package eu.etaxonomy.cdm.api.service;
import java.util.ArrayList;
+import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
+import java.util.Map;
import java.util.Set;
-import org.apache.xerces.dom.ElementImpl;
-import org.apache.xerces.impl.xpath.regex.ParseException;
+import org.apache.commons.lang.StringUtils;
import org.springframework.stereotype.Component;
-import eu.etaxonomy.cdm.model.common.CdmBase;
-import eu.etaxonomy.cdm.model.common.VersionableEntity;
import eu.etaxonomy.cdm.model.description.CategoricalData;
-import eu.etaxonomy.cdm.model.description.DescriptionBase;
import eu.etaxonomy.cdm.model.description.DescriptionElementBase;
import eu.etaxonomy.cdm.model.description.Feature;
import eu.etaxonomy.cdm.model.description.FeatureNode;
import eu.etaxonomy.cdm.model.description.FeatureTree;
-import eu.etaxonomy.cdm.model.description.Modifier;
import eu.etaxonomy.cdm.model.description.QuantitativeData;
-import eu.etaxonomy.cdm.model.description.State;
-import eu.etaxonomy.cdm.model.description.StateData;
-import eu.etaxonomy.cdm.model.description.StatisticalMeasure;
-import eu.etaxonomy.cdm.model.description.StatisticalMeasurementValue;
import eu.etaxonomy.cdm.model.description.TaxonDescription;
import eu.etaxonomy.cdm.model.description.TextData;
-import eu.etaxonomy.cdm.model.taxon.Taxon;
-import eu.etaxonomy.cdm.model.taxon.TaxonBase;
+import eu.etaxonomy.cdm.model.description.TextFormat;
+import eu.etaxonomy.cdm.model.common.Annotation;
+import eu.etaxonomy.cdm.model.common.AnnotationType;
import eu.etaxonomy.cdm.model.common.Language;
+
+/**
+ * Generator of natural language descriptions from TaxonDescriptions.
+ *
+ * @author m.venin
+ * @created 13.04.2010
+ * @version 1.0
+ */
@Component
public class NaturalLanguageGenerator implements INaturalLanguageGenerator {
+ private String firstSeparator = ",";
+ private String secondSeparator = ".";
+ private List<Integer> levels = new ArrayList<Integer>();
+
+ private DescriptionBuilder<QuantitativeData> quantitativeDescriptionBuilder = new DefaultQuantitativeDescriptionBuilder();
+ private DescriptionBuilder<CategoricalData> categoricalDescriptionBuilder = new DefaultCategoricalDescriptionBuilder();
+
+ private TextData previousTextData;
+
+ private Map<String, INaturalLanguageTextDataProcessor> elementProcessors;
+
+ private Set<INaturalLanguageTextDataProcessor> applicableElementProcessors = new HashSet<INaturalLanguageTextDataProcessor>();
+
+ /**
+ * Change the first separator used by generateSingleTextData. By default ",".
+ *
+ * @param separator
+ */
+ public void setFirstSeparator(String separator){
+ firstSeparator=separator;
+ }
+
+ public String getFirstSeparator(){
+ return firstSeparator;
+ }
+
+ /**
+ * Change the second separator used by generateSingleTextData. By default ".".
+ *
+ * @param separator
+ */
+ public void setSecondSeparator(String separator){
+ secondSeparator=separator;
+ }
+
+ public String getSecondSeparator(){
+ return secondSeparator;
+ }
+
+ /**
+ * @param quantitativeDescriptionBuilder
+ */
+ public void setQuantitativeDescriptionBuilder(DescriptionBuilder<QuantitativeData> quantitativeDescriptionBuilder){
+ this.quantitativeDescriptionBuilder = quantitativeDescriptionBuilder;
+ }
+
+ /**
+ * @param categoricalDescriptionBuilder
+ */
+ public void setCategoricalDescriptionBuilder(DescriptionBuilder<CategoricalData> categoricalDescriptionBuilder){
+ this.categoricalDescriptionBuilder = categoricalDescriptionBuilder;
+ }
+
+ /**
+ * @return the element processors of this generator
+ */
+ public Map<String, INaturalLanguageTextDataProcessor> getElementProcessors() {
+ return elementProcessors;
+ }
+
+ /**
+ * The keys of the elementProcessors map are regular expressions which are
+ * being used to identify the those Descriptions to which the mapped
+ * NaturalLanguageTextDataProcessor is applicable.
