/**
* Copyright (C) 2013 - present by OpenGamma Inc. and the OpenGamma group of companies
*
* Please see distribution for license.
*/
package com.opengamma.analytics.math.interpolation;
import static org.testng.Assert.assertEquals;
import java.util.Arrays;
import org.testng.annotations.Test;
import com.opengamma.analytics.math.interpolation.data.Interpolator1DDataBundle;
import com.opengamma.util.test.TestGroup;
/**
* Test interpolateWithSensitivity method via PiecewisePolynomialInterpolator1D
*/
@Test(groups = TestGroup.UNIT)
public class NonnegativityPreservingQuinticSplineInterpolator1DTest {
private static final NonnegativityPreservingQuinticSplineInterpolator INTERP_NAT = new NonnegativityPreservingQuinticSplineInterpolator(new NaturalSplineInterpolator());
private static final NonnegativityPreservingQuinticSplineInterpolator1D INTERP1D_NAT = new NonnegativityPreservingQuinticSplineInterpolator1D();
private static final NonnegativityPreservingQuinticSplineInterpolator INTERP_NAK = new NonnegativityPreservingQuinticSplineInterpolator(new CubicSplineInterpolator());
private static final NonnegativityPreservingQuinticSplineInterpolator1D INTERP1D_NAK = new NonnegativityPreservingQuinticSplineInterpolator1D(new CubicSplineInterpolator());
private static final double EPS = 1.e-6;
/**
* Recovery test on polynomial, rational, exponential functions, and node sensitivity test by finite difference method
* Note that interpolations producing a C1 curve is not appropriate in this case. Matching with the finite difference approximation requires smooth second derivative
*/
@Test
public void sampleFunctionTest() {
final int nData = 10;
final double[] xValues = new double[nData];
final double[] yValues1 = new double[nData];
final double[] yValues2 = new double[nData];
final double[] yValues3 = new double[nData];
final double[] yValues1Up = new double[nData];
final double[] yValues2Up = new double[nData];
final double[] yValues3Up = new double[nData];
final double[] yValues1Dw = new double[nData];
final double[] yValues2Dw = new double[nData];
final double[] yValues3Dw = new double[nData];
final double[] xKeys = new double[10 * nData];
for (int i = 0; i < nData; ++i) {
xValues[i] = i + 1;
yValues1[i] = 0.5 * xValues[i] * xValues[i] * xValues[i] - 1.5 * xValues[i] * xValues[i] + xValues[i] - 2.;
yValues2[i] = Math.exp(0.1 * xValues[i] - 6.);
yValues3[i] = (2. * xValues[i] * xValues[i] + xValues[i]) / (xValues[i] * xValues[i] + xValues[i] * xValues[i] * xValues[i] + 5. * xValues[i] + 2.);
yValues1Up[i] = yValues1[i];
yValues2Up[i] = yValues2[i];
yValues3Up[i] = yValues3[i];
yValues1Dw[i] = yValues1[i];
yValues2Dw[i] = yValues2[i];
yValues3Dw[i] = yValues3[i];
}
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;
}
final NonnegativityPreservingQuinticSplineInterpolator[] bareInterp = new NonnegativityPreservingQuinticSplineInterpolator[] {INTERP_NAT, INTERP_NAK };
final NonnegativityPreservingQuinticSplineInterpolator1D[] wrappedInterp = new NonnegativityPreservingQuinticSplineInterpolator1D[] {INTERP1D_NAT, INTERP1D_NAK };
final int nMethods = bareInterp.length;
for (int k = 0; k < nMethods; ++k) {
final double[] resPrim1 = bareInterp[k].interpolate(xValues, yValues1, xKeys).getData();
final double[] resPrim2 = bareInterp[k].interpolate(xValues, yValues2, xKeys).getData();
final double[] resPrim3 = bareInterp[k].interpolate(xValues, yValues3, xKeys).getData();
Interpolator1DDataBundle dataBund1 = wrappedInterp[k].getDataBundle(xValues, yValues1);
Interpolator1DDataBundle dataBund2 = wrappedInterp[k].getDataBundle(xValues, yValues2);
Interpolator1DDataBundle dataBund3 = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues3);
for (int i = 0; i < 10 * nData; ++i) {
final double ref1 = resPrim1[i];
final double ref2 = resPrim2[i];
