{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\nimport matplotlib.pyplot as plt\nfrom tqdm import tqdm\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.svm import NuSVR\nfrom sklearn.metrics import mean_absolute_error\nimport lightgbm as lgb\n\nfrom keras.datasets import mnist\nfrom keras.layers.core import Activation, Dense, Dropout\nfrom keras.models import Sequential\nfrom keras.optimizers import SGD\nfrom keras.regularizers import l1, l2\nfrom keras.utils import np_utils\nimport scipy.stats as scs\nimport scipy.signal as sig\n\nimport eli5\nfrom eli5.sklearn import PermutationImportance\nfrom keras.wrappers.scikit_learn import KerasClassifier, KerasRegressor","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train = pd.read_csv('../input/train.csv', dtype={'acoustic_data': np.int16, 'time_to_failure': np.float32})","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\ntemp = train['acoustic_data'][:100]\ntemp_smooth = temp.rolling(10).mean()\nprint(len(sig.find_peaks(temp_smooth.values)[0]))\n\nplt.plot(temp)\nplt.plot(temp_smooth)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# rolling = train.acoustic_data.rolling(window=50).quantile(0.25)\n# rolling[]\ntrain.shape","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"rows = 150000\nsegments = int(np.floor(train.shape[0] / rows))\ncol_names = ['fft_{}'.format(i) for i in range(20)]\ncol_names = ['ave', 'std'] + col_names\n\n\nX_train = pd.DataFrame(index=range(segments), dtype=np.float64,\n                       columns=col_names)\ny_train = pd.DataFrame(index=range(segments), dtype=np.float64,\n                       columns=['time_to_failure'])\nfor segment in tqdm(range(segments)):\n    seg = train.iloc[segment*rows:segment*rows+rows]\n    seg_smooth = seg.rolling(10).mean()\n\n    x = seg['acoustic_data'].values\n    x_smooth = seg_smooth['acoustic_data'].values\n    y = seg['time_to_failure'].values[-1]\n    y_train.loc[segment, 'time_to_failure'] = y\n    \n    X_train.loc[segment, 'ave'] = x.mean()\n    X_train.loc[segment, 'abs_mean'] = np.absolute(x).mean()\n    X_train.loc[segment, 'std'] = x.std()\n#     X_train.loc[segment, 'max'] = x.max()\n#     X_train.loc[segment, 'min'] = x.min()\n    X_train.loc[segment, 'log_diff'] = np.log(x.ptp())\n    \n    X_train.loc[segment, 'kurt'] = scs.kurtosis(x)\n    X_train.loc[segment, 'skew'] = scs.skew(x)\n    \n#     X_train.loc[segment, 'p25'] = np.percentile(x,0.25)\n#     X_train.loc[segment, 'p50'] = np.percentile(x,0.50)\n#     X_train.loc[segment, 'p75'] = np.percentile(x,0.75)\n#     X_train.loc[segment, 'p80'] = np.percentile(x,0.80)\n#     X_train.loc[segment, 'p85'] = np.percentile(x,0.85)\n#     X_train.loc[segment, 'p90'] = np.percentile(x,0.90)\n#     X_train.loc[segment, 'p95'] = np.percentile(x,0.95)\n#     X_train.loc[segment, 'pinter'] = X_train.loc[segment, 'p75'] - X_train.loc[segment, 'p25']\n    \n    for i in range(0,10,2):\n        temp_range = x[int(len(x)*i/10):int(len(x)*(i+2)/10)]\n        temp_range_smooth = x_smooth[int(len(x)*i/10):int(len(x)*(i+2)/10)]\n        X_train.loc[segment, f'ave{10*i}'] = temp_range.mean()\n        X_train.loc[segment, f'std{10*i}'] = temp_range.std()\n#         X_train.loc[segment, 'max{}'.format(10*i)] = x[int(len(x)*i/10):int(len(x)*(i+2)/10)].max()\n#         X_train.loc[segment, 'min{}'.format(10*i)] = x[int(len(x)*i/10):int(len(x)*(i+2)/10)].min()\n        X_train.loc[segment, f'log_diff{10*i}'] = np.log(temp_range.ptp())\n        X_train.loc[segment, f'peaks_smooth{10*i}'] = len(sig.find_peaks(temp_range_smooth)[0])\n        X_train.loc[segment, f'zeros_smooth{10*i}'] = ((temp_range_smooth[:-1] * temp_range_smooth[1:]) < 0).sum()\n        X_train.loc[segment, f'peaks_diff_smooth{10*i}'] = np.mean(np.diff(sig.find_peaks(temp_range_smooth)[0]))\n        \n    freq = np.fft.fft(x, n=50).real\n    freq_i = np.fft.fft(x, n=50).imag\n    \n    X_train.loc[segment, 'fftp80'] = np.percentile(freq,0.80)\n    X_train.loc[segment, 'fftp85'] = np.percentile(freq,0.85)\n    X_train.loc[segment, 'fftp90'] = np.percentile(freq,0.90)\n    X_train.loc[segment, 'fftp95'] = np.percentile(freq,0.95)\n    \n    X_train.loc[segment, 'fftip80'] = np.percentile(freq_i,0.80)\n    X_train.loc[segment, 'fftip85'] = np.percentile(freq_i,0.85)\n    X_train.loc[segment, 'fftip90'] = np.percentile(freq_i,0.90)\n    X_train.loc[segment, 'fftip95'] = np.percentile(freq_i,0.95)\n    \n    for idx, freq_val in enumerate(freq):\n        X_train.loc[segment, f'fft_{idx}'] = freq_val\n        \n    for idx, freq_val in enumerate(freq_i):\n        X_train.loc[segment, f'ffti_{idx}'] = freq_val\n        \n    X_train.loc[segment, 'peaks_smooth'] = len(sig.find_peaks(x_smooth)[0])\n    X_train.loc[segment, 'zeros_smooth'] = ((x_smooth[:-1] * x_smooth[1:]) < 0).sum()\n    \n        ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(X_train.shape)\nX_train.head()\n","execution_count":20,"outputs":[{"output_type":"stream","text":"(4194, 146)\n","name":"stdout"},{"output_type":"execute_result","execution_count":20,"data":{"text/plain":"        ave       std      ...       peaks_smooth  zeros_smooth\n0  4.884113  5.101089      ...            18892.0        1201.0\n1  4.725767  6.588802      ...            18681.0        1521.0\n2  4.906393  6.967374      ...            17784.0        1814.0\n3  4.902240  6.922282      ...            18279.0        1423.0\n4  4.908720  7.301086      ...            18387.0        1399.0\n\n[5 rows x 146 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>ave</th>\n      <th>std</th>\n      <th>fft_0</th>\n      <th>fft_1</th>\n      <th>fft_2</th>\n      <th>fft_3</th>\n      <th>fft_4</th>\n      <th>fft_5</th>\n      <th>fft_6</th>\n      <th>fft_7</th>\n      <th>fft_8</th>\n      <th>fft_9</th>\n      <th>fft_10</th>\n      <th>fft_11</th>\n      <th>fft_12</th>\n      <th>fft_13</th>\n      <th>fft_14</th>\n      <th>fft_15</th>\n      <th>fft_16</th>\n      <th>fft_17</th>\n      <th>fft_18</th>\n      <th>fft_19</th>\n      <th>abs_mean</th>\n      <th>log_diff</th>\n      <th>kurt</th>\n      <th>skew</th>\n      <th>ave0</th>\n      <th>std0</th>\n      <th>log_diff0</th>\n      <th>peaks_smooth0</th>\n      <th>zeros_smooth0</th>\n      <th>peaks_diff_smooth0</th>\n      <th>ave20</th>\n      <th>std20</th>\n      <th>log_diff20</th>\n      <th>peaks_smooth20</th>\n      <th>zeros_smooth20</th>\n      <th>peaks_diff_smooth20</th>\n      <th>ave40</th>\n      <th>std40</th>\n      <th>...</th>\n      <th>ffti_12</th>\n      <th>ffti_13</th>\n      <th>ffti_14</th>\n      <th>ffti_15</th>\n      <th>ffti_16</th>\n      <th>ffti_17</th>\n      <th>ffti_18</th>\n      <th>ffti_19</th>\n      <th>ffti_20</th>\n      <th>ffti_21</th>\n      <th>ffti_22</th>\n      <th>ffti_23</th>\n      <th>ffti_24</th>\n      <th>ffti_25</th>\n      <th>ffti_26</th>\n      <th>ffti_27</th>\n      <th>ffti_28</th>\n      <th>ffti_29</th>\n      <th>ffti_30</th>\n      <th>ffti_31</th>\n      <th>ffti_32</th>\n      <th>ffti_33</th>\n      <th>ffti_34</th>\n      <th>ffti_35</th>\n      <th>ffti_36</th>\n      <th>ffti_37</th>\n      <th>ffti_38</th>\n      <th>ffti_39</th>\n      <th>ffti_40</th>\n      <th>ffti_41</th>\n      <th>ffti_42</th>\n      <th>ffti_43</th>\n      <th>ffti_44</th>\n      <th>ffti_45</th>\n      <th>ffti_46</th>\n      <th>ffti_47</th>\n      <th>ffti_48</th>\n      <th>ffti_49</th>\n      <th>peaks_smooth</th>\n      <th>zeros_smooth</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>4.884113</td>\n      <td>5.101089</td>\n      <td>264.0</td>\n      <td>-2.303813</td>\n      <td>52.686075</td>\n      <td>15.618281</td>\n      <td>29.632689</td>\n      <td>-30.568884</td>\n      <td>11.800139</td>\n      <td>1.700900</td>\n      <td>12.941437</td>\n      <td>8.077661</td>\n      <td>2.354102</td>\n      <td>0.236701</td>\n      <td>-0.809184</td>\n      <td>-5.441019</td>\n      <td>-4.558937</td>\n      <td>27.568884</td>\n      <td>11.473272</td>\n      <td>9.100764</td>\n      <td>1.474881</td>\n      <td>6.070857</td>\n      <td>5.576567</td>\n      <td>5.308268</td>\n      <td>33.661319</td>\n      <td>-0.024061</td>\n      <td>5.011700</td>\n      <td>7.367657</td>\n      <td>5.308268</td>\n      <td>3477.0</td>\n      <td>359.0</td>\n      <td>8.623705</td>\n      <td>4.846700</td>\n      <td>4.630004</td>\n      <td>4.317488</td>\n      <td>3582.0</td>\n      <td>295.0</td>\n      <td>8.375035</td>\n      <td>5.132100</td>\n      <td>4.939836</td>\n      <td>...</td>\n      <td>-6.676739</td>\n      <td>11.833114</td>\n      <td>-13.354416</td>\n      <td>28.168424</td>\n      <td>-14.649066</td>\n      <td>-17.494519</td>\n      <td>0.243226</td>\n      <td>25.910591</td>\n      <td>20.388459</td>\n      <td>4.726624</td>\n      <td>13.538039</td>\n      <td>-3.637904</td>\n      <td>-6.482257</td>\n      <td>-1.776357e-15</td>\n      <td>6.482257</td>\n      <td>3.637904</td>\n      <td>-13.538039</td>\n      <td>-4.726624</td>\n      <td>-20.388459</td>\n      <td>-25.910591</td>\n      <td>-0.243226</td>\n      <td>17.494519</td>\n      <td>14.649066</td>\n      <td>-28.168424</td>\n      <td>13.354416</td>\n      <td>-11.833114</td>\n      <td>6.676739</td>\n      <td>23.384878</td>\n      <td>24.429710</td>\n      <td>-20.911228</td>\n      <td>-25.903651</td>\n      <td>-16.642425</td>\n      <td>9.550020</td>\n      <td>-16.094716</td>\n      <td>2.974841</td>\n      <td>19.945442</td>\n      <td>21.001824</td>\n      <td>-19.314820</td>\n      <td>18892.0</td>\n      <td>1201.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>4.725767</td>\n      <td>6.588802</td>\n      <td>260.0</td>\n      <td>4.517977</td>\n      <td>8.278116</td>\n      <td>-0.146959</td>\n      <td>-14.437908</td>\n      <td>15.163119</td>\n      <td>-5.472516</td>\n      <td>22.067701</td>\n      <td>-22.987180</td>\n      <td>-7.122994</td>\n      <td>1.281153</td>\n      <td>-7.034724</td>\n      <td>-4.341058</td>\n      <td>-3.391908</td>\n      <td>-8.408600</td>\n      <td>7.336881</td>\n      <td>3.771483</td>\n      <td>-10.050371</td>\n      <td>12.538109</td>\n      <td>0.510207</td>\n      <td>5.734167</td>\n      <td>5.814131</td>\n      <td>98.755185</td>\n      <td>0.390557</td>\n      <td>4.646933</td>\n      <td>8.111347</td>\n      <td>5.814131</td>\n      <td>3823.0</td>\n      <td>287.0</td>\n      <td>7.844061</td>\n      <td>4.772633</td>\n      <td>8.617011</td>\n      <td>5.710427</td>\n      <td>3124.0</td>\n      <td>544.0</td>\n      <td>9.603266</td>\n      <td>4.647767</td>\n      <td>4.107582</td>\n      <td>...</td>\n      <td>19.529306</td>\n      <td>-2.368246</td>\n      <td>17.283206</td>\n      <td>2.661412</td>\n      <td>-9.430245</td>\n      <td>-1.072172</td>\n      <td>-7.451373</td>\n      <td>-5.637336</td>\n      <td>13.539305</td>\n      <td>-8.734061</td>\n      <td>-7.294023</td>\n      <td>3.903175</td>\n      <td>12.045657</td>\n      <td>4.440892e-16</td>\n      <td>-12.045657</td>\n      <td>-3.903175</td>\n      <td>7.294023</td>\n      <td>8.734061</td>\n      <td>-13.539305</td>\n      <td>5.637336</td>\n      <td>7.451373</td>\n      <td>1.072172</td>\n      <td>9.430245</td>\n      <td>-2.661412</td>\n      <td>-17.283206</td>\n      <td>2.368246</td>\n      <td>-19.529306</td>\n      <td>8.321965</td>\n      <td>5.739095</td>\n      <td>25.311089</td>\n      <td>-6.457876</td>\n      <td>12.345194</td>\n      <td>15.321796</td>\n      <td>12.812763</td>\n      <td>4.547940</td>\n      <td>-16.518327</td>\n      <td>-35.017832</td>\n      <td>1.014123</td>\n      <td>18681.0</td>\n      <td>1521.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>4.906393</td>\n      <td>6.967374</td>\n      <td>252.0</td>\n      <td>18.875669</td>\n      <td>22.563093</td>\n      <td>-7.797494</td>\n      <td>-31.484588</td>\n      <td>-7.309017</td>\n      <td>17.184343</td>\n      <td>-16.048661</td>\n      <td>-6.226354</td>\n      <td>-0.680103</td>\n      <td>-9.281153</td>\n      <td>-5.103302</td>\n      <td>-3.019328</td>\n      <td>24.071897</td>\n      <td>-19.228432</td>\n      <td>-6.190983</td>\n      <td>-2.972375</td>\n      <td>4.492341</td>\n      <td>0.550932</td>\n      <td>17.620605</td>\n      <td>6.152647</td>\n      <td>5.505332</td>\n      <td>33.554053</td>\n      <td>0.217388</td>\n      <td>4.644500</td>\n      <td>6.623201</td>\n      <td>5.214936</td>\n      <td>3573.0</td>\n      <td>428.0</td>\n      <td>8.394737</td>\n      <td>4.818400</td>\n      <td>6.295947</td>\n      <td>4.844187</td>\n      <td>3376.0</td>\n      <td>390.0</td>\n      <td>8.886222</td>\n      <td>4.934900</td>\n      <td>5.533967</td>\n      <td>...