Fri, 16 Jan 2026 19:39:22 -0500
Lipschitz estimation attempt (incomplete, not implemented for sliding. Doesn't work anyway for basic FB either.)
| 35 | 1 | /*! |
| 2 | Simple parametric forward model. | |
| 3 | */ | |
| 4 | ||
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parents:
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5 | use super::{BasicCurvatureBoundEstimates, BoundedCurvature, BoundedCurvatureGuess, ForwardModel}; |
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parents:
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6 | use crate::dataterm::QuadraticDataTerm; |
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7 | use crate::measures::{Radon, RNDM}; |
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8 | use crate::prox_penalty::{RadonSquared, StepLengthBoundPair}; |
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9 | use crate::seminorms::DiscreteMeasureOp; |
| 35 | 10 | use alg_tools::direct_product::Pair; |
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parents:
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11 | use alg_tools::error::{DynError, DynResult}; |
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parents:
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12 | use alg_tools::euclidean::ClosedEuclidean; |
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13 | use alg_tools::linops::{BoundedLinear, IdOp, RowOp, AXPY}; |
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parents:
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14 | use alg_tools::loc::Loc; |
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15 | use alg_tools::mapping::{Mapping, Space}; |
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16 | use alg_tools::nalgebra_support::ToNalgebraRealField; |
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17 | use alg_tools::norms::{Norm, NormExponent, PairNorm, L2}; |
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18 | use alg_tools::types::{ClosedAdd, Float}; |
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19 | use numeric_literals::replace_float_literals; |
| 35 | 20 | |
| 21 | impl<Domain, F, A, E> ForwardModel<Pair<Domain, A::Observable>, F, PairNorm<E, L2, L2>> | |
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22 | for RowOp<A, IdOp<A::Observable>> |
| 35 | 23 | where |
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24 | E: NormExponent, |
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25 | Domain: Space + Norm<E, F>, |
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26 | F: Float, |
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27 | A::Observable: ClosedAdd + Norm<L2, F> + AXPY<Field = F> + 'static, |
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28 | A: ForwardModel<Domain, F, E> + 'static, |
| 35 | 29 | { |
| 30 | type Observable = A::Observable; | |
| 31 | ||
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32 | fn write_observable(&self, b: &Self::Observable, prefix: String) -> DynError { |
| 35 | 33 | self.0.write_observable(b, prefix) |
| 34 | } | |
| 35 | ||
| 36 | /// Returns a zero observable | |
| 37 | fn zero_observable(&self) -> Self::Observable { | |
| 38 | self.0.zero_observable() | |
| 39 | } | |
| 40 | } | |
| 41 | ||
| 42 | #[replace_float_literals(F::cast_from(literal))] | |
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43 | impl<'a, F, A, 𝒟, Z, const N: usize> |
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44 | StepLengthBoundPair<F, QuadraticDataTerm<F, Pair<RNDM<N, F>, Z>, RowOp<A, IdOp<Z>>>> |
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45 | for Pair<&'a 𝒟, &'a IdOp<Z>> |
| 35 | 46 | where |
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47 | RNDM<N, F>: Space + for<'b> Norm<&'b 𝒟, F>, |
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48 | F: Float + ToNalgebraRealField, |
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49 | 𝒟: DiscreteMeasureOp<Loc<N, F>, F>, |
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50 | Z: Clone + ClosedEuclidean<F>, |
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51 | A: for<'b> BoundedLinear<RNDM<N, F>, &'b 𝒟, L2, F, Codomain = Z>, |
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52 | for<'b> &'b 𝒟: NormExponent, |
| 35 | 53 | { |
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54 | fn step_length_bound_pair( |
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55 | &self, |
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56 | f: &QuadraticDataTerm<F, Pair<RNDM<N, F>, Z>, RowOp<A, IdOp<Z>>>, |
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57 | ) -> DynResult<(F, F)> { |
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58 | let l_0 = f.operator().0.opnorm_bound(self.0, L2)?.powi(2); |
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59 | // [A_*; B_*][A, B] = [A_*A, A_* B; B_* A, B_* B] ≤ diag(2A_*A, 2B_*B) |
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60 | // ≤ diag(2l_A𝒟_A, 2l_B𝒟_B), where now 𝒟_B=Id and l_B=1. |
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61 | Ok((2.0 * l_0, 2.0)) |
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62 | } |
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63 | } |
| 35 | 64 | |
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parents:
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65 | #[replace_float_literals(F::cast_from(literal))] |
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66 | impl<'a, F, A, Z, const N: usize> |
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67 | StepLengthBoundPair<F, QuadraticDataTerm<F, Pair<RNDM<N, F>, Z>, RowOp<A, IdOp<Z>>>> |
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68 | for Pair<&'a RadonSquared, &'a IdOp<Z>> |
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69 | where |
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70 | RNDM<N, F>: Space + Norm<Radon, F>, |
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71 | F: Float + ToNalgebraRealField, |
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72 | Z: Clone + ClosedEuclidean<F>, |
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73 | A: BoundedLinear<RNDM<N, F>, Radon, L2, F, Codomain = Z>, |
