// Tests the MatrixFloat type
TEST(DynamicType, MatrixFloatTest) {
DynamicType type;
MatrixFloat a(3,1);
a[0][0] = 1.1; a[1][0] = 1.2; a[2][0] = 1.3;
EXPECT_TRUE( type.set( a ) );
MatrixFloat b = type.get< MatrixFloat >();
EXPECT_EQ( a.getSize(), b.getSize() );
EXPECT_EQ( a.getNumRows(), b.getNumRows() );
EXPECT_EQ( a.getNumCols(), b.getNumCols() );
for(unsigned int i=0; i<a.getNumRows(); i++){
for(unsigned int j=0; j<a.getNumCols(); j++){
EXPECT_EQ( a[i][j], b[i][j] );
}
}
}
bool TimeSeriesClassificationData::loadDatasetFromCSVFile(const std::string &filename){
numDimensions = 0;
datasetName = "NOT_SET";
infoText = "";
//Clear any previous data
clear();
//Parse the CSV file
FileParser parser;
if( !parser.parseCSVFile(filename,true) ){
errorLog << "loadDatasetFromCSVFile(const std::string &filename) - Failed to parse CSV file!" << std::endl;
return false;
}
if( !parser.getConsistentColumnSize() ){
errorLog << "loadDatasetFromCSVFile(const std::string &filename) - The CSV file does not have a consistent number of columns!" << std::endl;
return false;
}
if( parser.getColumnSize() <= 2 ){
errorLog << "loadDatasetFromCSVFile(const std::string &filename) - The CSV file does not have enough columns! It should contain at least three columns!" << std::endl;
return false;
}
//Set the number of dimensions
numDimensions = parser.getColumnSize()-2;
//Reserve the memory for the data
data.reserve( parser.getRowSize() );
UINT sampleCounter = 0;
UINT lastSampleCounter = 0;
UINT classLabel = 0;
UINT j = 0;
UINT n = 0;
VectorFloat sample(numDimensions);
MatrixFloat timeseries;
for(UINT i=0; i<parser.getRowSize(); i++){
sampleCounter = grt_from_str< UINT >( parser[i][0] );
//Check to see if a new timeseries has started, if so then add the previous time series as a sample and start recording the new time series
if( sampleCounter != lastSampleCounter && i != 0 ){
//Add the labelled sample to the dataset
if( !addSample(classLabel, timeseries) ){
warningLog << "loadDatasetFromCSVFile(const std::string &filename,const UINT classLabelColumnIndex) - Could not add sample " << i << " to the dataset!" << std::endl;
}
timeseries.clear();
}
lastSampleCounter = sampleCounter;
//Get the class label
classLabel = grt_from_str< UINT >( parser[i][1] );
//Get the sample data
j=0;
n=2;
while( j != numDimensions ){
sample[j++] = grt_from_str< Float >( parser[i][n] );
n++;
}
//Add the sample to the timeseries
timeseries.push_back( sample );
}
if ( timeseries.getSize() > 0 )
//Add the labelled sample to the dataset
if( !addSample(classLabel, timeseries) ){
warningLog << "loadDatasetFromCSVFile(const std::string &filename,const UINT classLabelColumnIndex) - Could not add sample " << parser.getRowSize()-1 << " to the dataset!" << std::endl;
}
return true;
}