git-svn-id: https://svn.d4science.research-infrastructures.eu/gcube/trunk/data-analysis/EcologicalEngine@51844 82a268e6-3cf1-43bd-a215-b396298e98cf
This commit is contained in:
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@ -10,10 +10,12 @@ import org.gcube.contentmanagement.lexicalmatcher.analysis.core.LexicalEngineCon
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import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
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import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
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import org.gcube.dataanalysis.ecoengine.interfaces.Evaluator;
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import org.gcube.dataanalysis.ecoengine.models.cores.aquamaps.Hspen;
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import org.gcube.dataanalysis.ecoengine.processing.factories.EvaluatorsFactory;
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import org.gcube.dataanalysis.ecoengine.utils.DatabaseFactory;
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import org.gcube.dataanalysis.ecoengine.utils.DatabaseUtils;
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import org.gcube.dataanalysis.ecoengine.utils.Operations;
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import org.gcube.dataanalysis.ecoengine.utils.Tuple;
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import org.hibernate.SessionFactory;
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import org.jfree.data.category.DefaultCategoryDataset;
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@ -22,23 +24,27 @@ public class BioClimateAnalysis {
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private static String countHighProbabilityCells = "select count(*) from %1$s where probability>%2$s";
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private static String countSeaCells = "select count(*) from %1$s as a join %2$s as b on a.oceanarea>0 and a.csquarecode=b.csquarecode and ((a.iceconann<b.iceconann-%3$s or a.iceconann>b.iceconann+%3$s) or " + "(a.salinitymean<b.salinitymean-%3$s or a.salinitymean>b.salinitymean+%3$s) or (a.sstanmean<b.sstanmean-%3$s or a.sstanmean>b.sstanmean+%3$s))";
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private static String iceLeakage = "select count(*) from %1$s as a join %2$s as b on a.csquarecode=b.csquarecode and (a.iceconann<b.iceconann) and a.oceanarea>0";
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private static String takeRangeOfDepths= "select distinct depthmin, max(depthmax) from %1$s group by depthmin order by depthmin";
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private static String countNumberOfSpecies= "count(*) from %1$s where depthmin<%2$s and depthmin>=%3$s and depthmax<%4$s and depthmax>=%5$s";
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// private static String takeRangeOfDepths = "select distinct depthmin, max(depthmax) from %1$s group by depthmin order by depthmin";
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private static String takeRangeOfDepths = "select distinct depthmin, depthmax from %1$s order by depthmin";
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private static String takeRangeOfParam = "select %1$s from %2$s where %1$s is not null %3$s order by %1$s";
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private static String countNumberOfSpeciesPerRange = "select count(*) from %1$s where %4$s>%2$s and %4$s<=%3$s ";
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private static String countNumberOfSpecies = "select count(*) from %1$s where depthmin<%2$s and depthmin>=%3$s and depthmax<%4$s and depthmax>=%5$s";
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private static String countProbabilityPerArea = "select count(*) from %1$s as a join hcaf_s as b on b.%2$s = %3$s and a.probability > #THRESHOLD# and a.csquarecode=b.csquarecode";
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public static String salinityDefaultRange = "salinitymin>27.44 and salinitymin<=36.57";
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public static String salinityMinFeature = "salinitymin";
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private static enum FIELD {
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iceconann, sstanmean, salinitymean
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};
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private static String takeAvgSelection = "select avg(%1$s),%2$s from %3$s %4$s group by %2$s order by %2$s";
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private static String [] selectionCriteria = {"faoaream", "lme"};
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private static String [] timeseriesNames = {"Ice Conc.", "Sea Surface Temperature","Salinity"};
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private static String [] quantitiesNames= {FIELD.iceconann.name(), FIELD.sstanmean.name(),FIELD.salinitymean.name()};
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private static String [] selectionFilters= {"where faoaream>0", "where lme>0"};
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private static String [] criteriaNames = {"FaoArea", "LME"};
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private static String[] selectionCriteria = { "faoaream", "lme" };
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private static String[] timeseriesNames = { "Ice Conc.", "Sea Surface Temperature", "Salinity" };
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private static String[] quantitiesNames = { FIELD.iceconann.name(), FIELD.sstanmean.name(), FIELD.salinitymean.name() };
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private static String[] criteriaFilters = { "where faoaream>0", "where lme>0" };
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private static String[] criteriaNames = { "FaoArea", "LME" };
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// private static String takeSubHspec = "select %1$s from #CLAUSE# order by %1$s";
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private static String meanVal = "select avg(%2$s) from %1$s where oceanarea>0";
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@ -71,6 +77,7 @@ public class BioClimateAnalysis {
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static int width = 680;
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static int height = 420;
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static int defaultNumOfFeatureClusters = 10;
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public static void main(String[] args) throws Exception {
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String configPath = "./cfg/";
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@ -81,7 +88,7 @@ public class BioClimateAnalysis {
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bioClimate.produceGraphs2D();
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}
