MATH-511

Implement "DifferentiableUnivariateRealFunction".


git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1070698 13f79535-47bb-0310-9956-ffa450edef68

src/main/java/org/apache/commons/math/analysis/function/Gaussian.java

@@ -18,6 +18,7 @@
 package org.apache.commons.math.analysis.function;
 
 import org.apache.commons.math.analysis.UnivariateRealFunction;
+import org.apache.commons.math.analysis.DifferentiableUnivariateRealFunction;
 import org.apache.commons.math.exception.NotStrictlyPositiveException;
 import org.apache.commons.math.util.FastMath;
 
@@ -28,7 +29,7 @@ import org.apache.commons.math.util.FastMath;
  * @version $Revision$ $Date$
  * @since 3.0
  */
-public class Gaussian implements UnivariateRealFunction {
+public class Gaussian implements DifferentiableUnivariateRealFunction {
     /** Mean. */
     private final double mean;
     /** Inverse of twice the square of the standard deviation. */
@@ -80,4 +81,22 @@ public class Gaussian implements UnivariateRealFunction {
         final double diff = x - mean;
         return norm * FastMath.exp(-diff * diff * i2s2);
     }
+
+    /** {@inheritDoc} */
+    public UnivariateRealFunction derivative() {
+        return new UnivariateRealFunction() {
+            /** {@inheritDoc} */
+            public double value(double x) {
+                final double diff = x - mean;
+                final double g = Gaussian.this.value(x);
+
+                if (g == 0) {
+                    // Avoid returning NaN in case of overflow.
+                    return 0;
+                } else {
+                    return -2 * diff * i2s2 * g;
+                }
+            }
+        };
+    }
 }

src/test/java/org/apache/commons/math/analysis/function/GaussianTest.java

@@ -39,8 +39,49 @@ public class GaussianTest {
     public void testSomeValues() {
         final UnivariateRealFunction f = new Gaussian();
 
-        Assert.assertEquals(0, f.value(Double.NEGATIVE_INFINITY), 0);
         Assert.assertEquals(1 / FastMath.sqrt(2 * Math.PI), f.value(0), EPS);
+    }
+
+    @Test
+    public void testLargeArguments() {
+        final UnivariateRealFunction f = new Gaussian();
+
+        Assert.assertEquals(0, f.value(Double.NEGATIVE_INFINITY), 0);
+        Assert.assertEquals(0, f.value(-Double.MAX_VALUE), 0);
+        Assert.assertEquals(0, f.value(-1e2), 0);
+        Assert.assertEquals(0, f.value(1e2), 0);
+        Assert.assertEquals(0, f.value(Double.MAX_VALUE), 0);
         Assert.assertEquals(0, f.value(Double.POSITIVE_INFINITY), 0);
     }
+
+    @Test
+    public void testDerivative() {
+        final Gaussian f = new Gaussian();
+        final UnivariateRealFunction dfdx = f.derivative();
+
+        Assert.assertEquals(0, dfdx.value(0), 0);
+    }
+
+    @Test
+    public void testDerivativeLargeArguments() {
+        final Gaussian f = new Gaussian(0, 1e-50);
+        final UnivariateRealFunction dfdx = f.derivative();
+
+        Assert.assertEquals(0, dfdx.value(Double.NEGATIVE_INFINITY), 0);
+        Assert.assertEquals(0, dfdx.value(-Double.MAX_VALUE), 0);
+        Assert.assertEquals(0, f.value(-1e50), 0);
+        Assert.assertEquals(0, f.value(-1e2), 0);
+        Assert.assertEquals(0, f.value(1e2), 0);
+        Assert.assertEquals(0, f.value(1e50), 0);
+        Assert.assertEquals(0, dfdx.value(Double.MAX_VALUE), 0);
+        Assert.assertEquals(0, dfdx.value(Double.POSITIVE_INFINITY), 0);        
+    }
+
+    @Test
+    public void testDerivativeNaN() {
+        final Gaussian f = new Gaussian(0, 1e-50);
+        final UnivariateRealFunction dfdx = f.derivative();
+
+        Assert.assertTrue(Double.isNaN(dfdx.value(Double.NaN)));
+    }
 }