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# komasaru/calc.cpp

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C++ source code to compute multiple regression equations.(2d)
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 #include "calc.hpp" #include #include #include #include /** * @brief 重回帰式（説明変数2個; 2次多項式モデル）の計算 * * @param[ref] a (double) * @param[ref] b (double) * @param[ref] c (double) * @param[ref] d (double) * @param[ref] e (double) * @param[ref] f (double) * @return 真偽(bool) * @retval true 成功 * @retval false 失敗 */ bool Calc::reg_multi_2e_2d( double& a, double& b, double& c, double& d, double& e, double& f ) { unsigned int i; // loop インデックス double s_x1 = 0.0; // sum(x1 ) double s_x1x1 = 0.0; // sum(x1 * x1) double s_x1x2 = 0.0; // sum(x1 * x2) double s_x1x3 = 0.0; // sum(x1 * x3) double s_x1x4 = 0.0; // sum(x1 * x4) double s_x1x5 = 0.0; // sum(x1 * x5) double s_x1y = 0.0; // sum(x1 * y ) double s_x2 = 0.0; // sum(x2 ) double s_x2x2 = 0.0; // sum(x2 * x2) double s_x2x3 = 0.0; // sum(x2 * x3) double s_x2x4 = 0.0; // sum(x2 * x4) double s_x2x5 = 0.0; // sum(x2 * x5) double s_x2y = 0.0; // sum(x2 * y ) double s_x3 = 0.0; // sum(x3 ) double s_x3x3 = 0.0; // sum(x3 * x3) double s_x3x4 = 0.0; // sum(x3 * x4) double s_x3x5 = 0.0; // sum(x3 * x5) double s_x3y = 0.0; // sum(x3 * y ) double s_x4 = 0.0; // sum(x4 ) double s_x4x4 = 0.0; // sum(x4 * x4) double s_x4x5 = 0.0; // sum(x4 * x5) double s_x4y = 0.0; // sum(x4 * y ) double s_x5 = 0.0; // sum(x5 ) double s_x5x5 = 0.0; // sum(x5 * x5) double s_x5y = 0.0; // sum(x5 * y ) double s_y = 0.0; // sum(y ) double x1 = 0.0; // x1 計算用 double x2 = 0.0; // x2 計算用 double x3 = 0.0; // x3 計算用 double x4 = 0.0; // x4 計算用 double x5 = 0.0; // x5 計算用 double y = 0.0; // y 計算用 try { // データ数 cnt = data.size(); // sum(x1), sum(x1 * x1), sum(x1 * x2), ... for (i = 0; i < cnt; i++) { x1 = data[i][0]; x2 = data[i][1]; x3 = x1 * x2; x4 = x1 * x1; x5 = x2 * x2; y = data[i][2]; s_x1 += x1; s_x1x1 += x1 * x1; s_x1x2 += x1 * x2; s_x1x3 += x1 * x3; s_x1x4 += x1 * x4; s_x1x5 += x1 * x5; s_x1y += x1 * y; s_x2 += x2; s_x2x2 += x2 * x2; s_x2x3 += x2 * x3; s_x2x4 += x2 * x4; s_x2x5 += x2 * x5; s_x2y += x2 * y; s_x3 += x3; s_x3x3 += x3 * x3; s_x3x4 += x3 * x4; s_x3x5 += x3 * x5; s_x3y += x3 * y; s_x4 += x4; s_x4x4 += x4 * x4; s_x4x5 += x4 * x5; s_x4y += x4 * y; s_x5 += x5; s_x5x5 += x5 * x5; s_x5y += x5 * y; s_y += y; } // 行列1行目 mtx.push_back({(double)cnt, s_x1, s_x2, s_x3, s_x4, s_x5, s_y}); // 行列2行目 mtx.push_back({mtx[0][1], s_x1x1, s_x1x2, s_x1x3, s_x1x4, s_x1x5, s_x1y}); // 行列3行目 mtx.push_back({mtx[0][2], mtx[1][2], s_x2x2, s_x2x3, s_x2x4, s_x2x5, s_x2y}); // 行列4行目 mtx.push_back({mtx[0][3], mtx[1][3], mtx[2][3], s_x3x3, s_x3x4, s_x3x5, s_x3y}); // 行列5行目 mtx.push_back({mtx[0][4], mtx[1][4], mtx[2][4], mtx[3][4], s_x4x4, s_x4x5, s_x4y}); // 行列6行目 mtx.push_back({mtx[0][5], mtx[1][5], mtx[2][5], mtx[3][5], mtx[4][5], s_x5x5, s_x5y}); // 計算（ガウスの消去法） if (!solve_ge(mtx)) { std::cout << "[ERROR] Failed to solve by the Gauss-Ellimination method!" << std::endl; return false; } // b0, ..., b5 a = mtx[0][6]; b = mtx[1][6]; c = mtx[2][6]; d = mtx[3][6]; e = mtx[4][6]; f = mtx[5][6]; } catch (...) { return false; // 計算失敗 } return true; // 計算成功 } /** * @brief ガウスの消去法 * * @param[ref] 行列（配列） mtx (double) * @return 真偽(bool) * @retval true 成功 * @retval false 失敗 */ bool Calc::solve_ge(std::vector>& mtx) { int i; // loop インデックス int j; // loop インデックス int k; // loop インデックス int n; // 元（行）の数 double d; // 計算用 try { n = (int)mtx.size(); // 前進消去 for (k = 0; k < n - 1; k++) { for (i = k + 1; i < n; i++) { d = mtx[i][k] / mtx[k][k]; for (j = k + 1; j <= n; j++) mtx[i][j] -= mtx[k][j] * d; } } // 後退代入 for (i = n - 1; i >= 0; i--) { d = mtx[i][n]; for (j = i + 1; j < n; j++) d -= mtx[i][j] * mtx[j][n]; mtx[i][n] = d / mtx[i][i]; } } catch (...) { return false; // 計算失敗 } return true; // 計算成功 }
