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refactor(alert): move AHDC track-finding from AHDCEngine to ALERTEngine #1242

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refactor(alert): move AHDC track-finding from AHDCEngine to ALERTEngine #1242

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f948e24
refactor(alert): move AHDC track-finding from AHDCEngine to ALERTEngine
mathieuouillon May 4, 2026
abdc253
refactor(ahdc): unify track finders behind a TrackFinder strategy int…
mathieuouillon May 4, 2026
125f16c
test(ahdc): AHDCTest should test hits-only AHDCEngine
mathieuouillon May 4, 2026
b86b62e
feat(track-finding): add GNN track finder
mathieuouillon May 4, 2026
c55f394
fix(alert): unify DatabaseConstantProvider usage and improve track ma…
mathieuouillon May 11, 2026
a2424f5
refactor(alert): split Track into TrackCandidate (finder output) and …
mathieuouillon May 18, 2026
423a03b
refactor(alert): rename AHDC Cluster/ClusterFinder -> AHDCCluster/AHD…
mathieuouillon May 18, 2026
1a5cf0c
refactor(alert): rename enum ModeTrackFinding -> TrackFindingMode
mathieuouillon May 22, 2026
1210873
refactor(alert): rename MLP_Track_Finding/GNN_Track_Finding -> AI_MLP…
mathieuouillon May 22, 2026
47af4bf
docs(alert): document ALERTEngine YAML config, default Mode to AI_GNN
mathieuouillon May 22, 2026
f744c34
refactor(alert): pass ATOF hits to TrackFinder as List<AtofHitStub>, …
mathieuouillon May 22, 2026
e268719
refactor(alert): move ALERT-level track finding from rec.ahdc to rec.…
mathieuouillon May 22, 2026
1eade2c
docs(alert): update documentation for DJL usage in ModelTrackFindingGNN
mathieuouillon May 22, 2026
8693354
docs(alert): add source reference for SeedExtendTrackExtractor
mathieuouillon May 22, 2026
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41 changes: 35 additions & 6 deletions ...va/org/jlab/rec/ahdc/Cluster/Cluster.java → ...lab/rec/ahdc/AHDCCluster/AHDCCluster.java
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@whit2333 whit2333 May 14, 2026

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Since Cluster is an overloaded term. It would be a good idea to rename this class AHDCCluster. Or be explicit with interfaces using clusters

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@mathieuouillon mathieuouillon May 18, 2026

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76cfe77

Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
package org.jlab.rec.ahdc.Cluster;
package org.jlab.rec.ahdc.AHDCCluster;

import org.jlab.rec.ahdc.Hit.Hit;
import org.jlab.rec.ahdc.PreCluster.PreCluster;
Expand All @@ -9,9 +9,9 @@
import org.jlab.geom.prim.Point3D;

/**
* Cluster are compose by 2 PreCluster on layer with a different stereo angle
* AHDCCluster are compose by 2 PreCluster on layer with a different stereo angle
*/
public class Cluster {
public class AHDCCluster {

private int _trackId = -1;
private double _Radius;
Expand Down Expand Up @@ -50,7 +50,7 @@ private static double stereoTwistFromLine(Line3D line) {

return wrapPi(phi1 - phi0);
}
public Cluster(PreCluster precluster, PreCluster other_precluster) {
public AHDCCluster(PreCluster precluster, PreCluster other_precluster) {
this._PreClusters_list = new ArrayList<>();
_PreClusters_list.add(precluster);
_PreClusters_list.add(other_precluster);
Expand Down Expand Up @@ -80,15 +80,44 @@ public Cluster(PreCluster precluster, PreCluster other_precluster) {
this._V = this._Y / (this._X * this._X + this._Y * this._Y);
}

public Cluster(double X, double Y, double Z) {
public AHDCCluster(double X, double Y, double Z) {
this._X = X;
this._Y = Y;
this._Z = Z;
}