+ *
+ * @param elementProcessors
+ */
+ public void setElementProcessors(
+ Map<String, INaturalLanguageTextDataProcessor> elementProcessors) {
+ this.elementProcessors = elementProcessors;
+ }
+
+ /**
+ * Looks for technical annotations, if one matches a regular expression of the element processors
+ * the associated processor is added to the applicable element processors which will then be applied
+ * when generating the description.
+ *
+ * @param annotations the set of annotations of the description
+ */
+ private void initNaturalLanguageDescriptionElementProcessors(Set<Annotation> annotations) {
+
+ if(annotations != null){
+ for(Annotation annotation : annotations){
+ if(annotation.getAnnotationType().equals(AnnotationType.TECHNICAL())){
+ if (elementProcessors!=null){
+ for(String regex : elementProcessors.keySet()){
+ if(annotation.getText().matches(regex)){
+ applicableElementProcessors.add(elementProcessors.get(regex));
+ }
+ }
+ }
+ }
+ }
+ }
+ }
+
+
+ /**
+ * Applies the list of applicable processors to a TextData.
+ *
+ * @param textData the TextData to be modified
+ * @param previousTextData the TextData corresponding to the feature of the previous level in the tree
+ */
+ private void applyNaturalLanguageDescriptionElementProcessors(TextData textData, TextData previousTextData){
+ for(INaturalLanguageTextDataProcessor processor : applicableElementProcessors){
+ processor.process(textData, previousTextData);
+ }
+ }
+
+
+ /**
+ * The most simple function to generate a description. The language used is the default one.
+ *
+ * @param featureTree the FeatureTree holding the order in which features and their states must be printed
+ * @param description the TaxonDescription with all the data
+ *
+ * @return a list of TextData, each one being a basic element of the natural language description
+ */
public List<TextData> generateNaturalLanguageDescription(FeatureTree featureTree,TaxonDescription description) {
- return buildBranchesDescr(featureTree.getRootChildren(), featureTree.getRoot(), description, false);
+ return generateNaturalLanguageDescription(featureTree,description,Language.DEFAULT());
+ }
+
+
+
+ /**
+ * Generate a description in a specified language.
+ *
+ * @param featureTree the FeatureTree holding the order in which features and their states must be printed
+ * @param description the TaxonDescription with all the data
+ * @param language the language in which the description has to be printed
+ *
+ * @return a list of TextData, each one being a basic element of the natural language description
+ */
+ public List<TextData> generateNaturalLanguageDescription(FeatureTree featureTree, TaxonDescription description, Language language) {
+ List<Language> languages = new ArrayList<Language>();
+ languages.add(language);
+ initNaturalLanguageDescriptionElementProcessors(description.getAnnotations());
+ return generatePreferredNaturalLanguageDescription(featureTree,description,languages);
+ }
+
+ /**
+ * Generate a description with a specified list of preferred languages.
+ *
+ * @param featureTree the FeatureTree holding the order in which features and their states must be printed
+ * @param description the TaxonDescription with all the data
+ * @param languages the ordered list of languages preferred for printing the description
+ *
+ * @return a list of TextData, each one being a basic element of the natural language description
+ */
+ public List<TextData> generatePreferredNaturalLanguageDescription(FeatureTree featureTree,TaxonDescription description, List<Language> languages) {
+ initNaturalLanguageDescriptionElementProcessors(description.getAnnotations());
+ return buildBranchesDescr(featureTree.getRootChildren(), featureTree.getRoot(), description, languages,0);
+ }
+
+ /**
+ * Generate a description as a single paragraph in a TextData.
+ *
+ * @param featureTree the FeatureTree holding the order in which features and their states must be printed
+ * @param description the TaxonDescription with all the data
+ *
+ * @return a TextData in the default language.
