sklears_decomposition/dictionary_learning/
lars_algorithms.rs

1//! Least Angle Regression (LARS) algorithms for dictionary learning
2
3use scirs2_core::ndarray::{Array1, Array2};
4#[cfg(feature = "serde")]
5use serde::{Deserialize, Serialize};
6use sklears_core::{error::Result, types::Float};
7
8/// Configuration for LARS algorithm
9#[derive(Debug, Clone)]
10#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
11pub struct LARSConfig {
12    /// Maximum number of active variables
13    pub max_iter: usize,
14    /// Regularization parameter
15    pub alpha: Float,
16}
17
18impl Default for LARSConfig {
19    fn default() -> Self {
20        Self {
21            max_iter: 500,
22            alpha: 1.0,
23        }
24    }
25}
26
27/// LARS algorithm result
28#[derive(Debug, Clone)]
29#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
30pub struct LARSResult {
31    /// Path coefficients
32    pub coefficients: Array2<Float>,
33    /// Active set indices
34    pub active_set: Vec<usize>,
35    /// Number of iterations
36    pub n_iter: usize,
37}
38
39/// LARS direction computation
40#[derive(Debug, Clone)]
41#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
42pub struct LARSDirection {
43    pub direction: Array1<Float>,
44    pub correlation: Float,
45}
46
47/// LARS step size computation
48#[derive(Debug, Clone)]
49#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
50pub struct LARSStepSize {
51    pub step_size: Float,
52    pub next_variable: Option<usize>,
53}
54
55/// LARS algorithm encoder
56#[derive(Debug, Clone)]
57#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
58pub struct LARSEncoder {
59    config: LARSConfig,
60}
61
62impl LARSEncoder {
63    pub fn new(config: LARSConfig) -> Self {
64        Self { config }
65    }
66
67    /// Perform LARS algorithm
68    pub fn encode(
69        &self,
70        dictionary: &Array2<Float>,
71        _signal: &Array1<Float>,
72    ) -> Result<LARSResult> {
73        let n_atoms = dictionary.nrows();
74
75        // Placeholder implementation
76        let coefficients = Array2::zeros((1, n_atoms));
77        let active_set = Vec::new();
78
79        Ok(LARSResult {
80            coefficients,
81            active_set,
82            n_iter: 0,
83        })
84    }
85}
sklears_decomposition/dictionary_learning/lars_algorithms.rs

sklears_decomposition/dictionary_learning/
lars_algorithms.rs
