Update documentation build

.github/workflows/main.yaml

@@ -24,6 +24,9 @@ jobs:
       - name: Run flake8
         run: |
           tox -e flake8
+      - name: Run doc test
+        run: |
+          tox -e docs
       - name: Run test-suite
         run: |
           tox -e py

.gitignore

@@ -127,3 +127,5 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+docs/source/api/

chemicalx/data/__init__.py

@@ -2,15 +2,24 @@
 
 from class_resolver import Resolver
 
-from .batchgenerator import *  # noqa:F401,F403
-from .contextfeatureset import *  # noqa:F401,F403
-from .datasetloader import (  # noqa:F401,F403
-    DatasetLoader,
-    DrugCombDatasetLoader,
-    DrugCombDbDatasetLoader,
-)
-from .drugfeatureset import *  # noqa:F401,F403
-from .drugpairbatch import *  # noqa:F401,F403
-from .labeledtriples import *  # noqa:F401,F403
+from .batchgenerator import BatchGenerator
+from .contextfeatureset import ContextFeatureSet
+from .datasetloader import DatasetLoader, DrugCombDatasetLoader, DrugCombDbDatasetLoader
+from .drugfeatureset import DrugFeatureSet
+from .drugpairbatch import DrugPairBatch
+from .labeledtriples import LabeledTriples
+
+__all__ = [
+    "BatchGenerator",
+    "ContextFeatureSet",
+    "DrugFeatureSet",
+    "DrugPairBatch",
+    "LabeledTriples",
+    # Datasets
+    "dataset_resolver",
+    "DatasetLoader",
+    "DrugCombDatasetLoader",
+    "DrugCombDbDatasetLoader",
+]
 
 dataset_resolver = Resolver.from_subclasses(base=DatasetLoader)

chemicalx/models/__init__.py

@@ -1,19 +1,38 @@
 """Models for ChemicalX."""
 
-from class_resolver import Resolver  # noqa:F401,F403
+from class_resolver import Resolver
 
-from .base import UnimplementedModel  # noqa:F401,F403
-from .caster import *  # noqa:F401,F403
-from .deepcci import *  # noqa:F401,F403
-from .deepddi import *  # noqa:F401,F403
-from .deepdds import *  # noqa:F401,F403
-from .deepdrug import *  # noqa:F401,F403
-from .deepsynergy import *  # noqa:F401,F403
-from .epgcnds import *  # noqa:F401,F403
-from .gcnbmp import *  # noqa:F401,F403
-from .matchmaker import *  # noqa:F401,F403
-from .mhcaddi import *  # noqa:F401,F403
-from .mrgnn import *  # noqa:F401,F403
-from .ssiddi import *  # noqa:F401,F403
+from .base import UnimplementedModel
+from .caster import CASTER
+from .deepcci import DeepCCI
+from .deepddi import DeepDDI
+from .deepdds import DeepDDS
+from .deepdrug import DeepDrug
+from .deepsynergy import DeepSynergy
+from .epgcnds import EPGCNDS
+from .gcnbmp import GCNBMP
+from .matchmaker import MatchMaker
+from .mhcaddi import MHCADDI
+from .mrgnn import MRGNN
+from .ssiddi import SSIDDI
+
+__all__ = [
+    "model_resolver",
+    # Base models
+    "UnimplementedModel",
+    # Implementations
+    "CASTER",
+    "DeepCCI",
+    "DeepDDI",
+    "DeepDDS",
+    "DeepDrug",
+    "DeepSynergy",
+    "EPGCNDS",
+    "GCNBMP",
+    "MatchMaker",
+    "MHCADDI",
+    "MRGNN",
+    "SSIDDI",
+]
 
 model_resolver = Resolver.from_subclasses(base=UnimplementedModel)

chemicalx/models/deepsynergy.py

@@ -11,8 +11,8 @@
 class DeepSynergy(torch.nn.Module):
     r"""The DeepSynergy model from [deepsynergy]_.
 
-    .. [deepsynergy] `"DeepSynergy: Predicting Anti-Cancer Drug Synergy with Deep Learning"
-    <https://academic.oup.com/bioinformatics/article/34/9/1538/4747884>`_
+    .. [deepsynergy] `DeepSynergy: Predicting Anti-Cancer Drug Synergy with Deep Learning
+       <https://academic.oup.com/bioinformatics/article/34/9/1538/4747884>`_
     """
 
     def __init__(

chemicalx/models/epgcnds.py

@@ -13,9 +13,9 @@
 class EPGCNDS(torch.nn.Module):
     r"""The EPGCN-DS model from [epgcnds]_.
 
