[CI] Quick fix on the docstring of ADMG, PAG algorithms typing and pyproject toml for dowhy dev dependency

.circleci/config.yml

@@ -139,12 +139,12 @@ jobs:
       - run:
           name: make linkcheck
           command: |
-            make -C doc linkcheck
+            make -C docs linkcheck
       - run:
           name: make linkcheck-grep
           when: always
           command: |
-            make -C doc linkcheck-grep
+            make -C docs linkcheck-grep
       - store_artifacts:
           path: docs/_build/linkcheck
           destination: linkcheck

docs/Makefile

@@ -130,6 +130,12 @@ latexpdfja:
 	$(MAKE) -C $(BUILDDIR)/latex all-pdf-ja
 	@echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex."
 
+linkcheck:
+	$(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck
+	@echo
+	@echo "Link check complete; look for any errors in the above output " \
+			"or in $(BUILDDIR)/linkcheck/output.txt."
+
 text:
 	$(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text
 	@echo

docs/installation.md

@@ -14,10 +14,10 @@ Installation
 
 ## Installing from source
 
-To install **pywhy-graphs** from source, first clone [the repository](https://github.com/pywhy/pywhy-graphs):
+To install **pywhy-graphs** from source, first clone [the repository](https://github.com/py-why/pywhy-graphs):
 
 
-    git clone https://github.com/pywhy/pywhy-graphs.git
+    git clone https://github.com/py-why/pywhy-graphs.git
     cd pywhy-graphs
 
 Then run installation via poetry (recommended)

pyproject.toml

@@ -40,7 +40,7 @@ numpy = "^1.23.0"
 scipy = "^1.9.0"
 networkx = { git = "https://github.com/adam2392/networkx.git", branch = 'mixededge' }
 importlib-resources = { version = "*", python = "<3.9" }
-dynetx = { version="*", optional=true }
+dynetx = { version = "*", optional = true }
 pygraphviz = { version = "*", optional = true }
 
 [tool.poetry.group.test]
@@ -50,7 +50,7 @@ poethepoet = "^0.16.0"
 pytest = "^7.1.2"
 pytest-cov = "^3.0.0"
 memory_profiler = { version = "^0.60.0" }
-causal-learn = { version="^0.1.2.8" }
+causal-learn = { version = "^0.1.2.8" }
 
 [tool.poetry.group.style]
 optional = true
@@ -80,18 +80,21 @@ sphinx-copybutton = { version = "^0.5.0" }
 sphinx-gallery = { version = "^0.11.0" }
 sphinx_rtd_theme = { version = "^1.0.0" }
 graphviz = { version = "^0.20.1" }
-dowhy = { version = "^0.8" }
 ipython = { version = "^7.4.0" }
 nbsphinx = { version = "^0.8" }
-scikit-learn = { version = "^1.1.0" }
-pandas = { version = "^1.1" }
+dowhy = { version = "^0.8" }
+scikit-learn = { version = "^1.1.0" }         # needed in dowhy's package
+pandas = { version = "^1.1" }                 # needed in dowhy's package
+joblib = { version = "^1.1.0" }               # needed in dowhy's package
+tqdm = { version = "^4.64.0" }                # needed in dowhy's package
+typing-extensions = { version = "*" }         # needed in dowhy's package 
 
 [tool.poetry.extras]
 ts = ['dynetx']
 viz = ['pygraphviz']
 
 [build-system]
-requires = ["poetry-core>=1.0.0"]
+requires = ["poetry-core>=1.0.8"]
 build-backend = "poetry.core.masonry.api"
 
 [tool.poe.tasks]
@@ -156,12 +159,7 @@ profile = 'black'
 multi_line_output = 3
 line_length = 100
 py_version = 38
-extend_skip_glob = [
-    'setup.py',
-    'docs/*',
-    'examples/*',
-    'pywhy_graphs/__init__.py',
-]
+extend_skip_glob = ['setup.py', 'docs/*', 'pywhy_graphs/__init__.py']
 
 [tool.pydocstyle]
 convention = 'numpy'

pywhy_graphs/algorithms/pag.py

@@ -4,7 +4,6 @@
 from typing import List, Optional, Set, Tuple
 
 import networkx as nx
-import numpy as np
 
 from pywhy_graphs import PAG
 from pywhy_graphs.algorithms.generic import single_source_shortest_mixed_path
@@ -168,7 +167,7 @@ def is_definite_noncollider(G: PAG, node1: Node, node2: Node, node3: Node) -> bo
 
 
 def discriminating_path(
-    graph: PAG, u: Node, a: Node, c: Node, max_path_length: int = np.inf
+    graph: PAG, u: Node, a: Node, c: Node, max_path_length: Optional[int] = None
 ) -> Tuple[bool, List[Node], Set[Node]]:
     """Find the discriminating path for <..., a, u, c>.
 
