bundles / numpy latest / numpy / ma / extras / dstack
function
numpy.ma.extras:dstack
source: build-install/usr/lib/python3.14/site-packages/numpy/lib/_shape_base_impl.py :673
Signature
def dstack ( tup ) Summary
Stack arrays in sequence depth wise (along third axis).
Extended Summary
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 dsplit.
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 and block provide more general stacking and concatenation operations.
Parameters
tup: sequence of arraysThe arrays must have the same shape along all but the third axis. 1-D or 2-D arrays must have the same shape.
Returns
stacked: ndarrayThe array formed by stacking the given arrays, will be at least 3-D.
Notes
The function is applied to both the _data and the _mask, if any.
Examples
import numpy as np a = np.array((1,2,3)) b = np.array((4,5,6)) np.dstack((a,b))✓
a = np.array([[1],[2],[3]]) b = np.array([[4],[5],[6]])✓
np.dstack((a,b))
✗See also
- block
Assemble an nd-array from nested lists of blocks.
- column_stack
Stack 1-D arrays as columns into a 2-D array.
- concatenate
Join a sequence of arrays along an existing axis.
- dsplit
Split array along third axis.
- hstack
Stack arrays in sequence horizontally (column wise).
- stack
Join a sequence of arrays along a new axis.
- vstack
Stack arrays in sequence vertically (row wise).
Aliases
-
numpy.ma.dstack