--- /dev/null
+package jalview.gui.structurechooser;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.BitSet;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.Comparator;
+import java.util.List;
+
+import jalview.datamodel.SequenceI;
+import jalview.fts.api.FTSData;
+import jalview.fts.core.FTSRestRequest;
+
+public class TDBResultAnalyser
+{
+
+ /**
+ * model categories - update as needed. warnings output if unknown types
+ * encountered.
+ *
+ * Order denotes 'trust'
+ */
+ private static List<String> EXP_CATEGORIES = Arrays
+ .asList(new String[]
+ { "EXPERIMENTALLY DETERMINED", "DEEP LEARNING",
+ "TEMPLATE-BASED" });
+
+ private SequenceI seq;
+
+ private Collection<FTSData> collectedResults;
+
+ private FTSRestRequest lastTdbRequest;
+
+ private int idx_ups;
+
+ private int idx_upe;
+
+ private int idx_mcat;
+
+ private int idx_mqual;
+
+ private int idx_resol;
+
+ public TDBResultAnalyser(SequenceI seq,
+ Collection<FTSData> collectedResults,
+ FTSRestRequest lastTdbRequest)
+ {
+ this.seq = seq;
+ this.collectedResults = collectedResults;
+ this.lastTdbRequest = lastTdbRequest;
+ idx_ups = lastTdbRequest.getFieldIndex("Uniprot Start");
+ idx_upe = lastTdbRequest.getFieldIndex("Uniprot End");
+ idx_mcat = lastTdbRequest.getFieldIndex("Model Category");
+ idx_mqual = lastTdbRequest.getFieldIndex("Qmean");
+ idx_resol = lastTdbRequest.getFieldIndex("Resolution");
+ }
+ private final int scoreCategory(String cat)
+ {
+ // TODO: make quicker
+ int idx = EXP_CATEGORIES.indexOf(cat.toUpperCase());
+ if (idx == -1)
+ {
+ System.out.println("Unknown category: '" + cat + "'");
+ }
+ return -EXP_CATEGORIES.size() - idx;
+ }
+
+ /**
+ * sorts records discovered by 3D beacons and excludes any that don't
+ * intersect with the sequence's start/end rage
+ *
+ * @return
+ */
+ public List<FTSData> getFilteredResponse()
+ {
+ List<FTSData> filteredResponse = new ArrayList<FTSData>();
+
+ // ignore anything outside the sequence region
+ for (FTSData row : collectedResults)
+ {
+ int up_s = (Integer) row.getSummaryData()[idx_ups];
+ int up_e = (Integer) row.getSummaryData()[idx_upe];
+
+ if (seq == row.getSummaryData()[0] && up_e > seq.getStart()
+ && up_s < seq.getEnd())
+ {
+ filteredResponse.add(row);
+ }
+ }
+ // sort according to decreasing length,
+ // increasing start
+ Collections.sort(filteredResponse, new Comparator<FTSData>()
+ {
+
+
+ @Override
+ public int compare(FTSData o1, FTSData o2)
+ {
+ Object[] o1data = o1.getSummaryData();
+ Object[] o2data = o2.getSummaryData();
+ int o1_s = (Integer) o1data[idx_ups];
+ int o1_e = (Integer) o1data[idx_upe];
+ int o1_cat = scoreCategory((String) o1data[idx_mcat]);
+ int o2_s = (Integer) o2data[idx_ups];
+ int o2_e = (Integer) o2data[idx_upe];
+ int o2_cat = scoreCategory((String) o2data[idx_mcat]);
+
+ if (o1_cat == o2_cat)
+ {
+ if (o1_s == o2_s)
+ {
+ int o1_xtent = o1_e - o1_s;
+ int o2_xtent = o2_e - o2_s;
+ if (o1_xtent == o2_xtent)
+ {
+ if (o1_cat == scoreCategory(EXP_CATEGORIES.get(0)))
+ {
+ // experimental structures, so rank on quality
+ double o1_res = (Double) o1data[idx_resol];
+ double o2_res = (Double) o2data[idx_resol];
+ return (o2_res < o1_res) ? 1 : (o2_res == o1_res) ? 0 : -1;
