From 0cf7b5415aae7fb4a4e1db5227173b360b70bc6e Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Wed, 5 Aug 2026 17:15:17 +0200
Subject: [PATCH 01/10] [ARCHITECTURE] Instantiate enabled quality metrics in
 QC pipeline

- Initialize the MetricsRegistry in the pipeline constructor
- Instantiate enabled quality metric implementations from configuration
- Add unit tests for valid and invalid metric configurations
---
 src/wf_psf/quality_control/pipeline.py        | 45 +++++++++++------
 .../data/valid/imaginary_metric.yaml          |  4 ++
 .../test_quality_control/pipeline_test.py     | 48 +++++++++++++++++++
 3 files changed, 83 insertions(+), 14 deletions(-)
 create mode 100644 src/wf_psf/tests/test_quality_control/data/valid/imaginary_metric.yaml
 create mode 100644 src/wf_psf/tests/test_quality_control/pipeline_test.py

diff --git a/src/wf_psf/quality_control/pipeline.py b/src/wf_psf/quality_control/pipeline.py
index 0624e0ef..02a18ec6 100644
--- a/src/wf_psf/quality_control/pipeline.py
+++ b/src/wf_psf/quality_control/pipeline.py
@@ -2,11 +2,10 @@
 
 Defines the orchestration layer for dataset quality control.
 
-The QualityControlPipeline coordinates quality metric evaluation,
-application of rejection policies, reporting, and dataset filtering.
-Individual quality metrics and rejection policies are provided through
-their respective interfaces, allowing new methods to be added without
-modifying the pipeline implementation.
+The QualityControlPipeline coordinates quality metric evaluation and
+sample rejection. Individual quality metrics and rejection policies are
+provided through their respective interfaces, allowing new methods to
+be added without modifying the pipeline implementation.
 
 :Authors: Jennifer Pollack <jennifer.pollack@cea.fr>
 
@@ -15,6 +14,12 @@
 from dataclasses import dataclass
 import numpy as np
 
+from wf_psf.quality_control.config import QualityControlConfigHandler
+from wf_psf.quality_control.metrics.base import QualityMetric
+from wf_psf.quality_control.metrics.registry import build_metrics_registry
+from wf_psf.quality_control.rejection.registry import build_rejection_policy_registry
+
+
 @dataclass
 class QualityControlResult:
     """Results produced by the quality control pipeline.
@@ -50,15 +55,27 @@ class QualityControlPipeline:
     of the pipeline execution.
     """
 
-    def __init__(
-            self,
-            metrics,
-            rejection_policies,
-    ):
-        ...
+    def __init__(self, qc_config_path):
+        self.config = QualityControlConfigHandler(qc_config_path).load()
+        self.metrics_registry = build_metrics_registry()
+        self.rejection_registry = build_rejection_policy_registry()
 
-    def run(self, dataset):
+    def _instantiate_metrics(self) -> dict[str, QualityMetric]:
+        """Instantiate enabled quality metric implementation from configuration."""
+        metrics = {}
 
-        ...
+        for name, metric_config in self.config.metrics.items():
+            if not metric_config.enabled:
+                continue
 
