Z30G0D/gist:70728f88a218371097e91e6ee3caa876

## gistfile1.txt
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy.io import loadmat\n",
    "import pandas\n",
    "import matplotlib.pyplot as plt\n",
    "from load_matlab_csv import *\n",
    "from IPython.display import display\n",
    "from scipy.spatial.distance import pdist, squareform\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((12555, 155), (12555, 2))"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Opening features and labels\n",
    "#features are created using the extractFeatures function in Matlab , converted to \"writetable\" function in Matlab and imported using \n",
    "# load_matlab_csv function\n",
    "\n",
    "scalar_features, windows_features = load_matlab_csv(\"features.txt\")\n",
    "scalar_features.shape,windows_features.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now have have the windowsr_features for array shaped features.<br>\n",
    "scalar_features contains all the scalar features, let's get rid of missing (or NAN) values.<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "userID                     0\n",
       "expID                      0\n",
       "i                          0\n",
       "j                          0\n",
       "p                          0\n",
       "qualitys1Spot              0\n",
       "periodSize                 0\n",
       "S1p                        0\n",
       "S2p                      267\n",
       "S1pOverS2p               267\n",
       "S1pS1wOverS2pS2w         267\n",
       "S1w                      267\n",
       "S2w                      267\n",
       "S1wOverS2w               267\n",
       "S2_S1_Int                  0\n",
       "S1_S2_Int                  0\n",
       "LVDT                       0\n",
       "LVST                       0\n",
       "meanAbs                    0\n",
       "meanAbs2                   0\n",
       "meanSound                  0\n",
       "meanSound2                 0\n",
       "meanSalo                   0\n",
       "meanSalo2                  0\n",
       "RatioMaxMeanAbs         4691\n",
       "RatioMeanOverMaxAbs     4691\n",
       "RatioMeanMeanAbs        4691\n",
       "freqBin4                   0\n",
       "freqBin5                   0\n",
       "freqBin6                   0\n",
       "freqBin7                   0\n",
       "freqBin8                   0\n",
       "freqBin9                   0\n",
       "freqBin10                  0\n",
       "freqBin11                  0\n",
       "freqBin12                  0\n",
       "GRLT3                      0\n",
       "RR                         0\n",
       "RR_QF                      0\n",
       "RespPhase                  0\n",
       "RespInExRatio              0\n",
       "zeroCrossingsX             0\n",
       "zeroCrossingsY             0\n",
       "KTEmuX                     0\n",
       "KTEsigX                    0\n",
       "KTEiqrX                    0\n",
       "KTEskewX                  18\n",
       "KTEkurtX                  18\n",
       "KTEmuY                     0\n",
       "KTEsigY                    0\n",
       "KTEiqrY                    0\n",
       "KTEskewY                  18\n",
       "KTEkurtY                  18\n",
       "enX20                      0\n",
       "enY20                      0\n",
       "enX25                      0\n",
       "enY25                      0\n",
       "enX30                      0\n",
       "enY30                      0\n",
       "enX35                      0\n",
       "enY35                      0\n",
       "enX40                      0\n",
       "enY40                      0\n",
       "enX20PerP                  0\n",
       "enY20PerP                  0\n",
       "enX25PerP                  0\n",
       "enY25PerP                  0\n",
       "enX30PerP                  0\n",
       "enY30PerP                  0\n",
       "enX35PerP                  0\n",
       "enY35PerP                  0\n",
       "enX40PerP                  0\n",
       "enY40PerP                  0\n",
       "alpha1S1                   0\n",
       "alpha2S1                  36\n",
       "alpha1S2                   0\n",
       "alpha2S2                  36\n",
       "alpha1S1S2                 0\n",
       "alpha2S1S2                 0\n",
       "hS1                        0\n",
       "hS2                        0\n",
       "hS1S2                      0\n",
       "PatternCount               0\n",
       "EnSymbX                    0\n",
       "EnSymbY                    0\n",
       "PatternCountSymbX          0\n",
       "PatternCountSymbY          0\n",
       "sEnX                       0\n",
       "sEnY                       0\n",
       "SampleEntropy              0\n",
       "aire                       0\n",
       "minSemAxis                 0\n",
