fix naming

tests/node_tests/level_plane.py

@@ -0,0 +1,40 @@
+import numpy as np
+from tests.node_tests._shared import make_field
+
+
+def test_plane_level():
+    from backend.nodes.level_plane import PlaneLevelField
+    node = PlaneLevelField()
+
+    N = 64
+    y, x = np.mgrid[0:N, 0:N] / N
+    signal = np.sin(2 * np.pi * 5 * x)
+    data = 100 * x + 50 * y + signal
+    field = make_field(data=data)
+
+    result, = node.process(field)
+    assert result.data.shape == field.data.shape
+    assert abs(result.data.mean()) < 1e-10
+    corr = np.corrcoef(result.data.ravel(), signal.ravel())[0, 1]
+    assert corr > 0.98
+
+    yy_px, xx_px = np.mgrid[0:N, 0:N]
+
+    def fit_pixel_plane(data_in, region):
+        A = np.column_stack([np.ones(int(np.count_nonzero(region))), xx_px[region].astype(np.float64), yy_px[region].astype(np.float64)])
+        coeffs, _, _, _ = np.linalg.lstsq(A, data_in[region].ravel().astype(np.float64), rcond=None)
+        return float(coeffs[0]), float(coeffs[1]), float(coeffs[2])
+
+    mask = np.zeros((N, N), dtype=np.uint8)
+    mask[20:44, 22:46] = 255
+    feature = np.zeros((N, N), dtype=np.float64)
+    feature[mask > 0] = 35.0
+    masked_field = make_field(data=100 * x + 50 * y + feature)
+
+    unmasked, = node.process(masked_field)
+    masked, = node.process(masked_field, masking="exclude", mask=mask)
+
+    outside = mask == 0
+    _, unmasked_bx, unmasked_by = fit_pixel_plane(unmasked.data, outside)
+    _, masked_bx, masked_by = fit_pixel_plane(masked.data, outside)
+    assert np.hypot(masked_bx, masked_by) < np.hypot(unmasked_bx, unmasked_by) * 1e-3