diff --git a/changes/9214.outlier_detection.rst b/changes/9214.outlier_detection.rst new file mode 100644 index 0000000000..48736df5fc --- /dev/null +++ b/changes/9214.outlier_detection.rst @@ -0,0 +1 @@ +Made in-memory processing the default for outlier detection imaging observations diff --git a/docs/jwst/outlier_detection/outlier_detection_imaging.rst b/docs/jwst/outlier_detection/outlier_detection_imaging.rst index bbcc8bbc91..bf418ee618 100644 --- a/docs/jwst/outlier_detection/outlier_detection_imaging.rst +++ b/docs/jwst/outlier_detection/outlier_detection_imaging.rst @@ -104,8 +104,8 @@ final output product. Specifically, These concerns have been addressed by implementing an overall memory model for outlier detection that includes options to minimize memory usage at the expense of temporary file I/O and runtime. Control over this memory model happens -with the use of the ``in_memory`` parameter. The full impact of setting this parameter -to `False` includes: +with the use of the ``in_memory`` parameter, which defaults to True. +The full impact of setting this parameter to `False` includes: #. The input :py:class:`~jwst.datamodels.ModelLibrary` object is loaded with `on_disk=True`. This ensures that input models are loaded into memory one at at time, diff --git a/jwst/outlier_detection/outlier_detection_step.py b/jwst/outlier_detection/outlier_detection_step.py index 9162241691..304355622d 100644 --- a/jwst/outlier_detection/outlier_detection_step.py +++ b/jwst/outlier_detection/outlier_detection_step.py @@ -52,7 +52,7 @@ class OutlierDetectionStep(Step): resample_data = boolean(default=True) good_bits = string(default="~DO_NOT_USE") # DQ flags to allow search_output_file = boolean(default=False) - in_memory = boolean(default=False) # in_memory flag ignored if run within the pipeline; set at pipeline level instead + in_memory = boolean(default=True) # in_memory flag ignored if run within the pipeline; set at pipeline level instead """ # noqa: E501 def process(self, input_data):