/**
* Copyright (C) 2009 - 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.AssertJUnit.assertEquals;
import java.util.Arrays;
import org.testng.annotations.Test;
import cern.jet.random.engine.MersenneTwister;
import cern.jet.random.engine.MersenneTwister64;
import cern.jet.random.engine.RandomEngine;
import com.opengamma.analytics.math.function.Function1D;
import com.opengamma.analytics.math.interpolation.data.Interpolator1DCubicSplineDataBundle;
import com.opengamma.analytics.math.interpolation.data.Interpolator1DDataBundle;
/**
*
*/
public class NaturalCubicSplineInterpolator1DNodeSensitivityCalculatorTest {
private static final RandomEngine RANDOM = new MersenneTwister64(MersenneTwister.DEFAULT_SEED);
private static final Interpolator1D INTERPOLATOR = new NaturalCubicSplineInterpolator1D();
private static final Interpolator1DDataBundle DATA1;
private static final double EPS = 1e-7;
private static final Function1D<Double, Double> FUNCTION = new Function1D<Double, Double>() {
private static final double a = -0.045;
private static final double b = 0.03;
private static final double c = 0.3;
private static final double d = 0.05;
@Override
public Double evaluate(final Double x) {
return (a + b * x) * Math.exp(-c * x) + d;
}
};
static {
final double[] t = new double[] {0.0, 0.5, 1.0, 2.0, 3.0, 5.0, 7.0, 10.0, 15.0, 17.5, 20.0, 25.0, 30.0};
final int n = t.length;
final double[] r = new double[n];
for (int i = 0; i < n; i++) {
r[i] = FUNCTION.evaluate(t[i]);
}
DATA1 = INTERPOLATOR.getDataBundleFromSortedArrays(t, r);
}
@Test(expectedExceptions = IllegalArgumentException.class)
public void nullInputMap() {
INTERPOLATOR.interpolate(null, 3.);
}
@Test(expectedExceptions = IllegalArgumentException.class)
public void nullInterpolateValue() {
INTERPOLATOR.interpolate(DATA1, null);
}
@Test(expectedExceptions = IllegalArgumentException.class)
public void testHighValue() {
INTERPOLATOR.interpolate(DATA1, 31.);
}
@Test(expectedExceptions = IllegalArgumentException.class)
public void testLowValue() {
INTERPOLATOR.interpolate(DATA1, -1.);
}
@Test
public void testSensitivities() {
final double tmax = DATA1.lastKey();
double[] sensitivity;
for (int i = 0; i < 100; i++) {
final double t = tmax * RANDOM.nextDouble();
sensitivity = INTERPOLATOR.getNodeSensitivitiesForValue(DATA1, t);
for (int j = 0; j < sensitivity.length; j++) {
assertEquals(getSensitivity(DATA1, INTERPOLATOR, t, j), sensitivity[j], EPS);
}
}
}
@Test
public void testYieldCurve() {
final double[] fwdTimes = new double[] {0.0, 1.0, 2.0, 5.0, 10.0, 20.0, 31.0};
final int n = fwdTimes.length;
final double[] rates = new double[n];
for (int i = 0; i < n; i++) {
rates[i] = FUNCTION.evaluate(fwdTimes[i]);
}
final Interpolator1DCubicSplineDataBundle data = new Interpolator1DCubicSplineDataBundle(INTERPOLATOR.getDataBundleFromSortedArrays(fwdTimes, rates));
final double[] sensitivity1 = INTERPOLATOR.getNodeSensitivitiesForValue(data, 0.25);
final double[] sensitivity2 = INTERPOLATOR.getNodeSensitivitiesForValue(data, 0.25, true);
for (int j = 0; j < sensitivity1.length; j++) {
assertEquals(sensitivity1[j], sensitivity2[j], EPS);
}
}
private double getSensitivity(final Interpolator1DDataBundle model, final Interpolator1D interpolator, final double t, final int node) {
final double[] x = model.getKeys();
final double[] y = model.getValues();
final int n = y.length;
double[] yUp = new double[n];
double[] yDown = new double[n];
yUp = Arrays.copyOf(y, n);
yDown = Arrays.copyOf(y, n);
yUp[node] += EPS;
yDown[node] -= EPS;
final Interpolator1DDataBundle modelUp = interpolator.getDataBundleFromSortedArrays(x, yUp);
final Interpolator1DDataBundle modelDown = interpolator.getDataBundleFromSortedArrays(x, yDown);
final double up = interpolator.interpolate(modelUp, t);
final double down = interpolator.interpolate(modelDown, t);
return (up - down) / 2.0 / EPS;
}
}