M-Labs/nalgebra
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Restructured usage of convolves, added unit testing.

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This commit is contained in:
Nathan 2019-02-24 19:53:09 -06:00
parent a3d571ea6b
commit 28525bfc20
3 changed files with 103 additions and 101 deletions
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17
examples/convolution.rs
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@ -1,17 +0,0 @@
extern crate nalgebra;
use nalgebra::{Vector2,Vector3,Vector4,Vector5,convolve_full,convolve_same,convolve_valid};
fn main(){
let vec = Vector4::new(1.0,2.0,3.0,4.0);
let ker = Vector3::new(1.0,2.0,2.1);
let actual = Vector5::from_vec(vec![1.0,4.0,7.0,10.0,8.0]);
let expected = convolve_full(vec,ker);
let expected2 = convolve_same(vec,ker);
// let expected3 = convolve_valid(vec,ker);
println!("{}", actual);
println!("{}", expected);
println!("{}", expected2);
// println!("{}", expected3);
}

64
src/linalg/convolution.rs
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@ -1,20 +1,19 @@
use base::allocator::Allocator;
use base::default_allocator::DefaultAllocator;
use base::dimension::{DimAdd, DimDiff, DimMax, DimMaximum, DimName, DimSub, DimSum,Dim};
use base::dimension::{Dim, DimAdd, DimDiff, DimMax, DimMaximum, DimSub, DimSum};
use std::cmp;
use storage::Storage;
use {zero, Real, Vector, VectorN, U1};
/// Returns the convolution of the vector and a kernel
/// Returns the convolution of the target vector and a kernel
///
/// # Arguments
///
/// * `vector` - A Vector with size > 0
/// * `kernel` - A Vector with size > 0
///
/// This function is commutative. If kernel > vector,
/// they will swap their roles as in
/// (self, kernel) = (kernel,self)
/// # Errors
/// Inputs must statisfy `vector.len() >= kernel.len() > 0`.
///
pub fn convolve_full<N, D1, D2, S1, S2>(
vector: Vector<N, D1, S1>,
@ -27,18 +26,13 @@ where
DimSum<D1, D2>: DimSub<U1>,
S1: Storage<N, D1>,
S2: Storage<N, D2>,
DimSum<D1, D2>: Dim,
DefaultAllocator: Allocator<N, DimDiff<DimSum<D1, D2>, U1>>,
{
let vec = vector.len();
let ker = kernel.len();
if vec == 0 || ker == 0 {
panic!("Convolve's inputs must not be 0-sized. ");
}
if ker > vec {
return convolve_full(kernel, vector);
if ker == 0 || ker > vec {
panic!("convolve_full expects `vector.len() >= kernel.len() > 0`, received {} and {} respectively.",vec,ker);
}
let result_len = vector.data.shape().0.add(kernel.data.shape().0).sub(U1);
@ -61,45 +55,38 @@ where
conv
}
/// Returns the convolution of the vector and a kernel
/// The output convolution consists only of those elements that do not rely on the zero-padding.
/// # Arguments
///
/// * `vector` - A Vector with size > 0
/// * `kernel` - A Vector with size > 0
///
/// This function is commutative. If kernel > vector,
/// they will swap their roles as in
/// (self, kernel) = (kernel,self)
///
///
/// # Errors
/// Inputs must statisfy `vector.len() >= kernel.len() > 0`.
///
pub fn convolve_valid<N, D1, D2, S1, S2>(
vector: Vector<N, D1, S1>,
kernel: Vector<N, D2, S2>,
) -> VectorN<N, DimSum<DimDiff<D1, D2>, U1>>
) -> VectorN<N, DimDiff<DimSum<D1, U1>, D2>>
where
N: Real,
D1: DimSub<D2>,
D2: DimSub<D1, Output = DimDiff<D1, D2>>,
DimDiff<D1, D2>: DimAdd<U1>,
D1: DimAdd<U1>,
D2: Dim,
DimSum<D1, U1>: DimSub<D2>,
S1: Storage<N, D1>,
S2: Storage<N, D2>,
DimDiff<D1, D2>: DimName,
DefaultAllocator: Allocator<N, DimSum<DimDiff<D1, D2>, U1>>
DefaultAllocator: Allocator<N, DimDiff<DimSum<D1, U1>, D2>>,
{
let vec = vector.len();
let ker = kernel.len();
if vec == 0 || ker == 0 {
panic!("Convolve's inputs must not be 0-sized. ");
if ker == 0 || ker > vec {
panic!("convolve_valid expects `vector.len() >= kernel.len() > 0`, received {} and {} respectively.",vec,ker);
}
if ker > vec {
return convolve_valid(kernel, vector);
}
let result_len = vector.data.shape().0.sub(kernel.data.shape().0).add(U1);
let result_len = vector.data.shape().0.add(U1).sub(kernel.data.shape().0);
let mut conv = VectorN::zeros_generic(result_len, U1);
for i in 0..(vec - ker + 1) {
@ -117,10 +104,8 @@ where
/// * `vector` - A Vector with size > 0
/// * `kernel` - A Vector with size > 0
///
/// This function is commutative. If kernel > vector,
/// they will swap their roles as in
/// (self, kernel) = (kernel,self)
///
/// # Errors
/// Inputs must statisfy `vector.len() >= kernel.len() > 0`.
