refactor main

my_main.py

@@ -7,48 +7,43 @@
 import efm_summary as efms
 import time
 
-# G = examples.generate_barabasi(7); graph_name = 'barabasi'
-# G = examples.generate_graph()
 
-
-# G = examples.example30()
-G = examples.example31S2()
-# G = generate_graph_test_loops()
-
-
-nx.write_graphml(G, 'data/input_graph.graphml')
-
-# [save_graphml(G3, z) for G3 in result ]
-# save_graphml(G3, z)
-# save_stoichimetric_matrices(G3, z, file_prefix=graph_name)
-
-
-start = time.time()
-
-stoichiometric_matrix = ig.InhibitionRemovalFromMethabolicPathway.stat_generate_stoichiometric_matrix(G)
-ig.InhibitionRemovalFromMethabolicPathway.stat_save_stoichimetric_matrix(stoichiometric_matrix)
-
-a = ig.InhibitionRemovalFromMethabolicPathway(G)
-a.save_stoichimetric_matrices(file_prefix='Stoic')
-a.save_graphml(file_prefix='graphML')
-
-for node in G.nodes():
-    temp_graph = copy.deepcopy(G)
-    temp_graph.remove_node(node)
-    a = ig.InhibitionRemovalFromMethabolicPathway(temp_graph)
-    a.save_stoichimetric_matrices(file_prefix='Stoic_remove_node' + str(node))
-    a.save_graphml(file_prefix='GraphML_remove_node' + str(node))
-
-print('Stoichiometric Matrices generated in %s' % str(time.time() - start))
-start = time.time()
-
-# ----summary
-
-dirpath = 'data/'
-print('Processing files in {}'.format(dirpath))
-summary = efms.EFMSummary(dirpath)
-
-print('\nNumber of EFMs in expanded graph: {}'.format(summary.EFM_in_expanded_graph))
-summary.print_EFM_by_node()
-
-print('#EFM calculated in %s' % str(time.time() - start))
+def calculate_EFM():
+    dirpath = 'data/'
+    print('Processing files in {}'.format(dirpath))
+    summary = efms.EFMSummary(dirpath)
+    print('\nNumber of EFMs in expanded graph: {}'.format(summary.EFM_in_expanded_graph))
+    summary.print_EFM_by_node()
+
+
+def write_stoichimetric_matrices_to_files():
+    stoichiometric_matrix = ig.InhibitionRemovalFromMethabolicPathway.stat_generate_stoichiometric_matrix(G)
+    ig.InhibitionRemovalFromMethabolicPathway.stat_save_stoichimetric_matrix(stoichiometric_matrix)
+    a = ig.InhibitionRemovalFromMethabolicPathway(G)
+    a.save_stoichimetric_matrices(file_prefix='Stoic')
+    a.save_graphml(file_prefix='graphML')
+    for node in G.nodes():
+        print('Working with node %s out of %s' % (node, len(G.nodes())))
+        temp_graph = copy.deepcopy(G)
+        temp_graph.remove_node(node)
+        a = ig.InhibitionRemovalFromMethabolicPathway(temp_graph)
+        a.save_stoichimetric_matrices(file_prefix='Stoic_remove_node' + str(node))
+        a.save_graphml(file_prefix='GraphML_remove_node' + str(node))
+
+
+if __name__ == '__main__':
+    # G = generate_graph_test_loops()
+    # G = examples.generate_barabasi(7)
+    # G = examples.generate_graph()
+    # G = examples.example30()
+    G = examples.example31S2()
+
+    nx.write_graphml(G, 'data/input_graph.graphml')
+
+    print('Start generating stoichiometric matrices')
+    start = time.time()
+    write_stoichimetric_matrices_to_files()
+    print('Stoichiometric Matrices generated in {} seconds'.format(int(time.time() - start)))
+    start = time.time()
+    calculate_EFM()
+    print('\n#EFM calculated in {} seconds'.format(int(time.time() - start)))