1 files changed, 108 insertions, 0 deletions
diff --git a/src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java b/src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java
new file mode 100644
index 0000000..3e8e62a
--- /dev/null
+++ b/src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java
@@ -0,0 +1,108 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.math.optimization.fitting;
+
+import org.apache.commons.math.FunctionEvaluationException;
+import org.apache.commons.math.analysis.polynomials.PolynomialFunction;
+import org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer;
+import org.apache.commons.math.optimization.OptimizationException;
+
+/** This class implements a curve fitting specialized for polynomials.
+ * <p>Polynomial fitting is a very simple case of curve fitting. The
+ * estimated coefficients are the polynomial coefficients. They are
+ * searched by a least square estimator.</p>
+ * @version $Revision: 1073270 $ $Date: 2011-02-22 10:19:27 +0100 (mar. 22 févr. 2011) $
+ * @since 2.0
+ */
+
+public class PolynomialFitter {
+
+    /** Fitter for the coefficients. */
+    private final CurveFitter fitter;
+
+    /** Polynomial degree. */
+    private final int degree;
+
+    /** Simple constructor.
+     * <p>The polynomial fitter built this way are complete polynomials,
+     * ie. a n-degree polynomial has n+1 coefficients.</p>
+     * @param degree maximal degree of the polynomial
+     * @param optimizer optimizer to use for the fitting
+     */
+    public PolynomialFitter(int degree, final DifferentiableMultivariateVectorialOptimizer optimizer) {
+        this.fitter = new CurveFitter(optimizer);
+        this.degree = degree;
+    }
+
+    /** Add an observed weighted (x,y) point to the sample.
+     * @param weight weight of the observed point in the fit
+     * @param x abscissa of the point
+     * @param y observed value of the point at x, after fitting we should
+     * have P(x) as close as possible to this value
+     */
+    public void addObservedPoint(double weight, double x, double y) {
+        fitter.addObservedPoint(weight, x, y);
+    }
+
+    /**
+     * Remove all observations.
+     * @since 2.2
+     */
+    public void clearObservations() {
+        fitter.clearObservations();
+    }
+
+    /** Get the polynomial fitting the weighted (x, y) points.
+     * @return polynomial function best fitting the observed points
+     * @exception OptimizationException if the algorithm failed to converge
+     */
+    public PolynomialFunction fit() throws OptimizationException {
+        try {
+            return new PolynomialFunction(fitter.fit(new ParametricPolynomial(), new double[degree + 1]));
+        } catch (FunctionEvaluationException fee) {
+            // should never happen
+            throw new RuntimeException(fee);
+        }
+    }
+
+    /** Dedicated parametric polynomial class. */
+    private static class ParametricPolynomial implements ParametricRealFunction {
+
+        /** {@inheritDoc} */
+        public double[] gradient(double x, double[] parameters) {
+            final double[] gradient = new double[parameters.length];
+            double xn = 1.0;
+            for (int i = 0; i < parameters.length; ++i) {
+                gradient[i] = xn;
+                xn *= x;
+            }
+            return gradient;
+        }
+
+        /** {@inheritDoc} */
+        public double value(final double x, final double[] parameters) {
+            double y = 0;
+            for (int i = parameters.length - 1; i >= 0; --i) {
+                y = y * x + parameters[i];
+            }
+            return y;
+        }
+
+    }
+
+}