/*

 * All Sigmah code is released under the GNU General Public License v3

 * See COPYRIGHT.txt and LICENSE.txt.

 */



package org.sigmah.server.report.generator.map;



import org.junit.Assert;

import org.junit.Test;

import org.sigmah.server.report.generator.MapSymbol;

import org.sigmah.shared.report.content.LatLng;

import org.sigmah.shared.report.content.Point;



import java.io.BufferedReader;

import java.io.InputStreamReader;

import java.util.ArrayList;

import java.util.List;



/*

* Real example that didn't work.

*

* @author Alex Bertram

*/

public class CoincidentPointsClusterTest extends GraphTest {





    @Test

    public void testSimpleData() throws Exception {

        List<PointValue> points = new ArrayList<PointValue>();

        points.add(new PointValue(null, new MapSymbol(), 7.0, new Point(0, 0)));

        points.add(new PointValue(null, new MapSymbol(), 2.0, new Point(0, 0)));

        points.add(new PointValue(null, new MapSymbol(), 41.0, new Point(100, 100)));

        points.add(new PointValue(null, new MapSymbol(), 9.0, new Point(0, 0)));

        points.add(new PointValue(null, new MapSymbol(), 39.0, new Point(100, 100)));



        double originalSum = 7 + 2 + 9 + 41 + 39;



        // Now build the graph



        MarkerGraph graph = new MarkerGraph(points,

                new BubbleLayerGenerator.IntersectionCalculator(15));



        GeneticSolver solver = new GeneticSolver();



        List<Cluster> clusters = solver.solve(graph, new GsLogCalculator(5, 15),

                new CircleFitnessFunctor(), UpperBoundsCalculator.calculate(graph, new FixedRadiiCalculator(5)));



        // check to make sure all values were included

        double sumAfterClustering = 0;

        for (Cluster cluster : clusters) {

            sumAfterClustering += cluster.sumValues();

        }



        Assert.assertEquals(originalSum, sumAfterClustering, 0.0001);



        Assert.assertEquals(2, clusters.size());



        saveClusters(graph, "clusterTest-solution", clusters);





    }





    @Test

    public void testRealData() throws Exception {



        // Define projection for the test case

        TiledMap map = new TiledMap(492, 690, new LatLng(2.293492496, 30.538372993), 9);



        // Read data

        BufferedReader in = new BufferedReader(new InputStreamReader(

                GraphTest.class.getResourceAsStream("/distribscolaire-points.csv")));



        double originalSum = 0;



        List<PointValue> points = new ArrayList<PointValue>();

        while (in.ready()) {



            String line = in.readLine();

            String[] columns = line.split(",");



            double lat = Double.parseDouble(columns[0]);

            double lng = Double.parseDouble(columns[1]);



            PointValue pv = new PointValue();

            pv.px = map.fromLatLngToPixel(new LatLng(lat, lng));

            pv.value = Double.parseDouble(columns[2]);

            pv.symbol = new MapSymbol();



            originalSum += pv.value;



            points.add(pv);

        }



        // Now build the graph



        MarkerGraph graph = new MarkerGraph(points,

                new BubbleLayerGenerator.IntersectionCalculator(15));



        // make sure nothing was lost in the merging of coincident points

        double nodeSum = 0;

        for (MarkerGraph.Node node : graph.getNodes()) {

            nodeSum += node.getPointValue().value;

        }

        Assert.assertEquals("values after construction of graph", originalSum, nodeSum, 0.001);





        saveGraphImage("clusterTest2", graph, 15);



        GeneticSolver solver = new GeneticSolver();



        List<Cluster> clusters = solver.solve(graph, new GsLogCalculator(5, 15),

                new CircleFitnessFunctor(), UpperBoundsCalculator.calculate(graph, new FixedRadiiCalculator(5)));



        // check to make sure all values were included

        double sumAfterClustering = 0;

        for (Cluster cluster : clusters) {

            sumAfterClustering += cluster.sumValues();

        }



        Assert.assertEquals(originalSum, sumAfterClustering, 0.001);



        Assert.assertEquals(16, clusters.size());



        saveClusters(graph, "clusterTest-solution", clusters);

    }



}