</td>\n      <td>19.934405</td>\n      <td>3.390490</td>\n      <td>3.758795</td>\n      <td>-19.951942</td>\n      <td>-1.037428</td>\n      <td>13.558678</td>\n      <td>-10.716722</td>\n      <td>2.474338</td>\n      <td>6.379881</td>\n      <td>-10.588433</td>\n      <td>-0.089594</td>\n      <td>-5.943655</td>\n      <td>-6.945732</td>\n      <td>1.776357e-15</td>\n      <td>6.945732</td>\n      <td>5.943655</td>\n      <td>0.089594</td>\n      <td>10.588433</td>\n      <td>-6.379881</td>\n      <td>-2.474338</td>\n      <td>10.716722</td>\n      <td>-13.558678</td>\n      <td>1.037428</td>\n      <td>19.951942</td>\n      <td>-3.758795</td>\n      <td>-3.390490</td>\n      <td>-19.934405</td>\n      <td>4.132263</td>\n      <td>-3.942983</td>\n      <td>34.053058</td>\n      <td>-0.085877</td>\n      <td>-15.520893</td>\n      <td>-7.604475</td>\n      <td>-15.269905</td>\n      <td>16.696351</td>\n      <td>-1.978471</td>\n      <td>73.273200</td>\n      <td>22.042090</td>\n      <td>17784.0</td>\n      <td>1814.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4.902240</td>\n      <td>6.922282</td>\n      <td>259.0</td>\n      <td>-9.656895</td>\n      <td>-2.603818</td>\n      <td>-42.806298</td>\n      <td>-21.631266</td>\n      <td>-4.826238</td>\n      <td>3.623042</td>\n      <td>8.725675</td>\n      <td>-15.472959</td>\n      <td>-3.928317</td>\n      <td>-0.208204</td>\n      <td>10.976091</td>\n      <td>16.428168</td>\n      <td>-7.664769</td>\n      <td>18.877959</td>\n      <td>10.826238</td>\n      <td>2.017080</td>\n      <td>10.379233</td>\n      <td>-3.276274</td>\n      <td>10.245858</td>\n      <td>5.933960</td>\n      <td>5.981414</td>\n      <td>116.544247</td>\n      <td>0.757270</td>\n      <td>4.858567</td>\n      <td>5.740252</td>\n      <td>4.812184</td>\n      <td>3511.0</td>\n      <td>351.0</td>\n      <td>8.542735</td>\n      <td>4.770833</td>\n      <td>6.113061</td>\n      <td>4.897840</td>\n      <td>3670.0</td>\n      <td>331.0</td>\n      <td>8.172799</td>\n      <td>4.896433</td>\n      <td>10.593513</td>\n      <td>...</td>\n      <td>14.661317</td>\n      <td>-1.535395</td>\n      <td>2.963235</td>\n      <td>7.285670</td>\n      <td>4.706244</td>\n      <td>-5.868700</td>\n      <td>3.386888</td>\n      <td>3.918552</td>\n      <td>-0.746787</td>\n      <td>13.491326</td>\n      <td>-2.512091</td>\n      <td>3.334230</td>\n      <td>-4.791039</td>\n      <td>8.881784e-15</td>\n      <td>4.791039</td>\n      <td>-3.334230</td>\n      <td>2.512091</td>\n      <td>-13.491326</td>\n      <td>0.746787</td>\n      <td>-3.918552</td>\n      <td>-3.386888</td>\n      <td>5.868700</td>\n      <td>-4.706244</td>\n      <td>-7.285670</td>\n      <td>-2.963235</td>\n      <td>1.535395</td>\n      <td>-14.661317</td>\n      <td>-3.755863</td>\n      <td>-30.691079</td>\n      <td>3.517255</td>\n      <td>-22.659051</td>\n      <td>9.335881</td>\n      <td>4.239345</td>\n      <td>-58.390230</td>\n      <td>-77.256655</td>\n      <td>-62.877598</td>\n      <td>45.575599</td>\n      <td>39.764737</td>\n      <td>18279.0</td>\n      <td>1423.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4.908720</td>\n      <td>7.301086</td>\n      <td>217.0</td>\n      <td>-25.349518</td>\n      <td>-15.492360</td>\n      <td>73.228914</td>\n      <td>-17.578653</td>\n      <td>-3.180340</td>\n      <td>6.181140</td>\n      <td>34.955702</td>\n      <td>33.269520</td>\n      <td>4.953447</td>\n      <td>33.180340</td>\n      <td>-22.193369</td>\n      <td>7.373956</td>\n      <td>-4.328421</td>\n      <td>3.453263</td>\n      <td>19.180340</td>\n      <td>0.988250</td>\n      <td>-2.909645</td>\n      <td>6.627672</td>\n      <td>22.864745</td>\n      <td>6.110587</td>\n      <td>5.602119</td>\n      <td>52.976099</td>\n      <td>0.064530</td>\n      <td>4.891000</td>\n      <td>5.938669</td>\n      <td>5.241747</td>\n      <td>3727.0</td>\n      <td>248.0</td>\n      <td>8.045357</td>\n      <td>4.891600</td>\n      <td>5.149879</td>\n      <td>4.962845</td>\n      <td>3842.0</td>\n      <td>248.0</td>\n      <td>7.808383</td>\n      <td>5.022367</td>\n      <td>10.084324</td>\n      <td>...</td>\n      <td>-0.838970</td>\n      <td>6.186925</td>\n      <td>-26.430570</td>\n      <td>-1.453085</td>\n      <td>8.641240</td>\n      <td>-2.708737</td>\n      <td>6.715263</td>\n      <td>1.488390</td>\n      <td>-4.147253</td>\n      <td>10.256836</td>\n      <td>-0.016188</td>\n      <td>-0.919367</td>\n      <td>-0.414541</td>\n      <td>-2.220446e-15</td>\n      <td>0.414541</td>\n      <td>0.919367</td>\n      <td>0.016188</td>\n      <td>-10.256836</td>\n      <td>4.147253</td>\n      <td>-1.488390</td>\n      <td>-6.715263</td>\n      <td>2.708737</td>\n      <td>-8.641240</td>\n      <td>1.453085</td>\n      <td>26.430570</td>\n      <td>-6.186925</td>\n      <td>0.838970</td>\n      <td>20.029047</td>\n      <td>23.723412</td>\n      <td>-14.221063</td>\n      <td>29.611382</td>\n      <td>-26.126090</td>\n      <td>-10.846613</td>\n      <td>6.155367</td>\n      <td>-19.617625</td>\n      <td>18.076109</td>\n      <td>12.101613</td>\n      <td>-9.664463</td>\n      <td>18387.0</td>\n      <td>1399.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"scaler = StandardScaler()\nscaler.fit(X_train)\nX_train_scaled = scaler.transform(X_train)","execution_count":25,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"svm = NuSVR(nu=0.5, verbose=True, kernel='rbf', degree=3, tol=0.00005, gamma='scale', shrinking=True)\nsvm.fit(X_train_scaled, y_train.values.flatten())\ny_pred = svm.predict(X_train_scaled)","execution_count":75,"outputs":[{"output_type":"stream","text":"[LibSVM]","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"d_train = lgb.Dataset(X_train_scaled, label=y_train.values.flatten())\nparams = {'num_leaves': 128,\n          'min_child_samples': 79,\n          'objective': 'gamma',\n          'max_depth': -1,\n          'learning_rate': 0.01,\n          \"boosting_type\": \"gbdt\",\n          \"subsample_freq\": 5,\n          \"subsample\": 0.9,\n          \"bagging_seed\": 11,\n          \"metric\": 'mae',\n          \"verbosity\": -1,\n          'reg_alpha': 0.1302650970728192,\n          'reg_lambda': 0.3603427518866501,\n          'colsample_bytree': 0.1\n         }\n\nclf = lgb.train(params, d_train)\ny_pred = clf.predict(X_train_scaled)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Design a Deep Feedforward Neural Network and Its Training\n## Several major considerations: network architecture, activation function, loss function, dropout, regularization.\t\ndef DefineModel_FNN():\n    ################################################################\n    ## Network Structure\n    first_layer_width = 10\n    second_layer_width = 20\n    ## Try more layers\n    third_layer_width = 0\n    forth_layer_width = 0\n    fifth_layer_width = 0\n    \n    ################################################################\n    ## Activation Function: relu, sigmoid, tanh, elu\n    activation_func = 'relu' \n    # activation_func = 'sigmoid'\n    # activation_func = 'tanh'\n    ################################################################\n    ################################################################    \n    ## Loss Function:\n    #\n    loss_function = 'mae'\n    # loss_function = 'mean_squared_error'\n    ################################################################\n    \n    ################################################################    \n    ## Dropout option\n    #\n    dropout_rate = 0.2\n    # dropout_rate = 0.5\n    # dropout_rate = 0.9\n    ################################################################ \n    \n    ################################################################    \n    ## Regularization option\n    #\n    # weight_regularizer = l1(0.01)\n#     weight_regularizer = l2(0.01)\n    weight_regularizer = None\n    ################################################################\n    ################################################################    \n    ## Learning Rate\n    learning_rate = 0.025\n    # learning_rate = 0.0001\n    # learning_rate = 0.5\n    ################################################################\n    \n    ## Initialize model.\n    model = Sequential()\n    ## First hidden layer with 'first_layer_width' neurons. \n    ## Also need to specify input dimension.\n    ## 'Dense' means fully-connected.\n    model.add( Dense(first_layer_width, input_dim=146, W_regularizer=weight_regularizer) )\n    model.add( Activation(activation_func) )\n    if dropout_rate > 0:\n        model.add(Dropout(dropout_rate))\n    ## Second hidden layer.\n    if second_layer_width > 0:\n        model.add( Dense(second_layer_width) )\n        model.add( Activation(activation_func) )\n        if dropout_rate > 0:\n            model.add(Dropout(dropout_rate)) \n    \n    ## Third hidden layer.\n    if third_layer_width > 0:\n        model.add( Dense(third_layer_width) )\n        model.add( Activation(activation_func) )\n        if dropout_rate > 0:\n            model.add(Dropout(dropout_rate)) \n            \n    ## forth hidden layer.\n    if forth_layer_width > 0:\n        model.add( Dense(forth_layer_width) )\n        model.add( Activation(activation_func) )\n        if dropout_rate > 0:\n            model.add(Dropout(dropout_rate)) \n    \n    ## fifth hidden layer.\n    if fifth_layer_width > 0:\n        model.add( Dense(fifth_layer_width) )\n        model.add( Activation(activation_func) )\n        if dropout_rate > 0:\n            model.add( Dropout(dropout_rate) )\n    \n    ## Last layer has the same dimension as the number of classes\n    model.add(Dense(1, activation='linear'))\n    \n    ## Define optimizer. In this tutorial/codelab, we select SGD.\n    ## You can also use other methods, e.g., opt = RMSprop()\n    opt = SGD(lr=learning_rate, clipnorm=5.)\n    # opt = 'adam'\n    \n    ## Compile the model\n    model.compile(loss=loss_function, optimizer=opt, metrics=['mse'])\n    \n    return model","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"X_train_scaled = scaler.transform(X_train)\n# model = DefineModel_FNN()\nmodel = KerasRegressor(build_fn=DefineModel_FNN)\nmodel.fit(X_train_scaled, y_train.values.flatten(),epochs=300)\ny_pred = model.predict(X_train_scaled)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"perm = PermutationImportance(model, random_state=1).fit(X_train_scaled, y_train.values.flatten())","execution_count":21,"outputs":[{"output_type":"stream","text":"4194/4194 [==============================] - 0s 41us/step\n4194/4194 [==============================] - 0s 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18us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 20us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 19us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 18us/step\n4194/4194 [==============================] - 0s 18us/step\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"eli5.show_weights(perm, top=200, feature_names = X_train.columns.tolist())","execution_count":22,"outputs":[{"output_type":"execute_result","execution_count":22,"data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"\n    <style>\n    table.eli5-weights tr:hover {\n        filter: brightness(85%);\n    }\n</style>\n\n\n\n    \n\n    \n\n    \n\n    \n\n    \n\n    \n\n\n    \n\n    \n\n    \n\n    \n\n    \n\n    \n\n\n    \n\n    \n\n    \n\n    \n\n    \n        <table class=\"eli5-weights eli5-feature-importances\" style=\"border-collapse: collapse; border: none; margin-top: 0em; table-layout: auto;\">\n    <thead>\n    <tr style=\"border: none;\">\n        <th style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">Weight</th>\n        <th style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">Feature</th>\n    </tr>\n    </thead>\n    <tbody>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 80.00%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1850\n                \n                    &plusmn; 0.0155\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_diff_smooth0\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 81.17%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1697\n                \n                    &plusmn; 0.0050\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_diff_smooth40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 83.07%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1458\n                \n                    &plusmn; 0.0081\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_diff_smooth80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 83.34%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1425\n                \n                    &plusmn; 0.0032\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_smooth0\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 83.57%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1398\n                \n                    &plusmn; 0.0107\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_diff_smooth60\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 84.26%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1314\n                \n                    &plusmn; 