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private static String[] SERIES = { "High Probability Cells Trend (>0.8)", "Number of Changing Cells", "Reducing Ice Concentration Trend", "Average Discrepancy Between Distributions", "Average Trends", "Ice Concentration", "Sea Surface Temperature", "Salinity" };
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private static String[] SERIES = { "High Probability Cells Trend (>%1$s)", "Number of Changing Cells", "Reducing Ice Concentration Trend", "Average Discrepancy Between Distributions", "Average Trends", "Ice Concentration", "Sea Surface Temperature", "Salinity" };
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public void produceGraphs2D() throws Exception {
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DefaultCategoryDataset testpoints = new DefaultCategoryDataset();
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@ -98,14 +105,14 @@ public class BioClimateAnalysis {
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lineg9.render(testpoints);
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}
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private List<Image> producedImages;
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private HashMap<String,Image> producedImages;
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public List<Image> getProducedImages() {
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public HashMap<String,Image> getProducedImages() {
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return producedImages;
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}
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private void produceGraphs(String [] csquareTableNames,String[] hspecTableNames) throws Exception {
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producedImages = new ArrayList<Image>();
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private void produceGraphs(String[] csquareTableNames, String[] hspecTableNames, float threshold) throws Exception {
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producedImages = new HashMap<String,Image> ();
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int numberOfTrends = highProbabilityCells.length;
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// create the datasets...
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@ -129,7 +136,6 @@ public class BioClimateAnalysis {
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}
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}
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}
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if (doHspecAn) {
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@ -137,14 +143,14 @@ public class BioClimateAnalysis {
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discrepancies[0] = min;
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if (liveRender) {
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BioClimateGraph lineg1 = new BioClimateGraph(SERIES[0], Operations.getMax(highProbabilityCells), Operations.getMin(highProbabilityCells));
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BioClimateGraph lineg1 = new BioClimateGraph(String.format(SERIES[0],threshold), Operations.getMax(highProbabilityCells), Operations.getMin(highProbabilityCells));
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BioClimateGraph lineg4 = new BioClimateGraph(SERIES[3], Operations.getMax(discrepancies), min);
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lineg4.render(discrepanciesTrend);
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lineg1.render(probabilityTrend);
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}
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producedImages.add(BioClimateGraph.renderStaticImgObject(width, height, probabilityTrend, SERIES[0], Operations.getMax(highProbabilityCells), Operations.getMin(highProbabilityCells)));
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producedImages.add(BioClimateGraph.renderStaticImgObject(width, height, discrepanciesTrend, SERIES[3], Operations.getMax(discrepancies), min));
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producedImages.put("Probability_Trend",BioClimateGraph.renderStaticImgObject(width, height, probabilityTrend, String.format(SERIES[0],threshold), Operations.getMax(highProbabilityCells), Operations.getMin(highProbabilityCells)));
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producedImages.put("Probability_Discrepancies_Trend",BioClimateGraph.renderStaticImgObject(width, height, discrepanciesTrend, SERIES[3], Operations.getMax(discrepancies), min));
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}
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if (doHcafAn) {
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@ -158,9 +164,9 @@ public class BioClimateAnalysis {
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lineg8.render(avgSalinityD);
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}
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producedImages.add(BioClimateGraph.renderStaticImgObject(width, height, avgIceD, SERIES[5], Operations.getMax(avgIce), Operations.getMin(avgIce)));
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producedImages.add(BioClimateGraph.renderStaticImgObject(width, height, avgSSTD, SERIES[6], Operations.getMax(avgSST), Operations.getMin(avgSST)));
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producedImages.add(BioClimateGraph.renderStaticImgObject(width, height, avgSalinityD, SERIES[7], Operations.getMax(avgSalinity), Operations.getMin(avgSalinity)));
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producedImages.put("Average_Ice_Concentration",BioClimateGraph.renderStaticImgObject(width, height, avgIceD, SERIES[5], Operations.getMax(avgIce), Operations.getMin(avgIce)));
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producedImages.put("Average_SST",BioClimateGraph.renderStaticImgObject(width, height, avgSSTD, SERIES[6], Operations.getMax(avgSST), Operations.getMin(avgSST)));
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producedImages.put("Average_Salinity",BioClimateGraph.renderStaticImgObject(width, height, avgSalinityD, SERIES[7], Operations.getMax(avgSalinity), Operations.getMin(avgSalinity)));
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}
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@ -168,44 +174,220 @@ public class BioClimateAnalysis {
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}
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public void hcafEvolutionAnalysis(String[] hcafTable,String[] hcafTableNames) throws Exception {
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globalEvolutionAnalysis(hcafTable, null, hcafTableNames, null, null, null);
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public void hcafEvolutionAnalysis(String[] hcafTable, String[] hcafTableNames) throws Exception {
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globalEvolutionAnalysis(hcafTable, null, hcafTableNames, null, null, null,0f);
