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6 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| ab8d98ed81 | |||
| 3d9890e16a | |||
| dd64ac2731 | |||
| a5238624f1 | |||
| d8ba42b801 | |||
| 8edd89d784 |
27
readme.md
27
readme.md
@@ -29,17 +29,13 @@ Unfortunately, it's a fairly new algorithm, and not yet implemented by the graph
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So this program instead uses the Fibonacci heap-based algorithm of Fredman and Tarjan (1987), which has a worst-case
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So this program instead uses the Fibonacci heap-based algorithm of Fredman and Tarjan (1987), which has a worst-case
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runtime of **O(n (n log(n) + m))**. The algorithm is implemented as described in Melhorn and Näher (1999).
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runtime of **O(n (n log(n) + m))**. The algorithm is implemented as described in Melhorn and Näher (1999).
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The current version of the program uses a pairing heap instead of a Fibonacci heap for its priority queue,
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which has lower theoretical efficiency but also lower complexity overhead, and is often equivalently performant
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in practice.
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## USAGE
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## USAGE
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### RUNNING THE PROGRAM
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### RUNNING THE PROGRAM
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[Download the current version of BiGpairSEQ_Sim.](https://gitea.ejsf.synology.me/efischer/BiGpairSEQ/releases)
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[Download the current version of BiGpairSEQ_Sim.](https://gitea.ejsf.synology.me/efischer/BiGpairSEQ/releases)
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BiGpairSEQ_Sim is an executable .jar file. Requires Java 11 or higher. [OpenJDK 17](https://jdk.java.net/17/)
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BiGpairSEQ_Sim is an executable .jar file. Requires Java 14 or higher. [OpenJDK 17](https://jdk.java.net/17/)
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recommended.
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recommended.
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Run with the command:
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Run with the command:
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@@ -82,16 +78,17 @@ These files are often generated in sequence. When entering filenames, it is not
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(.csv or .ser). When reading or writing files, the program will automatically add the correct extension to any filename without one.
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(.csv or .ser). When reading or writing files, the program will automatically add the correct extension to any filename without one.
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To save file I/O time, the most recent instance of each of these four
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To save file I/O time, the most recent instance of each of these four
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files either generated or read from disk can be cached in program memory. This is especially important for Graph/Data files,
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files either generated or read from disk can be cached in program memory. This is could be important for Graph/Data files,
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which can be several gigabytes in size. Since some simulations may require running multiple,
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which can be several gigabytes in size. Since some simulations may require running multiple,
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differently-configured BiGpairSEQ matchings on the same graph, keeping the most recent graph cached can reduce execution time
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differently-configured BiGpairSEQ matchings on the same graph, keeping the most recent graph cached may reduce execution time.
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(The manipulation necessary to re-use a graph incurs its own performance overhead, though, which may scale with graph
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size faster than file I/O does. If so, caching is best for smaller graphs.)
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Subsequent uses of the same data file won't need to be read in again until another file of that type is used or generated,
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When caching is active, subsequent uses of the same data file won't need to be read in again until another file of that type is used or generated,
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or caching is turned off for that file type. The program checks whether it needs to update its cached data by comparing
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or caching is turned off for that file type. The program checks whether it needs to update its cached data by comparing
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filenames as entered by the user. On encountering a new filename, the program flushes its cache and reads in the new file.
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filenames as entered by the user. On encountering a new filename, the program flushes its cache and reads in the new file.
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The program's caching behavior can be controlled in the Options menu. By default, caching for cell sample and
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The program's caching behavior can be controlled in the Options menu. By default, all caching is OFF.
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sample plate files is OFF, and caching for graph/data files is ON.
