/**
* Retrieves the current LRE parameters from the Profile
*
* @param profile
* @return
*/
private LreParameters getLreParameters() {
// Setup the initial parameters
LreParameters lreDerivedParam = new LreParameters();
// Testing indicates that if Fb=0 the NR fails
if (profile.getNrFb() == 0) {
lreDerivedParam.setFb(profile.getFb()); // This Fb is derived from the average of cycles 4-9
} else {
lreDerivedParam.setFb(profile.getNrFb());
}
lreDerivedParam.setEmax(profile.getEmax()); // Current LRE-derived Emax
lreDerivedParam.setFmax(profile.getFmax()); // Current LRE-derived Fmax
lreDerivedParam.setFo(profile.getAvFo()); // Current LRE-derived average Fo
lreDerivedParam.setFbSlope(profile.getNrFbSlope()); // Current Fb slope
return lreDerivedParam;
}
/**
* This conducts both nonlinear regression-derived Fb subtraction and baseline slope correction.
*
* @param profile
*/
private void conductBaselineCorrection() {
// Start with correcting for the NR-derived Fb slope
double[] rawFcReadings = profile.getRawFcReadings();
double[] processedFcDataset = new double[rawFcReadings.length]; // The new optimized Fc dataset
// This assumes that nonlinear regression has been conducted AND it was successfully completed
double nrFb = profile.getNrFb(); // The regression derived Fb
double nrFbSlope = profile.getNrFbSlope(); // The regression-derived Fb slope
for (int i = 0; i < processedFcDataset.length; i++) {
processedFcDataset[i] = rawFcReadings[i] - nrFb - (nrFbSlope * (i + 1));
}
profile.setFcReadings(processedFcDataset);
}