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}
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public void hspecEvolutionAnalysis(String[] hspecTables, String[] hspecTableNames, String probabilityColumn, String csquareColumn) throws Exception {
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globalEvolutionAnalysis(null, hspecTables, null, hspecTableNames, probabilityColumn, csquareColumn);
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public void hspecEvolutionAnalysis(String[] hspecTables, String[] hspecTableNames, String probabilityColumn, String csquareColumn,float threshold) throws Exception {
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globalEvolutionAnalysis(null, hspecTables, null, hspecTableNames, probabilityColumn, csquareColumn, threshold);
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}
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private List<Image> producedCharts;
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public void produceCharts(HashMap<String,HashMap<String,double []>> GeoMap,String[] hcafTablesNames){
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//produce a char for each feature
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producedCharts = new ArrayList<Image>();
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for (String featurename:GeoMap.keySet()){
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public void produceCharts(HashMap<String, HashMap<String, double[]>> GeoMap, String[] tablesNames) {
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// produce a char for each feature
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producedImages = new HashMap<String,Image> ();
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for (String featurename : GeoMap.keySet()) {
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DefaultCategoryDataset chart = new DefaultCategoryDataset();
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HashMap<String,double []> timeseries = GeoMap.get(featurename);
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HashMap<String, double[]> timeseries = GeoMap.get(featurename);
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double absmax = -Double.MAX_VALUE;
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double absmin = Double.MAX_VALUE;
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for (String timeserie:timeseries.keySet()){
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for (String timeserie : timeseries.keySet()) {
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double[] points = timeseries.get(timeserie);
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for (int i=0;i<points.length;i++){
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if (points [i]>absmax)
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for (int i = 0; i < points.length; i++) {
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if (points[i] > absmax)
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absmax = points[i];
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if (points [i]<absmin)
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if (points[i] < absmin)
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absmin = points[i];
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chart.addValue(points[i], timeserie,hcafTablesNames[i]);
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chart.addValue(points[i], timeserie, tablesNames[i]);
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}
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}
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if (liveRender) {
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BioClimateGraph lineg1 = new BioClimateGraph(featurename, absmax, absmin);
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lineg1.render(chart);
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}
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producedCharts.add(BioClimateGraph.renderStaticImgObject(width, height, chart, featurename, absmax, absmin));
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producedImages.put(featurename.replace(" ", "_"),BioClimateGraph.renderStaticImgObject(width, height, chart, featurename, absmax, absmin));
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}
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}
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/**
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* Generates a chart for hspens in time according to a certain interval in the parameter
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* e.g. : a chart for several salinity intervals
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* @param hspenTables
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* @param hspenTableNames
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* @param parameterName
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* @param condition
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* @throws Exception
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*/
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public void speciesEvolutionAnalysis(String[] hspenTables, String[] hspenTableNames, String parameterName, String condition) throws Exception {
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try {
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referencedbConnection = DatabaseFactory.initDBConnection(configPath + AlgorithmConfiguration.defaultConnectionFile, config);
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AnalysisLogger.getLogger().debug("ReferenceDB initialized");
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status = 0f;
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int numbOfTables = (hspenTables != null) ? hspenTables.length : 0;
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if (numbOfTables > 0) {
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// a map for each range of features: depth[0,100] ,depth [100,200]
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HashMap<String, HashMap<String, double[]>> GeoMap = new HashMap<String, HashMap<String, double[]>>();
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float statusstep = 80f / (float) numbOfTables;
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if (condition != null && (condition.length() > 0))
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condition = "and " + condition;
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// take the spectrum of depths
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AnalysisLogger.getLogger().trace("Range query: " + String.format(takeRangeOfParam, parameterName, hspenTables[0], condition));
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List<Object> paramrange = DatabaseFactory.executeSQLQuery(String.format(takeRangeOfParam, parameterName, hspenTables[0], condition), referencedbConnection);
