pointsource_algs: comparison src/measures/merging.rs

--1:000000000000
+:eb3c7813b67a
+/*!
+Spike merging heuristics for [`DiscreteMeasure`]s.
+This module primarily provides the [`SpikeMerging`] trait, and within it,
+the [`SpikeMerging::merge_spikes`] method. The trait is implemented on
+[`DiscreteMeasure<Loc<F, N>, F>`]s in dimensions `N=1` and `N=2`.
+*/
+use numeric_literals::replace_float_literals;
+use std::cmp::Ordering;
+use serde::{Serialize, Deserialize};
+//use clap::builder::{PossibleValuesParser, PossibleValue};
+use alg_tools::nanleast::NaNLeast;
+use crate::types::*;
+use super::delta::*;
+use super::discrete::*;
+/// Spike merging heuristic selection
+#[derive(Clone, Copy, Eq, PartialEq, Serialize, Deserialize, Debug)]
+#[allow(dead_code)]
+pub enum SpikeMergingMethod<F> {
+/// Try to merge spikes within a given radius of eachother
+HeuristicRadius(F),
+/// No merging
+None,
+}
+// impl<F : Float> SpikeMergingMethod<F> {
+//     /// This is for [`clap`] to display command line help.
+//     pub fn value_parser() -> PossibleValuesParser {
+//         PossibleValuesParser::new([
+//             PossibleValue::new("none").help("No merging"),
+//             PossibleValue::new("<radius>").help("Heuristic merging within indicated radius")
+//         ])
+//     }
+// }
+impl<F : ClapFloat> std::fmt::Display for SpikeMergingMethod<F> {
+fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> Result<(), std::fmt::Error> {
+match self {
+Self::None => write!(f, "none"),
+Self::HeuristicRadius(r) => std::fmt::Display::fmt(r, f),
+}
+}
+}
+impl<F : ClapFloat> std::str::FromStr for SpikeMergingMethod<F> {
+type Err = F::Err;
+fn from_str(s: &str) -> Result<Self, Self::Err> {
+if s == "none" {
+Ok(Self::None)
+} else {
+Ok(Self::HeuristicRadius(F::from_str(s)?))
+}
+}
+}
+#[replace_float_literals(F::cast_from(literal))]
+impl<F : Float> Default for SpikeMergingMethod<F> {
+fn default() -> Self {
+SpikeMergingMethod::HeuristicRadius(0.02)
+}
+}
+/// Trait for dimension-dependent implementation of heuristic peak merging strategies.
+pub trait SpikeMerging<F> {
+/// Attempt spike merging according to [`SpikeMerging`] method.
+///
+/// Returns the last [`Some`] returned by the merging candidate acceptance decision closure
+/// `accept` if any merging is performed. The closure should accept as its only parameter a
+/// new candidate measure (it will generally be internally mutated `self`, although this is
+/// not guaranteed), and return [`None`] if the merge is accepted, and otherwise a [`Some`] of
+/// an arbitrary value. This method will return that value for the *last* accepted merge, or
+/// [`None`] if no merge was accepted.
+///
+/// This method is stable with respect to spike locations:  on merge, the weight of existing
+/// spikes is set to zero, and a new one inserted at the end of the spike vector.
+fn merge_spikes<G, V>(&mut self, method : SpikeMergingMethod<F>, accept : G) -> Option<V>
+where G : Fn(&'_ Self) -> Option<V> {
+match method {
+SpikeMergingMethod::HeuristicRadius(ρ) => self.do_merge_spikes_radius(ρ, accept),
+SpikeMergingMethod::None => None,
+}
+}
+/// Attempt to merge spikes based on a value and a fitness function.
+///
+/// Calls [`SpikeMerging::merge_spikes`] with `accept` constructed from the composition of
+/// `value` and `fitness`, compared to initial fitness. Returns the last return value of `value`
+// for a merge  accepted by `fitness`. If no merge was accepted, `value` applied to the initial
+/// `self` is returned.
+fn merge_spikes_fitness<G, H, V, O>(
+&mut self,
+method : SpikeMergingMethod<F>,
+value : G,
+fitness : H
+) -> V
+where G : Fn(&'_ Self) -> V,
+H : Fn(&'_ V) -> O,
+O : PartialOrd {
+let initial_res = value(self);
+let initial_fitness = fitness(&initial_res);
+self.merge_spikes(method, |μ| {
+let res = value(μ);
+(fitness(&res) <= initial_fitness).then_some(res)
+}).unwrap_or(initial_res)
+}
+/// Attempt to merge spikes that are within radius $ρ$ of each other (unspecified norm).