final double ref3 = resPrim3[i];
assertEquals(ref1, wrappedInterp[k].interpolate(dataBund1, xKeys[i]), 1.e-14 * Math.max(Math.abs(ref1), 1.));
assertEquals(ref2, wrappedInterp[k].interpolate(dataBund2, xKeys[i]), 1.e-14 * Math.max(Math.abs(ref2), 1.));
assertEquals(ref3, wrappedInterp[k].interpolate(dataBund3, xKeys[i]), 1.e-14 * Math.max(Math.abs(ref3), 1.));
}
for (int j = 0; j < nData; ++j) {
yValues1Up[j] = yValues1[j] * (1. + EPS);
yValues2Up[j] = yValues2[j] * (1. + EPS);
yValues3Up[j] = yValues3[j] * (1. + EPS);
yValues1Dw[j] = yValues1[j] * (1. - EPS);
yValues2Dw[j] = yValues2[j] * (1. - EPS);
yValues3Dw[j] = yValues3[j] * (1. - EPS);
Interpolator1DDataBundle dataBund1Up = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues1Up);
Interpolator1DDataBundle dataBund2Up = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues2Up);
Interpolator1DDataBundle dataBund3Up = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues3Up);
Interpolator1DDataBundle dataBund1Dw = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues1Dw);
Interpolator1DDataBundle dataBund2Dw = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues2Dw);
Interpolator1DDataBundle dataBund3Dw = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues3Dw);
for (int i = 0; i < 10 * nData; ++i) {
double res1 = 0.5 * (wrappedInterp[k].interpolate(dataBund1Up, xKeys[i]) - wrappedInterp[k].interpolate(dataBund1Dw, xKeys[i])) / EPS / yValues1[j];
double res2 = 0.5 * (wrappedInterp[k].interpolate(dataBund2Up, xKeys[i]) - wrappedInterp[k].interpolate(dataBund2Dw, xKeys[i])) / EPS / yValues2[j];
double res3 = 0.5 * (wrappedInterp[k].interpolate(dataBund3Up, xKeys[i]) - wrappedInterp[k].interpolate(dataBund3Dw, xKeys[i])) / EPS / yValues3[j];
assertEquals(res1, wrappedInterp[k].getNodeSensitivitiesForValue(dataBund1, xKeys[i])[j], Math.max(Math.abs(yValues1[j]) * EPS, EPS) * 10.);
assertEquals(res2, wrappedInterp[k].getNodeSensitivitiesForValue(dataBund2, xKeys[i])[j], Math.max(Math.abs(yValues2[j]) * EPS, EPS) * 10.);
assertEquals(res3, wrappedInterp[k].getNodeSensitivitiesForValue(dataBund3, xKeys[i])[j], Math.max(Math.abs(yValues3[j]) * EPS, EPS) * 10.);
}
yValues1Up[j] = yValues1[j];
yValues2Up[j] = yValues2[j];
yValues3Up[j] = yValues3[j];
yValues1Dw[j] = yValues1[j];
yValues2Dw[j] = yValues2[j];
yValues3Dw[j] = yValues3[j];
}
}
}
/**
* Derivative values are modified
*/
@Test
public void modifiedFunctionTest() {
final int nData = 10;
final double[] xValues = new double[nData];
final double[] yValues1 = new double[] {4., 3., 2., 1., 0.1, 0.1, 1., 2., 3., 4. };
final double[] yValues2 = new double[] {-4., -3., -2., -1., -0.1, -0.1, -1., -2., -3., -4. };
final double[] yValues3 = new double[] {1., 0.01, 0.5, 5., 0.1, 0.2, 0.5, 3., 2., 2. };
final double[] yValues1Up = new double[nData];
final double[] yValues2Up = new double[nData];
final double[] yValues3Up = new double[nData];
final double[] yValues1Dw = new double[nData];
final double[] yValues2Dw = new double[nData];
final double[] yValues3Dw = new double[nData];
final double[] xKeys = new double[10 * nData];
for (int i = 0; i < nData; ++i) {
xValues[i] = i + 1;
yValues1Up[i] = yValues1[i];
yValues2Up[i] = yValues2[i];
yValues3Up[i] = yValues3[i];
yValues1Dw[i] = yValues1[i];
yValues2Dw[i] = yValues2[i];
yValues3Dw[i] = yValues3[i];
}
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;
}
final NonnegativityPreservingQuinticSplineInterpolator[] bareInterp = new NonnegativityPreservingQuinticSplineInterpolator[] {INTERP_NAT, INTERP_NAK };
final NonnegativityPreservingQuinticSplineInterpolator1D[] wrappedInterp = new NonnegativityPreservingQuinticSplineInterpolator1D[] {INTERP1D_NAT, INTERP1D_NAK };
final int nMethods = bareInterp.length;
for (int k = 0; k < nMethods; ++k) {
