Examples with XorShift128PlusRandom jcog.math.random.XorShift128PlusRandom used on opensource projects

Example 6 with XorShift128PlusRandom

use of jcog.math.random.XorShift128PlusRandom in project narchy by automenta.

the class BaggieTest method testSampling.

@Test
public void testSampling() {
    int cap = 8;
    Baggie<String> s = new Baggie(cap);
    for (int i = 0; i < cap; i++) {
        s.put("x" + i, i / ((float) cap));
    }
    String t = Joiner.on(",").join(s.toList());
    assertEquals("x7=0.87498856,x6=0.7500076,x5=0.6249962,x4=0.50001526,x3=0.3750038,x2=0.24999237,x1=0.12501144,x0=0.0", t);
    Random rng = new XorShift128PlusRandom(1);
    Frequency f = new Frequency();
    final int[] num = { cap * 100 };
    s.sample(rng, (x) -> {
        f.addValue(x.get());
        return num[0]-- > 0;
    });
    System.out.println(f);
    assertTrue(f.getCount("x" + (cap - 1)) > f.getCount("x0"));
    {
        // change all to a new value (0.5)
        final int[] resetNum = { cap * 100 };
        // TODO use s.commit()
        s.sample(rng, (x) -> {
            x.set(0.5f);
            return resetNum[0]-- > 0;
        });
        s.forEach((x, p) -> {
            assertEquals(0.5f, p, 0.001f);
            return true;
        });
        // effectively cleared
        assertEquals(cap, s.size());
        assertEquals(0.5f, s.priMax(), 0.001f);
        assertEquals(0.5f, s.priMin(), 0.001f);
    }
    {
        // remove everything
        final int[] remNum = { 0 };
        s.sample(rng, (x) -> {
            // delete it
            x.set(Float.NaN);
            remNum[0]++;
            return true;
        });
        // all removed during sampling
        assertEquals(cap, remNum[0]);
        // effectively cleared
        assertEquals(0, s.size());
        assertEquals(Float.NaN, s.priMax(), 0.001f);
        assertEquals(Float.NaN, s.priMin(), 0.001f);
    }
}

Example 7 with XorShift128PlusRandom

use of jcog.math.random.XorShift128PlusRandom in project narchy by automenta.

the class TestLSTM1 method testLSTM1.

@Test
public void testLSTM1() {
    // System.out.println("Test of SimpleLSTM\n");
    Random r = new XorShift128PlusRandom(1234);
    DistractedSequenceRecall task = new DistractedSequenceRecall(r, 12, 3, 22, 1000);
    int cell_blocks = 4;
    // double learningRate = 0.05;
    SimpleLSTM slstm = task.lstm(cell_blocks);
    int epochs = 150;
    double error = 0;
    for (int epoch = 0; epoch < epochs; epoch++) {
        double fit = task.scoreSupervised(slstm, 0.1f);
        error = 1 - fit;
        if (epoch % 10 == 0)
            System.out.println("[" + epoch + "] error = " + error);
    }
    // System.out.println("done.");
    assertTrue(error < 0.01f);
}

Example 8 with XorShift128PlusRandom

use of jcog.math.random.XorShift128PlusRandom in project narchy by automenta.

the class BagLab method update.

private synchronized void update() {
    int inputRate = 20;
    for (int j = 0; j < inputRate; j++) {
        int n = inputSliders.size();
        for (int i = 0; i < n; i++) {
            if (Math.random() < inputSliders.get(i).value()) {
                float p = (i + (float) Math.random()) / (n - 1);
                // float q = (float)Math.random(); //random quality
                bag.put(new PLink<>((int) Math.floor(Math.random() * uniques), p));
            }
        }
    }
    bag.commit();
    int bins = selectionHistogram.length;
    float sampleBatches = 1;
    int batchSize = 32;
    if (iteration++ % histogramResetPeriod == 0)
        Arrays.fill(selectionHistogram, 0);
    // System.out.println(bag.size());
    XorShift128PlusRandom rng = new XorShift128PlusRandom(1);
    List<PriReference<Integer>> sampled = $.newArrayList(1024);
    for (int i = 0; i < (int) sampleBatches; i++) {
        sampled.clear();
        // System.out.println(h + " " + v);
        bag.sample(rng, batchSize, (Consumer<PriReference<Integer>>) sampled::add);
        // BLink<Integer> sample = bag.sample();
        for (PriReference<Integer> sample : sampled) {
            if (sample != null) {
                float p = sample.priElseZero();
                selectionHistogram[Util.bin(p, bins - 1)]++;
            } else {
                break;
            }
        }
    }
}

Example 9 with XorShift128PlusRandom

use of jcog.math.random.XorShift128PlusRandom in project narchy by automenta.

the class BaggieTest method testSustainedAdd.

@Test
public void testSustainedAdd() {
    int cap = 256;
    int uniq = cap * 2;
    Baggie<String> s = new Baggie<>(cap);
    Random rng = new XorShift128PlusRandom(1);
    for (int i = 0; i < cap * 256; i++) {
        s.put("x" + i, rng.nextFloat());
    }
    assertEquals(cap, s.size());
}

Example 10 with XorShift128PlusRandom

use of jcog.math.random.XorShift128PlusRandom in project narchy by automenta.

the class PermutationsTest method testShuffleReset.

public void testShuffleReset(int size, int selected) {
    int expected = factorial(size);
    // just to be safe
    int attempts = (1 + expected / selected) * (1 + expected / selected);
    Set<String> sequences = new HashSet();
    Set<String> arrays = new TreeSet();
    Random rng = new XorShift128PlusRandom(2);
    int[] n = new int[size];
    ShuffledPermutations perm = new ShuffledPermutations();
    int attempt;
    for (attempt = 1; attempt < attempts; attempt++) {
        perm.restart(size, rng);
        StringBuilder sb = new StringBuilder();
        int x;
        for (x = 0; perm.hasNext() && x < selected; x++) {
            String aa = Arrays.toString(perm.nextPermute(n));
            arrays.add(aa);
            sb.append(aa).append(' ');
        }
        /*System.out.println(//perm.shuffle +
                    " " + sb.toString());*/
        sequences.add(sb.toString());
        if (arrays.size() == expected)
            break;
    }
    System.out.println(size + " exhausted all " + expected + " permutations after " + attempt + " attempts when sets of " + selected + " are selected");
    // by this point there should be at least > 1
    assertTrue(sequences.size() >= 1);
    // arrays.forEach(a -> System.out.println(a));
    assertTrue(expected >= arrays.size());
}