Mercurial > repos > pointsource_algs / file comparison
comparison: src/forward_model.rs
src/forward_model.rs
- changeset 2
- 7a953a87b6c1
- parent 0
- eb3c7813b67a
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| 0:eb3c7813b67a | 2:7a953a87b6c1 |
|---|---|
| 51 /// It is assumed to be a [`Euclidean`] space, and therefore also (identified with) | 51 /// It is assumed to be a [`Euclidean`] space, and therefore also (identified with) |
| 52 /// the domain of the preadjoint. | 52 /// the domain of the preadjoint. |
| 53 type Observable : Euclidean<F, Output=Self::Observable> | 53 type Observable : Euclidean<F, Output=Self::Observable> |
| 54 + AXPY<F> | 54 + AXPY<F> |
| 55 + Clone; | 55 + Clone; |
| 56 | 56 /// Finite-dimensional model for weight optimisation |
| 57 /// Return A_*A and A_* b | 57 type FindimModel : Linear<DVector<F::MixedType>, Codomain=Self::Observable>; |
| 58 | |
| 59 /// Return A_*A and A_* b instantiated at the locations of the spikes of `μ`. | |
| 58 fn findim_quadratic_model( | 60 fn findim_quadratic_model( |
| 59 &self, | 61 &self, |
| 60 μ : &DiscreteMeasure<Domain, F>, | 62 μ : &DiscreteMeasure<Domain, F>, |
| 61 b : &Self::Observable | 63 b : &Self::Observable |
| 62 ) -> (DMatrix<F::MixedType>, DVector<F::MixedType>); | 64 ) -> (DMatrix<F::MixedType>, DVector<F::MixedType>); |
| 65 | |
| 66 /// Return A instantiated at the locations of the spikes of `μ` | |
| 67 fn findim_model( | |
| 68 &self, | |
| 69 μ : &DiscreteMeasure<Domain, F>, | |
| 70 ) -> Self::FindimModel; | |
| 63 | 71 |
| 64 /// Write an observable into a file. | 72 /// Write an observable into a file. |
| 65 fn write_observable(&self, b : &Self::Observable, prefix : String) -> DynError; | 73 fn write_observable(&self, b : &Self::Observable, prefix : String) -> DynError; |
| 66 | 74 |
| 67 /// Returns a zero observable | 75 /// Returns a zero observable |
| 515 P : Spread<F, N>, | 523 P : Spread<F, N>, |
| 516 Convolution<S, P> : Spread<F, N>, | 524 Convolution<S, P> : Spread<F, N>, |
| 517 ShiftedSensor<F, S, P, N> : LocalAnalysis<F, BT::Agg, N>, | 525 ShiftedSensor<F, S, P, N> : LocalAnalysis<F, BT::Agg, N>, |
| 518 Weighted<ShiftedSensor<F, S, P, N>, F> : LocalAnalysis<F, BT::Agg, N> { | 526 Weighted<ShiftedSensor<F, S, P, N>, F> : LocalAnalysis<F, BT::Agg, N> { |
| 519 type Observable = DVector<F>; | 527 type Observable = DVector<F>; |
| 528 type FindimModel = DMatrix<F>; | |
| 520 | 529 |
| 521 fn findim_quadratic_model( | 530 fn findim_quadratic_model( |
| 522 &self, | 531 &self, |
| 523 μ : &DiscreteMeasure<Loc<F, N>, F>, | 532 μ : &DiscreteMeasure<Loc<F, N>, F>, |
| 524 b : &Self::Observable | 533 b : &Self::Observable |
| 525 ) -> (DMatrix<F::MixedType>, DVector<F::MixedType>) { | 534 ) -> (DMatrix<F::MixedType>, DVector<F::MixedType>) { |
| 526 assert_eq!(b.len(), self.n_sensors()); | 535 assert_eq!(b.len(), self.n_sensors()); |
| 536 let mA = self.findim_model(μ); | |
| 537 let mAt = mA.transpose(); | |
| 538 (&mAt * mA, &mAt * b) | |
| 539 } | |
| 540 | |
| 541 fn findim_model( | |
| 542 &self, | |
| 543 μ : &DiscreteMeasure<Loc<F, N>, F>, | |
| 544 ) -> DMatrix<F::MixedType> { | |
| 527 let mut mA = DMatrix::zeros(self.n_sensors(), μ.len()); | 545 let mut mA = DMatrix::zeros(self.n_sensors(), μ.len()); |
| 528 let grid = self.grid(); | 546 let grid = self.grid(); |
| 529 for (mut mAcol, δ) in mA.column_iter_mut().zip(μ.iter_spikes()) { | 547 for (mut mAcol, δ) in mA.column_iter_mut().zip(μ.iter_spikes()) { |
| 530 for &d in self.bt.iter_at(&δ.x) { | 548 for &d in self.bt.iter_at(&δ.x) { |
| 531 let sensor = self.shifted_sensor(grid.entry_linear_unchecked(d)); | 549 let sensor = self.shifted_sensor(grid.entry_linear_unchecked(d)); |
| 532 mAcol[d] += sensor.apply(&δ.x); | 550 mAcol[d] += sensor.apply(&δ.x); |
| 533 } | 551 } |
| 534 } | 552 } |
| 535 let mAt = mA.transpose(); | 553 mA |
| 536 (&mAt * mA, &mAt * b) | |
| 537 } | 554 } |
| 538 | 555 |
| 539 fn write_observable(&self, b : &Self::Observable, prefix : String) -> DynError { | 556 fn write_observable(&self, b : &Self::Observable, prefix : String) -> DynError { |
| 540 let it = self.grid().into_iter().zip(b.iter()).map(|(x, &v)| (x, v)); | 557 let it = self.grid().into_iter().zip(b.iter()).map(|(x, &v)| (x, v)); |
| 541 write_csv(it, prefix + ".txt") | 558 write_csv(it, prefix + ".txt") |