final double[] resPrim1 = bareInterp[k].interpolate(xValues, yValues1, xKeys).getData();
final double[] resPrim2 = bareInterp[k].interpolate(xValues, yValues2, xKeys).getData();
final double[] resPrim3 = bareInterp[k].interpolate(xValues, yValues3, xKeys).getData();
Interpolator1DDataBundle dataBund1 = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues1);
Interpolator1DDataBundle dataBund2 = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues2);
Interpolator1DDataBundle dataBund3 = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues3);
for (int i = 0; i < 10 * nData; ++i) {
final double ref1 = resPrim1[i];
final double ref2 = resPrim2[i];
final double ref3 = resPrim3[i];
assertEquals(ref1, wrappedInterp[k].interpolate(dataBund1, xKeys[i]), 1.e-14 * Math.max(Math.abs(ref1), 1.));
assertEquals(ref2, wrappedInterp[k].interpolate(dataBund2, xKeys[i]), 1.e-14 * Math.max(Math.abs(ref2), 1.));
assertEquals(ref3, wrappedInterp[k].interpolate(dataBund3, xKeys[i]), 1.e-14 * Math.max(Math.abs(ref3), 1.));
}
for (int j = 0; j < nData; ++j) {
yValues1Up[j] = yValues1[j] * (1. + EPS);
yValues2Up[j] = yValues2[j] * (1. + EPS);
yValues3Up[j] = yValues3[j] * (1. + EPS);
yValues1Dw[j] = yValues1[j] * (1. - EPS);
yValues2Dw[j] = yValues2[j] * (1. - EPS);
yValues3Dw[j] = yValues3[j] * (1. - EPS);
Interpolator1DDataBundle dataBund1Up = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues1Up);
Interpolator1DDataBundle dataBund2Up = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues2Up);
Interpolator1DDataBundle dataBund3Up = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues3Up);
Interpolator1DDataBundle dataBund1Dw = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues1Dw);
Interpolator1DDataBundle dataBund2Dw = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues2Dw);
Interpolator1DDataBundle dataBund3Dw = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues3Dw);
for (int i = 0; i < 10 * nData; ++i) {
double res1 = 0.5 * (wrappedInterp[k].interpolate(dataBund1Up, xKeys[i]) - wrappedInterp[k].interpolate(dataBund1Dw, xKeys[i])) / EPS / yValues1[j];
double res2 = 0.5 * (wrappedInterp[k].interpolate(dataBund2Up, xKeys[i]) - wrappedInterp[k].interpolate(dataBund2Dw, xKeys[i])) / EPS / yValues2[j];
double res3 = 0.5 * (wrappedInterp[k].interpolate(dataBund3Up, xKeys[i]) - wrappedInterp[k].interpolate(dataBund3Dw, xKeys[i])) / EPS / yValues3[j];
assertEquals(res1, wrappedInterp[k].getNodeSensitivitiesForValue(dataBund1, xKeys[i])[j], Math.max(Math.abs(yValues1[j]) * EPS, EPS) * 10.);
assertEquals(res2, wrappedInterp[k].getNodeSensitivitiesForValue(dataBund2, xKeys[i])[j], Math.max(Math.abs(yValues2[j]) * EPS, EPS) * 10.);
assertEquals(res3, wrappedInterp[k].getNodeSensitivitiesForValue(dataBund3, xKeys[i])[j], Math.max(Math.abs(yValues3[j]) * EPS, EPS) * 100.);
}
yValues1Up[j] = yValues1[j];
yValues2Up[j] = yValues2[j];
yValues3Up[j] = yValues3[j];
yValues1Dw[j] = yValues1[j];
yValues2Dw[j] = yValues2[j];
yValues3Dw[j] = yValues3[j];
}
}
}
/**
* Primary interpolator is cubic spline with clamped endpoint condition
*/
@Test
public void clampedTest() {
final int nData = 10;
final double[] xValues = new double[nData];
final double[] yValues1 = new double[nData];
final double[] yValues2 = new double[nData];
final double[] yValues3 = new double[nData];
final double[] yValues1Clamped = new double[nData + 2];
final double[] yValues2Clamped = new double[nData + 2];
final double[] yValues3Clamped = new double[nData + 2];
Arrays.fill(yValues1Clamped, 0.);
Arrays.fill(yValues2Clamped, 0.);
Arrays.fill(yValues3Clamped, 0.);
final double[] yValues1Up = new double[nData];
final double[] yValues2Up = new double[nData];
final double[] yValues1Dw = new double[nData];
final double[] yValues2Dw = new double[nData];
final double[] yValues3Up = new double[nData];
