X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=src%2Fjalview%2Fanalysis%2FPCA.java;h=3ec7995f9f67aa84c2553fcd154df0b4c934a223;hb=d3149ce8aaa35531acd228b89622b8fac2565258;hp=43f21615c10ba6c990997ef96ed0686a2311485a;hpb=74c5bd7b1f98214a6d57d7c64d0548013530d397;p=jalview.git

diff --git a/src/jalview/analysis/PCA.java b/src/jalview/analysis/PCA.java
index 43f2161..3ec7995 100755
--- a/src/jalview/analysis/PCA.java
+++ b/src/jalview/analysis/PCA.java
@@ -20,10 +20,8 @@
  */
 package jalview.analysis;
 
-import jalview.api.analysis.DistanceScoreModelI;
 import jalview.api.analysis.ScoreModelI;
 import jalview.api.analysis.SimilarityParamsI;
-import jalview.api.analysis.SimilarityScoreModelI;
 import jalview.datamodel.AlignmentView;
 import jalview.math.MatrixI;
 
@@ -34,8 +32,6 @@ import java.io.PrintStream;
  */
 public class PCA implements Runnable
 {
-  boolean jvCalcMode = true;
-
   MatrixI symm;
 
   double[] eigenvalue;
@@ -44,7 +40,7 @@ public class PCA implements Runnable
 
   StringBuilder details = new StringBuilder(1024);
 
-  private AlignmentView seqs;
+  final private AlignmentView seqs;
 
   private ScoreModelI scoreModel;
   
@@ -173,11 +169,7 @@ public class PCA implements Runnable
     // long now = System.currentTimeMillis();
     try
     {
-      details.append("PCA Calculation Mode is "
-              + (jvCalcMode ? "Jalview variant" : "Original SeqSpace")
-              + "\n");
-
-      eigenvector = computeSimilarity(seqs);
+      eigenvector = scoreModel.findSimilarities(seqs, similarityParams);
 
       details.append(" --- OrigT * Orig ---- \n");
       eigenvector.print(ps, "%8.2f");
@@ -220,44 +212,6 @@ public class PCA implements Runnable
   }
 
   /**
-   * Computes a pairwise similarity matrix for the given sequence regions using
-   * the configured score model. If the score model is a similarity model, then
-   * it computes the result directly. If it is a distance model, then use it to
-   * compute pairwise distances, and convert these to similarity scores by
-   * substracting from the maximum value.
-   * 
-   * @param av
-   * @return
-   */
-  MatrixI computeSimilarity(AlignmentView av)
-  {
-    MatrixI result = null;
-    if (scoreModel instanceof SimilarityScoreModelI)
-    {
-      result = ((SimilarityScoreModelI) scoreModel).findSimilarities(av,
-              similarityParams);
-    }
-    else if (scoreModel instanceof DistanceScoreModelI)
-    {
-      result = ((DistanceScoreModelI) scoreModel).findDistances(av,
-              similarityParams);
-      result.reverseRange(false);
-    }
-    else
-    {
-      System.err
-              .println("Unexpected type of score model, cannot calculate similarity");
-    }
-
-    return result;
-  }
-
-  public void setJvCalcMode(boolean calcMode)
-  {
-    this.jvCalcMode = calcMode;
-  }
-
-  /**
    * Answers the N dimensions of the NxN PCA matrix. This is the number of
    * sequences involved in the pairwise score calculation.
    *