/** * Z-Normalize routine. * * @param series the input timeseries. * @param normalizationThreshold the zNormalization threshold value. * @return Z-normalized time-series. */ public double[] znorm(double[] series, double normalizationThreshold) { double[] res = new double[series.length]; double sd = stDev(series); if (sd < normalizationThreshold) { // return series.clone(); // return array of zeros return res; } double mean = mean(series); for (int i = 0; i < res.length; i++) { res[i] = (series[i] - mean) / sd; } return res; }
/** * Z-Normalize routine. * * @param series the input timeseries. * @param normalizationThreshold the zNormalization threshold value. * @return Z-normalized time-series. */ public double[] znorm(double[] series, double normalizationThreshold) { double[] res = new double[series.length]; double sd = stDev(series); if (sd < normalizationThreshold) { // return series.clone(); // return array of zeros return res; } double mean = mean(series); for (int i = 0; i < res.length; i++) { res[i] = (series[i] - mean) / sd; } return res; }
if (tsProcessor.stDev(subseries) > normThreshold) { subseries = tsProcessor.znorm(subseries, normThreshold);
if (tsProcessor.stDev(subseries) > normThreshold) { subseries = tsProcessor.znorm(subseries, normThreshold);
double subsequenceDistance = 0.; if (tsProcessor.stDev(subseries) > normThreshold) { subseries = tsProcessor.znorm(subseries, normThreshold);
double subsequenceDistance = 0.; if (tsProcessor.stDev(subseries) > normThreshold) { subseries = tsProcessor.znorm(subseries, normThreshold);