/**
* Performs Principal Component Analysis on given sequences
*/
-public class PCA implements Runnable
+public class PCA implements Runnable, SpatialCalculationI
{
/*
* inputs
@Override
public void run()
{
+ isCancelled=false;
try
{
/*
* sequence pairwise similarity scores
*/
pairwiseScores = scoreModel.findSimilarities(seqs, similarityParams);
-
+ if (isCancelled())
+ {
+ pairwiseScores=null;
+ return;
+ }
/*
* tridiagonal matrix
*/
+
tridiagonal = pairwiseScores.copy();
+ if (isCancelled()) {
+ clearResults();
+ return;
+ }
tridiagonal.tred();
-
+ if (isCancelled()) {
+ clearResults();
+ return;
+ }
/*
* the diagonalization matrix
*/
eigenMatrix = tridiagonal.copy();
+ if (isCancelled()) {
+ clearResults();
+ return;
+ }
eigenMatrix.tqli();
+ if (isCancelled()) {
+ clearResults();
+ return;
+ }
} catch (Exception q)
{
Console.error("Error computing PCA: " + q.getMessage());
q.printStackTrace();
}
}
-
+ private void clearResults()
+ {
+ pairwiseScores = null;
+ tridiagonal = null;
+ eigenMatrix = null;
+ }
/**
* Returns a PrintStream that wraps (appends its output to) the given
* StringBuilder
// TODO can any of seqs[] be null?
return pairwiseScores.height();// seqs.getSequences().length;
}
-
+ @Override
+ public int getWidth()
+ {
+ return getHeight();
+ }
+ @Override
+ public int getDim()
+ {
+ return component(1).length;
+ }
+ public int getTop()
+ {
+ return pairwiseScores.height()-1;
+ }
/**
* Answers the sequence pairwise similarity scores which were the first step
* of the PCA calculation
{
this.tridiagonal = tridiagonal;
}
+
+ volatile boolean isCancelled = false;
+ @Override
+ public void cancel()
+ {
+ isCancelled = true;
+ }
+ @Override
+ public boolean isCancellable()
+ {
+ return true;
+ }
+ @Override
+ public boolean isCancelled()
+ {
+ return isCancelled;
+ }
+ @Override
+ public String getAlignmentOutput()
+ {
+ // TODO Auto-generated method stub
+ return null;
+ }
+
+
}
*
* @AUTHOR MorellThomas
*/
-public class PaSiMap implements Runnable
+public class PaSiMap implements Runnable,SpatialCalculationI
{
/*
* inputs
// TODO can any of seqs[] be null?
return eigenMatrix.width();// seqs.getSequences().length;
}
+
+ public int getTop()
+ {
+ return getWidth()-1;
+ }
/**
* Answers the sequence pairwise similarity scores which were the first step
return alignment.getAlignmentOutput();
}
- public byte getDim()
+ public int getDim()
{
return dim;
}
--- /dev/null
+package jalview.analysis;
+
+import jalview.datamodel.Point;
+
+public interface SpatialCalculationI
+{
+
+ void run();
+
+ boolean isCancelled();
+
+ int getHeight();
+
+ int getWidth();
+
+ Point[] getComponents(int i, int j, int k, float f);
+
+ int getDim();
+
+ String getAlignmentOutput();
+
+ String getDetails();
+
+ double[] component(int s);
+
+ void cancel();
+
+ boolean isCancellable();
+
+ int getTop();
+
+}
/**
* The panel holding the Principal Component Analysis 3-D visualisation
*/
-public class PCAPanel extends GPCAPanel
+public class PCAPanel extends SpatialPanel
implements Runnable, IProgressIndicator
{
private static final int MIN_WIDTH = 470;
import jalview.datamodel.SequenceI;
import jalview.gui.ImageExporter.ImageWriterI;
import jalview.gui.JalviewColourChooser.ColourChooserListener;
-import jalview.jbgui.GPaSiMapPanel;
+import jalview.jbgui.GPCAPanel;
import jalview.math.RotatableMatrix.Axis;
import jalview.util.ImageMaker;
import jalview.util.MessageManager;
/**
* The panel holding the Pairwise Similarity Map 3-D visualisation
*/
-public class PaSiMapPanel extends GPaSiMapPanel
+public class PaSiMapPanel extends SpatialPanel
implements Runnable, IProgressIndicator
{
private static final int MIN_WIDTH = 470;
{
}
- Object[] alAndColsel = getPasimapModel().getInputData()
- .getAlignmentView(false).getAlignmentAndHiddenColumns(gc);
+ // TODO - this possibly now does compeltely the wrong thing - returns the alignment view for the model, which may be spurious
+ Object[] alAndColsel = getPasimapModel().getInputData().getAlignmentAndHiddenColumns(gc);
if (alAndColsel != null && alAndColsel[0] != null)
{
--- /dev/null
+/*
+ * Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
+ * Copyright (C) $$Year-Rel$$ The Jalview Authors
+ *
+ * This file is part of Jalview.
