EDIT

package eu.etaxonomy.cdm.api.service;

import java.util.List;

import java.util.Map;

import eu.etaxonomy.cdm.model.common.Language;

import eu.etaxonomy.cdm.model.description.MeasurementUnit;

import eu.etaxonomy.cdm.model.description.NaturalLanguageTerm;

import eu.etaxonomy.cdm.model.description.StatisticalMeasure;

import eu.etaxonomy.cdm.model.description.TextData;

import eu.etaxonomy.cdm.model.description.TextFormat;

/**

 * @author m.venin

 *

 */

public class DefaultQuantitativeDescriptionBuilder extends AbstractQuantitativeDescriptionBuilder {

	String space = " ";

	@Override

	protected TextData doBuild(Map<StatisticalMeasure,Float> measures, MeasurementUnit mUnit, List<Language> languages){

		StringBuilder QuantitativeDescription = new StringBuilder(); // this StringBuilder is used to concatenate the different words of the description before saving it in the TextData

		TextData textData = TextData.NewInstance(); // TextData that will contain the description and the language corresponding

		// booleans indicating whether a kind of value is present or not and the float that will eventually hold the value

		String unit = "";

		if ((mUnit!=null)&&(mUnit.getLabel()!=null)){

			unit = mUnit.getLabel();

		}

		// the different linking words are taken from NaturalLanguageTerm.class (should this be changed ?)

		NaturalLanguageTerm nltFrom = NaturalLanguageTerm.FROM();

		String from = nltFrom.getPreferredRepresentation(languages).getLabel();

		NaturalLanguageTerm nltTo = NaturalLanguageTerm.TO();

		String to = nltTo.getPreferredRepresentation(languages).getLabel();

		NaturalLanguageTerm nltUp_To = NaturalLanguageTerm.UP_TO();

		String up_To = nltUp_To.getPreferredRepresentation(languages).getLabel();

		NaturalLanguageTerm nltMost_Frequently = NaturalLanguageTerm.MOST_FREQUENTLY();

		String most_Frequently = nltMost_Frequently.getPreferredRepresentation(languages).getLabel();

		NaturalLanguageTerm nltOn_Average = NaturalLanguageTerm.ON_AVERAGE();

		String on_Average = nltOn_Average.getPreferredRepresentation(languages).getLabel();

		NaturalLanguageTerm nltMore_Or_Less = NaturalLanguageTerm.MORE_OR_LESS();

		String more_Or_Less = nltMore_Or_Less.getPreferredRepresentation(languages).getLabel();

		// the booleans and floats are updated according to the presence or absence of values

		Boolean max, min, upperb, lowerb, average, sd;

		String averagevalue = getValue(measures,StatisticalMeasure.AVERAGE());

		if (averagevalue!=null) average=true; else average=false;

		String sdvalue = getValue(measures,StatisticalMeasure.STANDARD_DEVIATION());

		if (sdvalue!=null) sd=true; else sd=false;

		String minvalue = getValue(measures,StatisticalMeasure.MIN());

		if (minvalue!=null) min=true; else min=false;

		String maxvalue = getValue(measures,StatisticalMeasure.MAX());

		if (maxvalue!=null) max=true; else max=false;

		String lowerbvalue = getValue(measures,StatisticalMeasure.TYPICAL_LOWER_BOUNDARY());

		if (lowerbvalue!=null) lowerb=true; else lowerb=false;

		String upperbvalue = getValue(measures,StatisticalMeasure.TYPICAL_UPPER_BOUNDARY());

		if (upperbvalue!=null) upperb=true; else upperb=false;

		// depending on the different associations of values, a sentence is built	

		if (max && min) {

			QuantitativeDescription.append(space + from + space + minvalue + space + to + space + maxvalue + space + unit);

		}

		else if (min) {

			QuantitativeDescription.append(space + from + space + minvalue + space + unit);

		}

		else if (max) {

			QuantitativeDescription.append(space + up_To + space + maxvalue + space + unit);

		}

		if ((max||min)&&(lowerb||upperb)) {

			QuantitativeDescription.append(separator); // merge with below ?

		}

		if ((lowerb||upperb)&&(min||max)) {

			QuantitativeDescription.append(space + most_Frequently);

		}

		if (upperb && lowerb) {

			QuantitativeDescription.append(space + from + space + lowerbvalue + space + to + space + upperbvalue + space + unit);

		}

		else if (lowerb) {

			QuantitativeDescription.append(space + from + space + lowerbvalue + space + unit);

		}

		else if (upperb) {

			QuantitativeDescription.append(space + up_To + space + upperbvalue + space + unit);

		}

		if (((max||min)&&(average))||((lowerb||upperb)&&(average))) {

			QuantitativeDescription.append(separator);

		}

		if (average) {

			QuantitativeDescription.append(space + averagevalue + space + unit + space + on_Average);

			if (sd) {

				QuantitativeDescription.append("("+ more_Or_Less + space + sdvalue + ")");

			}

		}

		textData.putText(languages.get(0), QuantitativeDescription.toString()); // which language should be put here ?

		textData.setFormat(TextFormat.NewInstance(null, "Text",null ));

		return textData;

	}

	/**

	 * Returns the value of a given type of measure as a String. If the value is an integer it is printed

	 * as an integer instead of a float.

	 * If no value of this type is present, returns null.

	 * 

	 * @param measures the map with the values

	 * @param key the desired measure

	 * @return

	 */

	private String getValue(Map<StatisticalMeasure,Float> measures, Object key) {

		Float floatValue;

		Integer intValue;

		if(measures.containsKey(key)) {

			floatValue = measures.get(key);

			intValue=floatValue.intValue();

			if (floatValue.equals(intValue.floatValue())) return intValue.toString();

			else return floatValue.toString();

		}

		else return null;

	}

}