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Fix 256: Makes instantiating DenseMatrix and others fallible #258

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Fix 256: Makes instantiating DenseMatrix and others fallible #258

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2c781ec
initial commit
Apr 4, 2023
4c9a650
final
Apr 4, 2023
de1a43a
final-clean
Apr 4, 2023
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3 changes: 2 additions & 1 deletion src/algorithm/neighbour/bbd_tree.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -343,7 +343,8 @@ 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 tree = BBDTree::new(&data);

Expand Down
18 changes: 11 additions & 7 deletions src/algorithm/neighbour/fastpair.rs
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Expand Up @@ -17,7 +17,7 @@
/// &[4.6, 3.1, 1.5, 0.2],
/// &[5.0, 3.6, 1.4, 0.2],
/// &[5.4, 3.9, 1.7, 0.4],
/// ]);
/// ]).unwrap();
/// let fastpair = FastPair::new(&x);
/// let closest_pair: PairwiseDistance<f64> = fastpair.unwrap().closest_pair();
/// ```
Expand Down Expand Up @@ -271,7 +271,7 @@ mod tests_fastpair {
fn dataset_has_at_least_three_points() {
// Create a dataset which consists of only two points:
// A(0.0, 0.0) and B(1.0, 1.0).
let dataset = DenseMatrix::<f64>::from_2d_array(&[&[0.0, 0.0], &[1.0, 1.0]]);
let dataset = DenseMatrix::<f64>::from_2d_array(&[&[0.0, 0.0], &[1.0, 1.0]]).unwrap();

// We expect an error when we run `FastPair` on this dataset,
// becuase `FastPair` currently only works on a minimum of 3
Expand All @@ -288,7 +288,7 @@ mod tests_fastpair {

#[test]
fn one_dimensional_dataset_minimal() {
let dataset = DenseMatrix::<f64>::from_2d_array(&[&[0.0], &[2.0], &[9.0]]);
let dataset = DenseMatrix::<f64>::from_2d_array(&[&[0.0], &[2.0], &[9.0]]).unwrap();

let result = FastPair::new(&dataset);
assert!(result.is_ok());
Expand All @@ -308,7 +308,8 @@ mod tests_fastpair {

#[test]
fn one_dimensional_dataset_2() {
let dataset = DenseMatrix::<f64>::from_2d_array(&[&[27.0], &[0.0], &[9.0], &[2.0]]);
let dataset =
DenseMatrix::<f64>::from_2d_array(&[&[27.0], &[0.0], &[9.0], &[2.0]]).unwrap();

let result = FastPair::new(&dataset);
assert!(result.is_ok());
Expand Down Expand Up @@ -343,7 +344,8 @@ mod tests_fastpair {
&[6.9, 3.1, 4.9, 1.5],
&[5.5, 2.3, 4.0, 1.3],
&[6.5, 2.8, 4.6, 1.5],
]);
])
.unwrap();
let fastpair = FastPair::new(&x);
assert!(fastpair.is_ok());

Expand Down Expand Up @@ -516,7 +518,8 @@ mod tests_fastpair {
&[6.9, 3.1, 4.9, 1.5],
&[5.5, 2.3, 4.0, 1.3],
&[6.5, 2.8, 4.6, 1.5],
]);
])
.unwrap();
// compute
let fastpair = FastPair::new(&x);
assert!(fastpair.is_ok());
Expand Down Expand Up @@ -564,7 +567,8 @@ mod tests_fastpair {
&[6.9, 3.1, 4.9, 1.5],
&[5.5, 2.3, 4.0, 1.3],
&[6.5, 2.8, 4.6, 1.5],
]);
])
.unwrap();
// compute
let fastpair = FastPair::new(&x);
assert!(fastpair.is_ok());
Expand Down
6 changes: 4 additions & 2 deletions src/cluster/dbscan.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -443,7 +443,8 @@ mod tests {
&[2.2, 1.2],
&[1.8, 0.8],
&[3.0, 5.0],
]);
])
.unwrap();

let expected_labels = vec![1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 0];

Expand Down Expand Up @@ -488,7 +489,8 @@ 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 dbscan = DBSCAN::fit(&x, Default::default()).unwrap();

Expand Down
12 changes: 7 additions & 5 deletions src/cluster/kmeans.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@
//! &[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 kmeans = KMeans::fit(&x, KMeansParameters::default().with_k(2)).unwrap(); // Fit to data, 2 clusters
//! let y_hat: Vec<u8> = kmeans.predict(&x).unwrap(); // use the same points for prediction
Expand Down Expand Up @@ -249,7 +249,7 @@ impl<TX: Number, TY: Number, X: Array2<TX>, Y: Array1<TY>> Predictor<X, Y>

impl<TX: Number, TY: Number, X: Array2<TX>, Y: Array1<TY>> KMeans<TX, TY, X, Y> {
/// Fit algorithm to _NxM_ matrix where _N_ is number of samples and _M_ is number of features.
/// * `data` - training instances to cluster
/// * `data` - training instances to cluster
/// * `parameters` - cluster parameters
pub fn fit(data: &X, parameters: KMeansParameters) -> Result<KMeans<TX, TY, X, Y>, Failed> {
let bbd = BBDTree::new(data);
Expand Down Expand Up @@ -424,7 +424,7 @@ mod tests {
)]
#[test]
fn invalid_k() {
let x = DenseMatrix::from_2d_array(&[&[1, 2, 3], &[4, 5, 6]]);
let x = DenseMatrix::from_2d_array(&[&[1, 2, 3], &[4, 5, 6]]).unwrap();

assert!(KMeans::<i32, i32, DenseMatrix<i32>, Vec<i32>>::fit(
&x,
Expand Down Expand Up @@ -492,7 +492,8 @@ 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 kmeans = KMeans::fit(&x, Default::default()).unwrap();