-    .. [epgcnds] `"Structure-Based Drug-Drug Interaction Detection
-    via Expressive Graph Convolutional Networks and Deep Sets"
-    <https://ojs.aaai.org/index.php/AAAI/article/view/7236>`_ paper.
+    .. [epgcnds] `Structure-Based Drug-Drug Interaction Detection
+       via Expressive Graph Convolutional Networks and Deep Sets
+       <https://ojs.aaai.org/index.php/AAAI/article/view/7236>`_
     """
 
     def __init__(self, in_channels: int, hidden_channels: int = 32, out_channels: int = 16):

docs/Makefile

@@ -1,9 +1,19 @@
-SPHINXBUILD   = sphinx-build
-SPHINXPROJ    = chemicalx
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line.
+SPHINXOPTS    =
+SPHINXBUILD   = python -m sphinx
+SPHINXPROJ    = ChemicalX
 SOURCEDIR     = source
 BUILDDIR      = build
 
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
 .PHONY: help Makefile
 
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
 %: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)"

docs/source/conf.py

@@ -13,12 +13,15 @@
     "sphinx.ext.autodoc",
     "sphinx.ext.autosummary",
     "sphinx.ext.doctest",
+    "sphinx.ext.coverage",
     "sphinx.ext.intersphinx",
     "sphinx.ext.mathjax",
     "sphinx.ext.napoleon",
     "sphinx.ext.viewcode",
     "sphinx.ext.githubpages",
     "jupyter_sphinx",
+    "sphinx_autodoc_typehints",
+    "sphinx_automodapi.automodapi",
 ]
 
 source_suffix = ".rst"
@@ -45,7 +48,7 @@
 
 html_logo = "_static/img/chemicalx.jpg"
 html_static_path = ["_static"]
-html_context = {"css_files": ["_static/css/custom.css"]}
+# html_context = {"css_files": ["_static/css/custom.css"]}
 rst_context = {"chemicalx": chemicalx}
 
 add_module_names = False

docs/source/index.rst

@@ -1,7 +1,7 @@
 :github_url: https://github.com/AstraZeneca/chemicalx
 
 ChemicalX Documentation
-===============================
+=======================
 
 
 

docs/source/modules/root.rst

@@ -1,94 +1,16 @@
 ChemicalX
-==================
-
+=========
 .. contents:: Contents
     :local:
 
-
 Data Structures and Loaders
---------------------
-
-.. autoclass:: chemicalx.data.drugfeatureset.DrugFeatureSet
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.data.labelset.LabelSet
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.data.contextfeatureset.ContextFeatureSet
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.data.datasetloader.DatasetLoader
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.data.batchgenerator.BatchGenerator
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.data.drugpairbatch.DrugPairBatch
-    :members:
-    :undoc-members:
+---------------------------
+.. automodapi:: chemicalx.data
+    :no-heading:
+    :headings: --
 
 Pair Scoring Models
 --------------------
-
-
-
-.. autoclass:: chemicalx.models.caster.CASTER
-    :members:
-    :undoc-members:
-
-
-.. autoclass:: chemicalx.models.deepcci.DeepCCI
-    :members:
-    :undoc-members:
-
-
-.. autoclass:: chemicalx.models.deepddi.DeepDDI
-    :members:
-    :undoc-members:
-
-
-.. autoclass:: chemicalx.models.deepdds.DeepDDS
-    :members:
-    :undoc-members:
-
-
-.. autoclass:: chemicalx.models.deepdrug.DeepDrug
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.models.deepsynergy.DeepSynergy
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.models.epgcnds.EPGCNDS
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.models.gcnbmp.GCNBMP
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.models.matchmaker.MatchMaker
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.models.mhcaddi.MHCADDI
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.models.mrgnn.MRGNN
-    :members:
-    :undoc-members:
-
-.. autoclass:: chemicalx.models.ssiddi.SSIDDI
-    :members:
-    :undoc-members:
-
-
-
-
+.. automodapi:: chemicalx.models
+    :no-heading:
+    :headings: --

docs/source/notes/installation.rst

@@ -1,6 +1,5 @@
 Installation
 ============
-
 The installation of ChemicalX requires the presence of certain prerequisites. These are described in great detail in the installation description of PyTorch Geometric. Please follow the instructions laid out `here <https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html>`_. You might also take a look at the `readme file <https://github.com/AstraZeneca/chemicalx>`_ of the ChemicalX repository. The torch-scatter binaries are provided for Python version <= 3.9.
 
 **PyTorch 1.10.0**
@@ -21,20 +20,18 @@ where `${CUDA}` should be replaced by either `cpu`, `cu102`, or `cu111` dependin
 
 The package itself can be installed via pip:
 
-    .. code-block:: none
+.. code-block:: shell
 
-        $ pip install chemicalx
+    $ pip install chemicalx
 
 Upgrade your outdated ChemicalX version by using:
 
-    .. code-block:: none
-
-        $ pip install chemicalx --upgrade
+.. code-block:: shell
 
+    $ pip install chemicalx --upgrade
 
 To check your current package version just simply run:
 
-    .. code-block:: none
-
-        $ pip freeze | grep chemicalx
+.. code-block:: shell
 
+    $ pip freeze | grep chemicalx

docs/source/notes/introduction.rst

@@ -2,9 +2,7 @@ Introduction by example
 =======================
 
 Overview
-=======================
---------------------------------------------------------------------------------
-
+========
 We shortly overview the fundamental concepts and features of **ChemicalX** through simple examples. These are the following:
 
 .. contents::