Correlation Library  1.0
Public Member Functions
CCrossCorrelationBB Class Reference

A class that computes the cross-correlation for two vectors of time stamps (Binary - Binary). More...

#include <CrossCorrelation-BB.h>

List of all members.

Public Member Functions

 CCrossCorrelationBB (int piCorrelationWindow, int piTrialLength, int &piIsError)
 Constructor.
 ~CCrossCorrelationBB ()
 Destructor.
void ComputeCrossCorrelation (int *piaTimeStampsA, int piNrTimeStampsInA, int *piaTimeStampsB, int piNrTimeStampsInB, int pbNormalizeCorrelogram)
 Compute the cross-correlation of two vectors of time stamps.
void ComputeWindowedCrossCorrelationPerTrial (int *piaTimeStampsA, int piNrTimeStampsInA, int *piaTimeStampsB, int piNrTimeStampsInB, int piFromOffsetInTrial, int piToOffsetInTrial, int pbNormalizeCorrelogram)
 Compute the cross-correlation of two vectors of time stamps, on a partial window of the trial. ONLY ACCEPTS ONE TRIAL!!!
float * GetCrossCorrelogram ()
 Returns the buffer with the computed cross-correlogram; returns NULL if there was an error; please check the buffer for NULL before using it!!
int ModifyCorrelationWindow (int piNewCorrelationWindow)
 Set the size of the correlation window; the parameter specifies the correlation window; for example for a window of -100..+100 pass 100 as a parameter.
int ModifyTrialLength (int piNewTrialLength)
 Set the length of the trial in original sampling units.
int ModifyAllParameters (int piNewCorrelationWindow, int piNewTrialLength)
 Sets all parameters at once.
int GetCorrelationWindow ()
 Get the size of the correlation window.
int GetTrialLength ()
 Get the trial length in original sampling units.

Detailed Description

A class that computes the cross-correlation for two vectors of time stamps (Binary - Binary).

Cross-correlation is computed in the classical way by counting.

Constructor & Destructor Documentation

CCrossCorrelationBB::CCrossCorrelationBB ( int  piCorrelationWindow,
int  piTrialLength,
int &  piIsError 
)

Constructor.

Parameters:
piCorrelationWindow- The size of the cross-correlation window (eg. 80 for a cross-correlation with lags of -80..+80); use the same units as the sampling of your time stamps
piTrialLength- The size of the trial in sampling units of the time stamps
piIsError- A return parameter, set to 0 on success. It is set to -1 by the constructor if there is a mismatch of window sizes and the GetCrossCorrelogram() function will return NULL;
CCrossCorrelationBB::~CCrossCorrelationBB ( )

Destructor.

Member Function Documentation

void CCrossCorrelationBB::ComputeCrossCorrelation ( int *  piaTimeStampsA,
int  piNrTimeStampsInA,
int *  piaTimeStampsB,
int  piNrTimeStampsInB,
int  pbNormalizeCorrelogram 
)

Compute the cross-correlation of two vectors of time stamps.

Parameters:
piaTimeStampsA- The vector holding the time stamps of the first binary variable
piNrTimeStampsInA- Number of time stamps in the first vector
piaTimeStampsB- The vector holding the time stamps of the second binary variable
piNrTimeStampsInB- Number of time stamps in the second vector
pbNormalizeCorrelogram- Set to 1 to normalize the correlogram; normalization is made by dividing the correlogram to the number of time stamps in the first buffer (rate-normalized correlogram)
void CCrossCorrelationBB::ComputeWindowedCrossCorrelationPerTrial ( int *  piaTimeStampsA,
int  piNrTimeStampsInA,
int *  piaTimeStampsB,
int  piNrTimeStampsInB,
int  piFromOffsetInTrial,
int  piToOffsetInTrial,
int  pbNormalizeCorrelogram 
)

Compute the cross-correlation of two vectors of time stamps, on a partial window of the trial. ONLY ACCEPTS ONE TRIAL!!!

Parameters:
piaTimeStampsA- The vector holding the time stamps of the first binary variable
piNrTimeStampsInA- Number of time stamps in the first vector
piaTimeStampsB- The vector holding the time stamps of the second binary variable
piNrTimeStampsInB- Number of time stamps in the second vector
piFromOffsetInTrial- The start offset in the trial where the desired window starts (time stamp)
piToOffsetInTrial- The end offset in the trial where the desired window stops (time stamp)
pbNormalizeCorrelogram- Set to 1 to normalize the correlogram
int CCrossCorrelationBB::GetCorrelationWindow ( )

Get the size of the correlation window.

Returns:
The size of the correlation window
float * CCrossCorrelationBB::GetCrossCorrelogram ( )

Returns the buffer with the computed cross-correlogram; returns NULL if there was an error; please check the buffer for NULL before using it!!

The size of the cross correlogram buffer is (2*iCorrelationWindow+1), and element with lag 0 is at position iCorrelationWindow.

Returns:
Returns a pointer to the internal cross-correlation buffer. Do not write into the buffer!
The buffer is filled with NAN (Not A Number) = -100000000.0 if one of the input buffers was empty and thus the correlation was not defined; please check in your code for this!!!!
int CCrossCorrelationBB::GetTrialLength ( )

Get the trial length in original sampling units.

Returns:
The length of the trial in sampling units
int CCrossCorrelationBB::ModifyAllParameters ( int  piNewCorrelationWindow,
int  piNewTrialLength 
)

Sets all parameters at once.

Parameters:
piNewCorrelationWindow- The new correlation window
piNewTrialLength- The new length of the trial
Returns:
Returns 0 on success, -1 if the new correlation window is too small; -2 if the trial length is smaller than the correlation window
int CCrossCorrelationBB::ModifyCorrelationWindow ( int  piNewCorrelationWindow)

Set the size of the correlation window; the parameter specifies the correlation window; for example for a window of -100..+100 pass 100 as a parameter.

Parameters:
piNewCorrelationWindow- The new correlation window
Returns:
Returns 0 on success, -1 if the window is too small; -2 if the window is larger than the length of the trial;
int CCrossCorrelationBB::ModifyTrialLength ( int  piNewTrialLength)

Set the length of the trial in original sampling units.

Parameters:
piNewTrialLength- The new length of the trial
Returns:
Returns 0 on success and -1 if the trial length is smaller than the correlation window
The documentation for this class was generated from the following files: