Examples with StatSummary utilities.StatSummary used on opensource projects

Example 21 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class NTuple method printNonEmpty.

public void printNonEmpty() {
    if (ntArray != null) {
        for (int i = 0; i < ntArray.length; i++) {
            if (ntArray[i] != null) {
                StatSummary ss = ntArray[i];
                // System.out.println(i + "\t " + ss.n() + "\t " + ss.mean());
                System.out.format("%d\t %.2f\t %d\n", i, ss.mean(), ss.n());
            }
        }
    } else {
        for (Double key : ntMap.keySet()) {
            StatSummary ss = ntMap.get(key);
            System.out.println(key + "\t " + ss.n() + "\t " + ss.mean());
        }
    }
}

Example 22 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class NTuple method printNonEmpty.

public void printNonEmpty(Param[] params) {
    for (int i : tuple) {
        System.out.println(params[i].getName() + "\t ");
    }
    System.out.println();
    if (ntArray != null) {
        for (int i = 0; i < ntArray.length; i++) {
            if (ntArray[i] != null) {
                StatSummary ss = ntArray[i];
                // System.out.println(i + "\t " + ss.n() + "\t " + ss.mean());
                int[] ind = getIndices(i);
                System.out.println(Arrays.toString(ind));
                System.out.println(paramString(params, ind));
                System.out.format("%d\t %.2f\t %.3f\t %d\n", i, ss.mean(), ss.stdErr(), ss.n());
                System.out.println();
            }
        }
    } else {
        for (Double key : ntMap.keySet()) {
            StatSummary ss = ntMap.get(key);
            System.out.println(key + "\t " + ss.n() + "\t " + ss.mean());
        }
    }
}

Example 23 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class NTupleBanditEA method runTrial.

@Override
public int[] runTrial(SolutionEvaluator evaluator, int nEvals) {
    this.evaluator = evaluator;
    // set  up some convenient references
    SearchSpace searchSpace = evaluator.searchSpace();
    EvolutionLogger logger = evaluator.logger();
    DefaultMutator mutator = new DefaultMutator(searchSpace);
    nNeighbours = (int) Math.min(nNeighbours, SearchSpaceUtil.size(searchSpace) / 4);
    System.out.println("Set neighbours to: " + nNeighbours);
    // force creation
    banditLandscapeModel = null;
    // create an NTuple fitness landscape model
    if (banditLandscapeModel == null) {
        System.out.println("Creating new model");
        banditLandscapeModel = new NTupleSystem().setSearchSpace(searchSpace);
    }
    // banditLandscapeModel.addTuples();
    // then each time around the loop try the following
    // create a neighbourhood set of points and pick the best one that combines it's exploitation and evaluation scores
    StatSummary ss = new StatSummary();
    int[] p;
    if (seed == null) {
        p = SearchSpaceUtil.randomPoint(searchSpace);
    } else {
        p = seed;
    }
    while (evaluator.nEvals() < nEvals) {
        // each time around the loop we make one fitness evaluation of p
        // and add this NEW information to the memory
        int prevEvals = evaluator.nEvals();
        if (view != null) {
            view.repaint();
            try {
                Thread.sleep(400);
            } catch (Exception e) {
            }
        }
        // double fitness = evaluator.evaluate(p);
        // the new version enables resampling
        double fitness;
        if (nSamples == 1) {
            fitness = evaluator.evaluate(p);
        } else {
            fitness = fitness(evaluator, p).mean();
        }
        if (reportFrequency > 0 && evaluator.nEvals() % reportFrequency == 0) {
            System.out.format("Iteration: %d\t %.1f\n", evaluator.nEvals(), fitness);
            System.out.println(evaluator.logger().ss);
            System.out.println();
        // System.out.println(p.length);
        // System.out.println(p);
        }
        ElapsedTimer t = new ElapsedTimer();
        banditLandscapeModel.addPoint(p, fitness);
        // ss.add(t.elapsed());
        // System.out.println(ss);
        // System.out.println("N Neighbours: " + nNeighbours);
        EvaluateChoices evc = new EvaluateChoices(banditLandscapeModel, kExplore);
        while (evc.n() < nNeighbours) {
            int[] pp = mutator.randMut(p);
            evc.add(pp);
        }
        // evc.report();
        // now set the next point to explore
        p = evc.picker.getBest();
        // logger.keepBest(picker.getBest(), picker.getBestScore());
        int diffEvals = evaluator.nEvals() - prevEvals;
        int[] bestYet = banditLandscapeModel.getBestOfSampled();
        for (int i = 0; i < diffEvals; i++) {
            evaluator.logger().logBestYest(bestYet);
        }
    // System.out.println("Best solution: " + Arrays.toString(evc.picker.getBest()) + "\t: " + evc.picker.getBestScore());
    }
    // System.out.println("Time for calling addPoint: ");
    // System.out.println(ss);
    // int[] solution = banditLandscapeModel.getBestSolution();
    int[] solution = banditLandscapeModel.getBestOfSampled();
    // int[] solution = banditLandscapeModel.getBestOfSampledPlusNeighbours(neighboursWhenFindingBest);
    logger.keepBest(solution, evaluator.evaluate(solution));
    return solution;
}

