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    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<h1>Worked machine learning examples using SDSS data</h1>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[AstroHackWeek 2014 - J. S. Bloom @profjsb]\n",
      "\n",
      "See all the materials at: https://github.com/AstroHackWeek/day4\n",
      "<hr>\n",
      "Here we'll see some worked ML examples using `scikit-learn` on Sloan Digital Sky Survey Data (SDSS).\n",
      "\n",
      "It's easiest to grab data from the <a href=\"http://skyserver.sdss3.org/public/en/tools/search/sql.aspx\">SDSS skyserver SQL</a> server.\n",
      "\n",
      "\n",
      "For example to do a basic query to get two types of photometry (aperature and petrosian), corrected for extinction, for 1000 QSO sources with redshifts:\n",
      "<font color=\"blue\">\n",
      " <pre>SELECT *,dered_u - mag_u AS diff_u, dered_g - mag_g AS diff_g, dered_r - mag_r AS diff_g, dered_i - mag_i AS diff_i, dered_z - mag_z AS diff_z from\n",
      "(SELECT top 1000\n",
      "objid, ra, dec, dered_u,dered_g,dered_r,dered_i,dered_z,psfmag_u-extinction_u AS mag_u,\n",
      "psfmag_g-extinction_g AS mag_g, psfmag_r-extinction_r AS mag_r, psfmag_i-extinction_i AS mag_i,psfmag_z-extinction_z AS mag_z,z AS spec_z,dered_u - dered_g AS u_g_color, \n",
      "dered_g - dered_r AS g_r_color,dered_r - dered_i AS r_i_color,dered_i - dered_z AS i_z_color,class\n",
      "FROM SpecPhoto \n",
      "WHERE \n",
      " (class = 'QSO')\n",
      " ) as sp\n",
      " </pre>\n",
      " </font>\n",
      "Saving this and others like it as a `csv` we can then start to make our data set for classification/regression."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "## get the data locally ... I put this on a gist\n",
      "!curl -k -O https://gist.githubusercontent.com/anonymous/53781fe86383c435ff10/raw/4cc80a638e8e083775caec3005ae2feaf92b8d5b/qso10000.csv\n",
      "!curl -k -O https://gist.githubusercontent.com/anonymous/2984cf01a2485afd2c3e/raw/964d4f52c989428628d42eb6faad5e212e79b665/star1000.csv\n",
      "!curl -k -O https://gist.githubusercontent.com/anonymous/2984cf01a2485afd2c3e/raw/335cd1953e72f6c7cafa9ebb81b43c47cb757a9d/galaxy1000.csv"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\r\n",
        "                                 Dload  Upload   Total   Spent    Left  Speed\r\n",
        "\r",
        "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0"
       ]
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      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100 31763    0 31763    0     0  52127      0 --:--:-- --:--:-- --:--:-- 53653"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100  434k    0  434k    0     0   268k      0 --:--:--  0:00:01 --:--:--  271k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100  513k    0  513k    0     0   198k      0 --:--:--  0:00:02 --:--:--  199k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100  633k    0  633k    0     0   178k      0 --:--:--  0:00:03 --:--:--  178k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100  814k    0  814k    0     0   178k      0 --:--:--  0:00:04 --:--:--  179k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100  958k    0  958k    0     0   172k      0 --:--:--  0:00:05 --:--:--  187k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100 1086k    0 1086k    0     0   164k      0 --:--:--  0:00:06 --:--:--  130k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100 1267k    0 1267k    0     0   167k      0 --:--:--  0:00:07 --:--:--  150k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100 1505k    0 1505k    0     0   175k      0 --:--:--  0:00:08 --:--:--  173k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100 1939k    0 1939k    0     0   202k      0 --:--:--  0:00:09 --:--:--  223k"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "100 2378k    0 2378k    0     0   235k      0 --:--:--  0:00:10 --:--:--  311k\r\n"
       ]
      }
     ],
     "prompt_number": 61
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# For pretty plotting\n",
      "!pip install --upgrade seaborn"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Requirement already up-to-date: seaborn in /Users/jbloom/anaconda/lib/python2.7/site-packages\r\n",
        "Cleaning up...\r\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "pd.set_option('display.max_columns', None)\n",
      "%pylab inline\n",
      "import seaborn as sns\n",
      "sns.set()\n",
      "import copy"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.read_csv(\"qso10000.csv\",index_col=0).head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>ra</th>\n",
        "      <th>dec</th>\n",
        "      <th>dered_u</th>\n",
        "      <th>dered_g</th>\n",
        "      <th>dered_r</th>\n",
        "      <th>dered_i</th>\n",
        "      <th>dered_z</th>\n",
        "      <th>mag_u</th>\n",
        "      <th>mag_g</th>\n",
        "      <th>mag_r</th>\n",
        "      <th>mag_i</th>\n",
        "      <th>mag_z</th>\n",
        "      <th>spec_z</th>\n",
        "      <th>u_g_color</th>\n",
        "      <th>g_r_color</th>\n",
        "      <th>r_i_color</th>\n",
        "      <th>i_z_color</th>\n",
        "      <th>class</th>\n",
        "      <th>diff_u</th>\n",
        "      <th>diff_g</th>\n",
        "      <th>diff_g1</th>\n",
        "      <th>diff_i</th>\n",
        "      <th>diff_z</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>objid</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
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        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
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        "  <tbody>\n",
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        "      <th>1237648720142532813</th>\n",
        "      <td> 146.90229</td>\n",
        "      <td>-0.984913</td>\n",
        "      <td> 19.64289</td>\n",
        "      <td> 19.31131</td>\n",
        "      <td> 19.25328</td>\n",
        "      <td> 19.15353</td>\n",
        "      <td> 19.13345</td>\n",
        "      <td> 19.71604</td>\n",
        "      <td> 19.37595</td>\n",
        "      <td> 19.32818</td>\n",
        "      <td> 19.24847</td>\n",
        "      <td> 19.21259</td>\n",
        "      <td> 0.652417</td>\n",
        "      <td> 0.331583</td>\n",
        "      <td> 0.058027</td>\n",
        "      <td> 0.099751</td>\n",
        "      <td> 0.020077</td>\n",
        "      <td> QSO</td>\n",
        "      <td>-0.073151</td>\n",
        "      <td>-0.064648</td>\n",
        "      <td>-0.074903</td>\n",
        "      <td>-0.094942</td>\n",
        "      <td>-0.079136</td>\n",
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        "    <tr>\n",
        "      <th>1237658425156829371</th>\n",
        "      <td> 142.45853</td>\n",
        "      <td> 6.646406</td>\n",
        "      <td> 19.39569</td>\n",
        "      <td> 19.34811</td>\n",
        "      <td> 19.16626</td>\n",
        "      <td> 18.93152</td>\n",
        "      <td> 19.06013</td>\n",
        "      <td> 19.40327</td>\n",
        "      <td> 19.36566</td>\n",
        "      <td> 19.18335</td>\n",
        "      <td> 18.94222</td>\n",
        "      <td> 19.08077</td>\n",
        "      <td> 1.537123</td>\n",
        "      <td> 0.047575</td>\n",
        "      <td> 0.181847</td>\n",
        "      <td> 0.234743</td>\n",
        "      <td>-0.128612</td>\n",
        "      <td> QSO</td>\n",
        "      <td>-0.007589</td>\n",
        "      <td>-0.017550</td>\n",
        "      <td>-0.017090</td>\n",
        "      <td>-0.010700</td>\n",
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        "      <td> 143.15770</td>\n",
        "      <td> 8.175363</td>\n",
        "      <td> 19.10362</td>\n",
        "      <td> 18.88904</td>\n",
        "      <td> 18.70672</td>\n",
        "      <td> 18.58508</td>\n",
        "      <td> 18.61328</td>\n",
        "      <td> 19.11102</td>\n",
        "      <td> 18.88857</td>\n",
        "      <td> 18.70458</td>\n",
        "      <td> 18.57886</td>\n",
        "      <td> 18.62583</td>\n",
        "      <td> 1.467101</td>\n",
        "      <td> 0.214582</td>\n",
        "      <td> 0.182318</td>\n",
        "      <td> 0.121645</td>\n",
        "      <td>-0.028202</td>\n",
        "      <td> QSO</td>\n",
        "      <td>-0.007397</td>\n",
        "      <td> 0.000473</td>\n",
        "      <td> 0.002148</td>\n",
        "      <td> 0.006218</td>\n",
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        "      <th>1237660412651962520</th>\n",
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        "      <td> 19.52941</td>\n",
        "      <td> 19.65000</td>\n",
        "      <td> 19.52470</td>\n",
        "      <td> 19.88709</td>\n",
        "      <td> 19.75292</td>\n",
        "      <td> 19.53512</td>\n",
        "      <td> 19.67052</td>\n",
        "      <td> 19.50256</td>\n",
        "      <td> 1.014217</td>\n",
        "      <td> 0.136745</td>\n",
        "      <td> 0.222052</td>\n",
        "      <td>-0.120590</td>\n",
        "      <td> 0.125301</td>\n",
        "      <td> QSO</td>\n",
        "      <td> 0.001118</td>\n",
        "      <td>-0.001457</td>\n",
        "      <td>-0.005716</td>\n",
        "      <td>-0.020527</td>\n",
        "      <td> 0.022139</td>\n",
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        "    <tr>\n",
        "      <th>1237658493336944662</th>\n",
        "      <td> 142.64367</td>\n",
        "      <td> 7.917698</td>\n",
        "      <td> 18.45897</td>\n",
        "      <td> 18.40651</td>\n",
        "      <td> 18.15901</td>\n",
        "      <td> 17.77130</td>\n",
        "      <td> 17.75986</td>\n",
        "      <td> 18.55725</td>\n",
        "      <td> 18.55002</td>\n",
        "      <td> 18.40316</td>\n",
        "      <td> 18.01008</td>\n",
        "      <td> 18.03100</td>\n",
        "      <td> 0.215603</td>\n",
        "      <td> 0.052462</td>\n",
        "      <td> 0.247498</td>\n",
        "      <td> 0.387709</td>\n",
        "      <td> 0.011444</td>\n",
        "      <td> QSO</td>\n",
        "      <td>-0.098282</td>\n",
        "      <td>-0.143515</td>\n",
        "      <td>-0.244150</td>\n",
        "      <td>-0.238779</td>\n",
        "      <td>-0.271137</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 23 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "                            ra       dec   dered_u   dered_g   dered_r  \\\n",
        "objid                                                                    \n",
        "1237648720142532813  146.90229 -0.984913  19.64289  19.31131  19.25328   \n",
        "1237658425156829371  142.45853  6.646406  19.39569  19.34811  19.16626   \n",
        "1237660413189095710  143.15770  8.175363  19.10362  18.88904  18.70672   \n",
        "1237660412651962520  142.49264  7.800945  19.88820  19.75146  19.52941   \n",
        "1237658493336944662  142.64367  7.917698  18.45897  18.40651  18.15901   \n",
        "\n",
        "                      dered_i   dered_z     mag_u     mag_g     mag_r  \\\n",
        "objid                                                                   \n",
        "1237648720142532813  19.15353  19.13345  19.71604  19.37595  19.32818   \n",
        "1237658425156829371  18.93152  19.06013  19.40327  19.36566  19.18335   \n",
        "1237660413189095710  18.58508  18.61328  19.11102  18.88857  18.70458   \n",
        "1237660412651962520  19.65000  19.52470  19.88709  19.75292  19.53512   \n",
        "1237658493336944662  17.77130  17.75986  18.55725  18.55002  18.40316   \n",
        "\n",
        "                        mag_i     mag_z    spec_z  u_g_color  g_r_color  \\\n",
        "objid                                                                     \n",
        "1237648720142532813  19.24847  19.21259  0.652417   0.331583   0.058027   \n",
        "1237658425156829371  18.94222  19.08077  1.537123   0.047575   0.181847   \n",
        "1237660413189095710  18.57886  18.62583  1.467101   0.214582   0.182318   \n",
        "1237660412651962520  19.67052  19.50256  1.014217   0.136745   0.222052   \n",
        "1237658493336944662  18.01008  18.03100  0.215603   0.052462   0.247498   \n",
        "\n",
        "                     r_i_color  i_z_color class    diff_u    diff_g   diff_g1  \\\n",
        "objid                                                                           \n",
        "1237648720142532813   0.099751   0.020077   QSO -0.073151 -0.064648 -0.074903   \n",
        "1237658425156829371   0.234743  -0.128612   QSO -0.007589 -0.017550 -0.017090   \n",
        "1237660413189095710   0.121645  -0.028202   QSO -0.007397  0.000473  0.002148   \n",
        "1237660412651962520  -0.120590   0.125301   QSO  0.001118 -0.001457 -0.005716   \n",
        "1237658493336944662   0.387709   0.011444   QSO -0.098282 -0.143515 -0.244150   \n",
        "\n",
        "                       diff_i    diff_z  \n",
        "objid                                    \n",
        "1237648720142532813 -0.094942 -0.079136  \n",
        "1237658425156829371 -0.010700 -0.020636  \n",
        "1237660413189095710  0.006218 -0.012548  \n",
        "1237660412651962520 -0.020527  0.022139  \n",
        "1237658493336944662 -0.238779 -0.271137  \n",
        "\n",
        "[5 rows x 23 columns]"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notice that there are several things about this dataset. First, RA and DEC are probably not something we want to use in making predictions: it's the location of the object on the sky. Second, the magnitudes are highly covariant with the colors. So dumping all but one of the magnitudes might be a good idea to avoid overfitting. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "qsos = pd.read_csv(\"qso10000.csv\",index_col=0,usecols=[\"objid\",\"dered_r\",\"spec_z\",\"u_g_color\",\\\n",
      "                                                \"g_r_color\",\"r_i_color\",\"i_z_color\",\"diff_u\",\\\n",
      "                                                \"diff_g1\",\"diff_i\",\"diff_z\"])\n",
      "\n",
      "qso_features = copy.copy(qsos)\n",
      "qso_redshifts = qsos[\"spec_z\"]\n",
      "del qso_features[\"spec_z\"]\n",
      "qso_features.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
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        "      <th></th>\n",
        "      <th>dered_r</th>\n",
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        "      <th>r_i_color</th>\n",
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        "      <th>diff_g1</th>\n",
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        "      <th>1237660413189095710</th>\n",
        "      <td> 18.70672</td>\n",
        "      <td> 0.214582</td>\n",
        "      <td> 0.182318</td>\n",
        "      <td> 0.121645</td>\n",
        "      <td>-0.028202</td>\n",
        "      <td>-0.007397</td>\n",
        "      <td> 0.002148</td>\n",
        "      <td> 0.006218</td>\n",
        "      <td>-0.012548</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1237660412651962520</th>\n",
        "      <td> 19.52941</td>\n",
        "      <td> 0.136745</td>\n",
        "      <td> 0.222052</td>\n",
        "      <td>-0.120590</td>\n",
        "      <td> 0.125301</td>\n",
        "      <td> 0.001118</td>\n",
        "      <td>-0.005716</td>\n",
        "      <td>-0.020527</td>\n",
        "      <td> 0.022139</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1237658493336944662</th>\n",
        "      <td> 18.15901</td>\n",
        "      <td> 0.052462</td>\n",
        "      <td> 0.247498</td>\n",
        "      <td> 0.387709</td>\n",
        "      <td> 0.011444</td>\n",
        "      <td>-0.098282</td>\n",
        "      <td>-0.244150</td>\n",
        "      <td>-0.238779</td>\n",
        "      <td>-0.271137</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 9 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "                      dered_r  u_g_color  g_r_color  r_i_color  i_z_color  \\\n",
        "objid                                                                       \n",
        "1237648720142532813  19.25328   0.331583   0.058027   0.099751   0.020077   \n",
        "1237658425156829371  19.16626   0.047575   0.181847   0.234743  -0.128612   \n",
        "1237660413189095710  18.70672   0.214582   0.182318   0.121645  -0.028202   \n",
        "1237660412651962520  19.52941   0.136745   0.222052  -0.120590   0.125301   \n",
        "1237658493336944662  18.15901   0.052462   0.247498   0.387709   0.011444   \n",
        "\n",
        "                       diff_u   diff_g1    diff_i    diff_z  \n",
        "objid                                                        \n",
        "1237648720142532813 -0.073151 -0.074903 -0.094942 -0.079136  \n",
        "1237658425156829371 -0.007589 -0.017090 -0.010700 -0.020636  \n",
        "1237660413189095710 -0.007397  0.002148  0.006218 -0.012548  \n",
