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API.h
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#ifndef EDM_API_H
#define EDM_API_H
#include "Common.h" // Non DataFrame return struct definitions
#include "Parameter.h"
#include "Simplex.h"
#include "SMap.h"
#include "CCM.h"
#include "Multiview.h"
//-------------------------------------------------------------
// API function declarations.
//
// API functions generally have two call-signatures.
// The first takes a (path, file name) pair specifying the data
// file image on disk to be loaded and converted to a data frame.
// The second replaces these two arguments with a DataFrame object.
//
// NOTE: These are the first declarations seen by the compiler
// for the API and provide default argument values
//-------------------------------------------------------------
DataFrame< double > Embed( std::string path = "",
std::string dataFile = "",
int E = 0,
int tau = 0,
std::string columns = "",
bool verbose = false );
DataFrame< double > Embed( DataFrame< double > & dataFrame,
int E = 0,
int tau = 0,
std::string columns = "",
bool verbose = false );
DataFrame< double > MakeBlock( DataFrame< double > & dataFrame,
int E,
int tau,
std::vector<std::string> columns,
bool deletePartial = false );
SimplexValues Simplex( std::string pathIn = "./data/",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
bool embedded = false,
bool const_predict = false,
bool verbose = true,
std::vector<bool> validLib = std::vector<bool>(),
int generateSteps = 0,
bool generateLibrary = false,
bool parameterList = false );
SimplexValues Simplex( DataFrame< double > & dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
bool embedded = false,
bool const_predict = false,
bool verbose = true,
std::vector<bool> validLib = std::vector<bool>(),
int generateSteps = 0,
bool generateLibrary = false,
bool parameterList = false );
// SMap is a special case since it can be called with a function pointer
// to the SVD solver. This is done so that interfaces such as pybind11
// can provide their own object for the solver.
// 1) Data path/file with default SVD (LAPACK) assigned in Smap.cc 2)
SMapValues SMap( std::string pathIn = "./data/",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
double theta = 0,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
std::string smapCoefFile = "",
std::string smapSVFile = "",
bool embedded = false,
bool const_predict = false,
bool verbose = true,
std::vector<bool> validLib = std::vector<bool>(),
bool ignoreNan = true,
int generateSteps = 0,
bool generateLibrary = false,
bool parameterList = false );
// 2) DataFrame with default SVD (LAPACK) assigned in Smap.cc 2)
SMapValues SMap( DataFrame< double > &dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
double theta = 0,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
std::string smapFile = "",
std::string smapSVFile = "",
bool embedded = false,
bool const_predict = false,
bool verbose = true,
std::vector<bool> validLib = std::vector<bool>(),
bool ignoreNan = true,
int generateSteps = 0,
bool generateLibrary = false,
bool parameterList = false );
// 3) Data path/file with external solver object, init to default SVD
SMapValues SMap( std::string pathIn = "./data/",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
double theta = 0,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
std::string smapFile = "",
std::string smapSVFile = "",
SVDValues (*solver) (DataFrame < double >,
std::valarray < double >) = & SVD,
bool embedded = false,
bool const_predict = false,
bool verbose = true,
std::vector<bool> validLib = std::vector<bool>(),
bool ignoreNan = true,
int generateSteps = 0,
bool generateLibrary = false,
bool parameterList = false );
// 4) DataFrame with external solver object, init to default SVD
SMapValues SMap( DataFrame< double > &dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
double theta = 0,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
std::string smapFile = "",
std::string smapSVFile = "",
SVDValues (*solver) (DataFrame < double >,
std::valarray < double >) = & SVD,
bool embedded = false,
bool const_predict = false,
bool verbose = true,
std::vector<bool> validLib = std::vector<bool>(),
bool ignoreNan = true,
int generateSteps = 0,
bool generateLibrary = false,
bool parameterList = false );
CCMValues CCM( std::string pathIn = "./data/",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
int E = 0,
int Tp = 0,
int knn = 0,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
std::string libSizes_str = "",
int sample = 0,
bool random = true,
bool replacement = false,
unsigned seed = 0, // seed=0: use RNG
bool embedded = false,
bool includeData = false,
bool parameterList = false,
bool verbose = true );
CCMValues CCM( DataFrame< double > & dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
int E = 0,
int Tp = 0,
int knn = 0,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
std::string libSizes_str = "",
int sample = 0,
bool random = true,
bool replacement = false,
unsigned seed = 0, // seed=0: use RNG
bool embedded = false,
bool includeData = false,
bool parameterList = false,
bool verbose = true );
MultiviewValues Multiview( std::string pathIn = "./",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int D = 0,
int E = 1,
int Tp = 1,
int knn = 0,
int tau = -1,
std::string columns = "",
std::string target = "",
int multiview = 0,
int exclusionRadius = 0,
bool trainLib = true,
bool excludeTarget = false,
bool parameterList = false,
bool verbose = false,
unsigned nThreads = 4 );
MultiviewValues Multiview( DataFrame< double > & dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int D = 0,
int E = 1,
int Tp = 1,
int knn = 0,
int tau = -1,
std::string columns = "",
std::string target = "",
int multiview = 0,
int exclusionRadius = 0,
bool trainLib = true,
bool excludeTarget = false,
bool parameterList = false,
bool verbose = false,
unsigned nThreads = 4 );
DataFrame< double > EmbedDimension( std::string pathIn = "./data/",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int maxE = 10,
int Tp = 1,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
bool embedded = false,
bool verbose = true,
std::vector<bool> validLib =
std::vector<bool>(),
unsigned nThreads = 4 );
DataFrame< double > EmbedDimension( DataFrame< double > & dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int maxE = 10,
int Tp = 1,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
bool embedded = false,
bool verbose = true,
std::vector<bool> validLib =
std::vector<bool>(),
unsigned nThreads = 4 );
DataFrame< double > PredictInterval( std::string pathIn = "./data/",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int maxTp = 10,
int E = 0,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
bool embedded = false,
bool verbose = true,
std::vector<bool> validLib =
std::vector<bool>(),
unsigned nThreads = 4 );
DataFrame< double > PredictInterval( DataFrame< double > & dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
int maxTp = 10,
int E = 0,
int tau = -1,
int exclusionRadius = 0,
std::string colNames = "",
std::string target = "",
bool embedded = false,
bool verbose = true,
std::vector<bool> validLib =
std::vector<bool>(),
unsigned nThreads = 4 );
DataFrame< double > PredictNonlinear( std::string pathIn = "./data/",
std::string dataFile = "",
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
std::string theta = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
bool embedded = false,
bool verbose = true,
std::vector<bool> validLib =
std::vector<bool>(),
bool ignoreNan = true,
unsigned nThreads = 4 );
DataFrame< double > PredictNonlinear( DataFrame< double > & dataFrameIn,
std::string pathOut = "./",
std::string predictFile = "",
std::string lib = "",
std::string pred = "",
std::string theta = "",
int E = 0,
int Tp = 1,
int knn = 0,
int tau = -1,
int exclusionRadius = 0,
std::string columns = "",
std::string target = "",
bool embedded = false,
bool verbose = true,
std::vector<bool> validLib =
std::vector<bool>(),
bool ignoreNan = true,
unsigned nThreads = 4 );
#endif