Fix notebook and update docs for CI

Signed-off-by: Adam Li <adam2392@gmail.com>

doc/conf.py

@@ -264,7 +264,7 @@
 }
 
 # prevent jupyter notebooks from being run even if empty cell
-nbsphinx_execute = "never"
+# nbsphinx_execute = "never"
 nbsphinx_allow_errors = True
 
 # Custom sidebar templates, maps document names to template names.

doc/whats_new/_contributors.rst

@@ -22,3 +22,4 @@
 
 .. _Adam Li: https://adam2392.github.io
 .. _Chris Trevino: https://py-why.github.io
+.. _Robert Osazuwa Ness: https://py-why.github.io

doc/whats_new/v0.1.rst

@@ -37,7 +37,7 @@ Changelog
 - |Feature| Implement FCI algorithm, :class:`dodiscover.constraint.FCI` for learning causal structure from observational data with latent confounders under the ``dodiscover.constraint`` submodule, by `Adam Li`_ (:pr:`52`)
 - |Feature| Implement Structural Hamming Distance metric to compare directed graphs, :func:`dodiscover.metrics.structure_hamming_dist`, by `Adam Li`_ (:pr:`55`)
 - |Fix| Update dependency on networkx, which removes a PR branch dependency with pywhy-graphs having the MixedEdgeGraph class that was causing a dependency conflict, by `Adam Li`_ (:pr:`74`)
-- |Chore| Add tutorial for PC algorithm with Asia data, by `Robert Osazuwa Ness`_ (:pr:`67`)
+- |Enhancement| Add tutorial for PC algorithm with Asia data, by `Robert Osazuwa Ness`_ (:pr:`67`)
 
 Code and Documentation Contributors
 -----------------------------------
@@ -47,3 +47,4 @@ the project since version inception, including:
 
 * `Adam Li`_
 * `Chris Trevino`_
+* `Robert Osazuwa Ness`_

dodiscover/constraint/pcalg.py

@@ -1,5 +1,5 @@
 import logging
-from itertools import combinations, permutations
+from itertools import combinations
 from typing import Optional
 
 import networkx as nx
@@ -134,37 +134,36 @@ def orient_edges(self, graph: EquivalenceClass) -> None:
             A skeleton graph. If ``None``, then will initialize PC using a
             complete graph. By default None.
         """
-        node_ids = graph.nodes
-
         # For all the combination of nodes i and j, apply the following
         # rules.
         idx = 0
         finished = False
         while idx < self.max_iter and not finished:  # type: ignore
             change_flag = False
-            for (i, j) in permutations(node_ids, 2):
-                if i == j:
-                    continue
-                # Rule 1: Orient i-j into i->j whenever there is an arrow k->i
-                # such that k and j are nonadjacent.
-                r1_add = self._apply_meek_rule1(graph, i, j)
-
-                # Rule 2: Orient i-j into i->j whenever there is a chain
-                # i->k->j.
-                r2_add = self._apply_meek_rule2(graph, i, j)
-
-                # Rule 3: Orient i-j into i->j whenever there are two chains
-                # i-k->j and i-l->j such that k and l are nonadjacent.
-                r3_add = self._apply_meek_rule3(graph, i, j)
-
-                # Rule 4: Orient i-j into i->j whenever there are two chains
-                # i-k->l and k->l->j such that k and j are nonadjacent.
-                #
-                # However, this rule is not necessary when the PC-algorithm
-                # is used to estimate a DAG.
-
-                if any([r1_add, r2_add, r3_add]) and not change_flag:
-                    change_flag = True
+            for i in graph.nodes:
+                for j in graph.neighbors(i):
+                    if i == j:
+                        continue
+                    # Rule 1: Orient i-j into i->j whenever there is an arrow k->i
+                    # such that k and j are nonadjacent.
+                    r1_add = self._apply_meek_rule1(graph, i, j)
+
+                    # Rule 2: Orient i-j into i->j whenever there is a chain
+                    # i->k->j.
+                    r2_add = self._apply_meek_rule2(graph, i, j)
+
+                    # Rule 3: Orient i-j into i->j whenever there are two chains
+                    # i-k->j and i-l->j such that k and l are nonadjacent.
+                    r3_add = self._apply_meek_rule3(graph, i, j)
+
+                    # Rule 4: Orient i-j into i->j whenever there are two chains
+                    # i-k->l and k->l->j such that k and j are nonadjacent.
+                    #
+                    # However, this rule is not necessary when the PC-algorithm
+                    # is used to estimate a DAG.
+
+                    if any([r1_add, r2_add, r3_add]) and not change_flag:
+                        change_flag = True
             if not change_flag:
                 finished = True
                 logger.info(f"Finished applying R1-3, with {idx} iterations")

pyproject.toml

@@ -48,7 +48,6 @@ importlib-resources = { version = "*", python = "<3.9" }
 networkx = "^2.8.8"
 pywhy-graphs = { git = "https://github.com/py-why/pywhy-graphs.git", branch = 'main', optional = true }
 pygraphviz = { version = "*", optional = true }
-bnlearn = { git = "https://github.com/erdogant/bnlearn.git", branch = 'master', optional = true }
 
 [tool.poetry.group.style]
 optional = true
@@ -89,6 +88,7 @@ sphinx_rtd_theme = { version = "^1.0.0" }
 graphviz = { version = "^0.20.1" }
 ipython = { version = "^7.4.0" }
 nbsphinx = { version = "^0.8" }
+bnlearn = { git = "https://github.com/erdogant/bnlearn.git", branch = 'master', optional = true }
 dowhy = { version = "^0.8" }
 typing-extensions = { version = "*" }         # needed in dowhy's package 
 joblib = { version = "^1.1.0" }               # needed in dowhy's package
@@ -97,7 +97,6 @@ tqdm = { version = "^4.64.0" }                # needed in dowhy's package
 [tool.poetry.extras]
 graph_func = ['pywhy-graphs']
 viz = ['pygraphviz']
-data = ['bnlearn']
 
 [tool.portray]
 output_dir = ['site']