--- a/src/forward_model/sensor_grid.rs Sun Apr 27 15:03:51 2025 -0500
+++ b/src/forward_model/sensor_grid.rs Thu Feb 26 11:38:43 2026 -0500
@@ -2,13 +2,17 @@
Sensor grid forward model
*/
-use nalgebra::base::{DMatrix, DVector};
-use numeric_literals::replace_float_literals;
-use std::iter::Zip;
-use std::ops::RangeFrom;
-
+use super::{BasicCurvatureBoundEstimates, ForwardModel};
+use crate::frank_wolfe::FindimQuadraticModel;
+use crate::kernels::{AutoConvolution, BoundedBy, Convolution};
+use crate::measures::{DiscreteMeasure, Radon, RNDM};
+use crate::preadjoint_helper::PreadjointHelper;
+use crate::seminorms::{ConvolutionOp, SimpleConvolutionKernel};
+use crate::types::*;
use alg_tools::bisection_tree::*;
-use alg_tools::error::DynError;
+use alg_tools::bounds::Bounded;
+use alg_tools::error::{DynError, DynResult};
+use alg_tools::euclidean::Euclidean;
use alg_tools::instance::Instance;
use alg_tools::iter::{MapX, Mappable};
use alg_tools::lingrid::*;
@@ -18,79 +22,74 @@
use alg_tools::nalgebra_support::ToNalgebraRealField;
use alg_tools::norms::{Linfinity, Norm, L1, L2};
use alg_tools::tabledump::write_csv;
+use anyhow::anyhow;
+use nalgebra::base::{DMatrix, DVector};
+use numeric_literals::replace_float_literals;
+use std::iter::Zip;
+use std::ops::RangeFrom;
-use super::{AdjointProductBoundedBy, BoundedCurvature, ForwardModel};
-use crate::frank_wolfe::FindimQuadraticModel;
-use crate::kernels::{AutoConvolution, BoundedBy, Convolution};
-use crate::measures::{DiscreteMeasure, Radon};
-use crate::preadjoint_helper::PreadjointHelper;
-use crate::seminorms::{ConvolutionOp, SimpleConvolutionKernel};
-use crate::types::*;
-
-type RNDM<F, const N: usize> = DiscreteMeasure<Loc<F, N>, F>;
-
-pub type ShiftedSensor<F, S, P, const N: usize> = Shift<Convolution<S, P>, F, N>;
+pub type ShiftedSensor<F, S, P, const N: usize> = Shift<Convolution<S, P>, N, F>;
/// Trait for physical convolution models. Has blanket implementation for all cases.
-pub trait Spread<F: Float, const N: usize>:
- 'static + Clone + Support<F, N> + RealMapping<F, N> + Bounded<F>
+pub trait Spread<const N: usize, F: Float = f64>:
+ 'static + Clone + Support<N, F> + RealMapping<N, F> + Bounded<F>
{
}
-impl<F, T, const N: usize> Spread<F, N> for T
+impl<F, T, const N: usize> Spread<N, F> for T
where
F: Float,
- T: 'static + Clone + Support<F, N> + Bounded<F> + RealMapping<F, N>,
+ T: 'static + Clone + Support<N, F> + Bounded<F> + RealMapping<N, F>,
{
}
/// Trait for compactly supported sensors. Has blanket implementation for all cases.
