xorbits.numpy.ones#
- 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.
- Parameters
shape (int or sequence of ints) – Shape of the new array, e.g.,
(2, 3)
or2
.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).
- Returns
out – Array of ones with the given shape, dtype, and order.
- Return type
ndarray
See also
Examples
>>> np.ones(5) array([1., 1., 1., 1., 1.])
>>> np.ones((5,), dtype=int) array([1, 1, 1, 1, 1])
>>> np.ones((2, 1)) array([[1.], [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.