Add mixed hypergraphs

.gitignore

@@ -53,3 +53,8 @@ coverage.xml
 docs/_build/
 
 /main.py
+
+# Test artifacts
+test_directed_read_and_write.txt
+test_undirected_read_and_write.txt
+test_mixed_read_and_write.txt

README.md

@@ -1,7 +1,7 @@
 halp: Hypergraph Algorithms Package<br>
 ==========
 
-_halp_ is a Python software package that provides both a directed and an undirected hypergraph implementation, as well as several important and canonical algorithms that operate on these hypergraphs.
+_halp_ is a Python software package that provides directed, undirected, and mixed hypergraph implementations, as well as several important and canonical algorithms that operate on these hypergraphs.
 
 See [http://murali-group.github.io/halp/](http://murali-group.github.io/halp/) for documentation, code examples, and more information.
 

halp/algorithms/directed_random_walk.py

@@ -30,13 +30,13 @@ def stationary_distribution(H, pi=None, P=None):
             it will be created.
     :returns: list -- list of the stationary probabilities for all nodes
             in the hypergraph.
-    :raises: TypeError -- Algorithm only applicable to undirected hypergraphs
+    :raises: TypeError -- Algorithm only applicable to directed hypergraphs
     :raises: AssertionError -- Each node must have at least 1 outgoing
              hyperedge (even if it's only a self-loop).
 
     """
     if not isinstance(H, DirectedHypergraph):
-        raise TypeError("Algorithm only applicable to undirected hypergraphs")
+        raise TypeError("Algorithm only applicable to directed hypergraphs")
 
     for node in H.node_iterator():
         if len(H.get_forward_star(node)) == 0:

halp/directed_hypergraph.py

@@ -210,6 +210,11 @@ def add_node(self, node, attr_dict=None, **attr):
         :param attr: keyword arguments of attributes of the node;
                     attr's values will override attr_dict's values
                     if both are provided.
+        :note: Following the NetworkX model, we allow both a dictionary
+            of attributes to be passed in by the user as well as key-value
+            pairs of attributes to be passed in by the user to provide
+            greater flexibility. This pattern is followed in methods such
+            as add_nodes, add_hyperedge, and add_hyperedges.
 
         Examples:
         ::
@@ -344,7 +349,7 @@ def remove_nodes(self, nodes):
             self.remove_node(node)
 
     def trim_node(self, node):
-        """Removes a node from the hypergraph. Modifies hypredges with the 
+        """Removes a node from the hypergraph. Modifies hyperedges with the 
         trimmed node in their head or tail so that they no longer include 
         the trimmed node. If a hyperedge has solely the trimmed node in its
         head or tail, that hyperedge is removed.
@@ -361,10 +366,6 @@ def trim_node(self, node):
             >>> H.trim_node('A')
         """
 
-        fs = self.get_forward_star(node)
-        bs = self.get_backward_star(node)
-        remove_set = set()
-
         def get_attrs(H, hyperedge):
             #copies the attribute dictionary of a hyperedge except for the head and tail
             new_attrs = {}
@@ -374,6 +375,10 @@ def get_attrs(H, hyperedge):
                 if key not in {'head', 'tail'}:
                     new_attrs[key] = old_attrs[key]
             return new_attrs
+
+        remove_set = set()
+        fs = self.get_forward_star(node)
+        bs = self.get_backward_star(node)
 
         for hedge in fs:
             tail = set(self.get_hyperedge_tail(hedge))
@@ -1244,7 +1249,7 @@ def _check_hyperedge_attributes_consistency(self):
                     raise ValueError(
                         'Consistency Check 1.7 Failed: hyperedge ' +
                         'id ' + hyperedge_id + ' is not in the ' +
-                        'backward star of head node ' + tail_node)
+                        'backward star of head node ' + head_node)
 
     def _check_node_attributes_consistency(self):
         """Consistency Check 2: consider all nodes listed in