+ */
+ public TextData generateSingleTextData(FeatureTree featureTree, TaxonDescription description) {
+ return generateSingleTextData(featureTree,description,Language.DEFAULT());
}
-
- private List<TextData> buildBranchesDescr(List<FeatureNode> children, FeatureNode parent, TaxonDescription description, boolean leaf) {
- List<TextData> listTextData = new ArrayList<TextData>(); ;
- if (!parent.isLeaf()){
- Feature fref = parent.getFeature();
+
+ /**
+ * Generate a description as a single paragraph in a TextData.
+ *
+ * @param featureTree the FeatureTree holding the order in which features and their states must be printed
+ * @param description the TaxonDescription with all the data
+ * @param language the language in which the description has to be printed
+ *
+ * @return a TextData in the specified language.
+ */
+ public TextData generateSingleTextData(FeatureTree featureTree, TaxonDescription description, Language language) {
+ List<Language> languages = new ArrayList<Language>();
+ languages.add(language);
+ return generatePreferredSingleTextData(featureTree,description,languages);
+ }
+
+ /**
+ * Generate a description with a specified list of preferred languages.
+ *
+ * @param featureTree the FeatureTree holding the order in which features and their states must be printed
+ * @param description the TaxonDescription with all the data
+ * @param languages the ordered list of languages preferred for printing the description
+ *
+ * @return a TextData using the languages (in the given order of preference)
+ */
+ public TextData generatePreferredSingleTextData(FeatureTree featureTree, TaxonDescription description, List<Language> languages) {
+ levels.clear(); // before the start, the table containing the levels of each node must be cleared
+ // Note: this is not the most efficient way to keep track of the levels of the nodes but it allows some flexibility
+ List<TextData> texts = generatePreferredNaturalLanguageDescription(featureTree,description, languages);// first get the description as a raw list of TextData
+
+ StringBuilder descriptionStringBuilder = new StringBuilder(); // the StringBuilder used to generate the description
+ int i = 0,j,level; // i is used to store the index of the TextData to use
+ boolean startSentence = false, firstOne = true;
+
+ for (j=0 ; j<levels.size() ; j++){
+ level = levels.get(j);
+ if (level==-1){
+ if ((j+1)<levels.size() && levels.get(j+1).equals(0)){ // if this node is the direct father of a leaf
+ descriptionStringBuilder.append(secondSeparator + " ");
+ startSentence=true;
+ firstOne=false;
+ String asString = texts.get(i).getText(Language.DEFAULT()).toString();
+ if (asString.length()>1) descriptionStringBuilder.append(asString.substring(0,1).toUpperCase() + asString.substring(1));
+ }
+ i++;
+ }
+ else if (level==0) { // if this node is a leaf
+ if (startSentence) descriptionStringBuilder.append(texts.get(i).getText(Language.DEFAULT()));
+ else descriptionStringBuilder.append(firstSeparator + texts.get(i).getText(Language.DEFAULT()));
+ startSentence=false;
+ i++;
+ }
+ else {
+ if (!firstOne && levels.get(j-1).equals(0)){ // if this node corresponds to the states linked to the previous leaf
+ if (i<texts.size()) descriptionStringBuilder.append(texts.get(i).getText(Language.DEFAULT()));
+ i++;
+ }
+ }
+ }
+ descriptionStringBuilder.append(secondSeparator);
+ String returnString = descriptionStringBuilder.toString();
+ returnString = StringUtils.replace(returnString, " ", " ");
+ returnString = StringUtils.removeStart(returnString, secondSeparator + " ");
+ return TextData.NewInstance(returnString,Language.DEFAULT(),TextFormat.NewInstance("", "Text", ""));
+ }
+
+
+
+ /** recursive function that goes through a tree containing the order in which the description has to be generated,
+ * if an element of this tree matches one of the TaxonDescription, a DescriptionBuilder is called which returns a TextData with the corresponding description.
