test(ReforceXY): factor out common code

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/ReforceXY/reward_space_analysis/README.md b/ReforceXY/reward_space_analysis/README.md
index c4a3dd25646e4c289ecc6a65b4c63db995ea8a28..6e74cf0816567c2c790b55cc43a0c90eee1d2b67 100644 (file)
--- a/ReforceXY/reward_space_analysis/README.md
+++ b/ReforceXY/reward_space_analysis/README.md
@@ -352,6 +352,7 @@ where:
 
 - `r_pnl = pnl / pnl_target`
 - `r_dur = clamp(duration_ratio, 0, 1)`
+- `scale = base_factor · hold_potential_ratio`
 - `g = hold_potential_gain`
 - `T_pnl`, `T_dur` = configured transforms
 - `m_dur = 1.0` if `r_pnl >= 0` (profit side)

diff --git a/ReforceXY/reward_space_analysis/pyproject.toml b/ReforceXY/reward_space_analysis/pyproject.toml
index 52d0b1dd83cc5bbc42550c845b2ebf3d7b4b6c42..c99aa8f36b765850926fc12444636ae48e2075f1 100644 (file)
--- a/ReforceXY/reward_space_analysis/pyproject.toml
+++ b/ReforceXY/reward_space_analysis/pyproject.toml
@@ -8,10 +8,10 @@ authors = [
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
-    "numpy",
+    "numpy>=1.26",
     "pandas",
     "scikit-learn",
-    "scipy",
+    "scipy>=1.11",
     "pytest",
 ]
 
@@ -66,9 +66,17 @@ addopts = [
     "--strict-markers",
     "--color=yes",
     "--cov=reward_space_analysis",
+    "--cov-config=pyproject.toml",
     "--cov-fail-under=85"
 ]
 
+[tool.coverage.run]
+source = ["reward_space_analysis"]
+omit = [
+    "tests/*",
+    "test_*.py",
+]
+
 [tool.ruff]
 line-length = 100
 target-version = "py311"

diff --git a/ReforceXY/reward_space_analysis/reward_space_analysis.py b/ReforceXY/reward_space_analysis/reward_space_analysis.py
index 09561c3dabbbf44fb3ef5b7d19f87883d53ee5e2..0445bf2e69c3cc8c5564b7c2311eea224f14c933 100644 (file)
--- a/ReforceXY/reward_space_analysis/reward_space_analysis.py
+++ b/ReforceXY/reward_space_analysis/reward_space_analysis.py
@@ -3056,7 +3056,7 @@ def _compute_hold_potential(
     if not _get_bool_param(params, "hold_potential_enabled"):
         return _fail_safely("hold_potential_disabled")
 
-    return _compute_bi_component(
+    return _compute_pnl_duration_signal(
         kind="hold_potential",
         pnl=pnl,
         pnl_target=pnl_target,
@@ -3081,7 +3081,7 @@ def _compute_entry_additive(
 ) -> float:
     if not _get_bool_param(params, "entry_additive_enabled"):
         return _fail_safely("entry_additive_disabled")
-    return _compute_bi_component(
+    return _compute_pnl_duration_signal(
         kind="entry_additive",
         pnl=pnl,
         pnl_target=pnl_target,
@@ -3105,7 +3105,7 @@ def _compute_exit_additive(
 ) -> float:
     if not _get_bool_param(params, "exit_additive_enabled"):
         return _fail_safely("exit_additive_disabled")
-    return _compute_bi_component(
+    return _compute_pnl_duration_signal(
         kind="exit_additive",
         pnl=pnl,
         pnl_target=pnl_target,
@@ -3182,8 +3182,7 @@ def compute_pbrs_components(
 ) -> tuple[float, float, float, float, float]:
     """Compute potential-based reward shaping (PBRS) components.
 
-    This function computes the PBRS shaping terms without combining them with the base reward,
-    allowing the caller to construct the total reward as R'(s,a,s') = R(s,a,s') + Δ(s,a,s') + additives.
+    This function computes the PBRS shaping terms.
 
     Canonical PBRS Formula
     ----------------------
@@ -3197,6 +3196,7 @@ def compute_pbrs_components(
     Let:
         r_pnl = pnl / pnl_target
         r_dur = clamp(duration_ratio, 0, 1)
+        scale = base_factor · hold_potential_ratio
         g = gain
         T_pnl, T_dur = configured bounded transforms
         m_dur = 1.0 if r_pnl >= 0 else loss_duration_multiplier(r_pnl, risk_reward_ratio)
@@ -3325,7 +3325,7 @@ def apply_potential_shaping(
     )
 