-pub trait Sensor<F: Float, const N: usize>:
- Spread<F, N> + Norm<F, L1> + Norm<F, Linfinity>
+pub trait Sensor<const N: usize, F: Float = f64>:
+ Spread<N, F> + Norm<L1, F> + Norm<Linfinity, F>
{
}
-impl<F, T, const N: usize> Sensor<F, N> for T
+impl<F, T, const N: usize> Sensor<N, F> for T
where
F: Float,
- T: Spread<F, N> + Norm<F, L1> + Norm<F, Linfinity>,
+ T: Spread<N, F> + Norm<L1, F> + Norm<Linfinity, F>,
{
}
pub trait SensorGridBT<F, S, P, const N: usize>:
- Clone + BTImpl<F, N, Data = usize, Agg = Bounds<F>>
+ Clone + BTImpl<N, F, Data = usize, Agg = Bounds<F>>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
{
}
impl<F, S, P, T, const N: usize> SensorGridBT<F, S, P, N> for T
where
- T: Clone + BTImpl<F, N, Data = usize, Agg = Bounds<F>>,
+ T: Clone + BTImpl<N, F, Data = usize, Agg = Bounds<F>>,
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
{
}
// We need type alias bounds to access associated types
#[allow(type_alias_bounds)]
pub type SensorGridBTFN<F, S, P, BT: SensorGridBT<F, S, P, N>, const N: usize> =
- BTFN<F, SensorGridSupportGenerator<F, S, P, N>, BT, N>;
+ BTFN<F, SensorGridSupportGenerator<S, F, P, N>, BT, N>;
/// Sensor grid forward model
#[derive(Clone)]
pub struct SensorGrid<F, S, P, BT, const N: usize>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
BT: SensorGridBT<F, S, P, N>,
{
- domain: Cube<F, N>,
+ domain: Cube<N, F>,
sensor_count: [usize; N],
sensor: S,
spread: P,
@@ -102,16 +101,16 @@
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N> + LocalAnalysis<F, BT::Agg, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F> + LocalAnalysis<F, BT::Agg, N>,
{
/// Create a new sensor grid.
///
/// The parameter `depth` indicates the search depth of the created [`BT`]s
/// for the adjoint values.
pub fn new(
- domain: Cube<F, N>,
+ domain: Cube<N, F>,
sensor_count: [usize; N],
sensor: S,
spread: P,
@@ -141,12 +140,12 @@
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
/// Return the grid of sensor locations.
- pub fn grid(&self) -> LinGrid<F, N> {
+ pub fn grid(&self) -> LinGrid<N, F> {
lingrid_centered(&self.domain, &self.sensor_count)
}
@@ -157,7 +156,7 @@
/// Constructs a sensor shifted by `x`.
#[inline]
- fn shifted_sensor(&self, x: Loc<F, N>) -> ShiftedSensor<F, S, P, N> {
+ fn shifted_sensor(&self, x: Loc<N, F>) -> ShiftedSensor<F, S, P, N> {
self.base_sensor.clone().shift(x)
}
@@ -180,44 +179,44 @@
}
}
-impl<F, S, P, BT, const N: usize> Mapping<RNDM<F, N>> for SensorGrid<F, S, P, BT, N>
+impl<F, S, P, BT, const N: usize> Mapping<RNDM<N, F>> for SensorGrid<F, S, P, BT, N>
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
type Codomain = DVector<F>;
#[inline]
- fn apply<I: Instance<RNDM<F, N>>>(&self, μ: I) -> DVector<F> {
+ fn apply<I: Instance<RNDM<N, F>>>(&self, μ: I) -> DVector<F> {
let mut y = self._zero_observable();
self.apply_add(&mut y, μ);
y
}
}
-impl<F, S, P, BT, const N: usize> Linear<RNDM<F, N>> for SensorGrid<F, S, P, BT, N>
+impl<F, S, P, BT, const N: usize> Linear<RNDM<N, F>> for SensorGrid<F, S, P, BT, N>
