3x3 matrix tests

src/matrix.rs

@@ -1,15 +1,13 @@
 use crate::impl_matrix_op;
 use crate::index::Index2D;
-use crate::util::{checked_div, checked_inv};
+use crate::util::checked_inv;
 
 use num_traits::real::Real;
 use num_traits::{Num, NumOps, One, Zero};
 use std::fmt::Debug;
 use std::iter::{zip, Flatten, Product, Sum};
-use std::mem::swap;
 
 use std::ops::{Add, AddAssign, Deref, DerefMut, Index, IndexMut, Mul, MulAssign, Neg};
-use std::process::id;
 
 /// A 2D array of values which can be operated upon.
 ///
@@ -306,23 +304,6 @@ impl<T: Copy, const M: usize, const N: usize> Matrix<T, M, N> {
             })
             .collect()
     }
-
-    // pub fn mmul<const P: usize, R, O>(&self, rhs: &Matrix<R, P, N>) -> Matrix<T, P, M>
-    // where
-    //     R: Num,
-    //     T: Scalar + Mul<R, Output = T>,
-    //     Vector<T, N>: Dot<Vector<R, M>, Output = T>,
-    // {
-    //     let mut result: Matrix<T, P, M> = Zero::zero();
-    //
-    //     for (m, a) in self.rows().enumerate() {
-    //         for (n, b) in rhs.cols().enumerate() {
-    //             // result[(m, n)] = a.dot(b)
-    //         }
-    //     }
-    //
-    //     return result;
-    // }
 }
 
 // 1D vector implementations
@@ -366,11 +347,11 @@ impl<T: Copy> Vector<T, 3> {
         ])
     }
 
-    pub fn cross_l<R: Copy>(&self, rhs: &Vector<R, 3>) -> Self
+    pub fn cross_l<R: Copy>(&self, rhs: &Vector<R, 3>) -> Vector<R, 3>
     where
-        T: NumOps<R> + NumOps + Neg<Output = T>,
+        R: NumOps<T> + NumOps,
     {
-        -self.cross_r(rhs)
+        rhs.cross_r(self)
     }
 }
 
@@ -583,12 +564,11 @@ where
 
         Matrix::from_cols(bp.cols().map(|mut x| {
             // Implementation from Numerical Recipes §2.3
-
             // When ii is set to a positive value,
             // it will become the index of the first nonvanishing element of b
             let mut ii = 0usize;
             for i in 0..N {
-                // forward substitution
+                // forward substitution using L
                 let mut sum = x[i];
                 if ii != 0 {
                     for j in (ii - 1)..i {
@@ -600,7 +580,7 @@ where
                 x[i] = sum;
             }
             for i in (0..N).rev() {
-                // back substitution
+                // back substitution using U
                 let mut sum = x[i];
                 for j in (i + 1)..N {
                     sum = sum - (lu[(i, j)] * x[j]);

tests/ops.rs

@@ -2,10 +2,59 @@ use generic_parameterize::parameterize;
 use num_traits::real::Real;
 use num_traits::Zero;
 use std::fmt::Debug;
-use std::iter::{Product, Sum};
+use std::iter::{zip, Product, Sum};
 use std::ops;
 use vector_victor::{LUSolve, Matrix, Vector};
 
+macro_rules! scalar_eq {
+    ($left:expr, $right:expr $(,)?) => {
+        match (&$left, &$right) {
+            (_left_val, _right_val) => {
+                scalar_eq!($left, $right, "Difference is less than epsilon")
+            }
+        }
+    };
+    ($left:expr, $right:expr, $($arg:tt)+) => {
+        match (&$left, &$right) {
+            (left_val, right_val) => {
+                let epsilon = f32::epsilon() as f64;
+                let lf : f64 = (*left_val).into();
+                let rf : f64 = (*right_val).into();
+                let diff : f64 = (lf - rf).abs();
+                if diff >= epsilon {
+                    assert_eq!(left_val, right_val, $($arg)+) // done this way to get nice errors
+                }
+            }
+        }
+    };
+}
+
+macro_rules! matrix_eq {
+    ($left:expr, $right:expr $(,)?) => {
+        match (&$left, &$right) {
+            (_left_val, _right_val) => {
+                matrix_eq!($left, $right, "Difference is less than epsilon")
+            }
+        }
+    };
+    ($left:expr, $right:expr, $($arg:tt)+) => {
+        match (&$left, &$right) {
+            (left_val, right_val) => {
+                let epsilon = f32::epsilon() as f64;
+                for (l, r) in zip(left_val.elements(), right_val.elements()) {
+                    let lf : f64 = (*l).into();
+                    let rf : f64 = (*r).into();
+                    let diff : f64 = (lf - rf).abs();
+                    if diff >= epsilon {
+                        assert_eq!($left, $right, $($arg)+) // done this way to get nice errors
+                    }
+                }
+
+            }
+        }
+    };
+}
+
 #[parameterize(S = (i32, f32, u32), M = [1,4], N = [1,4])]
 #[test]
 fn test_add<S: Copy + From<u16> + PartialEq + Debug, const M: usize, const N: usize>()
@@ -22,7 +71,7 @@ where
 
