Example usage for org.apache.commons.math.stat.descriptive DescriptiveStatistics DescriptiveStatistics

Introduction

In this page you can find the example usage for org.apache.commons.math.stat.descriptive DescriptiveStatistics DescriptiveStatistics.

Prototype

public DescriptiveStatistics() 

Source Link

Document

Construct a DescriptiveStatistics instance with an infinite window

Usage

From source file:playground.johannes.coopsim.analysis.AbstractTrajectoryProperty.java

public DescriptiveStatistics statistics(Set<? extends Trajectory> trajectories, boolean ignoreZeros) {
    if (!ignoreZeros)
        return this.statistics(trajectories);
    else {//from www.  j  ava 2s .co  m
        TObjectDoubleHashMap<Trajectory> values = values(trajectories);
        DescriptiveStatistics stats = new DescriptiveStatistics();

        int zeros = 0;
        TObjectDoubleIterator<Trajectory> it = values.iterator();
        for (int i = 0; i < values.size(); i++) {
            it.advance();
            if (it.value() > 0)
                stats.addValue(it.value());
            else
                zeros++;
        }

        if (zeros > 0)
            logger.debug(String.format("Ignored %1$s zero values.", zeros));

        return stats;
    }
}

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From source file:playground.johannes.coopsim.analysis.AbstractTrajectoryProperty.java

@Override
public DescriptiveStatistics statistics(Set<? extends Trajectory> trajectories) {
    TObjectDoubleHashMap<Trajectory> values = values(trajectories);
    DescriptiveStatistics stats = new DescriptiveStatistics();

    TObjectDoubleIterator<Trajectory> it = values.iterator();
    for (int i = 0; i < values.size(); i++) {
        it.advance();/*from w w  w . j a v  a2s  .  c  o m*/
        stats.addValue(it.value());
    }

    return stats;
}

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From source file:playground.johannes.coopsim.analysis.DesiredTimeDiffTask.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    DescriptiveStatistics durStats = new DescriptiveStatistics();
    DescriptiveStatistics arrStats = new DescriptiveStatistics();

    for (Trajectory t : trajectories) {
        Activity act = (Activity) t.getElements().get(2);
        String type = act.getType();
        if (!type.equals("idle")) {
            ActivityDesires desire = desires.get(t.getPerson());

            double desiredDuration = desire.getActivityDuration(type);
            double desiredStartTime = desire.getActivityStartTime(type);

            double realizedDuration = t.getTransitions().get(3) - t.getTransitions().get(2);
            double realizedStartTime = t.getTransitions().get(2);

            durStats.addValue(Math.abs(realizedDuration - desiredDuration));
            arrStats.addValue(Math.abs(realizedStartTime - desiredStartTime));
        }//from   w  w w .  j  a  v a 2 s. c  om
    }
    results.put("dur_diff", durStats);
    results.put("arr_diff", arrStats);

    try {
        writeHistograms(durStats, "dur_diff", 50, 50);
        writeHistograms(arrStats, "arr_diff", 50, 50);
    } catch (IOException e) {
        e.printStackTrace();
    }
}

---

From source file:playground.johannes.coopsim.analysis.JointActivityTask.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    DescriptiveStatistics timeStatsAll = new DescriptiveStatistics();
    DescriptiveStatistics visitorStatsAll = new DescriptiveStatistics();
    Map<String, DescriptiveStatistics> timeStatsTypeMap = new HashMap<String, DescriptiveStatistics>();
    Map<String, DescriptiveStatistics> visitorStatsTypeMap = new HashMap<String, DescriptiveStatistics>();

    for (Trajectory t : trajectories) {
        Person person = t.getPerson();/*from w w  w . j av  a2  s  .  c  o m*/
        SocialVertex ego = personVertexMap.get(person);
        String type = ((Activity) t.getElements().get(2)).getType();

        DescriptiveStatistics timeStatsType = timeStatsTypeMap.get(type);
        DescriptiveStatistics visitorStatsType = visitorStatsTypeMap.get(type);

        if (timeStatsType == null) {
            timeStatsType = new DescriptiveStatistics();
            timeStatsTypeMap.put(type, timeStatsType);
            visitorStatsType = new DescriptiveStatistics();
            visitorStatsTypeMap.put(type, visitorStatsType);
        }

        int visitors = 0;
        List<Person> alterPersons = new ArrayList<Person>(ego.getNeighbours().size());
        for (SocialVertex alter : ego.getNeighbours()) {
            double time = tracker.timeOverlap(person, alter.getPerson().getPerson());
            if (time > 0) {
                timeStatsType.addValue(time);
                timeStatsAll.addValue(time);
            }

            alterPersons.add(alter.getPerson().getPerson());
        }

        visitors = tracker.metAlters(person, alterPersons);
        visitorStatsType.addValue(visitors);
        visitorStatsAll.addValue(visitors);
    }