pub fn convolve_same<N, D1, D2, S1, S2>(
vector: Vector<N, D1, S1>,
kernel: Vector<N, D2, S2>,
@ -131,18 +116,13 @@ where
D2: DimMax<D1, Output = DimMaximum<D1, D2>>,
S1: Storage<N, D1>,
S2: Storage<N, D2>,
DimMaximum<D1, D2>: Dim,
DefaultAllocator: Allocator<N, DimMaximum<D1, D2>>,
{
let vec = vector.len();
let ker = kernel.len();
if vec == 0 || ker == 0 {
panic!("Convolve's inputs must not be 0-sized. ");
}
if ker > vec {
return convolve_same(kernel, vector);
if ker == 0 || ker > vec {
panic!("convolve_same expects `vector.len() >= kernel.len() > 0`, received {} and {} respectively.",vec,ker);
}
let result_len = vector.data.shape().0.max(kernel.data.shape().0);

123
tests/linalg/convolution.rs
View File

@ -1,7 +1,6 @@
#[allow(unused_imports)] // remove after fixing unit test
use na::linalg::{convolve_full,convolve_valid,convolve_same};
#[allow(unused_imports)]
use na::{Vector2,Vector3,Vector4,Vector5,DVector};
use std::panic;
//
// Should mimic calculations in Python's scipy library
@ -12,70 +11,110 @@ use na::{Vector2,Vector3,Vector4,Vector5,DVector};
// array([ 1, 4, 7, 10])
#[test]
fn convolve_same_check(){
let vec_s = Vector4::new(1.0,2.0,3.0,4.0);
let ker_s = Vector2::new(1.0,2.0);
// Static Tests
let actual_s = Vector4::from_vec(vec![1.0,4.0,7.0,10.0]);
let expected_s = convolve_same(vec_s,ker_s);
let expected_s_r = convolve_same(ker_s,vec_s);
let expected_s = convolve_same(Vector4::new(1.0,2.0,3.0,4.0), Vector2::new(1.0,2.0));
assert!(relative_eq!(actual_s, expected_s, epsilon = 1.0e-7));
assert!(relative_eq!(actual_s, expected_s_r, epsilon = 1.0e-7));
let vec_d = DVector::from_vec(4,vec![1.0,2.0,3.0,4.0]);
let ker_d = DVector::from_vec(2,vec![1.0,2.0]);
let actual_d = DVector::from_vec(4,vec![1.0,4.0,7.0,10.0]);
let expected_d = convolve_same(vec_d.clone(),ker_d.clone());
let expected_d_r = convolve_same(ker_d,vec_d);
// Dynamic Tests
let actual_d = DVector::from_vec(vec![1.0,4.0,7.0,10.0]);
let expected_d = convolve_same(DVector::from_vec(vec![1.0,2.0,3.0,4.0]),DVector::from_vec(vec![1.0,2.0]));
assert!(relative_eq!(actual_d, expected_d, epsilon = 1.0e-7));
assert!(relative_eq!(actual_d, expected_d_r, epsilon = 1.0e-7));
// Panic Tests
// These really only apply to dynamic sized vectors
assert!(
panic::catch_unwind(|| {
convolve_same(DVector::from_vec(vec![1.0,2.0]), DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
}).is_err()
);
assert!(
panic::catch_unwind(|| {
convolve_same(DVector::<f32>::from_vec(vec![]), DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
}).is_err()
);
assert!(
panic::catch_unwind(|| {
convolve_same(DVector::from_vec(vec![1.0,2.0,3.0,4.0]),DVector::<f32>::from_vec(vec![]));
}).is_err()
);
}
// >>> convolve([1,2,3,4],[1,2],"full")
// array([ 1, 4, 7, 10, 8])
#[test]
fn convolve_full_check(){
let vec_s = Vector4::new(1.0,2.0,3.0,4.0);
let ker_s = Vector2::new(1.0,2.0);
// Static Tests