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int numberOfParams = paramrange.size();
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double absolutePMin = Double.parseDouble("" + ((Object) paramrange.get(0)));
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double absolutePMax = Double.parseDouble("" + ((Object) paramrange.get(numberOfParams - 1)));
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double step = (absolutePMax - absolutePMin) / (double) defaultNumOfFeatureClusters;
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int pClusters[] = new int[defaultNumOfFeatureClusters + 1];
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pClusters[0] = 0;
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for (int i = 1; i < pClusters.length; i++) {
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double pToFind = absolutePMin + step * (i + 1);
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int k = 0;
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for (Object row : paramrange) {
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if (Double.parseDouble("" + ((Object) row)) > pToFind)
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break;
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k++;
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}
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if (k >= numberOfParams)
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k = numberOfParams - 1;
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pClusters[i] = k;
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}
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// for each table
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for (int i = 0; i < numbOfTables; i++) {
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double pmax = 0;
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// for each cluster build up a chart
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for (int j = 1; j < pClusters.length; j++) {
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double prevpmax = MathFunctions.roundDecimal(Double.parseDouble("" + (Object) paramrange.get(pClusters[j - 1])),2);
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pmax = MathFunctions.roundDecimal(Double.parseDouble("" + (Object) paramrange.get(pClusters[j])),2);
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if (prevpmax != pmax) {
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// take the number of elements for this range
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String countSpeciesQuery = String.format(countNumberOfSpeciesPerRange, hspenTables[i], prevpmax, pmax, parameterName);
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AnalysisLogger.getLogger().trace("count elements query: " + countSpeciesQuery);
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List<Object> elementsInRange = DatabaseFactory.executeSQLQuery(countSpeciesQuery, referencedbConnection);
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int nelements = (elementsInRange == null) ? 0 : Integer.parseInt("" + elementsInRange.get(0));
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AnalysisLogger.getLogger().trace("Number of elements for " + hspenTables[i] + " in (" + prevpmax + " - " + pmax + ")" + " : " + nelements);
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// take the chart for this range
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String chartName = parameterName + " envelope for interval (" + prevpmax + " ; " + pmax + ")";
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// build the chart
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HashMap<String, double[]> submap = GeoMap.get(chartName);
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if (submap == null) {
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submap = new HashMap<String, double[]>();
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GeoMap.put(chartName, submap);
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}
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String timeseries = "number of species";
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double[] elements = submap.get(timeseries);
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if (elements == null) {
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elements = new double[numbOfTables];
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submap.put(timeseries, elements);
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}
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elements[i] = nelements;
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}
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}
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status = status + statusstep;
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}
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status = 80f;
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produceCharts(GeoMap, hspenTableNames);
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}
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} catch (Exception e) {
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e.printStackTrace();
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throw e;
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} finally {
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status = 100f;
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referencedbConnection.close();
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}
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}
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/**
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* Generates a chart for hspec probability > thr in each Fao Area and LME
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* @param hspecTables
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* @param hspecTablesNames
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* @throws Exception
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*/
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public void speciesGeographicEvolutionAnalysis(String[] hspecTables, String[] hspecTablesNames, float threshold) throws Exception {
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try {
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referencedbConnection = DatabaseFactory.initDBConnection(configPath + AlgorithmConfiguration.defaultConnectionFile, config);
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AnalysisLogger.getLogger().debug("ReferenceDB initialized");
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status = 0f;
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int numbOfTables = (hspecTables != null) ? hspecTables.length : 0;
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if (numbOfTables > 0) {
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// a map for each feature. each sub map contains a trend for faoaream, lme etc.
