*/
package jalview.analysis;
-import jalview.analysis.scoremodels.PairwiseDistanceModel;
-import jalview.analysis.scoremodels.ScoreMatrix;
-import jalview.analysis.scoremodels.ScoreModels;
+import jalview.analysis.scoremodels.PIDModel;
+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;
import java.io.PrintStream;
StringBuilder details = new StringBuilder(1024);
- private String[] seqs;
+ private AlignmentView seqs;
- private ScoreMatrix scoreMatrix;
+ private ScoreModelI scoreModel;
+
+ private SimilarityParamsI similarityParams;
- /**
- * Creates a new PCA object. By default, uses blosum62 matrix to generate
- * sequence similarity matrices
- *
- * @param s
- * Set of amino acid sequences to perform PCA on
- */
- public PCA(String[] s)
- {
- this(s, false);
- }
-
- /**
- * Creates a new PCA object. By default, uses blosum62 matrix to generate
- * sequence similarity matrices
- *
- * @param s
- * Set of sequences to perform PCA on
- * @param nucleotides
- * if true, uses standard DNA/RNA matrix for sequence similarity
- * calculation.
- */
- public PCA(String[] s, boolean nucleotides)
- {
- this(s, nucleotides, null);
- }
-
- public PCA(String[] s, boolean nucleotides, String s_m)
+ public PCA(AlignmentView s, ScoreModelI sm, SimilarityParamsI options)
{
this.seqs = s;
-
- scoreMatrix = null;
- String sm = s_m;
- if (sm != null)
- {
- scoreMatrix = (ScoreMatrix) ((PairwiseDistanceModel) ScoreModels
- .getInstance()
- .forName(sm)).getScoreModel();
- }
- if (scoreMatrix == null)
- {
- // either we were given a non-existent score matrix or a scoremodel that
- // isn't based on a pairwise symbol score matrix
- scoreMatrix = ScoreModels.getInstance().getDefaultModel(!nucleotides);
- }
- details.append("PCA calculation using " + sm
+ this.similarityParams = options;
+ this.scoreModel = sm;
+
+ details.append("PCA calculation using " + sm.getName()
+ " sequence similarity matrix\n========\n\n");
}
+ (jvCalcMode ? "Jalview variant" : "Original SeqSpace")
+ "\n");
- eigenvector = scoreMatrix.computePairwiseScores(seqs);
+ eigenvector = computeSimilarity(seqs);
details.append(" --- OrigT * Orig ---- \n");
eigenvector.print(ps, "%8.2f");
// + (System.currentTimeMillis() - now) + "ms"));
}
+ /**
+ * 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.
+ *
+ * @param av
+ * @return
+ */
+ MatrixI computeSimilarity(AlignmentView av)
+ {
+ MatrixI result = null;
+ if (scoreModel instanceof SimilarityScoreModelI)
+ {
+ result = ((SimilarityScoreModelI) scoreModel).findSimilarities(av,
+ similarityParams);
+ if (scoreModel instanceof PIDModel)
+ {
+ /*
+ * scale % identities to width of alignment for backwards
+ * compatibility with Jalview 2.10.1 SeqSpace PCA calculation
+ */
+ result.multiply(av.getWidth() / 100d);
+ }
+ }
+ else if (scoreModel instanceof DistanceScoreModelI)
+ {
+ /*
+ * find distances and convert to similarity scores
+ * reverseRange(false) preserves but reverses the min-max range
+ */
+ 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;
public int getHeight()
{
// TODO can any of seqs[] be null?
- return seqs.length;
+ return seqs.getSequences().length;
}
}