 #[parameterize(S = (f32, f64), M = [1,2,3,4])]
 #[test]
-fn test_lu_identity<S: Default + Real + Debug + Product + Sum, const M: usize>() {
+fn test_lu_identity<S: Default + Real + Debug + Product + Sum + Into<f64>, const M: usize>() {
     // let a: Matrix<f32, 3, 3> = Matrix::<f32, 3, 3>::identity();
     let i = Matrix::<S, M, M>::identity();
     let ones = Vector::<S, M>::fill(S::one());
@@ -33,8 +82,8 @@ fn test_lu_identity<S: Default + Real + Debug + Product + Sum, const M: usize>()
         (0..M).eq(idx.elements().cloned()),
         "Incorrect permutation matrix",
     );
-    assert_eq!(d, S::one(), "Incorrect permutation parity");
-    assert_eq!(i.det(), S::one());
+    scalar_eq!(d, S::one(), "Incorrect permutation parity");
+    scalar_eq!(i.det(), S::one());
     assert_eq!(i.inverse(), Some(i));
     assert_eq!(i.solve(&ones), Some(ones));
     assert_eq!(decomp.separate(), (i, i));
@@ -58,22 +107,42 @@ fn test_lu_singular<S: Default + Real + Debug + Product + Sum, const M: usize>()
 fn test_lu_2x2() {
     let a = Matrix::new([[1.0, 2.0], [3.0, 0.0]]);
     let decomp = a.lu().expect("Singular matrix encountered");
-    let (lu, idx, d) = decomp;
+    let (_lu, idx, _d) = decomp;
     // the decomposition is non-unique, due to the combination of lu and idx.
     // Instead of checking the exact value, we only check the results.
     // Also check if they produce the same results with both methods, since the
     // Matrix<> methods use shortcuts the decomposition methods don't
 
     let (l, u) = decomp.separate();
-    assert_eq!(l.mmul(&u), a.permute_rows(&idx));
+    matrix_eq!(l.mmul(&u), a.permute_rows(&idx));
 
-    assert_eq!(a.det(), -6.0);
-    assert_eq!(a.det(), decomp.det());
+    scalar_eq!(a.det(), -6.0);
+    scalar_eq!(a.det(), decomp.det());
 
-    assert_eq!(
-        a.inverse(),
-        Some(Matrix::new([[0.0, 2.0], [3.0, -1.0]]) * (1.0 / 6.0))
+    matrix_eq!(
+        a.inverse().unwrap(),
+        Matrix::new([[0.0, 2.0], [3.0, -1.0]]) * (1.0 / 6.0)
     );
-    assert_eq!(a.inverse(), Some(decomp.inverse()));
-    assert_eq!(a.inverse().unwrap().inverse().unwrap(), a)
+    matrix_eq!(a.inverse().unwrap(), decomp.inverse());
+    matrix_eq!(a.inverse().unwrap().inverse().unwrap(), a)
+}
+
+#[test]
+fn test_lu_3x3() {
+    let a = Matrix::new([[1.0, -5.0, 8.0], [1.0, -2.0, 1.0], [2.0, -1.0, -4.0]]);
+    let decomp = a.lu().expect("Singular matrix encountered");
+    let (_lu, idx, _d) = decomp;
+
+    let (l, u) = decomp.separate();
+    matrix_eq!(l.mmul(&u), a.permute_rows(&idx));
+
+    scalar_eq!(a.det(), 3.0);
+    scalar_eq!(a.det(), decomp.det());
+
+    matrix_eq!(
+        a.inverse().unwrap(),
+        Matrix::new([[9.0, -28.0, 11.0], [6.0, -20.0, 7.0], [3.0, -9.0, 3.0]]) * (1.0 / 3.0)
+    );
+    matrix_eq!(a.inverse().unwrap(), decomp.inverse());
+    matrix_eq!(a.inverse().unwrap().inverse().unwrap(), a)
 }