-Clazz.declarePackage ("jalview.analysis.scoremodels");\r
-Clazz.load (["jalview.api.analysis.ScoreModelI", "$.ViewBasedAnalysisI"], "jalview.analysis.scoremodels.FeatureScoreModel", ["jalview.util.Comparison", "java.util.ArrayList", "$.Arrays", "$.Hashtable"], function () {\r
-c$ = Clazz.decorateAsClass (function () {\r
-this.fr = null;\r
-Clazz.instantialize (this, arguments);\r
-}, jalview.analysis.scoremodels, "FeatureScoreModel", null, [jalview.api.analysis.ScoreModelI, jalview.api.analysis.ViewBasedAnalysisI]);\r
-Clazz.overrideMethod (c$, "configureFromAlignmentView", \r
-function (view) {\r
-this.fr = view.cloneFeatureRenderer ();\r
-return true;\r
-}, "jalview.api.AlignmentViewPanel");\r
-Clazz.overrideMethod (c$, "findDistances", \r
-function (seqData) {\r
-var nofeats = 0;\r
-var dft = java.util.Arrays.asList (this.fr.getDisplayedFeatureTypes ());\r
-if (dft != null) {\r
-nofeats = dft.size ();\r
-}var sequenceString = seqData.getVisibleAlignment (jalview.util.Comparison.GapChars.charAt (0)).getSequencesArray ();\r
-var noseqs = sequenceString.length;\r
-var cpwidth = seqData.getWidth ();\r
-var distance = Clazz.newFloatArray (noseqs, noseqs, 0);\r
-if (nofeats == 0) {\r
-for (var d, $d = 0, $$d = distance; $d < $$d.length && ((d = $$d[$d]) || true); $d++) {\r
-for (var i = 0; i < d.length; d[i++] = 0) {\r
-;}\r
-}\r
-return distance;\r
-}var max = 0;\r
-for (var cpos = 0; cpos < cpwidth; cpos++) {\r
-var sfap = new java.util.ArrayList ();\r
-for (var i = 0; i < noseqs; i++) {\r
-var types = new java.util.Hashtable ();\r
-var sfs = this.fr.findFeaturesAtRes (sequenceString[i], sequenceString[i].findPosition (cpos));\r
-for (var sf, $sf = sfs.iterator (); $sf.hasNext () && ((sf = $sf.next ()) || true);) {\r
-types.put (sf.getType (), sf);\r
-}\r
-sfap.add (types);\r
-}\r
-for (var i = 0; i < (noseqs - 1); i++) {\r
-if (cpos == 0) {\r
-distance[i][i] = 0;\r
-}for (var j = i + 1; j < noseqs; j++) {\r
-var sfcommon = 0;\r
-var fi = sfap.get (i);\r
-var fk;\r
-var fj = sfap.get (j);\r
-if (fi.size () > fj.size ()) {\r
-fk = fj;\r
-} else {\r
-fk = fi;\r
-fi = fj;\r
-}for (var k, $k = fi.keySet ().iterator (); $k.hasNext () && ((k = $k.next ()) || true);) {\r
-var sfj = fk.get (k);\r
-if (sfj != null) {\r
-sfcommon++;\r
-}}\r
-distance[i][j] += (fi.size () + fk.size () - 2 * sfcommon);\r
-distance[j][i] += distance[i][j];\r
-}\r
-}\r
-}\r
-for (var i = 0; i < noseqs; i++) {\r
-for (var j = i + 1; j < noseqs; j++) {\r
-distance[i][j] /= cpwidth;\r
-distance[j][i] = distance[i][j];\r
-}\r
-}\r
-return distance;\r
-}, "jalview.datamodel.AlignmentView");\r
-Clazz.overrideMethod (c$, "getName", \r
-function () {\r
-return "Sequence Feature Similarity";\r
-});\r
-Clazz.overrideMethod (c$, "isDNA", \r
-function () {\r
-return true;\r
-});\r
-Clazz.overrideMethod (c$, "isProtein", \r
-function () {\r
-return true;\r
-});\r
-Clazz.overrideMethod (c$, "toString", \r
-function () {\r
-return "Score between sequences based on hamming distance between binary vectors marking features displayed at each column";\r