        "1237660412651962520  0.001118 -0.005716 -0.020527  0.022139  \n",
        "1237658493336944662 -0.098282 -0.244150 -0.238779 -0.271137  \n",
        "\n",
        "[5 rows x 9 columns]"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bins =  hist(qso_redshifts.values,bins=100) ; xlabel(\"redshift\") ; ylabel(\"N\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "<matplotlib.text.Text at 0x109722ed0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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wB2zAbXwArES4AxHQU1gnJ9/R6/7Hj3+jx1/czZABAEsQ7hiyruXqufuxPd1z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\nRPsAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10424aad0>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Pretty clearly a big cut at around $z=2$."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib as mpl\n",
      "import matplotlib.cm as cm\n",
      "## truncate the color at z=2.5 just to keep some contrast.\n",
      "norm = mpl.colors.Normalize(vmin=min(qso_redshifts.values), vmax=2.5)\n",
      "cmap = cm.jet_r\n",
      "#x = 0.3\n",
      "m = cm.ScalarMappable(norm=norm, cmap=cmap)\n",
      "rez = pd.scatter_matrix(qso_features[0:2000], alpha=0.2,figsize=[15,15],color=m.to_rgba(qso_redshifts.values))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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hhBBCiOszq6TvO9/5znzHIYQQQgghhBBiHswq6evu7qZQKHD+/Hk2b9483zEJ\nIYQQQgghhJgjs+rT97Of/Yzf+Z3f4c/+7M8AeO2113jooYfmNTAhhBBCCCGEENdvVknfvn37+Pa3\nv00qlQJg69at9Pf3z2tgQgghhBBCCCGu36ySPoC2trbL/g4EAnMejBBCCCGEEEKIuTWrpC8ejzM2\nNjb19wsvvEAymZy3oIQQQgghhBBCzI1ZDeTymc98hj/+4z/m4sWL/OEf/iF9fX088cQT8x2bEEII\nIYQQQojrdNWkr1wuA7BhwwaefPJJjh07htaazZs3T/XvE0IIIYQQQgixeF016bv11lun/UwpxfHj\nx+c8ICGEEEIIIYQQc+eqSd+JEycA+Md//EdCoRAf+9jH0Frz7W9/G9u2FyRAIYQQQgghhBDv3KwG\ncnn22WfZs2cPiUSCZDLJJz/5SX74wx/Od2xCCCGEEEIIIa7TrJK+arVKX1/f1N/nz5+nUqm8oxUO\nDAywc+dOHnjgAT75yU8C8LWvfY3du3ezd+9eXNcF4JlnnuG+++7joYceolAovKN1CSGEEEIIIcRy\nN6vROx9++GE+9rGPsXnzZgDeeOMNPv/5z7/jlb773e/my1/+MgATExO8+OKL7N+/n3/6p3/iRz/6\nEe973/s4cOAA+/fv5wc/+AEHDhyYShCFEEIIIYQQQszerJK+D3zgA9x2220cOXIEpRTbtm2jubn5\nHa/0hRde4P777+e3fuu3WLNmDXfeeScAO3fu5Hvf+x7r169nw4YNGIbBzp07+Zu/+Zt3vC4hhBBC\nCCGEWM5mlfQBtLS08L73ve+6V9jW1sYPf/hDAoEAf/qnf0qxWJxKIOPxOLlcjlwuRzwev2yaEEII\nIYQQQohrN+ukb64Eg8Gp/7/3ve8lHo8zMjICQKFQIJlMkkgkpvrxvTntahobo1iWOX9BLwOZTHxW\n8zU1xWltTTA2lp/niIQQQgghhBBzYcGTvmKxSCwWA+CVV17hgQce4Pvf/z579uzhueeeY/v27axe\nvZre3l5835+adjWZTGkhQl/S0unZDZaTThck4RNCCCGEEOIGsuBJ36FDh9i3bx/BYJA77riDrVu3\nsmPHDnbv3k1nZycf//jHsSyLe++9l927d9PQ0MBjjz220GEKIYQQQgghxJKgtNa63kFcL2l5un5n\nzvTyyFefJ97YNe08hcxFvvipu1m3bv0CRiaEEEIIIYSYSWtrYtrPZvWePiGEEEIIIYQQNyZJ+oQQ\nQgghhBDbU0C8AAAgAElEQVRiCZOkTwghhBBCCCGWMEn6hBBCCCGEEGIJk6RPCCGEEEIIIZYwSfqE\nEEIIIYQQYgmTpE8IIYQQQgghljBJ+oQQQgghhBBiCZOkTwghhBBCCCGWMEn6hBBCCCGEEGIJk6RP\nCCGEEEIIIZYwSfqEEEIIIYQQYgmTpE8IIYQQQgghljBJ+oQQQgghhBBiCZOkTwghhBBCCCGWsEWd\n9P393/89999/P3/3d39X71DEEqOqY6jqWL3DuDHYE6jqSL2jEHPJszHKF8Cz6x3J4uOVa2WjvXpH\nIhYjryT7x43EyaAqQ/WOYslTlSFwMvUOY3Fz0qjqcF1DWLRJ37FjxyiXyzz99NM4jsPrr79e75DE\nUuHmMcvnMct94BbrHc3i5tuYxTOYlQGUPVHvaMQcMUtnMOxxzNKZeoey6JjFXgx7HKN4rt6hiEXI\nLFzaP0rn6x2KmIn2MAunMSuDUnE5j1R1GLMyiFk4LZUh0/EdzEIvZuUiyh6vWxhW3dY8gyNHjhAI\nBPijP/ojxsfHaWtr45Zbbql3WGIpUCFAoVFghOodzeKmLDACgI82o/WORswRbcbALaADsXqHsuho\nM46yx9EhKRvxdtqKoZwM2orXOxQxIwPMIPgO2pDr13zRRgzQYIZYxG1J9aVMMIKgPbQRqVsYizbp\nGxwc5Pz583zzm9/k4MGDvPLKKzN+5+Spkxw5cuSq8zQ0pFi3du1chblk9Pefp5Qdveo8M31+wzCD\nuA231zuKG4My8FK3gtagVL2jEXPEj66ESI9s0yvwY2vxo2ukbMQV+bGb8OV8eGNQCi+5Ta5f8y2Q\nwE3dLmV8NYvkXkpprXXd1n4Ve/fuZWRkBNM0CQaDvOc97+HBBx+84rxjY/kFjk6I5UtrjZKT+5Ig\n21IIsdTIeW3hSFkvPq2tiWk/W7TtsKlUipGREb75zW8yNjaGbcuAA/Xk+5qfnzzHT0/0UirLtliu\nhoYKvPzyEOfOTQJg4zBiTpJX5TpHJq7VxESJl18e4uTJWl/NyqVtWWB5b8tKxeXVV4c5fHiYvF9h\nxJykgpzzRI1t1/aPV18dwnX9a/rupFFg1Mjic23fWyp8fEaNLJNGYd7WMTRU4NChIfr6JudtHTcS\nbx7L/JfvB5aSElVGzElKVK97Wbbt8sortWuK59X32F+0j3euW7eO06dPc//999PR0YHrutPO29gY\nxbLMBYxu+Sk7NiqliRkhvKgPi7J9WMy3YtEhEDApFms3wTmjhKs8smaRhFu/59TFtXtzW5bLDgD5\nqW1ZIu4t321ZKjmAxnE0aQpYSpEzS4S9YL1DE4tAteqhtUbr2v8ta3Z15x4+WVXCUiY5XaZBL78+\nozlVxjFcyrpKkijGPLQ75PM2waB56TgWeaNW5hVtkySGwdy1yhUKNoHA0izrvFnCVT45s0jUu76x\nH8plF9B4Xu2cEY3Wr71t0SZ9t912G6dPn+Zzn/scX/3qV+nq6pp23kymtICRLV9tsRgV2yWm5eZn\nuVq9OsXwcIGmpjAAcT+CowpE9fJNEm5U3d1JTFORTNa2ZcKPkFEFon64zpHVV1NTBMfxsSxF0FQU\ndHlZJ8HicolEiJ6eJACxWGDW3zMxiOkwHh5xvTyPsbgOU9U2IR2Yl4QPYM2aFCMjRVpaZOAWgLgf\npqJswjo4pwkfwJo1DQwPF2huXnrnx7gXJWcW5+Tcn0qF6eqqXW+j0dmfM+bDou3TB/ClL32Jo0eP\n0tTUxOOPP45lXTlHlT59QgghhBBCiOXsan36FnXSN1uS9AkhhBBCCCGWs6slfYv28U6xuGitOX58\nHNf12bChmXD4xtx1PM+jr+/sjPOtXr0W05R+olczNlZkYCBHW1uMrq5kvcMR16i3N02pZLNmTSPJ\npLyv8hfZtsvx4xMEAgY339wio9Mtc0NDBYaH87S3J+jokPfzLWaZTJnz57OkUmHWrGmodzhL2sWL\nOUZHi3R1JWlrW359VGfr3LlJstkKq1alaGys76OwN+adu1hwjuNfGvjBIJer3rBJX1/fWf63Lz9D\nNNU27Tyl7Cj7PruLdevWL2BkN57JySqGYTA5WZGk7waUy1WxrNrxLEnf5XK5KlprSiUHx/EJBqUC\naDnLZisYhkE2W5Gkb5HLZqsopcjlKvUOZcmbnHzzuKhK0ncVuVwFpRSTk1VJ+sSNIRg06elJ4boe\nra03dgfpaKqNeOP0AwOJ2enpSV7qxH1j7w/L1Zo1DeTzVTo7p38UZLlqaYlRqXhYlikJn6CnJ8no\naIkVK+Rct9h1ddXOZ42Ny3OwnIW0cmUDExMl2tulIuRqVq9uIJOpTO2b9SRJn5i19mQF5TtoJa06\nAsJhi9WrG8BzMCb78eNtYMmF9kbR1BShqelSrWMli1HN4ye7QB5lBGqjmwJQGkf5Hjq+or4BibqJ\nxYKsWTPLUavtIkY5felYWrSvQq6vah6jksVPds55GQUCZu26JN7O9zDyg/iRZghefwVGIhEkkVii\no7m7FYzCKH68Hazr+42pVJhUanHcG0nSJ2bHczDTZ1DKxFMWOtZS74jEImFkzmE4RVQ1h7diS73D\nEe+ANdE7dfPlp7rrHM0i4lQw0+dQSuGaQYg01jsisciZE70oNHguftOaeoezKFnpXkCB9vAbVtU7\nnGXDmDyPUc2iyhm89q31DmdRM9NnUV4V5ZTwWjfVO5w5I9VQYnYMs1bboUAH5dlt8QuCMbTnyn5x\nA9NWBLSPH5LHdC5jBsA0a62fAXm0T8xMB2Pgy/nwanwrCr6LL2W0oHQwXts35Vw2Ix2I1u5rltg1\ncdG39H3zm9/khz/8Ifv37693KMubMhjQN2HbLiut8By/4lPcaAYHc3iepqcnVXuMKdEpjwXeQGzb\nZWAgT2NjmMbGCN6KzaC1bMNfcOFCFtNUdHbeVu9QxCLiuj4XLuRIJAK0tLw9afGb1+PLsXRVfuum\neS2jiYkSuZxNT08Sy5K2jTfpeBturHXOyt33Nf39WSKRACtWLK0E3m9cDQ2r5qysBgfzeJ5PT09q\nTpb3Ti3qo8G2bU6cOCHDZS8Ctu0xMJAjM1lhdLRY73BEHRUKNkNDBcbGSmQy5dpEOUZvKAMDefJ5\nm/7+7FsTZRtOmZgoMT5eZnCwQLns1DscsYgMDubJ5ar09+emn0mOpZnNYxmdP58ll6syOCjvcH6b\nOSz34eEC2WyV/v5JfP+Gf+X3281RWZXLDoODecbHy0xMlOZkme/Uok76vv3tb/N7v/d7LIH3x9/w\nAgGD0YTJ6ZBPfJF0SBX1UQ0EuBiMUggESCSDZI0cFWR47BtJbWQ7TawhwqFSmRNV2X6/KJUKM2wG\nGQ5FKQdt8koqupYzH5+0yvFayWMiWmvRqPfQ62J62SaDkyaYCblXmU9mAxwPuOQTMQxDKjqmEwyZ\nXEhAX0ARS9T39UiLNulzHIeXXnqJu+++u96hCKCifYawyWmHAV9uEJerkZEizx3PkGqK0LyulWKg\nSNkok7ayM39ZLBqNjRG2bWunr1zlSN8opyoFXO3VO6xFw/Y1eW3imHBeF8ibecqU6x2WqJOskWPE\nqzBGHj8UJJQMUyza5PN2vUMTv+T4+SHOFMqEO6EUDtQ7nCXt4MUxSrh47QE8aZuZ1utDI4zZLroV\niqq+rwBatH36vvvd7/LhD394VvM2NkaxLHmX0nyyHZdmfAiZdAel9my5SqdLtGhNbrJMZ1uIoB+g\nYJQI+XJxvdE4jkckVyUQdomVypip5nqHtGgUJis0eA6Fqkej9gCDALKPL1dBP0giUKbJUTQZPhOZ\nEqZpkMmUl+6Q9Teo3LhLU8DGz1t0paT1ab64rk80VyUXCJIq2JgNS6tP31xy0y4xbaOy0NRW31gW\nbdLX19fH8ePH+Zd/+RdOnz7N008/zf3333/FeTOZ+j4ju1zclWykUvGJGJJgL1ddXUmskSJb2qMk\nAgARulx5zOlGFAiYrOluoKPisXpFCiXDM01pbY2yvugQCgXpDCTBrXdEop5iRIl5UbovPZkV6U6S\nz9u0t8uN7mKzpqeJlrzNys4kAVPOafPFsgy2dHRzU8VjdWd9BydZ7NZ1t9AwUaazM1737r6LNunb\nu3fv1P/vv//+aRM+sXBWdFr4ysXQciJdrmJJj9Upg4CW2u2loLVLY+gghiR8l1PQvdbH0FKhsRw5\n5FAYWFx5uPa2thhtbZLwLUZtbTEaVzgY2gbk+J1PHZ1RHJVFaR+QxoDpNDSGiTeVMRbB+CSLtk/f\nL3r66afrHcKyp/Eom/3Y5jCOusqoZWLJqu0DF7DNMRw1We9wxHVyVA7bHKZs9qOR/ny/yDbGqZoT\nVKz+eociFphLEdsaomJexEP67N1obDVB1RylYl2odyhLXsUcxDHTVMyL9Q5lUbONEarmBFVzoN6h\n3BhJn1gMFCozBKO9GL7U6CxPBkprSF/AyF9K/H0fVRgH369vaOKaGeUKTAyA40G1BGWpzMH3MUbP\nYeTyoD2UtqBakLJZRhQWGlBKYbzZeqH1pfOcB76HMXoO8hN1jXMpU4UJcN9Zwq20hZocQmWlYnLW\n7AqUMtf8NWVrVLofVVxGg/tpXds//dlXlCpPYaT7UaX6d0VbtI93isVFVas0HOlDWRbO6gF0x8Z6\nhyQWmEIRHwlh5JMofwz3ppUY42cwqnn80gR+m+wTN5LgyAhBL4XOapQ+AUrhtW6ASLLeodWNkR7A\nKEwSybpY8dvAcTCHX6uVTdsmCCfqHaKYZyYhYu5N1M54tXpxY+IcRnkSXRhFmzGMwiRGbgI3IYMf\nzTUjcwGjMIo2LLyubdf8/WDOITwWBc/HW2uDJV0RrkprrOGjAHiNK9GJ2Y80Eh1zoZxEUcJbM18B\nLi5Gug+jlEHnh/A6tszqO+GxEhRTGNrBXTvPAc5gTlr6fN/nxIkTc7EosUhpM8DPnA7+LdNEKdJU\n73BEnVSsFGf6ymR1lDcqipfdOHnHB0NGNrzR6FgDFwZLDBRCKGDUs3jZDnGuWu/I6qeg4vQPlXnN\nbOGlvMFYRdcGuNEa6jzUtlg4CnMq4QNwtaJaqaANEz/WSCbr8HwuzktFxZBTx0CXIG1Yl1pRrv32\n9Nykzf8cCXKyGsaxImDKdWk2tFJo7aOvYZC+iYrH9zMxXkgH8CLLaCAXZYLngjG7NjPf1/xsIsqz\nY2HGg/W/d56Tlj7DMPjsZz/L9773vblYnFiE8rbPEz83wLEJdbn8WkO9IxIL7dgbI3z7O4cws1V2\n3Kpp6QKjoZ0RpeiJNEk37hvMG+Mh/q/v57GsEn/xmVvIhKJYKkLB18DlHc6151E4eRyUIr7xZpSx\ndHoGeOUyxdO9GOEIZ8sJDh6HC+eK3LR2lLGg4q6NPSSiIUJmtN6higViU8ZTVQZOOgweOcFopoTR\nFGfr1hbWtSQ46XXTb4VJpcsU2iL88vEi3jmd6sCNNIAVoqpygCKkZ9fCfvxCgQvjZf6f/xplezDN\nnk+vJtKwfJ9cmBWl8Lq2g+dgBzSeyhDWDTOO5nzifI4XfnqOc6NZdt2i+eg9CxRvnflNK/HjrTgB\njTuLshoczPGj/z7Hmb5Jen+lk4e6FzDYK5izK/eqVau4cEE6zi5VdjFPR/llOjhFuf9IvcMRC8z3\nNcOFc4QSExRVGkpF1hZHaTj/HM2ZMxTM8XqHKK7RSCZNqHGSgNGLe+Ygzc5ZkmaVNcG338A6uSx+\ntYpXKuGVl9ZLyu1MrX+GM5nB1SWyzjAt4X7cTJbOzCl07wuUCmfw5b0Ny4LGp2ANUTGzjIz2o1yH\njHkBP5lheHIEw1BEwhYd50/SPdrLKr2Mm8bnSzCCbVQomhMUzHFcZlfG6yIGpZN9bPUOYpjnyWTO\nzHOgS4RhogMhCtYwFTNHZRYDta2yqpQH+niXdxh38rnlNRhYMEI+MErFzFE2rl5WsSCEXj3KGusk\n1tjLlHR975XmrE9foVBg165d3H777USjtRpRpRT79u2bq1WIOmpqiPK7d7jkSzbvuWtVvcMRC8ww\nFJs2toBVIVK06UquJT6ZIaVcqtkcRvemeocortFdd3RTDQySytgYaMLZLC0p84p1lsHGJtx8DgwD\nK7a0hqoPt3fiVx2CkQhb25P4iQ4qVZc2q4HGkWGisQA6V0Sllk7rppiewsDQQTzlsOmWdYxbA7Q1\n+2SJkiBGLldh84YUlm+C6eAVJ9HhOr9xeQkyCV56tBqMWd6qbrypgTXlOD89FCfRGKRpdc88R7l0\nKBSGDuArB1OHZ5y/e107f/6bDbzW189NNy+jxzsvMbWFpxwsP3TV+RrbUjz0wUaeH07Tc1sLpmHV\n9cGAOUv6du3axa5duy6bpq7zLYRHjhzhi1/8IoZhcMstt/DII49c1/LEO+cRJJ/7VUyvTM7tZGnd\n9onZ6EytY8VtXQxdsJmYKDOZdVgfaaMvt4L4OZOY1AXcUMJWnO7EJk6djBKrOlhtN5O4ysMf0ZWr\nFy64BaQMg9iat0YhuHXt7Rx6aZjX+ydY2djM7cEOjNZuZLDrJezN92ddumdp8LrRaFRK0XJ3A5qb\nGR7LcfLYJK+/cpr3vGcV3R09KLuKbmqtY+BLlNaYyqLBXTXjY4a/bMhqIRndxrAdpjARIdwyTzEu\nJb4PhvHWfj/LMrc23kVoQHG8N0L3Np9odPl08kh53WjfQ82iH+Rk9y0EJhKcH2jjlu317Rs1Z0nf\nPffM/QO9XV1dPPXUUwSDQfbu3cupU6fYsGHDnK9HzMxzPCpnXsN1oHrnRuhcfjU7y9XkJIyPQ2en\nIhqNEA5UcEYO06JL5M04AdsiHU6xapV09Lxx+DiOZuCcQ+XEcSpNGSLv6gFa8PAw69xDs1SCwUFo\nbYXUgpxqfN5M6nzHpFx2iDlncUcLlCMdpIpZ3LU3Q1Squ240vm2jiwXMxrcPomDbLnapQsNgbSA6\nd/1WCNRGe3zzxndiAibH8jSFTlKZrGCabWSzZbre1SE9+eaIl8+DYWDGYlAqYp07QdXXlFdtIZ68\nequTRuPjT52zogmf0UqefDXJxYsVWlrkmP1lWmu8dBqzoQFjchxjsB+dbMDuWke57JBIvL316krX\nBVPn6J/wCDcGmZysEI0u3YFz/GoVXS5hNjQCYIwOUjjTR3BFK9ba9dN+T6MpmDBc9jBHCniej2nW\nrwJxztacTqd5+OGHueuuu7jrrrv4zGc+Qzqdvq5ltrS0EAzWTsCBQADTXD61CIuNW8pxIjvJqdI4\n+eFz9Q5HzBHH8Rgaqp2IptPfrzlxIse//dsQ/eczZM68AJlXKaZfpRobwF2Rp6N75sdBxCKhxxkZ\n+Cm9b/yMiyfGGD2X4eypEsFyhkljgjFriNwM/RTm28WLUCzCQnQTVwxjcgiDU9i2y0unz5AODLCi\nbQi7/yKv//gQuZKHqlz+jiXf1wwPF6hWpa/fQrBzWUoXL6Cv8Z2g1WNHsfvO4QwNXTbd9zVHj45x\n8tgw6YwNvgb77X3H/uM/xnnlxZc4Wz3P5l8for0nIokEUJ0Yp/xLZfpOePk89qkT2MeP4VerKLuC\nrzWvHZ/k5PEx0unp322m0YyZw4yaQ1SovSuuOXIemMB0z5LNLt0kBMBzHEoD/bjX+P43++xZnAvn\nsU+fQpWLqICFqpQ4enSU3t40w8PFy+Z/87qQNS5/l19+fJhUagKcAdraasdEsWgzNnb59xcb33Vr\n5VacfZzVY69jnzuDOzICQHowzalBm6OvjaD1lat/fHxGrUEmuIARHKYpNk42azMxUb/39c1Z0ve5\nz32O1atX88wzz/Dd736XVatW8bnPfW5Oln3ixAnS6TTr1q2bk+WJa1co26jiGFZugvMjMmjHUnHm\nTIbR0SLnzmWnnUfrIuPjBTKZNGcOn6U4OUxpOI3OFFDDozSu66GxVUY2vFFk0hOkM1UuDIwSsMfw\nx0dw+/sp5h085WFg4tW5U35zc+1Ju+YFeA2aooQigKLCyEiRi8NZymWF65WxByfIXcziphpRxQJm\n7xtg114aff58lpGRIr2911e5KWancOYM9vg45cEBtNb41ekH9/BPn8Z/42itdl77eJUSyprmwaZw\nDK9zJV7XGohdGiVSa/B9yodfgf7/JlPy8alQ8kKEIyYjI4v7pna++bZN8exZKsOD2OmJWmvqFZJx\nPzuJf/Q1/MGBaZfluS6+4wIKZRjohma8Fd347T1gWTN2E/KVj4HC923M00cZPn4MK+gyMO5RrRYW\nfQJyPUp9fVTHxsifuvyVaf7QUK3cM9Ocm5SuJYqGid+5Gr+xFW9lrbXqSgnMm9cFX9cquIwL5zBP\nHcb1x6m4FoG4yfh4LZE5eXKCgYE8Q0OFOfylc6vU14c9MUHuxPHLpvulUq3c+i5v2NC+j1utoj0f\nLjU++V2r8BMN+O3TD8dpDPThnzvN5GQeMwyuWebsmVH6+7Ok0/UZEG3OHu/s7+/nK1/5ytTff/7n\nf/62Pn7vxOTkJF/4wheuOiBMY2MUy5JWwPkUr4TYcuJHlD3Fzg/fVu9wxByxLINczqa5efrjZ8OG\nEOPjFUqlAB09eXjmP6m+dISUjqA/9BuUJl3aG4O4ro9lFYEc0AnX2BdDLIxkw030///svWeQZFl9\n6Pk716bPrMwsk+VNezfTYxlgBgb74A0IM8ATAoXMvvf2xbIfCCSkCMUSQtpVBEPwYiMUMruxCkkL\ns0ISGqEHyLwHQsMMMH6mva/q8i69z2vO2Q/Z09Mz7buru6q78xdRHyqr6t5/nXPvOefvZ2pUm0He\nNfEzpr/3A7yCy+KPwwzd+z+hW90EVfLMfK5PGEoy2f66GUhGUSyiSJJK6XRPpqm5+9BmS9jP/x1+\nqg8WxhFd/QgzjZZfQfYNEggYZLN14vFLJ/J3WBv0YADnyBHMRp3c1BRCKcKbNhPoH0BJiTs/ixaJ\nosfieFOT+E4T3QrQ9H08Hwyl3nTg8Qt5tg3bqGCUYDmLP3kaempoyQhGdoq851FNLTExPEWuEWVL\nZhPl1iDlloEVu7PzO4VhICwL5bRo7HuN+uQprJ27Sb3tIQD8Wg0vt4peb6D5Pqxmob99OPaWl/Fa\nDYxkO9mueuok0nVI7LkL1WigDuxHhYJsHY0jIxFiXcGLy4EgvVJD1VcJODF0dYKusEY17BAYs4jF\nXCzr9p0rIxIh/w9PoVyHQHcPwYFBnKUlOHYUoyvRzss4J6y5fuI4RihMLZvF933MriRoGm7Dwd33\nNNs2bcftzpwX3tnlp2nW54iuzqKsPCJXQo9Okey1YahCQE+RSrXnyTB0Wi2PQGBjnsndyUnU3CyF\n01OYoRBWLE5k82b8chnvyEFM00Zls/ipNM7CAkZvL/WFOVwFViJJsKsL96fPEnZdNj/wIHbIerNh\nwnMwFg60W7vmHHpDQbqDLWYTk2zakqDZlHiewrLWZ3zWTOlTSpHNZkmn2y9yNpu9qMvzSvE8j9/8\nzd/ky1/+MqlLmHwLhfVzld4pzD73Eq3ZKoZUvPD97/PvPvnr6y1ShzVg06YkrutjmhdfgGZnK/i+\nwnU9ogKmnvonZKnJnB0hcuI08ewqB6qTtJpBhoZPk8kEUdIHhm/eP9LhitF1nVIlhVbKM3nsMNbc\nDL4SFI8eIKqWGMZjcSnM7GyJWMxi69bbvRKChmIAgFAInMYyM/uOUf3bvyeyWsDOFaksvEIq0cQP\n9SPTfQBkMhHS6eAl350Oa0NrdZVgdy9mNYtbLdM8NQuhIIHBtiJRePYnNCZPoYfCyESU+oFXidQd\nLDuASnRRP3UCWcwT33MXerWKUypSPXQIqytJ4qMfg2oFYeioSgUtDGg6qzGQKsbJMrROHGb///kq\n933+fWT2/sIdaWRuZbNoloUZiyE0ja677sZfXSX3w3/BWVlGBkK4D+7GyxUoPPtziIdIpkcQgEim\naB4+SPnAfnTHwVAKc2IzgU2bac7NUT+0D5ldIXXv/QgBlZdfRloWmqmjPvJxxCVSe+xGC312BaUX\nkX0xTpyeY3G6jmO0UMpmevo+9uy5uOJ4q6GUorW8jBGPY3d3o3kuvgGVwy8ifJ/icz/D9RvY2QDE\nkpiVClaiC9wW1X/8Pm6jTsMOYvf2Ed26HYD6Ky/TOHgQa26OxK/9x/PuqaERqfsIzUQsTSFaBios\n+JcXs8wen6crkkd73y6gn927u/F9tW4Gw0vh1mo0T55AaQILiVA+rlehcvoI+eefw9Bs5LGjmFt3\nEFU+zZOn8GoVWo6LtCzsbJZQKkVj6iSt6RnsUgH9fR8E6xxVyqmDUgglkck09uwpSsdPsVhepjSz\nyi//2gex7b51y+tbM6Xv13/91/n4xz/Ou9/9bpRSPP3003zpS1+6rmv+8z//MwcPHuTrX/86AF/6\n0pe4++6710LcDldJ5fQMgUYTUHjTk+stToc15HKH1nBY5/TpIj09IQ7916+jLTcxfAiHq2jBCIF6\ng2Ylh0qN0GqagAdEborsHa6NZtNjtagRnJxBq7XVHic7R7K2jLIGabVcLEvHca4uf+pWRykFcpFa\nXZLIrWI3GggfbL+OMoPIwQk4J0zwTlf4fKqAQL+Ces71xUXKx49jBCzCI2ME+/qu6B6t1VUaczO4\nfg2zX+IVPWxrGzRbaKZNK5eldeIYrWPHMBNx5gMOnltHLefo+rcW6YEBms8+SzMeR5bLyGIBZ2UZ\nIxTCL5WIZFfxPRczEkbLDCJ9B6gSi/dRbFYJZp/FKC1iJWz8pSzB8Zsz5wqFJ4roKoLG9eWm1ZeX\ncctlNNPAyWYJ9mcI9V95l+hWLkdj9jTSlyTuvgftzDugpdMEN23B1zRIhaisvErjlQOU51bxKmHq\nbgM1tYIejRBEg1Mn8JSilC9gFAv0RkOIpQW0apXa/v1Yo+M4szO0GnVa+14h0N9PaHUZq68fZ3Ya\nVS1jZzKQeMMQJQ0Ns7mEl9yGn7iLoKwSKv8UpIahj+G6EikVmnZ9kSceZQQGOlefyqCUojI1hWbq\nRGgFKWAAACAASURBVIZG8B2H8qGD7YqZu3ZfUql9K43ZaZx8HpaXSNx1N8F77qdw8hlUyqO+fJz6\nwhT5hSmqAYOk2U3q7nsQ01P4uRyFl1/A8TyMeBKtUsL67OcAWDlyhMbRg8QjEeK+j3CaCKdJq+6g\nqlXM0VFIjsBqGaOVRUZHkYG92HP/SLSZh1YYXXOBdtV+w3jzWCsknihhqBhijYqE1U5PUV9cQAmd\n6KZNBNOXN07WThxD6hrK8whu24FbWIZQgZkff5fm8UWalTqRcC/i8CGcQgH/pReQhRxq8zaEJtCC\nAbAsKrUGxSOHCAhB4J578Qs5VLGINdiPSKTxE4NorWmggUqmSFRfILBcJhAW1OsGodD6KcRrpvR9\n7GMfY8eOHTz//PMIIfjlX/7l6660+dhjj/HYY4+tkYQdrgfDq5I0W6DAE831FufORkkQN2/RkBK2\nb++mXHgJfeYFNAv0JtiRMOO+Q6hSI7EnRcEK09t7H0pCJ7RzA3JOWfqhwShuI0HkeB4s0B0I5+sk\nZh3ccB/DwzFsu0YicQcU6JENEAEQAiEEI70u8U0nqJlFTBNQYJ524K5xMG+z8VDqbJuCy9Jqoi3P\nI7tSEE3gU6Olz6GQBPwJdC4c5upUqzRLBZrzC7Tyq8hIBLtSgStU+rRAAOVLdMNCDHZhD/cTbo3S\nWlzCza7CqiI4MITZbGJEoliVadxgAtsRRBcPwumXUBUNMxai1WiiexIvFMJOdhPYtp3W9GkEIE2L\n0KCGfvoEAkF3wqC33sTa1KLQLCMTw0S2XH/KymVRCm3hNK1gEbcnjOOtIueDBJNpjOC1eazq83MI\nXcPJ5QimUniVq8u30iwL5Ss0w0Bob+w9Qgii9z+Ank7hllepnjyB0A1UPofojaOyBfx8Aau7p622\nRhPgNwlJDyN3DHFcIxAJIDKDaJlenHyOVq2Gq2mY4+PYg8M41RparUbz0CHM0jKqMIi27e6zrTJ0\ny0H2j4DQUNEuxkeTLD5TwsoYGPoWJjanrl/hq8/j1Y5SU4qQdTfBxNVFPzSzWZxyEem5BLt78ZsN\nQKI8D99xrmpe9UAI5S5jRNv5p8GxcXxjCX16nmAqSHN0HFFYRFaLiEQaHZDHDuHXFogNR6k1dBBB\nzDN/rzwP13ehfwgZiyGEQBx9Dc0yaU3OoaV6EEEba3AYYYPMDCDqdWQ8xdtHNA7P5rF3pWg0+7jY\nv+Foi0itjqcKBP3x9pi2WjSyK0Tw0IVAZkaufC0CvFoVp1BAKoketK9I6dMsCxWPEx4bx4zGUPtf\npLjvVdwT07RWyoS270JzbXQEXiGPIRzCaQ0lF3Dj2wgOjeDls3jRCGpwCM938TUdf+Y04th+9OUh\njAfeiQoGEFJH0EJGbbb2xfFWjqAnekmuc4uXNVP6ALZs2dJpqXCbEunto/T+EErXibY6pfnXC625\ngKjPoew0Mjx+U+4ZDBo4jkd3/jDG3QaNuI2saeiBbrRoD3h1wrJIIJxAiY6Hb0PitzDKB9sJ/PG9\nxEMnieV/Rui9XRRXc9jP1gihI6wYWqWITMXp67v951KTc2hyHiWi+PoOAEZVgUPHs3BXCs2pEaxK\nEql+ZCy6ztKuIUqhl/YhlIcX2Qrm5f83bWkOrVFBNCr4W+8GdKCtNGqXsN6XTp4AAb7TIjyawAp3\nExq5eFPPUgOC5hsRU7KQIxhPYE1MgJQIKRC6jh4KU1vYhxEKE4xG0O57EFPXGJ2JUJUumr5K0Cvg\niiyRgT4Cu/ZgDg+SPzpJONRDyNRQc9PUXZ/qs08TSKVQywvEh/tQAjBNZGyAfO0UzbsNulQILxxf\n20PTBRD5VbRyAb2SxenSqM2VEPkoTrFIaufuK7yKi6CAohsQ2OkUbqVC15678etVAj19SAmFBnQF\nQbuMDdGMRknsvQclJa1Tp9DCIaz+dki09H3cUhFnapZYKI6ScUITJr6rsAYnaPSMEewfwK/XMIM2\n7vF92IkAmgpjRePIWJzQrjGM7jRydh6l57DSaaJ330Pt2X+j/E8/IOc5GJUqVm6J4GMfRp3jbfcD\nfaiMjR8cBiEoTy/ijddxTI3t9mGigUHAuqa5eB1jcZ66s4BXrlHSI9h7u9CuwjsX6PJp5sDUEmi2\njR4I4PcNgKadp/AV6hC14a0RxEopnMlJMHXie+89621VTgtjsoaoO2ipED3vfxRfKZLZEqHBYYxi\nAenVMFUN66692NFhUDbW+CbcbJbaKy8QGx6hMTlJ18QmCk//K82fP42ey6FFkzA2hrVrDwAykEET\nBl5mEK16ErN5CH8r5Pw6hnbx4l8CE4mDoWJnPytPncKvVdGXpomNT6DsECrVc0XjqWQOpydDCIHn\ntrCvQOEDCE9spjU1iTM/jyvmCDqKwLxDOr6ZegLi2/cQ3rWH4ssv4/z0R8Q2DWKaDbTxbbTim3E9\nD//QfoKmiRocwBAGhe9/j9ap44SrRVSpTOShR8EMI40YIPAHJyi3voe2o46w8gjfAW39jIfXvX59\n8pOfvOjPhBB85zvfud5bdNgAVKoFrPEwyoPyynpLcwfj1RG6Cd7Nq0hWr/skEhbl6QZ9ooZIBmgl\nTSrJAbS77sWP2+gKlHWbeUFuJ/wGoFBSge8SDkF4IE99UhIbDdLc5+KOTeBbQ0j7TipH7wEmnK1W\nWsZRGmQSuC+BPRhBug28vQLLPAxMcHuELktQLggNIRsoLq/0yXgXolFFxdv59ToBgn7byHupkC0j\nFMIpl0lu7yaUqiPw8C4SrrhUgcWSBkKxd0Dh1+u4KysIw8DP5zHPOdz5pTJWqpvmj39EQyj0QIDU\nf/pfaEyeRC4uE9l9F/rQMK25GSI9KQLhAJXVPMm99+FOnkL3XCrLKzQ9l2Y2h16r0Zqexn30/bj5\nLIaExUMHcIcgoEAb6L9mT9vVoGIJVHYJ0xgEJlBGjpo7jxW78oaVOkcBF0UVyTjR4dFzftoewxOr\ngqojyDcUm9OXr78gdB13aQFZr+IVC5h9GaTjkHv6x1Sff45QwMLcs5va0hKtWBddb3uI4MAg8oXn\nqB14DREIYg8NETIdgrqG2rIXLRqhcXKGZnaF1sxpbCuAZRiIWBQ7mcJNdFF97TWcRoOQaWMMjeOn\nBpFosLKC2dODCmbwgxmg3YKook0S7nXw4gFKSpHwGyjz+pp9apF+wosOrWYD0RV8k7fzsuPGArqx\nSHob+Gw9+3kwkznvd+eLsFLVMHTF7syb58RbXcWrlFCei9nTB4ZBY36e4j99H1YWiY6Mk52ZQ+QK\nBMNdWJt2YUYjtI4fpXYK4g+9l8jbHoXUKPWFeapzsxQPHyKgaahajcToKFYsRv6116iXapiFMpHu\nfoxIFL9cbnsWAz34gR6QHvhNiuEqyVCDRcPC8TzMi9S0smQPhkwgznnvzXAYt1JFT6ZQmoGKXZkz\nQbDCfHGWpgLVey+brsLp6i0t4BZyrHz7/0MkurA0jdjWrSTH4iR37kEoRWN+DpnLEZzYTKAnSvDu\n3TjJUXLPvYS7OI9eKhHuHyS9+27qUyepHDmKXF1B9vbREkFChoUmBDL6+toIzdg80YCkErXwpIvJ\nLaz0ffnLX77ozy5XarfDrYPVPcI//+QuvIDNllqncM56IcNj0FxEWjenuMbsbIkTJ3IcOnAKTRpk\nS5vpnzmGryt6t0SRiTDc/16UbV/eXNxh/bAS+GoUhQAjwEp2gKnZbkJTdY6dzDDfew/v/eR78Efv\nvaPmUYoRlBZBiTMHDmWQ1+B01uRYbRN6LcUmdYz7ZBQVidJu4n4bIHT8yBaE30DZV2ZdJ5HCT7y5\noNqV5Od0bdmKUgohCsBJFAbLy3WWlir09ETIZN5QonXRbpennzk6aMEgRjwBvofR1XX295Tv4y7O\nU3vxeaQBanYesXkrXrMJ1RrKbbHw1F/jlMok73+QcN8mmrPTCMMm/8JzhMbG8d0m7tICWm8GY+9e\nTMsgmBmkeeQIUheUF5b58ek6S9m9PDR2jC39D13ZOF0vpoW/te1Z0YBIpp9wX+aKz1ONhsv8TJlg\nsMrQ8MXnVgjw5RtjfTncbJbWwiKyUSMwNILQNHynhZI+lRPHcCJRglu34rZaaAKwLAr/41+oLy7g\nTp7CzRdIfeIThN77yXahC01Dui7NIz8g9/wLMDQIW7YRyGQQgSDOoX1E+wdo3H0ftmkQMA1Cvb1I\n26b+s2fRe/tACMygjuY0OJ4LcKTgY5g7sUSJUK1BaPguVODKwogvhewdRO8dJK3UFc2DUopjx3I4\njmTbVp2g7cNFwp/PRQjwFRc0iQjbpjU7gx6JIuz2tQqHD1CfOY3lurRaLXyngTs7jd7fT7NaQ2zZ\nQunZn4ARwHzoFyCZxKtUWPqz/4t6rY49MoK9aSuhZBJhmqh0D6G77wbbxGi6RAYHaTTruCvLCA0C\nERukh0pk+LfVMU6UHiJiTJKJpQiFLm040t7ibY0OjRAZHEYIcVUNgup1mJ3O0lIBhi4eMHAWr1ig\nNTONkUphpHtQs7NoyRTVA/twMgNY8TieUvDSC+hdKeovPoczv4Bxz32Id32YSjZH7ptPUpqaIrhp\nM4HBoXbP8FaT+Ec+juP9Hdq27WgLC+i9aZrz84QGB9CKi8hYD/uXPF6oP4TuJtht6Ojm+hoNr1vp\ne/DBB9/0ff1Mk8hQqNO363aivO8Qp3ITCAGx2dfWW5w7F6Ejg1eegH+9NJs+sXiQquswc1rntPcg\n9+Rha+446fEK+r1VxE2wfne4fpR9jpek0SCd2Mappzxmh0coD/bzynGNd3h1sG4HT9YVIgRKnGNA\nkQYnjqd5ZqoPI6Jjr0jcVgJjPoa3bRsQu+ilbjnM+HV7QK6U9kE5ic/dgEGxmAcExWLjTUpfdwQi\nljwb2imEILD5/JQRr1xCCwYJjIyhA27/CPbAADRqRLZtp3riGJXnn0edPkVxeQl58iiJvfcRLKxi\nV7LUa8tUF3I4lRp6vUE4YNMqlakuzxOSHjIzQNN1WDVd9nvj1KYmCI8OsysO61G752oM6MVii1pz\nglK1Sd9APxeLQpxIKWqOInyFkY9eLotmmejhbuyxdmqBFYsT3ryVxDsfQbcs9B170Cs15PIylSf/\nX+rHj+EohdbdjRGPUfrXH6KZFol3PAxA7dAB/FdeJnjsIKK4hEonENEo9dOTGPU6hdnTGD39xHbs\nIvi2t6NcB3X8GKJURIbDaLaFvnQMoRt4hSCOCDPnxthXeTeDIsGW8BUaNK6QK50H15VUKg6mqVEs\nRbF62s/95eiPQzwgCV5A6/PKRezhEZTrnZXDTnfj3XM/ZihEuLsb9eorGM0mzWPH0CMRWqvLOPk8\nfqvB6nefIvnoe/Cf+hvsQ/tplPOInhiqXEQvFqjmclQW5jFCYSJDQ4QfeDvi1EncmdP4K0togwNo\ny1MIXcc3LAqtCsv2ID/IbuYDRpIHfEHgKjWKa3EMFYpBgmInTgNGEpLLtRv3cnlQCi+Xwx4YIvHO\nR7BGx1n+/j+A6yCB6jPP4BYL6F0JnFoN6UuisTi6HaD8wnM4z/+c0OoipuYS6g9Tfekggd4MrXqd\nUHc3umFiKIkvJVqljL7qIJw6olklV4tS0rt4uvx+iok4911nfun1sqZ9+n7jN36DI0fazQ537tzJ\n17/+dYaGhtbqFh3WEbdviJGe43hCQwvcRgefDpdkcDDGiy/9lEz8FWK7pzEOFtB0gd/VgwrYWIUp\nXCnvKO/QrYaPg4aBOGdzTE2scHD++8Q+PsjYQoE5FUI0V6m+/COC934Y3bq+aoG3Isp1EbrG8eIC\n3X1V9EqNuCqzZfsiIjwFjsmZKkVnCykpJBIP/TpzhjYKHi10LMQNK8TUHqehoRhLSzV6es4PJQ5e\nwVCaXUn8ShmjuxszGsebPImwbcy+fmSjRcxp4aFwWi1UNIpIppG+j9I19Moq4Z4JaiuK2vIShvRR\noQjUa9QLOZRpEt48Tqq3hGOnSPQaVKRF3lml6Q3dEKWv/Ry5Fy2GczX09YVxHI9AIHrJsvBCQOQq\nbmcNDuEuLmL0vKFIOQvzUCgQ33sv9ugYtuviVSoo00CLpGisrhCIxwne/zYap07gFotUjx0jcs99\nGMEg1ug4RiiE6EmgRSyM5gpW8m3UXnyJZq2IKOaR2WWapRLOqRMEP/Ah7FwWMxSm1WhS/+//iNE6\njtGfYeyuf08g+2N+oFaoeWMc9nwOS42Hr2cwrxHL0hkcjOG6Pt3doTPz66NfRkEBCF8sRLKvH8f1\n0SJvGEliW7cTygzgH9iH88rLmApMTccWPg0pCQwPI5dXaOZWcKsVKgf205XpI5CKEglJDFlGoDBi\nUcQrz6ECAUQyQ7NaQx45iqGptmKp64hTr1J/7WkY3YbZ3c+j8e/yXChMYrSbH7RsPtZ06Itc+uX1\naaFhvmkvulr6+iK4rk+m37yitgfmwADMKfTUG/0KQ4ODdN17H86xo9jSw23UsBsNjHAI1d2DBIx0\nivrx44hQkFC6G1XNEqKCphqYzTy1V5YxilW8aplITz+hrgTuqePUZ05i7Ugiwgn0XQ/zsPE8PwrN\nkkl287Qv+F+lxFjH89KaKX1f+cpX+PSnP80nPvEJAP7+7/+er3zlK/z5n//5Wt2iwzriT/8Lu2vH\nUJpO0Jhfb3E63CT2/+w40dIT0BslXqySmT9JIFtkwKsTFX1ocRttdRrZO7beona4AC5lGvoyAo2o\nP9H+sHGMyvSX2bZSYzXSjRVUDJz8CX5snJNPLeAcaLLnfXsJZDIQvI2Kl1yC5rHD1Ben+cfRBuX4\nFD2s0Ns4xHZvjrElD/2/fwvtUB7/s5+CRA9eaDdKN6nqUyh8gn4G8wry4jYyTW0VRytgqBAh/8ZG\nE4RCFuPj16coB87JU9P33guA5iwQ6WtRN4fp7u3Gi4Rg+y7czVsQ5TKFA4dQxSVig0PodY9ws46o\nrhBePE2z2qRRruJVC0hDsbDJZOeH7mFkSz8NDBq5GaL2Pdcl88Wo6bNI0cKSSQLy+kL3hRCMjKx9\nsTU9HEbftOns91rzNFr1OMJIYFkhgqYBP/0x8aUZ/MFhePgD2OlefKGoLS+jaTqi2cBEIet1CAYR\ntQrRj30Kb2EKte8ZhDJpvPwS1ivPQX4BOZCBcoHqq/vxwxH8pQWMBx6k+d/+jtaJoxRritmwxdDm\nKOGDf82Ee4D3b0tQTv0iFSfM0fwqD3f/ypqPxZXwugdbIakYk6AUQb8f8xpzgjXTJDB+pnibUmiN\nE9hCYBZcWs/+GKNUQO3ajbZ1G3p/P4lkmnqphOyfR7bqaE4TzbLgHY8S6koQbSzRKpVozi9SnzxC\ndPE0XqOClxmmWWhSLJUwenrojkUQCwtk80VWzRCZrf9G78++Qbxnjvfe+wA/Nd5BUs2hW7uB5EXl\nb4k8LX0VTdlE/NFrGgMATbu651sPBN703L5OwGoQbhzCn2vRf9du/HoD/76HUIcP4yzP4x4+gPnA\nQwgrQPShBzGG08jsFOLVV9GOnkI3wrR+Po9XKqBpJjLdjWw0EPlZ5n2d4sQe+sa/Q1/Xz3ns3m38\nqOsD9DmnmW1tYuwmRmu9lTVT+vL5PI8//vjZ7z/5yU/yl3/5l2t1+Q7rTHH+h4SSWzCkQ8vrFOxY\nX2oI8ij6YY163pyHlIj8IlsmP0+kz+UwdyHrKQLWAhl/AU0HUxeoYAhlejdGhg7XjRQSIdo9v17H\nyP8D9ok5zKLFQmwLllMmaelkl/LQn8abfA13NkZIFZFj94J2+/aic48dQVZrNFePM2lX6Fr8V+o7\n0rhukMyUS2jVwKx42DN15M7ncF/owfvAJwAX2sdX9Pwq0o5A4PqUPnWF+UJXzxLtLKHUJX9L4QM6\n6kJ5i1IiCkuoUByCG7fQj+YsAYJgOoDzyLsJzM8h3v0+WkLDn56iHomg7FGcqo1RymFVs+RCJjUT\nYtOzmB5ENAj50DXvsrU2z5FKikoygLRfBtZ4nnwfrbAIiSYEzlRDvRVQEuGuYPenESUN0b0VfB+U\nhhGPY6TS+CNjaMk0qpin7jgYnofeP0hwaAgz2VYOZKGAMHT8U9NoK01aR/dh9PZizByn2qzT6pWI\nqInaN4PwoLg6T/DVH2HNzmFXKogGtJoBNKuKXlLofWB1CwKRFl7YoJH9N9j6K2+W/cyYy2ga7Jt3\nlhFCY83m1y+h+WVAIXUdc2gYYWroD74db2QTVEqIzAAc2I8WChPo7sMcGSY0sQnltBCBCM7xEv7R\nY0jLxpo8Rv3UKRrjcbTyPP5iGStfgNwULTS6Wi3qIkx3ZJlYpYU5CyyDf3+AiHJpei7lRp1u6+JK\nnxKSsxV/1wFRXEXpGkTb62BwOIo6lSAQ8FBWP2pgCG9iG8bSEqpRRQRCmN3diEoFPR6j8fzT6IUK\nHD2KaDoIKSnu7MFo1dBOrqJWThPSfEKOxLJMrCPPEnUa6MNgbREEQg4NI8KxIz9ndO/j61bzZM2U\nPl3XOXXqFBMTbWvy5OQkhnF9l/+DP/gDDh06xI4dO/id3/mdtRCzwzUStMtEQw2alk245Ky3OHc0\nGicRQqKUi+TGtG3QVmfQiiv0NU6w6GxFs3VaaYNYNo8FuBGdUjTDYmIXXYHxyxwnO1wpKys1HMdn\nYCC6JpuCrRIIX0dXbxxumtUnKFu9uBMpquUo6UiB2GoRK14j/I7N2CKA0SxROpDFrBjYe+6+qmp1\ntxKqVse3G+wf6+VU9jBOpJfp9Ci7dx2m6zlFtthPX2QSGuDNzOPZI3jaEOhhBBBd1BFlMNQi3ub+\na5bDmZxE5rIYg0MYF6jqdzGqVYdstk5fX4TABRNqcuhiHvDwVZRLla4PyF50VcFU53sitNUZtGoB\nVVzGn9h7xfLdbHwrg+aVkHYfxqd+CTwPTBPb85ATm+nZvovmzDTB3j78/AJNrUGouEjD80CCJkEK\ncCXEXFB6FcOUhFyPoLNKa2UJNTOLlujCuoD34GrRlqbQmhViFY3m+BiWukVSJ4SGMnsRsoGemQDt\nTDj4xz6Jv7wIiWS7lUcsBrEYXekeWrMzWD296OHw2bXNHB7Fy2YJ7dqFV6+CZaG7dejPYOezFDwL\n0WoS81sID7TiCs0jFWyvgWhBXICvuUQUBABhgl1XxHBwG0G8C9irXh9zUSngj11pC4zrGCo0wt4w\nCg+DNTKY6HGkkQAEbBpDS/RDOIoMhdCEgFj7OQrv2InZ3YMwDTQEZnc3fqOBvzhPaGILjtDhyCHE\n6Bja9ClqrsD0G3Q5RZTy8V0f6YHrQkTViMTbY65XQRuB8EqTcMKjYGj86LkfM/HBz19U5IBMoykL\nQ61DvY9KAX1lGqUk/ngUTAsVGUF/94fxm2HoHQdNQxeC1OOfpnHyKMHxLRiRCF4whCyV0T71a/C3\nTyLSefSpKeyAiWjWMAIamgK95eJrIFwICZdAxCWm2iny4XKNcLek0vT5V3+Sd778ImYwhL1z100f\nijVT+r74xS/yuc99jm3btgFw9OhRnnjiiWu+3qFDh2g0Gjz55JP87u/+LgcOHGD37hv/gna4MAeH\n7uPeuI+lXH6aeoj711ugO5owigLyBpaOV3YYZl/mqNHNU96/Y0tqhjFtBtOXoIHVF+Fk9G3E8iaV\niksqdPt6g24WnieZmSlhGBqGoa1ZnzxLveGBUiimW2FmEyk0I0bDijDnDzPUPIpmKcL9E6hAP/uc\nCWStws56E9v3b9ucTbG5h/3uPC+EIvz41D1Y4TrBoseukkbx3l4awxarz5RJksWoK9Rrr+J9+D+/\n8feBGHohh7rOYkaqXkVYJrJ2da1YpqeLeJ7CdSWbN1/Iyh5CAULZXG67F4iLKh3KDqOKK6jQxlZK\nlJXBt85Rms22MiIMAz0aRY9uxdrSLpuvf/l/I/Av/wCvPk/06HEikXlaDdDcdo1W1YRjwQGCeplV\nM87/WP0gj9RqCNNA1deoZU4ghKrmIZq6dRS+M8jABUonahpkBs772AiFMLZuO+9zPRZDj8Ug04c5\nPII68gpGtUR9x078A0eIH32FSLVC1G6n1LoeqFoDJLQcMEwwmkAFWg2wumFydIQuI8dSK84+697z\nZTwz5ip688a7nat5/fmaZxECGTzH6NBz4QqlmmkS6H+zMUoPBtHf8QgszGKOb8J+20PIVo3sqy8T\nXSgQ0ep049G0oOyA5kFTgm5AyAP3NLgm2INQ7onTJVc4Xu7lzyzFf7qM2Ov2jFsBQLSjVl6PXDHT\n+MnzQ6mNUIjonjfCuI1kCpIpzNFR3OERmn/xf+NVaqhWnaGsS7yapS6gpsBqQcsDUwOjAq0l0LfB\nof6dJFmiQj//3LWXoq+TbjZvYHTHxVkzpe+RRx7h+9//Pvv27UMIwV133UUyeXFX7+XYt28f73jH\nOwB4+9vfzmuvvXZppc/JoTdnUVYPMnDtFtcOF+ZUdJzx3iq+1GlUu9dbnDsaySZQCm5YsQVQiW5m\nB97JXxyfYlrbxjZjAXQdq09RrPYj3/VxohObiURtkkkTbXkekc/iZ4baVt4OV42uC8Jhk1bLJx5f\nwwPCObi1Eser4/TUW1RsWA6nODT0KD3GYXr7u/G2PII+eD/GXB1pZTHHexHm7VPURaFo4WCfKVbi\nRZO0jEXqzx6hr7REqS9OzhzhZHozVS9Kys3TVy6Dk0X3wT15BEpF6DrzjMfS+JHkdSvF5sRm/HwW\no+/q9q5YzCabrV/ieQki1QUOvleJSnTjx1K3lfKv9Q3C5/8LXfe9DY7sR/t//ojw9HG8JjguNBuQ\njfUhrCC1cIz9sb3owyOImVcwghLlFsDsuvyNLoFM9UNX3201rtdEMISY2IKhWqAkcrlEINZDpK8H\na34K6+RBbL+F11LonotWzFGV7fYGXguaBbB8oAbmB12y6R5qsS5my5vQqicQsoEf3gJ6oDPmALoO\nQ6NvJIfUaoQ/92uEf/JDgvNTGG4FS2nEGi0CzRqOA00fmjXQG+2xbj0HzU/Z5MNpiloPY/Yivqzb\nZAAAIABJREFUWvUEMrJ5Pf+zC2MH8TafUeSuUckSQmANDuG/54Mo6aF5DuF8FvO1n6O5eYKGhlVr\nIl2ouKBaQA7050E9DNWuBCWzi21ygURiJ2bsytuwrCVrpvQdO3aMwcFB3vOe9wBQq9U4ceIEmzdf\n2wNQqVTOVv6MRqOcOHHior/b1RXCqC1AIASiCclbO6F+I9JswlyuH8ts0Zy7gxfLDcONWyxEYRFZ\nnGOZI/ww9Shj5QZzYoiu5gpFEaf0nofY8l9+h0TqjTAdkc8ipETL55Adpe+aEEKwfft1GFSkRJ87\nBCj8gR1t0+xbWDJepTYWpv5DHVc3WRQDmKUax7u2MHLvLpK9mwn0xUlFgmhamlDo9lH4AHJagZbm\nEpA2KZnAkkFYjJCQC/Swn3ljmMNWH8/Jt7Fbvkj5eJSHSy+1U1F0kINjWMeewxvfjuw5U7xoDQ6P\nWjCINnD1la6HhuIMDd2ctgu35SFZ01A774Ute6C7F/m9v8J65VmM5RxuFfSjkuV4DwtOhki6gqEb\n6EkLgUK28sjrVPpel6EDoOv4W+8GILjZRzt6GHt8qN3EO9aFefBVhPTQ/vUfMGYmic5P47TqNM54\n+WwT3AZEflRl9XMpTlTH0UMS4RUQwkS4BZR+xgvcGfM3oYfD2L/wGdQ9D2DV8siVefy+CcyDz6N/\n9y8IlpaxAceBahYsE/QS5E/HyG1OMRMcZfviEmKsAMoHsQEjf9ZIwbLvfxCtpxfNtjCqOcS+h9Ec\nF82vY337z1CLc/gKarW2l1Qsg3YcltNpTvibGWjsJ7IpBvZNWrffwpopfb/927/N3/zN35z93jRN\nfuu3founnnrqmq4XiUSoVqtAWwGMxS7uFi4U6uAn0Bp1pJ2E1co13bPDxUnv+CDVpZcQrk1uZ2fB\nvJ3R6kWUEHiqQSLn0OPM4DVdVodDHHzi3/POzH+gy3hz6KGfGWorfBcI7elwk3AaCLcBmo5olFGR\n85XvMh6Lc3twHlkgdqCO/Vye07VxFvp20vyFTxM40+02cpnS27cuAtot6gFYXKgSzyWIOSkam+IM\nJ/OI0n5eXX6Al+r3kpqqsXN4jsFAAG1iM/Ijn4dkHFEvrec/0WGtMU38d30YbecuZHkVDr5GoNDA\nnfs7yu4OAk4FN9d+n/zQMForjwx21robhdB1AjvbkV3emRA4b3iibdTauQW3WsfvGUeYOuazT2M8\n8yOKroOjt5gxczh5hTaqESnmkIF7EH4DZfeu83+1sTEzGchk8JXCF+2mLeqR99L6xf8My/OIgI0Q\nitC3v4W77yXKqkIwW2B+9EEG0rN8Vt2PDAxtTIVvDdFME3tT25klGUFuvwd8D/30y/gPPYRfc8DT\nMY4cQr78M3JTr6FZFVaaKUK9DXpzMbCuPG97rVkzpU9KiXlOGJBlWfi+f83X27t3L9/+9rf50Ic+\nxM9//vOzrSAuih5CRq4/sbrDhfmPD7+Xrx/PY+Gxt/f6w4U6bFz89AiitMRQ+v187r5lnnouTWvX\nFNWPpAnTQ6yZgbcW7EwkOx6+9SYQRiYHwPcvqPABDFn3sDtu8lL4MFOPV1kY2kzrJ3uJPPwfsMYV\nt0z1wGskJRO0ZDu8E9rhkcu5Eg8MfoD4yAMczr/GwZRHOl7Fbth84n/fy7s3fRAncOYg4zpohXlk\nZA08PB02HDI5CNJHvvsX0GNpYoVdLM0doBxM8JnwmUx2M4k0O2vdTeMcD42fHkErryL7t4HdLghi\nfvTT8NFPYwF16WCefpaKcYyUscL77EdQgcxtvqqtMed6xISAZBqS6bNjqP/2/4EOmJUKJ48+iZaR\nBKXLvXvejrqNKz1fEt1ApscQTh21dQRDCIwHH4Zf+Z9xKyWOzf83mlGBKT0ei//imnkdr4U1U/oM\nw2BmZobh4WEApqen0fVrfwB27NiBbdv80i/9Etu3b+8UcVln+sw4D+/cRkO5fEhsXW9xOtxI7BD5\nTBBNeHzkbdt4364uysZuptyTBFWIpFyfsIQOl0d2Xdz74OHgGFV2bh+nmwmm1RLv3ZNi25ZRdFMS\nvgP2a4EgcE5BhVBMY/geBfgk/E0M9O4kxDzT7gp3BVLs9N9ikTWtN8I6O9x+aNqb5vedXfdRTksa\nrs4H9IHb3Say8QlEkIGLF7gKaRbbNm2hZvoUaxE+o12g2EyHNUGLRvno29/Ba84yY6of605V+M6g\n4j0XXB7MaJxP7fggP+VVEm6CzfqNK8B3JayZ0veFL3yBz372s7zrXe9CKcVPfvITfv/3f/+6rtlp\n07Bx0BBsWk3SdCXhPgs6EZ53DN0h6CbGWGsvJ2fy5JoNEhM2un5jHwLflzf8HjcDpdpbwXr15TlH\nEvL5JpVqi81d40yEMgSEAddXePK24yH6uc/sxfYvvz1mszVyuQYDA7HzQmKlVGjaes95h6ul0XCZ\nmSkRjwdI9AneKTbhWz5dTgglbn61vQ7nU606zM+X6eoK0tPz5jYIEWzucSYIW2FseWcrItdDreYw\nN3fhMX6dYZkipYdJkuRC7T3vRJaXaxSLDYaGYoRC7T1hRKYwtE3YlgnXHgC5JqzZierRRx/lm9/8\nJjt27GDnzp08+eSTPProo2t1+Q7rjNuSHPyRx+RPFUvTrfUWp8MNJuH3Eve6icg3wth8V1JabtFo\nuKys1G/o/U+fLvLKK0vMz5dv6H1uNJ4nefXVZV59dQnHWd8m9gY21dMhtFyS3JJLYO1sfrcsBiZd\nfoYuvxfzjAdQQ2Bf4dgsLFRpNn2Wlqpv+jyXq/PKK4scObK65jJ3uLEsL9doNn0WFysECNPl9RIp\n9fLaqyvs27eMlB1333qztFQ9O0dvZeW4xtwr0Jhfh35wtxFLS7WLjvHrGIUEiy8LJl/r9G5+ncXF\nypk94Y22LqWCw+KLJksHDax1trKu6a4/NjbG2NiFQ18ef/xxvvOd76zl7TrcRDRNEA2GUEoSDt+Y\ncvIdNg4CDYvAmz4zTZ10OoTjeHR339gNtdn0sCydWm19FaXrxXH8M714oNXysaz1VbT6e7ooFhsX\ntdzeiRhce4XS3t4I+Xz9vPFsNDwMQ6PZXGezboerprs7RKPhEo+3D2cWNpVmHU1rG3F8X6Ld4aFs\n601PT5j5+TKJxPkHaKclCWphGvVbe+9Yb3p6wjiOd8Exfp16TWIRxHX9dek5txHp7Y2ct8fW6y6W\nbuE11t9gdNNOIJ7XeQFvZUxT513vGsFx/M6B8Q5mbCxxU+4zPp4gm731lZNQyGRsLI6UEI2uv7Ek\nk4mQyaxvTsHtRG9vmN7e85/RgYEouq4Ri92uVVBvX8Jh67zWKalUCN9XWJaOaXYUvvUmFrOJxS7c\n3mZioot8vnHB97LDlRONnv8evJVMJoIQ7X2uo/C1udAe298fRdM0otH13w868T0drph4wqTzyHS4\nFhQOgitf8CzLoL//9ui3mUxu7DAjhQR8xHV4vG5X1JkyteIq1z0hREe5vo1QOHT3hBA3sD9qh6tD\n4QDmeXMSCNw+e8dG4mJ7eF9fZ527EOc+nxtpP+ic4DtcEQqJYxxFKYnpj6GzMR7gDhsfV5tFagU0\nmcSUg+stToe34OrHUbgY/iA6nVYEr6PwcIyjoBSmP4HGxlbeO9wYPG0JX1tBkzFMObre4nQAPLGK\nry8hVADL37ze4tz2uNo0UiuhyzSG7F9vcTY8Z9cMFcX0N1a151u/NF6Hm4QCJRFCY93LD3W4tRDe\nGS9SJ8R7I6KED0JHic78vBl1pvKqhuqseXcsbW+v0Xk/NhLCB3Q6JSNvEmf2cIW73pLcEpxdMzbg\nmeemefruuuuuq/r9v/7rv+app54C4POf/zyPPfbYjRCrwxUi0DH9CRQeOrH1FqfDLYThDyNFEU11\nvEgbEdPbhBJNdNXpv3guAhPLn0Dho9MJF7tTMeQAUgXROu/HhsGQfQhlI1Qn4uhmYPijnT38Kmiv\nGSGE2nj7xpopfU8++eR5n0WjUfbs2cPo6Chf/epXr+p673znO/nMZz6D53l8+tOf7ih9G4BOeFOH\na0Ggo6vUeovR4SJo2KDWv8jMRqSz5nUQiM76tQHROwrITaOzh18d7TUjud5iXJA1U/qeeeYZXnzx\nRR566CGUUjz//PPs2bOHb3zjG3zhC1/gU5/61FVdb2BgAABd1zGMTurhhmByEpwmbNoCnTnpsFbM\nz0K5DMOjEO5UXLsgrgunToAVgPHx9Zbm9mdpEQo5GByGaCey4Y4il4WVJejpg1R6vaW5c6mUYW4G\nulLQl1lvaTqsrEBuBfr6oWtjKjS3FK/vMQNDELt5UQRrdnIXQvC9732P/v52kufi4iJf/epX+du/\n/Vt+9Vd/9aqVvtf5q7/6K973vvdd8ne6ukIYRqeM8o1EOQ6erCFCNppokevUAOqwViyvgKFBdgXC\nGyvpecOQz4HTgmoVhobA7FTavKGsLAOqfdDpKH13FqsrbSPL6kpH6VtPVs7Mw8pyR+nbCGSXwfMg\nu9pR+taC1WVQClZXb02lb3Z29qzCB5DJZJibm6Onp+eSnrpsNssXv/jFN33W09PDN77xDfbt28cz\nzzzDH//xH1/y3oVC/fqE73Bl2DFwHBAXb9bZocNV09/ftur2djb2i5LuhmoFuqyOwncz6B+EfLZz\n2LwTyfTD8hL09q23JHc2fRmY9yDZUbw3BJmBtiGksyauDZn12WPWTOlLpVL86Z/+KZ/4xCdQSvHd\n736XZDKJ7/uXbNqYTqf55je/ed7ny8vLfO1rX+NP/uRPOk0fNwjewAiegkCn5usdh6+g5UPoRjh4\n+zKdjeRy6DpM3JjS5DUPAjronWX2DdLp9tctjFJQ8yGsQ2cLvQriifbXW6h7YHfek5tHOAxbtl3T\nn7qyvWcFOgFga0dX8oIevoYHptYO1rnVWNe9b532mDWbpieeeIJDhw7xkY98hI9+9KMcPHiQJ554\nAs/z+NrXvnbV1/ujP/ojcrkcX/jCF/j85z9Pq9VaK1E7XANSwf6S4GBZo+istzQdbjYHyoIjFY3V\nzmt4W7HcgqMVjYPlzkn2dmOyJjhW0Zisdeb2ellpwZGKxoHOe7Lh8RXsL2scLGuUOx0Gbij5Fhw6\n814otd7SXB136t63Znb73t5e/vAP//CCP9u6dSvf+c53ePzxx6/4er/3e7+3VqJ1WCOUEGiqrQB2\nuLNQCjTR3lA73D74sj2vt9qG3eHySNpz2+lkdv103pNbB6XaX6IzXzccSbtb4q04zvLMO32nnWdv\nWjWOb33rW1el9HXYWGgCdkUlLR9i1npL0+FmszOqaPiKeGfubyv6gxDWJcFOGNRtx0RYUXAVXZ0U\n0OsmE4RQ5z25JTC0/5+9O4+S67oLff/dZ6q5qqtntbplSa3ZtmR5ShzbMQGSQEICDmASm9yVCwQe\nXKbwIIEb1np5sB4B8u5b8Fgvd7234N5kAbnJvUkWNwkEQhIwcTzPljUP3S11q6fqru6az7D3+6Nk\n2bIlqyVVd7W6f5+1tGRVn97186na5+zf2RPcmNWEBjKy3tyy6o6BpzSx63AI+Xqt01IlxJLF7OYf\nsf54dvOPWHskkV+bLAVd8tm2jNST68d6a8i30/XcCbAe6/R1OPVSCCGEEEIIIcRSSdInhBBCCCGE\nEGuYJH1CCCGEEEIIsYa1bE7fW9/61je8ppTiscceA+DTn/50q95KCCGEEEIIIcQStSzp+/KXv3z+\nvxuNBt/4xjew7Vdn0+7evfuqyv3lX/5ldu7cyW/+5m9ec4xCCCGEEEIIsd60bHjn4ODg+T/Dw8P8\nxm/8Bg8//PA1lXn48GF830ddb2vBCiGEEEIIIcQqsWxz+sbGxpibm7umMv7mb/6GD33oQ5jrcedH\nIYQQQgghhFgFlmVOnzGGIAj45Cc/edXlnThxgq6uLrLZbCvCE0IIIYQQQoh1aVnm9DmOQ3d3N45z\n+eJnZ2f52Mc+dsFrPT09pNNpfv3Xf50TJ05ctox8PonjyG6cK2lmptTuEIQQQgghhBBL0LKkb3Bw\n8Kp+r7u7m7/+679+w+s///M/z+/+7u+ysLBAsVjknnvu4fbbb79oGfPz1at6byGEEEIIIYRY61qW\n9LXaX/3VXwHw5JNP8thjj10y4RNCCCGEEEIIcWmrNul7xZ133smdd97Z7jCEEEIIIYQQ4rq0bKt3\nCiGEEEIIIYRoP0n6hBBCCCGEEGINk6RPCCGEEEIIIdYwSfqEEEIIIYQQYg2TpE8IIYQQQggh1jBJ\n+sTSaQ1R1O4ohFheWkMYXvha4LcnFrFy5DNeWy5Wj0VTFDXPjxDLQereylviOV+1WzYYY/jTP/1T\nDh8+TC6X48/+7M/aHdL6FkU4Lz+HMYZo+x5IptodkRCtZwz2wechDIi27oJsDuvsaaypCXSuE71l\ne7sjFMvAGh/FmplEd/agN21tdziiBexDL0AQEG3dDtl8u8NZPaoV7GMHUUoR3rgfbLvdEYm15CL3\nULHMXn/OezKXPHTVJn3f/OY3GR4e5hOf+ES7QxEAOsJojbIsCIN2RyPE8jAGFUVg26jAxwD4Prge\nSnqC1q5XPmO/0e5IRCsYgwojcGxU41w9Fk2Bj1IKozXoSJI+0VoXu4eK5fW6c/5mVm3S9/DDD5PP\n5/nwhz/M+9//fn76p3+63SGtb65HNLwLdAjZjnZHI8TysCzCbbtRfgOT7wJAD23BzM1gpLdgzdI3\nDGMK05h8d7tDEa2gFOH23ah6DdMpn+kFcnnCG7aC5YDrtTsasdZc5B4qltkVnPNVO6dvdnaW4eFh\nPve5z/G1r32NQqHQ7pBEJgu5znZHIcTySqUvvHBaFqa7DzxpIK1ZloXp6Qdn1T4HFVcqmZKE71Jy\nnc37uRDL4fX3ULH8lnjO236Hm52d5WMf+9gFr/X09JDJZLjjjjuwbZv9+/czOjpKV9fF/4fy+SSO\nI0MUVtLMTKndISwbozVjY6OXPW7z5q3YMjRGCCGEEEKscm1P+rq7u/nrv/7rN7z++c9/nsOHD7N5\n82aOHj3KQw89dMky5ueryxmiWGdqpRn+05dmSebOXvKY6sI0f/4772d4WBb2EEIIIYQQq1vbk75L\n+amf+il+93d/l89//vPce++99PX1tTskUZ1HhXVMdkO7I1l2yVwv6fzGdoexqqjSFMayISVDpkSL\nLce1pV7CaiygsxtBqdaVK9YFtXgW48QgKVMarjuNClZtDp0dAEtG41yVV66fmQGwVu1MsOtLdQ4V\nNtrahl61SV8qleIv/uIv2h2GeIWOsAvHUZZFpCxMRpLwdaU2j71wurllh5cGN97uiMRasUzXFmf2\naLOxYjS6Y1NLyhTrgyrPYJfOYnRIFLsV7FXbVBIXYReOoTCgQ3TnlnaHc106f/3UETp/Q7vDuf5F\n4bn7nENku5g2PTyXK5lYGmWB40EUYNxku6Npu6XM+1tTc/6cJKCaNwHbbXc0Yi1ZpmuL8ZKoRgXt\npVtWplgfjJsEY8D2pKfoOmTcFKpexLiyn/DVal4/y2hPzmFLWHbzehKFGCfRtjCUMea630ZjLS8q\nsuoYc8FQqedfeIGnn3nmTX+lp6ebm/bsXu7IlmRsbJT/9KUXSOZ6L3lM4cwhEpmuyx6DiYinLz70\np16e4/c/+k42bbr2J2Qyb1CsC6+7tqzaMsX6IN+d65t8ftdOzmHrrcA57XmTzdkl6RPLRy4Y17Uo\nihgZOXnZ49ZUj+alyHd57ZPPeO2Rz1SI9pC6t/LOnfM3S/pkeKdYGq2xD72A0ppwx40Qe/M5Xfax\ng6hatbkJrOztd10aGTnJb3zma2/a47keVjFV02exz55B57vQm7a2OxyxDKzJM1iTE+juXvTg5naH\nI1rAPnIAVa8TbtkO2Vy7w1k9GnWcoy9jLIto9z5ZpEO0ljHYR15C+QHh1h2QvnQCIlrk9edckj5x\nzcKg+ce2UbUK5jJJn6rXwLaxKmW0JH3XLVnFFFSlDI6DqlXaHYpYJqpaAddt/i2uf8agGnWwLVS9\nipGk7zxVq4CieT+PQrC8dock1hKtoVEHy27WPUn6lt/rzvmbkaRPLI0XI9q0FRVGmI6uyx4ebt6O\nVVlE963vhEFc//TQFpieQHf2tDsUsUyiwS1Ys5Porkv3aovriFKEm7c1G509/e2OZlUxHV1EQYhx\nbHAl4RMtZttEW7aj6jVMt6zyviKu4JxL0ieWLt/NkieAZrLoTHY5oxFiZTgOekCW/F/TPE8+47Um\n24HJdrQ7ilXJ9EhjXCyjbB6Tzbc7ivVliedcBnMLIYQQQgghxBomSZ8QQgghhBBCrGGS9AkhhBBC\nCCHEGiZJnxBCCCGEEEKsYZL0CSGEEEIIIcQaJkmfEEIIIYQQQqxhkvQJIYQQQgghxBq2apK+6elp\n7r//fvbu3YvWGoC//Mu/5MEHH+S3f/u3CcOwzREKIYQQQgghxPVn1SR9HR0dfP7zn2ffvn0AFAoF\nnnzySb7whS+wc+dOvv3tb7c5QiGEEEIIIYS4/qyapM/zPLLZLADGGA4cOMCdd94JwNve9jaef/75\ndoYnhBBCCCGEENelVZP0vV6pVCKdTgOQTqdZXFxsc0RCCCGEEEIIcf1x2h3AxSilyGQyTE5OAlAu\nl8/3Al5MPp/EceyVCk8AMzOldocghBBCCCGEWIJVmfQZY7jpppv4whe+wC/8wi/w6KOPcsstt1zy\n+Pn56gpGJ4QQQgghhBDXj1UzvDMMQz7ykY9w5MgRfuEXfoHx8XFuv/12HnzwQY4cOcIP//APtztE\nIYQQQgghhLjurJqePsdx+NznPnfBa3v37uWjH/1oewISQgghhBBCiDVg1fT0CSGEEEIIIYRoPUn6\nhBBCCCGEEGINk6RPCCGEEEIIIdYwSfqEEEIIIYQQYg1rSdIXhiH3339/K4oSQgghhBBCCNFCLUn6\nHMchmUxSr9dbUZwQQgghhBBCiBZp2ZYNmzdv5md/9md597vfTTKZPP/6Qw891Kq3EEIIIYQQQghx\nhVqW9EVRxLZt2zh58mSrihRCCCGEEEIIcY1alvT98R//cauKEkIIIYQQQgjRIi1L+rTWfOlLX+Kx