-        return QualityControlResult(...)
\ No newline at end of file
+            metric_cls = self.metrics_registry.get(name)
+
+            metrics[name] = metric_cls()
+
+        return metrics
+
+    def run(self, dataset):
+        """Run quality control pipeline."""
+        #        metrics = self._instantiate_metrics()
+        ...
+        return QualityControlResult(...)
diff --git a/src/wf_psf/tests/test_quality_control/data/valid/imaginary_metric.yaml b/src/wf_psf/tests/test_quality_control/data/valid/imaginary_metric.yaml
new file mode 100644
index 00000000..eb6ebf8d
--- /dev/null
+++ b/src/wf_psf/tests/test_quality_control/data/valid/imaginary_metric.yaml
@@ -0,0 +1,4 @@
+metrics:
+
+  imaginary_metric:
+    enabled: true
\ No newline at end of file
diff --git a/src/wf_psf/tests/test_quality_control/pipeline_test.py b/src/wf_psf/tests/test_quality_control/pipeline_test.py
new file mode 100644
index 00000000..254dccf7
--- /dev/null
+++ b/src/wf_psf/tests/test_quality_control/pipeline_test.py
@@ -0,0 +1,48 @@
+from pathlib import Path
+import pytest
+
+from wf_psf.quality_control.pipeline import QualityControlPipeline
+from wf_psf.quality_control.config import QualityControlConfig
+from wf_psf.quality_control.metrics.mask_obscuration import MaskObscurationMetric
+from wf_psf.quality_control.metrics.goodness_of_fit import GoodnessOfFitMetric
+from wf_psf.quality_control.rejection.threshold import ThresholdRejectionPolicy
+
+
+@pytest.fixture
+def pipeline_factory():
+    def build(config_file):
+        path = Path(__file__).parent / "data" / config_file
+        return QualityControlPipeline(path)
+
+    return build
+
+
+def test_pipeline_constructor(pipeline_factory):
+    pipeline = pipeline_factory("valid/quality_control.yaml")
+
+    # Check config
+    assert isinstance(pipeline.config, QualityControlConfig)
+
+    # Check metrics registry
+    assert pipeline.metrics_registry.get("mask_obscuration") is MaskObscurationMetric
+    assert pipeline.metrics_registry.get("goodness_of_fit") is GoodnessOfFitMetric
+
+    # Check rejection registry
+    assert pipeline.rejection_registry.get("threshold") is ThresholdRejectionPolicy
+
+
+def test_pipeline_instantiate_metrics_valid(pipeline_factory):
+    pipeline = pipeline_factory("valid/quality_control.yaml")
+
+    metrics = pipeline._instantiate_metrics()
+
+    assert len(metrics) == 2
+    assert isinstance(metrics["mask_obscuration"], MaskObscurationMetric)
+    assert isinstance(metrics["goodness_of_fit"], GoodnessOfFitMetric)
+
+
+def test_pipeline_instantiate_metrics_unknown_metric(pipeline_factory):
+    pipeline = pipeline_factory("valid/imaginary_metric.yaml")
+
+    with pytest.raises(KeyError):
+        pipeline._instantiate_metrics()

From e73cf8ce4d3b3d61fa495e3019ce3e78948c6c44 Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Thu, 20 Aug 2026 16:56:17 +0200
Subject: [PATCH 02/10] [architecture] add quality control context definition

---
 src/wf_psf/quality_control/context.py | 31 +++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)
 create mode 100644 src/wf_psf/quality_control/context.py

diff --git a/src/wf_psf/quality_control/context.py b/src/wf_psf/quality_control/context.py
new file mode 100644
index 00000000..824f5b69
--- /dev/null
+++ b/src/wf_psf/quality_control/context.py
@@ -0,0 +1,31 @@
+"""Quality control context.
+
+Encapsulates contextual information, such as datasets and resolved resources,
+required by the quality control pipeline and its metrics.
+
+:Authors:
+    Jennifer Pollack <jennifer.pollack@cea.fr>
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+
+@dataclass
+class QualityControlContext:
+    """Context shared across the quality control pipeline.
+
+    Attributes
+    ----------
+    dataset : dict[str, Any]
+        Dataset or data container supplied to the quality control pipeline.
+
+    resources : dict[str, Any]
+        Ready-to-use resources required by enabled quality metrics, keyed by
+        resource identifier.
+    """
+
+    dataset: Any = None
+    resources: dict[str, Any] = field(default_factory=dict)

From a2b3c8143d88118cdfb8ee62742879fdc552e9e2 Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Tue, 25 Aug 2026 17:24:58 +0200
Subject: [PATCH 03/10] Allow flexible dataset typing in quality control
 context

---
 src/wf_psf/quality_control/context.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/wf_psf/quality_control/context.py b/src/wf_psf/quality_control/context.py
index 824f5b69..f085de7f 100644
--- a/src/wf_psf/quality_control/context.py
+++ b/src/wf_psf/quality_control/context.py
@@ -19,7 +19,7 @@ class QualityControlContext:
 
     Attributes
     ----------
-    dataset : dict[str, Any]
+    dataset : Any
         Dataset or data container supplied to the quality control pipeline.
 
