weapon safety criminal law police issue bullet kill politics away movie shoot defense unless \n",
      "Cluster 10: action zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 11: game win play team season fan hit score baseball player playoff lose abc watch away pitching throw night league pitch \n",
      "Cluster 12: version guess text patch late driver rom luck windows resolution model early paper vms useful pgp peter os unix hi \n",
      "Cluster 13: port printer pc board bus motherboard controller serial pin print ide scsi mb disk mode jumper cable stand video connector \n",
      "Cluster 14: car engine price model dealer driver mile speed pay light oil window condition sell ford fast rear month owner automobile \n",
      "Cluster 15: list mailing add interested appreciate address advance chicago nickname fourth edition faq software newsgroup instruction count option white sox person \n",
      "Cluster 16: answer 800 simple twice soundblaster sound share quality pose past nope multiple cheer business 9000 playing geo simply sandberg quite \n",
      "Cluster 17: lead motto zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 18: speculation zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 19: pitt gordon geb banks soon surrender skepticism shameful n3jxp intellect dsl chastity cadre blood patient lyme migraine usually disease pressure \n",
      "Cluster 20: window pointer display server appreciate manager hi application ms implement create open feature multiple option font code xwd icon draw \n",
      "Cluster 21: bike ride mile motorcycle dod honda turn sell road cost fast sound advice helmet eat insurance big class max sport \n",
      "Cluster 22: card video slot vga graphic cache nubus color lc able price sell bus hi pds fast fpu mode height novell \n",
      "Cluster 23: watch jump video 1993 weekend ump theist sunrise quote pitcher cool camera league hockey disagree common agree suck stone sore \n",
      "Cluster 24: sale offer 00 condition price shipping sell interested pay contact excellent 50 box original 250 pair trade list brand card \n",
      "Cluster 25: tigers zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 26: ftp site driver zip available win3 pub pc advance indiana cica hello windows archie hi package map project ok ca \n",
      "Cluster 27: team player game nhl baseball win expansion record toronto lose fan cubs pitching yankees happy rbi thought 50 mlb research \n",
      "Cluster 28: objective cheer value statement kent morality define meaningless science agree exist subjective absolute claim religion accept wrongly spite spell robert \n",
      "Cluster 29: sound sale price pro tea card nice technical audio projector cheap theory mac specific objection life oil game hardware oscillator \n",
      "Cluster 30: spring zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal zaphod \n",
      "Cluster 31: key maybe answer ring practical ornament 128 60 large des statistic sort result reliable nsa lifetime gee figure feed equal \n",
      "Cluster 32: team player play trade season game hockey win fan nhl league stat goal captain score playoff coach lose baseball compare \n",
      "Cluster 33: car particularly driver dream spell fit dad alignment small 000 info fun radar mile fast dealer danny recently model oscillator \n",
      "Cluster 34: god son receive eternal atheism hell definition bible exist pro trash readable paint allah impossible agree faith jesus prepared damnation \n",
      "Cluster 35: wonder exactly comparison jesus ok warning nyc heh totally sue sane posting pittsburgh offensive ibm float financial difficulty cup confirm \n",
      "Cluster 36: driver card printer windows video window anybody diamond version hi ftp info available color appreciate cica panasonic speedstar mode mouse \n",
      "Cluster 37: font type truetype windows adobe tt anybody file value ps search convert xterm atm char print pixel monitor lcd kind \n",
      "Cluster 38: chip clipper key intel pin datum algorithm phone encryption simm standard serial code nsa cpu build upgrade motorola slot design \n",
      "Cluster 39: article reader news generate buggy sound print section joke subject software relate paper classroom ago sue server seriously picture optimally \n",
      "Cluster 40: man gay john woman homosexual white pocket sox umanitoba service lost eng arch anonymous mom straight hand appear verse record \n",
      "Cluster 41: anybody advance interested format client archie cd tobacco file compile pc scanner surface board technology thread function wonder experience page \n",
      "Cluster 42: usually stuff zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 43: phone address company chip hook cellular hold australia encryption weitek room university answer machine traffic single seriously ring flow washington \n",
      "Cluster 44: info assume zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 45: address email lose corporation reconsider monthly eric uk white house advance snail postal competitor ticket texas ranger printer moscow indicate \n",
      "Cluster 46: mouse driver keyboard bus ball adb windows port com sys apple com1 simple screw dos com3 serial microsoft button modem \n",
      "Cluster 47: word processor preliminary negotiation load carefully leave release job convict child bobby request hey easter meaning toshiba supposedly spread savior \n",
      "Cluster 48: claim religion evidence away pretty argument posting news survivor close truth wow wrong israel uranus tonight certainly quote model benefit \n",
      "Cluster 49: mac se modem apple internal portable fax software advance available 30 grayscale boot powerbook sound mb original plus upgrade cable \n",
      "Cluster 50: agree totally amen uh service armed vote vladimir trick quite outta flood expect alan memorable kinda hurricane home eclipse clemens \n",
      "Cluster 51: yes norton non freedom wheelie shaft motorcycle morality coast speed recovery perry low formation decrease dangerous blood value protest procedure \n",
      "Cluster 52: play game puck player hockey traffic ralph playoff draft pick team tv cup pittsburgh season man everybody yes channel white \n",
      "Cluster 53: window application motif widget manager display value file windows icon button event mode create client user gl xterm dos xt \n",
      "Cluster 54: disk floppy boot able switch format model 386 controller 25 machine appreciate manual computer scsi check hi dd datum offer \n",
      "Cluster 55: message test suck kindly interesting zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen \n",
      "Cluster 56: windows dos file ms os pc advance microsoft nt package window product screen hi version reader anybody unix application directory \n",
      "Cluster 57: matter knowledge zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand zeal \n",
