enh(stan) updated with improved coverage of language keywords and patterns.

AUTHORS.en.txt

@@ -264,3 +264,4 @@ Contributors:
 - Harmon <Harmon.Public@gmail.com>
 - Eric Bailey <eric.w.bailey@gmail.com>
 - Gustavo Costa <gusbemacbe@gmail.com>
+- Jeffrey Arnold <jeffrey.arnold@gmail.com>

CHANGES.md

@@ -28,6 +28,7 @@ Improvements:
 - *PHP*: Added alias for php7, by [Vijaya Chandran Mani][]
 - *C++* string handling, by [David Benjamin][]
 - *Swift* Add `@objcMembers` to `@attributes`, by [Berk Çebi][]
+- *Stan* updated with improved coverage of language keywords and patterns.
 
 [Ahmad Awais]: https://github.com/ahmadawais
 [Arctic Ice Studio]: https://github.com/arcticicestudio
@@ -45,6 +46,7 @@ Improvements:
 [John Foster]: https://github.com/jf990
 [David Benjamin]: https://github.com/davidben
 [Berk Çebi]: https://github.com/berkcebi
+[Jeffrey Arnold]: https://github.com/jrnold
 
 ## Version 9.12.0
 

docs/css-classes-reference.rst

@@ -408,7 +408,7 @@ Language names and aliases
 +-------------------------+---------------------------------------------------+
 | Smalltalk               | smalltalk, st                                     |
 +-------------------------+---------------------------------------------------+
-| Stan                    | stan                                              |
+| Stan                    | stan, stanfuncs                                              |
 +-------------------------+---------------------------------------------------+
 | Stata                   | stata                                             |
 +-------------------------+---------------------------------------------------+

src/languages/stan.js

@@ -1,89 +1,227 @@
 /*
 Language: Stan
 Author: Brendan Rocks <rocks.brendan@gmail.com>
- Category: scientific
+Contributors: Jeffrey B. Arnold <jeffrey.arnold@gmail.com>
+Category: scientific
 Description: The Stan probabilistic programming language (http://mc-stan.org/).
 */
 
-function(hljs) {
+function (hljs) {
+  // variable names cannot conflict with block identifiers
+  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 {
+    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
       }
     ]
-  };
+  }
 }