//---------------------------------------------
#region Protected Methods
/// <summary>
/// Adjusts a data matrix, centering and standardizing its values
/// using the already computed column's means and standard deviations.
/// </summary>
///
protected internal double[,] Adjust(double[,] matrix, bool inPlace)
{
// Center the data around the mean. Will have no effect if
// the data is already centered (the mean will be zero).
double[,] result = matrix.Center(columnMeans, inPlace);
// Check if we also have to standardize our data (convert to Z Scores).
if (this.analysisMethod == AnalysisMethod.Standardize)
{
for (int j = 0; j < columnStdDev.Length; j++)
{
if (columnStdDev[j] == 0)
{
columnStdDev[j] = 1;
//manual modifed 2m0rr0w2
//throw new ArithmeticException("Standard deviation cannot be" +
//" zero (cannot standardize the constant variable at column index " + j + ").");
}
}
// Yes. Divide by standard deviation
result.Standardize(columnStdDev, true);
}
return(result);
}
public static double[,] Covariance(this double[,] matrix)
{
double[,] covMatrix = new double[matrix.RowCount(), matrix.ColumnCount()];
matrix = matrix.Center();
var covarianceMatrix = Multiply(matrix.Transpose(), matrix);
return(Divide(covarianceMatrix, matrix.RowCount() - 1));
}
/// <summary>
/// Applies the translation operator to translate the dataset to the given coordinate
/// </summary>
///
/// <param name="samples">Dataset to translate</param>
/// <param name="centroid">New center of the dataset</param>
///
/// <returns>The translated dataset</returns>
///
double[,] Translate(double[,] samples, double[] centroid)
{
if (centroid.Length != samples.GetLength(1))
{
throw new ArgumentException("Centroid length should be the same length of the samples columns !");
}
double[,] res = new double[samples.GetLength(0), samples.GetLength(1)];
// Calculate the matrix mean and translate it according to the required centroid
double[] translated_avg = samples.Mean(0).Subtract(centroid);
// Translate the sample data to the new centroid
res = samples.Center(translated_avg);
return(res);
}
protected internal double[,] Adjust(double[,] matrix, bool inPlace)
{
if (Means == null || Means.Length == 0)
{
Means = matrix.Mean(dimension: 0);
StandardDeviations = matrix.StandardDeviation(Means);
}
double[,] result = matrix.Center(Means, inPlace);
if (this.Method == PrincipalComponentMethod.Standardize || this.Method == PrincipalComponentMethod.CorrelationMatrix)
{
result.Standardize(StandardDeviations, true);
}
return(result);
}
/// <summary>
/// Transforms the dataset to match the given reference original dataset
/// </summary>
/// <param name="p_reference">Dataset to match</param>
/// <returns>The transformed dataset matched to the reference</returns>
public double[,] Transform(ProcrustedDataset p_reference)
{
// Make a copy of the current Procrustes dataset
double[,] tData = (double[, ])Dataset.Clone();
// Rotate the dataset to match the reference dataset rotation
tData = tData.Dot(p_reference.RotationMatrix.Transpose());
// Scale the dataset to match the reference scale
tData = tData.Multiply(p_reference.Scale);
// Prepare a negative translation vector to...
double[] refCenter = p_reference.Center.Multiply(-1);
// ... move the dataset to the same center as the reference
tData = tData.Center(refCenter);
return(tData);
}
protected internal double[,] Adjust(double[,] matrix, bool inPlace)
{
if (Means == null || Means.Length == 0)
{
Means = matrix.Mean(dimension: 0);
StandardDeviations = matrix.StandardDeviation(Means);
}
// Center the data around the mean. Will have no effect if
// the data is already centered (the mean will be zero).
double[,] result = matrix.Center(Means, inPlace);
// Check if we also have to standardize our data (convert to Z Scores).
if (this.Method == PrincipalComponentMethod.Standardize || this.Method == PrincipalComponentMethod.CorrelationMatrix)
{
// Yes. Divide by standard deviation
result.Standardize(StandardDeviations, true);
}
return(result);
}