      "Cluster 58: server display terminal client screen sun pixmap cursor gxxor memory mit ncd value ms dos size multi available x11r5 numlock \n",
      "Cluster 59: key chip public encryption escrow pgp secret clipper algorithm rsa keyboard secure 80 message attack phone security session file encrypt \n",
      "Cluster 60: reply subject hp regard pick informative model slave configure law brother 48 250 message yeah phillies phillie mets return interlaced \n",
      "Cluster 61: article issue news class newspaper response practice reply ago education reaction month alt delete email drug add mention zionism paper \n",
      "Cluster 62: book reference hi copy subject guide motorcycle answer offer publish learn recommend example regard list fix code contain history rule \n",
      "Cluster 63: available cost speed build price turn computer low design datum current interested sell company check 50 fast model big switch \n",
      "Cluster 64: info appreciate greatly effect scope equivalent accept datum hope model computer friend available cost modern sir pc address card list \n",
      "Cluster 65: image format package convert screen file copyright level export graphic datum display pixel available gif animation newspaper bitmap permission quality \n",
      "Cluster 66: kill cruel jews death neutral israel israeli wording israelis die suppose messenger koresh sleep soldier shoot missile human brad handgun \n",
      "Cluster 67: code source mode graphic ftp algorithm motif simple method processor datum class kind obtain hello xtpointer widget interested appreciate radiosity \n",
      "Cluster 68: government encryption clipper issue key law chip public care protect phone federal trust service agency technology citizen nsa force libertarian \n",
      "Cluster 69: com netcom tek article hp bob away vice ico sun list blow bobbe sea stay sink queens manhattan bronx beauchaine \n",
      "Cluster 70: machine speed ram fine board fast 486 simm black centris slow faq video add cpu quadra memory hot windows driver \n",
      "Cluster 71: god jesus sin bible love christ faith life belief exist man christian existence christians hell lord human truth atheism atheist \n",
      "Cluster 72: file format directory windows create ftp convert dos bmp floppy copy zip manager gif graphic window library available advance person \n",
      "Cluster 73: scsi controller ide bus device isa pc interface mac seagate tape performance card fast ship manager doc bug dos chip \n",
      "Cluster 74: game boy irq espn assume wife slot sit season schedule rid refer previous offer moto list drinking classic child trouble \n",
      "Cluster 75: color screen 256 monitor display image 16 picture mono vram cell card foreground rgb xterm anybody liver hope bright mb \n",
      "Cluster 76: wrong oh posting distribution rain cal comment signal news yes motto andi guess okay jokerit green ed digital deal announce \n",
      "Cluster 77: computer friend control phone leave forsale output mad explain europe diff couple broken com cable newsgroup graphics loser tough total \n",
      "Cluster 78: law legal live moral behavior pass force rule illegal god enforce court note evidence away islamic warn sabbath verb ah \n",
      "Cluster 79: monitor vga card video connect soon lc mac screen spec switch t560i info anybody box 17 color 1280x1024 dan viewsonic \n",
      "Cluster 80: advance hi source subject kind application appreciate binary recommend book email form wonder thanx graphic usa map draw date current \n",
      "Cluster 81: remember quite ago proof inch feeling al campbell apostle testify understand stack koresh expand cica certain witness jesus evidence prozac \n",
      "Cluster 82: stuff delete application holiday warrant electronic serve clock unit nice glad stealth diamond wow waffle smoking sam response reference redirect \n",
      "Cluster 83: sorry minor cubs cost server neglect message machine fine c650 area sunset sunrise library virtual update public location directory technology \n",
      "Cluster 84: win mydisplay manager icon spread prediction pennant bet event volvo pool land jim freeway cup underdog intel future series yes \n",
      "Cluster 85: game hockey detroit baseball espn score toronto team copy playoff fan wings pens roster pick watch octopus tv home play \n",
      "Cluster 86: cause feel effect israel leave person issue area guess live war law kind mention report evidence hand big life stop \n",
      "Cluster 87: maybe french jewish guy sound club night somebody certainly able western russians resource language count faq stuff figure technology layer \n",
      "Cluster 88: version dos window refer recently satisfied quite plain ghostscript 386 zx zoom zoo zone zip zionist zionism zinc zimmerman zeus \n",
      "Cluster 89: hope goal clinton simply horn week target stop president marriage graduate grade civilian agree topic sport rec suppose nolan news \n",
      "Cluster 90: window manager position size app stuff registration omit reply default object decoration xterm micro hello emulator root outside visible display \n",
      "Cluster 91: sell price condition model encryption cover sale company 70 manual excellent available version guide dollar simm tape cheap rid plastic \n",
      "Cluster 92: phone incredibly bored book zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile \n",
      "Cluster 93: interested response mind mark impression general experience 486dx2 zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr \n",
      "Cluster 94: wasp anybody advance zx zoom zoo zone zip zionist zionism zinc zimmerman zeus zero zephyr zeos zenith zen zeile zealand \n",
      "Cluster 95: memory mb simm mode ram meg windows server error vram fast correct board 16 main video advance virtual window excuse \n",
      "Cluster 96: hardware dan cost dealer board workstation sigma plan pc licensing level figure double compression bob trouble sell necessarily incentive factory \n",
      "Cluster 97: brand patch assistance objective morality goal pleasing logical head fourth zx zoom zoo zone zip zionist zionism zinc zimmerman zeus \n",
      "Cluster 98: week ago month couple past fan likewise check hope trade kind west mike tear half challenge intrepid sixth harvey fifth \n",
      "Cluster 99: card bus video slot mb graphic driver monitor pc fast vga controller port mode board color speed ati nubus computer \n",
      "\n"
     ]
    }
   ],
   "source": [
    "for candidate_num_clusters, candidate_model in zip(num_clusters_to_try, candidate_models):\n",
    "    print(f'[Number of clusters {candidate_num_clusters}]')\n",
    "    for cluster_idx in range(candidate_num_clusters):\n",
    "        print(f'Cluster {cluster_idx}:', end=' ')\n",
    "        cluster_assignments = candidate_model.predict(prob_vectors_pca)\n",
    "        print_top_words(prob_vectors[cluster_assignments == cluster_idx].mean(axis=0), filtered_vocab)\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we make a plot of RSS vs the number of clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rss_score(X, cluster_assignments):\n",