/** Build an AHDCCluster from a single PreCluster (one layer of a superlayer).
* Used by the GNN path when a track covers a superlayer on only one
* stereo layer — no stereo pair is available, so Z is taken from the
* average wire-midpoint z of the PreCluster's hits rather than from a
* stereo-angle computation. DocaClusterRefiner falls back to a degenerate
* DocaCluster when {@code get_PreClusters_list().size() != 2}, so
* downstream is unaffected. */
public AHDCCluster(PreCluster precluster) {
this._PreClusters_list = new ArrayList<>();
_PreClusters_list.add(precluster);
this._Radius = precluster.get_Radius();
this._Phi = precluster.get_Phi();
this._X = precluster.get_X();
this._Y = precluster.get_Y();
this._Num_wire = (int) precluster.get_Num_wire();
double r2 = this._X * this._X + this._Y * this._Y;
if (r2 > 0.0) {
this._U = this._X / r2;
this._V = this._Y / r2;
}
double zSum = 0.0;
int zCount = 0;
for (Hit h : precluster.get_hits_list()) {
Line3D line = h.getLine();
if (line != null) { zSum += line.midpoint().z(); zCount++; }
}
this._Z = (zCount > 0) ? zSum / zCount : 0.0;
}

@Override
public String toString() {
return "Cluster{" + "_X=" + _X + ", _Y=" + _Y + ", _Z=" + _Z + '}';
return "AHDCCluster{" + "_X=" + _X + ", _Y=" + _Y + ", _Z=" + _Z + '}';
}

public ArrayList<PreCluster> get_PreClusters_list() {
Expand Down
20 changes: 10 additions & 10 deletions .../jlab/rec/ahdc/Cluster/ClusterFinder.java → ...c/ahdc/AHDCCluster/AHDCClusterFinder.java
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Original file line number Diff line number Diff line change
@@ -1,21 +1,21 @@
package org.jlab.rec.ahdc.Cluster;
package org.jlab.rec.ahdc.AHDCCluster;

import org.jlab.rec.ahdc.PreCluster.PreCluster;

import java.util.ArrayList;
import java.util.List;

/** ClusterFinder
/** AHDCClusterFinder
*
* \todo description of what it does and how it works
*
*/
public class ClusterFinder {
public class AHDCClusterFinder {

private final ArrayList<Cluster> _AHDCClusters = new ArrayList<>();
private final ArrayList<Cluster> _list_with_maybe_same_cluster = new ArrayList<>();
private final ArrayList<AHDCCluster> _AHDCClusters = new ArrayList<>();
private final ArrayList<AHDCCluster> _list_with_maybe_same_cluster = new ArrayList<>();

public ClusterFinder() {}
public AHDCClusterFinder() {}

private void find_associate_cluster(PreCluster precluster, List<PreCluster> AHDC_precluster_list, int window, int minimal_distance, int super_layer, int layer, int associate_super_layer) {
//System.out.println(" precluster superlayer " + precluster.get_Super_layer() + " ref superlayer " + super_layer + " layer " + precluster.get_Layer() + " ref " + layer);
Expand Down Expand Up @@ -52,7 +52,7 @@ private void find_associate_cluster(PreCluster precluster, List<PreCluster> AHDC
if (best_precluster != null) {
precluster.set_Used(true);
best_precluster.set_Used(true);
Cluster new_Cluster = new Cluster(precluster, best_precluster);
AHDCCluster new_Cluster = new AHDCCluster(precluster, best_precluster);
_list_with_maybe_same_cluster.add(new_Cluster);
}
}
Expand Down Expand Up @@ -81,18 +81,18 @@ public void findCluster(List<PreCluster> AHDC_precluster_list) {
find_associate_cluster(precluster, AHDC_precluster_list, window, minimal_distance, 4, 2, 5);
}

for (Cluster cluster : _list_with_maybe_same_cluster) {
for (AHDCCluster cluster : _list_with_maybe_same_cluster) {
if (!containsCluster(_AHDCClusters, cluster.get_Phi(), cluster.get_Radius())) {
_AHDCClusters.add(cluster);
}
}
}

public boolean containsCluster(final List<Cluster> list, double phi, double radius) {
public boolean containsCluster(final List<AHDCCluster> list, double phi, double radius) {
return list.stream().anyMatch(o -> o.get_Radius() == (radius) && o.get_Phi() == phi);
}

public ArrayList<Cluster> get_AHDCClusters() {
public ArrayList<AHDCCluster> get_AHDCClusters() {
return _AHDCClusters;
}

