/******************************************************** * ██████╗ ██████╗████████╗██╗ * ██╔════╝ ██╔════╝╚══██╔══╝██║ * ██║ ███╗██║ ██║ ██║ * ██║ ██║██║ ██║ ██║ * ╚██████╔╝╚██████╗ ██║ ███████╗ * ╚═════╝ ╚═════╝ ╚═╝ ╚══════╝ * Geophlatsical Computational Tools & Library (GCTL) * * Copyright (c) 2022 Yi Zhang (yizhang-geo@zju.edu.cn) * * GCTL is degributed under a dual licensing scheme. You can redegribute * it and/or modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation, either version 2 * of the License, or (at your option) any later version. You should have * received a copy of the GNU Lesser General Public License along with this * program. If not, see . * * If the terms and conditions of the LGPL v.2. would prevent you from using * the GCTL, please consider the option to obtain a commercial license for a * fee. These licenses are offered by the GCTL's original author. As a rule, * licenses are provided "as-is", unlimited in time for a one time fee. Please * send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget * to include some description of your company and the realm of its activities. * Also add information on how to contact you by electronic and paper mail. ******************************************************/ // linear conjugate gradient solver library //#include "lcg/solver.h" // GCTL library #include "gctl/core.h" #include "gctl/geometry.h" #include "gctl/io.h" #include "gctl/utility.h" #include "gctl/optimization.h" #if defined _WINDOWS || __WIN32__ #include "io.h" // Test for file existence #define F_OK 0 #endif using namespace gctl; struct data_point { double lon, lat; std::vector vals; }; class LBSI : public gctl::lcg_solver { public: LBSI(){} virtual ~LBSI(){} virtual void LCG_Ax(const array &a, array &b); virtual void LCG_Mx(const array &a, array &b){} void Routine(std::string in_name, std::string tar_name, std::string out_name, std::string col_str, gctl::text_descriptor &desc, unsigned int kernel_size, unsigned int box_size, double epsilon); void ReadConstrainNodes(std::string filename, gctl::text_descriptor &desc); void WriteTargetNodes(std::string filename, const gctl::text_descriptor &desc); void InitTargetNodes(std::string para, gctl::text_descriptor &desc); void CalKernel(); void CalKernel(const data_point &tar_node); void UpdateTarVec(size_t idx, bool if_global = true); void set_kernel_size(unsigned int k){MatSize = k;} public: array ConsNodes; array TargNodes; std::vector LocalNodes; boxes_sph PntBoxes; double LONmin, LONmax, LATmin, LATmax; // 对输入数据进行归一化处理 size_t MatSize, ValSize, MaxCol; matrix Kernel; array Wgts; array MidPdt; array B; gctl::_1i_vector col_index; }; void LBSI::Routine(std::string in_name, std::string tar_name, std::string out_name, std::string col_str, gctl::text_descriptor &desc, unsigned int kernel_size, unsigned int box_size, double epsilon) { gctl::parse_string_to_vector(col_str, ',', col_index); if (col_index.size() < 3) { throw gctl::runtime_error("Invalid column index. From LBSI::Routine(...)"); } MaxCol = 0; for (size_t i = 0; i < col_index.size(); i++) { if (MaxCol < col_index[i]) MaxCol = col_index[i]; } ReadConstrainNodes(in_name, desc); InitTargetNodes(tar_name, desc); unsigned int k_size = kernel_size; if (k_size <= 1) { throw gctl::runtime_error("Invalid local size. From