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Stan\nDescription: The Stan probabilistic programming language\nAuthor: Sean Pinkney <sean.pinkney@gmail.com>\nWebsite: http://mc-stan.org/\nCategory: scientific\n*/\n\nfunction stan(hljs) {\n const regex = hljs.regex;\n // variable names cannot conflict with block identifiers\n const BLOCKS = [\n 'functions',\n 'model',\n 'data',\n 'parameters',\n 'quantities',\n 'transformed',\n 'generated'\n ];\n\n const STATEMENTS = [\n 'for',\n 'in',\n 'if',\n 'else',\n 'while',\n 'break',\n 'continue',\n 'return'\n ];\n\n const TYPES = [\n 'array',\n 'complex',\n 'int',\n 'real',\n 'vector',\n 'ordered',\n 'positive_ordered',\n 'simplex',\n 'unit_vector',\n 'row_vector',\n 'matrix',\n 'cholesky_factor_corr|10',\n 'cholesky_factor_cov|10',\n 'corr_matrix|10',\n 'cov_matrix|10',\n 'void'\n ];\n\n // to get the functions list\n // clone the [stan-docs repo](https://github.com/stan-dev/docs)\n // then cd into it and run this bash script https://gist.github.com/joshgoebel/dcd33f82d4059a907c986049893843cf\n //\n // the output files are\n // distributions_quoted.txt\n // functions_quoted.txt\n\n const FUNCTIONS = [\n 'Phi',\n 'Phi_approx',\n 'abs',\n 'acos',\n 'acosh',\n 'add_diag',\n 'algebra_solver',\n 'algebra_solver_newton',\n 'append_array',\n 'append_col',\n 'append_row',\n 'asin',\n 'asinh',\n 'atan',\n 'atan2',\n 'atanh',\n 'bessel_first_kind',\n 'bessel_second_kind',\n 'binary_log_loss',\n 'binomial_coefficient_log',\n 'block',\n 'cbrt',\n 'ceil',\n 'chol2inv',\n 'cholesky_decompose',\n 'choose',\n 'col',\n 'cols',\n 'columns_dot_product',\n 'columns_dot_self',\n 'conj',\n 'cos',\n 'cosh',\n 'cov_exp_quad',\n 'crossprod',\n 'csr_extract_u',\n 'csr_extract_v',\n 'csr_extract_w',\n 'csr_matrix_times_vector',\n 'csr_to_dense_matrix',\n 'cumulative_sum',\n 'determinant',\n 'diag_matrix',\n 'diag_post_multiply',\n 'diag_pre_multiply',\n 'diagonal',\n 'digamma',\n 'dims',\n 'distance',\n 'dot_product',\n 'dot_self',\n 'eigenvalues_sym',\n 'eigenvectors_sym',\n 'erf',\n 'erfc',\n 'exp',\n 'exp2',\n 'expm1',\n 'fabs',\n 'falling_factorial',\n 'fdim',\n 'floor',\n 'fma',\n 'fmax',\n 'fmin',\n 'fmod',\n 'gamma_p',\n 'gamma_q',\n 'generalized_inverse',\n 'get_imag',\n 'get_lp',\n 'get_real',\n 'head',\n 'hmm_hidden_state_prob',\n 'hmm_marginal',\n 'hypot',\n 'identity_matrix',\n 'inc_beta',\n 'int_step',\n 'integrate_1d',\n 'integrate_ode',\n 'integrate_ode_adams',\n 'integrate_ode_bdf',\n 'integrate_ode_rk45',\n 'inv',\n 'inv_Phi',\n 'inv_cloglog',\n 'inv_logit',\n 'inv_sqrt',\n 'inv_square',\n 'inverse',\n 'inverse_spd',\n 'is_inf',\n 'is_nan',\n 'lambert_w0',\n 'lambert_wm1',\n 'lbeta',\n 'lchoose',\n 'ldexp',\n 'lgamma',\n 'linspaced_array',\n 'linspaced_int_array',\n 