Java tutorial
/* * 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; /** * An interface representing a real function that depends on one independent * variable plus some extra parameters. * * @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 fvr. 2011) $ */ public interface ParametricRealFunction { /** * Compute the value of the function. * @param x the point for which the function value should be computed * @param parameters function parameters * @return the value * @throws FunctionEvaluationException if the function evaluation fails */ double value(double x, double[] parameters) throws FunctionEvaluationException; /** * Compute the gradient of the function with respect to its parameters. * @param x the point for which the function value should be computed * @param parameters function parameters * @return the value * @throws FunctionEvaluationException if the function evaluation fails */ double[] gradient(double x, double[] parameters) throws FunctionEvaluationException; }