SumFunction¶
- class probnum.functions.SumFunction(*summands)[source]¶
Bases:
FunctionPointwise sum of
Functions.Given functions \(f_1, \dotsc, f_n \colon \mathbb{R}^n \to \mathbb{R}^m\), this defines a new function
\[\sum_{i = 1}^n f_i \colon \mathbb{R}^n \to \mathbb{R}^m, x \mapsto \sum_{i = 1}^n f_i(x).\]- Parameters:
*summands (Function) – The functions \(f_1, \dotsc, f_n\).
Attributes Summary
Syntactic sugar for
len(input_shape).Shape of the function's input.
Syntactic sugar for
len(output_shape).Shape of the function's output.
The functions \(f_1, \dotsc, f_n\) to be added.
Methods Summary
__call__(x)Evaluate the function at a given input.
Attributes Documentation
- input_ndim¶
Syntactic sugar for
len(input_shape).
- input_shape¶
Shape of the function’s input.
For a scalar-input function, this is an empty tuple.
- output_ndim¶
Syntactic sugar for
len(output_shape).
- output_shape¶
Shape of the function’s output.
For scalar-valued function, this is an empty tuple.
- summands¶
The functions \(f_1, \dotsc, f_n\) to be added.
Methods Documentation
- __call__(x)¶
Evaluate the function at a given input.
The function is vectorized over the batch shape of the input.
- Parameters:
x (ArrayLike) – 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
xdoes not matchinput_shapealong its last dimensions.