term_pj_ys.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import shap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.gaussian_process import GaussianProcessRegressor\n",
    "from sklearn.gaussian_process.kernels import DotProduct, WhiteKernel\n",
    "from sklearn.gaussian_process.kernels import RBF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVR\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import linear_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>F1_CC</th>\n",
       "      <th>F2_CV</th>\n",
       "      <th>F3_CC_slope</th>\n",
       "      <th>F4_CC_kurt</th>\n",
       "      <th>SOH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.878529</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.256147</td>\n",
       "      <td>0.483536</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.984806</td>\n",
       "      <td>0.606921</td>\n",
       "      <td>0.397590</td>\n",
       "      <td>0.580847</td>\n",
       "      <td>1.001942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.994428</td>\n",
       "      <td>0.550300</td>\n",
       "      <td>0.386424</td>\n",
       "      <td>0.585378</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>0.943717</td>\n",
       "      <td>0.377366</td>\n",
       "      <td>0.042422</td>\n",
       "      <td>0.657359</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>0.944729</td>\n",
       "      <td>0.361224</td>\n",
       "      <td>0.042337</td>\n",
       "      <td>0.619481</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4524</th>\n",
       "      <td>4537</td>\n",
       "      <td>0.634733</td>\n",
       "      <td>0.031338</td>\n",
       "      <td>0.085357</td>\n",
       "      <td>0.962193</td>\n",
       "      <td>0.917476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4525</th>\n",
       "      <td>4538</td>\n",
       "      <td>0.634469</td>\n",
       "      <td>0.031865</td>\n",
       "      <td>0.086304</td>\n",
       "      <td>0.698442</td>\n",
       "      <td>0.917476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4526</th>\n",
       "      <td>4539</td>\n",
       "      <td>0.710758</td>\n",
       "      <td>0.033976</td>\n",
       "      <td>0.958762</td>\n",
       "      <td>0.714654</td>\n",
       "      <td>0.919417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4527</th>\n",
       "      <td>4540</td>\n",
       "      <td>0.711042</td>\n",
       "      <td>0.109779</td>\n",
       "      <td>0.477329</td>\n",
       "      <td>0.701941</td>\n",
       "      <td>0.919417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4528</th>\n",
       "      <td>4541</td>\n",
       "      <td>0.713112</td>\n",
       "      <td>0.112442</td>\n",
       "      <td>0.484668</td>\n",
       "      <td>0.733076</td>\n",
       "      <td>0.919417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4529 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      cycle     F1_CC     F2_CV  F3_CC_slope  F4_CC_kurt       SOH\n",
       "0         1  0.878529  1.000000     0.256147    0.483536  1.000000\n",
       "1         2  0.984806  0.606921     0.397590    0.580847  1.001942\n",
       "2         3  0.994428  0.550300     0.386424    0.585378  1.002913\n",
       "3         5  0.943717  0.377366     0.042422    0.657359  1.002913\n",
       "4         6  0.944729  0.361224     0.042337    0.619481  1.002913\n",
       "...     ...       ...       ...          ...         ...       ...\n",
       "4524   4537  0.634733  0.031338     0.085357    0.962193  0.917476\n",
       "4525   4538  0.634469  0.031865     0.086304    0.698442  0.917476\n",
       "4526   4539  0.710758  0.033976     0.958762    0.714654  0.919417\n",
       "4527   4540  0.711042  0.109779     0.477329    0.701941  0.919417\n",
       "4528   4541  0.713112  0.112442     0.484668    0.733076  0.919417\n",
       "\n",
       "[4529 rows x 6 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_F = pd.read_csv('features_for_project.csv')\n",
    "data_F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "F_X = data_F[['F1_CC', 'F2_CV', 'F3_CC_slope', 'F4_CC_kurt']]\n",
    "F_y = data_F['SOH']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "F_X_train, F_X_test, F_y_train, F_y_test = train_test_split(F_X, F_y, test_size=0.2, shuffle=True, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycles</th>\n",
       "      <th>v_start</th>\n",
       "      <th>v_end</th>\n",
       "      <th>v_nplat_area</th>\n",
       "      <th>v_nplat_slope</th>\n",
       "      <th>curr_area</th>\n",
       "      <th>curr_nplat_slope</th>\n",
       "      <th>Qc_end</th>\n",
       "      <th>Qc_area</th>\n",
       "      <th>Qc_slope</th>\n",
       "      <th>...</th>\n",
       "      <th>v_slope_dis</th>\n",
       "      <th>curr_end_dis</th>\n",
       "      <th>curr_area_dis</th>\n",
       "      <th>curr_slope_dis</th>\n",
       "      <th>Qd_end_dis</th>\n",
       "      <th>Qd_area_dis</th>\n",
       "      <th>Qd_slope_dis</th>\n",
       "      <th>Qd_skew_dis</th>\n",
       "      <th>Qd_kurt_dis</th>\n",
       "      <th>SOH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2.940</td>\n",
       "      <td>3.435</td>\n",
       "      <td>2179.099</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>351.549</td>\n",
       "      <td>-0.000066</td>\n",
       "      <td>1.019</td>\n",
       "      <td>342.890</td>\n",
       "      <td>0.000123</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000104</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-403.398</td>\n",
       "      <td>0.000075</td>\n",
       "      <td>1.030</td>\n",
       "      <td>416.239</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>-0.546358</td>\n",
       "      <td>-0.626673</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2.725</td>\n",
       "      <td>3.438</td>\n",
       "      <td>2264.986</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>370.408</td>\n",
       "      <td>-0.000136</td>\n",
       "      <td>1.037</td>\n",
       "      <td>358.829</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000103</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-403.922</td>\n",
       "      <td>0.000075</td>\n",
       "      <td>1.032</td>\n",
       "      <td>417.209</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>-0.547812</td>\n",
       "      <td>-0.619922</td>\n",
       "      <td>1.001942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2.737</td>\n",
       "      <td>3.442</td>\n",
       "      <td>2265.727</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>370.294</td>\n",
       "      <td>-0.000136</td>\n",
       "      <td>1.037</td>\n",
       "      <td>358.950</td>\n",
       "      <td>0.000129</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000104</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-403.918</td>\n",
       "      <td>0.000075</td>\n",
       "      <td>1.033</td>\n",
       "      <td>417.017</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>-0.546900</td>\n",
       "      <td>-0.629195</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>2.986</td>\n",
       "      <td>3.511</td>\n",
       "      <td>189.347</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>31.397</td>\n",
       "      <td>-0.000070</td>\n",
       "      <td>1.037</td>\n",
       "      <td>36.424</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000449</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>-31.898</td>\n",
       "      <td>-0.000325</td>\n",
       "      <td>1.033</td>\n",
       "      <td>15.913</td>\n",
       "      <td>0.000306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>2.986</td>\n",
       "      <td>3.512</td>\n",
       "      <td>189.338</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>31.385</td>\n",
       "      <td>-0.000070</td>\n",
       "      <td>1.037</td>\n",
       "      <td>36.425</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000449</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>-31.897</td>\n",
       "      <td>-0.000325</td>\n",
       "      <td>1.033</td>\n",
       "      <td>15.913</td>\n",
       "      <td>0.000306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4524</th>\n",
       "      <td>4537</td>\n",
       "      <td>2.967</td>\n",
       "      <td>3.525</td>\n",
       "      <td>174.913</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>28.886</td>\n",
       "      <td>-0.000078</td>\n",
       "      <td>0.950</td>\n",
       "      <td>29.941</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000494</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>-28.600</td>\n",
       "      <td>-0.000356</td>\n",
       "      <td>0.945</td>\n",
       "      <td>12.855</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.917476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4525</th>\n",
       "      <td>4538</td>\n",
       "      <td>2.967</td>\n",
       "      <td>3.525</td>\n",
       "      <td>174.911</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>28.885</td>\n",
       "      <td>-0.000078</td>\n",
       "      <td>0.950</td>\n",
       "      <td>29.940</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000494</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>-28.600</td>\n",
       "      <td>-0.000356</td>\n",
       "      <td>0.945</td>\n",
       "      <td>12.855</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.917476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4526</th>\n",
       "      <td>4539</td>\n",
       "      <td>1.996</td>\n",
       "      <td>3.468</td>\n",
       "      <td>2205.342</td>\n",
       "      <td>0.000262</td>\n",
       "      <td>366.382</td>\n",
       "      <td>-0.000077</td>\n",
       "      <td>0.950</td>\n",
