import {
  __commonJS
} from "/build/_shared/chunk-PNG5AS42.js";

// ../../node_modules/highlight.js/lib/languages/stan.js
var require_stan = __commonJS({
  "../../node_modules/highlight.js/lib/languages/stan.js"(exports, module) {
    function stan(hljs) {
      const BLOCKS = [
        "functions",
        "model",
        "data",
        "parameters",
        "quantities",
        "transformed",
        "generated"
      ];
      const STATEMENTS = [
        "for",
        "in",
        "if",
        "else",
        "while",
        "break",
        "continue",
        "return"
      ];
      const SPECIAL_FUNCTIONS = [
        "print",
        "reject",
        "increment_log_prob|10",
        "integrate_ode|10",
        "integrate_ode_rk45|10",
        "integrate_ode_bdf|10",
        "algebra_solver"
      ];
      const VAR_TYPES = [
        "int",
        "real",
        "vector",
        "ordered",
        "positive_ordered",
        "simplex",
        "unit_vector",
        "row_vector",
        "matrix",
        "cholesky_factor_corr|10",
        "cholesky_factor_cov|10",
        "corr_matrix|10",
        "cov_matrix|10",
        "void"
      ];
      const FUNCTIONS = [
        "Phi",
        "Phi_approx",
        "abs",
        "acos",
        "acosh",
        "algebra_solver",
        "append_array",
        "append_col",
        "append_row",
        "asin",
        "asinh",
        "atan",
        "atan2",
        "atanh",
        "bernoulli_cdf",
        "bernoulli_lccdf",
        "bernoulli_lcdf",
        "bernoulli_logit_lpmf",
        "bernoulli_logit_rng",
        "bernoulli_lpmf",
        "bernoulli_rng",
        "bessel_first_kind",
        "bessel_second_kind",
        "beta_binomial_cdf",
        "beta_binomial_lccdf",
        "beta_binomial_lcdf",
        "beta_binomial_lpmf",
        "beta_binomial_rng",
        "beta_cdf",
        "beta_lccdf",
        "beta_lcdf",
        "beta_lpdf",
        "beta_rng",
        "binary_log_loss",
        "binomial_cdf",
        "binomial_coefficient_log",
        "binomial_lccdf",
        "binomial_lcdf",
        "binomial_logit_lpmf",
        "binomial_lpmf",
        "binomial_rng",
        "block",
        "categorical_logit_lpmf",
        "categorical_logit_rng",
        "categorical_lpmf",
        "categorical_rng",
        "cauchy_cdf",
        "cauchy_lccdf",
        "cauchy_lcdf",
        "cauchy_lpdf",
        "cauchy_rng",
        "cbrt",
        "ceil",
        "chi_square_cdf",
        "chi_square_lccdf",
        "chi_square_lcdf",
        "chi_square_lpdf",
        "chi_square_rng",
        "cholesky_decompose",
        "choose",
        "col",
        "cols",
        "columns_dot_product",
        "columns_dot_self",
        "cos",
        "cosh",
        "cov_exp_quad",
        "crossprod",
        "csr_extract_u",
        "csr_extract_v",
        "csr_extract_w",
        "csr_matrix_times_vector",
        "csr_to_dense_matrix",
        "cumulative_sum",
        "determinant",
        "diag_matrix",
        "diag_post_multiply",
        "diag_pre_multiply",
        "diagonal",
        "digamma",
        "dims",
        "dirichlet_lpdf",
        "dirichlet_rng",
        "distance",
        "dot_product",
        "dot_self",
        "double_exponential_cdf",
        "double_exponential_lccdf",
        "double_exponential_lcdf",
        "double_exponential_lpdf",
        "double_exponential_rng",
        "e",
        "eigenvalues_sym",
        "eigenvectors_sym",
        "erf",
        "erfc",
        "exp",
        "exp2",
        "exp_mod_normal_cdf",
        "exp_mod_normal_lccdf",
        "exp_mod_normal_lcdf",
        "exp_mod_normal_lpdf",
        "exp_mod_normal_rng",
        "expm1",
        "exponential_cdf",
        "exponential_lccdf",
        "exponential_lcdf",
        "exponential_lpdf",
        "exponential_rng",
        "fabs",
        "falling_factorial",
        "fdim",
        "floor",
        "fma",
        "fmax",
        "fmin",
        "fmod",
        "frechet_cdf",
        "frechet_lccdf",
        "frechet_lcdf",
        "frechet_lpdf",
        "frechet_rng",
        "gamma_cdf",
        "gamma_lccdf",
        "gamma_lcdf",
        "gamma_lpdf",
        "gamma_p",
        "gamma_q",
        "gamma_rng",
        "gaussian_dlm_obs_lpdf",
        "get_lp",
        "gumbel_cdf",
        "gumbel_lccdf",
        "gumbel_lcdf",
        "gumbel_lpdf",
