PCA with Digit Data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.datasets import load_digits\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "digit = load_digits()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "for i in range(4):\n",
    "    plt.matshow(digit.images[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.  0.  5. ...  0.  0.  0.]\n",
      " [ 0.  0.  0. ... 10.  0.  0.]\n",
      " [ 0.  0.  0. ... 16.  9.  0.]\n",
      " ...\n",
      " [ 0.  0.  1. ...  6.  0.  0.]\n",
      " [ 0.  0.  2. ... 12.  0.  0.]\n",
      " [ 0.  0. 10. ... 12.  1.  0.]]\n"
     ]
    }
   ],
   "source": [
    "print(digit.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797, 64)\n"
     ]
    }
   ],
   "source": [
    "print(digit.data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "digit.data.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scaling the DataSet\n",
    "this is very important to scale the data before pca , standard scaler will make it mean = 0 and std dev = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "sc = StandardScaler()\n",
    "digit_new = sc.fit_transform(digit.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = PCA()\n",
    "digit_pca = pca.fit_transform(digit_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.12  0.096 0.084 0.065 0.049 0.042 0.039 0.034 0.03  0.029 0.028 0.026\n",
      " 0.023 0.022 0.022 0.019 0.018 0.016 0.016 0.015 0.013 0.013 0.012 0.011\n",
      " 0.01  0.009 0.009 0.008 0.008 0.007 0.007 0.007 0.007 0.006 0.006 0.006\n",
      " 0.005 0.005 0.005 0.004 0.004 0.004 0.004 0.003 0.003 0.003 0.003 0.003\n",
      " 0.003 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.001 0.001 0.001 0.001\n",
      " 0.001 0.    0.    0.   ]\n"
     ]
    }
   ],
   "source": [
    "print(np.round(pca.explained_variance_ratio_,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>pc1</th>\n",
       "      <th>pc2</th>\n",
       "      <th>pc3</th>\n",
       "      <th>pc4</th>\n",
       "      <th>pc5</th>\n",
       "      <th>pc6</th>\n",
       "      <th>pc7</th>\n",
       "      <th>pc8</th>\n",
       "      <th>pc9</th>\n",
       "      <th>pc10</th>\n",
       "      <th>...</th>\n",
       "      <th>pc55</th>\n",
       "      <th>pc56</th>\n",
       "      <th>pc57</th>\n",
       "      <th>pc58</th>\n",
       "      <th>pc59</th>\n",
       "      <th>pc60</th>\n",
       "      <th>pc61</th>\n",
       "      <th>pc62</th>\n",
       "      <th>pc63</th>\n",
       "      <th>pc64</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.914214</td>\n",
       "      <td>-0.954502</td>\n",
       "      <td>-3.946035</td>\n",
       "      <td>2.028723</td>\n",
       "      <td>-0.267173</td>\n",
       "      <td>0.530327</td>\n",
       "      <td>-1.415321</td>\n",
       "      <td>1.496062</td>\n",
       "      <td>0.124914</td>\n",
       "      <td>-0.822246</td>\n",
       "      <td>...</td>\n",
       "      <td>0.217284</td>\n",
       "      <td>-0.184659</td>\n",
       "      <td>-0.152393</td>\n",
       "      <td>0.486203</td>\n",
       "      <td>0.009390</td>\n",
       "      <td>-0.009188</td>\n",
       "      <td>-0.027512</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>8.243855e-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.588980</td>\n",
       "      <td>0.924636</td>\n",
       "      <td>3.924755</td>\n",
       "      <td>-1.779850</td>\n",
       "      <td>-0.993430</td>\n",
       "      <td>-0.675652</td>\n",
       "      <td>1.878565</td>\n",
       "      <td>0.556336</td>\n",
       "      <td>1.079877</td>\n",
       "      <td>0.087451</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005322</td>\n",
       "      <td>0.267950</td>\n",
       "      <td>-0.511874</td>\n",
       "      <td>-0.422479</td>\n",
       "      <td>-0.090586</td>\n",
       "      <td>0.127878</td>\n",
       "      <td>-0.103101</td>\n",
       "      <td>5.672049e-16</td>\n",
       "      <td>2.746971e-16</td>\n",
       "      <td>3.086705e-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.302039</td>\n",
       "      <td>-0.317189</td>\n",
       "      <td>3.023333</td>\n",
       "      <td>-2.043376</td>\n",
       "      <td>-2.081155</td>\n",
