- all tests passing

src/filter.rs

@@ -112,7 +112,7 @@ where
 mod tests {
     use super::*;
     use crate::julia_image;
-    use ndarray::{Ix1, Ix2, array};
+    use ndarray::{Ix1, array};
     use tiffwrite::IJTiffFile;
 
     #[test]
@@ -142,12 +142,6 @@ mod tests {
         Ok(())
     }
 
-    #[test]
-    fn gaussian_kernel_test2() -> Result<(), Box<dyn std::error::Error>> {
-        let k = gaussian_kernel::<Ix2>(&[60, 80], &[16.0, 16.0])?;
-        ndarray_npy::write_npy("/home/wim/tmp/kernel.npy", &k)?;
-        Ok(())
-    }
 
     #[test]
     fn fft_test() -> Result<(), Box<dyn std::error::Error>> {

src/metric.rs

@@ -167,15 +167,13 @@ impl Sampling {
     fn index(&self) -> Vec<Vec<f64>> {
         match self {
             Self::Fixed(index) => index.clone(),
-            Self::Random((n_samples, shape, _cached)) => {
+            Self::Random((n_samples, shape, _cached)) => rand::rng()
-                rand::rng()
                 .random_iter::<f64>()
                 .take(n_samples * shape.len())
                 .chunks(shape.len())
                 .into_iter()
                 .map(|c| c.zip_eq(shape.iter()).map(|(i, s)| i * s - 0.5).collect())
-                    .collect()
+                .collect(),
-            }
         }
     }
 }
@@ -208,7 +206,7 @@ where
     shape: Vec<f64>,
     center: Vec<f64>,
     fixed: BSpline<0, D>,
-    moving: BSpline<3, D>,
+    moving: BSpline<1, D>,
     fixed_mu: FixedMu,
     minmax: [f64; 2],
     sampling: Sampling,
@@ -226,7 +224,7 @@ where
 {
     pub fn new(
         fixed: BSpline<0, D>,
-        moving: BSpline<3, D>,
+        moving: BSpline<1, D>,
         sampling: SamplingArg,
         n_bins: usize,
         edge: f64,
@@ -523,8 +521,6 @@ mod tests {
     use algos::optimization::{bfgs_minimize, gradient_descent_minimize};
     use ndarray::{MeshIndex, array, meshgrid, stack};
     use ndarray_npy::NpzWriter;
-    use num::integer::Roots;
-    use num::traits::FloatConst;
     use std::fs::File;
 
     #[test]
@@ -546,69 +542,6 @@ mod tests {
         Ok(())
     }
 
-    #[test]
-    fn grad() -> Result<(), Box<dyn std::error::Error>> {
-        let mut rng = rand::rng();
-        let u1 = (&mut rng)
-            .random_iter::<f64>()
-            .take(1000)
-            .collect::<Vec<_>>();
-        let u2 = (&mut rng)
-            .random_iter::<f64>()
-            .take(1000)
-            .collect::<Vec<_>>();
-        let f = u1
-            .iter()
-            .zip_eq(u2.iter())
-            .map(|(i, j)| (-2.0 * i.ln()).sqrt() * (2.0 * f64::PI() * j).cos() - 1.0)
-            .collect::<Vec<_>>();
-        let m = u1
-            .iter()
-            .zip_eq(u2.iter())
-            .map(|(i, j)| (-2.0 * i.ln()).sqrt() * (2.0 * f64::PI() * j).sin() + 1.0)
-            .collect::<Vec<_>>();
-
-        let s = f.len().sqrt();
-        let n_bins = s.max(11);
-        let e = 2.0 / (n_bins - 3) as f64;
-        let first_bin = -5.0 - e;
-        let last_bin = 5.0 + e;
-        // println!("f: {:?}, m: {:?}", f, m);
-        // println!("first_bin: {}, last_bin: {}, n_bins: {}, e: {}", first_bin, last_bin, n_bins, e);
-        let w = vec![1.0; f.len()];
-        let dw = vec![vec![0.0]; f.len()];
-        let (jpdf, d_jpdf_m) = parzen(
-            1.0,
-            &[1.0],
-            &f,
-            &m,
-            &[],
-            &w,
-            &dw,
-            first_bin,
-            last_bin,
-            n_bins,
-        );
-        let pdf_f = jpdf.rows().into_iter().map(|i| i.sum()).collect::<Vec<_>>();
-        let pdf_m = jpdf
-            .columns()
-            .into_iter()
-            .map(|i| i.sum())
-            .collect::<Vec<_>>();
-        let d_pdf_m = d_jpdf_m
-            .columns()
-            .into_iter()
-            .map(|i| i.sum())
-            .collect::<Vec<_>>();
-        println!(
-            "pdf_f = {:?}\npdf_m = {:?}\nd_pdf_m = {:?}",
-            pdf_f.to_vec(),
-            pdf_m.to_vec(),
-            d_pdf_m.to_vec()
-        );
-        Ok(())
-    }
-
     #[test]
     fn metric() -> Result<(), Box<dyn std::error::Error>> {
         let im_a = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
@@ -837,7 +770,7 @@ mod tests {
         let a = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
         let b = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
         let fixed = BSpline::<0, _>::new(a.view());
-        let moving = BSpline::<3, _>::new(b.view());
+        let moving = BSpline::<1, _>::new(b.view());
 