    String timeKey = "t_joint";
    results.put(timeKey, timeStatsAll);
    for (Entry<String, DescriptiveStatistics> entry : timeStatsTypeMap.entrySet()) {
        results.put("t_joint_" + entry.getKey(), entry.getValue());
    }

    String visitorKey = "visitors";
    results.put(visitorKey, visitorStatsAll);
    for (Entry<String, DescriptiveStatistics> entry : visitorStatsTypeMap.entrySet()) {
        results.put("visitors_" + entry.getKey(), entry.getValue());
    }

    if (outputDirectoryNotNull()) {
        try {
            writeHistograms(timeStatsAll, timeKey, 50, 50);
            writeHistograms(visitorStatsAll, new DummyDiscretizer(), visitorKey, false);

            for (Entry<String, DescriptiveStatistics> entry : timeStatsTypeMap.entrySet()) {
                writeHistograms(entry.getValue(), "t_joint_" + entry.getKey(), 50, 50);
            }

            for (Entry<String, DescriptiveStatistics> entry : visitorStatsTypeMap.entrySet()) {
                writeHistograms(entry.getValue(), new DummyDiscretizer(), "visitors_" + entry.getKey(), false);
            }
        } catch (IOException e) {
            e.printStackTrace();
        }
    }

}

---

From source file:playground.johannes.coopsim.analysis.LegFrequencyTask.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    Set<String> modes = TrajectoryUtils.getModes(trajectories);
    modes.add(null);/*from w ww.ja va2  s  .c  o  m*/

    for (String mode : modes) {
        PlanElementCondition<Leg> condition;
        if (mode != null) {
            condition = new LegModeCondition(mode);
        } else {
            condition = DefaultCondition.getInstance();
        }

        DescriptiveStatistics stats = new DescriptiveStatistics();
        for (Trajectory t : trajectories) {
            int cnt = 0;
            for (int i = 1; i < t.getElements().size(); i += 2) {
                if (condition.test(t, (Leg) t.getElements().get(i), i)) {
                    cnt++;
                }
            }
            stats.addValue(cnt);
        }

        String key;
        if (mode == null)
            key = String.format("%s.all", KEY, mode);
        else
            key = String.format("%s.%s", KEY, mode);

        results.put(key, stats);

        if (outputDirectoryNotNull()) {
            try {
                writeHistograms(stats, DummyDiscretizer.getInstance(), key, false);
            } catch (IOException e) {
                // TODO Auto-generated catch block
                e.printStackTrace();
            }
        }
    }

}

---

From source file:playground.johannes.coopsim.analysis.PersonAgeTask.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    DescriptiveStatistics stats = new DescriptiveStatistics();
    for (Trajectory t : trajectories) {
        stats.addValue(((PersonImpl) t.getPerson()).getAge());
    }/*from  w w  w .  j a  v  a  2 s.c  o m*/

    results.put("person_age", stats);
    try {
        writeHistograms(stats, new DummyDiscretizer(), "age", false);
    } catch (IOException e) {
        e.printStackTrace();
    }
}

---

From source file:playground.johannes.coopsim.analysis.PkmRouteTask.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    Map<String, PlanElementConditionComposite<Leg>> conditions = Conditions.getLegConditions(trajectories);

    for (Entry<String, PlanElementConditionComposite<Leg>> entry : conditions.entrySet()) {
        double sum = 0;
        int cnt = 0;
        for (Trajectory t : trajectories) {
            for (int i = 1; i < t.getElements().size(); i += 2) {
                Leg leg = (Leg) t.getElements().get(i);
                if (entry.getValue().test(t, leg, i)) {
                    if (leg.getRoute() instanceof NetworkRoute) {
                        NetworkRoute route = (NetworkRoute) leg.getRoute();
                        sum += RouteUtils.calcDistance(route, network);

                        Link startLink = network.getLinks().get(route.getStartLinkId());
                        sum += startLink.getLength() * startEndFactor;

                        Link endLink = network.getLinks().get(route.getEndLinkId());
                        sum += endLink.getLength() * startEndFactor;
                    } else {
                        sum += leg.getRoute().getDistance();

                        if (leg.getMode().equals("car")) {
                            cnt++;//from w ww  .  j  a v  a2 s  .com
                        }
                    }
                }
            }

        }

        DescriptiveStatistics stats = new DescriptiveStatistics();
        stats.addValue(sum);

        results.put(String.format("%s.%s.%.2f", KEY, entry.getKey(), startEndFactor), stats);

        if (cnt > 0) {
            logger.warn(String.format("mode=car, type=%s: %s not NetworkRoute", entry.getKey(), cnt));
        }
    }