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 #ifndef REGRESSION_MULTI_2E_2D_CALC_HPP_ #define REGRESSION_MULTI_2E_2D_CALC_HPP_ #include class Calc { std::vector> data; // 元データ std::vector> mtx; // 計算用行列 bool solve_ge(std::vector>&); // ガウスの消去法 public: Calc(std::vector>& data) : data(data) {} unsigned int cnt; // データ件数 bool reg_multi_2e_2d(double&, double&, double&, double&, double&, double&); // 重回帰式（説明変数2個; 2次多項式モデル）の計算 }; #endif
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 #include "file.hpp" #include #include #include #include bool File::get_text(std::vector>& data) { try { // ファイル OPEN std::ifstream ifs(f_data); if (!ifs.is_open()) return false; // 読み込み失敗 // ファイル READ std::string buf; // 1行分バッファ while (getline(ifs, buf)) { std::vector rec; // 1行分ベクタ std::istringstream iss(buf); // 文字列ストリーム std::string field; // 1列分文字列 // 1行分文字列を1行分ベクタに追加 double x, y, z; while (iss >> x >> y >> z) { rec.push_back(x); rec.push_back(y); rec.push_back(z); } // １行分ベクタを data ベクタに追加 if (rec.size() != 0) data.push_back(rec); } return true; } catch (...) { std::cerr << "EXCEPTION!" << std::endl; return false; } return true; // 読み込み成功 }
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 #ifndef REGRESSION_MULTI_2E_2D_FILE_HPP_ #define REGRESSION_MULTI_2E_2D_FILE_HPP_ #include #include #include class File { std::string f_data; public: File(std::string f_data) : f_data(f_data) {} bool get_text(std::vector>&); }; #endif
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 /*********************************************************** 重回帰式計算（説明（独立）変数2個、2次多項式モデル） * y = b0 + b1x1 + b2x2 + b3x1x2 + b4x1^2 + b5x2^2 * y = b0 + b1x1 + b2x2 + b3x3 + b4x4 + b5x5 (x3 = x1x2, x4 = x1^2, x5 = x2^2) ということ。 DATE AUTHOR VERSION 2020.07.15 mk-mode.com 1.00 新規作成 Copyright(C) 2020 mk-mode.com All Rights Reserved. ***********************************************************/ #include "calc.hpp" #include "file.hpp" #include // for EXIT_XXXX #include // for setprecision #include #include #include int main(int argc, char* argv[]) { std::string f_data; // データファイル名 std::vector> data; // データ配列 std::size_t i; // loop インデックス double a; // 定数 b0 double b; // 係数 b1 double c; // 係数 b2 double d; // 係数 b3 double e; // 係数 b4 double f; // 係数 b5 try { // コマンドライン引数のチェック if (argc != 2) { std::cerr << "[ERROR] Number of arguments is wrong!\n" << "[USAGE] ./regression_multi_2e_2d " << std::endl; return EXIT_FAILURE; } // ファイル名取得 f_data = argv[1]; // データ取得 File file(f_data); if (!file.get_text(data)) { std::cout << "[ERROR] Failed to read the file!" << std::endl; return EXIT_FAILURE; } // データ一覧出力 std::cout << std::fixed << std::setprecision(4); std::cout << "説明変数 X 説明変数 Y 目的変数 Z" << std::endl; for (i = 0; i < data.size(); i++) std::cout << std::setw(10) << std::right << data[i][0] << " " << std::setw(10) << std::right << data[i][1] << " " << std::setw(10) << std::right << data[i][2] << std::endl; // 計算 Calc calc(data); if (!calc.reg_multi_2e_2d(a, b, c, d, e, f)) { std::cout << "[ERROR] Failed to calculate!" << std::endl; return EXIT_FAILURE; } // 結果出力 std::cout << std::fixed << std::setprecision(8); std::cout << "---\n" << "b0 = " << std::setw(16) << std::right << a << "\n" << "b1 = " << std::setw(16) << std::right << b << "\n" << "b2 = " << std::setw(16) << std::right << c << "\n" << "b3 = " << std::setw(16) << std::right << d << "\n" << "b4 = " << std::setw(16) << std::right << e << "\n" << "b5 = " << std::setw(16) << std::right << f << std::endl; } catch (...) { std::cerr << "EXCEPTION!" << std::endl; return EXIT_FAILURE; } return EXIT_SUCCESS; }
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