--- a
+++ b/PCG_segmentation.py
@@ -0,0 +1,111 @@
+"""
+Segmenting & Timing
+Created on Wed Nov 14 05:55:10 2018
+
+@author: colossus
+"""
+import os
+import numpy as np
+#import wavio as wa
+#import sounddevice as sd
+import ppfunctions_1 as ppf
+import scipy.io.wavfile as wf
+import matplotlib.pyplot as plt
+
+# -----------------------------------------------------------------------------
+#     Signal Loading Process
+# -----------------------------------------------------------------------------
+print('importing all training-a data base')
+# Looking for heart sounds data absolute path 
+l1=os.path.abspath('Data Base HS\\non_pathologic\\1.1.wav')
+#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
+# -----------------------------------------------------------------------------
+#     Pre-Process: Signal basic information (SBI)
+# -----------------------------------------------------------------------------
+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)
+# -----------------------------------------------------------------------------
+#     Pre-Process: Segmentationg and Timing
+# -----------------------------------------------------------------------------
+# Segmenting in an specific frequency band
+pcgPeaks, peaks, allpeaks = ppf.PDP(data1, Fs1)
+
+f_data1 = ppf.butter_bp_fil(data1, 50, 150, Fs1)
+f_pcgPeaks, f_peaks, f_allpeaks = ppf.PDP(f_data1, Fs1)
+# -----------------------------------------------------------------------------
+# Time processing
+dT = 0.4          # Diastole time in ms
+timeV = []
+timeV.append(0)
+pointV = []
+pointV.append(0)
+segmV = np.zeros(len(data1))
+
+for i in range(len(pcgPeaks)-1):
+    if pcgPeaks[i]>0.5:
+        timeV.append(i/Fs1)       # Gives the time when a peak get found
+        pointV.append(i)       # Gives the time when a peak get found
+        if (pointV[-1]/Fs1)-(pointV[-2]/Fs1)< dT:
+            segmV[pointV[-2]:pointV[-1]] = 0.6  # Marc a diastolic segment
+        else:
+            segmV[pointV[-2]:pointV[-1]] = 0.4  # Marc a systolic segment
+
+# -----------------------------------------------------------------------------
+                         # Plotting Time Signal
+# -----------------------------------------------------------------------------
+plt.figure(1)
+plt.title('Pathologic Heart sounds in time')
+
+plt.subplot(3,1,1)
+plt.plot(vt1, data1,'r', vt1, pcgPeaks, 'b')
+
+plt.subplot(3,1,2)
+plt.plot(vt1, data1,'r', vt1, peaks, 'b')
+
+plt.subplot(3,1,3)
+plt.plot(vt1, data1,'r', vt1, allpeaks, 'b')
+
+plt.figure(2)
+plt.title('Pathologic Heart sounds in time')
+
+plt.subplot(3,1,1)
+plt.plot(vt1, data1,'r', vt1, pcgPeaks, 'b')
+
+plt.subplot(2,1,2)
+plt.plot(vt1, data1,'r', vt1, segmV, 'b')
+
+plt.show()