cdmlib-services/src/main/java/eu/etaxonomy/cdm/api/service/NaturalLanguageGenerator.java

   1 package eu.etaxonomy.cdm.api.service;
   2
   3 import java.util.ArrayList;
   4 import java.util.Iterator;
   5 import java.util.List;
   6 import java.util.Set;
   7
   8 import org.apache.xerces.dom.ElementImpl;
   9 import org.apache.xerces.impl.xpath.regex.ParseException;
  10 import org.springframework.stereotype.Component;
  11
  12 import eu.etaxonomy.cdm.model.common.CdmBase;
  13 import eu.etaxonomy.cdm.model.common.VersionableEntity;
  14 import eu.etaxonomy.cdm.model.description.CategoricalData;
  15 import eu.etaxonomy.cdm.model.description.DescriptionBase;
  16 import eu.etaxonomy.cdm.model.description.DescriptionElementBase;
  17 import eu.etaxonomy.cdm.model.description.Feature;
  18 import eu.etaxonomy.cdm.model.description.FeatureNode;
  19 import eu.etaxonomy.cdm.model.description.FeatureTree;
  20 import eu.etaxonomy.cdm.model.description.QuantitativeData;
  21 import eu.etaxonomy.cdm.model.description.State;
  22 import eu.etaxonomy.cdm.model.description.StateData;
  23 import eu.etaxonomy.cdm.model.description.StatisticalMeasure;
  24 import eu.etaxonomy.cdm.model.description.StatisticalMeasurementValue;
  25 import eu.etaxonomy.cdm.model.description.TaxonDescription;
  26 import eu.etaxonomy.cdm.model.description.TextData;
  27 import eu.etaxonomy.cdm.model.taxon.Taxon;
  28 import eu.etaxonomy.cdm.model.taxon.TaxonBase;
  29 import eu.etaxonomy.cdm.model.common.Language;
  30
  31 @Component
  32 public class NaturalLanguageGenerator implements INaturalLanguageGenerator {
  33
  34         public List<TextData> generateNaturalLanguageDescription(FeatureTree featureTree,Set<TaxonDescription> descriptions) {
  35                 return buildBranchesDescr(featureTree.getRootChildren(), featureTree.getRoot(), descriptions, false);
  36         }
  37
  38         private List<TextData> buildBranchesDescr(List<FeatureNode> children, FeatureNode parent, Set<TaxonDescription> descriptions, boolean leaf) {
  39                 List<TextData> listTextData = new ArrayList<TextData>(); ;
  40                 if (!parent.isLeaf()){
  41                         Feature fref = parent.getFeature();
  42                         for (Iterator<FeatureNode> ifn = children.iterator() ; ifn.hasNext() ;){
  43                                 FeatureNode fn = ifn.next();
  44                                 listTextData.addAll(buildBranchesDescr(fn.getChildren(),fn,descriptions, leaf));
  45                         }
  46                 }
  47                 else {
  48                         Feature fref = parent.getFeature();
  49                         if (fref!=null) { // needs a better algorithm
  50                                 for (Iterator<TaxonDescription> db = descriptions.iterator() ; db.hasNext() ;){
  51                                         TaxonDescription descriptionBase = db.next();
  52                                         Set<DescriptionElementBase> elements = descriptionBase.getElements();
  53                                         for (Iterator<DescriptionElementBase> deb = elements.iterator() ; deb.hasNext() ;){
  54                                                 DescriptionElementBase descriptionElement = deb.next();
  55                                                 TextData textData = TextData.NewInstance();
  56                                                 if (descriptionElement.getFeature().getLabel().equals(fref.getLabel())){
  57                                                         if (descriptionElement instanceof CategoricalData) {
  58                                                                 CategoricalData categoricalData = (CategoricalData) descriptionElement;
  59                                                                 textData = buildCategoricalDescr(categoricalData);
  60                                                                 listTextData.add(textData);
  61                                                         }
  62                                                         if (descriptionElement instanceof QuantitativeData) {
  63                                                                 QuantitativeData quantitativeData = (QuantitativeData) descriptionElement;
  64                                                                 textData = buildQuantitativeDescr(quantitativeData);
  65                                                                 listTextData.add(textData);
  66                                                         }
  67                                                 }
  68                                         }
  69                                 }
  70                                 leaf = true;
  71                         }
  72                 }
  73                 return listTextData;
  74         }
  75
  76         //TODO manage different languages
  77         private TextData buildQuantitativeDescr (QuantitativeData quantitativeData) throws ParseException {
  78
  79                 boolean average = false;
  80                 float averagevalue = new Float(0);
  81                 boolean sd = false;
  82                 float sdvalue = new Float(0);
  83                 boolean min = false;
