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175 lines
3.0 KiB
Python
175 lines
3.0 KiB
Python
# -*- coding: utf-8 -*-
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"""
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pygments.lexers._stan_builtins
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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This file contains the names of functions for Stan used by
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``pygments.lexers.math.StanLexer.
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:copyright: Copyright 2006-2013 by the Pygments team, see AUTHORS.
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:license: BSD, see LICENSE for details.
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"""
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CONSTANTS=[ 'e',
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'epsilon',
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'log10',
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'log2',
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'negative_epsilon',
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'negative_infinity',
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'not_a_number',
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'pi',
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'positive_infinity',
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'sqrt2']
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FUNCTIONS=[ 'Phi',
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'abs',
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'acos',
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'acosh',
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'asin',
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'asinh',
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'atan',
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'atan2',
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'atanh',
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'bernoulli_log',
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'beta_binomial_log',
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'beta_log',
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'binary_log_loss',
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'binomial_coefficient_log',
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'categorical_log',
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'cauchy_log',
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'cbrt',
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'ceil',
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'chi_square_log',
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'cholesky_decompose',
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'col',
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'cols',
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'cos',
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'cosh',
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'determinant',
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'diag_matrix',
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'diagonal',
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'dirichlet_log',
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'dot_product',
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'dot_self',
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'double_exponential_log',
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'eigenvalues',
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'eigenvalues_sym',
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'erf',
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'erfc',
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'exp',
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'exp2',
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'expm1',
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'exponential_cdf',
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'exponential_log',
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'fabs',
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'fdim',
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'floor',
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'fma',
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'fmax',
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'fmin',
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'fmod',
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'gamma_log',
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'hypergeometric_log',
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'hypot',
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'if_else',
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'int_step',
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'inv_chi_square_log',
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'inv_cloglog',
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'inv_gamma_log',
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'inv_logit',
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'inv_wishart_log',
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'inverse',
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'lbeta',
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'lgamma',
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'lkj_corr_cholesky_log',
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'lkj_corr_log',
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'lkj_cov_log',
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'lmgamma',
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'log',
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'log10',
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'log1m',
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'log1p',
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'log1p_exp',
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'log2',
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'log_sum_exp',
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'logistic_log',
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'logit',
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'lognormal_cdf',
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'lognormal_log',
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'max',
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'mean',
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'min',
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'multi_normal_cholesky_log',
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'multi_normal_log',
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'multi_student_t_log',
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'multinomial_log',
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'multiply_log',
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'multiply_lower_tri_self_transpose',
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'neg_binomial_log',
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'normal_cdf',
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'normal_log',
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'ordered_logistic_log',
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'pareto_log',
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'poisson_log',
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'pow',
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'prod',
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'round',
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'row',
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'rows',
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'scaled_inv_chi_square_log',
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'sd',
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'sin',
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'singular_values',
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'sinh',
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'softmax',
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'sqrt',
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'square',
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'step',
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'student_t_log',
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'sum',
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'tan',
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'tanh',
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'tgamma',
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'trace',
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'trunc',
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'uniform_log',
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'variance',
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'weibull_cdf',
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'weibull_log',
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'wishart_log']
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DISTRIBUTIONS=[ 'bernoulli',
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'beta',
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'beta_binomial',
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'categorical',
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'cauchy',
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'chi_square',
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'dirichlet',
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'double_exponential',
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'exponential',
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'gamma',
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'hypergeometric',
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'inv_chi_square',
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'inv_gamma',
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'inv_wishart',
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'lkj_corr',
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'lkj_corr_cholesky',
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'lkj_cov',
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'logistic',
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'lognormal',
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'multi_normal',
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'multi_normal_cholesky',
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'multi_student_t',
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'multinomial',
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'neg_binomial',
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'normal',
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'ordered_logistic',
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'pareto',
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'poisson',
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'scaled_inv_chi_square',
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'student_t',
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'uniform',
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'weibull',
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'wishart']
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