Struct Subject 

pub struct Subject { /* private fields */ }

A subject in a pharmacometric dataset

A Subject represents a single individual with one or more occasions of data, each containing events (doses, observations) and covariates.

Implementations

impl Subject

pub fn occasions(&self) -> &[Occasion]

Get a vector of references to all occasions for this subject

Returns

A slice of all occasions for this subject

pub fn id(&self) -> &String

Get the ID of the subject

Returns

The subject’s identifier

pub fn from_occasions(id: String, occasions: Vec<Occasion>) -> Self

Create a new subject from one or more occasions

This is useful when you want to create a subject from specific occasions rather than building it completely from scratch.

Arguments

• id - The subject identifier
• occasions - Vector of occasions to include in this subject

Returns

A new subject containing the specified occasions

pub fn occasions_mut(&mut self) -> &mut Vec<Occasion>

Iterate over a mutable reference to the occasions

pub fn occasions_iter_mut(&mut self) -> IterMut<'_, Occasion>

Get a mutable iterator to the occasions

pub fn get_output_equations(&self) -> Vec<usize>

pub fn get_occasion_mut(&mut self, index: usize) -> Option<&mut Occasion>

Get a mutable reference to an occasion by index

Arguments

• index - The index of the occasion to retrieve

Returns

An Option containing a mutable reference to the occasion if found, or None if not found

pub fn iter(&self) -> Iter<'_, Occasion>

Get an iterator over all occasions

Returns

An iterator yielding references to occasions

pub fn iter_mut(&mut self) -> IterMut<'_, Occasion>

Get a mutable iterator over all occasions

Returns

A mutable iterator yielding references to occasions

pub fn len(&self) -> usize

Get the number of occasions for this subject

Returns

The number of occasions

pub fn is_empty(&self) -> bool

Check if the subject has any occasions

Returns

true if there are no occasions, false otherwise

pub fn hash(&self) -> u64

Calculate the hash for a subject

The hash takes into account all events, so that if a subject is modified, it will not produce the same likelihood when simulated with the same support point. Note that covariates are not included in the hash, but a method exists to hash covariates if needed.

impl Subject

pub fn nca_with_dose( &self, dose_amount: f64, route: Route, infusion_duration: Option<f64>, options: &NCAOptions, ) -> Result<NCAResult, NCAError>

Run NCA with an explicit dose on the first occasion, overriding what is embedded in the subject’s events.

Use this when you want to supply or override dose amount, route, or infusion duration without modifying the underlying data.

Trait Implementations

impl Clone for Subject

fn clone(&self) -> Subject

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Subject

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for Subject

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for Subject

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

Formats the value using the given formatter.

impl Into<Data> for Subject

fn into(self) -> Data

Convert a subject into a Data object

impl<'a> IntoIterator for &'a Subject

fn into_iter(self) -> Self::IntoIter

Iterate immutably over all occasions in the subject

type Item = &'a Occasion

The type of the elements being iterated over.

type IntoIter = Iter<'a, Occasion>

Which kind of iterator are we turning this into?

impl<'a> IntoIterator for &'a mut Subject

fn into_iter(self) -> Self::IntoIter

Iterate mutably over all occasions in the subject

type Item = &'a mut Occasion

The type of the elements being iterated over.

type IntoIter = IterMut<'a, Occasion>

Which kind of iterator are we turning this into?

impl IntoIterator for Subject

fn into_iter(self) -> Self::IntoIter

Consumes the subject and yields owned occasions

type Item = Occasion

The type of the elements being iterated over.

type IntoIter = IntoIter<Occasion>

Which kind of iterator are we turning this into?

impl NCA for Subject

fn nca(&self, options: &NCAOptions) -> Result<NCAResult, NCAError>

NCA on the first occasion (the common case). Returns a single result.

fn nca_all(&self, options: &NCAOptions) -> Vec<Result<NCAResult, NCAError>>

NCA on all occasions. Returns a Vec of results.

impl ObservationMetrics for Subject

fn auc_blq( &self, outeq: usize, method: &AUCMethod, blq_rule: &BLQRule, ) -> Vec<Result<f64, MetricsError>>

