X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;ds=sidebyside;f=src%2Fjalview%2Fviewmodel%2FPCAModel.java;h=aa7c938a3c8b733b2fc0ba2ded1f28b1c95ba411;hb=cf6ec9416dae77d30b5be628c1112a609ed088fe;hp=324c69a538bb0be5f9e0d886aaa43eb729ea4124;hpb=74c5bd7b1f98214a6d57d7c64d0548013530d397;p=jalview.git

diff --git a/src/jalview/viewmodel/PCAModel.java b/src/jalview/viewmodel/PCAModel.java
index 324c69a..aa7c938 100644
--- a/src/jalview/viewmodel/PCAModel.java
+++ b/src/jalview/viewmodel/PCAModel.java
@@ -21,7 +21,6 @@
 package jalview.viewmodel;
 
 import jalview.analysis.PCA;
-import jalview.analysis.scoremodels.ScoreModels;
 import jalview.api.RotatableCanvasI;
 import jalview.api.analysis.ScoreModelI;
 import jalview.api.analysis.SimilarityParamsI;
@@ -33,57 +32,59 @@ import java.util.Vector;
 
 public class PCAModel
 {
-  private volatile PCA pca;
-
-  int top;
+  /*
+   * inputs
+   */
+  private final AlignmentView seqstrings;
 
-  AlignmentView seqstrings;
+  private final SequenceI[] seqs;
 
-  SequenceI[] seqs;
+  private final SimilarityParamsI similarityParams;
 
   /*
-   * Score model used to calculate PCA
+   * options - score model, nucleotide / protein
    */
-  ScoreModelI scoreModel;
+  private ScoreModelI scoreModel;
 
   private boolean nucleotide = false;
 
-  private Vector<SequencePoint> points;
+  /*
+   * outputs
+   */
+  private PCA pca;
 
-  private boolean jvCalcMode = true;
+  int top;
 
-  private SimilarityParamsI similarityParams;
+  private Vector<SequencePoint> points;
 
   /**
-   * Constructor given sequence data and score calculation parameter options.
-   * The initial state is to compute PCA using a default score model (BLOSUM62
-   * for peptide, DNA for nucleotide).
+   * 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,
-          SimilarityParamsI params)
+          ScoreModelI modelName, SimilarityParamsI params)
   {
     seqstrings = seqData;
     seqs = sqs;
     nucleotide = nuc;
-    scoreModel = ScoreModels.getInstance().getDefaultModel(!nucleotide);
+    scoreModel = modelName;
     similarityParams = params;
   }
 
-  public boolean isJvCalcMode()
-  {
-    return jvCalcMode;
-  }
-
-  public void run()
+  /**
+   * Performs the PCA calculation (in the same thread) and extracts result data
+   * needed for visualisation by PCAPanel
+   */
+  public void calculate()
   {
     pca = new PCA(seqstrings, scoreModel, similarityParams);
-    pca.setJvCalcMode(jvCalcMode);
-    pca.run();
+    pca.run(); // executes in same thread, wait for completion
 
     // Now find the component coordinates
     int ii = 0;
@@ -97,7 +98,7 @@ public class PCAModel
     // top = pca.getM().height() - 1;
     top = height - 1;
 
-    points = new Vector<SequencePoint>();
+    points = new Vector<>();
     float[][] scores = pca.getComponents(top - 1, top - 2, top - 3, 100);
 
     for (int i = 0; i < height; i++)
@@ -229,11 +230,6 @@ public class PCAModel
     return pts;
   }
 
-  public void setJvCalcMode(boolean state)
-  {
-    jvCalcMode = state;
-  }
-
   public String getScoreModelName()
   {
     return scoreModel == null ? "" : scoreModel.getName();