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
}
#[replace_float_literals(F::cast_from(literal))]
-impl<F, S, P, BT, const N: usize> GEMV<F, RNDM<F, N>, DVector<F>> for SensorGrid<F, S, P, BT, N>
+impl<F, S, P, BT, const N: usize> GEMV<F, RNDM<N, F>, DVector<F>> for SensorGrid<F, S, P, BT, N>
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
- fn gemv<I: Instance<RNDM<F, N>>>(&self, y: &mut DVector<F>, α: F, μ: I, β: F) {
+ fn gemv<I: Instance<RNDM<N, F>>>(&self, y: &mut DVector<F>, α: F, μ: I, β: F) {
let grid = self.grid();
if β == 0.0 {
y.fill(0.0)
@@ -227,38 +226,42 @@
if α == 1.0 {
self.apply_add(y, μ)
} else {
- for δ in μ.ref_instance() {
- for &d in self.bt.iter_at(&δ.x) {
- let sensor = self.shifted_sensor(grid.entry_linear_unchecked(d));
- y[d] += sensor.apply(&δ.x) * (α * δ.α);
+ μ.eval_ref(|μr| {
+ for δ in μr {
+ for &d in self.bt.iter_at(&δ.x) {
+ let sensor = self.shifted_sensor(grid.entry_linear_unchecked(d));
+ y[d] += sensor.apply(&δ.x) * (α * δ.α);
+ }
}
- }
+ })
}
}
- fn apply_add<I: Instance<RNDM<F, N>>>(&self, y: &mut DVector<F>, μ: I) {
+ fn apply_add<I: Instance<RNDM<N, F>>>(&self, y: &mut DVector<F>, μ: I) {
let grid = self.grid();
- for δ in μ.ref_instance() {
- for &d in self.bt.iter_at(&δ.x) {
- let sensor = self.shifted_sensor(grid.entry_linear_unchecked(d));
- y[d] += sensor.apply(&δ.x) * δ.α;
+ μ.eval_ref(|μr| {
+ for δ in μr {
+ for &d in self.bt.iter_at(&δ.x) {
+ let sensor = self.shifted_sensor(grid.entry_linear_unchecked(d));
+ y[d] += sensor.apply(&δ.x) * δ.α;
+ }
}
- }
+ })
}
}
-impl<F, S, P, BT, const N: usize> BoundedLinear<RNDM<F, N>, Radon, L2, F>
+impl<F, S, P, BT, const N: usize> BoundedLinear<RNDM<N, F>, Radon, L2, F>
for SensorGrid<F, S, P, BT, N>
where
F: Float,
- BT: SensorGridBT<F, S, P, N, Agg = Bounds<F>>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N> + LocalAnalysis<F, BT::Agg, N>,
+ BT: SensorGridBT<F, S, P, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
/// An estimate on the operator norm in $𝕃(ℳ(Ω); ℝ^n)$ with $ℳ(Ω)$ equipped
/// with the Radon norm, and $ℝ^n$ with the Euclidean norm.
- fn opnorm_bound(&self, _: Radon, _: L2) -> F {
+ fn opnorm_bound(&self, _: Radon, _: L2) -> DynResult<F> {
// With {x_i}_{i=1}^n the grid centres and φ the kernel, we have
// |Aμ|_2 = sup_{|z|_2 ≤ 1} ⟨z,Αμ⟩ = sup_{|z|_2 ≤ 1} ⟨A^*z|μ⟩
// ≤ sup_{|z|_2 ≤ 1} |A^*z|_∞ |μ|_ℳ
@@ -271,22 +274,22 @@
// = |φ|_∞ √N_ψ |μ|_ℳ.
// Hence
let n = self.max_overlapping();
- self.base_sensor.bounds().uniform() * n.sqrt()
+ Ok(self.base_sensor.bounds().uniform() * n.sqrt())
}
}
-type SensorGridPreadjoint<'a, A, F, const N: usize> = PreadjointHelper<'a, A, RNDM<F, N>>;
+type SensorGridPreadjoint<'a, A, F, const N: usize> = PreadjointHelper<'a, A, RNDM<N, F>>;
-impl<F, S, P, BT, const N: usize> Preadjointable<RNDM<F, N>, DVector<F>>
+impl<F, S, P, BT, const N: usize> Preadjointable<RNDM<N, F>, DVector<F>>
for SensorGrid<F, S, P, BT, N>
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N> + LocalAnalysis<F, BT::Agg, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F> + LocalAnalysis<F, BT::Agg, N>,
