--- a/src/sliding_pdps.rs Tue Aug 04 23:47:29 2026 -0500
+++ b/src/sliding_pdps.rs Wed Aug 05 17:50:38 2026 -0500
@@ -138,15 +138,11 @@
Plot: Plotter<P::ReturnMapping, S, DiscreteMeasure<U, F>>,
{
// Check parameters
- /*ensure!(
- config.τ0 > 0.0
- && config.τ0 < 1.0
- && config.σp0 > 0.0
- && config.σp0 < 1.0
- && config.σd0 > 0.0
- && config.σp0 * config.σd0 <= 1.0,
+ ensure!(
+ config.τ0 > 0.0 && config.σp0 > 0.0,
+ //&& config.τ0 < 1.0 && config.σp0 < 1.0
"Invalid step length parameters"
- );*/
+ );
config.transport.check()?;
// Initialise iterates
@@ -165,30 +161,40 @@
let opKz_adj = opKz.adjoint();
let (l, l_z) = Pair(prox_penalty, &idOpZ).step_length_bound_pair(&f)?;
- // We need to satisfy
- //
- // τσ_dM(1-σ_p L_z)/(1 - τ L) + [σ_p L_z + σ_pσ_d‖K_z‖^2] < 1
- // ^^^^^^^^^^^^^^^^^^^^^^^^^
- // with 1 > σ_p L_z and 1 > τ L.
- //
- // To do so, we first solve σ_p and σ_d from standard PDPS step length condition
- // ^^^^^ < 1. then we solve τ from the rest.
- // If opKZ is the zero operator, then we set σ_d = 0 for τ to be calculated correctly below.
- let σ_d = if is_fb { 0.0 } else { config.σd0 / nKz };
- let σ_p = config.σp0 / (l_z + config.σd0 * nKz);
- // Observe that = 1 - ^^^^^^^^^^^^^^^^^^^^^ = 1 - σ_{p,0}
- // We get the condition τσ_d M (1-σ_p L_z) < (1-σ_{p,0})*(1-τ L)
- // ⟺ τ [ σ_d M (1-σ_p L_z) + (1-σ_{p,0}) L ] < (1-σ_{p,0})
- let φ = 1.0 - config.σp0;
- let a = 1.0 - σ_p * l_z;
- let τ = config.τ0 * φ / (σ_d * bigM * a + φ * l);
- let ψ = 1.0 - τ * l;
- let β = σ_p * config.σd0 * nKz / a; // σ_p * σ_d * (nKz * nK_z) / a;
- ensure!(β < 1.0);
- // Now we need κ‖K_μ(π_♯^1 - π_♯^0)γ‖^2 ≤ (1/θ - τ[ℓ_F + ℓ]) ∫ c_2 dγ for κ defined as:
- let κ = τ * σ_d * ψ / ((1.0 - β) * ψ - τ * σ_d * bigM);
- // The factor two in the manuscript disappears due to the definition of 𝚹 being
- // for ‖x-y‖₂² instead of c_2(x, y)=‖x-y‖₂²/2.
+ let (τ, σ_p, σ_d, κ) = if is_fb {
+ (config.τ0 / l, config.σp0 / l_z, 0.0, 0.0)
+ } else {
+ ensure!(
+ //config.τ0 < 1.0 &&
+ config.σp0 < 1.0 && config.σd0 > 0.0 && config.σp0 * config.σd0 <= 1.0,
+ "Invalid step length parameters"
+ );
+ // We need to satisfy
+ //
+ // τσ_dM(1-σ_p L_z)/(1 - τ L) + [σ_p L_z + σ_pσ_d‖K_z‖^2] < 1
+ // ^^^^^^^^^^^^^^^^^^^^^^^^^
+ // with 1 > σ_p L_z and 1 > τ L.
+ //
+ // To do so, we first solve σ_p and σ_d from standard PDPS step length condition
+ // ^^^^^ < 1. then we solve τ from the rest.
+ // If opKZ is the zero operator, then we set σ_d = 0 for τ to be calculated correctly below.
+ let σ_d = config.σd0 / nKz;
+ let σ_p = config.σp0 / (l_z + config.σd0 * nKz);
+ // Observe that = 1 - ^^^^^^^^^^^^^^^^^^^^^ = 1 - σ_{p,0}
+ // We get the condition τσ_d M (1-σ_p L_z) < (1-σ_{p,0})*(1-τ L)
+ // ⟺ τ [ σ_d M (1-σ_p L_z) + (1-σ_{p,0}) L ] < (1-σ_{p,0})
+ let φ = 1.0 - config.σp0;
+ let a = 1.0 - σ_p * l_z;
+ let τ = config.τ0 * φ / (σ_d * bigM * a + φ * l);
+ let ψ = 1.0 - τ * l;
+ let β = σ_p * config.σd0 * nKz / a; // σ_p * σ_d * (nKz * nK_z) / a;
+ ensure!(β < 1.0);
+ // Now we need κ‖K_μ(π_♯^1 - π_♯^0)γ‖^2 ≤ (1/θ - τ[ℓ_F + ℓ]) ∫ c_2 dγ for κ defined as:
+ // The factor two in the manuscript disappears due to the definition of 𝚹 being
+ // for ‖x-y‖₂² instead of c_2(x, y)=‖x-y‖₂²/2.
+ let κ = τ * σ_d * ψ / ((1.0 - β) * ψ - τ * σ_d * bigM);
+ (τ, σ_p, σ_d, κ)
+ };
let mut τθ_or_adaptive = prox_penalty.get_transport_steplength(
f.curvature_bound_components(config.guess),