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#### Cell Sample Files
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#### Cell Sample Files
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Cell Sample files consist of any number of distinct "T cells." Every cell contains
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Cell Sample files consist of any number of distinct "T cells." Every cell contains
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@@ -256,7 +253,8 @@ slightly less time than the simulation itself. Real elapsed time from start to f
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* ~~Try invoking GC at end of workloads to reduce paging to disk~~ DONE
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* ~~Try invoking GC at end of workloads to reduce paging to disk~~ DONE
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* Hold graph data in memory until another graph is read-in? ~~ABANDONED~~ ~~UNABANDONED~~ DONE
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* Hold graph data in memory until another graph is read-in? ~~ABANDONED~~ ~~UNABANDONED~~ DONE
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* ~~*No, this won't work, because BiGpairSEQ simulations alter the underlying graph based on filtering constraints. Changes would cascade with multiple experiments.*~~
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* ~~*No, this won't work, because BiGpairSEQ simulations alter the underlying graph based on filtering constraints. Changes would cascade with multiple experiments.*~~
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* Might have figured out a way to do it, by taking edges out and then putting them back into the graph. This may actually be possible. If so, awesome.
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* Might have figured out a way to do it, by taking edges out and then putting them back into the graph. This may actually be possible.
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* It is possible, though the modifications to the graph incur their own performance penalties. Need testing to see which option is best.
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* See if there's a reasonable way to reformat Sample Plate files so that wells are columns instead of rows.
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* See if there's a reasonable way to reformat Sample Plate files so that wells are columns instead of rows.
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* ~~Problem is variable number of cells in a well~~
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* ~~Problem is variable number of cells in a well~~
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* ~~Apache Commons CSV library writes entries a row at a time~~
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* ~~Apache Commons CSV library writes entries a row at a time~~
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@@ -270,9 +268,10 @@ slightly less time than the simulation itself. Real elapsed time from start to f
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* Re-implement CDR1 matching method
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* Re-implement CDR1 matching method
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* Implement Duan and Su's maximum weight matching algorithm
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* Implement Duan and Su's maximum weight matching algorithm
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* Add controllable algorithm-type parameter?
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* Add controllable algorithm-type parameter?
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* Test whether pairing heap (currently used) or Fibonacci heap is more efficient for priority queue in current matching algorithm
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* ~~Test whether pairing heap (currently used) or Fibonacci heap is more efficient for priority queue in current matching algorithm~~ DONE
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* in theory Fibonacci heap should be more efficient, but complexity overhead may eliminate theoretical advantage
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* ~~in theory Fibonacci heap should be more efficient, but complexity overhead may eliminate theoretical advantage~~
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* Add controllable heap-type parameter?
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* ~~Add controllable heap-type parameter?~~
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* Parameter implemented. For large graphs, Fibonacci heap wins. Now the new default.
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@@ -12,7 +12,8 @@ public class BiGpairSEQ {
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private static String graphFilename = null;
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private static String graphFilename = null;
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private static boolean cacheCells = false;
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private static boolean cacheCells = false;
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private static boolean cachePlate = false;
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private static boolean cachePlate = false;
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private static boolean cacheGraph = true;
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private static boolean cacheGraph = false;
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private static String priorityQueueHeapType = "FIBONACCI";
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public static void main(String[] args) {