+ *
+ * @param children the children of the feature node considered
+ * @param parent the feature node considered
+ * @param description the TaxonDescription element for which we want a natural language output
+ * @param language The language in which the description has to be written
+ * @param floor integer to keep track of the level in the tree
+ * @return a list of TextData elements containing the part of description corresponding to the feature node considered
+ */
+ private List<TextData> buildBranchesDescr(List<FeatureNode> children, FeatureNode parent, TaxonDescription description, List<Language> languages, int floor) {
+ List<TextData> listTextData = new ArrayList<TextData>();
+ floor++; // counter to know the current level in the tree
+
+ if (!parent.isLeaf()){ // if this node is not a leaf, continue recursively (only the leaves of a FeatureTree contain states)
+ levels.add(new Integer(floor)); // the level of the different nodes in the tree are kept, thus it is easier to build a structured text out of the List<TextData>
+ Feature feature = parent.getFeature();
+ TextData featureName;
+ if (feature!=null && feature.getLabel()!=null){ // if a node is associated to a feature
+ featureName = categoricalDescriptionBuilder.buildTextDataFeature(feature, languages);
+ levels.add(new Integer(-1)); // it is indicated by a '-1' after its level
+ listTextData.add(featureName); // the TextData representing the name of the feature is concatenated to the list
+ }
+ else featureName = new TextData(); // else an empty TextData is created (because we keep track of the features, it is useful to inform when the upper node has no feature attached)
+
for (Iterator<FeatureNode> ifn = children.iterator() ; ifn.hasNext() ;){
+ previousTextData = featureName; // this allows to keep track of the name of the feature one level up in the tree
FeatureNode fn = ifn.next();
- listTextData.addAll(buildBranchesDescr(fn.getChildren(),fn,description, leaf));
+ listTextData.addAll(buildBranchesDescr(fn.getChildren(),fn,description, languages, floor));
}
}
- else {
- Feature fref = parent.getFeature();
- if (fref!=null) { // needs a better algorithm
- int k=0;
- Set<DescriptionElementBase> elements = description.getElements();
- for (Iterator<DescriptionElementBase> deb = elements.iterator() ; deb.hasNext() ;){
- DescriptionElementBase descriptionElement = deb.next();
- TextData textData = TextData.NewInstance();
- if (descriptionElement.getFeature().equals(fref)){
- if (descriptionElement instanceof CategoricalData) {
+ else { //once a leaf is reached
+ Feature feature = parent.getFeature();
+ if (feature!=null && (feature.isSupportsQuantitativeData() || feature.isSupportsCategoricalData())) {
+ Set<DescriptionElementBase> elements = description.getElements();
+ for (Iterator<DescriptionElementBase> deb = elements.iterator() ; deb.hasNext() ;){ // iterates over all the descriptions enclosed in the TaxonDescription
+ DescriptionElementBase descriptionElement = deb.next();
+ if (descriptionElement.getFeature().equals(feature)){ // if one matches the corresponding feature associated to this leaf
+ if (descriptionElement instanceof CategoricalData || descriptionElement instanceof QuantitativeData){
+ TextData featureTextData;
+ TextData statesTextData;
+ if (descriptionElement instanceof CategoricalData) { // if this description is a CategoricalData, generate the according TextData
CategoricalData categoricalData = (CategoricalData) descriptionElement;
- textData = buildCategoricalDescr(categoricalData);
- listTextData.add(textData);
+ statesTextData = categoricalDescriptionBuilder.build(categoricalData, languages);
+ featureTextData = categoricalDescriptionBuilder.buildTextDataFeature(feature, languages);
}
- if (descriptionElement instanceof QuantitativeData) {
+ else { // if this description is a QuantitativeData, generate the according TextData
QuantitativeData quantitativeData = (QuantitativeData) descriptionElement;
- textData = buildQuantitativeDescr(quantitativeData);
- listTextData.add(textData);
+ statesTextData = quantitativeDescriptionBuilder.build(quantitativeData, languages);
+ featureTextData = quantitativeDescriptionBuilder.buildTextDataFeature(feature, languages);
}
+ applyNaturalLanguageDescriptionElementProcessors(featureTextData, previousTextData);
+ levels.add(new Integer(0)); // 0 indicates a feature, which is a leaf of the tree
+ listTextData.add(featureTextData);
+ levels.add(new Integer(floor)); // this represents the level of the feature and means it is followed by a TextData containing the states of the feature
+ listTextData.add(statesTextData);
}
}
- leaf = true;
+ }
}
}
return listTextData;
- }
+ }
- //TODO manage different languages ?
