1use thiserror::Error;
2pub type Result<T> = std::result::Result<T, Error>;
3
4#[derive(Error, Debug)]
5pub enum Error {
6 #[error(transparent)]
7 LinfaError(#[from] linfa::Error),
8 #[error("More than two classes for logistic regression")]
9 TooManyClasses,
10 #[error("Fewer than two classes for logistic regression")]
11 TooFewClasses,
12 #[error(transparent)]
13 ArgMinError(#[from] argmin::core::Error),
14 #[error("Expected `x` and `y` to have same number of rows, got {0} != {1}")]
15 MismatchedShapes(usize, usize),
16 #[error("Values must be finite and not `Inf`, `-Inf` or `NaN`")]
17 InvalidValues,
18 #[error("Rows of initial parameter ({rows}) must be the same as the number of features ({n_features})")]
19 InitialParameterFeaturesMismatch { rows: usize, n_features: usize },
20 #[error("Columns of initial parameter ({cols}) must be the same as the number of classes ({n_classes})")]
21 InitialParameterClassesMismatch { cols: usize, n_classes: usize },
22 #[error("gradient_tolerance must be a positive, finite number")]
23 InvalidGradientTolerance,
24 #[error("alpha must be a positive, finite number")]
25 InvalidAlpha,
26 #[error("Initial parameters must be finite")]
27 InvalidInitialParameters,
28 #[error("Offset must be finite")]
29 InvalidOffset,
30 #[error("Offset length ({offset_len}) must match the number of samples ({n_samples})")]
31 OffsetLengthMismatch { offset_len: usize, n_samples: usize },
32}