write unit tests for the set_default_batchsize() function

test/utils/test_set_batching.py

@@ -0,0 +1,55 @@
+# This code is part of a Qiskit project.
+#
+# (C) Copyright IBM 2022, 2024.
+#
+# This code is licensed under the Apache License, Version 2.0. You may
+# obtain a copy of this license in the LICENSE.txt file in the root directory
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+"""Test set batching."""
+
+from test import QiskitAlgorithmsTestCase
+
+from qiskit_optimization.optimizers import SPSA, COBYLA
+
+from qiskit_optimization.utils.set_batching import _set_default_batchsize
+
+
+class TestSetBatching(QiskitAlgorithmsTestCase):
+    """Set Batching tests."""
+
+    def test_set_default_batchsize_updates(self):
+        """Test that the default batchsize is set when it is None."""
+        # Create an instance of SPSA with _max_evals_grouped as None
+        optimizer = SPSA()
+        optimizer._max_evals_grouped = None  # Directly set the private variable for testing
+        # Call the function
+        updated = _set_default_batchsize(optimizer)
+        # Check that the batch size was updated
+        self.assertTrue(updated)
+        self.assertEqual(optimizer._max_evals_grouped, 50)
+
+    def test_set_default_batchsize_no_update(self):
+        """Test that the batchsize is not updated when it is already set."""
+        # Create an instance of SPSA with _max_evals_grouped already set
+        optimizer = SPSA()
+        optimizer._max_evals_grouped = 10  # Already set to a value
+        # Call the function
+        updated = _set_default_batchsize(optimizer)
+        # Check that the batch size was not updated
+        self.assertFalse(updated)
+        self.assertEqual(optimizer._max_evals_grouped, 10)
+
+    def test_set_default_batchsize_not_spsa(self):
+        """Test that the function does not update when not an SPSA instance."""
+        # Create a mock optimizer that is not an instance of SPSA
+        optimizer = COBYLA()
+        optimizer._max_evals_grouped = None  # COBYLA doesn't need the actual implementation
+        # Call the function
+        updated = _set_default_batchsize(optimizer)
+        # Check that the batch size was not updated
+        self.assertFalse(updated)