    "    rss = 0.0\n",
    "    num_clusters = int(cluster_assignments.max() + 1)\n",
    "    for cluster_idx in range(num_clusters):\n",
    "        cluster_mask = (cluster_assignments == cluster_idx)\n",
    "        if np.sum(cluster_mask) > 0:\n",
    "            points_in_current_cluster = X[cluster_mask]\n",
    "            cluster_mean = points_in_current_cluster.mean(axis=0)\n",
    "            rss += ((points_in_current_cluster - cluster_mean) ** 2).sum()\n",
    "    return rss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'RSS')"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rss_scores = []\n",
    "for candidate_model in candidate_models:\n",
    "    cluster_assignments = candidate_model.predict(prob_vectors_pca)\n",
    "    rss_scores.append(rss_score(prob_vectors_pca, cluster_assignments))\n",
    "\n",
    "plt.plot(num_clusters_to_try, rss_scores)\n",
    "plt.xlabel('Number of clusters')\n",
    "plt.ylabel('RSS')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that for k-means, looking for an \"elbow\" in the RSS vs number of clusters plot is a popular way to select the number of clusters. However, when clustering on real text data, it could be the case that it's simply not obvious where the \"knee\" of the plot is."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In lecture, we talked about CH index. Historically, when CH index was defined, higher CH indices were considered better. However, when clustering on text data, here we find that CH index does *not* have the desired behavior where higher is better (since the highest value achieved is for the minimum number of clusters...). **Note that CH index was developed so that you're *not* supposed to look for the knee in the CH index vs number of clusters plot to find the number of clusters to use; instead you're just supposed to pick whichever number of clusters yields the highest CH index.**\n",
    "\n",
    "One reason for why CH index might work poorly here: CH index is designed to work with clusters with shapes that basically look like sphere/balls. This condition unlikely holds in many text datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'CH index')"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/jpeg": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import calinski_harabasz_score\n",
    "\n",
    "ch_indices = []\n",
    "for candidate_model in candidate_models:\n",
    "    cluster_assignments = candidate_model.predict(prob_vectors_pca)\n",
    "    ch_indices.append(calinski_harabasz_score(prob_vectors_pca, cluster_assignments))\n",
    "\n",
    "plt.plot(num_clusters_to_try, ch_indices)\n",
    "plt.xlabel('Number of clusters')\n",
    "plt.ylabel('CH index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's another score function: silhouette score. Silhouette scores are between -1 and 1 where higher is considered better (in particular, silhouette score was developed where you're not supposed to look for a knee in a plot). However, on this dataset, the highest silhouette score achieved is for the smallest number of clusters. Silhouette score is meant for clusters that are spherical and well-separated. For this text dataset, it's quite likely the case that these assumptions don't hold..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Silhouette score')"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "\n",
    "silhouette_scores = []\n",
    "for candidate_model in candidate_models:\n",
    "    cluster_assignments = candidate_model.predict(prob_vectors_pca)\n",
    "    silhouette_scores.append(silhouette_score(prob_vectors_pca, cluster_assignments))\n",
    "\n",
    "plt.plot(num_clusters_to_try, silhouette_scores)\n",
    "plt.xlabel('Number of clusters')\n",
    "plt.ylabel('Silhouette score')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Clustering using HDBSCAN (here, we still cluster in 100-dim PCA space but visualize in 2D t-SNE space)\n",
    "\n",
    "Here we illustrate using HDBSCAN on the 100-dimensional PCA representation of the data. Note that the clustering result that we're showing here is *not* good. You can play with HDBSCAN parameters a bit to see for yourself that HDBSCAN really struggles with finding \"good\" clusters at least in terms of grouping together different clumps of the 2D t-SNE plot into distinct clusters. Later on (at the end of this demo) when we run HDBSCAN directly on the 2D t-SNE representation of the data, we get much more reasonable clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "from hdbscan import HDBSCAN\n",
    "\n",
    "min_cluster_size = 5\n",
    "min_samples = 2\n",
    "hdbscan = HDBSCAN(min_cluster_size=min_cluster_size, min_samples=min_samples)\n",
    "hdbscan_cluster_assignments = hdbscan.fit_predict(prob_vectors_pca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_dbscan(data_2d, cluster_assignments):\n",
    "    \"\"\"\n",
    "    Makes a scatter plot where x coordinates are in data_2d[:, 0], y coordinates are in data_2d[:, 1],\n",
    "    and points are colored based on what cluster they are in\n",
    "    (points declared as noise are labeled as \"noise\" in the legend and show up as gray points)\n",
    "    \"\"\"\n",
    "    assert len(data_2d.shape) == 2\n",
    "    assert data_2d.shape[1] == 2\n",
    "\n",
    "    for cluster_idx in range(int(cluster_assignments.max()) + 1):\n",
    "        cluster_mask = (cluster_assignments == cluster_idx)\n",
    "        plt.scatter(data_2d[:, 0][cluster_mask],\n",
    "                    data_2d[:, 1][cluster_mask],\n",
    "                    label=cluster_idx)\n",
    "    noise_mask = (cluster_assignments == -1)\n",
    "    frac_noise = noise_mask.mean()\n",
    "    if frac_noise > 0:\n",
    "        plt.scatter(data_2d[:, 0][noise_mask],\n",
    "                    data_2d[:, 1][noise_mask],\n",
    "                    color='gray', label='noise', alpha=.25)\n",
    "    plt.legend()\n",
    "    plt.axis('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
