xorbits.numpy.empty#
- xorbits.numpy.empty(shape, dtype=float, order='C', *, like=None)[source]#
Return a new array of given shape and type, without initializing entries.
- Parameters
shape (int or tuple of int) – Shape of the empty array, e.g.,
(2, 3)
or2
.dtype (data-type, optional) – Desired output data-type for the array, e.g, numpy.int8. Default is numpy.float64.
order ({'C', 'F'}, optional, default: 'C') – Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.
like (array_like, optional) –
Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as
like
supports the__array_function__
protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.New in version 1.20.0(numpy).
- Returns
out – Array of uninitialized (arbitrary) data of the given shape, dtype, and order. Object arrays will be initialized to None.
- Return type
ndarray
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
empty, unlike zeros, does not set the array values to zero, and may therefore be marginally faster. On the other hand, it requires the user to manually set all the values in the array, and should be used with caution.
Examples
>>> 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
This docstring was copied from numpy.