-});\r
-});\r
+Clazz.declarePackage ("jalview.analysis.scoremodels");
+Clazz.load (["jalview.api.analysis.ScoreModelI", "$.ViewBasedAnalysisI"], "jalview.analysis.scoremodels.FeatureScoreModel", ["jalview.util.Comparison", "java.util.ArrayList", "$.Arrays", "$.Hashtable"], function () {
+c$ = Clazz.decorateAsClass (function () {
+this.fr = null;
+Clazz.instantialize (this, arguments);
+}, jalview.analysis.scoremodels, "FeatureScoreModel", null, [jalview.api.analysis.ScoreModelI, jalview.api.analysis.ViewBasedAnalysisI]);
+Clazz.overrideMethod (c$, "configureFromAlignmentView",
+function (view) {
+this.fr = view.cloneFeatureRenderer ();
+return true;
+}, "jalview.api.AlignmentViewPanel");
+Clazz.overrideMethod (c$, "findDistances",
+function (seqData) {
+var nofeats = 0;
+var dft = java.util.Arrays.asList (this.fr.getDisplayedFeatureTypes ());
+if (dft != null) {
+nofeats = dft.size ();
+}var sequenceString = seqData.getVisibleAlignment (jalview.util.Comparison.GapChars.charAt (0)).getSequencesArray ();
+var noseqs = sequenceString.length;
+var cpwidth = seqData.getWidth ();
+var distance = Clazz.newFloatArray (noseqs, noseqs, 0);
+if (nofeats == 0) {
+for (var d, $d = 0, $$d = distance; $d < $$d.length && ((d = $$d[$d]) || true); $d++) {
+for (var i = 0; i < d.length; d[i++] = 0) {
+;}
+}
+return distance;
+}var max = 0;
+for (var cpos = 0; cpos < cpwidth; cpos++) {
+var sfap = new java.util.ArrayList ();
+for (var i = 0; i < noseqs; i++) {
+var types = new java.util.Hashtable ();
+var sfs = this.fr.findFeaturesAtRes (sequenceString[i], sequenceString[i].findPosition (cpos));
+for (var sf, $sf = sfs.iterator (); $sf.hasNext () && ((sf = $sf.next ()) || true);) {
+types.put (sf.getType (), sf);
+}
+sfap.add (types);
+}
+for (var i = 0; i < (noseqs - 1); i++) {
+if (cpos == 0) {
+distance[i][i] = 0;
+}for (var j = i + 1; j < noseqs; j++) {
+var sfcommon = 0;
+var fi = sfap.get (i);
+var fk;
+var fj = sfap.get (j);
+if (fi.size () > fj.size ()) {
+fk = fj;
+} else {
+fk = fi;
+fi = fj;
+}for (var k, $k = fi.keySet ().iterator (); $k.hasNext () && ((k = $k.next ()) || true);) {
+var sfj = fk.get (k);
+if (sfj != null) {
+sfcommon++;
+}}
+distance[i][j] += (fi.size () + fk.size () - 2 * sfcommon);
+distance[j][i] += distance[i][j];
+}
+}
+}
+for (var i = 0; i < noseqs; i++) {
+for (var j = i + 1; j < noseqs; j++) {
+distance[i][j] /= cpwidth;
+distance[j][i] = distance[i][j];
+}
+}
+return distance;
+}, "jalview.datamodel.AlignmentView");
+Clazz.overrideMethod (c$, "getName",
+function () {
+return "Sequence Feature Similarity";
+});
+Clazz.overrideMethod (c$, "isDNA",
+function () {
+return true;
+});
+Clazz.overrideMethod (c$, "isProtein",
+function () {
+return true;
+});
+Clazz.overrideMethod (c$, "toString",
+function () {
+return "Score between sequences based on hamming distance between binary vectors marking features displayed at each column";
+});
+});
git://source.jalview.org / jalviewjs.git / blobdiff