Examples with INodeView com.amazon.randomcutforest.tree.INodeView used on opensource projects

Example 16 with INodeView

use of com.amazon.randomcutforest.tree.INodeView in project random-cut-forest-by-aws by aws.

the class SimpleInterpolationVisitorTest method testAcceptLeafNotEquals.

@Test
public void testAcceptLeafNotEquals() {
    float[] point = { 1.0f, 9.0f, 4.0f };
    float[] anotherPoint = { 4.0f, 5.0f, 6.0f };
    INodeView leafNode = mock(NodeView.class);
    when(leafNode.getLeafPoint()).thenReturn(anotherPoint);
    when(leafNode.getBoundingBox()).thenReturn(new BoundingBox(anotherPoint, anotherPoint));
    when(leafNode.getMass()).thenReturn(4);
    int leafDepth = 100;
    int sampleSize = 99;
    SimpleInterpolationVisitor visitor = new SimpleInterpolationVisitor(point, sampleSize, 1, false);
    visitor.acceptLeaf(leafNode, leafDepth);
    InterpolationMeasure result = visitor.getResult();
    double expectedSumOfNewRange = 3.0 + 4.0 + 2.0;
    double[] expectedDifferenceInRangeVector = { 0.0, 3.0, 4.0, 0.0, 0.0, 2.0 };
    double[] expectedProbVector = Arrays.stream(expectedDifferenceInRangeVector).map(x -> x / expectedSumOfNewRange).toArray();
    double[] expectedmeasure = Arrays.stream(expectedProbVector).toArray();
    double[] expectedDistances = new double[2 * point.length];
    for (int i = 0; i < 2 * point.length; i++) {
        expectedDistances[i] = expectedProbVector[i] * expectedDifferenceInRangeVector[i];
    }
    for (int i = 0; i < 2 * point.length; i++) {
        expectedmeasure[i] = expectedmeasure[i] * 5;
    }
    for (int i = 0; i < point.length; i++) {
        assertEquals(expectedProbVector[2 * i], result.probMass.high[i]);
        assertEquals(expectedProbVector[2 * i + 1], result.probMass.low[i]);
        assertEquals(expectedmeasure[2 * i], result.measure.high[i]);
        assertEquals(expectedmeasure[2 * i + 1], result.measure.low[i]);
        assertEquals(expectedDistances[2 * i], result.distances.high[i]);
        assertEquals(expectedDistances[2 * i + 1], result.distances.low[i]);
    }
}

Example 17 with INodeView

use of com.amazon.randomcutforest.tree.INodeView in project random-cut-forest-by-aws by aws.

the class AnomalyAttributionVisitorTest method testAcceptLeafNotEquals.

@Test
public void testAcceptLeafNotEquals() {
    float[] point = new float[] { 1.1f, -2.2f, 3.3f };
    float[] anotherPoint = new float[] { -4.0f, 5.0f, 6.0f };
    INodeView leafNode = mock(NodeView.class);
    when(leafNode.getLeafPoint()).thenReturn(anotherPoint);
    when(leafNode.getBoundingBox()).thenReturn(new BoundingBox(anotherPoint, anotherPoint));
    int leafDepth = 100;
    int leafMass = 4;
    when(leafNode.getMass()).thenReturn(leafMass);
    int treeMass = 21;
    AnomalyAttributionVisitor visitor = new AnomalyAttributionVisitor(point, treeMass, 0);
    visitor.acceptLeaf(leafNode, leafDepth);
    double expectedScoreSum = defaultScoreUnseenFunction(leafDepth, leafMass);
    double sumOfNewRange = (1.1 - (-4.0)) + (5.0 - (-2.2)) + (6.0 - 3.3);
    DiVector result = visitor.getResult();
    assertEquals(defaultScalarNormalizerFunction(expectedScoreSum * (1.1 - (-4.0)) / sumOfNewRange, treeMass), result.high[0], EPSILON);
    assertEquals(0.0, result.low[0]);
    assertEquals(0.0, result.high[1]);
    assertEquals(defaultScalarNormalizerFunction(expectedScoreSum * (5.0 - (-2.2)) / sumOfNewRange, treeMass), result.low[1], EPSILON);
    assertEquals(0.0, result.high[2]);
    assertEquals(defaultScalarNormalizerFunction(expectedScoreSum * (6.0 - 3.3) / sumOfNewRange, treeMass), result.low[2], EPSILON);
    visitor = new AnomalyAttributionVisitor(point, treeMass, 3);
    visitor.acceptLeaf(leafNode, leafDepth);
    result = visitor.getResult();
    assertEquals(defaultScalarNormalizerFunction(expectedScoreSum * (1.1 - (-4.0)) / sumOfNewRange, treeMass), result.high[0], EPSILON);
    assertEquals(0.0, result.low[0]);
    assertEquals(0.0, result.high[1]);
    assertEquals(defaultScalarNormalizerFunction(expectedScoreSum * (5.0 - (-2.2)) / sumOfNewRange, treeMass), result.low[1], EPSILON);
    assertEquals(0.0, result.high[2]);
    assertEquals(defaultScalarNormalizerFunction(expectedScoreSum * (6.0 - 3.3) / sumOfNewRange, treeMass), result.low[2], EPSILON);
    visitor = new AnomalyAttributionVisitor(point, treeMass, 4);
    visitor.acceptLeaf(leafNode, leafDepth);
    double expectedScore = expectedScoreSum / (2 * point.length);
    result = visitor.getResult();
    for (int i = 0; i < point.length; i++) {
        assertEquals(defaultScalarNormalizerFunction(expectedScore, treeMass), result.low[i], EPSILON);
        assertEquals(defaultScalarNormalizerFunction(expectedScore, treeMass), result.high[i], EPSILON);
    }
}