       "majSemAxis                 0\n",
       "phi                        0\n",
       "airePerP                   0\n",
       "minSemAxisPerP             0\n",
       "majSemAxisPerP             0\n",
       "phiPerP                    0\n",
       "bOverA                   153\n",
       "cOverA                 12474\n",
       "dOverA                 12474\n",
       "eOverA                   153\n",
       "AgeIndex                 153\n",
       "abTime                  9396\n",
       "acTime                 12555\n",
       "adTime                 12555\n",
       "aeTime                  9909\n",
       "bcTime                 12555\n",
       "bdTime                 12555\n",
       "beTime                  9909\n",
       "cdTime                 12555\n",
       "ceTime                 12555\n",
       "deTime                 12555\n",
       "bOverAVAR                153\n",
       "cOverAVAR              12474\n",
       "dOverAVAR              12474\n",
       "eOverAVAR                153\n",
       "AgeIndexVAR              153\n",
       "abTimeVAR               9396\n",
       "acTimeVAR              12555\n",
       "adTimeVAR              12555\n",
       "aeTimeVAR               9909\n",
       "bcTimeVAR              12555\n",
       "bdTimeVAR              12555\n",
       "beTimeVAR               9909\n",
       "cdTimeVAR              12555\n",
       "ceTimeVAR              12555\n",
       "deTimeVAR              12555\n",
       "peak2Notch               153\n",
       "notchOverPeak            153\n",
       "PressureIndex          10206\n",
       "arcPI                    153\n",
       "PressureIndex2           153\n",
       "areaRatio                702\n",
       "peak2NotchVAR            153\n",
       "notchOverPeakVAR         153\n",
       "PressureIndexVAR       10206\n",
       "arcPIVAR                 153\n",
       "areaRatioVAR             702\n",
       "pir                      153\n",
       "pirVAR                   153\n",
       "PP                       153\n",
       "PN                       153\n",
       "NP                       153\n",
       "NN                       153\n",
       "PPvar                    153\n",
       "PNvar                    153\n",
       "NPvar                    153\n",
       "NNvar                    153\n",
       "sysCuff                    0\n",
       "diaCuff                    0\n",
       "sys                        0\n",
       "dia                        0\n",
       "sysPTT                     0\n",
       "diaPTT                     0\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "NaN_number = scalar_features.isna().sum()\n",
    "pandas.options.display.max_rows = None\n",
    "display(NaN_number)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's get rid of the features(columns) that contain 153 NAN and up since they are not very informative with that many missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "userID                 0\n",
       "expID                  0\n",
       "i                      0\n",
       "j                      0\n",
       "p                      0\n",
       "qualitys1Spot          0\n",
       "periodSize             0\n",
       "S1p                    0\n",
       "S2_S1_Int              0\n",
       "S1_S2_Int              0\n",
       "LVDT                   0\n",
       "LVST                   0\n",
       "meanAbs                0\n",
       "meanAbs2               0\n",
       "meanSound              0\n",
       "meanSound2             0\n",
       "meanSalo               0\n",
       "meanSalo2              0\n",
       "freqBin4               0\n",
       "freqBin5               0\n",
       "freqBin6               0\n",
       "freqBin7               0\n",
       "freqBin8               0\n",
       "freqBin9               0\n",
       "freqBin10              0\n",
       "freqBin11              0\n",
       "freqBin12              0\n",
       "GRLT3                  0\n",
       "RR                     0\n",
       "RR_QF                  0\n",
       "RespPhase              0\n",
       "RespInExRatio          0\n",
       "zeroCrossingsX         0\n",
       "zeroCrossingsY         0\n",
       "KTEmuX                 0\n",
       "KTEsigX                0\n",
       "KTEiqrX                0\n",
       "KTEskewX              18\n",
       "KTEkurtX              18\n",
       "KTEmuY                 0\n",
       "KTEsigY                0\n",
       "KTEiqrY                0\n",
       "KTEskewY              18\n",
       "KTEkurtY              18\n",
       "enX20                  0\n",
       "enY20                  0\n",
       "enX25                  0\n",
       "enY25                  0\n",
       "enX30                  0\n",
       "enY30                  0\n",
       "enX35                  0\n",