+///
+/// This method implements [`SpikeMerging::merge_spikes`] for
+/// [`SpikeMergingMethod::HeuristicRadius`]. The closure `accept` and the return value are
+/// as for that method.
+fn do_merge_spikes_radius<G, V>(&mut self, ρ : F, accept : G) -> Option<V>
+where G : Fn(&'_ Self) -> Option<V>;
+}
+#[replace_float_literals(F::cast_from(literal))]
+impl<F : Float, const N : usize>  DiscreteMeasure<Loc<F, N>, F> {
+/// Attempts to merge spikes with indices `i` and `j`.
+///
+/// This assumes that the weights of the two spikes have already been checked not to be zero.
+///
+/// The parameter `res` points to the current “result” for [`SpikeMerging::merge_spikes`].
+/// If the merge is accepted by `accept` returning a [`Some`], `res` will be replaced by its
+/// return value.
+fn attempt_merge<G, V>(
+&mut self,
+res : &mut Option<V>,
+i : usize,
+j : usize,
+accept : &G
+) -> bool
+where G : Fn(&'_ Self) -> Option<V> {
+let &DeltaMeasure{ x : xi, α : αi } = &self.spikes[i];
+let &DeltaMeasure{ x : xj, α : αj } = &self.spikes[j];
+// Merge inplace
+self.spikes[i].α = 0.0;
+self.spikes[j].α = 0.0;
+//self.spikes.push(DeltaMeasure{ α : αi + αj, x : (xi + xj)/2.0 });
+self.spikes.push(DeltaMeasure{ α : αi + αj, x : (xi * αi + xj * αj) / (αi + αj) });
+match accept(self) {
+some@Some(..) => {
+// Merge accepted, update our return value
+*res = some;
+// On next iteration process the newly merged spike.
+//indices[k+1] = self.spikes.len() - 1;
+true
+},
+None => {
+// Merge not accepted, restore modification
+self.spikes[i].α = αi;
+self.spikes[j].α = αj;
+self.spikes.pop();
+false
+}
+}
+}
+/*
+/// Attempts to merge spikes with indices i and j, acceptance through a delta.
+fn attempt_merge_change<G, V>(
+&mut self,
+res : &mut Option<V>,
+i : usize,
+j : usize,
+accept_change : &G
+) -> bool
+where G : Fn(&'_ Self) -> Option<V> {
+let &DeltaMeasure{ x : xi, α : αi } = &self.spikes[i];
+let &DeltaMeasure{ x : xj, α : αj } = &self.spikes[j];
+let δ = DeltaMeasure{ α : αi + αj, x : (xi + xj)/2.0 };
+let λ = [-self.spikes[i], -self.spikes[j], δ.clone()].into();
+match accept_change(&λ) {
+some@Some(..) => {
+// Merge accepted, update our return value
+*res = some;
+self.spikes[i].α = 0.0;
+self.spikes[j].α = 0.0;
+self.spikes.push(δ);
+true
+},
+None => {
+false
+}
+}
+}*/
+}
+/// Sorts a vector of indices into `slice` by `compare`.
+///
+/// The closure `compare` operators on references to elements of `slice`.
+/// Returns the sorted vector of indices into `slice`.
+pub fn sort_indices_by<V, F>(slice : &[V], mut compare : F) -> Vec<usize>
+where F : FnMut(&V, &V) -> Ordering
+{
+let mut indices = Vec::from_iter(0..slice.len());
+indices.sort_by(|&i, &j| compare(&slice[i], &slice[j]));
+indices
+}
+#[replace_float_literals(F::cast_from(literal))]
+impl<F : Float> SpikeMerging<F> for DiscreteMeasure<Loc<F, 1>, F> {
+fn do_merge_spikes_radius<G, V>(
+&mut self,
+ρ : F,
+accept : G
+) -> Option<V>
+where G : Fn(&'_ Self) -> Option<V> {
+// Sort by coordinate into an indexing array.
+let mut indices = sort_indices_by(&self.spikes, |&δ1, &δ2| {
+let &Loc([x1]) = &δ1.x;
+let &Loc([x2]) = &δ2.x;
+// nan-ignoring ordering of floats
+NaNLeast(x1).cmp(&NaNLeast(x2))
+});
+// Initialise result
+let mut res = None;
+// Scan consecutive pairs and merge if close enough and accepted by `accept`.
