dask.array.tile
dask.array.tile¶
- dask.array.tile(A, reps)[source]¶
Construct an array by repeating A the number of times given by reps.
This docstring was copied from numpy.tile.
Some inconsistencies with the Dask version may exist.
If reps has length
d
, the result will have dimension ofmax(d, A.ndim)
.If
A.ndim < d
, A is promoted to be d-dimensional by prepending new axes. So a shape (3,) array is promoted to (1, 3) for 2-D replication, or shape (1, 1, 3) for 3-D replication. If this is not the desired behavior, promote A to d-dimensions manually before calling this function.If
A.ndim > d
, reps is promoted to A.ndim by prepending 1’s to it. Thus for an A of shape (2, 3, 4, 5), a reps of (2, 2) is treated as (1, 1, 2, 2).Note : Although tile may be used for broadcasting, it is strongly recommended to use numpy’s broadcasting operations and functions.
- Parameters
- Aarray_like
The input array.
- repsarray_like
The number of repetitions of A along each axis.
- Returns
- cndarray
The tiled output array.
See also
repeat
Repeat elements of an array.
broadcast_to
Broadcast an array to a new shape
Examples
>>> import numpy as np >>> a = np.array([0, 1, 2]) >>> np.tile(a, 2) array([0, 1, 2, 0, 1, 2]) >>> np.tile(a, (2, 2)) array([[0, 1, 2, 0, 1, 2], [0, 1, 2, 0, 1, 2]]) >>> np.tile(a, (2, 1, 2)) array([[[0, 1, 2, 0, 1, 2]], [[0, 1, 2, 0, 1, 2]]])
>>> b = np.array([[1, 2], [3, 4]]) >>> np.tile(b, 2) array([[1, 2, 1, 2], [3, 4, 3, 4]]) >>> np.tile(b, (2, 1)) array([[1, 2], [3, 4], [1, 2], [3, 4]])
>>> c = np.array([1,2,3,4]) >>> np.tile(c,(4,1)) array([[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]])