bundles / numpy 2.4.3 / numpy / zeros
built-in
numpy:zeros
Signature
zeros ( shape , dtype = None , order = C , * , device = None , like = None ) Summary
Return a new array of given shape and type, filled with zeros.
Parameters
shape: int or tuple of intsShape of the new array, e.g.,
(2, 3)or2.dtype: data-type, optionalThe 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.
device: str, optionalThe device on which to place the created array. Default:
None. For Array-API interoperability only, so must be"cpu"if passed.like: array_like, optionalReference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as
likesupports 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.
Returns
out: ndarrayArray of zeros with the given shape, dtype, and order.
Examples
import numpy as np
✓np.zeros(5)
✗np.zeros((5,), dtype=int)
✓np.zeros((2, 1))
✗s = (2,2)
✓np.zeros(s)
✗np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
✗See also
- empty
Return a new uninitialized array.
- full
Return a new array of given shape filled with value.
- ones
Return a new array setting values to one.
- zeros_like
Return an array of zeros with shape and type of input.
Aliases
-
numpy.zeros