numpy.empty#

numpy.empty(shape,dtype=float,order='C',*,device=None,like=None)#

Return a new array of given shape and type, without initializing entries.

Parameters:
shapeint or tuple of int

Shape of the empty array, e.g.,(2,3) or2.

dtypedata-type, optional

Desired output data-type for the array, e.g,numpy.int8. Default isnumpy.float64.

order{‘C’, ‘F’}, optional, default: ‘C’

Whether to store multi-dimensional data in row-major(C-style) or column-major (Fortran-style) order inmemory.

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.

likearray_like, optional

Reference object to allow the creation of arrays which are notNumPy arrays. If an array-like passed in aslike supportsthe__array_function__ protocol, the result will be definedby it. In this case, it ensures the creation of an array objectcompatible with that passed in via this argument.

New in version 1.20.0.

Returns:
outndarray

Array of uninitialized (arbitrary) data of the given shape, dtype, andorder. Object arrays will be initialized to None.

See also

empty_like

Return an empty array with shape and type of input.

ones

Return a new array setting values to one.

zeros

Return a new array setting values to zero.

full

Return a new array of given shape filled with value.

Notes

Unlike other array creation functions (e.g.zeros,ones,full),empty does not initialize the values of the array, and may therefore bemarginally faster. However, the values stored in the newly allocated arrayare arbitrary. For reproducible behavior, be sure to set each element ofthe array before reading.

Examples

>>>importnumpyasnp>>>np.empty([2,2])array([[ -9.74499359e+001,   6.69583040e-309],       [  2.13182611e-314,   3.06959433e-309]])         #uninitialized
>>>np.empty([2,2],dtype=int)array([[-1073741821, -1067949133],       [  496041986,    19249760]])                     #uninitialized
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