d=0; #take d also as input

#load a data y

y = []

"""

with open(file_name,'r+') as f:

reader = csv.reader(f,delimiter = ' ', quotechar='|')

for number in reader:

y.append(number[d])

ts=y

(ca, cd) = pywt.dwt(ts,'haar')

"""

series = read_csv(file_name, header=0, index_col=0, squeeze=True)

series.columns = ['a', 'b', 'c', 'd']

series['e'] = pow((series['a']*series['a'] + series['b']*series['b'] + series['c']*series['c']), 0.5)

df1 = pd.DataFrame({'$a': series['e']})

df= df1.iloc[:,0]

#print(df)

(ca, cd) = pywt.dwt(df,'haar')

cat = pywt.threshold(ca, np.std(ca)/2, 'soft')

cdt = pywt.threshold(cd, np.std(cd)/2, 'soft')

ts_rec = pywt.idwt(cat, cdt, 'haar')

plt.close('all')

plt.subplot(211)

# Original coefficients

plt.plot(ca, '--*b')

plt.plot(cd, '--*r')

# Thresholded coefficients

plt.plot(cat, '--*c')

plt.plot(cdt, '--*m')

plt.legend(['ca','cd','ca_thresh', 'cd_thresh'], loc=0)

plt.grid(True)

plt.subplot(212)

#plt.plot(ts)

plt.plot(df)

#plt.hold('on')

plt.plot(ts_rec, 'r')

plt.legend(['original signal', 'reconstructed signal'])

plt.grid(True)