low pri features

tests/node_tests/tip_shape_estimate.py

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+import numpy as np
+import pytest
+from tests.node_tests._shared import make_field
+
+
+def run_tip_shape(field, feature_type="edge", feature_radius=100e-9, n_points=100):
+    from backend.nodes.tip_shape_estimate import TipShapeEstimate
+    node = TipShapeEstimate()
+    tip_shape, parameters = node.process(
+        field=field,
+        feature_type=feature_type,
+        feature_radius=feature_radius,
+        n_points=n_points,
+    )
+    return tip_shape, parameters
+
+
+# ── Output shape and type ────────────────────────────────────────────────────
+
+def test_output_shape():
+    """tip_shape must be a 2D DataField."""
+    from backend.data_types import DataField
+    field = make_field(shape=(64, 64), xreal=64e-9, yreal=64e-9)
+    tip_shape, _ = run_tip_shape(field, feature_type="edge", n_points=33)
+    assert isinstance(tip_shape, DataField)
+    assert tip_shape.data.ndim == 2
+    assert tip_shape.data.shape[0] == tip_shape.data.shape[1]
+
+
+# ── Parameters table ─────────────────────────────────────────────────────────
+
+def test_parameters_table():
+    """parameters must be a RecordTable containing a tip_radius entry."""
+    from backend.data_types import RecordTable
+    field = make_field(shape=(64, 64), xreal=64e-9, yreal=64e-9)
+    _, parameters = run_tip_shape(field, feature_type="edge", n_points=33)
+    assert isinstance(parameters, RecordTable)
+    quantities = {row["quantity"] for row in parameters}
+    assert "tip_radius" in quantities
+
+
+# ── Tip apex is maximum ──────────────────────────────────────────────────────
+
+def test_tip_apex_is_maximum():
+    """The centre of the tip shape should be the highest point."""
+    field = make_field(shape=(64, 64), xreal=64e-9, yreal=64e-9)
+    tip_shape, _ = run_tip_shape(field, feature_type="edge", n_points=33)
+    n = tip_shape.data.shape[0]
+    ci = n // 2
+    assert tip_shape.data[ci, ci] == pytest.approx(tip_shape.data.max(), abs=1e-20)
+
+
+# ── Sphere feature produces valid estimate ───────────────────────────────────
+
+def test_sphere_feature():
+    """Using a synthetic sphere as input produces a valid tip estimate."""
+    from backend.data_types import DataField
+
+    # Create a synthetic sphere on a 64x64 grid.
+    R = 100e-9  # sphere radius
+    n = 64
+    pixel_size = 10e-9
+    xreal = n * pixel_size
+    Y, X = np.mgrid[:n, :n]
+    r = np.sqrt((X - 32) ** 2 + (Y - 32) ** 2) * pixel_size
+    data = np.sqrt(np.maximum(R ** 2 - r ** 2, 0.0))
+
+    field = make_field(data=data, xreal=xreal, yreal=xreal)
+
+    tip_shape, parameters = run_tip_shape(
+        field, feature_type="sphere", feature_radius=R, n_points=33,
+    )
+
+    # The output must be a valid 2D DataField.
+    assert isinstance(tip_shape, DataField)
+    assert tip_shape.data.ndim == 2
+
+    # Apex should be the maximum.
+    ci = tip_shape.data.shape[0] // 2
+    assert tip_shape.data[ci, ci] == pytest.approx(tip_shape.data.max(), abs=1e-20)
+
+    # Parameters should contain tip_radius.
+    quantities = {row["quantity"]: row["value"] for row in parameters}
+    assert "tip_radius" in quantities
+    # The estimated radius must be a positive finite number.
+    assert quantities["tip_radius"] > 0