--- a/src/experiments.rs Sun Dec 11 23:19:17 2022 +0200
+++ b/src/experiments.rs Sun Dec 11 23:25:53 2022 +0200
@@ -20,13 +20,14 @@
use crate::types::*;
use crate::run::{
RunnableExperiment,
- Experiment,
+ ExperimentV2,
Named,
DefaultAlgorithm,
AlgorithmConfig
};
//use crate::fb::FBGenericConfig;
use crate::rand_distr::{SerializableNormal, SaltAndPepper};
+use crate::regularisation::Regularisation;
/// Experiments shorthands, to be used with the command line parser
@@ -136,10 +137,10 @@
Experiment1D => {
let base_spread = Gaussian { variance : Variance1 };
let spread_cutoff = BallIndicator { r : CutOff1, exponent : Linfinity };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]].into(),
sensor_count : [N_SENSORS_1D],
- α : cli.alpha.unwrap_or(0.09),
+ regularisation : Regularisation::Radon(cli.alpha.unwrap_or(0.09)),
noise_distr : SerializableNormal::new(0.0, cli.variance.unwrap_or(0.2))?,
dataterm : DataTerm::L2Squared,
μ_hat : MU_TRUE_1D_BASIC.into(),
@@ -153,10 +154,10 @@
},
Experiment1DFast => {
let base_spread = HatConv { radius : Hat1 };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]].into(),
sensor_count : [N_SENSORS_1D],
- α : cli.alpha.unwrap_or(0.06),
+ regularisation : Regularisation::Radon(cli.alpha.unwrap_or(0.06)),
noise_distr : SerializableNormal::new(0.0, cli.variance.unwrap_or(0.2))?,
dataterm : DataTerm::L2Squared,
μ_hat : MU_TRUE_1D_BASIC.into(),
@@ -171,10 +172,10 @@
Experiment2D => {
let base_spread = Gaussian { variance : Variance1 };
let spread_cutoff = BallIndicator { r : CutOff1, exponent : Linfinity };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]; 2].into(),
sensor_count : [N_SENSORS_2D; 2],
- α : cli.alpha.unwrap_or(0.19), // 0.18, //0.17, //0.16,
+ regularisation : Regularisation::Radon(cli.alpha.unwrap_or(0.19)),
noise_distr : SerializableNormal::new(0.0, cli.variance.unwrap_or(0.25))?,
dataterm : DataTerm::L2Squared,
μ_hat : MU_TRUE_2D_BASIC.into(),
@@ -190,10 +191,10 @@
},
Experiment2DFast => {
let base_spread = HatConv { radius : Hat1 };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]; 2].into(),
sensor_count : [N_SENSORS_2D; 2],
- α : cli.alpha.unwrap_or(0.12), //0.10, //0.14,
+ regularisation : Regularisation::Radon(cli.alpha.unwrap_or(0.12)),
noise_distr : SerializableNormal::new(0.0, cli.variance.unwrap_or(0.15))?, //0.25
dataterm : DataTerm::L2Squared,
μ_hat : MU_TRUE_2D_BASIC.into(),
@@ -210,10 +211,10 @@
Experiment1D_L1 => {
let base_spread = Gaussian { variance : Variance1 };
let spread_cutoff = BallIndicator { r : CutOff1, exponent : Linfinity };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]].into(),
sensor_count : [N_SENSORS_1D],
- α : cli.alpha.unwrap_or(0.1),
+ regularisation : Regularisation::NonnegRadon(cli.alpha.unwrap_or(0.1)),
noise_distr : SaltAndPepper::new(
cli.salt_and_pepper.as_ref().map_or(0.6, |v| v[0]),
cli.salt_and_pepper.as_ref().map_or(0.4, |v| v[1])
@@ -230,10 +231,10 @@
},
Experiment1D_L1_Fast => {
let base_spread = HatConv { radius : Hat1 };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]].into(),
sensor_count : [N_SENSORS_1D],
- α : cli.alpha.unwrap_or(0.12),
+ regularisation : Regularisation::NonnegRadon(cli.alpha.unwrap_or(0.12)),
noise_distr : SaltAndPepper::new(
cli.salt_and_pepper.as_ref().map_or(0.6, |v| v[0]),
cli.salt_and_pepper.as_ref().map_or(0.4, |v| v[1])
@@ -251,10 +252,10 @@
Experiment2D_L1 => {
let base_spread = Gaussian { variance : Variance1 };
let spread_cutoff = BallIndicator { r : CutOff1, exponent : Linfinity };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]; 2].into(),
sensor_count : [N_SENSORS_2D; 2],
- α : cli.alpha.unwrap_or(0.35),
+ regularisation : Regularisation::NonnegRadon(cli.alpha.unwrap_or(0.35)),
noise_distr : SaltAndPepper::new(
cli.salt_and_pepper.as_ref().map_or(0.8, |v| v[0]),
cli.salt_and_pepper.as_ref().map_or(0.2, |v| v[1])
@@ -273,10 +274,10 @@
},
Experiment2D_L1_Fast => {
let base_spread = HatConv { radius : Hat1 };
- Box::new(Named { name, data : Experiment {
+ Box::new(Named { name, data : ExperimentV2 {
domain : [[0.0, 1.0]; 2].into(),
sensor_count : [N_SENSORS_2D; 2],
- α : cli.alpha.unwrap_or(0.40),
+ regularisation : Regularisation::NonnegRadon(cli.alpha.unwrap_or(0.40)),
noise_distr : SaltAndPepper::new(
cli.salt_and_pepper.as_ref().map_or(0.8, |v| v[0]),
cli.salt_and_pepper.as_ref().map_or(0.2, |v| v[1])