split node tests into standalone files

tests/node_tests/test_acf_2d.py

@@ -0,0 +1,39 @@
+import numpy as np
+from backend.data_types import DataField
+
+
+def test_acf():
+    from backend.nodes.acf_2d import ACF2D
+
+    node = ACF2D()
+    data = np.array([
+        [1.0, 2.0, 3.0, 4.0],
+        [5.0, 6.0, 7.0, 8.0],
+        [2.0, 1.0, 0.0, -1.0],
+        [0.0, 1.0, 2.0, 3.0],
+    ], dtype=np.float64)
+    field = DataField(data=data, xreal=8.0, yreal=4.0, si_unit_xy="nm", si_unit_z="V")
+
+    acf, = node.process(field, level="none")
+    assert acf.data.shape == (3, 3)
+    assert acf.domain == "spatial"
+    assert acf.si_unit_xy == "nm"
+    assert acf.si_unit_z == "V^2"
+    assert np.isclose(acf.xreal, 6.0)
+    assert np.isclose(acf.yreal, 3.0)
+    assert np.isclose(acf.xoff, -3.0)
+    assert np.isclose(acf.yoff, -1.5)
+
+    expected = np.zeros((3, 3), dtype=np.float64)
+    for iy, dy in enumerate(range(-1, 2)):
+        for ix, dx in enumerate(range(-1, 2)):
+            y0a = max(0, dy)
+            y1a = min(data.shape[0], data.shape[0] + dy)
+            x0a = max(0, dx)
+            x1a = min(data.shape[1], data.shape[1] + dx)
+            lhs = data[y0a:y1a, x0a:x1a]
+            rhs = data[y0a - dy:y1a - dy, x0a - dx:x1a - dx]
+            expected[iy, ix] = float(np.mean(lhs * rhs))
+
+    assert np.allclose(acf.data, expected)
+    assert np.allclose(acf.data, acf.data[::-1, ::-1])