+ }
+ else
+ {
+ // models, so rank on qmean
+ float o1_mq = (Float) o1data[idx_mqual];
+ float o2_mq = (Float) o2data[idx_mqual];
+ return (o2_mq < o1_mq) ? 1 : (o2_mq == o1_mq) ? 0 : -1;
+ }
+ }
+ else
+ {
+ return o1_xtent - o2_xtent;
+ }
+ }
+ else
+ {
+ return o1_s - o2_s;
+ }
+ }
+ else
+ {
+ return o2_cat - o1_cat;
+ }
+ }
+
+ @Override
+ public boolean equals(Object obj)
+ {
+ return super.equals(obj);
+ }
+ });
+ return filteredResponse;
+ }
+
+ /**
+ * return list of structures to be marked as selected for this sequence according to given criteria
+ * @param filteredStructures - sorted, filtered structures from getFilteredResponse
+ *
+ */
+ public List<FTSData> selectStructures(List<FTSData> filteredStructures)
+ {
+ List<FTSData> selected = new ArrayList<FTSData>();
+ BitSet cover = new BitSet();
+ cover.set(seq.getStart(),seq.getEnd());
+ // walk down the list of structures, selecting some to add to selected
+ for (FTSData structure:filteredStructures)
+ {
+ Object[] odata=structure.getSummaryData();
+ int o1_s = (Integer) odata[idx_ups];
+ int o1_e = (Integer) odata[idx_upe];
+ int o1_cat = scoreCategory((String) odata[idx_mcat]);
+ BitSet scover = new BitSet();
+ // measure intersection
+ scover.set(o1_s,o1_e);
+ scover.and(cover);
+ if (scover.cardinality()>4)
+ {
+ selected.add(structure);
+ // clear the range covered by this structure
+ cover.andNot(scover);
+ }
+ }
+ // final step is to sort on length - this might help the superposition process
+ Collections.sort(selected,new Comparator<FTSData>()
+ {
+ @Override
+ public int compare(FTSData o1, FTSData o2)
+ {
+ Object[] o1data = o1.getSummaryData();
+ Object[] o2data = o2.getSummaryData();
+ int o1_xt = ((Integer) o1data[idx_upe]) - ((Integer) o1data[idx_ups]);
+ int o1_cat = scoreCategory((String) o1data[idx_mcat]);
+ int o2_xt = ((Integer) o2data[idx_upe]-(Integer) o2data[idx_ups]);
+ int o2_cat = scoreCategory((String) o2data[idx_mcat]);
+ return o2_xt-o1_xt;
+ }
+ });
+ return selected;
+ }
+
+}
}
/**
- * model categories - update as needed. warnings output if unknown types
- * encountered.
- *
- * Order denotes 'trust'
- */
- private static List<String> EXP_CATEGORIES = Arrays
- .asList(new String[]
- { "EXPERIMENTALLY DETERMINED", "DEEP LEARNING", "TEMPLATE-BASED" });
-
- /**
* FTSRestClient specific query builder to pick top ranked entry from a
* fetchStructuresMetaData query
*
boolean b) throws Exception
{
- List<FTSData> filteredResponse = new ArrayList<FTSData>();
- final int idx_ups = lastTdbRequest.getFieldIndex("Uniprot Start");
- final int idx_upe = lastTdbRequest.getFieldIndex("Uniprot End");
- final int idx_mcat = lastTdbRequest.getFieldIndex("Model Category");
- final int idx_mqual = lastTdbRequest.getFieldIndex("Qmean");
- final int idx_resol = lastTdbRequest.getFieldIndex("Resolution");
-
- // ignore anything outside the sequence region
- for (FTSData row : collectedResults)
- {
- int up_s = (Integer) row.getSummaryData()[idx_ups];
- int up_e = (Integer) row.getSummaryData()[idx_upe];
-
- if (seq == row.getSummaryData()[0] && up_e > seq.getStart()
- && up_s < seq.getEnd())
- {
- filteredResponse.add(row);
- }
- }
- // sort according to decreasing length,
