low pri features

tests/node_tests/presentation_ops.py

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+import numpy as np
+from tests.node_tests._shared import make_field
+
+
+def test_output_shape():
+    from backend.nodes.presentation_ops import PresentationOps
+
+    node = PresentationOps()
+    field = make_field(shape=(32, 32))
+    result, = node.process(field, "logscale", blend_factor=0.5)
+    assert result.data.shape == field.data.shape
+
+
+def test_logscale():
+    from backend.nodes.presentation_ops import PresentationOps
+
+    node = PresentationOps()
+    data = np.array([[1.0, 10.0], [100.0, 1000.0]])
+    field = make_field(data=data)
+    result, = node.process(field, "logscale", blend_factor=0.5)
+    assert np.all(np.isfinite(result.data))
+    # logscale should preserve ordering
+    assert result.data[0, 0] < result.data[0, 1] < result.data[1, 0] < result.data[1, 1]
+
+
+def test_blend_at_zero():
+    from backend.nodes.presentation_ops import PresentationOps
+
+    node = PresentationOps()
+    field = make_field(data=np.array([[1.0, 2.0], [3.0, 4.0]]))
+    overlay = make_field(data=np.array([[10.0, 20.0], [30.0, 40.0]]))
+    result, = node.process(field, "blend", blend_factor=0.0, overlay=overlay)
+    assert np.allclose(result.data, field.data)
+
+
+def test_blend_at_one():
+    from backend.nodes.presentation_ops import PresentationOps
+
+    node = PresentationOps()
+    field = make_field(data=np.array([[1.0, 2.0], [3.0, 4.0]]))
+    overlay = make_field(data=np.array([[10.0, 20.0], [30.0, 40.0]]))
+    result, = node.process(field, "blend", blend_factor=1.0, overlay=overlay)
+    assert np.allclose(result.data, overlay.data)