From bfe1da094fd8b7fabb2693c6a86d572a6610ef1f Mon Sep 17 00:00:00 2001 From: Steffen Roecker Date: Fri, 19 May 2017 10:36:55 +0200 Subject: [PATCH] Fix typos in docstrings --- pgmpy/factors/continuous/ContinuousFactor.py | 8 ++++---- pgmpy/factors/distributions/CustomDistribution.py | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pgmpy/factors/continuous/ContinuousFactor.py b/pgmpy/factors/continuous/ContinuousFactor.py index 41c9e6dcf..4db684ef8 100644 --- a/pgmpy/factors/continuous/ContinuousFactor.py +++ b/pgmpy/factors/continuous/ContinuousFactor.py @@ -29,10 +29,10 @@ def __init__(self, variables, pdf, *args, **kwargs): >>> import numpy as np >>> from scipy.special import beta >>> from pgmpy.factors.continuous import ContinuousFactor - # Two variable drichlet ditribution with alpha = (1,2) - >>> def drichlet_pdf(x, y): + # Two variable dirichlet distribution with alpha = (1,2) + >>> def dirichlet_pdf(x, y): ... return (np.power(x, 1) * np.power(y, 2)) / beta(x, y) - >>> dirichlet_factor = ContinuousFactor(['x', 'y'], drichlet_pdf) + >>> dirichlet_factor = ContinuousFactor(['x', 'y'], dirichlet_pdf) >>> dirichlet_factor.scope() ['x', 'y'] >>> dirichlet_factor.assignment(5,6) @@ -129,7 +129,7 @@ def copy(self): >>> import numpy as np >>> from scipy.special import beta >>> from pgmpy.factors.continuous import ContinuousFactor - # Two variable drichlet ditribution with alpha = (1,2) + # Two variable dirichlet distribution with alpha = (1,2) >>> def dirichlet_pdf(x, y): ... return (np.power(x, 1) * np.power(y, 2)) / beta(x, y) >>> dirichlet_factor = ContinuousFactor(['x', 'y'], dirichlet_pdf) diff --git a/pgmpy/factors/distributions/CustomDistribution.py b/pgmpy/factors/distributions/CustomDistribution.py index df0d88e51..49df343fd 100644 --- a/pgmpy/factors/distributions/CustomDistribution.py +++ b/pgmpy/factors/distributions/CustomDistribution.py @@ -131,7 +131,7 @@ def copy(self): >>> import numpy as np >>> from scipy.special import beta >>> from pgmpy.factors.distributions import CustomDistribution - # Two variable drichlet ditribution with alpha = (1,2) + # Two variable dirichlet distribution with alpha = (1,2) >>> def dirichlet_pdf(x, y): ... return (np.power(x, 1) * np.power(y, 2)) / beta(x, y) >>> dirichlet_dist = CustomDistribution(variables=['x', 'y'],