435             for(int sampleIndex = 0; sampleIndex < nsamples; sampleIndex++)  in clusterTrainSamples()  local
437                 if(labels.at<int>(sampleIndex) == clusterIndex)  in clusterTrainSamples()
439                     const Mat sample = trainSamples.row(sampleIndex);  in clusterTrainSamples()
639         for(int sampleIndex = 0; sampleIndex < trainSamples.rows; sampleIndex++)  in eStep()  local
641             Mat sampleProbs = trainProbs.row(sampleIndex);  in eStep()
642             Vec2d res = computeProbabilities(trainSamples.row(sampleIndex), &sampleProbs, CV_64F);  in eStep()
643             trainLogLikelihoods.at<double>(sampleIndex) = res[0];  in eStep()
644             trainLabels.at<int>(sampleIndex) = static_cast<int>(res[1]);  in eStep()
676             for(int sampleIndex = 0; sampleIndex < trainSamples.rows; sampleIndex++)  in mStep()  local
677 …   clusterMean += trainProbs.at<double>(sampleIndex, clusterIndex) * trainSamples.row(sampleIndex);  in mStep()
706             for(int sampleIndex = 0; sampleIndex < trainSamples.rows; sampleIndex++)  in mStep()  local
708                 centeredSample = trainSamples.row(sampleIndex) - means.row(clusterIndex);  in mStep()
711 …clusterCov += trainProbs.at<double>(sampleIndex, clusterIndex) * centeredSample.t() * centeredSamp…  in mStep()
714                     double p = trainProbs.at<double>(sampleIndex, clusterIndex);  in mStep()