Expand Down Expand Up @@ -531,7 +532,8 @@ 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 kmeans: KMeans<f32, f32, DenseMatrix<f32>, Vec<f32>> =
KMeans::fit(&x, Default::default()).unwrap();
Expand Down
20 changes: 13 additions & 7 deletions src/decomposition/pca.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -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
//!
Expand Down Expand Up @@ -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")),
Expand All @@ -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();

Expand Down Expand Up @@ -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],
Expand Down Expand Up @@ -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,
Expand Down Expand Up @@ -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],
Expand Down Expand Up @@ -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,
Expand Down Expand Up @@ -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();

Expand Down
10 changes: 6 additions & 4 deletions src/decomposition/svd.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -292,15 +292,17 @@ 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],
&[268.36802004, -33.79304302],
&[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();
Expand Down Expand Up @@ -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();

Expand Down
11 changes: 7 additions & 4 deletions src/ensemble/random_forest_classifier.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@
//! &[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 y = vec![
//! 0, 0, 0, 0, 0, 0, 0, 0,
//! 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
Expand Down Expand Up @@ -660,7 +660,8 @@ 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 y = vec![0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1];

let classifier = RandomForestClassifier::fit(
Expand Down Expand Up @@ -733,7 +734,8 @@ 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 y = vec![0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1];

let classifier = RandomForestClassifier::fit(
Expand Down Expand Up @@ -786,7 +788,8 @@ 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 y = vec![0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1];

let forest = RandomForestClassifier::fit(&x, &y, Default::default()).unwrap();
Expand Down
11 changes: 7 additions & 4 deletions src/ensemble/random_forest_regressor.rs
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Expand Up @@ -29,7 +29,7 @@
//! &[502.601, 393.1, 251.4, 125.368, 1960., 69.564],
//! &[518.173, 480.6, 257.2, 127.852, 1961., 69.331],
//! &[554.894, 400.7, 282.7, 130.081, 1962., 70.551],
//! ]);
//! ]).unwrap();
//! let y = vec![
//! 83.0, 88.5, 88.2, 89.5, 96.2, 98.1, 99.0, 100.0, 101.2,
//! 104.6, 108.4, 110.8, 112.6, 114.2, 115.7, 116.9
Expand Down Expand Up @@ -574,7 +574,8 @@ mod tests {
&[502.601, 393.1, 251.4, 125.368, 1960., 69.564],
&[518.173, 480.6, 257.2, 127.852, 1961., 69.331],
&[554.894, 400.7, 282.7, 130.081, 1962., 70.551],
]);
])
.unwrap();
let y = vec![
83.0, 88.5, 88.2, 89.5, 96.2, 98.1, 99.0, 100.0, 101.2, 104.6, 108.4, 110.8, 112.6,
114.2, 115.7, 116.9,
Expand Down Expand Up @@ -648,7 +649,8 @@ mod tests {
&[502.601, 393.1, 251.4, 125.368, 1960., 69.564],
&[518.173, 480.6, 257.2, 127.852, 1961., 69.331],
&[554.894, 400.7, 282.7, 130.081, 1962., 70.551],
]);
])
.unwrap();
let y = vec![
83.0, 88.5, 88.2, 89.5, 96.2, 98.1, 99.0, 100.0, 101.2, 104.6, 108.4, 110.8, 112.6,
114.2, 115.7, 116.9,
Expand Down Expand Up @@ -702,7 +704,8 @@ mod tests {
&[502.601, 393.1, 251.4, 125.368, 1960., 69.564],
&[518.173, 480.6, 257.2, 127.852, 1961., 69.331],
&[554.894, 400.7, 282.7, 130.081, 1962., 70.551],
]);
])
.unwrap();
let y = vec![
83.0, 88.5, 88.2, 89.5, 96.2, 98.1, 99.0, 100.0, 101.2, 104.6, 108.4, 110.8, 112.6,
114.2, 115.7, 116.9,
Expand Down
19 changes: 19 additions & 0 deletions src/error/mod.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,8 @@ pub enum FailedError {
SolutionFailed,
/// Error in input parameters
ParametersError,
/// Invalid state error (should never happen)
InvalidStateError,
}

impl Failed {
Expand Down Expand Up @@ -64,6 +66,22 @@ impl Failed {
}
}

/// new instance of `FailedError::ParametersError`
pub fn input(msg: &str) -> Self {
Failed {
err: FailedError::ParametersError,
msg: msg.to_string(),
}
}

/// new instance of `FailedError::InvalidStateError`
pub fn invalid_state(msg: &str) -> Self {
Failed {
err: FailedError::InvalidStateError,
msg: msg.to_string(),
}
}

/// new instance of `err`
pub fn because(err: FailedError, msg: &str) -> Self {
Failed {
Expand Down Expand Up @@ -97,6 +115,7 @@ impl fmt::Display for FailedError {
FailedError::DecompositionFailed => "Decomposition failed",
FailedError::SolutionFailed => "Can't find solution",
FailedError::ParametersError => "Error in input, check parameters",
FailedError::InvalidStateError => "Invalid state, this should never happen", // useful in development phase of lib
};
write!(f, "{failed_err_str}")
}
Expand Down
2 changes: 1 addition & 1 deletion src/lib.rs
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Expand Up @@ -64,7 +64,7 @@
//! &[3., 4.],
//! &[5., 6.],
//! &[7., 8.],
//! &[9., 10.]]);
//! &[9., 10.]]).unwrap();
//! // Our classes are defined as a vector
//! let y = vec![2, 2, 2, 3, 3];
//!
Expand Down
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