negative#
- ivy.negative(x, /, *, out=None)[source]#
Return a new array with the negative value of each element in
x
.Note
For signed integer data types, the numerical negative of the minimum representable integer is implementation-dependent.
Note
If
x
has a complex floating-point data type, both the real and imaginary components for eachx_i
must be negated (a result which follows from the rules of complex number multiplication).- Parameters:
- Return type:
- Returns:
ret – A new array with the negative value of each element in
x
.
This function conforms to the Array API Standard. This docstring is an extension of the docstring in the standard.
Both the description and the type hints above assumes an array input for simplicity, but this function is nestable, and therefore also accepts
ivy.Container
instances in place of any of the arguments.Examples
With
ivy.Array
input:>>> x = ivy.array([0,1,1,2]) >>> y = ivy.negative(x) >>> print(y) ivy.array([ 0, -1, -1, -2])
>>> x = ivy.array([0,-1,-0.5,2,3]) >>> y = ivy.zeros(5) >>> ivy.negative(x, out=y) >>> print(y) ivy.array([-0. , 1. , 0.5, -2. , -3. ])
>>> x = ivy.array([[1.1, 2.2, 3.3], ... [-4.4, -5.5, -6.6]]) >>> ivy.negative(x,out=x) >>> print(x) ivy.array([[-1.1, -2.2, -3.3], [4.4, 5.5, 6.6]])
With
ivy.Container
input:>>> x = ivy.Container(a=ivy.array([0., 1., 2.]), ... b=ivy.array([3., 4., -5.])) >>> y = ivy.negative(x) >>> print(y) { a: ivy.array([-0., -1., -2.]), b: ivy.array([-3., -4., 5.]) }
- Array.negative(self, *, out=None)[source]#
ivy.Array instance method variant of ivy.negative. This method simply wraps the function, and so the docstring for ivy.negative also applies to this method with minimal changes.
- Parameters:
self (
Array
) – input array. Should have a numeric data type.out (
Optional
[Array
], default:None
) – optional output, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
Array
- Returns:
ret – an array containing the evaluated result for each element in
self
. The returned array must have the same data type asself
.
Examples
With
ivy.Array
input:>>> x = ivy.array([2, 3 ,5, 7]) >>> y = x.negative() >>> print(y) ivy.array([-2, -3, -5, -7])
>>> x = ivy.array([0,-1,-0.5,2,3]) >>> y = ivy.zeros(5) >>> x.negative(out=y) >>> print(y) ivy.array([-0. , 1. , 0.5, -2. , -3. ])
>>> x = ivy.array([[1.1, 2.2, 3.3], ... [-4.4, -5.5, -6.6]]) >>> x.negative(out=x) >>> print(x) ivy.array([[ -1.1, -2.2, -3.3], [4.4, 5.5, 6.6]])
- Container.negative(self, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#
ivy.Container instance method variant of ivy.negative. This method simply wraps the function, and so the docstring for ivy.negative also applies to this method with minimal changes.
- Parameters:
self (
Container
) – input container. Should have a numeric data type.key_chains (
Optional
[Union
[List
[str
],Dict
[str
,str
],Container
]], default:None
) – The key-chains to apply or not apply the method to. Default isNone
.to_apply (
Union
[bool
,Container
], default:True
) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default isTrue
.prune_unapplied (
Union
[bool
,Container
], default:False
) – Whether to prune key_chains for which the function was not applied. Default isFalse
.map_sequences (
Union
[bool
,Container
], default:False
) – Whether to also map method to sequences (lists, tuples). Default isFalse
.out (
Optional
[Container
], default:None
) – optional output container, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
Container
- Returns:
ret – a container containing the evaluated result for each element in
self
. The returned container must have the same data type asself
.
Examples
With
ivy.Container
input:>>> x = ivy.Container(a=ivy.array([0., 1., 2.]), ... b=ivy.array([3., 4., -5.])) >>> y = x.negative() >>> print(y) { a: ivy.array([-0., -1., -2.]), b: ivy.array([-3., -4., 5.]) }