/src/quantlib/ql/math/matrixutilities/expm.cpp
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1 | | /* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */ |
2 | | |
3 | | /* |
4 | | Copyright (C) 2013 Klaus Spanderen |
5 | | |
6 | | This file is part of QuantLib, a free-software/open-source library |
7 | | for financial quantitative analysts and developers - http://quantlib.org/ |
8 | | |
9 | | QuantLib is free software: you can redistribute it and/or modify it |
10 | | under the terms of the QuantLib license. You should have received a |
11 | | copy of the license along with this program; if not, please email |
12 | | <quantlib-dev@lists.sf.net>. The license is also available online at |
13 | | <http://quantlib.org/license.shtml>. |
14 | | |
15 | | This program is distributed in the hope that it will be useful, but WITHOUT |
16 | | ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
17 | | FOR A PARTICULAR PURPOSE. See the license for more details. |
18 | | */ |
19 | | |
20 | | /*! \file expm.cpp |
21 | | \brief matrix exponential |
22 | | */ |
23 | | |
24 | | |
25 | | #include <ql/math/matrixutilities/expm.hpp> |
26 | | #include <ql/math/ode/adaptiverungekutta.hpp> |
27 | | #include <algorithm> |
28 | | #include <numeric> |
29 | | #include <utility> |
30 | | |
31 | | namespace QuantLib { |
32 | | |
33 | | namespace { |
34 | | class MatrixVectorProductFct { |
35 | | public: |
36 | 0 | explicit MatrixVectorProductFct(Matrix m) : m_(std::move(m)) {} |
37 | | |
38 | | // implements x = M*y |
39 | 0 | std::vector<Real> operator()(Real t, const std::vector<Real>& y) { |
40 | |
|
41 | 0 | std::vector<Real> result(m_.rows()); |
42 | 0 | for (Size i=0; i < result.size(); i++) { |
43 | 0 | result[i] = std::inner_product(y.begin(), y.end(), |
44 | 0 | m_.row_begin(i), Real(0.0)); |
45 | 0 | } |
46 | 0 | return result; |
47 | 0 | } |
48 | | private: |
49 | | const Matrix m_; |
50 | | }; |
51 | | } |
52 | | |
53 | 0 | Matrix Expm(const Matrix& M, Real t, Real tol) { |
54 | 0 | const Size n = M.rows(); |
55 | 0 | QL_REQUIRE(n == M.columns(), "Expm expects a square matrix"); |
56 | | |
57 | 0 | AdaptiveRungeKutta<> rk(tol); |
58 | 0 | AdaptiveRungeKutta<>::OdeFct odeFct = MatrixVectorProductFct(M); |
59 | |
|
60 | 0 | Matrix result(n, n); |
61 | 0 | for (Size i=0; i < n; ++i) { |
62 | 0 | std::vector<Real> x0(n, 0.0); |
63 | 0 | x0[i] = 1.0; |
64 | |
|
65 | 0 | const std::vector<Real> r = rk(odeFct, x0, 0.0, t); |
66 | 0 | std::copy(r.begin(), r.end(), result.column_begin(i)); |
67 | 0 | } |
68 | 0 | return result; |
69 | 0 | } |
70 | | } |