        "gumbel_rng",
        "head",
        "hypergeometric_lpmf",
        "hypergeometric_rng",
        "hypot",
        "inc_beta",
        "int_step",
        "integrate_ode",
        "integrate_ode_bdf",
        "integrate_ode_rk45",
        "inv",
        "inv_Phi",
        "inv_chi_square_cdf",
        "inv_chi_square_lccdf",
        "inv_chi_square_lcdf",
        "inv_chi_square_lpdf",
        "inv_chi_square_rng",
        "inv_cloglog",
        "inv_gamma_cdf",
        "inv_gamma_lccdf",
        "inv_gamma_lcdf",
        "inv_gamma_lpdf",
        "inv_gamma_rng",
        "inv_logit",
        "inv_sqrt",
        "inv_square",
        "inv_wishart_lpdf",
        "inv_wishart_rng",
        "inverse",
        "inverse_spd",
        "is_inf",
        "is_nan",
        "lbeta",
        "lchoose",
        "lgamma",
        "lkj_corr_cholesky_lpdf",
        "lkj_corr_cholesky_rng",
        "lkj_corr_lpdf",
        "lkj_corr_rng",
        "lmgamma",
        "lmultiply",
        "log",
        "log10",
        "log1m",
        "log1m_exp",
        "log1m_inv_logit",
        "log1p",
        "log1p_exp",
        "log2",
        "log_determinant",
        "log_diff_exp",
        "log_falling_factorial",
        "log_inv_logit",
        "log_mix",
        "log_rising_factorial",
        "log_softmax",
        "log_sum_exp",
        "logistic_cdf",
        "logistic_lccdf",
        "logistic_lcdf",
        "logistic_lpdf",
        "logistic_rng",
        "logit",
        "lognormal_cdf",
        "lognormal_lccdf",
        "lognormal_lcdf",
        "lognormal_lpdf",
        "lognormal_rng",
        "machine_precision",
        "matrix_exp",
        "max",
        "mdivide_left_spd",
        "mdivide_left_tri_low",
        "mdivide_right_spd",
        "mdivide_right_tri_low",
        "mean",
        "min",
        "modified_bessel_first_kind",
        "modified_bessel_second_kind",
        "multi_gp_cholesky_lpdf",
        "multi_gp_lpdf",
        "multi_normal_cholesky_lpdf",
        "multi_normal_cholesky_rng",
        "multi_normal_lpdf",
        "multi_normal_prec_lpdf",
        "multi_normal_rng",
        "multi_student_t_lpdf",
        "multi_student_t_rng",
        "multinomial_lpmf",
        "multinomial_rng",
        "multiply_log",
        "multiply_lower_tri_self_transpose",
        "neg_binomial_2_cdf",
        "neg_binomial_2_lccdf",
        "neg_binomial_2_lcdf",
        "neg_binomial_2_log_lpmf",
        "neg_binomial_2_log_rng",
        "neg_binomial_2_lpmf",
        "neg_binomial_2_rng",
        "neg_binomial_cdf",
        "neg_binomial_lccdf",
        "neg_binomial_lcdf",
        "neg_binomial_lpmf",
        "neg_binomial_rng",
        "negative_infinity",
        "normal_cdf",
        "normal_lccdf",
        "normal_lcdf",
        "normal_lpdf",
        "normal_rng",
        "not_a_number",
        "num_elements",
        "ordered_logistic_lpmf",
        "ordered_logistic_rng",
        "owens_t",
        "pareto_cdf",
        "pareto_lccdf",
        "pareto_lcdf",
        "pareto_lpdf",
        "pareto_rng",
        "pareto_type_2_cdf",
        "pareto_type_2_lccdf",
        "pareto_type_2_lcdf",
        "pareto_type_2_lpdf",
        "pareto_type_2_rng",
        "pi",
        "poisson_cdf",
        "poisson_lccdf",
        "poisson_lcdf",
        "poisson_log_lpmf",
        "poisson_log_rng",
        "poisson_lpmf",
        "poisson_rng",
        "positive_infinity",
        "pow",
        "print",
        "prod",
        "qr_Q",
        "qr_R",
        "quad_form",
        "quad_form_diag",
        "quad_form_sym",
        "rank",
        "rayleigh_cdf",
        "rayleigh_lccdf",
        "rayleigh_lcdf",
        "rayleigh_lpdf",
        "rayleigh_rng",
        "reject",
        "rep_array",
        "rep_matrix",
        "rep_row_vector",
        "rep_vector",
        "rising_factorial",
        "round",
        "row",
        "rows",
        "rows_dot_product",
        "rows_dot_self",
        "scaled_inv_chi_square_cdf",
        "scaled_inv_chi_square_lccdf",
        "scaled_inv_chi_square_lcdf",
        "scaled_inv_chi_square_lpdf",
        "scaled_inv_chi_square_rng",
        "sd",
        "segment",
        "sin",
        "singular_values",
        "sinh",
        "size",
        "skew_normal_cdf",
        "skew_normal_lccdf",
        "skew_normal_lcdf",
        "skew_normal_lpdf",
        "skew_normal_rng",