       "      <td>307.497</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-376.200</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.947</td>\n",
       "      <td>360.821</td>\n",
       "      <td>0.000139</td>\n",
       "      <td>-0.545592</td>\n",
       "      <td>-0.623715</td>\n",
       "      <td>0.919417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4527</th>\n",
       "      <td>4540</td>\n",
       "      <td>2.690</td>\n",
       "      <td>3.472</td>\n",
       "      <td>2109.691</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>346.197</td>\n",
       "      <td>-0.000153</td>\n",
       "      <td>0.952</td>\n",
       "      <td>307.015</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000122</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-376.750</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.947</td>\n",
       "      <td>361.237</td>\n",
       "      <td>0.000139</td>\n",
       "      <td>-0.546539</td>\n",
       "      <td>-0.623438</td>\n",
       "      <td>0.919417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4528</th>\n",
       "      <td>4541</td>\n",
       "      <td>2.680</td>\n",
       "      <td>3.471</td>\n",
       "      <td>2112.245</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>346.751</td>\n",
       "      <td>-0.000153</td>\n",
       "      <td>0.953</td>\n",
       "      <td>307.051</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000122</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-376.750</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.947</td>\n",
       "      <td>361.371</td>\n",
       "      <td>0.000139</td>\n",
       "      <td>-0.546558</td>\n",
       "      <td>-0.620925</td>\n",
       "      <td>0.919417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4529 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      cycles  v_start  v_end  v_nplat_area  v_nplat_slope  curr_area  \\\n",
       "0          1    2.940  3.435      2179.099       0.000103    351.549   \n",
       "1          2    2.725  3.438      2264.986       0.000133    370.408   \n",
       "2          3    2.737  3.442      2265.727       0.000131    370.294   \n",
       "3          5    2.986  3.511       189.347       0.000095     31.397   \n",
       "4          6    2.986  3.512       189.338       0.000095     31.385   \n",
       "...      ...      ...    ...           ...            ...        ...   \n",
       "4524    4537    2.967  3.525       174.913       0.000105     28.886   \n",
       "4525    4538    2.967  3.525       174.911       0.000105     28.885   \n",
       "4526    4539    1.996  3.468      2205.342       0.000262    366.382   \n",
       "4527    4540    2.690  3.472      2109.691       0.000149    346.197   \n",
       "4528    4541    2.680  3.471      2112.245       0.000150    346.751   \n",
       "\n",
       "      curr_nplat_slope  Qc_end  Qc_area  Qc_slope  ...  v_slope_dis  \\\n",
       "0            -0.000066   1.019  342.890  0.000123  ...    -0.000104   \n",
       "1            -0.000136   1.037  358.829  0.000128  ...    -0.000103   \n",
       "2            -0.000136   1.037  358.950  0.000129  ...    -0.000104   \n",
       "3            -0.000070   1.037   36.424  0.000131  ...    -0.000449   \n",
       "4            -0.000070   1.037   36.425  0.000131  ...    -0.000449   \n",
       "...                ...     ...      ...       ...  ...          ...   \n",
       "4524         -0.000078   0.950   29.941  0.000133  ...    -0.000494   \n",
       "4525         -0.000078   0.950   29.940  0.000133  ...    -0.000494   \n",
       "4526         -0.000077   0.950  307.497  0.000133  ...    -0.000120   \n",
       "4527         -0.000153   0.952  307.015  0.000132  ...    -0.000122   \n",
       "4528         -0.000153   0.953  307.051  0.000132  ...    -0.000122   \n",
       "\n",
       "      curr_end_dis  curr_area_dis  curr_slope_dis  Qd_end_dis  Qd_area_dis  \\\n",
       "0              0.0       -403.398        0.000075       1.030      416.239   \n",
       "1              0.0       -403.922        0.000075       1.032      417.209   \n",
       "2              0.0       -403.918        0.000075       1.033      417.017   \n",
       "3             -1.1        -31.898       -0.000325       1.033       15.913   \n",
       "4             -1.1        -31.897       -0.000325       1.033       15.913   \n",
       "...            ...            ...             ...         ...          ...   \n",
       "4524          -1.1        -28.600       -0.000356       0.945       12.855   \n",
       "4525          -1.1        -28.600       -0.000356       0.945       12.855   \n",
       "4526           0.0       -376.200        0.000081       0.947      360.821   \n",
       "4527           0.0       -376.750        0.000081       0.947      361.237   \n",
       "4528           0.0       -376.750        0.000081       0.947      361.371   \n",
       "\n",
       "      Qd_slope_dis  Qd_skew_dis  Qd_kurt_dis       SOH  \n",
       "0         0.000140    -0.546358    -0.626673  1.000000  \n",
       "1         0.000140    -0.547812    -0.619922  1.001942  \n",
       "2         0.000140    -0.546900    -0.629195  1.002913  \n",
       "3         0.000306          NaN          NaN  1.002913  \n",
       "4         0.000306          NaN          NaN  1.002913  \n",
       "...            ...          ...          ...       ...  \n",
       "4524      0.000305          NaN          NaN  0.917476  \n",
       "4525      0.000305          NaN          NaN  0.917476  \n",
       "4526      0.000139    -0.545592    -0.623715  0.919417  \n",
       "4527      0.000139    -0.546539    -0.623438  0.919417  \n",
       "4528      0.000139    -0.546558    -0.620925  0.919417  \n",
       "\n",
       "[4529 rows x 25 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_PM = pd.read_csv('231130_several_processmap.csv')\n",
    "data_PM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "PM_X = data_PM.drop(['SOH', 'cycles', 'Qd_skew_dis', 'Qd_kurt_dis'], axis=1)\n",
    "PM_y = data_PM['SOH']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(PM_X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(PM_X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in data_PM.columns:\n",
    "    if i not in data_PM.columns:\n",
    "        print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "PM_X_train, PM_X_test, PM_y_train, PM_y_test = train_test_split(PM_X, PM_y, test_size=0.2, shuffle = True, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "ch = pd.read_csv('ch_features_ys.csv')\n",
    "dis = pd.read_csv('dis_features_cncnf_ys.csv').drop(['cycles'], axis=1)\n",
    "data = pd.concat([ch, dis], axis=1)\n",
    "soh = pd.read_csv('soh_ys.csv')\n",
    "data = pd.concat([data, soh], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = []\n",
    "for i in range(len(data)):\n",
    "    soh = data['SOH'].tolist()[i]\n",
    "    if soh > 1.1 or soh < 0.9:\n",
    "        l.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop(l, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4529"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.drop(['SOH', 'cycles', 'Qd_skew_dis', 'Qd_kurt_dis'], axis=1)\n",
    "y = data['SOH']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Linear regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 512,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-54 {color: black;}#sk-container-id-54 pre{padding: 0;}#sk-container-id-54 div.sk-toggleable {background-color: white;}#sk-container-id-54 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-54 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-54 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-54 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-54 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-54 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-54 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-54 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-54 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-54 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-54 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-54 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-54 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-54 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-54 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-54 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-54 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-54 div.sk-item {position: relative;z-index: 1;}#sk-container-id-54 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-54 div.sk-item::before, #sk-container-id-54 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-54 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-54 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-54 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-54 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-54 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-54 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-54 div.sk-label-container {text-align: center;}#sk-container-id-54 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-54 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-54\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-88\" type=\"checkbox\" checked><label for=\"sk-estimator-id-88\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 512,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = linear_model.LinearRegression()\n",
    "lr_F = linear_model.LinearRegression()\n",
    "lr_PM = linear_model.LinearRegression()\n",
    "\n",
    "# train\n",
    "lr.fit(X_train, y_train)\n",
    "lr_F.fit(F_X_train, F_y_train)\n",
    "lr_PM.fit(PM_X_train, PM_y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 513,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = lr.predict(X_test)\n",