0.0104\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_smooth40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 85.45%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1174\n                \n                    &plusmn; 0.0085\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_smooth80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 86.09%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.1102\n                \n                    &plusmn; 0.0021\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_smooth\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 87.30%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0967\n                \n                    &plusmn; 0.0060\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_diff_smooth20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 87.60%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0934\n                \n                    &plusmn; 0.0065\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_smooth20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 90.50%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0639\n                \n                    &plusmn; 0.0080\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                peaks_smooth60\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 90.93%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0598\n                \n                    &plusmn; 0.0107\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ave0\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 91.00%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0592\n                \n                    &plusmn; 0.0051\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                log_diff40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 92.11%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0490\n                \n                    &plusmn; 0.0109\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                zeros_smooth80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 92.18%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0484\n                \n                    &plusmn; 0.0060\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                log_diff0\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 92.25%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0478\n                \n                    &plusmn; 0.0077\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ave20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 92.41%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0464\n                \n                    &plusmn; 0.0028\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ave80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 92.69%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0439\n                \n                    &plusmn; 0.0047\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ave60\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 92.81%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0429\n                \n                    &plusmn; 0.0084\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                zeros_smooth40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 93.39%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0381\n                \n                    &plusmn; 0.0066\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                log_diff60\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 93.68%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0357\n                \n                    &plusmn; 0.0102\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                zeros_smooth0\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 93.84%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0344\n                \n                    &plusmn; 0.0036\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                log_diff80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.04%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0328\n                \n                    &plusmn; 0.0026\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_27\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.08%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0325\n                \n                    &plusmn; 0.0071\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                kurt\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.27%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0310\n                \n                    &plusmn; 0.0059\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                zeros_smooth20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.40%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0300\n                \n                    &plusmn; 0.0039\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_44\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.57%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0287\n                \n                    &plusmn; 0.0046\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_38\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.61%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0284\n                \n                    &plusmn; 0.0026\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_6\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.73%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0275\n                \n                    &plusmn; 0.0046\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_23\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.76%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0273\n                \n                    &plusmn; 0.0068\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                log_diff20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.80%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0270\n                \n                    &plusmn; 0.0031\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_5\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.89%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0264\n                \n                    &plusmn; 0.0031\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_10\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 94.99%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0256\n                \n                    &plusmn; 0.0053\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_32\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.00%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0255\n                \n                    &plusmn; 0.0031\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_26\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.00%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0255\n                \n                    &plusmn; 0.0050\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_24\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.01%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0255\n                \n                    &plusmn; 0.0040\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                zeros_smooth60\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.06%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0251\n                \n                    &plusmn; 0.0020\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.06%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0251\n                \n                    &plusmn; 0.0021\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ave40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.11%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0247\n                \n                    &plusmn; 0.0046\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_42\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.13%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0246\n                \n                    &plusmn; 0.0020\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_18\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.15%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0244\n                \n                    &plusmn; 0.0039\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                skew\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.18%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0242\n                \n                    &plusmn; 0.0051\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_25\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.33%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0231\n                \n                    &plusmn; 0.0054\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_12\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.34%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0231\n                \n                    &plusmn; 0.0054\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ave\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.38%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0228\n                \n                    &plusmn; 0.0091\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                zeros_smooth\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.38%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0228\n                \n                    &plusmn; 0.0034\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_21\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.39%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0227\n                \n                    &plusmn; 0.0043\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_7\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.43%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0224\n                \n                    &plusmn; 0.0038\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_13\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.43%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0224\n                \n                    &plusmn; 0.0039\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_6\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.44%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0224\n                \n                    &plusmn; 0.0034\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_36\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.44%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0224\n                \n                    &plusmn; 0.0020\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_35\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.47%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0222\n                \n                    &plusmn; 0.0037\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_19\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.49%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0220\n                \n                    &plusmn; 0.0008\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_42\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.52%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0218\n                \n                    &plusmn; 0.0049\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_18\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.56%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0216\n                \n                    &plusmn; 0.0020\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_10\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.60%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0213\n                \n                    &plusmn; 0.0026\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.60%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0213\n                \n                    &plusmn; 0.0036\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_16\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.62%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0211\n                \n                    &plusmn; 0.0025\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_44\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.66%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0209\n                \n                    &plusmn; 0.0025\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_19\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.66%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0208\n                \n                    &plusmn; 0.0040\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_15\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.66%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0208\n                \n                    &plusmn; 0.0022\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_21\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.69%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0207\n                \n                    &plusmn; 