Make MMS into a regression test

test/tests/ver-1dc/test.py

@@ -1,8 +1,16 @@
-#!/usr/bin/env python3
-
 import mms
-df1 = mms.run_spatial('mms.i', 4, y_pp=['L2u'])
+import unittest
+from mooseutils import fuzzyEqual, fuzzyAbsoluteEqual
+
+class TestMMS(unittest.TestCase):
+    def test(self):
+        df1 = mms.run_spatial('mms.i', 4, y_pp=['L2u'])
+        fig = mms.ConvergencePlot(xlabel=r'$\Delta$t', ylabel='$L_2$ Error')
+        fig.plot(df1, label=['L2u'], marker='o', markersize=8, num_fitted_points=3, slope_precision=1)
+        fig.save('mms_spatial.png')
+        for key,value in fig.label_to_slope.items():
+            print("%s, %f" % (key, value))
+            self.assertTrue(fuzzyAbsoluteEqual(value, 2., .1))
 
-fig = mms.ConvergencePlot(xlabel=r'$\Delta$t', ylabel='$L_2$ Error')
-fig.plot(df1, label=['L2u'], marker='o', markersize=8)
-fig.save('mms_spatial.png')
+if __name__ == '__main__':
+    unittest.main(__name__, verbosity=2)

test/tests/ver-1dc/tests

@@ -32,4 +32,14 @@
     requirement = 'The system shall be able to generate comparison plots between the analytical solution and simulated solutions of verification cases 1dc, modeling a breakthrough problem of multiple traps.'
     required_python_packages = 'matplotlib numpy pandas os'
   []
+  [ver-1dc-mms]
+    type = PythonUnitTest
+    input = test.py
+    test_case = TestMMS
+    requirement = 'The system shall show second order spatial convergence for a diffusion-trapping-release test case.'
+    method = '!dbg'
+    required_python_packages = 'pandas matplotlib'
+    # skip test if test is being run out-of-tree. Issue Ref: idaholab/moose#25279
+    installation_type = in_tree
+  []
 []