\nxx4D4O677+aBBx5AKdWqtxBCCCGEEEIIcYValvR95jOf4dChQ3zgAx/AGMPf/d3fMTIywic+8YlW\nvYUQQgghhBBCiCvUsqTvkUce4atf/Squ6wLwnve8hw984AOS9K0h5bJPGEZ0dCTaHcqS1WoBtVpI\nZ+f1E7NYWxYXGwBks7E2RyJW0uxshXQ6RjzestusaKNisYbr2qRSXrtDEW8iDDVzczV6epIy0mwF\nzM3VSCQcEgm33aGsaqvlftDSd39tBZPKtraEoebw4VksS7FlC+Tzqz+JMsZw6NAsSkEQaPr6Uu0O\nSawz9XrA0aNzKAU7d3aRTkuDcT2YmCgxNVUBSuzf39/ucMQ1mp+vMTKygNaGffv6cJyW7HYllsHR\nowV8P6JcDti6taPd4axp09MVxscXMQb27++Xdv8lTEyUmJ6uYEz77wctS/ruuecePvrRj14wvPOe\ne+5pVfGizZRqJvJaGxzHbnc4S6KUwrIUvq9xXbkYiZVnWc3vnTEG25bv4HrhOBZhqNv+VFe0huPY\nRJHGshTSrl3dHMeiWg3wPEnMl5vrWoShwXUtSfjehOtaBIEmFmt/21kZY0wrCoqiiC996Us8/vjj\nANx11138zM/8DJa1/BVvZqa07O8hIIo0Whtct/1f3KXS2hCGGs+7fmJeLU6cOMbv/X+Pk85vvOQx\n5flxPv2Lb2V4ePsKRnZ9CUMNIL0D64zvRziOdT7xF9e3IIiwLIVtSz1ezYwx+H5ELCYPXFaCXOeW\nZiXPU09P5pI/a1mtsG2bBx98kAcffLBVRXLmzBkeeOABhoeH8TyPv/qrv2pZ2eLK2baFfZ3lTpal\nJOETbSXJ3vok15215Xp62LmeKaUk4VtBcp1bmtVynq65ZvzJn/zJBf9+pYvXGINSio9//OPXVP7d\nd9/NZz7zmWsqQ7RIFIHW4K6iCbth2Bx7er1lo0JcqSAAy5Lv+kowBnwfYrL4zrrUaMhnvxo0GuB5\nyJjaVULqReu06R5zzUlfMpm8INF7rVaM8X3iiSd46KGHeOc738lHPvKRay5PXCWt4cXnmn/v3A3p\nS3cfr5hyGY4cBGXBvv3SGBZrV2kRjh5uJn37bm3+LZbP0cNQKsHAAAwMtjsasZJOnYTCDHT1wJat\n7Y5m/Zo4AxMTkM3Cjl3tjkacOAbzc9DXD0M3tDua69+xI7C4uOL3mGtO+n7t136tFXFcVG9vL9/6\n1rdwXZdf+ZVf4a677mLnzp3L9n7iTWgN2oBlN3scVoMobCZ8Rjfjk6RPrFV+0Pyua9N8QiiWVxiC\n6zTPu1hfwqDZuxSF7Y5kffODZh1cLe2N9c73m/UikHrREsG573fDX9G3bdnA52q1ymc/+1keffRR\noLma5y//8i+TSFz90v6e9+ry5j/wAz/AsWPHLpr05fPJ62ZFyeuZztwJvo/V2bk6Fs/JdcDWYXDc\n1TXkVIhW6+oCS4EXk4cbK2H7TigWoaen3ZGIlbZ1GxQKzTon2ueGzTCTgg7ZdmFV2LGrWS+6u9sd\nydqwYxfMz6/4PaZlSd8f/uEforXmk5/8JMYYvvzlL/MHf/AHfPrTn77qMiuVCqlUc2+1Z599lg9/\n+MMXPW5+vnrV7yGulAurIeF7RUe+3REIsTLyne2OYP3wPOjtbXcUoh1sWz771UAp+RxWE6kXreW6\nbTmfLUv6Dhw4wNe//vXz/77tttt4//vff01lPv300/z5n/85nudxxx13sHfv3msNUwghhBBCCCHW\nlZaua/vanrlq9dp73+677z7uu+++ay5HCCGEEEIIIdarliV973vf+/jgBz/Ie9/7Xowx/MM//MM1\n9/QJIYQQQgghhLg2LUv6fvEXf5GdO3fy2GOPoZTid37nd3j729/equLFKqCpYFSAbVaHw8IQAAAg\nAElEQVTvxGpNA6PKWKYTheztI8TlaOoYVcU2Mmfw9SLKQIRNrt2hiDYxaLSaQ5kcFrJg2GpgMGhV\nQJkMFrJv3HIzhESqiG06Uch2QZezmq8ZLR3eKcMx1y5DSGCfbC4bH7FqE7/QPolRBlsHOLq/3eEI\nseoFzknAYKIQx8hE/VdofEL7JCgbQgubVbA3qVhxoTWOscpg5vGi7e0ORwCRNUlkzaPMLF4ke/gt\nt9Aew6gGRpdx9eZ2h7PqhdYExiqtymtGy1L2D37wgywsLJz/9/z8PA899FCrihdtZ53fE0+Z1fXk\n4kIOmBCMd/lDhRAoY4OJVnm9Xnnq/DXPoFbZ01qxchQuxoRSP1YT44IJUa3ttxCXYhwMAUp6VZdk\nNV8zWlZjarUaudyrQ2Dy+TyVSqVVxYs2U1h44W5Ar+oLrRttA6JVHaMQq4kb7UDqzBspHLxwD2BQ\nyN6I65Wj+7HplvqxijimGzvqAKmXK8LVmzB6gzz8WiJH92HTtSqvGS3r6dNaX7BiZ6VSIQzDVhUv\nVgGFtSq/xK+lUKs+RiFWE6kzl9a85knDcr2T+rH6KByZt7+CJOG7Mqv1mtGyqH7sx36Mn/u5n+ND\nH/oQxhi++MUv8r73va9VxYtVQZ/7szq/zMvPB2TYqFjLfMAFaUy9TkjzGaksYrB+BTR7luQ7sPoZ\nmp+X3K+X33pvFy5VRPN72d7z1LJ3/6Vf+iV6e3v57ne/CzTn+P3ET/xEq4oXbadR1vNAiNG7Yd0t\najCGsiYxJg9mdU3MFaI1zqKs02DSGLOn3cGsImWUdRCwMfoWZEjZejSHso4BHkbvb3cw4nLUEZRa\nwOhBYGO7o1nDNMp6DojWabtwqcJz7WeD0TcCybZF0tKU8/777+f++++/6M8+9alP8alPfaqVbydW\nlMYvl4lqIfEuv93BXLvauaHIiaVVvjBq4NcsUkkfs4xhCbHi6nWIQki90svXHJZfLvskky6WtT57\n/UqlBqmUh2X5gA1BAyrzkO1ud2hiuUURqrSA6WhuY+L7NSKtSCY1zaf167NOrEphCNUyZF9dUbxa\nqRFPuFgqaGNga1RpEWJx8DzAUC77JBIOlloD7cLlUCljrJBS5JPNejR7oNtnxfoZn3/++ZV6K7EM\nIt8w8uXTYHz63rGb7KZ2R3QNalXsoy8DEO3aC7HLr0h14KUUUdRgaGiQ3lataq8jrPIkOtkFTrxF\nhQpxBcIQ5/BLmKCK3tiL2TAAqoOJiUXOni0Tj7vceGNPu6NccSMjRQqFGum0y84hBSaDNdJARSNE\nfT6mb6DdIYplZJ84jKrX0OVFgg2bePFFBWTYvr2PXO4yCZ9fRTWKmHR/c/VX8UZ+BdVYwKQ3gLq2\nBNo++jIqDNB9G9B9G5maqnD6dCeOU+GWW25oUcBrhNGo8iQmngc3ccW/ruZmsU+PgFKEN9/KxNkq\nZ8/24XkRN9/c1fp42yn0sSrT6HQf2Fc5n7G0iH3iCKfHikz2DZLvTbBlS3v3fJVBuGJpooC5s08R\nWRG9C/uADe2O6NqYyz+tVcWz2PPj6GwP+GCpLMa8WmXGxxdRCjYMpKmrBTyTxg5BVQuYdC9Yr97w\nQ0JKVomEThCnmeBZ86ew/BKqNkfUd/MbQ8SwYFVwtEMaSQpF652dqhDOTtBdP4jbyFCpbiY28Ba0\njp3r4Vuf/dozM1UKhSpueYax6EnSpOipDoPrSEP+OmRNHMZqVAj7t0Hi8o2uQPkYKriq+cBDExL6\ns8yXMhQKit7eFOn0xeeL2YVjKDQ6aKA7t1zwszJ1Qiskp1PrchESoyMWp58jMXWEZOd2dBSgO16X\nmBmDKk9jYjkaXohC4ZF684KDABM0e5oirZmjSmUuZGctJJFY3wuQGAyLU88R8wOSTgKLCFOZJerf\n++pBjQrKr+Jn0oTKJ2EuXkeMpZqjQnQEQM2uMhmUceeT3HijWVOjQqLxJyhVRkk5vVg73vXqD7RG\nlafxkwlCl0ueK6DZBtQhJmxwulalthhjy6WPXhGS9IklKftFSkOz6EbEiH6Zfdza7pCuXiJJtHsv\noAicGFEIcQcIA7CdV588FmfQ83PYZ0bYbaWZiNs0cvuZ12UWJ09TerlEkN+G5x8lnooo9w+Snyhi\naR/dKKN7tp1/y0VrEd8K8FVAPDqXwLlJTG0OE8sCUChUiSJDb2/zBldSVcpWHa0MycjDkgUERAvN\nFSo8//1nGV54jMn6SWZv3YaOdZNQh9k2eCuZTP6SDdu1bCFaoGKPUA4Vp5LHSc6PsXlkgvRgAu/W\n90Em2+4QxWWYMMSEIVb83AO2RhksG6u2iD6X9BnfB8dBKYU1fgpdqaBv2I49f5ZKssjkpk78VJye\nWsSg+xIzhUMUjz4JXQ/SaITs6YkwDR82XjjsxbgJqBcx3oWJikYzZ5ewlMIyFlnTvnk9K0lXq6h4\nHGVZlEyJKhWqGZd4vYju3PqG463CCM6JF2nYAeX9e8GxyJkhHGJw/CDKsTFD28Buzq2dGe7APXiC\nbBHo7sfkypwcOU12IMfYeJGd29bfSAVjDKZWw0omWaRMxZQox23iDQ9FgEmkXz24WsF77h8Jk0kq\nWzswXQNYZ8eJV2yijl6sjjxla5GqVSGVz5D1FCqysGYnmM3VOOlPsCPfzdRUhQ0b0pcO6jqhazWU\n51F0fCJH47sNugCiCJTCmhvBqi/QKIxgTJp611biuWE4fhAsBZt3nn/gb1yHRWeW8fwYE1EAHkSR\nxrbb15aTpE8siT9doPPQOCoIqfiHYF+7I7pGsTjRQpGTB48RJpNsTx8nPTeFtnsJM11E2X4Ym8U+\nfpAwmaQ88Qy+0pgXn8G6oRM3mULZWdJzZ8jEyjRqDQ7ZA8RMB7uDsySTFzaWEzqBr0Li5tUeO50d\ngExzCFC9HnDyZBHHUbiuRT6fIGY8DDU8HEn4RMudeeQFct/7DpnjX6e+MU66XObovZ3U7WEGkjW6\nc+tz7lqtMIb19MNkzkyi1VnivQ2CqsI//RyJ3huJtu5qzmkRK84Y0+wJsi5yPdQaa/xxVEITnKxj\nVJZoyxa041IvK7yMi8r0E40dxVTLhKUQ5bkkPQ1PfR8zW8Rs2oa17QZcM0EpoeHQBFMHz1ArLOAO\nlmh4ndi2T38qxtjEWQp2gl53joHezlfD6N4BRr+hR9jCwsMmQBNbhZs2Xym7cgClGwTxbeBkUa88\nLNUaqhWo1tBBA3P2LKRSqN034tYMUa4fJ96Fzu0BZaGrVRrHjuF4AV4YoF56GmNqUC7hTo9g3bAF\na8cgevwU1nNPNctKpjG9G9FogsUx4ovjNDoyFA8f4h+nikzFFAujc9wxvI1GIyQWW2NNXRNiV14E\nFGHyJohAzc9DMgHpDObYUUxpEd3Tgzc0wGK6l1itRpS6gdD3UV4KfegZ7I034BQX0GdOYz/zPZKb\n+qj92I/jLcZgZApSWfTuvTSGXNCacOJprIUi+Bblco3vxjLM+S7exAz37t572bBXA2MMaI0djGEt\njBEFnZjB5kgrPTODGTsFtouz7w6q0ymSOot/6CCx8hSmXsJs6EI9+zje6CEqN91EvBf0YAr7mcfB\ni2GyeZRqoBamieqaaG6CU3M+p3OK0ukqP767vW25ltWEUqlEJnPplXtsW1Y8u55ZR49SfPQsDWVx\nw5Fvwy/9UbtDumbhzBSVM+N0WhM45cNYhTEiP0bkW/h9HczlEvD0yyQnRpgplpk3HXTlO3DespnC\njgGG7H7mdt4O9bOkXQvHHYS4TdnuJR678KaeIEGpnmC+1GDk9CSZTJytWzvONwxc18Z1LbQ254ej\nxHAZCtdnw1ssJ5/ywhHmZ08Smz7IS1Oa5Mtn6Lm7zMDWPYz3QzjvsWg1yGYvP9/1+lfH4gxhlGN6\nJsH4gSpuYwFr4lkWnpvGNBrccE8Ga28HKgqw5mfR/YPtDnrdMVpTfvFfURq8oZuI/Abx/gGUbaPn\n5whOnYDJZ3GySaKpgGDRQR8/QnjoMNqyqHV0kOh4lJg1R5hKgc5SXNTM1at0H3kaJ51HD2yF6dOk\nZsbZPTrK2YUQZ+pfMW6GuLWHQv9N5GNZpubqFBcsOnsVlcRFen4vMQS4P+q86OvXHaNB19C1AP/A\nozQWIX7HnZjqaTgxQnD4DM72HRjfx06kcBIJ9KmTuDMz5E8eI8KmfqPG3bSJ4le/QnjoWdIDOWIb\nOiDRRzQXMed3UX+pykBtEVV+hvrZSajUiaUzYLmop76Hm1R0Fb5HaDVITBxmYvAHGRp9lmT3CNX6\nABPJPZQWffbv7381KV0LoioKjdGa6jf/J8ELTxPfvAFn+HbqHd2o8TPYfg3LjeGUy/Q+9yzkO1kc\nexwrnSKYOoNlqqRvvRnrtndiJmuohkXtNFS/N01HVxKzUKThJNDHjpAoZgmDUfJjT2JbijDcyOLm\nt7P98S8y3avxFgdJJn+03WdlSYIDL6EbDdyuMtG//jOWMtR23kej4ZDKd+JZFhiN/Y8Pk3v2ObTv\nU9/QQ+XMCTKDOayFTTgzM9gzFosHNNzXReL738McOIg7MIB9ZgR3+hnc8lF0GKNxw9ug8TJbiv+G\nX93E/Pzt5PNXPp+yVVqS9GmteeCBB/jmN795yWO+8pWvtOKtRJscffifGDll43qGRnyUtbCg+8kz\nDfJP/3c6nvpXaqMz+HFY6O6lPlem2J+m1OViNRo4z88ShhCpacrdGc5s66ejpDiUMCRrNarxQTaY\nAuEzL5K/cZjeaBqdymEynefnbYzO1RkLHBZKEX1GUSzWgFdXG7Nti1tu6ccYc8HNqVisU60GDAzI\nUsiiNSwmWCxP033TCU69NMrM9zXGz2M/PMXm99foqScZP1FB6zI339xDPO5itKZy/Bgoi9S2bWum\nA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mCYbXCuly/QbyzT6+3FfscPY3nNh2LKtiGRID4wQHLjIGZ6GiubJTp7lq5yCdW/ETuX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3oKK6+GMqZvfw21c2cJ96l5X+0gMjJGEATokQia0bkXwkuJ77kVe/I8kTY+320EVncer1zC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\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dB83QkaHFTiEjkUBoGka6hcTNLwNDJ7apj+pK2MpohTznv0yPx9F0AwIGWiiMdFyseJyW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\nVuEAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x109d607d0>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Egad. Some pretty crazy values for `dered_r` and `g_r_color`. Let's figure out why."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "min(qso_features[\"dered_r\"].values)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "-9999.0"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Looks like there are some missing values in the catalog which are set at -9999. Let's zoink those from the dataset for now."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "qsos = pd.read_csv(\"qso10000.csv\",index_col=0,usecols=[\"objid\",\"dered_r\",\"spec_z\",\"u_g_color\",\\\n",
      "                                                \"g_r_color\",\"r_i_color\",\"i_z_color\",\"diff_u\",\\\n",
      "                                                \"diff_g1\",\"diff_i\",\"diff_z\"])\n",
      "\n",
      "qsos = qsos[(qsos[\"dered_r\"] > -9999) & (qsos[\"g_r_color\"] > -10) & (qsos[\"g_r_color\"] < 10)]\n",
      "qso_features = copy.copy(qsos)\n",
      "qso_redshifts = qsos[\"spec_z\"]\n",
      "del qso_features[\"spec_z\"]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "rez = pd.scatter_matrix(qso_features[0:2000], alpha=0.2,figsize=[15,15],\\\n",
      "                        color=m.to_rgba(qso_redshifts.values))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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DAD+eb+NbBR3dDLDfcpkptnIPOsY7noiu1eIXv+tupO83uy1vc44V4tzQPZyd\nGaVj/iQvhO5gyqxg5k8zOhnnYKxAW1uYiqgSkds/4VWaYtLgxVqe6doSF1pDGNLHqs8Sz6fQNEE9\nJ+iNOxgxtZTLRtAIYXiDl//9TmcrWc7ZBcpDYbK25D9tQHzbjeENIEXxqmcraTi8oDvMtAvyOXDr\nHlZk+1dgrweN8FXnt+vCgtjJXOtJGnGX/549y91tdxLSby6jVr+OsmUJDHR5/RqTTlPyk+d+whfH\ndxHYpRMcc/GmT3HwbsmRtkE6EFSB/haNfA8Y1gTBaA7qBrtnFpEtJkTKeOwnlQpSLNbRDg5RGHCx\nfBfrGtVftu0xO1ElbzaQukXPNl87V9g5Zk6+xtdevwen3WWiXWPhrSke/YBDwdQwRkpYfpUuzcZr\nOURPzzAilaSPHiwjA4D27irZ5T4Pfdnf/Lbiu7w29Syzk5OM1kJ8t3SEnqVzZHYkmYvt5D8fGqLN\nW1mScjskdwAv5gq8NDFJdnGGZ+s6xYGf4buLlKcgsVjitbOdHNoLmrw9jofSFK1ZnHz6NeyeAH3l\nC8zXJfXIIaIBi4WFCjLZhxsx2RXdXOPjbyc6V3d7K1VhbDbL88+9jhGuwmwL9fYqNX+YsGpZuiUa\nJrzjPluqwmunfsrChQXiKUEdi0xhkYHI7TFuez288/w++RZ8++kMtWQNs18irZ/wnGzll+m5qX2q\nBE/ZOpxL3fLMd0+gcm1ziyM82/BotOhouonVZTCba+fMqW+hDd/DA70d1NwBcm4LHe0Ct1ahMZcl\n1PAQFYFWncXd1SzAWlqC3H13JxV9Cl/42FoBy2vW5jrkaRjzGH6cgNlJMhJjupHAMxIUXYhv46tM\nWglmyoK0N0WmbYBqOsJiMMjUuR9zT6SIHkgibBd6D9FOFukVgRAGBl1ucymANV0mwfeh0YDQ++jf\nsMnj8DWdsayggM2ppS7uaT3Fjv7znK3u5EeVDyLH30BPxPA6hiCgWqMWFsssFYu4lQJzeoSLdgcU\nK/TFFxiyMuR6W0in36ByBqI9QbyOO2883bWypUl8qpXXKS5MEgu/Rr/bTcyzyb8Osd8cQE+1YuUK\nNHIVEgm1Vt6aq9eb9/drtVQ4NvriKDIYw092U1rMYy39jEDgRbqsLhLS57w3iCUl7+nHqdy8UhZ9\nYQIZDFBe9ND5GXekXapukqqV5Pk5nYHujQ5ym/A9tPmLYFgIr4bINQh2/4Q9cYeGEyYvoswsFqHz\nUoK3wueNFxyhAAAgAElEQVSJVXn01G+y2VBRbprjwOsnAQn79kP4xg+srmaiWTr+xQCL3XG8muR+\nnmVX/WXi+Td5Lfwf+OFIkFTD5QODJv3zNdAMzOgShu/gthzGZxfYOYTvIIPtWF4KW1/C8q6sv+Np\nVQQ6vqghhGDfvjbq5Wa7lCb8tTsmm0C1lmHg391L/fVz1CaLDFoTDBtjODWHyWyFGX0vLS097Mhn\nkX4OcykMbeuQ2L3trTNQrUJ3N3T3rv3nXc+bZ6BWhd5e6Fydu6KGIN7bzrmT46QKNtpOn9Zokd6Z\nsyTrp/mG3srnRIYAAr9reMWzem0XLi4lrULYDxHAIhKySMxqDLemybbYvDQRZah1nHtHX2VuKogd\n8yj2x2nUxhGNSUQ1itB1/EDvlUSvVgHD3P7HslYBKwD6Nq6dAuTUONr4i0TdCeqFIFY2y3Sgi0Sw\njrNYRKZb6e2JEe1fpZa7aqlZ2aKemd4rn4ML50HX4OC976lc0fIziEYVUS3iR9O0ZF/gpyOvMNMI\n4fbEsc0Ygbp87ymrjvn7ov/sJ1BYwnDPMbB7kH+dmmfM308k4FMLRxFbfTZZ34daGSIrGx6ylkRh\nHq1RQRbmEZVJDF7AbXSRt9uxWsPMOd0I8Y7nhjNvNBO83n5YZtb9ZUvvCxcuLBvUrl27APj2t799\nzb9PTU3xsY99jKGhISzL4h/+4R/4+te/zjPPPEN3dzdf+tKXMAyDJ598kmPHjl2eZOXtdfEU5TK/\nOQMgQoDvregt3cl+Gok8wX4byyzzmwvf4SONH3G//TLzyQ+RmxujXriLejCLYy+hRUroS3MUqxNM\nyEFa2oIkfQe9fA4hDDxNx7RaEY0g2WyVtjaJpgksvx2HLMalpRQMAQcjPr6EwHa+pyyMUSu9heWG\nWLJ6aQtmuavxGgcaF2g38zgLBjKfpXGwm7Yh6Jz//2jMvcKs3kVXdytaPoPf1rO2D8tSgqGDt7Jz\nZu3i8JtxuO7q7RJJJRJjaM8kF6WF6xoMLk2gT0X4cPA5NP0+7FqWcCOPVqvh7rrntnrIKWglbM3B\nFg4dXppIxOIj+7s5p83wovkWg9YSEa2Ke17SbswTt2xa5n2SsogIvoGWCiD8BFILIK12KC2hz15E\nCA136NCVxZi3GVFYRJ8fBaE1z5lt3Iqp+QIzMIheK7G38BaOFSSr5yiG2riz8AqJvoFVK8NFdgZ9\ncRppWng7r7X+6m3O85vl09sLcL/rvPPjHQi7ipR1Av/zL6mUinTpS8zHYwRZIKMJdMPmp6+fZ19f\nH8lkSB3zW+CFUljn/ye6O4cUo7RGLfY1Rph2u+nwF3BTlY0O8Zbok2cQjTp+oh2/vX9DY5HRNFz4\nF/TqEpozQkv1PEMRj9N2jHBAstOY5EKshwZRAujN52FNv+Gz8LIJ3u/93u9d/vfMzAyxWAwhBMVi\nke7ubp555pkbBv7BD36QL3/5y0Bz4fMTJ05w7Ngxvva1r/H000/z4IMPcvz4cY4dO8YPfvADjh8/\nzmc+85mVHBPldhIIwJ47AAk3GAfRoEJFLxIhTjWSpWOPR10EiE6VMBdtlhItuPkE2mKQ39TOEU2U\n6R3ajbBDGC1hFp6bwbBcCuM2c/NLxN0q/T1RpNZc3PjixSXqdY9i0Wb37hQaBgG/46oYTA0qFZsz\n55awLJ077khvuwWmy2aRaqiOXtXYFV1kqtSC2aeTIo/uVolaNhPVO4me9ogHauRGGhjFSebnXoTF\nnfQlmwmP37977YLcsw8KBWjd4HF7e/ZBsbhqcUgkeW0C3VtgerwLz9Op6wGmFgfYLU9j5U7TWfWx\nOx9g5vQZzKRBYteqfPSWEfQD1DWboGx26XZnZyhURlnY0SAlysjJOOetveh9Lg8v/BMRfxrzgka0\nZReFdpNYvY4MCaT+dnkjmx2/5BavuV4RsX2+p/RBXErGF+ZhdgY6OqGzC/oGEA0brVRlT/4prEGP\nc7FhFnMVrPk47o4aZy4WVq8MF9vouN6qt4/D28e0tbVZCWY34PTrzZaVnTuvvD4QouFHCLx6HH3q\nLG0hGNoxSNE7RzFQxQw6jHMQ0w9TLtskk6Er+1fH/Orr4J2mJ2FxEXr7oPUdyxPtP4R47b+h5ZZw\njXY+2DXPSDZBR0+Nt+Ru3MU4DK5b9KtvLc+J6x1rgNERKBVhx06INVsPxcgriJE3oFHFHuphwH2d\nIecirgxhBQ1+FD3MsFfCxW0meHvvhEoZkssvVbFsgvd2AvcXf/EXHD58mF/7tV8D4Ac/+AEvvfTS\nir7niy++yG//9m/zy7/8y+zYsYP7778fgCNHjvDUU0+xe/duhoeH0TSNI0eO8IUvfGFF+1VuQyts\n2a3qJaTwyPglhG7QZY0QW3I4qd1NUBSp+wk660PsszJESq8T3v2/48pOZM1CZF+lJTWIdBJIo0q+\nHmbWGyY/q6NnagwNBanVHN58M0tvb4zdy6wFUy7bCAG1moPnSYxtNHezj08t3UK4tpd4aYlfib7A\nfx39BEuJDl7rOcAdO99k0ovRdSaHnSlypr6LbhYQ42do7R+nlokzNlHG3rGfwd5mS+iaMIyNT+6g\nOa5kFeNwcajqOe6Kz5OJL1H2Yhg1n/9n/ufpz+3lfu088ekFbGuUfHw/nh8lcRu13gFECBNxr3Tl\ndjNzNGIVerNV7m6r89y8QbQxQiPiUjD7MCsZLo53srd1lqX+XYSTH22eP2+LteLqFpiBbdt6ByBb\n0rhmoPk9t3illD5/CmHXcNt2QzABuaXm8Kx8DuIRjAuvIs+dxYslOCWH0YIRpiIdTLzVxn/ovJM3\nTs4zPl7EMDQ6OyO3tMi9bO3GDUYgqNZSxKlhLJxBIvC6D155GG5JwMQY+D7a+BmkXkNzJV66G1pS\n+JlFPLMDT5xDWn2E2n+B156rU3XSlAZ7yGQ76ByK09PTrJRRx/ySyiJ6bhQZiOG37b36b9lFjJFX\nkLNv4X30t66UbULgtXQiCwXs+hAjpzNkIzEKqW7mtS5+UcwAm+De+j55fXdArQTRVZ4Zt5bDWLyA\ntEJ4Hfvf+/dcDvIzmNOv4dz/K9DaibuUQy87yFAM2f3vqU24TPzbJDP7U5S9HnQPfjXWSoRL44At\nC6wbr0O4orvUiRMnLid3AL/6q7+6ogSvvb2dH/7whzzxxBP89Kc/5dSpU5e7X0ajUYrFIsVi8T3b\nFOVWhL04mjTxa3FoRDmQGyFVy5KIjfNmdBdVw+JixKSeTOL1D0I0hJc1cZ/+Z+yxHIG+fXTua6cz\n4ZEgRyIZolrzaTQ85ucrzM6W8TwfU3joE6fQ5kauGUd7e4S2tjA7diQwjKsvNc/zse0N7jZ4CzQ0\nQjKOHkoSKKUpVkLcGXsLa7GKLDq8Iu8m3Z6jETcJlWdI5keIFwUdA/sJRQO4kQTVYJKSq1Ep1Tf6\n69yymZki588v4XnrM+bSxCLm9WAYJqm9ZQ6lXiNaL5AN9XMytg97oU44HCdtNDDiraT27FiXuDYz\ns6efkNZKPHGAfjFMxKhiJAykrpENxMgvhfj16A/ps8ZprZevTu7eFo5t2Pi7YrHBuXNZcrna2n/Y\nBn7PW+b7UGs+RwinDpqOsKvNv/X2Q6wFevvRM6PoE28Q8LLo2XFaUgVGF9tw3/JZbAnws2orLREd\nb3qU3mCRctm+9dgiLdt+XON7uDbUr+7OJ5wqIMF3wH9Xt/XuXoTuoyXDmKOvIRpV9NwCAHpvH17P\nfry7fgWGDlA9dY6D86eIZhrU3rKh3qCtI3R1heHteMwbNXAal/9Xs8sIzUA47y07RMREbxQwqCGy\nc1feU5pD3vvrOH0PoA320zo7RXypjnmmQGVWsKivQzm0lnT91pO7egm8q89fzak2yxy3ce33DAxg\n5SfRgibm2OvgexitMZydP4d9939EX5rFGXNIBBcIzNm441WWsjH6/PS197eMFZ/1L730Evfddx8A\nL7/8MnIFzZuWdeUG8ZGPfIRoNMr8/DwA5XKZeDxOLBajXC5ftW05yWQYw9hcNdG53OqNGUylorQt\nM2hyI2QypY0O4aYECBPwwiTC0BmIM5HrJGsHEEsN7hg/y2wyyeSeFI2OPo42ZoAY2sUTFEpl5sZz\nBHvuZVfcwysXqMgQRm6JHr9CNdBFMhnE96FadWgP1BCNGjSq0D74nlp9IcQ113eTUvL66/O4rmTX\nruTlriQNXARgbZHJbaN+cy2613MRNCeC3uZgZ2ucXxyg/ycj1LoEFyNJuvoT3B0oktp1mICe40w2\nhpyYxI1Cm5Qkyi5eyx0b/G3eP8/zmZ4uY1k68/MVurvX5/qN+23UK8PY9RNEtBJO2EKv2Qxb08gd\nBiOaJBVvpb/Dwezf3Ot1OE4zn1rLBiO9NU3yUhek81NnyRgDiESdkepePDvCb/vHSJfmCDWWYOfw\npptCYHa2RL3uMTNTutL9THkPfeYMwq3jx9tx08MIu4KMXZrOPRJBxMKI4iIymsJv60dE8li6JPJU\njko0yPnEAKaZoRiosy/t8uADCaTv0NUevKk4PHxsXEJs0UR5Nfg+3uSrCCHQ2oYh0rxnyHArnu8h\nNR10CzE/hXAd/O5BMAzknruaLUrBMFhRvLbmBBN6ezvEw2g/OoN+8VWSVgvd1UWOLQxxythPTa9j\n3e6rbzcqNGbfIOgLZN9BMAP4iX7QDPxQEqoVtMwsfms7ROPI/mH83ARS6MjUlaEmfiiOdeEUej2H\nXjxHm5YhNyb40dDPk68E+Y/RrfVcuOoKs9j5cQJYyIF7Lm/2Y91IBDIQA88B3USbHW8e/44eaE3j\nHvwgxtxFnL49oOlosRT6rgiubWA+99+JzY4SKVd5PbaP0dJOPFkhqBfgJtdmXdGT5J/92Z/xuc99\njvClmQvr9Tp/9Vd/dcP3VSoVIpcWg3711Vf55Cc/yfe+9z0ee+wxnn/+eQ4ePMjg4CDnz5/H9/3L\n25aTy1VXEvK6Wloqr+q+tlpCtVkVXId83eTH1SP01afpL45hxHTCtk3nW6fwuoL48SE018MAqtLE\nO3CIkgjjd3SyWJ3DrZ5l4nSGjvQO7umuIMNtRCIme/emiYSLiMIExDtuusuWlGAYAsdptvg0sJnX\nCwB0eUnMLZLkSXziA1UKrQF8u8G54CHuHXuFVH+N+myc+PQkfTuTtN7bjuWX0USa8OQU1WgQMzaH\naHPw2NqLweu6Rjodpl53SafX78HbwcYNphmsXaA2Z/CG3Ek+10WtWqDkxmmhwUybScjMEdEqtLDx\ns4Vdy8ICjI9DJAJ3rHmeX6bC62QSSzR2dVBy2qiWE7TnTjFdH8TTAuTDHURn5nCyGWRr21oHtGLt\n7RFmZkq0td3m3c3eJj2Es4g0264/3iUYRwbfcd67DtrsOMIw8dp6cD7wMNJ1kd//r+gNk0ZrDD8a\nRaY8DraeZfDQb6DNmWBZ+KGbS/Dm9CU8IWnxwrTIbfCbucXm2CJz5a0eNWyWIjZI6EJe1WVMRi9V\nOpWymK8/DYaJY4WQbZ1gWnj9d117p1YQTBM32kr0pR8SMxz0hMBydObLO6k7gvDKVlLaOqREOBmk\nngB9+QqDrFamHmxg+YLLpZfQ8Fuas0jr469jTJ9CTlnY9/17sEI4h/+39+4oGEV6EhEwcU6eJla9\nQHH372BoQYSW4IKxTZfe8crg22Au3wUya1RpBG0sJFe1rQmBjHejLZxD1HJAGFGxm/MNtKQgGMLf\neTf225P+SIkfS+MbEeSP/l+8zAzhhQuE4n1oiTA0guTDKXJ2K6mbPK9X9BR5+PBh/vVf/5WRkWZX\ntJ07d17VOnc9L7/8Ml/96lexLIv77ruPu+66i8OHD3P06FG6u7t59NFHMQyDRx55hKNHj16eRVNR\nbpWHz3crb2G3z/PvjDxBt4p9IIScirDn/HOMxHbzoTe/j//B/xO/4pLpqGNE2okFDpJqS0CjTmdh\nnEp5jFJLGs2o40aT+KJOcqiKU9FJRU1ky06kfnPrIzWXUkhTq7mkUlcnBBKJ2EJr+FRFiWi6QXff\nW5wv/hxt0RL14QTDoX9DFuv0VXT6KhUqxT58TZDMzjAUaaPgN5jbtZNKNITXtoetXue6Y8cq9+Nf\ngbKew4pFCRvg3eGz1xxnPjjMucYuurJnSZZeJRS4E+Ix2HTtUVc4TnOIor0KPeBuRGOJmm4zF8xw\nZyKHY0ZohAM4Cxad5XkuFHZwyJ5GvPUq+sA+/EYNv3tjZ1h7WzIZUi1376DXziH8Or5Xwg9dmUHI\n694HjQqErlGhoRsQjiFdB+k10L/3BLnTzxN49SmW+j8Evxiiw6qTWTTYN2Tjaxp+963NTrR1SvNl\neHX02tnmP8VeMFbYS0HT8Np3IT0X9GuXkUJICIXBdShYC7B0jnBwD0b4UmuS5yHmp+HNN/GrBfS5\nZ3EvnEbkZ3EK08R3xbHuC7A3MEl02ma00M2dN9+bbVPTGuNozhJSzOFFr5P4vi0Qxm/fiS8tuMaz\niR+J4Xs+UpYoL72A2zNEzOtGx4BqBUp5xGsvo536DizO4M5MgJ1BMyTevVGG05OUl7Is3uSi21uC\ndNGrbzZnSoZlkzwZa8ML6HjXuRaE20DoFlWzjpd9E8uPoZuHr7ygVoUzb6BlL2DOvUD1wiT2VAGj\nNoYVzJI8GCV6t8udgQkmzqc41+jkgZvsNr/iZoKXX36ZkZERPvGJT7C4uEipVGLHjuXHdXz4wx/m\nwx/+8FXbHn/8cR5//PGrtj388MM8/PDDNxG2oizPwaEaLBCMLaA1anRGMoSyNgx57K+foq86Sda8\nh55qgXqig0Z9BlIm6ZhJVAbAdRFCY6i3l5a7ejHiOzBiFhVtkYEdUXwkpt2HV15Ahm9+oHEoZBIK\nXamOCWDR6SURgLGF0h1LBqlpZe4o/4xXdh+iFgnTFp0j5FVJPbdEeKlM0j9Pvv8wVvoQJbuF9tYk\nZv8Okqk0bjCCrm2N1srNJuCHqGgLTIoQ/lCCgOezIzNOkCJdtVGS4SBmuAuDJLqMbdonze7uZoIX\nW4eerT49RLwKtdxpdnblWJJpnHmL1sA8pTtD9JaniJychzMnkLsP4fWqsYublRQmQhZBvKv80PRr\nJ3fQnDhi6A6QEvN//F9o3/sOsYVRjEYJ56OC1u4stViVfT0X8Fr+8y1dMl1eChuX4LbooqldORbv\nPt7LCGHRQTu6Lq677qmMpnEOPYivG/jVV9BdD6842kzw7Drmi/8L/6UT+G+eRctNY4YK+HMZsHyC\nMcj3RegbmqCsJUimZtGM+1jh9BJbhzABF7QbtyK3+jEiWgCLazf3yO4duIaEpVFcWUE6NRy9ijmf\nQz/5E/wzZ5FvnsEYexFh1hDlBl4A9F3QfWCWoukg2z0mF2+uYntr0BAIpO+CtnxzWdqPUzeCBK5z\nnL32PYjqErVAHk224UuDaK2AbwTQXvox2lunEfMZ8Iow/hLB2SnMioMedhHd4CdN+ndPUPXDdERG\n6bcO3PS3WdGV+nd/93f8+Mc/ZnFxkU984hM4jsMf//Ef861vfeumP1BR1kMAi6FggDM1h2ylnb3e\nOYJ+A+utKq+l7qWihwgWYWJhlp7ZEuF7WoECIacMWgoMA3f/PSAlyXdMthD0E0gkph8CTUPGO1ct\n5q0y9u6dTAKk7U7K9TiWUaOtI0vUKzN3uh1bs7gzc4p6UCP6zGkK9x1kx8/9J2xczLZeAlqWiK9a\nJN6vsIyzkBlFy2vou106/FkmtH66tBna5zK8duTn6YvdRftIGUcbITA0tCmX6hAC2tdjiKBfRZej\nyDkXe0ZnPDWIbRjsHTtLxClzZ/YUHYEcIiLQMlN4bh2Z3txjF29nfmgXvt8H2k08aDo22pkTMHYR\n//nnYGSUQLWI1EFGTBKlBehoo7wUhLZb++01tG2S3AG6hRu9h+ZatDd3nwosd1+zG1CvIeOtCCDo\n7QR7CmtBg/I50Gz4X99BO/kiWiaPMH0kNkJIfBd8A0J5F83yCJs1DM8nFdx8Zdyt8gM9+GbbpUTv\nxm503sn0AHqtQjg3g1PLEwiG0N58DvH9/4F+7jz+fB49DL7TAAuogV0BaTYIh8vURZCEtnpDkzYN\noeFGDzW7It8gwYMbHGfDQhIkLLpwtAKhuom8MIo+9QacPY32kx/hBiLoM5MgGoiKjRU3cG0XJwcl\nPYgVaKAjKbgS5Dxwc/N9rOhK/d73vse3v/1tPvaxjwHQ1dVFpbK1FzlUtjcXnyF2EK2+iD9nEDBt\nUuUl4qMZnJCg3B0m53SgNcp0+xFq4xbpVDtWoMbluS2vMa28jkHU3zzjcjaFeom0myHxszLauCTR\nmydBkdxShMJUhJZKkXrMJxCbJTA8i9BA+IJIR99GR77l+bpFXKsSyJdpvBAgMVnAH5FIXzBXjtCy\n5NNarYNbxq91o4e36biJFdDI4FOkmH8VUU3juQ5LspWaFmWocI7SXJyJV9IcKE1BvYiYOAvVMoRX\nbxItZZXdTHInJfrFUxj/8l3shQX8k6/jZIsERHM3QVEitlCjsVgjq8UQO7ZOT4p1IVb5eEiJceH/\nZ+9NY+S6zrvP37lr3dqret/YC9kkm7s2WqJkxbHsN3HGsRK8r+F55QxmDFsBAmQCBMmHGIgDBMkH\nf0wC2MkLB2NPMOFYr2NPYsdZvEiWrZUStXAnu9n7Ur3Uvt31nPnQNC3ZWkiKUpNy/wACrNtV955z\n6t5b9znnef7/M6AUUd8OVL6bWHwYuQ7qB1/HWJtFNCvI8y8TFcsozyXubDYjMBO0ERjlBrFqi+R8\nCw/FUmWI+D0R15Gcdvug3cTJAqGBp4hfKhJdfAZRWUdfvYCanSMqroMLhBB1OkSBS+gqtBXoWylR\nkhaFejcZ5/1W6HgFod+Uc10UV9EL8xiahrHnHtT/9z8RizOYp55EFdfwq01kaQpTjzAEBJpGFI8R\nViLYCEk1C6Qmm3gi4kJrjOSR658Mv6arIBaLXVPN3Zvxta99je9973scP36cv//7v+fxxx+nv7+f\nL37xixiGwbe//W2OHz9+tQYveY1+Z9ts81rqdZ9q1aW/P8Wa2aYuXAZFBXFqid6+MrIeMFBeYCXR\ni31ug2ioG/3EPLN5QVOMUivVmTjQv2XtL5fbVKseQ0NpdP02STFREr08zf2FV7hsH6AWmqTDGsnI\np/OJKVInV1C2QaqzQfwuEyolyGQ21dNuAWo1j3rdo68vhaYJpFSsrNRJpWzS6Vs/BaUnniSaKWJO\natRn8oy1JxGzGwxMXUTc/xFG8zvQayFC136pgzsASR+eNoM5NMhObZKG2abczqLH2nQsriCLgmaY\nRNQBDVSpAM61iWMsL9dxHGO7Ru4WRTt/BuW2iS6dpT61hHXxZRqFCrYLkba5SDE6uUypYaHnJZEd\nY3W1SU9PgkKhSRCEDA6mb8kV8NsWIVACVLVCuFFBFUtEKNorBWLP/oiosICpgww0hGGhfBe3Aaaz\nWQJoWSZmGTrLTcbPX2K6ZxfVjTix2+Snc8uoVpAnniU88RR+FOI99yxxt4pq11BSodqgC2h5YHoR\ndORximWEkEycusgrfUnCOsQ73/u689sJ2WggHv8+KgxpzK2gzU6jPfUE3toChgl6qKECgdsCaYFp\nS2TgYcViIBrsObfBdMcci5kh2m4MW1x/KdA1XQp9fX28+OKLAERRxJe//GV27959TQfwfZ8LFy4g\nhKBUKnHixAmOHz/Onj17+MEPfkAQBDz22GMcP36cT3ziEzz22GPX3YlttgGYni5RLLZZWKjiKAMT\nCxm7g2SszMvLg/gyZH5ohK7KGn2Ts2g/msZZ38DcmCdwYxjOOGgpVlZqPPmtFyk8+zLyZik/KIWo\nL4P/5mkNMzMVqlWPpaXbSEU1CtBKM3i+iQrXqSV0WhmHZS9P5uUlVNvDqFYJSJM+dIRQmviRQZTc\nlMvGb2yOyzXYrrwbXL5cZmOjzdLSpm/W0lKNjY0209PlLWnP9WIGRdxindMLfTQSJhs9XSS6aiSK\nGww/85/EozaxXbuwR8e2uqlbTqRJIqMTsyNHd9jD/CsJxIkN6mECL2dibdSINSqoCCIPog987Jp8\nG1ZXG6yuNrl8ufye+SBucx0oBZ4LUUhzcQU3slhfKeMFkkYEfrQp9BNWItqGpORqFPNJlpZqFIst\n5uerFItt1tbeIGsp9NGqi5ty6Nu8OX5rc5zU66+PcNch/KpHODtPODNN+akf0/7x49SmL9MMFQ0P\nZP8g7BjDM9N4SqMtTYKWRCt7aCaYwKqTpVXw8To9fHX7+svedEJ3c9zla8ak3SI8cwpvaZXKK6do\ntV2abkTTlbREnHYyh6cgCMFtgVjzEb6EFKyoDF41xLNcNsw38Xn7ZSH00WpLmz6Pb4B0A8JIo3Z5\niebTT1H67neQjSrNABqtEC+RhHwvvmHRUBZBAMGqi6wpdAsSls+KliUouoieNuYNeDleU4D3p3/6\np3zpS19icnKSw4cPc+LECT7/+c9f0wG+8Y1v8Fu/9VsopTh9+jRHjx4F4NixY7zyyivMz8+ze/du\nNE27um2bbW6EeNwiCCTJpEVextgfdnN02ad0f47LBwdZ25kjzMJiI0NzPaBnxSVVWqG3X+OesRrj\no3GkVLz44gqrUwVOnV6H1ZWb0jatOo/eWMXYuPim78lmHUCRzd76K0dXMWzCrr2UVR8qFqClPapj\nKRZ686TtBqbwiKuIOB5srKHs2KZK6PqmH6ZRvITeWEWrzm9J8+NxkzDcPGcAkkmLMJSvE8C5lYm0\nnVzwhinlsswOdVHcmaIRGBjKQzgR2uUXtrqJtwwCDYGGKTuRu/cjgLKdJGuvo7IawmliRQrhg3As\n5Ni1eTYkkxZKKWzbeL3B8jZbRxShn3kF7dRJlOfRdj3aq2swvhfRqCBjCaQTQ2RTaA54CprDguWh\nDtQArKym8byIZNIklTLRNEEm84sCF3ppCq21jl6a3oJO3j78dJy08iz4Ptqpk8jv/Svek48Tyggh\nNAOalhIAACAASURBVKK+PrR4At13MRNpMEzE+G7EXfegT+zH6uvHHRjH7RokMLMoEaeZyNEAmqaJ\n0ReR8VbRrtOy6P2Mvn4J/eWnMZ7+DsH587gvniCMJ1GJJMLUsFp1bE2hZ/PIA3fhThxCGxxE9e3A\ny3UT2mlUpBEksgQV2DAz6DmfrLlBv/0eyB7fwuily2jNNfTSZQCi+RnkN/9f5LM/QUURUghkPAm9\nPVCrYpgawnPREg7agSOEd90Le/ahRvcR9e6glu1B6imkmaEpbBaSeXQnRHUrUosF1A0oYb9tSBhF\nEU888QRf/epXabVaSCmvOYUyCAJeeOEFPv3pT/M3f/M31Ov1q59NJpPUajVqtdovbNtmmxthfPwX\nJW3njU7smMuRcI5kO6CrXcZaXyfqUoSeRbN3HyrmoCOJ3CpasoeBgRSXC1mGBg3o6nmDI10/0kog\nGmtgvXnK19jY7ZnyoJId6GMG3aLOfN0mcanJzvIy6kCKzEwdqyKwa6sE1fLmj0etBlfEK5TugN9A\nvsW4vJvs2fP6tIdczuGuu26fNDtr9cf0TLSYPavILNUZKhXIxiCng2H60HXFYzAK0RdeBQTR0KFN\nufhfMjQsYtFuRG2NifVX2NFZwawaRA2bdpAgns3RJy+ADVEmj14pEobhpgP7W5BIWNx55+3t5fi+\nIwzA9xGGTrSySPvll9DPvkjclsT6OknP2LiWiRMT6MomaFboosFzfgfCl3Qn5zh6tB9d15iYePOa\na2XGwW+gfsnTn98OZTrQrqCsxGZdq5KEC4uEvo9aWiRGm1xcJ5tPEPR1IYmI0gnM3j6CXA/a+jJa\nTxdW5zDBqefwvABlhNi5Xmr9FnHfZzXooT+5TuxWlQveApSwwGuhUinCMy9BBN7J50m0iwi3TDKd\nQK3V0Tq7UEfvwJtfwGqa+EYvjHchZl/ED0KkFFhjebqsEq9Wd5CMtbinc3Cru7elKCsOjTrKufLc\nubCwmXa8vIQ8cxrx3X9ELyzidA3hjI1hFZcQBZ9oZITgVz6CdvoF9HoFfc9uongaee4pwkIdGbSw\nuwcg3wRXUnJz9MTXN20srpO3/YSu6zz22GN86lOfump0fq38y7/8Cx//+Mevvk6lUhQKBQAajQbp\ndJpUKkWj0Xjdtrcil4tjGLdG/c5PKZdvXs1gPp+kq+s90Au/Dm5n4/W0zDPXipOvN8jVPWwvItkO\nSHlFFg9bkE1S6jtMPJ5FJTaDjjvv7OfOO29yLV68k8jJv7kh722MCOpkRJt0TieesKjJGMeeOoFT\nU3jKIYzpaKaN3tGJ1tsP/T/7YYi6JzbTdt6H4/JeoPxdpEyLzoxHfNklWV4gUg5t28TsvQvVtWfz\njUEbIeVmymHQBv3Wuse8VwgMNNclXdUYSJZx2x1kam2Cqs3Q8hoxESAdkLv2oDQNorcP8La5BbFj\nRMOjEIZouQ6Myjq63ySyTZAKc8cI+kYJlTKhUSRsCIqn8vTscVnKdTMRXrimOmiZG4Hsju3719sg\nO8Zfd5+Xvo/aWUNMTWFkMxjlKrgBkQbtwQHsfC9ifQXZvwMtnUPaDsKwYOoCwkkQ+A3QdWKBi4jp\neJk8yYTGZW03t6wfzBYge/cijRxEEt1cIJqfRy+tI+IaWipF24yBLjB0A80xsbq7YWEW2i5mq0bo\nJBBhgDAsQlvDt3PEu3Xm5ADx3C+3VobMDkNm6Oo5LQ7fiXpVoXr6oFBAVIooAaZyUR15Gvt2YzWb\naPEM2tg+jMkzqI4ORGEFvcciQiO0TQglUipSpkvUmUW34yyHOwiUwrzOGuBr+uX6wAc+wL//+7/z\nsY997Lp2Pjs7y/nz5/n617/O1NQUp0+f5vTp03zuc5/jmWee4ciRI4yMjDA5OYmU8uq2t6Jcbl1X\nG94LSqWbJxdbKjVu64DqVqO7t5vMVIVirZeWkaCrsk42tk4sStB78DDhvgfpGx8jnJmBlXO4iQRh\nuUJscBCr4ya7pb5vHwJscplelAfLzR2kmyV8wwGl4+sgXAju3k//yAhBsQiFFTTb3ky/EeJ9PC7v\nPsbQMVKLDcITScqVLBU7j59sUTcTdHzqf//ZG2Mpos6RzXqk2C9ncPdTZOcwzViJhFBEumJxZQgp\nYX3hDIMtiKVMZCqNIAD77X2ntrk1CWNxWhfPY0xfJtbRjbc0yer4IEH3ML0vTCMPOITnT5NIJBF+\nwEClxMm5DvR1k95729d+oO3717XxmnEKXQ9jrYC2Yxh2jaLP5ymceJpCXxr7yEESZ2eJDwyjxWLY\nQ8MIr4FotjHNJIZbQyQtZKOGpjy6F+o4xTYn3aP4fRHiNvKRfbeJKmVEPIUW+NhdHQT1KtrEPqoz\nl6npSVoHM5h9R0m/MIXR1HG6h3CyUximi+rswLLZFLhptzHWmvTUlvhJ9BEKHR2E6jqukfcrV87p\nqFhEpFLo9/8KvPoyamMNL9lF5BZohzGaGRPv/iPYA110yjxObz/B3Q+inXgaQ25gtzaIRvYgIx/N\n99A8QXotQMspziXvID+6iFDiuucurinA+9a3vsVXv/pV/uRP/gTH2UxfEkLw7LPPvuXn/viP//jq\n/z/96U/z+7//+3zlK1/hkUceob+/n8985jMYhsEnP/lJHnnkkasqmttsc7MIWy69l0oEpMEH1xck\nqm2CUJB+cpL4x4dRvk/p6eewozb1uKBauUDihV76Pv4IZu/N87l7v6Iy/YSJYaovexxIXMJs1pEZ\naNkWor5pO1HfWMEonSP+fA117jzm2E7M/gHEtmLuO0LGLJwLFsqv0YxSzLc6GVw8TSEWI/3N/wsz\n/X9iDQ4DoNLb9h4AMpIw0yRdXYPxPcQSHsGaYt3tZMOdI+EYGOuLMHuR6OB9qPQvpn5vc3NwAzA0\neKOkHF9UUETY6s3V41p4tDSPtIxjKh3leWixzaC8NXUJ/9Il3LUCicmLtOsBgbKRi8tIFMbaKgEa\n3uIi0t/0Vdu5PM16fxcLM3th57vV660hiCCSELtJ5cUKhadtoEsbDxNPC8jJJEIJpOuiO2+c6h7V\nqqgXn0fOzGCMAh/+LwSGTfUHTxKev4QWBmjZQaLJSYSuIzu7qEodGxOztEyUTBF27SBKtDHW59CL\nRWIrAQfyF3gxsf/mdO49IpLgh+Bcp0i9pxURSsdSWdygTd1okxLJ1/myReUS4ewMRJKYY6EpiR4E\nRH3D1Kdm8WZnCeoCq/ODyGSOaHYef2wnejtE21hBmhbawbsJVwrIU8+jN0K0WZP9Xedpxg+SaOUh\nc5MH5DqQEtoBJN4lyYKAGpHmEcoUruaTlQk0N7h6f/kp4dIC0doaQtOxDh+BShndbSF0G69jmNrc\nNJ5fg4E02tge/NPLiONfxbj/Q0TlKubUJGJ0EH/iCNHwHuznfoQelFDrGrF0yIMdT3MyuRtj5Pr7\ncE0B3je/+c3r3/PP8Y//+I8APProozz66KOv+9vDDz/Mww8//I6Psc02P89OK4WxXMHrmqcSi9Od\nXiI2IfFqeSolj8L3nmbj2WeR5y6QSCXI7mthtCq0DpmodhsVRYRrq5vphe/AKuR9jZKI/B30jf47\nwQYIs0n2pUs0F0G1DcjpmF4d99kfYtp5hLYDw7YR23Ur7xiBidM9SLL7FSa7hsn4VTInl+gsF2jP\nvUB4+hnMvkHEG3g6/rLiF5ZRGw0S6zEOpF+hbuUYrb1KJpglsDSKuU66Uj3IfDcq8dYlA9vcODUX\nLq1rCODIgOS1GZERPp6+CuhokYmprnwPUsLSAqQzkMlS0RsoAaXaMvbJKVhbw/Q9nF/9CHZXD80n\nf4RotfGGRzHdHlJRErGxjrY4h24btKSi4YLyBW1Hw8y16IitMhAb3YohedeIJJxa0ZAK9nRJ0jdh\nYdpXRaLl8/gJh3JuBwYGVVqY5+bxl5cxXRenswutuxttZHM8VRThT00RbKxjZ7Ooo/eBrqPddZTE\n3SfRn/sxtpxHF+u0yxWcHTsQ5RJ+KGnVXZJ2ltCO42d7CNtriEQPuh+xRz9PJZHmIfF9FJ/YFPK6\nDTi9IoikYEdO0nWNc51+a5mwMons6YC2YmXhDL6u8HdP0K868WanEbOzCMNAmRZRuUhLRZiOg3bX\nXYhYArtQILp4nlQYkH15kvLcGoHuwMAgcngcv7COE4TQM0bDN0GdQWu77GpNsZAc5XD2PPsTH313\nB+dtOLcqcENBf1rSf5MDTSUDvMJLqEyG9WwGW2VYm7+AM72O0ATpo/ehWRbRmdNEK8v4q8uIbAfG\nnr1EwyOY8RjGzl1YXoj53e9gN6pYlxaR51ZpV6qovgGiHz+O7kfEuvuQo3touhGhsAl37cc8d5ZE\ny2BX8izn44f49fAp4JPX3Y9rCvAGBwdpNBrMzc2xf//tNUOyzS83+e4set/9NIInGY77ZHoDdDND\n9VQn1Woc91vfoj03hVhfRctkyeqCoMvCnHFhpIh//hyqp4uoWiG299pU9X7pMCxkdpSOEYGRWSG4\n2MCJJGEYUcn3QGEB6g06qi+T/rWPI4RA7+tFbKudvWOEikj1xFElxQ65iv7UBvHZOTwf9FNzGJ/N\nbwd3P4eZ7yTqHmQgcQfh8gmy5kU6i6eolDb9fbV9XXgf/zTRh7cnHd9NfloS+kYOKRoGQpkoJJr6\n2UpQdPE87ReeR487OP/tvxNXNq25SYzvP03w8hmiVpMg30lzcgrjgQexdQ3Pa1OeXsbo6ye1/y7a\n3osEIyHSNHFn5okSKaJEEssxGRxYQE8rkiNb+/B6s1Fq85/2JuN9vXjT0/gXXwZvBsuKk/j4Hlx8\nzJNnUSdeJAxCRCJOZOgo00RGEi2fI1hfp/HD7xOtLBIcvpPY2irNZ5+hsbJMYmQnmaP34i0tUClX\nMDJZ9Fic5IO/SvPr/4BMpWj5JsbdD6CnE5jpWcxqEWWNI0ae557hl/CimyOK9l6h2PxO5DV+J1Gr\nRfBP/4ofLhA7dACxewB7pYacO4PT0Ag6mvinXoW5GZwPHMMY20nrmy/TPv0q1q5xMiO78C9OUj93\nhsCyyRy+B7+2QevcDGEmgZbrIFQQ9vYjbAdrZAxLCIyxXWiJvQSZk+zdd57BWJYoEltanqzY9Ou7\nWQ5LUa2KNzuDns5gF9cwCmdR2TSJez6Ef/ks8aZG9OpLaIaO39WLkUwSzUyhrBj+0jLCC/D+8f9G\nS6YwslmCVgu3UkHbvRujsEhYLNLemAM7gTBNtF17CTwfPZ1C27kPTdMxUFipJHYsjrAjUrue4678\nKwTu0A316Zq+nieffJI/+7M/Q9M0nnjiCU6dOsWXv/xl/u7v/u6GDrrNNu8l1m89zMB3v4tmNkmV\ny2zUOtFn6iSLF9C6D5CxQmq2IBuUaM85mI0EeqVCI/xP4hP7kBsljNxNrsd7n6GSDt3lCrF2k2qn\nSXikE3N9g9TaEm7bR/iCILCJTi9iHsigKYEKAoR5e9gR3LJETYz1Ik0jTke1Qm05IFbeVCIWTR1z\n79EtbuCth55IkDh4mMH2AItL06TOnsGvgiVAb4IlYuh+hahehlRuq5v7viUbh3FNYmrw83omAg37\nrItstWFXC5VI4s7NEczNogoFgjDEfvYZsvkc6abEO/kKcm2NlmXhNpr49TrJRh1D6ARuG62/D7+4\nRvPJJ4hiDqJ/B1okYLGA3tNLIpPGsc9RlD4qbxLX3a0ZlHcJQ4f9PZJQQeodpLTJWg33/FmaJ1/A\nzueJrUhiVIiH/4mnWUSTl1BK4ZgWYuIAYbOOVqtiaoKoWUc6CRQgEfjr68hkivbSEv75s3inT9H9\nid9Gz3eiTc/itltYqSzR6ZdITxygESrMKMBslBAjOzDuvBvr/KvoaxfpSlZYTfWQEdFts3oHsL9H\n0Q4UmWsUbg6WFwlnFxGXzmOcWkX7WILM2gaZ+QZ6fB7sLMH8/ObvazaP0dlF2Kwjm3Xc4ga5mEPY\nbOKeP4tqNGkdPYY9lCYaXMH0A7S1AjKbx+jtw5I++sIs1t33YnZ2YC6fpzv1DNVkRCLmIcytrU+e\n6FbUPUXuJiQCBZcu0jp9ijAMMXp7sZfncZYqiIzCvPCvhLoJToKws4uouIFcXUbVEohcnqBSIRIQ\nLi/gjO9BBQFSKRqvvkxrdhazt5/kAx9EPvdjNCeF2TeA2LOPsFrB6RvArqwTrSwT//hvo2Uym8qa\np19C1C+QT9fZyFg45o1Nhl9TgPfXf/3XfOMb3+B3f/d3ATh06BDz82/vWzU5OckXvvAFdF1n165d\n/Pmf/zl///d/z+OPP05/fz9f/OIXMQyDb3/72xw/fvxqDd612jBss83bEUk4v7AB2TF6UqeQtThE\ncbSMQdrJ0P2xj9JcWyN6+if4K8vY8STEbMy+QbS+fhqZXja6RunryLKdoPkWhAHpYoN6SqeR6kfd\nZdJ58mX0holquhRj3cQGxuk7fBfGYB9iYGA7uLsZGBnc1D7qRgW/w6TTKnKJDBKNg6Njmw7O27wh\ntbBGxmtDSUPrFCw2UmiaycCBw6h4BuLb6ZnvNm+VKiibLYSho+o1vHqNqF5FxhOIvfux2k1EzERW\na8i+fqyJAwScwersxtUtnFQS0Wzi9ffhHLmTaHqKtabORkmSc6pYHXlENkn2gV9BVaokUnH8VhbV\n+wwqHqOku7zfKlavt87rjZCNOuFGEWFaBIkUqfsfICqsIKplRHf/pr+aUjj/5dfASRCtrhCsFtD8\nACyLqFKC0ZHNlM14AquvF3I5WqdP0dLiTJ4vMPbwR0j3DdKemsI0DMJqjdSBg1gPfhj5zeNgWSi3\nhYYgvP/DsN5LVP8u2VqTpfztNaFlGZv/rhU9nkQ7eIhoYQ7Z3Us4fRltcBi6e6CrG3J5YkNDKM/H\n2LED6bpoE/tBaMQP34FbLqGyGTRNEJkGhcuriHseYOA3OjGXFwnW1xC2Tfahj6LOn0UAIghQe/YR\n3ncf3onvEG8EBHqCph5h3aTVsxvB0LkpwR2AbDVRmo5y6yilYGAIGU8iLANZLCEqNcTIGHZvD9H0\nNKRSRJEEx0Ef3QlhhNZuYO7ajVepEho65PLos5cRfptGGKdx4KMMjM2hBT4yZiOEIDM6TPjySYzO\nHmhU0RJxxM7dyOExtIv/QRg9QbbSZjW/98bG6Frf2N3d/brX5jU8nI2OjvL1r38dgM9//vOcOnWK\nEydOcPz4cb7yla/wgx/8gIceeojHHnuM48eP8x//8R889thjfPazn73ObmyzzRvT3qhQrloIzyCa\nzTHkS/T+UaKqhjawm9bKKqFtkf3gbmpnEuixDKHQccbHMHoHKPSM43kRKyuNNzS63eYKhSW8pQ6K\nUmeuc4SRU6ch20vYaKDpNhvOOF3DOykUW+z9zK8j+ge2usXvG8zY7xBUF1HL61QwWSVJDMlaooeR\nzu2V5zcjceFHmNUi1VYcnhaskiKeTjF/7yfZ9eDdW9282x7BGgod6KDR8InHzesygjd27UI16uj9\ng4hWi/blacx0lsT9HyTyfWrP/ISwVIbJS1hj40S6AZksqXwOM5K0Lk+iCh5e4DPwvz7CnHqcaGYG\ntz9P54CNXFmj2WiS/tWP4K4s4D43R3UlA5FFRk9C99u38VYgiiS+u4iTSAHv7oqz3tePWa2gUglE\nMomPoPaTJ/Fdj+zv/B/EP/zRqxN30nUJlhaJGk30fAcimUDUIghCnJ270JJJYsOjhOfPkpjYy8KF\nKvFsN/VYN/3jFuH6Bsq2se87RnNjAzk3S/xXPoxYWSaMxZFrBWjU0IYGCU5lWR2IUWqPwZtr8rxr\nKKVoNgMSCRMhaghaKG6+N6bR14eVyeIeOERrZYlWJDC7e8n81n/F7uvbtJ/YNQ6miXTb+FOT6JUK\nyQMHcPZO4BVWQAhid96De/Y8675J3orjjo5hp1K0VpaxdYFx5C60TIrIspH1GlGjDpaNVxqnYayw\n2B5gX4+5ZY4USnm0m8s4iQGEeOczF+bYLqShowcRZk836tJFvMV5ypXK5j3lVz9Kcv8BlNy0MEAp\nZBBCFGAaJvGREVSthh5PYgCR66ELDVJZ4gcOczmKk9gzSrnZS4e3invyBeyxcYydu9BjNl4IBCHR\n0gIqlUZPpQhSHbRPpSgOZNCbQzd0Xl9TgJdMJllfX7/6+vnnn39bvzoA4zUJup7ncfr0aY4e3Zxh\nOXbsGN/5zncYHx9n9+7daJrGsWPH+MIXvnC9fdhmmzellkmBaFOYEfSoOhvWDrqWFIYYQtZ9Fp/7\nEXq/xsD/9hADh0dY/eaZzVlHbzemYdLZ6bC62qSz8/Yxv94KlFuhGOtjOuxm/umIjlKddGMDrbcT\nTeTJRR56cZ14LkO0sYEx8MttknozEaFGeWGYWNzFMookHZeorZGsLN+8AoX3GdHqMmp1gXhxkWjF\npagcEjQRWppkVNvq5t32CEpozAOSxWXF8opPLGayf/+1r4vpmSxksgBErouecAiK64QbG7SmLhAa\nJl67iRFGhAsLCNNCy+XRu3vQS0UsO0b50hSxzh6klAx++F6KMzsYTPjYtkH5yR+jGjWqUYiVy3Fh\now2NHEEsSbb39lm9nbx4AY15urpj5Do/CO+iTYAQAmdiP1EYIdttWjNTuPUmUoY0T5/CSqYw9u0n\najbxF+Yhl8OMQhAaZm8/wooR7y3Tnp1BHx7FqFTQ7Bj2/kMMJUvUvDYdsYhgagZqFZQQ4MSRngem\nQaAZYDv4U5Oo2VlETy9W14MsJCeQtSbL8TGU2qztfC+Znq5QqbhkMiZ7ds0AGhJuepAnhMDbWEM6\nDmLPXvxXXiE88QKGHcf69Y8hDANzzwTewgLuhfNYto3m2LRXliGMSN7/AGGjjjx6H3rg0yXSCBmS\nDiu4kxcQjSa6phNGEuPuY7g/epzgqScRhon5oYeYSe+l7tlEjRxrrsHQFj0WLc2/RLvVIJHcoH/o\nnne8Py2dxjlwGNisxZOGTmDF8JZXCKYmkdUqzvhudMsitG00qZCNJpploqIQf3GBYGOdzNAQTnc3\nYbmMffReVKuF0nV6dw/gaRrJ+Vlap17a9HAcHkb1DRFE4P3ge4hyCW1wAE2BOboTzDRL9h6MdZ9C\n1435Ml9TgPdHf/RHPProoywtLfE7v/M7zM7O8rd/+7fXdIAf/vCH/NVf/RX79+8nk8mgXyn4TyaT\n1Go1arXa1ZTMn27bZpubRcbQyOV9nCEfb9om1SrRmN9AmgEqlaWxtIwdSyNbFYzcLqwggCjCnblM\n+tiDZDoTdHYmtrobtzzT8XFS2iuY3QZqJEX4koeUFfxyiL8hGXDi2I5LrG8v5Lfrmm4mkR4Q16oI\nqVMbzNMfzaIDIurfVLLYFln5BVSocDL91BudVGOraO0m/YDpecTi26nD7xSFgwAUBpHU0TSxmfp0\ng2iWtRkweB7t555FCUnUapO66yimrqPWVmm89CLtU6+iZ/PgtqBRR+/Ko2sazenLpH0P+/LLBOsF\ngs4eNATkchiBC5UyqYyildQwZURv14GbNxjvMlEUw7RAKQt494WromIRWVjBX13FHN5B8r5jNGdm\nUK5L6V+/jblaQLZaePNzKCVJHLmT1N596IkEQtMILk9RPXsau93CW14iMbSD7L33kbBOItstxE/+\nkyieQLbaWJ2dyHIZa8cwMvCg1SacmUUuryA6OhGpNO3kALmwQd2M6MvZ73lwB1cEbDSBUgKwAR/F\nzVeJVmFIKCVRGBE7dISEF+BOXsK/fIm140VUzMKIOfjlKpouEBP78J0E9RMn8DbWST/0UaLZWXTP\nJW7bDNcLpO76TaTvEWWy6Ik4VlcXyIhw8iJqcQHpuhhj/QgUia4IVps0ZQf9sa0TSQsjB12vEEY3\nN8KMikWCuRnQDMx7jxGLJwi+9+9EhQLF4/8PviZwz54hPjFB7tgHsbq6EMkUYaNB0Kiz/E//k8Su\n3aQOHMLo7SHRkUe0XfLxAGt0iHo5T8O00LMZ9Ctxj1xbg7U1sC2k0DEsC3wXMn1kWi28hGJkx42p\n2bzlp9rtTSPD3bt38z/+x//g7NmzKKWuBmvXwkMPPcRDDz3EX/7lX+I4DoVCAYBGo0E6nSaVStFo\nNF637a3I5eIYb2Sas4WUyzevZjCfT9LVdWsZEd/OxuvJdok77HWqCY9ah0awlkHJBioeJ/BdMp0J\ngqZBMvsh9J4+nCNl5Esv4QyP0jp/jsSePVvdhVufKERqeVRigPuNKQ61q9TTGbyLNSKp0CwTTdOg\nrx/nQx/CGBre6ha/r9Bakww4EXU/TtdMnaK/mTmj+ge36xzfBD2jaFsamZ2/QvDktyAJqgaWYyCs\nd8lY6ZcKh5C7AMHgICQSbdLpGx9XI5Uite8QslIiWF9DtVxiPb0kd+9BmCa+YeL+6AfIwMcrrhPb\nvYegXoNQYnbkEVFIsFEkctsIoaGHLtbEBLJYxD58BK3RpG/cRy2fQcslsfTb57rZMzFCs9lH5lqV\nOt4puoaVy2NkMtgHDxPk8oh8nnBxCU8o1OIi5sAA3vw8oddG2DFSR+4EQHMcAsMgNjxCY3qa/P0f\n3CymCkKcBx6k8Q9fJWo20HbsIPsbvwkyxOjpQU9sTrLKVovo0kXMO+5CSySxpE/w8nN0t0v0pWMc\nEBeAY+/NOLyGnTuzV1bwYkR0sKnx+C5EmkLg7NyNGomw9+1HN3VM26a1uIDR1Y177hzW4BDt6WmM\nfAfW6BgYJnpnF6SSBNUKXqmIYZoQSMyBAdyTL2D09pG4427ih+6EKMTs7kFaNiLfgX3vMYyRUbRi\ngezyRXq6Ig7Gl9C3UMtmx8hhqtVxstmbHETrGiqSiFgMe/9Buif2YwoN/+IZgkYVb3qayHXxlhfR\nMhmaszNomk78A8dof//f0NFonDuDPTBIamQUs68fubpKdP4s7VIJq7+f3MMPI3QDa2QMAGN0lHBi\nH5gm1sQE+vISWrlIOHeSsWAdjDgyeWOTY28Z4N1xxx1v+jchBOfPn3/Lnfu+j3XFOyyRSFCvZdk5\niwAAIABJREFU13nhhRf43Oc+xzPPPMORI0cYGRlhcnISKeXVbW9Fudx6y79vBaVS46bu63YOqG41\nlJNBbGgYMyYJy4S0hHt7aVkT2Jkuqo//kPT4OCqRwowbdH5gH86Bg9RPn9v07KlWsK6kCW3zJugG\nY5kEql4jfGYJsklER47KeJxI03GiEiLVSezeB0h94P6tbu37CxlgJbOoQKOrHJCMWfhZqAUmyaP3\nbnXrblnC5WXM9YBsdRlnNEa736LmSGIdGZLD2+nDN4efPQHmcu88+LDGx5HNJpZp4k9eBNMEw8Bb\nW6OxuoLV6RCsN1AdQ9jDo8T6+tGcOJmj99I4d5aw1cQ6dBBdt/DrNbTlJczduzHHdmKNjGI80SBc\nrCHOVeDXbp+sDcPQ3rvgDtCzOcSBgwjDQBgG+oFDaLkcXk8/YnUVe3gEr1LG7OtHq5WJje5EtloI\n1UC4NUQiTnttneT4OFZnJ3Z3L3ouR3tlhainB70gMXsHcPb+orCEFo8T//gnUFIiShtoy4v4T58k\nv7RGsNvA3j/+no3DaxFC/Nw5/u5EP0LXid1xJyoM0WIx7PEJMG2MO+8hLG6AHcOfmcbsypOdGMC0\nPRjZR2t+FivfQXt+DqnAGBiA9VVkEGLkOhCahjB07JGf+T/qnZ3Ef+Pjm3ZGSwt4kxfIv7KBSJdw\nfmM/W5n8r2mCXO7mX6N6Nod98NDmua1pCE0j/6n/Tv35Z5Guh5nM0F4tENs1Tu3cWWLZLDQ2SHWb\n+IcOsvHEj7E7u1GaIASidBozkUK2m+imAb6PM/H67AA9lyfxmw9vntNSom2sgZSEc9NkTq/ijzmY\nD9zYQsNbBngXLlwA4Etf+hK2bfOpT30KpRTf+MY38H3/bXf+k5/8hK997WsopRgcHOQP/uAPWF9f\n55FHHqG/v5/PfOYzGIbBJz/5SR555JGrKprbbHPT0A1CsxMZBhhajdjdBqo8jL7h0SIkfv8HAUHj\n2WfQnCrpBz+EnrZxywPoyRRuobAd4F0DeuMyYnWFqFoC30U+dB/iaRdndZbE2AhC19G7OrZTBm82\nQkPlEmg7fMTUDEZbEos5kDVRxrbP4Juh9ezGf+Kf0CqXEMUSjKawrZDUrkHU9Dm4wZqH9xVR9J5f\nq+7UFMptYe0cR3deH7QIIa6mNTkHDgEQrK3hzc3SfvlFsgNpvM4cyaE9mP1jGLE4QtMwEgn0ZALd\nzaBl8igUehjgaTpOMoE1tAPp+zQLk8QLG5jdDuLyc3Dkf3lvOn3VpO7Wu17Dcgl/YR6jsxOr/2cT\nH1rs9YJj1sAQ1sCmV5e/ukp7fg6jI0/87ntIju0EIJo6iZbOoSrrJA8fJmq3EbaN3d9PfXIS2Wog\n+vtx7r4Hc2AI7+IFZKuFtXMnejqzuXKytITRkcfK5qCjC+/saeTGKgZN4sWAsPwc5D/4zju+Bef+\nzxNsbBAsL2J09WD1/ayW76eBNYCeThM/9LNFkcpzzxA1G5gxSSzrIIIKka5IHT5C5Ho0Z2dI7hhB\ni8VRozuRYYgzNARXnufbJ1/E7O/H6OvHXZzftLwYGiayYwTlElZtAzNVJ1p4FXEgRFy7TuPruYXO\n+bBawZ+fw8jlsAZ3/MK5LXSd9LEHAFBRRPXki7iXJ1HlIvT0YDTLCJlDa24Q37MHGUUYqRTNuRn0\nTBbR3YuTzRKtFVCaQfulk+jZHNbYGCqKaM3NYSQS2D09oGn4sTjR/CyiWEZzWiTLLcL1H0Lff73u\nvl3Tt/P973+ff/7nf776+rOf/Sy//du/ze/93u+95ed+mp75Wh599FEeffTR1217+OGHefjhbVPZ\nbW4+2vI8avoiemMBvc9FRBZmdhCjs5tmoUp7ZRoVBhjZLEpvwuWztHJ70U2TYH2N5O7tFM1rwVy5\ngNooIMpNos4Uoq+DmL5EGLhE05dRgzvRihVUFG0bb99MhE7kp9GWK+itOlrFQ9d92m2dfCS3unW3\nLHomiz3WQ/B4FSuMKC4F2KGLmp/GTKe3dHb6lqBSRJ+/DPE40a7NGWdFBKgbf6h7G5SURJUSwjSJ\nykV0541XUsNmEzQNw3Hw6lWaM5cJowivEuLs20+Y6sLu7sW4EiAqKVGahruxjpNMIhREjTqxvn6M\nVAZhGLiXL6ECHzMWYroeQW32PahmA6REv/gKQkr80V2IeArxLoqkXC9hsQRKERaLVwO8sF5H2Db6\nlewsb3UVAKuri/blywT1OnZPN1Y+R/q++1G+T+P0q5huhGX7+J4kbHk4g4NEbRclJVYuR7vVwB7a\ncTVQlI0GwtCJ6jX0dAZvcRF3bprgxefJfuA+zB3DRLEE5uFDmE//G0YoEeuzqJ3vsNOlDbSlKVQi\njho79A53duNExQ1QiqhchCsBnooigkYdK5NFRRHt5UXMbJ6oViFqNjGyWZzRMeyeXlTxIjKKiKpN\nNDtG5eWXiPX3o2XSWB0d+OtrmAkbs7sXIQTuhfMIQyes1ZDxOO2FRfyZafyReWJdvZh3HsWa+ges\nVkDgNZBKvOlCpcRHYCDe6CqSEv3CywilCEcnIL61q+VRsQRS4q2soGXz6PH45rim0qgwxF9fw+7r\nx8xkEbpOYu9ecFtoiSSy2SIyM/ilMqHm0Fo6j7NjjMTOcZqXp5Ceh5nNojsO+vAo/swMQteIGpta\nI9WnnsRfKWD09mB1dyOEQJo2dPVgrDg4hTYy4aDC5Rvq2zXdqT3PY3Z2lpGREQDm5uZw3feXEeg2\n71M8F5k0iWQSfbaJcNK0PvJB2pcu01opYMRiNOdWIZuh1ZNA3xHHswKiuTqx4RHaS4uE1SqJ16Qu\nbPOLRJ6F5cQJzU6a5U68uSRBto7bbEJREBXa7PxvB6/OPG5z89CjXpizkPUY9d1pmkgap1zarSat\nxXnigzu2uom3JGH/B/Ar/0KzYSFHk7TXQlQNot6x9+bh/hZG81oI0wDPAzaDu7ZxCZTCjkbQ3wUB\nCaFpmANDqFaLIIponX4VZ3Bos34XMDNZwnqd2qULqCAkc/gIXrGIls3hnztLU+SJDxwkPTj0uv0G\n1cpm7VYYEtUbpPfvxzpyB8HyIloiSdRuE7g+/mKIVzLQOx3CYOC98T2VEYQhkenhahfAyOKEu9/4\nwXgLMAcGCJaW0DIZaufO0F5YICiuo8fi9Pzmw0jXpbW46YkcuW2CZh0lQ5zxPRiJBPLKypBmWoR6\nPzLZRawvDeXSZq2TbYAQ2J2d2K+xdFFKEToxNCWx+zYtdaIopDk9gzM4gGw1CS5dIGo1IN2JlduN\nYglZ63/HyZHCq+NmVpGawmQMna3xZTYHBgkKBczunynPrv3w+7RXlrGSCaxMDqOjE69UQgtCEGB2\nd5PsG8DMZGjP2/hr68TSaUToEx8YxF1fRz9wEN2yyBw6fHW/YbtNaOjoehJ7aAhhmpuTDo06LC9j\nIKBUxMmNoMQctEcR4o0nIgJRwtcLaMrGid4g2pYRRCFoOiJwUWxtgGf09yPnAtxikfK/fQd3bpbk\n6BjO8ChGIo4KAvxCYfP+47poMYf0fQ8gNI3m5EWilo4a3oUWTeN0lVC+i9A0Unten2LslUuEGhjZ\nLGZu0/Mgcj3aG2skuzoRV9SBomadcGUZ00mipXYQaW2U8YEbOq+v6WnrD//wD/nUpz7F/v37ATh3\n7hx/8Rd/cQOH22ab9xZfmNRjkmDfXSgbwqxBq34GuVYnvmN4c4alowMZT+Bl6vhrVcrPP4VZzRJv\n1ElP7MMrFrcDvLdB9k3QWq4RVudpPjhGy6+g8in8SY1mpYptVnBrVbK3QErG+41Gj05r3wQi1YFf\natB6agmJoHZpCn9lhVhXD5q9LRzyWmSzSW21SL17hGCwRPWVSyjXQPOSjGW3wEjrFkN2D6I0A5X4\nqeiZuqIboV1ZyXt3+GkqWvvUK6AU7cUl8DYnk5MT+0AIGlOTKM/FGR7GWy3graxg5LIo06K9tIhf\nKhEf24l5JZ3TzOYw0mXyd91DfMcw2pVJJuvKxEfz8mU0FM0oRHbvpBI3yL1X9auGSTQ8ThgVIRmi\nUHALrR/rjoO+axfu2hqR7+OuLBIVSwhdp3F5kuSu3Wi6gUJh9/UjPQ+h6WiOw/qPf0TpxPOkJvaR\nOXQEogi7qxvleqRyOZyBIdC0qw+2r6W9skTo+6hIEv/pg2+9TurOOxFRiDW2i/DSRbRsDlWpsNE9\niuzsx5sYfcf2hbJ3iLCxBE4SKUL0Lfo69GQSfdeu121rFQq405fxbYvckTsIG3WcgSHCRo3mpYvI\n+XmsbBoZBJvKpbk8YeAR6+0n0XZJHzhIfOgXJ/xaczNIz0M6cZwrKYrJO+4kbDZQQNRuoytFOTuK\n+v/Zu7MYu67z0PP/PZ55rHmuIlkkRYoWLcm0rNi5SezOTSNq2fHtdAL7wjBgO3nLBeIBcBtxJ4gR\nO0j8YCBPidFQDFiIkU4Cy0ji2+0xTuRYE0WJM1msea4zj3taqx9OsURKHIrFmmv9DMni4alzVq2z\n9z77W8P3tWdxHjtJJxLtDmGH1Hw0jLtfJ0yLYOgomu8jUzt/rTXCYcKjo9TzK9QuXUA0HWpSEBkc\nItTZjbu8iN3dTWNpkeX/91/xSmXST54hfvQoVkcnbj6PZpgkjoxi2jZ2R2dr3+ItpBDUxsbQTAO9\nsxtjNZmknkwSP/4IocHhtedqgG5ZOMlhqiPHCdrDiEhlQ+Ud1xXg/fqv/zqPP/44586dQ9M0Hnvs\nMdradv6DUZT7EcUC+ugpxLHDBPEwpasXqF26RlR0EMm20fbBX6e+skTh7FnM+Ai5n/2YxsUcsk0j\nmc5ixBKE11Hz8aALTv4q3kINjr8HvfQm1cUFjJeWCHccx8/NYYZD+IXcTjdzX9I1l8b7P4SeX6L5\nf5+lkdfRhAZ6aymiZm/LXMSeIvIrhNu6KfT1UVrUqdamCOZ8Eof62JFCWruNpiE7btn3g0koGALE\ntsxoRAYGcVdy2O3tNMaug6a1EnqEQkQHh9F0DU1CdGgEu6OT2pVLhHt6aOaWMS0bZ3mRzHuewkom\n0TSN+OHDNJaWKFx4k0hnF9Get/ZY+s0alYsX8DyTZv8AkSdP0pYMb1+clcxgkgG/srqsbfcs0bwp\n1NFBUKuSeeqXcKemwDQx7DC6aZI6/VYyvvjRY/j1Ovg+TrGIpkncpQVy//5vhLs60UMW8dFRvGqV\n/Pk3sWJxkrcEMV65TP3G9dYWLSEwopG1ANBub6e5tERs9DhGOEwzncaZuEHYNHEffZJGpoY+fIyH\nHX/QNJNQ4kkkHqbcXRnNO375VyiGbMxwmOixR4gdbiWVqU6MExkeoTY5hWg0EUKy8rN/w4hECff2\nIDUdt1Enkrj771O+cIHI4CCsbkvRQyH0tiygEfgBVKvw5NNUQ3PI0RNo8s7XSFt0okkbXd5jlj+Z\n2UXDGK3VA+kn3oNbLODOz5M69RipJ9+DpmnY7e1IKWlcu9oq81Gt4C4tUcjnMBJxrESSxvw88cOH\n8ZH4C/OtZZm3ZLB2V1ZoTE6gx2LEVz8zKQRGtg0jHifU0ZqllVLiWCH8fJ7EiZOUrKfxBkNE070b\nOq7XvV6qvb39Hfvp7ufcuXN89atfRdd1Tp06xRe/+EW++c1v8qMf/Yje3l6+9rWvYZomL7zwAs8/\n//xakpWbdfEU5WEZ/YMkikXS/f1Uxq4RLGlY5RjJU48SGz2CEYnglkpEBwZwl1ewRJJQVzfJd52m\n7Yknsdvb7zjCqLyNYaE//gGsfA7t6lUSkwbGkUfRIxGsaC8EAeE+tVRwK4RFL91mCKP9DNf0Mcx0\nD0GzSezQIRJqD+kd6d292E2HaOQ4XtjE7XJw3Fmiq+n1VWKld9qKZZl34jebmNEYodEsANZjp/Fy\nOfTVG6b0Y6cJajVCHR04hRx+rUbs+HGsRAozFqdy4U0i3b24uRzWLYNzTrEAQLOQvy3A0yRIQ4dY\nijBpet/137Dl9n/+JrsrmPArlbXadZqmERtppXXn+Ama8/NYtyypvKl64wZufgU700bHL/8Xqr29\nIAWiUsGvVAi1tW5knWIekGufyU1euYimacggIPvEkwAI328l6YonILdCfXwMO/0ETj6Hlkrj1+sk\nO54gfiiJGayvfNf9GISB8H2ftx1kEBDU65iJBPHhYexUEgwTe/XYdstl3OVlvHKJzg/9L3jlEn6l\nSnN2iqBWA3S8eiv7/NuP/ZusRIL0yZMIz0f4PrppUr1+FU3TcMtV7EwaL5kkkR4iNPQklrx3P1s7\ncP5sVOC6yCDAjETo/o3fxK/VkI5z231f5doV/HKZ8PAhUk++l/qNMULZNoTvoZkmoY52gmYTv15D\nNy28UgnjlvPDLxVJHDnSKkSfSCClpHzlEqJRx0q3YaVbtYG9conAbSK6ugl0nY7Dv0kQrWNs8Lje\n0g0xfX19fOtb38K2bT73uc/x8ssv89JLL/H888/zN3/zN/zgBz/ggx/8IN/5znd4/vnn+f73v893\nvvMdPvWpT21ls5QDxGhvXzvR/GYDf6WBpoeJDo+g6ya1K5eJdnbhVWukHzlJUMqhhW1ktUJzdhq/\nWnnri025J6O9HS2ZJPiBBqEEke5urHAENxrHmZ5E+C7NhQXC3d073dR9RUPHFq0bp+iRUbxQCBMw\nE2rm+W50y8I6dJhQPo9/6QKGbhLp6yMUCuGrAG/H+PU6lYvnkUDq1GMYoRD18RsE9RpepUJ8dBQz\nGsWMtoJNXdcJtbVhp9JEB4dojI0R6e7FTCQJ35J5ECDWP0BjYYFwR8dtj0cGhyldvoIXCEIdQ4RT\najl+fXYaZ3ERIxQmefL2tO71mSm85WWc5aXb9nEBeMU8zZlpNCTxw4eJdHS2lnZOTWEmk5ir9eyi\nPX1IP8CM3x7URnr7aQiBtXrtcosFyteutmZue29PuhPu7MQrlYgeOdp63d00JbSJyhcvIFyHcE8v\nRiRCffwGCIn17sdbCctEAIaOlU5jxmIEuRyWbWMefwS8gOjICH6jccdj/6ZwTx8yCPBrdQpnX8NM\nJdcWX4ba20DXiZ54FLura/t+8W0gfJ/yG+eA1uyzlUxSH7sOUhA060T6BvBKRepXr2EkE0QHh4gN\njxDp6MBdyRHq7V07pgFivf3IwCf8tsGP8MAgzYV57PZW/5cuXqB8+RKhTAbrli0BViKJGU+0rl9H\nRluZg8XG9yhuaYDXfssvaVkW165d48yZMwA8/fTTfO9732N0dJSjR4+i6zpPP/00f/RHf7SVTVIO\nsEhPP23vOYMeiREdGaHy+lmCUhG9kCf1VKs4avbM+6iNjxHU6kjfRzN333KZ3S7z2LvJ6BpW4OOu\n5NBKFcKPnsJOplWSlS2WOvko2dFRgmqNuBqYuCfNMEg9coL6hfPEenpoTE0RO3wYXVfH6M66fWeP\npht4y8ure/Fur3OWOHoct1jEzmZxl5YIGjU0ERAZGkJ/29JkKxrFOvTOc8JKJkmdepRwbw9WOrsF\nv88eJCWiXiPI55DHH7kt87Gum8jAx7Dfua/XCkcQ2Sxm+K0SF4ZtE3vbXjLdMEjcYV+7putEb9mP\nFDSa6KaJ8APstjaMSATNttE0rRXw9e7fmpVBpYJXyLVmiXQNiWx9DoEAQ19bRm6nM8SPjKJbNqLZ\nxCvkQNcJt41gZ1Znwe9y7N90s99rk+MEroN0XJInH8WvVdeC7f1CBgHO7DRmOou+OlB069iAZhgI\nx0UzWisG3Pl5or09+I5DdGgYACuTxcq881oR6+2743sa4fBteRyE5xI7dAgrGiE28tbjmq6T3MRV\nN9vyTXb58mXy+TzJZHItI1Y8HqdcLlMul9eWZN58TFG2QrS3F92yMKNRNE3DymZxblwj1NuPt7yM\n1dFBbGiktSk/Fkd43lqqbWV9dNsmfeoU0vfBcQmKLxE/doxwXz+hkUMY4d2x7GW/imbb6Povv4Yo\nl8k+8Z6dbs6uZyWTZJ56itqFC2ROvQszHifcq2rg7RQzGiVx4iRoGsZqYqDI4CD+wjyGHcJbWblt\naaBmGIRW8wHY7e34pQJ6MvWO4O5+YoeOYCZTRDr31wzFRkX7B1u1wbLtONNThG+5OQ339mJmMmuf\nz61CPT2gQWiT+jHS04Nmmmvf2bfOlux3zfExkJJwPInR2bG2qiD52Gk0w7gtkYedbC3hk1JiJtMg\nBdYGViFEB4fRQ4vY6XQrq+0+C+4AnOkpglKRoFAg9ti7STx6CnwfczUOSZw4SeA4a/d+dlcXzsI8\nieGRTduukzx6vLVkebU0wlbZ8gCvWCzyla98hW984xucP3+ehYUFAKrVKslkkkQiQbVave2xe8lk\nopi7bFalUNi8PYPZbJyOjt21Fn95ubLTTdg04Y4OGvoSdX0Wa7iNWPUk0nPRYrHW0iDPJ3bsOLpp\nrmVbUx6MnUwR4FAzp3Gm6hjjZUKHj6jg7iFVjQmE5hP1+zC588CDHo8TSqfxTQv50AnDD4b48RP4\nuTzu7DThJ9971+fV9Vl8vU7E78Jib9/4eFRomAsYIkJM7K5ZkJvLL2/STLNVp9Tz0N+2P99ZWqI5\nO4Pd2UGkb4DY0dtTk6+XYVl33Ju0FZr6Cq6exxZZwuKd+9h2i1B3H0GxsJbx71a3Dnw25+dxFuYJ\ndXUS7u2/48zGw7jbssLdytEKOMYylkgRERsPdI1EEr9QwMxkbgvW3j54ETSbVC9fQrcs4idOEh0d\nfftLrZumaUQ2YQuFRFI1xpGaIOYPYLB7sjgbySR+Po+xGhSbby9svlpjE6A5N4OzuESotw8ru3mJ\nJW9dZr6VtvQO1vd9Pv/5z/OFL3yBtrY2Hn30UZ5//nk+/elP8+KLL3L69GmGh4e5du0aQoi1x+6l\nUKhvZZM3JJ+vbupr7aeAajcKtCYaJlJrEl3dXyA8j6DWqv3k5fMYahT/oQRas7XuIRshEulXS10f\nkkQg8ACdQGtgyjsHeEYohNnXjxkEBJUKdD5s0vD9T3oeWiRM6OixO97M3hRoDhoGvt7EEns7wAv0\nJhoGgd4EsdOtuTdN14k9euqOf+eXSmi6hpfLEe7t3xMJsQKtgYbZukbuYpF7LOm7lV9ufQZ+uQy9\nrVkkpHxHqviDItDqm/L5hkcOwTq2g/qVCiDxqlWE4+yKgVRJgMBDxyDQmhhy9wR4VrZt3cGat3p9\n8UtFWN1/KIVoZfXdA9ca44//+I//eKte/F/+5V/4h3/4By5fvsw//dM/rdXR+/rXv47ruvze7/0e\npmliGAZ/8id/wuTkJH/4h3+IfY/lFfW6u1XN3bBCIc8PX53Bjtz9S79WnMcKx+/5HLdZ4UNP9JPd\nxJEC5Z0MGQY0QqKd6uQktckJjEgEK5GkvrSAU6sgpVhb9qA8OIMw9fkFnMkSzcVcq2KObmDdI02z\ncncaGroMYUgbW2buWH8IWlnS5v/tx1RnZsk8/jhmZHsyH+5lmmniez7z//4T6osLxPoH7niTZMgw\nGjph0XbX/t8rDBlBIggFbehY9/+BXcqIxWjm8xTHrlO88Cbh9k6sXb6Mz1hNHx8Sbei7sCTC/Qjf\np3DhPM3lJcLtHZjxOML3Cff0gWFQOHeW+vw8ViqFcQBLtLQ+X7n6+W7eHMpav68sE74lu7cZi+HV\nazSWFvGqVUJt7ejGzh5XGjqGDKHLECGZ2dG2PAi3XKZ0+RJ+vU4ok8GIxhBBQKSvH900cSsVihfe\nxFleJtzVtSuCvFjs7sHzls7gPfPMMzzzzDO3PXb69Gk+85nP3PbYhz/8YT784Q9vZVMUZY1BCEO0\nTgqvWALALZZIjIxQ+dEPkc0ahhki3q/S+j8MrQiWH2b54jkCxyPcpmaTHoZF/L6Z4px8DmdpCa9S\noTk/T1gNFq2LWy5Sn57ELZXwqlXs1DsHd0wimGJ/7MltBapbtzzQq1Ypj12DQBDp6dmy5Y9GOEy4\no5PStStI38ct5Ins8llrAwtjC/teSkl9fg4jEsGZnwMhSRx/ZNO2HHiVMtL3EELgNxpYsdhaAgnh\neQg/QDN1Aqe564PtraBjYpTDNIqLRHv60A2D+vwcztIi0b4BQncoL7Eea/0eBPjNJtYtS/xCnd24\nhQJSBgjP2xWBtUViyzObNhcXaSzModkhrFSa2EOuvHJXy3e4q+U7zFgMM/bWNGrQaKDpOsLzkELc\nlnxoN1KbjJQDLTY8jJsvEO3ro5nPIdwmQb2BpWoxPrRY/yC1iQnsTBteqYypZu+2nJ3OgGlhZzME\nzd29BGw3EfVWPSIMk1BWZVJ8WOWx69QmJzEsCzMcgi3c3xbp6SFz+gn8eo3Y4NCWvc9eUZ+fX53N\nqWGHbHTTxCuXCG3SYE8ok8WrVdF14x0BnG5ZJEdHkX5woAeXyjfGWvX/vIDkyAhePodGawBuowHe\nbf3+tv1bdjy+ljX5IAXVbiGPDAJKF94kfvgIhmU91J7NaN8AUsi1GoNvd3PwyAiHdnyWdD1UgHcf\nQRAwMXHjns+ZmprclPeSQqzrtYaHD2HsgYNrLwil0oRWNzDLaIzowCBBs058eHhnG7YPWPE4nb/0\nAYLgx4QyWRU0bwM7kaTjvU/h5nLEDx/e6ebsGfHRoySXlwi3dTxwBkblncxoDHs1XX50G1ZCpNSx\nvsaKx2ksSEKZDOFMGoJg04K7m+61uiWU3jtL8raKFY3hFAtrwVZ0YKi1rO9ttRkf1D37/QAG1NGB\nQRrz88QGB5ESjIdMXHK38h232u0rBG6lSSm3dBJ1aWmJ3//932dsbIzXX38dXdf55je/yY9+9CN6\ne3v52te+hmmavPDCCzz//POk02n+8i//cq10wtttdwKSsbFr/I+/eIFo6u4fam7mEm39jxDP3LkG\nBsDSxGtEU133fQ5o93yvemmJb3z+WQ4f3nimJEVRFEVRFEVR9q57Zd3f8jRH6XSav/3bv+Wxxx4D\nIJfL8dJLL/H8889z7NgxfvCDH+B5Ht/5znd4/vnnefbZZ/nOd76z1c16INFUJ/FM312t5l8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LEbaOE5utMNrMEwoVuyQe6He0VRreLnlhGuh18qUH7jdVKnHsNYTSIppURUqzB+o/V8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zzm0DlP/mCzw5t4e9Tpaa66cw1cZd7+vA2tK+pq6Vq9m7t4tq1SMcXn+9SJxE28VWWHNbs5WE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\n+dbtjx5N8sILoxeXdJqPmnrwfud3fof3v//9vPnNb8YYw49+9CP+5//8n7X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qFOpxUhfP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1wmmMngOy4y/faNZoQQJA49im9ZGNF7WWOlKNvLes8/gLe0RDAWJZkY5VAIap7GQW8Ej/uZ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\nf0ylUuFzn/vcq/7/8Y9//JaMGBnp+Gjruo5xBweASinc0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n2DRB0N0qPrbvOVTUJ2ASGg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\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QGeqhXnFpu/t+ldzdBF1odNx1D6Wnfog9sg/e+S5oV/MVm4135nn0yhzmwCDheJzwnj3U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ygVkssl1rTP7WpsbJmZmRJ797ZhGFc/0YL0PPyxEYRlYURimLncBkZ5FQb2NH9a7SrOt/UgpWJk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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x109d80b10>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Ok. This looks pretty clean. Let's save this for future use."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "qsos.to_csv(\"qsos.clean.csv\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Data Munging done. Let's do some ML!\n",
      "\n",
      "### Basic Model Fitting\n",
      "\n",
      "We need to create a **training set** and a **testing set**."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "X = qso_features.values  # 9-d feature space\n",
      "Y = qso_redshifts.values # redshifts"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print \"feature vector shape=\", X.shape\n",
      "print \"class shape=\", Y.shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "feature vector shape= (9988, 9)\n",
        "class shape= (9988,)\n"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# half of data\n",
      "half = floor(len(Y)/2)\n",
      "train_X = X[:half]\n",
      "train_Y = Y[:half]\n",
      "test_X = X[half:]\n",
      "test_Y = Y[half:]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "** Linear Regression **\n",
      "\n",
      "http://scikit-learn.org/stable/modules/linear_model.html"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn import linear_model\n",
      "clf = linear_model.LinearRegression()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf."
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "SyntaxError",
       "evalue": "invalid syntax (<ipython-input-85-95a498422503>, line 1)",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-85-95a498422503>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    clf.\u001b[0m\n\u001b[0m        ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
       ]
      }
     ],
     "prompt_number": 85
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# fit the model\n",
      "clf.fit(train_X, train_Y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "LinearRegression(copy_X=True, fit_intercept=True, normalize=False)"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# now do the prediction\n",
      "Y_lr_pred = clf.predict(test_X)\n",
      "\n",
      "# how well did we do?\n",
      "from sklearn.metrics import mean_squared_error\n",
      "mse = np.sqrt(mean_squared_error(test_Y,Y_lr_pred)) ; print \"MSE\",mse"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "MSE 0.659053404786\n"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot(test_Y,Y_lr_pred - test_Y,'o',alpha=0.2)\n",
      "title(\"Linear Regression Residuals - MSE = %.1f\" % mse)\n",
      "xlabel(\"Spectroscopic Redshift\")\n",
      "ylabel(\"Residual\")\n",
      "hlines(0,min(test_Y),max(test_Y),color=\"red\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
       "text": [
        "<matplotlib.collections.LineCollection at 0x10e61f250>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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XvYqVK1fyl3/5l1x88cX8xV/8RfO4e++9d9q67VWrVjUD//5QLBa57bbbuPXWW1mzZg2P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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10f96fb50>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# here's the MSE guessing the AVERAGE value\n",
      "print \"naive mse\", ((1./len(train_Y))*(train_Y - train_Y.mean())**2).sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "naive mse 0.643120844956\n"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mean_squared_error?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "** *k*-Nearest Neighbor (KNN) Regression **"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn import neighbors\n",
      "from sklearn import preprocessing\n",
      "X_scaled = preprocessing.scale(X) # many methods work better on scaled X\n",
      "clf1 = neighbors.KNeighborsRegressor(5)\n",
      "train_X = X_scaled[:half]\n",
      "test_X = X_scaled[half:]\n",
      "clf1.fit(train_X,train_Y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\n",
        "          metric_params=None, n_neighbors=5, p=2, weights='uniform')"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Y_knn_pred = clf1.predict(test_X)\n",
      "mse = mean_squared_error(test_Y,Y_knn_pred) ; print \"MSE (KNN)\", mse\n",
      "plot(test_Y, Y_knn_pred - test_Y,'o',alpha=0.2)\n",
      "title(\"k-NN Residuals - MSE = %.1f\" % mse)\n",
      "xlabel(\"Spectroscopic Redshift\")\n",
      "ylabel(\"Residual\")\n",
      "hlines(0,min(test_Y),max(test_Y),color=\"red\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "MSE (KNN) 0.239666881833\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "<matplotlib.collections.LineCollection at 0x10dac27d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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rRN1/m7re78i2Vkb5ZCXP0bl2f2WgJ9ZhnMrnDOX6j6+M5k/mlqdQKBSKc4uB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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10ddd62d0>"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn import neighbors\n",
      "from sklearn import preprocessing\n",
      "\n",
      "X_scaled = preprocessing.scale(X) # many methods work better on scaled X\n",
      "train_X = X_scaled[:half]\n",
      "train_Y = Y[:half]\n",
      "test_X = X_scaled[half:]\n",
      "test_Y = Y[half:]\n",
      "clf1 = neighbors.KNeighborsRegressor(10)\n",
      "clf1.fit(train_X,train_Y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\n",
        "          metric_params=None, n_neighbors=10, p=2, weights='uniform')"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Y_knn_pred = clf1.predict(test_X)\n",
      "mse = mean_squared_error(test_Y,Y_knn_pred) ; print mse\n",
      "scatter(test_Y, Y_knn_pred - test_Y,alpha=0.2)\n",
      "title(\"k-NN Residuals - MSE = %.1f\" % mse)\n",
      "xlabel(\"Spectroscopic Redshift\")\n",
      "ylabel(\"Residual\")\n",
      "hlines(0,min(test_Y),max(test_Y),color=\"red\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0.234493621244\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 98,
       "text": [