'linspaced_row_vector',\n 'linspaced_vector',\n 'lmgamma',\n 'lmultiply',\n 'log',\n 'log1m',\n 'log1m_exp',\n 'log1m_inv_logit',\n 'log1p',\n 'log1p_exp',\n 'log_determinant',\n 'log_diff_exp',\n 'log_falling_factorial',\n 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'qr_thin_Q',\n 'qr_thin_R',\n 'quad_form',\n 'quad_form_diag',\n 'quad_form_sym',\n 'quantile',\n 'rank',\n 'reduce_sum',\n 'reject',\n 'rep_array',\n 'rep_matrix',\n 'rep_row_vector',\n 'rep_vector',\n 'reverse',\n 'rising_factorial',\n 'round',\n 'row',\n 'rows',\n 'rows_dot_product',\n 'rows_dot_self',\n 'scale_matrix_exp_multiply',\n 'sd',\n 'segment',\n 'sin',\n 'singular_values',\n 'sinh',\n 'size',\n 'softmax',\n 'sort_asc',\n 'sort_desc',\n 'sort_indices_asc',\n 'sort_indices_desc',\n 'sqrt',\n 'square',\n 'squared_distance',\n 'step',\n 'sub_col',\n 'sub_row',\n 'sum',\n 'svd_U',\n 'svd_V',\n 'symmetrize_from_lower_tri',\n 'tail',\n 'tan',\n 'tanh',\n 'target',\n 'tcrossprod',\n 'tgamma',\n 'to_array_1d',\n 'to_array_2d',\n 'to_complex',\n 'to_matrix',\n 'to_row_vector',\n 'to_vector',\n 'trace',\n 'trace_gen_quad_form',\n 'trace_quad_form',\n 'trigamma',\n 'trunc',\n 'uniform_simplex',\n 'variance',\n 'zeros_array',\n 'zeros_int_array',\n 'zeros_row_vector'\n ];\n\n const DISTRIBUTIONS = [\n 'bernoulli',\n 'bernoulli_logit',\n 'bernoulli_logit_glm',\n 'beta',\n 'beta_binomial',\n 'beta_proportion',\n 'binomial',\n 'binomial_logit',\n 'categorical',\n 'categorical_logit',\n 'categorical_logit_glm',\n 'cauchy',\n 'chi_square',\n 'dirichlet',\n 'discrete_range',\n 'double_exponential',\n 'exp_mod_normal',\n 'exponential',\n 'frechet',\n 'gamma',\n 'gaussian_dlm_obs',\n 'gumbel',\n 'hmm_latent',\n 'hypergeometric',\n 'inv_chi_square',\n 'inv_gamma',\n 'inv_wishart',\n 'lkj_corr',\n 'lkj_corr_cholesky',\n 'logistic',\n 'lognormal',\n 'multi_gp',\n 'multi_gp_cholesky',\n 'multi_normal',\n 'multi_normal_cholesky',\n 'multi_normal_prec',\n 'multi_student_t',\n 'multinomial',\n 'multinomial_logit',\n 'neg_binomial',\n 'neg_binomial_2',\n 'neg_binomial_2_log',\n 'neg_binomial_2_log_glm',\n 'normal',\n 'normal_id_glm',\n 'ordered_logistic',\n 'ordered_logistic_glm',\n 'ordered_probit',\n 'pareto',\n 'pareto_type_2',\n 'poisson',\n 'poisson_log',\n 'poisson_log_glm',\n 'rayleigh',\n 'scaled_inv_chi_square',\n 'skew_double_exponential',\n 'skew_normal',\n 'std_normal',\n 'student_t',\n 'uniform',\n 'von_mises',\n 'weibull',\n 'wiener',\n 'wishart'\n ];\n\n const BLOCK_COMMENT = hljs.COMMENT(\n /\\/\\*/,\n /\\*\\//,\n {\n relevance: 0,\n contains: [\n {\n scope: 'doctag',\n match: /@(return|param)/\n }\n ]\n }\n );\n\n const INCLUDE = {\n scope: 'meta',\n begin: /#include\\b/,\n end: /$/,\n contains: [\n {\n match: /[a-z][a-z-._]+/,\n