- // increasing start
- Collections.sort(filteredResponse, new Comparator<FTSData>()
- {
-
- private final int scoreCategory(String cat)
- {
- // TODO: make quicker
- int idx = EXP_CATEGORIES.indexOf(cat.toUpperCase());
- if (idx == -1)
- {
- System.out.println("Unknown category: '" + cat + "'");
- }
- return -EXP_CATEGORIES.size() - idx;
- }
-
- @Override
- public int compare(FTSData o1, FTSData o2)
- {
- int o1_s = (Integer) o1.getSummaryData()[idx_ups];
- int o1_e = (Integer) o1.getSummaryData()[idx_upe];
- int o1_cat = scoreCategory((String) o1.getSummaryData()[idx_mcat]);
- int o2_s = (Integer) o2.getSummaryData()[idx_ups];
- int o2_e = (Integer) o2.getSummaryData()[idx_upe];
- int o2_cat = scoreCategory((String) o2.getSummaryData()[idx_mcat]);
-
- if (o1_cat == o2_cat)
- {
- if (o1_s == o2_s)
- {
- int o1_xtent = o1_e - o1_s;
- int o2_xtent = o2_e - o2_s;
- if (o1_xtent == o2_xtent)
- {
- if (o1_cat == scoreCategory(EXP_CATEGORIES.get(0)))
- {
- // experimental structures, so rank on quality
- double o1_res = (Double) o1.getSummaryData()[idx_resol];
- double o2_res = (Double) o2.getSummaryData()[idx_resol];
- return (o2_res < o1_res) ? 1 : (o2_res == o1_res) ? 0 : -1;
- }
- else
- {
- // models, so rank on qmean
- float o1_mq = (Float) o1.getSummaryData()[idx_mqual];
- float o2_mq = (Float) o2.getSummaryData()[idx_mqual];
- return (o2_mq < o1_mq) ? 1 : (o2_mq == o1_mq) ? 0 : -1;
- }
- }
- else
- {
- return o1_xtent - o2_xtent;
- }
- }
- else
- {
- return o1_s - o2_s;
- }
- }
- else
- {
- return o2_cat - o1_cat;
- }
- }
-
- @Override
- public boolean equals(Object obj)
- {
- return super.equals(obj);
- }
- });
+ TDBResultAnalyser analyser= new TDBResultAnalyser(seq,collectedResults, lastTdbRequest);
+
+
FTSRestResponse resultList = new FTSRestResponse();
- resultList.setNumberOfItemsFound(filteredResponse.size());
- resultList.setSearchSummary(filteredResponse);
+
+ List<FTSData> filteredResponse = analyser.getFilteredResponse();
+
+ List<FTSData> selectedStructures = analyser.selectStructures(filteredResponse);
+ resultList.setNumberOfItemsFound(selectedStructures.size());
+ resultList.setSearchSummary(selectedStructures);
return resultList;
}
int typeColumnIndex = restable.getColumn("Provider").getModelIndex();
int categoryColumnIndex = restable.getColumn("Model Category")
.getModelIndex();
+ final int up_start_idx = restable.getColumn("Uniprot Start").getModelIndex();
+ final int up_end_idx = restable.getColumn("Uniprot End").getModelIndex();
+ int i=0;
+
+ // bleugh!
+ Integer[] sellist = new Integer[selectedRows.length];
+ for (Integer row: selectedRows)
+ {
+ sellist[i++] = row;
+ }
+ // Sort rows by coverage
+ Arrays.sort(sellist,new Comparator<Integer>()
+ {
+ @Override
+ public int compare(Integer o1, Integer o2)
+ {
+ int o1_xt = ((Integer)restable.getValueAt(o1, up_end_idx)) - (Integer)restable.getValueAt(o1, up_start_idx);
+ int o2_xt = ((Integer)restable.getValueAt(o2, up_end_idx)) - (Integer)restable.getValueAt(o2, up_start_idx);
+ return o2_xt-o1_xt;
+ }
+ });
- for (int row : selectedRows)
+
+ for (int row : sellist)
{
// unique id - could be a horrible hash
git://source.jalview.org / jalview.git / commitdiff