{
- type PreadjointCodomain = BTFN<F, SensorGridSupportGenerator<F, S, P, N>, BT, N>;
+ type PreadjointCodomain = BTFN<F, SensorGridSupportGenerator<S, F, P, N>, BT, N>;
type Preadjoint<'a>
= SensorGridPreadjoint<'a, Self, F, N>
where
@@ -303,10 +306,10 @@
for SensorGridPreadjoint<'a, SensorGrid<F, S, P, BT, N>, F, N>
where F : Float,
BT : SensorGridBT<F, S, P, N>,
- S : Sensor<F, N>,
- P : Spread<F, N>,
- Convolution<S, P> : Spread<F, N> + Lipschitz<L2, FloatType=F> + DifferentiableMapping<Loc<F,N>> + LocalAnalysis<F, BT::Agg, N>,
- for<'b> <Convolution<S, P> as DifferentiableMapping<Loc<F,N>>>::Differential<'b> : Lipschitz<L2, FloatType=F>,
+ S : Sensor<N, F>,
+ P : Spread<N, F>,
+ Convolution<S, P> : Spread<N, F> + Lipschitz<L2, FloatType=F> + DifferentiableMapping<Loc<N, F>> + LocalAnalysis<F, BT::Agg, N>,
+ for<'b> <Convolution<S, P> as DifferentiableMapping<Loc<N, F>>>::Differential<'b> : Lipschitz<L2, FloatType=F>,
{
type FloatType = F;
@@ -332,55 +335,49 @@
*/
#[replace_float_literals(F::cast_from(literal))]
-impl<'a, F, S, P, BT, const N: usize> BoundedCurvature for SensorGrid<F, S, P, BT, N>
+impl<'a, F, S, P, BT, const N: usize> BasicCurvatureBoundEstimates<F> for SensorGrid<F, S, P, BT, N>
where
- F: Float,
+ F: Float + ToNalgebraRealField,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ DVector<F>: Euclidean<F>,
+ Convolution<S, P>: Spread<N, F>
+ Lipschitz<L2, FloatType = F>
- + DifferentiableMapping<Loc<F, N>>
+ + DifferentiableMapping<Loc<N, F>>
+ LocalAnalysis<F, BT::Agg, N>,
- for<'b> <Convolution<S, P> as DifferentiableMapping<Loc<F, N>>>::Differential<'b>:
+ for<'b> <Convolution<S, P> as DifferentiableMapping<Loc<N, F>>>::Differential<'b>:
Lipschitz<L2, FloatType = F>,
{
- type FloatType = F;
-
- /// Returns factors $ℓ_F$ and $Θ²$ such that
- /// $B_{F'(μ)} dγ ≤ ℓ_F c_2$ and $⟨F'(μ)+F'(μ+Δ)|Δ⟩ ≤ Θ²|γ|(c_2)‖γ‖$,
- /// where $Δ=(π_♯^1-π_♯^0)γ$.
- ///
- /// See Lemma 3.8, Lemma 5.10, Remark 5.14, and Example 5.15.
- fn curvature_bound_components(&self) -> (Option<Self::FloatType>, Option<Self::FloatType>) {
+ fn basic_curvature_bound_components(&self) -> (DynResult<F>, DynResult<F>) {
let n_ψ = self.max_overlapping();
let ψ_diff_lip = self.base_sensor.diff_ref().lipschitz_factor(L2);
let ψ_lip = self.base_sensor.lipschitz_factor(L2);
- let ℓ_F = ψ_diff_lip.map(|l| (2.0 * n_ψ).sqrt() * l);
- let θ2 = ψ_lip.map(|l| 4.0 * n_ψ * l.powi(2));
+ let ℓ_F0 = ψ_diff_lip.map(|l| (2.0 * n_ψ).sqrt() * l);
+ let Θ2 = ψ_lip.map(|l| 4.0 * n_ψ * l.powi(2));
- (ℓ_F, θ2)
+ (ℓ_F0, Θ2)
}
}
#[derive(Clone, Debug)]
-pub struct SensorGridSupportGenerator<F, S, P, const N: usize>
+pub struct SensorGridSupportGenerator<S, F, P, const N: usize>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
{
base_sensor: Convolution<S, P>,
- grid: LinGrid<F, N>,
+ grid: LinGrid<N, F>,
weights: DVector<F>,
}
-impl<F, S, P, const N: usize> SensorGridSupportGenerator<F, S, P, N>
+impl<F, S, P, const N: usize> SensorGridSupportGenerator<S, F, P, N>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