     resources : dict[str, Any]
@@ -27,5 +27,5 @@ class QualityControlContext:
         resource identifier.
     """
 
-    dataset: Any = None
+    dataset: Any
     resources: dict[str, Any] = field(default_factory=dict)

From dd0624f3756e440413f4819c97d8226dc93dbc79 Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Tue, 25 Aug 2026 17:25:44 +0200
Subject: [PATCH 04/10] Add value attribute to ThresholdRejectionPolicy

---
 src/wf_psf/quality_control/rejection/threshold.py | 15 ++++++++++++++-
 1 file changed, 14 insertions(+), 1 deletion(-)

diff --git a/src/wf_psf/quality_control/rejection/threshold.py b/src/wf_psf/quality_control/rejection/threshold.py
index f4936059..3a2590b5 100644
--- a/src/wf_psf/quality_control/rejection/threshold.py
+++ b/src/wf_psf/quality_control/rejection/threshold.py
@@ -16,10 +16,23 @@
 
 
 class ThresholdRejectionPolicy(RejectionPolicy):
-    """Reject dataset samples based on configurable metric thresholds."""
+    """Reject dataset samples based on configurable metric threshold.
+
+    Attributes
+    ----------
+    name : str
+        Policy identifier used by the rejection policy registry.
+
+    value : float
+        Threshold applied by the rejection policy.
+
+    """
 
     name = "threshold"
 
+    def __init__(self, value: float):
+        self.value = value
+
     def apply(self, metric: np.ndarray) -> np.ndarray:
         """Apply threshold-based rejection to metric values."""
         raise NotImplementedError

From c02eea346a6139b8beba0a5a41d500cd0616998a Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Tue, 25 Aug 2026 17:29:58 +0200
Subject: [PATCH 05/10] Update structure of rejection policy section in
 configuration fixture

---
 .../data/invalid/rejection_metric_not_enabled.yaml            | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/src/wf_psf/tests/test_quality_control/data/invalid/rejection_metric_not_enabled.yaml b/src/wf_psf/tests/test_quality_control/data/invalid/rejection_metric_not_enabled.yaml
index 0dc25183..1b76b0fe 100644
--- a/src/wf_psf/tests/test_quality_control/data/invalid/rejection_metric_not_enabled.yaml
+++ b/src/wf_psf/tests/test_quality_control/data/invalid/rejection_metric_not_enabled.yaml
@@ -19,4 +19,6 @@ rejection:
 
   mask_obscuration:
     enabled: true
-    threshold: 0.25
+    policy:
+      threshold:
+        value: 0.25

From c0b79545d58cf571c577706edec4a0d0717ab68c Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Tue, 25 Aug 2026 17:31:10 +0200
Subject: [PATCH 06/10] Implement minimal quality control pipeline
 orchestration

- Add helpers to instantiate enabled metrics and rejection policies
- Build the processing sequence for resource resolution, metric computation, and policy application
- Add unit and integration tests for the orchestration
- Clean up whitespace in the quality control configuration fixture
---
 src/wf_psf/quality_control/pipeline.py        | 90 +++++++++++++++++--
 .../data/valid/quality_control.yaml           |  1 -
 .../test_quality_control/pipeline_test.py     | 75 ++++++++++++++++
 3 files changed, 159 insertions(+), 7 deletions(-)

diff --git a/src/wf_psf/quality_control/pipeline.py b/src/wf_psf/quality_control/pipeline.py
index 02a18ec6..4ac645ba 100644
--- a/src/wf_psf/quality_control/pipeline.py
+++ b/src/wf_psf/quality_control/pipeline.py
@@ -15,9 +15,12 @@
 import numpy as np
 
 from wf_psf.quality_control.config import QualityControlConfigHandler
+from wf_psf.quality_control.context import QualityControlContext
 from wf_psf.quality_control.metrics.base import QualityMetric
 from wf_psf.quality_control.metrics.registry import build_metrics_registry
+from wf_psf.quality_control.rejection.base import RejectionPolicy
 from wf_psf.quality_control.rejection.registry import build_rejection_policy_registry
+from wf_psf.quality_control.resources import Resources
 