LBSI::Routine(...)"); } // Throw errors only set_lcg_message(LCG_THROW); if (k_size >= ConsNodes.size()) { GCTL_ShowWhatError("The local size is equal to or bigger than the input node's size. Reduced to the global algorithm.", GCTL_WARNING_ERROR, 0, 0, 0); k_size = ConsNodes.size(); set_kernel_size(k_size); Kernel.resize(MatSize, MatSize); Wgts.resize(MatSize); MidPdt.resize(MatSize); B.resize(MatSize); lcg_para my_para = default_lcg_para(); //my_para.max_iterations = 1000; my_para.epsilon = epsilon; set_lcg_para(my_para); CalKernel(); for (size_t s = 0; s < ValSize; s++) { UpdateTarVec(s, true); Wgts.assign(0.0); lcg(Wgts, B); double deg, sum; for (int i = 0; i < TargNodes.size(); ++i) { sum = 0.0; for (int j = 0; j < MatSize; ++j) { deg = PntBoxes.spherical_angle(TargNodes[i].lon, TargNodes[i].lat, ConsNodes[j].lon, ConsNodes[j].lat); if (deg >= GCTL_ZERO) { sum += deg*deg*(log(deg)-1.0)*Wgts[j]; } } TargNodes[i].vals[s] = sum; } } WriteTargetNodes(out_name, desc); return; } set_kernel_size(k_size); LocalNodes.resize(MatSize); Kernel.resize(MatSize, MatSize); Wgts.resize(MatSize); MidPdt.resize(MatSize); B.resize(MatSize); lcg_para my_para = default_lcg_para(); my_para.epsilon = epsilon; set_lcg_para(my_para); gctl::array lons(ConsNodes.size()); gctl::array lats(ConsNodes.size()); for (int i = 0; i < ConsNodes.size(); ++i) { lons[i] = ConsNodes[i].lon; lats[i] = ConsNodes[i].lat; } PntBoxes.init(lons, lats, ConsNodes, box_size, box_size); double deg, sum; progress_bar bar(TargNodes.size()); for (int i = 0; i < TargNodes.size(); ++i) { bar.progressed(i); Kernel.assign_all(0.0); CalKernel(TargNodes[i]); for (size_t s = 0; s < ValSize; s++) { UpdateTarVec(s, false); Wgts.assign(0.0); lcg(Wgts, B); sum = 0.0; for (int j = 0; j < MatSize; ++j) { deg = PntBoxes.spherical_angle(TargNodes[i].lon, TargNodes[i].lat, LocalNodes[j]->lon, LocalNodes[j]->lat); if (deg >= GCTL_ZERO) { sum += deg*deg*(log(deg)-1.0)*Wgts[j]; } } TargNodes[i].vals[s] = sum; } } WriteTargetNodes(out_name, desc); return; } void LBSI::ReadConstrainNodes(std::string filename, gctl::text_descriptor &desc) { gctl::_2d_vector table_data; desc.file_name_ = filename; gctl::read_text2vector2d(desc, table_data); if (table_data.size() <= 1) { throw gctl::runtime_error("Not enough constraint points. From LBSI::ReadConstrainNodes(...)"); } if (table_data[0].size() - 1 < MaxCol) { throw gctl::runtime_error("Invalid constraint point format. From LBSI::ReadConstrainNodes(...)"); } LONmin = LATmin = 1e+30; LONmax = LATmax = -1e+30; ValSize = col_index.size() - 2; ConsNodes.resize(table_data.size()); for (size_t i = 0; i < table_data.size(); ++i) { ConsNodes[i].lon = table_data[i][col_index[0]]; ConsNodes[i].lat = table_data[i][col_index[1]]; LONmin = std::min(LONmin, ConsNodes[i].lon); LONmax = std::max(LONmax, ConsNodes[i].lon); LATmin = std::min(LATmin, ConsNodes[i].lat); LATmax = std::max(LATmax, ConsNodes[i].lat); for (size_t j = 0; j < ValSize; j++) { ConsNodes[i].vals.push_back(table_data[i][col_index[2+j]]); } } for (size_t i = 0; i < ConsNodes.size(); i++) { ConsNodes[i].lon = (ConsNodes[i].lon - LONmin)/(LONmax - LONmin); ConsNodes[i].lat = (ConsNodes[i].lat - LATmin)/(LATmax - LATmin); } destroy_vector(table_data); return; } void LBSI::WriteTargetNodes(std::string filename, const gctl::text_descriptor &desc) { std::ofstream