SIENTIAPDE-1430: Introduce static_threshold parameter for static window removal.

This parameter allows customizing the threshold (1-1000) used when rem_static_win is enabled, defaulting to 1 if null.
Updates include parameter definition, business rule validation, repository logic for passing the threshold, documentation in README.md and PIPELINE_PARAMS_CHANGELOG.md, and new unit and integration tests.

tests/utils/models/test_train_model_params.py

@@ -34,6 +34,7 @@ def valid_train_params_dict():
         'end_date': None,
         'scaler_name': 'Standard Scaler',
         'support_filters': {},
+        'static_threshold': None,
     }
 
 
@@ -564,3 +565,96 @@ def test_validate_business_rules_polynomial_regression_valid(valid_train_params_
     params = TrainModelParams.from_dict(valid_train_params_dict)
 
     params.validate_business_rules()  # Should not raise
+
+
+def test_validate_business_rules_static_threshold_valid(valid_train_params_dict):
+    """Test validate_business_rules accepts valid static_threshold when rem_static_win is True."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['rem_static_win'] = True
+    valid_train_params_dict['static_threshold'] = 500
+    params = TrainModelParams.from_dict(valid_train_params_dict)
+
+    params.validate_business_rules()  # Should not raise
+
+
+def test_validate_business_rules_static_threshold_min_valid(valid_train_params_dict):
+    """Test validate_business_rules accepts static_threshold = 1."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['rem_static_win'] = True
+    valid_train_params_dict['static_threshold'] = 1
+    params = TrainModelParams.from_dict(valid_train_params_dict)
+
+    params.validate_business_rules()  # Should not raise
+
+
+def test_validate_business_rules_static_threshold_max_valid(valid_train_params_dict):
+    """Test validate_business_rules accepts static_threshold = 1000."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['rem_static_win'] = True
+    valid_train_params_dict['static_threshold'] = 1000
+    params = TrainModelParams.from_dict(valid_train_params_dict)
+
+    params.validate_business_rules()  # Should not raise
+
+
+def test_validate_business_rules_static_threshold_below_min(valid_train_params_dict):
+    """Test validate_business_rules raises error when static_threshold < 1."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['rem_static_win'] = True
+    valid_train_params_dict['static_threshold'] = 0
+    params = TrainModelParams.from_dict(valid_train_params_dict)
+
+    with pytest.raises(ValueError, match='static_threshold must be between 1 and 1000, got 0'):
+        params.validate_business_rules()
+
+
+def test_validate_business_rules_static_threshold_above_max(valid_train_params_dict):
+    """Test validate_business_rules raises error when static_threshold > 1000."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['rem_static_win'] = True
+    valid_train_params_dict['static_threshold'] = 1001
+    params = TrainModelParams.from_dict(valid_train_params_dict)
+
+    with pytest.raises(ValueError, match='static_threshold must be between 1 and 1000, got 1001'):
+        params.validate_business_rules()
+
+
+def test_validate_business_rules_static_threshold_none_when_rem_static_win_true(
+    valid_train_params_dict,
+):
+    """Test validate_business_rules accepts None static_threshold when rem_static_win is True."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['rem_static_win'] = True
+    valid_train_params_dict['static_threshold'] = None
+    params = TrainModelParams.from_dict(valid_train_params_dict)
+
+    params.validate_business_rules()  # Should not raise - None is allowed
+
+
+def test_validate_business_rules_static_threshold_ignored_when_rem_static_win_false(
+    valid_train_params_dict,
+):
+    """Test validate_business_rules ignores static_threshold when rem_static_win is False."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['rem_static_win'] = False
+    valid_train_params_dict['static_threshold'] = 5000  # Invalid value, but should be ignored
+    params = TrainModelParams.from_dict(valid_train_params_dict)
+
+    params.validate_business_rules()  # Should not raise - validation skipped
+
+
+def test_from_dict_static_threshold_type_error(valid_train_params_dict):
+    """Test from_dict raises TypeError when static_threshold has wrong type."""
+    from model_manager.utils.models.train_model_params import TrainModelParams
+
+    valid_train_params_dict['static_threshold'] = 'not_an_int'
+
+    with pytest.raises(TypeError, match='static_threshold must be of type int, but got str'):
+        TrainModelParams.from_dict(valid_train_params_dict)

tests/utils/models/test_train_model_result.py

@@ -40,6 +40,7 @@ def sample_params():
         end_date=None,
         scaler_name='Standard Scaler',
         support_filters={},
+        static_threshold=None,
     )
 
 

tests/utils/repository/test_model_repository.py

@@ -55,6 +55,8 @@ def mock_train_result():
     result.params.include_ar = False
     result.params.train_size = 80
     result.params.removed_intervals = []
+    result.params.rem_static_win = True
+    result.params.static_threshold = None
     result.run_name = 'test_run'
     result.run_dir = '/tmp/test_run'  # noqa: S108
     result.report_path = '/tmp/test_run/report.html'  # noqa: S108

tests/utils/repository/test_training_repository.py

@@ -56,6 +56,7 @@ def sample_params():
         end_date=None,
         scaler_name='None',
         support_filters={},
+        static_threshold=None,
     )
 
 
@@ -137,6 +138,7 @@ class TestExtractModelEquation:
             end_date=None,
             scaler_name='None',
             support_filters={},
+            static_threshold=None,
         )
 
         # Mock model with single coefficient
@@ -221,12 +223,33 @@ class TestInitDataPreprocessor:
         assert preprocessor.ar_var is None
 
     def test_init_preprocessor_with_static_removal(self, training_repo, sample_params):
-        """Test preprocessor with static window removal enabled."""
+        """Test preprocessor with static window removal enabled and no static_threshold."""
         sample_params.rem_static_win = True
+        sample_params.static_threshold = None
         preprocessor = training_repo._init_data_preprocessor(sample_params)
 
         assert preprocessor.static_threshold == 1
 
+    def test_init_preprocessor_with_static_removal_custom_threshold(
+        self, training_repo, sample_params
+    ):
+        """Test preprocessor with static window removal and custom static_threshold."""
+        sample_params.rem_static_win = True
+        sample_params.static_threshold = 500
+        preprocessor = training_repo._init_data_preprocessor(sample_params)
+
+        assert preprocessor.static_threshold == 500
+
+    def test_init_preprocessor_without_static_removal_ignores_threshold(
+        self, training_repo, sample_params
+    ):
+        """Test preprocessor without static removal ignores static_threshold."""
+        sample_params.rem_static_win = False
+        sample_params.static_threshold = 500
+        preprocessor = training_repo._init_data_preprocessor(sample_params)
+
+        assert preprocessor.static_threshold is None
+
     def test_init_preprocessor_lag_configuration(self, training_repo, sample_params):
         """Test preprocessor lag configuration."""
         sample_params.lag_train = {'var1': 5, 'var2': 5, 'var3': 5}