Fix ML_models specification for tests

Author: laurator

examples/LFP_developing_brain/LFP_developing_brain.py

@@ -56,7 +56,7 @@ def load_model_features(method, zenodo_dir_sim):
 
 
 @timer("Loading the inverse model.")
-def load_inference_data(method, X, theta, zenodo_dir_sim):
+def load_inference_data(method, X, theta, zenodo_dir_sim, ML_model):
     # Load the Inference objects and add the simulation data
 
     # Create inference object
@@ -232,7 +232,7 @@ def save_data(emp_data, method):
         X, theta = load_model_features(method, zenodo_dir_sim)
 
         # Load the Inference objects and add the simulation data
-        inference = load_inference_data(method, X, theta, zenodo_dir_sim)
+        inference = load_inference_data(method, X, theta, zenodo_dir_sim, ML_model)
 
         # Load empirical data
         emp_data = load_empirical_data(zenodo_dir_emp)

tests/test_LFP/test_LFP.py

@@ -41,6 +41,9 @@
 # Paths to zenodo empirical files
 zenodo_dir_emp= os.path.join(test_dir, "..", "data", "zenodo_test_files_LFP", "zenodo_emp_files") # Dir of GitHub testing downloaded files (set in tests.yml)
 
+# ML model used to compute the predictions (MLPRegressor, Ridge or NPE)
+ML_model = 'MLPRegressor'
+
 def LFP_mean(method):
     """
     Compute only certain data for testing and calculate the average
@@ -50,7 +53,7 @@ def LFP_mean(method):
     X, theta = lfp.load_model_features(method, zenodo_dir_sim)
 
     # Load the Inference objects and add the simulation data
-    inference = lfp.load_inference_data(method, X, theta, zenodo_dir_sim)
+    inference = lfp.load_inference_data(method, X, theta, zenodo_dir_sim, ML_model)
 
     # Load empirical data
     emp_data = lfp.load_empirical_data(zenodo_dir_emp)