 
 @dataclass
@@ -61,7 +64,18 @@ def __init__(self, qc_config_path):
         self.rejection_registry = build_rejection_policy_registry()
 
     def _instantiate_metrics(self) -> dict[str, QualityMetric]:
-        """Instantiate enabled quality metric implementation from configuration."""
+        """Instantiate enabled quality metric implementations from configuration.
+
+        Returns
+        -------
+        dict[str, QualityMetric]
+            Enabled quality metric implementations keyed by metric name.
+
+        Notes
+        -----
+        The quality control configuration is assumed to have been validated
+        before policy instantiation.
+        """
         metrics = {}
 
         for name, metric_config in self.config.metrics.items():
@@ -74,8 +88,72 @@ def _instantiate_metrics(self) -> dict[str, QualityMetric]:
 
         return metrics
 
-    def run(self, dataset):
-        """Run quality control pipeline."""
-        #        metrics = self._instantiate_metrics()
-        ...
-        return QualityControlResult(...)
+    def _instantiate_rejection_policies(self) -> dict[str, RejectionPolicy]:
+        """Instantiate enabled rejection policy implementations.
+
+        Returns
+        -------
+        dict[str, RejectionPolicy]
+            Enabled rejection policy implementations keyed by metric name.
+
+        Notes
+        -----
+        The quality control configuration is assumed to have been validated
+        before policy instantiation.
+        """
+        rejection_policies = {}
+
+        for metric_name, rejection_config in self.config.rejection.items():
+            if not rejection_config.enabled:
+                continue
+
+            policy_name, policy_params = next(iter(rejection_config.policy.items()))
+            policy_cls = self.rejection_registry.get(policy_name)
+
+            rejection_policies[metric_name] = policy_cls(**policy_params)
+        return rejection_policies
+
+    def run(self, dataset, provided_resources=None):
+        """Run quality control pipeline.
+
+        Parameters
+        ----------
+        dataset : Any
+            Dataset or data container supplied to the quality control pipeline.
+
+        provided_resources : Mapping[str, Any] or None
+            Ready-to-use resources supplied by the pipeline caller, keyed by resource identifier.
+
+        Notes
+        -----
+        The pipeline is expected to be invoked only when at least one quality metric is enabled in the quality control configuration.
+        """
+        resource_manager = Resources(self.config)
+        resolved_resources = resource_manager.resolve(provided_resources)
+
+        context = QualityControlContext(dataset, resolved_resources)
+
+        metrics = self._instantiate_metrics()
+
+        metric_results = {
+            name: metric.compute(context) for name, metric in metrics.items()
+        }
+
+        rejection_policies = self._instantiate_rejection_policies()
+
+        rejection_masks = {
+            name: policy.apply(metric_results[name])
+            for name, policy in rejection_policies.items()
+        }
+
+        if rejection_masks:
+            valid_mask = np.logical_and.reduce(list(rejection_masks.values()))
+        else:
+            metric_result = next(iter(metric_results.values()))
+            valid_mask = np.ones(metric_result.shape, dtype=bool)
+
+        return QualityControlResult(
+            metrics=metric_results,
+            rejection_masks=rejection_masks,
+            valid_mask=valid_mask,
+        )
diff --git a/src/wf_psf/tests/test_quality_control/data/valid/quality_control.yaml b/src/wf_psf/tests/test_quality_control/data/valid/quality_control.yaml
index d7222a92..7a5e4636 100644
--- a/src/wf_psf/tests/test_quality_control/data/valid/quality_control.yaml
+++ b/src/wf_psf/tests/test_quality_control/data/valid/quality_control.yaml
@@ -18,7 +18,6 @@ metrics:
     enabled: true
     required_resources:
       - psf_models.standard
-
     params:
       statistic: reduced_chi_square
       normalize_residuals: true
diff --git a/src/wf_psf/tests/test_quality_control/pipeline_test.py b/src/wf_psf/tests/test_quality_control/pipeline_test.py
index 254dccf7..5f5d8e01 100644
--- a/src/wf_psf/tests/test_quality_control/pipeline_test.py
+++ b/src/wf_psf/tests/test_quality_control/pipeline_test.py
@@ -1,5 +1,7 @@
+import numpy as np
 from pathlib import Path
 import pytest
+from unittest.mock import patch
 
