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MAINT: comment out overloads that result in ambiguous calls
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@gabrielbmotta
gabrielbmotta committed Jan 12, 2022
1 parent 8d005ca commit 917106a
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Showing 3 changed files with 145 additions and 145 deletions.
208 changes: 104 additions & 104 deletions libraries/utils/ioutils.h
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Original file line number Diff line number Diff line change
Expand Up @@ -397,49 +397,49 @@ bool IOUtils::write_eigen_matrix(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::D

//=============================================================================================================

template<typename T>
bool IOUtils::write_eigen_matrix(const Eigen::Matrix<T, 1, Eigen::Dynamic>& in, const std::string& sPath, const std::string& sDescription)
{
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName(1,in.cols());
matrixName.row(0)= in;
return IOUtils::write_eigen_matrix(matrixName, sPath, sDescription);
}

//=============================================================================================================

template<typename T>
bool IOUtils::write_eigen_matrix(const Eigen::Matrix<T, Eigen::Dynamic, 1>& in, const std::string& sPath, const std::string& sDescription)
{
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName(in.rows(),1);
matrixName.col(0)= in;
return IOUtils::write_eigen_matrix(matrixName, sPath, sDescription);
}

//=============================================================================================================

template<typename T>
bool IOUtils::write_eigen_matrix(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& in, const std::string& sPath, const std::string& sDescription)
{
std::ofstream outputFile(sPath);
if(outputFile.is_open())
{
if(!sDescription.empty()) {
outputFile<<"# Dimensions (rows x cols): "<<in.rows()<<" x "<<in.cols()<<"\n";
outputFile<<"# Description: "<<sDescription<<"\n";
}

for(int row = 0; row<in.rows(); row++) {
for(int col = 0; col<in.cols(); col++)
outputFile << in(row, col)<<" ";
outputFile<<"\n";
}
} else {
qWarning()<<"Could not write Eigen element to file! Path does not exist!";
return false;
}

return true;
}
//template<typename T>
//bool IOUtils::write_eigen_matrix(const Eigen::Matrix<T, 1, Eigen::Dynamic>& in, const std::string& sPath, const std::string& sDescription)
//{
// Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName(1,in.cols());
// matrixName.row(0)= in;
// return IOUtils::write_eigen_matrix(matrixName, sPath, sDescription);
//}

////=============================================================================================================

//template<typename T>
//bool IOUtils::write_eigen_matrix(const Eigen::Matrix<T, Eigen::Dynamic, 1>& in, const std::string& sPath, const std::string& sDescription)
//{
// Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName(in.rows(),1);
// matrixName.col(0)= in;
// return IOUtils::write_eigen_matrix(matrixName, sPath, sDescription);
//}

////=============================================================================================================

//template<typename T>
//bool IOUtils::write_eigen_matrix(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& in, const std::string& sPath, const std::string& sDescription)
//{
// std::ofstream outputFile(sPath);
// if(outputFile.is_open())
// {
// if(!sDescription.empty()) {
// outputFile<<"# Dimensions (rows x cols): "<<in.rows()<<" x "<<in.cols()<<"\n";
// outputFile<<"# Description: "<<sDescription<<"\n";
// }

// for(int row = 0; row<in.rows(); row++) {
// for(int col = 0; col<in.cols(); col++)
// outputFile << in(row, col)<<" ";
// outputFile<<"\n";
// }
// } else {
// qWarning()<<"Could not write Eigen element to file! Path does not exist!";
// return false;
// }

// return true;
//}

//=============================================================================================================

Expand Down Expand Up @@ -523,86 +523,86 @@ bool IOUtils::read_eigen_matrix(Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>

//=============================================================================================================

template<typename T>
bool IOUtils::read_eigen_matrix(Eigen::Matrix<T, 1, Eigen::Dynamic>& out, const std::string& path)
{
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName;
bool bStatus = IOUtils::read_eigen_matrix(matrixName, path);
//template<typename T>
//bool IOUtils::read_eigen_matrix(Eigen::Matrix<T, 1, Eigen::Dynamic>& out, const std::string& path)
//{
// Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName;
// bool bStatus = IOUtils::read_eigen_matrix(matrixName, path);

if(matrixName.rows() > 0)
{
out = matrixName.row(0);
}
// if(matrixName.rows() > 0)
// {
// out = matrixName.row(0);
// }

return bStatus;
}
// return bStatus;
//}

//=============================================================================================================
////=============================================================================================================

template<typename T>
bool IOUtils::read_eigen_matrix(Eigen::Matrix<T, Eigen::Dynamic, 1>& out, const std::string& path)
{
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName;
bool bStatus = IOUtils::read_eigen_matrix(matrixName, path);
//template<typename T>
//bool IOUtils::read_eigen_matrix(Eigen::Matrix<T, Eigen::Dynamic, 1>& out, const std::string& path)
//{
// Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrixName;
// bool bStatus = IOUtils::read_eigen_matrix(matrixName, path);

if(matrixName.cols() > 0)
{
out = matrixName.col(0);
}
// if(matrixName.cols() > 0)
// {
// out = matrixName.col(0);
// }

return bStatus;
}
// return bStatus;
//}

//=============================================================================================================
////=============================================================================================================

template<typename T>
bool IOUtils::read_eigen_matrix(Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& out, const std::string& path)
{
std::ifstream inputFile(path);
//template<typename T>
//bool IOUtils::read_eigen_matrix(Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& out, const std::string& path)
//{
// std::ifstream inputFile(path);

if(inputFile.is_open()) {
//Start reading from file
std::vector<Eigen::VectorXd> help;
// if(inputFile.is_open()) {
// //Start reading from file
// std::vector<Eigen::VectorXd> help;

std::string line;
// std::string line;

while(std::getline(inputFile, line)){
if(line.find('#') == std::string::npos){
std::vector<double> elements;
std::stringstream stream{line};
std::string element;
// while(std::getline(inputFile, line)){
// if(line.find('#') == std::string::npos){
// std::vector<double> elements;
// std::stringstream stream{line};
// std::string element;

stream >> std::ws;
while(stream >> element){
elements.push_back(std::stod(element));
stream >> std::ws;
}
// stream >> std::ws;
// while(stream >> element){
// elements.push_back(std::stod(element));
// stream >> std::ws;
// }

