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Java example source code file (DifferentiableMultivariateFunction.java)

This example Java source code file (DifferentiableMultivariateFunction.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

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Java - Java tags/keywords

deprecated, differentiablemultivariatefunction, multivariatefunction, multivariatevectorfunction

The DifferentiableMultivariateFunction.java Java example source code

/*
 * 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.math3.analysis;

/**
 * Extension of {@link MultivariateFunction} representing a differentiable
 * multivariate real function.
 * @since 2.0
 * @deprecated as of 3.1 replaced by {@link org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableFunction}
 */
@Deprecated
public interface DifferentiableMultivariateFunction extends MultivariateFunction {

    /**
     * Returns the partial derivative of the function with respect to a point coordinate.
     * <p>
     * The partial derivative is defined with respect to point coordinate
     * x<sub>k. If the partial derivatives with respect to all coordinates are
     * needed, it may be more efficient to use the {@link #gradient()} method which will
     * compute them all at once.
     * </p>
     * @param k index of the coordinate with respect to which the partial
     * derivative is computed
     * @return the partial derivative function with respect to k<sup>th point coordinate
     */
    MultivariateFunction partialDerivative(int k);

    /**
     * Returns the gradient function.
     * <p>If only one partial derivative with respect to a specific coordinate is
     * needed, it may be more efficient to use the {@link #partialDerivative(int)} method
     * which will compute only the specified component.</p>
     * @return the gradient function
     */
    MultivariateVectorFunction gradient();

}

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