 from wf_psf.quality_control.pipeline import QualityControlPipeline
 from wf_psf.quality_control.config import QualityControlConfig
@@ -46,3 +48,76 @@ def test_pipeline_instantiate_metrics_unknown_metric(pipeline_factory):
 
     with pytest.raises(KeyError):
         pipeline._instantiate_metrics()
+
+
+def test_pipeline_instantiate_rejection_policy_valid(pipeline_factory):
+    pipeline = pipeline_factory("valid/quality_control.yaml")
+
+    rejection_policies = pipeline._instantiate_rejection_policies()
+
+    assert len(rejection_policies) == 1
+    assert isinstance(rejection_policies["mask_obscuration"], ThresholdRejectionPolicy)
+    assert rejection_policies["mask_obscuration"].value == 3.0
+
+    assert "goodness_of_fit" not in rejection_policies
+
+
+# Test pipeline runner
+def test_pipeline_run(pipeline_factory):
+    metric_result = np.array([1.0, 2.0, 3.0])
+    rejection_mask = np.array([True, False, True])
+
+    with (
+        patch.object(
+            MaskObscurationMetric,
+            "compute",
+            return_value=metric_result,
+        ) as mock_mask_compute,
+        patch.object(
+            GoodnessOfFitMetric,
+            "compute",
+            return_value=metric_result,
+        ) as mock_gof_compute,
+        patch.object(
+            ThresholdRejectionPolicy,
+            "apply",
+            return_value=rejection_mask,
+        ) as mock_apply,
+    ):
+        pipeline = pipeline_factory("valid/quality_control.yaml")
+
+        dataset = np.array([1.0, 2.0, 3.0])
+        provided_resources = {"psf_models.standard": np.array([1.0, 2.0, 3.0])}
+
+        result = pipeline.run(
+            dataset=dataset,
+            provided_resources=provided_resources,
+        )
+
+        mock_mask_compute.assert_called_once()
+        mock_gof_compute.assert_called_once()
+        mock_apply.assert_called_once_with(metric_result)
+
+        assert np.array_equal(
+            result.metrics["mask_obscuration"],
+            np.array([1.0, 2.0, 3.0]),
+        )
+
+        assert np.array_equal(
+            result.metrics["goodness_of_fit"],
+            np.array([1.0, 2.0, 3.0]),
+        )
+
+        assert np.array_equal(
+            result.rejection_masks["mask_obscuration"],
+            np.array([True, False, True]),
+        )
+
+        assert "goodness_of_fit" not in result.rejection_masks
+        assert "shapes" not in result.metrics
+        assert "shapes" not in result.rejection_masks
+
+        assert np.array_equal(
+            result.valid_mask,
+            np.array([True, False, True]),
+        )

From e05480531a22314b1a4c5149af865d23118e8d20 Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Thu, 27 Aug 2026 10:59:46 +0200
Subject: [PATCH 07/10] Add logger debug statements for metrics and policies
 registry classes skipped/processed

---
 src/wf_psf/quality_control/pipeline.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/src/wf_psf/quality_control/pipeline.py b/src/wf_psf/quality_control/pipeline.py
index 4ac645ba..02e77527 100644
--- a/src/wf_psf/quality_control/pipeline.py
+++ b/src/wf_psf/quality_control/pipeline.py
@@ -22,6 +22,10 @@
 from wf_psf.quality_control.rejection.registry import build_rejection_policy_registry
 from wf_psf.quality_control.resources import Resources
 
+import logging
+
+logger = logging.getLogger(__name__)
+
 
 @dataclass
 class QualityControlResult:
@@ -80,12 +84,15 @@ def _instantiate_metrics(self) -> dict[str, QualityMetric]:
 
         for name, metric_config in self.config.metrics.items():
             if not metric_config.enabled:
+                logger.debug("Skipping metric %s: not enabled.", name)
                 continue
 
             metric_cls = self.metrics_registry.get(name)
 
             metrics[name] = metric_cls()
 
