| 26 | |
| 27 | template <typename T> |
| 28 | void linear_least_squares() |
| 29 | { |
| 30 | typedef exprtk::symbol_table<T> symbol_table_t; |
| 31 | typedef exprtk::expression<T> expression_t; |
| 32 | typedef exprtk::parser<T> parser_t; |
| 33 | |
| 34 | const std::string linear_least_squares_program = |
| 35 | " if (x[] == y[]) " |
| 36 | " { " |
| 37 | " beta := (sum(x * y) - sum(x) * sum(y) / x[]) / " |
| 38 | " (sum(x^2) - sum(x)^2 / x[]); " |
| 39 | " " |
| 40 | " alpha := avg(y) - beta * avg(x); " |
| 41 | " " |
| 42 | " rmse := sqrt(sum((beta * x + alpha - y)^2) / y[]); " |
| 43 | " } " |
| 44 | " else " |
| 45 | " { " |
| 46 | " alpha := null; " |
| 47 | " beta := null; " |
| 48 | " rmse := null; " |
| 49 | " } "; |
| 50 | |
| 51 | T x[] = {T( 1), T( 2), T(3), T( 4), T( 5), T(6), T( 7), T( 8), T( 9), T(10)}; |
| 52 | T y[] = {T(8.7), T(6.8), T(6), T(5.6), T(3.8), T(3), T(2.4), T(1.7), T(0.4), T(-1)}; |
| 53 | |
| 54 | T alpha = T(0); |
| 55 | T beta = T(0); |
| 56 | T rmse = T(0); |
| 57 | |
| 58 | symbol_table_t symbol_table; |
| 59 | symbol_table.add_variable("alpha", alpha); |
| 60 | symbol_table.add_variable("beta" , beta ); |
| 61 | symbol_table.add_variable("rmse" , rmse ); |
| 62 | symbol_table.add_vector ("x" , x ); |
| 63 | symbol_table.add_vector ("y" , y ); |
| 64 | |
| 65 | expression_t expression; |
| 66 | expression.register_symbol_table(symbol_table); |
| 67 | |
| 68 | parser_t parser; |
| 69 | parser.compile(linear_least_squares_program,expression); |
| 70 | |
| 71 | expression.value(); |
| 72 | |
| 73 | printf("alpha: %15.12f\n", alpha); |
| 74 | printf("beta: %15.12f\n", beta ); |
| 75 | printf("rmse: %15.12f\n", rmse ); |
| 76 | printf("y = %15.12fx + %15.12f\n", beta, alpha); |
| 77 | } |
| 78 | |
| 79 | int main() |
| 80 | { |