quick update on docs and setup

Author: kunwuz

docs/source/score_functions_index/bdeu.rst

@@ -8,8 +8,8 @@ Usage
 --------
 .. code-block:: python
 
-    from causallearn.score.LocalScoreFunction import local_score_bdeu
-    score = local_score_bdeu(Data, i, PAi, parameters)
+    from causallearn.score.LocalScoreFunction import local_score_BDeu
+    score = local_score_BDeu(Data, i, PAi, parameters)
 
 
 Parameters

docs/source/score_functions_index/bic.rst

@@ -8,8 +8,8 @@ Usage
 --------
 .. code-block:: python
 
-    from causallearn.score.LocalScoreFunction import local_score_bic
-    score = local_score_bic(Data, i, PAi, parameters)
+    from causallearn.score.LocalScoreFunction import local_score_BIC
+    score = local_score_BIC(Data, i, PAi, parameters)
 
 
 Parameters

docs/source/search_methods_index/Score-based causal discovery methods/GES.rst

@@ -45,9 +45,9 @@ and n_features is the number of features.
 **score_func**: The score function you would like to use, including (see :ref:`score_functions`.). Default: 'local_score_BIC'.
               - ":ref:`local_score_BIC <BIC score>`": BIC score [3]_.
               - ":ref:`local_score_BDeu <BDeu score>`": BDeu score [4]_.
-              - ":ref:`local_score_CV_general <Generalized score with cross validation>`": Generalized score with cross validation for data with single-dimensional variables [2]_.
+              - ":ref:`local_score_cv_general <Generalized score with cross validation>`": Generalized score with cross validation for data with single-dimensional variables [2]_.
               - ":ref:`local_score_marginal_general <Generalized score with marginal likelihood>`": Generalized score with marginal likelihood for data with single-dimensional variables [2]_.
-              - ":ref:`local_score_CV_multi <Generalized score with cross validation>`": Generalized score with cross validation for data with multi-dimensional variables [2]_.
+              - ":ref:`local_score_cv_multi <Generalized score with cross validation>`": Generalized score with cross validation for data with multi-dimensional variables [2]_.
               - ":ref:`local_score_marginal_multi <Generalized score with marginal likelihood>`": Generalized score with marginal likelihood for data with multi-dimensional variables [2]_.
 
 **maxP**: Allowed maximum number of parents when searching the graph. Default: None.

setup.py

@@ -28,8 +28,8 @@
     packages=setuptools.find_packages(),
     classifiers=[
         'Programming Language :: Python :: 3',
-        'License :: OSI Approved :: MIT License (MIT)',
+        'License :: OSI Approved :: MIT License',
         'Operating System :: OS Independent',
     ],
-    python_requires='>=3.6',
+    python_requires='>=3.7',
 )