Vous êtes un professionnel et vous avez besoin d'une formation ? Programmation Python
Les fondamentaux Voir le programme détaillé

Module « numpy.matlib »

Fonction tile - module numpy.matlib

Signature de la fonction tile

def tile(A, reps) 

Description

help(numpy.matlib.tile)

Construct an array by repeating A the number of times given by reps.

If `reps` has length ``d``, the result will have dimension of
``max(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
----------
A : array_like
    The input array.
reps : array_like
    The number of repetitions of `A` along each axis.

Returns
-------
c : ndarray
    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]])

Vous êtes un professionnel et vous avez besoin d'une formation ? Sensibilisation à
l'Intelligence Artificielle Voir le programme détaillé