27 Commits

Author SHA1 Message Date
ab8d98ed81 Update readme to reflect new default caching behavior. 2022-02-24 15:39:15 -06:00
3d9890e16a Change GraphModificationFunctions to only save edges if graph data is cached 2022-02-24 15:32:27 -06:00
dd64ac2731 Change GraphModificationFunctions to interface 2022-02-24 15:18:09 -06:00
a5238624f1 Change default graph caching behavior to false 2022-02-24 15:14:28 -06:00
d8ba42b801 Fix Algorithm Options menu output 2022-02-24 14:59:08 -06:00
8edd89d784 Added heap type selection, fixed error handling 2022-02-24 14:48:19 -06:00
2829b88689 Update readme to reflect caching changes 2022-02-24 12:47:26 -06:00
108b0ec13f Improve options menu wording 2022-02-24 12:42:09 -06:00
a8b58d3f79 Output new setting when changing options 2022-02-24 12:38:15 -06:00
bf64d57731 implement option menu for file caching 2022-02-24 12:30:47 -06:00
c068c3db3c implement option menu for file caching 2022-02-23 20:35:31 -06:00
4bcda9b66c update readme 2022-02-23 13:22:04 -06:00
17ae763c6c Generate populations correctly 2022-02-23 10:37:40 -06:00
decdb147a9 Cache everything 2022-02-23 10:30:42 -06:00
74ffbfd8ac make everything use same random number generator 2022-02-23 09:29:21 -06:00
08699ce8ce Change output order to match interactive UI 2022-02-23 08:56:09 -06:00
69b0cc535c Error checking 2022-02-23 08:55:07 -06:00
e58f7b0a55 checking for possible divide by zero error. 2022-02-23 08:54:14 -06:00
dd2164c250 implement sample plates with random well populations 2022-02-23 08:14:17 -06:00
7323093bdc change "getRandomNumber" to "getRandomInt" for consistency. 2022-02-23 08:13:52 -06:00
f904cf6672 add more data caching code 2022-02-23 08:13:06 -06:00
3ccee9891b change "concentrations" to "populations" for consistency 2022-02-23 08:12:48 -06:00
40c2be1cfb create populations string correctly 2022-02-23 08:11:01 -06:00
4b597c4e5e remove old testing code 2022-02-23 08:10:35 -06:00
b2398531a3 Update readme 2022-02-23 05:11:36 +00:00
8e9a250890 Cache graph data on creation 2022-02-22 22:23:55 -06:00
e2a996c997 update readme 2022-02-22 22:23:40 -06:00
12 changed files with 529 additions and 179 deletions

