MatrixFloat MatrixFloat::multiple(const MatrixFloat &b) const{
const unsigned int M = rows;
const unsigned int N = cols;
const unsigned int K = b.getNumRows();
const unsigned int L = b.getNumCols();
if( N != K ) {
errorLog << "multiple(MatrixFloat b) - The number of rows in b (" << K << ") does not match the number of columns in this matrix (" << N << ")" << std::endl;
return MatrixFloat();
}
MatrixFloat c(M,L);
Float **pb = b.getDataPointer();
Float **pc = c.getDataPointer();
unsigned int i,j,k = 0;
for(i=0; i<M; i++){
for(j=0; j<L; j++){
pc[i][j] = 0;
for(k=0; k<K; k++){
pc[i][j] += dataPtr[i*cols+k] * pb[k][j];
}
}
}
return c;
}
MatrixFloat TimeSeriesClassificationData::getSampleData(UINT classLabel, UINT recordID) const {
int record = 0;
for(UINT x=0; x<totalNumSamples; x++){
if( data[x].getClassLabel() == classLabel ){
if(record == recordID) {
return data[x].getData();
} else
record++;
}
}
return MatrixFloat();
}
MatrixFloat MatrixFloat::multiple(const Float value) const{
if( dataPtr == NULL ) return MatrixFloat();
MatrixFloat d(rows,cols);
Float *d_p = &(d[0][0]);
unsigned int i = 0;
for(i=0; i<rows*cols; i++){
d_p[i] = dataPtr[i] * value;
}
return d;
}
MatrixFloat ClassificationDataStream::getTimeSeriesData( const TimeSeriesPositionTracker &trackerInfo ) const {
if( trackerInfo.getStartIndex() >= totalNumSamples || trackerInfo.getEndIndex() > totalNumSamples ){
warningLog << "getTimeSeriesData(TimeSeriesPositionTracker trackerInfo) - Invalid tracker indexs!" << std::endl;
return MatrixFloat();
}
UINT startIndex = trackerInfo.getStartIndex();
UINT endIndex = trackerInfo.getEndIndex();
UINT M = endIndex > 0 ? trackerInfo.getLength() : totalNumSamples - startIndex;
UINT N = getNumDimensions();
MatrixFloat tsData(M,N);
for(UINT i=0; i<M; i++){
for(UINT j=0; j<N; j++){
tsData[i][j] = data[ i+startIndex ][j];
}
}
return tsData;
}
MatrixFloat TimeSeriesClassificationData::getDataAsMatrixFloat() const {
//Count how many samples are in the entire dataset
UINT M = 0;
UINT index = 0;
for(UINT x=0; x<totalNumSamples; x++){
M += data[x].getLength();
}
if( M == 0 ) MatrixFloat();
//Get all the data and concatenate it into 1 matrix
MatrixFloat matrixData(M,numDimensions);
for(UINT x=0; x<totalNumSamples; x++){
for(UINT i=0; i<data[x].getLength(); i++){
for(UINT j=0; j<numDimensions; j++){
matrixData[index][j] = data[x][i][j];
}
index++;
}
}
return matrixData;
}
