Function¶

class probnum.Function(input_shape, output_shape=())¶

Bases: abc.ABC

Callable with information about the shape of expected in- and outputs.

This class represents a, uni- or multivariate, scalar- or tensor-valued, mathematical function. Hence, the call method should not have any observable side-effects.

Parameters

input_shape (Union[int, Integral, integer, Iterable[Union[int, Integral, integer]]]) – Input shape.
output_shape (Union[int, Integral, integer, Iterable[Union[int, Integral, integer]]]) – Output shape.

See also

LambdaFunction: Define a Function from an anonymous function.
Zero: Zero mean function of a random process.

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)[source]¶

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.