from pyannote.core import SlidingWindowFeature, SlidingWindow

"""
Explanation: SlidingWindowFeature (pyannote.core.feature.SlidingWindowFeature)
End of explanation
"""


# one 4-dimensional feature vector extracted every 100ms from a 200ms window
frame = SlidingWindow(start=0.0, step=0.100, duration=0.200)

# random for illustration purposes
data = np.random.randn(100, 4)

features = SlidingWindowFeature(data, frame)

"""
Explanation: SlidingWindowFeature are used to manage feature vectors extracted on a sliding window (e.g. MFCC in audio processing).
End of explanation
"""


help(features.crop)

from pyannote.core import Segment
features.crop(Segment(2, 3))

"""
Explanation: Cropping
You may use crop to extract a temporal subset:
End of explanation
"""


help(SlidingWindowFeature)

"""
Explanation: Need help?
You can always try the following...
Who knows? It might give you the information you are looking for!
End of explanation
"""


