improve coverage

tests/node_tests/acf_1d.py

@@ -0,0 +1,72 @@
+import numpy as np
+from backend.data_types import LineData, RecordTable
+
+
+def test_acf_1d():
+    from backend.nodes.acf_1d import ACF1D
+
+    node = ACF1D()
+
+    # Periodic signal — ACF should show a peak at the period
+    n = 256
+    period = 32
+    t = np.arange(n, dtype=np.float64)
+    signal = np.sin(2 * np.pi * t / period)
+    profile = LineData(
+        data=signal,
+        x_axis=t * 1e-9,
+        x_unit="m",
+        y_unit="V",
+    )
+
+    acf, measurement = node.process(profile, level="mean")
+
+    assert isinstance(acf, LineData)
+    assert isinstance(measurement, RecordTable)
+
+    # ACF should be symmetric about zero lag
+    center = len(acf) // 2
+    assert np.allclose(acf.data, acf.data[::-1], atol=1e-10)
+
+    # Peak period should be close to the input period in metres
+    expected_period_m = period * 1e-9
+    assert len(measurement) == 1
+    assert measurement[0]["quantity"] == "Peak period"
+    assert abs(measurement[0]["value"] - expected_period_m) / expected_period_m < 0.1
+    assert measurement[0]["unit"] == "m"
+
+    # x_axis should be centred on zero
+    assert acf.x_axis is not None
+    assert acf.x_axis[center] == 0.0 or abs(acf.x_axis[center]) < 1e-15
+
+    # ACF at zero lag should equal variance (signal is mean-subtracted)
+    assert acf.data[center] > 0
+
+
+def test_acf_1d_no_peak():
+    from backend.nodes.acf_1d import ACF1D
+
+    node = ACF1D()
+
+    # White noise — ACF should have no reliable peak, measurement table may be empty
+    rng = np.random.default_rng(0)
+    noise = rng.standard_normal(64)
+    profile = LineData(data=noise, x_axis=np.arange(64, dtype=np.float64), x_unit="m")
+
+    acf, measurement = node.process(profile, level="none")
+    assert isinstance(acf, LineData)
+    # measurement is either empty or has one row — no assertion on content
+
+
+def test_acf_1d_level_none():
+    from backend.nodes.acf_1d import ACF1D
+
+    node = ACF1D()
+
+    # With level="none", a DC offset should not be removed
+    data = np.ones(32, dtype=np.float64) * 5.0
+    profile = LineData(data=data, x_axis=np.arange(32, dtype=np.float64))
+
+    acf, _ = node.process(profile, level="none")
+    # ACF of a constant is a constant
+    assert acf.data[len(acf) // 2] > 0