internal static double[][] Preprocess(T[] sequence)
{
if (sequence.Length == 0)
{
return(new double[0][]);
}
int dims = Datapoint <T> .Dimensions;
double[][] result = new double[sequence.Length][];
for (int i = 0; i < sequence.Length; i++)
{
//result[i] = new double[] { sequence[i].X, sequence[i].Y };
result[i] = ((IDatapoint)sequence[i])
.AsArray()
//.Cast<double>()
.Select(f => (double)f)
.ToArray();
}
double[] currentAxisValues = new double[sequence.Length]; // Just to save on allocations a tiny bit by reusing it within a single axis.
double[] means = new double[dims];
double[] sigmas = new double[dims];
for (int j = 0; j < dims; j++)
{
for (int i = 0; i < sequence.Length; i++)
{
currentAxisValues[i] = result[i][j];
}
means[j] = currentAxisValues.Average();
sigmas[j] = Accord.Statistics.Measures.StandardDeviation(currentAxisValues);
}
sigmas = CrosslinkAxes.Apply <T>(sigmas); // Datapoint<T>.CrosslinkScalingFactors(sigmas); // Locks values in the same space - like X and Y axes - to the same window size.
double[][] zscores = Accord.Statistics.Tools.ZScores(result, means, sigmas);
return(Accord.Math.Elementwise.Add(zscores, 10));
}
public double[][] Preprocess(double[][] extracted, PreprocessorCoefficients?coefficients = null)
{
// If not using the (more advanced) precalculated full-dataset averages & sigmas, calculate them locally here.
if (coefficients == null)
{
//var dims = Datapoint.From<Tsource>(default(Tsource)).Dimensions;
var dims = Dimensions;
double[] currentAxisValues = new double[extracted.Length]; // Just to save on allocations a tiny bit by reusing it within a single axis.
double[] means = new double[dims];
double[] sigmas = new double[dims];
for (int j = 0; j < dims; j++)
{
for (int i = 0; i < extracted.Length; i++)
{
currentAxisValues[i] = extracted[i][j];
}
means[j] = currentAxisValues.Average();
sigmas[j] = Accord.Statistics.Measures.StandardDeviation(currentAxisValues);
}
// Use our standard crosslinking function to lock values which should share a normalization constant into the same scale as each other.
if (doCrosslink)
{
sigmas = CrosslinkAxes.Apply <Tin>(sigmas); // Locks values in the same space - like X and Y axes - to the same window size.
}
coefficients = new PreprocessorCoefficients()
{
Means = means, Sigmas = sigmas
};
}
// Calculate the z-scores, then make them positive by the simple expedient of adding ten to them. (Yes, yes, but ten-sigma? Gotta mean an error anyway.)
double[][] zscores = Accord.Statistics.Tools.ZScores(extracted, coefficients.Value.Means, coefficients.Value.Sigmas);
return(Accord.Math.Elementwise.Add(zscores, 10));
}