final double[] yValues3Dw = new double[nData];
final double[] yValues4Up = new double[nData];
final double[] yValues4Dw = new double[nData];
final double[] yValues5Up = new double[nData];
final double[] yValues5Dw = new double[nData];
final double[] xKeys = new double[10 * nData];
final double[] yValues4 = new double[] {1.0, 2.0, 2.0, 2.0, 1.0, 3.0, 1.0, 3.0, 1.0, 4.0 };
final double[] yValues5 = new double[] {1.0, 2.0, 1.0, 2.0, 1.0, 3.0, 1.0, 3.0, 1.0, 3.0 };
final double[] yValues4Clamped = new double[] {0., 1.0, 2.0, 2.0, 2.0, 1.0, 3.0, 1.0, 3.0, 1.0, 4.0, 0. };
final double[] yValues5Clamped = new double[] {0., 1.0, 2.0, 1.0, 2.0, 1.0, 3.0, 1.0, 3.0, 1.0, 3.0, 0. };
for (int i = 0; i < nData; ++i) {
xValues[i] = i + 1;
yValues1[i] = 0.5 * xValues[i] * xValues[i] * xValues[i] - 1.5 * xValues[i] * xValues[i] + xValues[i] - 2.;
yValues2[i] = Math.exp(0.1 * xValues[i] - 6.);
yValues3[i] = (2. * xValues[i] * xValues[i] + xValues[i]) / (xValues[i] * xValues[i] + xValues[i] * xValues[i] * xValues[i] + 5. * xValues[i] + 2.);
yValues1Clamped[i + 1] = yValues1[i];
yValues2Clamped[i + 1] = yValues2[i];
yValues3Clamped[i + 1] = yValues3[i];
yValues1Up[i] = yValues1[i];
yValues2Up[i] = yValues2[i];
yValues1Dw[i] = yValues1[i];
yValues2Dw[i] = yValues2[i];
yValues3Up[i] = yValues3[i];
yValues3Dw[i] = yValues3[i];
yValues4Up[i] = yValues4[i];
yValues4Dw[i] = yValues4[i];
yValues5Up[i] = yValues5[i];
yValues5Dw[i] = yValues5[i];
}
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;
}
final double[] bdConds = new double[] {-1., -0.1, 0., 1. / 3., 0.9 };
final int nConds = bdConds.length;
final NonnegativityPreservingQuinticSplineInterpolator bare = new NonnegativityPreservingQuinticSplineInterpolator(new CubicSplineInterpolator());
final NonnegativityPreservingQuinticSplineInterpolator1D wrap = new NonnegativityPreservingQuinticSplineInterpolator1D(new CubicSplineInterpolator());
for (int l = 0; l < nConds; ++l) {
for (int m = 0; m < nConds; ++m) {
yValues1Clamped[0] = bdConds[l];
yValues1Clamped[nData + 1] = bdConds[m];
yValues2Clamped[0] = bdConds[l];
yValues2Clamped[nData + 1] = bdConds[m];
yValues3Clamped[0] = bdConds[l];
yValues3Clamped[nData + 1] = bdConds[m];
yValues4Clamped[0] = bdConds[l];
yValues4Clamped[nData + 1] = bdConds[m];
yValues5Clamped[0] = bdConds[l];
yValues5Clamped[nData + 1] = bdConds[m];
final double[] resPrim1 = bare.interpolate(xValues, yValues1Clamped, xKeys).getData();
final double[] resPrim2 = bare.interpolate(xValues, yValues2Clamped, xKeys).getData();
final double[] resPrim3 = bare.interpolate(xValues, yValues3Clamped, xKeys).getData();
final double[] resPrim4 = bare.interpolate(xValues, yValues4Clamped, xKeys).getData();
final double[] resPrim5 = bare.interpolate(xValues, yValues5Clamped, xKeys).getData();
Interpolator1DDataBundle dataBund1 = wrap.getDataBundleFromSortedArrays(xValues, yValues1, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund2 = wrap.getDataBundleFromSortedArrays(xValues, yValues2, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund3 = wrap.getDataBundleFromSortedArrays(xValues, yValues3, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund4 = wrap.getDataBundleFromSortedArrays(xValues, yValues4, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund5 = wrap.getDataBundleFromSortedArrays(xValues, yValues5, bdConds[l], bdConds[m]);
for (int i = 0; i < 10 * nData; ++i) {
final double ref1 = resPrim1[i];
final double ref2 = resPrim2[i];
final double ref3 = resPrim3[i];
final double ref4 = resPrim4[i];
final double ref5 = resPrim5[i];
assertEquals(ref1, wrap.interpolate(dataBund1, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref1), 1.));
assertEquals(ref2, wrap.interpolate(dataBund2, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref2), 1.));
