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%matplotlib inline

load the modules



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from lsst.cwfs.instrument import Instrument
from lsst.cwfs.algorithm import Algorithm
from lsst.cwfs.image import Image, readFile
import lsst.cwfs.plots as plots

Define the image objects. Input arguments: file name, field coordinates in deg, image type

The colorbar() below may produce a warning message if your matplotlib version is older than 1.5.0 ( https://github.com/matplotlib/matplotlib/issues/5209 )



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fieldXY = [1.185,1.185]

I1 = Image(readFile('../tests/testImages/LSST_NE_SN25/z11_0.25_intra.txt'), fieldXY, Image.INTRA)
I2 = Image(readFile('../tests/testImages/LSST_NE_SN25/z11_0.25_extra.txt'), fieldXY, Image.EXTRA)



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plots.plotImage(I1.image,'intra')
plots.plotImage(I2.image,'extra')

Define the instrument. Input arguments: instrument name, size of image stamps



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inst=Instrument('lsst',I1.sizeinPix)

Define the algorithm being used. Input arguments: baseline algorithm, instrument, debug level



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algo=Algorithm('exp',inst,0)

Run it



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algo.runIt(inst,I1,I2,'offAxis')

Print the Zernikes Zn (n>=4)



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print(algo.zer4UpNm)

plot the Zernikes Zn (n>=4)



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plots.plotZer(algo.zer4UpNm,'nm')



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plots.plotImage(algo.Wconverge,'Final wavefront')



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plots.plotImage(algo.Wconverge,'Final wavefront with pupil mask applied', mask=algo.pMask)