outfile; gctl::open_outfile(outfile, filename, ".txt"); for (size_t i = 0; i < desc.head_num_; i++) { outfile << desc.head_strs_[i] << "\n"; } for (size_t i = 0; i < TargNodes.size(); i++) { TargNodes[i].lon = TargNodes[i].lon*(LONmax - LONmin) + LONmin; TargNodes[i].lat = TargNodes[i].lat*(LATmax - LATmin) + LATmin; outfile << TargNodes[i].lon << " " << TargNodes[i].lat << " " << std::setprecision(12); for (size_t j = 0; j < ValSize; j++) { outfile << TargNodes[i].vals[j] << " "; } outfile << std::endl; } outfile.close(); return; } void LBSI::InitTargetNodes(std::string para, gctl::text_descriptor &desc) { // try to use the para as a file name if (access(para.c_str(), F_OK) != -1) { std::vector tmp_vec; desc.file_name_ = para; read_text2vector(desc, tmp_vec); TargNodes.resize(tmp_vec.size()); for (size_t i = 0; i < tmp_vec.size(); ++i) { TargNodes[i].lon = tmp_vec[i].x; TargNodes[i].lat = tmp_vec[i].y; TargNodes[i].lon = (TargNodes[i].lon - LONmin)/(LONmax - LONmin); TargNodes[i].lat = (TargNodes[i].lat - LATmin)/(LATmax - LATmin); } for (size_t i = 0; i < TargNodes.size(); i++) { TargNodes[i].vals.resize(ValSize); } destroy_vector(tmp_vec); return; } double dx, dy, lonmin, lonmax, latmin, latmax; parse_string_to_value(para, '/', true, lonmin, dx, lonmax, latmin, dy, latmax); size_t M = floor((latmax - latmin)/dy) + 1; size_t N = floor((lonmax - lonmin)/dx) + 1; TargNodes.resize(M*N); for (size_t j = 0; j < M; j++) { for (size_t i = 0; i < N; i++) { TargNodes[i + j*N].lon = lonmin + dx*i; TargNodes[i + j*N].lat = latmin + dy*j; TargNodes[i + j*N].lon = (TargNodes[i + j*N].lon - LONmin)/(LONmax - LONmin); TargNodes[i + j*N].lat = (TargNodes[i + j*N].lat - LATmin)/(LATmax - LATmin); } } for (size_t i = 0; i < TargNodes.size(); i++) { TargNodes[i].vals.resize(ValSize); } return; } void LBSI::CalKernel() { // 计算出所有成对的格林函数值 double deg; for (int j = 0; j < MatSize-1; ++j) { for (int k = j+1; k < MatSize; ++k) { deg = sqrt((ConsNodes[j].lon - ConsNodes[k].lon)*(ConsNodes[j].lon - ConsNodes[k].lon) + (ConsNodes[j].lat - ConsNodes[k].lat)*(ConsNodes[j].lat - ConsNodes[k].lat)); if (deg >= GCTL_ZERO) { Kernel[j][k] = Kernel[k][j] = deg*deg*(log(deg)-1.0); } } } return; } void LBSI::CalKernel(const data_point &tar_node) { // 找出距离tar_node最近的一组控制点 PntBoxes.get_by_number(tar_node.lon, tar_node.lat, MatSize, LocalNodes); // 计算出所有成对的格林函数值 double deg; for (int j = 0; j < MatSize-1; ++j) { for (int k = j+1; k < MatSize; ++k) { deg = PntBoxes.spherical_angle(LocalNodes[j]->lon, LocalNodes[j]->lat, LocalNodes[k]->lon, LocalNodes[k]->lat); if (deg >= GCTL_ZERO) { Kernel[j][k] = Kernel[k][j] = deg*deg*(log(deg)-1.0); } } } return; } void LBSI::UpdateTarVec(size_t idx, bool if_global) { if (if_global) { for (int i = 0; i < MatSize; ++i) { B[i] = 0; for (int j = 0; j < MatSize; ++j) { B[i] += Kernel[j][i] * ConsNodes[j].vals[idx]; } } } else { for (int i = 0; i < MatSize; ++i) { B[i] = 0; for (int j = 0; j < MatSize; ++j) { B[i] += Kernel[j][i] * LocalNodes[j]->vals[idx]; } } } return; } void LBSI::LCG_Ax(const array &a, array &b) { for (int i = 0; i < MatSize; ++i) { MidPdt[i] = 0; for (int j = 0; j < MatSize; ++j) { MidPdt[i] += a[j] * Kernel[i][j]; } } for (int i = 0; i < MatSize; ++i) { b[i] = 0; for (int j = 0; j < MatSize; ++j) { b[i] += MidPdt[j] * Kernel[j][i]; } } return; }