  84                 float minvalue = new Float(0);
  85                 boolean max = false;
  86                 float maxvalue = new Float(0);
  87                 boolean lowerb = false;
  88                 float lowerbvalue = new Float(0);
  89                 boolean upperb = false;
  90                 float upperbvalue = new Float(0);
  91
  92                 StringBuilder QuantitativeDescription = new StringBuilder();
  93                 Feature feature = quantitativeData.getFeature();
  94                 TextData textData = TextData.NewInstance(feature);
  95                 QuantitativeDescription.append(" "+feature.getLabel());
  96                 String unit = quantitativeData.getUnit().getLabel();
  97                 Set<StatisticalMeasurementValue> statisticalValues = quantitativeData.getStatisticalValues();
  98                 for (Iterator<StatisticalMeasurementValue> smv = statisticalValues.iterator() ; smv.hasNext() ;){
  99                         StatisticalMeasurementValue statisticalValue = smv.next();
 100                         StatisticalMeasure type = statisticalValue.getType();
 101                         String label = type.getLabel();
 102                         if (label.equals("Average")) {
 103                                 average = true;
 104                                 averagevalue = statisticalValue.getValue();
 105                         } else if (label.equals("StandardDeviation")) {
 106                                 sd = true;
 107                                 sdvalue = statisticalValue.getValue();
 108                         } else if (label.equals("Min")) {
 109                                 min = true;
 110                                 minvalue = statisticalValue.getValue();
 111                         } else if (label.equals("Max")) {
 112                                 max = true;
 113                                 maxvalue = statisticalValue.getValue();
 114                         } else if (label.equals("TypicalLowerBoundary")) {
 115                                 lowerb = true;
 116                                 lowerbvalue = statisticalValue.getValue();
 117                         } else if (label.equals("TypicalUpperBoundary")) {
 118                                 upperb = true;
 119                                 upperbvalue = statisticalValue.getValue();
 120                         }
 121                 }
 122                 if (max && min) {
 123                         QuantitativeDescription.append(" from " + minvalue + " to " + maxvalue + unit);
 124                 }
 125                 else if (min) {
 126                         QuantitativeDescription.append(" from " + minvalue + " " + unit);
 127                 }
 128                 else if (max) {
 129                         QuantitativeDescription.append(" up to " + maxvalue + " " + unit);
 130                 }
 131                 if ((max||min)&&(lowerb||upperb)) {
 132                         QuantitativeDescription.append(",");
 133                 }
 134                 if ((lowerb||upperb)&&(min||max)) {
 135                         QuantitativeDescription.append(" most frequently");
 136                 }
 137                 if (upperb && lowerb) {
 138                         QuantitativeDescription.append(" from " + lowerbvalue + " to " + upperbvalue + unit);
 139                 }
 140                 else if (lowerb) {
 141                         QuantitativeDescription.append(" from " + lowerbvalue + " " + unit);
 142                 }
 143                 else if (upperb) {
 144                         QuantitativeDescription.append(" up to " + upperbvalue + " " + unit);
 145                 }
 146                 if (((max||min)&&(average))||((lowerb||upperb)&&(average))) {
 147                         QuantitativeDescription.append(",");
 148                 }
 149                 if (average) {
 150                         QuantitativeDescription.append(" " + averagevalue + unit + " on average ");
 151                         if (sd) {
 152                                 QuantitativeDescription.append("(+/- " + sdvalue + ")");
 153                         }
 154                 }
 155                 textData.putText(QuantitativeDescription.toString(), Language.ENGLISH());
 156                 return textData;
 157         }
 158
 159         private TextData buildCategoricalDescr(CategoricalData categoricalData) throws ParseException {
 160                 Feature feature = categoricalData.getFeature();
 161                 TextData textData = TextData.NewInstance(feature);
 162                 List<StateData> states = categoricalData.getStates();
 163                 StringBuilder CategoricalDescription = new StringBuilder();
 164                 CategoricalDescription.append(" "+feature.getLabel());
 165                 for (Iterator<StateData> sd = states.iterator() ; sd.hasNext() ;){
 166                         StateData stateData = sd.next();
 167                         State s = stateData.getState();
 168                         CategoricalDescription.append(" " + s.getLabel());
 169                 }
 170                 textData.putText(CategoricalDescription.toString(), Language.ENGLISH());
 171                 return textData ;
 172         }
 173
 174 }