improve api page+some fixes

Author: OriolAbril

docs/_templates/autosummary/base.rst

@@ -0,0 +1,5 @@
+{{ objname | escape | underline }}
+
+.. currentmodule:: {{ module }}
+
+.. auto{{ objtype }}:: {{ objname }}

docs/_templates/autosummary/class.rst

@@ -0,0 +1,29 @@
+{{ objname | escape | underline}}
+
+.. currentmodule:: {{ module }}
+
+.. autoclass:: {{ objname }}
+
+   {% block methods %}
+   .. automethod:: __init__
+
+   {% if methods %}
+   .. rubric:: {{ _('Methods') }}
+
+   .. autosummary::
+   {% for item in methods %}
+      ~{{ name }}.{{ item }}
+   {%- endfor %}
+   {% endif %}
+   {% endblock %}
+
+   {% block attributes %}
+   {% if attributes %}
+   .. rubric:: {{ _('Attributes') }}
+
+   .. autosummary::
+   {% for item in attributes %}
+      ~{{ name }}.{{ item }}
+   {%- endfor %}
+   {% endif %}
+   {% endblock %}

docs/api_reference.rst

@@ -4,51 +4,51 @@ API Reference
 This reference provides detailed documentation for all modules, classes, and
 methods in the current release of PyMC experimental.
 
+.. currentmodule:: pymc_experimental
+.. autosummary::
+   :toctree: generated/
 
-.. toctree::
-  :maxdepth: 2
+   marginal_model.MarginalModel
+   model_builder.ModelBuilder
 
+Inference
+=========
 
-:mod:`pymc_experimental`
-=============================
+.. currentmodule:: pymc_experimental.inference
+.. autosummary::
+   :toctree: generated/
 
-.. automodule:: pymc_experimental.marginal_model
-   :members: MarginalModel
+   fit
 
-.. automodule:: pymc_experimental.model_builder
-   :members: ModelBuilder
 
+Distributions
+=============
 
-:mod:`pymc_experimental.inference`
-=============================
+.. currentmodule:: pymc_experimental.distributions
+.. autosummary::
+   :toctree: generated/
 
-.. automodule:: pymc_experimental.inference.fit
-   :members: fit
+   GenExtreme
+   histogram_utils.histogram_approximation
 
 
-:mod:`pymc_experimental.distributions`
-=============================
+Gaussian Processess
+===================
 
-.. automodule:: pymc_experimental.distributions.continuous
-   :members: GenExtreme
+.. currentmodule:: pymc_experimental.gp
+.. autosummary::
+   :toctree: generated/
 
-.. automodule:: pymc_experimental.distributions.histogram_utils
-   :members: histogram_approximation
+   latent_approx.HSGP
 
 
-:mod:`pymc_experimental.gp`
-=============================
+Utils
+=====
 
-.. automodule:: pymc_experimental.gp.latent_approx
-   :members: HSGP
+.. currentmodule:: pymc_experimental.utils
+.. autosummary::
+   :toctree: generated/
 
-
-:mod:`pymc_experimental.utils`
-=============================
-
-.. automodule:: pymc_experimental.utils.spline
-   :members: bspline_interpolation
-
-.. automodule:: pymc_experimental.utils.prior
-   :members: prior_from_idata
+   spline.bspline_interpolation
+   prior.prior_from_idata
 

docs/conf.py

@@ -56,16 +56,18 @@
 # ones.
 extensions = [
     "sphinx.ext.autodoc",
+    "sphinx.ext.autosummary",
     "sphinx.ext.viewcode",
     "sphinx.ext.napoleon",
     "sphinx.ext.mathjax",
     "nbsphinx",
+    "matplotlib.sphinxext.plot_directive",
 ]
 
 nbsphinx_execute = "never"
 
 # Add any paths that contain templates here, relative to this directory.
-# templates_path = ["_templates"]
+templates_path = ["_templates"]
 
 # The suffix(es) of source filenames.
 # You can specify multiple suffix as a list of string:
@@ -81,7 +83,7 @@
 #
 # This is also used if you do content translation via gettext catalogs.
 # Usually you set "language" from the command line for these cases.
-language = None
+# language = None
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.

pymc_experimental/distributions/continuous.py

@@ -119,13 +119,13 @@ class GenExtreme(Continuous):
 
     Parameters
     ----------
-    mu: float
+    mu : float
         Location parameter.
-    sigma: float
+    sigma : float
         Scale parameter (sigma > 0).
-    xi: float
+    xi : float
         Shape parameter
-    scipy: bool
+    scipy : bool
         Whether or not to use the Scipy interpretation of the shape parameter
         (defaults to `False`).
 

pymc_experimental/marginal_model.py

@@ -54,6 +54,7 @@ class MarginalModel(Model):
     Marginalize over a single variable
 
     .. code-block:: python
+
         import pymc as pm
         from pymc_experimental import MarginalModel