Expand Down
10 changes: 5 additions & 5 deletions reconstruction/alert/src/main/java/org/jlab/rec/ahdc/Banks/RecoBankWriter.java
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Original file line number Diff line number Diff line change
Expand Up @@ -2,13 +2,13 @@

import org.jlab.io.base.DataBank;
import org.jlab.io.base.DataEvent;
import org.jlab.rec.ahdc.AI.InterCluster;
import org.jlab.rec.ahdc.AI.TrackPrediction;
import org.jlab.rec.ahdc.Cluster.Cluster;
import org.jlab.rec.alert.AI.InterCluster;
import org.jlab.rec.alert.AI.TrackPrediction;
import org.jlab.rec.ahdc.AHDCCluster.AHDCCluster;
import org.jlab.rec.ahdc.DocaCluster.DocaCluster;
import org.jlab.rec.ahdc.Hit.Hit;
import org.jlab.rec.ahdc.PreCluster.PreCluster;
import org.jlab.rec.ahdc.Track.Track;
import org.jlab.rec.alert.Track.Track;

import java.util.ArrayList;
import java.util.List;
Expand Down Expand Up @@ -50,7 +50,7 @@ public DataBank fillPreClustersBank(DataEvent event, ArrayList<PreCluster> preCl
return bank;
}

public DataBank fillClustersBank(DataEvent event, ArrayList<Cluster> clusters) {
public DataBank fillClustersBank(DataEvent event, ArrayList<AHDCCluster> clusters) {
if (clusters == null || clusters.size() == 0) return null;

DataBank bank = event.createBank("AHDC::clusters", clusters.size());
Expand Down
100 changes: 50 additions & 50 deletions reconstruction/alert/src/main/java/org/jlab/rec/ahdc/Distance/Distance.java
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
package org.jlab.rec.ahdc.Distance;

import org.jlab.rec.ahdc.Cluster.Cluster;
import org.jlab.rec.ahdc.Track.Track;
import org.jlab.rec.ahdc.AHDCCluster.AHDCCluster;
import org.jlab.rec.alert.Track.TrackCandidate;

import java.util.ArrayList;
import java.util.Arrays;
Expand All @@ -14,13 +14,13 @@
*/
public class Distance {

private ArrayList<Track> _AHDCTracks;
private ArrayList<TrackCandidate> _AHDCTrackCandidates;

public Distance(){
_AHDCTracks = new ArrayList<>();
_AHDCTrackCandidates = new ArrayList<>();
}

public void find_track(List<Cluster> AHDC_Cluster){
public void find_track(List<AHDCCluster> AHDC_Cluster){
find_track_4_clusters(AHDC_Cluster);
find_track_3_clusters(AHDC_Cluster);
}
Expand All @@ -41,14 +41,14 @@ public static <T> List<List<T>> computeCombinations2(List<List<T>> lists) {
return combinations;
}

private void find_track_4_clusters(List<Cluster> AHDC_Cluster){
List<Cluster> clusters_to_remove = new ArrayList<>();
List<Cluster> layer1 = new ArrayList<>(); // List of all cluster with a radius equal 35
List<Cluster> layer2 = new ArrayList<>(); // List of all cluster with a radius equal 45
List<Cluster> layer3 = new ArrayList<>(); // List of all cluster with a radius equal 55
List<Cluster> layer4 = new ArrayList<>(); // List of all cluster with a radius equal 65
private void find_track_4_clusters(List<AHDCCluster> AHDC_Cluster){
List<AHDCCluster> clusters_to_remove = new ArrayList<>();
List<AHDCCluster> layer1 = new ArrayList<>(); // List of all cluster with a radius equal 35
List<AHDCCluster> layer2 = new ArrayList<>(); // List of all cluster with a radius equal 45
List<AHDCCluster> layer3 = new ArrayList<>(); // List of all cluster with a radius equal 55
List<AHDCCluster> layer4 = new ArrayList<>(); // List of all cluster with a radius equal 65