       "enY35                  0\n",
       "enX40                  0\n",
       "enY40                  0\n",
       "enX20PerP              0\n",
       "enY20PerP              0\n",
       "enX25PerP              0\n",
       "enY25PerP              0\n",
       "enX30PerP              0\n",
       "enY30PerP              0\n",
       "enX35PerP              0\n",
       "enY35PerP              0\n",
       "enX40PerP              0\n",
       "enY40PerP              0\n",
       "alpha1S1               0\n",
       "alpha2S1              36\n",
       "alpha1S2               0\n",
       "alpha2S2              36\n",
       "alpha1S1S2             0\n",
       "alpha2S1S2             0\n",
       "hS1                    0\n",
       "hS2                    0\n",
       "hS1S2                  0\n",
       "PatternCount           0\n",
       "EnSymbX                0\n",
       "EnSymbY                0\n",
       "PatternCountSymbX      0\n",
       "PatternCountSymbY      0\n",
       "sEnX                   0\n",
       "sEnY                   0\n",
       "SampleEntropy          0\n",
       "aire                   0\n",
       "minSemAxis             0\n",
       "majSemAxis             0\n",
       "phi                    0\n",
       "airePerP               0\n",
       "minSemAxisPerP         0\n",
       "majSemAxisPerP         0\n",
       "phiPerP                0\n",
       "bOverA               153\n",
       "eOverA               153\n",
       "AgeIndex             153\n",
       "bOverAVAR            153\n",
       "eOverAVAR            153\n",
       "AgeIndexVAR          153\n",
       "peak2Notch           153\n",
       "notchOverPeak        153\n",
       "arcPI                153\n",
       "PressureIndex2       153\n",
       "peak2NotchVAR        153\n",
       "notchOverPeakVAR     153\n",
       "arcPIVAR             153\n",
       "pir                  153\n",
       "pirVAR               153\n",
       "PP                   153\n",
       "PN                   153\n",
       "NP                   153\n",
       "NN                   153\n",
       "PPvar                153\n",
       "PNvar                153\n",
       "NPvar                153\n",
       "NNvar                153\n",
       "sysCuff                0\n",
       "diaCuff                0\n",
       "sys                    0\n",
       "dia                    0\n",
       "sysPTT                 0\n",
       "diaPTT                 0\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "max_nan_value_count = 154\n",
    "scalar_features = scalar_features.drop(scalar_features.columns[scalar_features.apply(lambda col: col.isnull().sum() > max_nan_value_count)], axis=1)\n",
    "\n",
    "NaN_number = scalar_features.isna().sum()\n",
    "pandas.options.display.max_rows = None\n",
    "display(NaN_number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12348, 118)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scalar_features = scalar_features.dropna() #drop **rows** with NAN\n",
    "scalar_features.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "left with 12348 and 113 features(5 first columns are i,j,p, user ID and exp ID).<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## group by i ,j , p , userID or expID\n",
    "# features_titles = scalar_features.columns.values[5:]\n",
    "# scalar_features_grouped= scalar_features.groupby(['userID', 'i'])[features_titles].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seperation between ppg_features, speckle features and blood pressure (preidcted variable)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((12348, 23), (12348, 6), (12348, 89))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scalar_features.columns.get_loc(\"bOverA\")\n",
    "speckle_features= scalar_features.iloc[:, :scalar_features.columns.get_loc(\"bOverA\")]\n",
    "ppg_features = scalar_features.iloc[:, scalar_features.columns.get_loc(\"bOverA\"):scalar_features.columns.get_loc(\"sysCuff\")]\n",
    "BP_features = scalar_features.iloc[:, scalar_features.columns.get_loc(\"sysCuff\"):]\n",
    "ppg_features.shape,BP_features.shape,speckle_features.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok, left with 23 features for ppg and 89 features for speckle, we also have our predicted variable (BP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def corrmatrix(correlations_frame):\n",
    "    correlations = correlations_frame.corr()\n",
    "    titles = correlations_frame.columns.values\n",
    "    # plot correlation matrix\n",
    "    fig = plt.figure(figsize=(20, 20))\n",
    "    ax = fig.add_subplot(111)\n",
    "    cax = ax.matshow(correlations, vmin=-1, vmax=1)\n",
    "    fig.colorbar(cax)\n",
    "    ticks = np.arange(0,correlations_frame.shape[1],1)\n",
    "    ax.set_xticks(ticks)\n",
    "    ax.set_yticks(ticks)\n",