 
-def _compute_bi_component(
+def _compute_pnl_duration_signal(
     kind: str,
     pnl: float,
     pnl_target: float,

diff --git a/ReforceXY/reward_space_analysis/tests/api/test_api_helpers.py b/ReforceXY/reward_space_analysis/tests/api/test_api_helpers.py
index 496a974ee4f372ffd911150a08e4909a8d7e56bb..227e76a638ead0d147d6db698c89dbca05fb925f 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/api/test_api_helpers.py
+++ b/ReforceXY/reward_space_analysis/tests/api/test_api_helpers.py
@@ -48,7 +48,7 @@ class TestAPIAndHelpers(RewardSpaceTestBase):
 
         def sample_entry_rate(*, idle_duration: int, short_allowed: bool) -> float:
             rng = random.Random(SEEDS.REPRODUCIBILITY)
-            draws = 2000
+            draws = 2_000
             entries = 0
             for _ in range(draws):
                 action, _, _, _ = _sample_action(
@@ -64,8 +64,11 @@ class TestAPIAndHelpers(RewardSpaceTestBase):
                     entries += 1
             return entries / draws
 
-        low_idle_rate = sample_entry_rate(idle_duration=0, short_allowed=True)
-        high_idle_rate = sample_entry_rate(idle_duration=60, short_allowed=True)
+        idle_duration_low = 0
+        idle_duration_high = 60
+
+        low_idle_rate = sample_entry_rate(idle_duration=idle_duration_low, short_allowed=True)
+        high_idle_rate = sample_entry_rate(idle_duration=idle_duration_high, short_allowed=True)
 
         self.assertGreater(
             high_idle_rate,
@@ -73,8 +76,10 @@ class TestAPIAndHelpers(RewardSpaceTestBase):
             "Entry rate should increase after exceeding max idle duration",
         )
 
-        low_idle_rate_spot = sample_entry_rate(idle_duration=0, short_allowed=False)
-        high_idle_rate_spot = sample_entry_rate(idle_duration=60, short_allowed=False)
+        low_idle_rate_spot = sample_entry_rate(idle_duration=idle_duration_low, short_allowed=False)
+        high_idle_rate_spot = sample_entry_rate(
+            idle_duration=idle_duration_high, short_allowed=False
+        )
         self.assertGreater(high_idle_rate_spot, low_idle_rate_spot)
 
     def test_parse_overrides(self):
@@ -99,12 +104,14 @@ class TestAPIAndHelpers(RewardSpaceTestBase):
         any_exit = df[df["reward_exit"] != 0].head(1)
         if not any_exit.empty:
             row = any_exit.iloc[0]
+            unrealized_pad = PARAMS.PNL_SMALL / 2
+            pnl = float(row["pnl"])
             ctx = self.make_ctx(
-                pnl=float(row["pnl"]),
+                pnl=pnl,
                 trade_duration=int(row["trade_duration"]),
                 idle_duration=int(row["idle_duration"]),
-                max_unrealized_profit=float(row["pnl"]) + 0.01,
-                min_unrealized_profit=float(row["pnl"]) - 0.01,
+                max_unrealized_profit=pnl + unrealized_pad,
+                min_unrealized_profit=pnl - unrealized_pad,
                 position=Positions.Long,
                 action=Actions.Long_exit,
             )
@@ -114,14 +121,14 @@ class TestAPIAndHelpers(RewardSpaceTestBase):
     def test_simulate_samples_trading_modes_spot_vs_margin(self):
         """simulate_samples coverage: spot should forbid shorts, margin should allow them."""
         df_spot = simulate_samples_with_defaults(
-            self.base_params(max_trade_duration_candles=100),
+            self.base_params(max_trade_duration_candles=PARAMS.TRADE_DURATION_MEDIUM),
             num_samples=SCENARIOS.SAMPLE_SIZE_SMALL,
             trading_mode="spot",
         )
         short_positions_spot = (df_spot["position"] == float(Positions.Short.value)).sum()
         self.assertEqual(short_positions_spot, 0, "Spot mode must not contain short positions")
         df_margin = simulate_samples_with_defaults(
-            self.base_params(max_trade_duration_candles=100),
+            self.base_params(max_trade_duration_candles=PARAMS.TRADE_DURATION_MEDIUM),
             num_samples=SCENARIOS.SAMPLE_SIZE_SMALL,
         )
         for col in [
@@ -156,18 +163,23 @@ class TestAPIAndHelpers(RewardSpaceTestBase):
         values = (
             df[["sample_entry_prob", "sample_exit_prob", "sample_neutral_prob"]].stack().dropna()
         )
-        self.assertTrue(((values >= 0.0) & (values <= 0.9)).all())
+        prob_upper_bound = 0.9
+        self.assertTrue(((values >= 0.0) & (values <= prob_upper_bound)).all())
 
