Struct GaussCPD 

pub struct GaussCPD { /* private fields */ }

A Gaussian CPD.

Implementations

impl GaussCPD

pub fn new( labels: Labels, conditioning_labels: Labels, parameters: GaussCPDP, ) -> Self

Creates a new Gaussian CPD instance.

Arguments

• labels - Labels of the variables.
• conditioning_labels - Labels of the conditioning variables.
• parameters - Parameters of the CPD.

Panics

• Panics if labels and conditioning_labels are not disjoint.
• Panics if the dimensions of parameters do not match the lengths of labels and conditioning_labels.

Returns

A new Gaussian CPD instance.

pub fn marginalize(&self, x: &Set<usize>, z: &Set<usize>) -> Self

Marginalizes the over the variables X and conditioning variables Z.

Arguments

• x - The variables to marginalize over.
• z - The conditioning variables to marginalize over.

Returns

A new instance with the marginalized variables.

pub fn with_optionals( labels: Labels, conditioning_labels: Labels, parameters: GaussCPDP, sample_statistics: Option<GaussCPDS>, sample_log_likelihood: Option<f64>, ) -> Self

Creates a new Gaussian CPD instance.

Arguments

• labels - Labels of the variables.
• conditioning_labels - Labels of the conditioning variables.
• parameters - Parameters of the CPD.
• sample_statistics - Sample (sufficient) statistics, if any.
• sample_log_likelihood - Sample log-likelihood, if any.

Returns

A new Gaussian CPD instance.

pub fn from_phi(phi: GaussPhi, x: &Set<usize>, z: &Set<usize>) -> Self

Converts a potential \phi(X \cup Z) to a CPD P(X | Z).

Arguments

• x - The set of variables.
• z - The set of conditioning variables.

Returns

The corresponding CPD.

pub fn into_phi(self) -> GaussPhi

Converts a CPD P(X | Z) to a potential \phi(X \cup Z).

Arguments

• cpd - The CPD to convert.

Returns

The corresponding potential.

Trait Implementations

impl AbsDiffEq for GaussCPD

type Epsilon = f64

Used for specifying relative comparisons.

fn default_epsilon() -> Self::Epsilon

The default tolerance to use when testing values that are close together.

fn abs_diff_eq(&self, other: &Self, epsilon: Self::Epsilon) -> bool

A test for equality that uses the absolute difference to compute the approximate equality of two numbers.

fn abs_diff_ne(&self, other: &Rhs, epsilon: Self::Epsilon) -> bool

The inverse of AbsDiffEq::abs_diff_eq.

impl CPD for GaussCPD

type Support = ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>

The type of the support.

type Parameters = GaussCPDP

The type of the parameters.

type Statistics = GaussCPDS

The type of the sufficient statistics.

fn conditioning_labels(&self) -> &Labels

Returns the labels of the conditioned variables.

fn parameters(&self) -> &Self::Parameters

Returns the parameters.

fn parameters_size(&self) -> usize

Returns the parameters size.

fn sample_statistics(&self) -> Option<&Self::Statistics>

Returns the sufficient statistics, if any.

fn sample_log_likelihood(&self) -> Option<f64>

Returns the log-likelihood of the fitted dataset, if any.

fn pf(&self, x: &Self::Support, z: &Self::Support) -> f64

Returns the value of probability (mass or density) function for P(X = x | Z = z).

fn sample<R: Rng>(&self, rng: &mut R, z: &Self::Support) -> Self::Support

Samples from the conditional distribution P(X | Z = z).

impl CPDEstimator<GaussCPD> for MLE<'_, GaussTable>

fn fit(&self, x: &Set<usize>, z: &Set<usize>) -> GaussCPD

Fits the estimator to the dataset and returns a CPD.

impl CPDEstimator<GaussCPD> for MLE<'_, GaussWtdTable>

fn fit(&self, x: &Set<usize>, z: &Set<usize>) -> GaussCPD

Fits the estimator to the dataset and returns a CPD.

impl Clone for GaussCPD

fn clone(&self) -> GaussCPD

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GaussCPD

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for GaussCPD

fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl JsonIO for GaussCPD

fn from_json(json: &str) -> Self

Create an instance of the type from a JSON string.

fn to_json(&self) -> String

Convert the instance to a JSON string.

fn read_json(path: &str) -> Self

Create an instance of the type from a JSON file.

fn write_json(&self, path: &str)

Write the instance to a JSON file.

impl Labelled for GaussCPD

fn labels(&self) -> &Labels

Returns the labels of the variables.

fn label_to_index(&self, x: &str) -> usize

Return the variable index for a given label.

fn index_to_label(&self, x: usize) -> &str

Return the label for a given variable index.

fn index_to(&self, x: usize, other: &Labels) -> usize

Maps an index from this model to another model with the same label.

fn indices_to(&self, x: &Set<usize>, other: &Labels) -> Set<usize>

Maps a set of indices from this model to another model with the same labels.

fn index_from(&self, x: usize, other: &Labels) -> usize

Maps an index from another model to this model with the same label.

fn indices_from(&self, x: &Set<usize>, other: &Labels) -> Set<usize>

Maps a set of indices from another model to this model with the same labels.

impl ParCPDEstimator<GaussCPD> for MLE<'_, GaussTable>

fn par_fit(&self, x: &Set<usize>, z: &Set<usize>) -> GaussCPD

Fits the estimator to the dataset and returns a CPD in parallel.

impl ParCPDEstimator<GaussCPD> for MLE<'_, GaussWtdTable>

fn par_fit(&self, x: &Set<usize>, z: &Set<usize>) -> GaussCPD

Fits the estimator to the dataset and returns a CPD in parallel.

impl PartialEq for GaussCPD

fn eq(&self, other: &Self) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl RelativeEq for GaussCPD

fn default_max_relative() -> Self::Epsilon

The default relative tolerance for testing values that are far-apart.

fn relative_eq( &self, other: &Self, epsilon: Self::Epsilon, max_relative: Self::Epsilon, ) -> bool

A test for equality that uses a relative comparison if the values are far apart.

fn relative_ne( &self, other: &Rhs, epsilon: Self::Epsilon, max_relative: Self::Epsilon, ) -> bool

The inverse of RelativeEq::relative_eq.

impl Serialize for GaussCPD

fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>

where S: Serializer,

Serialize this value into the given Serde serializer.