From e589dc0daedd3bd3d8736465cbc2ff6124515038 Mon Sep 17 00:00:00 2001
From: Marc Haubenstock <marchaubenstock@Marcs-MacBook-Pro.local>
Date: Sun, 28 Jul 2019 14:22:42 +0200
Subject: [PATCH] added test comments

---
 src/linalg/convolution.rs   |  9 +------
 tests/linalg/convolution.rs | 54 +++++++++----------------------------
 2 files changed, 14 insertions(+), 49 deletions(-)

diff --git a/src/linalg/convolution.rs b/src/linalg/convolution.rs
index eba9dec9..aa269a18 100644
--- a/src/linalg/convolution.rs
+++ b/src/linalg/convolution.rs
@@ -162,10 +162,9 @@ impl<N: RealField> DMatrix<N>  {
 
     //TODO: rest ?
 
-
 }
 
-impl<N: RealField, R1: Dim +DimName, C1: Dim +DimName> MatrixMN<N, R1, C1> where DefaultAllocator: Allocator<N, R1, C1>  {
+impl<N: RealField, R1: Dim + DimName, C1: Dim + DimName> MatrixMN<N, R1, C1> where DefaultAllocator: Allocator<N, R1, C1>  {
     /// Returns the convolution of the target vector and a kernel.
     ///
     /// # Arguments
@@ -184,8 +183,6 @@ impl<N: RealField, R1: Dim +DimName, C1: Dim +DimName> MatrixMN<N, R1, C1> where
             C2: Dim,
             S2: Storage<N, R2, C2>
     {
-
-
         let mat_rows = self.nrows() as i32;
         let mat_cols = self.ncols() as i32;
 
@@ -193,13 +190,11 @@ impl<N: RealField, R1: Dim +DimName, C1: Dim +DimName> MatrixMN<N, R1, C1> where
 
         convolve(&self, &kernel,&mut conv,mat_rows,mat_cols);
 
-
         conv
     }
 
     //TODO: rest ?
 
-
 }
 
 
@@ -213,7 +208,6 @@ fn convolve<N, R1, C1, R2, C2, S2>(mat: &MatrixMN<N,R1,C1>, kernel: &Matrix<N, R
         S2: Storage<N, R2, C2>,
         DefaultAllocator: Allocator<N, R1, C1>
     {
-
         let ker_rows =  kernel.data.shape().0.value() as i32;
         let ker_cols = kernel.data.shape().1.value() as i32;
 
@@ -225,7 +219,6 @@ fn convolve<N, R1, C1, R2, C2, S2>(mat: &MatrixMN<N,R1,C1>, kernel: &Matrix<N, R
                 mat_rows, ker_rows, mat_cols, ker_cols);
         }
 
-
         let kernel_size = ker_rows;
         let kernel_min = kernel_size/2;
         let zero = zero::<N>();
diff --git a/tests/linalg/convolution.rs b/tests/linalg/convolution.rs
index 69783cd9..3aa0ee2a 100644
--- a/tests/linalg/convolution.rs
+++ b/tests/linalg/convolution.rs
@@ -118,50 +118,22 @@ fn convolve_valid_check(){
 
 }
 
-//// >>> convolve([1,2,3,4],[1,2],"same")
-//// array([ 1,  4,  7, 10])
-//#[test]
-//fn convolve_same_integers_check(){
-//    // Static Tests
-//    let actual_s =  Vector4::new(1, 4, 7, 10);
-//    let expected_s = Vector4::new(1, 2, 3, 4).convolve_same(Vector2::new(1, 2));
 //
-//    assert!(relative_eq!(actual_s, expected_s, epsilon = 1.0e-7));
+// mat([ 1, 1, 1, 1, 1,
+//       1, 1, 1, 1, 1,
+//       1, 1, 1, 1, 1,
+//       1, 1, 1, 1, 1,
+//       1, 1, 1, 1, 1])
 //
-//    // Dynamic Tests
-//    let actual_d =  DVector::from_vec(vec![1, 4, 7, 10]);
-//    let expected_d = DVector::from_vec(vec![1, 2, 3, 4]).convolve_same(DVector::from_vec(vec![1, 2]));
+// kernel([ 0, 1, 0,
+//          1, 1, 1,
+//          0, 1, 0,])
 //
-//    assert!(relative_eq!(actual_d, expected_d, epsilon = 1.0e-7));
-//
-//    // Panic Tests
-//    // These really only apply to dynamic sized vectors
-//    assert!(
-//        panic::catch_unwind(|| {
-//            DVector::from_vec(vec![1, 2]).convolve_same(DVector::from_vec(vec![1, 2, 3, 4]));
-//        }).is_err()
-//    );
-//
-//    assert!(
-//        panic::catch_unwind(|| {
-//            DVector::<usize>::from_vec(vec![]).convolve_same(DVector::from_vec(vec![1, 2, 3, 4]));
-//        }).is_err()
-//    );
-//
-//    assert!(
-//        panic::catch_unwind(|| {
-//            DVector::from_vec(vec![1, 2, 3, 4]).convolve_same(DVector::<usize>::from_vec(vec![]));
-//        }).is_err()
-//    );
-//}
-
-//
-// Should mimic calculations in Python's scipy library
-// >>>from scipy.signal import convolve
-//
-
-// >>> convolve([1,2,3,4],[1,2],"same")
-// array([ 1,  4,  7, 10])
+// res([ 3, 4, 4, 4, 3,
+//       4, 5, 5, 5, 4,
+//       4, 5, 5, 5, 4,
+//       4, 5, 5, 5, 4,
+//       3, 4, 4, 4, 3])
 #[test]
 fn convolve_same_mat_check(){
     let actual_s =  Matrix5::from_vec( vec![3.0,4.0,4.0,4.0,3.0,4.0,5.0,5.0,5.0,4.0,4.0,5.0,5.0,5.0,4.0,4.0,5.0,5.0,5.0,4.0,3.0,4.0,4.0,4.0,3.0]);