Merge pull request #21 from termoshtt/numtest

Refactoring tests using ndarray-numtest

Author: termoshtt

Cargo.toml

@@ -18,6 +18,5 @@ version = "0.7"
 features = ["blas"]
 
 [dev-dependencies]
-rand = "0.3.14"
 ndarray-rand = "0.3"
-float-cmp = "0.2.3"
+ndarray-numtest = "0.1.4"

src/eigh.rs

@@ -6,7 +6,7 @@ use num_traits::Zero;
 use error::LapackError;
 
 pub trait ImplEigh: Sized {
-    fn eigh(layout: Layout, n: usize, mut a: Vec<Self>) -> Result<(Vec<Self>, Vec<Self>), LapackError>;
+    fn eigh(layout: Layout, n: usize, a: Vec<Self>) -> Result<(Vec<Self>, Vec<Self>), LapackError>;
 }
 
 macro_rules! impl_eigh {

src/norm.rs

@@ -3,9 +3,9 @@
 use lapack::c::*;
 
 pub trait ImplNorm: Sized {
-    fn norm_1(m: usize, n: usize, mut a: Vec<Self>) -> Self;
-    fn norm_i(m: usize, n: usize, mut a: Vec<Self>) -> Self;
-    fn norm_f(m: usize, n: usize, mut a: Vec<Self>) -> Self;
+    fn norm_1(m: usize, n: usize, a: Vec<Self>) -> Self;
+    fn norm_i(m: usize, n: usize, a: Vec<Self>) -> Self;
+    fn norm_f(m: usize, n: usize, a: Vec<Self>) -> Self;
 }
 
 macro_rules! impl_norm {

src/prelude.rs

@@ -3,4 +3,4 @@ pub use vector::Vector;
 pub use matrix::Matrix;
 pub use square::SquareMatrix;
 pub use hermite::HermiteMatrix;
-pub use triangular::TriangularMatrix;
+pub use triangular::{TriangularMatrix, drop_lower, drop_upper};

src/qr.rs

@@ -7,7 +7,7 @@ use num_traits::Zero;
 use error::LapackError;
 
 pub trait ImplQR: Sized {
-    fn qr(layout: Layout, n: usize, m: usize, mut a: Vec<Self>) -> Result<(Vec<Self>, Vec<Self>), LapackError>;
+    fn qr(layout: Layout, n: usize, m: usize, a: Vec<Self>) -> Result<(Vec<Self>, Vec<Self>), LapackError>;
 }
 
 macro_rules! impl_qr {

src/svd.rs

@@ -7,11 +7,7 @@ use num_traits::Zero;
 use error::LapackError;
 
 pub trait ImplSVD: Sized {
-    fn svd(layout: Layout,
-           n: usize,
-           m: usize,
-           mut a: Vec<Self>)
-           -> Result<(Vec<Self>, Vec<Self>, Vec<Self>), LapackError>;
+    fn svd(layout: Layout, n: usize, m: usize, a: Vec<Self>) -> Result<(Vec<Self>, Vec<Self>, Vec<Self>), LapackError>;
 }
 
 macro_rules! impl_svd {

src/triangular.rs

@@ -38,3 +38,21 @@ impl<A> TriangularMatrix for Array<A, Ix2>
         Ok(Array::from_vec(x))
     }
 }
+
+pub fn drop_upper(mut a: Array<f64, Ix2>) -> Array<f64, Ix2> {
+    for ((i, j), val) in a.indexed_iter_mut() {
+        if i < j {
+            *val = 0.0;
+        }
+    }
+    a
+}
+
+pub fn drop_lower(mut a: Array<f64, Ix2>) -> Array<f64, Ix2> {
+    for ((i, j), val) in a.indexed_iter_mut() {
+        if i > j {
+            *val = 0.0;
+        }
+    }
+    a
+}

tests/cholesky.rs

@@ -1,42 +1,25 @@
-
-extern crate rand;
-extern crate ndarray;
-extern crate ndarray_rand;
-extern crate ndarray_linalg;
-
-use rand::distributions::*;
-use ndarray::prelude::*;
-use ndarray_linalg::prelude::*;
-use ndarray_rand::RandomExt;
-
-fn all_close(a: Array<f64, Ix2>, b: Array<f64, Ix2>) {
-    if !a.all_close(&b, 1.0e-7) {
-        panic!("\nTwo matrices are not equal:\na = \n{:?}\nb = \n{:?}\n",
-               a,
-               b);
-    }
-}
+include!("header.rs");
 
