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With inspiration from other libraries
/*
* 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.
*
* The partial derivative is defined with respect to point coordinate
* xk. 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.
*
* @param k index of the coordinate with respect to which the partial
* derivative is computed
* @return the partial derivative function with respect to kth point coordinate
*/
MultivariateFunction partialDerivative(int k);
/**
* Returns the gradient function.
* 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.
* @return the gradient function
*/
MultivariateVectorFunction gradient();
}