use mock in docs

BasisResearch · Nov 10, 2021 · f01bbef · f01bbef
1 parent e32d1f8
commit f01bbef
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Showing 4 changed files with 6 additions and 5 deletions.
diff --git a/docs/requirements.txt b/docs/requirements.txt
@@ -4,3 +4,4 @@ readthedocs-sphinx-search==0.1.0
 sphinx==4.0.3
 sphinx-gallery
 sphinx_rtd_theme==0.5.2
+mock
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -1,6 +1,6 @@
 import os
 import sys
-
+import mock
 import sphinx_rtd_theme
 
 # import pkg_resources
@@ -74,6 +74,10 @@
 #     'exclude-members': '__dict__,__module__,__weakref__',
 # }
 
+MOCK_MODULES = ['numpy', 'pandas', 'torch', 'scipy']
+for mod_name in MOCK_MODULES:
+   sys.modules[mod_name] = mock.Mock()
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]
 

diff --git a/docs/source/samplers.rst b/docs/source/samplers.rst
@@ -5,8 +5,6 @@ For most users it suffices to use the predefined Bayesian variable selection cla
 like :class:`millipede.NormalLikelihoodVariableSelector`.
 However advanced users also have the option of using the MCMC samplers directly.
 
-.. automodule:: millipede
-
 NormalLikelihoodSampler
 -----------------------
 .. autofunction:: millipede.normal.NormalLikelihoodSampler

diff --git a/docs/source/selection.rst b/docs/source/selection.rst
@@ -4,8 +4,6 @@ Bayesian Variable Selection
 Most usage cases of millipede are covered by making use of
 one of the four Bayesian variable selection methods listed below.
 
-.. automodule:: millipede
-
 NormalLikelihoodVariableSelector
 --------------------------------
 .. autofunction:: millipede.selection.NormalLikelihoodVariableSelector