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HashMap<String, HashMap<String, double[]>> GeoMap = new HashMap<String, HashMap<String, double[]>>();
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float statusstep = 80f / (float) numbOfTables;
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// for each table
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for (int i = 0; i < numbOfTables; i++) {
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// for each criterion to apply: fao area, lme etc.
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for (int j = 0; j < criteriaNames.length; j++) {
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List<Object> listCriterion = DatabaseFactory.executeSQLQuery(DatabaseUtils.getDinstictElements("hcaf_s", selectionCriteria[j],criteriaFilters[j]),referencedbConnection);
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for (Object code: listCriterion){
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String code$ = ""+code;
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String query = String.format(countProbabilityPerArea,hspecTables[i],selectionCriteria[j],code$);
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query = query.replace("#THRESHOLD#", ""+threshold);
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AnalysisLogger.getLogger().trace("Executing query for counting probabilities: "+query);
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List<Object> counts = DatabaseFactory.executeSQLQuery(query, referencedbConnection);
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AnalysisLogger.getLogger().trace("Query Executed");
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int countPerArea = (counts==null)?0:Integer.parseInt(""+counts.get(0));
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String chartName = "Hspec (prob>0.8) for " + criteriaNames[j] + "_" + code$;
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// put the code and the value in the timeseries associated to the feature name
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HashMap<String, double[]> submap = GeoMap.get(chartName);
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if (submap == null) {
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submap = new HashMap<String, double[]>();
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GeoMap.put(chartName, submap);
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}
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String timeseries = "number of occupied cells";
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double[] elements = submap.get(timeseries);
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if (elements == null) {
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elements = new double[numbOfTables];
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submap.put(timeseries, elements);
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}
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elements[i] = countPerArea;
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}
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}
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status = status + statusstep;
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}
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status = 80f;
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produceCharts(GeoMap, hspecTablesNames);
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}
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} catch (Exception e) {
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e.printStackTrace();
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throw e;
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} finally {
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status = 100f;
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referencedbConnection.close();
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}
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}
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public void geographicEvolutionAnalysis(String[] hcafTable,String []hcafTableNames) throws Exception {
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/**
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* Generates a geographic trend for each hspec feature: ice con, salinity, sst in each fao area
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* @param hcafTable
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* @param hcafTableNames
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* @throws Exception
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*/
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public void geographicEvolutionAnalysis(String[] hcafTable, String[] hcafTableNames) throws Exception {
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try {
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referencedbConnection = DatabaseFactory.initDBConnection(configPath + AlgorithmConfiguration.defaultConnectionFile, config);
|
||||
AnalysisLogger.getLogger().debug("ReferenceDB initialized");
|
||||
|
|
@ -217,40 +399,40 @@ public class BioClimateAnalysis {
|
|||
int numbOfTables = (hcafTable != null) ? hcafTable.length : 0;
|
||||
|
||||
if (numbOfTables > 0) {
|
||||
|
||||
//a map for each feature. each sub map contains a trend for faoaream, lme etc.
