# minimum#

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

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

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

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

• use_where (`bool`, default: `True`) – Whether to use `where()` to calculate the minimum. If `False`, the minimum 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 exceed the x2 values.

Examples

With `ivy.Array` inputs:

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

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

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

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

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

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

• use_where (`bool`, default: `True`) – Whether to use `where()` to calculate the minimum. If `False`, the minimum 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 exceed the x2 values.

Examples

With `ivy.Array` inputs:

```>>> x = ivy.array([7, 9, 5])
>>> y = ivy.array([9, 3, 2])
>>> z = x.minimum(y)
>>> print(z)
ivy.array([7, 3, 2])
```
```>>> x = ivy.array([1, 5, 9, 8, 3, 7])
>>> y = ivy.array([[9], [3], [2]])
>>> z = ivy.zeros((3, 6))
>>> x.minimum(y, out=z)
>>> print(z)
ivy.array([[1.,5.,9.,8.,3.,7.],
[1.,3.,3.,3.,3.,3.],
[1.,2.,2.,2.,2.,2.]])
```
```>>> x = ivy.array([[7, 3]])
>>> y = ivy.array([0, 7])
>>> x.minimum(y, out=x)
>>> print(x)
ivy.array([[0, 3]])
```
Container.minimum(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.minimum. This method simply wraps the function, and so the docstring for ivy.minimum also applies to this method with minimal changes.

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

• x2 (`Union`[`Container`, `Array`, `NativeArray`]) – The other container or number to compute the minimum against.

• 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 minimum. If `False`, the minimum is calculated using the `(x + y - |x - y|)/2` formula. Default is `True`.

• 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:

Container object with all sub-arrays having the minimum values computed.

Examples

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 = x.minimum(y)
>>> print(z)
{
a: ivy.array([1, 3, 1]),
b: ivy.array([2, 8, 5])
}
```