       "      <td>0.935121</td>\n",
       "      <td>-1.296200</td>\n",
       "      <td>1.156160</td>\n",
       "      <td>0.785606</td>\n",
       "      <td>-1.099206</td>\n",
       "      <td>...</td>\n",
       "      <td>0.178624</td>\n",
       "      <td>0.067011</td>\n",
       "      <td>0.112209</td>\n",
       "      <td>0.034327</td>\n",
       "      <td>0.444446</td>\n",
       "      <td>-0.518823</td>\n",
       "      <td>0.179429</td>\n",
       "      <td>2.438054e-16</td>\n",
       "      <td>1.588655e-16</td>\n",
       "      <td>2.155553e-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-3.020770</td>\n",
       "      <td>-0.868772</td>\n",
       "      <td>-0.801744</td>\n",
       "      <td>-2.187039</td>\n",
       "      <td>-0.556813</td>\n",
       "      <td>0.727124</td>\n",
       "      <td>0.959766</td>\n",
       "      <td>-1.382638</td>\n",
       "      <td>0.259075</td>\n",
       "      <td>0.744555</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.115443</td>\n",
       "      <td>0.264125</td>\n",
       "      <td>0.018912</td>\n",
       "      <td>-0.153687</td>\n",
       "      <td>0.275277</td>\n",
       "      <td>-0.115922</td>\n",
       "      <td>0.101748</td>\n",
       "      <td>9.273795e-18</td>\n",
       "      <td>-1.533521e-16</td>\n",
       "      <td>1.432069e-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.528949</td>\n",
       "      <td>-1.093480</td>\n",
       "      <td>0.973121</td>\n",
       "      <td>-1.419510</td>\n",
       "      <td>-1.715106</td>\n",
       "      <td>1.431592</td>\n",
       "      <td>1.073649</td>\n",
       "      <td>-0.968240</td>\n",
       "      <td>-1.660216</td>\n",
       "      <td>1.174593</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.335099</td>\n",
       "      <td>-0.098695</td>\n",
       "      <td>0.292078</td>\n",
       "      <td>0.157340</td>\n",
       "      <td>-0.122873</td>\n",
       "      <td>-0.084901</td>\n",
       "      <td>-0.072045</td>\n",
       "      <td>3.948776e-16</td>\n",
       "      <td>1.382606e-16</td>\n",
       "      <td>9.037551e-18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        pc1       pc2       pc3       pc4       pc5       pc6       pc7  \\\n",
       "0  1.914214 -0.954502 -3.946035  2.028723 -0.267173  0.530327 -1.415321   \n",
       "1  0.588980  0.924636  3.924755 -1.779850 -0.993430 -0.675652  1.878565   \n",
       "2  1.302039 -0.317189  3.023333 -2.043376 -2.081155  0.935121 -1.296200   \n",
       "3 -3.020770 -0.868772 -0.801744 -2.187039 -0.556813  0.727124  0.959766   \n",
       "4  4.528949 -1.093480  0.973121 -1.419510 -1.715106  1.431592  1.073649   \n",
       "\n",
       "        pc8       pc9      pc10  ...      pc55      pc56      pc57      pc58  \\\n",
       "0  1.496062  0.124914 -0.822246  ...  0.217284 -0.184659 -0.152393  0.486203   \n",
       "1  0.556336  1.079877  0.087451  ...  0.005322  0.267950 -0.511874 -0.422479   \n",
       "2  1.156160  0.785606 -1.099206  ...  0.178624  0.067011  0.112209  0.034327   \n",
       "3 -1.382638  0.259075  0.744555  ... -0.115443  0.264125  0.018912 -0.153687   \n",
       "4 -0.968240 -1.660216  1.174593  ... -0.335099 -0.098695  0.292078  0.157340   \n",
       "\n",
       "       pc59      pc60      pc61          pc62          pc63          pc64  \n",
       "0  0.009390 -0.009188 -0.027512 -0.000000e+00 -0.000000e+00  8.243855e-15  \n",
       "1 -0.090586  0.127878 -0.103101  5.672049e-16  2.746971e-16  3.086705e-17  \n",
       "2  0.444446 -0.518823  0.179429  2.438054e-16  1.588655e-16  2.155553e-17  \n",
       "3  0.275277 -0.115922  0.101748  9.273795e-18 -1.533521e-16  1.432069e-17  \n",
       "4 -0.122873 -0.084901 -0.072045  3.948776e-16  1.382606e-16  9.037551e-18  \n",
       "\n",
       "[5 rows x 64 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dp = pd.DataFrame(digit_pca)\n",
    "a=[]\n",
    "for i in range(1,65):\n",
    "    a.append('pc{}'.format(i))\n",
    "dp.columns = [a]\n",
    "dp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#scree plot\n",
    "plt.figure(figsize = (20,5))\n",
    "plt.plot(range(digit_pca.shape[1]), pca.explained_variance_ratio_)\n",
    "plt.xticks(range(digit_pca.shape[1]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797, 64)\n"
