1 /*
2 * Copyright (C) 2023 Alberto Irurueta Carro (alberto@irurueta.com)
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16 package com.irurueta.numerical.integration;
17
18 import com.irurueta.algebra.Matrix;
19 import com.irurueta.algebra.WrongSizeException;
20 import com.irurueta.numerical.EvaluationException;
21
22 /**
23 * This is an exact replacement for MidPointMatrixQuadrature, except that upper limit is assumed to be
24 * infinite. It is assumed that the function decreases exponentially rapidly at infinity.
25 */
26 public class ExponentialMidPointMatrixQuadrature extends MidPointMatrixQuadrature {
27
28 /**
29 * Constructor.
30 *
31 * @param a Lower limit of integration.
32 * @param listener listener to evaluate a single dimension function at required points.
33 * @throws WrongSizeException if size notified by provided listener is invalid.
34 */
35 public ExponentialMidPointMatrixQuadrature(
36 final double a, final MatrixSingleDimensionFunctionEvaluatorListener listener) throws WrongSizeException {
37 super(0.0, Math.exp(-a), listener);
38 }
39
40 /**
41 * Gets type of quadrature.
42 *
43 * @return type of quadrature.
44 */
45 @Override
46 public QuadratureType getType() {
47 return QuadratureType.EXPONENTIAL_MID_POINT;
48 }
49
50 /**
51 * Evaluates function at f(-log(x))/x.
52 *
53 * @param x point where function is evaluated.
54 * @param result instance where result of evaluation is stored.
55 * @throws EvaluationException if evaluation fails.
56 */
57 @Override
58 protected void func(final double x, final Matrix result) throws EvaluationException {
59 listener.evaluate(-Math.log(x), result);
60 result.multiplyByScalar(1.0 / x);
61 }
62 }