/// <summary>Constructs a new Independent Component Analysis.</summary>
public IndependentComponentAnalysis(double[,] data, AnalysisMethod method, IndependentComponentAlgorithm algorithm)
{
if (data == null) throw new ArgumentNullException("data");
this.sourceMatrix = data;
this.algorithm = algorithm;
this.analysisMethod = method;
// Calculate common measures to speedup other calculations
this.columnMeans = Accord.Statistics.Tools.Mean(sourceMatrix);
this.columnStdDev = Accord.Statistics.Tools.StandardDeviation(sourceMatrix, columnMeans);
}
/// <summary>
/// Constructs a new Independent Component Analysis.
/// </summary>
///
/// <param name="data">The source data to perform analysis. The matrix should contain
/// variables as columns and observations of each variable as rows.</param>
/// <param name="method">The analysis method to perform. Default is
/// <see cref="AnalysisMethod.Center"/>.</param>
/// <param name="algorithm">The FastICA algorithm to be used in the analysis. Default
/// is <see cref="IndependentComponentAlgorithm.Parallel"/>.</param>
///
public IndependentComponentAnalysis(double[][] data, AnalysisMethod method = AnalysisMethod.Center,
IndependentComponentAlgorithm algorithm = IndependentComponentAlgorithm.Parallel)
{
if (data == null)
{
throw new ArgumentNullException("data");
}
this.sourceMatrix = data.ToMatrix();
this.algorithm = algorithm;
this.analysisMethod = method;
// Calculate common measures to speedup other calculations
this.columnMeans = Measures.Mean(sourceMatrix);
this.columnStdDev = Measures.StandardDeviation(sourceMatrix, columnMeans);
}
public IndependentComponentAnalysis(double[,] data, AnalysisMethod method,
IndependentComponentAlgorithm algorithm)
{
if (data == null)
{
throw new ArgumentNullException("data");
}
this.sourceMatrix = data;
this.algorithm = algorithm;
this.analysisMethod = method;
// Calculate common measures to speedup other calculations
this.columnMeans = Measures.Mean(sourceMatrix, dimension: 0);
this.columnStdDev = Measures.StandardDeviation(sourceMatrix, columnMeans);
this.NumberOfInputs = data.Columns();
this.NumberOfOutputs = data.Columns();
}
/// <summary>
/// Constructs a new Independent Component Analysis.
/// </summary>
///
public IndependentComponentAnalysis(AnalysisMethod method = AnalysisMethod.Center,
IndependentComponentAlgorithm algorithm = IndependentComponentAlgorithm.Parallel)
{
this.algorithm = algorithm;
this.analysisMethod = method;
}
public IndependentComponentAnalysis(double[,] data, IndependentComponentAlgorithm algorithm)
: this(data, AnalysisMethod.Center, algorithm)
{
}
