jax.numpy.full_likeΒΆ

jax.numpy.full_like(a, fill_value, dtype=None, shape=None)[source]ΒΆ

Return a full array with the same shape and type as a given array.

LAX-backend implementation of full_like(). Original docstring below.

Parameters
  • a (array_like) – The shape and data-type of a define these same attributes of the returned array.

  • fill_value (scalar) – Fill value.

  • dtype (data-type, optional) – Overrides the data type of the result.

  • shape (int or sequence of ints, optional.) – Overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied.

Returns

out – Array of fill_value with the same shape and type as a.

Return type

ndarray

See also

empty_like()

Return an empty array with shape and type of input.

ones_like()

Return an array of ones with shape and type of input.

zeros_like()

Return an array of zeros with shape and type of input.

full()

Return a new array of given shape filled with value.

Examples

>>> x = np.arange(6, dtype=int)
>>> np.full_like(x, 1)
array([1, 1, 1, 1, 1, 1])
>>> np.full_like(x, 0.1)
array([0, 0, 0, 0, 0, 0])
>>> np.full_like(x, 0.1, dtype=np.double)
array([0.1, 0.1, 0.1, 0.1, 0.1, 0.1])
>>> np.full_like(x, np.nan, dtype=np.double)
array([nan, nan, nan, nan, nan, nan])
>>> y = np.arange(6, dtype=np.double)
>>> np.full_like(y, 0.1)
array([0.1,  0.1,  0.1,  0.1,  0.1,  0.1])