Mercurial > dive4elements > river
view artifacts/src/main/java/org/dive4elements/river/artifacts/model/fixings/FixAnalysisCalculation.java @ 6152:0587819960c3
Waterlevel differences & bed height differences: Add new model LinearInterpolated intented to unify the two very similiar calculations. The focus of the current implementation is correctness and not speed! The fact that the data sets more mostly sorted by station is not exploited. Doing so would improve performance significantly.
author | Sascha L. Teichmann <teichmann@intevation.de> |
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date | Sun, 02 Jun 2013 17:52:53 +0200 |
parents | af13ceeba52a |
children | 767b51f8fa9c |
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/* Copyright (C) 2011, 2012, 2013 by Bundesanstalt für Gewässerkunde * Software engineering by Intevation GmbH * * This file is Free Software under the GNU AGPL (>=v3) * and comes with ABSOLUTELY NO WARRANTY! Check out the * documentation coming with Dive4Elements River for details. */ package org.dive4elements.river.artifacts.model.fixings; import org.dive4elements.river.artifacts.access.FixAnalysisAccess; import org.dive4elements.river.artifacts.math.fitting.Function; import org.dive4elements.river.artifacts.model.CalculationResult; import org.dive4elements.river.artifacts.model.DateRange; import org.dive4elements.river.artifacts.model.FixingsOverview.AndFilter; import org.dive4elements.river.artifacts.model.FixingsOverview.DateRangeFilter; import org.dive4elements.river.artifacts.model.FixingsOverview.Fixing.Filter; import org.dive4elements.river.artifacts.model.FixingsOverview.Fixing; import org.dive4elements.river.artifacts.model.FixingsOverview.IdsFilter; import org.dive4elements.river.artifacts.model.FixingsOverview.KmFilter; import org.dive4elements.river.artifacts.model.FixingsOverview.SectorFilter; import org.dive4elements.river.artifacts.model.FixingsOverview; import org.dive4elements.river.artifacts.model.Parameters; import org.dive4elements.river.artifacts.model.Range; import org.dive4elements.river.utils.DateAverager; import org.dive4elements.river.utils.KMIndex; import gnu.trove.TIntIntHashMap; import java.util.ArrayList; import java.util.Date; import java.util.List; import org.apache.commons.math.stat.descriptive.moment.StandardDeviation; import org.apache.log4j.Logger; public class FixAnalysisCalculation extends FixCalculation { private static Logger log = Logger.getLogger(FixAnalysisCalculation.class); protected DateRange referencePeriod; protected DateRange [] analysisPeriods; public FixAnalysisCalculation() { } public FixAnalysisCalculation(FixAnalysisAccess access) { super(access); DateRange referencePeriod = access.getReferencePeriod(); DateRange [] analysisPeriods = access.getAnalysisPeriods(); if (referencePeriod == null) { addProblem("fix.missing.reference.period"); } if (analysisPeriods == null || analysisPeriods.length < 1) { addProblem("fix.missing.analysis.periods"); } if (!hasProblems()) { this.referencePeriod = referencePeriod; this.analysisPeriods = analysisPeriods; } } @Override public CalculationResult innerCalculate( FixingsOverview overview, Function func ) { ColumnCache cc = new ColumnCache(); FitResult fitResult = doFitting(overview, cc, func); if (fitResult == null) { return new CalculationResult(this); } KMIndex<AnalysisPeriod []> analysisPeriods = calculateAnalysisPeriods( func, fitResult.getParameters(), overview, cc); analysisPeriods.sort(); FixAnalysisResult far = new FixAnalysisResult( fitResult.getParameters(), fitResult.getReferenced(), fitResult.getOutliers(), analysisPeriods); return new CalculationResult(far, this); } @Override protected Filter createFilter() { Filter ids = super.createFilter(); DateRangeFilter rdf = new DateRangeFilter( referencePeriod.getFrom(), referencePeriod.getTo()); return new AndFilter().add(rdf).add(ids); } protected KMIndex<AnalysisPeriod []> calculateAnalysisPeriods( Function