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public static void main(String[] args) {
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if (args.length == 0) {
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if (args.length == 0) {
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@@ -151,4 +152,16 @@ public class BiGpairSEQ {
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}
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}
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BiGpairSEQ.cacheGraph = cacheGraph;
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BiGpairSEQ.cacheGraph = cacheGraph;
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}
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}
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public static String getPriorityQueueHeapType() {
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return priorityQueueHeapType;
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}
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public static void setPairingHeap() {
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priorityQueueHeapType = "PAIRING";
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}
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public static void setFibonacciHeap() {
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priorityQueueHeapType = "FIBONACCI";
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}
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}
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}
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@@ -6,59 +6,74 @@ import java.util.List;
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import java.util.Map;
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import java.util.Map;
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import java.util.Set;
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import java.util.Set;
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public abstract class GraphModificationFunctions {
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public interface GraphModificationFunctions {
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//remove over- and under-weight edges
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//remove over- and under-weight edges
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public static List<Integer[]> filterByOverlapThresholds(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
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static List<Integer[]> filterByOverlapThresholds(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
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int low, int high) {
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int low, int high, boolean saveEdges) {
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List<Integer[]> removedEdges = new ArrayList<>();
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List<Integer[]> removedEdges = new ArrayList<>();
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for(DefaultWeightedEdge e: graph.edgeSet()){
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for (DefaultWeightedEdge e : graph.edgeSet()) {
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if ((graph.getEdgeWeight(e) > high) || (graph.getEdgeWeight(e) < low)){
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if ((graph.getEdgeWeight(e) > high) || (graph.getEdgeWeight(e) < low)) {
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Integer source = graph.getEdgeSource(e);
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if(saveEdges) {
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Integer target = graph.getEdgeTarget(e);
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Integer source = graph.getEdgeSource(e);
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Integer weight = (int) graph.getEdgeWeight(e);
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Integer target = graph.getEdgeTarget(e);
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Integer[] edge = {source, target, weight};
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Integer weight = (int) graph.getEdgeWeight(e);
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removedEdges.add(edge);
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Integer[] edge = {source, target, weight};
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removedEdges.add(edge);
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}
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else {
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graph.setEdgeWeight(e, 0.0);
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}
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}
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}
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}
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}
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for (Integer[] edge : removedEdges) {
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if(saveEdges) {
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graph.removeEdge(edge[0], edge[1]);
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for (Integer[] edge : removedEdges) {
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graph.removeEdge(edge[0], edge[1]);
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}
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}
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}
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return removedEdges;
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return removedEdges;
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}
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}
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//Remove edges for pairs with large occupancy discrepancy
