Added download of test data if tests are run locally

Author: laurator

tests/test_LFP/test_LFP.py

@@ -7,6 +7,7 @@
 
 # Import the python package 'ncpi'
 import ncpi
+from ncpi import tools
 
 # Import the test module
 import pytest
@@ -32,18 +33,42 @@
 # Methods used to compute the features
 # all_methods = ['catch22','power_spectrum_parameterization_1']
 
+# Zenodo URL that contains the simulation and empirical test data and ML models for LFP method
+zenodo_URL_test = "https://zenodo.org/api/records/17479326"
+
 # Get the directory where this test file is located
 test_dir = os.path.dirname(os.path.abspath(__file__))
 
+# Path to save zenodo test files locally
+zenodo_test_files = os.path.join(test_dir, "..", "data", "zenodo_test_files_LFP")
+
 # Paths to zenodo simulation files
-zenodo_dir_sim = os.path.join(test_dir, "..", "data", "zenodo_test_files_LFP", "zenodo_sim_files") # Dir of GitHub testing downloaded files (set in tests.yml)
+zenodo_dir_sim = os.path.join(zenodo_test_files, "zenodo_sim_files") # Dir of GitHub testing downloaded files (set in tests.yml)
 
 # 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)
+zenodo_dir_emp= os.path.join(zenodo_test_files, "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 download_data_if_needed():
+    """Download test data only when running locally and data is missing"""    
+    # Skip if running in GitHub Actions
+    if os.getenv('GITHUB_ACTIONS'):
+        print("Running in CI - assuming test data is cached")
+        return
+    
+    # Download if zenodo sim files data don't exist locally
+    if not os.path.exists(zenodo_dir_sim):
+        tools.timer("Downloading simulation data for local execution...")(
+            tools.download_zenodo_record
+        )(zenodo_URL_test, download_dir=zenodo_test_files)
+    else:
+        print("Zenodo sim and emp test files already exist locally")
+
+# Download the data if it's not already downloaded
+download_data_if_needed()
+
 def LFP_mean(method):
     """
     Compute only certain data for testing and calculate the average
@@ -83,3 +108,4 @@ def test_LFP():
 # mean_power = LFP_mean('power_spectrum_parameterization_1')
 # print(f'Is \n{mean_catch} equal or similar to \n-0.8690581451462226?')
 # print(f'Is \n{mean_power} equal or similar to \n-1.2395402659827317?')
+# print('If no error messages were showed, the tests completed successfully.')