function, Parameters parameters, FixingsOverview overview, ColumnCache cc ) { Range range = new Range(from, to); int kmIndex = parameters.columnIndex("km"); int maxQIndex = parameters.columnIndex("max_q"); double [] wq = new double[2]; int [] parameterIndices = parameters.columnIndices(function.getParameterNames()); double [] parameterValues = new double[parameterIndices.length]; DateAverager dateAverager = new DateAverager(); KMIndex<AnalysisPeriod []> results = new KMIndex<AnalysisPeriod []>(parameters.size()); IdsFilter idsFilter = new IdsFilter(events); TIntIntHashMap [] col2indices = new TIntIntHashMap[analysisPeriods.length]; for (int i = 0; i < analysisPeriods.length; ++i) { col2indices[i] = new TIntIntHashMap(); } for (int row = 0, R = parameters.size(); row < R; ++row) { double km = parameters.get(row, kmIndex); parameters.get(row, parameterIndices, parameterValues); // This is the paraterized function for a given km. org.dive4elements.river.artifacts.math.Function instance = function.instantiate(parameterValues); KmFilter kmFilter = new KmFilter(km); ArrayList<AnalysisPeriod> periodResults = new ArrayList<AnalysisPeriod>(analysisPeriods.length); for (int ap = 0; ap < analysisPeriods.length; ++ap) { DateRange analysisPeriod = analysisPeriods[ap]; TIntIntHashMap col2index = col2indices[ap]; DateRangeFilter drf = new DateRangeFilter( analysisPeriod.getFrom(), analysisPeriod.getTo()); QWD [] qSectorAverages = new QWD[4]; double [] qSectorStdDevs = new double[4]; ArrayList<QWD> allQWDs = new ArrayList<QWD>(); // for all Q sectors. for (int qSector = qSectorStart; qSector < qSectorEnd; ++qSector) { Filter filter = new AndFilter() .add(kmFilter) .add(new SectorFilter(qSector)) .add(drf) .add(idsFilter); List<Fixing.Column> metas = overview.filter(range, filter); if (metas.isEmpty()) { // No fixings for km and analysis period continue; } double sumQ = 0.0; double sumW = 0.0; StandardDeviation stdDev = new StandardDeviation(); List<QWD> qwds = new ArrayList<QWD>(metas.size()); dateAverager.clear(); for (Fixing.Column meta: metas) { if (meta.findQSector(km) != qSector) { // Ignore not matching sectors. continue; } Column column = cc.getColumn(meta); if (column == null || !column.getQW(km, wq)) { continue; } double fw = instance.value(wq[1]); if (Double.isNaN(fw)) { continue; } double dw = (wq[0] - fw)*100.0; stdDev.increment(dw); Date date = column.getDate(); String description = column.getDescription(); QWD qwd = new QWD( wq[1], wq[0], description, date, true, dw, getIndex(col2index, column.getIndex())); qwds.add(qwd); sumW += wq[0]; sumQ += wq[1]; dateAverager.add(date); } // Calulate average per Q sector. int N = qwds.size(); if (N > 0) { allQWDs.addAll(qwds); double avgW = sumW / N; double avgQ = sumQ / N; double avgFw = instance.value(avgQ); if (!Double.isNaN(avgFw)) { double avgDw = (avgW - avgFw)*100.0; Date avgDate = dateAverager.getAverage(); String avgDescription = "avg.deltawt." + qSector; QWD avgQWD = new QWD( avgQ, avgW, avgDescription, avgDate, true, avgDw, 0); qSectorAverages[qSector] = avgQWD; } qSectorStdDevs[qSector] = stdDev.getResult(); } else { qSectorStdDevs[qSector] = Double.NaN; } } // for all Q sectors QWD [] aqwds = allQWDs.toArray(new QWD[allQWDs.size()]); AnalysisPeriod periodResult = new AnalysisPeriod( analysisPeriod, aqwds, qSectorAverages, qSectorStdDevs); periodResults.add(periodResult); } double maxQ = -Double.MAX_VALUE; for (AnalysisPeriod ap: periodResults) { double q = ap.getMaxQ(); if (q > maxQ) { maxQ = q; } } double oldMaxQ = parameters.get(row, maxQIndex); if (oldMaxQ < maxQ) { parameters.set(row, maxQIndex, maxQ); } results.add(km, periodResults.toArray( new AnalysisPeriod[periodResults.size()])); } return results; } private static final int getIndex(TIntIntHashMap map, int colIdx) { if (map.containsKey(colIdx)) { return map.get(colIdx); } int index = map.size(); map.put(colIdx, index); return index; } } // vim:set ts=4 sw=4 si et sta sts=4 fenc=utf8 :