public void train(List<Sample> samples) {
BLEBeacon.setBLEBeaconIdsToSamples(bleBeacons, samples);
List<List<Sample>> samplesList = Sample.samplesToConsecutiveSamplesList(samples);
if (doHyperParameterOptimize) {
doHyperParameterOptimize = false;
trainWithHyperParameters(samplesList);
}
List<Sample> samplesAvaragedTrain = Sample.meanTrimList(samplesList, minRssi);
this.trainByAveragedSamples(samplesAvaragedTrain);
}
protected void trainByAveragedSamples(List<Sample> samples) {
int nBeacons = bleBeacons.size();
BLEBeacon.setBLEBeaconIdsToSamples(bleBeacons, samples);
setupGPLDPL();
this.samples = samples;
double[][] X = ModelAdaptUtils.samplesToLocationsMat(samples);
double[][] Y = ModelAdaptUtils.samplesToBeaconsListMat(samples, minRssi, nBeacons);
double[][] bLocs = ModelAdaptUtils.BLEBeaconsToMat(bleBeacons, nBeacons);
gpLDPL.setSourceLocs(bLocs);
int[] actBecList = new int[nBeacons];
for (int i = 0; i < nBeacons; i++) actBecList[i] = i;
gpLDPL.setActiveBeaconList(actBecList);
gpLDPL.fit(X, Y);
}