- numpy.ma.dstack(tup) = <numpy.ma.extras._fromnxfunction_seq instance at 0x52d1dd4c>¶
Stack arrays in sequence depth wise (along third axis).
Takes a sequence of arrays and stack them along the third axis to make a single array. Rebuilds arrays divided by dsplit. This is a simple way to stack 2D arrays (images) into a single 3D array for processing.
This function continues to be supported for backward compatibility, but you should prefer np.concatenate or np.stack. The np.stack function was added in NumPy 1.10.
tup : sequence of arrays
Arrays to stack. All of them must have the same shape along all but the third axis.
stacked : ndarray
The array formed by stacking the given arrays.
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]]])