numpy.full_like

numpy.full_like(a, fill_value, dtype=None, order='K', subok=True)[源代码]

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

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.

order : {‘C’, ‘F’, ‘A’, or ‘K’}, optional

Overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible.

subok : bool, optional.

If True, then the newly created array will use the sub-class type of ‘a’, otherwise it will be a base-class array. Defaults to True.

Returns:
out : ndarray

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

参见

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])