M-Labs/nalgebra
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test compiles but fails

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This commit is contained in:
Marc Haubenstock 2019-07-28 04:25:31 +02:00
parent 6651aeba6f
commit 8b85ba1081
2 changed files with 74 additions and 55 deletions
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18
src/linalg/convolution.rs
View File

@ -167,25 +167,9 @@ impl<N: RealField> DMatrix<N> {
let kernel_min = kernel_size/2;
let zero = zero::<N>();
let mut conv = DMatrix::from_element(mat_cols, mat_rows, zero);
//
// for i in 0..(vec + ker - 1) {
// let u_i = if i > vec { i - ker } else { 0 };
// let u_f = cmp::min(i, vec - 1);
//
// if u_i == u_f {
// conv[i] += self[u_i] * kernel[(i - u_i)];
// } else {
// for u in u_i..(u_f + 1) {
// if i - u < ker {
// conv[i] += self[u] * kernel[(i - u)];
// }
// }
// }
// }
for i in 0..mat_rows {
for j in 0..mat_cols {
let val = *self.index((i,j));
for k_i in 0..kernel_size {
for k_j in 0..kernel_size {
let i_matrix = (i + k_i - kernel_min) as i32;
@ -195,7 +179,7 @@ impl<N: RealField> DMatrix<N> {
let is_j_in_range = j_matrix >=0 && j_matrix < mat_cols as i32;
let convolved_value =
match is_i_in_range && is_i_in_range {
match is_i_in_range && is_j_in_range {
true => {
let pixel_value = *self.index((i_matrix as usize, j_matrix as usize));
let kernel_value = *kernel.index((k_i,k_j));

111
tests/linalg/convolution.rs
View File

@ -1,4 +1,4 @@
use na::{Vector2,Vector3,Vector4,Vector5,DVector};
use na::{Vector2,Vector3,Vector4,Vector5,DVector, DMatrix};
use std::panic;
//
@ -43,43 +43,6 @@ fn convolve_same_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));
//
// // 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]));
//
// 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()
// );
//}
// >>> convolve([1,2,3,4],[1,2],"full")
// array([ 1, 4, 7, 10, 8])
#[test]
@ -153,4 +116,76 @@ fn convolve_valid_check(){
}).is_err()
);
}
//// >>> 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));
//
// // 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]));
//
// 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])
#[test]
fn convolve_same_dmat_check(){
let actual_d = DMatrix::from_vec(5,5, 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]);
let expected_d = DMatrix::from_element(5,5,1.0).mat_convolve_full(DMatrix::from_vec(3,3,vec![0.0,1.0,0.0,1.0,1.0,1.0,0.0,1.0,0.0]));
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![1.0, 2.0]).convolve_same(DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]));
// }).is_err()
// );
//
// assert!(
// panic::catch_unwind(|| {
// DVector::<f32>::from_vec(vec![]).convolve_same(DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]));
// }).is_err()
// );
//
// assert!(
// panic::catch_unwind(|| {
// DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]).convolve_same(DVector::<f32>::from_vec(vec![]));
// }).is_err()
// );
}