xorbits.numpy.ones(shape, dtype=None, chunk_size=None, gpu=None, order='C')[source]#

Return a new array of given shape and type, filled with ones.

  • shape (int or sequence of ints) – Shape of the new array, e.g., (2, 3) or 2.

  • dtype (data-type, optional) – The desired 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 (Not supported yet)) –

    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).


out – Array of ones with the given shape, dtype, and order.

Return type


See also


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


Return a new uninitialized array.


Return a new array setting values to zero.


Return a new array of given shape filled with value.


>>> np.ones(5)  
array([1., 1., 1., 1., 1.])
>>> np.ones((5,), dtype=int)  
array([1, 1, 1, 1, 1])
>>> np.ones((2, 1))  
>>> s = (2,2)  
>>> np.ones(s)  
array([[1.,  1.],
       [1.,  1.]])
chunk_sizeint or tuple of int or tuple of ints, optional

Desired chunk size on each dimension

gpubool, optional

Allocate the tensor on GPU if True, False as default

This docstring was copied from numpy.