assertEquals(ref3, wrap.interpolate(dataBund3, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref3), 1.));
assertEquals(ref4, wrap.interpolate(dataBund4, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref4), 1.));
assertEquals(ref5, wrap.interpolate(dataBund5, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref5), 1.));
}
for (int j = 0; j < nData; ++j) {
yValues1Up[j] = yValues1[j] * (1. + EPS);
yValues2Up[j] = yValues2[j] * (1. + EPS);
yValues3Up[j] = yValues3[j] * (1. + EPS);
yValues1Dw[j] = yValues1[j] * (1. - EPS);
yValues2Dw[j] = yValues2[j] * (1. - EPS);
yValues3Up[j] = yValues3[j] * (1. + EPS);
yValues3Dw[j] = yValues3[j] * (1. - EPS);
yValues4Up[j] = yValues4[j] * (1. + EPS);
yValues4Dw[j] = yValues4[j] * (1. - EPS);
yValues5Up[j] = yValues5[j] * (1. + EPS);
yValues5Dw[j] = yValues5[j] * (1. - EPS);
Interpolator1DDataBundle dataBund1Up = wrap.getDataBundleFromSortedArrays(xValues, yValues1Up, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund2Up = wrap.getDataBundleFromSortedArrays(xValues, yValues2Up, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund1Dw = wrap.getDataBundleFromSortedArrays(xValues, yValues1Dw, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund2Dw = wrap.getDataBundleFromSortedArrays(xValues, yValues2Dw, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund3Up = wrap.getDataBundleFromSortedArrays(xValues, yValues3Up, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund3Dw = wrap.getDataBundleFromSortedArrays(xValues, yValues3Dw, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund4Up = wrap.getDataBundleFromSortedArrays(xValues, yValues4Up, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund4Dw = wrap.getDataBundleFromSortedArrays(xValues, yValues4Dw, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund5Up = wrap.getDataBundleFromSortedArrays(xValues, yValues5Up, bdConds[l], bdConds[m]);
Interpolator1DDataBundle dataBund5Dw = wrap.getDataBundleFromSortedArrays(xValues, yValues5Dw, bdConds[l], bdConds[m]);
for (int i = 0; i < 10 * nData; ++i) {
double res1 = 0.5 * (wrap.interpolate(dataBund1Up, xKeys[i]) - wrap.interpolate(dataBund1Dw, xKeys[i])) / EPS / yValues1[j];
double res2 = 0.5 * (wrap.interpolate(dataBund2Up, xKeys[i]) - wrap.interpolate(dataBund2Dw, xKeys[i])) / EPS / yValues2[j];
double res3 = 0.5 * (wrap.interpolate(dataBund3Up, xKeys[i]) - wrap.interpolate(dataBund3Dw, xKeys[i])) / EPS / yValues3[j];
double res4 = 0.5 * (wrap.interpolate(dataBund4Up, xKeys[i]) - wrap.interpolate(dataBund4Dw, xKeys[i])) / EPS / yValues4[j];
double res5 = 0.5 * (wrap.interpolate(dataBund5Up, xKeys[i]) - wrap.interpolate(dataBund5Dw, xKeys[i])) / EPS / yValues5[j];
assertEquals(res1, wrap.getNodeSensitivitiesForValue(dataBund1, xKeys[i])[j], Math.max(Math.abs(yValues1[j]) * EPS, EPS) * 100.);
assertEquals(res2, wrap.getNodeSensitivitiesForValue(dataBund2, xKeys[i])[j], Math.max(Math.abs(yValues2[j]) * EPS, EPS) * 100.);
assertEquals(res3, wrap.getNodeSensitivitiesForValue(dataBund3, xKeys[i])[j], Math.max(Math.abs(yValues3[j]) * EPS, EPS) * 10.);
assertEquals(res4, wrap.getNodeSensitivitiesForValue(dataBund4, xKeys[i])[j], Math.max(Math.abs(yValues4[j]) * EPS, EPS) * 10.);
assertEquals(res5, wrap.getNodeSensitivitiesForValue(dataBund5, xKeys[i])[j], Math.max(Math.abs(yValues5[j]) * EPS, EPS) * 10.);
}
yValues1Up[j] = yValues1[j];
yValues2Up[j] = yValues2[j];
yValues1Dw[j] = yValues1[j];
yValues2Dw[j] = yValues2[j];
yValues3Up[j] = yValues3[j];
yValues3Dw[j] = yValues3[j];
yValues4Up[j] = yValues4[j];
yValues4Dw[j] = yValues4[j];
yValues5Up[j] = yValues5[j];
yValues5Dw[j] = yValues5[j];
}
}
}
}
/**
*
*/
@Test
public void linearDataTest() {
final double[] xValues = new double[] {1., 2., 3., 4., 5., 6., 7., 8. };
final double[][] yValues = new double[][] { {0., 0., 0., 0., 0., 0., 0., 0. }, {1., 1., 1., 1., 1., 1., 1., 1. }, {1., 3., 5., 7., 9., 11., 13., 15. },
