configure docs

.readthedocs.yml

@@ -7,7 +7,7 @@ version: 2
 
 # Build documentation in the "docs/" directory with Sphinx
 sphinx:
-  configuration: docs/conf.py
+  configuration: docs/source/conf.py
 
 # Optionally build your docs in additional formats such as PDF and ePub
 # formats:
@@ -29,14 +29,15 @@ build:
   jobs:
     pre_build:
       # Generate the Sphinx configuration for this Jupyter Book so it builds.
-      - "jupyter-book config sphinx docs/"
+      - "jupyter-book config sphinx docs/source/"
       # Create font cache ahead of jupyter book
       - 'python -c "import matplotlib.pyplot as plt"'
       # Get the API documentation dynamically
       - "sphinx-apidoc -f -o docs/source/ src/caskade/"
 
 python:
   install:
+    - requirements: docs/requirements.txt # Path to your requirements.txt file
     - requirements: requirements.txt # Path to your requirements.txt file
     - method: pip
       path: . # Install the package itself

docs/Makefile

@@ -0,0 +1,19 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line.
+SPHINXOPTS    =
+SPHINXBUILD   = sphinx-build
+SOURCEDIR     = .
+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)" $(SPHINXOPTS) $(O)

docs/requirements.txt

@@ -0,0 +1,5 @@
+ipywidgets
+jupyter-book
+matplotlib
+sphinx
+sphinx_rtd_theme

docs/_config.yml → docs/source/_config.yml

@@ -25,7 +25,7 @@ latex:
 # Information about where the book exists on the web
 repository:
   url: https://github.com/ConnorStoneAstro/caskade # Online location of your book
-  path_to_book: docs # Optional path to your book, relative to the repository root
+  path_to_book: docs/source # Optional path to your book, relative to the repository root
   branch: main # Which branch of the repository should be used when creating links (optional)
 
 # Add GitHub buttons to your book

src/caskade/decorators.py

@@ -51,59 +51,3 @@ def wrapped(self, *args, **kwargs):
             return method(self, *args, **kwargs)
 
     return wrapped
-
-
-def apply_all_descendants(with_type=None):
-    """
-    Decorator to apply a method to all descendants of the current node.
-
-    Parameters
-    ----------
-    method: (Callable)
-        The method to be decorated.
-
-    Returns
-    -------
-    Callable
-        The decorated method.
-    """
-
-    def _apply_all_descendants(method):
-        @functools.wraps(method)
-        def wrapped(self, *args, **kwargs):
-            method(self, *args, **kwargs)
-            for node in self.descendants(with_type):
-                if hasattr(node, method.__name__):
-                    getattr(node, method.__name__)(*args, **kwargs)
-
-        return wrapped
-
-    return _apply_all_descendants
-
-
-def apply_all_ancestors(with_type=None):
-    """
-    Decorator to apply a method to all ancestors of the current node.
-
-    Parameters
-    ----------
-    method: (Callable)
-        The method to be decorated.
-
-    Returns
-    -------
-    Callable
-        The decorated method.
-    """
-
-    def _apply_all_ancestors(method):
-        @functools.wraps(method)
-        def wrapped(self, *args, **kwargs):
-            method(self, *args, **kwargs)
-            for node in self.ancestors(with_type):
-                if hasattr(node, method.__name__):
-                    getattr(node, method.__name__)(*args, **kwargs)
-
-        return wrapped
-
-    return _apply_all_ancestors

src/caskade/module.py

@@ -140,7 +140,7 @@ def fill_params(self, params: Union[Tensor, Sequence, Mapping]):
                         f"Error filling params: {e}. Filling params with a list-by-children, rather than one element per dynamic parameter is tricky, consider using alternate format."
                     )
             else:
-                raise ValueError(
+                raise AssertionError(
                     f"Input params length ({len(params)}) does not match dynamic params length ({len(self.dynamic_params)})"
                 )
         elif isinstance(params, Mapping):

tests/test_base.py

@@ -82,24 +82,31 @@ def test_topological_ordering():
     ordering = node1.topological_ordering()
     assert ordering == (node1, node3, node6)
 
-    node1.unlink("subnode2")
+    node1.unlink(node3)
     ordering = node1.topological_ordering()
     assert ordering == (node1,)
 
-
-def test_active():
+@pytest.mark.parametrize("linkbyname": [True, False], "graphviz_order": [True, False])
+def test_active(linkbyname, graphviz_order):
     node1 = Node("node1")
     node2 = Node("node2")
     node3 = Node("node3")
     node4 = Node("node4")
     node5 = Node("node5")
     node6 = Node("node6")
 
-    node1.link("subnode1", node2)
-    node1.link("subnode2", node3)
-    node2.link("subnode3", node4)
-    node2.link("subnode4", node5)
-    node3.link("subnode5", node6)
+    if linkbyname:
+        node1.link("subnode1", node2)
+        node1.link("subnode2", node3)
+        node2.link("subnode3", node4)
+        node2.link("subnode4", node5)
+        node3.link("subnode5", node6)
+    else:    
+        node1.link(node2)
+        node1.link(node3)
+        node2.link(node4)
+        node2.link(node5)
+        node3.link(node6)
 
     node1.active = True
     assert node1.active == True
@@ -125,6 +132,8 @@ def test_active():
     assert node5.active == False
     assert node6.active == False
 
+    graph = node1.graphviz(graphviz_order)
+    assert graph is not None, "should return a graphviz object"
 
 def test_test():
     test()

tests/test_forward.py

@@ -56,6 +56,10 @@ def __call__(self, d=None, e=None, live_c=None):
     assert result.shape == (2, 2)
     result = main1.testfun(1.0, params)
     assert result.shape == (2, 2)
+    # Wrong number of params, too many
+    params = params + params + params
+    with pytest.raises(AssertionError):
+        result = main1.testfun(1.0, params=params)
 
     # Tensor as params
     params = torch.cat(tuple(p.flatten() for p in params))