bundles / numpy 2.4.4 / numpy / empty
built-in
numpy:empty
Signature
empty ( shape , dtype = None , order = C , * , device = None , like = None ) Summary
Return a new array of given shape and type, without initializing entries.
Parameters
shape: int or tuple of intShape of the empty array, e.g.,
(2, 3)or2.dtype: data-type, optionalDesired 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.
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 uninitialized (arbitrary) data of the given shape, dtype, and order. Object arrays will be initialized to None.
Notes
Unlike other array creation functions (e.g. zeros, ones, full), empty does not initialize the values of the array, and may therefore be marginally faster. However, the values stored in the newly allocated array are arbitrary. For reproducible behavior, be sure to set each element of the array before reading.
Examples
import numpy as np
✓np.empty([2, 2])
✗np.empty([2, 2], dtype=int)
✗See also
- empty_like
Return an empty array with shape and type of input.
- full
Return a new array of given shape filled with value.
- ones
Return a new array setting values to one.
- zeros
Return a new array setting values to zero.
Aliases
-
numpy.empty