29{
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}