 #[test]
 fn cholesky() {
-    let r_dist = Range::new(0., 1.);
+    let r_dist = RealNormal::new(0., 1.);
     let mut a = Array::<f64, _>::random((3, 3), r_dist);
     a = a.dot(&a.t());
     println!("a = \n{:?}", a);
     let c = a.clone().cholesky().unwrap();
     println!("c = \n{:?}", c);
     println!("cc = \n{:?}", c.t().dot(&c));
-    all_close(c.t().dot(&c), a);
+    c.t().dot(&c).assert_allclose_l2(&a, 1e-7);
 }
 
 #[test]
 fn cholesky_t() {
-    let r_dist = Range::new(0., 1.);
+    let r_dist = RealNormal::new(0., 1.);
     let mut a = Array::<f64, _>::random((3, 3), r_dist);
     a = a.dot(&a.t()).reversed_axes();
     println!("a = \n{:?}", a);
     let c = a.clone().cholesky().unwrap();
     println!("c = \n{:?}", c);
     println!("cc = \n{:?}", c.t().dot(&c));
-    all_close(c.t().dot(&c), a);
+    c.t().dot(&c).assert_allclose_l2(&a, 1e-7);
 }

tests/det.rs

@@ -1,27 +1,7 @@
-
-extern crate ndarray;
-extern crate ndarray_linalg;
-extern crate ndarray_rand;
-extern crate rand;
-extern crate float_cmp;
-
-use ndarray::prelude::*;
-use ndarray_linalg::prelude::*;
-use rand::distributions::*;
-use ndarray_rand::RandomExt;
-use float_cmp::ApproxEqRatio;
-
-fn approx_eq(val: f64, truth: f64, ratio: f64) {
-    if !val.approx_eq_ratio(&truth, ratio) {
-        panic!("Not almost equal! val={:?}, truth={:?}, ratio={:?}",
-               val,
-               truth,
-               ratio);
-    }
-}
+include!("header.rs");
 
 fn random_hermite(n: usize) -> Array<f64, Ix2> {
-    let r_dist = Range::new(0., 1.);
+    let r_dist = RealNormal::new(0., 1.);
     let a = Array::<f64, _>::random((n, n), r_dist);
     a.dot(&a.t())
 }
@@ -32,5 +12,5 @@ fn deth() {
     let (e, _) = a.clone().eigh().unwrap();
     let deth = a.clone().deth().unwrap();
     let det_eig = e.iter().fold(1.0, |x, y| x * y);
-    approx_eq(deth, det_eig, 1.0e-7);
+    deth.assert_close(det_eig, 1.0e-7);
 }

tests/eigh.rs

@@ -1,17 +1,4 @@
-
-extern crate ndarray;
-extern crate ndarray_linalg;
-
-use ndarray::prelude::*;
-use ndarray_linalg::prelude::*;
-
-fn assert_almost_eq(a: f64, b: f64) {
-    let rel_dev = (a - b).abs() / (a.abs() + b.abs());
-    if rel_dev > 1.0e-7 {
-        panic!("a={:?}, b={:?} are not almost equal", a, b);
-    }
-}
-
+include!("header.rs");
 
 #[test]
 fn eigen_vector_manual() {
@@ -31,6 +18,6 @@ fn diagonalize() {
     let (e, vecs) = a.clone().eigh().unwrap();
     let s = vecs.t().dot(&a).dot(&vecs);
     for i in 0..3 {
-        assert_almost_eq(e[i], s[(i, i)]);
+        e[i].assert_close(s[(i, i)], 1e-7);
     }
 }