Refactor test for test factorizers

Author: bobleesj

tests/test_containers.py

@@ -90,14 +90,17 @@ def test_apply_stretch(inputs, expected):
     np.testing.assert_allclose(actual, expected, rtol=1e-01)
 
 
-@pytest.mark.parametrize("inputs, expected", [
-    ([np.arange(5), 2, 0, [0, 1, 2, 3, 4], 0.5], [0, 0.5, 1, 1.5, 2]),
-    ([np.arange(5), 20, 2, [0, -1, -2, -3, -4], 0.25], [0, -0.25, -0.5, -0.75, -1]),
-    ([np.arange(40), 200, 4, np.arange(0, 10, 0.25), 0.3], np.arange(0, 10, 0.25) * 0.3),
-    ([np.arange(1), 10, 2, [10.5, 11.5, -10.5], 0], [0, 0, 0]),
-    ([[-12, -10, -15], 5, 2, [-0.5, -1, -1.2], 0.9], [-0.45, -0.9, -1.08]),
-    ([[-12, -10, -15], 5, 2, [0, 0, 0], 0.9], [0, 0, 0]),
-])
+@pytest.mark.parametrize(
+    "inputs, expected",
+    [
+        ([np.arange(5), 2, 0, [0, 1, 2, 3, 4], 0.5], [0, 0.5, 1, 1.5, 2]),
+        ([np.arange(5), 20, 2, [0, -1, -2, -3, -4], 0.25], [0, -0.25, -0.5, -0.75, -1]),
+        ([np.arange(40), 200, 4, np.arange(0, 10, 0.25), 0.3], np.arange(0, 10, 0.25) * 0.3),
+        ([np.arange(1), 10, 2, [10.5, 11.5, -10.5], 0], [0, 0, 0]),
+        ([[-12, -10, -15], 5, 2, [-0.5, -1, -1.2], 0.9], [-0.45, -0.9, -1.08]),
+        ([[-12, -10, -15], 5, 2, [0, 0, 0], 0.9], [0, 0, 0]),
+    ],
+)
 def test_apply_weight(inputs, expected):
     component = ComponentSignal(inputs[0], inputs[1], inputs[2])
     component.iq = np.array(inputs[3])

tests/test_factorizers.py

@@ -3,19 +3,19 @@
 
 from diffpy.snmf.factorizers import lsqnonneg
 
-tl = [
-    ([[[1, 0], [1, 0], [0, 1]], [2, 1, 1]], [1.5, 1.0]),
-    ([[[2, 3], [1, 2], [0, 0]], [7, 7, 2]], [0, 2.6923]),
-    ([[[3, 2, 4, 1]], [3.2]], [0, 0, 0.8, 0]),
-    ([[[-0.4, 0], [0, 0], [-9, -18]], [-2, -3, -4.9]], [0.5532, 0]),
-    ([[[-0.1, -0.2], [-0.8, -0.9]], [0, 0]], [0, 0]),
-    ([[[0, 0], [0, 0]], [10, 10]], [0, 0]),
-    ([[[2], [1], [-4], [-0.3]], [6, 4, 0.33, -5]], 0.767188240872451),
-]
 
-
-@pytest.mark.parametrize("tl", tl)
-def test_lsqnonneg(tl):
-    actual = lsqnonneg(tl[0][0], tl[0][1])
-    expected = tl[1]
+@pytest.mark.parametrize(
+    "stretched_component_matrix, target_signal, expected",
+    [
+        ([[1, 0], [1, 0], [0, 1]], [2, 1, 1], [1.5, 1.0]),
+        ([[2, 3], [1, 2], [0, 0]], [7, 7, 2], [0, 2.6923]),
+        ([[3, 2, 4, 1]], [3.2], [0, 0, 0.8, 0]),
+        ([[-0.4, 0], [0, 0], [-9, -18]], [-2, -3, -4.9], [0.5532, 0]),
+        ([[-0.1, -0.2], [-0.8, -0.9]], [0, 0], [0, 0]),
+        ([[0, 0], [0, 0]], [10, 10], [0, 0]),
+        ([[2], [1], [-4], [-0.3]], [6, 4, 0.33, -5], 0.767188240872451),
+    ],
+)
+def test_lsqnonneg(stretched_component_matrix, target_signal, expected):
+    actual = lsqnonneg(stretched_component_matrix, target_signal)
     np.testing.assert_array_almost_equal(actual, expected, decimal=4)