Big refactoring

tests/property/test_recommendation_properties.py

@@ -0,0 +1,104 @@
+from __future__ import annotations
+
+from hypothesis import given, settings, strategies as st
+
+from app.services.recommendation_service import direction_analyzer, probability_estimator
+
+
+@settings(max_examples=100, deadline=None)
+@given(
+    technical=st.floats(min_value=0, max_value=100),
+    momentum=st.floats(min_value=0, max_value=100),
+    fundamental=st.floats(min_value=0, max_value=100),
+    sentiment=st.sampled_from(["bearish", "neutral", "bullish", None]),
+)
+def test_property_confidence_bounds(technical, momentum, fundamental, sentiment):
+    """Feature: intelligent-trade-recommendations, Property 3: Confidence Score Bounds."""
+    scores = {
+        "technical": technical,
+        "momentum": momentum,
+        "fundamental": fundamental,
+    }
+
+    long_conf = direction_analyzer.calculate_confidence("long", scores, sentiment, conflicts=[])
+    short_conf = direction_analyzer.calculate_confidence("short", scores, sentiment, conflicts=[])
+
+    assert 0 <= long_conf <= 100
+    assert 0 <= short_conf <= 100
+
+
+@settings(max_examples=100, deadline=None)
+@given(
+    strength_low=st.floats(min_value=0, max_value=50),
+    strength_high=st.floats(min_value=50, max_value=100),
+)
+def test_property_strength_monotonic_probability(strength_low, strength_high):
+    """Feature: intelligent-trade-recommendations, Property 11: S/R Strength Monotonicity."""
+    config = {
+        "recommendation_signal_alignment_weight": 0.15,
+        "recommendation_sr_strength_weight": 0.20,
+        "recommendation_distance_penalty_factor": 0.10,
+    }
+    scores = {"technical": 65.0, "momentum": 65.0}
+
+    base_target = {
+        "classification": "Moderate",
+        "distance_atr_multiple": 3.0,
+    }
+
+    low = probability_estimator.estimate_probability(
+        {**base_target, "sr_strength": strength_low},
+        scores,
+        "bullish",
+        "long",
+        config,
+    )
+    high = probability_estimator.estimate_probability(
+        {**base_target, "sr_strength": strength_high},
+        scores,
+        "bullish",
+        "long",
+        config,
+    )
+
+    assert high >= low
+
+
+@settings(max_examples=100, deadline=None)
+@given(
+    near_distance=st.floats(min_value=1.0, max_value=3.0),
+    far_distance=st.floats(min_value=3.1, max_value=8.0),
+)
+def test_property_distance_probability_relationship(near_distance, far_distance):
+    """Feature: intelligent-trade-recommendations, Property 12: Distance Probability Relationship."""
+    config = {
+        "recommendation_signal_alignment_weight": 0.15,
+        "recommendation_sr_strength_weight": 0.20,
+        "recommendation_distance_penalty_factor": 0.10,
+    }
+    scores = {"technical": 65.0, "momentum": 65.0}
+
+    near_prob = probability_estimator.estimate_probability(
+        {
+            "classification": "Conservative",
+            "sr_strength": 60,
+            "distance_atr_multiple": near_distance,
+        },
+        scores,
+        "bullish",
+        "long",
+        config,
+    )
+    far_prob = probability_estimator.estimate_probability(
+        {
+            "classification": "Aggressive",
+            "sr_strength": 60,
+            "distance_atr_multiple": far_distance,
+        },
+        scores,
+        "bullish",
+        "long",
+        config,
+    )
+
+    assert near_prob >= far_prob