    "    plt.xticks(rotation=90)\n",
    "    ax.set_xticklabels(titles)\n",
    "    ax.set_yticklabels(titles)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlations_frame = pandas.concat([ppg_features,BP_features],axis=1)\n",
    "corrmatrix(correlations_frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlations_frame = pandas.concat([speckle_features,BP_features],axis=1)\n",
    "corrmatrix(correlations_frame)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's check all of the correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "freqBin9            -7.391700e-01\n",
       "freqBin10           -6.598251e-01\n",
       "majSemAxis          -6.527226e-01\n",
       "freqBin5            -6.370617e-01\n",
       "freqBin8            -6.113788e-01\n",
       "majSemAxisPerP      -6.042250e-01\n",
       "meanAbs             -5.967539e-01\n",
       "meanSalo            -5.961416e-01\n",
       "minSemAxis          -5.848759e-01\n",
       "freqBin6            -5.835449e-01\n",
       "freqBin7            -5.776733e-01\n",
       "freqBin11           -5.652277e-01\n",
       "PressureIndex2      -5.575553e-01\n",
       "minSemAxisPerP      -5.405849e-01\n",
       "NN                  -5.387352e-01\n",
       "aire                -5.195670e-01\n",
       "freqBin12           -5.130302e-01\n",
       "S1p                 -4.855392e-01\n",
       "freqBin4            -4.849168e-01\n",
       "meanSound           -4.661839e-01\n",
       "meanAbs2            -4.612791e-01\n",
       "KTEmuX              -4.553465e-01\n",
       "airePerP            -4.540131e-01\n",
       "meanSalo2           -4.523255e-01\n",
       "KTEsigX             -4.253748e-01\n",
       "KTEiqrX             -3.967255e-01\n",
       "KTEmuY              -3.932909e-01\n",
       "RR                  -3.763083e-01\n",
       "expID               -3.757049e-01\n",
       "meanSound2          -3.750585e-01\n",
       "KTEsigY             -3.741875e-01\n",
       "KTEiqrY             -3.698486e-01\n",
       "hS1S2               -2.707120e-01\n",
       "peak2Notch          -2.524711e-01\n",
       "RR_QF               -2.477462e-01\n",
       "notchOverPeak       -2.041049e-01\n",
       "i                   -2.007798e-01\n",
       "KTEskewY            -1.726243e-01\n",
       "PatternCountSymbY   -1.483643e-01\n",
       "AgeIndex            -1.400494e-01\n",
       "NPvar               -1.283336e-01\n",
       "KTEkurtY            -1.279129e-01\n",
       "KTEskewX            -1.220831e-01\n",
       "RespInExRatio       -1.058694e-01\n",
       "phiPerP             -9.389244e-02\n",
       "PN                  -9.110098e-02\n",
       "qualitys1Spot       -8.841453e-02\n",
       "hS1                 -8.590829e-02\n",
       "NNvar               -8.409881e-02\n",
       "hS2                 -8.066306e-02\n",
       "peak2NotchVAR       -7.582856e-02\n",
       "KTEkurtX            -7.555492e-02\n",
       "notchOverPeakVAR    -6.808311e-02\n",
       "bOverA              -6.362452e-02\n",
       "PNvar               -6.337716e-02\n",
       "p                   -6.047871e-02\n",
       "enX25               -3.344901e-02\n",
       "enY20               -2.795879e-02\n",
       "RespPhase           -2.659550e-02\n",
       "EnSymbX             -2.575467e-02\n",
       "eOverAVAR           -2.030149e-02\n",
       "phi                 -1.837832e-02\n",
       "pirVAR              -1.640209e-02\n",
       "enX30               -8.611264e-03\n",
       "enX20               -5.124698e-03\n",
       "zeroCrossingsX      -4.662531e-03\n",
       "enY25               -4.425077e-03\n",
       "j                    1.266672e-17\n",
       "arcPI                3.036538e-03\n",
       "enY25PerP            1.460051e-02\n",
       "alpha2S1S2           1.493545e-02\n",
       "enX20PerP            1.739231e-02\n",
       "arcPIVAR             2.493542e-02\n",
       "enX25PerP            3.491625e-02\n",
       "periodSize           3.948952e-02\n",
       "AgeIndexVAR          4.138650e-02\n",
       "alpha1S1             4.504675e-02\n",
       "PatternCount         4.727968e-02\n",
       "pir                  5.148254e-02\n",
       "S2_S1_Int            5.430631e-02\n",
       "LVDT                 7.231005e-02\n",
       "LVST                 7.347622e-02\n",
       "alpha2S2             8.949468e-02\n",
       "PatternCountSymbX    9.236819e-02\n",
       "alpha1S1S2           9.791530e-02\n",
       "enY20PerP            1.019123e-01\n",
       "GRLT3                1.030784e-01\n",
       "alpha1S2             1.112021e-01\n",
       "bOverAVAR            1.206583e-01\n",
       "enY35                1.359299e-01\n",
       "enY40                1.422447e-01\n",
       "enX40PerP            1.437276e-01\n",
       "enX40                1.457562e-01\n",
       "enX35                1.459160e-01\n",