        "<matplotlib.collections.LineCollection at 0x116849690>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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4RaPh943btkEq5Tc3W5ZFT0+WyckqigKxmIckdTE9HePRR4tccMFq9u51CYfb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\naSwtjdje7hCGAd2uw/XrZcLQYzwe0m4PWFtLUa1mkaR1FhbyVKsrbG3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fD1hdtXjttTH9\nfrwNF0UR6+sCipJGUVSgyPr68RovnTSrq21efTXk9dcFrlxp3fc1lhUQhnFSXhj65HLRuznEhIQH\n8kAh/9KXvsRLL72EZcUZq4uLi/ftaJaQkPD+plYLUBQTURSRpAy1Wtx/PBbBw2VmYfj4Q+v9/ohm\n00JVU8iyzmhUYGend8/rFhfzTEx0Sac7TE0NmJpKDPMTniweuEeuKArp9OHa0SRrPSEh4W6iSODO\nre8oih9IkoRljbFtE0EQ8P0RpdLj78nuuj6SdGAbK4oivn//1XYi3glPMg9U5Hw+z40bN/Yff+Ur\nX2FycvJEB5WQkPD0USqFhKEHQBCMKZcPVP3MmTyVSod8vs3yckQ2+/hL5/L5NHAQTg/DHqXS4x9X\nQsLb5YHT4j/5kz/hs5/9LKurq3z84x9H13VefPHFd2NsCQkJTxEzMzlSqQG2PcCyFDKZAwMZQRCe\nuFWtKIpcuGCxsdECBCoVA1VN6sQTnj7eUsg7nQ6DwYAvfOELtFrxzPWf/umf+PVf/3W++c1vvisD\nTEhIeHooFI5n4XoUvZ7N2ppDFIlkswHz8ydrGCPL/3979x4cVXX4Afx7793dZLNJyCbkgWKQRyBC\nf4oOjSiUCAIWgQiCDCoFIxZGWwHRoijUqQ+oMKVjwbFSRdBaK1BAtNKZSoS0PEV5iCAPA5gYkpDs\n5rXv3Xt+f6QsRghkQ5KTm3w/M854k5u73w0hX859nGNCevrln2svLq5CRYUCTRPo2tWC+Hhri2Yi\nilSDp9Y//vhj3HHHHXj00UcxfPhwnDx5Eo899hhOnDiBdevWtWZGIuoAdF3HyZMB6HoihEiAw5GA\nkpKLbz5rTeXlNSgtjYOuJyAQsOPkyeD/5r0najsaHJG/8cYbWLduHTIyMrBv3z5MnToVy5Ytw89/\n/vPWzEdEHUQgEICuR0P73w3uqqpB9kSSLpcOVb3wa1LXrfD5/IiJ4aic2o4GR+SapiEjIwMAMGDA\nAKSnp7PEiajFWCwWmM0XmlvXg4iNlfuYms2mQtcvTF6jqh5ERXFWN2pbGhyR+3w+nDx5EkDdhA6K\nooS3AaBXr14tn46IOgxFUZCREY3vvnMgFFJhtwskJ8u9Qa5z5zj4fJVwOFRomkD37hZoGpdepbbl\nskU+Y8aMeh/74XZeXl7LpSKiDikmJgqZmVGyY9Rz7bUJuPZa2SmIGtZgkbOoiYiI2j750ysRUYvy\neHwoKvICUJCcrCEhwXbFryEi4+Bcq0TtWCgUwjffeOF22+F2J+Dbb7XwYiZE1D5wRE7UjtXWeiBE\nfHjbZIpBdbUTcXF8fKotEUKgsLAKXq+K2FjR5mbBo7aNRU7UjkVHW6DrPmha3Rziuh6C2Sx/5TGq\n7+TJSrhciVAUBS6XjlCoEtddd/kZ54jO46l1onYsKsqC664LIBSqRCBQBbu9Eikp8Vf+QmpVLpcG\n5X9Lx6mqipoa/mqmxuOInKidS02NQ2qq7BR0OSaTjh/O/Goy6fLCkOHwn31ERJL16GGFojgQCFRD\n0ypw/fV8soAajyNyIiLJYmKicOONUeFZNIkiwRE5EVEbwRKnpuCInIhahMfjQ2GhF7quIDFRQUpK\nnOxIRO0Si5yImp2u6zh+3AvADgAoLPTBZKqF1xtCMAjY7RY+y07UTHhqnYiandfrQyBw4YYtkykK\nBw9WoKwsAU6nHcePA9XVbokJidoPFjkRNbuoKAsUxRveDgb98HpjwteATSYbysuDDX05EUWAp9aJ\nqNlpmoYePRR8950Tuq6iUycfhLD+aB8+K03UHFjkRNQi7HYb7PbzW3E4e7YaRUUuKIoZFksNunbl\nDHNEzYFFTkStokuXeHTuHEAgEIDVmtDhHrUKhUL47rtahEIKOnVSkJzMu/ipebDIiajVmM1mmM1m\n2TGkOHq0CqFQZwBAdbUfqlqLpKRYyamoPeDNbkRELSwYDMLjuXCPgKZZUFnJewSoeXBETkTUwjRN\ng6rWf9zOYml8kfv9ARw/Xgufz4SoqCB6946FxdIxz2zQxTgiJyJqYYqioEcPDbruRCBQg6ioclx7\nbeNv9isocCEUSoLJ1AmhUBJOnXK1YFoyGo7IiYhawfm7+HVdh6pGtrpZIFB/zOX3cwxGF/CngYio\nFalq5L92bTYdQggAgBACNtvVXV/3+fwoLa1Cba3nqo5DbYPUIl+1ahUyMzNRWVkpMwYRUZvWvXsn\nJCY6ER1dicREJ7p379TkY1VXu3H4cBAlJXYcO6ahpKS6GZOSDNJOrZ89exY7duzANddcIysCEZEh\nKIqC9PSEZjlWcXEAJlPdTD0mUzRKSjxIS2uWQ5Mk0kbkixcvxm9+8xtZL09E1CFdPBFPx5qYpz2S\nUuSffvop0tLSkJmZKePliYg6rNRUDaFQ3aNwoZAfKSlCciK6Wi12aj03Nxfl5eUXfXzOnDlYuXIl\nVq1aFf7Y+Zs4iIioZSUk2JCZ6UVVlRM2mwnx8U2/3k5tgyJauUWPHz+Ohx56CNHR0QCA0tJSpKam\nYt26dUhKSmrNKERE0gkhUFnpgqIACQmcspUi1+pF/mPDhg3Dhg0bkJBw5Rs5zp2raYVELSs5Oc7w\n76M9vAeA76MtaQ/vAYj8fQghcOSIEz6fHYoiEBNTiT59EuvtEwwG8f33tQAUJCdHIyYmqplT19dR\n/yzaqsYsriN9QpiOtgISEdF5ZWXVCASSoGl1vwfdbjuczhrY7XW/vHVdx+HDNVCUurOVFRXV6NtX\nQXS0RVrm85xOF4qKghBCQVKSjmuvbZ676ily0ieE2bp1a6NG40RE7Y2u1x/MKIoKXb9wkrSqygUh\nwou6Q9Pi4XA0zyQuPp8f585VwePxRfy1gUAABQUKdN0OIRJQVhYHh6O2WXJR5KQXORFRR5WSEgtd\nrwhva1oFEhMvnEq1WEzQ9UB4W9d1aNrVv67T6cLhwyEUF9tx5IgecQm73T4oyoXV3FTVDLc7dPXB\nqEmkn1onIuqoNE3DjTfGo7TUCUUBUlMT6o3QbTYrUlIqUVIShKKoiI93ITU18TJHbJzi4uAPJoWx\nobjYicQIDmuzRQNwAahb+CUY9CE2lnUiC7/zREQSaZqGa65p+BGw665LQFpaAEIIWCxXX+IAIMTV\nTQpjMpmQkaHh+++d0HUFaWlAQkLjV3Oj5sUiJyJq48zmpq89HgqF8O23NfB6VURHh9CzZzxSUhQU\nFXmhadEIBn1NmqI1Ls6KzEzrlXekFsciJyJqx779tgYeT91I3uMBCgocyMhIQHS0G7W1TsTGmhEf\nz9G0kbHIiYjaMa9XveR2fHwM2N/tA+9aJyJqx6KjQz/avrq1zKntYZETEbVjPXvGw2p1QFUrERNT\ngR49rjxTGBkLT60TEbVjmqahd29OutWecURORERkYByRExFRk5WWVsPlAqKjxWWfh6eWwyInIqIm\nKS6uQmlpHFTVhOpqHX6/E9dfb7/yF1Kz4ql1IqIWJHml6BbldCpQ1brxoKKoqK5uhongKWIckRMR\ntQAhBI4fd6K21gJVDeL6682w222yYzUrTdMRDF7YVlU+2iYDR+RERC2gqKgKXm9nmEzxUNVEnDoV\nanej827drBDCgUDAA113olu3KNmROiSOyImIWoDfX3+cFAqZEQqFYDK1n1+7VmsUbrrJgkAgALM5\nvt7KbdR6OCInImoB8fEKQiF/eNtq9barEj9PURRYLBaWuETt76eKiKgNSE6OgxA1qKx0Q9N0dOvG\nGdWoZbDIiYhaSEpKHFJSZKdo+xyOWlRUuFBTIxAfH4PUVDPi4rhEamOxyImISJri4ioUFUXh1KlY\nCGFFSooP1dUCN9zgg9XKm+cag9fIiYhImvJyBW53AKraCZpmQWUloGmxqKz0yo5mGCxyIiKSRlEE\nLBYzQiEfAEBVBUKhAKKjOblMY/HUOhERtSqXy4uKCh9UVeCaazScPq0jIaEGDkcFUlIUdO7sg93O\nqV4bi0VOREStxuXy4tgxHZpWV9SaVo7/+78oeDw6bLZYaJrGR9kixCInIqJW43D4wiUOAD5fPILB\nADp1ipWYyth4jZyIiFqNqtafplbXgzCZeD38arDIiYio1XTpEg+TqRyBgA8+nwtdunhhsVhkxzI0\nnlonIqJWo6oq+vVLhMdTN2Wt2cyJX64Wi5yIiFqd1RotO0K7wVPrREREBsYiJyIiMjAWORERkYGx\nyImIiAyMRU5ERGRgLHIiIiIDY5ETEREZGIuciIjIwFjkREREBsYiJyIiMjAWORERkYGxyImIyLB0\nXUdNjQs+n192FGm4aAoRERmS1+vHN994oOtx0HU/unatRlpavOxYrU7aiPzdd9/FqFGjMGbMGCxd\nulRWDCIiMqiiIg8UxQ5NM8FsjsH338tOJIeUEfnu3buRl5eHzZs3w2w2w+FwyIhBRESGptTbEkKF\nEAKKojSwf/skZUT+/vvvY8aMGTCbzQCAxMREGTGIiMjAOnfWEAy6AQBC6LDbAx2uxAFJRX7mzBns\n27cPkyZNwi9+8Qt89dVXMmIQEZGBJSTY0Lu3QFKSE9dcU42ePe2yI0nRYqfWc3NzUV5eftHH58yZ\ng1AohKqqKqxduxaHDh3CnDlzsHXr1paKQkRE7VRcnBVxcVbZMaRShBCitV/0kUcewYwZM5CVlQUA\nGDFiBNauXQu7vWP+a4qIiKippNzsNnz4cOzevRtZWVk4deoUAoFAo0r83LmaVkjXspKT4wz/PtrD\newD4PtqS9vAegPbxPmS8h8rKWvj9ISQlxULTtGY5Znv4swDq3seVSCnyCRMm4Nlnn8XYsWNhNpvx\nyiuvyIhBRESSFRQ4UFWVAFU1objYgb59bbBYzLJjGYqUIjebzXx2nIiog/P7/aioiIH0lOwZAAAP\nxUlEQVTFUldFipKIs2cd6NYtQXIyY+EUrUREJM2PHxdr/bu2jI9FTkREUlgsFiQkuKDrIQCArlch\nLS1Gcirj4VzrREQkTa9eiSgvr0YgIJCUFMPr403AIiciIqk6d+54C500J55aJyIiMjAWORERkYGx\nyImIiAyMRU5ERGRgLHIiIiIDY5ETEREZGIuciIjIwFjkREREBsYiJyIiMjAWORERkYGxyImIiAyM\nRU5ERGRgLHIiIiIDY5ETEREZGIuciIjIwFjkREREBsYiJyIiMjAWORERkYGxyImIiAyMRU5ERGRg\nLHIiIiIDY5ETEREZGIuciIjIwFjkREREBsYiJyIiMjAWORERkYGxyImIiAyMRU5ERGRgLHIiIiID\nY5ETEREZGIuciIjIwFjkREREBsYiJyIiMjAWORERkYGxyImIiAyMRU5ERGRgLHIiIiIDY5ETEREZ\nmJQiP3ToECZOnIhx48ZhwoQJOHTokIwYREREhielyJcuXYrZs2dj06ZNmDVrFpYuXSojBhERkeFJ\nKfLk5GTU1NQAAGpqapCamiojBhERkeGZZLzok08+iQceeABLliyBruv44IMPZMQgIiIyvBYr8tzc\nXJSXl1/08Tlz5uDdd9/FggULMGLECGzZsgXPPvss3n777ZaKQkRE1G4pQgjR2i96yy234MsvvwQA\nCCEwYMAAfPHFF60dg4iIyPCkXCPv1q0b9u7dCwDYvXs3rr/+ehkxiIiIDE/KiPyrr77CCy+8AL/f\nj+joaDz//PPo27dva8cgIiIyPClFTkRERM2DM7sREREZGIuciIjIwFjkREREBiZlQpim2rJlC1as\nWIGCggKsX78e/fr1kx2p0fLz87Fo0SLouo6JEydixowZsiNFbP78+di+fTuSkpLw0UcfyY7TZGfP\nnsW8efPgcDigKAomTZqEqVOnyo4VEZ/PhylTpsDv9yMQCODOO+/Ek08+KTtWk4VCIUyYMAFpaWn4\n85//LDtOxIYNGwabzQZN02AymbB+/XrZkZqkuroaCxYswIkTJ6AoChYtWoT+/fvLjhWRgoICzJ07\nN7xdWFiI2bNnG+7v+BtvvIHNmzdDVVX07t0bixcvhsViufTOwkBOnjwpCgoKxJQpU8Thw4dlx2m0\nYDAohg8fLgoLC4Xf7xc5OTni5MmTsmNF7PPPPxdff/21GDNmjOwoV6WsrEwcOXJECCFEbW2tGDly\npCH/PNxutxBCiEAgIO677z7x+eefS07UdKtWrRJz584VM2fOlB2lSYYOHSqcTqfsGFdt3rx5Yt26\ndUKIup+r6upqyYmuTigUEoMGDRLFxcWyo0SksLBQDBs2TPh8PiGEELNnzxYbNmxocH9DnVrv2bMn\nunfvLjtGxA4dOoT09HR07doVZrMZo0ePxtatW2XHitiAAQMQHx8vO8ZVS05Oxg033AAAsNls6Nmz\nJ8rKyiSnipzVagUABAIBhEIhJCQkSE7UNCUlJdi+fTvuu+8+2VGuijD4A0A1NTXYt28fJk6cCAAw\nmUyIi4uTnOrq7Ny5E9dddx26dOkiO0pEYmNjYTKZ4PF4EAwG4fV6L7smiaGK3KhKS0vr/SClpqai\ntLRUYiI6r6ioCEePHsWNN94oO0rEdF3HPffcg9tvvx233norevXqJTtSkyxatAjz5s2Dqhr315Gi\nKMjNzcW9996LtWvXyo7TJEVFRUhMTMT8+fMxfvx4LFiwAB6PR3asq/LPf/4TY8aMkR0jYgkJCXj4\n4Ydxxx134Gc/+xni4uJw++23N7h/m/ubk5ubi7Fjx170X15enuxoTaYoiuwIdAkulwuzZs3Cc889\nB5vNJjtOxFRVxYcffoj8/Hzs27cPe/bskR0pYp999hmSkpLQt29fQ49o33//fWzatAlvvvkm3nvv\nPezbt092pIgFg0EcOXIE999/PzZu3Air1YqVK1fKjtVkfr8fn332GUaNGiU7SsS+++47rFmzBnl5\nefjPf/4Dt9uNzZs3N7h/m7vZrT0unpKamoqzZ8+Gt0tKSrh0q2SBQACzZs1CTk4Ohg8fLjvOVYmL\ni0N2djYOHz6MW2+9VXaciOzfvx95eXnYvn07/H4/amtrMW/ePCxZskR2tIikpKQAABITEzFixAgc\nOnQIAwYMkJwqMmlpaUhNTQ2fnbrrrrvwl7/8RXKqpsvPz0e/fv2QmJgoO0rEDh8+jJtvvhl2ux0A\nMGLECOzfvx85OTmX3L/Njcgby0j/ev/JT36CM2fOoKioCH6/H5988gnuvPNO2bE6LCEEnnvuOfTs\n2RMPPfSQ7DhN4nA4UF1dDQDwer3YuXOnIac5njt3LrZv3468vDwsW7YMAwcONFyJezwe1NbWAgDc\nbjf++9//onfv3pJTRS45ORldunTBqVOnAAC7du0y7OUawLin1QGgR48eOHjwILxeL4QQV/yzaHMj\n8sv597//jZdeeglOpxMzZ87EDTfcgDfffFN2rCsymUxYuHAhpk+fHn78rGfPnrJjRWzu3LnYu3cv\nKisrkZ2djVmzZmHChAmyY0Xsiy++wObNm9GnTx+MGzcOQN17GzJkiORkjXfu3Dk888wz0HU9fK38\ntttukx2rQyovL8evf/1rAHWP0Y0dOxaDBw+WnKppFi5ciKeeegqBQADp6elYvHix7EhN4na7sXPn\nTrz44ouyozRJZmYm7rnnHkyYMAGqqqJv376YNGlSg/tzrnUiIiIDM+ypdSIiImKRExERGRqLnIiI\nyMBY5ERERAbGIiciIjIwFjkREZGBsciJIrBlyxaMHz8e48aNw6hRo1p06dDly5cjEAi02PGbw4wZ\nM1BYWBjR12RmZiInJwf33HMPxo8fj507d0b8ukVFRRg4cOBl99mwYQNmzZp1yc/l5eXVm3jmj3/8\nI0aNGoUpU6Zg79692LFjR8SZiGQx1IQwRDKVlZXhhRdewKZNm8JT7B49erTFXu+1117D9OnTYTab\nL/pcMBiEyST/r29T5+L+4IMPYLVakZ+fj7lz52L37t3NnOzyaxwMGzYMw4YNC2+vXr0a27Ztg91u\nx/Lly+F2uzFo0KBmz0TUEuT/JiAyiPLycphMJnTq1Cn8sfPLoQJ1I81f/epX2Lp1K7xeL+bOnYuR\nI0cCAA4ePIg//OEP4ak8Z8+ejezsbAB1C4esWLECwWAQqqri97//Pf7+978DACZPngxN0/DOO+/g\n5ZdfhqZpOH36NNxuNzZu3IiVK1fio48+AlA3FfDChQsRExODTz/9FK+++io0TUMoFMLChQuRlZWF\n0tJSvPTSSzhz5gwAYMyYMZgxYwbKy8vx/PPPo7CwEEIITJ8+PTzr3bBhwzB69Gjs2LEDtbW1mDZt\nGh588MHw51auXIlevXo1eOzLycrKQmVlJRwOBxITEy/7fXrvvfewZs0axMbG1puFr6KiAk8++SQq\nKioAAIMGDcIzzzwDIQRcLheeeOIJnDhxAnFxcVi+fDk6d+6MDRs2YNu2bfjTn/6EBx54AD6fD9Om\nTUN6ejoOHDgAXdexa9cujB49Gr/85S8j+0Eham0tvD46Ubuh67p47LHHxK233ioef/xxsXr1auF0\nOsOf79Onj3jttdeEEEIUFBSIrKwsUVFRIaqqqsS4ceNEWVmZEEKI0tJSMWTIEFFTUyMKCgrEoEGD\nxJkzZ4QQQvj9flFbWxs+ntvtDh//6aefFhMmTBAej0cIIcS2bdvEmDFjwvvPmzdPLF26VAghRE5O\njjhw4EA4d01NjRBCiClTpoi33norfEyHwyGEEGL27Nni1VdfFUIIUVZWJgYPHixOnDghhBBi6NCh\n4tlnnxVCCFFeXi4GDx4sjh07Fv7c+f0aOvaP9enTR7hcLiGEEJs3bxbZ2dlC1/XLfp+OHj0qBg8e\nLCoqKoQQQjz//PNi4MCBQggh3n77bbFw4cLw8aurq4UQQvzjH/8QP/3pT0VJSYkQQogFCxaIZcuW\nhT/3+OOP18t0/nu9fPly8corr1wyO1FbxBE5USMpioLXXnsNJ06cwN69e7F161a89dZb+PjjjxEf\nHw8AmDhxIgCge/fu6NevHw4cOABN01BUVFRvZKeqKk6fPo2DBw8iOzsb6enpAACz2XzJU+nnX/+u\nu+5CdHQ0AIRHjOeXYJ00aRJefvllAMDAgQOxaNEijBw5EkOGDEFGRgZcLhcOHDiANWvWhI95fnWl\nXbt2Yf78+QDqFs/Izs7G7t27wws1nH9fSUlJuOOOO7Bnz556C4Nc7tiXMnnyZLhcLpw7dw6rV6+G\noijYv39/g9+nL7/8EkOHDg2vZDV58mT861//AgD0798fa9aswZIlS5CVlVVvnvNbbrklfBnkpptu\navT1eMGZq8lAWOREEcrIyEBGRgYefPBBjB49Gnv37g0vhfrjAjh/nbZPnz7461//etGxDh48GFFp\nxMTE1Dv2D7/2h/8/f/58nDhxArt27cLs2bORm5uLu++++5IZL0UIUe8a849fp6Hrz419L+evka9a\ntQpLly7F+++/DyFEg9+n/fv3N/he+/fvj02bNmHHjh348MMPsXLlSvztb38DAFgslvB+qqoiGAw2\nKh+RkfCudaJGKi0txf79+8PbJSUlcDgc6Nq1a/hjGzZsAACcPn0aR44cwU033YT+/fvj9OnT2LNn\nT3i/Q4cOAQAGDx6M/Pz88HVlv98Pl8sFALDZbOGlSi/ltttuwyeffAKXywUhBNavXx8ejRYUFCAj\nIwNTp05FTk4OvvrqK9hsNtx8881YvXp1+BhOpxMAcPvtt2Pt2rUA6lZWy8/Pr3dX+MaNGwHULZ+a\nn59/0brnlzv25Tz88MMIBoPYtGkTbrnllga/T1lZWdi+fTscDgcAYP369eF9ioqKEBMTg7vvvhvP\nPPMMvv766yu+7uXExsaGr9ETGQFH5ESNFAqFsGLFCnz//feIjo6Grut44oknkJmZWW+f8ePHw+Px\n4MUXXwyfCn799dexZMkSLFq0KLxE5Ouvv45u3brhxRdfxBNPPIFQKARN0/DKK68gIyMDubm5mDZt\nGqxWK955552L8gwZMgTHjh3D5MmTAdTd7Pboo48CAJYtW4YzZ85A0zTEx8eHT7kvXbo0fOe9qqoY\nO3YsHnnkESxYsAC//e1vkZOTAyEEnnrqqXpL7drtdtx7772ora3FzJkzkZGRcVGeho79Yz8ezT/9\n9NOYN28e7r777ga/T3369MHMmTNx//33w2azITs7O3ycPXv2YPXq1dA0Dbqu43e/+134dX74Wj/c\nvtTnzhs+fDg2bdqEcePG8WY3MgQuY0rUTDIzM7F//35YrVbZUZrVD+9MJ6K2h6fWiZrJ5Z5bJiJq\nKRyRExERGRhH5ERERAbGIiciIjIwFjkREZGBsciJiIgMjEVORERkYCxyIiIiA/t/7e2p/WhmF4gA\nAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x11d428f90>"
       ]
      }
     ],
     "prompt_number": 98
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#### Random Forests\n",
      "Pretty good intro\n",
      "http://blog.yhathq.com/posts/random-forests-in-python.html"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.ensemble import RandomForestRegressor\n",
      "clf2 = RandomForestRegressor(n_estimators=100, \n",
      "                            criterion='mse', max_depth=None, \n",
      "                            min_samples_split=2, min_samples_leaf=1, \n",
      "                            max_features='auto', max_leaf_nodes=None, \n",
      "                            bootstrap=True, oob_score=False, n_jobs=1, \n",
      "                            random_state=None, verbose=0, \n",
      "                            min_density=None, compute_importances=None)\n",
      "clf2.fit(train_X,train_Y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "RandomForestRegressor(bootstrap=True, compute_importances=None,\n",
        "           criterion='mse', max_depth=None, max_features='auto',\n",
        "           max_leaf_nodes=None, min_density=None, min_samples_leaf=1,\n",
        "           min_samples_split=2, n_estimators=100, n_jobs=1,\n",
        "           oob_score=False, random_state=None, verbose=0)"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Y_rf_pred = clf2.predict(test_X)\n",
      "mse = mean_squared_error(test_Y,Y_rf_pred) ; print mse\n",
      "scatter(test_Y, Y_rf_pred - test_Y,alpha=0.2)\n",
      "title(\"RF Residuals - MSE = %.1f\" % mse)\n",
      "xlabel(\"Spectroscopic Redshift\")\n",
      "ylabel(\"Residual\")\n",
      "hlines(0,min(test_Y),max(test_Y),color=\"red\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0.202398294159\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "<matplotlib.collections.LineCollection at 0x10ee0f450>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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MpER+hTtypEKzmUJVVfL5BmNjFp63/GN3nNN/n2s2I2zcGKBaraCqHslk5FJnWQghxHmQ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FLADE3kL7zwAhobGxGJRIwMgxBCCClYhiXy7u5uvPvuu6isrDQqBEIIIaTgGZbIH3nkEfz1X/+1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\nP/Cakhefe5SSAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10ef36650>"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## model selection: cross-validation"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn import cross_validation"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn import linear_model\n",
      "clf = linear_model.LinearRegression()\n",
      "from sklearn.cross_validation import cross_val_score\n",
      "\n",
      "def print_cv_score_summary(model, xx, yy, cv):\n",
      "    scores = cross_val_score(model, xx, yy, cv=cv, n_jobs=1)\n",
      "    print(\"mean: {:3f}, stdev: {:3f}\".format(\n",
      "        np.mean(scores), np.std(scores)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print_cv_score_summary(clf,X,Y,cv=cross_validation.KFold(len(Y), 5))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "mean: 0.237593, stdev: 0.026459\n"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print_cv_score_summary(clf,X,Y,\n",
      "    cv=cross_validation.KFold(len(Y),10,shuffle=True,random_state=1))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "mean: 0.246604, stdev: 0.041721\n"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print_cv_score_summary(clf2,X,Y,\n",
      "    cv=cross_validation.KFold(len(Y),10,shuffle=True,random_state=1))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "mean: 0.607408, stdev: 0.040491\n"
       ]
      }
     ],
     "prompt_number": 39
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Classification\n",
      "\n",
      "Let's do a 3-class classification problem: star, galaxy, or QSO"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "all_sources = pd.read_csv(\"qso10000.csv\",index_col=0,usecols=[\"objid\",\"dered_r\",\"u_g_color\",\\\n",
      "                                                \"g_r_color\",\"r_i_color\",\"i_z_color\",\"diff_u\",\\\n",
      "                                                \"diff_g1\",\"diff_i\",\"diff_z\",\"class\"])[:1000]\n",
      "\n",
      "all_sources = all_sources.append(pd.read_csv(\"star1000.csv\",index_col=0,usecols=[\"objid\",\"dered_r\",\"u_g_color\",\\\n",
      "                                                \"g_r_color\",\"r_i_color\",\"i_z_color\",\"diff_u\",\\\n",
      "                                                \"diff_g1\",\"diff_i\",\"diff_z\",\"class\"]))\n",
      "\n",
      "all_sources = all_sources.append(pd.read_csv(\"galaxy1000.csv\",index_col=0,usecols=[\"objid\",\"dered_r\",\"u_g_color\",\\\n",
      "                                                \"g_r_color\",\"r_i_color\",\"i_z_color\",\"diff_u\",\\\n",
      "                                                \"diff_g1\",\"diff_i\",\"diff_z\",\"class\"]))\n",
      "\n",
      "all_sources = all_sources[(all_sources[\"dered_r\"] > -9999) & (all_sources[\"g_r_color\"] > -10) & (all_sources[\"g_r_color\"] < 10)]\n",
      "all_features = copy.copy(all_sources)\n",
      "all_label = all_sources[\"class\"]\n",
      "del all_features[\"class\"]\n",
      "X = copy.copy(all_features.values)\n",
      "Y = copy.copy(all_label.values)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "all_sources.tail()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>dered_r</th>\n",
        "      <th>u_g_color</th>\n",
        "      <th>g_r_color</th>\n",
        "      <th>r_i_color</th>\n",
        "      <th>i_z_color</th>\n",
        "      <th>diff_u</th>\n",
        "      <th>diff_g1</th>\n",
        "      <th>diff_i</th>\n",
        "      <th>diff_z</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>objid</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1237657775542632759</th>\n",
        "      <td> 15.42325</td>\n",
        "      <td> 1.999353</td>\n",
        "      <td> 0.970126</td>\n",
        "      <td> 0.435975</td>\n",
        "      <td> 0.373470</td>\n",
        "      <td>-1.944487</td>\n",
        "      <td>-1.971534</td>\n",
        "      <td>-2.052320</td>\n",
        "      <td>-1.971382</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1237657775542698090</th>\n",
        "      <td> 17.51366</td>\n",
        "      <td> 2.212025</td>\n",
        "      <td> 0.965242</td>\n",
        "      <td> 0.410664</td>\n",
        "      <td> 0.371384</td>\n",
        "      <td>-0.778788</td>\n",
        "      <td>-0.944075</td>\n",
        "      <td>-0.895832</td>\n",
        "      <td>-0.830559</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1237657775542698177</th>\n",
