CSIM: Preprocessor Class Reference

Preprocessor Class Reference

#include <preprocessor.h>

Inheritance diagram for Preprocessor:

Advancable csimClass DiscretizationPreprocessor LinearPreprocessor Mean_Std_Preprocessor PCAPreprocessor List of all members.

Detailed Description

Base class of all preprocessors that can be applied to the filtered input of a readout. Examples are normalizers, PCA and linear transformations.

Public Member Functions

Protected Attributes

  • map< string, double * > params
    A map storing pointers to the parameters.
  • int nInputRows
    Number of rows for input vectors.
  • double dInputRows
    Dummy for parameter setting.
  • int nOutputRows
    Number of rows for output vectors.
  • double dOutputRows
    Dummy for parameter setting.

Constructor & Destructor Documentation

Preprocessor::Preprocessor unsigned int  in_rows,
unsigned int  out_rows
 

Constructs a new preprocessor object.

Parameters:
in_rows Number of rows in each input vector.
out_rows Number of rows in each output vector.


Member Function Documentation

virtual double* Preprocessor::exportRepresentation int *  rep_length  )  [pure virtual]
 

Exports the representation of this preprocessor for use in external objects.

Parameters:
rep_length Length of the representation vector.
Returns:
A list of parameters that represent the preprocessor.
Warning:
Do not forget to free the memory reserved for the representation!

Implemented in DiscretizationPreprocessor, LinearPreprocessor, Mean_Std_Preprocessor, and PCAPreprocessor.

virtual string Preprocessor::getFormatDescription  )  [pure virtual]
 

Returns a textual description of the representation format for import/export - Representation.

Implemented in DiscretizationPreprocessor, LinearPreprocessor, Mean_Std_Preprocessor, and PCAPreprocessor.

int Preprocessor::getInputRows  )  [inline]
 

Returns the number of input rows.

int Preprocessor::getOutputRows  )  [inline]
 

Returns the number of output rows.

double Preprocessor::getParameter string  name  )  [virtual]
 

Returns the current value of a parameter.

Parameters:
name Name of the parameter.
Returns:
The value of the parameter.

virtual int Preprocessor::importRepresentation const double *  rep,
int  rep_length
[pure virtual]
 

Imports the data from an externally (e.g. Matlab) trained preprocessor.

Parameters:
rep Representation of the preprocessor as a double vector.
rep_length Length of the representation vector.
Returns:
-1 if an error occured, 1 for success.

Implemented in DiscretizationPreprocessor, LinearPreprocessor, Mean_Std_Preprocessor, and PCAPreprocessor.

virtual int Preprocessor::process const double *  S,
double *  X
[pure virtual]
 

Preprocess a state representation.

Parameters:
S State of the liquid (= filtered response of the neural microcircuit).
X Target vector where to save the results.
Returns:
-1 if an error occured, 1 for success.

Implemented in DiscretizationPreprocessor, LinearPreprocessor, Mean_Std_Preprocessor, and PCAPreprocessor.

virtual void Preprocessor::reset  )  [pure virtual]
 

Resets the information stored within the preprocessor.

Implements Advancable.

Implemented in DiscretizationPreprocessor, LinearPreprocessor, Mean_Std_Preprocessor, and PCAPreprocessor.

void Preprocessor::setParameter string  name,
double  value
[virtual]
 

Sets a parameter of the preprocessor function.

Parameters:
name Name of the parameter.
value Value to set for the parameter.

int Preprocessor::updateInternal  )  [virtual]
 

This function is called after parameters are updated.

Reimplemented from csimClass.

list< string > Preprocessor::validParameters void   )  [virtual]
 

Returns the names of the valid parameters.

Returns:
A string list indicating the valid parameter names.


 
(C) 2003, Thomas Natschläger last modified 07/10/2006