View File

@@ -12,7 +12,7 @@ Unlike pairSEQ, which calculates p-values for every TCR alpha/beta overlap and c
against a null distribution, BiGpairSEQ does not do any statistical calculations
directly.
BiGpairSEQ creates a [simple bipartite weighted graph](https://en.wikipedia.org/wiki/Bipartite_graph) representing the sample plate.
BiGpairSEQ creates a [weightd bipartite graph](https://en.wikipedia.org/wiki/Bipartite_graph) representing the sample plate.
The distinct TCRA and TCRB sequences form the two sets of vertices. Every TCRA/TCRB pair that share a well
are connected by an edge, with the edge weight set to the number of wells in which both sequences appear.
(Sequences present in *all* wells are filtered out prior to creating the graph, as there is no signal in their occupancy pattern.)
@@ -29,17 +29,13 @@ Unfortunately, it's a fairly new algorithm, and not yet implemented by the graph
So this program instead uses the Fibonacci heap-based algorithm of Fredman and Tarjan (1987), which has a worst-case
runtime of **O(n (n log(n) + m))**. The algorithm is implemented as described in Melhorn and Näher (1999).
The current version of the program uses a pairing heap instead of a Fibonacci heap for its priority queue,
which has lower theoretical efficiency but also lower complexity overhead, and is often equivalently performant
in practice.
## USAGE
### RUNNING THE PROGRAM
[Download the current version of BiGpairSEQ_Sim.](https://gitea.ejsf.synology.me/efischer/BiGpairSEQ/releases)
BiGpairSEQ_Sim is an executable .jar file. Requires Java 11 or higher. [OpenJDK 17](https://jdk.java.net/17/)
BiGpairSEQ_Sim is an executable .jar file. Requires Java 14 or higher. [OpenJDK 17](https://jdk.java.net/17/)
recommended.
Run with the command:
@@ -58,27 +54,41 @@ main menu looks like this:
```
--------BiGPairSEQ SIMULATOR--------
ALPHA/BETA T CELL RECEPTOR MATCHING
USING WEIGHTED BIPARTITE GRAPHS
USING WEIGHTED BIPARTITE GRAPHS
------------------------------------
Please select an option:
1) Generate a population of distinct cells
2) Generate a sample plate of T cells
3) Generate CDR3 alpha/beta occupancy data and overlap graph
4) Simulate bipartite graph CDR3 alpha/beta matching (BiGpairSEQ)
8) Options
9) About/Acknowledgments
0) Exit
```
### OUTPUT
### INPUT/OUTPUT
To run the simulation, the program reads and writes 4 kinds of files:
* Cell Sample files in CSV format
* Sample Plate files in CSV format
* Graph and Data files in binary object serialization format
* Graph/Data files in binary object serialization format
* Matching Results files in CSV format
When entering filenames, it is not necessary to include the file extension (.csv or .ser). When reading or
writing files, the program will automatically add the correct extension to any filename without one.
These files are often generated in sequence. When entering filenames, it is not necessary to include the file extension
(.csv or .ser). When reading or writing files, the program will automatically add the correct extension to any filename without one.
To save file I/O time, the most recent instance of each of these four
files either generated or read from disk can be cached in program memory. This is could be important for Graph/Data files,
which can be several gigabytes in size. Since some simulations may require running multiple,
differently-configured BiGpairSEQ matchings on the same graph, keeping the most recent graph cached may reduce execution time.
(The manipulation necessary to re-use a graph incurs its own performance overhead, though, which may scale with graph
size faster than file I/O does. If so, caching is best for smaller graphs.)
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,
or caching is turned off for that file type. The program checks whether it needs to update its cached data by comparing
filenames as entered by the user. On encountering a new filename, the program flushes its cache and reads in the new file.
The program's caching behavior can be controlled in the Options menu. By default, all caching is OFF.
#### Cell Sample Files
Cell Sample files consist of any number of distinct "T cells." Every cell contains
@@ -121,7 +131,7 @@ Options when making a Sample Plate file:
* Standard deviation size
* Exponential
* Lambda value
* (Based on the slope of the graph in Figure 4C of the pairSEQ paper, the distribution of the original experiment was exponential with a lambda of approximately 0.6. (Howie, et al. 2015))
* *(Based on the slope of the graph in Figure 4C of the pairSEQ paper, the distribution of the original experiment was exponential with a lambda of approximately 0.6. (Howie, et al. 2015))*
* Total number of wells on the plate
* Number of sections on plate
* Number of T cells per well
@@ -129,7 +139,7 @@ Options when making a Sample Plate file:
* Dropout rate
Files are in CSV format. There are no header labels. Every row represents a well.
Every column represents an individual cell, containing four sequences, depicted as an array string:
Every value represents an individual cell, containing four sequences, depicted as an array string:
`[CDR3A, CDR3B, CDR1A, CDR1B]`. So a representative cell might look like this:
`[525902, 791533, -1, 866282]`
@@ -155,14 +165,16 @@ Structure:
---
#### Graph and Data Files
Graph and Data files are serialized binaries of a Java object containing the weigthed bipartite graph representation of a
#### Graph/Data Files
Graph/Data files are serialized binaries of a Java object containing the weigthed bipartite graph representation of a
Sample Plate, along with the necessary metadata for matching and results output. Making them requires a Cell Sample file
(to construct a list of correct sequence pairs for checking the accuracy of BiGpairSEQ simulations) and a
Sample Plate file (to construct the associated occupancy graph). These files can be several gigabytes in size.
Writing them to a file lets us generate a graph and its metadata once, then use it for multiple different BiGpairSEQ simulations.
Sample Plate file (to construct the associated occupancy graph).
Options for creating a Graph and Data file:
These files can be several gigabytes in size. Writing them to a file lets us generate a graph and its metadata once,
then use it for multiple different BiGpairSEQ simulations.
Options for creating a Graph/Data file:
* The Cell Sample file to use
* The Sample Plate file to use. (This must have been generated from the selected Cell Sample file.)
@@ -172,8 +184,8 @@ portable data format may be implemented in the future. The tricky part is encodi
---
#### Matching Results Files
Matching results files consist of the results of a BiGpairSEQ matching simulation.
Files are in CSV format. Rows are sequence pairings with extra relevant data. Columns are pairing-specific details.
Matching results files consist of the results of a BiGpairSEQ matching simulation. Making them requires a Graph and
Data file. Matching results files are in CSV format. Rows are sequence pairings with extra relevant data. Columns are pairing-specific details.
Metadata about the matching simulation is included as comments. Comments are preceded by `#`.
Options when running a BiGpairSEQ simulation of CDR3 alpha/beta matching:
@@ -241,7 +253,8 @@ slightly less time than the simulation itself. Real elapsed time from start to f
* ~~Try invoking GC at end of workloads to reduce paging to disk~~ DONE
* Hold graph data in memory until another graph is read-in? ~~ABANDONED~~ ~~UNABANDONED~~ DONE
* ~~*No, this won't work, because BiGpairSEQ simulations alter the underlying graph based on filtering constraints. Changes would cascade with multiple experiments.*~~
* 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.
* 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.
* It is possible, though the modifications to the graph incur their own performance penalties. Need testing to see which option is best.
* See if there's a reasonable way to reformat Sample Plate files so that wells are columns instead of rows.
* ~~Problem is variable number of cells in a well~~
* ~~Apache Commons CSV library writes entries a row at a time~~
@@ -255,9 +268,10 @@ slightly less time than the simulation itself. Real elapsed time from start to f
* Re-implement CDR1 matching method
* Implement Duan and Su's maximum weight matching algorithm
* Add controllable algorithm-type parameter?
* Test whether pairing heap (currently used) or Fibonacci heap is more efficient for priority queue in current matching algorithm
* in theory Fibonacci heap should be more efficient, but complexity overhead may eliminate theoretical advantage
* Add controllable heap-type parameter?
* ~~Test whether pairing heap (currently used) or Fibonacci heap is more efficient for priority queue in current matching algorithm~~ DONE
* ~~in theory Fibonacci heap should be more efficient, but complexity overhead may eliminate theoretical advantage~~
* ~~Add controllable heap-type parameter?~~
* Parameter implemented. For large graphs, Fibonacci heap wins. Now the new default.