     def test_simulate_samples_interprets_bool_string_params(self):
         """Test simulate_samples correctly interprets string boolean params like action_masking."""
         df1 = simulate_samples_with_defaults(
-            self.base_params(action_masking="true", max_trade_duration_candles=50),
+            self.base_params(
+                action_masking="true", max_trade_duration_candles=PARAMS.TRADE_DURATION_SHORT
+            ),
             num_samples=10,
             trading_mode="spot",
         )
         self.assertIsInstance(df1, pd.DataFrame)
         df2 = simulate_samples_with_defaults(
-            self.base_params(action_masking="false", max_trade_duration_candles=50),
+            self.base_params(
+                action_masking="false", max_trade_duration_candles=PARAMS.TRADE_DURATION_SHORT
+            ),
             num_samples=10,
             trading_mode="spot",
         )
@@ -176,7 +188,7 @@ class TestAPIAndHelpers(RewardSpaceTestBase):
     def test_short_allowed_via_simulation(self):
         """Test _is_short_allowed via different trading modes."""
         df_futures = simulate_samples_with_defaults(
-            self.base_params(max_trade_duration_candles=50),
+            self.base_params(max_trade_duration_candles=PARAMS.TRADE_DURATION_SHORT),
             num_samples=SCENARIOS.SAMPLE_SIZE_SMALL,
             trading_mode="futures",
         )
@@ -333,15 +345,13 @@ class TestPrivateFunctions(RewardSpaceTestBase):
                     0.0,
                     f"Exit component should be non-zero for {description}",
                 )
-                self.assertTrue(
-                    np.isfinite(breakdown.total), f"Total should be finite for {description}"
-                )
+                self.assertFinite(breakdown.total, name="total")
 
     def test_invalid_action_handling(self):
         """Test invalid action penalty."""
         context = self.make_ctx(
-            pnl=0.02,
-            trade_duration=50,
+            pnl=PARAMS.PNL_SMALL,
+            trade_duration=PARAMS.TRADE_DURATION_SHORT,
             idle_duration=0,
             max_unrealized_profit=0.03,
             min_unrealized_profit=0.01,

diff --git a/ReforceXY/reward_space_analysis/tests/cli/test_cli_params_and_csv.py b/ReforceXY/reward_space_analysis/tests/cli/test_cli_params_and_csv.py
index d89ba8d9c985545cbc59f0856620bd898793a1f1..ac4a2cbe16dbbde8089e550f467038264c921766 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/cli/test_cli_params_and_csv.py
+++ b/ReforceXY/reward_space_analysis/tests/cli/test_cli_params_and_csv.py
@@ -19,28 +19,36 @@ pytestmark = pytest.mark.cli
 SCRIPT_PATH = Path(__file__).parent.parent.parent / "reward_space_analysis.py"
 
 
+def _run_cli(*, out_dir: Path, args: list[str]) -> subprocess.CompletedProcess[str]:
+    cmd = [
+        "uv",
+        "run",
+        sys.executable,
+        str(SCRIPT_PATH),
+        "--out_dir",
+        str(out_dir),
+        *args,
+    ]
+    return subprocess.run(cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent)
+
+
+def _assert_cli_success(
+    testcase: unittest.TestCase, result: subprocess.CompletedProcess[str]
+) -> None:
+    testcase.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+
+
 class TestCsvEncoding(RewardSpaceTestBase):
     """Validate CSV output encoding invariants."""
 