+ *
+ * Jalview is free software: you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation, either version 3
+ * of the License, or (at your option) any later version.
+ *
+ * Jalview is distributed in the hope that it will be useful, but
+ * WITHOUT ANY WARRANTY; without even the implied warranty
+ * of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+ * PURPOSE. See the GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with Jalview. If not, see <http://www.gnu.org/licenses/>.
+ * The Jalview Authors are detailed in the 'AUTHORS' file.
+ */
+package jalview.gui;
+
+import jalview.jbgui.GPCAPanel;
+
+/**
+ * Base panel holding spatial projections
+ */
+
+public class SpatialPanel extends GPCAPanel
+{
+
+ public SpatialPanel()
+ {
+ this(8);
+ }
+ public SpatialPanel(int dim)
+ {
+ super(dim);
+ }
+}
protected JMenuItem originalSeqData;
+ protected JMenuItem outputAlignment;
+
/**
* Constructor
*/
public GPCAPanel()
{
- try
- {
- jbInit();
- } catch (Exception e)
- {
- e.printStackTrace();
- }
-
- for (int i = 1; i < 8; i++)
- {
- xCombobox.addItem("dim " + i);
- yCombobox.addItem("dim " + i);
- zCombobox.addItem("dim " + i);
- }
+ this(8);
}
public GPCAPanel(int dim)
private void jbInit() throws Exception
{
setFrameIcon(null);
- setName("jalview-pca");
+ setName("jalview-"+this.getClass().getName());
this.getContentPane().setLayout(new BorderLayout());
JPanel jPanel2 = new JPanel();
jPanel2.setLayout(new FlowLayout());
print_actionPerformed();
}
});
+ outputAlignment = new JMenuItem();
+ outputAlignment
+ .setText(MessageManager.getString("label.output_alignment"));
+ outputAlignment.addActionListener(new ActionListener()
+ {
+ @Override
+ public void actionPerformed(ActionEvent e)
+ {
+ outputAlignment_actionPerformed();
+ }
+ });
viewMenu.setText(MessageManager.getString("action.view"));
viewMenu.addMenuListener(new MenuListener()
{
fileMenu.add(originalSeqData);
fileMenu.add(outputPoints);
fileMenu.add(outputProjPoints);
+ fileMenu.add(outputAlignment);
saveMenu.add(eps);
saveMenu.add(png);
viewMenu.add(showLabels);
{
}
+ protected void outputAlignment_actionPerformed()
+ {
+ }
+
public void makePCAImage(TYPE imageType)
{
}
import java.util.List;
import java.util.Vector;
-public class PCAModel
+public class PCAModel extends SpatialModel<PCA>
{
- /*
- * inputs
- */
- private AlignmentView inputData;
-
- private final SequenceI[] seqs;
-
- private final SimilarityParamsI similarityParams;
-
- /*
- * options - score model, nucleotide / protein
- */
- private ScoreModelI scoreModel;
-
- private boolean nucleotide = false;
-
- /*
- * outputs
- */
- private PCA pca;
-
- int top;
-
- private List<SequencePoint> points;
-
- /**
- * Constructor given sequence data, score model and score calculation
- * parameter options.
