feat(generator): add 5-point gaussian smoothing on lateral

tests/test_generator.py

@@ -124,3 +124,35 @@ class TestPostProcessing:
             if len(values) > 1:
                 return  # at least one position has variation — pass
         pytest.fail("All 5 Δt sequences are identical at every position — diversity collapsed")
+
+
+class TestGaussianSmooth:
+    def test_endpoints_preserved(self):
+        from ai_mouse.generator import _gaussian_smooth
+        x = np.array([1.0, 5.0, 3.0, 7.0, 2.0], dtype=np.float64)
+        smoothed = _gaussian_smooth(x, sigma=1.0)
+        assert smoothed[0] == 1.0
+        assert smoothed[-1] == 2.0
+
+    def test_smooths_high_frequency(self):
+        """A high-frequency square wave should have reduced amplitude after smoothing."""
+        from ai_mouse.generator import _gaussian_smooth
+        x = np.array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1], dtype=np.float64)
+        smoothed = _gaussian_smooth(x, sigma=1.0)
+        # Interior amplitude should be reduced
+        interior_orig = x[2:-2]
+        interior_smooth = smoothed[2:-2]
+        assert interior_smooth.std() < interior_orig.std()
+
+    def test_constant_signal_unchanged(self):
+        from ai_mouse.generator import _gaussian_smooth
+        x = np.full(20, 0.5, dtype=np.float64)
+        smoothed = _gaussian_smooth(x, sigma=1.0)
+        np.testing.assert_allclose(smoothed, x, rtol=1e-6)
+
+    def test_short_array_returns_unchanged(self):
+        """Arrays shorter than the kernel are returned unchanged."""
+        from ai_mouse.generator import _gaussian_smooth
+        x = np.array([1.0, 2.0, 3.0], dtype=np.float64)
+        smoothed = _gaussian_smooth(x, sigma=1.0)
+        np.testing.assert_allclose(smoothed, x, rtol=1e-6)