|
||||
HashMap<String,HashMap<String,double []>> GeoMap= new HashMap<String, HashMap<String,double[]>>();
|
||||
|
||||
|
||||
// a map for each feature. each sub map contains a trend for faoaream, lme etc.
|
||||
HashMap<String, HashMap<String, double[]>> GeoMap = new HashMap<String, HashMap<String, double[]>>();
|
||||
|
||||
float statusstep = 80f / (float) numbOfTables;
|
||||
//for each table
|
||||
// for each table
|
||||
for (int i = 0; i < numbOfTables; i++) {
|
||||
//for each criterion to apply: fao area, lme etc.
|
||||
for (int j=0;j<criteriaNames.length;j++){
|
||||
//for each quantity to display: ice concentration
|
||||
for (int k=0;k<quantitiesNames.length;k++){
|
||||
String query = String.format(takeAvgSelection, quantitiesNames[k],selectionCriteria[j],hcafTable[i],selectionFilters[j]);
|
||||
AnalysisLogger.getLogger().debug("Query to be executed : "+query);
|
||||
//take couples (avg,code)
|
||||
// for each criterion to apply: fao area, lme etc.
|
||||
for (int j = 0; j < criteriaNames.length; j++) {
|
||||
// for each quantity to display: ice concentration
|
||||
for (int k = 0; k < quantitiesNames.length; k++) {
|
||||
String query = String.format(takeAvgSelection, quantitiesNames[k], selectionCriteria[j], hcafTable[i], criteriaFilters[j]);
|
||||
AnalysisLogger.getLogger().debug("Query to be executed : " + query);
|
||||
// take couples (avg,code)
|
||||
List<Object> quantityCriterion = DatabaseFactory.executeSQLQuery(query, referencedbConnection);
|
||||
//for each row
|
||||
for (Object element: quantityCriterion){
|
||||
Object [] row = (Object[]) element;
|
||||
//take avg value
|
||||
double value = (row[0]==null)?0:Double.parseDouble(""+row[0]);
|
||||
//take code for criterion
|
||||
String code = ""+row[1];
|
||||
|
||||
String chartName = timeseriesNames[k]+" for "+criteriaNames[j]+"_"+code;
|
||||
//put the code and the value in the timeseries associated to the feature name
|
||||
HashMap<String,double []> submap = GeoMap.get(chartName);
|
||||
if (submap==null){
|
||||
// for each row
|
||||
for (Object element : quantityCriterion) {
|
||||
Object[] row = (Object[]) element;
|
||||
// take avg value
|
||||
double value = (row[0] == null) ? 0 : Double.parseDouble("" + row[0]);
|
||||
// take code for criterion
|
||||
String code = "" + row[1];
|
||||
|
||||
String chartName = timeseriesNames[k] + " for " + criteriaNames[j] + "_" + code;
|
||||
// put the code and the value in the timeseries associated to the feature name
|
||||
HashMap<String, double[]> submap = GeoMap.get(chartName);
|
||||
if (submap == null) {
|
||||
submap = new HashMap<String, double[]>();
|
||||
GeoMap.put(chartName, submap);
|
||||
}
|
||||
|
||||
String timeseries = criteriaNames[j]+"_"+code;
|
||||
double [] elements = submap.get(timeseries);
|
||||
if (elements==null){
|
||||
|
||||
String timeseries = criteriaNames[j] + "_" + code;
|
||||
double[] elements = submap.get(timeseries);
|
||||
if (elements == null) {
|
||||
elements = new double[numbOfTables];
|
||||
submap.put(timeseries, elements);
|
||||
}
|
||||
|
|
@ -260,9 +442,9 @@ public class BioClimateAnalysis {
|
|||
}
|
||||
status = status + statusstep;
|
||||
}
|
||||
|
||||
|
||||
status = 80f;
|
||||
produceCharts(GeoMap,hcafTableNames);
|
||||
produceCharts(GeoMap, hcafTableNames);
|
||||
}
|
||||
} catch (Exception e) {
|
||||
e.printStackTrace();
|
||||
|
|