    "F_y_pred = lr_F.predict(F_X_test)\n",
    "PM_y_pred = lr_PM.predict(PM_X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 514,
   "metadata": {},
   "outputs": [],
   "source": [
    "e = y_test.tolist()\n",
    "e.sort()\n",
    "f = y_pred.tolist()\n",
    "f.sort()\n",
    "\n",
    "a = F_y_test.tolist()\n",
    "a.sort()\n",
    "b = F_y_pred.tolist()\n",
    "b.sort()\n",
    "\n",
    "c = PM_y_test.tolist()\n",
    "c.sort()\n",
    "d  = PM_y_pred.tolist()\n",
    "d.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 515,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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fe+89UlJSeOSRR/7z54qIiBSazWb2tjk5tIGCW4nXt29f4uPjeeSRR9iyZQuHDh3i+++/53//+x8OhwN/f38CAwOZOXMmBw4c4KeffmLgwIGF+ozt27fTqVMnFi9ezO7duzlw4ACzZ89mzpw5dOrUCYBKlSoxbtw4Jk+ezGuvvcaePXs4ePAgb731FoMHD+all17SilIRESnxNFRawpUrV47169fzyiuv0KFDB9LT06lcuTJ33XUXLi4uWCwWFi5cyIsvvki9evWoVasWb7/9Nm3atCnwZ1SoUIEqVaowcuTI3M1zc54PGDAg97wBAwZQvXp1JkyYwJQpU3A4HNStW5fp06fTu3fvIrh7ERGR4sViGE7ekOQalJiYiK+vLwkJCZQuXTrPa2lpaRw+fJiqVavi4eHhpBZKSaA/ayIiJcflssdfaahUREREpJhQcBMREREpJhTcRERERIoJBTcRERGRYkLBTURERKSYUHATERERKSYU3ERERESKCQU3ERERkWJCwU1ERETkcux2SEoyH51MJa/kP+nVqxfnzp3jiy++cHZTCqw4tllERJwkNhZ27YKUFPDygrp1ISjIac1Rj5sUSE6N0e3bt+c5PmXKFD744IMi//xevXrRuXPnIv+cHDNmzKBBgwZ4eXnh5+fHTTfdxJtvvpnnnPj4ePr370+VKlWw2WyEhobSu3dvoqKiCtT21atXY7FYOHfuXBHeiYiI/Gt2uxna4uPBzc183LXLqT1v6nGT/8TX19fZTbjiZs+ezcCBA3n77bdp3bo16enp7Nixg927d+eeEx8fT7NmzbDZbEybNo169epx5MgRhg0bxs0338zGjRupVq2aE+9CRET+s/R0iI6GPXvg1CkICYHatc3jNptTmqQetxLEMAzGjRtHtWrV8PT0pEGDBixevDj39bNnz/LYY49RpkwZPD09ueGGG5g7dy4AVatWBeCmm27CYrHQpk0bIH9vUps2bXjhhRfo378//v7+hISEMHPmTFJSUujduzc+Pj5Ur16db7/9Nvcah8PBk08+SdWqVfH09KRWrVpMmTIl9/URI0Ywb948vvzySywWCxaLhdWrVwNw4sQJunXrhr+/P4GBgXTq1IkjR47kee+BAwfi5+dHYGAggwcPxjCMy/4+ffXVV3Tt2pUnn3ySGjVqULduXR555BFGjRqVe85rr73GyZMn+eGHH7jnnnuoVKkSt912G9999x1ubm707du3UN+NiIhcgywWWLoU3n0XPvnEfFy61DzuJApuznYVJzwOGzaMuXPnMn36dHbt2sWAAQN4/PHHWbNmDQDh4eHs3r2bb7/9lj///JPp06cTlD2Ov2XLFgB++OEHoqOjWbJkySU/Z968eQQFBbFlyxZeeOEFnn32WR5++GFatGjBr7/+SocOHejRowepqakAZGVlUaFCBT799FN2795NREQEr776Kp9++ikAgwYNomvXrtx1111ER0cTHR1NixYtSE1NpW3btnh7e/Pzzz+zbt06vL29ueuuu7Bn/35OnDiROXPmMHv2bNatW0d8fDxLly697O9T2bJl2bRpE0ePHr3o61lZWSxcuJDHHnuMsmXL5nnN09OT5557ju+++474+Ph/+kpERORa89e/lw8cgDVrICHB7GVLSDCfHzjgvPYZkk9CQoIBGAkJCfleO3/+vLF7927j/Pnz//2DzpwxjNWrDeObb8zHM2f++3teQnJysuHh4WFs2LAhz/Enn3zSeOSRRwzDMIyOHTsavXv3vuj1hw8fNgDjt99+y3O8Z8+eRqdOnXKft27d2rj11ltzn2dmZhpeXl5Gjx49co9FR0cbgLFx48ZLtve5554zHnrooUt+jmEYxuzZs41atWoZWVlZucfS09MNT09P47vvvjMMwzBCQ0ONN954I/f1jIwMo0KFCvne669OnjxpNGvWzACMmjVrGj179jQWLVpkOBwOwzAMIyYmxgCMSZMmXfT6JUuWGICxefPm3LZbrVbDy8srz4+Hh4cBGGfPnr3o+1zRP2siIvLPzpwxjCVLDGPKFPPxvfcMw2Yzzrm4GF+7uRmG1WoYNpthfPLJFf/oy2WPv9IcN2fJmfCYlAQBARcmPDZvXiTj5rt37yYtLY0777zzb82wc9NNNwHw7LPP8tBDD/Hrr7/Svn17OnfuTIsWLQr9WfXr18/9tdVqJTAwkBtvvDH3WEhICACnT5/OPfbee+/x/vvvc/ToUc6fP4/dbqdhw4aX/Zxt27Zx4MABfHx88hxPS0vj4MGDJCQkEB0dTfPmzXNfc3V1pUmTJpcdLg0NDWXjxo3s3LmTNWvWsGHDBnr27Mn777/PihUr/vH+c97b8peu9LZt2zJ9+vQ8523evJnHH3/8H99PRESuArsd5s6Fzz6D5GTw9ia5WjXecTgYn5VFclYW+y0WKlutUKqU05qp4OYs6enm0uKAAHB3Nx/PnSuyCY9ZWVkAfPPNN5QvXz7Pa+7u7gDcfffdHD16lG+++YYffviBO+64g759+zJhwoRCfZabm1ue5xaLJc+xnECT06ZPP/2UAQMGMHHiRJo3b46Pjw/jx49n8+bN/3hPjRs35uOPP873WpkyZQrV5oupV68e9erVo2/fvqxbt45WrVqxZs0aWrdujZ+fX57FCn+1Z88eLBYL1atXzz3m5eVFjRo18px3/Pjx/9xGERG5QqKiYP58OHmSVIuF6UeO8Oa2bZzJ/ruqtsXCKauVymXLwl/+/361Kbg5i7u7uR9MfPyFHjcfH/N4EahTpw7u7u5ERUXRunXrS55XpkwZevXqRa9evWjVqhUvv/wyEyZMwJYdJh0OxxVv29q1a2nRogXPPfdc7rGDBw/mOcdms+X77EaNGrFo0SKCg4MpXbr0Rd87NDSUTZs2cdtttwGQmZnJtm3baNSoUaHaWKdOHQBSUlJwcXGha9eufPzxx0RGRuaZ53b+/HmmTZtGhw4dCAgIKNRniIiIEx06RFpUFLPOn2dMZiYx2aMnNby8GO7ryyOenlhtNmjfHqpUcVozFdycxWYzN/HbtcvsafPxMZ8X0fJiHx8fBg0axIABA8jKyuLWW28lMTGRDRs24O3tTc+ePYmIiKBx48bUrVuX9PR0vv76a8LCwgAIDg7G09OTFStWUKFCBTw8PK7YViA1atRg/vz5fPfdd1StWpUPP/yQX375JXclK0CVKlX47rvv2Lt3L4GBgfj6+vLYY48xfvx4OnXqRGRkJBUqVCAqKoolS5bw8ssvU6FCBfr168cbb7zBDTfcQFhYGG+99dY/7pv27LPPUq5cOW6//XYqVKhAdHQ0r7/+OmXKlMkddh09ejQ//vgjd955J+PGjaNevXocPnyYYcOGkZGRwdSpU6/I742IiBSR5GRITITSpbHbbMz95hteT0rieHZgqwxE2Gw8MWkSrqdPQ0wMlC0LXbqAt7fTmq3g5kxBQeactvR0s6etiPeEGTVqFMHBwYwdO5ZDhw7h5+dHo0aNePXVVwGzV2vo0KEcOXIET09PWrVqxcKFCwFzbtjbb79NZGQkERERtGrVKndLjv/qmWeeYfv27XTr1g2LxcIjjzzCc889l2fLkKeeeorVq1fTpEkTkpOTWbVqFW3atOHnn3/mlVde4cEHHyQpKYny5ctzxx135PbAvfTSS0RHR9OrVy9cXFz43//+xwMPPEBCQsIl29OuXTvmzJnD9OnTiYuLIygoiObNm/Pjjz8SGBgIQFBQEJs2bSIyMpI+ffoQHR1NYGAgd911Fx999BGVKlW6Ir83IiJSBPbuhY8+IvPQIT5MTCTyt984cuIEAOWBYS4u/M8wsHl5QcOGEBaWG/KcGdoA564qXbNmjXHfffcZoaGhBmAsXbr0H69ZvXq10ahRI8Pd3d2oWrWqMX369HznLF682AgLCzNsNpsRFhZmLFmypFDtumqrSkUuQ3/WRESKQFKSkdmli/GRt7dxg4uLARiAERIQYEwJDjbO+/oaRkCAYfj5GUbt2obxxx9XpVkFXVXq1H3cUlJSaNCgAe+++26Bzj98+DD33HMPrVq14rfffuPVV1/lxRdf5PPPP889Z+PGjXTr1o0ePXrw+++/06NHD7p27fqPE91FRETkOhQTA7/+CjExZGVl8dmkSdy4ZAmPJyezPyuLIGC8pyeHpk/nxTZt8KhSxZzDVrky1K8P2SMt1wqLYfzDNvJXicViYenSpZetR/nKK6+wbNky/vzzz9xjzzzzDL///jsbN24EoFu3biQmJuYZZrvrrrvw9/dnwYIFBWpLYmIivr6+JCQk5Jv0npaWxuHDh6latSoeHh6FuEORwtGfNRGR/2jFCpg8GSMmhi8tFoYnJLDj8GEA/IFB7u68YBj4uLjAzJnmNT/9BGlp4OEBt98O3bpdlfJWl8sef1Ws5rht3LiR9u3b5znWoUMHZs+eTUZGBm5ubmzcuJEBAwbkO2fy5MmXfN/09HTS09NznycmJl7RdouIiMhVFhODER7Ot3/8QURGBtuyt/UoXaoUAzIyGJCVha+rqznP3M0NKlaEevXM+eexsebjzTc7rSbppRSr4BYTE5O7eWuOkJAQMjMziY2NJTQ09JLnxMTEXPJ9x44dy8iRI4ukzSIiInKVxMTAyZMYoaH8OGcOEdu2sTF7YNELeNFqZdCECQR88gls3w6GYfasNWwItWqZYe2OO67aosF/o1gFN8i7Gz1cfJf6i53z92N/NXToUAYOHJj7PDExkYoVK162HdfICLNcx/RnTETkEuz2/OEqe1j054MHCY+L4+ezZwHwAPoCrwBlcvYDffppWLbswkrR+++/MJfNZrsmA1uOYhXcypYtm6/n7PTp07i6uuZu03Cpc/7eC/dX7u7uudUD/klOBYDU1FQ8PT0L03yRQklNTQXyV6IQESnRYmNh61Y4cwbKlIEmTSAzk00DBxK+bx8/ZIczG9AHGAqEurhAVhZYLODra26ie40PiV5KsQpuzZs356uvvspz7Pvvv6dJkya5f7k1b96clStX5pnn9v333/+rmpsXY7Va8fPzy62zWapUqcv25okUlmEYpKamcvr0afz8/LBarc5ukojItcFuN3vWfvwxt8dt2y+/EPHllyzPXrjoCjzp6sprLi5U9PIyN7l3cTGHRUNDoUGDYjEkeilODW7JyckcOHAg9/nhw4fZvn07AQEBVKpUiaFDh3LixAnmz58PmCtI3333XQYOHMhTTz3Fxo0bmT17dp7Vov369eO2227jzTffpFOnTnz55Zf88MMPrFu37oq1O6fE0V+LpItcaX5+fnnKaYmIlHhxcfD117B3LzvOn2d4TAxfZG+obgV6urkRHhBAlfPnweGAdu3MuWxJSWaFokcegRtuMN/rGh8SvRSnbgeyevVq2rZtm+94z549+eCDD+jVqxdHjhzJs0P/mjVrGDBgALt27aJcuXK88sorPPPMM3muX7x4McOGDePQoUNUr16d0aNH8+CDDxa4XQVdkutwOMjIyCjw+4oUlJubm3raRETArOWdM6QZHc2f997LiBMn+DQzEwAL8NgddxBx9Cg3xMSAqytkZpr7sH30EezZYxaQr1TJDHJBQc69n0soaPa4ZvZxu5YU9DdPREREitCmTTBtGhw7xgFfX0bGxPDJ5s1kZb/c1WplhLc3YcuXw7FjMHGi2SsXGAgvvWTuwXaxhQzXoOtyHzcREREpIeLjYehQjmzezKj0dOZlZZG9JpTO7u6M9PWlvsViBrKsLDOkNW8OR4+avW05NaOL6ZDopSi4iYiIyDXn+IoVjF67ltkOBzmTku6xWIi84QYa5/Sgpaebc9Zq1DBPqFTpQmC7Tim4iYiIiPNlD2nGnD3L2IkTmTFtGunZW3u0AyKB5oZhlqE6ceLCdiDPPQclaCGXgpuIiIg4V2wsZ374gXHz5zP1p584n12G8jZgVPZjrvr1YfhwOHkSypUrUaENFNxERETEieJjYpjYpw9TvvmGlOwetmY1ajDqqae4Izwci91+4WR3dwgLM8NaCQtsOVyc3QAREREpeRISEhg5ciRVa9ZkzLJlpDgcNLZY+MbdnQ2BgbRr3x7LLbeYtUTd3c3Hm282a4qWYOpxExERkasmOTmZdyZPZvzEiZw9dw6AGy0WIg2DToaBJT0dfv/dHAp9+mmzZ+1iNUVLKAU3ERERKXKpqalMmzaNN994g9i4OADCypdnxG230WXBAnMI0GIxS1OlpZnbejz8cLGtKVpUFNxERESkaBw4QNqffzJzyxbGvv8+MTExANSw2Rju68sjpUtjTUm5+LXe3sW6pmhRUXATERGRK84+fTpzRo5k9JkzHM8yax1ULleOCOAJV1dcQ0MhJgb++AP8/Mxi8DkCA6FePfPX19kGuv+VFieIiIjIf2e3Q1ISmampzBk7llovvMCzp05xPCuL8sB0Pz/2jR7N/2w2XAMCzMUG/v5mMfiWLc1qB8HB5uNDD10oBi95qMdNRERE/pvYWBw//MCCL75g5Jo1HMgeEg0BXrXZeDozE4+UFDh71lxsEB1tXnf2rLkX20svwc8/X9ibrXt3c6hU8lFwExERkX8tKy2Nxc8+y4gvv+TPDLM4VZDNxpCMDJ61WCjl5mb2qmVlmUOg/fvDO++YtUgrVIAXXoC2bc2FBzmrRxXaLknBTURERArNMAy+/PJLhr/yCjv27QPAH3gZeMFmw7t0abNHLWcD3aAgaNwY6ta9eDF4b28FtgJQcBMREZECM/bv59uFC4n49FO27dwJQGlgINAf8AVITobbboN9+y70oj366IV5ayWgGHxRUXATERGRf2QYBj8OHEj4jBlsOn8eAC93d/rdcgsvrV1LwN8vqFcPevSAqCgzpLVrp9WhV4CCm4iIiFzWzz//TPigQfz8yy8AeFos9PXwYHCFCpR54AFYuzb/RQ0bwoMPag+2K0zBTURERC5q0zffED5qFD9s3gyADXjGy4shQUGEZmSYe68FBpr1Q/fuvXBhrVrmggPtwXbFKbiJiIhIHtu2bSPi2WdZnt3D5max8GTz5ry2bx8V7HazLFVyMnh6QlgYTJ4M48bBiRNQvjwMHmxu+yFXnIKbiIhISWe3Q3o6O/btY/jrr/PFF18AYAV6enkR7ulJFTC37Pj11wuhrUULqFbNPN6w4YV92BTaioyCm4iISEkWG8ufS5YwYvZsPt2yBQCLxcJj7u5ElCrFDaVLQ2oqHDwIzz8PdeqYQ6R+ftCqFfj4mO9TtqwC21Wg4CYiIlKSJCfnbtGx/+hRIvv04ZMNG8gyDAC6Nm3KiKeeImzIEHPjXBcXyMgAqxVuvBG8vC4Et4YNNYftKlNwExERKSn27oUVKzhy+DCRGzcyf9s2HA4HAJ1r1mRk7drUL1sW6teHqlXh0CFISjLDW9WqZlALDdVKUSdScBMRESkJkpM5tmABo7/8ktk7dpCZlQXAPeXKEdmiBY3DwiAuzhwW9fWFXr3giy8ubKDbubMZ2rRS1KkU3ERERK5z0dHRjB02jBkffIA9O7C1K1OGyBYtaF6rFsTEmOWpkpOhZk1zgUHXrmYt0ZgYc+5aixYKbNcABTcREZHrUVQUZ37/nTe/+oppH33E+exqB7d5eDAqNJTbLBazd61jR9i82extq1IF7rvvQt3Qu+7SsOg1RsFNRESkOMveyuOv4Sp+9mwmhIfzdkwMKdmLDpo1bMiozEzuyMjA4ukJaWlw/jyEhECfPheGRP9a6F3DotccBTcREZHiKjbWLDd17BhUrEhCgwZMeucdJr39NonZQ6KNLRZGlSvHXZMmYXnzTXOlqL+/OTRqtZqb6eb0sMk1T8FNRESkOLLbYe5c+OwzkpOSeDspiQnx8ZzNHhKtb7EQWbo096elYYmLM8PdTTfBtm3mEKnFYj4vV87JNyKFoeAmIiJSHEVFkfrRR0w7dIg3U1OJze5hCytblpFxcTxkteLi5mYGPMMwh1J79jRXjJ4+DcHB5kpR9bQVKwpuIiIixUVUFBw9SlpICDPfeYexf/xBTPYcthoWCyNKlaL7hAlYR42Co0fNOWyGAZUrQ7NmUKkS9O178flsUiwouImIiBQHixZhf+cd5hw+zOjYWI7b7QBUASLc3emRmYmrYZiLDUaOhPHjzZWigYHw8stmaAPNZyvmFNxERESucZmHDjE/PJxRR45wJCMDgAqurgxzd6e3YWBzcQFXV7NuqIcHdOsGzZubvW6VK18IbVLsKbiJiIhcoxwOBwsWLGDkkCEcOHECgLI2G69WqsRTFgsepUub89Xc3Mx6orVqQY0a5sWVKimwXYcU3ERERK4xWTt3sviDDxi+dCl7Dh0CIMhqZYibG8/6+FAqNtbcLPfFF2HxYjhzBsqUgeeeM6scyHVLwU1EROQaYRgGX/7vfwz/6CN2ZGYC4O/pycsvvcQLq1fj/fvv5oIDiwX8/MwqB+3bw8mT5rYeCm3XPQU3ERERZ0pOxkhI4NtNm4gYPpxtu3YBUBoYCPR3d8e3SRPYtMmsF2q1mpvoOhxmYKtXT4GtBFFwExERuRouUprK2LOHH0aNIuL779kUGwuAF9APeMlqJcDhgHPnzE1zPT0hJcUcEj15Ery8zMUIUqIouImIiBS12FjYuvXCXLQmTVizdSsRTzzBz2fOAOAJ9A0IYHB8PGX+fn1OwfcVK8zFCF5e5vPQ0Kt9J+JkCm4iIiJFyW43A9c330BCAhszMgiPjubH7CFRG/BM6dIMNQzKZmSYPXLp6eZQKECpUtC2LVStChUqQEyMOTTaooUKwJdACm4iIiJFKS4OPviAbdu2EZ6SwrfZ+7C5Wa08abXymq8vFfz9zWoG589DmzawefOFYdVHH4UGDcyQdtdd+YZbpWRRcBMREbnSYmJyV3ruWLmSiJ9/5svswGYFetpshE+YQJV33oFTpyApySz8HhICkZGwezccOGDuyXbffRdCms2mwFbCKbiJiIj8W8nJ+et+rlgB773H7mPHGBETw2cnTwLgAjzm4kKExUINqxUqVjRLUU2aZL5H+fIwYADccgs0bKieNbkoBTcREZF/Y+9eWLbM7DELCYH77wdfX/a/+SYjt2/nk3PnMLJP7Wa1MtwwCPPwMAOZiwv4+0Pnzub8tYMHoXr1C1UP1LMml6DgJiIiUljJyfDhh7BuHWRlgYsLh48eZdTBg8xfvZrsZQV0DgxkpI8P9a1WczWoxWLuw