Mercurial > repos > pointsource_algs / file comparison
comparison: src/frank_wolfe.rs
src/frank_wolfe.rs
- changeset 4
- 5aa5c279e341
- parent 0
- eb3c7813b67a
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| 0:eb3c7813b67a | 4:5aa5c279e341 |
|---|---|
| 147 α : F, | 147 α : F, |
| 148 findim_data : &FindimData<F>, | 148 findim_data : &FindimData<F>, |
| 149 inner : &InnerSettings<F>, | 149 inner : &InnerSettings<F>, |
| 150 iterator : I | 150 iterator : I |
| 151 ) -> usize | 151 ) -> usize |
| 152 where F : Float + ToNalgebraRealField, | 152 where F : Float + ToNalgebraRealField<MixedType=F>, |
| 153 I : AlgIteratorFactory<F>, | 153 I : AlgIteratorFactory<F>, |
| 154 A : ForwardModel<Loc<F, N>, F> | 154 A : ForwardModel<Loc<F, N>, F> |
| 155 { | 155 { |
| 156 // Form and solve finite-dimensional subproblem. | 156 // Form and solve finite-dimensional subproblem. |
| 157 let (Ã, g̃) = opA.findim_quadratic_model(&μ, b); | 157 let (Ã, g̃) = opA.findim_quadratic_model(&μ, b); |
| 158 let mut x = μ.masses_dvector(); | 158 let mut x = μ.masses_mut(); |
| 159 | 159 |
| 160 // `inner_τ1` is based on an estimate of the operator norm of $A$ from ℳ(Ω) to | 160 // `inner_τ1` is based on an estimate of the operator norm of $A$ from ℳ(Ω) to |
| 161 // ℝ^n. This estimate is a good one for the matrix norm from ℝ^m to ℝ^n when the | 161 // ℝ^n. This estimate is a good one for the matrix norm from ℝ^m to ℝ^n when the |
| 162 // former is equipped with the 1-norm. We need the 2-norm. To pass from 1-norm to | 162 // former is equipped with the 1-norm. We need the 2-norm. To pass from 1-norm to |
| 163 // 2-norm, we estimate | 163 // 2-norm, we estimate |
| 166 // where C = √m satisfies ‖x‖_1 ≤ C ‖x‖_2. Since we are intested in ‖A_*A‖, no | 166 // where C = √m satisfies ‖x‖_1 ≤ C ‖x‖_2. Since we are intested in ‖A_*A‖, no |
| 167 // square root is needed when we scale: | 167 // square root is needed when we scale: |
| 168 let inner_τ = inner.τ0 / (findim_data.opAnorm_squared * F::cast_from(μ.len())); | 168 let inner_τ = inner.τ0 / (findim_data.opAnorm_squared * F::cast_from(μ.len())); |
| 169 let iters = quadratic_nonneg(inner.method, &Ã, &g̃, α, &mut x, inner_τ, iterator); | 169 let iters = quadratic_nonneg(inner.method, &Ã, &g̃, α, &mut x, inner_τ, iterator); |
| 170 // Update masses of μ based on solution of finite-dimensional subproblem. | 170 // Update masses of μ based on solution of finite-dimensional subproblem. |
| 171 μ.set_masses_dvector(&x); | 171 //μ.set_masses_dvector(&x); |
| 172 | 172 |
| 173 iters | 173 iters |
| 174 } | 174 } |
| 175 | 175 |
| 176 /// Solve point source localisation problem using a conditional gradient method | 176 /// Solve point source localisation problem using a conditional gradient method |
| 191 //domain : Cube<F, N>, | 191 //domain : Cube<F, N>, |
| 192 config : &FWConfig<F>, | 192 config : &FWConfig<F>, |
| 193 iterator : I, | 193 iterator : I, |
| 194 mut plotter : SeqPlotter<F, N>, | 194 mut plotter : SeqPlotter<F, N>, |
| 195 ) -> DiscreteMeasure<Loc<F, N>, F> | 195 ) -> DiscreteMeasure<Loc<F, N>, F> |
| 196 where F : Float + ToNalgebraRealField, | 196 where F : Float + ToNalgebraRealField<MixedType=F>, |
| 197 I : AlgIteratorFactory<IterInfo<F, N>>, | 197 I : AlgIteratorFactory<IterInfo<F, N>>, |
| 198 for<'b> &'b A::Observable : std::ops::Neg<Output=A::Observable>, | 198 for<'b> &'b A::Observable : std::ops::Neg<Output=A::Observable>, |
| 199 //+ std::ops::Mul<F, Output=A::Observable>, <-- FIXME: compiler overflow | 199 //+ std::ops::Mul<F, Output=A::Observable>, <-- FIXME: compiler overflow |
| 200 A::Observable : std::ops::MulAssign<F>, | 200 A::Observable : std::ops::MulAssign<F>, |
| 201 GA : SupportGenerator<F, N, SupportType = S, Id = usize> + Clone, | 201 GA : SupportGenerator<F, N, SupportType = S, Id = usize> + Clone, |