- *
- * @param seqData
- * @param sqs
- * @param nuc
- * @param modelName
- * @param params
- */
- public PCAModel(AlignmentView seqData, SequenceI[] sqs, boolean nuc,
- ScoreModelI modelName, SimilarityParamsI params)
- {
- inputData = seqData;
- seqs = sqs;
- nucleotide = nuc;
- scoreModel = modelName;
- similarityParams = params;
- }
-
- /**
- * Performs the PCA calculation (in the same thread) and extracts result data
- * needed for visualisation by PCAPanel
- */
- public void calculate()
- {
- pca = new PCA(inputData, scoreModel, similarityParams);
- pca.run(); // executes in same thread, wait for completion
-
- // Now find the component coordinates
- int ii = 0;
-
- while ((ii < seqs.length) && (seqs[ii] != null))
- {
- ii++;
- }
-
- int height = pca.getHeight();
- // top = pca.getM().height() - 1;
- top = height - 1;
-
- points = new Vector<>();
- Point[] scores = pca.getComponents(top - 1, top - 2, top - 3, 1);
-
- for (int i = 0; i < height; i++)
- {
- SequencePoint sp = new SequencePoint(seqs[i], scores[i]);
- points.add(sp);
- }
- }
-
- public void updateRc(RotatableCanvasI rc)
- {
- rc.setPoints(points, pca.getHeight());
- }
-
- public boolean isNucleotide()
- {
- return nucleotide;
- }
-
- public void setNucleotide(boolean nucleotide)
- {
- this.nucleotide = nucleotide;
- }
-
- /**
- * Answers the index of the principal dimension of the PCA
- *
- * @return
- */
- public int getTop()
- {
- return top;
- }
-
- public void setTop(int t)
- {
- top = t;
- }
-
- /**
- * Updates the 3D coordinates for the list of points to the given dimensions.
- * Principal dimension is getTop(). Next greatest eigenvector is getTop()-1.
- * Note - pca.getComponents starts counting the spectrum from rank-2 to zero,
- * rather than rank-1, so getComponents(dimN ...) == updateRcView(dimN+1 ..)
- *
- * @param dim1
- * @param dim2
- * @param dim3
- */
- public void updateRcView(int dim1, int dim2, int dim3)
- {
- // note: actual indices for components are dim1-1, etc (patch for JAL-1123)
- Point[] scores = pca.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 1);
-
- for (int i = 0; i < pca.getHeight(); i++)
- {
- points.get(i).coord = scores[i];
- }
- }
-
- public String getDetails()
+ @Override
+ public PCA constructModel()
{
- return pca.getDetails();
+ return new PCA(inputData,scoreModel,similarityParams);
}
-
- public AlignmentView getInputData()
+ public PCAModel(AlignmentView seqData, SequenceI[] sqs, boolean nuc,
+ ScoreModelI modelName, SimilarityParamsI params)
{
- return inputData;
+ super(null, seqData,sqs, nuc,modelName, params);
}
-
public void setInputData(AlignmentView data)
{
inputData = data;
}
-
- public String getPointsasCsv(boolean transformed, int xdim, int ydim,
- int zdim)
- {
- StringBuffer csv = new StringBuffer();
- csv.append("\"Sequence\"");
- if (transformed)
- {
- csv.append(",");
- csv.append(xdim);
- csv.append(",");
- csv.append(ydim);
- csv.append(",");
- csv.append(zdim);
- }
- else
- {
- for (int d = 1, dmax = pca.component(1).length; d <= dmax; d++)
- {
- csv.append("," + d);
- }
- }
- csv.append("\n");
- for (int s = 0; s < seqs.length; s++)
- {
- csv.append("\"" + seqs[s].getName() + "\"");
- double fl[];
- if (!transformed)
- {
- // output pca in correct order
- fl = pca.component(s);
- for (int d = fl.length - 1; d >= 0; d--)
- {
- csv.append(",");
- csv.append(fl[d]);
- }
- }
- else
- {
- Point p = points.get(s).coord;
- csv.append(",").append(p.x);
- csv.append(",").append(p.y);
- csv.append(",").append(p.z);
- }
- csv.append("\n");
- }
- return csv.toString();
- }
-
- public String getScoreModelName()
- {
- return scoreModel == null ? "" : scoreModel.getName();
- }
-
- public void setScoreModel(ScoreModelI sm)
- {
- this.scoreModel = sm;
- }
-
- /**
- * Answers the parameters configured for pairwise similarity calculations
- *
- * @return
- */
- public SimilarityParamsI getSimilarityParameters()
- {
- return similarityParams;
- }
-
- public List<SequencePoint> getSequencePoints()
- {
- return points;
- }
-
- public void setSequencePoints(List<SequencePoint> sp)
- {
- points = sp;
- }
-
- /**
- * Answers the object holding the values of the computed PCA
- *
- * @return
- */
public PCA getPcaData()
{
- return pca;
+ return outputModel;
}
-
- public void setPCA(PCA data)
+ public void setPCA(PCA pca)
{
- pca = data;
+ outputModel = pca;
}
}
*/
package jalview.viewmodel;
+import jalview.analysis.PCA;
import jalview.analysis.PaSiMap;
import jalview.api.RotatableCanvasI;
import jalview.api.analysis.ScoreModelI;
import java.util.List;
import java.util.Vector;
-public class PaSiMapModel
+public class PaSiMapModel extends SpatialModel<PaSiMap>
{
- /*
- * inputs
- */
- private AlignmentViewport inputData;
-
- private final SequenceI[] seqs;
-
- /*
- * options - score model, nucleotide / protein
- */
- private ScoreModelI scoreModel;
-
- private boolean nucleotide = false;
-
- /*
- * outputs
- */
- private PaSiMap pasimap;
-
- int top;
-
- private List<SequencePoint> points;
-
- /**
- * Constructor given sequence data, score model and score calculation
- * parameter options.