     ]
    }
   ],
   "source": [
    "print(digit.data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca1 = PCA(14)\n",
    "digit_pca1 = pca1.fit_transform(digit_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797, 14)\n"
     ]
    }
   ],
   "source": [
    "print(digit_pca1.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.12  0.096 0.084 0.065 0.049 0.042 0.039 0.034 0.03  0.029 0.028 0.026\n",
      " 0.023 0.022]\n"
     ]
    }
   ],
   "source": [
    "print(np.round(pca1.explained_variance_ratio_,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>PC1</th>\n",
       "      <th>PC2</th>\n",
       "      <th>PC3</th>\n",
       "      <th>PC4</th>\n",
       "      <th>PC5</th>\n",
       "      <th>PC6</th>\n",
       "      <th>PC7</th>\n",
       "      <th>PC8</th>\n",
       "      <th>PC9</th>\n",
       "      <th>PC10</th>\n",
       "      <th>PC11</th>\n",
       "      <th>PC12</th>\n",
       "      <th>PC13</th>\n",
       "      <th>PC14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.914239</td>\n",
       "      <td>-0.954439</td>\n",
       "      <td>-3.946050</td>\n",
       "      <td>2.028509</td>\n",
       "      <td>-0.266140</td>\n",
       "      <td>0.529207</td>\n",
       "      <td>-1.412167</td>\n",
       "      <td>1.495126</td>\n",
       "      <td>0.123416</td>\n",
       "      <td>-0.834507</td>\n",
       "      <td>-0.511636</td>\n",
       "      <td>-0.796097</td>\n",
       "      <td>0.200320</td>\n",
       "      <td>-0.226973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.588996</td>\n",
       "      <td>0.924644</td>\n",
       "      <td>3.924401</td>\n",
       "      <td>-1.779518</td>\n",
       "      <td>-0.993027</td>\n",
       "      <td>-0.680155</td>\n",
       "      <td>1.876393</td>\n",
       "      <td>0.551186</td>\n",
       "      <td>1.090916</td>\n",
       "      <td>0.089130</td>\n",
       "      <td>-0.503812</td>\n",
       "      <td>0.653721</td>\n",
       "      <td>-0.032193</td>\n",
       "      <td>-0.371553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.302011</td>\n",
       "      <td>-0.317256</td>\n",
       "      <td>3.023587</td>\n",
       "      <td>-2.043303</td>\n",
       "      <td>-2.082630</td>\n",
       "      <td>0.939594</td>\n",
       "      <td>-1.300039</td>\n",
       "      <td>1.159113</td>\n",
       "      <td>0.779048</td>\n",
       "      <td>-1.082624</td>\n",
       "      <td>2.213933</td>\n",
       "      <td>-2.304911</td>\n",
       "      <td>-0.501799</td>\n",
       "      <td>-0.975640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-3.020707</td>\n",
       "      <td>-0.868774</td>\n",
       "      <td>-0.801785</td>\n",
       "      <td>-2.187598</td>\n",
       "      <td>-0.556023</td>\n",
       "      <td>0.725659</td>\n",
       "      <td>0.962270</td>\n",
       "      <td>-1.389261</td>\n",
       "      <td>0.244095</td>\n",
       "      <td>0.724815</td>\n",
       "      <td>-1.071087</td>\n",
       "      <td>0.499982</td>\n",
       "      <td>-0.210025</td>\n",
       "      <td>0.971900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.528927</td>\n",
       "      <td>-1.093582</td>\n",
       "      <td>0.973263</td>\n",
       "      <td>-1.419932</td>\n",
       "      <td>-1.715875</td>\n",
       "      <td>1.435761</td>\n",
       "      <td>1.071396</td>\n",
       "      <td>-0.967498</td>\n",
       "      <td>-1.682746</td>\n",
       "      <td>1.182059</td>\n",
       "      <td>-0.999284</td>\n",
       "      <td>-1.361338</td>\n",
       "      <td>-0.330219</td>\n",
       "      <td>-0.117167</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        PC1       PC2       PC3       PC4       PC5       PC6       PC7  \\\n",
       "0  1.914239 -0.954439 -3.946050  2.028509 -0.266140  0.529207 -1.412167   \n",
       "1  0.588996  0.924644  3.924401 -1.779518 -0.993027 -0.680155  1.876393   \n",
       "2  1.302011 -0.317256  3.023587 -2.043303 -2.082630  0.939594 -1.300039   \n",
       "3 -3.020707 -0.868774 -0.801785 -2.187598 -0.556023  0.725659  0.962270   \n",
       "4  4.528927 -1.093582  0.973263 -1.419932 -1.715875  1.435761  1.071396   \n",
