Add a basic test

pytest_tests/test_normative.py

@@ -1,37 +1,24 @@
-import pytest_tests
-from pcntoolkit.normative import load_response_vars
-from pcntoolkit.dataio import fileio
-# from dataio import fileio
+import pytest
+import sys
+from unittest import mock
+from pcntoolkit.normative import get_args
 
-import numpy as np
+def test_get_args():
+    # Define the test arguments
+    test_args = ['program_name', 'responses', '-f', 'estimate', '-m', 'maskfile', '-c', 'covfile', '-k', '5', '-t', 'testcov', '-r', 'testresp', '-a', 'gpr', '-x', 'configparam']
 
-def create_dummy_data():
-    # Create a dummy 3D array for the datafile
-    data = np.random.rand(10, 10, 10)
-
-    # Create a dummy 3D array for the maskfile
-    mask = np.ones((10, 10, 10))
-
-    return data, mask
-
-# Use the function to create the dummy data
-data, mask = create_dummy_data()
-
-# Store the dummy data on disk
-datafile = 'test_data.nii.gz'
-maskfile = 'test_mask.nii.gz'
-fileio.save_nifti(data, datafile)
-fileio.save_nifti(mask, maskfile)
-
-
-def test_load_response_vars():
-
-    # Call the function with the test inputs
-    Y, volmask,my_str = load_response_vars(datafile, maskfile, vol=True)
+    # Replace sys.argv with the test arguments
+    with mock.patch.object(sys, 'argv', test_args):
+        # Call the function with the test arguments
+        args = get_args()
 
     # Assert that the function returns the expected results
-    # This will depend on what you expect the function to return
-    # For example, you might check that Y and volmask are not None
-    assert Y is not None
-    assert volmask is not None
-    assert my_str == 'test'
+    assert args.responses == 'responses'
+    assert args.func == 'estimate'
+    assert args.maskfile == 'maskfile'
+    assert args.covfile == 'covfile'
+    assert args.cvfolds == '5'
+    assert args.testcov == 'testcov'
+    assert args.testresp == 'testresp'
+    assert args.alg == 'gpr'
+    assert args.configparam == 'configparam'