     def test_action_column_integer_in_csv(self):
         """Ensure 'action' column in reward_samples.csv is encoded as integers."""
         out_dir = self.output_path / "csv_int_check"
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "200",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=["--num_samples", "200", "--seed", str(SEEDS.BASE)],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
         csv_path = out_dir / "reward_samples.csv"
         self.assertTrue(csv_path.exists(), "Missing reward_samples.csv")
         df = pd.read_csv(csv_path)
@@ -67,23 +75,17 @@ class TestParamsPropagation(RewardSpaceTestBase):
     def test_skip_feature_analysis_summary_branch(self):
         """CLI run with --skip_feature_analysis should mark feature importance skipped in summary and omit feature_importance.csv."""
         out_dir = self.output_path / "skip_feature_analysis"
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "200",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-            "--skip_feature_analysis",
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=[
+                "--num_samples",
+                "200",
+                "--seed",
+                str(SEEDS.BASE),
+                "--skip_feature_analysis",
+            ],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
         report_path = out_dir / "statistical_analysis.md"
         self.assertTrue(report_path.exists(), "Missing statistical_analysis.md")
         content = report_path.read_text(encoding="utf-8")
@@ -94,24 +96,18 @@ class TestParamsPropagation(RewardSpaceTestBase):
     def test_manifest_params_hash_generation(self):
         """Ensure params_hash appears when non-default simulation params differ (risk_reward_ratio altered)."""
         out_dir = self.output_path / "manifest_hash"
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "150",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-            "--risk_reward_ratio",
-            "1.5",
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=[
+                "--num_samples",
+                "150",
+                "--seed",
+                str(SEEDS.BASE),
+                "--risk_reward_ratio",
+                "1.5",
+            ],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
         manifest_path = out_dir / "manifest.json"
         self.assertTrue(manifest_path.exists(), "Missing manifest.json")
         manifest = json.loads(manifest_path.read_text())
@@ -123,22 +119,11 @@ class TestParamsPropagation(RewardSpaceTestBase):
         """When reward_shaping column exists, summary should include PBRS invariance section."""
         out_dir = self.output_path / "pbrs_invariance"
         # Use small sample for speed; rely on default shaping logic
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "180",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=["--num_samples", "180", "--seed", str(SEEDS.BASE)],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
         report_path = out_dir / "statistical_analysis.md"
         self.assertTrue(report_path.exists(), "Missing statistical_analysis.md")
         content = report_path.read_text(encoding="utf-8")
@@ -148,21 +133,15 @@ class TestParamsPropagation(RewardSpaceTestBase):
     def test_strict_diagnostics_constant_distribution_succeeds(self):
         """Run with --strict_diagnostics and low num_samples; expect success, exercising assertion branches before graceful fallback paths."""
         out_dir = self.output_path / "strict_diagnostics"
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "120",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-            "--strict_diagnostics",
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=[
+                "--num_samples",
+                "120",
+                "--seed",
+                str(SEEDS.BASE),
+                "--strict_diagnostics",
+            ],
         )
         # Should not raise; if constant distributions occur they should assert before graceful fallback paths, exercising assertion branches.
         self.assertEqual(
@@ -176,24 +155,18 @@ class TestParamsPropagation(RewardSpaceTestBase):
     def test_max_trade_duration_candles_propagation_params(self):
         """--params max_trade_duration_candles=X propagates to manifest and simulation params."""
         out_dir = self.output_path / "mtd_params"
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "120",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-            "--params",
-            "max_trade_duration_candles=96",
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=[
+                "--num_samples",
+                "120",
+                "--seed",
+                str(SEEDS.BASE),
+                "--params",
+                "max_trade_duration_candles=96",
+            ],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
         manifest_path = out_dir / "manifest.json"
         self.assertTrue(manifest_path.exists(), "Missing manifest.json")
         with open(manifest_path, "r") as f:
@@ -207,24 +180,18 @@ class TestParamsPropagation(RewardSpaceTestBase):
     def test_max_trade_duration_candles_propagation_flag(self):
         """Dynamic flag --max_trade_duration_candles X propagates identically."""
         out_dir = self.output_path / "mtd_flag"
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "120",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-            "--max_trade_duration_candles",
-            "64",
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=[
+                "--num_samples",
+                "120",
+                "--seed",
+                str(SEEDS.BASE),
+                "--max_trade_duration_candles",
+                "64",
+            ],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
         manifest_path = out_dir / "manifest.json"
         self.assertTrue(manifest_path.exists(), "Missing manifest.json")
         with open(manifest_path, "r") as f:
@@ -245,25 +212,19 @@ class TestParamsPropagation(RewardSpaceTestBase):
         - Column values align mathematically
         """
         out_dir = self.output_path / "pbrs_csv_columns"
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(SCRIPT_PATH),
-            "--num_samples",
-            "150",
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(out_dir),
-            # Enable PBRS shaping explicitly
-            "--params",
-            "exit_potential_mode=canonical",
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=out_dir,
+            args=[
+                "--num_samples",
+                "150",
+                "--seed",
+                str(SEEDS.BASE),
+                # Enable PBRS shaping explicitly
+                "--params",
+                "exit_potential_mode=canonical",
+            ],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
 
         csv_path = out_dir / "reward_samples.csv"
         self.assertTrue(csv_path.exists(), "Missing reward_samples.csv")
@@ -278,10 +239,8 @@ class TestParamsPropagation(RewardSpaceTestBase):
         # Verify all values are finite
         for col in required_cols:
             self.assertFalse(df[col].isna().any(), f"Column {col} contains NaN values")
-            self.assertTrue(
-                df[col].apply(lambda x: abs(x) < float("inf")).all(),
-                f"Column {col} contains infinite values",
-            )
+            for i, value in enumerate(df[col].to_numpy()):
+                self.assertFinite(float(value), name=f"{col}[{i}]")
 
         # Verify mathematical alignment (CSV-level invariants)
         # By construction in `calculate_reward()`: reward_shaping = pbrs_delta + invariance_correction

diff --git a/ReforceXY/reward_space_analysis/tests/components/test_reward_components.py b/ReforceXY/reward_space_analysis/tests/components/test_reward_components.py
index 416a3912678fe56d1867a9dc3123b14997ef535d..962df5d8a43c0fcf299e79ef1ccba2edbff16ef8 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/components/test_reward_components.py
+++ b/ReforceXY/reward_space_analysis/tests/components/test_reward_components.py
@@ -129,7 +129,7 @@ class TestRewardComponents(RewardSpaceTestBase):
         - Progressive scaling beyond max_duration threshold
         """
 