{19., 14., 9., 4., -1., -6., -11., -16. }, {-16., -11., -6., -1., 4., 9., 14., 19., },
{0., 0., 0., 0., 0., 0., 1., 1. }, {0., 0., 0., 0., 0., 0., -1., -1. } };
final int nData = xValues.length;
final int dim = yValues.length;
for (int l = 0; l < dim; ++l) {
double[] yValuesUp = Arrays.copyOf(yValues[l], nData);
double[] yValuesDw = Arrays.copyOf(yValues[l], 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;
}
final NonnegativityPreservingQuinticSplineInterpolator1D[] wrappedInterp = new NonnegativityPreservingQuinticSplineInterpolator1D[] {INTERP1D_NAT, INTERP1D_NAK };
final int nMethods = wrappedInterp.length;
for (int k = 0; k < nMethods; ++k) {
Interpolator1DDataBundle dataBund = wrappedInterp[k].getDataBundleFromSortedArrays(xValues, yValues[l]);
for (int j = 1; j < nData; ++j) {
final double den = Math.abs(yValues[l][j]) == 0. ? EPS : yValues[l][j] * EPS;
yValuesUp[j] = Math.abs(yValues[l][j]) == 0. ? EPS : yValues[l][j] * (1. + EPS);
yValuesDw[j] = Math.abs(yValues[l][j]) == 0. ? -EPS : yValues[l][j] * (1. - EPS);
Interpolator1DDataBundle dataBundUp = wrappedInterp[k].getDataBundle(xValues, yValuesUp);
Interpolator1DDataBundle dataBundDw = wrappedInterp[k].getDataBundle(xValues, yValuesDw);
for (int i = 0; i < 10 * nData; ++i) {
double res0 = 0.5 * (wrappedInterp[k].interpolate(dataBundUp, xKeys[i]) - wrappedInterp[k].interpolate(dataBundDw, xKeys[i])) / den;
assertEquals(res0, wrappedInterp[k].getNodeSensitivitiesForValue(dataBund, xKeys[i])[j], Math.max(Math.abs(yValues[l][j]) * EPS, EPS));
}
yValuesUp[j] = yValues[l][j];
yValuesDw[j] = yValues[l][j];
}
}
}
}
/**
*
*/
@Test
public void branchTest() {
final int nData = 10;
double[] xValues;
double[][] yValues1;
double[] yValues1Up = new double[nData];
double[] yValues1Dw = new double[nData];
final double[] xKeys = new double[10 * nData];
xValues = new double[] {1., 2., 3., 4., 5., 6., 7., 8., 9., 10. };
yValues1 = new double[][] {
{2.0, 2.0, 0.0, 1.0, 2.0, 0.0, 2.0, 1.0, 0.0, 2.0 },
{2.0, -1.0, 1.0, 1.0, 1.0, -1.0, 1.0, 1.0, -1.0, 2.0 },
{2.0, -1.0, 0.0, -1.0, 1.0, 2.0, 1.0, 2.0, -1.0, 2.0 } };
final int dim = yValues1.length;
for (int k = 0; k < dim; ++k) {
for (int i = 0; i < nData; ++i) {
yValues1Up[i] = yValues1[k][i];
yValues1Dw[i] = yValues1[k][i];
}
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;
}
final NonnegativityPreservingQuinticSplineInterpolator[] bareInterp = new NonnegativityPreservingQuinticSplineInterpolator[] {INTERP_NAT, INTERP_NAK };
final NonnegativityPreservingQuinticSplineInterpolator1D[] wrappedInterp = new NonnegativityPreservingQuinticSplineInterpolator1D[] {INTERP1D_NAT, INTERP1D_NAK };
final int nMethods = wrappedInterp.length;
for (int l = 0; l < nMethods; ++l) {
final double[] resPrim1 = bareInterp[l].interpolate(xValues, yValues1[k], xKeys).getData();
Interpolator1DDataBundle dataBund1 = wrappedInterp[l].getDataBundleFromSortedArrays(xValues, yValues1[k]);
for (int i = 0; i < 10 * nData; ++i) {
final double ref1 = resPrim1[i];
assertEquals(ref1, wrappedInterp[l].interpolate(dataBund1, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref1), 1.));
}
for (int j = 0; j < nData; ++j) {
final double den1 = Math.abs(yValues1[k][j]) == 0. ? EPS : yValues1[k][j] * EPS;
yValues1Up[j] = Math.abs(yValues1[k][j]) == 0. ? EPS : yValues1[k][j] * (1. + EPS);
yValues1Dw[j] = Math.abs(yValues1[k][j]) == 0. ? -EPS : yValues1[k][j] * (1. - EPS);
Interpolator1DDataBundle dataBund1Up = wrappedInterp[l].getDataBundleFromSortedArrays(xValues, yValues1Up);
Interpolator1DDataBundle dataBund1Dw = wrappedInterp[l].getDataBundleFromSortedArrays(xValues, yValues1Dw);
for (int i = 0; i < 10 * nData; ++i) {
double res1 = 0.5 * (wrappedInterp[l].interpolate(dataBund1Up, xKeys[i]) - wrappedInterp[l].interpolate(dataBund1Dw, xKeys[i])) / den1;
