updated tests file path location

main_package/classes/estimators/structure_score_based_estimator.py

@@ -47,7 +47,7 @@ class StructureScoreBasedEstimator(se.StructureEstimator):
         super().__init__(sample_path)
 
 
-    @timing
+    
     def estimate_structure(self, max_parents:int = None, iterations_number:int= 40, patience:int = None ):
         """
         Compute the score-based algorithm to find the optimal structure
@@ -86,7 +86,7 @@ class StructureScoreBasedEstimator(se.StructureEstimator):
             #list_edges_partial = p.map(estimate_parents, self.nodes)
 
         'Concatenate all the edges list'
-        list_edges =  list(itertools.chain.from_iterable(list_edges_partial))
+        set_list_edges =  set(itertools.chain.from_iterable(list_edges_partial))
 
         print('-------------------------')
 
@@ -95,7 +95,6 @@ class StructureScoreBasedEstimator(se.StructureEstimator):
         n_missing_edges = 0
         n_added_fake_edges = 0
 
-        set_list_edges = set(list_edges)
 
         n_added_fake_edges = len(set_list_edges.difference(true_edges))
 
@@ -121,7 +120,7 @@ class StructureScoreBasedEstimator(se.StructureEstimator):
         print(f"n archi reali non trovati: {n_missing_edges}")
         print(f"n archi non reali aggiunti: {n_added_fake_edges}")
         print(true_edges)
-        print(list_edges)
+        print(set_list_edges)
         print(f"precision: {precision} ")
         print(f"recall: {recall} ")
     
@@ -218,21 +217,5 @@ class StructureScoreBasedEstimator(se.StructureEstimator):
         return score 
 
 
-    def generate_possible_sub_sets_of_size(self, u: typing.List, size: int, parent_label: str):
-        """
-        Creates a list containing all possible subsets of the list u of size size,
-        that do not contains a the node identified by parent_label.
-
-        Parameters:
-            u: the list of nodes
-            size: the size of the subsets
-            parent_label: the nodes to exclude in the subsets generation
-        Returns:
-            a Map Object containing a list of lists
-
-        """
-        list_without_test_parent = u[:]
-        list_without_test_parent.remove(parent_label)
-        return map(list, itertools.combinations(list_without_test_parent, size))
 
 

main_package/tests/estimators/test_parameters_estimator.py

@@ -17,7 +17,7 @@ class TestParametersEstimatior(unittest.TestCase):
     @classmethod
     def setUpClass(cls) -> None:
         cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
-        cls.importer = ji.JsonImporter(cls.read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
         cls.s1 = sp.SamplePath(cls.importer)
         cls.s1.build_trajectories()
         cls.s1.build_structure()

main_package/tests/estimators/test_structure_constraint_based_estimator.py

@@ -21,7 +21,7 @@ class TestStructureConstraintBasedEstimator(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
-        cls.importer = ji.JsonImporter(cls.read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
         cls.s1 = sp.SamplePath(cls.importer)
         cls.s1.build_trajectories()
         cls.s1.build_structure()

main_package/tests/estimators/test_structure_score_based_estimator.py

@@ -21,8 +21,8 @@ class TestStructureScoreBasedEstimator(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
+        #cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
-        cls.importer = ji.JsonImporter(cls.read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
         cls.s1 = sp.SamplePath(cls.importer)
         cls.s1.build_trajectories()
         cls.s1.build_structure()
@@ -32,7 +32,7 @@ class TestStructureScoreBasedEstimator(unittest.TestCase):
     def test_esecuzione(self):
         se1 = se.StructureScoreBasedEstimator(self.s1)
         se1.estimate_structure(
-                            max_parents = 3,
+                            max_parents = 6,
                             iterations_number = 80,
                             patience = None 
                             )

main_package/tests/structure_graph/test_networkgraph.py

@@ -17,7 +17,7 @@ class TestNetworkGraph(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
-        cls.importer = ji.JsonImporter(cls.read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
         cls.s1 = sp.SamplePath(cls.importer)
         cls.s1.build_trajectories()
         cls.s1.build_structure()

main_package/tests/structure_graph/test_sample_path.py

@@ -14,7 +14,7 @@ class TestSamplePath(unittest.TestCase):
     @classmethod
     def setUpClass(cls) -> None:
         cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
-        cls.importer = ji.JsonImporter(cls.read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
 
     def test_init(self):
         s1 = sp.SamplePath(self.importer)