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Commit 0780cbfc authored by Laurent Mercadier's avatar Laurent Mercadier
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Simplifies load() input parameters

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......@@ -364,9 +364,8 @@ mnemonics = {
'dim': ['gott_pId','pixelId']}
}
def load(fields, runNB, proposalNB, semesterNB=None, topic='SCS', useRaw=True, display=False,
validate=False, runpath='/gpfs/exfel/exp/{}/{}/{}/raw/r{:04d}/',
subset=by_index[:], rois={}):
def load(fields, runNB, proposalNB, subFolder='raw', display=False, validate=False,
subset=by_index[:], rois={}):
""" Load a run and extract the data. Output is an xarray with aligned trainIds
Inputs:
......@@ -375,15 +374,10 @@ def load(fields, runNB, proposalNB, semesterNB=None, topic='SCS', useRaw=True, d
{"extra": {'SCS_CDIFFT_MAG/SUPPLY/CURRENT', 'actual_current.value', None}}
runNB: (str, int) run number as integer
proposalNB: (str, int) of the proposal number e.g. 'p002252' or 2252
semesterNB: (str, int) optional, depricated. The semester number where the proposal
data are saved. Depricated since karabo_data version 0.5
topic: string of the topic.
useRaw: (bool) if True, access data from 'raw' folder of the run, otherwise
from 'proc' folder (for processed data)
display: boolean, whether to show the run.info or not
validate: boolean, whether to run karabo-data-validate or not
runpath: a string to fromat the run folder path with topic,
semesterNB, proposalNB and runNB
subFolder: (str) sub-folder from which to load the data. Use 'raw' for raw
data or 'proc' for processed data.
display: (bool) whether to show the run.info or not
validate: (bool) whether to run karabo-data-validate or not
subset: a subset of train that can be load with by_index[:5] for the
first 5 trains
rois: a dictionnary of mnemonics with a list of rois definition and the desired
......@@ -399,8 +393,7 @@ def load(fields, runNB, proposalNB, semesterNB=None, topic='SCS', useRaw=True, d
runNB = 'r{:04d}'.format(runNB)
if isinstance(proposalNB,int):
proposalNB = 'p{:06d}'.format(proposalNB)
dataSubFolder = 'raw' if useRaw else 'proc'
runFolder = os.path.join(find_proposal(proposalNB), dataSubFolder, runNB)
runFolder = os.path.join(find_proposal(proposalNB), subFolder, runNB)
run = RunDirectory(runFolder).select_trains(subset)
if validate:
......
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