refactor: change get_objective_function into a static method and getter

Author: John Halloran

news/declass-obj.rst

@@ -0,0 +1,23 @@
+**Added:**
+
+* Implement tests for ``compute_objective_function()``
+
+**Changed:**
+
+* Refactor ``get_objective_function()`` into a static method and getter
+
+**Deprecated:**
+
+* <news item>
+
+**Removed:**
+
+* <news item>
+
+**Fixed:**
+
+* <news item>
+
+**Security:**
+
+* <news item>

tests/test_snmf_optimizer.py

@@ -45,3 +45,75 @@ def test_final_objective_below_threshold(inputs):
     # Basic sanity check and the actual assertion
     assert np.isfinite(model.objective_function)
     assert model.objective_function < 5e6
+
+
+@pytest.mark.parametrize(
+    "inputs, expected",
+    # inputs tuple: (components, residuals, stretch, rho, eta, spline smoothness operator)
+    [
+        # Case 0: No smoothness or sparsity penalty, reduces to standard NMF objective
+        # residual Frobenius norm^2 = 3^2 + 4^2 = 25 -> 0.5 * 25 = 12.5
+        (
+            (
+                np.array([[0.0, 0.0], [3.0, 4.0]]),
+                np.array([[0.0, 0.0], [3.0, 4.0]]),
+                np.ones((2, 2)),
+                0.0,
+                0.0,
+                np.zeros((2, 2)),
+            ),
+            12.5,
+        ),
+        # Case 1: rho = 0, sparsity penalty only
+        # sqrt components sum = 1 + 2 + 3 + 4 = 10 -> eta * 10 = 5
+        # residual term remains 12.5 -> total = 17.5
+        (
+            (
+                np.array([[1.0, 4.0], [9.0, 16.0]]),
+                np.array([[3.0, 4.0], [0.0, 0.0]]),
+                np.ones((2, 2)),
+                0.0,
+                0.5,
+                np.zeros((2, 2)),
+            ),
+            17.5,
+        ),
+        # Case 2: eta = 0, smoothness penalty only
+        # residual = 12.5, smoothing = 0.5 * 1 * 1 = 0.5 -> total = 13.0
+        (
+            (
+                np.array([[1.0, 2.0], [3.0, 4.0]]),
+                np.array([[3.0, 4.0], [0.0, 0.0]]),
+                np.array([[1.0, 2.0]]),
+                1.0,
+                0.0,
+                np.array([[1.0, -1.0]]),
+            ),
+            13.0,
+        ),
+        # Case 3: penalty for smoothness and sparsity
+        # residual = 2.5, sparsity = 1.5, smoothing = 9 -> total = 13.0
+        (
+            (
+                np.array([[1.0, 4.0]]),
+                np.array([[1.0, 2.0]]),
+                np.array([[1.0, 4.0]]),
+                2.0,
+                0.5,
+                np.array([[3.0, 0.0]]),
+            ),
+            13.0,
+        ),
+    ],
+)
+def test_compute_objective_function(inputs, expected):
+    components, residuals, stretch, rho, eta, operator = inputs
+    result = SNMFOptimizer._compute_objective_function(
+        components=components,
+        residuals=residuals,
+        stretch=stretch,
+        rho=rho,
+        eta=eta,
+        spline_smooth_operator=operator,
+    )
+    assert np.isclose(result, expected)