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4zuiVMP8AUnj9Afwr0MkAZJwB3NdEXdHDUVpWFrJ8QaDY67aKt4XQw5ZJUPK+v1HA/KtKOeKXPlyK+P7pzTyAQQRkHqKbVyE2ndHhbyRK7rAGEe7hn+8R2zTTIW4HJ9a7HXvh+9pDcXunTNLGnzLb7MsBnkA98D+VcrpenXOqX6WdtGWdzgnHCjuT7Vz2a0PQThJcyGowUEk10nhZ9O1DUI7C5WSKRl+RlbhyOcH04pzfDzVzKVilg8vs8jFT+QzWp4X8D3em6qmoahLF+5z5aRknJIxknHvWi5k7HPL2bTdzs7e3jtYVhiXCrTpZY4InllcJHGpZmPQAdTT6wPHBceFLvZIEztzk43DcMgVo3ZXMIq7SOW8TeNINUi+yWCSLGcq8kgA3D2H+NcpvC9ar96UAtxmufnbO72UVsXVcYyDxSscjjoahRDGnNPRtzgDp3rVM5nHW6ArgDHSvUPBdkLLw7F8pV5naR8+p4H6AV57phRdUtjIodDKoIxngnFevxosSBEGFUYAqkjOUnaw6iiiqICiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAMLwh/yBp/8AsJX3/pVLW7WF4Q/5A0//AGEr7/0qlrdoAKKKKACiiigAooooAwvCP/IEuP8AsJX3/pVLWxbf8esX+6Kx/CP/ACBLj/sJX3/pVLWxbf8AHrF/uigBt7dpY2M13ICUhQuQOpwOlcHD8RL/AO3Bp7aE2xblFB3Aexz1rvrm3ju7aW3mXdHKpRh6g1x8Pw5hS+Dy3xktg2fL2YZh6E5rmrKq2uQ5MQq7a9mdmrB1DKchhkGnUgAAAAwB0FLXSdZS1WyivbPZPeXFpDG3mO9vOYSQAcgsOQO/BHSsvwdJcTWV5KZ7mfT3uidOkumLSNDtXkk8lS24qTzjHtV3xDoMXiLTRYT3l1bReYsjG3KfvMfwsGVgVzgkEc4FT6bYTWELRzaldX+TkNciMFR6Dy0UY+ooAu0UUUAFRXP/AB6y/wC6alqK5/49Zf8AdNAEi/dH0paRfuj6UtABRRRQAUUUUAFUtZuhZaRdXBONkZII9au1ynjvXhptimnrEkj3ikMX6IvTP19PpSbsrlRi5OyOEuLh7ydpnAGegHQCr+leIJ9Eil8lQ7lTs3dAff271kowxk1HJIM8dalvQ0UW3Y6DRvHOrRarEb+6E1tI4WQMqjaCeowOMVa+IujGC+j1WGNvLnG2YjorjgH2yP5Vxwj4yf0r1Xwbq41fRBBMuZLYCJ887xjg/lWcbyVmbTag1KJ5NVxNI1GW1juorKaSGQkK8aFgSDjt0rrtY+Hl5Nqks2nywC3mcttclTHnqOByK7LQ9KTRNIhsVff5YJZ+m4k5JpKm29Sp10knE5zwyP8AhEvC8t3q4aHzptyxY+c8AAY9Tg8Vk654wn1iMW9sj20Gctz8z+xx2pvjPxDFrEq2VuhWO2kJ8wn756dK5mOQpwwrRO2hg1zLm6m7oN5Lb6nGN7FWznnnpXp9u5kt43bqygmvJtEuIYtVhkuJVhjB++wJAr1qDy/Ij8pgybRtIOcirRi00SUxFjBZkCgseSo61jeKdSFhYKNxBduVU4JFcxo/iVrfUo98YWFztYLTEeh0x5Y4xl5FX6nFUr7VI4dHur2A7zDEXA/DivLp765vJTNPMzuxz1oHbqevJIkq7o3DD1BzXH/EGe2u9MW1hvoPtFvKHeAygMRgjp689KxLDxFNZ6beQLMUneBhESTyeOh7MBnHviuUQ5Jz1NZzl0N6NP7XYbtOcYp6Hy2G4cU7IAwetJwR2NZWsdTldakzSALnP/16igyZOO/qcUqoCMkU/YTjbVavUy92KaOy8L+HJPt1vd3qAANvjQMD2yCcfhXoFeR2er39lHGkNwyiMYGDXoega3/aVjE0wKyn5SccMa2Rxvc2aKKQ8DNMQtFZkmpyKGlCL5ajOD1Irm9T8ZSxThFQFcZ2KcHnpk0AdvRXBWvj25iGJrUOuePm5x9a6/SNXttZsxc2xIAO1lbqp9KB2L1FFFAgooooAKKKKACiiigAooooAKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/5A0//YSvv/SqWt2gAooooAKKKxI/Fmlyarf2GZVGnwGea4ZR5W1ThsHOSVIIPGMgjqDQBt0Vi6X4ottTvIrVrK9spLiEz232uMKJ4xjJXBPTcvBweelbVAGF4R/5Alx/2Er7/wBKpa2Lb/j1i/3RWP4R/wCQJcf9hK+/9Kpa2Lb/AI9Yv90UAS00SIXKB1LjkrnkVU1mS5h0W9kswTcJA5jx1zjt714ja3V5HqEdxbyyfat4KsCSxbP65rGpV5GlY9LBYB4qMpc1rHvdFNjLGNS4AcgbgOxp1bHmkN3dQ2NrJczlhFGMsVQufwABJ/Cquma5p2rvLHZzOZYcGSKWF4pFB6Eq4BwcHBxjirF9e22n2cl1dzrbwJjdK3RcnAJ/EiuV8KzJceK9Rmg1Ntcha0iH9pFVAQhm/cgoAh6luBkZ5zxQB2VFFFABUVz/AMesv+6alqG7YLaSljj5TQBKv3R9KWsODxbpU0vlrIwA43EY/TrWykscihkdWU8gg0AEzmOF3UZKqSBWSJ5lIlErM3Xk8H2xVyPWNMnujax31u83TyxICSfT3qrNqWgWd6Ypr22jmXJKNJ90/wAgfaldDs+xrDkUtcbN8SLFZytvZTSxg/fJCk/QV0mk6tbazYrd2pO0nayt1U+hoTT2G4yW5erC8T+GIvEUEX77yJ4c7H25BB7Efh+FbtFDV9GKMnF3R4prGlz6HqL2NwQ5UBldeAwI6j9R+FUQ2XBr1/X/AAvY+IAjzl4p4xhZY8Zx6EHqK881zwfqOhW7XUzxSwBwodCc89CRjisJRa9Dup1IyVnuZAKgY9a9d8N6JBommiOJzK0uHeRlwTxxx2ryfS5Yk1K3e5hE0CSKZE9VzzXq1r4q0q64E5jfptYc1pDXUwraaGwSACScAdSa86174gPdw3Nlp0Bijf5BcF8MRnkgY4yP510vjC8m/wCEUupbF852q7L1VSQD/h9Ca8kpVJNaIqhTUlzMsJICM4OaeFB5PJNVQSDkVYEmOlRGV9zScLbEioZfljXJAyR6D1r0HQPFOjWOiR2098TLbx5YFD83svrXn1hZ3Gp3n2a2CmQqzBSwG7A6DPU+1Mnt5raUw3ETxOOqOpU/kapS7Eumnozd1zxCmu3pkhjeOIYChz83H06VnIxR1YdQQaoxgDBHGKsiQdzVxd1qYzgk9D07RWg1C2zhWieLy3Ru+eoIry6882wvri0kQq0MjJjPTBrvfClwlzaLJGcOknz9goAH6YpuqS+D/Et8LeS52XZOxbiNSu4+m4jB/H8DRLyYU2k2pLQ89Zy7A/lXqcng/SrvTmJsoobuWDb5gBG1sddvTOayrnR/DXgyOK7u0mvLhmJhViDkjvjgYHHXNbegeK7DX/MSJXhmiXc0cmPu+oI6jpUpK9mXNu14bHBReBNekvPs72yxpnmZpBsx68cn8qy9Q0bUdJmkS6tZUCHHmbTsb0IPSvStY8YW+mSCGOBppCM8nAxXO6j42bUbG5srmxCxTxkK0b/Mp6jOevOPSk6aQ415N6o40Fx7+1TQsGwTTY1RpFDOFBPJIPFSeWIyQrK4HRlBwfzpR3Lm00T5rqfC8zB1EZ3QJ80nsc/zrji7EgE4Naej3EsN0RFIyZAJweDj1/OtUzlcbI9cHIzWTrPiSy0VP34d3Y7VRB1NaNpK01pFK67WdASPwrzTxxe2s+qJFbzrKYS28rnAJPSiTsghHmdhs3iq+mlkEYSOFiQExkgfWsp38yQuepql9owcgVIspbGKlTTNZUmizniu88A2rxWFxO2QsrjH4CuQ0HSzq2oJE7FYdwDsP5V6rbW0VnbpBAu2NBgCrRi9NCaiiimSFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAYXhD/kDT/wDYSvv/AEqlrdrC8If8gaf/ALCV9/6VS1u0AFFFFAFXUoLm5025gsrn7LcyRssU+3d5bEcNjvivP7nwp4he8vdLR7I276A9qjw2kkaMSX2ruaRvm3EEk5yCeO9elUUAclaT3Ou+ItGuV0y9so9Ngla5N1AYgJHVVEa5+/8AxHIyOBzzXQalpVvqsaJcSXSBDkfZruWA/iY2BP41dooA57wXCtv4dkhQuVjv71QXcuxAuZRyxySfc8mty2/49Yv90Vj+Ef8AkCXH/YSvv/SqWti2/wCPWL/dFAEtUo9G0yG8N5Hp9ulwTnzFjAbPr9atySJFG0kjBUQFmY9ABXPQ+N9LlvBBtmRGOBKyjb+POQKpU3PVK9i4uavynR0UUVJAUVDd3cFhaS3d1KIoIULu7dABWJ4a1zUtWv8AVINQtI7UWrxGGNQd6o6bgH5xuxjOMY6c9aAOhooooAKpaoCbZiOgBzV2obsA2koP9w0AeOuAWI96cNRvYYWhS5dUYYIz2+tWtWsms7jeAPLlJK47HuKypRkYGTUSNYK7GpvRxIhKlTlWBwQe2KQxGQliTuY5JPOakUYAxTt2M8YqOVGvtGtiNYnRSCAdvJ2sDxV3SddvtFvUltpGEecyQk/K49x6+9UXI3ZBwaap2nPcUtjTfVnrt14jtdPsjd3qtGmBtC8liew96r6H4y07XLo2kaywTkEqsoHzgdcEHrXm+oaxdahZRwXDl/LfIY9+KteDLJ7zxJAVk8tYA0rtnB2gY/qPwzVOb5rIzVFcjb3Ot1Tx+lpfvb2lkLiONtrO0m3cR1xwfzrStdY0XxdZS2G8kyJ+8gcbWHuPXB9K8vmki8+QpJvXccNjqM9ak0S8ltNetbiA7X80L+DcH9DQ5hGlddmjU1rSLDRr5rezu2nIPzBiCU9jis5uRzUcqTW9zLHcKwmViJA3XOeajabnGKpNJGbjJs6PT783OnzWctxKWdCjLuzleneuUuIhBcyxBt4RyobGM4PWrEd3LBIs0T7HTkHGcVWlkaaVpWOWY5J96ym0zooxcbjKXJxjNJRWZ0Etssr3USQEiZnAjwcHdnjn61oa/BeW/iC7F8G85pGYMRwwzwR7YqjZkrdxSAkbHDZHUYNekDXLHxVZT6Y6C3nmjKxM/IDdv1rSMbowq1OWSR5yG3Lg8UowR64qS+0670u8e1u49kydecgjsQabHbyyDcqHB6cVSuRKy6l7T9YuLG1urOM/uruMoQBzkjHH8qz1BOAvOemO9aEUEOm3MF5eXEUnl/vY4YySWI5APHAyOe9ZyzyzXbTl9srvvJQbcEnsB0/ClfWw0ly3R13jO0kurHTZ5JgblIyrxk8kdiP1o8B6FK11cX0jqqrEY0UNySe5HpWDLczTuHlcswGM1u+E9QazuZy06xqyjIboSK05Ve5z+0ko8vQzdZEjXrzSDndsP1FZUjDBFavizUo7jXJY4I1SMbWJH8TFQSf1rIjDzdsk0c19ENQaSbIYoprhilvDJK4GSEUsQPXiteLw9qr2gla2kRjjbG64Zh6811ngK1FmLhCieZIAzMOw7DNT+JfE1jpeoCAK81wqjzFXACjqOfXn9alRtqy5VOZ2ijkrPwte3hcyYhZTgBuf68V2Ph7wlY2dus9wTczknluFGD0A/wAazbrxNplrpaahCJJprlyohB27SuM7jzjqOnXNaPhnxha6uslvLALSSFN+N+VZfUH156VScb2Iam43a0OmdS0bIp2kjAI7V4jqel3mk3bW97C0bAnDEcOPUHuK9jh1ewnYqlwoI7Nx/Os/xH4ct/EtrFifypYiTHKBuGD1BH4CiceZBRqcj12PIlQt9KkVdmDk12CeCEjQpLdOZwfuquB/Wrdn4St4FdZsOxOCHXdioVM1lXTMrwuZ0aZ43KJGQ2ccE/5xXpdrKZ7WKUjBdQSKyrDQ7L7NGVjKqOqKcK3vWu7LDEWxhUHQVqtDlbu7j6K5i88YwWcxjwsrA4KL/D+NWNP8X6feN5cpML+/Kn8aYjfopAQRkHINLQAUUUUAFFFFABRRRQAUUUUAFFFFAGF4Q/5A0/8A2Er7/wBKpa3awvCH/IGn/wCwlff+lUtbtABRRRQAUUUUAFFFFAGF4R/5Alx/2Er7/wBKpa2Lb/j1i/3RWP4R/wCQJcf9hK+/9Kpa2Lb/AI9Yv90UAR6ha/btPuLXdt86MoG9MivPofBusPeCCSARx5+aXeCuPUdzXpVFbU60qaaRcZuOw1FCIqDooxzTqKKxIKWq6Va61YmzvBIYi6v+6laNgykMpDKQRggGsnQPCv8AYmv6pqAurmWK7EaxLNeSzHAUBiwckE5HB5IHHHSujooAKKKKACorn/j1l/3TUtRXP/HrL/umgDkPH1tDbaXFPFBh5ZgGYE46E9PU4rgt2fT617Td2dtf2bW13EssLDlW/wA8V5f4ktNPtLiO306IIBlnO8s3sDnp+HrUST3NoONrMxAVBPPWl3hU6g5prdORzUYGGwDxjNZ3sbqKYkhyaaCQcinsARnvUdZvc3jaxIBuGWNLHNNay74JXjbGNyMQcfhTA+BgjNAbLgnpTCzHNEwRW4ORnA6j61Y0mGWfV7SKFdztMuB+NNUjOc/StKPVZVUPFBBBL0LxJtLfX/61UoamMqrS2M+6juYLqWK5V1mVjvD9c1WIZZWUqQwOCCOa7fSPFlvBayrqnzTKMQSCPcy59+3auRjVQxwQeevrVOOu5Malk20QSJIigtGyg9CR1q9pmq21nZ3Frd6dHexzMrDc5QoRnkEc96Rbo2oJ8uOVeuyRdyn8Kh1K6t724FxDbLbMygPFGMICBjK+mfT9aiSszSnLnWqN5bbw9c6PcXVtbFbhUO2BpiSp9fce9c35W0k4yKbFKYzwSPpT2kGMg07poVpRYsbrG2T0PFbWhQNdagpiydnPy9Se1YXUDPNW9K1m90O8+0WUgBPDIwyrj0IpqViZU+fbc9E1G0synmarEjOnO9x/Kubt2huLw2tiUcOx8tSduM9uayrrxJqurM6XlyWjY/cCgKPpUETvHKkkRw6sCpHrWqlfVHPKHK7MraoAmp3EYbdscqT7jg49s0yDCgH1q/4lFq2rNPao8YnHmSI/8LknOPbv+NZSuV6Vhe0tTsS5qasaAcYqzZ3UduzM6luOgrJjdsk5/CpGyUyRjJ61qpnO6NnY072TTLy1MojlS9D4CgjZsx3/AB+lQ2kioQjKNpPNU4CG4zt9zVwQ+WwyytxkFTTjrqRPRcrOx0S8j0HTLq/mBaMKPlHUtnCgfnXF6jdnV9Wmulj8triTIj3ZwT2zxWtZSG/t5dKuLjZHNjy3bna4PH4dvxqtPoFzo1y0t75TrbupKo+Q5zwM4pSTbHScUvM1/wDhALp9BV5Z44LxXL7Hb5ApA4JHfjOelZX9knR7C4nN7DJcuBHtgfOxSeTn14FW5/GGo36+TdpD5JYNtjUr+HXpWVPKZpGfn5jmhRW4OpNaMihdoGDxthxzkV6Z4Vkmm04yyA7Sflz39a8zRo450aQEoGBYDqRXqOiata3Wi/ao22wQnbyMFcY4I9eatdjKV9zXPrjmsKVfPczuxDn0OB9MVet9Zt7icRbJIyxwpccGm6