-
Type:
Task
-
Status: Done (View Workflow)
-
Priority:
Normal
-
Resolution: Done
-
Affects Version/s: None
-
Fix Version/s: None
-
Component/s: None
-
Labels:
-
Sprint:PreEng11Apr1
When reducing n2 data at LAM, we noticed that it takes quite a long time (~2min30) to get an postISR image, please profile the current code and try to find improvement that would shorten that time.
FYI, that how we get those images :
import numpy as np
from lsst.obs.pfs.isrTask import PfsIsrTask as IsrTask
config = IsrTask.ConfigClass()
config.doBias = False
config.doDark = False
config.doFringe = False
config.doFlat = False
config.doLinearize = False
config.doDefect = True
config.doIPC = True
config.ipcCoeffs = np.array([13e-3, 6e-3])
config.doSaturationInterpolation = False
config.validate()
isrTask = IsrTask(config=config)
raw = butler.get('raw', dataId=dataId)
defects = butler.get('defects', dataId)
calexp = isrTask.run(raw, defects=defects)