1use anyhow::Result;
2use faer::Mat;
3use faer_ext::IntoFaer;
4use faer_ext::IntoNdarray;
5use ndarray::{Array2, ArrayView2};
6use pharmsol::prelude::simulator::psi;
7use pharmsol::Data;
8use pharmsol::Equation;
9use pharmsol::ErrorModel;
10
11use super::theta::Theta;
12
13#[derive(Debug, Clone, PartialEq)]
15pub struct Psi {
16 matrix: Mat<f64>,
17}
18
19impl Psi {
20 pub fn new() -> Self {
21 Psi { matrix: Mat::new() }
22 }
23
24 pub fn matrix(&self) -> &Mat<f64> {
25 &self.matrix
26 }
27
28 pub fn nspp(&self) -> usize {
29 self.matrix.nrows()
30 }
31
32 pub fn nsub(&self) -> usize {
33 self.matrix.ncols()
34 }
35
36 pub(crate) fn filter_column_indices(&mut self, indices: &[usize]) {
38 let matrix = self.matrix.to_owned();
39
40 let new = Mat::from_fn(matrix.nrows(), indices.len(), |r, c| {
41 *matrix.get(r, indices[c])
42 });
43
44 self.matrix = new;
45 }
46
47 pub fn write(&self, path: &str) {
49 let mut writer = csv::Writer::from_path(path).unwrap();
50 for row in self.matrix.row_iter() {
51 writer
52 .write_record(row.iter().map(|x| x.to_string()))
53 .unwrap();
54 }
55 }
56}
57
58impl Default for Psi {
59 fn default() -> Self {
60 Psi::new()
61 }
62}
63
64impl From<Array2<f64>> for Psi {
65 fn from(array: Array2<f64>) -> Self {
66 let matrix = array.view().into_faer().to_owned();
67 Psi { matrix }
68 }
69}
70
71impl From<Mat<f64>> for Psi {
72 fn from(matrix: Mat<f64>) -> Self {
73 Psi { matrix }
74 }
75}
76
77impl From<ArrayView2<'_, f64>> for Psi {
78 fn from(array_view: ArrayView2<'_, f64>) -> Self {
79 let matrix = array_view.into_faer().to_owned();
80 Psi { matrix }
81 }
82}
83
84impl From<&Array2<f64>> for Psi {
85 fn from(array: &Array2<f64>) -> Self {
86 let matrix = array.view().into_faer().to_owned();
87 Psi { matrix }
88 }
89}
90
91pub(crate) fn calculate_psi(
92 equation: &impl Equation,
93 subjects: &Data,
94 theta: &Theta,
95 error_model: &ErrorModel,
96 progress: bool,
97 cache: bool,
98) -> Result<Psi> {
99 let psi_ndarray = psi(
100 equation,
101 subjects,
102 &theta.matrix().clone().as_ref().into_ndarray().to_owned(),
103 error_model,
104 progress,
105 cache,
106 )?;
107
108 Ok(psi_ndarray.view().into())
109}