frame#

class diffsptk.Frame(frame_length, frame_period, center=True, zmean=False, mode='constant')[source]#

See this page for details.

Parameters:

frame_lengthint >= 1: Frame length, \(L\).
frame_periodint >= 1: Frame period, \(P\).
centerbool: If True, assume that the center of data is the center of frame, otherwise assume that the center of data is the left edge of frame.
zmeanbool: If True, perform mean subtraction on each frame.
mode[‘constant’, ‘reflect’, ‘replicate’, ‘circular’]: Padding mode.

forward(x)[source]#

Apply framing to given waveform.

Parameters:

xTensor [shape=(…, T)]: Waveform.

Returns:

outTensor [shape=(…, T/P, L)]: Framed waveform.

Examples

>>> x = diffsptk.ramp(1, 9)
>>> frame = diffsptk.Frame(5, 2)
>>> y = frame(x)
>>> y
tensor([[0., 0., 1., 2., 3.],
        [1., 2., 3., 4., 5.],
        [3., 4., 5., 6., 7.],
        [5., 6., 7., 8., 9.],
        [7., 8., 9., 0., 0.]])

diffsptk.functional.frame(x, frame_length=400, frame_period=80, center=True, zmean=False, mode='constant')[source]#

Perform framing.

Parameters:

xTensor [shape=(…, T)]: Waveform.
frame_lengthint >= 1: Frame length, \(L\).
frame_peirodint >= 1: Frame period, \(P\).
centerbool: If True, assume that the center of data is the center of frame, otherwise assume that the center of data is the left edge of frame.
zmeanbool: If True, perform mean subtraction on each frame.
mode[‘constant’, ‘reflect’, ‘replicate’, ‘circular’]: Padding mode.

Returns:

outTensor [shape=(…, T/P, L)]: Framed waveform.

frame#

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