remove all sim, not just val ds

src/data/build_data.py

@@ -53,7 +53,7 @@ def build_load_save_data(file, hostfile, prefix, dataset, host, kmers_list=None,
                 nb_features_keep = nb_features_keep)
             save_Xy_data(data, data_file)
 
-        # Assign kmers_list to variable ater extracting database data
+        # Assign kmers_list to variable after extracting database data
         if kmers_list is None:
             kmers_list = data['kmers']
 

src/models/classification.py

@@ -137,12 +137,11 @@ def _train_model(self, taxa):
             self._binary_training(taxa)
         else:
             self._multiclass_training(taxa)
-        if isinstance(self.models[taxa], KerasTFModel):
-            for file in glob(os.path.join(self._outdirs['data_dir'], '*sim*')):
-                if os.path.isdir(file):
-                    rmtree(file)
-                else:
-                    os.remove(file)
+        for file in glob(os.path.join(self._outdirs['data_dir'], '*sim*')):
+            if os.path.isdir(file):
+                rmtree(file)
+            else:
+                os.remove(file)
 
     def _binary_training(self, taxa):
         print('_binary_training')
@@ -516,7 +515,6 @@ def _sim_4_cv(self, df, kmers_ds, name):
         cv_sim = readsSimulation(kmers_ds['fasta'], cls, sim_cls_dct['id'], 'miseq', sim_outdir, name)
         sim_data = cv_sim.simulation(self._k, self._database_data['kmers'])
         sim_ids = sim_data['ids']
-        sim_ids = sim_data['ids']
         sim_cls = pd.DataFrame({'sim_id':sim_ids}, dtype = object)
         sim_cls['id'] = sim_cls['sim_id'].str.replace('_[0-9]+_[0-9]+_[0-9]+', '', regex=True)
         sim_cls = sim_cls.set_index('id').join(cls.set_index('id'))