-        params = self.base_params(max_trade_duration_candles=100)
+        params = self.base_params(max_trade_duration_candles=PARAMS.TRADE_DURATION_MEDIUM)
         durations = list(SCENARIOS.DURATION_SCENARIOS)
         penalties = []
         for duration in durations:
@@ -476,7 +476,8 @@ class TestRewardComponents(RewardSpaceTestBase):
         - Plateau mode attenuates after grace period
         """
         modes_to_test = ["linear", "power"]
-        pnl = 0.02
+        pnl = PARAMS.PNL_SMALL
+
         pnl_target = 0.045  # 0.03 * 1.5 coefficient
         context = self.make_ctx(
             pnl=pnl,
@@ -633,7 +634,8 @@ class TestRewardComponents(RewardSpaceTestBase):
         base_factor = PARAMS.BASE_FACTOR
         profit_aim = PARAMS.PROFIT_AIM
         risk_reward_ratio = 1.0
-        max_trade_duration_candles = 100
+        max_trade_duration_candles = PARAMS.TRADE_DURATION_MEDIUM
+
         params = self.base_params(
             max_idle_duration_candles=None,
             max_trade_duration_candles=max_trade_duration_candles,
@@ -709,8 +711,8 @@ class TestRewardComponents(RewardSpaceTestBase):
             exit_additive_enabled=False,
         )
         context = self.make_ctx(
-            pnl=0.02,
-            trade_duration=50,
+            pnl=PARAMS.PNL_SMALL,
+            trade_duration=PARAMS.TRADE_DURATION_SHORT,
             idle_duration=0,
             max_unrealized_profit=0.03,
             min_unrealized_profit=0.01,

diff --git a/ReforceXY/reward_space_analysis/tests/helpers/assertions.py b/ReforceXY/reward_space_analysis/tests/helpers/assertions.py
index 101783c8e08acd14c767c7ac1a617eab0d39ea71..88f9fe20f49cd34f348c4c34a422c244d7afb953 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/helpers/assertions.py
+++ b/ReforceXY/reward_space_analysis/tests/helpers/assertions.py
@@ -1405,7 +1405,7 @@ def get_exit_factor_with_defaults(
 
         # Overriding specific parameters
         factor = get_exit_factor_with_defaults(
-            0.05, 0.5, ctx, params, base_factor=100.0
+            0.05, 0.5, ctx, params, base_factor=PARAMS.BASE_FACTOR
         )
     """
     if base_factor is None:

diff --git a/ReforceXY/reward_space_analysis/tests/integration/test_integration.py b/ReforceXY/reward_space_analysis/tests/integration/test_integration.py
index 2f691dc057aa0a8abdb8b5e9556f2a2b093f755e..e1eadef1331935541ffaf29ae3ae18cdc97bc7b3 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/integration/test_integration.py
+++ b/ReforceXY/reward_space_analysis/tests/integration/test_integration.py
@@ -14,28 +14,45 @@ from ..test_base import RewardSpaceTestBase
 
 pytestmark = pytest.mark.integration
 
+SCRIPT_PATH = Path(__file__).parent.parent.parent / "reward_space_analysis.py"
+CWD = Path(__file__).parent.parent
+
+
+def _run_cli(*, out_dir: Path, args: list[str]) -> subprocess.CompletedProcess[str]:
+    cmd = [
+        "uv",
+        "run",
+        sys.executable,
+        str(SCRIPT_PATH),
+        "--out_dir",
+        str(out_dir),
+        *args,
+    ]
+    return subprocess.run(cmd, capture_output=True, text=True, cwd=CWD)
+
+
+def _assert_cli_success(
+    testcase: unittest.TestCase, result: subprocess.CompletedProcess[str]
+) -> None:
+    testcase.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+
 
 class TestIntegration(RewardSpaceTestBase):
     """CLI + file output integration tests."""
 
     def test_cli_execution_produces_expected_files(self):
         """CLI produces expected files."""
-        cmd = [
-            "uv",
-            "run",
-            sys.executable,
-            str(Path(__file__).parent.parent.parent / "reward_space_analysis.py"),
-            "--num_samples",
-            str(SCENARIOS.SAMPLE_SIZE_SMALL),
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(self.output_path),
-        ]
-        result = subprocess.run(
-            cmd, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result = _run_cli(
+            out_dir=self.output_path,
+            args=[
+                "--num_samples",
+                str(SCENARIOS.SAMPLE_SIZE_SMALL),
+                "--seed",
+                str(SEEDS.BASE),
+            ],
         )
-        self.assertEqual(result.returncode, 0, f"CLI failed: {result.stderr}")
+        _assert_cli_success(self, result)
+
         expected_files = [
             "reward_samples.csv",
             "feature_importance.csv",
@@ -51,38 +68,27 @@ class TestIntegration(RewardSpaceTestBase):
 