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74 | { |
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75 | fn step_length_bound_pair( |
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76 | &self, |
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77 | f: &QuadraticDataTerm<F, Pair<RNDM<N, F>, Z>, RowOp<A, IdOp<Z>>>, |
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78 | ) -> DynResult<(F, F)> { |
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79 | let l_0 = f.operator().0.opnorm_bound(Radon, L2)?.powi(2); |
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80 | // [A_*; B_*][A, B] = [A_*A, A_* B; B_* A, B_* B] ≤ diag(2A_*A, 2B_*B) |
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81 | // ≤ diag(2l_A𝒟_A, 2l_B𝒟_B), where now 𝒟_B=Id and l_B=1. |
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82 | Ok((2.0 * l_0, 2.0)) |
| 35 | 83 | } |
| 84 | } | |
| 85 | ||
| 44 | 86 | /* |
| 35 | 87 | /// This `impl` is bit of an abuse as the codomain of `Apre` is a [`Pair`] of a measure predual, |
| 88 | /// to which this `impl` applies, and another space. | |
| 89 | impl<F, Apre, Z> LipschitzValues | |
| 90 | for ColOp<Apre, IdOp<Z>> | |
| 91 | where | |
| 92 | F : Float, | |
| 93 | Z : Clone + Space + ClosedAdd, | |
| 94 | Apre : LipschitzValues<FloatType = F>, | |
| 95 | { | |
| 96 | type FloatType = F; | |
| 97 | /// Return (if one exists) a factor $L$ such that $A_*z$ is $L$-Lipschitz for all | |
| 98 | /// $z$ in the unit ball. | |
| 99 | fn value_unit_lipschitz_factor(&self) -> Option<Self::FloatType> { | |
| 100 | self.0.value_unit_lipschitz_factor() | |
| 101 | } | |
| 102 | ||
| 103 | /// Return (if one exists) a factor $L$ such that $∇A_*z$ is $L$-Lipschitz for all | |
| 104 | /// $z$ in the unit ball. | |
| 105 | fn value_diff_unit_lipschitz_factor(&self) -> Option<Self::FloatType> { | |
| 106 | self.0.value_diff_unit_lipschitz_factor() | |
| 107 | } | |
| 108 | } | |
| 44 | 109 | */ |
| 35 | 110 | |
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111 | use BoundedCurvatureGuess::*; |
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112 | |
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113 | /// Curvature error control: helper bounds for (4.2d), (5.2a), (5.2b), (5.15a), and (5.16a). |
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114 | /// |
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115 | /// Based on Lemma 5.11 and Example 5.12, the helper bound for (5.15a) and (5.16a) is (3.8). |
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116 | /// Due to Example 6.1, defining $v^k$ as the projection $F'$ to the predual space of the |
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117 | /// measures, returns, if possible, and subject to the guess being correct, factors $ℓ_F$ and |
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118 | /// $Θ²$ such that $B_{P_ℳ^* F'(μ, z)} dγ ≤ ℓ_F c_2$ and |
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119 | /// $⟨P_ℳ^*[F'(μ+Δ, z)-F'(μ, z)]|Δ⟩ ≤ Θ²|γ|(c_2)‖γ‖$, where $Δ=(π_♯^1-π_♯^0)γ$. |
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120 | /// For our $F(μ, z)=\frac{1}{2}\|Aμ+z-b\|^2$, we have $F'(μ, z)=A\_*(Aμ+z-b)$, so |
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121 | /// $F'(μ+Δ, z)-F'(μ, z)=A\_*AΔ$ is independent of $z$, and the bounding can be calculated |
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122 | /// as in the case without $z$, based on Lemma 3.8. |
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123 | /// |
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124 | /// We use Remark 5.15 and Example 5.16 for (4.2d) and (5.2a) with the additional effect of $z$. |
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125 | /// This is based on a Lipschitz estimate for $∇v^k$, where we still, similarly to the Example, |
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126 | /// have $∇v^k(x)=∇A\_*(x)[Aμ^k+z^k-b]$. We estimate the final term similarly to the example, |
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127 | /// assuming for the guess [`BetterThanZero`] that every iterate is better than $(μ, z)=0$. |
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128 | /// This the final estimate is exactly as in the example, without $z$. |
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129 | /// Thus we can directly use [`BasicCurvatureBoundEstimates`] on the operator $A$. |
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130 | impl<F, A, Z, const N: usize> BoundedCurvature<F> |
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131 | for QuadraticDataTerm<F, Pair<RNDM<N, F>, Z>, RowOp<A, IdOp<Z>>> |
| 44 | 132 | where |
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133 | F: Float, |
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134 | Z: Clone + ClosedEuclidean<F>, |
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135 | A: Mapping<RNDM<N, F>, Codomain = Z>, |
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136 | A: BasicCurvatureBoundEstimates<F>, |
| 44 | 137 | { |
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138 | fn curvature_bound_components( |
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139 | &self, |
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140 | guess: BoundedCurvatureGuess, |
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141 | ) -> (DynResult<F>, DynResult<F>) { |
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142 | match guess { |
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143 | BetterThanZero => { |
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144 | let opA = &self.operator().0; |
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145 | let b = self.data(); |
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146 | let (ℓ_F0, θ2) = opA.basic_curvature_bound_components(); |
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147 | (ℓ_F0.map(|l| l * b.norm2()), θ2) |
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148 | } |
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149 | } |
| 35 | 150 | } |
| 151 | } |