affinitree 0.23.0

A crate to distill faithful decision trees out of neural networks
Documentation 
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//   Copyright 2025 affinitree developers
//
//   Licensed under the Apache License, Version 2.0 (the "License");
//   you may not use this file except in compliance with the License.
//   You may obtain a copy of the License at
//
//       http://www.apache.org/licenses/LICENSE-2.0
//
//   Unless required by applicable law or agreed to in writing, software
//   distributed under the License is distributed on an "AS IS" BASIS,
//   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
//   See the License for the specific language governing permissions and
//   limitations under the License.

/// The following test case has as subject the absolute value function.
///
/// The test case first manually constructs the function and then asserts
/// correctness on some inputs.
#[cfg(test)]
mod tests {
    use affinitree::linalg::affine::PolyRepr;
    use affinitree::pwl::afftree::AffTree;
    use affinitree::{aff, poly};
    use approx::assert_relative_eq;
    use ndarray::arr1;

    #[test]
    pub fn test_abs() {
        let mut dd =
            AffTree::<2>::from_aff(poly!([[1, 1]] < [0]).convert_to(PolyRepr::MatrixLeqBias)); // 0

        dd.add_decision(
            0,
            0,
            poly!([[-1, 1]] < [0]).convert_to(PolyRepr::MatrixLeqBias),
        )
        .unwrap(); // 1
        dd.add_decision(
            0,
            1,
            poly!([[-1, 1]] < [0]).convert_to(PolyRepr::MatrixLeqBias),
        )
        .unwrap(); // 2

        dd.add_terminal(1, 0, aff!([[0, 1]] + [0])).unwrap();
        dd.add_terminal(1, 1, aff!([[1, 0]] + [0])).unwrap();
        dd.add_terminal(2, 0, aff!([[-1, 0]] + [0])).unwrap();
        dd.add_terminal(2, 1, aff!([[0, -1]] + [0])).unwrap();

        assert_eq!(dd.len(), 7);
        assert_eq!(dd.num_terminals(), 4);

        assert_relative_eq!(dd.evaluate(&arr1(&[0., 0.])).unwrap()[0], 0.);
        assert_relative_eq!(dd.evaluate(&arr1(&[2., 0.])).unwrap()[0], 2.);
        assert_relative_eq!(dd.evaluate(&arr1(&[-3., 0.])).unwrap()[0], 3.);
        assert_relative_eq!(dd.evaluate(&arr1(&[0., -1.])).unwrap()[0], 1.);
        assert_relative_eq!(dd.evaluate(&arr1(&[0., 10.])).unwrap()[0], 10.);
    }
}