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# -*- coding: utf-8 -*-
"""
Created on Sun Sep 22 15:50:41 2019

@author: --deleted--
"""
#import necessary modules and functions
from scipy import io
import numpy as np
import matplotlib.pyplot as plt

#file path
path = "C:\\Users\\--deleted--\\"

#function to load EKG
def loadmat(path):
	
	mat = io.loadmat(path)
	print(type(mat))
	print(mat.keys())
	for key in mat.keys():
		if not key == 'val': print(mat[key])
	EKG = np.array(mat['val'], dtype = float)
	return EKG, mat.keys()

#function to plot results
def plot(lead, xmin = 0, xmax = 1):
	fs = 250
	time = np.arange(lead.size) / fs
	fig = plt.plot(time, lead)
	plt.xlim(xmin, xmax)
	plt.show()
#load EKG	
EKG, headers = loadmat(path + 's30731m.mat')
#view data about EKG
print(EKG.shape)
print(EKG)

#split into leads
lead_0 = EKG[0]
lead_1 = EKG[1]
lead_2 = EKG[2]

#save each lead as a numpy array (.npy)
np.save(path + 'ekg_lead_0', lead_0)
np.save(path + 'ekg_lead_1', lead_1)
np.save(path + 'ekg_lead_2', lead_2)

print(lead_1)

# -*- coding: utf-8 -*-
"""
Created on Mon Sep 23 20:52:19 2019

@author: --deleted--
"""
import numpy as np

path = 'C:\\Users\\--deleted--\\'
#load EKG
ecg = np.load(path + '30731_ekg_data\\ekg_lead_1.npy')

print(max(ecg))
print(min(ecg))

#remove extreme values
ecg[ecg > 200] = 200
ecg[ecg < -200] = -200
#take a slice of the EKG
ecg = ecg[400000:405000]

#assign a bin number to each note
notes = {1:'a3', 2:'b3', 3:'c4', 4:'d4', 5:'e4', 6:'f4', 7:'g4', 8:'a4', 9:'b4',
		 10:'c5', 11:'d5', 12:'e5', 13:'f5', 14:'g5'}
#create bins
bins = np.linspace(-200, 200, 14)
#show bins
print(bins)
#bin EKG
binned = np.digitize(ecg, bins)
print(binned)
#initialize note array
note = []

for x in binned:
	#append the corresponding note for each EKG sample to the array
	note.append(notes[x])
	 
print(np.bincount(binned))
#save as csv
np.savetxt(path + '1000_notes.csv', note, fmt = '%s', delimiter = ', ')

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