| /* |
| ************************************************************** |
| * C++ Mathematical Expression Toolkit Library * |
| * * |
| * Simple Example 16 * |
| * Author: Arash Partow (1999-2024) * |
| * URL: https://www.partow.net/programming/exprtk/index.html * |
| * * |
| * Copyright notice: * |
| * Free use of the Mathematical Expression Toolkit Library is * |
| * permitted under the guidelines and in accordance with the * |
| * most current version of the MIT License. * |
| * https://www.opensource.org/licenses/MIT * |
| * SPDX-License-Identifier: MIT * |
| * * |
| ************************************************************** |
| */ |
| |
| |
| #include <cstdio> |
| #include <cstdlib> |
| #include <string> |
| |
| #include "exprtk.hpp" |
| |
| |
| template <typename T> |
| void linear_least_squares() |
| { |
| typedef exprtk::symbol_table<T> symbol_table_t; |
| typedef exprtk::expression<T> expression_t; |
| typedef exprtk::parser<T> parser_t; |
| |
| const std::string linear_least_squares_program = |
| " if (x[] == y[]) " |
| " { " |
| " var mean_x := avg(x); " |
| " var mean_y := avg(y); " |
| " " |
| " beta := sum((x - mean_x) * (y - mean_y)) / " |
| " sum((x - mean_x)^2); " |
| " " |
| " alpha := mean_y - beta * mean_x; " |
| " " |
| " rmse := sqrt(sum((beta * x + alpha - y)^2) / y[]); " |
| " } " |
| " else " |
| " { " |
| " alpha := null; " |
| " beta := null; " |
| " rmse := null; " |
| " } "; |
| |
| T x[] = { T(1.0), T(2.0), T(3.0), T(4.0), T(5.0), T(6.0), T(7.0), T(8.0), T(9.0), T(10) }; |
| T y[] = { T(8.7), T(6.8), T(6.0), T(5.6), T(3.8), T(3.0), T(2.4), T(1.7), T(0.4), T(-1) }; |
| |
| T alpha = T(0); |
| T beta = T(0); |
| T rmse = T(0); |
| |
| symbol_table_t symbol_table; |
| symbol_table.add_variable("alpha", alpha); |
| symbol_table.add_variable("beta" , beta ); |
| symbol_table.add_variable("rmse" , rmse ); |
| symbol_table.add_vector ("x" , x ); |
| symbol_table.add_vector ("y" , y ); |
| |
| expression_t expression; |
| expression.register_symbol_table(symbol_table); |
| |
| parser_t parser; |
| if (!parser.compile(linear_least_squares_program,expression)) |
| { |
| printf("error: %s\n",parser.error().c_str()); |
| return; |
| } |
| |
| expression.value(); |
| |
| printf("alpha: %15.12f\n", alpha); |
| printf("beta: %15.12f\n", beta ); |
| printf("rmse: %15.12f\n", rmse ); |
| printf("y = %15.12fx + %15.12f\n", beta, alpha); |
| } |
| |
| int main() |
| { |
| linear_least_squares<double>(); |
| return 0; |
| } |