Examples with TObjectIntMap gnu.trove.map.TObjectIntMap used on opensource projects

Example 1 with TObjectIntMap

use of gnu.trove.map.TObjectIntMap in project OpenTripPlanner by opentripplanner.

the class PointSet method buildIdIndexMapIfNeeded.

/**
 * Build the ID - Index map if needed.
 */
private synchronized void buildIdIndexMapIfNeeded() {
    // by this method in another thread while this instantiation was blocked.
    if (idIndexMap == null) {
        // make a local object, don't expose to public view until it's built
        TObjectIntMap idIndexMap = new TObjectIntHashMap<String>(this.capacity, 1f, -1);
        for (int i = 0; i < this.capacity; i++) {
            if (ids[i] != null) {
                if (idIndexMap.containsKey(ids[i])) {
                    LOG.error("Duplicate ID {} in pointset.", ids[i]);
                } else {
                    idIndexMap.put(ids[i], i);
                }
            }
        }
        // now expose to public view; reference assignment is an atomic operation
        this.idIndexMap = idIndexMap;
    }
}

Example 2 with TObjectIntMap

use of gnu.trove.map.TObjectIntMap in project scheduler by btrplace.

the class CMinMigrations method injectPlacementHeuristic.

private void injectPlacementHeuristic(ReconfigurationProblem p, Parameters ps, IntVar cost) {
    List<CShareableResource> rcs = rp.getSourceModel().getViews().stream().filter(v -> v instanceof ShareableResource).map(v -> (CShareableResource) rp.getView(v.getIdentifier())).collect(Collectors.toList());
    useResources = !rcs.isEmpty();
    Model mo = p.getSourceModel();
    Mapping map = mo.getMapping();
    OnStableNodeFirst schedHeuristic = new OnStableNodeFirst(p);
    // Get the VMs to place
    Set<VM> onBadNodes = new HashSet<>(p.getManageableVMs());
    // Get the VMs that runs and have a pretty low chances to move
    Set<VM> onGoodNodes = map.getRunningVMs(map.getOnlineNodes());
    onGoodNodes.removeAll(onBadNodes);
    List<VMTransition> goodActions = p.getVMActions(onGoodNodes);
    List<VMTransition> badActions = p.getVMActions(onBadNodes);
    Solver s = p.getSolver();
    // Get the VMs to move for exclusion issue
    Set<VM> vmsToExclude = new HashSet<>(p.getManageableVMs());
    for (Iterator<VM> ite = vmsToExclude.iterator(); ite.hasNext(); ) {
        VM vm = ite.next();
        if (!(map.isRunning(vm) && p.getFutureRunningVMs().contains(vm))) {
            ite.remove();
        }
    }
    List<AbstractStrategy<?>> strategies = new ArrayList<>();
    Map<IntVar, VM> pla = VMPlacementUtils.makePlacementMap(p);
    if (!vmsToExclude.isEmpty()) {
        List<VMTransition> actions = new LinkedList<>();
        // Get all the involved slices
        for (VM vm : vmsToExclude) {
            if (p.getFutureRunningVMs().contains(vm)) {
                actions.add(p.getVMAction(vm));
            }
        }
        placeVMs(ps, strategies, actions, schedHeuristic, pla);
    }
    TObjectIntMap<VM> costs = CShareableResource.getWeights(rp, rcs);
    badActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    goodActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    placeVMs(ps, strategies, badActions, schedHeuristic, pla);
    placeVMs(ps, strategies, goodActions, schedHeuristic, pla);
    // Reinstantations. Try to reinstantiate first
    List<IntVar> migs = new ArrayList<>();
    for (VMTransition t : rp.getVMActions()) {
        if (t instanceof RelocatableVM) {
            migs.add(((RelocatableVM) t).getRelocationMethod());
        }
    }
    strategies.add(Search.intVarSearch(new FirstFail(rp.getModel()), new IntDomainMax(), migs.toArray(new IntVar[migs.size()])));
    if (!p.getNodeActions().isEmpty()) {
        // Boot some nodes if needed
        IntVar[] starts = p.getNodeActions().stream().map(Transition::getStart).toArray(IntVar[]::new);
        strategies.add(new IntStrategy(starts, new FirstFail(rp.getModel()), new IntDomainMin()));
        // Fix the duration. The side effect will be that states will be fixed as well
        // with the objective to not do un-necessary actions
        IntVar[] durations = p.getNodeActions().stream().map(Transition::getDuration).toArray(IntVar[]::new);
        strategies.add(new IntStrategy(durations, new FirstFail(rp.getModel()), new IntDomainMin()));
    }
    postCostConstraints();
    // /SCHEDULING PROBLEM
    MovementGraph gr = new MovementGraph(rp);
    IntVar[] starts = dSlices(rp.getVMActions()).map(Slice::getStart).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(new IntStrategy(starts, new StartOnLeafNodes(rp, gr), new IntDomainMin()));
    strategies.add(new IntStrategy(schedHeuristic.getScope(), schedHeuristic, new IntDomainMin()));
    IntVar[] ends = rp.getVMActions().stream().map(Transition::getEnd).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(Search.intVarSearch(new MyInputOrder<>(s), new IntDomainMin(), ends));
    // At this stage only it matters to plug the cost constraints
    strategies.add(new IntStrategy(new IntVar[] { p.getEnd(), cost }, new MyInputOrder<>(s, this), new IntDomainMin()));
    s.setSearch(new StrategiesSequencer(s.getEnvironment(), strategies.toArray(new AbstractStrategy[strategies.size()])));
}