+        logger.debug("Instantiated metrics: %s", list(metrics))
+
         return metrics
 
     def _instantiate_rejection_policies(self) -> dict[str, RejectionPolicy]:
@@ -105,12 +112,16 @@ def _instantiate_rejection_policies(self) -> dict[str, RejectionPolicy]:
 
         for metric_name, rejection_config in self.config.rejection.items():
             if not rejection_config.enabled:
+                logger.debug("Skipping rejection policy %s: not enabled.", metric_name)
                 continue
 
             policy_name, policy_params = next(iter(rejection_config.policy.items()))
             policy_cls = self.rejection_registry.get(policy_name)
 
             rejection_policies[metric_name] = policy_cls(**policy_params)
+
+        logger.debug("Instantiated rejection policies: %s", list(rejection_policies))
+
         return rejection_policies
 
     def run(self, dataset, provided_resources=None):

From fe41f8e1b45ba5bc2167c361bd8344bf24ceeee4 Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Thu, 27 Aug 2026 11:57:16 +0200
Subject: [PATCH 08/10] Add helper _resolve_resources for resource resolution

---
 src/wf_psf/quality_control/pipeline.py | 22 ++++++++++++++++++++--
 1 file changed, 20 insertions(+), 2 deletions(-)

diff --git a/src/wf_psf/quality_control/pipeline.py b/src/wf_psf/quality_control/pipeline.py
index 02e77527..97676214 100644
--- a/src/wf_psf/quality_control/pipeline.py
+++ b/src/wf_psf/quality_control/pipeline.py
@@ -124,6 +124,23 @@ def _instantiate_rejection_policies(self) -> dict[str, RejectionPolicy]:
 
         return rejection_policies
 
+    def _resolve_resources(self, provided_resources):
+        """Resolve resources required by enabled quality metrics.
+
+        Parameters
+        ----------
+        provided_resources : Mapping[str, Any] or None
+            Ready-to-use resources supplied by the pipeline caller, keyed by
+            resource identifier.
+
+        Returns
+        -------
+        dict[str, Any]
+            Resolved resources required by enabled quality metrics.
+        """
+        resource_manager = Resources(self.config)
+        return resource_manager.resolve(provided_resources)
+
     def run(self, dataset, provided_resources=None):
         """Run quality control pipeline.
 
@@ -139,8 +156,9 @@ def run(self, dataset, provided_resources=None):
         -----
         The pipeline is expected to be invoked only when at least one quality metric is enabled in the quality control configuration.
         """
-        resource_manager = Resources(self.config)
-        resolved_resources = resource_manager.resolve(provided_resources)
+        resolved_resources = self._resolve_resources(
+            provided_resources=provided_resources
+        )
 
         context = QualityControlContext(dataset, resolved_resources)
 

From be88f1185fc23b53336e355e1e67166f51727001 Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Thu, 27 Aug 2026 16:03:17 +0200
Subject: [PATCH 09/10] Improve validity masks semantics

- Rename rejection_masks to validity_masks
- Define boolean validity mask in RejectionPolicy apply method doc string
- Add pipeline integration test and fixture for multiple rejection policies
- Rename test test_pipeline_run to test_pipeline_run_single_rejection_policy
---
 src/wf_psf/quality_control/pipeline.py        | 14 ++--
 src/wf_psf/quality_control/rejection/base.py  | 11 ++-
 ...y_control_multiple_rejection_policies.yaml | 42 ++++++++++
 .../test_quality_control/pipeline_test.py     | 83 +++++++++++++++++--
 4 files changed, 135 insertions(+), 15 deletions(-)
 create mode 100644 src/wf_psf/tests/test_quality_control/data/valid/quality_control_multiple_rejection_policies.yaml

diff --git a/src/wf_psf/quality_control/pipeline.py b/src/wf_psf/quality_control/pipeline.py
index 97676214..ad5ea163 100644
--- a/src/wf_psf/quality_control/pipeline.py
+++ b/src/wf_psf/quality_control/pipeline.py
@@ -36,7 +36,7 @@ class QualityControlResult:
     metrics
         Computed quality metrics indexed by metric name.
 
