# maximum#

ivy.maximum(x1, x2, /, *, use_where=True, out=None)[source]#

Return the max of x1 and x2 (i.e. x1 > x2 ? x1 : x2) element-wise.

Parameters:
• x1 (`Union`[`Array`, `NativeArray`, `Number`]) – Input array containing elements to maximum threshold.

• x2 (`Union`[`Array`, `NativeArray`, `Number`]) – Tensor containing maximum values, must be broadcastable to x1.

• use_where (`bool`, default: `True`) – Whether to use `where()` to calculate the maximum. If `False`, the maximum is calculated using the `(x + y + |x - y|)/2` formula. Default is `True`.

• out (`Optional`[`Array`], default: `None`) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Array`

Returns:

ret – An array with the elements of x1, but clipped to not be lower than the x2 values.

Examples

With `ivy.Array` inputs:

```>>> x = ivy.array([7, 9, 5])
>>> y = ivy.array([9, 3, 2])
>>> z = ivy.maximum(x, y)
>>> print(z)
ivy.array([9, 9, 5])
```
```>>> x = ivy.array([1, 5, 9, 8, 3, 7])
>>> y = ivy.array([[9], [3], [2]])
>>> z = ivy.zeros((3, 6), dtype=ivy.int32)
>>> ivy.maximum(x, y, out=z)
>>> print(z)
ivy.array([[9, 9, 9, 9, 9, 9],
[3, 5, 9, 8, 3, 7],
[2, 5, 9, 8, 3, 7]])
```
```>>> x = ivy.array([[7, 3]])
>>> y = ivy.array([0, 7])
>>> ivy.maximum(x, y, out=x)
>>> print(x)
ivy.array([[7, 7]])
```

With one `ivy.Container` input:

```>>> x = ivy.array([[1, 3], [2, 4], [3, 7]])
>>> y = ivy.Container(a=ivy.array([1, 0,]),
...                   b=ivy.array([-5, 9]))
>>> z = ivy.maximum(x, y)
>>> print(z)
{
a: ivy.array([[1, 3],
[2, 4],
[3, 7]]),
b: ivy.array([[1, 9],
[2, 9],
[3, 9]])
}
```

With multiple `ivy.Container` inputs:

```>>> x = ivy.Container(a=ivy.array([1, 3, 1]),b=ivy.array([2, 8, 5]))
>>> y = ivy.Container(a=ivy.array([1, 5, 6]),b=ivy.array([5, 9, 7]))
>>> z = ivy.maximum(x, y)
>>> print(z)
{
a: ivy.array([1, 5, 6]),
b: ivy.array([5, 9, 7])
}
```
Array.maximum(self, x2, /, *, use_where=True, out=None)[source]#

ivy.Array instance method variant of ivy.maximum. This method simply wraps the function, and so the docstring for ivy.maximum also applies to this method with minimal changes.

Parameters:
• self (`Array`) – Input array containing elements to maximum threshold.

• x2 (`Union`[`Array`, `NativeArray`]) – Tensor containing maximum values, must be broadcastable to x1.

• use_where (`bool`, default: `True`) – Whether to use `where()` to calculate the maximum. If `False`, the maximum is calculated using the `(x + y + |x - y|)/2` formula. Default is `True`.

• out (`Optional`[`Array`], default: `None`) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Returns:

ret – An array with the elements of x1, but clipped to not be lower than the x2 values.

Examples

With `ivy.Array` inputs: >>> x = ivy.array([7, 9, 5]) >>> y = ivy.array([9, 3, 2]) >>> z = x.maximum(y) >>> print(z) ivy.array([9, 9, 5])

```>>> x = ivy.array([1, 5, 9, 8, 3, 7])
>>> y = ivy.array([[9], [3], [2]])
>>> z = ivy.zeros((3, 6))
>>> x.maximum(y, out=z)
>>> print(z)
ivy.array([[9.,9.,9.,9.,9.,9.],
[3.,5.,9.,8.,3.,7.],
[2.,5.,9.,8.,3.,7.]])
```
```>>> x = ivy.array([[7, 3]])
>>> y = ivy.array([0, 7])
>>> x.maximum(y, out=x)
>>> print(x)
ivy.array([[7, 7]])
```
Container.maximum(self, x2, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, use_where=True, out=None)[source]#

ivy.Container instance method variant of ivy.maximum. This method simply wraps the function, and so the docstring for ivy.maximum also applies to this method with minimal changes.

Parameters:
• self (`Union`[`Container`, `Array`, `NativeArray`]) – Input array containing elements to maximum threshold.

• x2 (`Union`[`Container`, `Array`, `NativeArray`]) – Tensor containing maximum values, must be broadcastable to x1.

• key_chains (`Optional`[`Union`[`List`[`str`], `Dict`[`str`, `str`], `Container`]], default: `None`) – The key-chains to apply or not apply the method to. Default is `None`.

• to_apply (`Union`[`bool`, `Container`], default: `True`) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default is `True`.

• prune_unapplied (`Union`[`bool`, `Container`], default: `False`) – Whether to prune key_chains for which the function was not applied. Default is `False`.

• map_sequences (`Union`[`bool`, `Container`], default: `False`) – Whether to also map method to sequences (lists, tuples). Default is `False`.

• use_where (`Union`[`bool`, `Container`], default: `True`) – Whether to use `where()` to calculate the maximum. If `False`, the maximum is calculated using the `(x + y + |x - y|)/2` formula. Default is `True`.

• out (`Optional`[`Container`], default: `None`) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Container`

Returns:

ret – An container with the elements of x1, but clipped to not be lower than the x2 values.

Examples

With one `ivy.Container` input:

```>>> x = ivy.array([[1, 3], [2, 4], [3, 7]])
>>> y = ivy.Container(a=ivy.array([1, 0,]),
...                   b=ivy.array([-5, 9]))
>>> z = x.maximum(y)
>>> print(z)
{
a: ivy.array([[1, 3],
[2, 4],
[3, 7]]),
b: ivy.array([[1, 9],
[2, 9],
[3, 9]])
}
```