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 2D arrays of shape (M,N)
have been reshaped to (M,N,1)
and 1D arrays of shape (N,)
have been reshaped to (1,N,1)
. Rebuilds arrays divided by dsplit
.
This function makes most sense for arrays with up to 3 dimensions. For instance, for pixeldata with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions concatenate
, stack
and block
provide more general stacking and concatenation operations.
Parameters: 


Returns: 

See also
stack
vstack
hstack
concatenate
dsplit
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([[1],[2],[3]]) >>> b = np.array([[2],[3],[4]]) >>> np.dstack((a,b)) array([[[1, 2]], [[2, 3]], [[3, 4]]])
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https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.ma.dstack.html