knowledgebase_law/node_modules/.vite/deps/chunk-SLBUMATW.js

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2025-04-11 23:47:09 +08:00
import {
__commonJS
} from "./chunk-2TUXWMP5.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 {
require_stan
};
//# sourceMappingURL=chunk-SLBUMATW.js.map