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//Remove edges for pairs with large occupancy discrepancy
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public static List<Integer[]> filterByRelativeOccupancy(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
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static List<Integer[]> filterByRelativeOccupancy(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
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Map<Integer, Integer> alphaWellCounts,
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Map<Integer, Integer> alphaWellCounts,
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Map<Integer, Integer> betaWellCounts,
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Map<Integer, Integer> betaWellCounts,
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Map<Integer, Integer> plateVtoAMap,
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Map<Integer, Integer> plateVtoAMap,
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Map<Integer, Integer> plateVtoBMap,
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Map<Integer, Integer> plateVtoBMap,
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Integer maxOccupancyDifference) {
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Integer maxOccupancyDifference, boolean saveEdges) {
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List<Integer[]> removedEdges = new ArrayList<>();
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List<Integer[]> removedEdges = new ArrayList<>();
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for (DefaultWeightedEdge e : graph.edgeSet()) {
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for (DefaultWeightedEdge e : graph.edgeSet()) {
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Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
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Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
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Integer betaOcc = betaWellCounts.get(plateVtoBMap.get(graph.getEdgeTarget(e)));
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Integer betaOcc = betaWellCounts.get(plateVtoBMap.get(graph.getEdgeTarget(e)));
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if (Math.abs(alphaOcc - betaOcc) >= maxOccupancyDifference) {
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if (Math.abs(alphaOcc - betaOcc) >= maxOccupancyDifference) {
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Integer source = graph.getEdgeSource(e);
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if (saveEdges) {
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Integer target = graph.getEdgeTarget(e);
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Integer source = graph.getEdgeSource(e);
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Integer weight = (int) graph.getEdgeWeight(e);
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Integer target = graph.getEdgeTarget(e);
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Integer[] edge = {source, target, weight};
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Integer weight = (int) graph.getEdgeWeight(e);
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removedEdges.add(edge);
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Integer[] edge = {source, target, weight};
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removedEdges.add(edge);
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}
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else {
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graph.setEdgeWeight(e, 0.0);
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}
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}
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}
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}
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}
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for (Integer[] edge : removedEdges) {
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if(saveEdges) {
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graph.removeEdge(edge[0], edge[1]);
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for (Integer[] edge : removedEdges) {
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graph.removeEdge(edge[0], edge[1]);
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}
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}
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}
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return removedEdges;
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return removedEdges;
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}
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}
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//Remove edges for pairs where overlap size is significantly lower than the well occupancy
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//Remove edges for pairs where overlap size is significantly lower than the well occupancy
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public static List<Integer[]> filterByOverlapPercent(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
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static List<Integer[]> filterByOverlapPercent(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
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Map<Integer, Integer> alphaWellCounts,
|
Map<Integer, Integer> alphaWellCounts,
|
||||||
Map<Integer, Integer> betaWellCounts,
|
Map<Integer, Integer> betaWellCounts,
|
||||||
Map<Integer, Integer> plateVtoAMap,
|
Map<Integer, Integer> plateVtoAMap,
|
||||||
Map<Integer, Integer> plateVtoBMap,
|
Map<Integer, Integer> plateVtoBMap,
|