Example 3 with TObjectIntMap

use of gnu.trove.map.TObjectIntMap in project scheduler by btrplace.

the class CMinMTTR method injectPlacementHeuristic.

private void injectPlacementHeuristic(ReconfigurationProblem p, Parameters ps, IntVar cost) {
    List<CShareableResource> rcs = rp.getSourceModel().getViews().stream().filter(v -> v instanceof ShareableResource).map(v -> (CShareableResource) rp.getView(v.getIdentifier())).collect(Collectors.toList());
    useResources = !rcs.isEmpty();
    Model mo = p.getSourceModel();
    Mapping map = mo.getMapping();
    OnStableNodeFirst schedHeuristic = new OnStableNodeFirst(p);
    // Get the VMs to place
    Set<VM> onBadNodes = new HashSet<>(p.getManageableVMs());
    // Get the VMs that runs and have a pretty low chances to move
    Set<VM> onGoodNodes = map.getRunningVMs(map.getOnlineNodes());
    onGoodNodes.removeAll(onBadNodes);
    List<VMTransition> goodActions = p.getVMActions(onGoodNodes);
    List<VMTransition> badActions = p.getVMActions(onBadNodes);
    Solver s = p.getSolver();
    // Get the VMs to move for exclusion issue
    Set<VM> vmsToExclude = new HashSet<>(p.getManageableVMs());
    for (Iterator<VM> ite = vmsToExclude.iterator(); ite.hasNext(); ) {
        VM vm = ite.next();
        if (!(map.isRunning(vm) && p.getFutureRunningVMs().contains(vm))) {
            ite.remove();
        }
    }
    List<AbstractStrategy<?>> strategies = new ArrayList<>();
    Map<IntVar, VM> pla = VMPlacementUtils.makePlacementMap(p);
    if (!vmsToExclude.isEmpty()) {
        List<VMTransition> actions = new LinkedList<>();
        // Get all the involved slices
        for (VM vm : vmsToExclude) {
            if (p.getFutureRunningVMs().contains(vm)) {
                actions.add(p.getVMAction(vm));
            }
        }
        placeVMs(ps, strategies, actions, schedHeuristic, pla);
    }
    TObjectIntMap<VM> costs = CShareableResource.getWeights(rp, rcs);
    badActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    goodActions.sort((v2, v1) -> costs.get(v1.getVM()) - costs.get(v2.getVM()));
    placeVMs(ps, strategies, badActions, schedHeuristic, pla);
    placeVMs(ps, strategies, goodActions, schedHeuristic, pla);
    // Reinstantations. Try to reinstantiate first
    List<IntVar> migs = new ArrayList<>();
    for (VMTransition t : rp.getVMActions()) {
        if (t instanceof RelocatableVM) {
            migs.add(((RelocatableVM) t).getRelocationMethod());
        }
    }
    strategies.add(Search.intVarSearch(new FirstFail(rp.getModel()), new IntDomainMax(), migs.toArray(new IntVar[migs.size()])));
    if (!p.getNodeActions().isEmpty()) {
        // Boot some nodes if needed
        IntVar[] starts = p.getNodeActions().stream().map(Transition::getStart).toArray(IntVar[]::new);
        strategies.add(new IntStrategy(starts, new FirstFail(rp.getModel()), new IntDomainMin()));
    }
    // /SCHEDULING PROBLEM
    MovementGraph gr = new MovementGraph(rp);
    IntVar[] starts = dSlices(rp.getVMActions()).map(Slice::getStart).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(new IntStrategy(starts, new StartOnLeafNodes(rp, gr), new IntDomainMin()));
    strategies.add(new IntStrategy(schedHeuristic.getScope(), schedHeuristic, new IntDomainMin()));
    IntVar[] ends = rp.getVMActions().stream().map(Transition::getEnd).filter(v -> !v.isInstantiated()).toArray(IntVar[]::new);
    strategies.add(Search.intVarSearch(new MyInputOrder<>(s), new IntDomainMin(), ends));
    // At this stage only it matters to plug the cost constraints
    strategies.add(new IntStrategy(new IntVar[] { p.getEnd(), cost }, new MyInputOrder<>(s, this), new IntDomainMin()));
    s.setSearch(new StrategiesSequencer(s.getEnvironment(), strategies.toArray(new AbstractStrategy[strategies.size()])));
}