       "S1_S2_Int            1.622780e-01\n",
       "alpha2S1             1.843004e-01\n",
       "enY30                1.850907e-01\n",
       "enY30PerP            1.922947e-01\n",
       "enY35PerP            1.951005e-01\n",
       "enX30PerP            1.963075e-01\n",
       "enY40PerP            2.197144e-01\n",
       "eOverA               2.283667e-01\n",
       "enX35PerP            2.561018e-01\n",
       "zeroCrossingsY       2.671982e-01\n",
       "NP                   3.049346e-01\n",
       "EnSymbY              3.920312e-01\n",
       "PPvar                4.084012e-01\n",
       "sEnX                 4.099899e-01\n",
       "diaPTT               4.211264e-01\n",
       "sysPTT               4.390896e-01\n",
       "SampleEntropy        4.721326e-01\n",
       "PP                   5.093825e-01\n",
       "sEnY                 5.241121e-01\n",
       "sysCuff              5.441170e-01\n",
       "sys                  7.428164e-01\n",
       "dia                  7.483266e-01\n",
       "userID               7.605716e-01\n",
       "diaCuff              1.000000e+00\n",
       "Name: diaCuff, dtype: float64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## find interesting correlation for the matrix\n",
    "correlations = scalar_features[scalar_features.columns[0:]].corr()['diaCuff']\n",
    "correlations.sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "expID               -8.210963e-01\n",
       "hS1S2               -6.933252e-01\n",
       "freqBin5            -5.852016e-01\n",
       "AgeIndex            -5.771143e-01\n",
       "freqBin10           -5.752940e-01\n",
       "LVDT                -5.513460e-01\n",
       "S1p                 -5.475776e-01\n",
       "freqBin11           -5.390084e-01\n",
       "pir                 -5.318574e-01\n",
       "bOverA              -5.278800e-01\n",
       "meanSound           -5.272509e-01\n",
       "KTEmuY              -5.251749e-01\n",
       "freqBin9            -5.222800e-01\n",
       "majSemAxis          -5.206129e-01\n",
       "freqBin4            -5.203712e-01\n",
       "freqBin8            -5.152257e-01\n",
       "freqBin6            -5.143102e-01\n",
       "freqBin12           -5.069037e-01\n",
       "KTEsigY             -5.020648e-01\n",
       "minSemAxis          -5.020377e-01\n",
       "KTEiqrY             -4.958868e-01\n",
       "meanAbs             -4.933961e-01\n",
       "minSemAxisPerP      -4.860320e-01\n",
       "meanSalo            -4.769828e-01\n",
       "majSemAxisPerP      -4.739576e-01\n",
       "aire                -4.738841e-01\n",
       "meanSound2          -4.709390e-01\n",
       "freqBin7            -4.553260e-01\n",
       "airePerP            -4.225908e-01\n",
       "phiPerP             -3.928616e-01\n",
       "meanAbs2            -3.869315e-01\n",
       "phi                 -3.866540e-01\n",
       "hS2                 -3.721507e-01\n",
       "hS1                 -3.591548e-01\n",
       "meanSalo2           -3.569722e-01\n",
       "RR                  -3.428120e-01\n",
       "PN                  -2.953441e-01\n",
       "RR_QF               -2.911906e-01\n",
       "NN                  -2.643855e-01\n",
       "enX20PerP           -2.485096e-01\n",
       "enY20               -2.476327e-01\n",
       "enX30               -2.397516e-01\n",
       "enX20               -2.366048e-01\n",
       "KTEsigX             -2.351359e-01\n",
       "PatternCountSymbY   -2.348539e-01\n",
       "enX25               -2.342416e-01\n",
       "enX25PerP           -2.259479e-01\n",
       "enY25               -2.151820e-01\n",
       "p                   -2.083273e-01\n",
       "peak2Notch          -2.065549e-01\n",
       "arcPIVAR            -1.886668e-01\n",
       "KTEskewX            -1.681166e-01\n",
       "RespInExRatio       -1.605694e-01\n",
       "PressureIndex2      -1.596741e-01\n",
       "KTEmuX              -1.489960e-01\n",
       "PatternCountSymbX   -1.412170e-01\n",
       "NPvar               -1.410295e-01\n",
       "KTEkurtX            -1.378334e-01\n",
       "i                   -1.359404e-01\n",
       "notchOverPeakVAR    -1.330634e-01\n",
       "enY20PerP           -1.267501e-01\n",
       "qualitys1Spot       -1.204199e-01\n",
       "KTEskewY            -1.170630e-01\n",
       "PNvar               -1.057596e-01\n",
       "KTEkurtY            -9.929070e-02\n",
       "enY30PerP           -9.036958e-02\n",
       "PatternCount        -8.357016e-02\n",
       "enY35PerP           -7.246532e-02\n",
       "alpha1S1            -5.134256e-02\n",
       "KTEiqrX             -4.688186e-02\n",
       "peak2NotchVAR       -3.830304e-02\n",
       "NNvar               -3.368845e-02\n",
       "enY40               -3.181139e-02\n",
       "enY35               -2.132919e-02\n",
       "RespPhase           -1.998134e-02\n",
