Updated mono process version of both the algorithms

main_package/classes/estimators/structure_constraint_based_estimator.py

@@ -236,9 +236,7 @@ class StructureConstraintBasedEstimator(se.StructureEstimator):
         'get the number of CPU'
         cpu_count = multiprocessing.cpu_count()
 
-        if disable_multiprocessing:
-            print("DISABILITATO")
-            cpu_count = 1
+
 
         'Remove all the edges from the structure'   
         self.sample_path.structure.clean_structure_edges()
@@ -246,6 +244,11 @@ class StructureConstraintBasedEstimator(se.StructureEstimator):
         'Estimate the best parents for each node'
         #with multiprocessing.Pool(processes=cpu_count) as pool:
         #with get_context("spawn").Pool(processes=cpu_count) as pool:
+        if disable_multiprocessing:
+            print("DISABILITATO")
+            cpu_count = 1
+            list_edges_partial = [ctpc_algo(n,total_vars_numb) for n in self.nodes]
+        else:
             with concurrent.futures.ProcessPoolExecutor(max_workers=cpu_count) as executor:
                 list_edges_partial = executor.map(ctpc_algo,
                                                                  self.nodes,

main_package/classes/estimators/structure_score_based_estimator.py

@@ -102,6 +102,9 @@ class StructureScoreBasedEstimator(se.StructureEstimator):
         #with multiprocessing.Pool(processes=cpu_count) as pool:
 
         'Estimate the best parents for each node'
+        if disable_multiprocessing:
+            list_edges_partial = [estimate_parents(n,max_parents,iterations_number,patience,tabu_length,tabu_rules_duration,optimizer) for n in self.nodes]
+        else:
             with concurrent.futures.ProcessPoolExecutor(max_workers=cpu_count) as executor:
                 list_edges_partial = executor.map(estimate_parents, 
                                                             self.nodes,
@@ -114,8 +117,6 @@ class StructureScoreBasedEstimator(se.StructureEstimator):
 
 
 
-
-            # list_edges_partial = [estimate_parents(n,max_parents,iterations_number,patience,tabu_length,tabu_rules_duration,optimizer) for n in self.nodes]
             #list_edges_partial = p.map(estimate_parents, self.nodes)
             #list_edges_partial= estimate_parents('Q',max_parents,iterations_number,patience,tabu_length,tabu_rules_duration,optimizer) 
 

main_package/tests/estimators/test_structure_score_based_estimator.py

@@ -23,7 +23,7 @@ class TestStructureScoreBasedEstimator(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         #cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
-        cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_10.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_15.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
         cls.s1 = sp.SamplePath(cls.importer)
         cls.s1.build_trajectories()
         cls.s1.build_structure()