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@@ -1,8 +1,19 @@
//main class. Only job is to choose which interface to use, and hold graph data in memory
import java.util.Random;
//main class. For choosing interface type and caching file data
public class BiGpairSEQ {
private static final Random rand = new Random();
private static CellSample cellSampleInMemory = null;
private static String cellFilename = null;
private static Plate plateInMemory = null;
private static String plateFilename = null;
private static GraphWithMapData graphInMemory = null;
private static String graphFilename = null;
private static boolean cacheCells = false;
private static boolean cachePlate = false;
private static boolean cacheGraph = false;
private static String priorityQueueHeapType = "FIBONACCI";
public static void main(String[] args) {
if (args.length == 0) {
@@ -15,28 +26,142 @@ public class BiGpairSEQ {
}
}
public static GraphWithMapData getGraph() {
return graphInMemory;
public static Random getRand() {
return rand;
}
public static void setGraph(GraphWithMapData g) {
public static CellSample getCellSampleInMemory() {
return cellSampleInMemory;
}
public static void setCellSampleInMemory(CellSample cellSample, String filename) {
if(cellSampleInMemory != null) {
clearCellSampleInMemory();
}
cellSampleInMemory = cellSample;
cellFilename = filename;
System.out.println("Cell sample file " + filename + " cached.");
}
public static void clearCellSampleInMemory() {
cellSampleInMemory = null;
cellFilename = null;
System.gc();
System.out.println("Cell sample file cache cleared.");
}
public static String getCellFilename() {
return cellFilename;
}
public static Plate getPlateInMemory() {
return plateInMemory;
}
public static void setPlateInMemory(Plate plate, String filename) {
if(plateInMemory != null) {
clearPlateInMemory();
}
plateInMemory = plate;
plateFilename = filename;
System.out.println("Sample plate file " + filename + " cached.");
}
public static void clearPlateInMemory() {
plateInMemory = null;
plateFilename = null;
System.gc();
System.out.println("Sample plate file cache cleared.");
}
public static String getPlateFilename() {
return plateFilename;
}
public static GraphWithMapData getGraphInMemory() {return graphInMemory;
}
public static void setGraphInMemory(GraphWithMapData g, String filename) {
if (graphInMemory != null) {
clearGraph();
clearGraphInMemory();
}
graphInMemory = g;
graphFilename = filename;
System.out.println("Graph and data file " + filename + " cached.");
}
public static void clearGraph() {
public static void clearGraphInMemory() {
graphInMemory = null;
graphFilename = null;
System.gc();
System.out.println("Graph and data file cache cleared.");
}
public static String getGraphFilename() {
return graphFilename;
}
public static void setGraphFilename(String filename) {
graphFilename = filename;
public static boolean cacheCells() {
return cacheCells;
}
public static void setCacheCells(boolean cacheCells) {
//if not caching, clear the memory
if(!cacheCells){
BiGpairSEQ.clearCellSampleInMemory();
System.out.println("Cell sample file caching: OFF.");
}
else {
System.out.println("Cell sample file caching: ON.");
}
BiGpairSEQ.cacheCells = cacheCells;
}
public static boolean cachePlate() {
return cachePlate;
}
public static void setCachePlate(boolean cachePlate) {
//if not caching, clear the memory
if(!cachePlate) {
BiGpairSEQ.clearPlateInMemory();
System.out.println("Sample plate file caching: OFF.");
}
else {
System.out.println("Sample plate file caching: ON.");
}
BiGpairSEQ.cachePlate = cachePlate;
}
public static boolean cacheGraph() {
return cacheGraph;
}
public static void setCacheGraph(boolean cacheGraph) {
//if not caching, clear the memory
if(!cacheGraph) {
BiGpairSEQ.clearGraphInMemory();
System.out.println("Graph/data file caching: OFF.");
}
else {
System.out.println("Graph/data file caching: ON.");
}
BiGpairSEQ.cacheGraph = cacheGraph;
}
public static String getPriorityQueueHeapType() {
return priorityQueueHeapType;
}
public static void setPairingHeap() {
priorityQueueHeapType = "PAIRING";
}
public static void setFibonacciHeap() {
priorityQueueHeapType = "FIBONACCI";
}
}

View File

@@ -13,6 +13,7 @@ public class CellFileReader {
private String filename;
private List<Integer[]> distinctCells = new ArrayList<>();
private Integer cdr1Freq;
public CellFileReader(String filename) {
if(!filename.matches(".*\\.csv")){
@@ -38,19 +39,37 @@ public class CellFileReader {
cell[3] = Integer.valueOf(record.get("Beta CDR1"));
distinctCells.add(cell);
}
} catch(IOException ex){
System.out.println("cell file " + filename + " not found.");
System.err.println(ex);
}
//get CDR1 frequency
ArrayList<Integer> cdr1Alphas = new ArrayList<>();
for (Integer[] cell : distinctCells) {
cdr1Alphas.add(cell[3]);
}
double count = cdr1Alphas.stream().distinct().count();
count = Math.ceil(distinctCells.size() / count);
cdr1Freq = (int) count;
}
public CellSample getCellSample() {
return new CellSample(distinctCells, cdr1Freq);
}
public String getFilename() { return filename;}
public List<Integer[]> getCells(){
//Refactor everything that uses this to have access to a Cell Sample and get the cells there instead.
public List<Integer[]> getListOfDistinctCellsDEPRECATED(){
return distinctCells;
}
public Integer getCellCount() {
public Integer getCellCountDEPRECATED() {
//Refactor everything that uses this to have access to a Cell Sample and get the count there instead.
return distinctCells.size();
}
}

View File

@@ -18,7 +18,7 @@ public class CellSample {
return cdr1Freq;
}
public Integer population(){
public Integer getCellCount(){
return cells.size();
}