for(Cluster cluster : AHDC_Cluster){
for(AHDCCluster cluster : AHDC_Cluster){
if(cluster.get_Radius() == 35){
layer1.add(cluster);
}
Expand All @@ -62,29 +62,29 @@ else if(cluster.get_Radius() == 65){
layer4.add(cluster);
}
}
List<List<Cluster>> merged_list = new ArrayList<>();
List<List<AHDCCluster>> merged_list = new ArrayList<>();
merged_list.add(layer1);
merged_list.add(layer2);
merged_list.add(layer3);
merged_list.add(layer4);
List<List<Cluster>> all_combinations = computeCombinations2(merged_list);
List<List<AHDCCluster>> all_combinations = computeCombinations2(merged_list);

List<Track> all_track = new ArrayList<>();
for(List<Cluster> combination : all_combinations){
all_track.add(new Track(combination));
List<TrackCandidate> all_track = new ArrayList<>();
for(List<AHDCCluster> combination : all_combinations){
all_track.add(new TrackCandidate(combination));
}

List<Track> tracks_possible = new ArrayList<>();
for(Track track : all_track){
List<TrackCandidate> tracks_possible = new ArrayList<>();
for(TrackCandidate track : all_track){
if(track.get_Distance() < 45){
tracks_possible.add(track);
}
}

double window = 3.8;
for(Track track : tracks_possible){
List<Track> tracks_with_close_starting_point = new ArrayList<>();
for(Track other_track : tracks_possible){
for(TrackCandidate track : tracks_possible){
List<TrackCandidate> tracks_with_close_starting_point = new ArrayList<>();
for(TrackCandidate other_track : tracks_possible){
if(other_track.get_Clusters().get(0).get_X() > track.get_Clusters().get(0).get_X() - window
&& other_track.get_Clusters().get(0).get_X() < track.get_Clusters().get(0).get_X() + window
&& other_track.get_Clusters().get(0).get_Y() > track.get_Clusters().get(0).get_Y() - window
Expand All @@ -97,12 +97,12 @@ else if(cluster.get_Radius() == 65){

if(tracks_with_close_starting_point.size() > 0){
double chisq_min = Double.MAX_VALUE;
Track best_track = null;
for(Track other_track : tracks_with_close_starting_point){
TrackCandidate best_track = null;
for(TrackCandidate other_track : tracks_with_close_starting_point){
ArrayList<Double> x_ = new ArrayList<>();
ArrayList<Double> y_ = new ArrayList<>();
ArrayList<Double> w_ = new ArrayList<>(); // weight for circlefit
for(Cluster cluster : other_track.get_Clusters()){
for(AHDCCluster cluster : other_track.get_Clusters()){
x_.add(cluster.get_X());
y_.add(cluster.get_Y());
w_.add(1.);
Expand All @@ -119,32 +119,32 @@ else if(cluster.get_Radius() == 65){
}
if (best_track != null ){
clusters_to_remove.addAll(best_track.get_Clusters());
_AHDCTracks.add(best_track);
_AHDCTrackCandidates.add(best_track);
}
}
}

List<Cluster> clusters_to_remove_without_double = new ArrayList<>();
for(Cluster cluster : clusters_to_remove){
List<AHDCCluster> clusters_to_remove_without_double = new ArrayList<>();
for(AHDCCluster cluster : clusters_to_remove){
if(!containsCluster(clusters_to_remove_without_double, cluster.get_Phi(), cluster.get_Radius())){
clusters_to_remove_without_double.add(cluster);
}
}

for(Cluster cluster : clusters_to_remove_without_double){
for(AHDCCluster cluster : clusters_to_remove_without_double){
AHDC_Cluster.remove(cluster);
}
}

public boolean containsCluster(final List<Cluster> list, double phi, double radius){
public boolean containsCluster(final List<AHDCCluster> list, double phi, double radius){
return list.stream().anyMatch(o -> o.get_Radius() == (radius) && o.get_Phi() == phi);
}


private ArrayList<ArrayList<Cluster>> combination(List<Cluster> arr, ArrayList<Cluster> data, int start,
private ArrayList<ArrayList<AHDCCluster>> combination(List<AHDCCluster> arr, ArrayList<AHDCCluster> data, int start,
int end, int index, int r) {