@ -273,7 +455,18 @@ public class BioClimateAnalysis {
|
|||
}
|
||||
}
|
||||
|
||||
public void globalEvolutionAnalysis(String[] hcafTable, String[] hspecTables,String[] hcafTablesNames, String [] hspecTableNames, String probabilityColumn, String csquareColumn) throws Exception {
|
||||
/**
|
||||
* Generates a chart for each hspec feature
|
||||
* Generates a chart for hspec prob > thr and performs a discrepancy analysis on hspec
|
||||
* @param hcafTable
|
||||
* @param hspecTables
|
||||
* @param hcafTablesNames
|
||||
* @param hspecTableNames
|
||||
* @param probabilityColumn
|
||||
* @param csquareColumn
|
||||
* @throws Exception
|
||||
*/
|
||||
public void globalEvolutionAnalysis(String[] hcafTable, String[] hspecTables, String[] hcafTablesNames, String[] hspecTableNames, String probabilityColumn, String csquareColumn,float threshold) throws Exception {
|
||||
try {
|
||||
referencedbConnection = DatabaseFactory.initDBConnection(configPath + AlgorithmConfiguration.defaultConnectionFile, config);
|
||||
AnalysisLogger.getLogger().debug("ReferenceDB initialized");
|
||||
|
|
@ -301,7 +494,7 @@ public class BioClimateAnalysis {
|
|||
|
||||
for (int i = 0; i < numbOfPoints; i++) {
|
||||
if (doHspecAn)
|
||||
highProbabilityCells[i] = calcHighProbabilityCells(hspecTables[i], 0.8);
|
||||
highProbabilityCells[i] = calcHighProbabilityCells(hspecTables[i], threshold);
|
||||
|
||||
if (doHcafAn) {
|
||||
avgIce[i] = avgValue(hcafTable[i], FIELD.iceconann.name());
|
||||
|
|
@ -325,7 +518,7 @@ public class BioClimateAnalysis {
|
|||
status = status + statusstep;
|
||||
}
|
||||
status = 80f;
|
||||
produceGraphs(hcafTablesNames,hspecTableNames);
|
||||
produceGraphs(hcafTablesNames, hspecTableNames,threshold);
|
||||
|
||||
} catch (Exception e) {
|
||||
e.printStackTrace();
|
||||
|
|
@ -362,8 +555,6 @@ public class BioClimateAnalysis {
|
|||
return count;
|
||||
}
|
||||
|
||||
|
||||
|
||||
public double avgValue(String hcaf1, String field) throws Exception {
|
||||
|
||||
List<Object> countage = DatabaseFactory.executeSQLQuery(String.format(meanVal, hcaf1, field), referencedbConnection);
|
||||
|
|
|
|||
|
|
@ -101,6 +101,10 @@ public class DatabaseUtils {
|
|||
return "drop table " + table;
|
||||
}
|
||||
|
||||
public static String getDinstictElements(String table, String column,String filter) {
|
||||
return "select distinct " + column + " from " + table + " " + filter+" order by " + column;
|
||||
}
|
||||
|
||||
public static String getOrderedElements(String table, String key, String column) {
|
||||
return "select " + key + "," + column + " from " + table + " order by " + key;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,30 @@
|
|||
package org.gcube.dataanalysis.ecoengine.utils;
|
||||
|
||||
import java.io.Serializable;
|
||||
import java.util.ArrayList;
|
||||
|
||||
public class Tuple <A> implements Serializable{
|
||||
|
||||
private static final long serialVersionUID = 1L;
|
||||
|
||||
ArrayList<A> elements;
|
||||
|
||||
public Tuple(A... elements){
|
||||
this.elements = new ArrayList<A>();
|
||||
for (A element:elements){
|
||||
this.elements.add(element);
|
||||
}
|
||||
}
|
||||
|
||||
public ArrayList<A> getElements(){
|
||||
return elements;
|
||||
}
|
||||
|
||||
public String toString(){
|
||||
String s = "";
|
||||
for (A element:elements){
|
||||
s+=element+" ";
|
||||
}
|
||||
return s;
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue