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rcal-954 updates for run
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ddavis-stsci committed Dec 2, 2024
1 parent 47aa049 commit 89e2109
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15 changes: 6 additions & 9 deletions docs/roman/pipeline_run.rst
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Expand Up @@ -63,11 +63,8 @@ Exit Status
From the Python Prompt
------------------------------

You can execute a pipeline or a step from within python by using the
``run`` method.

The ``run`` method creates a new instance of the class and runs the pipeline or
step. Optional parameter settings can be specified by via keyword arguments or
You can execute a pipeline or a step from within python.
Optional parameter settings can be specified by via keyword arguments or
supplying a parameter file. Some examples are shown below.

For the exposure pipeline and steps,
Expand All @@ -76,11 +73,11 @@ For the exposure pipeline and steps,

from romancal.pipeline import ExposurePipeline
elp = ExposurePipeline()
result = elp.run('r0000101001001001001_0001_wfi01_uncal.asdf')
result = elp('r0000101001001001001_0001_wfi01_uncal.asdf')

from romancal.linearity import LinearityStep
linearity = LinearityStep()
result = linearity.run('r0000101001001001001_0001_wfi01_uncal.asdf')
result = linearity('r0000101001001001001_0001_wfi01_uncal.asdf')

One difference between the mosaic level pipeline and the exposure level pipeline is that the
mosaic level pipeline is generally designed to run on multiple overlapping exposures. To achieve
Expand All @@ -91,11 +88,11 @@ For the mosaic level pipeline and steps,

from romancal.pipeline import MosaicPipeline
mosp = MosaicPipeline()
result = mosp.run('r0000101001001001001_asn.json')
result = mosp('r0000101001001001001_asn.json')

from romancal.skymatch import SkyMatchStep
skymatch = SkyMatchStep()
result = skymatch.run('r0000101001001001001_asn.json')
result = skymatch('r0000101001001001001_asn.json')


For details on the different ways to run a pipeline step, see
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2 changes: 1 addition & 1 deletion docs/roman/stpipe/user_pipeline.rst
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Expand Up @@ -186,7 +186,7 @@ From Python
Once the pipeline has been configured (as above) it can be executed
using run.

pipe.run(input_data)
pipe(input_data)

Caching details
---------------
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