Example 24 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class NTupleView2D method paintComponent.

public void paintComponent(Graphics gx) {
    setupNTuples();
    Graphics2D g = (Graphics2D) gx;
    g.setRenderingHint(RenderingHints.KEY_TEXT_ANTIALIASING, RenderingHints.VALUE_TEXT_ANTIALIAS_ON);
    g.setColor(bg);
    g.fillRect(0, 0, getWidth(), getHeight());
    for (int i = 0; i < m; i++) {
        for (int j = 0; j < m; j++) {
            int[] p = new int[] { i, j };
            StatSummary ss = xyn.getStats(p);
            String cellString = String.format("[%d,%d]", i, j);
            String trueVal = null;
            if (solutionEvaluator != null) {
                trueVal = String.format("(%.3f)", solutionEvaluator.evaluate(p));
            }
            drawCell(g, ss, i, j, cellString, trueVal);
        }
    }
    for (int i = 0; i < m; i++) {
        // show the 1-tuple ones
        // note that each of these only samples the
        // non-zero dimension: we could set the other value to anything
        int[] px = new int[] { i, 0 };
        int[] py = new int[] { 0, i };
        String cellStringX = String.format("[%d,*]", i);
        String cellStringY = String.format("[*,%d]", i);
        // calculate the trueval for each one
        StatSummary xTrue = new StatSummary();
        StatSummary yTrue = new StatSummary();
        for (int j = 0; j < m; j++) {
            xTrue.add(solutionEvaluator.evaluate(new int[] { i, j }));
            yTrue.add(solutionEvaluator.evaluate(new int[] { j, i }));
        }
        String xs = null, ys = null;
        if (solutionEvaluator != null) {
            xs = String.format("(%.3f)", xTrue.mean());
            ys = String.format("(%.3f)", yTrue.mean());
        }
        drawCell(g, xn.getStats(px), i, m, cellStringX, xs);
        drawCell(g, yn.getStats(py), m, i, cellStringY, ys);
        // draw the borders:
        g.setColor(Color.red);
        int linwWidth = 6;
        g.fillRect(0, m * cellSize - linwWidth / 2, getWidth(), linwWidth);
        g.fillRect(m * cellSize - linwWidth / 2, 0, linwWidth, getHeight());
    }
}

Example 25 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class SlidingMeanEDA method fitness.

static StatSummary fitness(SolutionEvaluator evaluator, int[] sol, int nSamples) {
    StatSummary ss = new StatSummary();
    for (int i = 0; i < nSamples; i++) {
        double fitness = evaluator.evaluate(sol);
        ss.add(fitness);
    }
    return ss;
}