baseline

def calcBaseline(time_series):
    time_series = np.asarray(time_series, dtype=int)
    baseline_values = peakutils.baseline(time_series)
    with open('baseline_values.txt', 'w') as filehandle:
        filehandle.writelines("%s\n" % value for value in baseline_values)

def subtractBaseline(file):
    time_series = []
    baseline_values = []
    new_time_series = []
    nts = np.array(new_time_series, dtype=float)
    #read baseline values
    with open('baseline_values.txt', 'r') as filehandle:
        for line in filehandle:
            baseline_values.append(line.split()[0])
    bv = np.array(baseline_values, dtype=float)
    #read time series
    with open('C:/Users/João/Desktop/ECG/data/'+file) as f:
        for line in f:
            time_series.append(line.split()[6])
            if len(time_series) == 100:
                ts = np.array(time_series, dtype=float)
                nts = ts - bv
                time_series = []
            if time_series:
                ts = np.array(time_series, dtype=float)
                nts = ts - bv
    return nts

def plotWithoutBaseline(signal):
    x = np.arange(0, len(signal), 1)
    y = np.asarray(signal)
    fig, ax = plt.subplots()
    ax.plot(x, y)
    plt.show()

def filterSignal():
    print("Choose file from list of files:")
    files = os.listdir('data')
    for i in range(0,len(files)-1):
        if files[i].endswith('.txt'):
            print(files[i])
    file = input("Write the desired file name:")
    #remove baseline from the signal
    with open('C:/Users/João/Desktop/ECG/data/'+file, 'r') as f:
        result = []
        for line in f:
            result.append(line.split()[6])
            if len(result) == 100:
                calcBaseline(result)
                result = []
        if result:
            calcBaseline(result)
    signal = subtractBaseline(file)
    plotWithoutBaseline(signal)