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/*
 * Copyright 2013 SPZ
 *
 * Licensed 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 math.function;

import math.MathConsts;

/**
 * Finite difference numerical gradient calculation using the forward difference
 * approximation {@code f'(x) = (f(x + h) - f(x)) / h}.
 * 

* Scaling of {@code h} is taken into account by each individual {@code h} being * based upon the absolute magnitude of the corresponding element in the vector * {@code x}. */ public abstract class NumericallyDiffMultivariateFunction implements DiffMultivariateFunction { protected final double diffScale; public NumericallyDiffMultivariateFunction() { this(1.5 * Math.sqrt(MathConsts.MACH_EPS)); } public NumericallyDiffMultivariateFunction(double diffScale) { this.diffScale = diffScale; } @Override public final void derivativeAt(double[] x, double[] grad) { double fx = this.valueAt(x); for (int i = 0; i < x.length; ++i) { double xi = x[i]; double hi = (xi != 0.0) ? diffScale * Math.abs(xi) : diffScale; double xi_plus_hi = xi + hi; // account for potential round-off errors hi = xi_plus_hi - xi; x[i] = xi_plus_hi; // new function value for advance in variable i double fx_plus_hi = this.valueAt(x); // estimated gradient component for variable i grad[i] = (fx_plus_hi - fx) / hi; // restore the old value for variable i x[i] = xi; } } }





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