@@ -189,8 +188,9 @@ def discriminating_path(
         A node in the graph.
     c : node
         A node in the graph.
-    max_path_length : int
-        The maximum distance to check in the graph.
+    max_path_length : optional, int
+        The maximum distance to check in the graph. By default None, which sets
+        it to 1000.
 
     Returns
     -------
@@ -201,7 +201,7 @@ def discriminating_path(
     disc_path : list
         The discriminating path starting from node c.
     """
-    if max_path_length == np.inf:
+    if max_path_length is None:
         max_path_length = 1000
 
     explored_nodes: Set[Node] = set()
@@ -312,7 +312,7 @@ def uncovered_pd_path(
     graph: PAG,
     u: Node,
     c: Node,
-    max_path_length: int,
+    max_path_length: Optional[int] = None,
     first_node: Optional[Node] = None,
     second_node: Optional[Node] = None,
 ) -> Tuple[List[Node], bool]:
@@ -331,8 +331,9 @@ def uncovered_pd_path(
         A node in the graph to start the uncovered path.
     c : node
         A node in the graph.
-    max_path_length : int
-        The maximum distance to check in the graph.
+    max_path_length : optional, int
+        The maximum distance to check in the graph. By default None, which sets
+        it to 1000.
     first_node : node, optional
         The node previous to 'u'. If it is before 'u', then we will check
         that 'u' is unshielded. If it is not passed, then 'u' is considered
@@ -361,7 +362,7 @@ def uncovered_pd_path(
     ):
         raise RuntimeError("Some nodes are not in graph... Double check function arguments.")
 
-    if max_path_length == np.inf:
+    if max_path_length is None:
         max_path_length = 1000
 
     explored_nodes: Set[Node] = set()
@@ -454,7 +455,9 @@ def uncovered_pd_path(
     return uncov_pd_path, found_uncovered_pd_path
 
 
-def pds(graph: PAG, node_x: Node, node_y: Node = None, max_path_length: int = np.inf) -> Set[Node]:
+def pds(
+    graph: PAG, node_x: Node, node_y: Node = None, max_path_length: Optional[int] = None
+) -> Set[Node]:
     """Find all PDS sets between node_x and node_y.
 
     Parameters
@@ -465,8 +468,9 @@ def pds(graph: PAG, node_x: Node, node_y: Node = None, max_path_length: int = np
         The node 'x'.
     node_y : node
         The node 'y'.
-    max_path_length : int
-        The maximum length of a path to search on.
+    max_path_length : optional, int
+        The maximum length of a path to search on. By default None, which sets
+        it to 1000.
 
     Returns
     -------
@@ -492,7 +496,7 @@ def pds(graph: PAG, node_x: Node, node_y: Node = None, max_path_length: int = np
     ----------
     .. footbibliography::
     """
-    if max_path_length == np.inf:
+    if max_path_length is None:
         max_path_length = 1000
 
     distance = 0
@@ -606,7 +610,9 @@ def pds(graph: PAG, node_x: Node, node_y: Node = None, max_path_length: int = np
     return dsep
 
 
-def pds_path(graph: PAG, node_x: Node, node_y: Node, max_path_length: int = np.inf) -> Set[Node]:
+def pds_path(
+    graph: PAG, node_x: Node, node_y: Node, max_path_length: Optional[int] = None
+) -> Set[Node]:
     """Compute the possibly-d-separating set path.
 
     Returns the PDS_path set defined in definition 3.4 of :footcite:`Colombo2012`.
@@ -620,7 +626,8 @@ def pds_path(graph: PAG, node_x: Node, node_y: Node, max_path_length: int = np.i
     node_y : node
         The ending node
     max_path_length : int, optional
-        The maximum length of a path to search on for PDS set, by default np.inf.
+        The maximum length of a path to search on for PDS set, by default None, which
+        sets it to 1000.
 
     Returns
     -------

pywhy_graphs/classes/admg.py

@@ -92,6 +92,9 @@ def bidirected_edge_name(self) -> str:
     def c_components(self) -> Iterator[Set]:
         """Generate confounded components of the graph.
 
+        Note the trivial c-component of a node without bidirected
+        edges is the node themself.
+
         Returns
         -------
         comp : iterator of sets