     def test_manifest_structure_and_reproducibility(self):
         """Manifest structure + reproducibility."""
-        cmd1 = [
-            "uv",
-            "run",
-            sys.executable,
-            str(Path(__file__).parent.parent.parent / "reward_space_analysis.py"),
-            "--num_samples",
-            str(SCENARIOS.SAMPLE_SIZE_SMALL),
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(self.output_path / "run1"),
-        ]
-        cmd2 = [
-            "uv",
-            "run",
-            sys.executable,
-            str(Path(__file__).parent.parent.parent / "reward_space_analysis.py"),
-            "--num_samples",
-            str(SCENARIOS.SAMPLE_SIZE_SMALL),
-            "--seed",
-            str(SEEDS.BASE),
-            "--out_dir",
-            str(self.output_path / "run2"),
-        ]
-        result1 = subprocess.run(
-            cmd1, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result1 = _run_cli(
+            out_dir=self.output_path / "run1",
+            args=[
+                "--num_samples",
+                str(SCENARIOS.SAMPLE_SIZE_SMALL),
+                "--seed",
+                str(SEEDS.BASE),
+            ],
         )
-        result2 = subprocess.run(
-            cmd2, capture_output=True, text=True, cwd=Path(__file__).parent.parent
+        result2 = _run_cli(
+            out_dir=self.output_path / "run2",
+            args=[
+                "--num_samples",
+                str(SCENARIOS.SAMPLE_SIZE_SMALL),
+                "--seed",
+                str(SEEDS.BASE),
+            ],
         )
-        self.assertEqual(result1.returncode, 0)
-        self.assertEqual(result2.returncode, 0)
+        _assert_cli_success(self, result1)
+        _assert_cli_success(self, result2)
+
         for run_dir in ["run1", "run2"]:
             with open(self.output_path / run_dir / "manifest.json", "r") as f:
                 manifest = json.load(f)
@@ -105,6 +111,7 @@ class TestIntegration(RewardSpaceTestBase):
             self.assertNotIn("params", manifest)
             self.assertEqual(manifest["num_samples"], SCENARIOS.SAMPLE_SIZE_SMALL)
             self.assertEqual(manifest["seed"], SEEDS.BASE)
+
         with open(self.output_path / "run1" / "manifest.json", "r") as f:
             manifest1 = json.load(f)
         with open(self.output_path / "run2" / "manifest.json", "r") as f:

diff --git a/ReforceXY/reward_space_analysis/tests/integration/test_reward_calculation.py b/ReforceXY/reward_space_analysis/tests/integration/test_reward_calculation.py
index 01e80d7d02342c190def2aec1554f17d1f4fbf90..caa59b799ce4cbe8a564607f4cc4f4a979d65d07 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/integration/test_reward_calculation.py
+++ b/ReforceXY/reward_space_analysis/tests/integration/test_reward_calculation.py
@@ -12,6 +12,7 @@ Detailed invariant ownership is tracked in tests/README.md Coverage Mapping.
 import pytest
 
 from reward_space_analysis import (
+    DEFAULT_MODEL_REWARD_PARAMETERS,
     Actions,
     Positions,
 )
@@ -20,6 +21,14 @@ from ..constants import PARAMS, TOLERANCE
 from ..helpers import calculate_reward_with_defaults
 from ..test_base import RewardSpaceTestBase
 
+_DEFAULT_MAX_TRADE_DURATION_CANDLES = DEFAULT_MODEL_REWARD_PARAMETERS.get(
+    "max_trade_duration_candles"
+)
+if isinstance(_DEFAULT_MAX_TRADE_DURATION_CANDLES, (int, float)):
+    HOLD_PENALTY_ACTIVE_TRADE_DURATION = int(_DEFAULT_MAX_TRADE_DURATION_CANDLES) + 1
+else:
+    HOLD_PENALTY_ACTIVE_TRADE_DURATION = PARAMS.TRADE_DURATION_LONG
+
 pytestmark = pytest.mark.integration
 
 
@@ -39,9 +48,9 @@ class TestRewardCalculation(RewardSpaceTestBase):
         scenarios = [
             (
                 "hold_penalty_active",
-                dict(
+                self.make_ctx(
                     pnl=0.0,
-                    trade_duration=160,  # > default threshold
+                    trade_duration=HOLD_PENALTY_ACTIVE_TRADE_DURATION,  # > default threshold
                     idle_duration=0,
                     max_unrealized_profit=0.02,
                     min_unrealized_profit=-0.01,
@@ -49,10 +58,11 @@ class TestRewardCalculation(RewardSpaceTestBase):
                     action=Actions.Neutral,
                 ),
                 "hold_penalty",
+                True,
             ),
             (
                 "idle_penalty_active",
-                dict(
+                self.make_ctx(
                     pnl=0.0,
                     trade_duration=0,
                     idle_duration=25,
@@ -62,10 +72,11 @@ class TestRewardCalculation(RewardSpaceTestBase):
                     action=Actions.Neutral,
                 ),
                 "idle_penalty",
+                True,
             ),
             (
                 "profitable_exit_long",
-                dict(
+                self.make_ctx(
                     pnl=0.04,
                     trade_duration=40,
                     idle_duration=0,
@@ -75,10 +86,11 @@ class TestRewardCalculation(RewardSpaceTestBase):
                     action=Actions.Long_exit,
                 ),
                 "exit_component",
+                True,
             ),
             (
                 "invalid_action_penalty",
-                dict(
+                self.make_ctx(
                     pnl=0.01,
                     trade_duration=10,
                     idle_duration=0,
@@ -88,16 +100,16 @@ class TestRewardCalculation(RewardSpaceTestBase):
                     action=Actions.Long_exit,  # invalid pairing
                 ),
                 "invalid_penalty",
+                False,
             ),
         ]
 
