# -*- coding: utf-8 -*-

"""

Matrix de caracteristicas de 5 registros PATOLOGICOS

Created on Thu May  3 07:09:12 2018

@author: Kevin Machado G.

Ref:

    [1] https://www.datacamp.com/community/blog/python-pandas-cheat-sheet

"""

import matplotlib.pyplot as plt

import numpy as np

# Data manipulation

import pandas as pd

# Own Library

import ppfunctions_1 as ppf

import os 

import scipy.io.wavfile as wf

# -----------------------------------------------------------------------------

print('importing all training-a data base')

# Looking for heart sounds data absolute path

l1=os.path.abspath('Data Base HS\\pathologic\\2.1.wav')

l1=l1.replace('\\','/')

l2=os.path.abspath('Data Base HS\\pathologic\\2.3.wav')

l2=l2.replace('\\','/')

l3=os.path.abspath('Data Base HS\\pathologic\\3.2.wav')

l3=l3.replace('\\','/')

l4=os.path.abspath('Data Base HS\\pathologic\\4.3.wav')

l4=l4.replace('\\','/')

l5=os.path.abspath('Data Base HS\\pathologic\\4.5.wav')

l5=l5.replace('\\','/')

# reading file

Fs1, data1 = wf.read(l1)

Fs2, data2 = wf.read(l2)

Fs3, data3 = wf.read(l3)

Fs4, data4 = wf.read(l4)

Fs5, data5 = wf.read(l5)

# Clear paths

del l1, l2, l3, l4, l5

#

duration1 = 1/Fs1*np.size(data1)

duration2 = 1/Fs2*np.size(data2)

duration3 = 1/Fs3*np.size(data3)

duration4 = 1/Fs4*np.size(data4)

duration5 = 1/Fs5*np.size(data5)

vt1 = np.linspace(0,duration1,np.size(data1)) # Vector time 1

vt2 = np.linspace(0,duration2,np.size(data2)) # Vector time 3

vt3 = np.linspace(0,duration3,np.size(data3)) # Vector time 5

vt4 = np.linspace(0,duration4,np.size(data4)) # Vector time 7

vt5 = np.linspace(0,duration5,np.size(data5)) # Vector time 9

data1 = ppf.vec_nor(data1)

data2 = ppf.vec_nor(data2)

data3 = ppf.vec_nor(data3)

data4 = ppf.vec_nor(data4)

data5 = ppf.vec_nor(data5)

pcgFFT1, vTfft1 = ppf.fft_k_N(data1, Fs1, 2000)

pcgFFT2, vTfft2 = ppf.fft_k_N(data2, Fs2, 2000)

pcgFFT3, vTfft3 = ppf.fft_k_N(data3, Fs3, 2000)

pcgFFT4, vTfft4 = ppf.fft_k_N(data4, Fs4, 2000)

pcgFFT5, vTfft5 = ppf.fft_k_N(data5, Fs5, 2000)

idx1 = (np.abs(vt1-5)).argmin()                # Find the index of time vector in 10 seconds

idx2 = (np.abs(vt2-5)).argmin()                # Find the index of time vector in 10 seconds

idx3 = (np.abs(vt3-5)).argmin()                # Find the index of time vector in 10 seconds

idx4 = (np.abs(vt4-5)).argmin()                # Find the index of time vector in 10 seconds

idx5 = (np.abs(vt5-5)).argmin()                # Find the index of time vector in 10 seconds

#

# -----------------------------------------------------------------------------

# Energy of vibratory signal spectrum

# 1. 0-5Hz, 2. 5-25Hz; 3. 25-120Hz; 4. 120-240Hz; 5. 240-500Hz; 6. 500-1000Hz; 7. 1000-2000Hz

EVS1 = ppf.E_VS(pcgFFT1, vTfft1, 'percentage')

EVS2 = ppf.E_VS(pcgFFT2, vTfft2, 'percentage')

EVS3 = ppf.E_VS(pcgFFT3, vTfft3, 'percentage')

EVS4 = ppf.E_VS(pcgFFT4, vTfft4, 'percentage')

EVS5 = ppf.E_VS(pcgFFT5, vTfft5, 'percentage')

# Showing Results in Pandas

data = {'P1': np.round(EVS1),'P2': np.round(EVS2), 'P3': np.round(EVS3), 'P4': np.round(EVS4), 'P5': np.round(EVS5)}

print('Registros Patologicos')

df=pd.DataFrame(data,index=['Total (%)','0-5Hz','5-25Hz','25-120Hz','120-240Hz','240-500Hz','500-1kHz','1k-2kHz'],columns=['P1','P2', 'P3', 'P4', 'P5'])

print (df)

# df.to_excel('pato_5.xlsx') # writing to excel

plt.figure(1)

plt.subplot(5,1,1)

plt.title('Transformada de Fourier')

plt.plot(vTfft1, pcgFFT1,'r')

plt.subplot(5,1,2)

plt.plot(vTfft2, pcgFFT2,'r')

plt.subplot(5,1,3)

plt.plot(vTfft3, pcgFFT3,'r')

plt.subplot(5,1,4)

plt.plot(vTfft4, pcgFFT4,'r')

plt.subplot(5,1,5)

plt.plot(vTfft5, pcgFFT5,'r')