jNYWH76dCWPO1e/v6UyS3HPHHbxtIyxblHBOKj1JmOmzGNhyh+Ydh615xrWuS6nqEkyO6RdI1zjArU8Oatdlfs8kxkiYlSjc8Y7UAcqVZJGWQEODyDU9qZBcp5almJwF9c9q7q+8Jm8JKyRx55zt60mkeEo7K9WedkYxnIAOealp9CrrqdBYwvb2MEMhy6RgE++KsUhIAyTgDuaakscufLdWx6GqJH0UUUAFFFFABRRRQAUUUUAFFFFAGF4Q/5A0//AGEr7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUUUAFFR3HnfZ5PswQz7D5YkJC7scZxzjNYVnq2q2viFNJ1Z7GfzbR7oS2kbx+SFZRh1ZmyDu4OR908UAdDRXIaf4n1eWPSdUvILNdL1iZY4Y4w3nQBwTEzMThs4AIAGN3euuJA6kCgDD8I/wDIEuP+wlff+lUtbFt/x6xf7orG8I/8gS4/7CV9/wClUtbNt/x6xf7ooAi1O8/s7TLm82b/ACImcL6kCvMYPHeux3wuJbhZY93zQlAFI9BxkfWvVZYkmieKVQ6OpVlPQg9RXMQfD3R4b4XBaeSNW3LC7Ar9DxkiokpPY2pSgk+ZHUI4kjVxnDAEZp1FFWYmX4l0l9d8O3ulxyJE1zHsDuuQOR1HesnwxDHo2u3uiNpml2sxt47oTabb+SsqbmXDrkkEEHHJyD2ror6yt9RtHtLpWaKTG4JIyHggjDKQRyB0NV9M0PTtHaV7KBlknx5sskryyPjpl3JYgdhmgDQooooAKiuf+PWX/dNS1WvphHbSAjJKmgCf+Dk44ryvxDot/Z6pKxt5XidspIqkg+3FWNa8X6lfSKLci1iQY2Lhix9SSKxE1/V7e48+LUbhZDnPzkj8ulZylY3p029SW+06606yg+12pie4ZnXeuGCjAx7d+PpWeUwd9dBaeJI9Vs57LxFL5iqhe3nCfOr+nA5z71iytGHPlElOxap0Zq+aLtYhY5UYFRMhBOPyo3Nu4yQKXcBz+lQ2mapOOxHRRRUGo5Dg1MspQ9c5qvRTTsTKCluWXff1/wD1UyKT5lVmIGeSPSo9zEYzSYI7YqnLW5KppKxdv44hcyJbvviQ4Vv72O9Ual8wEcn8KjJyc0pNMKaaVmKq569KGXAyKFbbQzZ47UtLFa3AMQMA0gBY0lOVgODQN6bEq/LgjpVgOoGCapswIwKejluK0UraGE6d1ctXF5FcIkckJZ048wNgkenSlfSpf7OW+R4njY4Cq3zj6iqvlKx+9tPqelacd3GLCO3hQgjl3b+I/SmlzPUmUuSK5TOSIL1BzV+ecWmki0aNHa5Im3EcoOgx78fkabGivIAy5GckZxmpfFDWz3lubaJogsCq6E5AIJ7/AExTkuVaEwlzz1M6LGSOKmXjkGqcbNuGDVqMnHSiDuFWNmWmm+zxZK4Y+tWZfEj6lazx3yoJGAIKA/MR/XpWbdSSXKqpACr37029sPssEE8chljlXk7cbW9Ovpjn6+lEpO+gU4Qas9xQ4J/lTxkD0qpbnL85JqyzbUJNOMrq5M4crsJI3FW9K1e7s7C4tImHlzurn1BHp+n5Vnu38OOKfAQgwOnelf3imrQaNm01W6W5jZrhgAwPPNWvFutTXV3bISY42gDHb0c7iD+HFYgcKQc8V12v2tjH4HtnmSKS4Kg27FsMAxBOPXg9KuW2hjBLm1OQDqcYNWrSY288cqkhlINUdPfZdxgxh1LAEMM1e1JI0uysO3YB/CeM0Rd0E42dj0z+1YZNIM8dxEZPKyPmH3sVyt1qaW0XnQSkz9RIDzn3rm7G6e0l3A8elPluSZHZcYeqIZpvrM6sspvJXJOWBYkH8K1F8To2z7KDHM3y7mAxXHkk05DhgeeD2oEegaRq941/Hb3EvnJLkAkAFTjPbtXS1zPhUWFwDOjSNdRrhhJ/CD3FdNQAUUUUAFFFFABRRRQAUUUUAYXhD/kDT/8AYSvv/SqWt2sLwh/yBp/+wlff+lUtbtABRRRQBFdG4FpMbQRG58tvJEpIQvj5dxHOM4ziud8M6TrVjJO2sWthLNdgtdXsV48kkrdlCmJQqAZAAPHuSTXT0UAchp/hjV4o9J0u8ns20vR5lkhkjLedOEBEaspGFxkEkE529q6PUdI0zV40j1PT7W9SM5RbiFZAp9RkcVcooA57wXDFbeHpYII0iiiv71EjRcKqi5lAAA6ACty2/wCPWL/dFY/hH/kCXH/YSvv/AEqlrYtv+PWL/dFAEtV1v7R5/IS5iaXpsDjNF+sr2E6QE+aYyFx64rz+GGdrlYokfzt2AAOQa0hBST1OvD4dVU23ax6RRSLkKNxyccmlrM5Cnqmp22k2ZubneQWWNI413PI7HCqo7kmjTr6W/hZ5dOu7FlbHl3ITcfcbGYY/GsTx3pUmp6ZYMtvNcxWeoRXFxBBnfJEAysAByeGzgdQCKPCNqYLzVZLSynsdJleP7JbzRtFhgp8xljblFJ28YHIJxzQB09FFFABVLUoi9uzDspq7UV1/x6y/7poA8aud0Ujo6lWUkEHtVCT71em+IPA8esX3262u/s0rgCRSm5WwMZ68HFUbb4aW6RyNe6k7H+ExKFC+5znP6VjJSZ105wir3OAihlnfZDG8jYJ2opJwBk/pVgWM62zTTBoV48sOCN5z29sZ59q9E0j/AIRHw6s0ltqEMs8anfK0gZyPRccflXH+JNbtta1D7RbiVEHQSgA9vQ+1Typbs0dSTei0MUAgY70x+tWoLG5v1me2j3i3Tc+DyRnsO/8A9aqdSzSPcUAk4FPCdzyKWOKUxtMInMQO0uFOAfTNIW28DvQrA272QjKAMimU7l6CpFJlLsx8IGcn8KlkTKGq4Yin+ZuHJ6VSatYylF81wEXHzHmmMu1iKk84dxUbNuYmk7dC4819RtFFFSWFFFFAC0oDIc0J94VKUIXORzVJESlZ2GGUsMAc1NCdo96g8t15x0qaNQRuwaqN7mdRR5dCyJShDDr1qpdzNPOzt1JyatBUIbJ24GQDzn2qg/3z9aqo9CKCV7jo8HirCNngHmqqfeFS5JHAAxUxZdSN2W0AI9alVVmXynJwensarxN8oyMVIt19mmSUIrlGB2sOD9a2urHJyvmsjTh02z0pBNez/vGHyRbTnnv+VZ2pSaezRtZlt7Z8xTwB6Yq7r2oLrd5DehTEDAqGMHIUjOfw5rKeJV+baOP1qXe2hpFq+r1IDlgaaGaP3FXRZST2Ul9EUEavhosncvTpnqOfXP8AOqyW81xKkEMZd3OFA7ms3fc6E1sT2UMuoXSW0C7pHPAJ/WtPxRaT2c1pDJIXjjt1SM9uOv68/iKjtJJdD3oiILo8M+ASvsP/AK1Z93JPcSmSeV5WPdzk1dny6mKac9NiS2cKp4ySOD6U8nPWq0TAHAqbdk4AJJ9qtPQxnH3gNKKSaOWCTy5UKMQCAR2NOjVpPujpz9KBNBTlODmkII60qqSRgE0yTt/BMKytNdbwCqhNgPP1NdfXI+CLKeAzzSqyBlAAPGa66mIKKKKACiiigAooooAKKKKAMLwh/wAgaf8A7CV9/wClUtbtYXhD/kDT/wDYSvv/AEqlrdoAKKKKACiiigAooooAwvCP/IEuP+wlff8ApVLWxbf8esX+6Kx/CP8AyBLj/sJX3/pVLWxbf8esX+6KAJaTaoYttGT3xzSMwRSzHAAyaprqQ3jdEQh755H4UAXqKSloAKKzPEWsf2BoVxqf2ZrnyNn7pW2ltzBeD+NZNz4xuNOnns9R0cxXuyJrWGG4EguPMk8tV3YG0hsZ6gDnJoA6miuS1LxRNBperw6ppjW13Y26TmG3vWxLG7EBklVVYcqQeB096uN4mnk8Sz6NaWVs5tWjWUzXoilYMobdHHtO5QD1yOQR2oA6Gorn/j1l/wB01yGo/EmwsL27QiyNtYzmGcvqCJcEg4YpCRlgDnqQTg4B79ddMotpMkcqaAI7+5a0sWmUAsAAuemTxXBeJPEVzNZy6fHdGTzeJcAAADtxXTeLriePSFihOFl4Zh6V5uw4IYc0nsVF2dyhsHQ5zTCMHFTzkKwOOtQVzSVtD0YNtXCtTTfDWqasiSWcCyRscF/MXCf73ORWVXSeCtTi0nULm5upxHb+QQyZ5kbIwAO56/SlFJvUc21G6LOv3BitbfR4nJhtUCs3ZyB1/PJrm54SBkc1rXl9BqmoN5CNGHb5A/f8qr3lrNaqDKmA3QjkV0NJo4YylGRlqduQeKGOeBzQ/JA70seFfDjqCPSsPI7fMYVI60lTsF24qCk1YcZXCipNg7nmmEYOKLDTTEooopDCilAJ6DNBBBwRigBVODzUokUY5qCimnYmUUy3uXGcg0IwHHYVBFknGeBUmwD5hwRWid9TBwS0JCxk4U4qMwlct1pUkwfmNOklUDA6mno1dkrmi7IjaIkA96ahJOxjjmrMRDjJp4gSR8sAMd6OXqg9rbRiiNliD7SEJwG7Zq5o+iNrkki/a4rcR4OXPJ+gqCR/3IhRiUBz+NRxrs5BOTWljBStqaWo6O9hP5EZ8wJ3z1HrWTOSpKHg9CK3NGulBlF1MqQxpuDvzt5xgfn0rFuxG15I8b70ZyVJGOtEtAhvdhCWRcKxAPYGtLSSGugvCHqHUciqMdtcM22OF3HYqpI/Ouh0y0bSIm1J4S7QRmTaw4OB0/8Ar0IUtWZuvwPaaliYr5kiB2APIJHeseaQYz+VNu7q6vLqW8nJaSZizH3P9Ku6FY2epS3KaheR2qCH93I7Y/eZGOO4xnNZud9DpVJR1bM2LJ6evNWo3kikWVGwyHINPvtNl0u5EMskUoKhleF9ysp7g/hQgGOOlOKJqyV7o3tOsP8AhMRIskwtr22UDIXKyJ9OxH9aSDS5NPeSOGVZCGKszLjOKoaZqVzpU5mtH2Mww3HBFdbp8EOtxSXjO1u+N0qp0b3Hp0q0jCUr6LYxIdBnuIlcQsQ5OGQE9+lbdn4VjsoFmvJVjC8s2eR7Vel1iPQ7AZjXyo1+WMHk/j9a5O48aaheTAXEUPkBtwjUEfrTuSk2d/p1xZOGjtpCW6kMCCavV5cviq5SZZoIVjZCdvzZ/OrbeLtQuVX955Lj7zKev0FFwaaPRqK5/wAM65LqQkt7lg0sYBVsY3D/ABroKYgooooAKKKKACiiigDC8If8gaf/ALCV9/6VS1u1heEP+QNP/wBhK+/9Kpa3aACiiigAoopCQqknoBmgBaK4fT9a1v7DoniC5vxLbavcxxvY+SgWFJciMqwG4sPlzkkHJ4FdXqWq2+lRo9xHdOHOB9mtJZz+IjUkfjQBn+Ef+QJcf9hK+/8ASqWti2/49Yv90VieCpVuPD0kyBwsuoXrAOhRgDcynlSAQfY8itiNbiJBGFjYKMA7iM/pQBNIgkjZG6MMGs8adKW2u67O5HUirm65/wCeUf8A32f8KN1z/wA8o/8Avs/4UASjgYpah3XP/PKP/vs/4Ubrn/nlH/32f8KAKmvaT/bmjzad5/keayHzNm7G11bpkf3cVn634TXWdUOofbWt5Vt40hKRgmKRJfMV+Tg8jBXHIzzW3uuf+eUf/fZ/wo3XP/PKP/vs/wCFAHO3Pg+41Gz1T+0dVWa+1GBLfz47bYkMaEsAqbierMSS3f2qbWvDN1rl2v2jULcWazRyogsgZ49pBwku75ckddueTW5uuf8AnlH/AN9n/Cjdc/8APKP/AL7P+FAGEPDl7Z3t02matDb213O1xJDNZiVkdjltjbhgE5OCG5JrVu+IZc9dpqOW8kikZJIQD/vdfpxU4FxPb7WjRA47nJA+lAENjaCbSY4byPcCDhW6gZ4/SsTWfC1mHQ28Sor5ByT1+tamp+KdI0iXyLm53Sjqkaliv1x0+nWprXXdG1MrFb31vK0gysZbDH8DzSuiuWVr2PLde0yPS7tIPtImcruIC42j35rNwW+UAkngAeteheMPB0upTrf2DwxsqbZI3O0HHcHp/wDqri9U0o6ZbQE3cNw8pO/yW3CPGMDP4n24rGSd3oddOUWkr6lSxspL67SFchc5d8cIvcn6VI9oiTP5bFkDEKT3HatLw1HqF5b6lZWu9omg3uo6ZDDH4kZqqUdWKshDDsRThFNXFWqSUrIrY2kY45qYXNxtkjMzukgw6sxIbvzUU+QCD61e0XSbvVUnmjiYxQLkuBwT6fXHNPrYjXl5imIFXOwEDtk5NRSQ+/NaP2O483y/KO734p7afHbkPf3McEeeByzOfYAVTirERnJsyliZlOcfXvUTxFGwOanjlDYXqfQd6syxNDIY3XDAVHKmjX2kovUzyxHUc0gXdyTUs6jdgY96YFZV5U49QKhrU2Ula6GFGpKk3BvbFMY5bIqWkXFt7k0GNnuabPjI9aiDEdDQTnrT5tLEqHvcwlFFFSaCqxU5FOMjPx0+lMpVODmmmJpbk0MZZ8tzxU7wiRSoHIGagVwB8p5pz3LYKjv14rVNJHNJTcrodbjk9sVcmzFGqADJ5Y96ow71YNu59MVaHPJqo7GVX4rickUoJpSOM00EOQB1JxVmW5IzI8AUIdwOWyetM2j0qWONYslmDN6A03HPSgGzo9DkS1s7d/MQSbjkt/CM1vzDzbKdbVlkM6MnqGyMVw0V9JBH5eAR7iui8KarBHM6zIRgcMBkLmmI4/YQSGHI4IqNoQF4H5Vs67DEmpSPEhTectzkE+v41mnpU2LUmnoUW3BxnOAMc1ZhZm4VSx9AK1vDWnSXOu27MoWJWyxk4De3PXPTFWfEd6qX6w2yLGyDLsFAyfT6CpirGk582liiLLZbie4lWJCcepz6YrrfDup6ZHaNb2xMjEYk835SfoK4me6lu9gmbcUyA1ETtE4eNipHcVZi0dB443RiyETFo5gzAkdCOMfrXKZz8vT3rppZ5dQ0tY7iHzvIHXuM8/nXP4GKTWpcZKw1BgDA4qQcU5YJWGUjJ+lSfZJwcGMgjrTRDdySy1G5sJxNBIVYH869O0TUP7T0qK6IwzZDfUVwOneF7/UPnChYw2GOefyr0HSbBdNsVt14x2pkl2iiigAooooAKKKKAMLwh/yBp/8AsJX3/pVLW7WF4Q/5A0//AGEr7/0qlrdoAKKKKACiiigDmLLwfLavY20mqGbStOn8+0tPICspGdgaTPzKueBgdBknFdPRRQBheEP+QNP/ANhK+/8ASqWt2sLwh/yBp/8AsJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAJgHtVXU7xbDTp7ljjYvy+57frVuqmp2C6lYSWrNtLYKt6EcigDx1oy7M7MWcnJJ6k1DsaKRZEJVlOQVOMH1rsLjwLqmZHiaA+i7zz9OKis/A2ov899iKIHlUO5zWbibxqNdTXk1K617wcs4XMqPidUH3gO9Y+m2g1DUYIUhWVdw8wMuVC9810Kq+kRw29mhgQqQGYckfj3q/o95K9w1vLtbK7gwUA/jitDFvXQ4C68SXkF7INIdLC0WQ+VHDGq7gOhbjkn3rqbORfEHhxL9oFM8UhFwqjAYjvj6EGqereA5ptSkms5kWGVyxUj7meuKv2MsWn6N/ZsMJaLawaXOGYnq2P8APAqIppmk5Ra0ON1P7DNeOYonVM/MAcAn+lN/4SXV7OJLezujbQRDCRIowB+XP4066sLiBpHaMmNSTvHIxWVMd7kdqUy6Tu7PY9C0rW5ta8I3dxcQxyXVqSCQg+bjIbHY/wCFcNIXnYtKSxPr2rV8OTtY6LqMqXEYknKIsIcFsAnLEenOKzWyCc8U46x1Iqe7N2KkkeEIycZpIpHEezceD09KsSY29M1QOQ5A55qJe69Den78WmTt1XNTAgjPaq4GTknimnjJX8qOawOHNoJKBkketR1ZMO4YJ59qgZSpwazknubQknoNoooqTQKKKKAClCk9KOtSxjJCnimlcmTshicEjvTiNxC981O6KRgqPrVdBjB6mratoZqXNqW1ACjHpSLOA5DdB1xULTYGORkUkWHPP5VfN0Rj7PRuReu/3JVAQwdA4IPYjNQJgkZNLtJAGOlS29ss8uDJsIxjjOarUz0SsFaElmY9GF7M2CzBI19cgnP6VM8OlWUKtMZHkHZeSf6Vc1LVNN1zSPs8CtbTQOGUSdTxjt2qjNK+pzoORVmxllim3Qtg4wfcelUpCbdtknX17VsaaEtdDutYkjV3iYJArHhmJAyR6CldFcjexpeK7OO3htJEzmWPcQe2Mf41yskrxASIcMpyD6Val1e/1RVa9uDNtztBAAX6AVA4VlIIye1F7rQEuWVmVtQupb3UJZp2yzOehyAM9B7VL50k75ldmOAMt6DpURh55OPSpRG0RAcdRkH1FZxTT1N5yi1ZEgHepYlDNgnHvUY5HFWLaBpJFyp2kgZrU5WdNa2ofw4/krl0YF2HO8H1+lczqEUUEuIznOTXo+i2aQKUjXMezDE9GNYPjjTdOtLNLgymKZmPlxgZ3ev0HT/Joew4q7Mrwrcx3uppp97nDgmJlwDuAzg+2M12r+G7AkGMPEw6lTnP515jpVyLO+iu9pbYSRg4wa9I8P8AiBdTXyZcCUdDnO6hbDna+hr2trFaQiKIEKOck5JPqamqlqErpsRGKhs5I/lTLCWTzjEWLLtzyc4pkGhRRRQAUUUUAFFFFAGF4Q/5A0//AGEr7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUUUAFFFFABRRRQBheEP+QNP/2Er7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUUUAFFFFABRRUcs0UCb5pEjT+87ACgCSis+/13S9NgE11eRorfdAO5m+gHJrAl+JGkJKVjt7qVB/GFUZP0JpOSW5cYSlsjr6KxdB8UWHiAuluHjmjG5opAM49RjqK2qE77EtNOzCiiimIrXllDexhZcgqcqynBFYeq39r4a02We1kE95IQibjnB9SB2FX/EuonTdHkmUZdiFUV5hcXE95KZZ5Wdj69B9B2pMaNnR/GOrjVYlvLn7RbzSBJEZFGATjIwOMV1raFciQpHJH5WeGOcgfSvMJVBHoa9K8N6u8fhi1kv2d5clFzyzgHj9O9THR2NJ2auZfj2zW30u3+zDb5bASkdSMYBP41wADE8nIr0vxJJBq2jXBQMsiBdyN1+9wa4DaAMYxilKN2VCpyxsV4XWG4jkcHarAsF6kdx+VeiReDNPv7VLqK7lZJkDxsABweea85lUs4UdK6Ox8ZXum2sECW6FYVC8ucED2pRdmy6keZJrcTxX4dbQxDJHOpjmO0IWy4I6np0/xrERESIYxk9eKu+IPEsviGSF5rdITCCBsYnOcVkmZgMK1LmV7lKnLlSHS4D4Xqe1K0LFeKhDYYN1wc1cDgjIpRtK5U7wtYhWcY5HNRyNn3JNS+TkEqODUDqVbGKUr21Khy30G0UuD6GggjrWZsJRRS4OM4oAcnf1p+QBgnBqGlCk9KpMlx6lkMSuCcmo3O0Y60xWYECplg8wZP51V3LYysoO7K/3m5q5BmB1kTAccg4Bx+dS2mlie3uJ5JcLAm7aBy1VTKY8KRnjg00uXVim+fSBYBZpCXfJJyT61KDtORVWGdDJ84IB6+1Wn2BNyPu9j1rSLTRzTi07MWYmRA5I4461HDkv8ucg8VBv3Sbcc/Wp4WMLhwASDnmhO7Bx5VZl62i+1z/vFDBRn5hkV0moyQP4TkWRVj/dABVXoc8cfWublu4orON7fPnzE+YSOEA6AU62u3voJLO8fAcDZJjkHPfHUVTJSa1MyJPLXGSaVpAOCcV0UfgvUz8zGIxHpJE27I9ccVZsfBVqLg/2leOUBztRNufqeeKVnbQq6bvJmFb6FqV1Ak6WxWBhu8+RgqAepJNaOq3Oh2em29pEp1GdF+aSN9iofY4yfpWt49uYrXTNP022O2N23bV6bVGAP1/SuLVQeaXkO6STZ0GijSryExvC8UnQjOcntzXQf2G1m0QJjBIyWC81xmmXDWkz7Qv7wYye1d9bazb6hp7SS4LxDI2HnPT+tUjJ7mlY3EjSGFzuG3KnFcd8Qo5Jru2kC5iiDIfYnB/z9K6DTtQMVyqyxjEpC788j0qzrWkf2igePiQcEeooauEXZ3PLEG1cVYs7iS1ukmiOGU5+tdBJ4Puy7Bl2f3cDOfyq7pngp1nSS6OADkjg0wbudRZgXmnRNMu4MMjPX2qxDBFACI1xnqepNORQiBFGAowBTqBBRRRQAUUUUAFFFFAGF4Q/5A0//AGEr7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUVS1LVrXSY0kuhclZDhfItZZz+IjViPxoAu0VjQa1Ya8JbC1k1GCR4yfMNlPblR6h3QDPP1rHsJ5NP1bVn027vL3TLGybzTdXDTL9qU52ozEnhc7gDgEjvmgDsaK4bTje6cvhfU21S8u5NYdY7yOaYvG5eF5NyIeE2soxtxwec11mpX1xYxo1vpd1qBY4K2zRAr7nzHUflmgDP8If8gaf/ALCV9/6VS1u1z/gmRpfD7yPE8LPqF6xjcgshNzLwcEjI9iRXQUAFFFFABRRRQBn65qq6NpM18ybymAqZxuYnArybUL+81a5a4vLhpHPQE/Kg9AOwr17VNOh1bTpbK4yEkHUdVI5BFcHN8PtUjnKwzQSxdnLFTj6Y6/jUSTZrTkkvM5Bk4+agoFA4zmu0h+HF3IuZr5I8nkeXnj863bfwHokUSLNHJM69WMhG78BUcjNvapdTnfh7pF2dVOplHjtUjZVYjAkJ4wPUDn8RXo9RwwxW8KQwxrHGg2qqjAAqStIqysc85ubuFFFFUQU9T06LVLJ7aXIB6EdjXn954TvICRDIshBxtwQ3/wBevTKTAznFA7nB6X4ImfEl6U9cHOB/jWvq32LT4IUW4QGEYYHgYOPwHSrviDUo7FYxIwCkEkZxn0rznVb37bJ8pITcWx2yaWw1q9S7qPiqS2umjs44ZE2bXLjcGB57Gs+HWLKS4Ju9OUI4wTG5yvqcHNZUi7myvSmoE81RKWCZG7aMnHfFYOcrnbGlBx2Ok1Pwy2mwNdJOZYSMglMcEgDnPPUdKxmjGzmuj1PxfYavpX9miyktQgUQuXDAYxwfbH1rMtdLuLiUIybEH3mPYVqrPY55c0X7xjtFzxxTvs+Fyea9Dm8L2ttoL3NlAfOeINIHJYkcE49K4mRAjYNL2aG676GY6FT0OK09D0G81x5Vs2iBhwWEjEZBz049qbDaTXkvlQRl3Pp2HvSkPbM0UUjoMgnaxG4+tRyamjre7YdNby20jRSxsjIcHI6VQdlLnB78Vry6zPc6Tc2N2FnkIUxTuP3i4YZBPfjPWsQxMOtOb7BSilq2WIogy5PemzQkDjmnWjqQUd9uBwSCc+3FSzKQivuUq2QCD6e1GjiK8ozKSJluR0qVl4zR0xt5pX5PUVKVkW5NsrVIpG3GaawIOcU2o2N90P4ZxV9VdVXcjLkAjIxWerMjBkYqw6EHBFbFvqD3iKtyxdlGN7HJI960pvU566skyp9peJzsJGQVPuDwRVZl8w5xWxcWTT2MjQxj92wdjjnHIxn8f0qmEAGDVuLb1MozUVdFKNCM7gRRIxAABOKsuuBxVWXJb2rOSsjaEud3HxgK+fSrIcdKrxIxBOMkelTIvQ9KuJnVs2S44q3YsI2Y+XuyOvoO9VlGeBW/oOjLfC5inm8kvCVjJ7E8A1ocxXj8bajbxR2lgIlhiGN7ruZv8BU9p4uuhIzXUSyBjkleDWHd6LfaNOY72HaezKdysPXIpg5qY36mlTlTtE6+5j07xhZQ2qStbXsO4ws4+U5/hPtwK5e40nUdMcxXts6MP4uoP0Irb8L2E82owttKIrglj7c4rvryxt76PZPGGA6H0qra3J53y8p5EqMT90/lWjp1ybZgXYeWeHycYFdX4lsIdK8N3TWaASybULkZIXPOPwrzwAkZxRcSV1c7uxvrGW6VzcebFEQxKD8sjriunj1OxllEUd3CznoocZNeQplTlSQfardq7bgFzkEYx1BpiZ67RUFozixhac4fyxvJ9cUyLU7KeUxxXCOwODg96BFqiiigAooooAKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/wCQNP8A9hK+/wDSqWt2gAooooAr39p9vsJ7T7RNbechTzoGCyJnupIOD71m6H4cGhwLax6pe3VokXlJbTpAEUevyRqSevUnOTnmtqigDB03wjZabd20y3d7PHYhls7eeUNHbAjHy4AJ+XIG4nAOBW9RRQBheEP+QNP/ANhK+/8ASqWt2sLwh/yBp/8AsJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUh6cUtFAHnPi1Znu0lfcRtw3scmubcgDmvY57K2uTmWFWPrjmsi58JaPIxeSPYncAgfr1pMaZ5OxG4jI4p9rZXOpXa21nC00rA4Vfaur1b4fvErXOl3qSwKCWEzYZfxAwf0q/wCGbY+HI3cqkrzY81scgDsKx5G3qdjqxjG61Zytt4T1medY5LN7ZM/NLP8AIqj156/hXY35gguhb2cabIFVS7HO84HUdKw/EniS41HVJEtpTHbwMUQL/Fjq34/yxVjQ2ivLSe5vr+O08tlUvJgByf61cUomNSUp7nQv4ut7PTQ91GWuNxQRJ0bA6+w5rjW1Wwub93urFYIZMn5GLBa1vEmiW502DUdPvIZoEBDuZVAY+xzjPt1rB0zR5dXkUB1SAHDvuGfoBnrVN9iIxXUuWXjKDTonhttFgKnozt8xPvx+lZ1/f29/Ks8Fs1uzD94m7coPtVC/sZ9Ou3t51IKng44YeopkcoUYb86xUnezOqVKNrxRoxLZLp0zyyN9pZtqpjgDqDn8MGqMrKBjPNaFlpE+q2U0tmyySwtl4idp246jPXoazEjE0mzzETGSWY8fpTkyYRu9TQNki2cF3b73SVPnJH3HBII47dD+NQSR4A3DGe3eoVnuY0WOO4kWNCSoDEAE98etMeSaSfzHYs7Hqe9HNpaw3Tble5OFUDIHSo2Kgj1IqxNPPCq2zRrGUGWDIMnPPf2xVQnJLHGabYoxfUGUY65pY0DyKjMEViAWPQe9TXNwk4jAgSPYgTKDG7Hc+9VQCXCZ4zioZpHVBLGYpXjLK20kblOQfcHuKltJzbyCRVVmHZulWUtI2tZGKgEY2+tZ5BBwaGnHUcZKomjeXWpltPISGJA338AnNQM0b2xlDKrrxtzy1ZscxwFIz70/zAeTnitFM53SsyRQZJQmRuYgDPSkeHa+x/vA80xZFY7gCD05NXNPspNQvY7WPhnz8x/hA5JoWoO8R1lZy3EpWAY4Iz7kYxVQFwxDEAA4616Tp/hiDT9MaVWM0vllwSMZbFedrGFXBHNVYzUlrc6uytPD8sKMdThG49ZDsZfwrPu9aNpPJBpZUQhseaRkv+fasMrhhxTwMVRLSR09nrKapAsOoojeX8pOOStWv+EcsHLNDJsIJ7cD/CuSjmaB/MXkjtmuk0rxdDcXJt76zWMSjYsynIVu2RRdCUW9jo9GjtLKBTJPkjOCRgfX61bGtwsx2LlF6knBx64rktX10p+7jCBFPGeS2PSsiTxDOZFIjUBei5zxRcSTZ6NqVvFq+mPFHKmXGUbPGa8yvLc2kzxSJtYEjjoavi++2uW3lMrwucYqG+8+6gjyHdogcn1FMRmd6tWo+fIxx1JqCOGSVgqqee9d7Y+FF+wRNLtScKM5XcPxoA5298Q38+li0L7UU4JGcsKyba8ltbhJo2IZTniuzv8AwUZYXNvcje3zbWTAz7elc7B4W1WW7EDWzJzgsegHrmncpNo9Isrj7VaRzf3h19anqK2gW1tYoE+7GoUVLSJCiiigAooooAKKKKAMLwh/yBp/+wlff+lUtbtYXhD/AJA0/wD2Er7/ANKpa3aACiiigAooooAKKKKAMLwh/wAgaf8A7CV9/wClUtbtYXhD/kDT/wDYSvv/AEqlrdoAKKKKACiiigAooooAKKKKACiiigAooooAKKKjmmSCMu54/nQA8kAEk4ArD1bV7aLy2kJEYzye59aw/EXiiVTJb2xZZGJBOeEH4d64+WeeTPmzSPnk7mJpXKSudbd+MrSC2m+yxmaSRdgRwQpz3NUPDeuHUtVhsL8BUkzhk45Azg+3FcxIQeM1CyN94d6ylJ30OmFOLjZnQeLNFGjX/nRTxtb3TM0SqclR3H0GcVhTziWOJFUqIwc5bO5ieW9uMD8BUJJICknA6D0pKzcrnRGHKTZcxCHzG2bt23PGemcVIkRIz3FQrJyMirkLh+B19KuCTMarkkdLNb3+veCIY4VM89pLuZFOXZfmH5/zFcslnJExWeJ43HVXUg/ka27DVbnQVa4t+WkXZhvuk/8A1qZ9vuvEmpwx3PlfaHGxHA256kA1birmKnLkaRL4dtJLn7faQffntyq49aw5NNu7Od4ru3khZTgh1xXo2haRF4bjlvtRnigBG3LNgD8fWqviG3h1y0e90yeO6RSC3ltkr9R2puKbFGpJJnCiIKuK7nwdYwQ+Hrm5uHRQ0hbcf4MDrXMW+lXc86xiByCeSBmt3VopdL0VYd2xpDkp3HHBxVWIcmzjtTvTe6hPdbChlbIB7CmbMjGBj+dTtErLggGm7SvfFZ8pt7RNJIl02wt7p3F1erbKuMEqSWqvd2bWF4InkSQY3K65wQenWphjFaklvp0+geZd3SR3luD5MYcbmBPAI9OSfxocVYcajvZ7GYspeE7zz0FVJkG4GpowSCO1MlibqDTeqJhaMiFUy4xxU7RBlIA/GoPnU5IxVlH5AIqY2NKjkrNEaQuq8V1+jOthYCZIELYAdQPmk46ZrnURmYbRkk8V1VxYHTtG+0TT7WIysYXJx9a0UUjnlNy3ORuNb1aS8N2b+cSA8bXICj0A6Ae1djZ+FINVsLXUpZ/s/nxh5F29z6ex6/jXF3DiaUyLCkZ64H/16mXU9QeXzGu5QVxgK21R9AOKiOjNZ2lH0O81bSbd7COzsQgECEoepY9+a4SSNo3KMMEHBBrb0jxUlvPjVVZ4W43oOVPrXYXGg6dqca3EBTEigiRRu3D1rS6ZztNHmEgIQ54B70QYjkRxg7CDz7VseNNLGjTWsaZaOVGO/wBSDz+mPzrCsxLczrEikju2Og9TUOSvY2UJcly5qBd5FmcAeYM4Hbmq6jnpV3ULVrcLufd2HtVMVZlfQs2rKsigoG57109oDdx/YZIIyHHyOnGCa5EHFamh6g1nfpJjeAfuk9aZJ09t4euI8Qm3VefmlyCMe3eurA2qB6CmwyrPCkqfddQwp9ABRRRQAUUUUAFFFFABRRRQAUUUUAYXhD/kDT/9hK+/9Kpa3awvCH/IGn/7CV9/6VS1u0AFFFUtSv5rCNHh0u81AscFbXy8r7ne6/pmgC7RXPz+J7uCxurl/DGrxeRCXUSLE3mNwAoEcjtk59OgNcroGpJb+JdclhkurjUJ9KjmeSWymiDzKZicB1G1QNqrnqBjkg0AelUV59pljaaZH4O1PT8/bdTdUvJQxLXavbvI7Of4sMoIJ6V2mpS6pFGh0u0tblyfnFzctCAPYhHz+lAGf4Q/5A0//YSvv/SqWt2uf8EmVvD7tOiJMdQvTIqMWVW+0y5AJAyM98D6V0FABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABVPVLeW5sXWA/vQCV9zirlFAHkN/C8NwwkVkbuG6g1Qkw3evV/EOiJrOmyRKFW4C5if37A+xrySVJrWeSC4jZJI2KurdQRUSdjWnG+qGMmOnI7+1PKrt5pxYYGOlR+fGrEMpcf7LY/oah2RsuaRBIMORTaVjuYn1pKxZ1rYVRuYAYGTjk4rW0rxFdaMClpFbuhYlvNi3F/YnqB7Csin7FMe5W+YdVIx+XrTTa2E0noyzeanc31w0tw+QSSEHCp7Adq1fC0mnxavHc3l2iGIFooyrfM+OATjA9fwrDt4HnmSKNQWkYKoPqeKuW2harPfLapYT+ZkZyhAA9SemPeqTZnKMbW2NXxRqUurXwi8xjDD0BPVj1P8AT8KZ4ZmlstTLRTeUChz/ALXTj3qnOu24kB5IY5J+taGiWgmuDIylwvCqB1Nb21ucXO+Wx6MlzbwKjCDEjqGYIoGM1ynicS3E00kas0LY5x0OBwa6L7NMgjDEPIyLuXcN2QKnj0tWjJlJV3PzbTxj0qjM8pPBwetXtLtGuZ9oiEgwc56V2d74OtriTzLSVUOclWG7mq8MEemtLAsSyyBDHvBxtz1x70AcNqmoxuwtbSJI4oicuvWRvX6elZfJPuakeFkmaM87SQSKkWIY+7XNZyep6F4QWg6A4GMk1Y602C3MhYjChcZJ7VcOn3GN6IXTpuA4raK0OSbTZTKAcitDTYU2q0xARsk7jgY6UyCyd5VDx7l7jOMiotblae/xF8kESKkSKcBRgZ/EnNN6Cj72jZ23hvSYLhXmZEaNX+RtoJP41pazpzXSTRFGKSrhWUZxxjFcF4a1a60e5ZUmPlSjLITxn1+tenadeLf2MdymMOOcetNO6JkrPQ8kvdNvrCRku7WWIKfvMp2n8agVc8iu91+YubpbgkqvGw+lcNjHSlYfNcqzoxHbFdD4HvLu1vJ41mZLYx7n/ug5GD9etZIiMp2gVtwW5tLaJULBWILov8XvS5dbl+19zlJ/E2vQXbfZ5YRc7OnO0D3+tYtnrLafujt7SDy5fvhwSSPrUd5EVupGIOGORmq5QHnFNpii0lYkur57uUlcpGOFTPSljUupCjgdeK3PC/hSLW7ea4uZpYkSQKvl4+bjJ6iun/4RXTdOgeUea8ca7jGxHzEepxQr9RTa6HnhjdRllOPXHFXtJ0+e+vEiiU5PfHSujeIsAZNjRDkx7BgD0BrrLOytbOPFtCsYI5wOTVGZLBEIIEiXoihRUlFFABRRRQAUUUUAFFFFABRRRQAUUUUAYXhD/kDT/wDYSvv/AEqlrdrC8If8gaf/ALCV9/6VS1u0AFFFFABVZLC1j1GXUFixczRJE8m48opYqMdOCzfnVmigDJsPC+jaXei8s7Ly5VDBMyOyxBjlgiklUz/sgVrUUUAYXhD/AJA0/wD2Er7/ANKpa3awvCH/ACBp/wDsJX3/AKVS1u0AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFIThSfQUALXkPibURq3iC4nj2GNTsRlH3lHfPen6tql7qd9LJcyyYDnZGWOE9gKztoToOKh6msHylZozkncSPSmMmBnGKskqG4FI+NpyKzcUbxqPQp0U9oyCcflTKzsdKaYVPZXC2l5FO8SzKjZaN+jjuD+FQUuD6Uhs7rSX8OG8aTTIGacE+Wj7sqPbNdlpk5aEQuu11GcZyMZryzwxC/9twSeYEWMlmOe2Mf1xXo9xqVhoQWfUblVaQYjRAWJHc10xemp51WPvWTuU9S8FW97fNcxXBhEjbnTbnnvim6zq1p4R0yGxskV7rb8isOgzyzfjW7p2q2Wq232iynEqA4bjBU+hBrzXxRdC+8RXMgBATCDPoBVN9iYrXUx5pp7i6a7lmka4Ztxk3c5r0yHUbi88LW85fMpVRMynnpya86trWW9uo7aFcs5xnHCjuT7CvTdCsUtIhBHlolTaxI+8amKsypybSuUdOZo9QhEB5Y/MAeCPer15o873Ly27IVkOSGJGDWf4p1pfD6xwafbxJcTgkvt+6Ko+GvF1xcajHZ32CJjtVxnGe3WquZ8rtcxvEfh8afqR8pzIXXzGGMBSSc49qyAu3jGK9R8QaPHqdoXAbz4x8pU8kdxXI/8Iu11OsdtvyfvbxjFFhuTe5gwfKxPbua7nwdaF7eaaSIGJsBdw4J5zj9Kzn8Px6VFuv5Uhjz8z7uo9hTvEPi/wCyadbW+hOqb8gyAA7AMcD3OaG7IIxcnZGpqPhoJbym1lCJ127OR+NcTqtlJaSr5kZUEYz2P410ngnxPf6jfPp+oyifMZeOQgAgjqDjr1rp9S0Wy1O0a3liUZOQyjkGhO6HKLi7M8ojG6RQOpNek+FreSC1cYIiwuM927kU3SPCNlpdz9oY+dIPu7hwK3mZY1yxCqO5OAKZLKWqaXDqEXzRqzjueMj0zXH3fgu980vbjMZ/hJGRXbS39rC6o8yhm6Cp1ZWAKkEHnigRzmh+E4bOJnvUEsj8bewFXbrRbC1sbiSKLa4jJDFidv0zWxTJYlmheJ/uuCDQB5HfXDz3DBsDacVVxxXV634SuFu/NgkVt4zj1xWBPpl3bkhomO3rgdKQztfBMqmwKIwIJJZf7h6V07KHUqwyCMEetch4Gsbm3M9xIrJHIoABGNx9a7CmIzE0K1SUPukZAciMnitOiigAooooAKKKKACiiigAooooAKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/5A0//YSvv/SqWt2gAooooAKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/wCQNP8A9hK+/wDSqWt2gAooooAKKKKACiiigAooooAKKKKACiiigAooooA4DxloX2SZtRt1xFI3zgdj9K5CXcRwSK9W8TW8lzpRRVLIGBdR3FcXbeGo7yYgzSRwIC0sm3hFHJ5qWi4uzOXH3c96Z87SKqAszHhQMkmpJpUclbePy4gTtLnLH6n/AAqOKSSG4SVGxIjBlPoRWDZ3RjvclRcjINBjHQcVNPMtxO84QI0h3MB03dyPxqIkqPb1rTQwu7kQiPmcdKm8keppVORkU8daFFClOQtvO1nOtxH95M8H3GKW+v7zWLiN52MsqqI0VV7DoAB9afBaTXswhhTLseOa6jw94ZOn3yahLNHM8ROxAp256ZOfxptN6CjOK1e5d+H+k3tjDdXN1E8KT7QiOMFsZ5x+NTa/4NW+nN3aOVkP319RXUQTCeFZAMZ6j0NSVaVlYxcm3c5zwz4ebSXeZwQzLj5iCT+Va2p6rZ6PZm5vJVjToo7sfQAVdrz/AOJ0c2/T5MHyQHXPYNx/T+VKTsrlU488kmcrPfXGpXkl5dSF5JCSfb2HtVzSB/xObRgpOyVWI+hzUPhnS5NY1iK1CnyuWlcfwrj/AB4r0fTfCWn6bMJVZ5WHTdjFTDVF1lyyF8S+JofDttEzRGaabPlx7scDqSfxFcPqXj/Vrx0+yFbFAOQmGLH1yR+lXPiFqem311HbQvI11aEq7BRs5xlc56jFcXUTk72RvRpR5U2tTTvdc1DV3U6hcmXb90YCgfgKrO4wRVWlyT3qeZlukr3RetZp7WRZraQxyDowr0Lwl4qbUiNPv+LsA7HxgSAf1rziCRe5wa3vC1tPc+IbVoFJET73YDhR7/yrWPkctRa2Z6pXnHxHlu21e3t3ZhaiEMgHQtk5P16f5Nej1zfieJb6RbOVR5apvUlQTnpmqkrqxnCXK7nmyrlVAJwBXQ6VrlxFEiG4KtF90kZz9axHhaCQxuuCKEJVwR60LQJO563p2oR39skgIDkZK1crnPDccxSMMpCxDOT79q6OqIIp7dLhQHyCOQR1FRRWFvGdxQSMf4nGTVqigBAABgDApaKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDC8If8gaf/ALCV9/6VS1u1heEP+QNP/wBhK+/9Kpa3aACiiqWpTanDGh0yxtrtyfnWe6MIUeoIRs/pQBdqna6vpl9dSWtpqNpcXEP+siinV3TtyAciue8Q3nid/Cus+ZpdraMthKY5La/aZ923spiXtnnPpWfp015p7Wen6ff29+t7pM0sSwQIn2ZlVdhQoM7CWx82TkDnrQB2VvqunXl1LaW1/az3EH+thjmVnj/3gDkfjVuvPtN/s/7H4D/svyvtORu8vG7yvs7+du/4Htzn+LHeu01KLVJY0Gl3drbOD85ubZpgR7AOmP1oAz/CH/IGn/7CV9/6VS1u1z/gkSr4fdZ3R5hqF6JGRSqs32mXJAJOBntk/WugoAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACqGtQGfQ72CNhG0sLIpHqRir9RzwieFoycZ6H0NA07aniU1nNaymC4jaKReqsMUwRnfnsK67xfA8bxGZl8zeygD0/zj865oKOg59qy5Ub+2uMUYFRPxkE8+1Xba2mvrhLeBC8jHAwKZfWMmn30trcL+8iOCPwz/Wm0EXrqV0wAKmBFQtwQF4zUyg7eetERT7m3pNrLuWeE7NnJfpiu3jtBHpy3JkKAx+Y4K55xk4rn/Bv2a5iK3EO7YwUHPBPbIrtpI0kiaJhlWGCPatDAwYNYntwu6JPJHVRncB659a6AEEZHQ1jpoAEoD3BaIH7u3k+xNO8RXEtppsksQyEjZgO2QOM+1ABqesSWdtcXESKywKxwf4iK82uvF2s3TSLcTxyxSdYnhRkHpgEdqpT3tzMGEs8jBzlgWOD+FUScnNYTl2O2jTS3N/Q/GN9oivGkNvLE/OzywmD65UDP413nh3xdZa6nlvttroHHks4O73X1rySp7S3up7uKO1R2nZx5YTrntUxm0XUpQl5M3PFXhm90zULi8Kh7OWUssoYcbjnBHXNc8yYGRmvW/F1pcXfheaONPNmTa5CjJOCM4ryojIweM1Uoozp1W1qQKpY8UFCCB61ajjwCDTZlGPcd6XJoX7a8rCrEvQCu48KTQeH7APd3cUf2p9xRm5A6CuHjZsAHg1NKzTf6xiSABn6Vorbowne9mz2iKWOaNZYpFkRhlWU5BHsaiurK3vFAnj3behBwR+Nc98P4LqHQXM4YRvKWhDemBkj2zXU1a1RhJWdjnNS8IW13FtgcREcqSMn86xLPwLeC8X7VInlKckqetd9RTERwwR28YjiUKoqSiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDC8If8gaf/sJX3/pVLW7WF4Q/wCQNP8A9hK+/wDSqWt2gAooooAKqWeladpzyPY6fa2rSnMhghVC598DmrdFAFS30rTrO6lu7XT7WC4n/wBbNHCqvJ/vEDJ/GrdFFAGF4Q/5A0//AGEr7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGT4g0GLXbMRFxFMjbkk25x6g+3/1qxdD8DmzvBc6jLFLsztiQZBOOpJ/l9K7CipcU3clxTdyra6dZ2TM1vAkbN1IHNUdX8MabrMwnuEZJgMF4zgke/rWxRVFXOQ1H4fWEkZkspZopVXAUncrH+dcS8DwyNE6kMhwQa9lrLu/Dum3lz9okh+cnLYPBpWQ3JvcyPB2mMumLOwCq8hf3bHA/DiurpkUSQxLFGoVFGAB2p9MQU10SRCjqGU8EEZBp1FAHiepwquqXiQArEs7qgPZQxwKoMCpwa6zxTpE1nrFxNs/cyuXDfXr+tc/JCHbd0rGUDshW7kMS4wa0tHS4fWbX7ID5qyKwK9hnk1U2hVJya6f4fWU0utS3gyIYYirH+8W6D9CfwFNK2hMpXuz0YdOa828beHotMuP7RhlOy5lOYsfdY8nn0r0qqWq6Va6xZNaXakoTkFTgqfUVo1dGEJcrPIbdTOyog+Y9BTWG44r0az8EaXpqyStNM7bT87MBsHfoK4KbTbi3uGx+8jyQjjgMOxqdSrq7aZW2YGe9KenTNSY7EfUU6IL5qbhlcjIp2Juep+HLp7vQbSWRNjbNuAMdOK06paRJHJpkIiXaEUKV9CKu1RAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGF4Q/5A0/8A2Er7/wBKpa3awvCH/IGn/wCwlff+lUtbtABRRRQAUUUUAFFFFAGF4Q/5A0//AGEr7/0qlrdrC8If8gaf/sJX3/pVLW7QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAYviqwkv9IZIk3OpyBjnpXmJR0YpIpVlOCCOle0VxfjDw7PNc/2jZxmQOMSooyQR3oHc5zQ9FGuXxtWlaMBdxZR0H+cV6TpOk22jWK2lqDtB3MzdWPqa5jwXpF3b30l5LG8cfllfmGNxJH+FdrSsF3sFFFFMRDdwfarSWDdt8xCufSuTPh6/uHFvLAEXPMu4YA9RXZUUAefaz4ZnhMzRxySuDlGVchx+HfFc9BazzTLGkTZJxyO9exVXWxtEnM620Syn+MKM0DuM060NlaLGx3OeWPvVuiigQUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGF4Q/wCQNP8A9hK+/wDSqWt2sLwh/wAgaf8A7CV9/wClUtbtABRRVLUo9VkjQaVc2cDg/Obq3aUEewV1x+tAFmaaK2gknnkWOKJS7uxwFUDJJPpis/TfEmk6vcG3s7l2l8vzVSSCSIumcbl3qNy8jkZHIrL1eLxFH4e1Y6gdO1SI2MoFpbWcsTSkr0yZW4xngDPoawNM/wBN1aKDT9cbX3Okzw+eyBfsJITaMqAAWIAw2W+Tr1oA7Gw8UaNql6LOzvRJKwYpmN1WUKcMUYgK+O+0mtavPtMvrTU4/B2maf8A8fumOr3kQUhrRUt3jdXH8OWYDB612mpWNxfRotvql1p5U5LWyxEt7HzEYfligDP8If8AIGn/AOwlff8ApVLW7XL6boPiTSLV7S116wkiM8soe501mkJkkZzuKyqpOWPRQParf2Txb/0GtI/8FUn/AMfoA3aK5SKfxbLr11pf9q6QPs1tDP5n9mSfN5jSLjHn8Y8vrnv7Ve+yeLf+g1pH/gqk/wDj9AG7RWF9k8W/9BrSP/BVJ/8AH6Psni3/AKDWkf8Agqk/+P0AbtFYX2Txb/0GtI/8FUn/AMfo+yeLf+g1pH/gqk/+P0AbtFYX2Txb/wBBrSP/AAVSf/H6o6vP4t0qzjuP7V0iXfcwQbf7MkXHmSrHn/X9t2cd8UAdXRWF9k8W/wDQa0j/AMFUn/x+j7J4t/6DWkf+CqT/AOP0AbtFYX2Txb/0GtI/8FUn/wAfo+yeLf8AoNaR/wCCqT/4/QBu0VhfZPFv/Qa0j/wVSf8Ax+j7J4t/6DWkf+CqT/4/QBu0VhG18WhSf7a0jgf9AuT/AOP1S0WbxbrGh2Gp/wBq6RD9st45/L/syRtm5Q2M+eM4zQB1VFYX2Txb/wBBrSP/AAVSf/H6Psni3/oNaR/4KpP/AI/QBu0VhfZPFv8A0GtI/wDBVJ/8fo+yeLf+g1pH/gqk/wDj9AG7RWF9k8W/9BrSP/BVJ/8AH6Psni3/AKDWkf8Agqk/+P0AbtFcpFP4tl1660v+1dIH2a2hn8z+zJPm8xpFxjz+MeX1z39qvfZPFv8A0GtI/wDBVJ/8foA3aKwvsni3/oNaR/4KpP8A4/R9k8W/9BrSP/BVJ/8AH6AN2isL7J4t/wCg1pH/AIKpP/j9H2Txb/0GtI/8FUn/AMfoA3aKwvsni3/oNaR/4KpP/j9UdQn8W2N5ptv/AGrpD/b7kwbv7MkGzEUkmf8AX8/6vGOOtAHV0VhfZPFv/Qa0j/wVSf8Ax+j7J4t/6DWkf+CqT/4/QBu0VhfZPFv/AEGtI/8ABVJ/8fo+yeLf+g1pH/gqk/8Aj9AG7RWF9k8W/wDQa0j/AMFUn/x+j7J4t/6DWkf+CqT/AOP0AbtFYRtfFoUn+2tI4H/QLk/+P1S0WbxbrGh2Gp/2rpEP2y3jn8v+zJG2blDYz54zjNAHVUVhfZPFv/Qa0j/wVSf/AB+j7J4t/wCg1pH/AIKpP/j9AG7RWF9k8W/9BrSP/BVJ/wDH6Psni3/oNaR/4KpP/j9AG7RWF9k8W/8AQa0j/wAFUn/x+j7J4t/6DWkf+CqT/wCP0AbtFcpp8/i2+vNSt/7V0hPsFyIN39mSHfmKOTP+v4/1mMc9KvfZPFv/AEGtI/8ABVJ/8foA3aKwvsni3/oNaR/4KpP/AI/R9k8W/wDQa0j/AMFUn/x+gDdorC+yeLf+g1pH/gqk/wDj9H2Txb/0GtI/8FUn/wAfoA3aKwvsni3/AKDWkf8Agqk/+P1R1CfxbY3mm2/9q6Q/2+5MG7+zJBsxFJJn/X8/6vGOOtAHV0VhfZPFv/Qa0j/wVSf/AB+j7J4t/wCg1pH/AIKpP/j9AG7RWF9k8W/9BrSP/BVJ/wDH6Psni3/oNaR/4KpP/j9AG7RWF9k8W/8AQa0j/wAFUn/x+j7J4t/6DWkf+CqT/wCP0AbtFYRtfFoUn+2tI4H/AEC5P/j9UtFm8W6xodhqf9q6RD9st45/L/syRtm5Q2M+eM4zQBd8If8AIGn/AOwlff8ApVLW7WboGlzaRpf2W4uUuJmnmneSOMxqTJI0hwpJwAWx1NaVABRRRQAUUUUAFFFFABWbrXiDS/D8Cz6pcNDG2SCsLycDGSdoOByOahuoPE7XUhs9R0mO3J/dpNYSO4HuwmAP5CsTx3f/ANn/AA91C31rULIXtzA6R+WphWU9gqszHOMdzQB0upajp+jw/bL2RYhIyxBghZ5DztUBQWY9cAA96iTxFpD6PJqwvUFnESryMrKUYHG0qRuDZwNuM5I4rE1rVtPmvfD3iCK7in0m3uZlluo23xxlo2VWJHQA5XPbdWPOwuEvtegR30n/AISC2utyoSHijjjR5QO6hxnI7KTQB3GmazYaxHI9jMX8ltkiPG0bxnGcMjAMODnkVerl9AuoNV8W6xqunyCawe2toBOnKTSKZCxU98B1GR9O1dRQAUUUUAFZOra/pmmOYr+O7IVRKWj0+eZFAOQSyIVBGM9eKhkt/FpkYx6powTJ2htOlJA7ZPn1U8VtdT6PZaA8qNe6xKttK8KlAI8bpmAJJA2Bh1PLDmgC9P4r0e3gsJmmuHXUYjNarDZzStIgCkttVCQPnXqB1rUtriO7to7iISBJBuUSRtG2PdWAI+hFc74lj8MxXNidW1RtMmtoZFtTFdNbna23IBUjP3F4/SrvhG5vrvwzazagZWmYuA8ybHkjDsI2YcYJQKT9aANqiiigAoorO1KLW5JEOlXlhAgHzi6tXlJPsVkXH60ATanqdpo+nyX19IY7eMqGZY2c5ZgoAVQSckgcCobDWNOuLGWaATW1tar85uLWS2VFAzwJFXgAduBWXqVvI2i3MXjDU7H7A7R4ktYZLbYQ4YZYyN3C88Yrnrk3GqaF4nsdHu7rVtMW1ja2kkkMpeT5jLGjnlxtVe55bFAHZ6V4i0rWpHisLkvIiByjxPGxQ9GAcAlT6jIrTrkrTU7LxB420+80eZbiCzsJ1uZYwdql2i2Rk/3vkY7eoxXW0AFFFFABRUN0ty1rILOSKO4I/dvMhdAfdQQT+YrKht/FYmQz6no7RBhvVNPlViueQCZjg474NADofEuhy6mLVJytxK/kq728iLIy5+QSFQrEc8AnvTpfFGlxapLpu67kuYHVJRDYzyKjMoYAuqFRwwPXvXPT+JdH8S+JoNOOrWUFrp16pCPOomu7lThVRSchVbHP8RwBxyYfE1xpVldaldaNq9wniSSRCtlDcM3nSqqqqmHoVIUAnHTJyKAO+opBnHPWloAKKKKACsvV9c0nSJYV1CXErbpI0SF5XAAwWwoJAAOC3TmtSuT1DUbPQfHUt/q0y21rc6ZHFBPJwu9JHLpn+8QykDqce1AHT29xDd20dzbyrLDKoeORDkMpGQQalrB8EW81r4QsI54mhYh3EbjBRWdmUEdsKQMdq3qACiiigAooooAyLLxTo2o3kdpb3TmWYExCSCSNZcDJ2MygPxzwTTbfxJpDXx0y2+0tJDL9nIisJjFGw427wmwY474FYFj4l0fxd4mtJE1ayS2sJmNlb+evnXU21lL7c5CAM2B1Oc9MZh1G40qx1J28OavcPrUupKZbCO4Z1cmQLLviPCqF3HdgYwOaAO+ooooAKKKKACsvUvEWm6VeR2d09w1xJGZVjt7Sac7AcEny1bAye9alcr4n/wCEbj1RJ9U1mbTb9bYrE0N00LlC2eAPvnK9Oeg4oA07zxHo2lLFJcytE92nnhFtpGkKgDLsiqWUAYBLAY6GtOCeK6t47iCRZYpVDo6HIZSMgg+lcFousvpWpxar4rk+ySX2jwKk0ybMujyFkx2ch0bb154HFdJ4Jtp7PwdpsNxE0LiIt5TjBRWYsqkdiAQMUAbtFFFABRRRQBV1DUbfTLcT3K3DIWC4gtpJmz/uopOOOuMVknxj4fkge5aW4ItrhYCr2E4kWVlyFCFN2Sp7DofetfUb+DS9NudQuW2w20TSufZRk1yUOm6Xa+ELOXxTdmymvLv7fNL57Qlbh8sBvGNu0fKOR90UAdZp+owanbme3WdUDFcT28kLZ/3XUHHPXGKtVzfg66luV1JUup73TYroLY3VwSzSJsUsAx5dQ5YBu/qcV0lABRRRQAVn6xrunaBa/atSnaGLn5lieTgDJOFBOAO9aFc74+1CysPBWrrd3UUBubKeGESOF8xzG2FGepPpQBpahrmm6ZbQT3c5Vbk4hVInkeQ4z8qKCx456cVENf0W30SHU0u41sGwkTRoTk52hFQDO7IxtAzx0rnDrelrqvh/XGvoJNLjs57VrpXBjhmPlEBm6LkKw5+neqMDC3Sw16dHTSf+EgubrcyEBIpI5ESUjspc5yf7wNAHdabqtlq9sbixm82NXKMCpRkYdVZWAKn2IFXK5rwtKl9rGv6raHfY3dxEIJQPlmKRKrOvqM8Z77a6WgAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAP/Z",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_dbscan(prob_vectors_tsne, hdbscan_cluster_assignments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster 0 has 6 points\n",
      "Cluster 1 has 5 points\n",
      "Cluster 2 has 5 points\n",
      "Cluster 3 has 8 points\n",
      "Cluster 4 has 6 points\n",
      "Cluster 5 has 5988 points\n",
      "Cluster 6 has 7 points\n"
     ]
    }
   ],
   "source": [
    "for cluster_idx in range(hdbscan_cluster_assignments.max() + 1):\n",
    "    cluster_size = (hdbscan_cluster_assignments == cluster_idx).sum()\n",
    "    print(f'Cluster {cluster_idx} has {cluster_size} points')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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