Package ch.idsia.utils

Examples of ch.idsia.utils.StatisticalSummary$Watch

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    }

    public static double testConfig (TimingAgent controller, EvaluationOptions options, int seed, int level, boolean paused) {
        options.setLevelDifficulty(level);
        options.setPauseWorld(paused);
        StatisticalSummary ss = test (controller, options, seed, level);
        System.out.printf("Level %d %s %.4f (%.4f) (min %.4f max %.4f) (avg time %.4f)\n",
                level, paused ? "paused" : "unpaused",
                ss.mean(), ss.sd(), ss.min(), ss.max(), controller.averageTimeTaken());
        return ss.mean();
    }
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        return ss.mean();
    }


    public static StatisticalSummary test (TimingAgent controller, EvaluationOptions options, int seed, int level) {
        StatisticalSummary ss = new StatisticalSummary ();
        for (int i = 0; i < numberOfTrials; i++) {
            options.setLevelRandSeed(seed + i);
            controller.reset();
            options.setAgent(controller);
            Evaluator evaluator = new Evaluator (options);
            EvaluationInfo result = evaluator.evaluate().get(0);
      System.out.printf("  map seed %d diff %2d -> %f (%f ms/frame)\n", seed+i, level, result.computeDistancePassed(), controller.averageTimeTaken());
            ss.add (result.computeDistancePassed());
        }
        return ss;
    }
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    }

    public static double testConfig (TimingAgent controller, EvaluationOptions options, int seed, int level, boolean paused) {
        options.setLevelDifficulty(level);
        options.setPauseWorld(paused);
        StatisticalSummary ss = test (controller, options, seed);
        double averageTimeTaken = controller.averageTimeTaken();
        System.out.printf("Difficulty %d score %.4f (avg time %.4f)\n",
                level, ss.mean(), averageTimeTaken);
        if (averageTimeTaken > 40) {
            System.out.println("Maximum allowed average time is 40 ms per time step.\n" +
                    "Controller disqualified");
            System.exit (0);
        }
        return ss.mean();
    }
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        }
        return ss.mean();
    }

    public static StatisticalSummary test (Agent controller, EvaluationOptions options, int seed) {
        StatisticalSummary ss = new StatisticalSummary ();
        for (int i = 0; i < numberOfTrials; i++) {
            options.setLevelRandSeed(seed + i);
            controller.reset();
            options.setAgent(controller);
            Evaluator evaluator = new Evaluator (options);
            EvaluationInfo result = evaluator.evaluate().get(0);
            ss.add (result.computeDistancePassed());
        }
        return ss;
    }
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