- *
- * @param seqData
- * @param sqs
- * @param nuc
- * @param modelName
- * @param params
- */
+ PairwiseAlignPanel pap = null;
+ @Override
+ public PaSiMap constructModel()
+ {
+ return new PaSiMap(av, scoreModel, pap);
+ }
public PaSiMapModel(AlignmentViewport seqData, SequenceI[] sqs,
boolean nuc, ScoreModelI modelName)
{
- inputData = seqData;
- seqs = sqs;
- nucleotide = nuc;
- scoreModel = modelName;
+ super(seqData,null,sqs,nuc, modelName,null);
}
/**
*/
public void calculate(PairwiseAlignPanel pap)
{
- pasimap = new PaSiMap(inputData, scoreModel, pap);
- pasimap.run(); // executes in same thread, wait for completion
- if (pasimap.isCancelled())
- {
- // no more work to do
- return;
- }
-
- // Now find the component coordinates
- int ii = 0;
-
- while ((ii < seqs.length) && (seqs[ii] != null))
- {
- ii++;
- }
-
- int width = pasimap.getWidth();
- int height = pasimap.getHeight();
- top = width;
-
- points = new Vector<>();
- Point[] scores = pasimap.getComponents(width - 1, width - 2, width - 3,
- 1);
-
- for (int i = 0; i < height; i++)
- {
- SequencePoint sp = new SequencePoint(seqs[i], scores[i]);
- points.add(sp);
- }
- }
-
- public void updateRc(RotatableCanvasI rc)
- {
- rc.setPoints(points, pasimap.getHeight());
- }
-
- public boolean isNucleotide()
- {
- return nucleotide;
- }
-
- public void setNucleotide(boolean nucleotide)
- {
- this.nucleotide = nucleotide;
- }
-
- /**
- * Answers the index of the principal dimension of the PaSiMap
- *
- * @return
- */
- public int getTop()
- {
- return top;
- }
-
- public void setTop(int t)
- {
- top = t;
+ this.pap = pap;
+ calculate();
}
-
- /**
- * Updates the 3D coordinates for the list of points to the given dimensions.
- * Principal dimension is getTop(). Next greatest eigenvector is getTop()-1.
- * Note - pasimap.getComponents starts counting the spectrum from rank-2 to
- * zero, rather than rank-1, so getComponents(dimN ...) == updateRcView(dimN+1
- * ..)
