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enh(stan) updated with improved coverage of language keywords and pat…
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…terns. (#1829)

-  Almost complete rewrite. Corrected most patterns and updated function 
definitions.
-  Add "stanfuncs" as an alias

Went ahead and gave @jrnold author credit vs contributor credit for this language since this is really a ground-up rewrite.

Co-authored-by: Marcos Cáceres <marcos@marcosc.com>
Co-authored-by: Josh Goebel <me@joshgoebel.com>
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@jrnold @marcoscaceres @joshgoebel
3 people committed Dec 24, 2019
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1 change: 1 addition & 0 deletions AUTHORS.en.txt
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Expand Up @@ -271,6 +271,7 @@ Contributors:
- Harmon <Harmon.Public@gmail.com>
- Eric Bailey <eric.w.bailey@gmail.com>
- Gustavo Costa <gusbemacbe@gmail.com>
- Jeffrey Arnold <jeffrey.arnold@gmail.com>
- Antoine Boisier-Michaud <aboisiermichaud@gmail.com>
- Alejandro Isaza <al@isaza.ca>
- Laurent Voullemier <laurent.voullemier@gmail.com>
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2 changes: 2 additions & 0 deletions CHANGES.md
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Expand Up @@ -15,7 +15,9 @@ Core Changes:
Language Improvements:

- (vbnet) add nameof operator to the keywords (#2329) [Youssef Victor][]
- (stan) updated with improved coverage of language keywords and patterns. (#1829) [Jeffrey Arnold][]

[Jeffrey Arnold]: https://github.com/jrnold
[Josh Goebel]: https://github.com/yyyc514
[Youssef Victor]: https://github.com/Youssef1313

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -208,7 +208,7 @@ The table below shows the full list of supported languages (and corresponding cl
| Smali | smali | |
| Smalltalk | smalltalk, st | |
| Solidity | solidity, sol | [highlightjs-solidity](https://github.com/highlightjs/highlightjs-solidity) |
| Stan | stan | |
| Stan | stan, stanfuncs | |
| Stata | stata | |
| Structured Text | iecst, scl, stl, structured-text | [highlightjs-structured-text](https://github.com/highlightjs/highlightjs-structured-text) |
| Stylus | stylus, styl | |
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261 changes: 199 additions & 62 deletions src/languages/stan.js
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@@ -1,90 +1,227 @@
/*
Language: Stan
Description: The Stan probabilistic programming language
Author: Brendan Rocks <rocks.brendan@gmail.com>
Author: Jeffrey B. Arnold <jeffrey.arnold@gmail.com>
Website: http://mc-stan.org/
Category: scientific
*/

function(hljs) {
// variable names cannot conflict with block identifiers
var BLOCKS = [
'functions',
'model',
'data',
'parameters',
'quantities',
'transformed',
'generated'
];
var STATEMENTS = [
'for',
'in',
'if',
'else',
'while',
'break',
'continue',
'return'
];
var SPECIAL_FUNCTIONS = [
'print',
'reject',
'increment_log_prob|10',
'integrate_ode|10',
'integrate_ode_rk45|10',
'integrate_ode_bdf|10',
'algebra_solver'
];
var 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'
];
var 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'
];
var 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 {
aliases: ['stanfuncs'],
keywords: {
'title': BLOCKS.join(' '),
'keyword': STATEMENTS.concat(VAR_TYPES).concat(SPECIAL_FUNCTIONS).join(' '),
'built_in': FUNCTIONS.join(' ')
},
lexemes: hljs.IDENT_RE,
contains: [
hljs.HASH_COMMENT_MODE,
hljs.C_LINE_COMMENT_MODE,
hljs.C_BLOCK_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)/
}
]
}
),
{
begin: hljs.UNDERSCORE_IDENT_RE,
lexemes: hljs.UNDERSCORE_IDENT_RE,
keywords: {
// Stan's keywords
name:
'for in while repeat until if then else',
// Stan's probablity distributions (less beta and gamma, as commonly
// used for parameter names). So far, _log and _rng variants are not
// included
symbol:
'bernoulli bernoulli_logit binomial binomial_logit ' +
'beta_binomial hypergeometric categorical categorical_logit ' +
'ordered_logistic neg_binomial neg_binomial_2 ' +
'neg_binomial_2_log poisson poisson_log multinomial normal ' +
'exp_mod_normal skew_normal student_t cauchy double_exponential ' +
'logistic gumbel lognormal chi_square inv_chi_square ' +
'scaled_inv_chi_square exponential inv_gamma weibull frechet ' +
'rayleigh wiener pareto pareto_type_2 von_mises uniform ' +
'multi_normal multi_normal_prec multi_normal_cholesky multi_gp ' +
'multi_gp_cholesky multi_student_t gaussian_dlm_obs dirichlet ' +
'lkj_corr lkj_corr_cholesky wishart inv_wishart',
// Stan's data types
'selector-tag':
'int real vector simplex unit_vector ordered positive_ordered ' +
'row_vector matrix cholesky_factor_corr cholesky_factor_cov ' +
'corr_matrix cov_matrix',
// Stan's model blocks
title:
'functions model data parameters quantities transformed ' +
'generated',
literal:
'true false'
},
relevance: 0
// hack: in range constraints, lower must follow "<"
begin: /<\s*lower\s*=/,
keywords: 'lower'
},
// The below is all taken from the R language definition
{
// hex value
className: 'number',
begin: "0[xX][0-9a-fA-F]+[Li]?\\b",
relevance: 0
// hack: in range constraints, upper must follow either , or <
// <lower = ..., upper = ...> or <upper = ...>
begin: /[<,]*upper\s*=/,
keywords: 'upper'
},
{
// hex value
className: 'number',
begin: "0[xX][0-9a-fA-F]+[Li]?\\b",
relevance: 0
className: 'keyword',
begin: /\btarget\s*\+=/,
relevance: 10
},
{
// explicit integer
className: 'number',
begin: "\\d+(?:[eE][+\\-]?\\d*)?L\\b",
relevance: 0
},
{
// number with trailing decimal
className: 'number',
begin: "\\d+\\.(?!\\d)(?:i\\b)?",
relevance: 0
begin: '~\\s*(' + hljs.IDENT_RE + ')\\s*\\(',
keywords: DISTRIBUTIONS.join(' ')
},
{
// number
className: 'number',
begin: "\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",
variants: [
{
begin: /\b\d+(?:\.\d*)?(?:[eE][+-]?\d+)?/
},
{
begin: /\.\d+(?:[eE][+-]?\d+)?\b/
}
],
relevance: 0
},
{
// number with leading decimal
className: 'number',
begin: "\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",
className: 'string',
begin: '"',
end: '"',
relevance: 0
}
]
};
}
}

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