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Patch to version 0.4.0 (#257)

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* uncomment test

* Add random test for logistic regression

* linting

* Bump version

* Add test for logistic regression

* linting

* initial commit

* final

* final-clean

* Bump to 0.4.0

* Fix linter

* cleanup

* Update CHANDELOG with breaking changes

* Update CHANDELOG date

* Add functional methods to DenseMatrix implementation

* linting

* add type declaration in test

* Fix Wasm tests failing

* linting

* fix tests

* linting

* Add type annotations on BBDTree constructor

* fix clippy

* fix clippy

* fix tests

* bump version

* run fmt. fix changelog

---------

Co-authored-by: Edmund Cape <edmund@Edmunds-MacBook-Pro.local>
This commit is contained in:
Lorenzo
2024-03-04 13:51:27 +00:00
committed by GitHub
parent 80a93c1a0e
commit 239c00428f
45 changed files with 759 additions and 406 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/linalg/traits/svd.rs
+19 -11
View File
@@ -17,7 +17,7 @@
//! &[0.9, 0.4, 0.7],
//! &[0.4, 0.5, 0.3],
//! &[0.7, 0.3, 0.8]
//! ]);
//! ]).unwrap();
//!
//! let svd = A.svd().unwrap();
//! let u: DenseMatrix<f64> = svd.U;
@@ -489,7 +489,8 @@ mod tests {
&[0.9000, 0.4000, 0.7000],
&[0.4000, 0.5000, 0.3000],
&[0.7000, 0.3000, 0.8000],
]);
])
.unwrap();
let s: Vec<f64> = vec![1.7498382, 0.3165784, 0.1335834];
@@ -497,13 +498,15 @@ mod tests {
&[0.6881997, -0.07121225, 0.7220180],
&[0.3700456, 0.89044952, -0.2648886],
&[0.6240573, -0.44947578, -0.639158],
]);
])
.unwrap();
let V = DenseMatrix::from_2d_array(&[
&[0.6881997, -0.07121225, 0.7220180],
&[0.3700456, 0.89044952, -0.2648886],
&[0.6240573, -0.44947578, -0.6391588],
]);
])
.unwrap();
let svd = A.svd().unwrap();
@@ -577,7 +580,8 @@ mod tests {
-0.2158704,
-0.27529472,
],
]);
])
.unwrap();
let s: Vec<f64> = vec![
3.8589375, 3.4396766, 2.6487176, 2.2317399, 1.5165054, 0.8109055, 0.2706515,
@@ -647,7 +651,8 @@ mod tests {
0.73034065,
-0.43965505,
],
]);
])
.unwrap();
let V = DenseMatrix::from_2d_array(&[
&[
@@ -707,7 +712,8 @@ mod tests {
0.1654796,
-0.32346758,
],
]);
])
.unwrap();
let svd = A.svd().unwrap();
@@ -723,10 +729,11 @@ mod tests {
)]
#[test]
fn solve() {
let a = DenseMatrix::from_2d_array(&[&[0.9, 0.4, 0.7], &[0.4, 0.5, 0.3], &[0.7, 0.3, 0.8]]);
let b = DenseMatrix::from_2d_array(&[&[0.5, 0.2], &[0.5, 0.8], &[0.5, 0.3]]);
let a = DenseMatrix::from_2d_array(&[&[0.9, 0.4, 0.7], &[0.4, 0.5, 0.3], &[0.7, 0.3, 0.8]])
.unwrap();
let b = DenseMatrix::from_2d_array(&[&[0.5, 0.2], &[0.5, 0.8], &[0.5, 0.3]]).unwrap();
let expected_w =
DenseMatrix::from_2d_array(&[&[-0.20, -1.28], &[0.87, 2.22], &[0.47, 0.66]]);
DenseMatrix::from_2d_array(&[&[-0.20, -1.28], &[0.87, 2.22], &[0.47, 0.66]]).unwrap();
let w = a.svd_solve_mut(b).unwrap();
assert!(relative_eq!(w, expected_w, epsilon = 1e-2));
}
@@ -737,7 +744,8 @@ mod tests {
)]
#[test]
fn decompose_restore() {
let a = DenseMatrix::from_2d_array(&[&[1.0, 2.0, 3.0, 4.0], &[5.0, 6.0, 7.0, 8.0]]);
let a =
DenseMatrix::from_2d_array(&[&[1.0, 2.0, 3.0, 4.0], &[5.0, 6.0, 7.0, 8.0]]).unwrap();
let svd = a.svd().unwrap();
let u: &DenseMatrix<f32> = &svd.U; //U
let v: &DenseMatrix<f32> = &svd.V; // V