public static IDataset interpolate(IDataset oldx, IDataset oldy, IDataset newx) {
// TODO more sanity checks on inputs
DoubleDataset dx = (DoubleDataset) DatasetUtils.cast(oldx, Dataset.FLOAT64);
DoubleDataset dy = (DoubleDataset) DatasetUtils.cast(oldy, Dataset.FLOAT64);
boolean sorted = true;
double maxtest = oldx.getDouble(0);
for (int i = 1; i < ((Dataset) oldx).count(); i++) {
if (maxtest > oldx.getDouble(i)) {
sorted = false;
break;
}
maxtest = dx.getDouble(i);
}
double[] sortedx = null;
double[] sortedy = null;
if (!sorted) {
IntegerDataset sIdx = getIndiciesOfSorted(dx);
sortedx = new double[dx.getData().length];
sortedy = new double[dy.getData().length];
for (int i = 0; i < sIdx.getSize(); i++) {
sortedx[i] = dx.getDouble(sIdx.get(i));
sortedy[i] = dy.getDouble(sIdx.get(i));
}
} else {
sortedx = dx.getData();
sortedy = dy.getData();
}
SplineInterpolator si = new SplineInterpolator();
PolynomialSplineFunction poly = si.interpolate(sortedx, sortedy);
IDataset newy = newx.clone();
newy.setName(oldy.getName() + "_interpolated");
for (int i = 0; i < ((Dataset) newx).count(); i++) {
newy.set(poly.value(newx.getDouble(i)), i);
}
return newy;
}
public Series fit() {
SplineInterpolator ipo = new SplineInterpolator();
double[] x = new double[this.size()];
double[] y = new double[this.size()];
for (int n = 0; n < size(); ++n) {
x[n] = (double) n;
y[n] = get(n);
}
PolynomialSplineFunction psf = ipo.interpolate(x, y);
Series ret = new Series(iId, iName);
for (int n = 0; n < size(); ++n) ret.add(psf.value(Math.max(.0, n - 0.5)));
return ret;
}