scope: 'string'\n },\n hljs.C_LINE_COMMENT_MODE\n ]\n };\n\n const RANGE_CONSTRAINTS = [\n \"lower\",\n \"upper\",\n \"offset\",\n \"multiplier\"\n ];\n\n return {\n name: 'Stan',\n aliases: [ 'stanfuncs' ],\n keywords: {\n $pattern: hljs.IDENT_RE,\n title: BLOCKS,\n type: TYPES,\n keyword: STATEMENTS,\n built_in: FUNCTIONS\n },\n contains: [\n hljs.C_LINE_COMMENT_MODE,\n INCLUDE,\n hljs.HASH_COMMENT_MODE,\n BLOCK_COMMENT,\n {\n scope: 'built_in',\n match: /\\s(pi|e|sqrt2|log2|log10)(?=\\()/,\n relevance: 0\n },\n {\n match: regex.concat(/[<,]\\s*/, regex.either(...RANGE_CONSTRAINTS), /\\s*=/),\n keywords: RANGE_CONSTRAINTS\n },\n {\n scope: 'keyword',\n match: /\\btarget(?=\\s*\\+=)/,\n },\n {\n // highlights the 'T' in T[,] for only Stan language distributrions\n match: [\n /~\\s*/,\n regex.either(...DISTRIBUTIONS),\n /(?:\\(\\))/,\n /\\s*T(?=\\s*\\[)/\n ],\n scope: {\n 2: \"built_in\",\n 4: \"keyword\"\n }\n },\n {\n // highlights distributions that end with special endings\n scope: 'built_in',\n keywords: DISTRIBUTIONS,\n begin: regex.concat(/\\w*/, regex.either(...DISTRIBUTIONS), /(_lpdf|_lupdf|_lpmf|_cdf|_lcdf|_lccdf|_qf)(?=\\s*[\\(.*\\)])/)\n },\n {\n // highlights distributions after ~\n begin: [\n /~/,\n /\\s*/,\n regex.concat(regex.either(...DISTRIBUTIONS), /(?=\\s*[\\(.*\\)])/)\n ],\n scope: { 3: \"built_in\" }\n },\n {\n // highlights user defined distributions after ~\n begin: [\n /~/,\n /\\s*\\w+(?=\\s*[\\(.*\\)])/,\n '(?!.*/\\b(' + regex.either(...DISTRIBUTIONS) + ')\\b)'\n ],\n scope: { 2: \"title.function\" }\n },\n {\n // highlights user defined distributions with special endings\n scope: 'title.function',\n begin: /\\w*(_lpdf|_lupdf|_lpmf|_cdf|_lcdf|_lccdf|_qf)(?=\\s*[\\(.*\\)])/\n },\n {\n scope: 'number',\n match: regex.concat(\n // Comes from @RunDevelopment accessed 11/29/2021 at\n // https://github.com/PrismJS/prism/blob/c53ad2e65b7193ab4f03a1797506a54bbb33d5a2/components/prism-stan.js#L56\n\n // start of big noncapture group which\n // 1. gets numbers that are by themselves\n // 2. numbers that are separated by _\n // 3. numbers that are separted by .\n /(?:\\b\\d+(?:_\\d+)*(?:\\.(?:\\d+(?:_\\d+)*)?)?|\\B\\.\\d+(?:_\\d+)*)/,\n // grabs scientific notation\n // grabs complex numbers with i\n /(?:[eE][+-]?\\d+(?:_\\d+)*)?i?(?!\\w)/\n ),\n relevance: 0\n },\n {\n scope: 'string',\n begin: /\"/,\n end: /\"/\n }\n ]\n };\n}\n\nmodule.exports = stan;\n"],"names":["module","exports","hljs","regex","DISTRIBUTIONS","BLOCK_COMMENT","COMMENT","relevance","contains","scope","match","INCLUDE","begin","end","C_LINE_COMMENT_MODE","RANGE_CONSTRAINTS","name","aliases","keywords","$pattern","IDENT_RE","title","type","keyword","built_in","HASH_COMMENT_MODE","concat","either"],"sourceRoot":""} |