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/*******************************************************************************
 * Copyright (c) 2010 Haifeng Li
 *   
 * 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 smile.math.rbf;

/**
 * Thin plate RBF. φ(r) = r2 log(r / r0)
 * with the limiting value φ(0)=0 assumed, where r0 is a scale factor.
 * This function has some physical justification in the energy minimization
 * problem associated with warping a thin elastic plate. However, there is no
 * indication that it is generally better than multiquadric or inverse
 * multiquadric function.
 * 

* In general, r0 should be larger than the typical separation of * points but smaller than the "outer scale" or feature size of the function * to interplate. There can be several orders of magnitude difference between * the interpolation accuracy with a good choice for r0, versus a * poor choice, so it is definitely worth some experimentation. One way to * experiment is to construct an RBF interpolator omitting one data point * at a time and measuring the interpolation error at the omitted point. * * @author Haifeng Li */ public class ThinPlateRadialBasis implements RadialBasisFunction { private double r0; /** * Constructor. */ public ThinPlateRadialBasis() { this(1.0); } /** * Constructor. */ public ThinPlateRadialBasis(double scale) { r0 = scale; } @Override public double f(double r) { return r <= 0.0 ? 0.0 : r * r * Math.log(r / r0); } }





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