115 lines
4.0 KiB
Java
115 lines
4.0 KiB
Java
package org.gcube.dataanalysis.geo.connectors.wfs;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
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import org.gcube.dataanalysis.ecoengine.utils.Tuple;
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import org.gcube.dataanalysis.geo.interfaces.GISDataConnector;
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import org.gcube.dataanalysis.geo.utils.CSquareCodesConverter;
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import com.vividsolutions.jts.geom.Coordinate;
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import com.vividsolutions.jts.geom.GeometryFactory;
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import com.vividsolutions.jts.geom.Point;
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import com.vividsolutions.jts.geom.PrecisionModel;
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import com.vividsolutions.jts.geom.impl.CoordinateArraySequence;
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public class WFS implements GISDataConnector {
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List<FeaturedPolygon> featuresInTime;
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HashMap<Double,Map<String, String>> polygonsFeatures;
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@Override
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public List<Double> getFeaturesInTimeInstantAndArea(String layerURL, String layerName, int time, List<Tuple<Double>> coordinates3d, double BBxL, double BBxR, double BByL, double BByR) throws Exception {
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if (time>0)
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throw new Exception("Error Time Dimension is not supported for WFS!");
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if (layerURL == null)
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return null;
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featuresInTime = new ArrayList<FeaturedPolygon>();
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AnalysisLogger.getLogger().debug("taking WFS features");
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featuresInTime = WFSDataExplorer.getFeatures(layerURL, layerName, BBxL, BByL, BBxR, BByR);
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polygonsFeatures=new HashMap<Double, Map<String,String>>();
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int tsize = coordinates3d.size();
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AnalysisLogger.getLogger().debug("Intersecting " + tsize + " vs " + featuresInTime.size() + " elements");
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int ttc = 0;
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Double[] featuresarray = new Double[tsize];
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int k = 0;
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GeometryFactory factory = new GeometryFactory(new PrecisionModel(), 4326);
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for (Tuple<Double> triplet : coordinates3d) {
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ArrayList<Double> elements = triplet.getElements();
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CoordinateArraySequence pcoords = new CoordinateArraySequence(new Coordinate[] { new Coordinate(elements.get(0), elements.get(1)), });
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Point po = new Point(pcoords, factory);
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boolean found = false;
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for (FeaturedPolygon poly : featuresInTime) {
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if (poly != null && poly.p != null && poly.p.covers(po)) {
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/*
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AnalysisLogger.getLogger().debug(poly.p.getCentroid()+
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"["+CSquareCodesConverter.convertAtResolution(poly.p.getCentroid().getY(), poly.p.getCentroid().getX(), 0.5)+"] "+
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"("+(poly.p.getCentroid().getX()-0.25)+" -- "+(poly.p.getCentroid().getX()+0.25) +" ; "+
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(poly.p.getCentroid().getY()-0.25)+" -- "+(poly.p.getCentroid().getY()+0.25) +") "+
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" ["+poly.features+"]"+
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" covers "+po+ "["+CSquareCodesConverter.convertAtResolution(po.getY(), po.getX(), 0.5)+"]");
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AnalysisLogger.getLogger().debug("{"+poly.p.contains(po)+
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";"+po.isWithinDistance(poly.p.getCentroid(), 0.24)+
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";"+po.isWithinDistance(poly.p.getCentroid(), 0.25)+
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";"+poly.p.getCentroid().distance(po)+
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";"+poly.p.distance(po)+
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";"+poly.p.convexHull().contains(po)+
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";"+poly.p.convexHull().touches(po)+
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";"+poly.p.touches(po)+
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";"+poly.p.crosses(po)+
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";"+po.crosses(poly.p)+
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";"+po.coveredBy(poly.p)+
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";"+po.intersection(poly.p)+
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";"+poly.p.contains(po)+
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";"+poly.p.covers(po)+
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"}");
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*/
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featuresarray[k] = poly.value;
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polygonsFeatures.put(poly.value, poly.features);
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found = true;
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break;
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}
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}
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po = null;
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if (!found) {
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featuresarray[k] = Double.NaN;
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}
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if (ttc % 10000 == 0) {
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AnalysisLogger.getLogger().debug("Status: " + ((double) ttc * 100d / (double) tsize));
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}
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ttc++;
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k++;
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}
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List<Double> features = Arrays.asList(featuresarray);
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return features;
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}
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@Override
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public double getMinZ(String layerURL, String layerName) {
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return 0;
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}
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@Override
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public double getMaxZ(String layerURL, String layerName) {
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return 0;
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}
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public HashMap<Double, Map<String, String>> getPolygonsFeatures() {
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return polygonsFeatures;
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}
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}
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