/* Stan Highlighting Example This file contains a syntatically correct but nonsensical Stan program that includes almost every feature of the language needed to validate syntax highlighters. It will compile (as of Stan 2.17.1), but it does nothing useful. Author: Jeffrey Arnold Copyright: Jeffrey Arnold (2018) License: MIT */ // line comment # deprecated line comment functions { #include stuff.stan #include "morestuff.stan" #include 'moststuff.stan' #include // declarations void oof(real x); // definitions // return types void oof(real x) { print("print ", x); } /* @param x A number @return x + 1 */ real foo(real x) { return x; } int bar(int x) { return x; } vector baz(vector x) { return x; } row_vector qux(row_vector x) { return x; } matrix quux(matrix x) { return x; } // numbers of arguments void corge() { print("no parameters"); } void grault(int a, real b, vector c, row_vector d, matrix f) { print("many parameters"); } void garply(real a, real[] b, real[,] c, real[,,] d) { print("array arguments"); } // array return types int[] waldo(int[] x) { return x; } int[,] fred(int[,] x) { return x; } int[,,] plough(int[,,] x) { return x; } // data only function argument real plugh(data real x) { return x; } // ode function real[] ode_func(real a, real[] b, real[] c, real[] d, int[] e) { return b; } } data { // non-int variable types int x_int; real x_real; real y_real; vector[1] x_vector; ordered[1] x_ordered; positive_ordered[1] x_positive_ordered; simplex[1] x_simplex; unit_vector[1] x_unit_vector; row_vector[1] x_row_vector; matrix[1, 1] x_matrix; cholesky_factor_corr[2] x_cholesky_factor_corr; cholesky_factor_cov[2] x_cholesky_factor_cov; cholesky_factor_cov[2, 3] x_cholesky_factor_cov_2; corr_matrix[2] x_corr_matrix; cov_matrix[2] x_cov_matrix; // range constraints real alpha; real bravo; real charlie; // arrays int echo[1]; int foxtrot[1, 1]; int golf[1, 1, 1]; // identifier with all valid letters real abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_0123456789; // hard pattern real charlie)> ranger; // identifier patterns real a; real a3; real a_3; real Sigma; real my_cpp_style_variable; real myCamelCaseVariable; real abcdefghijklmnojk; // names beginning with keywords real iffffff; real whilest; // name ending with truncation real fooT; // new array syntax array [N] real foo_new; } transformed data { // declaration and assignment int india = 1; real romeo = 1.0; row_vector[2] victor = [1, 2]; matrix[2, 2] mike = [[1, 2], [3, 4]]; real sierra[2] = {1., 2.}; complex zulu = 3+4.1i; } parameters { real hotel; real alpha; } transformed parameters { real juliette; juliette = hotel * 2.; } model { real x; int k; vector[2] y = [1., 1.]'; matrix[2, 2] A = [[1., 1.], [1., 1.]]; real odeout[2, 2]; real algout[2, 2]; // if else statements if (x_real < 0) x = 0.; if (x_real < 0) { x = 0.; } if (x_real < 0) x = 0.; else x = 1.; if (x_real < 0) { x = 0.; } else { x = 1.; } if (x_real < 0) x = 0.; else if (x_real > 1) x = 1.; else x = 0.5; if (x_real < 0) { x = 0.; } else if (x_real > 1) { x = 1.; } else { x = 0.5; } // for loops for (i in 1:5) { print("i = ", i); } // for (j in echo) { // print("j = ", j); // } // while loop while (1) { break; continue; } // reject statement reject("reject statment ", x_real); // print statement print("print statement ", x_real); print("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789_~@#$%^&*`'-+={}[].,;: "); // increment log probability statements; target += 1.; // valid integer literals k = 0; k = 1; k = -1; k = 256; k = -127098; k = 007; // valid real literals x = 0.0; x = 1.0; x = 3.14; x = 003.14; x = -217.9387; x = 0.123; x = .123; x = 1.; x = -0.123; x = -.123; x = -1.; x = 12e34; x = 12E34; x = 12.e34; x = 12.E34; x = 12.0e34; x = 12.0E34; x = .1e34; x = .1E34; x = -12e34; x = -12E34; x = -12.e34; x = -12.E34; x = -12.0e34; x = -12.0E34; x = -.1e34; x = -.1E34; x = 12e-34; x = 12E-34; x = 12.e-34; x = 12.E-34; x = 12.0e-34; x = 12.0E-34; x = .1e-34; x = .1E-34; x = -12e-34; x = -12E-34; x = -12.e-34; x = -12.E-34; x = -12.0e-34; x = -12.0E-34; x = -.1e-34; x = -.1E-34; x = 12e+34; x = 12E+34; x = 12.e+34; x = 12.E+34; x = 12.0e+34; x = 12.0E+34; x = .1e+34; x = .1E+34; x = -12e+34; x = -12E+34; x = -12.e+34; x = -12.E+34; x = -12.0e+34; x = -12.0E+34; x = -.1e+34; x = -.1E+34; // imaginary literals complex z = 3 + 3i; z = 2.3i; z = 3.4e10i; z = 0i; // assignment statements x = 1; x += 1.; x -= 1.; x *= 1.; x /= 1.; y .*= x_vector; y ./= x_vector; // operators x = x_real && 1; x = x_real || 1; x = x_real < 1.; x = x_real <= 1.; x = x_real > 1.; x = x_real >= 1.; x = x_real + 1.; x = x_real - 1.; x = x_real * 1.; x = x_real / 1.; x = x_real ^ 2.; x = x_real % 2; x = !x_real; x = +x_real; x = -x_real; x = x_int ? x_real : 0.; y = x_row_vector'; y = x_matrix \ x_vector; y = x_vector .* x_vector; y = x_vector ./ x_vector; // parenthized expression x = (x_real + x_real); // block statement { real z; z = 1.; } profile("profile-test") { real z; z = 1.; } // built-in functions x = log(1.); x = exp(1.); // non-built-in function x = foo(1.); // constants and nullary functions x = machine_precision(); x = pi(); x = e(); x = sqrt2(); x = log2(); x = log10(); // special values x = not_a_number(); x = positive_infinity(); x = negative_infinity(); x = machine_precision(); // log probability x = target(); // sampling statement x_real ~ normal(0., 1.); // truncation x_real ~ normal(0., 1.) T[-1., 1.]; x_real ~ normal(0., 1.) T[, 1.]; x_real ~ normal(0., 1.) T[-1., ]; x_real ~ normal(0., 1.) T[ , ]; // transformation on lhs of sampling log(x_real) ~ normal(0., 1.); // lhs indexes y[1] = 1.; A[1, 2] = 1.; A[1][2] = 1.; // special functions odeout = integrate_ode(ode_func, {1.}, x_real, {1.}, {1.}, {1.}, {0}); odeout = integrate_ode_bdf(ode_func, {1.}, x_real, {1.}, {1.}, {1.}, {0}, x_real, x_real, x_int); odeout = integrate_ode_rk45(ode_func, {1.}, x_real, {1.}, {1.}, {1.}, {0}, x_real, x_real, x_int); // algout = algebra_solver(algebra_func, x_vector, x_vector, {1.}, {0}); // distribution functions x = normal_lpdf(0.5 | 0., 1.); x = normal_cdf(0.5, 0., 1.); x = normal_lcdf(0.5 | 0., 1.); x = normal_lccdf(0.5 | 0., 1.); x = binomial_lpmf(1 | 2, 0.5); // deprecated features foo <- 1; increment_log_prob(0.0); y_hat = integrate_ode(sho, y0, t0, ts, theta, x_r, x_i); x = get_lp(); x = multiply_log(1.0, 1.0); x = binomial_coefficient_log(1.0, 1.0); // deprecated distribution functions versions x = normal_log(0.5, 0.0, 1.0); x = normal_cdf_log(0.5, 0.0, 1.0); x = normal_ccdf_log(0.5, 0.0, 1.0); } generated quantities { real Y; // rng function Y = normal_rng(0., 1.); tuple(real, int) tupl = (1.5, 2); complex_matrix C_mike = mike; }