tip modelling and deconvolution

tests/node_tests/gradient.py

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+import numpy as np
+import pytest
+from tests.node_tests._shared import make_field
+
+
+def test_gradient_flat_field():
+    from backend.nodes.gradient import Gradient
+
+    node = Gradient()
+    field = make_field(data=np.zeros((16, 16)))
+
+    for component in ("magnitude", "x", "y"):
+        result, = node.process(field, component)
+        assert np.allclose(result.data, 0.0)
+        assert result.data.shape == field.data.shape
+
+
+def test_gradient_x_ramp():
+    """Linear ramp in x should give uniform x-gradient and zero y-gradient."""
+    from backend.nodes.gradient import Gradient
+
+    node = Gradient()
+    data = np.tile(np.linspace(0.0, 1.0, 32), (32, 1))
+    field = make_field(data=data)
+
+    gx, = node.process(field, "x")
+    gy, = node.process(field, "y")
+
+    # Interior pixels should have nearly identical x-gradient values
+    interior_gx = gx.data[1:-1, 1:-1]
+    assert np.all(interior_gx > 0)
+    assert np.std(interior_gx) < np.mean(interior_gx) * 0.01
+
+    # y-gradient should be zero everywhere in the interior
+    assert np.allclose(gy.data[1:-1, 1:-1], 0.0, atol=1e-10)
+
+
+def test_gradient_magnitude_non_negative():
+    from backend.nodes.gradient import Gradient
+
+    node = Gradient()
+    field = make_field()
+
+    result, = node.process(field, "magnitude")
+    assert np.all(result.data >= 0.0)
+
+
+def test_gradient_azimuth_range():
+    from backend.nodes.gradient import Gradient
+
+    node = Gradient()
+    field = make_field()
+
+    result, = node.process(field, "azimuth")
+    assert np.all(result.data >= -np.pi - 1e-10)
+    assert np.all(result.data <= np.pi + 1e-10)
+    assert result.si_unit_z == "rad"
+
+
+def test_gradient_units():
+    from backend.nodes.gradient import Gradient
+
+    node = Gradient()
+    field = make_field()  # si_unit_z="m", si_unit_xy="m"
+
+    result, = node.process(field, "magnitude")
+    assert result.si_unit_z == "m/m"
+
+    result, = node.process(field, "x")
+    assert result.si_unit_z == "m/m"
+
+
+def test_gradient_shape_preserved():
+    from backend.nodes.gradient import Gradient
+
+    node = Gradient()
+    field = make_field(shape=(48, 64))
+
+    for component in ("magnitude", "x", "y", "azimuth"):
+        result, = node.process(field, component)
+        assert result.data.shape == (48, 64)
+
+
+def test_gradient_unknown_component():
+    from backend.nodes.gradient import Gradient
+
+    node = Gradient()
+    field = make_field()
+
+    with pytest.raises(ValueError):
+        node.process(field, "diagonal")