View File

@@ -297,7 +297,7 @@ public class CommandLineInterface {
Integer numWells, Integer[] concentrations, Double dropOutRate){
CellFileReader cellReader = new CellFileReader(cellFile);
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWellsExponential(cellReader.getFilename(), cellReader.getCells(), lambda);
samplePlate.fillWellsExponential(cellReader.getFilename(), cellReader.getListOfDistinctCellsDEPRECATED(), lambda);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
}
@@ -305,9 +305,9 @@ public class CommandLineInterface {
private static void makePlatePoisson(String cellFile, String filename, Integer numWells,
Integer[] concentrations, Double dropOutRate){
CellFileReader cellReader = new CellFileReader(cellFile);
Double stdDev = Math.sqrt(cellReader.getCellCount());
Double stdDev = Math.sqrt(cellReader.getCellCountDEPRECATED());
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getCells(), stdDev);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getListOfDistinctCellsDEPRECATED(), stdDev);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
}
@@ -316,7 +316,7 @@ public class CommandLineInterface {
Integer numWells, Integer[] concentrations, Double dropOutRate){
CellFileReader cellReader = new CellFileReader(cellFile);
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getCells(), stdDev);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getListOfDistinctCellsDEPRECATED(), stdDev);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
}

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@@ -4,10 +4,6 @@ import java.math.MathContext;
public abstract class Equations {
public static int getRandomNumber(int min, int max) {
return (int) ((Math.random() * (max - min)) + min);
}
//pValue calculation as described in original pairSEQ paper.
//Included for comparison with original results.
//Not used by BiGpairSEQ for matching.

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@@ -6,59 +6,74 @@ import java.util.List;
import java.util.Map;
import java.util.Set;
public abstract class GraphModificationFunctions {
public interface GraphModificationFunctions {
//remove over- and under-weight edges
public static List<Integer[]> filterByOverlapThresholds(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
int low, int high) {
static List<Integer[]> filterByOverlapThresholds(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
int low, int high, boolean saveEdges) {
List<Integer[]> removedEdges = new ArrayList<>();
for(DefaultWeightedEdge e: graph.edgeSet()){
if ((graph.getEdgeWeight(e) > high) || (graph.getEdgeWeight(e) < low)){
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, weight};
removedEdges.add(edge);
for (DefaultWeightedEdge e : graph.edgeSet()) {
if ((graph.getEdgeWeight(e) > high) || (graph.getEdgeWeight(e) < low)) {
if(saveEdges) {
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, weight};
removedEdges.add(edge);
}
else {
graph.setEdgeWeight(e, 0.0);
}
}
}
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
if(saveEdges) {
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
}
}
return removedEdges;
}
//Remove edges for pairs with large occupancy discrepancy
public static List<Integer[]> filterByRelativeOccupancy(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
static List<Integer[]> filterByRelativeOccupancy(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
Map<Integer, Integer> alphaWellCounts,
Map<Integer, Integer> betaWellCounts,
Map<Integer, Integer> plateVtoAMap,
Map<Integer, Integer> plateVtoBMap,
Integer maxOccupancyDifference) {
Integer maxOccupancyDifference, boolean saveEdges) {
List<Integer[]> removedEdges = new ArrayList<>();
for (DefaultWeightedEdge e : graph.edgeSet()) {
Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
Integer betaOcc = betaWellCounts.get(plateVtoBMap.get(graph.getEdgeTarget(e)));
if (Math.abs(alphaOcc - betaOcc) >= maxOccupancyDifference) {
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, weight};
removedEdges.add(edge);
if (saveEdges) {
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, weight};
removedEdges.add(edge);
}
else {
graph.setEdgeWeight(e, 0.0);
}
}
}
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
if(saveEdges) {
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
}
}
return removedEdges;
}
//Remove edges for pairs where overlap size is significantly lower than the well occupancy
public static List<Integer[]> filterByOverlapPercent(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
static List<Integer[]> filterByOverlapPercent(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
Map<Integer, Integer> alphaWellCounts,
Map<Integer, Integer> betaWellCounts,
Map<Integer, Integer> plateVtoAMap,
Map<Integer, Integer> plateVtoBMap,
Integer minOverlapPercent) {
Integer minOverlapPercent,
boolean saveEdges) {
List<Integer[]> removedEdges = new ArrayList<>();
for (DefaultWeightedEdge e : graph.edgeSet()) {
Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
@@ -66,20 +81,27 @@ public abstract class GraphModificationFunctions {
double weight = graph.getEdgeWeight(e);
double min = minOverlapPercent / 100.0;
if ((weight / alphaOcc < min) || (weight / betaOcc < min)) {
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer intWeight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, intWeight};
removedEdges.add(edge);
if(saveEdges) {
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer intWeight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, intWeight};
removedEdges.add(edge);
}
else {
graph.setEdgeWeight(e, 0.0);
}
}
}
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
if(saveEdges) {
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
}
}
return removedEdges;
}
public static void addRemovedEdges(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
static void addRemovedEdges(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
List<Integer[]> removedEdges) {
for (Integer[] edge : removedEdges) {
DefaultWeightedEdge e = graph.addEdge(edge[0], edge[1]);

