Merge pull request #2511 from cta-observatory/image_cleaner_api

Change `ImageCleaner` API

docs/changes/2511.api.rst

@@ -0,0 +1,3 @@
+Adding monitoring: MonitoringCameraContainer as keyword argument to
+the ``ImageCleaner`` API so cleaning algorithms can now access
+relevant information for methods that e.g. require monitoring information.

src/ctapipe/calib/camera/tests/test_calibrator.py

@@ -1,6 +1,7 @@
 """
 Tests for CameraCalibrator and related functions
 """
+
 from copy import deepcopy
 
 import astropy.units as u

src/ctapipe/conftest.py

@@ -50,7 +50,7 @@ def camera_geometry(request):
 def _global_example_event():
     """
     helper to get a single event from a MC file. Don't use this fixture
-    directly, rather use `test_event`
+    directly, rather use `example_event`
     """
     filename = get_dataset_path("gamma_test_large.simtel.gz")
 
@@ -93,8 +93,8 @@ def example_event(_global_example_event):
     example:
 
     .. code-block::
-        def test_my_thing(test_event):
-            assert len(test_event.r0.tel) > 0
+        def test_my_thing(example_event):
+            assert len(example_event.r0.tel) > 0
 
     """
     return deepcopy(_global_example_event)

src/ctapipe/image/cleaning.py

@@ -28,6 +28,8 @@
 
 import numpy as np
 
+from ctapipe.containers import MonitoringCameraContainer
+
 from ..core import TelescopeComponent
 from ..core.traits import (
     BoolTelescopeParameter,
@@ -466,7 +468,12 @@ class ImageCleaner(TelescopeComponent):
 
     @abstractmethod
     def __call__(
-        self, tel_id: int, image: np.ndarray, arrival_times: np.ndarray = None
+        self,
+        tel_id: int,
+        image: np.ndarray,
+        arrival_times: np.ndarray = None,
+        *,
+        monitoring: MonitoringCameraContainer = None,
     ) -> np.ndarray:
         """
         Identify pixels with signal, and reject those with pure noise.
@@ -480,6 +487,9 @@ def __call__(
             image pixel data corresponding to the camera geometry
         arrival_times: np.ndarray
             image of arrival time (not used in this method)
+        monitoring: `ctapipe.containers.MonitoringCameraContainer`
+            MonitoringCameraContainer to make use of additional parameters
+            from monitoring data e.g. pedestal std.
 
         Returns
         -------
@@ -514,7 +524,12 @@ class TailcutsImageCleaner(ImageCleaner):
     ).tag(config=True)
 
     def __call__(
-        self, tel_id: int, image: np.ndarray, arrival_times=None
+        self,
+        tel_id: int,
+        image: np.ndarray,
+        arrival_times: np.ndarray = None,
+        *,
+        monitoring: MonitoringCameraContainer = None,
     ) -> np.ndarray:
         """
         Apply standard picture-boundary cleaning. See `ImageCleaner.__call__()`
@@ -536,7 +551,12 @@ class MARSImageCleaner(TailcutsImageCleaner):
     """
 
     def __call__(
-        self, tel_id: int, image: np.ndarray, arrival_times=None
+        self,
+        tel_id: int,
+        image: np.ndarray,
+        arrival_times: np.ndarray = None,
+        *,
+        monitoring: MonitoringCameraContainer = None,
     ) -> np.ndarray:
         """
         Apply MARS-style image cleaning. See `ImageCleaner.__call__()`
@@ -563,9 +583,15 @@ class FACTImageCleaner(TailcutsImageCleaner):
     ).tag(config=True)
 
     def __call__(
-        self, tel_id: int, image: np.ndarray, arrival_times=None
+        self,
+        tel_id: int,
+        image: np.ndarray,
+        arrival_times: np.ndarray = None,
+        *,
+        monitoring: MonitoringCameraContainer = None,
     ) -> np.ndarray:
         """Apply FACT-style image cleaning. see ImageCleaner.__call__()"""
+
         return fact_image_cleaning(
             geom=self.subarray.tel[tel_id].camera.geometry,
             image=image,
@@ -592,7 +618,12 @@ class TimeConstrainedImageCleaner(TailcutsImageCleaner):
     ).tag(config=True)
 
     def __call__(
-        self, tel_id: int, image: np.ndarray, arrival_times=None
+        self,
+        tel_id: int,
+        image: np.ndarray,
+        arrival_times: np.ndarray = None,
+        *,
+        monitoring: MonitoringCameraContainer = None,
     ) -> np.ndarray:
         """
         Apply MAGIC-like image cleaning with timing information. See `ImageCleaner.__call__()`

src/ctapipe/image/image_processor.py

@@ -1,6 +1,7 @@
 """
 High level image processing  (ImageProcessor Component)
 """
+
 from copy import deepcopy
 
 import numpy as np
@@ -221,6 +222,7 @@ def _process_telescope_event(self, event):
                 tel_id=tel_id,
                 image=dl1_camera.image,
                 arrival_times=dl1_camera.peak_time,
+                monitoring=event.mon.tel[tel_id],
             )
 
             dl1_camera.parameters = self._parameterize_image(

src/ctapipe/image/reducer.py

@@ -1,6 +1,7 @@
 """
 Algorithms for the data volume reduction.
 """
+
 from abc import abstractmethod
 
 import numpy as np