Zero

class probnum.randprocs.mean_fns.Zero(input_shape, output_shape=())

Bases: probnum.Function

Zero mean function.

Attributes Summary

input_ndim	Syntactic sugar for len(input_shape).
input_shape	Shape of the function's input.
output_ndim	Syntactic sugar for len(output_shape).
output_shape	Shape of the function's output.

Methods Summary

__call__(x)

Evaluate the function at a given input.

Attributes Documentation

input_ndim

Syntactic sugar for len(input_shape).

Return type

int

input_shape

Shape of the function’s input.

For a scalar-input function, this is an empty tuple.

Return type

Tuple[int, ...]

output_ndim

Syntactic sugar for len(output_shape).

Return type

int

output_shape

Shape of the function’s output.

For scalar-valued function, this is an empty tuple.

Return type

Tuple[int, ...]

Methods Documentation

__call__(x)

Evaluate the function at a given input.

The function is vectorized over the batch shape of the input.

Parameters

x (Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]) – shape= batch_shape + input_shape – (Batch of) input(s) at which to evaluate the function.

Returns

shape= batch_shape + output_shape – Function evaluated at the given (batch of) input(s).

Return type

fx

Raises

ValueError – If the shape of x does not match input_shape along its last dimensions.