View File

@@ -11,7 +11,7 @@ public class GraphWithMapData implements java.io.Serializable {
private String sourceFilename;
private final SimpleWeightedGraph graph;
private Integer numWells;
private Integer[] wellConcentrations;
private Integer[] wellPopulations;
private Integer alphaCount;
private Integer betaCount;
private final Map<Integer, Integer> distCellsMapAlphaKey;
@@ -31,7 +31,7 @@ public class GraphWithMapData implements java.io.Serializable {
Map<Integer, Integer> betaWellCounts, Duration time) {
this.graph = graph;
this.numWells = numWells;
this.wellConcentrations = wellConcentrations;
this.wellPopulations = wellConcentrations;
this.alphaCount = alphaCount;
this.betaCount = betaCount;
this.distCellsMapAlphaKey = distCellsMapAlphaKey;
@@ -52,8 +52,8 @@ public class GraphWithMapData implements java.io.Serializable {
return numWells;
}
public Integer[] getWellConcentrations() {
return wellConcentrations;
public Integer[] getWellPopulations() {
return wellPopulations;
}
public Integer getAlphaCount() {

View File

@@ -1,14 +1,15 @@
import java.io.IOException;
import java.util.List;
import java.util.Scanner;
import java.util.InputMismatchException;
import java.util.*;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
//
public class InteractiveInterface {
final static Scanner sc = new Scanner(System.in);
static int input;
static boolean quit = false;
private static final Random rand = BiGpairSEQ.getRand();
private static final Scanner sc = new Scanner(System.in);
private static int input;
private static boolean quit = false;
public static void startInteractive() {
@@ -26,6 +27,7 @@ public class InteractiveInterface {
//Need to re-do the CDR3/CDR1 matching to correspond to new pattern
//System.out.println("5) Generate CDR3/CDR1 occupancy graph");
//System.out.println("6) Simulate CDR3/CDR1 T cell matching");
System.out.println("8) Options");
System.out.println("9) About/Acknowledgments");
System.out.println("0) Exit");
try {
@@ -36,9 +38,10 @@ public class InteractiveInterface {
case 3 -> makeCDR3Graph();
case 4 -> matchCDR3s();
//case 6 -> matchCellsCDR1();
case 8 -> mainOptions();
case 9 -> acknowledge();
case 0 -> quit = true;
default -> throw new InputMismatchException("Invalid input.");
default -> System.out.println("Invalid input.");
}
} catch (InputMismatchException | IOException ex) {
System.out.println(ex);
@@ -73,9 +76,13 @@ public class InteractiveInterface {
}
CellSample sample = Simulator.generateCellSample(numCells, cdr1Freq);
assert filename != null;
System.out.println("Writing cells to file");
CellFileWriter writer = new CellFileWriter(filename, sample);
writer.writeCellsToFile();
System.gc();
System.out.println("Cell sample written to: " + filename);
if(BiGpairSEQ.cacheCells()) {
BiGpairSEQ.setCellSampleInMemory(sample, filename);
}
}
//Output a CSV of sample plate
@@ -85,7 +92,7 @@ public class InteractiveInterface {
Double stdDev = 0.0;
Integer numWells = 0;
Integer numSections;
Integer[] concentrations = {1};
Integer[] populations = {1};
Double dropOutRate = 0.0;
boolean poisson = false;
boolean exponential = false;
@@ -124,10 +131,11 @@ public class InteractiveInterface {
}
case 3 -> {
exponential = true;
System.out.println("Please enter lambda value for exponential distribution.");
System.out.print("Please enter lambda value for exponential distribution: ");
lambda = sc.nextDouble();
if (lambda <= 0.0) {
throw new InputMismatchException("Value must be positive.");
lambda = 0.6;
System.out.println("Value must be positive. Defaulting to 0.6.");
}
}
default -> {
@@ -140,22 +148,57 @@ public class InteractiveInterface {
if(numWells < 1){
throw new InputMismatchException("No wells on plate");
}
System.out.println("\nThe plate can be evenly sectioned to allow multiple concentrations of T-cells/well");
System.out.println("How many sections would you like to make (minimum 1)?");
numSections = sc.nextInt();
if(numSections < 1) {
throw new InputMismatchException("Too few sections.");
//choose whether to make T cell population/well random
boolean randomWellPopulations;
System.out.println("Randomize number of T cells in each well? (y/n)");
String ans = sc.next();
Pattern pattern = Pattern.compile("(?:yes|y)", Pattern.CASE_INSENSITIVE);
Matcher matcher = pattern.matcher(ans);
if(matcher.matches()){
randomWellPopulations = true;
}
else if (numSections > numWells) {
throw new InputMismatchException("Cannot have more sections than wells.");
else{
randomWellPopulations = false;
}
int i = 1;
concentrations = new Integer[numSections];
while(numSections > 0) {
System.out.print("Enter number of T-cells per well in section " + i +": ");
concentrations[i - 1] = sc.nextInt();
i++;
numSections--;
if(randomWellPopulations) { //if T cell population/well is random
numSections = numWells;
Integer minPop;
Integer maxPop;
System.out.print("Please enter minimum number of T cells in a well: ");
minPop = sc.nextInt();
if(minPop < 1) {
throw new InputMismatchException("Minimum well population must be positive");
}
System.out.println("Please enter maximum number of T cells in a well: ");
maxPop = sc.nextInt();
if(maxPop < minPop) {
throw new InputMismatchException("Max well population must be greater than min well population");
}
//maximum should be inclusive, so need to add one to max of randomly generated values
populations = rand.ints(minPop, maxPop + 1)
.limit(numSections)
.boxed()
.toArray(Integer[]::new);
System.out.print("Populations: ");
System.out.println(Arrays.toString(populations));
}
else{ //if T cell population/well is not random
System.out.println("\nThe plate can be evenly sectioned to allow different numbers of T cells per well.");
System.out.println("How many sections would you like to make (minimum 1)?");
numSections = sc.nextInt();
if (numSections < 1) {
throw new InputMismatchException("Too few sections.");
} else if (numSections > numWells) {
throw new InputMismatchException("Cannot have more sections than wells.");
}
int i = 1;
populations = new Integer[numSections];
while (numSections > 0) {
System.out.print("Enter number of T cells per well in section " + i + ": ");
populations[i - 1] = sc.nextInt();
i++;
numSections--;
}
}
System.out.println("\nErrors in amplification can induce a well dropout rate for sequences");
System.out.print("Enter well dropout rate (0.0 to 1.0): ");
@@ -167,27 +210,40 @@ public class InteractiveInterface {
System.out.println(ex);
sc.next();
}
System.out.println("Reading Cell Sample file: " + cellFile);
assert cellFile != null;
CellFileReader cellReader = new CellFileReader(cellFile);
CellSample cells;
if (cellFile.equals(BiGpairSEQ.getCellFilename())){
cells = BiGpairSEQ.getCellSampleInMemory();
}
else {
System.out.println("Reading Cell Sample file: " + cellFile);
CellFileReader cellReader = new CellFileReader(cellFile);
cells = cellReader.getCellSample();
if(BiGpairSEQ.cacheCells()) {
BiGpairSEQ.setCellSampleInMemory(cells, cellFile);
}
}
assert filename != null;
Plate samplePlate;
PlateFileWriter writer;
if(exponential){
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWellsExponential(cellReader.getFilename(), cellReader.getCells(), lambda);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
samplePlate = new Plate(numWells, dropOutRate, populations);
samplePlate.fillWellsExponential(cellFile, cells.getCells(), lambda);
