2024-09-10 20:04:47 +08:00
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/********************************************************
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* ██████╗ ███████╗████████╗██╗
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* ██╔════╝ ██╔════╝╚══██╔══╝██║
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* ██║ ███╗███████╗ ██║ ██║
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* ██║ ██║╚════██║ ██║ ██║
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* ╚██████╔╝███████║ ██║ ███████╗
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* ╚═════╝ ╚══════╝ ╚═╝ ╚══════╝
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* Generic Scientific Template Library
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*
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* Copyright (c) 2022 Yi Zhang (yizhang-geo@zju.edu.cn)
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*
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* The GSTL is distributed under a dual licensing scheme. You can redistribute
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* it and/or modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation, either version 2
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* of the License, or (at your option) any later version. You should have
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* received a copy of the GNU Lesser General Public License (LGPL) along with
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* this program. If not, see <http://www.gnu.org/licenses/>.
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*
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* If the terms and conditions of the LGPL v.2. would prevent you from using
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* the GSTL, please consider the option to obtain a commercial license for a
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* fee. These licenses are offered by the GSTL's original author. As a rule,
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* licenses are provided "as-is", unlimited in time for a one time fee. Please
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* send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget
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* to include some description of your company and the realm of its activities.
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* Also add information on how to contact you by electronic and paper mail.
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******************************************************/
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#include "../lib/optimization.h"
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#define M 1000
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#define N 800
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double max_diff(const gctl::array<double> &a, const gctl::array<double> &b)
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{
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double max = -1.0;
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for (size_t i = 0; i < a.size(); i++)
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{
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max = std::max(sqrt((a[i] - b[i])*(a[i] - b[i])), max);
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}
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return max;
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}
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class ex1 : public gctl::lcg_solver
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{
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public:
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ex1();
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virtual ~ex1();
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// 计算共轭梯度的B项
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void cal_partb(const gctl::array<double> &x, gctl::array<double> &B);
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//定义共轭梯度中Ax的算法
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virtual void LCG_Ax(const gctl::array<double> &x, gctl::array<double> &ax);
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virtual void LCG_Mx(const gctl::array<double> &x, gctl::array<double> &mx);
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private:
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gctl::matrix<double> kernel; // 普通二维数组做核矩阵
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gctl::array<double> tmp_arr; // 中间结果数组
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gctl::array<double> p; // 预优矩阵
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};
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ex1::ex1()
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{
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kernel.resize(M, N);
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kernel.random_float(-1.0, 1.0, gctl::RdUniform);
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tmp_arr.resize(M);
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p.resize(N);
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for (size_t i = 0; i < N; i++)
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{
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p[i] = 1.0;
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}
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double diag;
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for (size_t i = 0; i < N; i++)
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{
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diag = 0.0;
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for (size_t j = 0; j < M; j++)
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{
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diag += kernel[j][i]*kernel[j][i];
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}
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p[i] = 1.0/diag;
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}
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}
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ex1::~ex1(){}
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void ex1::cal_partb(const gctl::array<double> &x, gctl::array<double> &B)
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{
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LCG_Ax(x, B);
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return;
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}
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void ex1::LCG_Ax(const gctl::array<double> &x, gctl::array<double> &ax)
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{
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matvec(tmp_arr, kernel, x);
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matvec(ax, kernel, tmp_arr, gctl::Trans);
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return;
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}
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void ex1::LCG_Mx(const gctl::array<double> &x, gctl::array<double> &mx)
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{
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vecmul(mx, p, x);
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return;
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}
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int main(int argc, char const *argv[])
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{
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// 生成一组正演解
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gctl::array<double> fm(N);
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fm.random_float(1.0, 2.0, gctl::RdUniform);
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ex1 test;
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// 计算共轭梯度B项
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gctl::array<double> B(N);
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test.cal_partb(fm, B);
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// 声明一组解
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gctl::array<double> m(N, 0.0);
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test.set_lcg_message(gctl::LCG_SOLUTION);
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std::ofstream ofile("log.txt");
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test.LCG_Minimize(m, B, gctl::LCG_CG, ofile);
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ofile << "maximal difference: " << max_diff(fm, m) << std::endl;
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m.assign_all(0.0);
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test.LCG_Minimize(m, B, gctl::LCG_PCG, ofile);
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ofile << "maximal difference: " << max_diff(fm, m) << std::endl;
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m.assign_all(0.0);
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test.LCG_Minimize(m, B, gctl::LCG_CGS, ofile);
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ofile << "maximal difference: " << max_diff(fm, m) << std::endl;
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ofile.close();
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test.set_lcg_message(gctl::LCG_SOLUTION);
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m.assign_all(0.0);
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test.LCG_Minimize(m, B, gctl::LCG_BICGSTAB);
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std::clog << "maximal difference: " << max_diff(fm, m) << std::endl;
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m.assign_all(0.0);
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test.LCG_Minimize(m, B, gctl::LCG_BICGSTAB2);
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std::clog << "maximal difference: " << max_diff(fm, m) << std::endl;
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gctl::array<double> low(N, 1.0);
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gctl::array<double> hig(N, 2.0);
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m.assign_all(0.0);
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test.LCG_MinimizeConstrained(m, B, low, hig, gctl::LCG_PG);
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std::clog << "maximal difference: " << max_diff(fm, m) << std::endl;
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m.assign_all(0.0);
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test.LCG_MinimizeConstrained(m, B, low, hig, gctl::LCG_SPG);
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std::clog << "maximal difference: " << max_diff(fm, m) << std::endl;
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return 0;
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}
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