Struct Scalar

pub struct Scalar { /* private fields */ }

A scalar-valued Amplitude which just contains a single parameter as its value.

Implementations

impl Scalar

pub fn new(name: &str, value: ParameterLike) -> Box<Scalar>

Create a new Scalar with the given name and parameter value.

Trait Implementations

impl Amplitude for Scalar

fn register( &mut self, resources: &mut Resources, ) -> Result<AmplitudeID, LadduError>

This method should be used to tell the Resources manager about all of the free parameters and cached values used by this Amplitude. It should end by returning an AmplitudeID, which can be obtained from the Resources::register_amplitude method.

fn compute( &self, parameters: &Parameters<'_>, _event: &Event, _cache: &Cache, ) -> Complex<f64>

This method constitutes the main machinery of an Amplitude, returning the actual calculated value for a particular Event and set of Parameters. See those structs, as well as Cache, for documentation on their available methods. For the most part, Events can be interacted with via Variables, while Parameters and the Cache are more like key-value storage accessed by ParameterIDs and several different types of cache IDs.

fn compute_gradient( &self, _parameters: &Parameters<'_>, _event: &Event, _cache: &Cache, gradient: &mut Matrix<Complex<f64>, Dyn, Const<1>, VecStorage<Complex<f64>, Dyn, Const<1>>>, )

This method yields the gradient of a particular Amplitude at a point specified by a particular Event and set of Parameters. See those structs, as well as Cache, for documentation on their available methods. For the most part, Events can be interacted with via Variables, while Parameters and the Cache are more like key-value storage accessed by ParameterIDs and several different types of cache IDs. If the analytic version of the gradient is known, this method can be overwritten to improve performance for some derivative-using methods of minimization. The default implementation calculates a central finite difference across all parameters, regardless of whether or not they are used in the Amplitude.

fn precompute(&self, event: &Event, cache: &mut Cache)

This method can be used to do some critical calculations ahead of time and store them in a Cache. These values can only depend on the data in an Event, not on any free parameters in the fit. This method is opt-in since it is not required to make a functioning Amplitude.

fn precompute_all(&self, dataset: &Dataset, resources: &mut Resources)

Evaluates Amplitude::precompute over ever Event in a Dataset.

fn central_difference_with_indices( &self, indices: &[usize], parameters: &Parameters<'_>, event: &Event, cache: &Cache, gradient: &mut Matrix<Complex<f64>, Dyn, Const<1>, VecStorage<Complex<f64>, Dyn, Const<1>>>, )

A helper function to implement a central difference only on indices which correspond to free parameters in the Amplitude. For example, if an Amplitude contains free parameters registered to indices 1, 3, and 5 of the its internal parameters array, then running this with those indices will compute a central finite difference derivative for those coordinates only, since the rest can be safely assumed to be zero.

impl Clone for Scalar

fn clone(&self) -> Scalar

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<'de> Deserialize<'de> for Scalar

fn deserialize<__D>( __deserializer: __D, ) -> Result<Scalar, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for Scalar

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.