# log10#

ivy.log10(x, /, *, out=None)[source]#

Calculate an implementation-dependent approximation to the base `10` logarithm, having domain `[0, +infinity]` and codomain `[-infinity, +infinity]`, for each element `x_i` of the input array `x`.

Special cases

For floating-point operands,

• If `x_i` is `NaN`, the result is `NaN`.

• If `x_i` is less than `0`, the result is `NaN`.

• If `x_i` is either `+0` or `-0`, the result is `-infinity`.

• If `x_i` is `1`, the result is `+0`.

• If `x_i` is `+infinity`, the result is `+infinity`.

Parameters:
• x (`Union`[`Array`, `NativeArray`]) – input array. Should have a floating-point data type.

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

Return type:

`Array`

Returns:

ret – an array containing the evaluated base `10` logarithm for each element in `x`. The returned array must have a floating-point data type determined by type-promotion.

This function conforms to the Array API Standard. This docstring is an extension of the docstring # noqa 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([4.0, 1, -0.0, -5.0])
>>> y = ivy.log10(x)
>>> print(y)
ivy.array([0.602, 0., -inf, nan])
```
```>>> x = ivy.array([[float('nan'), 1, 5.0, float('+inf')],
...                [+0, -1.0, -5, float('-inf')]])
>>> y = ivy.log10(x)
>>> print(y)
ivy.array([[nan, 0., 0.699, inf],
[-inf, nan, nan, nan]])
```

With `ivy.Container` input:

```>>> x = ivy.Container(a=ivy.array([0.0, float('nan')]),
...                   b=ivy.array([-0., -3.9, float('+inf')]),
...                   c=ivy.array([7.9, 1.1, 1.]))
>>> y = ivy.log10(x)
>>> print(y)
{
a: ivy.array([-inf, nan]),
b: ivy.array([-inf, nan, inf]),
c: ivy.array([0.898, 0.0414, 0.])
}
```
Array.log10(self, *, out=None)#

ivy.Array instance method variant of ivy.log10. This method simply wraps the function, and so the docstring for ivy.log10 also applies to this method with minimal changes.

Parameters:
• self (`Array`) – input array. Should have a real-valued floating-point data type.

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

Return type:

`Array`

Returns:

ret – an array containing the evaluated base `10` logarithm for each element in `self`. The returned array must have a real-valued floating-point data type determined by type-promotion.

Examples

Using `ivy.Array` instance method:

```>>> x = ivy.array([4.0, 1, -0.0, -5.0])
>>> y = x.log10()
>>> print(y)
ivy.array([0.602, 0., -inf, nan])
```
```>>> x = ivy.array([float('nan'), -5.0, -0.0, 1.0, 5.0, float('+inf')])
>>> y = x.log10()
>>> print(y)
ivy.array([nan, nan, -inf, 0., 0.699, inf])
```
```>>> x = ivy.array([[float('nan'), 1, 5.0, float('+inf')],
...                [+0, -1.0, -5, float('-inf')]])
>>> y = x.log10()
>>> print(y)
ivy.array([[nan, 0., 0.699, inf],
[-inf, nan, nan, nan]])
```
Container.log10(self, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)#

ivy.Container instance method variant of ivy.log10. This method simply wraps the function, and so the docstring for ivy.log10 also applies to this method with minimal changes.

Parameters:
• self (`Container`) – input container. Should have a real-valued floating-point data type.

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

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

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

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

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

Return type:

`Container`

Returns:

ret – a container containing the evaluated base `10` logarithm for each element in `self`. The returned array must have a real-valued floating-point data type determined by type-promotion.

Examples

Using `ivy.Container` instance method:

```>>> x = ivy.Container(a=ivy.array([0.0, float('nan')]),
...                   b=ivy.array([-0., -3.9, float('+inf')]),
...                   c=ivy.array([7.9, 1.1, 1.]))
>>> y = x.log10()
>>> print(y)
{
a: ivy.array([-inf, nan]),
b: ivy.array([-inf, nan, inf]),
c: ivy.array([0.898, 0.0414, 0.])
}
```