register_real_images test working

src/register.rs

@@ -59,35 +59,25 @@ impl RegistrationStep {
 
     /// Default registration steps matching elastix `FixedSmoothingImagePyramid`.
     ///
-    /// Elastix uses `MultiResolutionGaussianSmoothingPyramidImageFilter` which applies
-    /// Gaussian smoothing with σ = 0.5 × factor at **full resolution** — images are
-    /// **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).
+    /// Smooth-only multi-resolution pyramid (no downsampling).
+    /// Schedule [8, 4, 2, 1] → σ = [4.0, 2.0, 1.0, 0.5] at spacing=1.
+    /// Uses cached random sampling (NewSamplesEveryIteration=false per level).
     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();
-        let mut steps = Vec::new();
-
-        for i in 0..nlevels {
-            let fraction = 1.0 / 2.0_f64.powi((nlevels - 1 - i) as i32);
-            let samples = (n as f64 * fraction)
-                .sqrt()
-                .max(n as f64 * fraction / 10.0)
-                .max(2048.0) as usize;
-            steps.push(RegistrationStep::new(
-                Sigma::Absolute(vec![sigma_schedule[i]; ndim]),
-                SamplingArg::Random(samples),
-                32,
-                1e-6,
-                0.05,
-                256,
-                1.0,
-            ));
-        }
-
-        steps
+        let n_samples = (n / 16).clamp(2048, 8192);
+        sigma_schedule
+            .iter()
+            .map(|&s| Self {
+                sigma: Sigma::Absolute(vec![s; ndim]),
+                samples: SamplingArg::Random(n_samples),
+                n_bins: 32,
+                tolerance: 1e-6,
+                edge: 0.05,
+                max_iterations: 1500,
+                learning_rate: 4.0,
+                downsample: 1,
+            })
+            .collect()
     }
 }