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Integer minOverlapPercent) {
|
Integer minOverlapPercent,
|
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|
boolean saveEdges) {
|
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List<Integer[]> removedEdges = new ArrayList<>();
|
List<Integer[]> removedEdges = new ArrayList<>();
|
||||||
for (DefaultWeightedEdge e : graph.edgeSet()) {
|
for (DefaultWeightedEdge e : graph.edgeSet()) {
|
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Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
|
Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
|
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@@ -66,20 +81,27 @@ public abstract class GraphModificationFunctions {
|
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double weight = graph.getEdgeWeight(e);
|
double weight = graph.getEdgeWeight(e);
|
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double min = minOverlapPercent / 100.0;
|
double min = minOverlapPercent / 100.0;
|
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if ((weight / alphaOcc < min) || (weight / betaOcc < min)) {
|
if ((weight / alphaOcc < min) || (weight / betaOcc < min)) {
|
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Integer source = graph.getEdgeSource(e);
|
if(saveEdges) {
|
||||||
Integer target = graph.getEdgeTarget(e);
|
Integer source = graph.getEdgeSource(e);
|
||||||
Integer intWeight = (int) graph.getEdgeWeight(e);
|
Integer target = graph.getEdgeTarget(e);
|
||||||
Integer[] edge = {source, target, intWeight};
|
Integer intWeight = (int) graph.getEdgeWeight(e);
|
||||||
removedEdges.add(edge);
|
Integer[] edge = {source, target, intWeight};
|
||||||
|
removedEdges.add(edge);
|
||||||
|
}
|
||||||
|
else {
|
||||||
|
graph.setEdgeWeight(e, 0.0);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
for (Integer[] edge : removedEdges) {
|
if(saveEdges) {
|
||||||
graph.removeEdge(edge[0], edge[1]);
|
for (Integer[] edge : removedEdges) {
|
||||||
|
graph.removeEdge(edge[0], edge[1]);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
return removedEdges;
|
return removedEdges;
|
||||||
}
|
}
|
||||||
|
|
||||||
public static void addRemovedEdges(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
|
static void addRemovedEdges(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
|
||||||
List<Integer[]> removedEdges) {
|
List<Integer[]> removedEdges) {
|
||||||
for (Integer[] edge : removedEdges) {
|
for (Integer[] edge : removedEdges) {
|
||||||
DefaultWeightedEdge e = graph.addEdge(edge[0], edge[1]);
|
DefaultWeightedEdge e = graph.addEdge(edge[0], edge[1]);
|
||||||
|
|||||||
@@ -38,10 +38,10 @@ public class InteractiveInterface {
|
|||||||
case 3 -> makeCDR3Graph();
|
case 3 -> makeCDR3Graph();
|
||||||
case 4 -> matchCDR3s();
|
case 4 -> matchCDR3s();
|
||||||
//case 6 -> matchCellsCDR1();
|
//case 6 -> matchCellsCDR1();
|
||||||
case 8 -> options();
|
case 8 -> mainOptions();
|
||||||
case 9 -> acknowledge();
|
case 9 -> acknowledge();
|
||||||
case 0 -> quit = true;
|
case 0 -> quit = true;
|
||||||
default -> throw new InputMismatchException("Invalid input.");
|
default -> System.out.println("Invalid input.");
|
||||||
}
|
}
|
||||||
} catch (InputMismatchException | IOException ex) {
|
} catch (InputMismatchException | IOException ex) {
|
||||||
System.out.println(ex);
|
System.out.println(ex);
|
||||||
@@ -493,13 +493,14 @@ public class InteractiveInterface {
|
|||||||
// }
|
// }
|
||||||
// }
|
// }
|
||||||
|
|
||||||
private static void options(){
|
private static void mainOptions(){
|
||||||
boolean backToMain = false;
|
boolean backToMain = false;
|
||||||
while(!backToMain) {
|
while(!backToMain) {
|
||||||
System.out.println("\n--------------OPTIONS---------------");
|
System.out.println("\n--------------OPTIONS---------------");
|
||||||
System.out.println("1) Turn " + getOnOff(!BiGpairSEQ.cacheCells()) + " cell sample file caching");
|
System.out.println("1) Turn " + getOnOff(!BiGpairSEQ.cacheCells()) + " cell sample file caching");
|
||||||
System.out.println("2) Turn " + getOnOff(!BiGpairSEQ.cachePlate()) + " plate file caching");
|
System.out.println("2) Turn " + getOnOff(!BiGpairSEQ.cachePlate()) + " plate file caching");
|
||||||
System.out.println("3) Turn " + getOnOff(!BiGpairSEQ.cacheGraph()) + " graph/data file caching");
|
System.out.println("3) Turn " + getOnOff(!BiGpairSEQ.cacheGraph()) + " graph/data file caching");
|
||||||
|
System.out.println("4) Maximum weight matching algorithm options");
|
||||||
System.out.println("0) Return to main menu");
|
System.out.println("0) Return to main menu");
|
||||||
try {
|
try {
|
||||||
input = sc.nextInt();
|
input = sc.nextInt();
|
||||||
@@ -507,8 +508,9 @@ public class InteractiveInterface {
|
|||||||
case 1 -> BiGpairSEQ.setCacheCells(!BiGpairSEQ.cacheCells());
|
case 1 -> BiGpairSEQ.setCacheCells(!BiGpairSEQ.cacheCells());
|
||||||
case 2 -> BiGpairSEQ.setCachePlate(!BiGpairSEQ.cachePlate());
|
case 2 -> BiGpairSEQ.setCachePlate(!BiGpairSEQ.cachePlate());
|
||||||
case 3 -> BiGpairSEQ.setCacheGraph(!BiGpairSEQ.cacheGraph());
|
case 3 -> BiGpairSEQ.setCacheGraph(!BiGpairSEQ.cacheGraph());
|
||||||
|
case 4 -> algorithmOptions();
|
||||||
case 0 -> backToMain = true;
|
case 0 -> backToMain = true;
|
||||||
default -> throw new InputMismatchException("Invalid input.");
|
default -> System.out.println("Invalid input");
|
||||||
}
|
}
|
||||||
} catch (InputMismatchException ex) {
|
} catch (InputMismatchException ex) {
|
||||||
System.out.println(ex);
|
System.out.println(ex);
|
||||||
@@ -517,11 +519,49 @@ public class InteractiveInterface {
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
/**
|
||||||
|
* Helper function for printing menu items in mainOptions(). Returns a string based on the value of parameter.