#[inline]
fn construct_sensor(&self, id: usize, w: F) -> Weighted<ShiftedSensor<F, S, P, N>, F> {
@@ -397,12 +394,12 @@
}
}
-impl<F, S, P, const N: usize> SupportGenerator<F, N> for SensorGridSupportGenerator<F, S, P, N>
+impl<F, S, P, const N: usize> SupportGenerator<N, F> for SensorGridSupportGenerator<S, F, P, N>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
type Id = usize;
type SupportType = Weighted<ShiftedSensor<F, S, P, N>, F>;
@@ -434,14 +431,14 @@
}
}
-impl<F, S, P, BT, const N: usize> ForwardModel<DiscreteMeasure<Loc<F, N>, F>, F>
+impl<F, S, P, BT, const N: usize> ForwardModel<DiscreteMeasure<Loc<N, F>, F>, F>
for SensorGrid<F, S, P, BT, N>
where
F: Float + ToNalgebraRealField<MixedType = F> + nalgebra::RealField,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N> + LocalAnalysis<F, BT::Agg, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F> + LocalAnalysis<F, BT::Agg, N>,
{
type Observable = DVector<F>;
@@ -456,17 +453,17 @@
}
}
-impl<F, S, P, BT, const N: usize> FindimQuadraticModel<Loc<F, N>, F> for SensorGrid<F, S, P, BT, N>
+impl<F, S, P, BT, const N: usize> FindimQuadraticModel<Loc<N, F>, F> for SensorGrid<F, S, P, BT, N>
where
F: Float + ToNalgebraRealField<MixedType = F> + nalgebra::RealField,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N> + LocalAnalysis<F, BT::Agg, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F> + LocalAnalysis<F, BT::Agg, N>,
{
fn findim_quadratic_model(
&self,
- μ: &DiscreteMeasure<Loc<F, N>, F>,
+ μ: &DiscreteMeasure<Loc<N, F>, F>,
b: &Self::Observable,
) -> (DMatrix<F::MixedType>, DVector<F::MixedType>) {
assert_eq!(b.len(), self.n_sensors());
@@ -483,29 +480,29 @@
}
}
-/// Implements the calculation a factor $L$ such that $A_*A ≤ L 𝒟$ for $A$ the forward model
+/// Implements the calculation a factor $√L$ such that $A_*A ≤ L 𝒟$ for $A$ the forward model
/// and $𝒟$ a seminorm of suitable form.
///
/// **This assumes (but does not check) that the sensors are not overlapping.**
#[replace_float_literals(F::cast_from(literal))]
-impl<F, BT, S, P, K, const N: usize> AdjointProductBoundedBy<RNDM<F, N>, ConvolutionOp<F, K, BT, N>>
- for SensorGrid<F, S, P, BT, N>
+impl<'a, F, BT, S, P, K, const N: usize>
+ BoundedLinear<RNDM<N, F>, &'a ConvolutionOp<F, K, BT, N>, L2, F> for SensorGrid<F, S, P, BT, N>
where
- F: Float + nalgebra::RealField + ToNalgebraRealField,
+ F: Float + ToNalgebraRealField,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
- K: SimpleConvolutionKernel<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
+ K: SimpleConvolutionKernel<N, F>,
AutoConvolution<P>: BoundedBy<F, K>,
+ Weighted<Shift<K, N, F>, F>: LocalAnalysis<F, BT::Agg, N>,
{
- type FloatType = F;
-
- fn adjoint_product_bound(&self, seminorm: &ConvolutionOp<F, K, BT, N>) -> Option<F> {
+ fn opnorm_bound(&self, seminorm: &'a ConvolutionOp<F, K, BT, N>, _: L2) -> DynResult<F> {
// Sensors should not take on negative values to allow
// A_*A to be upper bounded by a simple convolution of `spread`.