1a16oUVoTVqXAhsIv9AwU1ERKSwoqPNIdGjRzmWmcnotDRmr1lDZvbL9/r4MLJuXRqnpJhF3xs3hp07ITPTLAbfqpVZ6UCkkBTcRERECuvMGaL372dsUhIzDAN79uE7mzQh8pZbaPbbb5CWZs5769wZ7rnH3A7k9GkIDjaP5cyJEykEBTcREZGCiIqCo0c54+3NmxMmMDUxkbTsl1oDkTYbt40YAU2bwpo1cOKEueCgdWsICjKLwv99IYNIIRU4uC1btqxA591///2FasC0adMYP3480dHR1K1bl8mTJ9OqVatLnj916lTeffddjhw5QqVKlXjttdd44okn8pwzefJkpk+fTlRUFEFBQXTp0oWxY8fi4eFRqLaJiIgAsGgR8RMmMOHwYd4+e5aUrCwAmgOjXF25PTMTi4uLOYctKAg6dsy/KtTbW4FN/rMCB7fOnTvneW6xWDAMI98xR85OzwWwaNEi+vfvz7Rp02jZsiUzZszg7rvvZvfu3VSqVCnf+dOnT2fo0KHMmjWLm2++mS1btvDUU0/h7+9Px44dAfj4448ZMmQIc+bMoUWLFuzbt49evXoBMGnSpAK3TUREBCBh504mDRjAWzExJGX/vdfY3Z1RHh7clZaGxWo15635+5uhDbQqVIqMxfh7+iogHx8ffv/9d6pVq/avP7xp06Y0atSI6dOn5x4LCwujc+fOjB07Nt/5LVq0oGXLlowfPz73WP/+/dm6dSvr1q0D4Pnnn+fPP//kxx9/zD3npZdeYsuWLaxdu7ZA7UpMTMTX15eEhARKly79b29PRESKseTkZN5++20mjB3L2eRkAOoDkRYL93t4YLnpJnOTXcMwe9oaN4aZMyEgwLkNl2KpoNnD5Sq2KQ+73c62bdto3759nuPt27dnw4YNF70mPT0933Cnp6cnW7ZsISN7R+pbb72Vbdu2sWXLFgAOHTrE8uXLuffeey/ZlvT0dBITE/P8iIhIyZR6+jQTIiKoWqUKr732GmeTkwkDPgV+AzoZBpa0NHPBwR13QL165uOgQQptUuSctjghNjYWh8NBSEhInuMhISHExMRc9JoOHTrw/vvv07lzZxo1asS2bduYM2cOGRkZxMbGEhoaSvfu3Tlz5gy33norhmGQmZnJs88+y5AhQy7ZlrFjxzJy5Mgren8iIlK8pKWlMWPUKMZOmcKplBQAbqhcmeF33033997D+teTDQMqVYJnn4XYWHOIVKFNrgKn9bjlsFgseZ4bhpHvWI7w8HDuvvtumjVrhpubG506dcqdv2a1mv9JrV69mtGjRzNt2jR+/fVXlixZwtdff82oUaMu2YahQ4eSkJCQ+3Ps2LErc3MiInJts9uxx8Ux/Z13qFG9Ov3HjOFUSgpVXFyY4+fH7ttu47HbbsPq5maen/P3k5ubuTo0IABq1lRok6vmXwc3i8VyyYBVEEFBQVit1ny9a6dPn87XC5fD09OTOXPmkJqaypEjR4iKiqJKlSr4+PgQlD0hNDw8nB49evB///d/3HjjjTzwwAOMGTOGsWPHkpW9Cujv3N3dKV26dJ4fERG5vmVERzP71VepGRbGcy++yImTJ6ng4sJ77u7s9fend2Ymrj/8YJ4cGmqGtZyf0FCzRJXIVVbgoVJ/f/88QS05OZmbbroJF5e82S8+Pr5A72ez2WjcuDErV67kgQceyD2+cuVKOnXqdNlr3dzcqFChAgALFy7kvvvuy21HampqvjZZrVYMw8i3ClZEREoeh8PBJ/PnM/LVVzmY3XlQtlQpXm3Rgqc2bsTDajWrHWRkQFKSedEDD8D335vH3NygfXtzXzaRq6zAwW3y5MlX/MMHDhxIjx49aNKkCc2bN2fmzJlERUXxzDPPAOYQ5okTJ5g/fz4A+/btY8uWLTRt2pSzZ8/y1ltvsXPnTubNm5f7nh07duStt97ipptuomnTphw4cIDw8HDuv//+3OFUEREpYWJiyDp+nM+2bWPE5Mns2bMHgCCLhSFubjzr6kqplBTw8oLUVHMPtqws83n16tCoEZQpAzExULYsdOmiPdnEKQoc3Hr27HnFP7xbt27ExcURGRlJdHQ09erVY/ny5VSuXBmA6OhooqKics93OBxMnDiRvXv34ubmRtu2bdmwYQNV/vKvnmHDhmGxWBg2bBgnTpygTJkydOzYkdGjR1/x9ouIyLXP+PZbvoiIYPiuXfxx/jwA/j4+DE5P53mHA283NzOs7dhh1hDdscPsWStdGtq1gzp1zJDWr58qH4jTFXoft/Pnz7Ny5Ur27duHxWKhZs2atGvXDk9Pz6Jq41WnfdxERIqxmBg4eRIjNJTlP/5IxLPP8mv2PmylLRZeqlyZ/s8+S+mICHOxgYeHWVfUMCAy0hwePX4cKlSAxx+HWrWcfENSEhQ0exRqO5Bly5bxf//3f8TGxuY5HhQUxOzZs3OrF4iIiDjFihUYU6fyw/79hJ86xeZz5wDwBvqVKsVLrq74p6RcWGRgt5uBLSvLrHRwyy3QpIl61uSaVeBVpRs2bKBLly7cdtttrF+/nvj4eOLj41m3bh2tWrWiS5cubNy4sSjbKiIicmkxMawZOpTW331H+7172XzuHJ4WCy+7uXG4VCle9/XF3+Ew569Vq2ZumuvuDpmZ5uMdd5ihzdsbypVTaJNrUoGHSu+55x4qVqzIjBkzLvp6nz59OHbsGMuXL7+iDXQGDZWKiBQDycm5PWMb//iD8Oef58dffwXAHXjGamWIhwdlfX3Nc61WcDggOBiWLjV73ObMgSNHzBWi//ufhkXFaa74UOnGjRt58803L/l63759ad26deFaKSIi8m/s3QsLFrB12zYi9uzh2wMHAHAD/s9i4VWbjQqZmebctbZtzXDmcJjh7Y47zKDm7Q3h4RoWlWKlwMEtLS3tsgnQ19eX9PT0K9IoERGRS0pO5veXX2b4ypV8mZYGgNViodcddzBs/XqqZNeuxmIxh0A7dzYXLFxsKw9vbwU2KVYKHNxq1qzJTz/9RO/evS/6+o8//kiNGjWuWMNEREQAcwFBejq4u7P7wAFGvPgin/34I2BO1H7M1ZUIf39q9OkD0dEQFQWurubctUqV4LbbzEoH6lmT60CBg1uvXr0YNGgQISEh3HPPPXle++abbxg8eDCvvfbaFW+giIiUYLGx8NNP7N+6lZEbN/LJ+vW5VXC6WSyMcHWltmGYc9gMA554Aj79FHI20+3aFSpXNleMKrDJdaDAwa1fv35s2LCB++67j1q1ahEWFgbA7t272b9/P507d6Zfv35F1lAREbmO/KUXDZvtkuccHjWKUfPmMT8hAUf24QdatGDk1q3cmJlpzlnL2dLD39+cz1a9Opw4AeXLQ+vWl35/kWKo0BvwLlq0iAULFrBv3z7AHELt3r073bt3L5IGOoNWlYqIFKHYWNi160KvWN26EBSU55Rjx47x+ksvMeezz8jMPnavzUZkaCiNJkyAl1+G06cvXBAcDEuWwE03FSwUilxjimQDXjDLVHXr1u0/NU5EREoou90MbUlJEBAA8fHm8+bNwWYjOjqaMWPGMHPmTOx2OwB3engQWakSzdLTL9QQbdkStm27sMVH48bmkCiYYU2BTa5TBQ5uWVlZZGVl4ep64ZJTp07x3nvvkZKSQseOHWnVqlWRNFJERK4T6elmT1tAgNkjFhAA585x+vhx3pw6lWnTppGWvVK0dZMmjIqJoVXOKtG0NPD1NXvoKlWCuXPNXrfgYOjd23wvketcgYPbk08+iZubGzNnzgQgKSmJm2++mbS0NEJDQ5k0aRJffvllvoULIiIiudzdzeHR+HgICCD+6FHGf/0173z5JSkpKQA0b96cUaNGcfutt2IZMwY++wzOnzeD2cMPww03mD1qNWuaw65BQQptUmIUOLitX7+ed999N/f5/PnzyczMZP/+/fj6+vLKK68wfvx4BTcREbk0mw3q1uXcpk1MevddJn35JUmpqQA0adKEyMhI7rrrLiwWi3n+Cy9AWJi5xUelStCu3YVh0IAABTYpcQoc3E6cOMENN9yQ+/zHH3/koYcewtfXF4CePXsyd+7cK99CERG5biQlJfH2jBlMmDCBc9kF4OvXr09kZCT333//hcCWIygIHnxQiw1EshU4uHl4eHD+/Pnc55s2bWL8+PF5Xk9OTr6yrRMRketCamoqU6dOZdy4ccTGxgIQVq4ckf378+BLL+Hi4nLpi7XYQCTXZf5LyatBgwZ8+OGHAKxdu5ZTp05x++23575+8OBBypUrd+VbKCIixVZaWhpTpkyhWrVqDB48mNjYWG4IDORjb2/+iI+ny7hxuLz+urObKVJsFDi4hYeHM3nyZKpXr06HDh3o1asXoaGhua8vXbqUli1bFkkjRUSkeLHb7UyfPp0aNWrQv39/Tp06RdUqVZg7ciS709N5NDkZa1qaubhgwgTYvt3ZTRYpFgo8VNq2bVu2bdvGypUrKVu2LA8//HCe1xs2bMgtt9xyxRsoIiLFR0ZGBvPnz2fUqFEcPXoUgAq+voQ3akSv22/HlpRklqcCswi8YZh7uv30EzRs6LyGixQThdqAt06dOtSpU+eirz399NNXpEEiIlL8OBwOPvnkE0aOHMnBgwcBCC1bllfDwngqPh732FizsoGn54WL/lq4x+FARP5ZoSsniIiI5MjKyuKzzz5jxIgR7NmzB4AygYEMefVVnm3dGs8nnjA3yc3pXfP0BFdXyMy88CZubuptEykgBTcRESk0wzD44osvGD58OH/88QcAAW5uvBwUxPN16uBdp445BHrypLmVh812oYZo3bqwe7cZ5CwWs3xV48ZOviOR4kHBTURECswwDJYvX05ERAS//vorAKV9fHjJx4f+Z89SOiEBNm6EiAgYPDjnogs9blYrPP00rF8PJ05A+fLmJrvaSFekQBTcRETkHxmGwQ8//EB4eDibN28GwNvDg35PPMFLt9+Of69eZi3RnKLvf/wBZ85A2bLmUKnVCi4uZl3R226D7t1VrkrkX1BwExGRy1qzZg3h4eGsXbsWAE83N553d2ewiwtBy5ebAS27MDw5lQ/S0sx5bB06wKpVkJVlBre2baFKFfD2VmAT+RcKFNz8/f3zlyG5hPj4+P/UIBERuTZs2LCBiNde48fVqwFwd3fnmYcfZsjy5ZTNLldFcjKsWHGhpy1npairK4SEQPv2UKYMxMSYvW9dupihTUT+lQIFt8mTJ+f+Oi4ujtdff50OHTrQvHlzADZu3Mh3331HeHh4kTRSRESunq1btxIeHs6KFSsAcHNx4f+aNOHVceOosHcvfPyxGdBcXMyetPPnzSHQ+HgzwFksUL06NGtmFobv1w8SE6F0aYU2kf/IYhh/3Ujnnz300EO0bduW559/Ps/xd999lx9++IEvvvjiSrbPKRITE/H19SUhIYHSpUs7uzkiIlfF77//TkREBMuWLQPAarHQy9ubcG9vKpcqBe3aQY0a8PLL+S/u2RN27oS4OAgMNM/p1u0q34FI8VXQ7FHo4Obt7c327dupUaNGnuP79+/npptuui4KzSu4iUhJsnv3boYPH87ixYsBcHFx4bG77yZi2zZqnD17YRi0TBl45RUYOBAyMi68gZsbLF0KN94IR49C5cpmT5uIFFhBs0eBa5XmCAwMZOnSpfmOf/HFFwQGBhb27URExEn27dvHY489Rr169Vi8eDEWi4Vu1auz6/nnmX/PPWZos9vNkGa3m4sQvLygQQMzrLm7m48NGpj7sFWqBK1aKbSJFKFCryodOXIkTz75JKtXr86d47Zp0yZWrFjB+++/f8UbKCIiV9bhw4eJjIzkww8/xJFdauqBKlUYmZnJjXY7fPONOeyZmWnOV8v5ycw056iNGgWTJ19YcNC/v/koIkWu0MGtV69ehIWF8fbbb7NkyRIMw6BOnTqsX7+epk2bFkUbRUTkCjh27Bivv/46c+bMITO75NR9993HyEcfpdHgwWaPWs6w6NmzUKqUufDAxcX8KV0aypUzKx00bGhWRShXTqFN5Cr6V/u4NW3alI8//vhKt0VERIpAdHQ0Y8aMYebMmdjtdgDaly5NZP36NO3b1yxDdeaMORyaU0fU4TDDWVTUhT3YbrkFwsLMNy1bVoFNxAn+VXA7ePAgc+fO5dChQ0yePJng4GBWrFhBxYoVqVu37pVuo4iI/AunT5/mzTFjmDZjBmnZG+S29vVllNVKKw8POHAA3nwTHn00/7CoYUCnTnDwIERHQ2go9OmjTXNFnKzQixPWrFnDjTfeyObNm/n8889zV5Hu2LGD4cOHX/EGiohI4cTFxTF06FCqVa3KW1OmkJaWRouwMH4cOZJVbm60cjjMoHb+POzaZT76+l4YEnVxMZ+3bQsTJ8Lbb5uPzZo5+9ZESrxCB7chQ4bw+uuvs3LlSmw2W+7xtm3bsnHjxivaOBERKbhz584xfPhwqlatyhtvvEFKaipNfHz49oYbWFe2LLefOYPFbjdDm9VqPqanm/PUWrQwe9NySlG1aGEOiwYEQM2a6mkTuUYUeqj0jz/+4JNPPsl3vEyZMsTFxV2RRomISMElJSXx9ttvM2HCBM5ll6JqEBZGZHo6Hc+cwRITA6dOmUOeAQFmhYOcgvDBwVC7Nrz2GsyYoWFRkWtcoYObn58f0dHRVK1aNc/x3377jfLly1+xhomIyOWlpKQwbdo03nzzzdx/ONepXZuRo0bxoI8PLg8/bC44KFUKUlPh2DGzduj+/ebiA6sV7rjjQtH3mjUhNhaCghTaRK5RhQ5ujz76KK+88gqfffYZFouFrKws1q9fz6BBg3jiiSeKoo0iIvIXaWlpvPfee7zxxhucOnUKgBsCAxnRuDHdWrfGeuONsHu3uRrUajXnrFmt5sW3325ulnuxou8BAQpsIte4Qge30aNH06tXL8qXL5+7h5vD4eDRRx9l2LBhRdFGEREB7HY7s2fPZvTo0Zw4cQKAqlWqEFGzJo+fPo1rdDQsXmz2mj3yiFmi6swZM8BZLObztm3NklQq+i5SLBW6VmmOQ4cO8euvv5KVlcVNN93EDTfccKXb5jSqVSoi15KMjAzmzZvHqFGjiIqKAqBixYoMGzaM3rfcgttjj8Hp02b5qYwMc97axx+b9UMXLYKUFLNUVbdu5ly2vywsE5FrQ0GzR6F73CIjIxk0aBDVqlWjWrVqucfPnz/P+PHjiYiI+HctFhGRPBwOBx9//DGRkZEcPHgQgNDQUF599VWeeuop3N3dYfVqM7Q5HGYPWlqa+fzcOXjhBXNlaFSUWT+0XTuFNpFirtA9blarlejoaIKDg/Mcj4uLIzg4OLfuXXGmHjcRcaasrCw+/fRTRowYwd69ewFz5f6QIUN4tkcPPDMyLgxzbtkCXbuavWo2m7kYwcsLPv3UrHRgt5tbfri7K7SJXMOKrMfNMAwsFku+47///jsBmtQqImKKjy/0Ck3DMFi6dCnDhw9n586dAAQEBPDyyy/z/PPP433iBMyefaFG6AMPQI0aUL8+/PKLOZfN1dV8XqOG+aY2mwKbyHWkwMHN398fi8WCxWKhZs2aecKbw+EgOTmZZ555pkgaKSJSrGzaBB98YA5ZBgdDr16XrTpgGAbffPMNERER/PbbbwD4+voycOBA+vfvb/7rOznZ3Gdt7doLJalOn4Zhw+Cuu8yetaQk8PExn2vRgch1qcDBbfLkyRiGwf/+9z9GjhyJr69v7ms2m40qVarQvHnzImmkiEixER8PU6fC77+bvV8HDpjDmBepPmAYBitXriQiIoLNmzcD4O3tTb9+/XjppZfw9/e/cPLRo7BundmrVrasuZ3HunXm+1epAv36maWrPD3NUJeerp42ketQgYNbz549AahatSotWrTAzc2tyBolIlKs/HVY9OhRc9jy3Dlz7zSHw3x+9Gie4LZ69WrCw8NZt24dAJ6enrzwwgu8/PLLBAUF5f8Mu918L5vNfN+c+WxgzmlLSjIDXXy82evm7n4VblxErrZCz3Fr3bp17q/Pnz9PRkZGntc1mV9ESpS/D4s2agRxcWYdUD8/M8DFxZm9YcCGDRsIDw/np59+AsDd3Z1nn32WIUOGEBIScunPqVzZXCG6e7f5funpUKeOOZctK8ssFn/unBna6tZVb5vIdarQReZTU1N5/vnnCQ4OxtvbG39//zw/hTVt2jSqVq2Kh4cHjRs3Zu3atZc9f+rUqYSFheHp6UmtWrWYP39+vnPOnTtH3759CQ0NxcPDg7CwMJYvX17otomIXFbOsOiGDWY5qQ0b4IsvwNf3Qo+YzQYBAfxy6BB33303LVu25KeffsLNzY3nnnuOgwcPMmnSpMuHNjB7655/Hm6+2QyIN99sPg8IMHv6mjeHVq3Mx4v12InIdaHQPW4vv/wyq1atYtq0aTzxxBNMnTqVEydOMGPGDN54441CvdeiRYvo378/06ZNo2XLlsyYMYO7776b3bt3U6lSpXznT58+naFDhzJr1ixuvvlmtmzZwlNPPYW/vz8dO3YEzJ3F77zzToKDg1m8eDEVKlTg2LFj+Pj4FPZWRUQu7+hR+O03OHvWLCuVlWWGtZo1zb3TbDZ+T0wkIjWVZT16AOaWSr1792bYsGFUrly5cJ/XrNml64lq9ahIyWAUUsWKFY1Vq1YZhmEYPj4+xv79+w3DMIz58+cbd999d6He65ZbbjGeeeaZPMdq165tDBky5KLnN2/e3Bg0aFCeY/369TNatmyZ+3z69OlGtWrVDLvdXqi2/FVCQoIBGAkJCf/6PUTkOpSUZBgnTpiPhmEYW7YYRkCAYbi6XvgJCDCM2bONnV26GF3KlTMAAzBcXFyMJ554wjhw4IBz70FErkkFzR6FHiqNj4+natWqgDmfLT4+HoBbb72Vn3/+ucDvY7fb2bZtG+3bt89zvH379mzYsOGi16Snp+Ph4ZHnmKenJ1u2bMmda7ds2TKaN29O3759CQkJoV69eowZM+ayGwOnp6eTmJiY50dEJI+9e2HyZIiMNB/37oXUVLNSQWameU5mJvtSU3lswQJu/PxzFp88icVioXv37uzatYt58+ZRvXp1Z96FiBRzhQ5u1apV48iRIwDUqVOHTz/9FICvvvoKPz+/Ar9PbGwsDocj37yOkJAQYmJiLnpNhw4deP/999m2bRuGYbB161bmzJlDRkYGsbGxgFlDdfHixTgcDpYvX86wYcOYOHEio0ePvmRbxo4di6+vb+5PxYoVC3wfIlICJCfDpEkwbx58+635OGmSuSDBagUPDw55eNDbaiUsLY1PfvgBwzB48MEH2bFjBwsWLKB27drOvgsRuQ4UOrj17t2b33//HYChQ4cybdo03N3dGTBgAC+//HKhG/D3KgzGJSozAISHh3P33XfTrFkz3Nzc6NSpE7169QLMeSNglooJDg5m5syZNG7cmO7du/Paa68xffr0S7Zh6NChJCQk5P4cO3as0PchIteZmBj49Vfz8cABWLECTp0yQ9ypU+Zzi4Uof3+edjiolZzMBw4HWcB9rVvz66+/8vnnn1OvXj1n34mIXEcKvThhwIABub9u27Yte/bsYevWrVSvXp0GDRoU+H2CgoKwWq35etdOnz59ydVVnp6ezJkzhxkzZnDq1ClCQ0OZOXMmPj4+ufsehYaG4ubmlhvkAMLCwoiJicFut2O7yORdd3d3s1iziAiYoWzyZDOghYRA06bmFhwOB7i5QWYm0WfOMGbuXGaeOIE9eypGey8vIrt1o+n06VooICJFotDB7e8qVap00RWg/8Rms9G4cWNWrlzJAw88kHt85cqVdOrU6bLXurm5UaFCBQAWLlzIfffdh4uL2XnYsmVLPvnkE7KysnKP7du3j9DQ0IuGNhEp4f5eUzQmBiIi4M8/zQoEBw7A4cO5ZaZOZ2bypt3ONIeDtOxthtrUqcOo227j1tatoV07hTYRKTL/Krht2bKF1atXc/r0abKysvK89tZbbxX4fQYOHEiPHj1o0qQJzZs3Z+bMmURFReXWPB06dCgnTpzI3att3759bNmyhaZNm3L27Fneeustdu7cybx583Lf89lnn+Wdd96hX79+vPDCC+zfv58xY8bw4osv/ptbFZHr2aZN8OGHF4Jbjx5mkNu929wwN2cvtqNHiStXjvEnT/JOYiKp2Ze3aNyYUePGcfutt5ob4rq7K7SJSJEqdHAbM2YMw4YNo1atWoSEhOSZj3apuWmX0q1bN+Li4oiMjCQ6Opp69eqxfPny3L2NoqOjiYqKyj3f4XAwceJE9u7di5ubG23btmXDhg1UqVIl95yKFSvy/fffM2DAAOrXr0/58uXp168fr7zySmFvVUSuZ/HxMHs27NtnloyKiTGfN25srhS1WMBq5RzwVno6k48fJyl79XqT0qUZ9fjjdHjrLSw50ywU2ETkKrAYhmEU5oKQkBDefPPN3EUB16PExER8fX1JSEhQCS+R69XOnfD00+bmuTn8/eH//g/69SMpNZUpFgsTHQ7OZb/coGpVIu++m47t22Np2VIVCkTkiilo9ih0j5uLiwstW7b8T40TEXGKAwfg4EGoXt3sUTt2DM6cuVAMPjmZlMqVmRoayrgDB4jLngpSx8uLke++y4Pdu+OSkaEhURFxmkJvBzJgwACmTp1aFG0RESk6s2bBPffA44+bjx99ZG6g63BAZiZpmZlMjo+neteuvLJ/P3GGwQ2ennx8663s+O47uvTqhYuHh1nEXaFNRJyk0EOlWVlZ3Hvvvezbt486derg5uaW5/UlS5Zc0QY6g4ZKRYq5v68UPXDALMB+6pS5UtRiMQMYkJ6RwWyLhdHnz3My+3+HVatWZfhLL/FY27a4li2btyaoiEgRKLKh0hdeeIFVq1bRtm1bAgMDC70gQUSkSG3aBHPnQnQ0hIZC796wY4e5+CCHYZCRmMg8Ly9GpacTlT0kWtFqJXzoUHpFROT7R6mIyLWg0MFt/vz5fP7559x7771F0R4RkX8vPh7eesuseGC1mtt6nD0L1arlnuIAPgZGAodSUgAItVp5zd+f/+vUCfdXXjE32RURuQYVOrgFBASoSLKIXDvs9gt7qB04YIY2ux28vc292H79FWrVIgv4FBgB7M2+NNjbmyEtW/JM+fJ4VqoE3bub14mIXKMKHdxGjBjB8OHDmTt3LqVKlSqKNomIFExsLHz//YWVoqVLmyEuKwtcXcHhwEhLY2laGsPd3NiZvQ9bADDY35/nN2zAq0IFSEw0r1VoE5FrXKEXJ9x0000cPHgQwzCoUqVKvnkgv/766xVtoDNocYJIMWC3w6uvwuLF5oa5Hh5w552waxccPYrh6so3yclEpKfzW/aQqK+LCy95e9OvUiVKDxsG3bo5+SZERExFtjihc+fO/6VdIiJXxu7d8PnnkJICfn5w7hysXInRrRsr7XYi9u5lc3IyAN7e3vTv35+BXbvif+4cVK4M/6LGsoiIsxU6uA0fPrwo2iEiUjjHj5tDnC4ukB3QVsfHE/7FF6zbtw+AUu7uPP/007wcEUGQqhyIyHXgXxWZFxG56v66CMFmgwoVzHlsSUlssNkIT0rip6wsSErC3d2dZ598kiFDhhBSsaKzWy4icsUUKLgFBASwb98+goKC8Pf3v+zebfHx8VescSIigLkI4fffzeFQPz9o0ACCg/nlhhuI2LqVFQkJALhZLDz1xBO8Ono05cuXd2qTRUSKQoGC26RJk/DJ3mV80qRJ2nRXRIrOX+uJ1qhh9rRt2GBuomuxgGGw/Y8/iPjuO75avx4Aq8VC77AwhnXpQuWXX9bqUBG5bhV6VWlJoFWlIk4ya5a5gW5CAvj6wsCB8OCDMGUKnD7NrpQUhq9fz+eHDwPg4uLC440bE9G8OdWrVYO77oJatZx8EyIihVdkq0qtVivR0dEEBwfnOR4XF0dwcDAOh6PwrRUROXAARo82S1NZrWYVhNGjoW5d9u3dy4hffmHh4cMYgAXo3rkzEWPHUlv7sIlICVLo4HapDrr09HRsNtt/bpCIlCBRUXD0qLk9x9atZhF4MEtOORwcio4mctAgPty0iazs//c8WKUKIzt0oN7o0RAYaJ6vwCYiJUSBg9vbb78NgMVi4f3338f7L/+jdDgc/Pzzz9SuXfvKt1BErk+LFsHEiebCg6AgaNnSrHhgGEQ5HLxutzPXMMjcuBGA+2rVIvKOO7gpNBRuvBGy592KiJQkBQ5ukyZNAswet/feew+r1Zr7ms1mo0qVKrz33ntXvoUicv2JioLhw+HIEXPBwcmTEBvLyaAgxsTEMCs5GXv2qR1atWLka6/R1Gq9sKq0YUNzSxARkRKmwMHtcPZk4LZt27JkyRL8/f2LrFEicp35+x5sW7aYQ6SZmWCzcdpu542oKKYDaVlZALT18iKyRw9unTLFvObv7yEiUgIVeo7bqlWr8jx3OBz88ccfVK5cWWFORPKLjYW1a+HYMahYEVq1gvPnISODOMNgfGYm72RlkZp9esvatRnVrh1t27SB1q0vhDSbTYFNREq8Qge3/v37c+ONN/Lkk0/icDi47bbb2LhxI6VKleLrr7+mTZs2RdBMESk2kpMvrPK02WDuXPjsM/O4tzccOMC5G2/kLTc3JqelkZTdw3az1cqot96ifZ8+WOx29ayJiFxEoYPbZ599xuOPPw7AV199xZEjR9izZw/z58/ntddeY332hpgiUgLt3QtLl5pz1sqVg0aNYP5887nNRlJMDFMmTGDi+fOcS0sDoKHVSqSPD/d17Ijlf/8zA5u7u5NvRETk2lTo4BYXF0fZsmUBWL58OQ8//DA1a9bkySefzF15KiIlUHIyzJgBa9aYc9dcXc25bCdPkmKxMNVuZ9y5c8Rlb+tR94YbGFm/Pg94e+NSsSI8/ri29RAR+QeFDm4hISHs3r2b0NBQVqxYwbRp0wBITU3Ns9JURK5zfx0S9fY2FxusXAlnzpgb6DocnI+NZUZ6OmNTUzmdHdhqWq2MGDaMruHhWM+f1+a5IiKFUOjg1rt3b7p27UpoaCgWi4U777wTgM2bN2sfN5GSYu9ec97a8eNQoQI8/LC5VceJE5CURDowOyuL0YbByezAVs1qJcLbm8datsT1xRfNcOftrcAmIlIIhQ5uI0aMoF69ehw7doyHH34Y9+y5KFarlSFDhlzxBorINSY5GSZNghUrLmzPcfw43H03GWlpzHM4GGUYRGWfXtHPj/A6dejl5YVb+fLQpw8EBDj1FkREiisVmb8IFZkXuYzt26F9e3ObD4sFDIPMwEA+ueceRn70EYeyV4mGWiy85unJ/y1ciHvLlhcqJCi0iYjkU9Ds4VLQN7znnntISEjIfT569GjOnTuX+zwuLo46der8u9aKyLUtOdlcGZqcDH/8AXFxYBhkubqywDCoFxtLz/nzOZSVRbDFwlu+vhwMCKBvWBjuDRqYYa1mTYU2EZH/qMBDpd999x3p6em5z998800eeeQR/Pz8AMjMzGTv3r1XvIEi4mR798KyZWYB+JAQSE8nyzBYarEw3G5nV/ZpAV5eDL7/fp4/eBCvc+fMAvD9+kGlSs5svYjIdaXAwe3vI6oaYRUpAZKT4cMPYcMGMAwM4Gs3NyIsFrZnD4n6Ai95eNBvxQpK33qrWYf06FGoXFmhTUTkCiv04gQRuY79PXRFR8OPP2IcO8b36elEJCSwJSMDAG+Lhf5ubgz08cG/c2do0MB8j0qVFNhERIpIgYObxWLBYrHkOyYi14lFi+CNN+D0aQgOhiFDoFo1Vu3dS0RCAuuye9hKAc+3b8/Ld9xBUGYm+PlB3bqqdiAichUUaqi0V69eudt/pKWl8cwzz+Dl5QWQZ/6biBQzUVEwcKC5AAHg5EnW9+1LeEgIq86eBcAdeM5q5RUvL0Kee84MbCkp4OVlBjfVFRURKXIFDm49e/bM8zynXulfPfHEE/+9RSJydWzfDrt3Q506uaWpALYAEcB3cXEQF4cb8LS7O6+WLk05hwN8fCA0FBo2vLCPm0KbiMhVUeDgNnfu3KJsh4hcTZGR8M47F3rMatRgO2Zg+yr7FFegd506DKtcmUp79+bu2cZNN0GNGmZYU2ATEbmqtDhBpKTZvh0mTICkJAB2nT/P8NhYPs9+2QXogRniqvXpA7fcAu+/DzExULYs/N//aT82EREnUXATKWl++gmSktgLjLRYWJi9zYcF6A4MB2qBuQ/bPfeYvWs1a6rygYjINUDBTeR6FxNjzl8rVw7KluXQuXNEAh8CWdn7MT4EjOjQgXr790N8vBnOhgwxQxuYzxXYREScTsFN5Hpit+ddMLBiBUybBqdOEeXjw+tubsxduZLM7NM7AiOBmwAGDYIqVeDgQahe/UJoExGRa4aCm8j1IjYWvv/+QvCqXx/efJOTu3Yx5vx5ZiUnY88+tYObG5EZGdySc21QEHh4mGFNgU1E5Jql4CZSHP29Z81uNzfPXbQo9/jphg1545dfmJ6aSlr2kGhbm41RgwfTcsUKsypCzrWhoWYdUhERuaYpuIkUN7Gx8PvvcO6cuQlugwZw/DgsWAAJCcS5uzP+1Cne+fprUrMvaVmqFKM8PWnr4QF33GHuxbZkCZw/D56e8OCDZpkrERG5pim4iRQndrtZ8H3rVvPXNpu5F1tKCucSEngrM5NJqakkZ/ew3VyqFKM8PGjv6YklZw+2+vWhXj1zOPXECShfHlq31p5sIiLFgIKbSHGSlATffQe//gqZmeDqSmJ0NFPS0piYmkpCdmBr6OJCZKlS3Dd+PJbNm81h0dBQ6NPnwurQjh1V+UBEpJhRcBMpTuLj4Zdf4MwZUkqV4t3oaMb98gvxDgcAda1WRrq784CHBy7t2sHjj0PXrhffg02VD0REih0FN5Fr2d8XISQnc/7sWd6LjeWN1FROZ2UBULNyZUa88AJdz5zBevw4VKoEPXuCt7f5PtqDTUTkuqDgJnKtio2FXbty64mm16jB+59/zpjDhzmZ3cNWzcWFiDJleOzLL3Ft0ACSkyExEUqXvhDaRETkuqHgJnItstvN0LZ9OxmxsXywfz+vr15N1KlTAFR0dSU8KIhe/v64Va0Kvr7mdd7eCmwiItcxF2c3YNq0aVStWhUPDw8aN27M2rVrL3v+1KlTCQsLw9PTk1q1ajF//vxLnrtw4UIsFgudO3e+wq0WKQLx8bBvn/mYnk7mjBnMe/VVao8ezdOLFhF16hShISFM7diR/fffz1N33IFbvXrQooU5f01ERK57Tu1xW7RoEf3792fatGm0bNmSGTNmcPfdd7N7924qVaqU7/zp06czdOhQZs2axc0338yWLVt46qmn8Pf3p2PHjnnOPXr0KIMGDaJVq1ZX63ZE/r1Nm+CDD+D0abLKlGERMGLRIvZlz2ELBoa6u9Pns8/wDA6Gr7+GuDizEPx996mXTUSkhLAYRvb+AU7QtGlTGjVqxPTp03OPhYWF0blzZ8aOHZvv/BYtWtCyZUvGjx+fe6x///5s3bqVdevW5R5zOBy0bt2a3r17s3btWs6dO8cXX3xR4HYlJibi6+tLQkICpUuX/nc3J1JQ8fHQrx9Zv/zC0sREhsfFsctuFqcKBAZ7eNDXMPACs+7o//6nuWwiIteZgmYPpw2V2u12tm3bRvv27fMcb9++PRs2bLjoNenp6Xh4eOQ55unpyZYtW8jIyMg9FhkZSZkyZXjyyScL1Jb09HQSExPz/IgUmZgYcx+2mBgAjCNH+Gr5chrv3UuX6Gh22e34AqNcXTnk5sZgDw+8DAOsVqhY0XwPb28oV06hTUSkhHFacIuNjcXhcBDyt/qIISEhxGT/hfZ3HTp04P3332fbtm0YhsHWrVuZM2cOGRkZxMbGArB+/Xpmz57NrFmzCtyWsWPH4uvrm/tTMecvR5ErbcUKePRReOwxjEce4bvRo2nWvTv3x8ezHfABwoEjFgvD6tWjtJsbpKWBqyvcdhs0b+7c9ouIiFM5fVWpxWLJ89wwjHzHcoSHhxMTE0OzZs0wDIOQkBB69erFuHHjsFqtJCUl8fjjjzNr1iyCCjFZe+jQoQwcODD3eWJiosKbXBl/HdJMToYBA2D/flY5HITv2cP61asBKAW8YLHwspsbgQ4HuLhA9+5w5gwcOgTVqsFTT6mHTUSkhHNacAsKCsJqtebrXTt9+nS+Xrgcnp6ezJkzhxkzZnDq1ClCQ0OZOXMmPj4+BAUFsWPHDo4cOZJnoUJW9uRuV1dX9u7dS/Xq1fO9r7u7O+7u7lfw7kSAvXth6VI4edIc1nRzY/3evYQbBquyT/EAnm3enFf27CEkKcnsWcvKMoPe7bdDWJjmsomISC6nBTebzUbjxo1ZuXIlDzzwQO7xlStX0qlTp8te6+bmRoUKFQBzy4/77rsPFxcXateuzR9//JHn3GHDhpGUlMSUKVPUiyZXT3IyzJgBP/0EGRlsycgg4vRpvsteC+QGPA28CpS76y6z+Ptnn5lVEry84OGHoUEDs1qCApuIiGRz6lDpwIED6dGjB02aNKF58+bMnDmTqKgonnnmGcAcwjxx4kTuXm379u1jy5YtNG3alLNnz/LWW2+xc+dO5s2bB4CHhwf16tXL8xl+fn4A+Y6LXFF/X+V59Ch88w2/HT9OhN3O15mZgPkfXG9gGJC74c0NN8Bzz8HNN8OBA1CjhrnFh+qIiojI3zg1uHXr1o24uDgiIyOJjo6mXr16LF++nMqVKwMQHR1NVFRU7vkOh4OJEyeyd+9e3NzcaNu2LRs2bKBKlSpOugMRzCHRDz6Aw4ehalXo1YtdGzYw/OBBPs8uTeUC9MguT1Utu/oBALVqQdu25ga6jz6aty6piIjI3zh1H7drlfZxk8uKibkwb83bGx5/HFatArudvVYrI/38WHjypLnQBuju4sJwi4VaViu88gqsWwcnTkD58jB4MNx1l7PvSEREnKyg2cPpq0pFipUVK2DmTDh7Fvz9oWlT+OEHDqakEGmx8JFhkJWSAsBDNhsjDIN6Hh5m7VEfH+jQwRwWzQl+Zcs6+YZERKQ4UXATuZS/9qyVLWs+nznTfAwJgZgYjs6Zw+spKXwAZGZ3XncEIvv3p+GBA/DLL2AYUKqUOYctLAwCAhTYRETkX1FwE7mYFSvM8lKxseb8s+eeg+BgOH4cHA5OHDzImOhoZsXGklOzo4PFQiRwi9VqFn7v1s1cWRodDaGh0KePGdpERET+JQU3ETCHMnMWBsTHw1tvwZ494OZmhrW33oIRIziVlMQbx48zPSWF9Owetts9PYlMT6eli4vZu1arFrRqZfaq1ax5IfwptImIyH+k4CYSGwubNl3oGQPYudPc3sNqBYeD2B07GD9hAu/u309q9krRll5ejGrWjLa9e8PcuReGVQcNujAUGhCgwCYiIleMgpuULH/tWbPZzOeffQZffWXWBPXwgOrVISEBHA7OubkxMSWFySkpJC9dCsAtZcsyqk0b7ixbFkuVKtCpE9xxhxYciIhIkVNwk5IjNha2bjXrf5YpA02aQEoKfPmleczXF06dgtOnSfTwYEpyMhPPnSMh+/KbbriByIEDuTctDUtCAvj5mVt5eHubPwpsIiJSxBTc5PoVH39hfpm3t7ng4McfL/S4xcZemIOWXVoqJTmZd48eZVxCAvHZQ6J1XV2JrFOHzt9+i0u5cvmrJIiIiFwlCm5yfdq0yZx3ljNvrWNH+Pprs7pBzhDp+fPw0ksQGMj5U6d4b/du3jh6lNPZ5alqeXkxIjSUrrVr49K3rzkMChd62ERERK4yBTe5/uSsCs3ZQ+2PP+DIEYiLM58HBppDoocOkW4YvO/nx5g1aziZng5AtaAghr/5Jo+2b4/r6dOatyYiItcMBTe5/hw4AOvXm9UNLBYzrCUnQ+XK4OoKGRlkuLjwQWIiozp35lh0NACVAgIIf+QRer72Gm45q0srVHDijYiIiOSl4CbF399XisbGmj92+4XglpEBt99OZmwsH586ReSBAxw6fx6AcuXK8dorr/Dko4/iXrq0CryLiMg1S8FNirfYWPj9dzh3zlzl2aABpKZC9jy1nODmcDhY5O7OyB072BcbC0BwYCBDhw2jT58+eHp6Ou0WRERECkrBTYovux02bIBdu8wKBxkZ5vYerq5m71taGlkuLizNymI4sOvDDwEI9Pdn8IAB9B04EC8vL+feg4iISCEouEnx8tdh0aQk+PNP87lhmK/9+Se0bYtRsSJfHTnC8MxMtgMYBn6lS/PSyy/Tr18/fHx8nHwjIiIihafgJsVHbCz89JO5QrRKFWjYEKKi4LffICsLXFwwGjbkuwMHiEhN5Re7HQAfFxf6t23LwE8+wS842Jl3ICIi8p8ouEnxYLfDu+/CRx+ZK0S9vaFzZzh0yHweGMhPR48SsXAh66dPB6CUuzsv3HorLz/+OIH33WduxCsiIlKMKbhJ8XDgAMycCadPm89jY+GDD6BxY9YFBRG+axers1/zcHfnub59Gdy/PyF+fhdWm4qIiBRzCm5ybdq+HXbvhjp1zCHRX381Q5vDAS4ukJXFlrg4wrdt4/u4OABsLi48XbcuQxcsoFzduk5tvoiISFFQcJNrT2QkTJtmrhD18oLnnjOLwmfXDv3NMIgAvgaIi8PVxYXeVasy7NZbqfTMM6DQJiIi1ykFN7m2bN8O77xjFnF3dTWrH7zzDkRGstNmY7jdzhLDAMAFeKJ9e8LHjqWat7c5hy0gwKnNFxERKUoKbuJcUVFw9KhZjqpSJXNINCHB3JMtKwsyM9l77hwj3n+fRXY7BmABHnFxYXiTJtRcsEBhTURESgwFN3GeRYtgyhSzV83fH/r1g1KlcqseHMzKIhL4KDOTrF9/BaBLxYqMCAmhbs2a8MILCm0iIlKiKLiJc0RFwfjx5qOnJ8TFmc+HDOGojw+vJyYyNysLR/bp9996KyPfeYeGlSqZK0o1LCoiIiWQgptcPTExcPIklCsHe/aYQ6QOh7lHW2YmJw4dYszMmcxKSiIj+5K73N2JrF+fmz/7DMqWNQ8qsImISAml4CZXx4oV8N57Zs9aYCA0a5Yb2E5ZrbyRlMT0zEzSV64E4PagICJDQmhZrZq5qjQntImIiJRgCm5y5cXH5x3OjIkxqx5ERZlz2Q4dgnPniA0JYfzRo7wbG0tq9qW3Nm7MqAkTaFO79oXeOYU2ERERQMFN/qu/Fn232WDTJrOiwenTEBwMvXqBxQInToCfHwQEcNZuZ+Lu3Uw5e5bk7IUIt3h7M+ree7lz1iwsOQXgFdhERETyUHCTfy82FrZuhTNnzA1yq1WDqVNh1y5zwcGRI+Ymui++CJ6eJMbFMeXkSSYePkxCVhYAN5UrR+Qtt3Bv06ZYHngAckKbiIiI5KPgJv+O3W7OW1u1ytxzzc0NqlY1y1S5u5tDpLGx8OefpKSm8q6fH+N++YX47B62emXLMnLKFB64+24sSUlQurRZOF5EREQuScFN/p24OFi50pyH5uEBaWlmUDMMM9Q5HJxPS2N6XBxvPPggZ+LjAagVHMyIRx+l69ChuAQHm++lXjYREZECUXCTgvn7XLakJDh82AxrNpv5up8f1K9P+h9/MGvXLsZERxOdYW7sUa1aNYa/9hqPPvAArl5e5jUiIiJSKApu8s9iY+H33+HcOTOcNWhgLjg4f97sacvucctIT2eury+vHzzIsYQEACqVK0f4yJH07NkTNzc3p96GiIhIcafgJpdnt8OGDeYiBLvd7ClLSYHataFiRXBzIxP4yMWFyD17OJxdmqpc2bIMe+UVnnzuOWzqXRMREbkiFNzk8pKS4LvvYPt2s8qB1WrOb2vQAMdNN7Fo+XJG7t7NvsREAILLlGHoq6/Sp08fPD09ndt2ERGR64yCm1xefDz89hskJJgrRePjyfr1V5YsW8bw+fPZfeAAAIGlSvFK3748N3w4Xl5eTm60iIjI9UnBTS4vPd2cyxYXh3HqFF9lZhJx6BC/b9oEgJ+fH4OefpoX+/fHJzTUyY0VERG5vim4SX7JyZCYaO6t5uGBce4c38XFEeFw8IthAODj5cWAl15iwIAB+Pn5Obe9IiIiJYSCm+S1dy989hkcPw4VKvCT3U74iRNsyN44txTwYqlSDFq6lMA773RuW0VEREoYBbeS7O/F4JOTYdIkWLWKdcnJhJ89y+rz5wHwAJ7z9uYVINjDw6yUICIiIleVgltJtWkTzJplVj4oVw6eego8PNjyzTeEnznD9+npANiAp318GOrqSjkPD7O8VVCQ+SMiIiJXlYJbSREVBUePQuXKZk3QMWNg2zbztR07+O3AASJSU/n6+HHA/IPxPy8vXitVikqtWsGBA5CVBS4u0LYtVKnitFsREREpqRTcSoJFi+Cdd+DsWfD3h/btczfU/cNmY3hcHEtPngTABXjC05PwoCCqZWRASAg8/bR5fkwMlC0LXbqoILyIiIgTKLhdb/5eUzQqCiZPNhcb+PiYvW6ffMLe5GRGpKezyG7HACzAI61bM/zmm6m5Zg2kpkKpUmZIa9sWWra8sNJUoU1ERMQpFNyuJ7Gx8NNPcOSIOZR5++3mEOfRo2ags9s5aLcTeeYMH6Wnk5V9WRc3N0ZUqkTdWbPMHrlmzeDECShfHlq3NgOgzabAJiIi4mQKbtcLux3efRc++shcHertDY8/bvaWnT/P0fPnGWWx8EFaGo7sS+739WWkvz8NAwOha1dz/pvNBh075u21ExERkWuCgltx9tdh0QMHYOZMOH3afC02FmbO5ESlSoy2WHg/PZ2M7Mvu8vYmcuJEbg4MzN+zBhd62EREROSa4uLsBkybNo2qVavi4eFB48aNWbt27WXPnzp1KmFhYXh6elKrVi3mz5+f5/VZs2bRqlUr/P398ff3p127dmzZsqUob8E5YmNh40ZYu9Z8XLUKTp0yC8E7HMQ4HPSPjqZ6nz5MP3uWDOAOPz/W16nDt926cXOXLmbPWu/e5qO29xAREbnmObXHbdGiRfTv359p06bRsmVLZsyYwd13383u3bupVKlSvvOnT5/O0KFDmTVrFjfffDNbtmzhqaeewt/fn44dOwKwevVqHnnkEVq0aIGHhwfjxo2jffv27Nq1i/Lly1/tWywadjvs2mVuoOvtbT7u2QNZWcQC44B3gfMAmZnc2qABoypXpo27uxnQnnjC3HAX1LMmIiJSjFgMI7v4pBM0bdqURo0aMX369NxjYWFhdO7cmbFjx+Y7v0WLFrRs2ZLx48fnHuvfvz9bt25l3bp1F/0Mh8OBv78/7777Lk888USB2pWYmIivry8JCQmULl26kHd1FSQlwTffmMOiaWng4cHZPXuY+N57TDEMkrNPuwUYNXw4dw4fjuXs2bxVEkREROSaUdDs4bQeN7vdzrZt2xgyZEie4+3bt2fDhg0XvSY9PR0PD488xzw9PdmyZQsZGRm4XaQMU2pqKhkZGQRcJqykp6eTnl0pAMzfvGvK37f4sFjg0CHYs4dEDw8mb9nCW3v2kJCdwW8CIl1cuLdePSzPPGOeHxCgwCYiIlLMOS24xcbG4nA4CAkJyXM8JCSEmJiYi17ToUMH3n//fTp37kyjRo3Ytm0bc+bMISMjg9jYWEJDQ/NdM2TIEMqXL0+7du0u2ZaxY8cycuTI/3ZDRSU21hwWTUkBLy+oWxcsFpITE3l3717G79hBfFoaAPUqViQyIIDOmZlYypWDgQPNDXNFRETkuuD0VaUWiyXPc8Mw8h3LER4eTkxMDM2aNcMwDEJCQujVqxfjxo3DarXmO3/cuHEsWLCA1atX5+up+6uhQ4cycODA3OeJiYlUrFjxX97RFZQzl+3oUXPRgdXK+fR0pm/YwBvvvsuZlBQAapcpw4h27Xh4yhRcHI4L9UcV2kRERK4rTgtuQUFBWK3WfL1rp0+fztcLl8PT05M5c+YwY8YMTp06RWhoKDNnzsTHx4egv62KnDBhAmPGjOGHH36gfv36l22Lu7s77u7u/+2GikJ6OqxZA99/T/q5c8w6f54xZ84QnZQEQPWAAIZ36MCj9ephrVsXfH3NoVQFNhERkeuS04KbzWajcePGrFy5kgceeCD3+MqVK+nUqdNlr3Vzc6NChQoALFy4kPvuuw8Xlws7m4wfP57XX3+d7777jiZNmhTNDVwNZ8+S8eWXzN2/n9dTUznmMLfOrVS+PBGDBvFE7dq4JSeDnx80bKgVoiIiItc5pw6VDhw4kB49etCkSROaN2/OzJkziYqK4plnngHMIcwTJ07k7tW2b98+tmzZQtOmTTl79ixvvfUWO3fuZN68ebnvOW7cOMLDw/nkk0+oUqVKbo+et7c33td6yabk5Nx6oJkeHnz03ntE7tjB4cxMAMpbrbzm58eTH36IrW3b/IsWRERE5Lrm1ODWrVs34uLiiIyMJDo6mnr16rF8+XIqV64MQHR0NFFRUbnnOxwOJk6cyN69e3Fzc6Nt27Zs2LCBKlWq5J4zbdo07HY7Xbp0yfNZw4cPZ8SIEVfjtv6dvXth6VIcx4+zKDaWkZs3s+/IEQBCXFwYGhBAH1dXPLy9zR42UIUDERGREsap+7hdq676Pm7JyWSFh7Pkyy8ZfvIku7O3Jgn09+eVsmV57uxZvFxdISsLGjWCefO0tYeIiMh15Jrfx01MhmGwbO5chr/3Hr9nb+vhZ7EwqEwZXly4EJ99++CXX8zqCAEBcPPNcJH96kREROT6p+DmJEZ6Oiu+/pqIsWPZum0bAD4WCwOCghhgteLn6mpunFu7Nvj7m/PY0tMhJMT8tYiIiJQ4Cm5OsHv9ep565hk27NwJQCkPD1709maQqyuB3t5w/rw5jy0o6MLWHikp5rG6dTWvTUREpIRScLva7HZ8o6PZtncvHjYbz91zD6907Urwhg2wbh0Yhlk4vnVrqFLF/HXz5lo9KiIiIgpuV116OuVLleKTESNo1qgR5UqXhnPnoHdvs3ctJsZ87NLFDG2g1aMiIiICKLhdfe7u4OXFg/XrQ+nS5qIDHx+oVw9q1szdx41rfc85ERERueoU3K42m82cp7Zrl9nT5uNzYd6azabAJiIiIpek4OYMQUGatyYiIiKFpuDmLJq3JiIiIoXk8s+niIiIiMi1QMFNREREpJhQcBMREREpJhTcRERERIoJBTcRERGRYkLBTURERKSYUHATERERKSYU3ERERESKCW3AexGGYQCQmJjo5JaIiIhISZCTOXIyyKUouF1EUlISABUrVnRyS0RERKQkSUpKwtfX95KvW4x/inYlUFZWFidPnsTHxweLxeLs5hRIYmIiFStW5NixY5QuXdrZzZF/Sd/j9UHf4/VB3+P1obh8j4ZhkJSURLly5XBxufRMNvW4XYSLiwsVKlRwdjP+ldKlS1/TfzClYPQ9Xh/0PV4f9D1eH4rD93i5nrYcWpwgIiIiUkwouImIiIgUEwpu1wl3d3eGDx+Ou7u7s5si/4G+x+uDvsfrg77H68P19j1qcYKIiIhIMaEeNxEREZFiQsFNREREpJhQcBMREREpJhTcRERERIoJBbdr1LRp06hatSoeHh40btyYtWvXXvb8qVOnEhYWhqenJ7Vq1WL+/Pl5Xp81axatWrXC398ff39/2rVrx5YtW4ryFoQr/z3+1cKFC7FYLHTu3PkKt1oupii+y3PnztG3b19CQ0Px8PAgLCyM5cuXF9UtCEXzPU6ePJlatWrh6elJxYoVGTBgAGlpaUV1CyXezz//TMeOHSlXrhwWi4UvvvjiH69Zs2YNjRs3xsPDg2rVqvHee+/lO+fzzz+nTp06uLu7U6dOHZYuXVoErb8CDLnmLFy40HBzczNmzZpl7N692+jXr5/h5eVlHD169KLnT5s2zfDx8TEWLlxoHDx40FiwYIHh7e1tLFu2LPecRx991Jg6darx22+/GX/++afRu3dvw9fX1zh+/PjVuq0Spyi+xxxHjhwxypcvb7Rq1cro1KlTEd+JFMV3mZ6ebjRp0sS45557jHXr1hlHjhwx1q5da2zfvv1q3VaJUxTf40cffWS4u7sbH3/8sXH48GHju+++M0JDQ43+/ftfrdsqcZYvX2689tprxueff24AxtKlSy97/qFDh4xSpUoZ/fr1M3bv3m3MmjXLcHNzMxYvXpx7zoYNGwyr1WqMGTPG+PPPP40xY8YYrq6uxqZNm4r4bgpPwe0adMsttxjPPPNMnmO1a9c2hgwZctHzmzdvbgwaNCjPsX79+hktW7a85GdkZmYaPj4+xrx58/57g+Wiiup7zMzMNFq2bGm8//77Rs+ePRXcroKi+C6nT59uVKtWzbDb7Ve+wXJRRfE99u3b17j99tvznDNw4EDj1ltvvUKtlsspSHAbPHiwUbt27TzH+vTpYzRr1iz3edeuXY277rorzzkdOnQwunfvfsXaeqVoqPQaY7fb2bZtG+3bt89zvH379mzYsOGi16Snp+Ph4ZHnmKenJ1u2bCEjI+Oi16SmppKRkUFAQMCVabjkUZTfY2RkJGXKlOHJJ5+88g2XfIrqu1y2bBnNmzenb9++hISEUK9ePcaMGYPD4SiaGynhiup7vPXWW9m2bVvu1JNDhw6xfPly7r333iK4C/k3Nm7cmO9779ChA1u3bs39Hi91zqX+bDiTgts1JjY2FofDQUhISJ7jISEhxMTEXPSaDh068P7777Nt2zYMw2Dr1q3MmTOHjIwMYmNjL3rNkCFDKF++PO3atbvi9yBF9z2uX7+e2bNnM2vWrCK/BzEV1Xd56NAhFi9ejMPhYPny5QwbNoyJEycyevToIr+nkqiovsfu3bszatQobr31Vtzc3KhevTpt27ZlyJAhRX5PUjAxMTEX/d4zMzNzv8dLnXOpPxvO5OrsBsjFWSyWPM8Nw8h3LEd4eDgxMTE0a9YMwzAICQmhV69ejBs3DqvVmu/8cePGsWDBAlavXp3vX5NyZV3J7zEpKYnHH3+cWbNmERQUdDWaL39xpf+bzMrKIjg4mJkzZ2K1WmncuDEnT55k/PjxREREFPn9lFRX+ntcvXo1o0ePZtq0aTRt2pQDBw7Qr18/QkNDCQ8PL/L7kYK52Pf+9+OF+bPhTOpxu8YEBQVhtVrzpfzTp0/n+9dADk9PT+bMmUNqaipHjhwhKiqKKlWq4OPjk+8v+AkTJjBmzBi+//576tevX2T3UdIVxfd48OBBjhw5QseOHXF1dcXV1ZX58+ezbNkyXF1dOXjw4NW4tRKnqP6bDA0NpWbNmnn+cRUWFkZMTAx2u73obqiEKqrvMTw8nB49evB///d/3HjjjTzwwAOMGTOGsWPHkpWVVeT3Jf+sbNmyF/3eXV1dCQwMvOw5l/qz4UwKbtcYm81G48aNWblyZZ7jK1eupEWLFpe91s3NjQoVKmC1Wlm4cCH33XcfLi4XvuLx48czatQoVqxYQZMmTYqk/WIqiu+xdu3a/PHHH2zfvj335/7776dt27Zs376dihUrFuUtlVhF9d9ky5YtOXDgQJ6/3Pft20doaCg2m+3K30gJV1TfY2pqap7/zwJYrVYMc/Hflb0J+VeaN2+e73v//vvvadKkCW5ubpc955/+bDjF1V8PIf8kZ8n67Nmzjd27dxv9+/c3vLy8jCNHjhiGYRhDhgwxevTokXv+3r17jQ8//NDYt2+fsXnzZqNbt25GQECAcfjw4dxz3nzzTcNmsxmLFy82oqOjc3+SkpKu9u2VGEXxPf6dVpVeHUXxXUZFRRne3t7G888/b+zdu9f4+uuvjeDgYOP111+/2rdXYhTF9zh8+HDDx8fHWLBggXHo0CHj+++/N6pXr2507dr1at9eiZGUlGT89ttvxm+//WYAxltvvWX89ttvudu6/P17zNkOZMCAAcbu3buN2bNn59sOZP369YbVajXeeOMN488//zTeeOMNbQcihTN16lSjcuXKhs1mMxo1amSsWbMm97WePXsarVu3zn2+e/duo2HDhoanp6dRunRpo1OnTsaePXvyvF/lypUNIN/P8OHDr9IdlUxX+nv8OwW3q6covssNGzYYTZs2Ndzd3Y1q1aoZo0ePNjIzM6/G7ZRYV/p7zMjIMEaMGGFUr17d8PDwMCpWrGg899xzxtmzZ6/SHZU8q1atuujfZz179jQMI//3aBiGsXr1auOmm24ybDabUaVKFWP69On53vezzz4zatWqZbi5uRm1a9c2Pv/886twN4VnMQz15YqIiIgUB5rjJiIiIlJMKLiJiIiIFBMKbiIiIiLFhIKbiIiISDGh4CYiIiJSTCi4iYiIiBQTCm4iIiIixYSCm4iIiEgxoeAmIiIiUkwouImIXMLp06fp06cPlSpVwt3dnbJly9KhQwc2btyYe86GDRu455578Pf3x8PDgxtvvJGJEyficDjyvJfFYuGLL77I9xm9evWic+fORXwnInK9cHV2A0RErlUPPfQQGRkZzJs3j2rVqnHq1Cl+/PFH4uPjAVi6dCldu3ald+/erFq1Cj8/P3744QcGDx7Mpk2b+PTTT7FYLE6+CxG5nii4iYhcxLlz51i3bh2rV6+mdevWAFSuXJlbbrkFgJSUFJ566inuv/9+Zs6cmXvd//3f/xESEsL999/Pp59+Srdu3ZzSfhG5PmmoVETkIry9vfH29uaLL74gPT093+vff/89cXFxDBo0KN9rHTt2pGbNmixYsOBqNFVEShAFNxGRi3B1deWDDz5g3rx5+Pn50bJlS1599VV27NgBwL59+wAICwu76PW1a9fOPSfHI488khsIc34+/vjjor0REbmuKLiJiFzCQw89xMmTJ1m2bBkdOnRg9erVNGrUiA8++CD3HMMwLnqtYRj55rdNmjSJ7du35/m5//77i/IWROQ6o+AmInIZHh4e3HnnnURERLBhwwZ69erF8OHDqVmzJgB//vnnRa/bs2cPN9xwQ55jZcuWpUaNGnl+fHx8ivweROT6oeAmIlIIderUISUlhfbt2xMQEMDEiRPznbNs2TL279/PI4884oQWisj1TMFNROQi4uLiuP322/noo4/YsWMHhw8f5rPPPmPcuHF06tQJLy8vZsyYwZdffsnTTz/Njh07OHLkCLNnz6ZXr1506dKFrl27Ovs2ROQ6o+1AREQuwtvbm6ZNmzJp0iQOHjxIRkYGFStW5KmnnuLVV18FoEuXLqxatYoxY8Zw2223cf78eWrUqMFrr71G//79tYebiFxxFuNSM2tFRERE5JqioVIRERGRYkLBTURERKSYUHATERERKSYU3ERERESKCQU3ERERkWJCwU1ERESkmFBwExERESkmFNxEREREigkFNxEREZFiQsFNREREpJhQcBMREREpJv4fy5Y0c34MgLQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##SOH##\n",
    "\n",
    "titles = ['without PM', 'with PM', 'Four Features']\n",
    "\n",
    "real = [e, c, a]\n",
    "est = [f, d, b]\n",
    "\n",
    "for i, (r, e, t) in enumerate(zip(real, est, titles)):\n",
    "    plt.figure(figsize=(7,4))\n",
    "    plt.plot(r, r, c='k', label='real SOH')\n",
    "    plt.scatter(r, e, c='r', alpha=0.2, s=3**2, label='estimated SOH')\n",
    "    plt.title(t)\n",
    "    plt.xlabel('SOH')\n",
    "    plt.ylabel('Estimated SOH')\n",
    "    plt.legend()\n",
    "    \n",
    "plt.show()    \n",
    "plt.savefig('/media/sf_share/Ridge_SOH_graph.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 516,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.95204406218031e-16"
      ]
     },
     "execution_count": 516,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##RMSE##\n",
    "s = []\n",
    "n = len(y_test)\n",
    "for  r, e in  zip(y_test.tolist(), y_pred.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "lr_rmse = math.sqrt(sum(s)/n)\n",
    "lr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 517,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0015487484359904252"
      ]
     },
     "execution_count": 517,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##RMSE##\n",
    "s =[]\n",
    "n = len(F_y_test)\n",
    "for r, e in zip(F_y_test.tolist(), F_y_pred.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "F_lr_rmse = math.sqrt(sum(s)/n)\n",
    "F_lr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 518,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.8934126710758207e-10"
      ]
     },
     "execution_count": 518,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##RMSE##\n",
    "s =[]\n",
    "n = len(PM_y_test)\n",
    "for r, e in zip(PM_y_test.tolist(), PM_y_pred.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "PM_lr_rmse = math.sqrt(sum(s)/n)\n",
    "PM_lr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 519,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##중간 생략 세로 막대 그래프 만들기\n",
    "plt.figure(figsize=(5,4))\n",
    "models = ['withou PM', 'with PM', 'Four Features']\n",
    "values = [lr_rmse, PM_lr_rmse, F_lr_rmse]\n",
    "plt.bar(models, values)\n",
    "plt.tick_params(axis='x', bottom=False)\n",
    "plt.ylim(0.0000, 1e-10)\n",
