split node tests into standalone files

tests/node_tests/test_line_correction.py

@@ -0,0 +1,54 @@
+import numpy as np
+from backend.data_types import LineData
+from backend.node_registry import get_node_info
+from tests.node_tests._shared import make_field
+
+
+def test_line_correction():
+    from backend.nodes.line_correction import LineCorrection
+
+    node = LineCorrection()
+    assert get_node_info("LineCorrection")["category"] == "Level & Correct"
+
+    rows = 96
+    cols = 128
+    y = np.linspace(0.0, 1.0, rows, dtype=np.float64)
+    x = np.linspace(-1.0, 1.0, cols, dtype=np.float64)
+    signal = (
+        0.15 * np.sin(8.0 * np.pi * x)[None, :]
+        + 0.05 * np.cos(4.0 * np.pi * y)[:, None]
+    )
+    row_offsets = 1.5 * np.sin(3.0 * np.pi * y) + 0.25 * np.cos(7.0 * np.pi * y)
+    field = make_field(data=signal + row_offsets[:, None], xreal=2.5e-6, yreal=1.5e-6)
+
+    corrected, background, shifts = node.process(
+        field, method="median", direction="horizontal", masking="ignore",
+        trim_fraction=0.05, polynomial_degree=1,
+    )
+    expected_shifts = row_offsets - row_offsets.mean()
+    assert corrected.data.shape == field.data.shape
+    assert background.data.shape == field.data.shape
+    assert np.allclose(corrected.data + background.data, field.data)
+    assert isinstance(shifts, LineData)
+    assert shifts.x_unit == field.si_unit_xy
+    assert shifts.y_unit == field.si_unit_z
+    assert np.isclose(shifts.x_axis[0], 0.0)
+    assert np.isclose(shifts.x_axis[-1], field.yreal)
+    assert np.corrcoef(shifts.data, expected_shifts)[0, 1] > 0.999
+    assert corrected.data.mean(axis=1).std() < field.data.mean(axis=1).std() * 0.03
+
+    poly_background = (
+        row_offsets[:, None]
+        + (0.35 * y - 0.15)[:, None] * x[None, :]
+        + (0.10 + 0.05 * y)[:, None] * (x[None, :] ** 2)
+    )
+    poly_signal = 0.08 * np.sin(10.0 * np.pi * x)[None, :] * (1.0 + 0.15 * np.cos(2.0 * np.pi * y)[:, None])
+    poly_field = make_field(data=poly_signal + poly_background)
+
+    leveled, poly_bg, poly_shifts = node.process(
+        poly_field, method="polynomial", direction="horizontal", masking="ignore",
+        trim_fraction=0.05, polynomial_degree=2,
+    )
+    assert np.allclose(leveled.data + poly_bg.data, poly_field.data)
+    assert np.corrcoef(leveled.data.ravel(), poly_signal.ravel())[0, 1] > 0.995
+    assert len(poly_shifts) == rows