- private TextData buildQuantitativeDescr (QuantitativeData quantitativeData) throws ParseException {
-
- boolean average = false;
- float averagevalue = new Float(0);
- boolean sd = false;
- float sdvalue = new Float(0);
- boolean min = false;
- float minvalue = new Float(0);
- boolean max = false;
- float maxvalue = new Float(0);
- boolean lowerb = false;
- float lowerbvalue = new Float(0);
- boolean upperb = false;
- float upperbvalue = new Float(0);
-
- StringBuilder QuantitativeDescription = new StringBuilder();
- Feature feature = quantitativeData.getFeature();
- TextData textData = TextData.NewInstance(feature);
- QuantitativeDescription.append(" "+feature.getLabel());
- String unit = quantitativeData.getUnit().getLabel();
- Set<StatisticalMeasurementValue> statisticalValues = quantitativeData.getStatisticalValues();
- for (Iterator<StatisticalMeasurementValue> smv = statisticalValues.iterator() ; smv.hasNext() ;){
- StatisticalMeasurementValue statisticalValue = smv.next();
- StatisticalMeasure type = statisticalValue.getType();
- if (type.equals(StatisticalMeasure.AVERAGE())) {
- average = true;
- averagevalue = statisticalValue.getValue();
- } else if(type.equals(StatisticalMeasure.STANDARD_DEVIATION())) {
- sd = true;
- sdvalue = statisticalValue.getValue();
- } else if (type.equals(StatisticalMeasure.MIN())) {
- min = true;
- minvalue = statisticalValue.getValue();
- } else if (type.equals(StatisticalMeasure.MAX())) {
- max = true;
- maxvalue = statisticalValue.getValue();
- } else if (type.equals(StatisticalMeasure.TYPICAL_LOWER_BOUNDARY())) {
- lowerb = true;
- lowerbvalue = statisticalValue.getValue();
- } else if (type.equals(StatisticalMeasure.TYPICAL_UPPER_BOUNDARY())) {
- upperb = true;
- upperbvalue = statisticalValue.getValue();
- }
- }
- if (max && min) {
- QuantitativeDescription.append(" from " + minvalue + " to " + maxvalue + unit);
- }
- else if (min) {
- QuantitativeDescription.append(" from " + minvalue + " " + unit);
- }
- else if (max) {
- QuantitativeDescription.append(" up to " + maxvalue + " " + unit);
- }
- if ((max||min)&&(lowerb||upperb)) {
- QuantitativeDescription.append(",");
- }
- if ((lowerb||upperb)&&(min||max)) {
- QuantitativeDescription.append(" most frequently");
- }
- if (upperb && lowerb) {
- QuantitativeDescription.append(" from " + lowerbvalue + " to " + upperbvalue + unit);
- }
- else if (lowerb) {
- QuantitativeDescription.append(" from " + lowerbvalue + " " + unit);
- }
- else if (upperb) {
- QuantitativeDescription.append(" up to " + upperbvalue + " " + unit);
- }
- if (((max||min)&&(average))||((lowerb||upperb)&&(average))) {
- QuantitativeDescription.append(",");
- }
- if (average) {
- QuantitativeDescription.append(" " + averagevalue + unit + " on average ");
- if (sd) {
- QuantitativeDescription.append("(+/- " + sdvalue + ")");
- }
- }
- textData.putText(QuantitativeDescription.toString(), Language.ENGLISH());
- return textData;
- }
-
- private TextData buildCategoricalDescr(CategoricalData categoricalData) throws ParseException {
- Feature feature = categoricalData.getFeature();
- TextData textData = TextData.NewInstance(feature);
- List<StateData> states = categoricalData.getStates();
-
- StringBuilder CategoricalDescription = new StringBuilder();
- //CategoricalDescription.append(" "+feature.getLabel());
-
- for (Iterator<StateData> sd = states.iterator() ; sd.hasNext() ;){
- StateData stateData = sd.next();
- State s = stateData.getState();
- Set<Modifier> modifiers = stateData.getModifiers();
- for (Iterator<Modifier> mod = modifiers.iterator() ; mod.hasNext() ;){
- Modifier modifier = mod.next();
- CategoricalDescription.append(" " + modifier.getLabel());
- }
- CategoricalDescription.append(" " + s.getLabel());
- }
- textData.putText(CategoricalDescription.toString(), Language.ENGLISH());
- return textData ;
- }
-
}
BGBM BDI Projects / cdmlib.git / blobdiff