        "softmax",
        "sort_asc",
        "sort_desc",
        "sort_indices_asc",
        "sort_indices_desc",
        "sqrt",
        "sqrt2",
        "square",
        "squared_distance",
        "step",
        "student_t_cdf",
        "student_t_lccdf",
        "student_t_lcdf",
        "student_t_lpdf",
        "student_t_rng",
        "sub_col",
        "sub_row",
        "sum",
        "tail",
        "tan",
        "tanh",
        "target",
        "tcrossprod",
        "tgamma",
        "to_array_1d",
        "to_array_2d",
        "to_matrix",
        "to_row_vector",
        "to_vector",
        "trace",
        "trace_gen_quad_form",
        "trace_quad_form",
        "trigamma",
        "trunc",
        "uniform_cdf",
        "uniform_lccdf",
        "uniform_lcdf",
        "uniform_lpdf",
        "uniform_rng",
        "variance",
        "von_mises_lpdf",
        "von_mises_rng",
        "weibull_cdf",
        "weibull_lccdf",
        "weibull_lcdf",
        "weibull_lpdf",
        "weibull_rng",
        "wiener_lpdf",
        "wishart_lpdf",
        "wishart_rng"
      ];
      const DISTRIBUTIONS = [
        "bernoulli",
        "bernoulli_logit",
        "beta",
        "beta_binomial",
        "binomial",
        "binomial_logit",
        "categorical",
        "categorical_logit",
        "cauchy",
        "chi_square",
        "dirichlet",
        "double_exponential",
        "exp_mod_normal",
        "exponential",
        "frechet",
        "gamma",
        "gaussian_dlm_obs",
        "gumbel",
        "hypergeometric",
        "inv_chi_square",
        "inv_gamma",
        "inv_wishart",
        "lkj_corr",
        "lkj_corr_cholesky",
        "logistic",
        "lognormal",
        "multi_gp",
        "multi_gp_cholesky",
        "multi_normal",
        "multi_normal_cholesky",
        "multi_normal_prec",
        "multi_student_t",
        "multinomial",
        "neg_binomial",
        "neg_binomial_2",
        "neg_binomial_2_log",
        "normal",
        "ordered_logistic",
        "pareto",
        "pareto_type_2",
        "poisson",
        "poisson_log",
        "rayleigh",
        "scaled_inv_chi_square",
        "skew_normal",
        "student_t",
        "uniform",
        "von_mises",
        "weibull",
        "wiener",
        "wishart"
      ];
      return {
        name: "Stan",
        aliases: ["stanfuncs"],
        keywords: {
          $pattern: hljs.IDENT_RE,
          title: BLOCKS,
          keyword: STATEMENTS.concat(VAR_TYPES).concat(SPECIAL_FUNCTIONS),
          built_in: FUNCTIONS
        },
        contains: [
          hljs.C_LINE_COMMENT_MODE,
          hljs.COMMENT(
            /#/,
            /$/,
            {
              relevance: 0,
              keywords: {
                "meta-keyword": "include"
              }
            }
          ),
          hljs.COMMENT(
            /\/\*/,
            /\*\//,
            {
              relevance: 0,
              // highlight doc strings mentioned in Stan reference
              contains: [
                {
                  className: "doctag",
                  begin: /@(return|param)/
                }
              ]
            }
          ),
          {
            // hack: in range constraints, lower must follow "<"
            begin: /<\s*lower\s*=/,
            keywords: "lower"
          },
          {
            // hack: in range constraints, upper must follow either , or <
            // <lower = ..., upper = ...> or <upper = ...>
            begin: /[<,]\s*upper\s*=/,
            keywords: "upper"
          },
          {
            className: "keyword",
            begin: /\btarget\s*\+=/,
            relevance: 10
          },
          {
            begin: "~\\s*(" + hljs.IDENT_RE + ")\\s*\\(",
            keywords: DISTRIBUTIONS
          },
          {
            className: "number",
            variants: [
              {
                begin: /\b\d+(?:\.\d*)?(?:[eE][+-]?\d+)?/
              },
              {
                begin: /\.\d+(?:[eE][+-]?\d+)?\b/
              }
            ],
            relevance: 0
          },
          {
            className: "string",
            begin: '"',
            end: '"',
            relevance: 0
          }
        ]
      };
    }
    module.exports = stan;
  }
});
export default require_stan();
//# sourceMappingURL=/build/_shared/stan-TKIBPMLN.js.map