writer = new PlateFileWriter(filename, samplePlate);
}
else {
if (poisson) {
stdDev = Math.sqrt(cellReader.getCellCount()); //gaussian with square root of elements approximates poisson
stdDev = Math.sqrt(cells.getCellCount()); //gaussian with square root of elements approximates poisson
}
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getCells(), stdDev);
assert filename != null;
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
System.out.println("Writing Sample Plate to file");
writer.writePlateFile();
System.out.println("Sample Plate written to file: " + filename);
System.gc();
samplePlate = new Plate(numWells, dropOutRate, populations);
samplePlate.fillWells(cellFile, cells.getCells(), stdDev);
writer = new PlateFileWriter(filename, samplePlate);
}
System.out.println("Writing Sample Plate to file");
writer.writePlateFile();
System.out.println("Sample Plate written to file: " + filename);
if(BiGpairSEQ.cachePlate()) {
BiGpairSEQ.setPlateInMemory(samplePlate, filename);
}
}
@@ -212,14 +268,37 @@ public class InteractiveInterface {
System.out.println(ex);
sc.next();
}
System.out.println("Reading Cell Sample file: " + cellFile);
assert cellFile != null;
CellFileReader cellReader = new CellFileReader(cellFile);
System.out.println("Reading Sample Plate file: " + plateFile);
CellSample cellSample;
//check if cells are already in memory
if(cellFile.equals(BiGpairSEQ.getCellFilename()) && BiGpairSEQ.getCellSampleInMemory() != null) {
cellSample = BiGpairSEQ.getCellSampleInMemory();
}
else {
System.out.println("Reading Cell Sample file: " + cellFile);
CellFileReader cellReader = new CellFileReader(cellFile);
cellSample = cellReader.getCellSample();
if(BiGpairSEQ.cacheCells()) {
BiGpairSEQ.setCellSampleInMemory(cellSample, cellFile);
}
}
assert plateFile != null;
PlateFileReader plateReader = new PlateFileReader(plateFile);
Plate plate = new Plate(plateReader.getFilename(), plateReader.getWells());
if (cellReader.getCells().size() == 0){
Plate plate;
//check if plate is already in memory
if(plateFile.equals(BiGpairSEQ.getPlateFilename())){
plate = BiGpairSEQ.getPlateInMemory();
}
else {
System.out.println("Reading Sample Plate file: " + plateFile);
PlateFileReader plateReader = new PlateFileReader(plateFile);
plate = new Plate(plateReader.getFilename(), plateReader.getWells());
if(BiGpairSEQ.cachePlate()) {
BiGpairSEQ.setPlateInMemory(plate, plateFile);
}
}
if (cellSample.getCells().size() == 0){
System.out.println("No cell sample found.");
System.out.println("Returning to main menu.");
}
@@ -228,13 +307,16 @@ public class InteractiveInterface {
System.out.println("Returning to main menu.");
}
else{
List<Integer[]> cells = cellReader.getCells();
List<Integer[]> cells = cellSample.getCells();
GraphWithMapData data = Simulator.makeGraph(cells, plate, true);
assert filename != null;
GraphDataObjectWriter dataWriter = new GraphDataObjectWriter(filename, data);
dataWriter.writeDataToFile();
System.out.println("Graph and Data file written to: " + filename);
System.gc();
if(BiGpairSEQ.cacheGraph()) {
BiGpairSEQ.setGraphInMemory(data, filename);
}
}
}
@@ -256,17 +338,28 @@ public class InteractiveInterface {
System.out.println("\nWhat is the minimum number of CDR3 alpha/beta overlap wells to attempt matching?");
lowThreshold = sc.nextInt();
if(lowThreshold < 1){
throw new InputMismatchException("Minimum value for low threshold set to 1");
lowThreshold = 1;
System.out.println("Value for low occupancy overlap threshold must be positive");
System.out.println("Value for low occupancy overlap threshold set to 1");
}
System.out.println("\nWhat is the maximum number of CDR3 alpha/beta overlap wells to attempt matching?");
highThreshold = sc.nextInt();
System.out.println("\nWhat is the maximum difference in alpha/beta occupancy to attempt matching?");
maxOccupancyDiff = sc.nextInt();
System.out.println("\nWell overlap percentage = pair overlap / sequence occupancy");
System.out.println("What is the minimum well overlap percentage to attempt matching? (0 to 100)");
if(highThreshold < lowThreshold) {
highThreshold = lowThreshold;
System.out.println("Value for high occupancy overlap threshold must be >= low overlap threshold");
System.out.println("Value for high occupancy overlap threshold set to " + lowThreshold);
}
System.out.println("What is the minimum percentage of a sequence's wells in alpha/beta overlap to attempt matching? (0 - 100)");
minOverlapPercent = sc.nextInt();
if (minOverlapPercent < 0 || minOverlapPercent > 100) {
throw new InputMismatchException("Value outside range. Minimum percent set to 0");
System.out.println("Value outside range. Minimum occupancy overlap percentage set to 0");
}
System.out.println("\nWhat is the maximum difference in alpha/beta occupancy to attempt matching?");
maxOccupancyDiff = sc.nextInt();
if (maxOccupancyDiff < 0) {
maxOccupancyDiff = 0;
System.out.println("Maximum allowable difference in alpha/beta occupancy must be nonnegative");
System.out.println("Maximum allowable difference in alpha/beta occupancy set to 0");
}
} catch (InputMismatchException ex) {
System.out.println(ex);
@@ -275,17 +368,15 @@ public class InteractiveInterface {
assert graphFilename != null;
//check if this is the same graph we already have in memory.
GraphWithMapData data;
if(!(graphFilename.equals(BiGpairSEQ.getGraphFilename())) || BiGpairSEQ.getGraph() == null) {
BiGpairSEQ.clearGraph();
//read object data from file
GraphDataObjectReader dataReader = new GraphDataObjectReader(graphFilename);
data = dataReader.getData();
//set new graph in memory and new filename
BiGpairSEQ.setGraph(data);
BiGpairSEQ.setGraphFilename(graphFilename);
if(graphFilename.equals(BiGpairSEQ.getGraphFilename())) {
data = BiGpairSEQ.getGraphInMemory();
}
else {
data = BiGpairSEQ.getGraph();
GraphDataObjectReader dataReader = new GraphDataObjectReader(graphFilename);
data = dataReader.getData();
if(BiGpairSEQ.cacheGraph()) {
BiGpairSEQ.setGraphInMemory(data, graphFilename);
}
}
//simulate matching
MatchingResult results = Simulator.matchCDR3s(data, graphFilename, lowThreshold, highThreshold, maxOccupancyDiff,
@@ -296,7 +387,6 @@ public class InteractiveInterface {
System.out.println("Writing results to file");
writer.writeResultsToFile();
System.out.println("Results written to file: " + filename);
System.gc();
}
///////
@@ -403,6 +493,75 @@ public class InteractiveInterface {
// }
// }
private static void mainOptions(){
boolean backToMain = false;
while(!backToMain) {
System.out.println("\n--------------OPTIONS---------------");
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("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");
try {
input = sc.nextInt();
switch (input) {
case 1 -> BiGpairSEQ.setCacheCells(!BiGpairSEQ.cacheCells());
case 2 -> BiGpairSEQ.setCachePlate(!BiGpairSEQ.cachePlate());
case 3 -> BiGpairSEQ.setCacheGraph(!BiGpairSEQ.cacheGraph());
case 4 -> algorithmOptions();
case 0 -> backToMain = true;
default -> System.out.println("Invalid input");
}
} catch (InputMismatchException ex) {
System.out.println(ex);
sc.next();
}
}
}
/**
* 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) {
if (b) { return "on";}
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(){
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.");