       "enY30               -1.784287e-02\n",
       "enX40               -1.271739e-02\n",
       "alpha1S1S2          -1.228698e-02\n",
       "enX35               -5.374969e-03\n",
       "j                    1.935645e-18\n",
       "enY25PerP            8.918355e-03\n",
       "enX35PerP            1.002853e-02\n",
       "notchOverPeak        2.951481e-02\n",
       "eOverAVAR            3.245120e-02\n",
       "pirVAR               3.732021e-02\n",
       "arcPI                3.843760e-02\n",
       "alpha1S2             4.267851e-02\n",
       "EnSymbX              4.712313e-02\n",
       "S1_S2_Int            5.671080e-02\n",
       "AgeIndexVAR          8.246910e-02\n",
       "PP                   8.867909e-02\n",
       "bOverAVAR            1.024117e-01\n",
       "enX40PerP            1.159683e-01\n",
       "alpha2S1             1.182927e-01\n",
       "PPvar                1.378101e-01\n",
       "alpha2S1S2           1.563608e-01\n",
       "alpha2S2             1.627488e-01\n",
       "EnSymbY              2.406274e-01\n",
       "sEnX                 2.576353e-01\n",
       "zeroCrossingsX       2.648628e-01\n",
       "SampleEntropy        2.949884e-01\n",
       "sEnY                 3.512298e-01\n",
       "LVST                 3.568190e-01\n",
       "zeroCrossingsY       3.932126e-01\n",
       "NP                   4.121474e-01\n",
       "GRLT3                4.421451e-01\n",
       "S2_S1_Int            5.142772e-01\n",
       "sys                  5.238222e-01\n",
       "dia                  5.279259e-01\n",
       "diaCuff              5.441170e-01\n",
       "periodSize           5.953643e-01\n",
       "eOverA               5.981178e-01\n",
       "enX30PerP            6.195817e-01\n",
       "enY40PerP            6.455793e-01\n",
       "userID               6.492787e-01\n",
       "sysPTT               8.058512e-01\n",
       "diaPTT               8.082806e-01\n",
       "sysCuff              1.000000e+00\n",
       "Name: sysCuff, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlations = scalar_features[scalar_features.columns[0:]].corr()['sysCuff']\n",
    "correlations.sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "strongest correlations for PPG features are NN for diaCuff and Age Index for sysCuff. Let's check non linear correlations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "freqBin9   -0.73917\n",
       "Name: diaCuff, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlations_frame_corr= correlations_frame[['freqBin9','diaCuff']].corr().iloc[0::2,-1]\n",
    "correlations_frame_corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAEICAYAAABfz4NwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAGbNJREFUeJzt3Xu0ZGV55/HvL6iseEFQDohcbDRNHHBiKyeAcXTIaOTipUFH04wBNMxqNZIZM2YixEw0OmRh4mXJqDjtyAATBYkEJBFHWxwlzkCkQeROaLCRlk7T0spFDAo888d+j5Sn61yrzqUP389atWrXs99d+31rd5+n3vfde1eqCkmSfmmhKyBJWhxMCJIkwIQgSWpMCJIkwIQgSWpMCJIkwISgPpJcn+TQha7HQkpydJI7ktyf5AULXZ+JJHlxkltaPY9KsnuSS5Pcl+RDQ95XJfmVYb6nFhcTwmNMkg1JXj4u9qYk3xx7XVUHVNXXp3ifZe0PxOPmqKoL7YPAiVX15Kr69kJXZhLvAz7W6nkhsBr4AbBTVb1zYaum7Y0JQYvSIkg0zwKuX+A6TMf4ej4LuKG84lSzYELQNnp7EUkOSrIuyb1JNif5cCt2aXv+URuueFGSX0ryJ0luT3JXkrOTPLXnfY9r6+5O8l/G7ee9ST6f5K+S3Au8qe37siQ/SrIpyceSPKHn/SrJ77Uhk/uSvD/Jc9o29yY5r7f8uDb2rWuSHZPcD+wAfCfJrX22TZKPtO3uSXJNkucl+fX2GT2up+zrklw9xWdJkn+V5P+1tt6R5E0t/vUk/76n3M97c61uzwb+th2Dc4DjgT9qr8f3BA9J8k9JduiJHZ3kmp76Tfh5j3uvCevVXj83ydokW5PcnOQNPeuOTHJDO2bfT/KH/fah+WdC0FQ+Cny0qnYCngOc1+Ivbc87t+GKy4A3tcdv0v2hejLwMYAk+wOfAN4I7AE8Fdhz3L5WAp8HdgY+AzwM/AGwK/Ai4GXA743b5nDgQOAQ4I+ANW0fewPPA46ZoF1961pVD1bVk1uZ51fVc/ps+4rW/v1aXX8buLuqrgDuBn6rp+zvAP+rLff9LJPsA3wJ+G/ACLACuHqCev9cq9v3gFe3Y3AM3ef2F+31V8eVvxz4MfBvesL/DvhsW57O5z2lJE8C1rb33Y3uGHwiyQGtyKeBt1TVU+iO0ddmug/NDRPCY9OF7Vvgj5L8iO4P9UR+BvxKkl2r6v72R2UibwQ+XFW3VdX9wMnAqvaN+d8Cf1tV36yqnwJ/Cowf1risqi6sqkeq6idVdWVVXV5VD1XVBuC/A/963DYfqKp7q+p64DrgK23/99D9kZ1oQniyuk7lZ8BTgOcCqaobq2pTW3cWXRIgydOAw3j0D+5En+Ubga9W1TlV9bOquruqpkwIs3QOLUkmeQpwZIsxzc97Ol4FbKiq/9ne6yrgfLp/A9B9Dvsn2amqftjWaxEwITw2HVVVO489mPxb4Al034RvSnJFkldNUvaZwO09r28HHgfs3tbdMbaiqh6g+zbd647eF0n2S/J3bZjjXuDP6b699trcs/yTPq+fTH+T1XVSVfU1up7Px4HNSdYk2amt/ivg1UmeDLwB+PueZDHRZ7k3sM3Q1Bz5LPDaJDsCrwWuqqrbYdqf93Q8Czh43JeONwLPaOtfR5eIbk/yjSQvGrRRGg4TgiZVVbe0oYjdgA8An29DAv0mLe+k+2MwZh/gIbo/0puAvcZWJPll4Onjdzfu9enATcDyNszyx0Bm35pp13VKVXVaVR0IHED3R/4/t/j3gcuAo4FjeXS4aLLP8g66IaR+fgw8sef1MyYoNy1VdQNd8juCXxwugpl93pPV6w7gG71fOtoQ1ttaHa6oqpV0n8OFPDoMqQVmQtCkkvxOkpGqegT4UQs/DGwBHqEbfx9zDvAHSfZt35D/HPhcVT1ENzfw6iS/0SYq/4yp/7g/BbgXuD/Jc4G3Da1hk9d1Um3y+OAkj6f7w/jPdJ/JmLPp5jP+JXBBz3YTfZafAV6e5A1JHpfk6UlWtPVX032jf2K6awBOGKjVnc8C/4FuHuSve+Iz+bwnq9ffAfslOTbJ49vj15P8iyRPSPLGJE+tqp+1/T3cbweafyYETeVw4Pp0Z958FFhVVf/chnxOAf5vGxY4BDiD7hvxpcB36f5Q/j5AG+P/feBcut7CfcBdwIOT7PsP6b7F3gd8CvjcENs1YV2nYadWnx/Sfdu+m+66hTEX0PU+LqiqH/fEJ/osv0c3hPJOYCvdH9vnt20+AvyUrudyFl3yGNQ5wKHA16rqBz3xmXzeE9arqu6jm3hfRdcT+ye6HtGOrcixwIY