        "      <td> 17.15747</td>\n",
        "      <td> 1.190033</td>\n",
        "      <td> 0.332136</td>\n",
        "      <td> 0.252352</td>\n",
        "      <td> 0.070980</td>\n",
        "      <td>-2.391565</td>\n",
        "      <td>-2.977261</td>\n",
        "      <td>-2.889906</td>\n",
        "      <td>-2.671612</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1237657630586634463</th>\n",
        "      <td> 17.19312</td>\n",
        "      <td> 1.179663</td>\n",
        "      <td> 0.678915</td>\n",
        "      <td> 0.394419</td>\n",
        "      <td> 0.272171</td>\n",
        "      <td>-1.563450</td>\n",
        "      <td>-1.913368</td>\n",
        "      <td>-1.791895</td>\n",
        "      <td>-1.615683</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1237657630049698007</th>\n",
        "      <td> 17.20485</td>\n",
        "      <td> 1.925320</td>\n",
        "      <td> 1.126934</td>\n",
        "      <td> 0.477961</td>\n",
        "      <td> 0.334377</td>\n",
        "      <td>-1.211906</td>\n",
        "      <td>-1.377165</td>\n",
        "      <td>-1.402037</td>\n",
        "      <td>-1.218332</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 9 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "                      dered_r  u_g_color  g_r_color  r_i_color  i_z_color  \\\n",
        "objid                                                                       \n",
        "1237657775542632759  15.42325   1.999353   0.970126   0.435975   0.373470   \n",
        "1237657775542698090  17.51366   2.212025   0.965242   0.410664   0.371384   \n",
        "1237657775542698177  17.15747   1.190033   0.332136   0.252352   0.070980   \n",
        "1237657630586634463  17.19312   1.179663   0.678915   0.394419   0.272171   \n",
        "1237657630049698007  17.20485   1.925320   1.126934   0.477961   0.334377   \n",
        "\n",
        "                       diff_u   diff_g1    diff_i    diff_z  \n",
        "objid                                                        \n",
        "1237657775542632759 -1.944487 -1.971534 -2.052320 -1.971382  \n",
        "1237657775542698090 -0.778788 -0.944075 -0.895832 -0.830559  \n",
        "1237657775542698177 -2.391565 -2.977261 -2.889906 -2.671612  \n",
        "1237657630586634463 -1.563450 -1.913368 -1.791895 -1.615683  \n",
        "1237657630049698007 -1.211906 -1.377165 -1.402037 -1.218332  \n",
        "\n",
        "[5 rows x 9 columns]"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print \"feature vector shape=\", X.shape\n",
      "print \"class shape=\", Y.shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "feature vector shape= (3000, 9)\n",
        "class shape= (3000,)\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Y[Y==\"QSO\"] = 0\n",
      "Y[Y==\"STAR\"] = 1\n",
      "Y[Y==\"GALAXY\"] = 2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's look at random forest"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.ensemble import RandomForestClassifier\n",
      "clf = RandomForestClassifier(n_estimators=200,oob_score=True)\n",
      "clf.fit(X,Y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 46,
       "text": [
        "RandomForestClassifier(bootstrap=True, compute_importances=None,\n",
        "            criterion='gini', max_depth=None, max_features='auto',\n",
        "            max_leaf_nodes=None, min_density=None, min_samples_leaf=1,\n",
        "            min_samples_split=2, n_estimators=200, n_jobs=1,\n",
        "            oob_score=True, random_state=None, verbose=0)"
       ]
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "what are the important features in the data?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sorted(zip(all_sources.columns.values,clf.feature_importances_),key=lambda q: q[1],reverse=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 47,
       "text": [
        "[('u_g_color', 0.24621379942513427),\n",
        " ('diff_g1', 0.17095210500690095),\n",
        " ('diff_i', 0.13073539972463408),\n",
        " ('diff_z', 0.12105441185550342),\n",
        " ('g_r_color', 0.094758188792464337),\n",
        " ('diff_u', 0.089870190147766496),\n",
        " ('r_i_color', 0.062334477766268478),\n",
        " ('dered_r', 0.052595128912769143),\n",
        " ('i_z_color', 0.03148629836855911)]"
       ]
      }
     ],
     "prompt_number": 47
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf.oob_score_  ## \"Out of Bag\" Error"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 49,
       "text": [
        "0.95433333333333337"
       ]
      }
     ],
     "prompt_number": 49
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "from sklearn import svm, datasets\n",
      "cmap = cm.jet_r\n",
      "\n",
      "# import some data to play with\n",
      "\n",
      "X = all_features.values[:, 1:3] # use only two features for training and plotting purposes\n",
      "\n",
      "h = .02  # step size in the mesh\n",
      "\n",
      "# we create an instance of SVM and fit out data. We do not scale our\n",
      "# data since we want to plot the support vectors\n",
      "C = 1.0  # SVM regularization parameter\n",
      "svc = svm.SVC(kernel='linear', C=C).fit(X, Y)\n",
      "rbf_svc = svm.SVC(kernel='rbf', gamma=0.7, C=C).fit(X, Y)\n",
      "poly_svc = svm.SVC(kernel='poly', degree=3, C=C).fit(X, Y)\n",
      "lin_svc = svm.LinearSVC(C=C).fit(X, Y)\n",
      "\n",
      "# create a mesh to plot in\n",
      "x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
      "y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
      "xx, yy = np.meshgrid(np.arange(x_min, x_max, h),\n",
      "                     np.arange(y_min, y_max, h))\n",
      "\n",
      "# title for the plots\n",
      "titles = ['SVC with linear kernel',\n",
      "          'SVC with RBF kernel',\n",
      "          'SVC with polynomial (degree 3) kernel',\n",
      "          'LinearSVC (linear kernel)']\n",
      "\n",
      "\n",
      "norm = mpl.colors.Normalize(vmin=min(Y), vmax=max(Y))\n",
      "m = cm.ScalarMappable(norm=norm, cmap=cmap)\n",
      "\n",
      "for i, clf in enumerate((svc, rbf_svc, poly_svc, lin_svc)):\n",
      "    # Plot the decision boundary. For that, we will assign a color to each\n",
      "    # point in the mesh [x_min, m_max]x[y_min, y_max].\n",
      "    subplot(2, 2, i + 1)\n",
      "    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
      "\n",
      "    # Put the result into a color plot\n",
      "    Z = Z.reshape(xx.shape)\n",
      "    contourf(xx, yy, Z,cmap=cm.Paired)\n",
      "    axis('off')\n",
      "\n",
      "    # Plot also the training points\n",
      "    scatter(X[:, 0], X[:, 1], c=m.to_rgba(Y),cmap=cm.Paired)\n",
      "\n",
      "    title(titles[i])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Oi8ZpdZI4OpHqg1VEpkRRvaccQ5QZRVGQJImGKjumhKDGySfGCDNFQf55ghOE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\nxREORHKiRawDTk2Sx08gjmP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g0bFnLj3tJKLl4QwH4Lgsx/NHoltb8Kkbj8xifVSor8MQ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       "text": [
        "<matplotlib.figure.Figure at 0x10a7b4d50>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## model improvement with GridSearchCV\n",
      "Hyperparameter optimization"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# fit a support vector machine classifier\n",
      "from sklearn import grid_search\n",
      "from sklearn import svm\n",
      "from sklearn import metrics\n",
      "import logging\n",
      "logging.basicConfig(level=logging.INFO,\n",
      "                    format='%(asctime)s %(levelname)s %(message)s')\n",
      "\n",
      "# instantiate the SVM object\n",
      "sdss_svm = svm.SVC()\n",
      "\n",
      "X = all_features.values\n",
      "Y = all_label.values\n",
      "\n",
      "# parameter values over which we will search\n",
      "parameters = {'kernel':('linear', 'rbf'), \\\n",
      "              'gamma':[0.5, 0.3, 0.1,  0.01],\n",
      "              'C':[0.1, 2, 4, 5, 10, 20,30]}\n",
      "#parameters = {'kernel':('linear', 'rbf')}\n",
      "\n",
      "# do a grid search to find the highest 3-fold CV zero-one score\n",
      "svm_tune = grid_search.GridSearchCV(sdss_svm, parameters, score_func=metrics.accuracy_score,\\\n",
      "                                    n_jobs = -1, cv = 3,verbose=1)\n",
      "svm_opt = svm_tune.fit(X, Y)\n",
      "\n",
      "# print the best score and estimator\n",
      "print(svm_opt.best_score_)\n",
      "print(svm_opt.best_estimator_)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Fitting 3 folds for each of 56 candidates, totalling 168 fits\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Users/jbloom/anaconda/lib/python2.7/site-packages/sklearn/grid_search.py:347: DeprecationWarning: Passing function as ``score_func`` is deprecated and will be removed in 0.15. Either use strings or score objects. The relevant new parameter is called ''scoring''.\n",
        "  score_func=self.score_func)\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "[Parallel(n_jobs=-1)]: Done   1 jobs       | elapsed:    0.1s\n",
        "[Parallel(n_jobs=-1)]: Done  50 jobs       | elapsed:    1.6s\n",
        "[Parallel(n_jobs=-1)]: Done 168 out of 168 | elapsed:    9.4s finished\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0.955\n",
        "SVC(C=20, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.1,\n",
        "  kernel='rbf', max_iter=-1, probability=False, random_state=None,\n",
        "  shrinking=True, tol=0.001, verbose=False)\n"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.cross_validation import train_test_split\n",
      "from sklearn.metrics import confusion_matrix\n",
      "\n",
      "X_train, X_test, y_train, y_test = train_test_split(X, Y, random_state=0)\n",
      "\n",
      "classifier = svm.SVC(**svm_opt.best_estimator_.get_params())\n",
      "y_pred = classifier.fit(X_train, y_train).predict(X_test)\n",
      "\n",
      "# Compute confusion matrix\n",
      "cm = confusion_matrix(y_test, y_pred)\n",
      "\n",
      "print(cm)\n",
      "\n",
      "# Show confusion matrix in a separate window\n",
      "plt.matshow(cm)\n",
      "plt.title('Confusion matrix')\n",
      "plt.colorbar()\n",
      "plt.ylabel('True label')\n",
      "plt.xlabel('Predicted label')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[[231   1   1]\n",
        " [  7 254  19]\n",
        " [  3   9 225]]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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BS3asN27cwKJFi3D69GmoVCqsXr0a7dq1w+zZs5Gbm4s2bdpgw4YNaNasmVnj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\nRCQxBisRkcQYrEREEmOwEhFJ7P8BC+vMVpDL/wYAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10a1cd990>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# instantiate the SVM object\n",
      "sdss_rf = RandomForestClassifier()\n",
      "\n",
      "X = all_features.values\n",
      "Y = all_label.values\n",
      "\n",
      "# parameter values over which we will search\n",
      "parameters = {'n_estimators':(10,50,200),\"max_features\": [\"auto\",3,5],\n",
      "              'criterion':[\"gini\",\"entropy\"],\"min_samples_leaf\": [1,2]}\n",
      "#parameters = {'kernel':('linear', 'rbf')}\n",
      "\n",
      "# do a grid search to find the highest 3-fold CV zero-one score\n",
      "rf_tune = grid_search.GridSearchCV(sdss_rf, parameters, score_func=metrics.accuracy_score,\\\n",
      "                                    n_jobs = -1, cv = 3,verbose=1)\n",
      "rf_opt = rf_tune.fit(X, Y)\n",
      "\n",
      "# print the best score and estimator\n",
      "print(rf_opt.best_score_)\n",
      "print(rf_opt.best_estimator_)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Fitting 3 folds for each of 36 candidates, totalling 108 fits\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Users/jbloom/anaconda/lib/python2.7/site-packages/sklearn/ensemble/forest.py:776: DeprecationWarning: Setting compute_importances is no longer required as version 0.14. Variable importances are now computed on the fly when accessing the feature_importances_ attribute. This parameter will be removed in 0.16.\n",
        "  DeprecationWarning)\n",
        "/Users/jbloom/anaconda/lib/python2.7/site-packages/sklearn/grid_search.py:347: DeprecationWarning: Passing function as ``score_func`` is deprecated and will be removed in 0.15. Either use strings or score objects. The relevant new parameter is called ''scoring''.\n",
        "  score_func=self.score_func)\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "[Parallel(n_jobs=-1)]: Done   1 jobs       | elapsed:    0.1s\n",
        "[Parallel(n_jobs=-1)]: Done  50 jobs       | elapsed:    6.8s\n",
        "[Parallel(n_jobs=-1)]: Done 108 out of 108 | elapsed:   21.5s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.1s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.1s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.1s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.3s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.1s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.1s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.1s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.3s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n",
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        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.2s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.3s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    1.1s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    1.1s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.3s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.3s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    1.1s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    1.1s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n",
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        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
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        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
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        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0.949666666667\n",
        "RandomForestClassifier(bootstrap=True, compute_importances=None,\n",
        "            criterion='gini', max_depth=None, max_features=3,\n",
        "            max_leaf_nodes=None, min_density=None, min_samples_leaf=1,\n",
        "            min_samples_split=2, n_estimators=50, n_jobs=1,\n",
        "            oob_score=False, random_state=None, verbose=1)\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.3s\n",
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        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.1s\n",
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        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
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        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.6s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    2.6s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.6s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    2.6s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.6s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    2.3s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.6s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    2.3s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.6s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.6s finished\n",
        "[Parallel(n_jobs=1)]: Done   1 jobs       | elapsed:    0.0s\n",
        "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s finished\n"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf.get_params()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 50,
       "text": [
        "{'bootstrap': True,\n",
        " 'compute_importances': None,\n",
        " 'criterion': 'gini',\n",
        " 'max_depth': None,\n",
        " 'max_features': 'auto',\n",
        " 'max_leaf_nodes': None,\n",
        " 'min_density': None,\n",
        " 'min_samples_leaf': 1,\n",
        " 'min_samples_split': 2,\n",
        " 'n_estimators': 200,\n",
        " 'n_jobs': 1,\n",
        " 'oob_score': True,\n",
        " 'random_state': None,\n",
        " 'verbose': 0}"
       ]
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "svm_opt.best_estimator_.get_params()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "{'C': 20,\n",
        " 'cache_size': 200,\n",
        " 'class_weight': None,\n",
        " 'coef0': 0.0,\n",
        " 'degree': 3,\n",
        " 'gamma': 0.1,\n",
        " 'kernel': 'rbf',\n",
        " 'max_iter': -1,\n",
        " 'probability': False,\n",
        " 'random_state': None,\n",
        " 'shrinking': True,\n",
        " 'tol': 0.001,\n",
        " 'verbose': False}"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "grid_search.GridSearchCV?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 57
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}