View File

@@ -10,7 +10,7 @@ import java.util.*;
public class Plate {
private String sourceFile;
private List<List<Integer[]>> wells;
private Random rand = new Random();
private final Random rand = BiGpairSEQ.getRand();
private int size;
private double error;
private Integer[] populations;
@@ -51,7 +51,6 @@ public class Plate {
int section = 0;
double m;
int n;
int test=0;
while (section < numSections){
for (int i = 0; i < (size / numSections); i++) {
List<Integer[]> well = new ArrayList<>();
@@ -61,13 +60,6 @@ public class Plate {
m = (Math.log10((1 - rand.nextDouble()))/(-lambda)) * Math.sqrt(cells.size());
} while (m >= cells.size() || m < 0);
n = (int) Math.floor(m);
//n = Equations.getRandomNumber(0, cells.size());
// was testing generating the cell sample file with exponential dist, then sampling flat here
//that would be more realistic
//But would mess up other things in the simulation with how I've coded it.
if(n > test){
test = n;
}
Integer[] cellToAdd = cells.get(n).clone();
for(int k = 0; k < cellToAdd.length; k++){
if(Math.abs(rand.nextDouble()) < error){//error applied to each seqeunce
@@ -80,7 +72,6 @@ public class Plate {
}
section++;
}
System.out.println("Highest index: " +test);
}
public void fillWells(String sourceFileName, List<Integer[]> cells, double stdDev) {