0.0039\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.70%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0206\n                \n                    &plusmn; 0.0032\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_27\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.74%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0203\n                \n                    &plusmn; 0.0051\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_13\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.74%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0203\n                \n                    &plusmn; 0.0035\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_33\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.78%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0201\n                \n                    &plusmn; 0.0031\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_30\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.91%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0192\n                \n                    &plusmn; 0.0048\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                log_diff\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.92%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0191\n                \n                    &plusmn; 0.0035\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_38\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.96%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0188\n                \n                    &plusmn; 0.0028\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_37\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 95.98%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0187\n                \n                    &plusmn; 0.0026\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_46\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.00%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0186\n                \n                    &plusmn; 0.0041\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_25\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.02%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0185\n                \n                    &plusmn; 0.0025\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_26\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.11%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0179\n                \n                    &plusmn; 0.0036\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_45\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.13%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0177\n                \n                    &plusmn; 0.0030\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_15\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.16%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0175\n                \n                    &plusmn; 0.0017\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_41\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.17%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0175\n                \n                    &plusmn; 0.0043\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_11\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.20%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0173\n                \n                    &plusmn; 0.0020\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_29\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.21%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0172\n                \n                    &plusmn; 0.0040\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_0\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.22%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0171\n                \n                    &plusmn; 0.0053\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_43\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.24%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0170\n                \n                    &plusmn; 0.0025\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_23\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.26%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0169\n                \n                    &plusmn; 0.0047\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_14\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.27%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0168\n                \n                    &plusmn; 0.0020\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_1\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.33%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0164\n                \n                    &plusmn; 0.0036\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_2\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.37%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0161\n                \n                    &plusmn; 0.0041\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_33\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.38%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0161\n                \n                    &plusmn; 0.0030\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_22\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.38%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0161\n                \n                    &plusmn; 0.0015\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_39\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.40%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0160\n                \n                    &plusmn; 0.0031\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_48\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.41%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0159\n                \n                    &plusmn; 0.0024\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_36\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.44%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0157\n                \n                    &plusmn; 0.0047\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_17\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.46%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0156\n                \n                    &plusmn; 0.0033\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_37\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.51%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0153\n                \n                    &plusmn; 0.0022\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                std60\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.52%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0152\n                \n                    &plusmn; 0.0029\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_47\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.53%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0151\n                \n                    &plusmn; 0.0025\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_31\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.54%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0151\n                \n                    &plusmn; 0.0047\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_49\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.57%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0149\n                \n                    &plusmn; 0.0028\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_24\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.57%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0149\n                \n                    &plusmn; 0.0031\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_31\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.58%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0148\n                \n                    &plusmn; 0.0029\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_39\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.63%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0145\n                \n                    &plusmn; 0.0023\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_5\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.65%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0144\n                \n                    &plusmn; 0.0032\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.65%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0144\n                \n                    &plusmn; 0.0015\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_1\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.65%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0144\n                \n                    &plusmn; 0.0039\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_3\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.67%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0143\n                \n                    &plusmn; 0.0029\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_28\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.68%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0142\n                \n                    &plusmn; 0.0033\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_17\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.74%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0139\n                \n                    &plusmn; 0.0027\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_48\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.76%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0137\n                \n                    &plusmn; 0.0045\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_16\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.80%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0135\n                \n                    &plusmn; 0.0021\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_34\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.82%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0134\n                \n                    &plusmn; 0.0022\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_43\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.83%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0133\n                \n                    &plusmn; 0.0028\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                std0\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.83%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0133\n                \n                    &plusmn; 0.0030\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_11\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.83%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0133\n                \n                    &plusmn; 0.0031\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_28\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.87%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0131\n                \n                    &plusmn; 0.0039\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_2\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 96.95%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0126\n                \n                    &plusmn; 0.0025\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_9\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.02%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0122\n                \n                    &plusmn; 0.0017\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_30\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.07%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0119\n                \n                    &plusmn; 0.0026\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_8\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.12%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0116\n                \n                    &plusmn; 0.0018\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_35\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.12%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0116\n                \n                    &plusmn; 0.0026\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_8\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.14%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0115\n                \n                    &plusmn; 0.0035\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_34\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.15%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0115\n                \n                    &plusmn; 0.0040\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_49\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.15%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0114\n                \n                    &plusmn; 0.0016\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_47\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.15%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0114\n                \n                    &plusmn; 0.0036\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_46\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.19%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0112\n                \n                    &plusmn; 0.0011\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftip90\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.20%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0112\n                \n                    &plusmn; 0.0041\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftip80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.26%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0108\n                \n                    &plusmn; 0.0039\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_3\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.40%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0100\n                \n                    &plusmn; 0.0004\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_29\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.43%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0099\n                \n                    &plusmn; 0.0027\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_12\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.45%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0098\n                \n                    &plusmn; 0.0023\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftp95\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.51%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0094\n                \n                    &plusmn; 0.0043\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_41\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.52%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0094\n                \n                    &plusmn; 0.0012\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftp80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.53%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0093\n                \n                    &plusmn; 0.0030\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftip95\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.60%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0089\n                \n                    &plusmn; 0.0018\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftip85\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.61%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0089\n                \n                    &plusmn; 0.0013\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_14\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.65%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0087\n                \n                    &plusmn; 0.0014\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_45\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.68%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0085\n                \n                    &plusmn; 0.0022\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_32\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.75%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0082\n                \n                    &plusmn; 0.0017\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_9\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.77%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0081\n                \n                    &plusmn; 0.0019\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_7\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.82%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0078\n                \n                    &plusmn; 0.0022\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_4\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.83%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0078\n                \n                    &plusmn; 0.0016\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftp90\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.84%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0077\n                \n                    &plusmn; 0.0029\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_4\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 97.90%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0074\n                \n                    &plusmn; 0.0015\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fftp85\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 98.11%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0063\n                \n                    &plusmn; 0.0016\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                std\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 98.13%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0063\n                \n                    &plusmn; 0.0018\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                abs_mean\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 98.13%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0063\n                \n                    &plusmn; 0.0019\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                fft_22\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 98.34%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0053\n                \n                    &plusmn; 0.0013\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                std20\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 98.49%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0046\n                \n                    &plusmn; 0.0010\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                std80\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(120, 100.00%, 98.60%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0.0042\n                \n                    &plusmn; 0.0025\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                std40\n            </td>\n        </tr>\n    \n        <tr style=\"background-color: hsl(0, 100.00%, 100.00%); border: none;\">\n            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n                0\n                \n                    &plusmn; 0.0000\n                \n            </td>\n            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n                ffti_0\n            </td>\n        </tr>\n    \n    \n    </tbody>\n</table>\n    \n\n    \n\n\n    \n\n    \n\n    \n\n    \n\n    \n\n    \n\n\n\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.figure(figsize=(6, 6))\nplt.scatter(y_train.values.flatten(), y_pred)\nplt.xlim(0, 20)\nplt.ylim(0, 20)\nplt.xlabel('actual', fontsize=12)\nplt.ylabel('predicted', fontsize=12)\nplt.plot([(0, 0), (20, 20)], [(0, 0), (20, 20)])\nplt.show()","execution_count":76,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x432 with 1 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3t4qfhz8Kof3H2R1SCJOkliEEBljw9pV8MrJtNI7WX/yFA4t/ZPVIYlGkMQihMgIP323grzJp5JPDZvKX6d77z9YHZJoJEksQgjL/bh6KQVTy8nDwy/DZnBwzzKrQxIJkMQihLDU2q8W0ur1YWgU24e/xYGHJjyNQljM6tWNhRBN2Pdffk7h66fhxcauEW/TVZJKTpDEIoSwxLeVH9N2xl/ZQzP2jHyXLt16Wx2SSBJJLEKItFu16D+0rziDXaoF3vNns99Bh1sdkkgiSSxCiLT6av77dHrnLLbbCrFd+B4du3azOiSRZDJ4L4RImxWfvcMBH1zEL/a25F88m3Ydu1odkkgBabEIIdJi+f9mcNAHF7DZvi8Fo+ZIUslhkliEECm3bO6/6Db3Epx5+9Hqsvdp275T9CeJrCVdYUKIlFoy51UO//wafjQOYJ/LZ9F6732tDkmkmLRYhBAps3j28xzx+dWsNQ5m3yvnSFJpIiSxCCFSYtHMJ+m94Aa+dRxK8dXv06pwb6tDEmkiiUUIkXRfvPUIfRbfzKpmR9Dlmvdo2arI6pBEGkliEUIk1YI3/km/ZbezIr8PB1wzi4KWra0OSaSZDN4LIZJm/tR7KVt9P8vy+9Pt6rdont/C6pCEBSSxCCGSYv7kOyn7biKVLY6mx9XTcTRrbnVIwiKSWIQQCZv/0i2U/fA4i1sewxFXv47haGZ1SMJCkliEEI2mvV7mv3gjA9Y/y6JWf6H3VVPIMxxWhyUsJolFCNEo2utl/nPXMGDDK3xROJi+V76KPU9OKUISixCiEbTXy4KnL2fApn+xYO9TOfKKF7HZ7VaHJTKEJBYhRFy8Hg8Ln7yYsl9msKDdX+l3+bMom8xcEL+TxCKEiJnX42HR4+fRf+s7zG9/Nv1HPSZJRTQgiUUIERNPbS1LHj2bftvfZ17xBZRd9JAkFRGWJBYhRFS1bhdLHx3BkTv+zbwulzHggvutDklkMEksQoiI3K49LH/kr5Tu/Jh5+1/JgPPGWR2SyHCSWIQQpvbsruarR4bRp/pz5h98AwPOvsPqkEQWSEsHqVLqBaXUZqXUiqDbJiilVimlvlRKvaWUKjR57g9KqeVKqaVKqUXpiFcIAbtrdrFq0qmUVH/OgkNvpkySiohRukbeXgJOCLntQ+BwrfURwDfAzRGef6zWurfWujRF8QkhgtTs+o1vJw6hZ/VCvjj8TvoPH2N1SCKLpCWxaK0/BraG3PaB1rrW/+18YL90xCKEiGzXb1WsmTSYHruXsrhkLP3+er3VIYkskym1ghcC75ncp4EPlFKLlVKjIr2IUmqUUmqRUmrRli1bkh6kELnut+1bWffIiXTbs4IlpfdzZPmVVockspDliUUpdStQC7xm8pCjtdZ9gBOBvyml/s/stbTWz2itS7XWpe3atUtBtELkru3bfmHDoydwkGs1X5Y9ROnJl1odkshSliYWpdT5wEnA2VprHe4xWmun///NwFtAv7QFKEQTUfXLz2x57Hj2d3/HioGP0OfEC6wOSWQxyxKLUuoE4EbgFK11tcljWiil9gp8DRwPrAj3WCFE4/y66Se2PjGITrXr+PqYpyk5fqTVIYksl65y46nAPKCbUuonpdRFwGPAXsCH/lLip/yP7aiUmu1/6r7Ap0qpZcAXwCyt9fvpiFmIpuCXDT/y29Mn0MGzgW/+9Dy9jj3d6pBEDkjLBEmt9YgwNz9v8tgNwGD/12uAXikMTYgma7NzLXueG8w+3l9Zc/xL9Bw4xOqQRI6QmfdCNEE/r/uW2hdPosi7nXWDJ9Oj//FWhyRyiCQWIZoY55qvsb1yMq3YhfPkKXQvPc7qkESOkcQiRBOy/rvlOCafSjP2sPm0N+jW62irQxI5SBKLEE3Ej6uWUPCvoeTh4ddh0zmoZ5nVIYkcJYlFiCZg7VcLafX6MDSK7cPf4sBDZdk9kTqWz7wXQqTWd8s+o/D10/Bgp/qst+kqSUWkmCQWIXLYN0v+xz5vnc4emuM+9106H9Lb6pBEEyCJRYgcteqLD+nw9nB2qpZ4z59F8QE9rA5JNBEyxiJEDvpq3nt0ef98ttraYFz4Du07HWR1SClXUelkwpzVbKiqoWNhPqMHdaO8pNjqsJokSSxC5JgVn7zNAf++hC32drS4eDZtO3axOqSUq6h0cvOM5dS4PQA4q2q4ecZyAEkuFoiYWJRSB8TyIv6lV4QQFvvyv9M55KNL2WjvyF6jZtG2fSerQ0qLCXNW1yWVgBq3hwlzVktisUC0Fst3+DbaUv7/A0K/tyc5LiFEnJb+eyqHfXIl6/M60+ay2RS165D2GBLtjmrs8zdU1cR1u0itiIP3Wmub1tqutbYBFwP/AroDzf3/TwEuSnmUQoiIKue8TI9P/sYPxgG0/dsHliWVm2csx1lVg+b37qiKSmfKn9+xMD+u20VqxVMVdg9wsdb6W621S2v9LXApMDY1oQkhglVUOhk4fi77j5nFwPFz6064i2c9R8/Pr2W1/SCusN1O7we+qHd/ukTqjkr180cP6ka+Ub/jJN+wM3pQt5iOLZIrnsF7G9AV+Droti5IN5gQKWc2OO1eMoWh68axIu8wLtzzd36ttte7H9I3eJ1od1Qizw/8jFIVlhniSSwPA3OVUi8C64FOwPn+24UQKRTuav4k738Ytu5Zvmrei2v1jfxaW/856R687liYjzNMEgjXHRVuLCWe54dTXlIsiSRDxNwVprWeAFyAb1fHU4D2wIVa6wdSFJsQgHkXUFMSetU+0v4hE4xn+MTbk4OumcUPO2J7XirF2h1lNpZybPd20p2VI+Kax+LfFli2BhZpk23zE1I1SS/4av4C+3vcabzKvz0ljM2/if8WtEz4aj8ZQrujCgsMtIbrpi1lwpzVdb8Ls7GUj1Zt4b6hPZP6+5NJk9aIObEopZoBdwAjgL211q2VUscDh2itH0tVgKJpy6b5CalMgqMHdePmGcs5x1vBLcZU3vMcyY36Gu458Yh69wf/rqy42g90R0X6XUQaS0lmd1a2XZTkkniqwh4GDgfO5vc5LCuBy5MdlBAB2TQ/IdGqqEjKS4q5v9373GJMZaZnALfbr8NuNOO6aUsZOH4uAPcN7UlxYT4KKC7M576hPWM6gaaiqzHS7yJdpcHR/h7SxZo68XSFnQYcpLXepZTyAmitnUopSf0iZTKhiydW8STBeLpotNfLghf+zilbX2Rh6+Op/cM/2fX219S43cDvV+L3De3JZ2PCbzNsdrxUXdWb/S6cVTWMLOvM9MXOeid9BRzbvV2jjxdPDBuqaqQ1k2LxtFhchCQipVQ74NekRiREkGyanxDrlXg8EwG118v8Z6+h7Kfn+aJoCH2umsqD//4+rpZRpOMlo5UV7so/UuKfvthJn86tUcE/p//2ZLYaIv09Utm6FPElljeAl5VS+wMopToAj+GbjS9ESpSXFDe6i8dMqrpAYk2CsZ7UtNfLgqcuY8DGV1iwdzmlV76KPS8v7u7BSMdLtKsxngqv4GPPX7Ot3ppQwTElS6S/RzZ1sWajeLrCbgHuB5YDBcC3wLPAP1IQV8KWO7czcPxcqQLJAZkyoBut+yrWSXqxnNS8Hg8Ln7yYsl9m8Ko+kdudp1M84X+Nmu8R6XjRXivazxytwuvaaUvDHtujQ9OKeawVlU7ufmcl26p9XX+F+QZ3ndIj6t8r0t9jwpzVWdPFmo1iTixaaxdwHXCdvwvsF61N3h0ZQvpNRajGVpnFmpBiSYLRTuZej4dFj51L/23v8rTnZO5znwmoumP26dw67PPNxijMjmdTimO7t2sw3hG4qg/3M187bSlvLFrHa5cMACKPpUDD1WoD7EqFTS7hug1Hv7kMt+f3x1bVuBn9xjIg+ufa7O+RKVV0uSrmrjCl1NbA11rrLYGkopTanIrAkkX6TUWwWLtAQrvL7n5nZdL65MN10QDs2lPLjEU/sviREfTb9i5P66F1SSX4mPPWbG3wXICPVm0JG7tZt5RHa6YvdjKsb3HYrsZwSRjgs++3cluFL6maXeEr4K6ZK8MmFQWM6N8pbExd967/ehPmrK6XVALcXp3Q5zoVXazid/F0hRmhNyilDLJgrTDpN81d8VRXVVQ6scVwpRzuSt1MY95bgfiCu3cAfqvZjfH2pRxpn8djnME/95SHfb7XpJ/ArNopkDymLljf4GcPdFuFqyaL9LNNXbCeseU9GT2oG9dNW9oggWh8LYtwNDC2vCdrt+zks+/rJ8lA0hpb3jNqDLH+7m+rWF73s9uVYkT/Towt7ylLwKRQ1MSilPoE33uhuVLq45C79wM+T0VgyeTIi6dGQWSL2yqW89r8dXUntUhdn4ETbrikEtoFYnalHk68ffLBidCmfm+JGNQyyXiMwfYvuM89gqc9J8f1uoFYzLr6XluwDrOOa7MTtFkXGvw+RlJeUmw6jhJJ1zGzTO8LJK1oMcTyu7+tYjmT56+r+96jNZPnr2Ptlp113Xki+WI54z4HvADUAs8H/XsO3+TIoSmLLkn21Hrrmu4iN1RUOusllYAat4dr/ZMGg6u9zJKFApobtrqJhhWVzogtlFDxzL0IraAKnJwduHnCmMhg+xf8w31Oo5JKtGqnSKOhZifoSOMN9qCkWJzkAe/g5D96UDcMu2rwGMOmYhoPmbpgfdjbP/t+q0yITKGoiUVr/bLW+iWgxP914N8rWus5Wuvw7d0MY/YGE9lpwpzVYfvvA4LnakRKFhrYVu2uK5W9wT8oHKvJ89fFXLIcLrk1w8UzxkP8xb6E29wX8ILnxLiOD/XHBxpT1bR1156w8ZeXFDPwwDZhnzOi/+9bHpuNGTVWIGkFWnduj8YWlFsK8w0mnN4rpm4ss+oz8HVFitSIp4/oCqXUUcE3KKWOUkpNTHJMKRHpDSayTyz964HWSzxdNR6zAYwIYt3pMDTmfHbzvDGB/7N9yY3uS5js+Uvcxwb4bMxxdSfZxlQ11bi9jH5jWdj4X7tkACPLOted7O1KMbKsc11XVfAky+BWTCJG9O9Ur3UHvnGlfMPOxOG9WXrn8TGPjUSKaVu1W1otKRJPYhkBLAq5bTFwVixPVkq9oJTarJRaEXRbG6XUh0qpb/3/F5k89zz/Y75VSp0XR8x1kvWmF5kh38iscbNYKsSCWxMtqOElxwMMsH3F392X8rrn2EYfO7ibt7ykuFG/G7dXc+20pfVeK1Bd9tr8dbRv3ZyJw3vz/X2DKe3ShoHj59J1zCyum7a07uSf6MVbcNJK1sz44JZVOHe/s1LWC0sBFetUFH9ZcWet9e6g2wqAdVrrtjE8//+AncArWuvD/bc9AGzVWo9XSo0BirTWN4U8rw2+hFaKr+diMdBXa70t0vGadThYdzjv98ZU8FWWyC6hlV9d985vUE2UKYojVKYFig1aUs2Ljgforb7jOvcVvOM9KswrNe7Yyfjd5Bs2hvXdL+z8lmF9ixvcnqhwEx73HzPLtFR57fghcb3+2c/Oi/l3ooCzm/C5Qim1WGtdmujrxHNp8wkwVill8wdgA+7y3x6V1vpjIPSveyrwsv/rl4Fw9ZWDgA+11lv9yeRD4IQ44mbggW2a7Bsl24VbMsTKpBKt5WvWLVZR6WT6Yid7sZNXHffSS33Ple6rk5ZUAsdOxu+mxu1l8vx1YVsMUxesT2pSAV9Z8rXTltL77g/qfm/JXAH5tUsGUJjfYLZEWBp4bf46abkkKJ7Ecg3wZ2CjUuoLYAPwF+CqBI6/r9Z6o//rn/HtThmqGN9WyAE/+W+Lqrgwn4nDe0tZYZaqqHRyw+vLkn4iS4RXayYO7x1xsDq0yybwczR3b2OK414OVeu4zH0t73v7pSPkpErlWGVgRn1FpTNsNZhhj60SLNxacHed0iPmAgMNMqk6QfFsTfwT0Adfq2KC//++/tsT5p/Jn9C7Vik1Sim1SCm1qL3DVW9QU2SXSPNOrNSxML9u1nZRgflVcGCgPvBzFOoqpjjGcbByMsp9A//x9k1XyFnF7dXcNdNfrRVu1mUUZotigm+/mljJpOrExDXKp7X2aq3naa3f0FrP11p7Ezz+Jv8qyYHVksMtD+MEgkfg9vPfFi6+Z7TWpVrr0l89zWVALovFM0kxXQJ7hoQuihhOoMtmwpzVtHT/wr/ulaHZAAAgAElEQVQcY+mqNnGBezT/8/ZKU8TZqarG7SszDqnQc3t1XYmw2QrVZoP+d7+zkvKS4ogXA8FkMcrERJx5r5T6Wmt9qP/r9ZhcM2itOzfy+DOB84Dx/v/fDvOYOcC9QRVjxwM3R3tht8fb4IpFWi+ZJdxyLIDpyrNW0/jmrQTP5DbjrKqh990f0LzmZ6Y5xrGv2sb5rptY4Ps4iSjM/v7bqt10HTOr3uKWsWx7HCgtjrUBLItRJiZiVZhS6mit9af+r/9o9jit9f+iHkipqcAxQFtgE3AnUAG8DnQGfgTO0FpvVUqVApdprS/2P/dCfMv2A4zTWr8Y7XihVWHFhfmmu+uJ9AkkE2dVTYOVbw27Ak2DK9VsVcwWpjjGUaR+43zXTSzRh1gdUk4LrABglpSKC/PZ4O8ii6SowKDyjuOTHF12SFZVWMzlxtkmNLEA/BBnmaJIrtAFEnNZZ7WJKY5x7EU157rGsEwfZHVIOU8BDw/vbTohVgGt8w3TxTHBV1LdlFc5TlZiidYVFtMmXlrrOxINJNVkgqT1MnHcJBX2VxuZ4hhHc1yc5bqVlXp/0/1HRPIECivumrkybPIoLDDYuafW9PmR5iCJ+ERb3Th40Lw5MAxYiK/bqjPQD5iemtCSSz7U1msKlTYHqZ+Y4rgXG17OdN3Gat25rgsm0xQYNhx59ohX8MFsynzJfqvlG3aO7d6Okn98EPbnyTfsaE3YvV2actdXqkSsCtNaXxD4h39/Hq31QK31WVrro4Ez0xJlEiR7BVYRv1yvtOmu1vEvx1iAuqRi2Hy7NNoysMWslGLpncfH/NnItKQS+I0WF+YzrG8x0xauD1upV5hvcN/Qnmw3SaDbqt1SPZpk8ZQbn4hvsD3YTGBw8sJJHanysF6yV8HNJD3UWqY6xuImj+Gu2/lO7wfA8H6dmLaw4QZbmWCXy8NtFcuz8u9SXJjPw8N788P4IYwe1I2pC9aHbY0AtGiWR3lJMa0jzL6PdSFREZt4Est3wN9Cbrsc+D554aTGyLLO0m9qocCcg+umLaV5hi0emQy91HdMcYxjF80Z7rqdtboD4BvXm7H4J9MTXiZ4zV86HW3CZ6YJjIXEMpE2sLPmLpf5+ArINubJFM+n/GLgeqXUT0qpBUqpn4Ab/LdnpNAlvkX6hc6EjjSpMBv1Ud8w2XEfVbolw/fczjr9+6pEHq2pdic6hzi1AsuXlJcUU3nH8bRwZE7LJVIXXSABxFIQEthZM5YEn4ljYdkoniVdKoGD8S2f/xC+5fIP1lovSVFsCfNozbQv1kvzNkXMZj8Hy+VKsP7qa1513MdmXchw1+04iX03yUzirKrh0Nvfo6LSybjTMuMirDhowmw4gQQQLREEdpqMNWHk+jhgukTd896M1vpjpVQLpZRDa70rmUElU2DtIekKS67QOSmBPupFP27lo1Vb6mbTZ+IM+mQYaFvOc8aDrNftONt1C1sIu5VQ1qhxe7l22lIK8w0GHtjG8m0JAl1dZqXDgQQQ6T0WvBx/LKs5BLZ3FomLucWilOoJfAM8i2/Pe4A/Ai+kIK6kirWcUsTObE2myfPX1VsAMBcdY1vKC8Y/+UHvywjXbVmfVIJV1bhZsm67pTEExnoGjp9LVY2b0Hq64ATQde+GLQzDrijMN9juX3MssFpyaIFC4HGK+ts7i8TFs9HXp8DTWutXlVLbtNZFSqkWwDda64z7a4TOvJ84vLe8aZLIbCOmVDFsUOtNcPnrJPizbTGPG5P4Vu/HSNfNVLGXxRGlRirmrNgVxFLH0MJhx1Xrrbe0T2D5n+BJjLdVLI9p3bbAbHqgwdp0ck6oLy0z70P0ACb7v9YAWutdSqms6JQMDFCK5Eh3N1cmjIGfYPuCR41HWam7cq7rJnbQ0uqQUiYVc1ZiLY7b5Wo4JhdIKsHr/U1dsL7B48IJVHvJNhrpE09V2A9AvU0klFL98JUhZ7xc7ZaxSjbOfUjEKbbPecx4hGX6QEa6bs7ppJKpQgfg45kb5PSXHIv0iCex3A7MUkrdDTiUUjcDbwC3pSSyJMvAic9ZLbDZVXFhPorcXottmO1jHjYeZ7E+hHNdY9hJgdUhWcauVN2YxMiyzmmd+xJasRXve04mQKZPPOXG7+Lba74d8D+gCzBUa/1BimJLqgyc+Jz1ykuK+WzMcawdP4QHz+iVky2Y4faPmGA8zTzvYZzvupFqmkd9jk3l7oVMaCthd5r6KMNVbI3o38nk0eHJBMj0iWmMRSllx1f9NUprfUVqQxLZKNB3nambdDXGSPuHjDVe5L+eXlzqvo49OGJ6XqatqRVKqcQutAIVf7EMnCfLsL7FDcZHAhOf44lDJkCmR0wtFq21B9/OjRkwhCpSLZaJj+GUlxQzelA3muVl/7ItF9rfY6zxIh96+jLKfX3MSSXZUtHyefiM3lnXunx32cawt48t7xnXArMyATI94jkDPAzcrZTKngWFQtxWsdzqEDJe6BIs8SzOV1Hp5IY3lrGnNruvPy6zz+QO41Vme/pxhfsaXFjzlrcpGszhSIYJc1YzrG9x3Qk5MFYR+n+6DTywjel9VTX1VyAOvvipdtVi2OrHbNhVg9tkAmT6xDOPZT3QHvAAW/C1iBWgE9jzPmXC7SBpV4rv78uKxZgtM3D83LBdWYH5A3e/s7Juva/gmc0VlU5ueH1ZRq7iG4+r7DO4wXiTtz1Hcb37cjxk15V9sNCtn0MVFRjceXKPsCW46Z6nBL73WGO7UQ27ooUjj+017ro5Kot+3MrUBb6Vpe1KMaJ/J1k3MAor5rGMTPRgVsv2k146mPVBO6tqGP3msnoL+VXVuBn9xjIW/biV6YudWf771Vyf9wZX51Uw3fMHRrsvxRtXgz7zaHzJw2zhz23Vbm6e4WvFhyaXaFv4psKGqpqI8Ubi9mhaNMtj6Z2+DbsqKp313pMerZm+2ElplzYylyUN4vnkzAP+BDwHzPb//2dgQQriSolcLolNlkKT8lGbCr/7nturmbpgfZYvNKkZkzeVq/MqmFp7LH/PgaQCvr9ZtJN0uEqp2yqWW7IMUsfCfIYc0aHRz3dW1dR1l5ktOSRVYekRT4vlSaAbcDW+rYm7ALcAxcCFyQ8t+eItT2yKzBodkSqdsr2lckfeq1yY9z6v1P6FO2vPQ+dAUoHYq9OcVTXsP2YWHQvzObZ7u7o9WpLBpqBZnr3eSd7wDx4FX6gEthaevjixeSaBMUGzCx2pCkuPeBJLOXCg1rrK//1XSqkF+GbeZ3xiUSD9qzEw2741Fym83JP3IiPz/sPztSdyT+1IUjNcnvlSVUJ8Vv/OlHZp02CNLmi4bleytliocXuwKxX2gkeqwtIjnsTyM1AAVAXdlg+ErwPMMBpfv6v0r0aWy0vdB7Ph5b685xie91+erD2Z+2vPpKkmlVQZWRY+qQQ+g8GfxYpKZ1Lfdx6tyTfqt5SkKix94mnzvwq8r5S6RCl1olJqFL6xlleUUscF/qUmzOS4ZcaXVoeQ8ZrCGmB2PEwwnmJ43n+ZVDtUkkoKFBfmU9qlTUyl6xWVTka/sSzm1w6MlUb6iwWWwQ8sOSTL4qdXPC2WS/3/3xJy+2X+f+BrGByQaFCpkunbxGaCwAcvF0qHw8mjloeNJzjZPp8J7jN43FNudUiNZrcpPBZP81f+uTbBYQRaBpEG0INP8HfNXFlvifxIfhg/BDAviw8+fnlJw9n6Ij3iWSts/xj+ZWxSEbErLynGm4NJxaCWx4xHOdk+n3Hus7I6qdgU7NWs0RvAJs3a+4bw0Bm9w7YMzAbKQ2+PtQIteIZ9pEF4aZlYz/p3pkiqQKlltIHSwKRGs/5vK+YxpFIzXDxuTOLP9krucp/LS54TrA4pIVpbX2gRmNge3DIIvKeum7YUWxIH0IPHRyoqnaavXVyYH1NSifTeF4mTxJJDwu1DP/qNZfVKO4P3pp++2Nlgz3rwnShyacpPM1w8YzzEH+1fcqv7Ql7z/NnqkBJmdmJNJ6+mrkw5cNIPfv+Fiy/cAHq0SZFFBQZaw3XTlnL3OyvZubs25tcOJ9znxGyiqGic3CjYF0D4fejdXt1gYmON2xN2UmPwBLLGzH7ORPns5gVjAn+wLWe0e1RWJJVYcrrVSSUgeFD+rpkrI5YLmw2g33lyD9PnFBUY7HZ7qapxo/G9L8ONx9iVirkLTCZPpp4klhwSz+QvsxNTYLJcLmhBDS85HqDM9hXXuy/nDc8xVocUlQLOLuucdZV5NW5PxK7TwLbC4U78kZLBtmp3THNbvFrH3NqIdexHNF6TSiyF+Vm7MHNM4um7jrS8TWZcCydmL6p5xTGevuobrnFfSYX3aKtDiokGPlq1pa5UFpJXCG1l72akk3ZFpTPh2OJ575s9ViZPJk+TSiwn9Wr8OkTZINwcFMOmMOwNlw8f0b9T1l0Vx6oVO5nsuJeeag1/c1/Du94BVocUlw1VNXW7cxYX5ict0af6gqGowDBNEJFO2hPmrE4otngnPob7nMjkyeSydPBeKdUNmBZ00wHAHVrriUGPOQZ4G1jrv2mG1vofjTneR6u2NDLS7BC8i2O4qjBnVQ12pahxe5j15UayrW1SVGCwvdodcbe5InYw2XEfByknl7mvY663T9riSxYNdB0zK+qy95kk37Bz58k9WPTjVl6bv65e3NFO2vF2QYVbIj+eQXezz4kM3CePpYlFa70a6A112x87gbfCPPQTrfVJiR6vKSxVEmlSWHAlTDYOzgcGcM20ZTuTHffSVf3MJe4b+NjbK22xpUK2JJXggfPykuKIy7iEE88yQsVJSgIyeTK1Mqnc+E/A91rrH1N5kKa6Xli0ip1sEKkQah+2McUxjo7qVy5w38g8r3mlkYhdsX/F449WbcFZVdOgFZVv2BtUY8V70h49qFvEFYnh91bKhqqauuqtpvg5zhaZlFjOBKaa3DdAKbUM2AD8XWu9MtyD/OuXjQKwt2oX9oVCl5NoCioqnTk12TFUB35limMs7dR2znPdxELd3eqQcsLAA9vw2iX1x6dSMbEwXNdUIJltqKqhsMBg5+7auvewzDvJfDFvTZzSIJRy4EsaPbTWm0LuawV4tdY7lVKDgUla64OjvWa4rYnBVxmz1r/eUFNR8o8PUtb1pVTklkSq7ae2MMUYS6Hayfmum1iiD7EumBw0cXhvy0/ekbbL/mxMRq97m3Ws2Jo4lU4EloQmFQCt9Y6gr2crpZ5QSrXVWv/SmAM1lZLC4CvLVJ73rUwqndUmpjjGsRfVjHTdwpf6QOuCMaGAow5sw5J127OyK3L0m8u4a+bKRg+UJ4PMO8k+mVJuPAKTbjClVHulfJMulFL98MX8a2MO0lRKCgNLVjhTnFSsdIDawOuOf1DAbka4bsvIpAK+8YjPvt8KaIpMtn2OVYFhY2RZ54RfJx5uj64rmjBb9j7VZN5J9rE8sSilWgB/AWYE3XaZUiqwFP9fgRX+MZZHgDN1HP13gbr6prQfQ7J24stUB6ufmOa4BzseznTdzle6q9UhRVXj9rLb7SXfaPxHrqhFM0q7tKHAkVe3knA6kwz4Ztjf8Poy9h8zq25/+VSTeSfZJyPGWFKhWYeDdek1Tzep+vRA91cul1Ufqn5ksuNearFzlutWvtdN428bEG5ui5XzXcJVhUXS2MF/WY04PZI1xpKziaW0tFQvWrTI6jDSJnTF1lx0uFrDZMd9VNOMs1y38oPO7ZUUUsmm6m/OlYhYB9HDvUfjTUwitXJt8D7pqqrdDBw/t8lc4eR691dv9R2vOMazgwLOcd/GD3ofq0PKanalom7mFmtLKNZB9Fh3lIxEWi7ZIWcTi7Oqhlr/G74p1L3ncoVMqVrFi44J/KpbcZbrVjbQ1tJ4DLtvS2CLdwVuNLtSMW0F3KDLzaS0PNZB9ESru2Qflexh+eB9qoRejeX6fguNrZCJtMpxJiizfcXLjvvZrAsZ7rrd8qQC0MKRR7O87PzoGLbGbxBWmG8kNIieaHWX7KOSPbLz09FIuXxVH65yJpriwvyM3tv+aNtyXjQewKnbcqbrdjbRxrJYgtNvVY2bGnekpTAjM+yqblvfdGt81L7u5cBy/oGqtGF9i5kwZ3VMVWKJVnfJfJbskbNdYeFk6UVmTAJdAXe/szLmWfYbqmoydm/7Y2yVPG1MZI3uwNmuW9hKK0viCOyJEmulnWGDSDmnOGjF6Xj+VsniSaD/rqN/P/ng/e3j6ZpKdFVhs8UqZT5L5mlSiSWBi8ysUF7iu3qM9WSlISOTyl9si3jcmMRq3YlzXDdTxV5xv4Y9SXvCx1u6Hek9VlRgMHpQt3on1jtP7pHUEvFkVnuFCm1ZNGYwPpFVhcMtVinzWTJTk0oskP2rG0erisn2boHBtvlMMh5nhd6f81w3sYMWcb+GYYttcDrdtte4Gf3GsrrYAlf4yazmS9WPXVRgNPjcJKtrKtZKL9lHJXs0ucSSyasbR/uARet6qKh0Wr4oZCJOsX3Gw8YTLNEHc4HrRnZS0KjXycSkAr6Tfriikkxn2BR3ntyjwfvTrBs1nq6pxnSnZernV/yuySWWTL2ij+UDFq0q5uYZy7O2BHaY7WMmGE+zwHsoF7n/TjXNrQ5J4KsEu+sU3942oe9Pw64atA7j7ZpKxtwWkXmaXGIpTPPaSrGK5QMWqeshmzfyOtM+l3vznudT7+GMcl/PbppZHVJOacySL6Gz6QeOn9vg/eX2+BbWLPBvwNWYrimp9MpNTS6x7E7yyTdZM4Fj+YCZVcUUFhhZtdXwyLLOTF2wHo/WnGP/gHuMl5jr6c3l7mvZg8Pq8HJKvmHHpmCXq+H7XgFnl3Vm+mJnvaSh8LVIBo6fW/d+Nnt/VlW7qbzj+EbHJ5VeuSmHC3DDS2T+QajQ5ekTWVY8lsljZvMAsm1MZWx5Tx48oxeXGe9xj/ESH3j6cpn7uqxMKvHOHUqnwnyDYX2LwyYV8LVixpb3rJubAvVbN8Hv51QtXS8rF+emJpdYkimZM4Fj+YCVlxTXOwnYlaLG7cnIkmEzhfkGFZVOvp3+D8bYX2WWpx9XuK/BRWZ2URYX5lOYbx5bjdtjyeoFkY4ZuKdFszxmfbnR9HGB91F5STGfjTmO4sL8Bl1mgfdzqhJA8Hs6MOlSFqXMfk2uKyyZ+1cks3+4vKSYRT9uresisivFsL71J6MFutwKC4yMLamNxlVby5o372C08SYVnqO4wX05HjL3qt9ZVcPIss5M+2K96e/bo3Val643bIrh/Trx2vx1YY8Z3OKIJNburg1VNSkt9ZVKr9yTs8vmm+15D7/Pfk70zZzMvbhvq1je4EQRWFIcyJEl8TV/z3udK/Pe5o3a/+Om2lF4s6DRbNgUXdsW8O3mXWHvtylonmejOk0zcIsKDCrvOJ6uY2Yl5fUMu6KFI8+05St7yzcdsmx+FJ2KCmhpUmefrFVRY5kJHMvgfkWlM+zVZ3C3Wi4klVvypjAqbxZTao/j1toL0VmQVMA3L8YsqYBvfkq6kgr4BszBd8JPxoz9wPbD4ch4h2iMnG2xBG/0lcyWRahIiSPWjY3M4oPf+8uz+6+kuTPvFS7Im8NLtcdzV+151F/WUTRGvmGj1qtxeyK/OwrzDZQi7srBZLXsRfaQFkscUlkrH6l/ONbJX5HiKPTPE8jW7YYVXsbmvcjZef/h2drBjKs9G0kqyVHj9nUkFhUYVFW7KXDYw1aAndSrAx+t2hJXYlEg3V+i0bKjLyJBqSqVjCaWhFZR6cQWocJn5+5auu6dnTX9Nrzcn/csZ+f9h8drT5GkkgJeoMCRx9rxQygsCF+u/dGqLXFfRMk8EpGIJtFisWpV1EiTvyoqnTEtm+72aj77fmuqQkwZOx7+aTzFafbPeNg9jEmeoUhSSY1A0oh0IWP2XrSphjtKNmacUIhgOTvGctBhvfS+5z5c92E4tnu7uiu3dH04zMZYhvUtbjDbOZXSWQoLkEctE43HOcm+gAfcZ/CEpzyNR296imLoLi0qMNi5u7ZBAglUHSY6TihyQ7LGWHI2seR3PETve+7Ddd8Hlq8YW94zrXGEu9pL5v4bmcaglseMRxhkX8RY99k85xlidUg5LVyLw0ygrHh7jTvmi6tUFr6IzCOD91GELk+ugcnz11HapU1ar7TCDe5fO21p2o6fTs1w8YQxiT/ZK7nTfR4vewZZHVLWimWjMgW0ah77DqBuj6ZFszyW3hn72l6ySKRojCYxeB/srpkrLT1+RaUzJ0camrOHZ40H+ZO9kpvdF0lSSVBgNn802+NczidZg/gyuC8iaXKJxep1tSbMWZ3lc1Iaymc3LxgTONq2gtHuUUz1/MnqkHJCtPdJpPttJlkp3m0jZJFI0Rg52xVmhViqZ3KtC6El1bzgmEBf9Q3XuS/nbe/RVofUpIRLLr5EoMOu5B3vkKpsBywaI2cTi1k3QoGRmkZarFusmpV9xtKnnmlasYuXHPdzhFrD1e6rmOUtszqkjJXqyrzgLamb5dlMW+bxdp2BLBIp4pezXWE2k76AZinaPyPWJfTNuhayLam0ZieTHfdyuFrLFe5rJKlEoSHi8vsJv37Q26eqxm16YSVjIyIdcjaxeEzKL6viXC8pVrFWz5SXFNOnc+t6t/Xp3Lpub4xs0IYdTHWMo5v6iUvd1/OB90irQ8oKe2rTt1ClpmGrXcZGRLrkbFeYYQ+fM1N1xRZti9VIM+0/+34rB+/TIu0TGRujHVVMdtxLF7WJi9038In3CKtDyhqBTcHS1TrV+OabyNiISLecTSztWzXHMOxpW8Yl0rIxFZVORr+5LOIqtJGWZc8U+7CNqY6xdFBbucB9I/O8PawOKevEm1QUvouTaldt2IsSpXxdbOHuk0mMwioZkViUUj8AvwEeoDZ05qdSSgGTgMFANXC+1npJpNcsLDA4oW+x6Y6MyRapembg+LlRlzbPdB34lSmOsbRT2znPdRMLdXerQ8p5wYkh0tIq0HAjuFguomQNMJEqGZFY/I7VWv9ict+JwMH+f/2BJ/3/m6qqdjNt4fq6K0SP1kxbuD7lM++rXbVofFVhd81cyaIft2b98i37qc1MNcbRWu3iHNfNVOqDrQ4pJsnaCCvVCvMN9tR6oyaG5oat7jGF+QZ3ndKj3ns5niQRaxWjEI2RSYklklOBV7RvYbP5SqlCpVQHrfVGsyds2F7DPiGtBLdHc/c7Kxv9wYm2qVdod1dVjZvJ89c16liZoov6mSmOcbRgN2e5bmGFPsDqkGISuNqvqHQy+o1lMa2lZZWqGjcjyzqbtq7DtVZCCwHiLQmOda8gIRojUxKLBj5QSmngaa31MyH3FwPrg77/yX9bvcSilBoFjAKwt2oX9kDx7qIXSCahV77BV3gAN7y+LOtKhqM5UDmZ4hhHHh5GuG7ja93F6pBidmz3oL9/hq+hY1MwfbGzXut68vx1zPpyI3ee3CMlSUDWABOplCmJ5WittVMptQ/woVJqldb643hfxJ+QngFo1uHghM/y4a4Ug9W4PVw7bWlWVHPF6xC1ntcc4wDFCNdtfKM7WR1SXD5atQXwXZlbMb4Vz3vCqwn7HttW7ea6aUtNXyeRJBCtilGIRGTEPBattdP//2bgLaBfyEOcQPCZbT//baYizbyvqHQycPxc9h8zi4Hj51JRGf6l7n5nZUx7puRaUjlU/chUx1i82DgzC5MK+FqUFZVOS67AiwoMmidphYdI761EkkC0NcBi/YwIEY7liUUp1UIptVfga+B4YEXIw2YC5yqfMmB7pPEVMP9Auj1ebp6xHGdVTd0g+80zljf44FRUOuPuNssFPdUapjrGshsHZ7ju4Hudvf3tN89YToEjNSstmDFsvpZG6DpdRQUGI8s6hz2ZxzIjP9mTHctLirlvaE+KC/NR+MakApt3BVrq0T4jQpjJhK6wfYG3fBXF5AFTtNbvK6UuA9BaPwXMxldq/B2+cuMLGnswtxfc3uj91aFLsTQFJepbXnaMZ7tuyQj3rfyk97E6pISka4fOYGHWfazz0aot9SZJFvt3Np31ZcRrJCA1kx3NBvxlYF8kyvLEorVeA/QKc/tTQV9r4G+pjMNZVcPA8XMj7g+ey0rVKl5yPMAvujVnuW5lA22tDimnbKt217WAPVqTb9g5tnu7mLeoNpvsmIq5KDKwLxJleVdYuimTwRcF9Zr+GV5IlFQDbCt5xXE/m3QRZ7jukKSSBjVuD1MXrI8pqZh1e6Wqy0o29xKJytnEEi4x2G2Ks/s37OcOV8GTawPyZv5g+5IXjQdYr9sx3HUHmymyOqQmI1J5erixj1CxrqgdL9ncSyQqZxPLfkUF9QZFiwoMHjy9F2PLezYYtGxsEskz26YvSxxrq+Q545+s0R0Z4bqNX2gd/Ukiaewmzedif5dWR/+YyoQ5q8O2QlLVZRVpYF+IWFg+xpIqhQUGt53So67/ucDx+48aGLQM9E83Vm0Gz+aOZpBtIY8aj7BKd+Yc181sp6XVIeWcSHNZFDCif6cGYyyBsZdENo1LRpeVbO4lEpGzLZaqajfXv760Xv/z9a8vrbvyC+6fbmqG2ObzuDGJFXp/RrpuafJJxWFXKRlTi5RUzi7rHLb1fN/QnnXVY8HCdXHVW10ghtuFSJecbbH8tK2a9iGfbK+GW2Z8SXlJcdj+6WC5OJse4FTbpzxkPMlifQgXuG5kFzIg60rjzPzgpALhWwbXTVsa9rmhXVyB1QVCmd0uRLrkbIvF7FRR7Z9oEK0fOheTyun2//Kw8SQLvIdynusmSSoW0EQ/8cdalSVlwSJT5WxiiaaplU6eZf8PE4xn+NR7OBe6R1NDc6tDyjlmg/Ghop34Y63KkrJgkalytisskgNvnp1zKxFHcp59DncbL/MfTwlXuK9hDw6rQ8oIRQUGWvuWrQ8VmB2vFATeKoHu0dBu0kgbboWjgYHj53Js93Z8tGpL3eTG4N7yb6QAABi0SURBVO8LCwya5dnYXuM2nfgYaddSIazUJBNLU0oqF9tncZvxGnM8pVzpvhp3jv7JC/MNWjTLY4O/WCPaY5XyFXgUFhgYNlVvvxazRKH99w3rW1wvIYSe9APbLNiUb1wvHGdVTb29ekK/31btJt+w8/Dw3qbVWZF2LRXCSkrn6Em2WYeDdYfzJlodhqWusFdwo/E673rKuNZ9BbU5mlQAJgadgM9+dh6ffb/V9LH5hr3eVb5hV7Rw5DVoHQwcPzds1WA8e8mb7ecTK7tSPHhGL0kWIi2UUotDt4Zv1OtIYslFmmvzpnNt3gxmeI5mtPtSPKR3ld90auGws/IfJwBE3TEy0MUVKnjHyUALINInQ0G9JBRtza79x8xqdEFIoAUlyUWkWrISS+5ewjZZmhvzpnFF3kxer/0jY2ovwZvjNRrVrt9bH3fNXGmaVEJbKsE2+PdviWWMBKi3NteiH7fWm+gYbkJjIgubysrCItvk9hmnydHcmvcaV+TN5LXaP3FTE0gqUL8KKtxAfEBgMqLZa0Sb2xSO2WKSoRMaw1V6xUNKiEU2ydmzTqyln7lC4eWuvJe5JG82L9YO4tbaC9G5++etoyDmKqjykuKIpbyRWhSR3k1mxSDBySCw/lYkI8s6m75vpYRYZJOcPfN0LMzP3R8uhMLLuLznOT/vA56uHcLdtecS+VSYOzS+LaR73/0B+4+Zhdm6oEr5xl8iLbBodlK3K8Xa8UNMWzuxJoPykmLT1yguzGdseU8ePKOXrCwssl5Oj7HY7QpvGpfrsIINLw8Yz/BX+8c8WlvOg7Wn01SSSkDwFtJmtShaU2/cI9x4hVnLw6M1FZVOqqpdYe8vO6CIJeu2xzSfJNrcEykhFrkgZ6vCWu7XTbcd+ZDVYaSUHQ8PGk9Sbv+ch9x/5RHPUKtDyniRSoXNyouLCgx2u72m4y+BZe5jTQap2PVRiGSQcuMocr3cOI9aJhmPMcT+Bfe7z+RJzylWh5Q1fhg/JOzJHRrOnM837DTLs0UsClDA2vFDUh22ECmXrMSSs8MQuTx478DNE8Ykhti/4B73yCaXVBL529qVMt3SFwg7/rI9QlKBxAfWKyqdDBw/l/3HzGLg+LkJby0shNVyd4wlR/NKM1w8aUzkOPtSbnefz6ue460OKa0Mu6Jf1yI+/35royYcerSOuKXvZ2OOa9AtFWnmfKID66FzZ8w29RIim+Rsi8WTxbs7mmnOHp4z/skxtmWMcV+cFUnFrhQTh/dm4vDeCb9WUYHB8CM7sWTd9kbPYrcrZZokzOaKmM1BKcw3Ep4Rn6p964WwUs62WAx7buXMAnbzvPFP+tu+5sbaUbzp+aPVIQG+uRcfrdoS9mQduhRJY9bMCn2NgePnxj2JMVikBUgLC4ywtyerUivcuI7sqSJyUc4mlvatmlNrdRBJ0pJqXnQ8QIn6jmvdVzDTO9DqkADfFXtgJ0SIXu00elA3rjXZHTFYcWG+6Ws09oQbvPy9mXD3B/9MhQUGrfMNNlTVcPc7K7lr5sqIy9qHvk64Lq/W+UbYwgCZECmyWc4mlsICg1/J/p0gW7GLlx33c7hay1Xuq3jP29/qkOqc1KtDve/N5ocE33/dtKVR/yZd9/adVDdU1dR1CSW65lYsxY+hg/ShySB4vkzw17GMi5h1eTU3bA3WMJMJkSLb5VZ/UZCqanfWJ5VCfuM1xzh6qLVc4b4mo5IKNNxiN1p1U0Wlk3wj+lvus++3NqjYCrxWomtuRRLaSohn7bBo4yJmLa2qarfpSgBCZKucbbH8vGM3ba0OIgF7s53Jjvs4QG1klPt6/ustsTqkBoJPltGqmyoqnYx+cxnuRqyEELy6b+CEG0uXWjwMm2rQSoi32y3S481aWh0L86O29ITINjnbYnF7vFaH0GjtqGKqYyxd1c9c5P57RiYVqH+FH6266e53VjYqqQSELuhotuZWJEUFRt3zgtcUK8w3mHB6w8204h3nsCll2lqLdR97IXJBzrZYzBYjzHT7spUpjnG0V1u5wH0j872HWR2SqeCTotnVurOqhoHj59Ybk2iM0JN8uDW3AjtBVtW4w+5Lf+fJPeJqGYwe1C2uVlag4izcmIusASaakpxNLNk4jaUjvzDFMY691Q7OdY1hsc7cq9l8w1bvpBhpUL2xG1wFhFsaP9qJOhnrcZWXFHPXzJWmy7mEJq9g4Tbnki4v0VTkbGLJNp3UJqY6xtGKas5x3cxSfZDVIUXUPKRbJ1wLIlk04autIp2ok3USj7Sci1mpcIDMRRFNVc6OsWSTrmoj0xz30ILdnOW6JeOTCviqmYIF73OSbKl4zViZjbMUFRgpX0NMiGxlaWJRSnVSSn2klPpKKbVSKXVNmMcco5TarpRa6v93Ryyv3bJZdjTGDlROpjnuoRluznLdygp9gNUhxSTcLPXykmI+G3OcaSIoKjBMl3ArLsxn4vDeGTfAHW7Q3bArtI4+R0oG5kVTZXWLpRa4QWt9GFAG/E0pFW60+hOtdW//v3/E8sJ7ajO/KuwQtZ5/Oe7BhuZM1+18rbtYEofRiEqHPRG6vMwqoIYc0YE8e8NjBUp9I+3uaJXQmIoKDNBE7ALD/zgZTxFNlaWX9VrrjcBG/9e/KaW+BoqBrxJ97UwvN+6hfuBVx724MDjLdStrdEdL4gjdpCrWmodqt7duq99QZgPrE+asDlth1bJ5Xr3qqUw7IQfHFEuFW6ACTYimKmP6i5RSXYESYEGYuwcopZYBG4C/a61XmrzGKGAUgKNwn9QEmgRHqO951XEfv1HAWa5bWaf3tSyWalct101bSsfCfB4e3juuhSJDq56ChUsQ15lMagwdr8lkkQbkFUgZsRBkSGJRSrUEpgPXaq13hNy9BOiitd6plBoMVAAHh3sdrfUzwDMABx3WS2fiIpR91De85LifKt2Ss9y38ZNul/BrGjZwN7KBFrj6dlbVMPrNZQw/shPTFztjqu5yVtXUa7VEK/GNNPs8W5j9DJG2PBaiqbF6jAWllIEvqbymtZ4Rer/WeofWeqf/69mAoZSKabUWy3+4EP3U17ziGM8vujXDXXckJakcvE+LRieVUG6PZtaXGxuMc0Ra3iuwjpfZrozBM9Czafa52bpn2fQzCGEVS1ssSikFPA98rbV+yOQx7YFNWmutlOqHL1/8Gu21M22tsKNsK3jOeJANem9GuG5lC0UJv6Zdwbebd8X8+KICg6pqd8TJjNuq3fW6sQJrfJnVQAUv22K2pEu2zT6PZVfHTP8ZhLCS0rGsJ56qgyt1NPAJsBwIXHffAnQG0Fo/pZS6ErgcXwVZDXC91vrzaK/drMPBusN5E1MSd7z+z7aMZ4yH+EG3Z6TrFn6hdVqPr4CzyzrX2zul65hZpo8vDjpZDhw/N+qYS6DOK9w7SQFrxw+JO2Yrmf3M0t0lcp1SarHWujTR17G6KuxTouxOr7V+DHgsPREl33G2JTxpTOQ7XcxI181so1Vaj1+Yb3DXKQ3XyCqMMGs8+Ao9ltnjgTGScCfjwMKM2XRlL7s6CpGYTBuGyCmDbAt5yniYVbozZ7luTXtSGVnWmaV3Hh/2ZH7XKT0izl8JdGNFG1gPjC+Y7ZPi0dp0zCVTmf3M2VRkIISVcjaxWL3n/Um2eTxuTGK5PoCRrlvYTsu0Hn/i8N71ur5ClZcUM+H0XhGXS9lQVRM2YQTSUfAExtCJhHbVMGlF2wwrU8gAvRCJyYhy41Ro36o5HqzZmvg02yf803iKRbobF7pGs4v0XukqzLfIDRZICGZjCoFNqCC2wergQf/9TcZwEl3pOB1kgF6IxORsYiksMOh2YBs++35rWo97uv2/3J/3LPO8h3Gx+wZqaJ7W44NvoD4ex3Zvx+T568LeDo2bDW9WeabAdMZ+JsnEFQCEyBY52xVWVe1Oe1I52/5vJhjP8Im3Jxe6R6c9qSh84yqRusDCCd27PtrtsRg9qFvYqgwNWdEdJoRovJxNLD/v2J3W451vf59xxgv821PCKPf17MGR1uMXFRisHT8k7qQCqamCKi8pNu2GlOoqIXJbznaFpXMRylH2d7jFmMp7niO52n0V7jT/WhNd9DBVS60UJ/i6ydgFUgiRfjnbYklXVdiV9re4xZjKO54yrkpTUsk3bEldWj5VVVCJvG4sS8QIITJTzrZY2rdqTmoXodRcl/cm1+S9xXTP0dzovhQPDedxpMJutzepM8AjVUEl0mpIpLpqwpzVUZeIEUJkppxNLIUFBjUOO7tcyd+Dnf9v786DpCjPOI5/H3YXlCMCapQQPBCPqAmIBI8YgyUKbkTQiGdEETVqSEVTqBiPUqoSSy0xMSpeUCqSuNGoQaNRk5jK5QkBFUE5CpTDRVEuj7Cz++SP7sFhdmZ3du3pnpn9faq2tne6p+fh3Zf32fft7vfFuaL6YS6qfpK61DCuTJ1HU4ydv2I8qJfrLqhC5sxqz3kLoaffRcpXxQ6FQbGGw5xrqh/iouonmZkazuSYk4oR35K3LfUaik1Pv4uUr4pOLBtaWT62rYwmplTfz4TqZ5iRGsk1qfF4niJs+2K/hTnz0N1iGwpKstegp99FyldFJ5Yo/7o1mvhl9XTGVT/PXanjmZI6i3zpwyjOE/+9uta063bi9kqy15A9RUwUNymISDwq9hoLBH/1Xvbo/JzrrLdFJ5q4ueZuflD1T25LjWFqaiz5kkonvpj/P0pJrKN+2Yh9t7nGko4jrl6Dnn4XKU8VnVjSjdL1Ty7YugRvWpUZjQWsRVNFI1NrpjG66j/M6vpDpm0aBeS/IWCHrjXNPitTt85VfLqlsU09mr4JPcOhObNEpD0qOrHAF43jdbMXbLP+SKN7q0NWNaT4dc3t1Fa9wg0Np3Pl5XfQ7b+ruLRuXs739dw+WKGxJU1e+DBZKSwspV6DiLRVRV9jgS9umc21qJWT/yJ7Zxq4s+ZX1Fa9wpSGs3iqxylA0NDeeuqgZmuZ1HQyrjvhgFavP3zW0JhzSvlscd79JSISpYpPLLlumc3k0GxNki5s4Z6aqRxTNZerG8Yzo/G4bRr5zLVM0heWbx47kDEH9c274FWmRvcWj0kvJayegoiUo4ofCmvt1tjM4aZB1z/H559t5t6aW/hOpwVc0XA+dY1H0XP7mmaNfL4hoszrEvnWHklfM0lfu+jZtQb34PZoXccoHZqrTKR9Kj6x5JtgEZrf4XTNMbvR98/n8G1bxKSGH/FY05Fb97VlDZF00sl+cj3zM3XtorRFMeuASEdV8UNh+YamenWt2ea5iI3r13HAC+MZYm9zhf9km6Sy/rOGdk2AqGcxyleSsw6IlLuK77EUcsvsho8+oP7OWvZqWMrrh93Ki/N2gy3b9nLaOwGieiblSXOVibRfxScWaLlxX//h+3w4rZY9UitYcMTtDD7mDFb/Pfd67WpUOo5irVEj0hFU/FBYS9bVr+TjO0fQL/Uui4bdzaBjzgA0AaJorjKRL6PDJpYPV69g890j2bVxNYuHT+dbR528dZ8aFdH1MZH26xBDYdnqVy5ly/Tj2blpHctGPMCBh9dus19TmQjo+phIe3W4xLJmxds03T+KXk0bebf2IQ445Nicx6lRERFpnw6VWFYtW0jVg6PowaesHv0w+w0elnRIIiIVp8MklvcWz6fLrDF0ZgtrT/w9+ww8IumQREQqUodILCsWzqFb3Ul0oomPxz7GgAMOSTokEZGKVfF3hS1782V61I0BYNOpT7CnkoqISFElnljMbKSZvW1mS8xsco79XcysLtz/spntUei5l8z/F70fPYkU1Xx25mx2/8bBUYYuIiI5JJpYzKwKuAM4DtgfON3M9s86bALwsbsPAG4Fbizk3J9/uomvPn4Kn7M9DeOeot/eA6MMXURE8ki6xzIUWOLuy9x9C/AwMDrrmNHAA+H2o8DRZq2vlNV5/TI2WXd8/J/o2z/eteJFRDqypBNLX+C9jJ9Xhq/lPMbdU8AGYMfWTpyimuoJz9Bndz0tLyISp4q6K8zMLgAuCH/83679BryZZDwF2An4MOkgCqA4o6U4o6U4oxPJX+JJJ5ZVQL+Mn78evpbrmJVmVg3sAKzLdTJ3vwe4B8DMXnP3IZFHHKFyiBEUZ9QUZ7QUZ3TM7LUozpP0UNirwN5mtqeZdQZOA2ZnHTMbODvcPhn4m7t7jDGKiEgbJNpjcfeUmU0EngWqgBnuvsDMpgCvuftsYDow08yWAB8RJB8RESlRSQ+F4e5PA09nvXZtxvbnwNh2nPqeLxlaHMohRlCcUVOc0VKc0YkkRtOokoiIRCnpaywiIlJhyjqxFHM6mAhj7GdmL5jZW2a2wMx+muOYYWa2wczmhV/X5jpXDLEuN7M3whia3R1igdvC8nzdzAYnEOO+GeU0z8w2mtklWcckUp5mNsPM1prZmxmv9Taz581scfi9V573nh0es9jMzs51TJHjvNnMFoW/18fNrGee97ZYR2KI8zozW5Xxu63N894W24Yix1iXEd9yM5uX571xlmXOdqho9dPdy/KL4GL/UqA/0BmYD+yfdczFwF3h9mlAXQJx9gEGh9s9gHdyxDkMeKoEynQ5sFML+2uBZwADDgVeLoE68D6weymUJ3AkMBh4M+O1m4DJ4fZk4MYc7+sNLAu/9wq3e8Uc57FAdbh9Y644C6kjMcR5HTCpgHrRYttQzBiz9t8CXFsCZZmzHSpW/SznHkvRpoOJkruvcfe54fYmYCHNZxcoF6OBBz3wEtDTzPokGM/RwFJ3X5FgDFu5+z8I7lzMlFkHHwDG5HjrCOB5d//I3T8GngdGxhmnuz/nwcwWAC8RPFOWqDzlWYhC2oZItBRj2NacAvyuGJ/dFi20Q0Wpn+WcWIo2HUyxhENxBwEv59h9mJnNN7NnzCypyc0ceM7M5lgwi0G2Qso8TqeR/z9tKZQnwC7uvibcfh/YJccxpVau5xL0THNprY7EYWI4ZDcjz9BNqZTnd4F6d1+cZ38iZZnVDhWlfpZzYikrZtYd+ANwibtvzNo9l2A4ZyDwG+CJuOMLHeHugwlmm/6xmR2ZUBytsuCB2hOAR3LsLpXy3IYH4wolfRummV0FpIBZeQ5Juo5MA/YCBgFrCIaaStXptNxbib0sW2qHoqyf5ZxY2jIdDNbKdDDFZGY1BL/MWe7+WPZ+d9/o7pvD7aeBGjPbKeYwcfdV4fe1wOMEQwqZCinzuBwHzHX3+uwdpVKeofr0cGH4fW2OY0qiXM3sHOB44MywkWmmgDpSVO5e7+6N7t4E3Jvn8xMvz7C9OQmoy3dM3GWZpx0qSv0s58RSFtPBhOOs04GF7j41zzG7pq/9mNlQgt9LrAnQzLqZWY/0NsHF3OxJPGcD4yxwKLAhoxsdt7x/DZZCeWbIrINnA3/MccyzwLFm1isc2jk2fC02ZjYSuBw4wd0/zXNMIXWkqLKu6Z2Y5/MLaRuKbTiwyN1X5toZd1m20A4Vp37GcUdCsb4I7lJ6h+AOkKvC16YQ/OcA2I5gqGQJ8ArQP4EYjyDoXr4OzAu/aoELgQvDYyYCCwjuXnkJODyBOPuHnz8/jCVdnplxGsHCbEuBN4AhCf3euxEkih0yXku8PAkS3RqggWAcegLBNb2/AouBvwC9w2OHAPdlvPfcsJ4uAcYnEOcSgnH0dB1N3035NeDplupIzHHODOve6wSNYp/sOMOfm7UNccUYvn5/uj5mHJtkWeZrh4pSP/XkvYiIRKqch8JERKQEKbGIiEiklFhERCRSSiwiIhIpJRYREYmUEotImTEzN7MBScchko8Si0iRhdOjD086DpG4KLGIiEiklFhE2sDMJpvZUjPbFC6adGLGvvPNbGHGvsFmNhPYDXjSzDab2eUWLES2Muu8W3s1ZjbUzF40s/VmtsbMbg+nJhEpC0osIm2zlGA69B2A64GHzKyPmY0lWIRqHPAVgpmX17n7WcC7wCh37+7uNxXwGY3ApcBOwGEE685cHPU/RKRYlFhE2sDdH3H31e7e5O51BHMsDQXOA25y91c9sMTbuQCZu89x95fcPeXuy4G7ge9F9o8QKbLqpAMQKSdmNg74GbBH+FJ3gp5FP4LeTBSfsQ8wlWAiwK4E/0/nRHFukTioxyJSIDPbnWANkInAju7ek2CqcyOYGXivPG/Nnun1E4KEkT5vFbBzxv5pwCJgb3f/CvDz8DNEyoISi0jhuhEkiQ8AzGw8cGC47z5gkpkdHK5XMyBMRAD1BNOkp70DbGdm3w8XX7oa6JKxvwewEdhsZvsBFxXtXyRSBEosIgVy97cIlsJ9kSBZfBP4d7jvEeAXwG+BTQTLIfcO33oDcHV4l9ckd99AcDH+PoKV+D4hWMsjbRJwRniee2lhFUKRUqT1WEREJFLqsYiISKSUWEREJFJKLCIiEiklFhERiZQSi4iIREqJRUREIqXEIiIikVJiERGRSCmxiIhIpP4P74K7Wiehb8kAAAAASUVORK5CYII=\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"score = mean_absolute_error(y_train.values.flatten(), y_pred)\nprint(f'Score: {score:0.3f}')\n# 2.277 w/ log_diff, var\n# 2.270 w/ log_diff\n# 2.207 w/ log_diff + last 10% data::fnn TURNED IN WITH SCORE 1.612\n# 2.173 increased epochs, increased layer width, added one layer, lowered learning rate\n# 2.143 doubled epochs\n# 2.169 doubled batch size\n# 2.493 lowered learning to 0.001\n# 2.111 back to 0.025 lr, doubled epochs\n# 2.108 added layer w/ 40 nodes\n# 2.081 added 10 nodes to layer 1 TURNED IN WITH LOWER SCORE 1.631\n# 2.121 Lowered epocks \n# 1.884 Added back in ptp, var, and fft features\n# 1.594 fft increased from 20 to 50 features\n# 0.065 Large network with 10% features added, total 113 TURNED IN WITH SCORE 2.017\n# 1.903 Added droppout and reduced features to 88 TURNED IN WITH SCORE 1.747\n# Same features with svm TURNED IN WITH LOWER SCORE NOPE\n# 1.929 Added regularization, reduced layer size TURNED IN WITH SCORE 1.84\n# 1.653 Increased fft to 100 TURNED IN WITH SCORE 1.913\n# 1.444 50 fft real and 50 fft imag\n# 1.380 reduced net size to 3 layers of 50, epochs to 300, and dropout to 0.2\n# 2.341 lightgbm model using grandmaster parameters\n# 1.230 Took out regularization TURNED IN WITH SCORE 1.902\n# 1.813 Dropout to 0.3, reduced layer size to 30 30 30 TURNED IN WITH SCORE 1.951\n# 1.609 Increased epochs to 500\n# 1.614 Feature changes (more percentiles and took out variance and max/min) with weight information\n# 1.580 Added fft and ffti percentiles COMMIT\n# 1.771 Removed third layer\n# 1.363 Added smoothed data peaks wow\n# 1.485 Added zero crossings TURNED IN WITH SCORE 2.064\n# 1.925 Same as above with SVM TURNED IN WITH SCORE 1.675\n# 1.795 Two layers of size 20, 300 epochs\n# 1.661 Removed percentile features and added rolling zero crosses TURNED IN WITH SCORE 1.831\n# 1.919 Same as above with SVM \n# 1.910 Added avg distance between peaks\n# 2.161 lightgbm TURNED IN WITH SCORE 1.919\n# 1.769 Reduced network and dropout \n# 1.715 SVR with nu = 1\n# 1.712 changed gamma to scale commited\n# 2.178 nu = 0.2 committed\n# 1.909 nu = 0.5 committed","execution_count":77,"outputs":[{"output_type":"stream","text":"Score: 1.909\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"submission = pd.read_csv('../input/sample_submission.csv', index_col='seg_id')","execution_count":29,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"X_test = pd.DataFrame(columns=X_train.columns, dtype=np.float64, index=submission.index)","execution_count":30,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for seg_id in X_test.index:\n    seg = pd.read_csv('../input/test/' + seg_id + '.csv')\n    seg_smooth = seg.rolling(10).mean()\n    \n    x = seg['acoustic_data'].values\n    x_smooth = seg_smooth['acoustic_data'].values\n    \n    \n    X_test.loc[seg_id, 'ave'] = x.mean()\n    X_test.loc[seg_id, 'abs_mean'] = np.absolute(x).mean()\n    X_test.loc[seg_id, 'std'] = x.std()\n#     X_test.loc[seg_id, 'max'] = x.max()\n#     X_test.loc[seg_id, 'min'] = x.min()\n    X_test.loc[seg_id, 'log_diff'] = np.log(x.max()-x.min())\n    \n    X_test.loc[seg_id, 'kurt'] = scs.kurtosis(x)\n    X_test.loc[seg_id, 'skew'] = scs.skew(x)\n    \n#     X_test.loc[seg_id, 'p25'] = np.percentile(x,0.25)\n#     X_test.loc[seg_id, 'p50'] = np.percentile(x,0.50)\n#     X_test.loc[seg_id, 'p75'] = np.percentile(x,0.75)\n#     X_test.loc[seg_id, 'p80'] = np.percentile(x,0.80)\n#     X_test.loc[seg_id, 'p85'] = np.percentile(x,0.85)\n#     X_test.loc[seg_id, 'p90'] = np.percentile(x,0.90)\n#     X_test.loc[seg_id, 'p95'] = np.percentile(x,0.95)\n#     X_test.loc[seg_id, 'pinter'] = X_test.loc[seg_id, 'p75'] - X_test.loc[seg_id, 'p25']\n    \n    for i in range(0,10,2):\n        temp_x = x[int(len(x)*i/10):int(len(x)*(i+2)/10)]\n        temp_x_smooth = x_smooth[int(len(x)*i/10):int(len(x)*(i+2)/10)]\n        X_test.loc[seg_id, 'ave{}'.format(10*i)] = temp_x.mean()\n        X_test.loc[seg_id, 'std{}'.format(10*i)] = temp_x.std()\n#         X_test.loc[seg_id, 'max{}'.format(10*i)] = x[int(len(x)*i/10):int(len(x)*(i+2)/10)].max()\n#         X_test.loc[seg_id, 'min{}'.format(10*i)] = x[int(len(x)*i/10):int(len(x)*(i+2)/10)].min()\n        X_test.loc[seg_id, 'log_diff{}'.format(10*i)] = np.log(temp_x.max()-temp_x.min())\n        X_test.loc[seg_id, f'peaks_smooth{10*i}'] = len(sig.find_peaks(temp_x_smooth)[0])\n        X_test.loc[seg_id, f'zeros_smooth{10*i}'] = ((temp_x_smooth[:-1] * temp_x_smooth[1:]) < 0).sum()\n        X_test.loc[seg_id, f'peaks_diff_smooth{10*i}'] = np.mean(np.diff(sig.find_peaks(temp_range_smooth)[0]))\n    \n    freq = np.fft.fft(x, n=50).real\n    freq_i = np.fft.fft(x, n=50).imag\n    \n    \n    X_test.loc[seg_id, 'fftp80'] = np.percentile(freq,0.80)\n    X_test.loc[seg_id, 'fftp85'] = np.percentile(freq,0.85)\n    X_test.loc[seg_id, 'fftp90'] = np.percentile(freq,0.90)\n    X_test.loc[seg_id, 'fftp95'] = np.percentile(freq,0.95)\n    \n    X_test.loc[seg_id, 'fftip80'] = np.percentile(freq_i,0.80)\n    X_test.loc[seg_id, 'fftip85'] = np.percentile(freq_i,0.85)\n    X_test.loc[seg_id, 'fftip90'] = np.percentile(freq_i,0.90)\n    X_test.loc[seg_id, 'fftip95'] = np.percentile(freq_i,0.95)\n    \n    for idx, freq_val in enumerate(freq):\n        X_test.loc[seg_id, 'fft_{}'.format(idx)] = freq_val\n        \n    for idx, freq_val in enumerate(freq_i):\n        X_test.loc[seg_id, 'ffti_{}'.format(idx)] = freq_val\n    \n    X_test.loc[seg_id, 'peaks_smooth'] = len(sig.find_peaks(x_smooth)[0])\n    X_test.loc[seg_id, 'zeros_smooth'] = ((x_smooth[:-1] * x_smooth[1:]) < 0).sum()","execution_count":31,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:37: RuntimeWarning: invalid value encountered in less\n/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:61: RuntimeWarning: invalid value encountered in less\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"X_test.head()","execution_count":32,"outputs":[{"output_type":"execute_result","execution_count":32,"data":{"text/plain":"                 ave       std      ...       peaks_smooth  zeros_smooth\nseg_id                              ...                                 \nseg_00030f  4.491780  4.893673      ...            18774.0        1296.0\nseg_0012b5  4.171153  5.922820      ...            19088.0        1618.0\nseg_00184e  4.610260  6.946967      ...            19697.0        1199.0\nseg_003339  4.531473  4.114133      ...            22166.0         610.0\nseg_0042cc  4.128340  5.797144      ...            