sklears_decomposition/dictionary_learning/
coordinate_descent.rs

1//! Coordinate Descent 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 Coordinate Descent algorithm
9#[derive(Debug, Clone)]
10#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
11pub struct CDConfig {
12    /// Maximum number of iterations
13    pub max_iter: usize,
14    /// Convergence tolerance
15    pub tol: Float,
16    /// Regularization parameter
17    pub alpha: Float,
18}
19
20impl Default for CDConfig {
21    fn default() -> Self {
22        Self {
23            max_iter: 1000,
24            tol: 1e-4,
25            alpha: 1.0,
26        }
27    }
28}
29
30/// Coordinate Descent result
31#[derive(Debug, Clone)]
32#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
33pub struct CDResult {
34    /// Sparse coefficients
35    pub coefficients: Array1<Float>,
36    /// Objective value
37    pub objective: Float,
38    /// Number of iterations
39    pub n_iter: usize,
40}
41
42/// Soft thresholding operator
43#[derive(Debug, Clone)]
44#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
45pub struct SoftThresholding {
46    pub threshold: Float,
47}
48
49impl SoftThresholding {
50    pub fn new(threshold: Float) -> Self {
51        Self { threshold }
52    }
53
54    pub fn apply(&self, x: Float) -> Float {
55        if x > self.threshold {
56            x - self.threshold
57        } else if x < -self.threshold {
58            x + self.threshold
59        } else {
60            0.0
61        }
62    }
63}
64
65/// Coordinate Descent encoder
66#[derive(Debug, Clone)]
67#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
68pub struct CDEncoder {
69    config: CDConfig,
70}
71
72impl CDEncoder {
73    pub fn new(config: CDConfig) -> Self {
74        Self { config }
75    }
76
77    /// Perform coordinate descent sparse coding
78    pub fn encode(&self, dictionary: &Array2<Float>, _signal: &Array1<Float>) -> Result<CDResult> {
79        let n_atoms = dictionary.nrows();
80        let coefficients = Array1::zeros(n_atoms);
81
82        // Placeholder implementation
83        let objective = 0.0;
84
85        Ok(CDResult {
86            coefficients,
87            objective,
88            n_iter: 0,
89        })
90    }
91}
sklears_decomposition/dictionary_learning/coordinate_descent.rs

sklears_decomposition/dictionary_learning/
coordinate_descent.rs
