[cmd] Add get_solutions_graph_data to get graph data about a graph processed...

[cmd] Add get_solutions_graph_data to get graph data about a graph processed from solutions (not models)

command_line/cadbiom_cmd/solution_sort.py

@@ -81,7 +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, merge_graphs
+from tools.graphs import export_graph, build_graph, merge_graphs, get_solutions_graph_data
 
 import cadbiom.commons as cm
 

command_line/cadbiom_cmd/tools/graphs.py

@@ -252,6 +252,76 @@ def build_graph(solution, steps, transitions):
     return G, transition_nodes, all_nodes, edges_in_cond, edges
 
 
+def get_solutions_graph_data(G, info, centralities):
+    """Complete the given dictionary with information specific to the graph considered
+
+    Doc::
+
+    https://networkx.github.io/documentation/networkx-1.10/reference/algorithms.component.html
+    https://networkx.github.io/documentation/stable/reference/algorithms/shortest_paths.html
+    average_shortest_path_length
+    https://networkx.github.io/documentation/stable/reference/algorithms/generated/networkx.algorithms.shortest_paths.generic.average_shortest_path_length.html#networkx.algorithms.shortest_paths.generic.average_shortest_path_length
+    weakly_connected_component_subgraphs
+    https://networkx.github.io/documentation/networkx-1.10/reference/generated/networkx.algorithms.components.weakly_connected.weakly_connected_component_subgraphs.html#networkx.algorithms.components.weakly_connected.weakly_connected_component_subgraphs
+    Measures
+    https://networkx.github.io/documentation/stable/reference/algorithms/index.html
+
+    By default the following information are added::
+
+        - graph_nodes: Number of nodes
+        - graph_edges: Number of edges
+
+    If centralities is True, the folliwing information are added to the a new
+    key named "centralities"::
+
+        - strongly_connected:
+        - weakly_connected
+        - max_degree
+        - min_degree
+        - average_degree
+        - degree
+        - connected_components_number
+        - connected_components
+        - average_shortest_paths
+
+    :param G: NetworkX directed graph
+    :param info: Dictionnary of data to be completed
+    :param centralities: Flag to activate the computation of centralities.
+    :type G: <networkx.classes.digraph.DiGraph>
+    :type info: <dict>
+    :type centralities: <boolean>
+    """
+
+    info.update({
+        'graph_nodes': len(G.nodes()),
+        'graph_edges': len(G.edges()),
+    })
+
+    if not centralities:
+        return
+
+    # largest_connected_component = max(nx.connected_component_subgraphs(G), key=len)
+    connected_components = [g for g in nx.weakly_connected_component_subgraphs(G) if len(g) > 1]
+    shortest_paths = [nx.average_shortest_path_length(g) for g in connected_components]
+    degree = G.degree()
+
+    info.update({
+        'centralities': {
+            'strongly_connected': nx.is_strongly_connected(G),
+            'weakly_connected': nx.is_weakly_connected(G),
+            'max_degree': max(degree.values()),
+            'min_degree': min(degree.values()),
+            'average_degree': sum(degree.values()) / float(len(degree)),
+            'degree': degree,
+            'connected_components_number': len(shortest_paths),
+            'connected_components': [len(g) for g in connected_components],
+            'average_shortest_paths': sum(shortest_paths) / len(shortest_paths) if shortest_paths else "UKN",
+        }
+    })
+
+    LOGGER.info("%s", info)
+
+
 def get_json_graph(G):
     """Translate Networkx graph into a dictionary ready to be dumped in a JSON file.