#145 Add unit tests for BayesianAggregation in TradeRoutines

Introduced tests to validate correct functionality of BayesianAggregation, ensuring type correctness and expected outputs. Includes both positive cases with expected results and negative cases to handle invalid inputs gracefully.

Author: Tim55667757

tests/test_TradeRoutines.py

@@ -1369,3 +1369,38 @@ def test_ZScoreNegative(self):
 
             except Exception:
                 pass  # Acceptable fallback on bad input
+
+    def test_BayesianAggregationCheckType(self):
+        result = TradeRoutines.BayesianAggregation(0.6, 0.7)
+
+        assert isinstance(result, float), "BayesianAggregation must return a float!"
+
+    def test_BayesianAggregationPositive(self):
+        testCases = [
+            (0.5, 0.5, 0.5),
+            (0.8, 0.9, (0.8 * 0.9) / (0.8 * 0.9 + 0.2 * 0.1)),
+            (0.0, 0.0, 0.0),
+            (1.0, 1.0, 1.0),
+        ]
+
+        for p1, p2, expected in testCases:
+            result = TradeRoutines.BayesianAggregation(p1, p2)
+
+            assert abs(result - expected) < 1e-10, f"Incorrect result for {p1}, {p2}: {result}, expected: {expected}"
+
+    def test_BayesianAggregationNegative(self):
+        testCases = [
+            (1.2, 0.5),
+            (0.5, -0.1),
+            ("bad", 0.5),
+            (None, 0.7),
+        ]
+
+        for p1, p2 in testCases:
+            try:
+                result = TradeRoutines.BayesianAggregation(p1, p2)
+
+                assert 0.0 <= result <= 1.0, f"Result out of bounds: {result}"
+
+            except Exception:
+                pass  # Acceptable on bad input