Upload tests/test_fitness_and_theme.py with huggingface_hub

tests/test_fitness_and_theme.py

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+"""Tests for fitness function and theme sampler."""
+import pytest
+from alpha_factory.deterministic.fitness import compute_fitness, would_pass_brain, regime_tag_years
+from alpha_factory.deterministic.theme_sampler import compute_gap_scores, pick_theme
+from alpha_factory.schemas import BrainMetrics
+
+
+class TestFitness:
+    def test_high_sharpe_alpha(self):
+        metrics = BrainMetrics(
+            alpha_id="test", sharpe_full=2.0, sharpe_is=2.2, sharpe_os=1.8,
+            fitness=1.5, turnover=0.3, returns=0.15, max_drawdown=0.03,
+            yearly_sharpe=[1.5, 2.0, 1.8, 2.1, 1.6], yearly_returns=[0.03]*5,
+        )
+        score = compute_fitness(metrics, max_corr_to_library=0.2, theme_novelty_score=0.8)
+        assert score > 1.0  # Should be a good score
+
+    def test_negative_sharpe_penalized(self):
+        metrics = BrainMetrics(
+            alpha_id="test", sharpe_full=-0.5, sharpe_is=0.5, sharpe_os=-0.5,
+            fitness=0.3, turnover=0.5, returns=-0.05, max_drawdown=0.15,
+            yearly_sharpe=[-1.0, -0.5, 0.2, -0.8, -0.3], yearly_returns=[-0.02]*5,
+        )
+        score = compute_fitness(metrics, max_corr_to_library=0.1, theme_novelty_score=0.5)
+        assert score < 0  # Should be negative
+
+    def test_high_correlation_penalized(self):
+        metrics = BrainMetrics(
+            alpha_id="test", sharpe_full=1.5, sharpe_is=1.6, sharpe_os=1.4,
+            fitness=1.2, turnover=0.25, returns=0.1, max_drawdown=0.04,
+            yearly_sharpe=[1.2, 1.5, 1.3, 1.4, 1.6], yearly_returns=[0.02]*5,
+        )
+        low_corr = compute_fitness(metrics, max_corr_to_library=0.1, theme_novelty_score=0.5)
+        high_corr = compute_fitness(metrics, max_corr_to_library=0.8, theme_novelty_score=0.5)
+        assert low_corr > high_corr  # Lower correlation = higher score
+
+    def test_would_pass_brain(self):
+        good = BrainMetrics(
+            alpha_id="test", sharpe_full=1.5, sharpe_is=1.6, sharpe_os=1.4,
+            fitness=1.2, turnover=0.25, returns=0.1, max_drawdown=0.04,
+            yearly_sharpe=[1.2, 1.5, 1.3, 1.4, 1.6], yearly_returns=[0.02]*5,
+        )
+        result = would_pass_brain(good)
+        assert result["sharpe_ge_1.25"] == True
+        assert result["fitness_ge_1.0"] == True
+
+    def test_regime_tags(self):
+        yearly = [1.5, 2.0, -0.5, 1.8, 1.2]
+        tags = regime_tag_years(yearly)
+        assert tags["2019"] == "moderate"
+        assert tags["2021"] == "negative"
+
+
+class TestThemeSampler:
+    def test_unexplored_themes_rank_higher(self):
+        existing = ["momentum", "momentum", "momentum", "value", "value"]
+        tags = ["momentum", "momentum", "momentum", "value", "value"]
+        scores = compute_gap_scores(existing, tags)
+        # Themes with 0 alphas should rank highest
+        top_theme = scores[0][0]
+        assert top_theme not in ["momentum", "value"]
+
+    def test_dead_themes_excluded(self):
+        existing = ["momentum"]
+        tags = ["momentum"]
+        dead = ["option_surface"]
+        scores = compute_gap_scores(existing, tags, dead_themes=dead)
+        theme_names = [s[0] for s in scores]
+        assert "option_surface" not in theme_names
+
+    def test_pick_theme_returns_string(self):
+        theme = pick_theme(["momentum"], ["momentum"])
+        assert isinstance(theme, str)
+        assert len(theme) > 0