Find large number of consecutive values fulfilling condition in a numpy array

Question

I have some audio data loaded in a numpy array and I wish to segment the data by finding silent parts, i.e. parts where the audio amplitude is below a certain threshold over

Answer 1

This should return a list of (start,length) pairs:

def silent_segs(samples,threshold,min_dur):
  start = -1
  silent_segments = []
  for idx,x in enumerate(samples):
    if start < 0 and abs(x) < threshold:
      start = idx
    elif start >= 0 and abs(x) >= threshold:
      dur = idx-start
      if dur >= min_dur:
        silent_segments.append((start,dur))
      start = -1
  return silent_segments

And a simple test:

>>> s = [-1,0,0,0,-1,10,-10,1,2,1,0,0,0,-1,-10]
>>> silent_segs(s,2,2)
[(0, 5), (9, 5)]

Answer 2

There is a very convenient solution to this using scipy.ndimage. For an array:

a = array([1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0])

which can be the result of a condition applied to another array, finding the contiguous regions is as simple as:

regions = scipy.ndimage.find_objects(scipy.ndimage.label(a)[0])

Then, applying any function to those regions can be done e.g. like:

[np.sum(a[r]) for r in regions]