- *
- * @param dim1
- * @param dim2
- * @param dim3
- */
- public void updateRcView(int dim1, int dim2, int dim3)
- {
- // note: actual indices for components are dim1-1, etc (patch for JAL-1123)
- Point[] scores = pasimap.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 1);
-
- for (int i = 0; i < pasimap.getHeight(); i++)
- {
- points.get(i).coord = scores[i];
- }
- }
-
- public String getDetails()
- {
- return pasimap.getDetails();
- }
-
- public String getAlignmentOutput()
- {
- return pasimap.getAlignmentOutput();
- }
-
- public AlignmentViewport getInputData()
- {
- return inputData;
- }
-
public void setInputData(AlignmentViewport data)
{
- inputData = data;
- }
-
- public String getPointsasCsv(boolean transformed, int xdim, int ydim,
- int zdim)
- {
- StringBuffer csv = new StringBuffer();
- csv.append("\"Sequence\"");
- if (transformed)
- {
- csv.append(",");
- csv.append(xdim);
- csv.append(",");
- csv.append(ydim);
- csv.append(",");
- csv.append(zdim);
- }
- else
- {
- for (int d = 1, dmax = (int) pasimap.getDim(); d <= dmax; d++)
- {
- csv.append("," + d);
- }
- }
- csv.append("\n");
- for (int s = 0; s < seqs.length; s++)
- {
- csv.append("\"" + seqs[s].getName() + "\"");
- if (!transformed)
- {
- double[] fl = pasimap.component(s);
- for (int d = fl.length - 1; d >= 0; d--)
- {
- csv.append(",");
- csv.append(fl[d]);
- }
- }
- else
- {
- Point p = points.get(s).coord;
- csv.append(",").append(p.x);
- csv.append(",").append(p.y);
- csv.append(",").append(p.z);
- }
- csv.append("\n");
- }
- return csv.toString();
+ av = data;
}
-
- public String getScoreModelName()
- {
- return scoreModel == null ? "" : scoreModel.getName();
- }
-
- public void setScoreModel(ScoreModelI sm)
- {
- this.scoreModel = sm;
- }
-
- public List<SequencePoint> getSequencePoints()
- {
- return points;
- }
-
- public void setSequencePoints(List<SequencePoint> sp)
- {
- points = sp;
- }
-
- /**
- * Answers the object holding the values of the computed PaSiMap
- *
- * @return
- */
public PaSiMap getPasimapData()
{
- return pasimap;
+ return outputModel;
}
-
- public void setPaSiMap(PaSiMap data)
+ public void setPasimapData(PaSiMap pasimapData)
{
- pasimap = data;
+ outputModel = pasimapData;
}
- public boolean isCancelled()
- {
- if (pasimap==null || pasimap.isCancelled())
- {
- return true;
- }
- return false;
- }
-
- public void cancel()
- {
- pasimap.cancel();
- }
-
- public boolean canCancel()
- {
- return (!isCancelled() && pasimap.isCancellable());
- }
}
--- /dev/null
+package jalview.viewmodel;
+
+import java.util.List;
+import java.util.Vector;
+
+import jalview.analysis.SpatialCalculationI;
+import jalview.api.RotatableCanvasI;
+import jalview.api.analysis.ScoreModelI;
+import jalview.api.analysis.SimilarityParamsI;
+import jalview.datamodel.AlignmentView;
+import jalview.datamodel.Point;
+import jalview.datamodel.SequenceI;
+import jalview.datamodel.SequencePoint;
+
+public abstract class SpatialModel<T extends SpatialCalculationI>
+{
+ /*
+ * inputs
+ */
+ protected AlignmentViewport av;
+
+ protected AlignmentView inputData;
+
+ protected final SequenceI[] seqs;
+
+ protected final SimilarityParamsI similarityParams;
+
+ /*
+ * options - score model, nucleotide / protein
+ */
+ protected ScoreModelI scoreModel;
+
+ protected boolean nucleotide = false;
+
+ protected T outputModel;
+
+ private int top;
+
+ private List<SequencePoint> points;
+
+ /**
+ * Constructor given sequence data, score model and score calculation
+ * parameter options.
+ *
+ * @param seqData
+ * @param sqs
+ * @param nuc
+ * @param modelName
+ * @param params
+ */
+ public SpatialModel(AlignmentViewport av, AlignmentView seqData, SequenceI[] sqs, boolean nuc,
+ ScoreModelI modelName, SimilarityParamsI params)
+ {
+ inputData = seqData;
+ seqs = sqs;
+ nucleotide = nuc;
+ scoreModel = modelName;
+ similarityParams = params;
+ }
+
+ public abstract T constructModel();
+
+ public void calculate()
+ {
+ outputModel = constructModel();
+ outputModel.run(); // executes in same thread, wait for completion
+ if (outputModel.isCancelled())
+ {
+ // no more work to do
+ return;
+ }
+
+ // Now find the component coordinates
+// // delete this ?
+// int ii = 0;
+//
+// while ((ii < seqs.length) && (seqs[ii] != null))
+// {
+// ii++;
+// }
+
+ // NB height for PaSiMap is Width.
