Update scripts/experiment_remote.py

cleaning up of the code and commenting

scripts/experiment_remote.py

@@ -1,34 +1,46 @@
-#imports for runmanager - labscript
-from runmanager_remote import run_experiment
-from lyse import *
-
-import pandas as pd
-
-import TestDA
-import xarray as xr
-
-if __name__ == '__main__':
-
-    routine_name = 'TestSetup'
-
-    TestVar = {'T_wlm': 1,
-            'delta_freq': 0,
-            'wait_AWG': 5,
-            'buffer_time': 5,
-            'carrier_amp': 2
-            }
-
-
-    hdf_output_file = run_experiment(routine_name, global_var = TestVar)
-
-    print('run finished')
-
-    #df = pd.DataFrame(lyse_run.get_result('wlm', 'wlm_df'), columns = ['timestamp [s]','wavelength [nm]', 'frequency [THz]'])
-    #print(df)
-
-    #results = TestDA.analysis(hdf_output_file)
-
-    cost = TestDA.cost(hdf_output_file)
-    #print('I am back')
-
+#imports for runmanager - labscript
+from runmanager_remote import run_experiment
+
+
+import importlib
+_module_cache = {}
+
+# use this script if you want to test a single iteration of NNDy with your sequence and DA, 
+#        if you get the cost dictionary printed at the end as expected, the test is passed
+
+def cost_function(cost_model, hdf5_file):
+            module_name = cost_model
+
+            #looks in the cache if the file was accessed already, otherwise imports the cost function
+            if module_name not in _module_cache:
+                try:
+                    module = importlib.import_module(module_name)
+                    cost_func = getattr(module, 'cost')
+                    _module_cache[module_name] = {
+                        "cost_func": cost_func , 
+                    }
+                except (ModuleNotFoundError, AttributeError) as e:
+                    raise ImportError(f'Failed to load cost function from "{module_name}.py": {e}')
+            
+            cost_model = _module_cache[module_name]["cost_func"]
+
+            return cost_model(hdf5_file)
+
+if __name__ == '__main__':
+
+        #provide routine_name and cost_model like in NNDy.py
+    routine_name = ''
+    cost_model = ''
+        #set the input parameters with the values that you want to test in a dictionary
+    TestVar = {
+            }
+
+    hdf_output_file = run_experiment(routine_name, global_var = TestVar)
+
+    print('run finished')
+
+
+    cost = cost_function(cost_model, hdf_output_file)
+    #print('I am back')
+
     print(cost)