Mercurial > repos > pointsource_algs / file comparison
comparison: src/sliding_fb.rs
src/sliding_fb.rs
- changeset 75
- 677a5fd1b014
- parent 72
- e9a460a0e638
- child 78
- 2a122736e91c
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| 74:df92e78cc3f4 | 75:677a5fd1b014 |
|---|---|
| 1039 | 1039 |
| 1040 let mut attempts = 0; | 1040 let mut attempts = 0; |
| 1041 | 1041 |
| 1042 // Solve finite-dimensional subproblem several times until the dual variable for the | 1042 // Solve finite-dimensional subproblem several times until the dual variable for the |
| 1043 // regularisation term conforms to the assumptions made for the transport above. | 1043 // regularisation term conforms to the assumptions made for the transport above. |
| 1044 let (maybe_d, _within_tolerances, mut τv̆, μ̆) = 'adapt_transport: loop { | 1044 let (mut τv̆, μ̆) = 'adapt_transport: loop { |
| 1045 // Set initial guess for μ=μ^{k+1}. | 1045 // Set initial guess for μ=μ^{k+1}. |
| 1046 γ.μ̆_into(&mut μ); | 1046 γ.μ̆_into(&mut μ); |
| 1047 let μ̆ = μ.clone(); | 1047 let μ̆ = μ.clone(); |
| 1048 | 1048 |
| 1049 // Calculate τv̆ = τA_*(A[μ_transported + μ_transported_base]-b) | 1049 // Calculate τv̆ = τA_*(A[μ_transported + μ_transported_base]-b) |
| 1052 // old residual2. | 1052 // old residual2. |
| 1053 // NOTE: This assumes that μ = γ1 | 1053 // NOTE: This assumes that μ = γ1 |
| 1054 let mut τv̆ = f.differential(&μ̆) * τ; | 1054 let mut τv̆ = f.differential(&μ̆) * τ; |
| 1055 | 1055 |
| 1056 // Construct μ^{k+1} by solving finite-dimensional subproblems and insert new spikes. | 1056 // Construct μ^{k+1} by solving finite-dimensional subproblems and insert new spikes. |
| 1057 let (maybe_d, within_tolerances) = prox_penalty.insert_and_reweigh( | 1057 prox_penalty.insert_and_reweigh( |
| 1058 &mut μ, | 1058 &mut μ, |
| 1059 &mut τv̆, | 1059 &mut τv̆, |
| 1060 τ, | 1060 τ, |
| 1061 ε, | 1061 ε, |
| 1062 &config.insertion, | 1062 &config.insertion, |
| 1079 reg, | 1079 reg, |
| 1080 &config.transport, | 1080 &config.transport, |
| 1081 &config.insertion.refinement, | 1081 &config.insertion.refinement, |
| 1082 &mut attempts, | 1082 &mut attempts, |
| 1083 ) { | 1083 ) { |
| 1084 break 'adapt_transport (maybe_d, within_tolerances, τv̆, μ̆); | 1084 break 'adapt_transport (τv̆, μ̆); |
| 1085 } | 1085 } |
| 1086 | 1086 |
| 1087 stats.get_transport_mut().readjustment_iters += 1; | 1087 stats.get_transport_mut().readjustment_iters += 1; |
| 1088 }; | 1088 }; |
| 1089 | 1089 |
| 1101 ε, | 1101 ε, |
| 1102 &config.insertion, | 1102 &config.insertion, |
| 1103 ®, | 1103 ®, |
| 1104 Some(|μ̃: &RNDM<N, F>| f.apply(μ̃)), | 1104 Some(|μ̃: &RNDM<N, F>| f.apply(μ̃)), |
| 1105 ); | 1105 ); |
| 1106 if m > 0 { | 1106 //if m > 0 { |
| 1107 stats.merged += m; | 1107 stats.merged += m; |
| 1108 v = f.differential(&μ); | 1108 //v = f.differential(&μ); |
| 1109 } | 1109 //} |
| 1110 } | 1110 } |
| 1111 | 1111 |
| 1112 γ.prune_compat(&mut μ, &mut stats); | 1112 γ.prune_compat(&mut μ, &mut stats); |
| 1113 | |
| 1114 // Do extra weight optimisation step heuristic | |
| 1115 for _ in 1..config.insertion.extra_weight_optimisation_steps { | |
| 1116 τv̆ = f.differential(&μ) * τ; | |
| 1117 prox_penalty.reweigh( | |
| 1118 &mut μ, | |
| 1119 &mut τv̆, | |
| 1120 τ, | |
| 1121 ε, | |
| 1122 &config.insertion, | |
| 1123 ®, | |
| 1124 &state, | |
| 1125 &mut stats, | |
| 1126 )?; | |
| 1127 } | |
| 1128 | |
| 1129 if config.insertion.extra_weight_optimisation_steps > 0 { | |
| 1130 γ.prune_compat(&mut μ, &mut stats); | |
| 1131 } | |
| 1113 | 1132 |
| 1114 let iter = state.iteration(); | 1133 let iter = state.iteration(); |
| 1115 stats.this_iters += 1; | 1134 stats.this_iters += 1; |
| 1116 | 1135 |
| 1117 // Give statistics if requested | 1136 // Give statistics if requested |
| 1118 state.if_verbose(|| { | 1137 state.if_verbose(|| { |
| 1119 plotter.plot_spikes(iter, maybe_d.as_ref(), Some(&τv̆), &μ); | 1138 plotter.plot_spikes(iter, None, Some(&τv̆), &μ); |
| 1120 full_stats(&μ, ε, std::mem::replace(&mut stats, IterInfo::new())) | 1139 full_stats(&μ, ε, std::mem::replace(&mut stats, IterInfo::new())) |
| 1121 }); | 1140 }); |
| 1122 | 1141 |
| 1123 // Update main tolerance for next iteration | 1142 // Update main tolerance for next iteration |
| 1124 ε = tolerance.update(ε, iter); | 1143 ε = tolerance.update(ε, iter); |
