bundles / numpy 2.4.4 / numpy / ma / extras / stack
function
numpy.ma.extras:stack
source: /numpy/_core/shape_base.py :378
Signature
def stack ( arrays , axis = 0 , out = None , * , dtype = None , casting = same_kind ) Summary
Join a sequence of arrays along a new axis.
Extended Summary
The axis parameter specifies the index of the new axis in the dimensions of the result. For example, if axis=0 it will be the first dimension and if axis=-1 it will be the last dimension.
Parameters
arrays: sequence of ndarraysEach array must have the same shape. In the case of a single ndarray array_like input, it will be treated as a sequence of arrays; i.e., each element along the zeroth axis is treated as a separate array.
axis: int, optionalThe axis in the result array along which the input arrays are stacked.
out: ndarray, optionalIf provided, the destination to place the result. The shape must be correct, matching that of what stack would have returned if no out argument were specified.
dtype: str or dtypeIf provided, the destination array will have this dtype. Cannot be provided together with
out.casting: {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optionalControls what kind of data casting may occur. Defaults to 'same_kind'.
Returns
stacked: ndarrayThe stacked array has one more dimension than the input arrays.
Notes
The function is applied to both the _data and the _mask, if any.
Examples
import numpy as np rng = np.random.default_rng() arrays = [rng.normal(size=(3,4)) for _ in range(10)] np.stack(arrays, axis=0).shape✓
np.stack(arrays, axis=1).shape
✓np.stack(arrays, axis=2).shape
✓a = np.array([1, 2, 3]) b = np.array([4, 5, 6]) np.stack((a, b))✓
np.stack((a, b), axis=-1)
✓See also
- block
Assemble an nd-array from nested lists of blocks.
- concatenate
Join a sequence of arrays along an existing axis.
- split
Split array into a list of multiple sub-arrays of equal size.
- unstack
Split an array into a tuple of sub-arrays along an axis.
Aliases
-
numpy.ma.stack