dask.array.dstack — Dask documentation (original) (raw)
Stack arrays in sequence depth wise (along third axis).
This docstring was copied from numpy.dstack.
Some inconsistencies with the Dask version may exist.
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 bydsplit.
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 concatenate, stack andblock provide more general stacking and concatenation operations.
Parameters
tupsequence of arrays
The arrays must have the same shape along all but the third axis. 1-D or 2-D arrays must have the same shape.
Returns
stackedndarray
The array formed by stacking the given arrays, will be at least 3-D.
See also
Join a sequence of arrays along an existing axis.
Join a sequence of arrays along a new axis.
Assemble an nd-array from nested lists of blocks.
Stack arrays in sequence vertically (row wise).
Stack arrays in sequence horizontally (column wise).
column_stack
Stack 1-D arrays as columns into a 2-D array.
dsplit
Split array along third axis.
Examples
import numpy as np
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]]])