Eigen::VectorXd x (elements.size());
// Eigen::VectorXd x (elements.size());

for(size_t i = 0; i < elements.size(); ++i){
x(i) = elements.at(i);
}
// for(size_t i = 0; i < elements.size(); ++i){
// x(i) = elements.at(i);
// }

help.push_back(std::move(x));
}
}
// help.push_back(std::move(x));
// }
// }

int rows = help.size();
int cols = rows <= 0 ? 0 : help.at(0).rows();
// int rows = help.size();
// int cols = rows <= 0 ? 0 : help.at(0).rows();

out.resize(rows, cols);
// out.resize(rows, cols);

for (size_t i = 0; i < help.size(); i++) {
out.row(i) = help[i].transpose();
}
} else {
qWarning()<<"IOUtils::read_eigen_matrix - Could not read Eigen element from file! Path does not exist!";
return false;
}
// for (size_t i = 0; i < help.size(); i++) {
// out.row(i) = help[i].transpose();
// }
// } else {
// qWarning()<<"IOUtils::read_eigen_matrix - Could not read Eigen element from file! Path does not exist!";
// return false;
// }

return true;
}
// return true;
//}
} // NAMESPACE

#endif // IOUTILS_H
Expand Down
48 changes: 24 additions & 24 deletions libraries/utils/kmeans.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -89,30 +89,30 @@ KMeans::KMeans(QString distance,

//=============================================================================================================

KMeans::KMeans(std::string distance,
std::string start,
qint32 replicates,
std::string emptyact,
bool online,
qint32 maxit)
: m_sDistance(distance)
, m_sStart(start)
, m_iReps(replicates)
, m_sEmptyact(emptyact)
, m_iMaxit(maxit)
, m_bOnline(online)
, emptyErrCnt(0)
, iter(0)
, k(0)
, n(0)
, p(0)
, totsumD(0)
, prevtotsumD(0)
{
// Assume one replicate
if (m_iReps < 1)
m_iReps = 1;
}
//KMeans::KMeans(std::string distance,
// std::string start,
// qint32 replicates,
// std::string emptyact,
// bool online,
// qint32 maxit)
//: m_sDistance(distance)
//, m_sStart(start)
//, m_iReps(replicates)
//, m_sEmptyact(emptyact)
//, m_iMaxit(maxit)
//, m_bOnline(online)
//, emptyErrCnt(0)
//, iter(0)
//, k(0)
//, n(0)
//, p(0)
//, totsumD(0)
//, prevtotsumD(0)
//{
// // Assume one replicate
// if (m_iReps < 1)
// m_iReps = 1;
//}

//=============================================================================================================

Expand Down
34 changes: 17 additions & 17 deletions libraries/utils/kmeans.h
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Original file line number Diff line number Diff line change
Expand Up @@ -96,23 +96,23 @@ class UTILSSHARED_EXPORT KMeans
bool online = true,
qint32 maxit = 100);

//=========================================================================================================
/**
* Constructs a KMeans algorithm object.
*
* @param[in] distance (optional) K-Means distance measure: "sqeuclidean" (default), "cityblock" , "cosine", "correlation", "hamming".
* @param[in] start (optional) Cluster initialization: "sample" (default), "uniform", "cluster".
* @param[in] replicates (optional) Number of K-Means replicates, which are generated. Best is returned.
* @param[in] emptyact (optional) What happens if a cluster wents empty: "error" (default), "drop", "singleton".
* @param[in] online (optional) If centroids should be updated during iterations: true (default), false.
* @param[in] maxit (optional) maximal number of iterations per replicate; 100 by default.
*/
explicit KMeans(std::string distance = std::string{"sqeuclidean"} ,
std::string start = std::string{"sample"},
qint32 replicates = 1,
std::string emptyact = std::string{"error"},
bool online = true,
qint32 maxit = 100);
// //=========================================================================================================
// /**
// * Constructs a KMeans algorithm object.
// *
// * @param[in] distance (optional) K-Means distance measure: "sqeuclidean" (default), "cityblock" , "cosine", "correlation", "hamming".
// * @param[in] start (optional) Cluster initialization: "sample" (default), "uniform", "cluster".
// * @param[in] replicates (optional) Number of K-Means replicates, which are generated. Best is returned.
// * @param[in] emptyact (optional) What happens if a cluster wents empty: "error" (default), "drop", "singleton".
// * @param[in] online (optional) If centroids should be updated during iterations: true (default), false.
// * @param[in] maxit (optional) maximal number of iterations per replicate; 100 by default.
// */
// explicit KMeans(std::string distance = std::string{"sqeuclidean"} ,
// std::string start = std::string{"sample"},
// qint32 replicates = 1,
// std::string emptyact = std::string{"error"},
// bool online = true,
// qint32 maxit = 100);

//=========================================================================================================
/**
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