Stick to established returning for reduce images

mirar/__main__.py

@@ -158,10 +158,11 @@
             night=night,
         )
 
-        batches, errorstack, processors = pipe.reduce_images(
+        batches, errorstack = pipe.reduce_images(
             catch_all_errors=not args.failfast,
         )
 
+        processors = pipe.get_latest_configuration()
         flowify(processors, pipe.get_flowchart_output_path(), include_stats=True)
 
         if args.postprocessconfig is not None:

mirar/pipelines/base_pipeline.py

@@ -72,6 +72,7 @@ def __init__(
         if not isinstance(selected_configurations, list):
             selected_configurations = [selected_configurations]
         self.selected_configurations = selected_configurations
+        self.latest_configuration = None
 
     @classmethod
     def __init_subclass__(cls, **kwargs):
@@ -183,6 +184,17 @@ def set_configuration(
         logger.debug("Pipeline initialisation complete.")
         return processors
 
+    def get_latest_configuration(self) -> list[BaseProcessor]:
+        """
+        Get the latest configuration used by the pipeline
+
+        :return: list of processors
+        """
+        if self.latest_configuration is None:
+            raise ValueError("No configuration has been set yet.")
+
+        return self.latest_configuration
+
     @staticmethod
     def download_raw_images_for_night(night: str | int):
         """
@@ -238,7 +250,7 @@ def reduce_images(
         output_error_path: Optional[str] = None,
         catch_all_errors: bool = True,
         selected_configurations: Optional[str | list[str]] = None,
-    ) -> tuple[Dataset, ErrorStack, list[BaseProcessor]]:
+    ) -> tuple[Dataset, ErrorStack]:
         """
         Function to process a given dataset.
 
@@ -296,11 +308,13 @@ def reduce_images(
 
             all_processors += processors
 
+        self.latest_configuration = all_processors
+
         err_stack.summarise_error_stack(output_path=output_error_path)
         err_stack.summarise_error_stack_tsv(
             output_path=output_error_path.with_suffix(".tsv")
         )
-        return dataset, err_stack, all_processors
+        return dataset, err_stack
 
     def postprocess_configuration(
         self,

tests/test_errors.py

@@ -33,7 +33,7 @@ def setUp(self):
     def test_pipeline(self):
         self.logger.info("\n\n Testing summer pipeline \n\n")
 
-        _, errorstack, _ = pipeline.reduce_images(
+        _, errorstack = pipeline.reduce_images(
             Dataset(ImageBatch()), catch_all_errors=True
         )
 

tests/test_forced_photometry.py

@@ -79,7 +79,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing forced photometry \n\n")
 
-        res, _, _ = pipeline.reduce_images(
+        res, _ = pipeline.reduce_images(
             dataset=Dataset(ImageBatch()), catch_all_errors=False
         )
         self.assertEqual(len(res), 1)

tests/test_sedmv2_stellar_pipeline.py

@@ -97,9 +97,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing SEDMv2 stellar pipeline \n\n")
 
-        res, _, _ = pipeline.reduce_images(
-            Dataset([ImageBatch()]), catch_all_errors=False
-        )
+        res, _ = pipeline.reduce_images(Dataset([ImageBatch()]), catch_all_errors=False)
 
         self.assertEqual(len(res), 29)
 

tests/test_sedmv2_transient_pipeline.py

@@ -72,9 +72,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing SEDMv2 transient pipeline \n\n")
 
-        res, _, _ = pipeline.reduce_images(
-            Dataset([ImageBatch()]), catch_all_errors=False
-        )
+        res, _ = pipeline.reduce_images(Dataset([ImageBatch()]), catch_all_errors=False)
 
         # Cleanup
         output_dir = get_output_dir("sedmv2/20230526")

tests/test_summer_imsub_pipeline.py

@@ -39,9 +39,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing summer pipeline \n\n")
 
-        res, _, _ = pipeline.reduce_images(
-            Dataset([ImageBatch()]), catch_all_errors=False
-        )
+        res, _ = pipeline.reduce_images(Dataset([ImageBatch()]), catch_all_errors=False)
 
         self.assertEqual(len(res), 1)
 

tests/test_summer_pipeline.py

@@ -66,9 +66,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing summer pipeline \n\n")
 
-        res, _, _ = pipeline.reduce_images(
-            Dataset([ImageBatch()]), catch_all_errors=False
-        )
+        res, _ = pipeline.reduce_images(Dataset([ImageBatch()]), catch_all_errors=False)
 
         # Cleanup - delete non-empty ouptut dir
         output_dir = get_output_dir(dir_root="summer/20220402")

tests/test_wfau_references.py

@@ -60,7 +60,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing WINTER reference building pipeline \n\n")
 
-        res, _, _ = run_winter_reference_build_pipeline(
+        res, _ = run_winter_reference_build_pipeline(
             subdet_id=0, field_id=TEST_WINTER_FIELD_ID, catch_all_errors=False
         )
 

tests/test_winter_pipeline.py

@@ -103,9 +103,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing winter pipeline \n\n")
 
-        res, _, _ = pipeline.reduce_images(
-            Dataset([ImageBatch()]), catch_all_errors=False
-        )
+        res, _ = pipeline.reduce_images(Dataset([ImageBatch()]), catch_all_errors=False)
 
         # Cleanup - delete ouptut dir
         output_dir = get_output_dir(dir_root="winter/20230726")

tests/test_wirc_imsub_pipeline.py

@@ -131,7 +131,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing wirc imsub pipeline \n\n")
 
-        res, _, _ = pipeline.reduce_images(
+        res, _ = pipeline.reduce_images(
             dataset=Dataset(ImageBatch()), catch_all_errors=False
         )
 

tests/test_wirc_pipeline.py

@@ -94,9 +94,7 @@ def test_pipeline(self):
         """
         self.logger.info("\n\n Testing wirc pipeline \n\n")
 
-        res, _, _ = pipeline.reduce_images(
-            Dataset([ImageBatch()]), catch_all_errors=False
-        )
+        res, _ = pipeline.reduce_images(Dataset([ImageBatch()]), catch_all_errors=False)
 
         self.assertEqual(len(res), 1)