Add dedicated test function for eye method

- Add test_eye_method() as requested in review comment
- Uses subTest for parameterized testing with sizes [1,2,3,4,5,10]
- Uses itertools.product for efficient nested loop iteration
- Tests both array comparison and individual element verification
- Provides better test isolation for debugging future issues

Addresses review comment: Create distinct test function for eye method
in addition to exercising it in matmul test function.

Author: tkoyama010

tests/test_gemm.py

@@ -26,6 +26,7 @@
 
 import unittest
 import numpy as np
+from itertools import product
 import modmesh as mm
 
 
@@ -84,6 +85,34 @@ def test_identity_matrix(self):
         self.assertEqual(list(result.shape), [3, 3])
         np.testing.assert_array_almost_equal(result.ndarray, a_data)
 
+    def test_eye_method(self):
+        """Test eye method creates correct identity matrices"""
+        # Test cases: different sizes
+        test_sizes = [1, 2, 3, 4, 5, 10]
+        
+        for size in test_sizes:
+            with self.subTest(size=size):
+                # Create identity matrix using our eye method
+                identity = self.SimpleArray.eye(size)
+                
+                # Create expected identity matrix using NumPy
+                expected = np.eye(size, dtype=self.dtype)
+                
+                # Check shape
+                self.assertEqual(list(identity.shape), [size, size])
+                
+                # Check array values
+                np.testing.assert_array_almost_equal(identity.ndarray, expected)
+                
+                # Verify diagonal and off-diagonal elements explicitly using product
+                for i, j in product(range(size), repeat=2):
+                    if i == j:
+                        self.assertEqual(identity[i, j], 1.0, 
+                                       f"Diagonal element ({i},{j}) should be 1.0")
+                    else:
+                        self.assertEqual(identity[i, j], 0.0,
+                                       f"Off-diagonal element ({i},{j}) should be 0.0")
+
     def test_zero_matrix(self):
         """Test multiplication with zero matrix"""
         a_data = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=self.dtype)