Calculate AUC from time 0 to Tlast with explicit BLQ handling

fn auc_interval_blq( &self, outeq: usize, start: f64, end: f64, method: &AUCMethod, blq_rule: &BLQRule, ) -> Vec<Result<f64, MetricsError>>

Calculate partial AUC over a time interval with explicit BLQ handling

fn cmax_blq( &self, outeq: usize, blq_rule: &BLQRule, ) -> Vec<Result<f64, MetricsError>>

Get Cmax with explicit BLQ handling

fn tmax_blq( &self, outeq: usize, blq_rule: &BLQRule, ) -> Vec<Result<f64, MetricsError>>

Get Tmax with explicit BLQ handling

fn clast_blq( &self, outeq: usize, blq_rule: &BLQRule, ) -> Vec<Result<f64, MetricsError>>

Get Clast with explicit BLQ handling

fn tlast_blq( &self, outeq: usize, blq_rule: &BLQRule, ) -> Vec<Result<f64, MetricsError>>

Get Tlast with explicit BLQ handling

fn aumc_blq( &self, outeq: usize, method: &AUCMethod, blq_rule: &BLQRule, ) -> Vec<Result<f64, MetricsError>>

Calculate AUMC with explicit BLQ handling

fn auc( &self, outeq: usize, method: &AUCMethod, ) -> Vec<Result<f64, MetricsError>>

Calculate AUC from time 0 to Tlast

fn auc_interval( &self, outeq: usize, start: f64, end: f64, method: &AUCMethod, ) -> Vec<Result<f64, MetricsError>>

Calculate partial AUC over a time interval

fn cmax(&self, outeq: usize) -> Vec<Result<f64, MetricsError>>

Get Cmax

fn tmax(&self, outeq: usize) -> Vec<Result<f64, MetricsError>>

Get Tmax

fn clast(&self, outeq: usize) -> Vec<Result<f64, MetricsError>>

Get Clast

fn tlast(&self, outeq: usize) -> Vec<Result<f64, MetricsError>>

Get Tlast

fn aumc( &self, outeq: usize, method: &AUCMethod, ) -> Vec<Result<f64, MetricsError>>

Calculate AUMC

fn auc_first( &self, outeq: usize, method: &AUCMethod, ) -> Result<f64, MetricsError>

Calculate AUC for the first occasion

fn cmax_first(&self, outeq: usize) -> Result<f64, MetricsError>

Get Cmax for the first occasion

fn tmax_first(&self, outeq: usize) -> Result<f64, MetricsError>

Get Tmax for the first occasion

fn clast_first(&self, outeq: usize) -> Result<f64, MetricsError>

Get Clast for the first occasion

fn tlast_first(&self, outeq: usize) -> Result<f64, MetricsError>

Get Tlast for the first occasion

fn aumc_first( &self, outeq: usize, method: &AUCMethod, ) -> Result<f64, MetricsError>

Calculate AUMC for the first occasion

fn auc_interval_first( &self, outeq: usize, start: f64, end: f64, method: &AUCMethod, ) -> Result<f64, MetricsError>

Calculate partial AUC for the first occasion

fn auc_blq_first( &self, outeq: usize, method: &AUCMethod, blq_rule: &BLQRule, ) -> Result<f64, MetricsError>

Calculate AUC for the first occasion with explicit BLQ handling

fn cmax_blq_first( &self, outeq: usize, blq_rule: &BLQRule, ) -> Result<f64, MetricsError>

Get Cmax for the first occasion with explicit BLQ handling

fn auc_interval_blq_first( &self, outeq: usize, start: f64, end: f64, method: &AUCMethod, blq_rule: &BLQRule, ) -> Result<f64, MetricsError>

Calculate partial AUC for the first occasion with explicit BLQ handling

impl Serialize for Subject

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl SubjectBuilderExt for Subject

fn builder(id: impl Into<String>) -> SubjectBuilder

Create a new SubjectBuilder with the specified ID

impl Superposition for Subject

fn superposition( &self, tau: f64, options: &NCAOptions, n_eval_points: Option<usize>, ) -> Result<SuperpositionResult, NCAError>

Predict steady-state profile via superposition

fn superposition_from_nca( &self, nca_result: &NCAResult, tau: f64, n_eval_points: Option<usize>, ) -> Result<SuperpositionResult, NCAError>

Predict steady-state profile using a pre-computed NCAResult