2LPVW2pyLFl48XVkLoX0r/xHd8MR3F7o+w9ZOCX3L+DN9pMXMHoLmTZJXtyGGJ9F9o74W2LCwtRq+JK+jmw/xdEptVxb6alA9tqykG6YJsI5uyGRJdVGTfB3YHzi2zRVI2w2HjCRJgENGkqRmyiGjJHvTnUb3DLrTDNdU1UfbVZifA5bRjQO/oap+mCR0Z1AcCTwAvGnsSsQkxwN/0t76v1bVWVPtf9ddd61ly5bNsFmS9Nh15ZVX/qCqRma63ZRDRkn2APaoqqvape5XAkfR3Qdma1WdmuQkYJeqeleSI+lO3zsSOJju3i0HtwSyDhilm3C7Ejiwqn442f5HR0dr3bp1M22XJD1mJbmyqkZnut2UQ0ZVtWnsG347v/hGupuSraQ7/5j2fFRbXgmcXZ3LgZ1bUjkMWFtVW1sSWEt3XrYkaRGY0RxCkmV0Nwv7B2D3sXu0tOfdWrE9+cV70mxssYni/fazOt1tgtdt2bJlJlWUJM3StBNCu5DofOAdVXXvZEX7xGqS+LbBqjVVNVpVoyMjMx4GkyTNwrQSQrtny/nAZ6rqb1p4cxsKGptnuKvFN9LdvXHMXnSXr08UlyQtAlMmhHbW0KeBG6vqwz2rLqL7dSba8xd64selcwhwTxtS+jLwiiS7JNmF7l4nXx5SOyRJA5rOlcovprsZ1bVpPwVId1vcU4HzkpxA96tNr2/rLqY7w2g93Wmnbwaoqq1J3g9c0cq9r6q2DqUVkqSBLforlT3tVJJmZs5OO5UkPTaYECRJwBK/2+myk7447bIbTn3lHNZEkhY/ewiSJMCEIElqTAiSJMCEIElqTAiSJMCEIElqTAiSJMCEIElqTAiSJMCEIElqTAiSJMCEIElqTAiSJMCEIElqpvObymckuSvJdT2xzyW5uj02jP20ZpJlSX7Ss+6TPdscmOTaJOuTnNZ+q1mStEhM5/cQzgQ+Bpw9Fqiq3x5bTvIh4J6e8rdW1Yo+73M6sBq4nO53lw8HvjTzKkuS5sKUPYSquhTY2m9d+5b/BuCcyd4jyR7ATlV1WXU/4nw2cNTMqytJmiuDziG8BNhcVbf0xPZN8u0k30jykhbbE9jYU2Zji0mSFolBf0LzGH6xd7AJ2Keq7k5yIHBhkgOAfvMFNdGbJllNN7zEPvvsM2AVJUnTMeseQpLHAa8FPjcWq6oHq+rutnwlcCuwH12PYK+ezfcC7pzovatqTVWNVtXoyMjIbKsoSZqBQYaMXg7cVFU/HwpKMpJkh7b8bGA5cFtVbQLuS3JIm3c4DvjCAPuWJA3ZdE47PQe4DPjVJBuTnNBWrWLbyeSXAtck+Q7weeCtVTU2If024H8A6+l6Dp5hJEmLyJRzCFV1zATxN/WJnQ+cP0H5dcDzZlg/SdI88UplSRJgQpAkNSYESRJgQpAkNSYESRJgQpAkNSYESRJgQpAkNSYESRJgQpAkNSYESRIw+O8hSJony0764rTLbjj1lXNYEy1V9hAkSYAJQZLUmBAkSYAJQZLUmBAkSYAJQZLUTOc3lc9IcleS63pi703y/SRXt8eRPetOTrI+yc1JDuuJH95i65OcNPymSJIGMZ0ewpnA4X3iH6mqFe1xMUCS/YFVwAFtm08k2SHJDsDHgSOA/YFjWllJ0iIx5YVpVXVpkmXTfL+VwLlV9SDw3STrgYPauvVVdRtAknNb2RtmXGNJ0pwYZA7hxCTXtCGlXVpsT+COnjIbW2yiuCRpkZhtQjgdeA6wAtgEfKjF06dsTRLvK8nqJOuSrNuyZcssqyhJmolZJYSq2lxVD1fVI8CneHRYaCOwd0/RvYA7J4lP9P5rqmq0qkZHRkZmU0VJ0gzNKiEk2aPn5dHA2BlIFwGrkuyYZF9gOfAt4ApgeZJ9kzyBbuL5otlXW5I0bFNOKic5BzgU2DXJRuA9wKFJVtAN+2wA3gJQVdcnOY9usvgh4O1V9XB7nxOBLwM7AGdU1fVDb40kadamc5bRMX3Cn56k/CnAKX3iFwMXz6h2kqR545XKkiTAhCBJakwIkiTAn9DUPJvJz0CCPwUpzSd7CJIkwIQgSWocMlJfMxnacVhHWhrsIUiSABOCJKkxIUiSABOCJKkxIUiSAM8y2q55JpCkYbKHIEkCTAiSpMaEIEkCTAiSpMaEIEkCppEQkpyR5K4k1/XE/jLJTUmuSXJBkp1bfFmSnyS5uj0+2bPNgUmuTbI+yWlJMjdNkiTNxnR6CGcCh4+LrQWeV1W/BvwjcHLPulurakV7vLUnfjqwGljeHuPfU5K0gKZMCFV1KbB1XOwrVfVQe3k5sNdk75FkD2Cnqrqsqgo4GzhqdlWWJM2FYcwh/C7wpZ7X+yb5dpJvJHlJi+0JbOwps7HF+kqyOsm6JOu2bNkyhCpKkqYyUEJI8m7gIeAzLbQJ2KeqXgD8J+CzSXYC+s0X1ETvW1Vrqmq0qkZHRkYGqaIkaZpmfeuKJMcDrwJe1oaBqKoHgQfb8pVJbgX2o+sR9A4r7QXcOdt9S5KGb1Y9hCSHA+8CXlNVD/TER5Ls0JafTTd5fFtVbQLuS3JIO7voOOALA9dekjQ0U/YQkpwDHArsmmQj8B66s4p2BNa2s0cvb2cUvRR4X5KHgIeBt1bV2IT02+jOWPplujmH3nkHSdICmzIhVNUxfcKfnqDs+cD5E6xbBzxvRrWTJM0br1SWJAEmBElSY0KQJAEmBElSY0KQJAEmBElSY0KQJAEmBElSY0KQJAEmBElSY0KQJAEmBElSY0KQJAEmBElSY0KQJAEmBElSY0KQJAEmBElSM62EkOSMJHclua4n9rQka5Pc0p53afEkOS3J+iTXJHlhzzbHt/K3JDl++M2RJM3WdHsIZwKHj4udBFxSVcuBS9prgCOA5e2xGjgdugQCvAc4GDgIeM9YEpEkLbxpJYSquhTYOi68EjirLZ8FHNUTP7s6lwM7J9kDOAxYW1Vbq+qHwFq2TTKSpAUyyBzC7lW1CaA979biewJ39JTb2GITxbeRZHWSdUnWbdmyZYAqSpKmay4mldMnVpPEtw1Wramq0aoaHRkZGWrlJEn9DZIQNrehINrzXS2+Edi7p9xewJ2TxCVJi8AgCeEiYOxMoeOBL/TEj2tnGx0C3NOGlL4MvCLJLm0y+RUtJklaBB43nUJJzgEOBXZNspHubKFTgfOSnAB8D3h9K34xcCSwHngAeDNAVW1N8n7gilbufVU1fqJakrRAppUQquqYCVa9rE/ZAt4+wfucAZwx7dpJkuaNVypLkgATgiSpMSFIkgATgiSpMSFIkgATgiSpMSFIkgATgiSpMSFIkgATgiSpMSFIkgATgiSpMSFIkgATgiSpMSFIkgATgiSpMSFIkgATgiSpmXVCSPKrSa7uedyb5B1J3pvk+z3xI3u2OTnJ+iQ3JzlsOE2QJA3DtH5TuZ+quhlYAZBkB+D7wAXAm4GPVNUHe8sn2R9YBRwAPBP4apL9qurh2dZBkjQ8wxoyehlwa1XdPkmZlcC5VfVgVX0XWA8cNKT9S5IGNKyEsAo4p+f1iUmuSXJGkl1abE/gjp4yG1tsG0lWJ1mXZN2WLVuGVEVJ0mQGTghJngC8BvjrFjodeA7dcNIm4ENjRftsXv3es6rWVNVoVY2OjIwMWkVJ0jQMo4dwBHBVVW0GqKrNVfVwVT0CfIpHh4U2Anv3bLcXcOcQ9i9JGoJhJIRj6BkuSrJHz7qjgeva8kXAqiQ7JtkXWA58awj7lyQNwazPMgJI8kTgt4C39IT/IskKuuGgDWPrqur6JOcBNwAPAW/3DCNJWjwGSghV9QDw9HGxYycpfwpwyiD7lCTNDa9UliQBJgRJUmNCkCQBJgRJUmNCkCQBA55lJG2vlp30xWmX3XDqK+ewJtLiYQ9BkgSYECRJjQlBkgSYECRJjQlBkgR4lpEkzZvFfnabPQRJEmAPQRKL/5ur5oc9BEkSYEKQJDUmBEkSYEKQJDUDJ4QkG5Jcm+TqJOta7GlJ1ia5pT3v0uJJclqS9UmuSfLCQfcvSRqOYfUQfrOqVlTVaHt9EnBJVS0HLmmvAY4AlrfHauD0Ie1fkjSguRoyWgmc1ZbPAo7qiZ9dncuBnZPsMUd1kCTNwDASQgFfSXJlktUttntVbQJoz7u1+J7AHT3bbmyxX5BkdZJ1SdZt2bJlCFWUJE1lGBemvbiq7kyyG7A2yU2TlE2fWG0TqFoDrAEYHR3dZr0kafgG7iFU1Z3t+S7gAuAgYPPYUFB7vqsV3wjs3bP5XsCdg9ZBkjS4gRJCkiclecrYMvAK4DrgIuD4Vux44Att+SLguHa20SHAPWNDS5KkhTXokNHuwAVJxt7rs1X1v5NcAZyX5ATge8DrW/mLgSOB9cADwJsH3L8kaUgGSghVdRvw/D7xu4GX9YkX8PZB9ilJmhteqSxJAkwIkqTG30OQFtBMfodAmmv2ECRJgAlBktSYECRJgAlBktSYECRJgAlBktSYECRJgAlBktSYECRJgAlBktR46wppyLwdhbZX9hAkSYA9BGlJspei2bCHIEkCTAiSpGbWCSHJ3kn+T5Ibk1yf5D+2+HuTfD/J1e1xZM82JydZn+TmJIcNowGSpOEYZA7hIeCdVXVVkqcAVyZZ29Z9pKo+2Fs4yf7AKuAA4JnAV5PsV1UPD1AHac45Hq/Hiln3EKpqU1Vd1ZbvA24E9pxkk5XAuVX1YFV9F1gPHDTb/UuShmsocwhJlgEvAP6hhU5Mck2SM5Ls0mJ7Anf0bLaRCRJIktVJ1iVZt2XLlmFUUZI0hYETQpInA+cD76iqe4HTgecAK4BNwIfGivbZvPq9Z1WtqarRqhodGRkZtIqSpGkYKCEkeTxdMvhMVf0NQFVtrqqHq+oR4FM8Oiy0Edi7Z/O9gDsH2b8kaXgGOcsowKeBG6vqwz3xPXqKHQ1c15YvAlYl2THJvsBy4Fuz3b8kabgGOcvoxcCxwLVJrm6xPwaOSbKCbjhoA/AWgKq6Psl5wA10Zyi93TOMJGnxmHVCqKpv0n9e4OJJtjkFOGW2+5S08GZyGu6GU185hzXRsHmlsiQJMCFIkhrvdqolwyuKF5+5PCYORw2fCUHSdmmxfAFYSonJISNJEmBCkCQ1JgRJEmBCkCQ1TiprYHM5ubdYJg6lxwJ7CJIkwIQgSWpMCJIkwDkESRrIUprnsocgSQJMCJKkxoQgSQJMCJKkxoQgSQIWICEkOTzJzUnWJzlpvvcvSepvXhNCkh2AjwNHAPsDxyTZfz7rIEnqb757CAcB66vqtqr6KXAusHKe6yBJ6mO+L0zbE7ij5/VG4ODxhZKsBla3l/cnuXmuK5YPzOnb7wr8YE73MIWl3r55sNTbuNTbB9tZG2fxf7a3fc+azT7nOyGkT6y2CVStAdbMfXXmR5J1VTW60PWYK0u9fbD027jU2wdLv43DaN98DxltBPbueb0XcOc810GS1Md8J4QrgOVJ9k3yBGAVcNE810GS1Me8DhlV1UNJTgS+DOwAnFFV189nHRbIkhn+msBSbx8s/TYu9fbB0m/jwO1L1TZD+JKkxyCvVJYkASYESVJjQhhQkjOS3JXkup7Y05KsTXJLe96lxZPktHbbjmuSvHDhaj59M2zjoUnuSXJ1e/zpwtV8eiZo3+uTXJ/kkSSj48qf3I7hzUkOm/8az9xM2phkWZKf9BzDTy5MrWdmgjb+ZZKb2v+3C5Ls3LNuuzqOM2nfbI+hCWFwZwKHj4udBFxSVcuBS9pr6G7Zsbw9VgOnz1MdB3Um028jwN9X1Yr2eN881XEQZ7Jt+64DXgtc2htst1pZBRzQtvlEuyXLYncm02xjc2vPMXzrXFduSM5k2zauBZ5XVb8G/CNwMmy3x/FMptm+ZsbH0IQwoKq6FNg6LrwSOKstnwUc1RM/uzqXAzsn2WN+ajp7M2zjdqdf+6rqxqrqd4X8SuDcqnqwqr4LrKe7JcuiNsM2bpcmaONXquqh9vJyumufYDs8jjNs36yYEObG7lW1CaA979bi/W7dsec8121YJmojwIuSfCfJl5IcsDDVmzNL6RhOZt8k307yjSQvWejKDMnvAl9qy0vxOPa2D2ZxDOf71hWPddO6dcd27irgWVV1f5IjgQvphsiWisfCMdwE7FNVdyc5ELgwyQFVde9CV2y2krwbeAj4zFioT7Ht9jj2ad+sjqE9hLmxeWwoqD3f1eJL6dYdfdtYVfdW1f1t+WLg8Ul2XbhqDt1SOoZ9tWGUu9vylcCtwH4LW6vZS3I88CrgjfXohVdL5jj2a99sj6EJYW5cBBzflo8HvtATP66dbXQIcM/YsMt2qG8bkzwjSdryQXT/xu5ekBrOjYuAVUl2TLIvXe/nWwtcp6FKMjI2wZrk2XRtvG1hazU7SQ4H3gW8pqoe6Fm1JI7jRO2b9TGsKh8DPIBz6LpnP6P71nEC8HS6M29uac9Pa2VD9wNBtwLXAqMLXf85aOOJwPXAd+gmuX5joes/y/Yd3ZYfBDYDX+4p/+52DG8Gjljo+g+7jcDreo7hVcCrF7r+A7RxPd1cwdXt8cnt9TjOpH2zPYbeukKSBDhkJElqTAiSJMCEIElqTAiSJMCEIElqTAiSJMCEIElq/j/sfWwnsT5yiQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(scalar_features.iloc[:,-6], bins='auto')  # arguments are passed to np.histogram\n",
    "plt.title(\"Histogram of syscuff values\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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.hist(scalar_features.iloc[:,-5], bins='auto')  # arguments are passed to np.histogram\n",
    "plt.title(\"Histogram of diacuff values\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "add features (delta T, stiffness index, crest time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def distcorr(column):\n",
    "    X= column\n",
    "    Y = scalar_features['diaCuff']\n",
    "    X = np.atleast_1d(X)\n",
    "    Y = np.atleast_1d(Y)\n",
    "    if np.prod(X.shape) == len(X):\n",
    "        X = X[:, None]\n",
    "    if np.prod(Y.shape) == len(Y):\n",
    "        Y = Y[:, None]\n",
    "    X = np.atleast_2d(X)\n",
    "    Y = np.atleast_2d(Y)\n",
    "    n = X.shape[0]\n",
    "    if Y.shape[0] != X.shape[0]:\n",
    "        raise NameError('Not equal sample numbers')\n",
    "    a = squareform(pdist(X))\n",
    "    b = squareform(pdist(Y))\n",
    "    A = a - a.mean(axis=0)[None, :] - a.mean(axis=1)[:, None] + a.mean()\n",
    "    B = b - b.mean(axis=0)[None, :] - b.mean(axis=1)[:, None] + b.mean()\n",
    "    dcov2_xy = (A * B).sum()/float(n * n)\n",
    "    dcov2_xx = (A * A).sum()/float(n * n)\n",
    "    dcov2_yy = (B * B).sum()/float(n * n)\n",
    "    dcor = np.sqrt(dcov2_xy)/np.sqrt(np.sqrt(dcov2_xx) * np.sqrt(dcov2_yy))\n",
    "    return dcor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pirVAR              0.172392\n",
       "arcPI               0.185321\n",
       "notchOverPeakVAR    0.189506\n",
       "peak2NotchVAR       0.189897\n",
       "NNvar               0.196319\n",
       "PNvar               0.209161\n",
       "NPvar               0.240197\n",
       "eOverAVAR           0.245751\n",
       "arcPIVAR            0.250088\n",
       "peak2Notch          0.251194\n",
       "AgeIndex            0.253422\n",
       "PN                  0.261102\n",
       "bOverA              0.272626\n",
       "eOverA              0.274141\n",
       "AgeIndexVAR         0.277888\n",
       "bOverAVAR           0.278662\n",
       "pir                 0.296747\n",
       "NP                  0.317300\n",
       "notchOverPeak       0.335206\n",
       "PPvar               0.461544\n",
       "PP                  0.531721\n",
       "PressureIndex2      0.545734\n",
       "NN                  0.549121\n",
       "dtype: float64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distance_correlations = ppg_features.apply(distcorr, axis=0)\n",
    "distance_correlations.sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best correlation is NN and PressureIndex2 feature, and still, not a very good one."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Consider for further PPG processing according to the next paragraph:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](capture.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}