tip modelling and deconvolution

tests/node_tests/tip_deconvolution.py

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+import numpy as np
+import pytest
+from tests.node_tests._shared import make_field
+from backend.data_types import DataField
+
+
+def run_deconv(field, tip):
+    from backend.nodes.tip_deconvolution import TipDeconvolution
+    node = TipDeconvolution()
+    result, = node.process(field=field, tip=tip)
+    return result
+
+
+def make_tip(shape="parabola", radius=10e-9, half_angle=20.0, n_pixels=33):
+    from backend.nodes.tip_model import TipModel
+    field = make_field(shape=(64, 64), xreal=64e-9, yreal=64e-9)
+    node = TipModel()
+    result, = node.process(field=field, shape=shape, radius=radius,
+                           half_angle=half_angle, n_pixels=n_pixels)
+    return result
+
+
+# ── Output type and shape ────────────────────────────────────────────────────
+
+def test_deconv_output_is_data_field():
+    field = make_field()
+    tip = DataField(data=np.zeros((1, 1)), xreal=1e-9, yreal=1e-9)
+    result = run_deconv(field, tip)
+    assert isinstance(result, DataField)
+
+
+def test_deconv_output_shape_matches_input():
+    field = make_field(shape=(64, 64))
+    tip = make_tip(n_pixels=11)
+    result = run_deconv(field, tip)
+    assert result.data.shape == field.data.shape
+
+
+def test_deconv_preserves_physical_dimensions():
+    field = make_field(xreal=2e-6, yreal=3e-6)
+    tip = DataField(data=np.zeros((1, 1)), xreal=1e-9, yreal=1e-9)
+    result = run_deconv(field, tip)
+    assert result.xreal == field.xreal
+    assert result.yreal == field.yreal
+
+
+def test_deconv_preserves_units():
+    field = make_field()
+    field.si_unit_xy = "nm"
+    field.si_unit_z = "V"
+    tip = DataField(data=np.zeros((1, 1)), xreal=1e-9, yreal=1e-9)
+    result = run_deconv(field, tip)
+    assert result.si_unit_xy == "nm"
+    assert result.si_unit_z == "V"
+
+
+# ── Identity with a point tip ────────────────────────────────────────────────
+
+def test_deconv_point_tip_is_identity():
+    """A 1×1 tip with value 0 is the identity: erosion with structure [[0]] = original."""
+    field = make_field(data=np.random.default_rng(0).standard_normal((32, 32)) + 10)
+    tip = DataField(data=np.zeros((1, 1)), xreal=1e-9, yreal=1e-9)
+    result = run_deconv(field, tip)
+    assert np.allclose(result.data, field.data, atol=1e-12)
+
+
+# ── Flat field invariance ────────────────────────────────────────────────────
+
+@pytest.mark.parametrize("shape", ["parabola", "cone", "sphere"])
+def test_deconv_flat_field_stays_flat(shape):
+    """Deconvolution of a constant-valued field must remain constant."""
+    flat_data = np.full((64, 64), 5.0)
+    field = make_field(data=flat_data)
+    tip = make_tip(shape=shape, n_pixels=15)
+    result = run_deconv(field, tip)
+    interior = result.data[8:-8, 8:-8]   # avoid border effects
+    assert np.allclose(interior, 5.0, atol=1e-10)
+
+
+# ── Deconvolution sharpens features ─────────────────────────────────────────
+
+def test_deconv_sharpens_broadened_image():
+    """
+    Forward tip dilation broadens a spike; deconvolution (erosion) should remove
+    the broadening.  Result must be ≤ input everywhere (erosion is a lower bound).
+    """
+    from scipy.ndimage import grey_dilation
+
+    # Build a field with a single spike
+    data = np.zeros((64, 64))
+    data[32, 32] = 1.0
+    field = make_field(data=data)
+
+    # Create a small parabolic tip
+    tip = make_tip(shape="parabola", radius=50e-9, n_pixels=11)
+    tip_data = tip.data
+
+    # Simulate measured image via tip dilation (Gwyddion gwy_tip_dilation):
+    #   dilation_tip = tip - max(tip)   (max shifted to 0, values ≤ 0)
+    #   measured[y,x] = max_{ty,tx}[surface[y−ty, x−tx] + dilation_tip[ty,tx]]
+    dilation_struct = tip_data - tip_data.max()
+    measured_data = grey_dilation(data, structure=dilation_struct)
+    measured = make_field(data=measured_data)
+
+    # Deconvolve
+    result = run_deconv(measured, tip)
+
+    # Erosion is a lower bound on the input
+    assert np.all(result.data <= measured_data + 1e-10)
+
+    # The spike should be recovered: result at spike position ≥ most surroundings
+    assert result.data[32, 32] > result.data[32, 36]
+
+
+def test_deconv_erosion_never_exceeds_input():
+    """Grey erosion is always ≤ the input (fundamental morphological property)."""
+    field = make_field(data=np.abs(np.random.default_rng(7).standard_normal((32, 32))))
+    tip = make_tip(shape="parabola", n_pixels=7)
+    result = run_deconv(field, tip)
+    assert np.all(result.data <= field.data + 1e-10)