From 045bc062c5bfdac7b3a45ff8b285b95e5f94aefa Mon Sep 17 00:00:00 2001 From: Shreyas Singh Date: Mon, 13 Mar 2023 02:14:03 +0530 Subject: [PATCH] Refactored RV _print_name to long names --- pytensor/tensor/random/basic.py | 44 ++++++++++++++++----------------- 1 file changed, 22 insertions(+), 22 deletions(-) diff --git a/pytensor/tensor/random/basic.py b/pytensor/tensor/random/basic.py index b0cbfe3431..cced395471 100644 --- a/pytensor/tensor/random/basic.py +++ b/pytensor/tensor/random/basic.py @@ -87,7 +87,7 @@ class UniformRV(RandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "floatX" - _print_name = ("U", "\\operatorname{U}") + _print_name = ("Uniform", "\\operatorname{Uniform}") def __call__(self, low=0.0, high=1.0, size=None, **kwargs): r"""Draw samples from a uniform distribution. @@ -141,7 +141,7 @@ class TriangularRV(RandomVariable): ndim_supp = 0 ndims_params = [0, 0, 0] dtype = "floatX" - _print_name = ("Triang", "\\operatorname{Triang}") + _print_name = ("Triangular", "\\operatorname{Triangular}") def __call__(self, left, mode, right, size=None, **kwargs): r"""Draw samples from a triangular distribution. @@ -242,7 +242,7 @@ class NormalRV(RandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "floatX" - _print_name = ("N", "\\operatorname{N}") + _print_name = ("Normal", "\\operatorname{Normal}") def __call__(self, loc=0.0, scale=1.0, size=None, **kwargs): r"""Draw samples from a normal distribution. @@ -322,7 +322,7 @@ class HalfNormalRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "floatX" - _print_name = ("N**+", "\\operatorname{N^{+}}") + _print_name = ("HalfNormal", "\\operatorname{HalfNormal}") def __call__(self, loc=0.0, scale=1.0, size=None, **kwargs): r"""Draw samples from a half-normal distribution. @@ -387,7 +387,7 @@ class LogNormalRV(RandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "floatX" - _print_name = ("LogN", "\\operatorname{LogN}") + _print_name = ("LogNormal", "\\operatorname{LogNormal}") def __call__(self, mean=0.0, sigma=1.0, size=None, **kwargs): r"""Draw sample from a lognormal distribution. @@ -651,7 +651,7 @@ class ExponentialRV(RandomVariable): ndim_supp = 0 ndims_params = [0] dtype = "floatX" - _print_name = ("Exp", "\\operatorname{Exp}") + _print_name = ("Exponential", "\\operatorname{Exponential}") def __call__(self, scale=1.0, size=None, **kwargs): r"""Draw samples from an exponential distribution. @@ -853,7 +853,7 @@ class MvNormalRV(RandomVariable): ndim_supp = 1 ndims_params = [1, 2] dtype = "floatX" - _print_name = ("N", "\\operatorname{N}") + _print_name = ("MultivariateNormal", "\\operatorname{MultivariateNormal}") def __call__(self, mean=None, cov=None, size=None, **kwargs): r""" "Draw samples from a multivariate normal distribution. @@ -931,7 +931,7 @@ class DirichletRV(RandomVariable): ndim_supp = 1 ndims_params = [1] dtype = "floatX" - _print_name = ("Dir", "\\operatorname{Dir}") + _print_name = ("Dirichlet", "\\operatorname{Dirichlet}") def __call__(self, alphas, size=None, **kwargs): r"""Draw samples from a dirichlet distribution. @@ -996,7 +996,7 @@ class PoissonRV(RandomVariable): ndim_supp = 0 ndims_params = [0] dtype = "int64" - _print_name = ("Pois", "\\operatorname{Pois}") + _print_name = ("Poisson", "\\operatorname{Poisson}") def __call__(self, lam=1.0, size=None, **kwargs): r"""Draw samples from a poisson distribution. @@ -1041,7 +1041,7 @@ class GeometricRV(RandomVariable): ndim_supp = 0 ndims_params = [0] dtype = "int64" - _print_name = ("Geom", "\\operatorname{Geom}") + _print_name = ("Geometric", "\\operatorname{Geometric}") def __call__(self, p, size=None, **kwargs): r"""Draw samples from a geometric distribution. @@ -1083,7 +1083,7 @@ class HyperGeometricRV(RandomVariable): ndim_supp = 0 ndims_params = [0, 0, 0] dtype = "int64" - _print_name = ("HyperGeom", "\\operatorname{HyperGeom}") + _print_name = ("HyperGeometric", "\\operatorname{HyperGeometric}") def __call__(self, ngood, nbad, nsample, size=None, **kwargs): r"""Draw samples from a geometric distribution. @@ -1131,7 +1131,7 @@ class CauchyRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "floatX" - _print_name = ("C", "\\operatorname{C}") + _print_name = ("Cauchy", "\\operatorname{Cauchy}") def __call__(self, loc=0.0, scale=1.0, size=None, **kwargs): r"""Draw samples from a Cauchy distribution. @@ -1181,7 +1181,7 @@ class HalfCauchyRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "floatX" - _print_name = ("C**+", "\\operatorname{C^{+}}") + _print_name = ("HalfCauchy", "\\operatorname{HalfCauchy}") def __call__(self, loc=0.0, scale=1.0, size=None, **kwargs): r"""Draw samples from a half-Cauchy distribution. @@ -1235,7 +1235,7 @@ class InvGammaRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "floatX" - _print_name = ("InvGamma", "\\operatorname{Gamma^{-1}}") + _print_name = ("InverseGamma", "\\operatorname{InverseGamma}") def __call__(self, shape, scale, size=None, **kwargs): r"""Draw samples from an inverse-gamma distribution. @@ -1332,7 +1332,7 @@ class TruncExponentialRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0, 0] dtype = "floatX" - _print_name = ("TruncExp", "\\operatorname{TruncExp}") + _print_name = ("TruncatedExponential", "\\operatorname{TruncatedExponential}") def __call__(self, b, loc=0.0, scale=1.0, size=None, **kwargs): r"""Draw samples from a truncated exponential distribution. @@ -1446,7 +1446,7 @@ class BernoulliRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0] dtype = "int64" - _print_name = ("Bern", "\\operatorname{Bern}") + _print_name = ("Bernoulli", "\\operatorname{Bernoulli}") def __call__(self, p, size=None, **kwargs): r"""Draw samples from a Bernoulli distribution. @@ -1539,7 +1539,7 @@ class BinomialRV(RandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "int64" - _print_name = ("Binom", "\\operatorname{Binom}") + _print_name = ("Binomial", "\\operatorname{Binomial}") def __call__(self, n, p, size=None, **kwargs): r"""Draw samples from a binomial distribution. @@ -1583,7 +1583,7 @@ class NegBinomialRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0] dtype = "int64" - _print_name = ("NB", "\\operatorname{NB}") + _print_name = ("NegativeBinomial", "\\operatorname{NegativeBinomial}") def __call__(self, n, p, size=None, **kwargs): r"""Draw samples from a negative binomial distribution. @@ -1638,7 +1638,7 @@ class BetaBinomialRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0, 0] dtype = "int64" - _print_name = ("BetaBinom", "\\operatorname{BetaBinom}") + _print_name = ("BetaBinomial", "\\operatorname{BetaBinomial}") def __call__(self, n, a, b, size=None, **kwargs): r"""Draw samples from a beta-binomial distribution. @@ -1689,7 +1689,7 @@ class GenGammaRV(ScipyRandomVariable): ndim_supp = 0 ndims_params = [0, 0, 0] dtype = "floatX" - _print_name = ("GG", "\\operatorname{GG}") + _print_name = ("GeneralizedGamma", "\\operatorname{GeneralizedGamma}") def __call__(self, alpha=1.0, p=1.0, lambd=1.0, size=None, **kwargs): r"""Draw samples from a generalized gamma distribution. @@ -1751,7 +1751,7 @@ class MultinomialRV(RandomVariable): ndim_supp = 1 ndims_params = [0, 1] dtype = "int64" - _print_name = ("MN", "\\operatorname{MN}") + _print_name = ("Multinomial", "\\operatorname{Multinomial}") def __call__(self, n, p, size=None, **kwargs): r"""Draw samples from a discrete multinomial distribution. @@ -1823,7 +1823,7 @@ class CategoricalRV(RandomVariable): ndim_supp = 0 ndims_params = [1] dtype = "int64" - _print_name = ("Cat", "\\operatorname{Cat}") + _print_name = ("Categorical", "\\operatorname{Categorical}") def __call__(self, p, size=None, **kwargs): r"""Draw samples from a discrete categorical distribution.