+ // TODO: Do we really need this restriction?
if self.sensor.bounds().lower() < 0.0 {
- return None;
+ return Err(anyhow!("Sensor not bounded from below by zero"));
}
// Calculate the factor $L_1$ for betwee $ℱ[ψ * ψ] ≤ L_1 ℱ[ρ]$ for $ψ$ the base spread
@@ -517,33 +514,33 @@
let l0 = self.sensor.norm(Linfinity) * self.sensor.norm(L1);
// The final transition factor is:
- Some(l0 * l1)
+ Ok((l0 * l1).sqrt())
}
}
macro_rules! make_sensorgridsupportgenerator_scalarop_rhs {
($trait:ident, $fn:ident, $trait_assign:ident, $fn_assign:ident) => {
impl<F, S, P, const N: usize> std::ops::$trait_assign<F>
- for SensorGridSupportGenerator<F, S, P, N>
+ for SensorGridSupportGenerator<S, F, P, N>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
fn $fn_assign(&mut self, t: F) {
self.weights.$fn_assign(t);
}
}
- impl<F, S, P, const N: usize> std::ops::$trait<F> for SensorGridSupportGenerator<F, S, P, N>
+ impl<F, S, P, const N: usize> std::ops::$trait<F> for SensorGridSupportGenerator<S, F, P, N>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
- type Output = SensorGridSupportGenerator<F, S, P, N>;
+ type Output = SensorGridSupportGenerator<S, F, P, N>;
fn $fn(mut self, t: F) -> Self::Output {
std::ops::$trait_assign::$fn_assign(&mut self.weights, t);
self
@@ -551,14 +548,14 @@
}
impl<'a, F, S, P, const N: usize> std::ops::$trait<F>
- for &'a SensorGridSupportGenerator<F, S, P, N>
+ for &'a SensorGridSupportGenerator<S, F, P, N>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
- type Output = SensorGridSupportGenerator<F, S, P, N>;
+ type Output = SensorGridSupportGenerator<S, F, P, N>;
fn $fn(self, t: F) -> Self::Output {
SensorGridSupportGenerator {
base_sensor: self.base_sensor.clone(),
@@ -575,14 +572,14 @@
macro_rules! make_sensorgridsupportgenerator_unaryop {
($trait:ident, $fn:ident) => {
- impl<F, S, P, const N: usize> std::ops::$trait for SensorGridSupportGenerator<F, S, P, N>
+ impl<F, S, P, const N: usize> std::ops::$trait for SensorGridSupportGenerator<S, F, P, N>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
- type Output = SensorGridSupportGenerator<F, S, P, N>;
+ type Output = SensorGridSupportGenerator<S, F, P, N>;
fn $fn(mut self) -> Self::Output {
self.weights = self.weights.$fn();
self
@@ -590,14 +587,14 @@
}
impl<'a, F, S, P, const N: usize> std::ops::$trait
- for &'a SensorGridSupportGenerator<F, S, P, N>
+ for &'a SensorGridSupportGenerator<S, F, P, N>
where
F: Float,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F>,
{
- type Output = SensorGridSupportGenerator<F, S, P, N>;
+ type Output = SensorGridSupportGenerator<S, F, P, N>;
fn $fn(self) -> Self::Output {
SensorGridSupportGenerator {
base_sensor: self.base_sensor.clone(),
@@ -612,13 +609,13 @@
make_sensorgridsupportgenerator_unaryop!(Neg, neg);
impl<'a, F, S, P, BT, const N: usize> Mapping<DVector<F>>
- for PreadjointHelper<'a, SensorGrid<F, S, P, BT, N>, RNDM<F, N>>
+ for PreadjointHelper<'a, SensorGrid<F, S, P, BT, N>, RNDM<N, F>>
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N> + LocalAnalysis<F, Bounds<F>, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F> + LocalAnalysis<F, Bounds<F>, N>,
{
type Codomain = SensorGridBTFN<F, S, P, BT, N>;
@@ -634,12 +631,12 @@
}
impl<'a, F, S, P, BT, const N: usize> Linear<DVector<F>>
- for PreadjointHelper<'a, SensorGrid<F, S, P, BT, N>, RNDM<F, N>>
+ for PreadjointHelper<'a, SensorGrid<F, S, P, BT, N>, RNDM<N, F>>
where
F: Float,
BT: SensorGridBT<F, S, P, N>,
- S: Sensor<F, N>,
- P: Spread<F, N>,
- Convolution<S, P>: Spread<F, N> + LocalAnalysis<F, Bounds<F>, N>,
+ S: Sensor<N, F>,
+ P: Spread<N, F>,
+ Convolution<S, P>: Spread<N, F> + LocalAnalysis<F, Bounds<F>, N>,
{
}