private double NormalizedError(
PatternFeature feature, double modelValue, double minError, double maxError) {
if (feature.isRange()) {
return StatUtil.calculate0to1NormalizedError(
feature.getValueMin(), feature.getValueMax(), modelValue, minError, maxError);
} else {
return StatUtil.calculate0to1NormalizedError(
feature.getValue(), modelValue, minError, maxError);
}
}
public double sfaError() {
int nPieceWiseParmsExp = expSpikePatternData.getSpikePatternClass().getnPieceWiseParms();
int nPieceWiseParmsModel = patternClassifier.getSpikePatternClass().getnPieceWiseParms();
double possibleWeightForFutureNEAR = nPieceWiseParmsExp - nPieceWiseParmsModel; // coarse!!
double error = 0;
double minError = 0;
double maxMerror = 1;
double maxCerror = 2;
double maxNsfaError = expSpikePatternData.getCurrentDuration() * 0.3;
SolverResultsStat modelStats =
patternClassifier.getSolverResultsStats()[nPieceWiseParmsExp - 1];
int modelNsfaISIs1 = modelStats.getBreakPoint();
int modelNsfaISIs2 = modelSpikePattern.getISIs().length - modelNsfaISIs1;
double[] model =
new double[] {
modelStats.getM1(),
modelStats.getM2(),
modelStats.getC1(),
modelStats.getC2(),
modelNsfaISIs1,
modelNsfaISIs2
};
double[] exp =
new double[] {
expSpikePatternData.getSfaLinearM1().getValue(),
expSpikePatternData.getSfaLinearM2().getValue(),
expSpikePatternData.getSfaLinearb1().getValue(),
expSpikePatternData.getSfaLinearb2().getValue(),
expSpikePatternData.getNSfaISIs1().getValue(),
expSpikePatternData.getNSfaISIs2().getValue(),
};
for (int i = 0; i < 6; i++) {
if (i < 2) { // slopes
error += StatUtil.calculate0to1NormalizedError(exp[i], model[i], minError, maxMerror);
} else {
if (i < 4) { // intercepts
error += StatUtil.calculate0to1NormalizedError(exp[i], model[i], minError, maxCerror);
} else {
error += StatUtil.calculate0to1NormalizedError(exp[i], model[i], minError, maxNsfaError);
}
}
}
error =
patternClassifier.getDynamicFeatWeightMatrix().get(PatternFeatureID.n_sfa_isis2) * error;
if (display) {
displayRoutineForSFA(null, model, error);
}
return error;
}
private double NormalizedErrorObsNormed(PatternFeature feature, double modelValue) {
/*
* the w here is manual weight assigned in JSON. only for special cases!! like 3-000 to get D.ASP.
* shouldn't be confused with dynamic W calculated in spikepatternclassifier
* Typically, w is 0 in JSON, so that this manual weight is ignored!
*/
double w = feature.getWeight();
if (GeneralUtils.isCloseEnough(w, 0, 0.001)) {
w = 1;
}
if (feature.isRange()) {
return w
* StatUtil.calculateObsNormalizedError(
feature.getValueMin(), feature.getValueMax(), modelValue);
} else {
return w * StatUtil.calculateObsNormalizedError(feature.getValue(), modelValue);
}
}
private float spikesBelowVrestError(float vR) {
double avgBelowVrestOffset = modelSpikePattern.calculateAvgBelowVrest(vR);
return (float) StatUtil.calculateObsNormalizedError(0, avgBelowVrestOffset);
}
/*
* other non-feature errors; like avoid bursting...
*/
private float nonBurstBelowVminError(float vMin) {
double avgBelowVminOffset = modelSpikePattern.calculateAvgBelowVminAfterLastSpike(vMin, 200);
return (float) StatUtil.calculateObsNormalizedError(0, avgBelowVminOffset);
}
private double singleBurstError(
int burstIdx, HashMap<BurstFeatureID, Double> expSingleBurstFeatures) {
if (burstIdx >= modelSpikePattern.getBurstPattern().getNBursts()) {
return 1;
}
double errorBW = 0;
double errorIBI = 0;
double errorNspikes = 0;
// 2. BW error
double bw = -1;
if (expSingleBurstFeatures.containsKey(BurstFeatureID.b_w)) {
bw = expSingleBurstFeatures.get(BurstFeatureID.b_w);
double modelBw = modelSpikePattern.getBurstPattern().getBW(burstIdx);
errorBW = StatUtil.calculateObsNormalizedError(bw, modelBw);
}
// 3. IBI error
double pbi = -1;
if (expSingleBurstFeatures.containsKey(BurstFeatureID.pbi)) {
pbi = expSingleBurstFeatures.get(BurstFeatureID.pbi);
double modelPbi = modelSpikePattern.getBurstPattern().getIBI(burstIdx);
errorIBI = StatUtil.calculateObsNormalizedError(pbi, modelPbi);
}
// 4. N spikes error
double nspikes = expSingleBurstFeatures.get(BurstFeatureID.nspikes);
errorNspikes =
StatUtil.calculateObsNormalizedError(
nspikes, modelSpikePattern.getBurstPattern().getNSpikes(burstIdx));
/*
* display
*/
if (display) {
System.out.print("\t");
if (expSingleBurstFeatures.containsKey(BurstFeatureID.b_w)) {
String displayString = "\tb_w\t" + GeneralUtils.formatTwoDecimal(bw);
displayString +=
"\t"
+ GeneralUtils.formatTwoDecimal(
modelSpikePattern.getBurstPattern().getBW(burstIdx));
displayString += "\t" + GeneralUtils.formatThreeDecimal(errorBW) + "\t/";
System.out.print(displayString);
}
if (expSingleBurstFeatures.containsKey(BurstFeatureID.pbi)) {
String displayString = "\tibi\t" + GeneralUtils.formatTwoDecimal(pbi);
displayString +=
"\t"
+ GeneralUtils.formatTwoDecimal(
modelSpikePattern.getBurstPattern().getIBI(burstIdx));
displayString += "\t" + GeneralUtils.formatThreeDecimal(errorIBI) + "\t/";
System.out.print(displayString);
}
String displayString = "\tnspikes\t" + GeneralUtils.formatTwoDecimal(nspikes);
displayString +=
"\t"
+ GeneralUtils.formatTwoDecimal(
modelSpikePattern.getBurstPattern().getNSpikes(burstIdx));
displayString += "\t" + GeneralUtils.formatThreeDecimal(errorNspikes) + "\t/";
System.out.print(displayString + "\n");
}
return ((expSpikePatternData.getBurstFeatures().getFeatureWeight(BurstFeatureID.b_w) * errorBW)
+ (expSpikePatternData.getBurstFeatures().getFeatureWeight(BurstFeatureID.pbi) * errorIBI)
+ (expSpikePatternData.getBurstFeatures().getFeatureWeight(BurstFeatureID.nspikes)
* errorNspikes));
}