Example 4 with TObjectIntMap

use of gnu.trove.map.TObjectIntMap in project BiomeTweaker by superckl.

the class ScriptCommandMaxSpawnPackSize method perform.

@Override
public void perform() throws Exception {
    if (this.entityClass == null) {
        EntityEventHandler.setGlobalPackSize(this.size);
        return;
    }
    Class<?> clazz;
    try {
        clazz = Class.forName(this.entityClass);
    } catch (final Exception e) {
        throw new IllegalArgumentException("Failed to load entity class: " + this.entityClass, e);
    }
    final Iterator<Biome> it = this.pack.getIterator();
    while (it.hasNext()) {
        final Biome biome = it.next();
        final TIntObjectMap<TObjectIntMap<String>> map = EntityEventHandler.getPackSizes();
        if (!map.containsKey(Biome.getIdForBiome(biome)))
            map.put(Biome.getIdForBiome(biome), new TObjectIntHashMap<String>());
        map.get(Biome.getIdForBiome(biome)).put(clazz.getName(), this.size);
    }
}

Example 5 with TObjectIntMap

use of gnu.trove.map.TObjectIntMap in project OpenTripPlanner by opentripplanner.

the class ConvertToFrequency method apply.

public void apply(List<FrequencyEntry> frequencyEntries, List<TripTimes> scheduledTrips, Graph graph, BitSet servicesRunning, RaptorWorkerTimetable.BoardingAssumption assumption) {
    // preserve existing frequency entries
    this.frequencyEntries.addAll(frequencyEntries);
    Set<String> routeIds = new HashSet<>();
    if (routeId != null)
        Stream.of(routeId).forEach(routeIds::add);
    // loop over scheduled trips and figure out what to do with them
    for (TripTimes tt : scheduledTrips) {
        if (routeId == null || routeIds.contains(tt.trip.getRoute().getId().getId())) {
            // put this in the appropriate group for frequency conversion
            String key;
            switch(groupBy) {
                case ROUTE_DIRECTION:
                    key = tt.trip.getRoute().getId().getId() + "_" + tt.trip.getDirectionId();
                    break;
                case ROUTE:
                    key = tt.trip.getRoute().getId().getId();
                    break;
                case PATTERN:
                    key = graph.index.patternForTrip.get(tt.trip).getExemplar().getId().getId();
                    break;
                default:
                    throw new RuntimeException("Unrecognized group by value");
            }
            tripsToConvert.put(key, tt);
        } else {
            // don't touch this trip
            this.scheduledTrips.add(tt);
        }
    }
    // loop over all the groups and create frequency entries
    GROUPS: for (Map.Entry<String, Collection<TripTimes>> e : tripsToConvert.asMap().entrySet()) {
        // get just the running services
        List<TripTimes> group = e.getValue().stream().filter(tt -> servicesRunning.get(tt.serviceCode)).filter(tt -> windowStart < tt.getDepartureTime(0) && tt.getDepartureTime(0) < windowEnd).collect(Collectors.toList());
        if (group.isEmpty())
            continue GROUPS;
        if (group.size() == 1) {
            group.stream().forEach(scheduledTrips::add);
            continue GROUPS;
        }
        // find the dominant pattern
        TObjectIntMap<TripPattern> patternCount = new TObjectIntHashMap<>(5, 0.75f, 0);
        group.forEach(tt -> patternCount.adjustOrPutValue(graph.index.patternForTrip.get(tt.trip), 1, 1));
        int maxCount = 0;
        TripPattern tripPattern = null;
        for (TObjectIntIterator<TripPattern> it = patternCount.iterator(); it.hasNext(); ) {
            it.advance();
            if (it.value() > maxCount) {
                maxCount = it.value();
                tripPattern = it.key();
            }
        }
        // find a stop that is common to all trip patterns. Sort the list so that the same common stop is always returned
        NavigableSet<Stop> stops = new TreeSet<>((s1, s2) -> s1.getId().compareTo(s2.getId()));
        stops.addAll(tripPattern.getStops());
        patternCount.keySet().stream().forEach(p -> stops.retainAll(p.getStops()));
        if (stops.isEmpty()) {
            LOG.warn("Unable to find common stop for key {}, not converting to frequencies", e.getKey());
            scheduledTrips.addAll(e.getValue());
            continue GROUPS;
        }
        Stop stop = stops.stream().findFirst().get();