|
||||||
|
*
|
||||||
|
* @param b - a boolean value
|
||||||
|
* @return String "on" if b is true, "off" if b is false
|
||||||
|
*/
|
||||||
private static String getOnOff(boolean b) {
|
private static String getOnOff(boolean b) {
|
||||||
if (b) { return "on";}
|
if (b) { return "on";}
|
||||||
else { return "off"; }
|
else { return "off"; }
|
||||||
}
|
}
|
||||||
|
|
||||||
|
private static void algorithmOptions(){
|
||||||
|
boolean backToOptions = false;
|
||||||
|
while(!backToOptions) {
|
||||||
|
System.out.println("\n---------ALGORITHM OPTIONS----------");
|
||||||
|
System.out.println("1) Use scaling algorithm by Duan and Su.");
|
||||||
|
System.out.println("2) Use LEDA book algorithm with Fibonacci heap priority queue");
|
||||||
|
System.out.println("3) Use LEDA book algorithm with pairing heap priority queue");
|
||||||
|
System.out.println("0) Return to Options menu");
|
||||||
|
try {
|
||||||
|
input = sc.nextInt();
|
||||||
|
switch (input) {
|
||||||
|
case 1 -> System.out.println("This option is not yet implemented. Choose another.");
|
||||||
|
case 2 -> {
|
||||||
|
BiGpairSEQ.setFibonacciHeap();
|
||||||
|
System.out.println("MWM algorithm set to LEDA with Fibonacci heap");
|
||||||
|
backToOptions = true;
|
||||||
|
}
|
||||||
|
case 3 -> {
|
||||||
|
BiGpairSEQ.setPairingHeap();
|
||||||
|
System.out.println("MWM algorithm set to LEDA with pairing heap");
|
||||||
|
backToOptions = true;
|
||||||
|
}
|
||||||
|
case 0 -> backToOptions = true;
|
||||||
|
default -> System.out.println("Invalid input");
|
||||||
|
}
|
||||||
|
} catch (InputMismatchException ex) {
|
||||||
|
System.out.println(ex);
|
||||||
|
sc.next();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
private static void acknowledge(){
|
private static void acknowledge(){
|
||||||
System.out.println("This program simulates BiGpairSEQ, a graph theory based adaptation");
|
System.out.println("This program simulates BiGpairSEQ, a graph theory based adaptation");
|
||||||
System.out.println("of the pairSEQ algorithm for pairing T cell receptor sequences.");
|
System.out.println("of the pairSEQ algorithm for pairing T cell receptor sequences.");
|
||||||
|
|||||||
@@ -3,6 +3,7 @@ import org.jgrapht.alg.matching.MaximumWeightBipartiteMatching;
|
|||||||
import org.jgrapht.generate.SimpleWeightedBipartiteGraphMatrixGenerator;
|
import org.jgrapht.generate.SimpleWeightedBipartiteGraphMatrixGenerator;
|
||||||
import org.jgrapht.graph.DefaultWeightedEdge;
|
import org.jgrapht.graph.DefaultWeightedEdge;
|
||||||
import org.jgrapht.graph.SimpleWeightedGraph;
|
import org.jgrapht.graph.SimpleWeightedGraph;
|
||||||
|
import org.jheaps.tree.FibonacciHeap;
|
||||||
import org.jheaps.tree.PairingHeap;
|
import org.jheaps.tree.PairingHeap;
|
||||||
|
|
||||||
import java.math.BigDecimal;
|
import java.math.BigDecimal;
|
||||||
@@ -16,7 +17,7 @@ import java.util.stream.IntStream;
|
|||||||
import static java.lang.Float.*;
|
import static java.lang.Float.*;
|
||||||
|
|
||||||
//NOTE: "sequence" in method and variable names refers to a peptide sequence from a simulated T cell
|
//NOTE: "sequence" in method and variable names refers to a peptide sequence from a simulated T cell
|
||||||
public class Simulator {
|
public class Simulator implements GraphModificationFunctions {
|
||||||
private static final int cdr3AlphaIndex = 0;
|
