31 #ifndef GRT_PRE_PROCESSING_HEADER
32 #define GRT_PRE_PROCESSING_HEADER
65 bool copyBaseVariables(
const PreProcessing *preProcessingModule);
93 std::string getPreProcessingType()
const;
114 bool getInitialized()
const;
132 static PreProcessing* createInstanceFromString(std::string
const &preProcessingType);
153 bool savePreProcessingSettingsToFile(std::fstream &file)
const;
160 bool loadPreProcessingSettingsFromFile(std::fstream &file);
162 std::string preProcessingType;
166 static StringPreProcessingMap *getMap() {
167 if( !stringPreProcessingMap ){ stringPreProcessingMap =
new StringPreProcessingMap; }
168 return stringPreProcessingMap;
172 static StringPreProcessingMap *stringPreProcessingMap;
173 static UINT numPreProcessingInstances;
177 template<
typename T >
PreProcessing *newPreProcessingModuleInstance() {
return new T; }
179 template<
typename T >
183 getMap()->insert( std::pair< std::string,
PreProcessing*(*)() >(newPreProcessingModuleName, &newPreProcessingModuleInstance< T > ) );
189 #endif // GRT_POST_PROCESSING_HEADER
virtual bool deepCopyFrom(const PreProcessing *rhs)
UINT getNumOutputDimensions() const
This is the main base class that all GRT machine learning algorithms should inherit from...
virtual bool process(const VectorFloat &inputVector)
UINT getNumInputDimensions() const
std::map< std::string, PreProcessing *(*)() > StringPreProcessingMap