    "plt.title('Linear Regression_RMSE')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GPR (mean_prediction, std_prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27.1**2 * RBF(length_scale=227)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kernel = 1 * RBF(length_scale=1.0, length_scale_bounds=(1e-5, 1e5))\n",
    "gaussian_process = GaussianProcessRegressor(kernel=kernel, n_restarts_optimizer=9)\n",
    "gaussian_process.fit(X_train, y_train)\n",
    "gaussian_process.kernel_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27.1**2 * RBF(length_scale=227)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kernel = 1 * RBF(length_scale=1.0, length_scale_bounds=(1e-5, 1e5))\n",
    "gaussian_process_F = GaussianProcessRegressor(n_restarts_optimizer=9)\n",
    "gaussian_process_F.fit(F_X_train, F_y_train)\n",
    "gaussian_process.kernel_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30.4**2 * RBF(length_scale=270)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kernel = 1 * RBF(length_scale=1.0, length_scale_bounds=(1e-5, 1e5))\n",
    "gaussian_process_PM = GaussianProcessRegressor(kernel=kernel, n_restarts_optimizer=9)\n",
    "gaussian_process_PM.fit(PM_X_train, PM_y_train)\n",
    "gaussian_process_PM.kernel_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Predicted variances smaller than 0. Setting those variances to 0.\n"
     ]
    }
   ],
   "source": [
    "mean_prediction, std_prediction = gaussian_process.predict(X_test, return_std=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_prediction_F, std_prediction_F = gaussian_process_F.predict(F_X_test, return_std=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Predicted variances smaller than 0. Setting those variances to 0.\n"
     ]
    }
   ],
   "source": [
    "mean_prediction_PM, std_prediction_PM = gaussian_process_PM.predict(PM_X_test, return_std=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(906,)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_prediction_F.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(mean_prediction_F)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "e1 = y_test.tolist()\n",
    "e1.sort()\n",
    "f1 = mean_prediction.tolist()\n",
    "f1.sort()\n",
    "\n",
    "a1 = F_y_test.tolist()\n",
    "a1.sort()\n",
    "b1 = mean_prediction_F.tolist()\n",
    "b1.sort()\n",
    "\n",
    "c1 = PM_y_test.tolist()\n",
    "c1.sort()\n",
    "d1  = mean_prediction_PM.tolist()\n",
    "d1.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##SOH##\n",
    "\n",
    "titles = ['without PM', 'with PM', 'Four Features']\n",
    "\n",
    "real = [e1, c1, a1]\n",
    "est = [f1, d1, b1]\n",
    "\n",
    "for i, (r, e, t) in enumerate(zip(real, est, titles)):\n",
    "    plt.figure(figsize=(7,4))\n",
    "    plt.plot(r, r, c='k', label='real SOH')\n",
    "    plt.scatter(r, e, c='r', alpha=0.2, s=3**2, label='estimated SOH')\n",
    "    plt.title(t)\n",
    "    plt.xlabel('SOH')\n",
    "    plt.ylabel('Estimated SOH')\n",
    "    plt.legend()\n",
    "    \n",
    "plt.show()    \n",
    "plt.savefig('Ridge_SOH_graph.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.09897853095333384"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##RMSE##\n",
    "s =[]\n",
    "n = len(y_test)\n",
    "for r, e in zip(y_test.tolist(), mean_prediction.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "gpr_rmse = math.sqrt(sum(s)/n)\n",
    "gpr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0007709052445919278"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##RMSE##\n",
    "s =[]\n",
    "n = len(F_y_test)\n",
    "for r, e in zip(F_y_test.tolist(), mean_prediction_F.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "F_gpr_rmse = math.sqrt(sum(s)/n)\n",
    "F_gpr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.00022203208602426217"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##RMSE##\n",
    "s =[]\n",
    "n = len(PM_y_test)\n",
    "for r, e in zip(PM_y_test.tolist(), mean_prediction_PM.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "PM_gpr_rmse = math.sqrt(sum(s)/n)\n",
    "PM_gpr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##세로 막대 그래프\n",
    "plt.figure(figsize=(5,4))\n",
    "models = ['without PM','with PM', 'Four Features']\n",
    "values = [gpr_rmse,PM_gpr_rmse, F_gpr_rmse]\n",
    "plt.bar(models, values)\n",
    "plt.tick_params(axis='x', bottom=False)\n",
    "#plt.ylim(0.0000, 1e-9)\n",
    "plt.title('Gaussian Progress Regression_RMSE')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Ridge Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Ridge(alpha=0.1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Ridge</label><div class=\"sk-toggleable__content\"><pre>Ridge(alpha=0.1)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "Ridge(alpha=0.1)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "\n",
    "ridge = linear_model.Ridge(alpha=0.1)\n",
    "ridge.fit(X_train, y_train)\n",
    "\n",
    "ridge_F = linear_model.Ridge(alpha=0.1)\n",
    "ridge_F.fit(F_X_train, F_y_train)\n",
    "\n",
    "ridge_PM = linear_model.Ridge(alpha=0.1)\n",
    "ridge_PM.fit(PM_X_train, PM_y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred1 = ridge.predict(X_test)\n",
    "F_y_pred1 = ridge_F.predict(F_X_test)\n",
    "PM_y_pred1 = ridge_PM.predict(PM_X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "e2 = y_test.tolist()\n",
    "e2.sort()\n",
    "f2 = y_pred1.tolist()\n",
    "f2.sort()\n",
    "\n",
    "a2 = F_y_test.tolist()\n",
    "a2.sort()\n",
    "b2 = F_y_pred1.tolist()\n",
    "b2.sort()\n",
    "\n",
    "c2 = PM_y_test.tolist()\n",
    "c2.sort()\n",
    "d2 = PM_y_pred1.tolist()\n",
    "d2.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##SOH##\n",
    "\n",
    "titles = ['without PM', 'with PM', 'Four Features']\n",
    "\n",
    "real = [e2, c2, a2]\n",
    "est = [f2, d2, b2]\n",
    "\n",
    "for i, (r, e, t) in enumerate(zip(real, est, titles)):\n",
    "    plt.figure(figsize=(7,4))\n",
    "    plt.plot(r, r, c='k', label='real SOH')\n",
    "    plt.scatter(r, e, c='r', alpha=0.2, s=3**2, label='estimated SOH')\n",
    "    plt.title(t)\n",
    "    plt.xlabel('SOH')\n",
    "    plt.ylabel('Estimated SOH')\n",
    "    plt.legend()\n",
    "    \n",
    "plt.show()    \n",
    "plt.savefig('Ridge_SOH_graph.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0014050912351366062"
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##without PM_RMSE##\n",
    "s = []\n",
    "n = len(y_test)\n",
    "for r, e in zip(y_test.tolist(), y_pred1.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "ridge_rmse = math.sqrt(sum(s)/n)\n",
    "ridge_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0015912003521055492"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##with PM_RMSE##\n",
    "s =[]\n",
    "n = len(F_y_test)\n",
    "for r, e in zip(F_y_test.tolist(), F_y_pred1.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "F_ridge_rmse = math.sqrt(sum(s)/n)\n",
    "F_ridge_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.001260838775138395"
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##4 Features_RMSE##\n",
    "s =[]\n",
    "n = len(PM_y_test)\n",
    "for r, e in zip(PM_y_test.tolist(), PM_y_pred1.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "PM_ridge_rmse = math.sqrt(sum(s)/n)\n",
    "PM_ridge_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 577,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##세로 막대 그래프\n",
    "plt.figure(figsize=(5,4))\n",
    "models = ['without PM', 'with PM', 'Four Features']\n",
    "values = [ridge_rmse, PM_ridge_rmse, F_ridge_rmse]\n",
    "plt.bar(models, values)\n",
    "plt.tick_params(axis='x', bottom=False)\n",
    "#plt.ylim(0.0000, 1e-9)\n",
    "plt.title('Ridge Regression_RMSE')\n",
    "plt.show()\n",
    "plt.savefig('/media/sf_share/ridge_rmse.svg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SVR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.96796117, 0.97281553, 0.98446602, ..., 0.95825243, 0.98058252,\n",
       "       0.93883495])"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_st = y_train.values.reshape(len(y_train),1)\n",
    "y_st = StandardScaler().fit_transform(y_st)\n",
    "y_st = y_st.ravel()\n",
    "\n",
    "svr = make_pipeline(StandardScaler(), SVR())\n",
    "svr.fit(X_train, y_st)\n",
    "\n",
    "y_pred_svr = svr.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test_st = y_test.values.reshape(len(y_test),1)\n",
    "y_test_st = StandardScaler().fit_transform(y_test_st)\n",
    "y_test_st = y_test_st.ravel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "e3 = y_test_st.tolist()\n",
    "e3.sort()\n",
    "f3 = y_pred_svr.tolist()\n",
    "f3.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,4))\n",
    "\n",
    "plt.plot(e3, f3, c='k', label='real SOH')\n",
    "plt.scatter(e3, f3, c='r', alpha=0.2, s=3**2, label='estimated SOH')\n",
    "plt.title('without PM')\n",
    "plt.xlabel('SOH')\n",
    "plt.ylabel('Estimated SOH')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06293339819843496"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##without PM_RMSE##\n",
    "s = []\n",
    "n = len(y_test_st)\n",
    "for r, e in zip(y_test_st.tolist(), y_pred_svr.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "svr_rmse = math.sqrt(sum(s)/n)\n",
    "svr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "PM_y_st = PM_y_train.values.reshape(len(PM_y_train),1)\n",
    "PM_y_st = StandardScaler().fit_transform(PM_y_st)\n",
    "PM_y_st = PM_y_st.ravel()\n",
    "\n",
    "PM_svr = make_pipeline(StandardScaler(), SVR())\n",
    "PM_svr.fit(PM_X_train, PM_y_st)\n",
    "\n",
    "PM_y_pred_svr = PM_svr.predict(PM_X_test)\n",
    "\n",
    "\n",
    "PM_y_test_st = PM_y_test.values.reshape(len(PM_y_test),1)\n",
    "PM_y_test_st = StandardScaler().fit_transform(PM_y_test_st)\n",
    "PM_y_test_st = PM_y_test_st.ravel()\n",
