internal virtual void printMatrix(Array2DRowRealMatrix array2DRowRealMatrix)
{
for (int i = 0; i < array2DRowRealMatrix.getRowDimension(); i++)
{
for (int j = 0; j < array2DRowRealMatrix.getColumnDimension(); j++)
{
[email protected](new StringBuilder().append(array2DRowRealMatrix.getEntry(i, j)).append(" ").toString());
}
[email protected]();
}
}
void PrintMatrix(Array2DRowRealMatrix a)
{
for (int i = 0; i < a.getRowDimension(); i++)
{
for (int j = 0; j < a.getColumnDimension(); j++)
{
Console.Write(a.getEntry(i, j) + " ");
}
Console.WriteLine();
}
}
internal virtual double getLikelihoodRatio(double num, int num2, Array2DRowRealMatrix array2DRowRealMatrix)
{
int num3 = 13;
double num4 = 0.5 * ((double)num3 + 0.5 * (double)num3 * (double)(num3 + 1)) * java.lang.Math.log((double)array2DRowRealMatrix.getRowDimension()) * 2.0;
int rowDimension = array2DRowRealMatrix.getRowDimension();
int columnDimension = array2DRowRealMatrix.getColumnDimension();
Array2DRowRealMatrix mat = (Array2DRowRealMatrix)array2DRowRealMatrix.getSubMatrix(0, num2 - 1, 0, columnDimension - 1);
Array2DRowRealMatrix mat2 = (Array2DRowRealMatrix)array2DRowRealMatrix.getSubMatrix(num2, rowDimension - 1, 0, columnDimension - 1);
double num5 = SpeakerIdentification.getBICValue(mat);
double num6 = SpeakerIdentification.getBICValue(mat2);
return(num - num5 - num6 - num4);
}
/**
*
* @param bicValue
* The bicValue of the model represented by only one Gaussian.
* This parameter it's useful when this function is called
* repeatedly for different frame values and the same features
* parameter
* @param frame
* the frame which is tested for being a change point
* @param features
* the feature vectors matrix
* @return the likelihood ratio
*/
static double GetLikelihoodRatio(double bicValue, int frame, Array2DRowRealMatrix features)
{
double bicValue1, bicValue2;
int d = Segment.FeaturesSize;
double penalty = 0.5 * (d + 0.5 * d * (d + 1)) * Math.Log(features.getRowDimension()) * 2;
int nrows = features.getRowDimension(), ncols = features.getColumnDimension();
Array2DRowRealMatrix sub1, sub2;
sub1 = (Array2DRowRealMatrix)features.getSubMatrix(0, frame - 1, 0, ncols - 1);
sub2 = (Array2DRowRealMatrix)features.getSubMatrix(frame, nrows - 1, 0, ncols - 1);
bicValue1 = GetBICValue(sub1);
bicValue2 = GetBICValue(sub2);
return(bicValue - bicValue1 - bicValue2 - penalty);
}
/**
* @param start
* The starting frame
* @param length
* The length of the interval, as numbers of frames
* @param features
* The matrix build with feature vectors as rows
* @return Returns the changing point in the input represented by features
*
*/
private static int GetPoint(int start, int length, int step, Array2DRowRealMatrix features)
{
double max = Double.NegativeInfinity;
int ncols = features.getColumnDimension(), point = 0;
var sub = (Array2DRowRealMatrix)features.getSubMatrix(start, start + length - 1, 0, ncols - 1);
double bicValue = GetBICValue(sub);
for (int i = Segment.FeaturesSize + 1; i < length - Segment.FeaturesSize; i += step)
{
double aux = GetLikelihoodRatio(bicValue, i, sub);
if (aux > max)
{
max = aux;
point = i;
}
}
if (max < 0)
{
point = Integer.MIN_VALUE;
}
return(point + start);
}
private int getPoint(int num, int num2, int num3, Array2DRowRealMatrix array2DRowRealMatrix)
{
double num4 = double.NegativeInfinity;
int columnDimension = array2DRowRealMatrix.getColumnDimension();
int num5 = 0;
Array2DRowRealMatrix array2DRowRealMatrix2 = (Array2DRowRealMatrix)array2DRowRealMatrix.getSubMatrix(num, num + num2 - 1, 0, columnDimension - 1);
double num6 = SpeakerIdentification.getBICValue(array2DRowRealMatrix2);
for (int i = 14; i < num2 - 13; i += num3)
{
double num7 = this.getLikelihoodRatio(num6, i, array2DRowRealMatrix2);
if (num7 > num4)
{
num4 = num7;
num5 = i;
}
}
if (num4 < (double)0f)
{
num5 = int.MinValue;
}
return(num5 + num);
}