-        for name, ctx_kwargs, expected_component in scenarios:
+        for name, ctx, expected_component, action_masking in scenarios:
             with self.subTest(scenario=name):
-                ctx = self.make_ctx(**ctx_kwargs)
                 breakdown = calculate_reward_with_defaults(
                     ctx,
                     self.DEFAULT_PARAMS,
-                    action_masking=expected_component != "invalid_penalty",
+                    action_masking=action_masking,
                 )
 
                 value = getattr(breakdown, expected_component)

diff --git a/ReforceXY/reward_space_analysis/tests/pbrs/test_pbrs.py b/ReforceXY/reward_space_analysis/tests/pbrs/test_pbrs.py
index caede000edf17f24ebed65ca76e3158b5f785d35..31c6ef7b9e193dd27912bce9a288bc7c4ff74cad 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/pbrs/test_pbrs.py
+++ b/ReforceXY/reward_space_analysis/tests/pbrs/test_pbrs.py
@@ -193,7 +193,8 @@ class TestPBRS(RewardSpaceTestBase):
         )
         unique_flags = set(df["pbrs_invariant"].unique().tolist())
         self.assertEqual(unique_flags, {True}, f"Unexpected invariant flags: {unique_flags}")
-        self.assertTrue(np.isfinite(df["reward_shaping"]).all())
+        for v in df["reward_shaping"].tolist():
+            self.assertFinite(float(v), name="reward_shaping")
         self.assertLessEqual(float(df["reward_shaping"].abs().max()), PBRS.MAX_ABS_SHAPING)
 
     def test_non_canonical_flag_false_and_sum_nonzero(self):
@@ -405,7 +406,7 @@ class TestPBRS(RewardSpaceTestBase):
         self.assertAlmostEqual(shaping, -0.789, delta=TOLERANCE.IDENTITY_RELAXED)
         residual = total - base_reward - shaping
         self.assertAlmostEqual(residual, 0.0, delta=TOLERANCE.IDENTITY_RELAXED)
-        self.assertTrue(np.isfinite(total))
+        self.assertFinite(float(total), name="total")
 
     def test_canonical_mode_suppresses_additives_even_if_enabled(self):
         """Verifies canonical mode forces entry/exit additive terms to zero."""
@@ -594,7 +595,7 @@ class TestPBRS(RewardSpaceTestBase):
                 position=Positions.Neutral, action=action, pnl=0.0, trade_duration=0
             )
             breakdown = calculate_reward_with_defaults(ctx, params, prev_potential=0.0)
-            self.assertTrue(np.isfinite(breakdown.next_potential))
+            self.assertFinite(float(breakdown.next_potential), name="next_potential")
             # With any nonzero fees, immediate unrealized pnl should be negative.
             self.assertLess(
                 breakdown.next_potential,
@@ -1011,7 +1012,7 @@ class TestPBRS(RewardSpaceTestBase):
             pnl_duration_vol_scale=PARAMS.PNL_DUR_VOL_SCALE,
         )
         abs_sum = float(df["reward_shaping"].abs().sum())
-        self.assertTrue(np.isfinite(abs_sum))
+        self.assertFinite(abs_sum, name="abs_sum")
         self.assertLessEqual(float(df["reward_shaping"].abs().max()), PBRS.MAX_ABS_SHAPING)
         # Even with trajectories, Σ can partially cancel; use L1 magnitude instead.
         self.assertGreater(
@@ -1106,8 +1107,8 @@ class TestPBRS(RewardSpaceTestBase):
                     params=params,
                 )
             )
-            self.assertTrue(np.isfinite(shap))
-            self.assertTrue(np.isfinite(next_pot))
+            self.assertFinite(float(shap), name="shaping")
+            self.assertFinite(float(next_pot), name="next_potential")
             self.assertLessEqual(abs(shap), PBRS.MAX_ABS_SHAPING)
 
     def test_report_cumulative_invariance_aggregation(self):

diff --git a/ReforceXY/reward_space_analysis/tests/robustness/test_branch_coverage.py b/ReforceXY/reward_space_analysis/tests/robustness/test_branch_coverage.py
index 96d4034df3e0395b12b80101ff7b7fe8cab92ab9..80b87afa8ad26c2b8fb408851ee2beaa1d1476a8 100644 (file)
--- a/ReforceXY/reward_space_analysis/tests/robustness/test_branch_coverage.py
+++ b/ReforceXY/reward_space_analysis/tests/robustness/test_branch_coverage.py
@@ -4,6 +4,7 @@ import unittest
 import pytest
 
 from reward_space_analysis import (
+    DEFAULT_MODEL_REWARD_PARAMETERS,
     Actions,
     Positions,
     RewardContext,
@@ -22,6 +23,11 @@ from ..helpers import (
 )
 from ..test_base import make_ctx
 
+_raw_max_trade_duration = DEFAULT_MODEL_REWARD_PARAMETERS.get("max_trade_duration_candles")
+DEFAULT_MAX_TRADE_DURATION_CANDLES = (
+    float(_raw_max_trade_duration) if isinstance(_raw_max_trade_duration, (int, float)) else 128.0
+)
+
 
 class _PyTestAdapter(unittest.TestCase):
     """Adapter leveraging unittest.TestCase for assertion + subTest support.
@@ -234,7 +240,7 @@ def test_hold_penalty_short_duration_returns_zero():
 
