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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/decomposition/pca.rs
+13 -7
View File
@@ -35,7 +35,7 @@
//! &[4.9, 2.4, 3.3, 1.0],
//! &[6.6, 2.9, 4.6, 1.3],
//! &[5.2, 2.7, 3.9, 1.4],
//! ]);
//! ]).unwrap();
//!
//! let pca = PCA::fit(&iris, PCAParameters::default().with_n_components(2)).unwrap(); // Reduce number of features to 2
//!
@@ -443,6 +443,7 @@ mod tests {
&[2.6, 53.0, 66.0, 10.8],
&[6.8, 161.0, 60.0, 15.6],
])
.unwrap()
}
#[cfg_attr(
all(target_arch = "wasm32", not(target_os = "wasi")),
@@ -457,7 +458,8 @@ mod tests {
&[0.9952, 0.0588],
&[0.0463, 0.9769],
&[0.0752, 0.2007],
]);
])
.unwrap();
let pca = PCA::fit(&us_arrests, Default::default()).unwrap();
@@ -500,7 +502,8 @@ mod tests {
-0.974080592182491,
0.0723250196376097,
],
]);
])
.unwrap();
let expected_projection = DenseMatrix::from_2d_array(&[
&[-64.8022, -11.448, 2.4949, -2.4079],
@@ -553,7 +556,8 @@ mod tests {
&[91.5446, -22.9529, 0.402, -0.7369],
&[118.1763, 5.5076, 2.7113, -0.205],
&[10.4345, -5.9245, 3.7944, 0.5179],
]);
])
.unwrap();
let expected_eigenvalues: Vec<f64> = vec![
343544.6277001563,
@@ -616,7 +620,8 @@ mod tests {
-0.0881962972508558,
-0.0096011588898465,
],
]);
])
.unwrap();
let expected_projection = DenseMatrix::from_2d_array(&[
&[0.9856, -1.1334, 0.4443, -0.1563],
@@ -669,7 +674,8 @@ mod tests {
&[-2.1086, -1.4248, -0.1048, -0.1319],
&[-2.0797, 0.6113, 0.1389, -0.1841],
&[-0.6294, -0.321, 0.2407, 0.1667],
]);
])
.unwrap();
let expected_eigenvalues: Vec<f64> = vec![
2.480241579149493,
@@ -732,7 +738,7 @@ mod tests {
// &[4.9, 2.4, 3.3, 1.0],
// &[6.6, 2.9, 4.6, 1.3],
// &[5.2, 2.7, 3.9, 1.4],
// ]);
// ]).unwrap();
// let pca = PCA::fit(&iris, Default::default()).unwrap();
src/decomposition/svd.rs
+6 -4
View File
@@ -32,7 +32,7 @@
//! &[4.9, 2.4, 3.3, 1.0],
//! &[6.6, 2.9, 4.6, 1.3],
//! &[5.2, 2.7, 3.9, 1.4],
//! ]);
//! ]).unwrap();
//!
//! let svd = SVD::fit(&iris, SVDParameters::default().
//! with_n_components(2)).unwrap(); // Reduce number of features to 2
@@ -292,7 +292,8 @@ mod tests {
&[5.7, 81.0, 39.0, 9.3],
&[2.6, 53.0, 66.0, 10.8],
&[6.8, 161.0, 60.0, 15.6],
]);
])
.unwrap();
let expected = DenseMatrix::from_2d_array(&[
&[243.54655757, -18.76673788],
@@ -300,7 +301,8 @@ mod tests {
&[305.93972467, -15.39087376],
&[197.28420365, -11.66808306],
&[293.43187394, 1.91163633],
]);
])
.unwrap();
let svd = SVD::fit(&x, Default::default()).unwrap();
let x_transformed = svd.transform(&x).unwrap();
@@ -341,7 +343,7 @@ mod tests {
// &[4.9, 2.4, 3.3, 1.0],
// &[6.6, 2.9, 4.6, 1.3],
// &[5.2, 2.7, 3.9, 1.4],
// ]);
// ]).unwrap();
// let svd = SVD::fit(&iris, Default::default()).unwrap();