assertEquals(res1, wrappedInterp[l].getNodeSensitivitiesForValue(dataBund1, xKeys[i])[j], Math.max(Math.abs(yValues1[k][j]) * EPS, EPS) * 10.);
}
yValues1Up[j] = yValues1[k][j];
yValues1Dw[j] = yValues1[k][j];
}
}
}
}
/**
*
*/
@Test
public void branchClamped1Test() {
final int nData = 10;
double[] xValues;
double[][] yValues1;
double[] yValues1Up = new double[nData];
double[] yValues1Dw = new double[nData];
final double[] xKeys = new double[10 * nData];
xValues = new double[] {1., 2., 3., 4., 5., 6., 7., 8., 9., 10. };
yValues1 = new double[][] {
{0.1, 0.1, 3.1, 1.1, 2.1, 0.1, 3.1, 0.1, 2.1, 1.1 },
{0.1, 1.1, 1.1, 1.1, 0.1, 2.1, 0.1, 3.1, 0.1, 0.1 }
};
final int dim = yValues1.length;
for (int k = 0; k < dim; ++k) {
final double[] yValues1Srt = new double[nData + 2];
Arrays.fill(yValues1Srt, 0.);
for (int i = 0; i < nData; ++i) {
yValues1Up[i] = yValues1[k][i];
yValues1Dw[i] = yValues1[k][i];
yValues1Srt[i + 1] = yValues1[k][i];
}
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;
}
final NonnegativityPreservingQuinticSplineInterpolator bareInterp = new NonnegativityPreservingQuinticSplineInterpolator(
new CubicSplineInterpolator());
final NonnegativityPreservingQuinticSplineInterpolator1D wrappedInterp = new NonnegativityPreservingQuinticSplineInterpolator1D(
new CubicSplineInterpolator());
final double[] resPrim1 = bareInterp.interpolate(xValues, yValues1Srt, xKeys).getData();
Interpolator1DDataBundle dataBund1 = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1[k], 0., 0.);
for (int i = 0; i < 10 * nData; ++i) {
final double ref1 = resPrim1[i];
assertEquals(ref1, wrappedInterp.interpolate(dataBund1, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref1), 1.));
}
for (int j = 0; j < nData; ++j) {
final double den1 = Math.abs(yValues1[k][j]) == 0. ? EPS : yValues1[k][j] * EPS;
yValues1Up[j] = Math.abs(yValues1[k][j]) == 0. ? EPS : yValues1[k][j] * (1. + EPS);
yValues1Dw[j] = Math.abs(yValues1[k][j]) == 0. ? -EPS : yValues1[k][j] * (1. - EPS);
Interpolator1DDataBundle dataBund1Up = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1Up, 0., 0.);
Interpolator1DDataBundle dataBund1Dw = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1Dw, 0., 0.);
for (int i = 0; i < 10 * nData; ++i) {
double res1 = 0.5 * (wrappedInterp.interpolate(dataBund1Up, xKeys[i]) - wrappedInterp.interpolate(dataBund1Dw, xKeys[i])) / den1;
assertEquals(res1, wrappedInterp.getNodeSensitivitiesForValue(dataBund1, xKeys[i])[j], Math.max(Math.abs(yValues1[k][j]) * EPS, EPS) * 10.);
}
yValues1Up[j] = yValues1[k][j];
yValues1Dw[j] = yValues1[k][j];
}
}
}
/**
*
*/
@Test
public void branchClamped2Test() {
final int nData = 10;
double[] xValues;
double[][] yValues1;
double[] yValues1Up = new double[nData];
double[] yValues1Dw = new double[nData];
final double[] xKeys = new double[10 * nData];
xValues = new double[] {1., 2., 3., 4., 5., 6., 7., 8., 9., 10. };
yValues1 = new double[][] { {1., 2., 3., 4., 5., 6., 7., 4., 7., 1. }, {-1., 2., 3., 4., 5., 6., 7., 4., 7., -1. } };
final int dim = yValues1.length;
final double[] bv = new double[] {5., -5 };
for (int k = 0; k < dim; ++k) {
final double[] yValues1Srt = new double[nData + 2];
Arrays.fill(yValues1Srt, 0.);
for (int i = 0; i < nData; ++i) {
yValues1Up[i] = yValues1[k][i];
yValues1Dw[i] = yValues1[k][i];
yValues1Srt[i + 1] = yValues1[k][i];
}
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;
}
final NonnegativityPreservingQuinticSplineInterpolator bareInterp = new NonnegativityPreservingQuinticSplineInterpolator(
new CubicSplineInterpolator());
final NonnegativityPreservingQuinticSplineInterpolator1D wrappedInterp = new NonnegativityPreservingQuinticSplineInterpolator1D(
new CubicSplineInterpolator());
for (int l = 0; l < 2; ++l) {
yValues1Srt[0] = bv[l];