}

---

From source file:playground.johannes.coopsim.analysis.ScoreTask.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    DescriptiveStatistics allScores = new DescriptiveStatistics();
    for (Trajectory t : trajectories)
        allScores.addValue(t.getPerson().getSelectedPlan().getScore());
    results.put("score", allScores);

    DescriptiveStatistics actScores = ActivityEvaluator.stopLogging();
    results.put("score_act", actScores);

    DescriptiveStatistics legScores = LegEvaluator.stopLogging();
    results.put("score_leg", legScores);

    Map<String, DescriptiveStatistics> jointScore = JointActivityEvaluator2.stopLogging();
    //      Map<String, DescriptiveStatistics> jointScore = JointActivityEvaluator.stopLogging();
    for (Entry<String, DescriptiveStatistics> entry : jointScore.entrySet()) {
        results.put("score_join_" + entry.getKey(), entry.getValue());
    }//from  w  w  w.j a  v  a 2s  .c om

    DescriptiveStatistics typeScore = ActivityTypeEvaluator.stopLogging();
    results.put("score_type", typeScore);

    try {
        writeHistograms(allScores, "score", 50, 50);
        writeHistograms(actScores, "score_act", 50, 50);
        writeHistograms(legScores, "score_leg", 50, 50);
        for (Entry<String, DescriptiveStatistics> entry : jointScore.entrySet()) {
            writeHistograms(entry.getValue(), new LinearDiscretizer(0.5), "score_join_" + entry.getKey(),
                    false);
            writeHistograms(entry.getValue(), "score_join_" + entry.getKey(), 50, 50);
        }

        writeHistograms(typeScore, new DummyDiscretizer(), "score_type", false);
    } catch (IOException e) {
        e.printStackTrace();
    }

    scores.add(allScores.getMean());

    if (scores.size() >= MIN_SAMPLES) {
        SimpleRegression reg = new SimpleRegression();

        for (int i = scores.size() - MIN_SAMPLES; i < scores.size(); i++) {
            reg.addData(i, scores.get(i));
        }

        if (reg.getSlope() < THRESHOLD)
            converged = true;
    }

}

---

From source file:playground.johannes.coopsim.analysis.SocialTripCorrelationTask.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    TDoubleArrayList xvals = new TDoubleArrayList(trajectories.size());
    TDoubleArrayList yvals = new TDoubleArrayList(trajectories.size());

    for (Trajectory t : trajectories) {
        SocialVertex v = vertexMapping.get(t.getPerson());
        double val_v = getValue(v);

        List<Person> alters = new ArrayList<Person>(v.getNeighbours().size());
        for (SocialVertex w : v.getNeighbours())
            alters.add(w.getPerson().getPerson());

        for (Person alter : alters) {
            if (tracker.timeOverlap(t.getPerson(), alter) > 0) {
                double val_w = getValue(vertexMapping.get(alter));

                xvals.add(val_v);
                yvals.add(val_w);
            }/*  w ww . j  a  v a  2 s.c  o m*/
        }
    }

    double r = new PearsonsCorrelation().correlation(xvals.toNativeArray(), yvals.toNativeArray());
    String key2 = String.format("r_trip_%1$s", key);
    DescriptiveStatistics stats = new DescriptiveStatistics();
    stats.addValue(r);
    results.put(key2, stats);

    try {
        TDoubleDoubleHashMap correl = Correlations.mean(xvals.toNativeArray(), yvals.toNativeArray());
        TXTWriter.writeMap(correl, key, key, String.format("%1$s/%2$s.txt", getOutputDirectory(), key2));

        TDoubleObjectHashMap<DescriptiveStatistics> table = Correlations.statistics(xvals.toNativeArray(),
                yvals.toNativeArray(), new DummyDiscretizer());
        TXTWriter.writeBoxplotStats(table, String.format("%1$s/%2$s.table.txt", getOutputDirectory(), key2));
        TXTWriter.writeScatterPlot(table, String.format("%1$s/%2$s.xy.txt", getOutputDirectory(), key2));
    } catch (IOException e) {
        e.printStackTrace();
    }
}

---

From source file:playground.johannes.coopsim.analysis.TransitionProbaAnalyzer.java

@Override
public void analyze(Set<Trajectory> trajectories, Map<String, DescriptiveStatistics> results) {
    DescriptiveStatistics stats = new DescriptiveStatistics();

    double pi = mentalEngine.getTotalPiSum() / (double) dumpInterval;

    stats.addValue(pi);//from  ww  w  .ja  v a  2  s  . c  o  m

    results.put("pi", stats);

    mentalEngine.cleatTotalPiSum();
}

---

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