Examples with TIntList gnu.trove.list.TIntList used on opensource projects

Example 16 with TIntList

use of gnu.trove.list.TIntList in project OpenTripPlanner by opentripplanner.

the class TNPropagatedTimesStore method setFromArray.

/**
 * @param times for search (varying departure time), an array of travel times to each transit stop.
 */
public void setFromArray(int[][] times, ConfidenceCalculationMethod confidenceCalculationMethod) {
    if (times.length == 0)
        // nothing to do
        return;
    // assume array is rectangular
    int stops = times[0].length;
    // cache random numbers. This should be fine as we're mixing it with the number of minutes
    // at which each destination is accessible, which is sometimes not 120, as well as the stop
    // position in the list (note that we have cleverly chosen a number which is a prime
    // so is not divisible by the number of iterations on the bootstrap). Finally recall that
    // the maximum number of times we're sampling from is generally 120 and we modulo this,
    // so the pigeonhole principle applies.
    // this is effectively a "random number generator" with phase 10007
    int[] randomNumbers = random.ints().limit(10007).map(Math::abs).toArray();
    int nextRandom = 0;
    // loop over stops on the outside so we can bootstrap
    STOPS: for (int stop = 0; stop < stops; stop++) {
        // compute the average
        int sum = 0;
        int count = 0;
        TIntList timeList = new TIntArrayList();
        ITERATIONS: for (int i = 0; i < times.length; i++) {
            if (times[i][stop] == RaptorWorker.UNREACHED)
                continue ITERATIONS;
            sum += times[i][stop];
            count++;
            timeList.add(times[i][stop]);
        }
        if (count == 0)
            continue STOPS;
        avgs[stop] = sum / count;
        switch(confidenceCalculationMethod) {
            case BOOTSTRAP:
                // now bootstrap out a 95% confidence interval on the time
                int[] bootMeans = new int[N_BOOTSTRAPS];
                for (int boot = 0; boot < N_BOOTSTRAPS; boot++) {
                    int bsum = 0;
                    // sample from the Monte Carlo distribution with replacement
                    for (int iter = 0; iter < count; iter++) {
                        bsum += timeList.get(randomNumbers[nextRandom++ % randomNumbers.length] % count);
                    // bsum += timeList.get(random.nextInt(count));
                    }
                    bootMeans[boot] = bsum / count;
                }
                Arrays.sort(bootMeans);
                // 2.5 percentile of distribution of means
                mins[stop] = bootMeans[N_BOOTSTRAPS / 40];
                // 97.5 percentile of distribution of means
                maxs[stop] = bootMeans[N_BOOTSTRAPS - N_BOOTSTRAPS / 40];
                break;
            case PERCENTILE:
                timeList.sort();
                mins[stop] = timeList.get(timeList.size() / 40);
                maxs[stop] = timeList.get(39 * timeList.size() / 40);
                break;
            case NONE:
                mins[stop] = maxs[stop] = avgs[stop];
                break;
            case MIN_MAX:
            default:
                mins[stop] = timeList.min();
                maxs[stop] = timeList.max();
                break;
        }
    }
}

Example 17 with TIntList

use of gnu.trove.list.TIntList in project OpenTripPlanner by opentripplanner.

the class TimeTracker method add.

/**
 * Add a variable number of int arguments or an array of ints to the bag for a given stopcluster.
 * Optionally sort all the entries after a bulk add.
 */
public void add(StopCluster stopCluster, boolean sort, int... time) {
    TIntList times = timesForCluster.get(stopCluster);
    if (times == null) {
        times = new TIntArrayList();
        timesForCluster.put(stopCluster, times);
    }
    times.add(time);
    if (sort) {
        times.sort();
    }
}

Example 18 with TIntList

use of gnu.trove.list.TIntList in project OpenTripPlanner by opentripplanner.

the class TimeTracker method dump.

public void dump() {
    for (StopCluster stopCluster : timesForCluster.keySet()) {
        TIntList ints = timesForCluster.get(stopCluster);
        System.out.printf("%s --> %s \n", stopCluster.toString(), ints.toString());
    }
}

Example 19 with TIntList

use of gnu.trove.list.TIntList in project OpenTripPlanner by opentripplanner.

the class Ride method calcStatsForTransfer.

/**
 * Calculates Stats for the transfer to the given ride from the previous ride.
 * This should only be called after all PatternRides have been added to the ride.
 * Distances can be stored in rides, including the first and last distance. But waits must be
 * calculated from full sets of patterns, which are not known until a round is over.
 */
public Stats calcStatsForTransfer(TimeWindow window, double walkSpeed) {
    TIntList arrivals = previous.getSortedStoptimes(window, true);
    TIntList departures = this.getSortedStoptimes(window, false);
    List<Integer> waits = Lists.newArrayList();
    TIntIterator departureIterator = departures.iterator();
    int departure = departureIterator.next();
    ARRIVAL: for (TIntIterator arrivalsIterator = arrivals.iterator(); arrivalsIterator.hasNext(); ) {
        int arrival = arrivalsIterator.next();
        // On transfers the access stats should have max=min=avg
        // We use the min, which would be best if min != max since it should only relax the bounds somewhat.
        int boardTime = arrival + accessStats.min + ProfileRouter.SLACK;
        while (departure <= boardTime) {
            if (!departureIterator.hasNext())
                break ARRIVAL;
            departure = departureIterator.next();
        }
        waits.add(departure - boardTime);
    }
    // Impossible to make this transfer.
    if (waits.isEmpty())
        return null;
    return new Stats(waits);
}

Example 20 with TIntList

use of gnu.trove.list.TIntList in project OpenTripPlanner by opentripplanner.

the class Ride method calcStatsForBoarding.

/**
 * Produce stats about boarding an initial Ride, which has no previous ride.
 * This assumes arrival times are uniformly distributed during the window.
 * The Ride must contain some trips, and the window must have a positive duration.
 */
public Stats calcStatsForBoarding(TimeWindow window) {
    Stats stats = new Stats();
    // You can always arrive just before a train departs.
    stats.min = 0;
    TIntList departures = getSortedStoptimes(window, false);
    int last = window.from;
    double avgAccumulated = 0.0;
    /* All departures in the list are known to be running and within the window. */
    for (TIntIterator it = departures.iterator(); it.hasNext(); ) {
        int dep = it.next();
        int maxWait = dep - last;
        if (maxWait > stats.max)
            stats.max = maxWait;
        /* Weight the average of each interval by the number of seconds it contains. */
        avgAccumulated += (maxWait / 2.0) * maxWait;
        stats.num += maxWait;
        last = dep;
    }
    if (stats.num > 0) {
        stats.avg = (int) (avgAccumulated / stats.num);
    }
    return stats;
}