private static final int cdr3AlphaIndex = 0;
|
||||||
private static final int cdr3BetaIndex = 1;
|
private static final int cdr3BetaIndex = 1;
|
||||||
private static final int cdr1AlphaIndex = 2;
|
private static final int cdr1AlphaIndex = 2;
|
||||||
@@ -146,8 +147,8 @@ public class Simulator {
|
|||||||
Integer highThreshold, Integer maxOccupancyDifference,
|
Integer highThreshold, Integer maxOccupancyDifference,
|
||||||
Integer minOverlapPercent, boolean verbose) {
|
Integer minOverlapPercent, boolean verbose) {
|
||||||
Instant start = Instant.now();
|
Instant start = Instant.now();
|
||||||
//Integer arrays will contain TO VERTEX, FROM VERTEX, and WEIGHT (which I'll need to cast to double)
|
|
||||||
List<Integer[]> removedEdges = new ArrayList<>();
|
List<Integer[]> removedEdges = new ArrayList<>();
|
||||||
|
boolean saveEdges = BiGpairSEQ.cacheGraph();
|
||||||
int numWells = data.getNumWells();
|
int numWells = data.getNumWells();
|
||||||
Integer alphaCount = data.getAlphaCount();
|
Integer alphaCount = data.getAlphaCount();
|
||||||
Integer betaCount = data.getBetaCount();
|
Integer betaCount = data.getBetaCount();
|
||||||
@@ -160,33 +161,50 @@ public class Simulator {
|
|||||||
|
|
||||||
//remove edges with weights outside given overlap thresholds, add those to removed edge list
|
//remove edges with weights outside given overlap thresholds, add those to removed edge list
|
||||||
if(verbose){System.out.println("Eliminating edges with weights outside overlap threshold values");}
|
if(verbose){System.out.println("Eliminating edges with weights outside overlap threshold values");}
|
||||||
removedEdges.addAll(GraphModificationFunctions.filterByOverlapThresholds(graph, lowThreshold, highThreshold));
|
removedEdges.addAll(GraphModificationFunctions.filterByOverlapThresholds(graph, lowThreshold, highThreshold, saveEdges));
|
||||||
if(verbose){System.out.println("Over- and under-weight edges removed");}
|
if(verbose){System.out.println("Over- and under-weight edges removed");}
|
||||||
|
|
||||||
//remove edges between vertices with too small an overlap size, add those to removed edge list
|
//remove edges between vertices with too small an overlap size, add those to removed edge list
|
||||||
if(verbose){System.out.println("Eliminating edges with weights less than " + minOverlapPercent.toString() +
|
if(verbose){System.out.println("Eliminating edges with weights less than " + minOverlapPercent.toString() +
|
||||||
" percent of vertex occupancy value.");}
|
" percent of vertex occupancy value.");}
|
||||||
removedEdges.addAll(GraphModificationFunctions.filterByOverlapPercent(graph, alphaWellCounts, betaWellCounts,
|
removedEdges.addAll(GraphModificationFunctions.filterByOverlapPercent(graph, alphaWellCounts, betaWellCounts,
|
||||||
plateVtoAMap, plateVtoBMap, minOverlapPercent));
|
plateVtoAMap, plateVtoBMap, minOverlapPercent, saveEdges));
|
||||||
if(verbose){System.out.println("Edges with weights too far below a vertex occupancy value removed");}
|
if(verbose){System.out.println("Edges with weights too far below a vertex occupancy value removed");}
|
||||||
|
|
||||||
//Filter by relative occupancy
|
//Filter by relative occupancy
|
||||||
if(verbose){System.out.println("Eliminating edges between vertices with occupancy difference > "
|
if(verbose){System.out.println("Eliminating edges between vertices with occupancy difference > "
