--- a/src/fb.rs Fri Aug 14 10:38:27 2026 -0500
+++ b/src/fb.rs Fri Oct 02 12:03:25 2026 -0500
@@ -79,17 +79,19 @@
use crate::domain::{AdmissibleDomain, FullSpace};
use crate::measures::merging::SpikeMerging;
-use crate::measures::DiscreteMeasure;
+use crate::measures::{DiscreteMeasure, Radon};
use crate::plot::Plotter;
pub use crate::prox_penalty::{InsertionConfig, ProxPenalty, StepLengthBound};
use crate::regularisation::RegTerm;
use crate::types::*;
+use alg_tools::bounds::MinMaxMapping;
use alg_tools::error::DynResult;
use alg_tools::instance::Instance;
use alg_tools::iterate::AlgIteratorFactory;
use alg_tools::linops::Space;
use alg_tools::mapping::DifferentiableMapping;
use alg_tools::nalgebra_support::ToNalgebraRealField;
+use alg_tools::norms::Norm;
use colored::Colorize;
use measures::DeltaMeasure;
use numeric_literals::replace_float_literals;
@@ -168,9 +170,9 @@
U: Space + Clone,
F: Float + ToNalgebraRealField,
I: AlgIteratorFactory<IterInfo<F>>,
- DiscreteMeasure<U, F>: SpikeMerging<F>,
+ DiscreteMeasure<U, F>: SpikeMerging<F> + Norm<Radon, F>,
Dat: DifferentiableMapping<DiscreteMeasure<U, F>, Codomain = F>,
- Dat::DerivativeDomain: ClosedMul<F>,
+ Dat::DerivativeDomain: ClosedMul<F> + MinMaxMapping<U, F>,
Reg: RegTerm<U, F>,
P: ProxPenalty<U, Dat::DerivativeDomain, Reg, F> + StepLengthBound<F, Dat>,
Plot: Plotter<P::ReturnMapping, Dat::DerivativeDomain, DiscreteMeasure<U, F>>,
@@ -187,23 +189,26 @@
let mut μ = μ0.unwrap_or_else(|| DiscreteMeasure::new());
// Statistics
- let full_stats = |μ: &DiscreteMeasure<U, F>, ε, stats| IterInfo {
- value: f.apply(μ) + reg.apply(μ),
- n_spikes: μ.len(),
- ε,
- //postprocessing: config.postprocessing.then(|| μ.clone()),
- ..stats
- };
+ let full_stats =
+ |μ: &DiscreteMeasure<U, F>, τv: &mut Dat::DerivativeDomain, ε, stats| IterInfo {
+ value: f.apply(μ) + reg.apply(μ),
+ n_spikes: μ.len(),
+ μ_norm: μ.norm(Radon),
+ ε,
+ discrepancy: Some(reg.discrepancy(τv, τ, ε, μ, config)),
+ //postprocessing: config.postprocessing.then(|| μ.clone()),
+ ..stats
+ };
let mut stats = IterInfo::new();
+ // Calculate smooth part of surrogate model.
+ let mut τv = f.differential(&μ) * τ;
+
// Run the algorithm
- for state in iterator.iter_init(|| full_stats(&μ, ε, stats.clone())) {
+ for state in iterator.iter_init(|| full_stats(&μ, &mut τv, ε, stats.clone())) {
let maybe_μ_base = config.if_merge_now_check(&state, || μ.clone());
let μ_base_len = μ.len();
- // Calculate smooth part of surrogate model.
- let mut τv = f.differential(&μ) * τ;
-
// Do spike insertiona nd finite-dimensional weight optimisation
prox_penalty.insert_and_reweigh(&mut μ, &mut τv, τ, ε, config, ®, &state, &mut stats)?;
@@ -256,10 +261,18 @@
let iter = state.iteration();
stats.this_iters += 1;
+ // Calculate smooth part of surrogate model.
+ τv = f.differential(&μ) * τ;
+
// Give statistics if needed
state.if_verbose(|| {
plotter.plot_spikes(iter, None, Some(&τv), &μ);
- full_stats(&μ, ε, std::mem::replace(&mut stats, IterInfo::new()))
+ full_stats(
+ &μ,
+ &mut τv,
+ ε,
+ std::mem::replace(&mut stats, IterInfo::new()),
+ )
});
// Update main tolerance for next iteration
@@ -284,9 +297,9 @@
U: Space + Clone,
F: Float + ToNalgebraRealField,
I: AlgIteratorFactory<IterInfo<F>>,
- DiscreteMeasure<U, F>: SpikeMerging<F>,
+ DiscreteMeasure<U, F>: SpikeMerging<F> + Norm<Radon, F>,
Dat: DifferentiableMapping<DiscreteMeasure<U, F>, Codomain = F>,
- Dat::DerivativeDomain: ClosedMul<F>,
+ Dat::DerivativeDomain: ClosedMul<F> + MinMaxMapping<U, F>,
Reg: RegTerm<U, F>,
P: ProxPenalty<U, Dat::DerivativeDomain, Reg, F> + StepLengthBound<F, Dat>,
Plot: Plotter<P::ReturnMapping, Dat::DerivativeDomain, DiscreteMeasure<U, F>>,
@@ -330,7 +343,7 @@
I: AlgIteratorFactory<IterInfo<F>>,
DiscreteMeasure<U, F>: SpikeMerging<F>,
Dat: DifferentiableMapping<DiscreteMeasure<U, F>, Codomain = F>,
- Dat::DerivativeDomain: ClosedMul<F>,
+ Dat::DerivativeDomain: ClosedMul<F> + MinMaxMapping<U, F>,
Reg: RegTerm<U, F>,
P: ProxPenalty<U, Dat::DerivativeDomain, Reg, F> + StepLengthBound<F, Dat>,
Plot: Plotter<P::ReturnMapping, Dat::DerivativeDomain, DiscreteMeasure<U, F>>,
@@ -350,17 +363,21 @@
let mut warned_merging = false;
// Statistics
- let full_stats = |ν: &DiscreteMeasure<U, F>, ε, stats| IterInfo {
+ let full_stats = |ν: &DiscreteMeasure<U, F>,
+ maybe_τv: Option<&mut Dat::DerivativeDomain>,
+ ε,
+ stats| IterInfo {
value: f.apply(ν) + reg.apply(ν),
n_spikes: ν.len(),
ε,
+ discrepancy: maybe_τv.map(|τv| reg.discrepancy(τv, τ, ε, ν, config)),
// postprocessing: config.postprocessing.then(|| ν.clone()),
..stats
};
let mut stats = IterInfo::new();
// Run the algorithm
- for state in iterator.iter_init(|| full_stats(&μ, ε, stats.clone())) {
+ for state in iterator.iter_init(|| full_stats(&μ, None, ε, stats.clone())) {
let μ_base_len = μ.len();
// Calculate smooth part of surrogate model.
let mut τv = f.differential(&μ) * τ;
@@ -410,7 +427,12 @@
// Give statistics if needed
state.if_verbose(|| {
plotter.plot_spikes(iter, None, Some(&τv), &μ_prev);
- full_stats(&μ_prev, ε, std::mem::replace(&mut stats, IterInfo::new()))
+ full_stats(
+ &μ_prev,
+ Some(&mut τv),
+ ε,
+ std::mem::replace(&mut stats, IterInfo::new()),
+ )
});
// Update main tolerance for next iteration