tidy up old code

tests/node_tests/stats.py

@@ -11,61 +11,58 @@ def test_stats():
     assert input_spec[0] == "DATA_FIELD"
     assert input_spec[1]["accepted_types"] == ["IMAGE", "LINE", "DATA_TABLE"]
 
+    from backend.execution_context import execution_callbacks, active_node
     captured = []
-    Stats._broadcast_value_fn = lambda node_id, payload: captured.append((node_id, payload))
-    Stats._current_node_id = "test"
+    with execution_callbacks(value=lambda nid, payload: captured.append((nid, payload))), active_node("test"):
+        line = np.array([1.0, 2.0, 3.0, 4.0], dtype=np.float64)
+        result, = node.process(line, operation="mean", column="value")
+        assert np.isclose(result, 2.5)
+        assert captured[-1] == ("test", {"value": result})
+        roughness, = node.process(line, operation="Rq", column="value")
+        assert np.isclose(roughness, np.sqrt(np.mean((line - line.mean()) ** 2)))
 
-    line = np.array([1.0, 2.0, 3.0, 4.0], dtype=np.float64)
-    result, = node.process(line, operation="mean", column="value")
-    assert np.isclose(result, 2.5)
-    assert captured[-1] == ("test", {"value": result})
-    roughness, = node.process(line, operation="Rq", column="value")
-    assert np.isclose(roughness, np.sqrt(np.mean((line - line.mean()) ** 2)))
+        table = DataTable([
+            {"name": "a", "value": 3.0, "unit": "m", "other": 10.0},
+            {"name": "b", "value": 7.0, "unit": "m", "other": 20.0},
+        ])
+        result, = node.process(table, operation="max", column="value")
+        assert result == 7.0
+        assert captured[-1] == ("test", {"value": 7.0, "unit": "m"})
+        count, = node.process(table, operation="count", column="other")
+        assert count == 2.0
+        auto_column_range, = node.process(table, operation="range", column="")
+        assert auto_column_range == 4.0
 
-    table = DataTable([
-        {"name": "a", "value": 3.0, "unit": "m", "other": 10.0},
-        {"name": "b", "value": 7.0, "unit": "m", "other": 20.0},
-    ])
-    result, = node.process(table, operation="max", column="value")
-    assert result == 7.0
-    assert captured[-1] == ("test", {"value": 7.0, "unit": "m"})
-    count, = node.process(table, operation="count", column="other")
-    assert count == 2.0
-    auto_column_range, = node.process(table, operation="range", column="")
-    assert auto_column_range == 4.0
+        field = make_field(data=np.array([[1.0, 5.0], [2.0, 4.0]], dtype=np.float64))
+        result, = node.process(field, operation="range", column="value")
+        assert result == 4.0
+        assert captured[-1] == ("test", {"value": 4.0, "unit": "m"})
 
-    field = make_field(data=np.array([[1.0, 5.0], [2.0, 4.0]], dtype=np.float64))
-    result, = node.process(field, operation="range", column="value")
-    assert result == 4.0
-    assert captured[-1] == ("test", {"value": 4.0, "unit": "m"})
+        image = np.array([[0, 10], [20, 30]], dtype=np.uint8)
+        result, = node.process(image, operation="avg", column="value")
+        assert np.isclose(result, 15.0)
+        assert captured[-1] == ("test", {"value": 15.0})
 
-    image = np.array([[0, 10], [20, 30]], dtype=np.uint8)
-    result, = node.process(image, operation="avg", column="value")
-    assert np.isclose(result, 15.0)
-    assert captured[-1] == ("test", {"value": 15.0})
+        try:
+            node.process(table, operation="Rq", column="value")
+            raise AssertionError("Expected invalid TABLE operation to raise ValueError")
+        except ValueError:
+            pass
 
-    try:
-        node.process(table, operation="Rq", column="value")
-        raise AssertionError("Expected invalid TABLE operation to raise ValueError")
-    except ValueError:
-        pass
+        try:
+            node.process([{"label": "only text"}], operation="max", column="label")
+            raise AssertionError("Expected non-numeric record-table input to raise ValueError")
+        except ValueError:
+            pass
 
-    try:
-        node.process([{"label": "only text"}], operation="max", column="label")
-        raise AssertionError("Expected non-numeric record-table input to raise ValueError")
-    except ValueError:
-        pass
-
-    try:
-        node.process(
-            RecordTable([{"quantity": "min", "value": 1.0, "unit": "m"}]),
-            operation="max", column="value",
-        )
-        raise AssertionError("Expected measurement table input to raise ValueError")
-    except ValueError:
-        pass
-
-    Stats._broadcast_value_fn = None
+        try:
+            node.process(
+                RecordTable([{"quantity": "min", "value": 1.0, "unit": "m"}]),
+                operation="max", column="value",
+            )
+            raise AssertionError("Expected measurement table input to raise ValueError")
+        except ValueError:
+            pass
 
 
 def test_stats_empty_inputs():