Struct CatCIM 

pub struct CatCIM { /* private fields */ }

A struct representing a categorical conditional intensity matrix.

Implementations

impl CatCIM

pub fn new( states: States, conditioning_states: States, parameters: Array3<f64>, ) -> Self

Creates a new categorical conditional intensity matrix.

Arguments

• states - The variables states.
• parameters - The intensity matrices of the states.

Panics

• If the labels and conditioning labels are not disjoint.
• If the product of the shape of the states does not match the length of the second and third axis.
• If the product of the shape of the conditioning states does not match the length of the first axis.
• If the parameters are not valid intensity matrices, unless empty.

Returns

A new CatCIM instance.

pub const fn states(&self) -> &States

Returns the states of the conditioned variable.

Returns

The states of the conditioned variable.

pub const fn shape(&self) -> &Array1<usize>

Returns the shape of the conditioned variable.

Returns

The shape of the conditioned variable.

pub const fn multi_index(&self) -> &MI

Returns the ravel multi index of the conditioning variables.

Returns

The ravel multi index of the conditioning variables.

pub const fn conditioning_states(&self) -> &States

Returns the states of the conditioning variables.

Returns

The states of the conditioning variables.

pub const fn conditioning_shape(&self) -> &Array1<usize>

Returns the shape of the conditioning variables.

Returns

The shape of the conditioning variables.

pub const fn conditioning_multi_index(&self) -> &MI

Returns the ravel multi index of the conditioning variables.

Returns

The ravel multi index of the conditioning variables.

pub fn with_optionals( states: States, conditioning_states: States, parameters: Array3<f64>, sample_statistics: Option<CatCIMS>, sample_log_likelihood: Option<f64>, ) -> Self

Creates a new categorical conditional intensity matrix.

Arguments

• states - The variables states.
• parameters - The intensity matrices of the states.
• sample_statistics - The sample statistics used to fit the distribution, if any.
• sample_log_likelihood - The sample log-likelihood given the distribution, if any.

Panics

See new method for panics.

Returns

A new CatCIM instance.

Trait Implementations

impl AbsDiffEq for CatCIM

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 CIM for CatCIM

type Support = ArrayBase<OwnedRepr<u8>, Dim<[usize; 1]>>

The type of the support.

type Parameters = ArrayBase<OwnedRepr<f64>, Dim<[usize; 3]>>

The type of the parameters.

type Statistics = CatCIMS

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.

impl CIMEstimator<CatCIM> for BE<'_, CatTrj, ()>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for BE<'_, CatTrj, (usize, f64)>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for BE<'_, CatTrjs, ()>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for BE<'_, CatTrjs, (usize, f64)>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for BE<'_, CatWtdTrj, ()>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for BE<'_, CatWtdTrj, (usize, f64)>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for BE<'_, CatWtdTrjs, ()>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for BE<'_, CatWtdTrjs, (usize, f64)>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for MLE<'_, CatTrj>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for MLE<'_, CatTrjs>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for MLE<'_, CatWtdTrj>

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

Fits the estimator to the dataset and returns a CIM.

impl CIMEstimator<CatCIM> for MLE<'_, CatWtdTrjs>

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

Fits the estimator to the dataset and returns a CIM.

impl<R: Rng + SeedableRng> CIMEstimator<CatCIM> for RAWE<'_, R, CatTrjEv, CatTrj>

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

Fits the estimator to the dataset and returns a CIM.

impl<R: Rng + SeedableRng> CIMEstimator<CatCIM> for RAWE<'_, R, CatTrjsEv, CatTrjs>

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

Fits the estimator to the dataset and returns a CIM.

impl Clone for CatCIM

fn clone(&self) -> CatCIM

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CatCIM

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for CatCIM

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

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl JsonIO for CatCIM

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 CatCIM

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 ParCIMEstimator<CatCIM> for BE<'_, CatTrjs, ()>

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

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

impl ParCIMEstimator<CatCIM> for BE<'_, CatTrjs, (usize, f64)>

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

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

impl ParCIMEstimator<CatCIM> for BE<'_, CatWtdTrjs, ()>

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

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

impl ParCIMEstimator<CatCIM> for BE<'_, CatWtdTrjs, (usize, f64)>

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

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

impl ParCIMEstimator<CatCIM> for MLE<'_, CatTrjs>

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

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

impl ParCIMEstimator<CatCIM> for MLE<'_, CatWtdTrjs>

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

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

impl<R: Rng + SeedableRng> ParCIMEstimator<CatCIM> for RAWE<'_, R, CatTrjsEv, CatTrjs>

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

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

impl PartialEq for CatCIM

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 CatCIM

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 CatCIM

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

where S: Serializer,

Serialize this value into the given Serde serializer.