Examples with TIntIntHashMap gnu.trove.map.hash.TIntIntHashMap used on opensource projects

Example 41 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project scheduler by btrplace.

the class BanSplitterTest method simpleTest.

@Test
public void simpleTest() {
    BanSplitter splitter = new BanSplitter();
    List<Instance> instances = new ArrayList<>();
    Model origin = new DefaultModel();
    Node n1 = origin.newNode();
    Node n2 = origin.newNode();
    VM vm1 = origin.newVM();
    VM vm2 = origin.newVM();
    VM vm3 = origin.newVM();
    VM vm4 = origin.newVM();
    /**
     * READY: vm1
     * n1 vm2
     * n2 (vm3) vm4
     */
    origin.getMapping().addOnlineNode(n1);
    origin.getMapping().addReadyVM(vm1);
    origin.getMapping().addRunningVM(vm2, n1);
    origin.getMapping().addOnlineNode(n2);
    origin.getMapping().addSleepingVM(vm3, n2);
    origin.getMapping().addRunningVM(vm4, n2);
    Model m0 = new DefaultModel();
    m0.newNode(n1.id());
    m0.newVM(vm1.id());
    m0.newVM(vm2.id());
    m0.getMapping().addOnlineNode(n1);
    m0.getMapping().addReadyVM(vm1);
    m0.getMapping().addRunningVM(vm2, n1);
    Model m1 = new DefaultModel();
    m1.newNode(n2.id());
    m1.newVM(vm3.id());
    m1.newVM(vm4.id());
    m1.getMapping().addOnlineNode(n2);
    m1.getMapping().addSleepingVM(vm3, n2);
    m1.getMapping().addRunningVM(vm4, n2);
    instances.add(new Instance(m0, new ArrayList<>(), new MinMTTR()));
    instances.add(new Instance(m1, new ArrayList<>(), new MinMTTR()));
    Set<VM> all = new HashSet<>(m0.getMapping().getAllVMs());
    all.addAll(m1.getMapping().getAllVMs());
    TIntIntHashMap vmIndex = Instances.makeVMIndex(instances);
    TIntIntHashMap nodeIndex = Instances.makeNodeIndex(instances);
    // Only VMs & nodes in m0
    Ban single = new Ban(vm1, m0.getMapping().getAllNodes());
    Assert.assertTrue(splitter.split(single, null, instances, vmIndex, nodeIndex));
    Assert.assertTrue(instances.get(0).getSatConstraints().contains(single));
    Assert.assertFalse(instances.get(1).getSatConstraints().contains(single));
    // All the VMs, nodes in m1.
    Ban among = new Ban(vm3, m1.getMapping().getAllNodes());
    Assert.assertTrue(splitter.split(among, null, instances, vmIndex, nodeIndex));
    Assert.assertTrue(instances.get(0).getSatConstraints().contains(new Ban(vm1, m0.getMapping().getAllNodes())));
    Assert.assertTrue(instances.get(1).getSatConstraints().contains(new Ban(vm3, m1.getMapping().getAllNodes())));
}

Example 42 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project scheduler by btrplace.

the class PreserveSplitterTest method simpleTest.

@Test
public void simpleTest() {
    PreserveSplitter splitter = new PreserveSplitter();
    List<Instance> instances = new ArrayList<>();
    Model m0 = new DefaultModel();
    VM v = m0.newVM(1);
    m0.getMapping().addReadyVM(v);
    m0.getMapping().addRunningVM(m0.newVM(2), m0.newNode(1));
    Model m1 = new DefaultModel();
    m1.getMapping().addReadyVM(m1.newVM(3));
    m1.getMapping().addSleepingVM(m1.newVM(4), m1.newNode(2));
    m1.getMapping().addRunningVM(m1.newVM(5), m1.newNode(3));
    instances.add(new Instance(m0, new ArrayList<>(), new MinMTTR()));
    instances.add(new Instance(m1, new ArrayList<>(), new MinMTTR()));
    TIntIntHashMap index = Instances.makeVMIndex(instances);
    Set<VM> all = new HashSet<>(m0.getMapping().getAllVMs());
    all.addAll(m1.getMapping().getAllVMs());
    // Only VMs in m0
    Preserve single = new Preserve(v, "foo", 3);
    Assert.assertTrue(splitter.split(single, null, instances, index, new TIntIntHashMap()));
    Assert.assertTrue(instances.get(0).getSatConstraints().contains(single));
    Assert.assertFalse(instances.get(1).getSatConstraints().contains(single));
}

Example 43 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project scheduler by btrplace.

the class RootSplitterTest method simpleTest.

