Added tests for SampleImporter

main_package/classes/utility/sample_importer.py

@@ -43,7 +43,7 @@ class SampleImporter(ai.AbstractImporter):
 
     def import_data(self, header_column = None):
 
-        if header_column is None:
+        if header_column is not None:
             self._sorter = header_column
         else:    
             self._sorter = self.build_sorter(self._df_samples_list[0])

main_package/tests/optimizers/test_tabu_search.py

@@ -46,7 +46,7 @@ class TestTabuSearch(unittest.TestCase):
                                         prior_net_structure=prior_net_structure
                                     )
         
-        cls.importer.import_data(0)
+        cls.importer.import_data()
         cls.s1 = sp.SamplePath(cls.importer)
 
         #cls.traj = cls.s1.concatenated_samples

main_package/tests/utility/test_sample_importer.py

@@ -0,0 +1,81 @@
+import sys
+sys.path.append("../../classes/")
+import unittest
+import os
+import glob
+import numpy as np
+import pandas as pd
+import utility.sample_importer as si
+import structure_graph.sample_path as sp
+
+import json
+
+
+
+class TestSampleImporter(unittest.TestCase):
+
+    @classmethod
+    def setUpClass(cls) -> None:
+        with open("../../data/networks_and_trajectories_binary_data_01_3.json") as f:
+            raw_data = json.load(f)
+
+            trajectory_list_raw= raw_data[0]["samples"]
+
+            cls.trajectory_list = [pd.DataFrame(sample) for sample in trajectory_list_raw]
+
+            cls.variables= pd.DataFrame(raw_data[0]["variables"])
+            cls.prior_net_structure = pd.DataFrame(raw_data[0]["dyn.str"])
+
+
+    def test_init(self):
+        sample_importer = si.SampleImporter(
+                                        trajectory_list=self.trajectory_list,
+                                        variables=self.variables,
+                                        prior_net_structure=self.prior_net_structure
+                                    )
+        
+        sample_importer.import_data()
+
+        s1 = sp.SamplePath(sample_importer)
+        s1.build_trajectories()
+        s1.build_structure()
+        s1.clear_memory() 
+
+        self.assertEqual(len(s1._importer._df_samples_list), 300)
+        self.assertIsInstance(s1._importer._df_samples_list,list)
+        self.assertIsInstance(s1._importer._df_samples_list[0],pd.DataFrame)
+        self.assertEqual(len(s1._importer._df_variables), 3)
+        self.assertIsInstance(s1._importer._df_variables,pd.DataFrame)
+        self.assertEqual(len(s1._importer._df_structure), 2)
+        self.assertIsInstance(s1._importer._df_structure,pd.DataFrame)
+
+    def test_order(self):
+        sample_importer = si.SampleImporter(
+                                        trajectory_list=self.trajectory_list,
+                                        variables=self.variables,
+                                        prior_net_structure=self.prior_net_structure
+                                    )
+        
+        sample_importer.import_data()
+
+        s1 = sp.SamplePath(sample_importer)
+        s1.build_trajectories()
+        s1.build_structure()
+        s1.clear_memory() 
+
+        for count,var in enumerate(s1._importer._df_samples_list[0].columns[1:]):
+            self.assertEqual(s1._importer._sorter[count],var)
+
+
+
+    def ordered(self, obj):
+        if isinstance(obj, dict):
+            return sorted((k, self.ordered(v)) for k, v in obj.items())
+        if isinstance(obj, list):
+            return sorted(self.ordered(x) for x in obj)
+        else:
+            return obj
+
+
+if __name__ == '__main__':
+    unittest.main()