numpy.full_like#

numpy.full_like(a,fill_value,dtype=None,order='K',subok=True,shape=None,*,device=None)[source]#

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

Parameters:
aarray_like

The shape and data-type ofa define these same attributes ofthe returned array.

fill_valuearray_like

Fill value.

dtypedata-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’ ifa is Fortran contiguous,‘C’ otherwise. ‘K’ means match the layout ofa as closelyas possible.

subokbool, optional.

If True, then the newly created array will use the sub-classtype ofa, otherwise it will be a base-class array. Defaultsto True.

shapeint or sequence of ints, optional.

Overrides the shape of the result. If order=’K’ and the number ofdimensions is unchanged, will try to keep order, otherwise,order=’C’ is implied.

devicestr, optional

The device on which to place the created array. Default: None.For Array-API interoperability only, so must be"cpu" if passed.

New in version 2.0.0.

Returns:
outndarray

Array offill_value with the same shape and type asa.

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

>>>importnumpyasnp>>>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])
>>>y=np.zeros([2,2,3],dtype=int)>>>np.full_like(y,[0,0,255])array([[[  0,   0, 255],        [  0,   0, 255]],       [[  0,   0, 255],        [  0,   0, 255]]])
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