public void DeNormalizeGeneralCorrectnessTest()
{
int m = 10000, n = 100;
double epsilon = 0.000000001;
Random rnd = new Random();
double[][] iData = new double[m][];
for (int i = 0; i < m; ++i)
{
iData[i] = new double[n];
for (int j = 0; j < n; ++j)
{
iData[i][j] = rnd.Next();
}
}
double iA = 0.1;
double iB = 0.9;
DataNormalizer target = new DataNormalizer(iData, iA, iB);
double[][] normalized = target.Normalize(iData);
Assert.AreEqual(iA, normalized.Min(row => row.Min()), epsilon);
Assert.AreEqual(iB, normalized.Max(row => row.Max()), epsilon);
double maxAllowedError = 0.1, expectedAvg = 0.5, actualAvg = normalized.Average(row => row.Average());
Assert.AreEqual(expectedAvg, actualAvg, maxAllowedError);
double[][] actual = target.DeNormalize(normalized);
AssertMatrixAreEqual(iData, actual);
}
public void DeNormalizeGeneralCorrectnessTest()
{
int m = 10000, n = 100;
double epsilon = 0.000000001;
Random rnd = new Random();
double[][] iData = new double[m][];
for (int i = 0; i < m; ++i)
{
iData[i] = new double[n];
for (int j = 0; j < n; ++j)
iData[i][j] = rnd.Next();
}
double iA = 0.1;
double iB = 0.9;
DataNormalizer target = new DataNormalizer(iData, iA, iB);
double[][] normalized = target.Normalize(iData);
Assert.AreEqual(iA, normalized.Min(row => row.Min()), epsilon);
Assert.AreEqual(iB, normalized.Max(row => row.Max()), epsilon);
double maxAllowedError = 0.1, expectedAvg = 0.5, actualAvg = normalized.Average(row => row.Average());
Assert.AreEqual(expectedAvg, actualAvg, maxAllowedError);
double[][] actual = target.DeNormalize(normalized);
AssertMatrixAreEqual(iData, actual);
}