let actual_s = Vector5::new(1.0,4.0,7.0,10.0,8.0);
let expected_s = convolve_full(vec_s,ker_s);
let expected_s_r = convolve_full(ker_s,vec_s);
let expected_s = convolve_full(Vector4::new(1.0,2.0,3.0,4.0), Vector2::new(1.0,2.0));
assert!(relative_eq!(actual_s, expected_s, epsilon = 1.0e-7));
assert!(relative_eq!(actual_s, expected_s_r, epsilon = 1.0e-7));
let vec_d = DVector::from_vec(4,vec![1.0,2.0,3.0,4.0]);
let ker_d = DVector::from_vec(2,vec![1.0,2.0]);
let actual_d = DVector::from_vec(5,vec![1.0,4.0,7.0,10.0,8.0]);
let expected_d = convolve_full(vec_d.clone(),ker_d.clone());
let expected_d_r = convolve_full(ker_d,vec_d);
// Dynamic Tests
let actual_d = DVector::from_vec(vec![1.0,4.0,7.0,10.0,8.0]);
let expected_d = convolve_full(DVector::from_vec(vec![1.0,2.0,3.0,4.0]), DVector::from_vec(vec![1.0,2.0]));
assert!(relative_eq!(actual_d, expected_d, epsilon = 1.0e-7));
assert!(relative_eq!(actual_d, expected_d_r, epsilon = 1.0e-7));
// Panic Tests
// These really only apply to dynamic sized vectors
assert!(
panic::catch_unwind(|| {
convolve_full(DVector::from_vec(vec![1.0,2.0]), DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
}).is_err()
);
assert!(
panic::catch_unwind(|| {
convolve_full(DVector::<f32>::from_vec(vec![]), DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
}).is_err()
);
assert!(
panic::catch_unwind(|| {
convolve_full(DVector::from_vec(vec![1.0,2.0,3.0,4.0]),DVector::<f32>::from_vec(vec![]));
}).is_err()
);
}
// >>> convolve([1,2,3,4],[1,2],"valid")
// array([ 4, 7, 10])
// #[test]
// fn convolve_valid_check(){
// let vec = Vector4::new(1.0,2.0,3.0,4.0);
// let ker = Vector2::new(1.0,2.0);
#[test]
fn convolve_valid_check(){
// Static Tests
let actual_s = Vector3::from_vec(vec![4.0,7.0,10.0]);
let expected_s = convolve_valid( Vector4::new(1.0,2.0,3.0,4.0), Vector2::new(1.0,2.0));
// let actual = Vector3::from_vec(vec![4.0,7.0,10.0]);
assert!(relative_eq!(actual_s, expected_s, epsilon = 1.0e-7));
// let expected1 = convolve_valid(vec, ker);
// let expected2 = convolve_valid(ker, vec);
// Dynamic Tests
let actual_d = DVector::from_vec(vec![4.0,7.0,10.0]);
let expected_d = convolve_valid(DVector::from_vec(vec![1.0,2.0,3.0,4.0]), DVector::from_vec(vec![1.0,2.0]));
assert!(relative_eq!(actual_d, expected_d, epsilon = 1.0e-7));
// assert!(relative_eq!(actual, expected1, epsilon = 1.0e-7));
// assert!(relative_eq!(actual, expected2, epsilon = 1.0e-7));
// Panic Tests
// These really only apply to dynamic sized vectors
assert!(
panic::catch_unwind(|| {
convolve_valid(DVector::from_vec(vec![1.0,2.0]), DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
}).is_err()
);
// }
assert!(
panic::catch_unwind(|| {
convolve_valid(DVector::<f32>::from_vec(vec![]), DVector::from_vec(vec![1.0,2.0,3.0,4.0]));
}).is_err()
);
assert!(
panic::catch_unwind(|| {
convolve_valid(DVector::from_vec(vec![1.0,2.0,3.0,4.0]),DVector::<f32>::from_vec(vec![]));
}).is_err()
);
}