public void TestMultistepSingleValue()
{
_classifier = new CLAClassifier(new[] { 1, 2 });
// Only should return one actual value bucket.
Classification <double> result = null;
int recordNum = 0;
for (int i = 0; i < 10; i++, recordNum++)
{
result = Compute <double>(_classifier, recordNum, new[] { 1, 5 }, 0, 10);
}
Assert.IsTrue(Arrays.AreEqual(new double[] { 10.0 }, result.GetActualValues()));
// Should have a probability of 100% for that bucket.
Assert.IsTrue(Arrays.AreEqual(new double[] { 1.0 }, result.GetStats(1)));
Assert.IsTrue(Arrays.AreEqual(new double[] { 1.0 }, result.GetStats(2)));
}
public void TestMultistepSingleValue()
{
var classifier = new SDRClassifier(new[] { 1, 2 });
Classification <double> retVal = null;
for (int i = 0; i < 10; i++)
{
retVal = _compute(classifier, i, new[] { 1, 5 }, 0, 10);
}
// Since overlap - should be previous with high likelihood
double[] actValues = retVal.GetActualValues();
Assert.AreEqual((double)actValues[0], 10);
double[] resultDoubles1 = (double[])retVal.GetStats(1);
double[] resultDoubles2 = (double[])retVal.GetStats(2);
Assert.AreEqual(resultDoubles1[0], 1);
Assert.AreEqual(resultDoubles2[0], 1);
}
public void TestMultistepSimple()
{
_classifier = new CLAClassifier(new[] { 1, 2 }, 0.001, 0.3, 0);
Classification <double> result = null;
int recordNum = 0;
for (int i = 0; i < 100; i++, recordNum++)
{
result = Compute <double>(_classifier, recordNum, new[] { i % 10 }, i % 10, (i % 10) * 10);
}
// Only should return one actual value bucket.
Assert.IsTrue(Arrays.AreEqual(new double[] { 0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0 }, result.GetActualValues()));
Assert.AreEqual(1.0, result.GetStat(1, 0), 0.1);
for (int i = 1; i < 10; i++)
{
Assert.AreEqual(0.0, result.GetStat(1, i), 0.1);
}
Assert.AreEqual(1.0, result.GetStat(2, 1), 0.1);
}