+ int height = outputModel.getHeight();
+ int width = outputModel.getWidth();
+
+ // top = pca.getM().height() - 1;
+ // top = pasimap.getWidth() - 1;
+ top = outputModel.getTop();
+
+ points = new Vector<>();
+ Point[] scores = outputModel.getComponents(top - 1, top - 2, top - 3, 1f);
+
+ for (int i = 0; i < height; i++)
+ {
+ SequencePoint sp = new SequencePoint(seqs[i], scores[i]);
+ points.add(sp);
+ }
+ }
+
+ public void updateRc(RotatableCanvasI rc)
+ {
+ rc.setPoints(points, outputModel.getHeight());
+ }
+
+ public boolean isNucleotide()
+ {
+ return nucleotide;
+ }
+
+ public void setNucleotide(boolean nucleotide)
+ {
+ this.nucleotide = nucleotide;
+ }
+
+ /**
+ * Answers the index of the principal dimension of the PCA
+ *
+ * @return
+ */
+ public int getTop()
+ {
+ return top;
+ }
+ /** ? used ?
+ *
+ * @param t
+ */
+ public void setTop(int t)
+ {
+ top = t;
+ }
+
+ /**
+ * Updates the 3D coordinates for the list of points to the given dimensions.
+ * Principal dimension is getTop(). Next greatest eigenvector is getTop()-1.
+ * Note - pca.getComponents starts counting the spectrum from rank-2 to zero,
+ * rather than rank-1, so getComponents(dimN ...) == updateRcView(dimN+1 ..)
+ *
+ * @param dim1
+ * @param dim2
+ * @param dim3
+ */
+ public void updateRcView(int dim1, int dim2, int dim3)
+ {
+ // note: actual indices for components are dim1-1, etc (patch for JAL-1123)
+ Point[] scores = outputModel.getComponents(dim1 - 1, dim2 - 1, dim3 - 1, 1);
+
+ for (int i = 0; i < outputModel.getHeight(); i++)
+ {
+ points.get(i).coord = scores[i];
+ }
+ }
+
+ public String getDetails()
+ {
+ return outputModel.getDetails();
+ }
+
+ public String getAlignmentOutput()
+ {
+ return outputModel.getAlignmentOutput();
+ }
+
+ public AlignmentViewport getInputAlignmentView()
+ {
+ return av;
+ }
+ public AlignmentView getInputData()
+ {
+ return inputData;
+ }
+
+ public String getPointsasCsv(boolean transformed, int xdim, int ydim,
+ int zdim)
+ {
+ StringBuffer csv = new StringBuffer();
+ csv.append("\"Sequence\"");
+ if (transformed)
+ {
+ csv.append(",");
+ csv.append(xdim);
+ csv.append(",");
+ csv.append(ydim);
+ csv.append(",");
+ csv.append(zdim);
+ }
+ else
+ {
+ // pca.component(1).length == pasimap.getDim
+ for (int d = 1, dmax = (int) outputModel.getDim(); d <= dmax; d++)
+ {
+ csv.append("," + d);
+ }
+ }
+ csv.append("\n");
+ for (int s = 0; s < seqs.length; s++)
+ {
+ csv.append("\"" + seqs[s].getName() + "\"");
+ if (!transformed)
+ {
+ double[] fl = outputModel.component(s);
+ for (int d = fl.length - 1; d >= 0; d--)
+ {
+ csv.append(",");
+ csv.append(fl[d]);
+ }
+ }
+ else
+ {
+ Point p = points.get(s).coord;
+ csv.append(",").append(p.x);
+ csv.append(",").append(p.y);
+ csv.append(",").append(p.z);
+ }
+ csv.append("\n");
+ }
+ return csv.toString();
+ }
+
+ public String getScoreModelName()
+ {
+ return scoreModel == null ? "" : scoreModel.getName();
+ }
+
+ public void setScoreModel(ScoreModelI sm)
+ {
+ this.scoreModel = sm;
+ }
+
+ /**
+ * Answers the parameters configured for pairwise similarity calculations
+ *
+ * @return
+ */
+ public SimilarityParamsI getSimilarityParameters()
+ {
+ return similarityParams;
+ }
+
+ public List<SequencePoint> getSequencePoints()
+ {
+ return points;
+ }
+
+ public void setSequencePoints(List<SequencePoint> sp)
+ {
+ points = sp;
+ }
+ public T getOutputModel() {
+ return outputModel;
+ }
+ public void setOutputModel(T newModel)
+ {
+ outputModel = newModel;
+ }
+
+ public boolean isCancelled()
+ {
+ if (outputModel==null || outputModel.isCancelled())
+ {
+ return true;
+ }
+ return false;
+ }
+
+ public void cancel()
+ {
+ outputModel.cancel();
+ }
+
+ public boolean canCancel()
+ {
+ return (!isCancelled() && outputModel.isCancellable());
+ }
+
+}
git://source.jalview.org / jalview.git / commitdiff