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dask 2021.10.0

empty(shape, dtype=float, order='C', *, like=None)

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.

Parameters

shape : int or tuple of int: Shape of the empty array, e.g., (2, 3) or 2 .
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: 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.

versionadded

Returns

out : ndarray: Array of uninitialized (arbitrary) data of the given shape, dtype, and order. Object arrays will be initialized to None.

Return a new array of given shape and type, without initializing entries.

Examples

This example is valid syntax, but we were not able to check execution

>>> np.empty([2, 2])
array([[ -9.74499359e+001,   6.69583040e-309],
       [  2.13182611e-314,   3.06959433e-309]])         #uninitialized

This example is valid syntax, but we were not able to check execution

>>> np.empty([2, 2], dtype=int)
array([[-1073741821, -1067949133],
       [  496041986,    19249760]])                     #uninitialized

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.creation.full_like dask.array.routines.array dask.array.wrap.full_like dask.array.creation.ones_like dask.array.creation.empty_like dask.utils.empty dask.array.creation.zeros_like

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