     **Setup:**
     - Trade duration: 1 candle (short)
-    - Max trade duration: 128 candles
+    - Max trade duration: DEFAULT_MAX_TRADE_DURATION_CANDLES
     - Position: Long, Action: Neutral (hold)
 
     **Assertions:**
@@ -242,14 +248,14 @@ def test_hold_penalty_short_duration_returns_zero():
     """
     context = make_ctx(
         pnl=0.0,
-        trade_duration=1,  # shorter than default max trade duration (128)
+        trade_duration=1,  # shorter than default max trade duration
         idle_duration=0,
         max_unrealized_profit=0.0,
         min_unrealized_profit=0.0,
         position=Positions.Long,
         action=Actions.Neutral,
     )
-    params: RewardParams = {"max_trade_duration_candles": 128.0}
+    params: RewardParams = {"max_trade_duration_candles": DEFAULT_MAX_TRADE_DURATION_CANDLES}
     penalty = _hold_penalty(context, hold_factor=1.0, params=params)
     assert penalty == 0.0
 

diff --git a/ReforceXY/reward_space_analysis/uv.lock b/ReforceXY/reward_space_analysis/uv.lock
index c08f221f12eeefb2398bf85498ad7c6acffa3365..fbd2d3c7d512420d28a7781f3670ebd9c94ee712 100644 (file)
--- a/ReforceXY/reward_space_analysis/uv.lock
+++ b/ReforceXY/reward_space_analysis/uv.lock
@@ -17,89 +17,89 @@ wheels = [
 
 [[package]]
 name = "coverage"
-version = "7.12.0"
+version = "7.13.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/89/26/4a96807b193b011588099c3b5c89fbb05294e5b90e71018e065465f34eb6/coverage-7.12.0.tar.gz", hash = "sha256:fc11e0a4e372cb5f282f16ef90d4a585034050ccda536451901abfb19a57f40c", size = 819341, upload-time = "2025-11-18T13:34:20.766Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/b6/45/2c665ca77ec32ad67e25c77daf1cee28ee4558f3bc571cdbaf88a00b9f23/coverage-7.13.0.tar.gz", hash = "sha256:a394aa27f2d7ff9bc04cf703817773a59ad6dfbd577032e690f961d2460ee936", size = 820905, upload-time = "2025-12-08T13:14:38.055Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/5a/0c/0dfe7f0487477d96432e4815537263363fb6dd7289743a796e8e51eabdf2/coverage-7.12.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:aa124a3683d2af98bd9d9c2bfa7a5076ca7e5ab09fdb96b81fa7d89376ae928f", size = 217535, upload-time = "2025-11-18T13:32:08.812Z" },
-    { url = "https://files.pythonhosted.org/packages/9b/f5/f9a4a053a5bbff023d3bec259faac8f11a1e5a6479c2ccf586f910d8dac7/coverage-7.12.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d93fbf446c31c0140208dcd07c5d882029832e8ed7891a39d6d44bd65f2316c3", size = 218044, upload-time = "2025-11-18T13:32:10.329Z" },
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diff --git a/ReforceXY/user_data/config-template.json b/ReforceXY/user_data/config-template.json
index 34f497c39a4a9c92f70866c77c2cf8b3f6b1e5b7..0e5ed803772b93f2b1f2cb47808578c422b32f16 100644 (file)
--- a/ReforceXY/user_data/config-template.json
+++ b/ReforceXY/user_data/config-template.json
@@ -159,9 +159,9 @@
       "model_type": "MaskablePPO",
       "policy_type": "MlpPolicy",
       "model_reward_parameters": {
-        "rr": 2,
+        "rr": 2.0,
         "profit_aim": 0.025,
-        "win_reward_factor": 2,
+        "win_reward_factor": 2.0,
         "max_trade_duration_candles": 96 // Maximum trade duration in candles
       },
       "train_cycles": 25,

diff --git a/ReforceXY/user_data/freqaimodels/ReforceXY.py b/ReforceXY/user_data/freqaimodels/ReforceXY.py
index 1e55c476271d5c670739e9e825684c7ea3bf508b..c04ffbece6c7ca09284dfd1098d04358a722e5c0 100644 (file)
--- a/ReforceXY/user_data/freqaimodels/ReforceXY.py
+++ b/ReforceXY/user_data/freqaimodels/ReforceXY.py
@@ -2217,8 +2217,7 @@ class MyRLEnv(Base5ActionRLEnv):
     ) -> tuple[float, float, float]:
         """Compute potential-based reward shaping (PBRS) components.
 
-        This method computes the PBRS shaping terms without combining them with the base reward,
-        allowing the caller to construct the total reward as R'(s,a,s') = R(s,a,s') + Δ(s,a,s') + additives.
+        This method computes the PBRS shaping terms.
 
         Canonical PBRS Formula
         ----------------------