@Test
public void simpleTest() {
    RootSplitter splitter = new RootSplitter();
    List<Instance> instances = new ArrayList<>();
    Model m0 = new DefaultModel();
    VM v = m0.newVM(1);
    m0.getMapping().addReadyVM(v);
    m0.getMapping().addRunningVM(m0.newVM(2), m0.newNode(1));
    Model m1 = new DefaultModel();
    m1.getMapping().addReadyVM(m1.newVM(3));
    m1.getMapping().addSleepingVM(m1.newVM(4), m1.newNode(2));
    m1.getMapping().addRunningVM(m1.newVM(5), m1.newNode(3));
    instances.add(new Instance(m0, new ArrayList<>(), new MinMTTR()));
    instances.add(new Instance(m1, new ArrayList<>(), new MinMTTR()));
    Set<VM> all = new HashSet<>(m0.getMapping().getAllVMs());
    all.addAll(m1.getMapping().getAllVMs());
    TIntIntHashMap index = Instances.makeVMIndex(instances);
    // Only VMs in m0
    Root single = new Root(v);
    Assert.assertTrue(splitter.split(single, null, instances, index, new TIntIntHashMap()));
    Assert.assertTrue(instances.get(0).getSatConstraints().contains(single));
    Assert.assertFalse(instances.get(1).getSatConstraints().contains(single));
}

Example 44 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project GDSC-SMLM by aherbert.

the class TcPalmAnalysis method createCumulativeCountData.

/**
 * Creates the cumulative count data.
 *
 * @param createPlotData set to true to create the plot data arrays
 * @return the cumulative count data
 */
private CumulativeCountData createCumulativeCountData(LocalList<ClusterData> clusters, boolean createPlotData) {
    final TIntIntHashMap all = new TIntIntHashMap(maxT - minT + 1);
    clusters.forEach(c -> c.results.forEach(peak -> all.adjustOrPutValue(peak.getFrame(), 1, 1)));
    final int[] frames = all.keys();
    final int[] counts = all.values();
    SortUtils.sortData(counts, frames, true, false);
    return new CumulativeCountData(frames, counts, createPlotData);
}

Example 45 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project GDSC-SMLM by aherbert.

the class ClassificationMatchCalculator method getMapper.

/**
 * Gets the mapper that can create a value from a natural sequence starting from 0 for each unique
 * key in the results. If the analysis is set to ignore then a single mapping to zero is created.
 *
 * @param allMatches the all matches
 * @param fun the function to get the key value
 * @param analysis the type of analysis
 * @return the mapper
 */
private static Mapper getMapper(List<PointPair> allMatches, ToIntFunction<PeakResult> fun, ClassAnalysis analysis) {
    if (analysis == ClassAnalysis.IGNORE) {
        return Mapper.single();
    }
    // Find the unique values
    final TIntHashSet set = new TIntHashSet();
    for (final PointPair r : allMatches) {
        set.add(fun.applyAsInt(((PeakResultPoint) r.getPoint1()).getPeakResult()));
        set.add(fun.applyAsInt(((PeakResultPoint) r.getPoint2()).getPeakResult()));
    }
    // Edge case of 1 value
    if (set.size() == 1) {
        return Mapper.single();
    }
    // Map to a natural sequence from zero
    final int[] keys = set.toArray();
    Arrays.sort(keys);
    // Check if a discrete sequence already
    if (keys[keys.length - 1] - keys[0] == set.size() - 1) {
        return Mapper.offset(set.size(), keys[0]);
    }
    // Map each key to a value starting from 0
    final TIntIntHashMap map = new TIntIntHashMap(keys.length);
    for (final int k : keys) {
        map.put(k, map.size());
    }
    return new Mapper() {

        @Override
        public int size() {
            return map.size();
        }

        @Override
        public int map(int key) {
            return map.get(key);
        }
    };
}