Find plateau in Numpy array

Question

I am looking for an efficient way to detect plateaus in otherwise very noisy data. The plateaus are always relatively broad A simple example of what this data could look like:

test=np.random.uniform(0.9,1,100)
test[10:20]=0
plt.plot(test)

Note that there can be multiple plateaus (which should all be detected) which can have different values.

I've tried using scipy.signal.argrelextrema, but it doesn't seem to be doing what I want it to:

peaks=argrelextrema(test,np.less,order=25)
plt.vlines(peaks,ymin=0, ymax=1)

I don't need the exact interval of the plateau- a rough range estimate would be enough, as long as that estimate is bigger or equal than the actual plateau range. It should be relatively efficient however.

Answer 1

There is a method scipy.signal.find_peaks that you can try, here is an exmple

import numpy
from scipy.signal import find_peaks

test = numpy.random.uniform(0.9, 1.0, 100)
test[10 : 20] = 0
peaks, peak_plateaus = find_peaks(- test, plateau_size = 1)

although find_peaks only finds peaks, it can be used to find valleys if the array is negated, then you do the following

for i in range(len(peak_plateaus['plateau_sizes'])):
    if peak_plateaus['plateau_sizes'][i] > 1:
        print('a plateau of size %d is found' % peak_plateaus['plateau_sizes'][i])
        print('its left index is %d and right index is %d' % (peak_plateaus['left_edges'][i], peak_plateaus['right_edges'][i]))

it will print

a plateau of size 10 is found
its left index is 10 and right index is 19