remaining med value features

tests/node_tests/cross_correlate.py

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+import numpy as np
+import pytest
+from tests.node_tests._shared import make_field
+
+
+def test_cross_correlate_same_field_peak_at_center():
+    """Correlating a field with itself in 'same' mode peaks at the centre."""
+    from backend.nodes.cross_correlate import CrossCorrelate
+
+    rng = np.random.default_rng(0)
+    data = rng.standard_normal((32, 32))
+    field = make_field(data=data)
+    node = CrossCorrelate()
+    result, = node.process(field, field, mode="same", normalize=True)
+
+    peak_y, peak_x = np.unravel_index(np.argmax(result.data), result.data.shape)
+    cy, cx = result.data.shape[0] // 2, result.data.shape[1] // 2
+    # Peak should be within a few pixels of centre
+    assert abs(peak_y - cy) <= 2
+    assert abs(peak_x - cx) <= 2
+
+
+def test_cross_correlate_same_mode_shape_equals_a():
+    from backend.nodes.cross_correlate import CrossCorrelate
+
+    rng = np.random.default_rng(1)
+    a = make_field(data=rng.standard_normal((32, 48)))
+    b = make_field(data=rng.standard_normal((32, 48)))
+    node = CrossCorrelate()
+    result, = node.process(a, b, mode="same", normalize=True)
+    assert result.data.shape == a.data.shape
+
+
+def test_cross_correlate_full_mode_shape():
+    """Full mode output shape should be Na+Nb-1 × Ma+Mb-1."""
+    from backend.nodes.cross_correlate import CrossCorrelate
+
+    rng = np.random.default_rng(2)
+    a = make_field(data=rng.standard_normal((20, 30)))
+    b = make_field(data=rng.standard_normal((20, 30)))
+    node = CrossCorrelate()
+    result, = node.process(a, b, mode="full", normalize=True)
+    assert result.data.shape == (20 + 20 - 1, 30 + 30 - 1)
+
+
+def test_cross_correlate_normalized_peak_is_one():
+    """Self-correlation normalised should give peak = 1."""
+    from backend.nodes.cross_correlate import CrossCorrelate
+
+    rng = np.random.default_rng(3)
+    data = rng.standard_normal((32, 32))
+    field = make_field(data=data)
+    node = CrossCorrelate()
+    result, = node.process(field, field, mode="same", normalize=True)
+    assert result.data.max() == pytest.approx(1.0, abs=1e-6)
+
+
+def test_cross_correlate_unnormalized_runs():
+    from backend.nodes.cross_correlate import CrossCorrelate
+
+    rng = np.random.default_rng(4)
+    data = rng.standard_normal((16, 16))
+    field = make_field(data=data)
+    node = CrossCorrelate()
+    result, = node.process(field, field, mode="same", normalize=False)
+    assert result.data.shape == (16, 16)
+
+
+def test_cross_correlate_valid_mode():
+    from backend.nodes.cross_correlate import CrossCorrelate
+
+    rng = np.random.default_rng(5)
+    a = make_field(data=rng.standard_normal((16, 16)))
+    b = make_field(data=rng.standard_normal((8, 8)))
+    node = CrossCorrelate()
+    result, = node.process(a, b, mode="valid", normalize=True)
+    # Valid mode output: (16-8+1, 16-8+1) = (9, 9)
+    assert result.data.shape == (9, 9)
+
+
+def test_cross_correlate_preserves_metadata_same_mode():
+    from backend.nodes.cross_correlate import CrossCorrelate
+
+    rng = np.random.default_rng(6)
+    field = make_field(data=rng.standard_normal((16, 16)))
+    node = CrossCorrelate()
+    result, = node.process(field, field, mode="same", normalize=True)
+    assert result.xreal == field.xreal
+    assert result.yreal == field.yreal