    "\n",
    "e3 =PM_y_test_st.tolist()\n",
    "e3.sort()\n",
    "f3 = PM_y_pred_svr.tolist()\n",
    "f3.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,4))\n",
    "\n",
    "plt.plot(e3, f3, c='k', label='real SOH')\n",
    "plt.scatter(e3, f3, c='r', alpha=0.2, s=3**2, label='estimated SOH')\n",
    "plt.title('with PM')\n",
    "plt.xlabel('SOH')\n",
    "plt.ylabel('Estimated SOH')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06536680469469125"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##with PM_RMSE##\n",
    "s = []\n",
    "n = len(PM_y_test_st)\n",
    "for r, e in zip(PM_y_test_st.tolist(), PM_y_pred_svr.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "PM_svr_rmse = math.sqrt(sum(s)/n)\n",
    "PM_svr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06293339819843496"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##RMSE##\n",
    "s =[]\n",
    "n = len(y_test)\n",
    "for r, e in zip(y_test_.tolist(), y_pred_svr.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "F_svr_rmse = math.sqrt(sum(s)/n)\n",
    "F_svr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "e4 = y_test_st.tolist()\n",
    "e4.sort()\n",
    "f4 = y_pred_svr.tolist()\n",
    "f4.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,4))\n",
    "\n",
    "plt.plot(e4, f4, c='k', label='real SOH')\n",
    "plt.scatter(e4, f4, c='r', alpha=0.2, s=3**2, label='estimated SOH')\n",
    "plt.title('Four Features')\n",
    "plt.xlabel('SOH')\n",
    "plt.ylabel('Estimated SOH')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##세로 막대 그래프\n",
    "plt.figure(figsize=(5,4))\n",
    "models = ['without PM', 'with PM', 'Four Features']\n",
    "values = [svr_rmse, PM_svr_rmse, F_svr_rmse]\n",
    "plt.bar(models, values)\n",
    "plt.tick_params(axis='x', bottom=False)\n",
    "#plt.ylim(0.0000, 1e-9)\n",
    "plt.title('Support Vector Regression_RMSE')\n",
    "plt.show()\n",
    "plt.savefig('idge_rmse.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 574,
   "metadata": {},
   "outputs": [],
   "source": [
    "F_y_st = F_y_train.values.reshape(len(F_y_train),1)\n",
    "F_y_st = StandardScaler().fit_transform(F_y_st)\n",
    "F_y_st = F_y_st.ravel()\n",
    "\n",
    "F_svr = make_pipeline(StandardScaler(), SVR())\n",
    "F_svr.fit(F_X_train, F_y_st)\n",
    "\n",
    "F_y_pred_svr = F_svr.predict(F_X_test)\n",
    "\n",
    "\n",
    "F_y_test_st = F_y_test.values.reshape(len(F_y_test),1)\n",
    "F_y_test_st = StandardScaler().fit_transform(F_y_test_st)\n",
    "F_y_test_st = F_y_test_st.ravel()\n",
    "\n",
    "e3 =F_y_test_st.tolist()\n",
    "e3.sort()\n",
    "f3 = F_y_pred_svr.tolist()\n",
    "f3.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 575,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,4))\n",
    "\n",
    "plt.plot(e3, e3, c='k', label='real SOH')\n",
    "plt.scatter(e3, f3, c='r', alpha=0.2, s=3**2, label='estimated SOH')\n",
    "plt.title('Four Features')\n",
    "plt.xlabel('SOH')\n",
    "plt.ylabel('Estimated SOH')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 576,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05831377381045383"
      ]
     },
     "execution_count": 576,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Four Features##\n",
    "s = []\n",
    "n = len(F_y_test_st)\n",
    "for r, e in zip(F_y_test_st.tolist(), F_y_pred_svr.tolist()):\n",
    "    s.append((r-e)**2)\n",
    "F_svr_rmse = math.sqrt(sum(s)/n)\n",
    "F_svr_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 476,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.93786408, 0.96893204, 0.95631068, ..., 0.95242718, 0.99708738,\n",
       "       0.92038835])"
      ]
     },
     "execution_count": 476,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.76405235,  0.40015721,  0.97873798,  2.2408932 ,  1.86755799,\n",
       "       -0.97727788,  0.95008842, -0.15135721, -0.10321885,  0.4105985 ])"
      ]
     },
     "execution_count": 475,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_samples, n_features = 10, 5\n",
    "rng = np.random.RandomState(0)\n",
    "yy = rng.randn(n_samples)\n",
    "xx = rng.randn(n_samples, n_features)\n",
    "yy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "결정계수 R : 0.40078242785737295\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plot\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "x = np.random.rand(100,1)\n",
    "x = x * 10-5\n",
    "\n",
    "y = np.array([math.sin(i) for i in x])\n",
    "#평균 0 표준편차 1인 가우시안 정규 분포 \n",
    "y = y + np.random.randn(100)\n",
    "#서포트 백터 머신 모듈 가져오기 \n",
    "from sklearn.svm import SVR\n",
    "model = SVR()\n",
    "model.fit(x,y)\n",
    "relation_square = model.score(x, y)\n",
    "print('결정계수 R :', relation_square)\n",
    "y_p = model.predict(x)\n",
    "\n",
    "plot.scatter(x, y, marker = '+')\n",
    "plot.scatter(x, y_p, marker = 'o')\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 628,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.drop(['SOH', 'cycles', 'Qd_skew_dis', 'Qd_kurt_dis'], axis=1)\n",
    "y = data[['SOH']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 629,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_T = X.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 630,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_T = y.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 634,
   "metadata": {},
   "outputs": [],
   "source": [
    "st_X_T = StandardScaler().fit_transform(X_T.values)\n",
    "features = [i for i in X_T.columns]\n",
    "st_X_T = pd.DataFrame(st_X_T, columns=features).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 635,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-16.915968</td>\n",
       "      <td>-0.643459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-15.993020</td>\n",
       "      <td>-0.720751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-15.859018</td>\n",
       "      <td>-0.732615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>290.345736</td>\n",
       "      <td>-5.351247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-22.010756</td>\n",
       "      <td>-0.168187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            X         Y\n",
       "0  -16.915968 -0.643459\n",
       "1  -15.993020 -0.720751\n",
       "2  -15.859018 -0.732615\n",
       "3  290.345736 -5.351247\n",
       "4  -22.010756 -0.168187"
      ]
     },
     "execution_count": 635,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca = PCA(n_components=2)\n",
    "printcipalComponenets = pca.fit_transform(st_X_T)\n",
    "principalDf = pd.DataFrame(data=printcipalComponenets, columns = ['X' ,'Y'])\n",
    "principalDf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 639,
   "metadata": {},
   "outputs": [],
   "source": [
    "label=[]\n",
    "for i in range(len(principalDf)):\n",
    "    label.append(i+1)\n",
    "\n",
    "features = pd.DataFrame(label, columns=['feautres'])\n",
    "\n",
    "finalDf = pd.concat([principalDf, features], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 652,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots(1,1, figsize=(5,4))\n",
    "\n",
    "for i, row in finalDf.iterrows():\n",
    "    feature = row['feautres']\n",
    "    ax.scatter(row['X'], row['Y'], label = f'No.{feature}')\n",
    "\n",
    "ax.set_xlabel('X', fontsize=10)\n",
    "ax.set_ylabel('Y', fontsize=10)\n",
    "ax.set_title('LFP_PCA', fontsize=12)\n",
    "#ax.legend()\n",
    "ax.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 602,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>SOH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36.533215</td>\n",
       "      <td>-9.494655</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>38.462329</td>\n",
       "      <td>-3.712096</td>\n",
       "      <td>1.001942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38.115339</td>\n",
       "      <td>-3.303283</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.569780</td>\n",
       "      <td>-4.147608</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.411963</td>\n",
       "      <td>-4.153535</td>\n",
       "      <td>1.002913</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           X         Y       SOH\n",
       "0  36.533215 -9.494655  1.000000\n",
       "1  38.462329 -3.712096  1.001942\n",
       "2  38.115339 -3.303283  1.002913\n",
       "3   0.569780 -4.147608       NaN\n",
       "4   0.411963 -4.153535  1.002913"
      ]
     },
     "execution_count": 602,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##15 charging##\n",
    "FinalDf = pd.concat([principalDf, y_T], axis=1)\n",
    "FinalDf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 603,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import matplotlib.cm as cm\n",
    "\n",
    "import matplotlib.colors as mcl\n",
    "\n",
    "fig = plt.figure(figsize=(8,6))\n",
    "h = 255\n",
    "colors = [\n",
    "    mcl.hsv_to_rgb((h/360,0.5,1)),\n",
    "    mcl.hsv_to_rgb((h/360,0.97,0.57)),\n",
    "    mcl.hsv_to_rgb((h/360,0.98,0.3))\n",
    "]\n",
    "\n",
    "cmap = mcl.LinearSegmentedColormap.from_list('my_cmap', colors, gamma=2)\n",
    "\n",
    "vmax = max(FinalDf['SOH'].tolist())\n",
    "vmin = min(FinalDf['SOH'].tolist())\n",
    "norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)\n",
    "colormapping = cm.ScalarMappable(norm=norm, cmap=cmap)\n",
    "\n",
    "fig.set_facecolor('white')\n",
    "plt.scatter(FinalDf['X'], FinalDf['Y'], c=FinalDf['SOH'], cmap=cmap)\n",
    "\n",
    "cbar = fig.colorbar(colormapping, ax = plt.gca())\n",
    "cbar.ax.set_title('SOH')\n",
    "plt.xlabel('X', fontsize=15)\n",
    "plt.ylabel('Y', fontsize=15)\n",
    "plt.title('LFP_PCA', fontsize=20)\n",
    "\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
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