+if indices.len() == 0 {
+return res
+}
+for k in 0..(indices.len()-1) {
+let i = indices[k];
+let j = indices[k+1];
+let &DeltaMeasure{ x : Loc([xi]), α : αi } = &self.spikes[i];
+let &DeltaMeasure{ x : Loc([xj]), α : αj } = &self.spikes[j];
+debug_assert!(xi <= xj);
+// If close enough, attempt merging
+if αi != 0.0 && αj != 0.0 && xj <= xi + ρ {
+if self.attempt_merge(&mut res, i, j, &accept) {
+indices[k+1] = self.spikes.len() - 1;
+}
+}
+}
+res
+}
+}
+/// Orders `δ1` and `δ1` according to the first coordinate.
+fn compare_first_coordinate<F : Float>(
+δ1 : &DeltaMeasure<Loc<F, 2>, F>,
+δ2 : &DeltaMeasure<Loc<F, 2>, F>
+) -> Ordering {
+let &Loc([x11, ..]) = &δ1.x;
+let &Loc([x21, ..]) = &δ2.x;
+// nan-ignoring ordering of floats
+NaNLeast(x11).cmp(&NaNLeast(x21))
+}
+#[replace_float_literals(F::cast_from(literal))]
+impl<F : Float> SpikeMerging<F> for DiscreteMeasure<Loc<F, 2>, F> {
+fn do_merge_spikes_radius<G, V>(&mut self, ρ : F, accept : G) -> Option<V>
+where G : Fn(&'_ Self) -> Option<V> {
+// Sort by first coordinate into an indexing array.
+let mut indices = sort_indices_by(&self.spikes, compare_first_coordinate);
+// Initialise result
+let mut res = None;
+let mut start_scan_2nd = 0;
+// Scan in order
+if indices.len() == 0 {
+return res
+}
+for k in 0..indices.len()-1 {
+let i = indices[k];
+let &DeltaMeasure{ x : Loc([xi1, xi2]), α : αi } = &self[i];
+if αi == 0.0 {
+// Nothin to be done if the weight is already zero
+continue
+}
+let mut closest = None;
+// Scan for second spike. We start from `start_scan_2nd + 1` with `start_scan_2nd`
+// the smallest invalid merging index on the previous loop iteration, because a
+// the _closest_ mergeable spike might have index less than `k` in `indices`, and a
+// merge with it might have not been attempted with this spike if a different closer
+// spike was discovered based on the second coordinate.
+'scan_2nd: for l in (start_scan_2nd+1)..indices.len() {
+if l == k {
+// Do not attempt to merge a spike with itself
+continue
+}
+let j = indices[l];
+let &DeltaMeasure{ x : Loc([xj1, xj2]), α : αj } = &self[j];
+if xj1 < xi1 - ρ {
+// Spike `j = indices[l]` has too low first coordinate. Update starting index
+// for next iteration, and continue scanning.
+start_scan_2nd = l;
+continue 'scan_2nd
+} else if xj1 > xi1 + ρ {
+// Break out: spike `j = indices[l]` has already too high first coordinate, no
+// more close enough spikes can be found due to the sorting of `indices`.
+break 'scan_2nd
+}
+// If also second coordinate is close enough, attempt merging if closer than
+// previously discovered mergeable spikes.
+let d2 = (xi2-xj2).abs();
+if αj != 0.0 && d2 <= ρ {
+let r1 = xi1-xj1;
+let d = (d2*d2 + r1*r1).sqrt();
+match closest {
+None => closest = Some((l, j, d)),
+Some((_, _, r)) if r > d => closest = Some((l, j, d)),
+_ => {},
+}
+}
+}
+// Attempt merging closest close-enough spike
+if let Some((l, j, _)) = closest {
+if self.attempt_merge(&mut res, i, j, &accept) {
+// If merge was succesfull, make new spike candidate for merging.
+indices[l] = self.spikes.len() - 1;
+let compare = |i, j| compare_first_coordinate(&self.spikes[i],
+&self.spikes[j]);
+// Re-sort relevant range of indices
+if l < k {
+indices[l..k].sort_by(|&i, &j| compare(i, j));
+} else {
+indices[k+1..=l].sort_by(|&i, &j| compare(i, j));
+}
+}
+}
+}
+res
+}
+}

Mercurial > repos > pointsource_algs / file comparison

comparison: src/measures/merging.rs

src/measures/merging.rs