automl 0.3.0

Automated machine learning for classification and regression
Documentation 
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use automl::utils::{CsvError, load_csv_features};
use smartcore::linalg::basic::arrays::Array;

#[test]
fn loads_features_matrix() {
    let x = load_csv_features("tests/fixtures/clustering_points.csv").unwrap();
    assert_eq!(x.shape(), (4, 2));
    assert!((*x.get((0, 0)) - 1.0).abs() < f64::EPSILON);
    assert!((*x.get((3, 1)) - 8.2).abs() < f64::EPSILON);
}

#[test]
fn errors_on_bad_path() {
    let err = load_csv_features("tests/fixtures/does_not_exist.csv").unwrap_err();
    assert!(matches!(err, CsvError::Io(_)));
}

#[test]
fn errors_on_non_numeric() {
    let err = load_csv_features("tests/fixtures/non_numeric_features.csv").unwrap_err();
    match err {
        CsvError::Parse(parse_err) => {
            let message = parse_err.to_string();
            assert!(message.contains("row 2"), "unexpected message: {message}");
            assert!(
                message.contains("column 1"),
                "unexpected message: {message}"
            );
        }
        other => panic!("expected parse error, got {other}"),
    }
}

#[test]
fn errors_on_inconsistent_rows() {
    let err = load_csv_features("tests/fixtures/inconsistent_features.csv").unwrap_err();
    match err {
        CsvError::Shape(message) => {
            assert!(message.contains("row 2"), "unexpected message: {message}");
        }
        other => panic!("expected shape error, got {other}"),
    }
}