|
||||||
+ maxOccupancyDifference);}
|
+ maxOccupancyDifference);}
|
||||||
removedEdges.addAll(GraphModificationFunctions.filterByRelativeOccupancy(graph, alphaWellCounts, betaWellCounts,
|
removedEdges.addAll(GraphModificationFunctions.filterByRelativeOccupancy(graph, alphaWellCounts, betaWellCounts,
|
||||||
plateVtoAMap, plateVtoBMap, maxOccupancyDifference));
|
plateVtoAMap, plateVtoBMap, maxOccupancyDifference, saveEdges));
|
||||||
if(verbose){System.out.println("Edges between vertices of with excessively different occupancy values " +
|
if(verbose){System.out.println("Edges between vertices of with excessively different occupancy values " +
|
||||||
"removed");}
|
"removed");}
|
||||||
|
|
||||||
//Find Maximum Weighted Matching
|
//Find Maximum Weighted Matching
|
||||||
//using jheaps library class PairingHeap for improved efficiency
|
//using jheaps library class PairingHeap for improved efficiency
|
||||||
if(verbose){System.out.println("Finding maximum weighted matching");}
|
if(verbose){System.out.println("Finding maximum weighted matching");}
|
||||||
//Attempting to use addressable heap to improve performance
|
MaximumWeightBipartiteMatching maxWeightMatching;
|
||||||
MaximumWeightBipartiteMatching maxWeightMatching =
|
//Use correct heap type for priority queue
|
||||||
new MaximumWeightBipartiteMatching(graph,
|
String heapType = BiGpairSEQ.getPriorityQueueHeapType();
|
||||||
|
switch (heapType) {
|
||||||
|
case "PAIRING" -> {
|
||||||
|
maxWeightMatching = new MaximumWeightBipartiteMatching(graph,
|
||||||
plateVtoAMap.keySet(),
|
plateVtoAMap.keySet(),
|
||||||
plateVtoBMap.keySet(),
|
plateVtoBMap.keySet(),
|
||||||
i -> new PairingHeap(Comparator.naturalOrder()));
|
i -> new PairingHeap(Comparator.naturalOrder()));
|
||||||
|
}
|
||||||
|
case "FIBONACCI" -> {
|
||||||
|
maxWeightMatching = new MaximumWeightBipartiteMatching(graph,
|
||||||
|
plateVtoAMap.keySet(),
|
||||||
|
plateVtoBMap.keySet(),
|
||||||
|
i -> new FibonacciHeap(Comparator.naturalOrder()));
|
||||||
|
}
|
||||||
|
default -> {
|
||||||
|
maxWeightMatching = new MaximumWeightBipartiteMatching(graph,
|
||||||
|
plateVtoAMap.keySet(),
|
||||||
|
plateVtoBMap.keySet());
|
||||||
|
}
|
||||||
|
}
|
||||||
|
//get the matching
|
||||||
MatchingAlgorithm.Matching<String, DefaultWeightedEdge> graphMatching = maxWeightMatching.getMatching();
|
MatchingAlgorithm.Matching<String, DefaultWeightedEdge> graphMatching = maxWeightMatching.getMatching();
|
||||||
if(verbose){System.out.println("Matching completed");}
|
if(verbose){System.out.println("Matching completed");}
|
||||||
Instant stop = Instant.now();
|
Instant stop = Instant.now();
|
||||||
@@ -292,10 +310,11 @@ public class Simulator {
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
//put the removed edges back on the graph
|
if(saveEdges) {
|
||||||
System.out.println("Restoring removed edges to graph.");
|
//put the removed edges back on the graph
|
||||||
GraphModificationFunctions.addRemovedEdges(graph, removedEdges);
|
System.out.println("Restoring removed edges to graph.");
|
||||||
|
GraphModificationFunctions.addRemovedEdges(graph, removedEdges);
|
||||||
|
}
|
||||||
//return MatchingResult object
|
//return MatchingResult object
|
||||||
return output;
|
return output;
|
||||||
}
|
}
|
||||||
|
|||||||
Reference in New Issue
Block a user