@Override
public void extractFeatures(List regions) throws FeatureExtractorException {
for (Region r : (List<Region>) regions) {
if (r.hasAttribute(f1) && r.hasAttribute(f2)) {
Contour c1, c2;
try {
c1 = ContourUtils.getSubContour((Contour) r.getAttribute(f1), r.getStart(), r.getEnd());
c2 = ContourUtils.getSubContour((Contour) r.getAttribute(f2), r.getStart(), r.getEnd());
} catch (AuToBIException e) {
throw new FeatureExtractorException(e.getMessage());
}
r.setAttribute("rmse[" + f1 + "," + f2 + "]", contourRMSE(c1, c2));
r.setAttribute("meanError[" + f1 + "," + f2 + "]", contourError(c1, c2));
}
}
}
@Override
public void extractFeatures(List regions) throws FeatureExtractorException {
for (Region r : (List<Region>) regions) {
if (r.hasAttribute(feature)) {
Contour super_c = (Contour) r.getAttribute(feature);
Contour c;
try {
c = ContourUtils.getSubContour(super_c, r.getStart(), r.getEnd());
} catch (AuToBIException e) {
throw new FeatureExtractorException(e.getMessage());
}
CurveShape falling = smooth(-1, true, c);
CurveShape rising = smooth(c.size(), true, c);
CurveShape best_peak = null;
double min_peak_rmse = Double.MAX_VALUE;
// Sample the curve at at most 20 points to calculate peak and valley likelihoods.
// On long regions calculating at every point gets *very* slow.
int step = Math.max(1, c.size() / 20);
for (int i = 1; i < c.size() - 1; i += step) {
CurveShape peak = smooth(i, true, c);
if (peak.rmse < min_peak_rmse) {
best_peak = peak;
min_peak_rmse = peak.rmse;
}
}
CurveShape best_valley = null;
double min_valley_rmse = Double.MAX_VALUE;
for (int i = 1; i < c.size() - 1; i += step) {
CurveShape valley = smooth(i, false, c);
if (valley.rmse < min_valley_rmse) {
best_valley = valley;
min_valley_rmse = valley.rmse;
}
}
r.setAttribute("risingCurve[" + feature + "]", rising);
r.setAttribute("fallingCurve[" + feature + "]", falling);
r.setAttribute("peakCurve[" + feature + "]", best_peak);
r.setAttribute("valleyCurve[" + feature + "]", best_valley);
}
}
}
