public void TestDomainDimensionSanity()
{
using (var eventStream = new RealValueFileEventStream(Tests.GetFullPath(@"/opennlp/data/maxent/real-valued-weights-training-data.txt"), Encoding.UTF8)) {
var di = new OnePassRealValueDataIndexer(eventStream, 1);
di.Execute();
var func = new NegLogLikelihood(di);
var correctDomainDimension = di.GetPredLabels().Length *di.GetOutcomeLabels().Length;
Assert.AreEqual(correctDomainDimension, func.Dimension);
}
}
public void TestValueAtNonInitialPoint02()
{
using (var eventStream = new RealValueFileEventStream(Tests.GetFullPath(@"/opennlp/data/maxent/real-valued-weights-training-data.txt"), Encoding.UTF8)) {
var di = new OnePassRealValueDataIndexer(eventStream, 1);
di.Execute();
var func = new NegLogLikelihood(di);
var nonInitialPoint = new double[] { 3, 2, 3, 2, 3, 2, 3, 2, 3, 2 };
var value = func.ValueAt(DealignDoubleArrayForTestData(nonInitialPoint,
di.GetPredLabels(),
di.GetOutcomeLabels()));
const double expectedValue = 53.163219721099026;
Assert.AreEqual(expectedValue, value, Tolerance2);
}
}
public void TestGradientAtInitialPoint()
{
using (var eventStream = new RealValueFileEventStream(Tests.GetFullPath(@"/opennlp/data/maxent/real-valued-weights-training-data.txt"), Encoding.UTF8)) {
var di = new OnePassRealValueDataIndexer(eventStream, 1);
di.Execute();
var func = new NegLogLikelihood(di);
var nonInitialPoint = new[] { 0.2, 0.5, 0.2, 0.5, 0.2, 0.5, 0.2, 0.5, 0.2, 0.5 };
var gradientAtNonInitialPoint = func.GradientAt(DealignDoubleArrayForTestData(nonInitialPoint, di.GetPredLabels(), di.GetOutcomeLabels()));
var expectedGradient =
new[] { -12.755042847945553, -21.227127506102434,
-72.57790706276435, 38.03525795198456,
15.348650889354925, 12.755042847945557,
21.22712750610244, 72.57790706276438,
-38.03525795198456, -15.348650889354925 };
Assert.True(CompareDoubleArray(expectedGradient, gradientAtNonInitialPoint, di, Tolerance1));
}
}