View File

@@ -16,7 +16,7 @@ public class PlateFileWriter {
private Double error;
private String filename;
private String sourceFileName;
private Integer[] concentrations;
private Integer[] populations;
private boolean isExponential = false;
public PlateFileWriter(String filename, Plate plate) {
@@ -35,8 +35,8 @@ public class PlateFileWriter {
}
this.error = plate.getError();
this.wells = plate.getWells();
this.concentrations = plate.getPopulations();
Arrays.sort(concentrations);
this.populations = plate.getPopulations();
Arrays.sort(populations);
}
public void writePlateFile(){
@@ -73,14 +73,12 @@ public class PlateFileWriter {
// rows.add(tmp);
// }
//get list of well populations
List<Integer> wellPopulations = Arrays.asList(concentrations);
//make string out of populations list
//make string out of populations array
StringBuilder populationsStringBuilder = new StringBuilder();
populationsStringBuilder.append(wellPopulations.remove(0).toString());
for(Integer i: wellPopulations){
populationsStringBuilder.append(populations[0].toString());
for(int i = 1; i < populations.length; i++){
populationsStringBuilder.append(", ");
populationsStringBuilder.append(i.toString());
populationsStringBuilder.append(populations[i].toString());
}
String wellPopulationsString = populationsStringBuilder.toString();

View File

@@ -1,9 +1,9 @@
import org.jgrapht.Graph;
import org.jgrapht.alg.interfaces.MatchingAlgorithm;
import org.jgrapht.alg.matching.MaximumWeightBipartiteMatching;
import org.jgrapht.generate.SimpleWeightedBipartiteGraphMatrixGenerator;
import org.jgrapht.graph.DefaultWeightedEdge;
import org.jgrapht.graph.SimpleWeightedGraph;
import org.jheaps.tree.FibonacciHeap;
import org.jheaps.tree.PairingHeap;
import java.math.BigDecimal;
@@ -14,8 +14,10 @@ import java.time.Duration;
import java.util.*;
import java.util.stream.IntStream;
import static java.lang.Float.*;
//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 cdr3BetaIndex = 1;
private static final int cdr1AlphaIndex = 2;
@@ -145,8 +147,8 @@ public class Simulator {
Integer highThreshold, Integer maxOccupancyDifference,
Integer minOverlapPercent, boolean verbose) {
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<>();
boolean saveEdges = BiGpairSEQ.cacheGraph();
int numWells = data.getNumWells();
Integer alphaCount = data.getAlphaCount();
Integer betaCount = data.getBetaCount();
@@ -159,33 +161,50 @@ public class Simulator {
//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");}
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");}
//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() +
" percent of vertex occupancy value.");}
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");}
//Filter by relative occupancy
if(verbose){System.out.println("Eliminating edges between vertices with occupancy difference > "
+ maxOccupancyDifference);}
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 " +
"removed");}
//Find Maximum Weighted Matching
//using jheaps library class PairingHeap for improved efficiency
if(verbose){System.out.println("Finding maximum weighted matching");}
//Attempting to use addressable heap to improve performance
MaximumWeightBipartiteMatching maxWeightMatching =
new MaximumWeightBipartiteMatching(graph,
MaximumWeightBipartiteMatching maxWeightMatching;
//Use correct heap type for priority queue
String heapType = BiGpairSEQ.getPriorityQueueHeapType();
switch (heapType) {
case "PAIRING" -> {
maxWeightMatching = new MaximumWeightBipartiteMatching(graph,
plateVtoAMap.keySet(),
plateVtoBMap.keySet(),
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();
if(verbose){System.out.println("Matching completed");}
Instant stop = Instant.now();
@@ -247,10 +266,16 @@ public class Simulator {
BigDecimal attemptRateTrunc = new BigDecimal(attemptRate, mc);
//rate of pairing error
double pairingErrorRate = (double) falseCount / (trueCount + falseCount);
BigDecimal pairingErrorRateTrunc = new BigDecimal(pairingErrorRate, mc);
//get list of well concentrations
Integer[] wellPopulations = data.getWellConcentrations();
//make string out of concentrations list
BigDecimal pairingErrorRateTrunc;
if(pairingErrorRate == NaN || pairingErrorRate == POSITIVE_INFINITY || pairingErrorRate == NEGATIVE_INFINITY) {
pairingErrorRateTrunc = new BigDecimal(-1, mc);
}
else{
pairingErrorRateTrunc = new BigDecimal(pairingErrorRate, mc);
}
//get list of well populations
Integer[] wellPopulations = data.getWellPopulations();
//make string out of populations list
StringBuilder populationsStringBuilder = new StringBuilder();
populationsStringBuilder.append(wellPopulations[0].toString());
for(int i = 1; i < wellPopulations.length; i++){
@@ -270,8 +295,8 @@ public class Simulator {
metadata.put("total betas found", betaCount.toString());
metadata.put("high overlap threshold", highThreshold.toString());
metadata.put("low overlap threshold", lowThreshold.toString());
metadata.put("maximum occupancy difference", maxOccupancyDifference.toString());
metadata.put("minimum overlap percent", minOverlapPercent.toString());
metadata.put("maximum occupancy difference", maxOccupancyDifference.toString());
metadata.put("pairing attempt rate", attemptRateTrunc.toString());
metadata.put("correct pairing count", Integer.toString(trueCount));
metadata.put("incorrect pairing count", Integer.toString(falseCount));
@@ -285,10 +310,11 @@ public class Simulator {
}
}
//put the removed edges back on the graph
System.out.println("Restoring removed edges to graph.");
GraphModificationFunctions.addRemovedEdges(graph, removedEdges);
if(saveEdges) {
//put the removed edges back on the graph
System.out.println("Restoring removed edges to graph.");
GraphModificationFunctions.addRemovedEdges(graph, removedEdges);
}
//return MatchingResult object
return output;
}