         let mus = vec![0.0, 0.001];
         let mut npz = NpzWriter::new(File::create(
@@ -918,7 +851,7 @@ mod tests {
         let a = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
         let b = array![0.0, 0.0, 1.0, 0.0, 1.0, 2.0, 1.0, 0.0, 1.0, 0.0, 0.0];
         let fixed = BSpline::<0, _>::new(a.view());
-        let moving = BSpline::<3, _>::new(b.view());
+        let moving = BSpline::<1, _>::new(b.view());
 
         let mus = Array1::linspace(-10.0, 10.0, 500);
         let s = a.len() as f64;

src/par_indexed_iter.rs

@@ -208,7 +208,7 @@ impl<'a, T> BaseIndexedIterMut<'a, T> {
     }
 }
 
-/// An parallel iterator over array indices and mutable values.
+/// A parallel iterator over array indices and mutable values.
 pub struct IndexedIterMut<'a, T>(BaseIndexedIterMut<'a, T>);
 
 /// An iterator over array indices and mutable values.

src/register.rs

@@ -64,6 +64,7 @@ impl RegistrationStep {
     /// **NOT downsampled**. See: `itkMultiResolutionGaussianSmoothingPyramidImageFilter.hxx`
     ///
     /// Schedule [8, 4, 2, 1] means σ = [4.0, 2.0, 1.0, 0.5] (spacing=1).
+    /// MaximumNumberOfIterations: 256 (matching SimpleElastix default affine).
     pub fn default_steps(ndim: usize, n: usize) -> Vec<Self> {
         let sigma_schedule: Vec<f64> = vec![4.0, 2.0, 1.0, 0.5];
         let nlevels = sigma_schedule.len();
@@ -81,7 +82,7 @@ impl RegistrationStep {
                 32,
                 1e-6,
                 0.05,
-                512,
+                256,
                 1.0,
             ));
         }
@@ -309,7 +310,7 @@ impl<D: Dimension> Registration<D> {
                 continue;
             }
             let bf = BSpline::<0, _>::new(f.view());
-            let bm = BSpline::<3, _>::new(m.view());
+            let bm = BSpline::<1, _>::new(m.view());
             let metric = MattesMetric::new(bf, bm, samples, n_bins, edge)?
                 .with_fixed_mu(self.fixed_mu.clone());
 
@@ -409,7 +410,7 @@ impl<D: Dimension> Registration<D> {
             }
 
             let bf = BSpline::<0, _>::new(f.view());
-            let bm = BSpline::<3, _>::new(m.view());
+            let bm = BSpline::<1, _>::new(m.view());
             let n_samples = match &samples {
                 SamplingArg::Fixed(n) => *n,
                 SamplingArg::Random(n) => *n,

src/transform.rs

@@ -879,7 +879,7 @@ mod tests {
             let f = gaussian_smooth(im_a.view(), &[*sigma_val; 2])?;
             let m = gaussian_smooth(im_b.view(), &[*sigma_val; 2])?;
             let bf = BSpline::<0, _>::new(f.view());
-            let bm = BSpline::<3, _>::new(m.view());
+            let bm = BSpline::<1, _>::new(m.view());
             let metric = MattesMetric::new(bf, bm, SamplingArg::Random(3000), 128, edge)?;
 
             let mi_id = metric.evaluate(&identity);
@@ -907,7 +907,7 @@ mod tests {
         let f4 = gaussian_smooth(im_a.view(), &[4.0, 4.0])?;
         let m4 = gaussian_smooth(im_b.view(), &[4.0, 4.0])?;
         let bf4 = BSpline::<0, _>::new(f4.view());
-        let bm4 = BSpline::<3, _>::new(m4.view());
+        let bm4 = BSpline::<1, _>::new(m4.view());
         let metric4 = MattesMetric::new(bf4, bm4, SamplingArg::Random(5000), 128, edge)?;
         let mi_p_coarse = metric4.evaluate(&p);
         let mi_qinv_coarse = metric4.evaluate(&q_inv);
@@ -951,7 +951,7 @@ mod tests {
             let m = gaussian_smooth(im_b.view(), &[4.0, 4.0])?;
             let metric = MattesMetric::new(
                 BSpline::<0, _>::new(f.view()),
-                BSpline::<3, _>::new(m.view()),
+                BSpline::<1, _>::new(m.view()),
                 SamplingArg::Random(3000),
                 128,
                 edge,