adding more nodes

tests/node_tests/outlier_mask.py

@@ -0,0 +1,54 @@
+import numpy as np
+import pytest
+from tests.node_tests._shared import make_field
+from backend.nodes.helpers import mask_to_bool
+
+
+def test_outlier_mask_detects_spikes():
+    from backend.nodes.outlier_mask import OutlierMask
+
+    node = OutlierMask()
+    data = np.zeros((64, 64))
+    data[30, 30] = 100.0  # extreme spike
+    field = make_field(data=data)
+    mask, = node.process(field, 3.0, "both")
+    binary = mask_to_bool(mask)
+    assert binary[30, 30]  # spike should be flagged
+
+
+def test_outlier_mask_clean_field():
+    from backend.nodes.outlier_mask import OutlierMask
+
+    node = OutlierMask()
+    # Uniform field has no outliers
+    field = make_field(data=np.ones((32, 32)) * 5.0)
+    mask, = node.process(field, 3.0, "both")
+    assert mask_to_bool(mask).sum() == 0
+
+
+def test_outlier_mask_high_only():
+    from backend.nodes.outlier_mask import OutlierMask
+
+    node = OutlierMask()
+    data = np.zeros((64, 64))
+    data[10, 10] = 100.0   # high spike
+    data[50, 50] = -100.0  # low spike
+    field = make_field(data=data)
+    mask, = node.process(field, 3.0, "high")
+    binary = mask_to_bool(mask)
+    assert binary[10, 10]
+    assert not binary[50, 50]
+
+
+def test_outlier_mask_low_only():
+    from backend.nodes.outlier_mask import OutlierMask
+
+    node = OutlierMask()
+    data = np.zeros((64, 64))
+    data[10, 10] = 100.0
+    data[50, 50] = -100.0
+    field = make_field(data=data)
+    mask, = node.process(field, 3.0, "low")
+    binary = mask_to_bool(mask)
+    assert not binary[10, 10]
+    assert binary[50, 50]