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Fix the return type of `convolve_same` to match the documentation.

This commit is contained in:
sebcrozet 2019-03-31 17:03:02 +02:00
parent ae4afa3d2c
commit bb06701eff
2 changed files with 37 additions and 37 deletions
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28
src/linalg/convolution.rs
View File

@ -7,14 +7,14 @@ use crate::storage::Storage;
use crate::{zero, RealField, Vector, VectorN, U1};
impl<N: RealField, D1: Dim, S1: Storage<N, D1>> Vector<N, D1, S1> {
/// Returns the convolution of the target vector and a kernel
/// Returns the convolution of the target vector and a kernel.
///
/// # Arguments
///
/// * `kernel` - A Vector with size > 0
///
/// # Errors
/// Inputs must statisfy `vector.len() >= kernel.len() > 0`.
/// Inputs must satisfy `vector.len() >= kernel.len() > 0`.
///
pub fn convolve_full<D2, S2>(
&self,
@ -53,7 +53,8 @@ impl<N: RealField, D1: Dim, S1: Storage<N, D1>> Vector<N, D1, S1> {
}
conv
}
/// Returns the convolution of the target vector and a kernel
/// Returns the convolution of the target vector and a kernel.
///
/// The output convolution consists only of those elements that do not rely on the zero-padding.
/// # Arguments
///
@ -61,10 +62,9 @@ impl<N: RealField, D1: Dim, S1: Storage<N, D1>> Vector<N, D1, S1> {
///
///
/// # Errors
/// Inputs must statisfy `self.len() >= kernel.len() > 0`.
/// Inputs must satisfy `self.len() >= kernel.len() > 0`.
///
pub fn convolve_valid<D2, S2>(&self, kernel: Vector<N, D2, S2>,
) -> VectorN<N, DimDiff<DimSum<D1, U1>, D2>>
pub fn convolve_valid<D2, S2>(&self, kernel: Vector<N, D2, S2>) -> VectorN<N, DimDiff<DimSum<D1, U1>, D2>>
where
D1: DimAdd<U1>,
D2: Dim,
@ -90,20 +90,20 @@ impl<N: RealField, D1: Dim, S1: Storage<N, D1>> Vector<N, D1, S1> {
conv
}
/// Returns the convolution of the targetvector and a kernel
/// Returns the convolution of the target vector and a kernel.
///
/// The output convolution is the same size as vector, centered with respect to the ‘full’ output.
/// # Arguments
///
/// * `kernel` - A Vector with size > 0
///
/// # Errors
/// Inputs must statisfy `self.len() >= kernel.len() > 0`.
pub fn convolve_same<D2, S2>(&self, kernel: Vector<N, D2, S2>) -> VectorN<N, DimMaximum<D1, D2>>
/// Inputs must satisfy `self.len() >= kernel.len() > 0`.
pub fn convolve_same<D2, S2>(&self, kernel: Vector<N, D2, S2>) -> VectorN<N, D1>
where
D1: DimMax<D2>,
D2: DimMax<D1, Output = DimMaximum<D1, D2>>,
D2: Dim,
S2: Storage<N, D2>,
DefaultAllocator: Allocator<N, DimMaximum<D1, D2>>,
DefaultAllocator: Allocator<N, D1>,
{
let vec = self.len();
let ker = kernel.len();
@ -112,8 +112,7 @@ impl<N: RealField, D1: Dim, S1: Storage<N, D1>> Vector<N, D1, S1> {
panic!("convolve_same expects `self.len() >= kernel.len() > 0`, received {} and {} respectively.",vec,ker);
}
let result_len = self.data.shape().0.max(kernel.data.shape().0);
let mut conv = VectorN::zeros_generic(result_len, U1);
let mut conv = VectorN::zeros_generic(self.data.shape().0, U1);
for i in 0..vec {
for j in 0..ker {
@ -125,6 +124,7 @@ impl<N: RealField, D1: Dim, S1: Storage<N, D1>> Vector<N, D1, S1> {
conv[i] += val * kernel[ker - j - 1];
}
}
conv
}
}

