scirs2_optimize/sparse_numdiff/
compression.rs

1//! Compression techniques for sparse matrices in numerical differentiation
2//!
3//! This module provides implementations of compression algorithms for
4//! sparse matrices to reduce the number of function evaluations required
5//! for finite differences.
6
7use crate::error::OptimizeError;
8use ndarray::{Array2, ArrayView2};
9use scirs2_sparse::csr_array::CsrArray;
10
11/// Type alias for the return type of compress_jacobian_pattern
12pub type CompressedJacobianPattern = (CsrArray<f64>, Array2<f64>, Array2<f64>);
13
14/// Compresses a sparse Jacobian pattern for more efficient finite differencing
15///
16/// # Arguments
17///
18/// * `sparsity` - Sparse matrix representing the Jacobian sparsity pattern
19///
20/// # Returns
21///
22/// * Compressed sparsity pattern and compression matrices
23pub fn compress_jacobian_pattern(
24    sparsity: &CsrArray<f64>,
25) -> Result<CompressedJacobianPattern, OptimizeError> {
26    let (m, n) = sparsity.shape();
27
28    // This is a placeholder implementation that would need to be expanded
29    // with proper implementation of algorithms like direct or Curtis-Powell-Reid
30    // compression techniques.
31
32    // For now, just return an uncompressed pattern
33    let b = Array2::eye(n);
34    let c = Array2::eye(m);
35
36    Ok((sparsity.clone(), b, c))
37}
38
39/// Compresses a sparse Hessian pattern for more efficient finite differencing
40///
41/// # Arguments
42///
43/// * `sparsity` - Sparse matrix representing the Hessian sparsity pattern
44///
45/// # Returns
46///
47/// * Compressed sparsity pattern and compression matrix
48pub fn compress_hessian_pattern(
49    sparsity: &CsrArray<f64>,
50) -> Result<(CsrArray<f64>, Array2<f64>), OptimizeError> {
51    let (n, _) = sparsity.shape();
52
53    // This is a placeholder implementation that would need to be expanded
54    // with proper implementation of algorithms like Hessian compression techniques.
55
56    // For now, just return an uncompressed pattern
57    let p = Array2::eye(n);
58
59    Ok((sparsity.clone(), p))
60}
61
62/// Reconstructs a sparse Jacobian from compressed gradient evaluations
63///
64/// # Arguments
65///
66/// * `gradients` - Matrix of compressed gradient evaluations
67/// * `b` - Column compression matrix
68/// * `c` - Row compression matrix
69///
70/// # Returns
71///
72/// * Reconstructed sparse Jacobian
73pub fn reconstruct_jacobian(
74    _gradients: &ArrayView2<f64>,
75    _b: &ArrayView2<f64>,
76    _c: &ArrayView2<f64>,
77    _sparsity: &CsrArray<f64>,
78) -> Result<CsrArray<f64>, OptimizeError> {
79    // This is a placeholder implementation that would need to be expanded
80    // with proper reconstruction algorithms.
81
82    Err(OptimizeError::NotImplementedError(
83        "Jacobian reconstruction from compressed gradients is not yet implemented".to_string(),
84    ))
85}
86
87/// Reconstructs a sparse Hessian from compressed gradient evaluations
88///
89/// # Arguments
90///
91/// * `gradients` - Matrix of compressed gradient evaluations
92/// * `p` - Compression matrix
93///
94/// # Returns
95///
96/// * Reconstructed sparse Hessian
97pub fn reconstruct_hessian(
98    _gradients: &ArrayView2<f64>,
99    _p: &ArrayView2<f64>,
100    _sparsity: &CsrArray<f64>,
101) -> Result<CsrArray<f64>, OptimizeError> {
102    // This is a placeholder implementation that would need to be expanded
103    // with proper reconstruction algorithms.
104
105    Err(OptimizeError::NotImplementedError(
106        "Hessian reconstruction from compressed gradients is not yet implemented".to_string(),
107    ))
108}
scirs2_optimize/sparse_numdiff/compression.rs

scirs2_optimize/sparse_numdiff/
compression.rs
