Peak Detection in Python: How does the scipy.signal.find_peaks_cwt function work?

Question

I'm looking to identify some peaks in some spectrograph data, and was trying to use the scipy.signal.find_peaks_cwt() function to do it.

However, the official documentation I've found isn't too descriptive, and tends to pick up false peaks in noise while sometimes not picking up actual peaks in the data.

Could anyone give me a better explanation of the parameters in this function that I can play with, including "widths", or could you show me some alternatives?

Lum

Did you try to look at the source for that function? – Nardone

Or even in notes at the bottom of the description you linked? – Demise

Possible duplicate of #28822827 – Viper

I have read the notes, and that post is very helpful when it comes to understanding the widths parameter, thank you for posting it. I'm still unclear on the other optional parameters though, any ideas on those? I looked at the source, and since I'm fairly new to python its hard to really gain something from it.. I'll keep examining it though – Lum

Answer 1

If your signal is relatively clean, I suggest first using simpler alternatives, like the PeakUtils indexes function. The code is way more direct than with scipy.signal.find_peaks_cwt:

import numpy as np
from peakutils.peak import indexes
vector = [ 0, 6, 25, 20, 15, 8, 15, 6, 0, 6, 0, -5, -15, -3, 4, 10, 8, 13, 8, 10, 3, 1, 20, 7, 3, 0 ]
print('Detect peaks with minimum height and distance filters.')
indexes = indexes(np.array(vector), thres=7.0/max(vector), min_dist=2)
print('Peaks are: %s' % (indexes))

The Scipy find_peaks_cwt will really prove usefull in presence of noisy data, as it uses continuous wavelet transform.

Beutler

Link is dead :(((( – Supramolecular

@Supramolecular the link is fixed, thx for the report – Beutler

Thanks for fixing after all these years! – Supramolecular