[cmd] Move merge_graphs() to graphs module

command_line/cadbiom_cmd/solution_sort.py

@@ -74,7 +74,6 @@ import json
 import os
 import glob
 import csv
-import networkx as nx
 
 # Library imports
 
@@ -82,7 +81,7 @@ from tools.solutions import get_solutions
 from tools.models import get_transitions_from_model_file
 from tools.solutions import load_solutions, convert_solutions_to_json, \
     get_query_from_filename, get_mac_lines
-from tools.graphs import export_graph, build_graph
+from tools.graphs import export_graph, build_graph, merge_graphs
 
 import cadbiom.commons as cm
 
@@ -396,40 +395,6 @@ def solutions_2_common_graph(output_dir, model_file, path):
         LOGGER.info("Files processed: %s", file_number)
         assert file_number != 0, "No *mac_complete.txt files found!"
 
-
-def merge_graphs(graphs):
-    """Merge graphs in the given iterable; count and add the weights to the edges
-    of the final graph
-
-    :param graphs: Networkx graph objects.
-    :type graphs: <generator <networkx.classes.digraph.DiGraph>>
-    :return: Networkx graph object.
-    :rtype: <networkx.classes.digraph.DiGraph>
-    """
-
-    G = nx.DiGraph()
-
-    for graph in graphs:
-
-        missing_nodes = set(graph.nodes_iter()) - set(G.nodes_iter())
-        if missing_nodes:
-            # Add missing nodes in G from the current graph
-            # Note: This step is mandatory even if add_edge() automatically adds
-            # nodes to the graph, because some nodes can be included in any
-            # transition.
-            # Build a tuple (node_name, attrs)
-            G.add_nodes_from((node, graph.node[node]) for node in missing_nodes)
-
-        for ori, ext, data in graph.edges_iter(data=True):
-            if G.has_edge(ori, ext):
-                # Update the edge
-                G[ori][ext]['weight'] += 1
-            else:
-                # Add the missing edge
-                G.add_edge(ori, ext, attr_dict=data, weight=1)
-
-    return G
-
 ## Matrices of occurrences #####################################################
 
 def solutions_2_occcurrences_matrix(output_dir, model_file, path,

command_line/cadbiom_cmd/tools/graphs.py

@@ -334,3 +334,37 @@ def export_graph(output_dir, solution, solution_index, G, *args):
     # Save
     # PS: inhibitors will still have not the attribute 'color' = 'white'
     nx.write_graphml(G, filename + ".graphml")
+
+
+def merge_graphs(graphs):
+    """Merge graphs in the given iterable; count and add the weights to the edges
+    of the final graph
+
+    :param graphs: Networkx graph objects.
+    :type graphs: <generator <networkx.classes.digraph.DiGraph>>
+    :return: Networkx graph object.
+    :rtype: <networkx.classes.digraph.DiGraph>
+    """
+
+    G = nx.DiGraph()
+
+    for graph in graphs:
+
+        missing_nodes = set(graph.nodes_iter()) - set(G.nodes_iter())
+        if missing_nodes:
+            # Add missing nodes in G from the current graph
+            # Note: This step is mandatory even if add_edge() automatically adds
+            # nodes to the graph, because some nodes can be included in any
+            # transition.
+            # Build a tuple (node_name, attrs)
+            G.add_nodes_from((node, graph.node[node]) for node in missing_nodes)
+
+        for ori, ext, data in graph.edges_iter(data=True):
+            if G.has_edge(ori, ext):
+                # Update the edge
+                G[ori][ext]['weight'] += 1
+            else:
+                # Add the missing edge
+                G.add_edge(ori, ext, attr_dict=data, weight=1)
+
+    return G