46
tests/linalg/convolution.rs
View File

@ -11,14 +11,14 @@ use std::panic;
#[test]
fn convolve_same_check(){
// Static Tests
let actual_s = Vector4::from_vec(vec![1.0,4.0,7.0,10.0]);
let expected_s = Vector4::new(1.0,2.0,3.0,4.0).convolve_same(Vector2::new(1.0,2.0));
let actual_s = Vector4::new(1.0, 4.0, 7.0, 10.0);
let expected_s = Vector4::new(1.0, 2.0, 3.0, 4.0).convolve_same(Vector2::new(1.0, 2.0));
assert!(relative_eq!(actual_s, expected_s, epsilon = 1.0e-7));
// Dynamic Tests
let actual_d = DVector::from_vec(vec![1.0,4.0,7.0,10.0]);
let expected_d = DVector::from_vec(vec![1.0,2.0,3.0,4.0]).convolve_same(DVector::from_vec(vec![1.0,2.0]));
let actual_d = DVector::from_vec(vec![1.0, 4.0, 7.0, 10.0]);
let expected_d = DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]).convolve_same(DVector::from_vec(vec![1.0, 2.0]));
assert!(relative_eq!(actual_d, expected_d, epsilon = 1.0e-7));
@ -26,19 +26,19 @@ fn convolve_same_check(){
// 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]));
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]));
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![]));
DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]).convolve_same(DVector::<f32>::from_vec(vec![]));
}).is_err()
);
}
@ -48,14 +48,14 @@ fn convolve_same_check(){
#[test]
fn convolve_full_check(){
// Static Tests
let actual_s = Vector5::new(1.0,4.0,7.0,10.0,8.0);
let expected_s = Vector4::new(1.0,2.0,3.0,4.0).convolve_full(Vector2::new(1.0,2.0));
let actual_s = Vector5::new(1.0, 4.0, 7.0, 10.0, 8.0);
let expected_s = Vector4::new(1.0, 2.0, 3.0, 4.0).convolve_full(Vector2::new(1.0, 2.0));
assert!(relative_eq!(actual_s, expected_s, epsilon = 1.0e-7));
// Dynamic Tests
let actual_d = DVector::from_vec(vec![1.0,4.0,7.0,10.0,8.0]);
let expected_d = DVector::from_vec(vec![1.0,2.0,3.0,4.0]).convolve_full(DVector::from_vec(vec![1.0,2.0]));
let actual_d = DVector::from_vec(vec![1.0, 4.0, 7.0, 10.0, 8.0]);
let expected_d = DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]).convolve_full(DVector::from_vec(vec![1.0, 2.0]));
assert!(relative_eq!(actual_d, expected_d, epsilon = 1.0e-7));
@ -63,36 +63,36 @@ fn convolve_full_check(){
// These really only apply to dynamic sized vectors
assert!(
panic::catch_unwind(|| {
DVector::from_vec(vec![1.0,2.0]).convolve_full(DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
DVector::from_vec(vec![1.0, 2.0] ).convolve_full(DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0] ));
}).is_err()
);
assert!(
panic::catch_unwind(|| {
DVector::<f32>::from_vec(vec![]).convolve_full(DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
DVector::<f32>::from_vec(vec![]).convolve_full(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_full(DVector::<f32>::from_vec(vec![]));
DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0] ).convolve_full(DVector::<f32>::from_vec(vec![]));
}).is_err()
);
}
// >>> convolve([1,2,3,4],[1,2],"valid")
// array([ 4, 7, 10])
// >>> convolve([1, 2, 3, 4],[1, 2],"valid")
// array([4, 7, 10])
#[test]
fn convolve_valid_check(){
// Static Tests
let actual_s = Vector3::from_vec(vec![4.0,7.0,10.0]);
let expected_s = Vector4::new(1.0,2.0,3.0,4.0).convolve_valid( Vector2::new(1.0,2.0));
let actual_s = Vector3::from_vec(vec![4.0, 7.0, 10.0]);
let expected_s = Vector4::new(1.0, 2.0, 3.0, 4.0).convolve_valid( Vector2::new(1.0, 2.0));
assert!(relative_eq!(actual_s, expected_s, epsilon = 1.0e-7));
// Dynamic Tests
let actual_d = DVector::from_vec(vec![4.0,7.0,10.0]);
let expected_d = DVector::from_vec(vec![1.0,2.0,3.0,4.0]).convolve_valid(DVector::from_vec(vec![1.0,2.0]));
let actual_d = DVector::from_vec(vec![4.0, 7.0, 10.0]);
let expected_d = DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]).convolve_valid(DVector::from_vec(vec![1.0, 2.0]));
assert!(relative_eq!(actual_d, expected_d, epsilon = 1.0e-7));
@ -100,19 +100,19 @@ fn convolve_valid_check(){
// These really only apply to dynamic sized vectors
assert!(
panic::catch_unwind(|| {
DVector::from_vec(vec![1.0,2.0]).convolve_valid(DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
DVector::from_vec(vec![1.0, 2.0]).convolve_valid(DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]));
}).is_err()
);
assert!(
panic::catch_unwind(|| {
DVector::<f32>::from_vec(vec![]).convolve_valid(DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
DVector::<f32>::from_vec(vec![]).convolve_valid(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_valid(DVector::<f32>::from_vec(vec![]));
DVector::from_vec(vec![1.0, 2.0, 3.0, 4.0]).convolve_valid(DVector::<f32>::from_vec(vec![]));
}).is_err()
);