19649.0        1512.0\n\n[5 rows x 146 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>ave</th>\n      <th>std</th>\n      <th>fft_0</th>\n      <th>fft_1</th>\n      <th>fft_2</th>\n      <th>fft_3</th>\n      <th>fft_4</th>\n      <th>fft_5</th>\n      <th>fft_6</th>\n      <th>fft_7</th>\n      <th>fft_8</th>\n      <th>fft_9</th>\n      <th>fft_10</th>\n      <th>fft_11</th>\n      <th>fft_12</th>\n      <th>fft_13</th>\n      <th>fft_14</th>\n      <th>fft_15</th>\n      <th>fft_16</th>\n      <th>fft_17</th>\n      <th>fft_18</th>\n      <th>fft_19</th>\n      <th>abs_mean</th>\n      <th>log_diff</th>\n      <th>kurt</th>\n      <th>skew</th>\n      <th>ave0</th>\n      <th>std0</th>\n      <th>log_diff0</th>\n      <th>peaks_smooth0</th>\n      <th>zeros_smooth0</th>\n      <th>peaks_diff_smooth0</th>\n      <th>ave20</th>\n      <th>std20</th>\n      <th>log_diff20</th>\n      <th>peaks_smooth20</th>\n      <th>zeros_smooth20</th>\n      <th>peaks_diff_smooth20</th>\n      <th>ave40</th>\n      <th>std40</th>\n      <th>...</th>\n      <th>ffti_12</th>\n      <th>ffti_13</th>\n      <th>ffti_14</th>\n      <th>ffti_15</th>\n      <th>ffti_16</th>\n      <th>ffti_17</th>\n      <th>ffti_18</th>\n      <th>ffti_19</th>\n      <th>ffti_20</th>\n      <th>ffti_21</th>\n      <th>ffti_22</th>\n      <th>ffti_23</th>\n      <th>ffti_24</th>\n      <th>ffti_25</th>\n      <th>ffti_26</th>\n      <th>ffti_27</th>\n      <th>ffti_28</th>\n      <th>ffti_29</th>\n      <th>ffti_30</th>\n      <th>ffti_31</th>\n      <th>ffti_32</th>\n      <th>ffti_33</th>\n      <th>ffti_34</th>\n      <th>ffti_35</th>\n      <th>ffti_36</th>\n      <th>ffti_37</th>\n      <th>ffti_38</th>\n      <th>ffti_39</th>\n      <th>ffti_40</th>\n      <th>ffti_41</th>\n      <th>ffti_42</th>\n      <th>ffti_43</th>\n      <th>ffti_44</th>\n      <th>ffti_45</th>\n      <th>ffti_46</th>\n      <th>ffti_47</th>\n      <th>ffti_48</th>\n      <th>ffti_49</th>\n      <th>peaks_smooth</th>\n      <th>zeros_smooth</th>\n    </tr>\n    <tr>\n      <th>seg_id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>seg_00030f</th>\n      <td>4.491780</td>\n      <td>4.893673</td>\n      <td>254.0</td>\n      <td>-3.319525</td>\n      <td>-20.728598</td>\n      <td>80.584637</td>\n      <td>-8.299891</td>\n      <td>3.298374</td>\n      <td>31.913591</td>\n      <td>-8.097701</td>\n      <td>-24.760416</td>\n      <td>-31.212905</td>\n      <td>6.500000</td>\n      <td>14.619558</td>\n      <td>20.423540</td>\n      <td>1.250528</td>\n      <td>8.580158</td>\n      <td>-21.298374</td>\n      <td>-5.945657</td>\n      <td>-5.334304</td>\n      <td>-12.268287</td>\n      <td>-12.983360</td>\n      <td>5.224607</td>\n      <td>5.247024</td>\n      <td>28.836567</td>\n      <td>0.327904</td>\n      <td>4.501200</td>\n      <td>6.181731</td>\n      <td>5.247024</td>\n      <td>3689.0</td>\n      <td>298.0</td>\n      <td>6.876175</td>\n      <td>4.488967</td>\n      <td>4.159521</td>\n      <td>4.330733</td>\n      <td>3794.0</td>\n      <td>206.0</td>\n      <td>6.876175</td>\n      <td>4.489433</td>\n      <td>4.741746</td>\n      <td>...</td>\n      <td>3.346482</td>\n      <td>-12.357964</td>\n      <td>-8.007109</td>\n      <td>21.564029</td>\n      <td>5.132729</td>\n      <td>11.716240</td>\n      <td>6.147031</td>\n      <td>-0.161808</td>\n      <td>15.539687</td>\n      <td>-4.096285</td>\n      <td>-8.055016</td>\n      <td>7.036576</td>\n      <td>18.975138</td>\n      <td>-8.881784e-15</td>\n      <td>-18.975138</td>\n      <td>-7.036576</td>\n      <td>8.055016</td>\n      <td>4.096285</td>\n      <td>-15.539687</td>\n      <td>0.161808</td>\n      <td>-6.147031</td>\n      <td>-11.716240</td>\n      <td>-5.132729</td>\n      <td>-21.564029</td>\n      <td>8.007109</td>\n      <td>12.357964</td>\n      <td>-3.346482</td>\n      <td>-46.444286</td>\n      <td>-44.283384</td>\n      <td>-29.435457</td>\n      <td>-3.777480</td>\n      <td>8.533951</td>\n      <td>-14.183617</td>\n      <td>-22.527597</td>\n      <td>-37.308796</td>\n      <td>-131.182236</td>\n      <td>-29.592679</td>\n      <td>9.542860</td>\n      <td>18774.0</td>\n      <td>1296.0</td>\n    </tr>\n    <tr>\n      <th>seg_0012b5</th>\n      <td>4.171153</td>\n      <td>5.922820</td>\n      <td>209.0</td>\n      <td>23.093759</td>\n      <td>-16.046699</td>\n      <td>-61.335659</td>\n      <td>36.115603</td>\n      <td>31.697561</td>\n      <td>-18.449304</td>\n      <td>10.260912</td>\n      <td>-19.594092</td>\n      <td>-11.476950</td>\n      <td>0.545085</td>\n      <td>18.123247</td>\n      <td>-11.396905</td>\n      <td>-1.826485</td>\n      <td>24.988325</td>\n      <td>-5.197561</td>\n      <td>8.965465</td>\n      <td>-14.180999</td>\n      <td>13.563489</td>\n      <td>12.721962</td>\n      <td>5.198340</td>\n      <td>5.676754</td>\n      <td>56.217041</td>\n      <td>0.295705</td>\n      <td>4.017900</td>\n      <td>5.161684</td>\n      <td>4.718499</td>\n      <td>3891.0</td>\n      <td>274.0</td>\n      <td>6.876175</td>\n      <td>4.137700</td>\n      <td>8.559397</td>\n      <td>5.676754</td>\n      <td>3485.0</td>\n      <td>504.0</td>\n      <td>6.876175</td>\n      <td>4.171700</td>\n      <td>4.736224</td>\n      <td>...</td>\n      <td>-17.011378</td>\n      <td>12.648766</td>\n      <td>-2.972819</td>\n      <td>-9.220539</td>\n      <td>-3.658732</td>\n      <td>5.356349</td>\n      <td>5.616267</td>\n      <td>-10.752873</td>\n      <td>-10.824893</td>\n      <td>6.467664</td>\n      <td>2.880041</td>\n      <td>4.049916</td>\n      <td>-2.735203</td>\n      <td>-1.776357e-15</td>\n      <td>2.735203</td>\n      <td>-4.049916</td>\n      <td>-2.880041</td>\n      <td>-6.467664</td>\n      <td>10.824893</td>\n      <td>10.752873</td>\n      <td>-5.616267</td>\n      <td>-5.356349</td>\n      <td>3.658732</td>\n      <td>9.220539</td>\n      <td>2.972819</td>\n      <td>-12.648766</td>\n      <td>17.011378</td>\n      <td>36.820266</td>\n      <td>-8.004480</td>\n      <td>6.164712</td>\n      <td>-0.451486</td>\n      <td>26.765915</td>\n      <td>6.207469</td>\n      <td>42.499784</td>\n      <td>97.447474</td>\n      <td>-7.628221</td>\n      <td>-71.283406</td>\n      <td>-35.130071</td>\n      <td>19088.0</td>\n      <td>1618.0</td>\n    </tr>\n    <tr>\n      <th>seg_00184e</th>\n      <td>4.610260</td>\n      <td>6.946967</td>\n      <td>210.0</td>\n      <td>24.989931</td>\n      <td>-3.460677</td>\n      <td>11.118656</td>\n      <td>-21.256362</td>\n      <td>-12.961493</td>\n      <td>23.516217</td>\n      <td>-29.427422</td>\n      <td>5.864547</td>\n      <td>-8.244729</td>\n      <td>14.572949</td>\n      <td>39.014307</td>\n      <td>-11.585978</td>\n      <td>-12.169548</td>\n      <td>2.735900</td>\n      <td>19.461493</td>\n      <td>23.506676</td>\n      <td>-0.392655</td>\n      <td>-3.646240</td>\n      <td>2.403952</td>\n      <td>5.597193</td>\n      <td>6.089045</td>\n      <td>162.112840</td>\n      <td>0.428684</td>\n      <td>4.467300</td>\n      <td>10.495224</td>\n      <td>6.089045</td>\n      <td>4004.0</td>\n      <td>280.0</td>\n      <td>6.876175</td>\n      <td>4.754700</td>\n      <td>7.426129</td>\n      <td>5.497168</td>\n      <td>3757.0</td>\n      <td>275.0</td>\n      <td>6.876175</td>\n      <td>4.729300</td>\n      <td>5.181521</td>\n      <td>...</td>\n      <td>19.853751</td>\n      <td>-14.530368</td>\n      <td>-5.912408</td>\n      <td>18.604858</td>\n      <td>7.423380</td>\n      <td>-0.273084</td>\n      <td>-4.676648</td>\n      <td>4.427817</td>\n      <td>-6.208368</td>\n      <td>-9.813725</td>\n      <td>-5.612174</td>\n      <td>1.413613</td>\n      <td>4.805265</td>\n      <td>0.000000e+00</td>\n      <td>-4.805265</td>\n      <td>-1.413613</td>\n      <td>5.612174</td>\n      <td>9.813725</td>\n      <td>6.208368</td>\n      <td>-4.427817</td>\n      <td>4.676648</td>\n      <td>0.273084</td>\n      <td>-7.423380</td>\n      <td>-18.604858</td>\n      <td>5.912408</td>\n      <td>14.530368</td>\n      <td>-19.853751</td>\n      <td>12.002158</td>\n      <td>-9.094293</td>\n      <td>-24.069578</td>\n      <td>3.775483</td>\n      <td>2.929676</td>\n      <td>-12.679662</td>\n      <td>0.330515</td>\n      <td>6.198940</td>\n      <td>8.943355</td>\n      <td>-7.389341</td>\n      <td>46.772511</td>\n      <td>19697.0</td>\n      <td>1199.0</td>\n    </tr>\n    <tr>\n      <th>seg_003339</th>\n      <td>4.531473</td>\n      <td>4.114133</td>\n      <td>227.0</td>\n      <td>9.775411</td>\n      <td>-18.246006</td>\n      <td>-5.980749</td>\n      <td>-10.538334</td>\n      <td>-24.916408</td>\n      <td>-0.130429</td>\n      <td>-4.160394</td>\n      <td>-20.989737</td>\n      <td>-2.593643</td>\n      <td>26.534442</td>\n      <td>6.498703</td>\n      <td>-0.454874</td>\n      <td>10.705448</td>\n      <td>-6.008928</td>\n      <td>1.916408</td>\n      <td>-3.174933</td>\n      <td>1.122593</td>\n      <td>10.986377</td>\n      <td>-9.389905</td>\n      <td>4.961487</td>\n      <td>5.181784</td>\n      <td>41.240413</td>\n      <td>0.061889</td>\n      <td>4.392533</td>\n      <td>3.704752</td>\n      <td>4.043051</td>\n      <td>4365.0</td>\n      <td>159.0</td>\n      <td>6.876175</td>\n      <td>4.680733</td>\n      <td>4.393253</td>\n      <td>4.762174</td>\n      <td>4358.0</td>\n      <td>142.0</td>\n      <td>6.876175</td>\n      <td>4.608967</td>\n      <td>5.214383</td>\n      <td>...</td>\n      <td>-21.248799</td>\n      <td>1.357387</td>\n      <td>13.859773</td>\n      <td>-6.069610</td>\n      <td>-11.432023</td>\n      <td>-0.908033</td>\n      <td>-11.512775</td>\n      <td>-13.444697</td>\n      <td>2.991927</td>\n      <td>15.229352</td>\n      <td>-2.952309</td>\n      <td>0.365636</td>\n      <td>-9.898795</td>\n      <td>8.881784e-16</td>\n      <td>9.898795</td>\n      <td>-0.365636</td>\n      <td>2.952309</td>\n      <td>-15.229352</td>\n      <td>-2.991927</td>\n      <td>13.444697</td>\n      <td>11.512775</td>\n      <td>0.908033</td>\n      <td>11.432023</td>\n      <td>6.069610</td>\n      <td>-13.859773</td>\n      <td>-1.357387</td>\n      <td>21.248799</td>\n      <td>-16.423924</td>\n      <td>5.792096</td>\n      <td>26.677619</td>\n      <td>2.022437</td>\n      <td>3.977798</td>\n      <td>-10.068076</td>\n      <td>5.065553</td>\n      <td>6.447494</td>\n      <td>31.671617</td>\n      <td>1.783595</td>\n      <td>-11.309352</td>\n      <td>22166.0</td>\n      <td>610.0</td>\n    </tr>\n    <tr>\n      <th>seg_0042cc</th>\n      <td>4.128340</td>\n      <td>5.797144</td>\n      <td>218.0</td>\n      <td>4.483136</td>\n      <td>10.655952</td>\n      <td>-13.043784</td>\n      <td>10.865419</td>\n      <td>5.163119</td>\n      <td>-17.927681</td>\n      <td>5.910628</td>\n      <td>23.922705</td>\n      <td>7.689221</td>\n      <td>3.427051</td>\n      <td>-0.368616</td>\n      <td>2.107469</td>\n      <td>11.180088</td>\n      <td>-2.205700</td>\n      <td>-2.663119</td>\n      <td>1.095267</td>\n      <td>1.575792</td>\n      <td>-3.869057</td>\n      <td>-11.578407</td>\n      <td>5.070900</td>\n      <td>5.780744</td>\n      <td>79.537016</td>\n      <td>0.073898</td>\n      <td>4.247367</td>\n      <td>4.384409</td>\n      <td>4.454347</td>\n      <td>3930.0</td>\n      <td>261.0</td>\n      <td>6.876175</td>\n      <td>4.248633</td>\n      <td>6.075060</td>\n      <td>5.214936</td>\n      <td>3783.0</td>\n      <td>329.0</td>\n      <td>6.876175</td>\n      <td>4.037833</td>\n      <td>3.827550</td>\n      <td>...</td>\n      <td>17.201207</td>\n      <td>-7.847091</td>\n      <td>7.338505</td>\n      <td>7.298181</td>\n      <td>12.695830</td>\n      <td>-5.549206</td>\n      <td>3.787048</td>\n      <td>1.879079</td>\n      <td>-5.865341</td>\n      <td>-12.029504</td>\n      <td>11.144645</td>\n      <td>6.243127</td>\n      <td>1.091920</td>\n      <td>0.000000e+00</td>\n      <td>-1.091920</td>\n      <td>-6.243127</td>\n      <td>-11.144645</td>\n      <td>12.029504</td>\n      <td>5.865341</td>\n      <td>-1.879079</td>\n      <td>-3.787048</td>\n      <td>5.549206</td>\n      <td>-12.695830</td>\n      <td>-7.298181</td>\n      <td>-7.338505</td>\n      <td>7.847091</td>\n      <td>-17.201207</td>\n      <td>10.031292</td>\n      <td>-35.168847</td>\n      <td>0.240658</td>\n      <td>-17.854208</td>\n      <td>1.982685</td>\n      <td>-23.680886</td>\n      <td>-13.710819</td>\n      <td>15.280036</td>\n      <td>-16.460912</td>\n      <td>12.847451</td>\n      <td>1.893552</td>\n      <td>19649.0</td>\n      <td>1512.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"X_test_scaled = scaler.transform(X_test)\nprint(X_test_scaled.size)\n# print(X_test_scaled[:10])\n# print(model.predict(X_test_scaled))\nsubmission['time_to_failure'] = svm.predict(X_test_scaled)\nsubmission.to_csv('submission.csv')","execution_count":33,"outputs":[{"output_type":"stream","text":"383104\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"sub = pd.read_csv('submission.csv')\nsub[:100]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}