Struct Data

pub struct Data { /* private fields */ }

The main data container for pharmacokinetic/pharmacodynamic data

Data is a collection of Subject instances, which themselves contain Occasion instances with Events. This structure represents the complete dataset for pharmacometric analysis.

Examples

use pharmsol::*;

// Create subjects
let subject1 = Subject::builder("patient_001")
    .bolus(0.0, 100.0, 0)
    .observation(1.0, 5.0, 0)
    .build();
     
let subject2 = Subject::builder("patient_002")
    .bolus(0.0, 120.0, 0)
    .observation(1.0, 6.0, 0)
    .build();
     
// Create dataset with multiple subjects
let mut data = Data::new(vec![subject1]);
data.add_subject(subject2);

// Filter data
let filtered = data.filter_include(&["patient_001".to_string()]);

Implementations

impl Data

pub fn new(subjects: Vec<Subject>) -> Data

Constructs a new Data object from a vector of Subjects

It is recommended to construct subjects using the [SubjectBuilder] to ensure proper data formatting.

Arguments

• subjects - Vector of Subjects to include in the dataset

pub fn get_subjects(&self) -> Vec<&Subject>

Get a vector of references to all subjects in the dataset

Returns

Vector of references to all subjects

pub fn add_subject(&mut self, subject: Subject)

Add a subject to the dataset

Arguments

• subject - Subject to add to the dataset

pub fn get_subject(&self, id: &str) -> Option<&Subject>

Get a specific subject by ID

Arguments

• id - The ID of the subject to retrieve

Returns

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

pub fn write_pmetrics(&self, file: &File) -> Result<(), PharmsolError>

Write the dataset to a file in Pmetrics format

Arguments

• file - The file to write to

pub fn filter_include(&self, include: &[String]) -> Data

Filter the dataset to include only subjects with specific IDs

Arguments

• include - Vector of subject IDs to include

Returns

A new Data object containing only the specified subjects

pub fn filter_exclude(&self, exclude: Vec<String>) -> Data

Filter the dataset to exclude subjects with specific IDs

Arguments

• exclude - Vector of subject IDs to exclude

Returns

A new Data object with the specified subjects excluded

pub fn expand(&self, idelta: f64, tad: f64) -> Data

Expand the dataset by adding observations at regular time intervals

This is useful for creating a dense grid of time points for simulations.

Arguments

• idelta - Time interval between added observations
• tad - Additional time to add after the last observation

Returns

A new Data object with expanded observations

Trait Implementations

impl Clone for Data

fn clone(&self) -> Data

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Data

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

Formats the value using the given formatter.

impl Default for Data

fn default() -> Data

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Data

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for Data

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

Formats the value using the given formatter.

impl IntoIterator for Data

type Item = Subject

The type of the elements being iterated over.

type IntoIter = IntoIter<Subject>

Which kind of iterator are we turning this into?

fn into_iter(self) -> <Data as IntoIterator>::IntoIter

Creates an iterator from a value.

impl Serialize for Data

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.