       "\n",
       "        PC8       PC9      PC10      PC11      PC12      PC13      PC14  \n",
       "0  1.495126  0.123416 -0.834507 -0.511636 -0.796097  0.200320 -0.226973  \n",
       "1  0.551186  1.090916  0.089130 -0.503812  0.653721 -0.032193 -0.371553  \n",
       "2  1.159113  0.779048 -1.082624  2.213933 -2.304911 -0.501799 -0.975640  \n",
       "3 -1.389261  0.244095  0.724815 -1.071087  0.499982 -0.210025  0.971900  \n",
       "4 -0.967498 -1.682746  1.182059 -0.999284 -1.361338 -0.330219 -0.117167  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dp1 = pd.DataFrame(digit_pca1)\n",
    "list2=[]\n",
    "\n",
    "for i in range(1,15):\n",
    "  list2.append('PC{}'.format(i))\n",
    "  \n",
    "\n",
    "dp1.columns = [list2]\n",
    "dp1.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlkAAAEvCAYAAAB2a9QGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3deXhU5f3+8fdnZrKvBEKAhFXWALIEWVRUXMGquLZqxVZrqV/X1lortT+Xti792vp1qXWp1mrVUndRUdxwl33HAAIKJOx7QiDr8/tjhhhDgDBkcibJ/bquuTJnGc89QZKbc555jjnnEBEREZGG5fM6gIiIiEhzpJIlIiIiEgEqWSIiIiIRoJIlIiIiEgEqWSIiIiIRoJIlIiIiEgEBrwPUpU2bNq5Lly4RPcauXbtISkqK6DHCpWzhUbbwKFt4lC08yhYeZQtPY2WbPXv2Zudc5j4bnHNR98jLy3ORNnXq1IgfI1zKFh5lC4+yhUfZwqNs4VG28DRWNmCWq6PP6HKhiIiISASoZImIiIhEgEqWiIiISASoZImIiIhEgEqWiIiISASoZImIiIhEgEqWiIiISATUq2SZ2WgzW2pmy83s5jq29zazL82s1MxurLG+o5lNNbN8M1tsZtc3ZHgRERGRaHXQGd/NzA88DJwCFAAzzWySc+6rGrttBa4Dzq718grg1865OWaWAsw2s/dqvVZERESk2anPmayhwHLn3ErnXBkwERhbcwfn3Ebn3EygvNb6dc65OaHnRUA+kN0gyQ/D58s3k7+l0usYIiIi0ozVp2RlA2tqLBcQRlEysy7AIGD6ob62IVVWOW6ftJgnFpZSUlbhZRQRERFpxix4y50D7GB2AXCac+6K0PI4YKhz7to69r0dKHbO/aXW+mTgY+BO59wr+znOeGA8QFZWVt7EiRMP/d3U09Ktldw9Yw9jusbwo16xETtOuIqLi0lOTvY6Rp2ULTzKFh5lC4+yhUfZwqNsMGrUqNnOuSH7bKjrhoY1H8AIYEqN5QnAhP3seztwY611McAU4IaDHWvvozFuED3uoXdctwlvuUWF2yN+rEOlm22GR9nCo2zhUbbwKFt4lC08TeEG0TOBHmbW1cxigQuBSfVpdmZmwJNAvnPuvvq8prH8sGcsrRJj+N2ri6isOvDZPBEREZFDddCS5ZyrAK4heDYqH3jBObfYzK40sysBzKydmRUANwC/N7MCM0sFjgHGASea2bzQ4/SIvZtDkBxr/L8zcpm/ZjvPTV/ldRwRERFpZg46hQOAc24yMLnWukdrPF8P5NTx0s8AO5yAkXTWgA68NLuA/31nKafmtqNdWrzXkURERKSZaNEzvpsZfzq7H+WVVdzxxmKv44iIiEgz0qJLFkDn1klcd1IP3l60nve/2uB1HBEREWkmWnzJAvj5yG70zErmtkmL2VWqubNERETk8KlkAbEBH3ef25/C7bv5v/eWeR1HREREmgGVrJC8zhlcPKwT//z8GxYV7vA6joiIiDRxKlk1/Pa03mQkxfG7Vxdq7iwRERE5LCpZNaQlxnDbmbksKNjBM19+63UcERERacJUsmo548j2HN8zk79MWcq6Hbu9jiMiIiJNlEpWLXvnzqp0jtte19xZIiIiEh6VrDp0zEjklyf35N2vNjBl8Xqv44iIiEgTpJK1Hz87tiu926Vw+6TFFGvuLBERETlEKln7EeP3cde5/Vm/cw9/fXep13FERESkiVHJOoDBnVpxybDOPP3Ftywo2O51HBEREWlCVLIO4jeje9EmOTh3VkVllddxREREpIlQyTqI1PgYbj+rL4sKd/KvL771Oo6IiIg0ESpZ9TCmXztO7N2W+95bRuF2zZ0lIiIiB6eSVQ9mxh1n9cU5uO31RTinW+6IiIjIgalk1VPHjERuOKUn7+dv1NxZIiIiclAqWYfgsmO60Kd9KrdNWkzRnnKv44iIiEgUU8k6BAG/j7vP7c/GolL++u4yr+OIiIhIFFPJOkQDO6bzkxFdePrLb5m3RnNniYiISN1UssLw61N70jYljgmvaO4sERERqZtKVhhS4mO446y+5K/byVOff+t1HBEREYlCKllhOq1vO07uk8V97y1jzdYSr+OIiIhIlFHJCpOZccfYvpjBrZo7S0RERGpRyToM2ekJ3HBKT6Yu3cTkhZo7S0RERL6jknWYfnp0F/plp3L7G4vZqbmzREREJEQl6zAF/D7uPudIthSXcu87S72OIyIiIlFCJasB9M9J4ydHd+HZ6auYvWqb13FEREQkCqhkNZBfn9qLdqnx3PLqQso1d5aIiEiLp5LVQJLjAtxxVl+WrC/iyc++8TqOiIiIeEwlqwGd2rcdp+Zmcf/7mjtLRESkpVPJamB3jO2L34xbXtPcWSIiIi2ZSlYDa5+WwI2n9eKTZZt4c8E6r+OIiIiIR1SyIuDSEV04MieNO974ih0lmjtLRESkJVLJigC/z7jrnP5s3VXKn6cs8TqOiIiIeEAlK0L6Zadx+TFdeX76amav2up1HBEREWlkKlkR9KtTepKdnsCEVxZSVqG5s0RERFoSlawISooL8IexfVm2oZh/fLrS6zgiIiLSiFSyIuykPlmM6deOBz/4mlVbdnkdR0RERBqJSlYjuP2svsT4ffxec2eJiIi0GCpZjSArNZ6bRvfi0683M2n+Wq/jiIiISCOoV8kys9FmttTMlpvZzXVs721mX5pZqZndeCivbSl+PKwzAzum88c3v2J7SZnXcURERCTCDlqyzMwPPAyMAXKBi8wst9ZuW4HrgL+E8doWYe/cWdtKyrnnbc2dJSIi0tzV50zWUGC5c26lc64MmAiMrbmDc26jc24mUHt684O+tiXJ7ZDKFcd2ZeLMNcz4RnNniYiINGf1KVnZwJoaywWhdfVxOK9tlq4/uQfZ6Qn87lXNnSUiItKc2cE+7WZmFwCnOeeuCC2PA4Y6566tY9/bgWLn3F/CeO14YDxAVlZW3sSJEw/nfR1UcXExycnJET3G/izYVMF9s0s5t0cMZx0Ru892L7MdjLKFR9nCo2zhUbbwKFt4lA1GjRo12zk3ZJ8NzrkDPoARwJQayxOACfvZ93bgxnBeW/ORl5fnIm3q1KkRP8aBXPXcbNfjlslu5abifbZ5ne1AlC08yhYeZQuPsoVH2cKjbM4Bs1wdfaY+lwtnAj3MrKuZxQIXApPqWe4O57XN2m1n5BIX8PH71xZq7iwREZFm6KAlyzlXAVwDTAHygRecc4vN7EozuxLAzNqZWQFwA/B7Mysws9T9vTZSb6YpaZsaz29H9+bz5Vt4dW6h13FERESkgQXqs5NzbjIwuda6R2s8Xw/k1Pe1EnTx0E68PKeAP72Vz6hebWmVtO/4LBEREWmaNOO7h3w+4+5z+7Nzdzl3v53vdRwRERFpQCpZHuvdLpWfH9eNF2YVMG3lFq/jiIiISANRyYoC153Yg44ZwbmzSisqvY4jIiIiDUAlKwokxPr509n9WblpF49+tNLrOCIiItIAVLKixPE9MzlrQAcenrqcdcWaCV5ERKSpU8mKIr8/ow/xMT7un7OHRYU7vI4jIiIih0ElK4q0TYnnH5cOobQSzv37Fzzx6UqqqjRRqYiISFOkkhVlhnVrzR+PSeC4npn86a18LvvXTDYVlXodS0RERA6RSlYUSok1/nFpHn88ux/TVm5hzAOf8NHSjV7HEhERkUOgkhWlzIxxwzsz6ZpjaZ0Ux0+fmskf3vhKUzyIiIg0ESpZUa5XuxRev+YYfjKiM//8/BvOfvgLlm8s8jqWiIiIHIRKVhMQH+PnjrH9eOLSIazfsZszHvqM/8xYjXMaFC8iIhKtVLKakJNzs3jnl8cxpHMGE15ZyFXPzWF7SZnXsURERKQOKllNTFZqPM9cPpQJY3rz3lcbGPPAp0zXPQ9FRESijkpWE+TzGb84/gheuepo4gI+LvrHNP767lLKKzVTvIiISLRQyWrCjsxJ563rRnLe4Bwe+nA5P3zsS9ZsLfE6loiIiKCS1eQlxQW494IBPHjRIJZvKOb0Bz7l9XmFXscSERFp8VSymomzBnRg8vUj6dkuhesnzuOGF+ZRXFrhdSwREZEWSyWrGemYkch/xw/nupN68NrcQn7w4KfMX7Pd61giIiItkkpWMxPw+7jhlJ5MHD+C8ooqznvkCx75aIVuNC0iItLIVLKaqaFdM3j7+uM4tW8Wf35nCZc8OZ0NO/d4HUtERKTFUMlqxtISY3j44sH8+bz+zF29ndH3f8J7X23wOpaIiEiLoJLVzJkZPzqqE29ceyzt0xL4+TOz+H+vLWJPuW40LSIiEkkqWS1E97bJvHr10fx8ZFf+PW0VY//2OUvX60bTIiIikaKS1YLEBfzc8oNcnr58KFt2lXHm3z7jmS+/1Y2mRUREIkAlqwU6vmcm7/xyJEcf0ZpbX1/Mz5+ZxdZdutG0iIhIQ1LJaqHaJMfx1E+P4tYzcvlk2WZG3/8Jny/f7HUsERGRZkMlqwUzMy4/tiuvXX0MKfEBLnlyOne/nU9ZhW40LSIicrhUsoTcDqm8ee1ILjyqE499vJLzH/2Cbzbv8jqWiIhIk6aSJQAkxPq5+9z+PHrJYFZtKeEHD37KS7MLNCheREQkTCpZ8j2j+7Xn7etH0j87jRtfnM91E+exc0+517FERESaHJUs2UeH9ASe//lwbjy1J5MXruP0Bz5l9qptXscSERFpUlSypE5+n3HNiT144RcjAPjhY1/y4AdfU6XLhyIiIvWikiUHlNe5FZOvH8kZR7bnvveW8dDcUqqqVLREREQORiVLDio1PoYHLhzE73/Qh7kbK7n//WVeRxIREYl6KllSbz87tisjswM8+OFypixe73UcERGRqKaSJfVmZozLjeXInDR+/cJ8lm8s9jqSiIhI1FLJkkMS6zcevSSPuICP8f+eRZGmdxAREamTSpYcsg7pCTz84+CkpTe8MF8D4UVEROqgkiVhGd6tNbec3of3vtrA36Yu9zqOiIhI1FHJkrBddkwXzhmUzf+9v4wPl2zwOo6IiEhUqVfJMrPRZrbUzJab2c11bDczezC0fYGZDa6x7VdmttjMFpnZf8wsviHfgHjHzLjrnP7ktk/l+onzdFNpERGRGg5asszMDzwMjAFygYvMLLfWbmOAHqHHeOCR0GuzgeuAIc65foAfuLDB0ovnEmL9PHpJHgGfMf6ZWRSXVngdSUREJCrU50zWUGC5c26lc64MmAiMrbXPWOAZFzQNSDez9qFtASDBzAJAIrC2gbJLlOiYkchDFw1mxaZifvPifJxuvSMiIlKvkpUNrKmxXBBad9B9nHOFwF+A1cA6YIdz7t3w40q0OrZHG24e05u3F63nkY9XeB1HRETEc3awsw5mdgFwmnPuitDyOGCoc+7aGvu8BdztnPsstPwBcBOwEngZ+BGwHXgReMk592wdxxlP8FIjWVlZeRMnTjz8d3cAxcXFJCcnR/QY4Wqq2ZxzPDK/lJnrK7khL47+mYGoyeY1ZQuPsoVH2cKjbOFRNhg1atRs59yQfTY45w74AEYAU2osTwAm1NrnMeCiGstLgfbABcCTNdZfCvz9YMfMy8tzkTZ16tSIHyNcTTnbrtJyd9r/feyOvH2KW7V5V+OECmnK3zcvKVt4lC08yhYeZQtPY2UDZrk6+kx9LhfOBHqYWVcziyU4cH1SrX0mAZeGPmU4nOBlwXUELxMON7NEMzPgJCC//t1QmprE2ACPjcsDYPy/Z1FSpoHwIiLSMh20ZDnnKoBrgCkEC9ILzrnFZnalmV0Z2m0ywUuDy4F/AFeFXjsdeAmYAywMHe/xhn4TEl06t07igQsHsnRDEb99eaEGwouISItUr0EzzrnJBItUzXWP1njugKv389rbgNsOI6M0QSf0asuNp/bi3ilLGZCTxhUju3kdSUREpFFpxneJmKtOOIIx/dpx1+R8vli+2es4IiIijUolSyLGzLj3ggEckZnM1c/PoWBbideRREREGo1KlkRUclxwIHxFpeMX/57NnvJKryOJiIg0CpUsibhumcncf+FAFq/dye9e0UB4ERFpGVSypFGc1CeLX53ck1fmFvL0F996HUdERCTiVLKk0Vx7YndO7pPFH9/KZ9rKLV7HERERiSiVLGk0Pp9x348G0Dkjkaufm8Pa7bu9jiQiIhIxKlnSqFLjY3j80jz2lFfyP89qILyIiDRfKlnS6Lq3TeGvPxzI/IId3Pr6Ig2EFxGRZkklSzwxul87rj2xOy/MKuC56au9jiMiItLgVLLEM788uScn9MrkjjcWM+vbrV7HERERaVAqWeIZv8944EeD6JCewP88N4cNO/d4HUlERKTBqGSJp9ISY3h83BB2lVbwP8/OpqyiyutIIiIiDUIlSzzXq10K954/gDmrt3PHG4u9jiMiItIgVLIkKvzgyPb84vhuPDd9NRNnaCC8iIg0fSpZEjVuOq03I3u04dbXFzN39Tav44iIiBwWlSyJGn6f8eCFg2ibGsf/PDuHTUWlXkcSEREJm0qWRJVWSbE8Ni6P7bvLuPq5OZRXaiC8iIg0TSpZEnX6dkjjz+cdyYxvt3LnW/lexxEREQlLwOsAInUZOzCbBQU7ePKzb+iXncb5eTleRxIRETkkOpMlUWvCmN4M75bB715dyMKCHV7HEREROSQqWRK1An4fD188mDZJsVz57Gy2FGsgvIiINB0qWRLVWifH8di4IWwqLuWa5+dSoYHwIiLSRKhkSdTrn5PGXef058uVW7jn7SVexxEREakXDXyXJuH8vBwWFmznic++oX9OGmMHZnsdSURE5IB0JkuajN+fkcvQLhn89uUFLF6rgfAiIhLdVLKkyYjx+3j4x4NJTwgOhN+2q8zrSCIiIvulkiVNSmZKHI9cMpgNO0q5buJcKquc15FERETqpJIlTc6gTq34w9i+fPr1Zu6dstTrOCIiInVSyZIm6cKhnbh4WCce/XgFby1Y53UcERGRfejThdJk3XZmLkvW7eQ3L82ne9tkr+OIiIh8j85kSZMVF/DzyCV5JMUFGP/vWewq1/gsERGJHipZ0qRlpcbzyI8HU7htN3+ft4fSikqvI4mIiAAqWdIMDOmSwV3n9mfxliqu/8883XpHRESigkqWNAs/HNKRi3rH8s7i9dz08gKqNLWDiIh4TAPfpdk4rUsM7Tt24b73lpEcF+COs/piZl7HEhGRFkolS5qVa0/sTnFpBY9/spLkuAA3je7tdSQREWmhVLKkWTEzJozpTdGeCv7+0QqS4gJcPaq717FERKQFUsmSZsfM+NPZ/Sgpq+DeKUtJiQ9w6YguXscSEZEWRiVLmiW/z/jLBQPYVVrJra8vJjE2wPl5OV7HEhGRFkSfLpRmK8bv428XD+KY7q256aX5vL1Qt98REZHGo5IlzVp8jJ/Hxw1hYMd0rps4l4+XbfI6koiItBD1KllmNtrMlprZcjO7uY7tZmYPhrYvMLPBNbalm9lLZrbEzPLNbERDvgGRg0mKC/DUZUPp0TaFX/x7FjO+2ep1JBERaQEOWrLMzA88DIwBcoGLzCy31m5jgB6hx3jgkRrbHgDecc71BgYA+Q2QW+SQpCXE8MzPhtIhPYHL/zWTBQXbvY4kIiLNXH3OZA0FljvnVjrnyoCJwNha+4wFnnFB04B0M2tvZqnAccCTAM65MuecfruJJ9okx/HcFcNIS4jhJ/+cwbINRV5HEhGRZsycO/DtR8zsfGC0c+6K0PI4YJhz7poa+7wJ3OOc+yy0/AHwW6ACeBz4iuBZrNnA9c65XXUcZzzBs2BkZWXlTZw48fDf3QEUFxeTnJwc0WOES9nCU99sG0uquGv6HgB+NyyetomRH5rYHL5vXlC28ChbeJQtPMoGo0aNmu2cG7LPBufcAR/ABcATNZbHAQ/V2uct4Ngayx8AecAQgkVrWGj9A8AfD3bMvLw8F2lTp06N+DHCpWzhOZRsS9fvdAPumOKOuecDt3Z7SeRChTSX71tjU7bwKFt4lC08yuYcMMvV0Wfq80/4AqBjjeUcYG099ykACpxz00PrXwIGI+KxnlkpPHP5ULaXlHPJE9PZXFzqdSQREWlm6lOyZgI9zKyrmcUCFwKTau0zCbg09CnD4cAO59w659x6YI2Z9QrtdxLBS4cinjsyJ51//vQoCrfv5tInZ7Bjd7nXkUREpBk5aMlyzlUA1wBTCH4y8AXn3GIzu9LMrgztNhlYCSwH/gFcVeM/cS3wnJktAAYCdzVgfpHDMrRrBo+NG8LXG4u47KkZ7Cqt8DqSiIg0E/W6rY5zbjLBIlVz3aM1njvg6v28dh7BsVkiUen4npk8dNEgrnpuDuP/PYsnf3IU8TF+r2OJiEgTpxnfRYDR/dpz7/kD+Hz5Fq79z1zKK6u8jiQiIk2cSpZIyHl5OfxhbF/e+2oDN744n6qqA09vIiIiciD1ulwo0lJcOqILxaUV/O87S0mKC3Dn2f0wM69jiYhIE6SSJVLLVSd0p3hPBX//aAXJcQEmjOmtoiUiIodMJUukDr85rRfFpRU8/slKUuICXHtSD68jiYhIE6OSJVIHM+P2M/tSXFrBX99bRlJcgMuP7ep1LBERaUJUskT2w+cz/ve8IykpreQPb35FclyAHx7V8eAvFBERQZ8uFDmggN/HAxcN5Liemdz8ygLeXFD7jlIiIiJ1U8kSOYi4gJ/HLsljSOcMfjlxHh8u2eB1JBERaQJUskTqISHWzxM/HUKf9qlc+ewcvlix2etIIiIS5VSyROopNT6Gpy8fSueMRH7+9Czmrt7mdSQREYliKlkihyAjKZZnrxhG6+Q4fvrUTPLX7fQ6koiIRCmVLJFDlJUaz3NXDCMhxs+4J2ewclOx15FERCQKqWSJhKFjRiLPXjGMKue45InpFG7f7XUkERGJMipZImHq3jaZZy4fSlFpBT/+xzQ2Fu3xOpKIiEQRlSyRw9AvO41/XXYUG3aWcumTM9heUuZ1JBERiRIqWSKHKa9zBv+4dAgrN+3iJ0/NpLi0wutIIiISBVSyRBrAsT3a8LeLB7GocAdXPD2TPeWVXkcSERGPqWSJNJBT+7bjvh8OYPo3W7nquTmUVVR5HUlERDykkiXSgMYOzObOs/vz4ZKN/OqFeVRWOa8jiYiIRwJeBxBpbi4e1oldpRXcOTmfpFg/95x7pNeRRETEAypZIhHw8+O6UVRawYMffE1SXIDjknVGS0SkpVHJEomQX53cg+I9Ffzz829YmROg+4ASOmYkeh1LREQaiUqWSISYGf/vjD44HE9/8S3H3TuVUb3aMm5EZ47vkYnPZ15HFBGRCFLJEokgM+O2M/vSP2YD3/iy+c+MNVz21Ew6t07kkmGduWBIDumJsV7HFBGRCNCnC0UaQUa8j1+f2osvbj6RBy8aRNuUOO6cnM+wuz7gNy/OZ2HBDq8jiohIA9OZLJFGFBvwcdaADpw1oANfrd3Js9NX8eqcQl6cXcDAjulcOqIzp/dvT3yM3+uoIiJymHQmS8QjuR1Sueuc/ky/5SRuOzOXnXvKueGF+Rx9z4fc8/YS1mwt8TqiiIgcBp3JEvFYanwMlx3TlZ8e3YUvVmzhmS+/5fFPVvDYJys4qXdbxo3owsjubTRQXkSkiVHJEokSZsYx3dtwTPc2rN2+m+enr2bizNW8nz+DLq0TuWR4Zy7I60haYozXUUVEpB50uVAkCnVIT+DG03rxxc0n8cCFA2mTHMef3spn2N3v89uXFrCoUAPlRUSinc5kiUSx2ICPsQOzGTswm8Vrd/DstFW8Nnct/521hsGd0hkXGigfF9BAeRGRaKMzWSJNRN8Oadx97pFM+91J3HpGLttLyvnVf+dz9N0f8r/vLKFgmwbKi4hEE53JEmli0hJiuPzY4ED5z1ds5t9fruLRj1fw6McrOLF3FpeO6MyxGigvIuI5lSyRJsrnM0b2yGRkj0wKt+/m+emrmDhjDe/nb6BrmyQuGd6Z8/NySEvQQHkRES/ocqFIM5CdnsBvTuvNFxNO5P4fDSQjKZY/vvkVw+56n5tfXsDitRooLyLS2HQmS6QZiQv4OXtQNmcPymZRYWig/LxCJs5cQ17nVlw6ojOj+7XTQHkRkUagkiXSTPXLTuOe845kwpg+vDSngGenreL6ifNokxzLj47qyMXDOpOdnuB1TBGRZkslS6SZS0uM4WfHduWyo7vw2fLNPPPlKh75aAWPfLSCk/tk0T2mgo6biunSOgm/BsuLiDQYlSyRFsLnM47rmclxPTMp2FbC89NX89+Za3h3Vxl/n/8xcQEfPbKS6ZWVSu92KfRql0LvdilkpsRhpvIlInKoVLJEWqCcVoncNLo3vzy5J8+/NZXknF4sXb+TJeuL+PTrTbw8p6B631aJMaHClUqvdin0zAoWsOQ4/fgQETmQev2UNLPRwAOAH3jCOXdPre0W2n46UAL81Dk3p8Z2PzALKHTOndFA2UXkMMUGfHRJ83NCXs731m/dVcbS9UUsXb+TpRuKWLK+iBdnrWFXWWX1PjmtEqrPePVqFzz71bVNEjF+fWhZRATqUbJCBelh4BSgAJhpZpOcc1/V2G0M0CP0GAY8Evq61/VAPpDaQLlFJIIykmIZcURrRhzRunpdVZWjcPtuloTKV/BrEVOXbqKyygEQ6/fRLTMpVL6+u+zYPi1elxxFpMWpz5msocBy59xKADObCIwFapasscAzzjkHTDOzdDNr75xbZ2Y5wA+AO4EbGja+iDQWn8/omJFIx4xETsnNql5fWlHJio27WLrhu+I1/ZutvDZvbfU+KfGB7856ZQULWK92KZooVUSatfqUrGxgTY3lAr5/lmp/+2QD64D7gZuAlPBjiki0igv4ye2QSm6H75+o3lFSztIN3z/r9frctRSVVlTv0z4tPnS5MTjIvldWKke0TdI8XiLSLFjw5NMBdjC7ADjNOXdFaHkcMNQ5d22Nfd4C7nbOfRZa/oBgsWoPnO6cu8rMTgBu3N+YLDMbD4wHyMrKyps4ceLhvrcDKi4uJjk5OaLHCJeyhUfZwtOY2ZxzbN3jWFNURUFxFQVFwce6XY7K0I8iv0FWkpGT7KNTYgUjOyeRFhd9l1XMyuoAABPrSURBVBr1ZxoeZQuPsoWnsbKNGjVqtnNuSO319TmTVQB0rLGcA6yt5z7nA2eZ2elAPJBqZs865y6pfRDn3OPA4wBDhgxxJ5xwQj2ihe+jjz4i0scIl7KFR9nCEw3ZyiurWLlpV/WZr6Xri8hfV8SM9ZW8+u1ujunehrMHduC0vu1IipJPNUbD921/lC08yhYeZdu/+vy0mgn0MLOuQCFwIXBxrX0mAdeExmsNA3Y459YBE0IPapzJ2qdgiUjLFuP3VV82ZECH6vXPvfkha2M68Pq8tdzwwnziYxZyam47zh7UgZE9MvVJRhGJagctWc65CjO7BphCcAqHfzrnFpvZlaHtjwKTCU7fsJzgFA6XRS6yiLQU2ck+fnxCb248tRezV23j1bmFvLVwHZPmryUjKZYzjmzP2IHZDO6Urk8vikjUqdd5d+fcZIJFqua6R2s8d8DVB/lvfAR8dMgJRaTFMzOGdMlgSJcMbjuzLx8v28Rr8wr578w1PPPlKjplJHL2wA6MHZTNEZnROTZERFqe6BjcICJST7EBH6fkZnFKbhZFe8qZsngDr80t5G9Tl/Pgh8vpn53G2YOyOXNAe9qmxHsdV0RaMJUsEWmyUuJjOD8vh/Pzctiwcw9vzF/La/MK+eObX3HnW1+FBsxnc1q/droNkIg0Ov3UEZFmISs1nitGduOKkd1YvrGI1+YGC9evX5zPLa8t5OQ+WZwzKJvjemrAvIg0DpUsEWl2urdN4cbTevHrU3syZ3VowPyCdby5YB2tEmP4wZHtOWdQNoM7tdKAeRGJGJUsEWm2zIy8zhnkdc7g1jP68klowPyLswp4dtpqOmYkcPbAbMYOzKZ7Ww2YF5GGpZIlIi1CbMDHyblZnJybRXFpBVMWree1eYU8PHU5D324nH7ZqZw9MJuzBnSgbaoGzIvI4VPJEpEWJzkuwHl5OZyXl8PGnXuYNH8tr89by5/eyueuyfkcfUQbzh6UzWl9s0iJ102sRSQ8Klki0qK1/d6A+WImzSvk1XmF3PjifG55NXj26+yB2RzfM5PYgAbMi0j9qWSJiIR0b5vMDaf24len9GTO6u28NreQNxes5a0F60hPjOEH/YMD5vM6t/I6qog0ASpZIiK1BAfMtyKvcytuPTOXT7/exKtz1/LynAKem76anFYJ9EurwLXfyFFdMjQHl4jUST8ZREQOIMbv48TeWZzYOzhg/t3F63l1biHvLd/MO0/NxO8z+menMeKI1gzv1pqjurQiMVY/WkVEJUtEpN6S4wKcOziHcwfnMOWDqSR37s+XK7bw5cot/OOTlTzy0QoCPmNAx3SGd8tgRLc25HVuRUKs3+voIuIBlSwRkTDE+Y1jurfhmO5tACgpq2DWt9v4cuUWpq3cwqMfr+ThqSuI8RuDOrZieLcMhh/RmsGdWhEfo9Il0hKoZImINIDE2ADH9czkuJ6ZABSXVjDz261MWxEsXXtvYB0b8DGoYzojjmjNiG6tGdgpnbiASpdIc6SSJSISAclxAUb1asuoXm0B2LmnnJnfbGXayuDlxQc++Jr73/+auICPvM6tGNGtNcOPaM2AnHRNFSHSTKhkiYg0gtT4GE7qk8VJfbIA2LG7nBnfbK0e0/XX95bBe5AQ42dIl1YM7xYcSH9kTppuaC3SRKlkiYh4IC0hhlNyszglN1i6tu0qY3roTNe0lVu4d8pSABJj/QzpksGIbq0ZcURr+nVIJaDSJdIkqGSJiESBVkmxjO7XjtH92gGwpbi0unR9uWILf35nCRC8DHlUl1ahMV1tyO2Qit9nXkYXkf1QyRIRiUKtk+M4vX97Tu/fHoBNRaXVZ7m+XLmFqUs3AZASH2BY14zqy4u57VO9jC0iNahkiYg0AZkpcZw5oANnDugAwIade74rXSu28H7+RiB4GbJdfCXPfDuThFg/iTF+EmP9JMQGSIzd+zz0Nab2usB3z2P8uiwpcphUskREmqCs1HjGDsxm7MBsANbt2F1duOatWMuGnXvYXVZJSVklJWUV7C6vpLzSHdIxYv2+7wpZ6GtiTGDfdbEBEmL8NQrb98taYux3r9ld4XDOYaZLnNL8qWSJiDQD7dMSOGdQDucMyuGjj7Zxwgkj99mnvLKKkrJK9pTXKF/VRayS3eUVwa8115UF15WU711fwfaSMtZu3/ua4Lo95VX1zprw8RTapsaRmRxH29Q42qbEk5kSR9uUuNDXeNqmxpGRGItP482kCVPJEhFpIWL8PtISfKQlxDT4f7uqyoUKV6iM7VPYgoVuzuIlpGbmsLGolI1Fe1iyvohPv95M0Z6Kff6bAZ/RJjmuuoC1TY0js0YhC66LJzM5TnOLSVRSyRIRkcPm8xlJcQGS4g78a6VdyUpOOCF3n/W7yyrZFCpeG4tK2bhzD5uKS9m4s5SNRaWs3bGH+QXb2bKrDFfHVc/0xJhQ8YqvPiOWGSphbWucJUuOC+hSpTQalSwREfFcQqyfTq0T6dQ68YD7VVRWsWVXWah8BQtZdTkLFbJvNu9iU1EpZZX7XsJMiPGHLlF+d5ly75mxDZsr6bplFx3SEzQBrDQIlSwREWkyAn4fWanxZKXGA2n73c85x47d5aGzYsESFixjpdVnyvLX7eSTZaUUlX53qfIvsz7CZ9AhPYFOGYl0ykikY+ixd7lVYozOhkm9qGSJiEizY2akJ8aSnhhLz6yUA+5bUlbBpqJSJn80jdade7JmawmrQ4/38zeyubj0e/snxwWCxatVqIi1/q6EZacnEB+jG35LkEqWiIi0aImxATq3DtCntZ8ThnTcZ/uu0goKtu2uLl5rQo9vNu/i42WbKK347rKkGWSlxFefAQuWsAQ6tgo+z0yJ01mwFkQlS0RE5ACS4gL0apdCr3b7nhFzzrGpqDRYvraVsHrL7uoi9vnyzby8c8/39o+P8VUXrtqXITtmJJAYq1/LzYn+NEVERMJkZsFPMKbGM6RLxj7b95RXUrj9u+K1ekuojG0NTh67q6zye/u3SY6jU0ZCdfna+3XbnipN4toEqWSJiIhESHyMnyMykzkiM3mfbc45tpWU73MZcvXWEmav2sYb89dSVWO6ijtnfUC/7FT6dUijX3Ya/bJTyU5PUPGKYipZIiIiHjAzMpJiyUiKZWDH9H22l1dWsW77HlZvLeHtz+dSmpTJosIdfPr1ZipD7Ss9MYZ+HdLoW6N8dc5I1Ez5UUIlS0REJArF+H3Vc4dVFMZwwgkDgOAlyCXri1hUuIPFa3ewqHAnT332bfW8YMlxAXI77C1dqfTPTqNbZjJ+Fa9Gp5IlIiLShMTH+BnYMf17Z7/KKqr4emMRiwt3smjtDhYW7uD5Gauq7ykZH+Mjt31q8DJj6MxXj7Ypuh1RhKlkiYiINHGxAR99O6TRt0MaPyQ4DUVFZRUrN+9iUWHwbNeitTt4ZU4hz3y5Kvgav49e7VKC47xC5atXuxTN89WAVLJERESaoYDfR8+sFHpmpXDu4OC6qirHqq0loeK1g0VrdzB54Xr+M2MNAH6f0aNtcqh0BctXn/apB70npdRN3zUREZEWwuczurZJomubJM4c0AEIfsqxYNvu6vFdi9bu4KOlG3lpdgEQnGC1W5uk711q7NshjbSEGC/fSpOgkiUiItKCmVn1xKij+7UHgsVrY1EpiwqD47sWFe5kxjdbeX3e2urXdW6dSL8Oafh2lbHYLScu4As9/MTF1Hge8IWWg89j61jfXAflq2SJiIjI95hZ9Y24T+qTVb1+c3Epi9furP5k48LCHazeWs4bK5ce1vECPguVLv8By1psPYvc3ufLNlZwwmF+Lw7rfXl4bBEREWlC2iTHcXzPTI7vmVm9burUqRw98jhKK6ooLa+itKJyn+dlFVXBdRWVofV171dze1mNfXaXV7J9d9l+X1tz0taaYv3wyx820jenDipZIiIiEjYzC51B8kN84x/fOUdFlauzyE2bMaPxA9VQrwkyzGy0mS01s+VmdnMd283MHgxtX2Bmg0PrO5rZVDPLN7PFZnZ9Q78BERERabnMjBi/j6S4ABlJsbRPS6BLmyR6tUuhc6q301EctGSZmR94GBgD5AIXmVlurd3GAD1Cj/HAI6H1FcCvnXN9gOHA1XW8VkRERKTZqc+ZrKHAcufcSudcGTARGFtrn7HAMy5oGpBuZu2dc+ucc3MAnHNFQD6Q3YD5RURERKJSfUpWNrCmxnIB+xalg+5jZl2AQcD0Qw0pIiIi0tSYc/sZkr93B7MLgNOcc1eElscBQ51z19bY5y3gbufcZ6HlD4CbnHOzQ8vJwMfAnc65V/ZznPEELzWSlZWVN3HixMN9bwdUXFxMcnJyRI8RLmULj7KFR9nCo2zhUbbwKFt4GivbqFGjZjvnhuyzwTl3wAcwAphSY3kCMKHWPo8BF9VYXgq0Dz2PAaYANxzsWHsfeXl5LtKmTp0a8WOES9nCo2zhUbbwKFt4lC08yhaexsoGzHJ19Jn6XC6cCfQws65mFgtcCEyqtc8k4NLQpwyHAzucc+vMzIAngXzn3H2HVAtFREREmrCDzpPlnKsws2sIno3yA/90zi02sytD2x8FJgOnA8uBEuCy0MuPAcYBC81sXmjd75xzkxv2bYiIiIhEl3pNRhoqRZNrrXu0xnMHXF3H6z4DmucNiUREREQOoF6TkYqIiIjIoVHJEhEREYmAg07h4AUz2wSsivBh2gCbI3yMcClbeJQtPMoWHmULj7KFR9nC01jZOjvnMmuvjMqS1RjMbJara06LKKBs4VG28ChbeJQtPMoWHmULj9fZdLlQREREJAJUskREREQioCWXrMe9DnAAyhYeZQuPsoVH2cKjbOFRtvB4mq3FjskSERERiaSWfCZLREREJGJaXMkys9FmttTMlpvZzV7nqcnM/mlmG81skddZajOzjmY21czyzWyxmV3vdaa9zCzezGaY2fxQtju8zlSTmfnNbK6Zvel1ltrM7FszW2hm88xsltd5ajKzdDN7ycyWhP6/G+F1JgAz6xX6fu197DSzX3qday8z+1Xo78EiM/uPmcV7nWkvM7s+lGux19+zun7emlmGmb1nZl+HvraKomwXhL5vVWbm2afl9pPt3tDf0wVm9qqZpUdRtj+Gcs0zs3fNrENjZmpRJcvM/MDDwBggF7jIzHK9TfU9/wJGex1iPyqAXzvn+gDDgauj6HtXCpzonBsADARGh25UHi2uB/K9DnEAo5xzA6PwI9gPAO8453oDA4iS76Fzbmno+zUQyCN4v9ZXPY4FgJllA9cBQ5xz/Qjeb/ZCb1MFmVk/4OfAUIJ/nmeYWQ8PI/2LfX/e3gx84JzrAXwQWvbCv9g32yLgXOCTRk/zff9i32zvAf2cc0cCy4AJjR0q5F/sm+1e59yRob+vbwK3NmagFlWyCP7lXu6cW+mcKwMmAmM9zlTNOfcJsNXrHHVxzq1zzs0JPS8i+Asv29tUQS6oOLQYE3pExWBDM8sBfgA84XWWpsTMUoHjgCcBnHNlzrnt3qaq00nACudcpCdPPhQBIMHMAkAisNbjPHv1AaY550qccxXAx8A5XoXZz8/bscDToedPA2c3aqiQurI55/Kdc0u9yFMrR13Z3g39mQJMA3IaPRj7zbazxmISjfy7oaWVrGxgTY3lAqKkKDQlZtYFGARM9zbJd0KX5OYBG4H3nHPRku1+4Cagyusg++GAd81stpmN9zpMDd2ATcBToUutT5hZkteh6nAh8B+vQ+zlnCsE/gKsBtYBO5xz73qbqtoi4Dgza21micDpQEePM9WW5ZxbB8F/WAJtPc7TFF0OvO11iJrM7E4zWwP8GJ3JiiirY11UnPFoKswsGXgZ+GWtfyF4yjlXGTodnAMMDV2a8JSZnQFsdM7N9jrLARzjnBtM8BL61WZ2nNeBQgLAYOAR59wgYBfeXbqpk5nFAmcBL3qdZa/QGKKxQFegA5BkZpd4myrIOZcP/JngpaV3gPkEhyFIM2FmtxD8M33O6yw1Oeducc51JJjrmsY8dksrWQV8/19OOUTPqfSoZ2YxBAvWc865V7zOU5fQJaWPiI6xbccAZ5nZtwQvTZ9oZs96G+n7nHNrQ183EhxXNNTbRNUKgIIaZyRfIli6oskYYI5zboPXQWo4GfjGObfJOVcOvAIc7XGmas65J51zg51zxxG8rPO115lq2WBm7QFCXzd6nKfJMLOfAGcAP3bROzfU88B5jXnAllayZgI9zKxr6F+hFwKTPM7UJJiZERwfk++cu8/rPDWZWebeT7OYWQLBXzRLvE0FzrkJzrkc51wXgv+vfeici4qzCgBmlmRmKXufA6cSvKTjOefcemCNmfUKrToJ+MrDSHW5iCi6VBiyGhhuZomhv7MnESUfGAAws7ahr50IDuKOtu/fJOAnoec/AV73MEuTYWajgd8CZznnSrzOU1OtD1ecRSP/bgg05sG85pyrMLNrgCkEP3XzT+fcYo9jVTOz/wAnAG3MrAC4zTn3pLepqh0DjAMWhsY+AfzOOTfZw0x7tQeeDn161Ae84JyLuukSolAW8GrwdzEB4Hnn3DveRvqea4HnQv8gWglc5nGeaqExRacAv/A6S03Ouelm9hIwh+Blm7lE12zcL5tZa6AcuNo5t82rIHX9vAXuAV4ws58RLKwXRFG2rcBDQCbwlpnNc86dFiXZJgBxwHuhnyfTnHNXRkm200P/WKsCVgGNmkszvouIiIhEQEu7XCgiIiLSKFSyRERERCJAJUtEREQkAlSyRERERCJAJUtEREQkAlSyRERERCJAJUtEREQkAlSyRERERCLg/wPdQoHdrGrK7wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(range(digit_pca1.shape[1]) ,pca1.explained_variance_ratio_)\n",
    "plt.xticks(range(digit_pca1.shape[1]))\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "a=[]\n",
    "for i in range(64):\n",
    "    a.append(np.var(digit_new[:,i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9531250000000011\n",
      "61.00000000000006\n",
      "61.0\n"
     ]
    }
   ],
   "source": [
    "print(np.var(digit_new).sum())\n",
    "print(sum(a))\n",
    "print(np.round(pca.explained_variance_.sum()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'PC2')"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(digit_pca1[:,0],digit_pca1[:,1],c=digit.target,edgecolor = 'black', alpha =0.5,cmap = plt.cm.get_cmap('Accent',10))\n",
    "plt.xlabel(\"PC1\")\n",
    "plt.ylabel(\"PC2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7.345 5.835 5.154 3.966 2.966 2.572 2.406 2.069 1.83  1.789 1.698 1.573\n",
      " 1.388 1.359]\n"
     ]
    }
   ],
   "source": [
    "print(np.round(pca1.explained_variance_,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14\n"
     ]
    }
   ],
   "source": [
    "print(pca1.n_components_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.38169509867702145"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca1.noise_variance_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.14853027e+02, 1.02374513e+02, 9.62107804e+01, 8.43999988e+01,\n",
       "       7.29901087e+01, 6.79661076e+01, 6.57357810e+01, 6.09535699e+01,\n",
       "       5.73285263e+01, 5.66919151e+01, 5.52207542e+01, 5.31496988e+01,\n",
       "       4.99411577e+01, 4.94101975e+01, 4.87181644e+01, 4.58066808e+01,\n",
       "       4.41169066e+01, 4.23745489e+01, 4.18329026e+01, 4.04030531e+01,\n",
       "       3.84396124e+01, 3.73396975e+01, 3.57485095e+01, 3.40493828e+01,\n",
       "       3.26972794e+01, 3.21775889e+01, 3.07572734e+01, 3.02837051e+01,\n",
       "       2.95703806e+01, 2.86052359e+01, 2.82021522e+01, 2.75400136e+01,\n",
       "       2.67730260e+01, 2.65031620e+01, 2.54609018e+01, 2.50218124e+01,\n",
       "       2.39581918e+01, 2.29813625e+01, 2.23014224e+01, 2.15373702e+01,\n",
       "       2.10974689e+01, 2.08631842e+01, 1.97680870e+01, 1.93277180e+01,\n",
       "       1.89568789e+01, 1.84646678e+01, 1.77856004e+01, 1.74091710e+01,\n",
       "       1.68552602e+01, 1.60322561e+01, 1.54675990e+01, 1.49391305e+01,\n",
       "       1.46394964e+01, 1.41756213e+01, 1.35682641e+01, 1.32944400e+01,\n",
       "       1.27268626e+01, 1.21701581e+01, 1.17103237e+01, 1.06615266e+01,\n",
       "       9.51170303e+00, 1.88304151e-14, 8.37161114e-15, 8.30748733e-15])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca.singular_values_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}