yValues1Srt[nData + 1] = bv[l];
final double[] resPrim1 = bareInterp.interpolate(xValues, yValues1Srt, xKeys).getData();
Interpolator1DDataBundle dataBund1 = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1[k], bv[l], bv[l]);
for (int i = 0; i < 10 * nData; ++i) {
final double ref1 = resPrim1[i];
assertEquals(ref1, wrappedInterp.interpolate(dataBund1, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref1), 1.));
}
for (int j = 0; j < nData; ++j) {
final double den1 = Math.abs(yValues1[k][j]) == 0. ? EPS : yValues1[k][j] * EPS;
yValues1Up[j] = Math.abs(yValues1[k][j]) == 0. ? EPS : yValues1[k][j] * (1. + EPS);
yValues1Dw[j] = Math.abs(yValues1[k][j]) == 0. ? -EPS : yValues1[k][j] * (1. - EPS);
Interpolator1DDataBundle dataBund1Up = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1Up, bv[l], bv[l]);
Interpolator1DDataBundle dataBund1Dw = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1Dw, bv[l], bv[l]);
for (int i = 0; i < 10 * nData; ++i) {
double res1 = 0.5 * (wrappedInterp.interpolate(dataBund1Up, xKeys[i]) - wrappedInterp.interpolate(dataBund1Dw, xKeys[i])) / den1;
assertEquals(res1, wrappedInterp.getNodeSensitivitiesForValue(dataBund1, xKeys[i])[j], Math.max(Math.abs(yValues1[k][j]) * EPS, EPS) * 1.e6);
}
yValues1Up[j] = yValues1[k][j];
yValues1Dw[j] = yValues1[k][j];
}
}
}
}
/**
*
*/
@Test
public void branchClamped3Test() {
final int nData = 5;
double[] xValues;
double[] yValues1;
double[] yValues1Up = new double[nData];
double[] yValues1Dw = new double[nData];
final double[] xKeys = new double[10 * nData];
xValues = new double[] {1., 2., 3., 4., 5. };
yValues1 = new double[] {-1.483840496565862, -0.23754175460045587, 0.011717993792625392, 0.011717993792625392, 0.5102374905787879 };
final int dim = yValues1.length;
for (int k = 0; k < dim; ++k) {
final double[] yValues1Srt = new double[nData + 2];
Arrays.fill(yValues1Srt, 0.);
for (int i = 0; i < nData; ++i) {
yValues1Up[i] = yValues1[i];
yValues1Dw[i] = yValues1[i];
yValues1Srt[i + 1] = yValues1[i];
}
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;
}
final NonnegativityPreservingQuinticSplineInterpolator bareInterp = new NonnegativityPreservingQuinticSplineInterpolator(
new CubicSplineInterpolator());
final NonnegativityPreservingQuinticSplineInterpolator1D wrappedInterp = new NonnegativityPreservingQuinticSplineInterpolator1D(
new CubicSplineInterpolator());
final double left = 4. / 3. * (yValues1[2] - yValues1[0]);
final double right = 2. / 3. * (yValues1[2] - yValues1[0]);
yValues1Srt[0] = left;
yValues1Srt[nData + 1] = right;
final double[] resPrim1 = bareInterp.interpolate(xValues, yValues1Srt, xKeys).getData();
Interpolator1DDataBundle dataBund1 = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1, left, right);
for (int i = 0; i < 10 * nData; ++i) {
final double ref1 = resPrim1[i];
assertEquals(ref1, wrappedInterp.interpolate(dataBund1, xKeys[i]), 1.e-15 * Math.max(Math.abs(ref1), 1.));
}
for (int j = 0; j < nData; ++j) {
final double den1 = Math.abs(yValues1[j]) == 0. ? EPS : yValues1[j] * EPS;
yValues1Up[j] = Math.abs(yValues1[j]) == 0. ? EPS : yValues1[j] * (1. + EPS);
yValues1Dw[j] = Math.abs(yValues1[j]) == 0. ? -EPS : yValues1[j] * (1. - EPS);
Interpolator1DDataBundle dataBund1Up = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1Up, left, right);
Interpolator1DDataBundle dataBund1Dw = wrappedInterp.getDataBundleFromSortedArrays(xValues, yValues1Dw, left, right);
for (int i = 0; i < 10 * nData; ++i) {
double res1 = 0.5 * (wrappedInterp.interpolate(dataBund1Up, xKeys[i]) - wrappedInterp.interpolate(dataBund1Dw, xKeys[i])) / den1;
assertEquals(res1, wrappedInterp.getNodeSensitivitiesForValue(dataBund1, xKeys[i])[j], Math.max(Math.abs(yValues1[j]) * EPS, EPS) * 1.e6);
}
yValues1Up[j] = yValues1[j];
yValues1Dw[j] = yValues1[j];
}
}
}
}