/** Constant or linearly increasing/decreasing yValues */
@Test
public void linearDataTest() {
final double[] xValues = new double[] {1., 2., 3., 4., 5., 6., 7., 8.};
final double[][] yValues =
new double[][] {
{1., 3., 5., 7., 9., 11., 13., 15.},
{1., 1., 1., 1., 1., 1., 1., 1.},
{1., -1., -3., -5., -7., -9., -11., -13.}
};
final int nData = xValues.length;
final int nDim = yValues.length;
for (int k = 0; k < nDim; ++k) {
double[] yValuesUp = Arrays.copyOf(yValues[k], nData);
double[] yValuesDw = Arrays.copyOf(yValues[k], nData);
final double[] xKeys = new double[10 * nData];
final double xMin = xValues[0];
final double xMax = xValues[nData - 1];
for (int i = 0; i < 10 * nData; ++i) {
xKeys[i] = xMin + (xMax - xMin) / (10 * nData - 1) * i;
}
Interpolator1DDataBundle dataBund =
INTERP1D.getDataBundleFromSortedArrays(xValues, yValues[k]);
for (int j = 0; j < nData; ++j) {
yValuesUp[j] = yValues[k][j] * (1. + EPS);
yValuesDw[j] = yValues[k][j] * (1. - EPS);
Interpolator1DDataBundle dataBundUp = INTERP1D.getDataBundle(xValues, yValuesUp);
Interpolator1DDataBundle dataBundDw = INTERP1D.getDataBundle(xValues, yValuesDw);
for (int i = 0; i < 10 * nData; ++i) {
double res0 =
0.5
* (INTERP1D.interpolate(dataBundUp, xKeys[i])
- INTERP1D.interpolate(dataBundDw, xKeys[i]))
/ EPS
/ yValues[k][j];
assertEquals(
res0,
INTERP1D.getNodeSensitivitiesForValue(dataBund, xKeys[i])[j],
Math.max(Math.abs(yValues[k][j]) * EPS, EPS));
}
yValuesUp[j] = yValues[k][j];
yValuesDw[j] = yValues[k][j];
}
}
}
@Test
public void badConditionedDataTest() {
final double[] xValues = new double[] {1., 2., 3.5, 5.5, 8., 11., 13., 14., 16., 17.};
final double[][] yValues =
new double[][] {
{
6.706599802399542E-11,
6.932869815957718E-11,
2.87869332927719E-11,
5.363437234730385E-11,
7.149182250540928E-11,
2.1005233282848234E-11,
8.692845461548654E-11,
7.808410446575907E-11,
3.1131590776828966E-11,
4.950537896543594E-12
},
{
-5.308664795777495E-11,
-5.542422564946849E-11,
-4.5930585175814465E-11,
-2.5553806762015985E-11,
-9.561076343552027E-11,
-8.126383784798095E-11,
-9.310456023675433E-11,
-8.619479603195128E-11,
-8.402362931611621E-11,
-3.833506843218892E-11
},
{
1.9906779848802714E-11,
6.441367027972245E-12,
-2.3752572108384883E-12,
-3.149892625189229E-11,
4.791854240887406E-12,
8.24613071357958E-12,
-1.1943895254480108E-11,
-1.975674153567708E-12,
4.3920535237286795E-11,
4.575947365163211E-11
}
};
final int nData = xValues.length;
final int nDim = yValues.length;
for (int k = 0; k < nDim; ++k) {
double[] yValuesUp = Arrays.copyOf(yValues[k], nData);
double[] yValuesDw = Arrays.copyOf(yValues[k], nData);
final double[] xKeys = new double[10 * nData];
final double xMin = xValues[0];
final double xMax = xValues[nData - 1];
for (int i = 0; i < 10 * nData; ++i) {
xKeys[i] = xMin + (xMax - xMin) / (10 * nData - 1) * i;
}
Interpolator1DDataBundle dataBund =
INTERP1D.getDataBundleFromSortedArrays(xValues, yValues[k]);
for (int j = 0; j < nData; ++j) {
yValuesUp[j] = yValues[k][j] * (1. + EPS);
yValuesDw[j] = yValues[k][j] * (1. - EPS);
Interpolator1DDataBundle dataBundUp = INTERP1D.getDataBundle(xValues, yValuesUp);
Interpolator1DDataBundle dataBundDw = INTERP1D.getDataBundle(xValues, yValuesDw);
for (int i = 0; i < 10 * nData; ++i) {
double res0 =
0.5
* (INTERP1D.interpolate(dataBundUp, xKeys[i])
- INTERP1D.interpolate(dataBundDw, xKeys[i]))
/ EPS
/ yValues[k][j];
assertEquals(
res0,
INTERP1D.getNodeSensitivitiesForValue(dataBund, xKeys[i])[j],
Math.max(Math.abs(yValues[k][j]) * 1.e-4, 1.e-4));
}
yValuesUp[j] = yValues[k][j];
yValuesDw[j] = yValues[k][j];
}
}
}