ArrayList<ArrayList<Cluster>> all = new ArrayList<>();
ArrayList<ArrayList<AHDCCluster>> all = new ArrayList<>();
if (index == r) {
all.add(data);
}
Expand All @@ -157,25 +157,25 @@ private ArrayList<ArrayList<Cluster>> combination(List<Cluster> arr, ArrayList<C
return all;
}

private void find_track_3_clusters(List<Cluster> AHDC_Cluster){
ArrayList<ArrayList<Cluster>> all_combinations = combination(AHDC_Cluster, new ArrayList<Cluster>(),0, AHDC_Cluster.size()-1, 0, 3);
private void find_track_3_clusters(List<AHDCCluster> AHDC_Cluster){
ArrayList<ArrayList<AHDCCluster>> all_combinations = combination(AHDC_Cluster, new ArrayList<AHDCCluster>(),0, AHDC_Cluster.size()-1, 0, 3);

List<Track> all_track = new ArrayList<>();
for(List<Cluster> combination : all_combinations){
all_track.add(new Track(combination));
List<TrackCandidate> all_track = new ArrayList<>();
for(List<AHDCCluster> combination : all_combinations){
all_track.add(new TrackCandidate(combination));
}

List<Track> tracks_possible = new ArrayList<>();
for(Track track : all_track){
List<TrackCandidate> tracks_possible = new ArrayList<>();
for(TrackCandidate track : all_track){
if(track.get_Distance() < 45){
tracks_possible.add(track);
}
}

double window = 3.8;
for(Track track : tracks_possible) {
List<Track> tracks_with_close_starting_point = new ArrayList<>();
for (Track other_track : tracks_possible) {
for(TrackCandidate track : tracks_possible) {
List<TrackCandidate> tracks_with_close_starting_point = new ArrayList<>();
for (TrackCandidate other_track : tracks_possible) {
if (other_track.get_Clusters().get(0).get_X() > track.get_Clusters().get(0).get_X() - window
&& other_track.get_Clusters().get(0).get_X() < track.get_Clusters().get(0).get_X() + window
&& other_track.get_Clusters().get(0).get_Y() > track.get_Clusters().get(0).get_Y() - window
Expand All @@ -188,12 +188,12 @@ private void find_track_3_clusters(List<Cluster> AHDC_Cluster){

if(tracks_with_close_starting_point.size() > 0){
double chisq_min = Double.MAX_VALUE;
Track best_track = null;
for(Track other_track : tracks_with_close_starting_point){
TrackCandidate best_track = null;
for(TrackCandidate other_track : tracks_with_close_starting_point){
ArrayList<Double> x_ = new ArrayList<>();
ArrayList<Double> y_ = new ArrayList<>();
ArrayList<Double> w_ = new ArrayList<>(); // weight for circlefit
for(Cluster cluster : other_track.get_Clusters()){
for(AHDCCluster cluster : other_track.get_Clusters()){
x_.add(cluster.get_X());
y_.add(cluster.get_Y());
w_.add(1.);
Expand All @@ -209,17 +209,17 @@ private void find_track_3_clusters(List<Cluster> AHDC_Cluster){
}
}
if (best_track != null ){
_AHDCTracks.add(best_track);
_AHDCTrackCandidates.add(best_track);
}
}
}
}

public ArrayList<Track> get_AHDCTracks() {
return _AHDCTracks;
public ArrayList<TrackCandidate> get_AHDCTrackCandidates() {
return _AHDCTrackCandidates;
}

public void set_AHDCTracks(ArrayList<Track> _AHDCTracks) {
this._AHDCTracks = _AHDCTracks;
public void set_AHDCTrackCandidates(ArrayList<TrackCandidate> _AHDCTrackCandidates) {
this._AHDCTrackCandidates = _AHDCTrackCandidates;
}
}
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