-    rejection_masks
+    validity_masks
         Boolean validity masks produced by each rejection policy.
 
     valid_mask
@@ -46,7 +46,7 @@ class QualityControlResult:
 
     metrics: dict[str, np.ndarray]
 
-    rejection_masks: dict[str, np.ndarray]
+    validity_masks: dict[str, np.ndarray]
 
     valid_mask: np.ndarray
 
@@ -170,19 +170,21 @@ def run(self, dataset, provided_resources=None):
 
         rejection_policies = self._instantiate_rejection_policies()
 
-        rejection_masks = {
+        validity_masks = {
             name: policy.apply(metric_results[name])
             for name, policy in rejection_policies.items()
         }
 
-        if rejection_masks:
-            valid_mask = np.logical_and.reduce(list(rejection_masks.values()))
+        if validity_masks:
+            # True indicates a valid sample. A sample is valid only if it passes
+            # every enabled rejection policy.
+            valid_mask = np.logical_and.reduce(list(validity_masks.values()))
         else:
             metric_result = next(iter(metric_results.values()))
             valid_mask = np.ones(metric_result.shape, dtype=bool)
 
         return QualityControlResult(
             metrics=metric_results,
-            rejection_masks=rejection_masks,
+            validity_masks=validity_masks,
             valid_mask=valid_mask,
         )
diff --git a/src/wf_psf/quality_control/rejection/base.py b/src/wf_psf/quality_control/rejection/base.py
index 38c5a87b..efcdfb28 100644
--- a/src/wf_psf/quality_control/rejection/base.py
+++ b/src/wf_psf/quality_control/rejection/base.py
@@ -37,7 +37,12 @@ class RejectionPolicy(ABC):
 
     @abstractmethod
     def apply(self, metric: np.ndarray) -> np.ndarray:
-        """Return a boolean mask identifying valid dataset samples.
-
-        The returned mask has one entry per dataset sample.
+        """Apply the rejection policy to metric values.
+
+        Returns
+        -------
+        np.ndarray
+            Boolean validity mask with one entry per dataset sample. ``True``
+            indicates that the sample passes the rejection policy and should
+            be retained; ``False`` indicates that it should be rejected.
         """
diff --git a/src/wf_psf/tests/test_quality_control/data/valid/quality_control_multiple_rejection_policies.yaml b/src/wf_psf/tests/test_quality_control/data/valid/quality_control_multiple_rejection_policies.yaml
new file mode 100644
index 00000000..d94f7e76
--- /dev/null
+++ b/src/wf_psf/tests/test_quality_control/data/valid/quality_control_multiple_rejection_policies.yaml
@@ -0,0 +1,42 @@
+resources:
+
+  psf_models:
+    standard:
+      inference_config: inference_standard.yaml
+    oversampled:
+      inference_config: inference_oversampled.yaml
+
+metrics:
+
+  mask_obscuration:
+    enabled: true
+    params:
+      aperture: gaussian
+      sigma: 2.5
+
+  goodness_of_fit:
+    enabled: true
+    required_resources:
+      - psf_models.standard
+    params:
+      statistic: reduced_chi_square
+      normalize_residuals: true
+
+rejection:
+
+  mask_obscuration:
+    enabled: true
+    policy:
+      threshold:
+        value: 3.0
+
+  goodness_of_fit:
+    enabled: true
+    policy:
+      threshold:
+        value: 3.0
+
+reporting:
+
+  save_metrics: true
+  log_statistics: true
\ No newline at end of file
diff --git a/src/wf_psf/tests/test_quality_control/pipeline_test.py b/src/wf_psf/tests/test_quality_control/pipeline_test.py
index 5f5d8e01..d3cbdd88 100644
--- a/src/wf_psf/tests/test_quality_control/pipeline_test.py
+++ b/src/wf_psf/tests/test_quality_control/pipeline_test.py
@@ -63,9 +63,9 @@ def test_pipeline_instantiate_rejection_policy_valid(pipeline_factory):
 