        // determine the median frequency at this stop
        // use a set to handle duplicated trips
        TIntSet arrivalTimes = new TIntHashSet();
        for (boolean filter : new boolean[] { true, false }) {
            for (TripTimes tt : group) {
                TripPattern tp = graph.index.patternForTrip.get(tt.trip);
                int arrivalTime = tt.getArrivalTime(tp.getStops().indexOf(stop));
                // however, if we apply the filter and end up with no trips at this stop, re-run with the filter disabled
                if (windowStart < arrivalTime && arrivalTime < windowEnd || !filter)
                    arrivalTimes.add(arrivalTime);
            }
            // if we didn't find stops, continue, which will turn off the filter
            if (arrivalTimes.size() > 1)
                break;
        }
        // now convert to elapsed times
        int[] arrivalTimeArray = arrivalTimes.toArray();
        Arrays.sort(arrivalTimeArray);
        int[] headway = new int[arrivalTimeArray.length - 1];
        for (int i = 1; i < arrivalTimeArray.length; i++) {
            headway[i - 1] = arrivalTimeArray[i] - arrivalTimeArray[i - 1];
        }
        Arrays.sort(headway);
        // the headway that we will use
        int aggregateHeadway;
        if (assumption == RaptorWorkerTimetable.BoardingAssumption.WORST_CASE)
            // simple: worst case analysis should use the worst case headway
            aggregateHeadway = Ints.max(headway);
        else {
            // we want the average headway, but we we want the average of the headways weighted
            // by themselves as if there is a two minute headway then a twenty-minute headway,
            // customers are ten times as likely to experience the twenty minute headway
            // (we want the average from the user's perspective, not the vehicle's perspective)
            // This is a weighted average where the weight is the same as the headway so it simplifies
            // to sum (headway^2) / sum(headway)
            aggregateHeadway = IntStream.of(headway).map(h -> h * h).sum() / IntStream.of(headway).sum();
        }
        LOG.info("Headway for route {} ({}) in direction {}: {}min", tripPattern.route.getShortName(), tripPattern.route.getId().getId(), tripPattern.directionId, aggregateHeadway / 60);
        // figure out running/dwell times based on the trips on this pattern
        final TripPattern chosenTp = tripPattern;
        List<TripTimes> candidates = group.stream().filter(tt -> graph.index.patternForTrip.get(tt.trip) == chosenTp).collect(Collectors.toList());
        // transposed from what you'd expect: stops on the rows
        int[][] hopTimes = new int[tripPattern.getStops().size() - 1][candidates.size()];
        int[][] dwellTimes = new int[tripPattern.getStops().size()][candidates.size()];
        int tripIndex = 0;
        for (TripTimes tt : candidates) {
            for (int stopIndex = 0; stopIndex < tripPattern.getStops().size(); stopIndex++) {
                dwellTimes[stopIndex][tripIndex] = tt.getDwellTime(stopIndex);
                if (stopIndex > 0)
                    hopTimes[stopIndex - 1][tripIndex] = tt.getArrivalTime(stopIndex) - tt.getDepartureTime(stopIndex - 1);
            }
            tripIndex++;
        }
        // collapse it down
        int[] meanHopTimes = new int[tripPattern.getStops().size() - 1];
        int hopIndex = 0;
        for (int[] hop : hopTimes) {
            meanHopTimes[hopIndex++] = IntStream.of(hop).sum() / hop.length;
        }
        int[] meanDwellTimes = new int[tripPattern.getStops().size()];
        int dwellIndex = 0;
        for (int[] dwell : dwellTimes) {
            meanDwellTimes[dwellIndex++] = IntStream.of(dwell).sum() / dwell.length;
        }
        // phew! now let's make a frequency entry
        TripTimes tt = new TripTimes(candidates.get(0));
        int cumulative = 0;
        for (int i = 0; i < tt.getNumStops(); i++) {
            tt.updateArrivalTime(i, cumulative);
            cumulative += meanDwellTimes[i];
            tt.updateDepartureTime(i, cumulative);
            if (i + 1 < tt.getNumStops())
                cumulative += meanHopTimes[i];
        }
        FrequencyEntry fe = new FrequencyEntry(windowStart - 60 * 60 * 3, windowEnd + 60 * 60 * 3, aggregateHeadway, false, tt);
        this.frequencyEntries.add(fe);
    }
}