numpy.ma.dstack(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_seq object>
Stack arrays in sequence depth wise (along third axis).
This is equivalent to concatenation along the third axis after 2-D arrays of shape
(M,N) have been reshaped to
(M,N,1) and 1-D arrays of shape
(N,) have been reshaped to
(1,N,1). Rebuilds arrays divided by
This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions
block provide more general stacking and concatenation operations.
The function is applied to both the _data and the _mask, if any.
>>> a = np.array((1,2,3)) >>> b = np.array((2,3,4)) >>> np.dstack((a,b)) array([[[1, 2], [2, 3], [3, 4]]])
>>> a = np.array([,,]) >>> b = np.array([,,]) >>> np.dstack((a,b)) array([[[1, 2]], [[2, 3]], [[3, 4]]])
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