 
 # Test pipeline runner
-def test_pipeline_run(pipeline_factory):
+def test_pipeline_run_single_rejection_policy(pipeline_factory):
     metric_result = np.array([1.0, 2.0, 3.0])
-    rejection_mask = np.array([True, False, True])
+    validity_mask = np.array([True, False, True])
 
     with (
         patch.object(
@@ -81,7 +81,7 @@ def test_pipeline_run(pipeline_factory):
         patch.object(
             ThresholdRejectionPolicy,
             "apply",
-            return_value=rejection_mask,
+            return_value=validity_mask,
         ) as mock_apply,
     ):
         pipeline = pipeline_factory("valid/quality_control.yaml")
@@ -109,15 +109,86 @@ def test_pipeline_run(pipeline_factory):
         )
 
         assert np.array_equal(
-            result.rejection_masks["mask_obscuration"],
+            result.validity_masks["mask_obscuration"],
             np.array([True, False, True]),
         )
 
-        assert "goodness_of_fit" not in result.rejection_masks
+        assert "goodness_of_fit" not in result.validity_masks
         assert "shapes" not in result.metrics
-        assert "shapes" not in result.rejection_masks
+        assert "shapes" not in result.validity_masks
 
         assert np.array_equal(
             result.valid_mask,
             np.array([True, False, True]),
         )
+
+
+def test_pipeline_run_multiple_rejection_policies(pipeline_factory):
+    metric_result = np.array([1.0, 2.0, 3.0])
+    validity_masks = [
+        np.array([True, True, False]),
+        np.array([True, False, True]),
+    ]
+
+    with (
+        patch.object(
+            MaskObscurationMetric,
+            "compute",
+            return_value=metric_result,
+        ) as mock_mask_compute,
+        patch.object(
+            GoodnessOfFitMetric,
+            "compute",
+            return_value=metric_result,
+        ) as mock_gof_compute,
+        patch.object(
+            ThresholdRejectionPolicy,
+            "apply",
+            side_effect=validity_masks,
+        ) as mock_apply,
+    ):
+        pipeline = pipeline_factory(
+            "valid/quality_control_multiple_rejection_policies.yaml"
+        )
+
+        dataset = np.array([1.0, 2.0, 3.0])
+        provided_resources = {"psf_models.standard": np.array([1.0, 2.0, 3.0])}
+
+        result = pipeline.run(
+            dataset=dataset,
+            provided_resources=provided_resources,
+        )
+
+        mock_mask_compute.assert_called_once()
+        mock_gof_compute.assert_called_once()
+        assert mock_apply.call_count == 2
+
+        assert np.array_equal(
+            result.metrics["mask_obscuration"],
+            np.array([1.0, 2.0, 3.0]),
+        )
+
+        assert np.array_equal(
+            result.metrics["goodness_of_fit"],
+            np.array([1.0, 2.0, 3.0]),
+        )
+
+        assert np.array_equal(
+            result.validity_masks["mask_obscuration"],
+            np.array([True, True, False]),
+        )
+
+        assert np.array_equal(
+            result.validity_masks["goodness_of_fit"],
+            np.array([True, False, True]),
+        )
+
+        assert np.array_equal(
+            result.valid_mask,
+            np.array([True, False, False]),
+        )
+
+        assert np.array_equal(
+            result.valid_mask,
+            np.array([True, False, False]),
+        )

From 0928fd555df784ebb56bb2a59137f13c6a3daf1c Mon Sep 17 00:00:00 2001
From: Jennifer Pollack <jennifer.pollack@cea.fr>
Date: Thu, 27 Aug 2026 16:08:42 +0200
Subject: [PATCH 10/10] Add missing policy section to mask_obscuration section

---
 config/quality_control.yaml | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/config/quality_control.yaml b/config/quality_control.yaml
index aac5553d..f11d04ca 100644
--- a/config/quality_control.yaml
+++ b/config/quality_control.yaml
@@ -18,7 +18,6 @@ metrics:
     enabled: true
     required_resources:
       - psf_models.standard
-
     params:
       statistic: reduced_chi_square
       normalize_residuals: true
@@ -28,7 +27,9 @@ rejection:
 
   mask_obscuration:
     enabled: true
-    threshold: 0.25
+    policy:
+      threshold:
+        value: 0.25
 
   goodness_of_fit:
     enabled: false