def __init__(self,**inputDict):
# initialize the parameter Dictionary, and update defaults from inputDict
self.paramDict = {"inputFile":"",
"writeToFits":False,
"outputPrefix":"testone",
"xDECam":0.0,
"yDECam":0.0,
"debugFlag":False,
"rootFlag":False,
"printLevel":0,
"iTelescope":0,
"waveLength":700.0e-9,
"nZernikeTerms":11,
"nbin":128,
"nPixels":32,
"gridCalcMode":True,
"pixelOverSample":4,
"scaleFactor":2.,
"randomFlag":False,
"gain":1.0}
self.paramDict.update(inputDict)
# declare fit function
self.gFitFunc = donutengine(**self.paramDict)
# check values of bins - prevent errors
if self.gFitFunc._nbin != self.gFitFunc._nPixels * self.gFitFunc._pixelOverSample:
print "makedonut: ERROR in values of nbin,nPixels,pixelOverSample!!!"
sys.exit(0)
# also require that _Lu > 2R, ie. that pupil fits in pupil plane
# this translates into requiring that (Lambda F / pixelSize) * pixelOverSample * scaleFactor > 1
if self.gFitFunc._pixelOverSample * self.gFitFunc.getScaleFactor() * (700.e-9 * 2.9 / 15.e-6) < 1. :
print "makedonut: ERROR pupil doesn't fit!!!"
sys.exit(0)
def __init__(self, **inputDict):
# init contains all initializations which are done only once for all fits
# parameters in fixParamArray1 are nEle,rzero,bkgd,Z2,Z3,Z4,....Z11
self.paramDict = {
"nZernikeTerms": 11,
"nFits": 1,
"fixedParamArray1":
[0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,
1], #need defaults up to quadrefoil
"debugFlag": False,
"outputWavefront": False,
"outputDiff": True,
"outputChi2": False,
"printLevel": 1,
"maxIterations": 1000,
"calcRzeroDerivative": True
}
# search for key in inputDict, change defaults
self.paramDict.update(inputDict)
# setup the fit engine
self.gFitFunc = donutengine(**self.paramDict)
# need dummy versions before calling self.chisq
self.imgarray = numpy.zeros(1)
self.weight = numpy.ones(1)
self.sigmasq = numpy.ones(1)
# get decam info or desi info
if self.paramDict["iTelescope"] == 6 or self.paramDict[
"iTelescope"] == 7 or self.paramDict["iTelescope"] == 8:
print('This is for DESI CI')
from donutlib.desiutil import desiciinfo
self.dInfo = desiciinfo()
elif self.paramDict["iTelescope"] == 5:
print('This is for DESI GFA')
from donutlib.desiutil import desiinfo
self.dInfo = desiinfo()
else:
print('This is for DECam')
from donutlib.decamutil import decaminfo
self.dInfo = decaminfo()
# setup MINUIT
self.gMinuit = ROOT.TMinuit(self.gFitFunc.npar)
self.gMinuit.SetFCN(self.chisq)
# arglist is for the parameters in Minuit commands
arglist = array('d', 10 * [0.])
ierflg = ctypes.c_int(1982) #L ROOT.Long(1982)
# set the definition of 1sigma
arglist[0] = 1.0
self.gMinuit.mnexcm("SET ERR", arglist, 1, ierflg)
# turn off Warnings
arglist[0] = 0
self.gMinuit.mnexcm("SET NOWARNINGS", arglist, 0, ierflg)
# set printlevel
arglist[0] = self.paramDict["printLevel"]
self.gMinuit.mnexcm("SET PRINTOUT", arglist, 1, ierflg)
# do initial setup of Minuit parameters
# status/limit arrays for Minuit parameters
self.startingParam = numpy.zeros(self.gFitFunc.npar)
self.errorParam = numpy.ones(self.gFitFunc.npar)
self.loParam = numpy.zeros(self.gFitFunc.npar)
self.hiParam = numpy.zeros(self.gFitFunc.npar)
self.paramStatusArray = numpy.zeros(
self.gFitFunc.npar) # store =0 Floating, =1 Fixed
# Set starting values and step sizes for parameters
# (note that one can redefine the parameters, so this method can be called multiple times)
for ipar in range(self.gFitFunc.npar):
self.gMinuit.DefineParameter(ipar, self.gFitFunc.parNames[ipar],
self.startingParam[ipar],
self.errorParam[ipar],
self.loParam[ipar],
self.hiParam[ipar])
def __init__(self, **inputDict):
""" initialize
"""
# initialize the parameter Dictionary, and update defaults from inputDict
self.paramDict = {
"inputFile": "",
"wfmFile": "",
"wfmArray": None,
"writeToFits": False,
"outputPrefix": "testone",
"xDECam": 0.0,
"yDECam": 0.0,
"debugFlag": False,
"rootFlag": False,
"iTelescope": 0,
"waveLength": 700.0e-9,
"nZernikeTerms": 37,
"nbin": 512,
"nPixels": 64,
"gridCalcMode": True,
"pixelOverSample": 8,
"scaleFactor": 1.,
"rzero": 0.125,
"nEle": 1.0e6,
"background": 4000.,
"randomFlag": False,
"randomSeed":
209823, # if this is an invalid integer, crazy errors will ensue
"gain": 1.0,
"flipFlag": False,
"ZernikeArray": []
}
self.paramDict.update(inputDict)
# check parameters are ok
if self.paramDict["nbin"] != self.paramDict[
"nPixels"] * self.paramDict["pixelOverSample"]:
print("makedonut: nbin must = nPixels * pixelOverSample !!!")
sys.exit(1)
# also require that _Lu > 2R, ie. that pupil fits in pupil plane
# this translates into requiring that (Lambda F / pixelSize) * pixelOverSample * scaleFactor > 1
# Why does this depend on scaleFactor, but not Z4?? Answer: scaleFactor effectively changes the wavelength, so
# it must be included. It is also possible that Z4 is too big for the nPixels - buts that another limit than this one
F = 2.9 # hardcode for DECam for now
pixelSize = 15.e-6
if self.paramDict["pixelOverSample"] * self.paramDict["scaleFactor"] * (
self.paramDict["waveLength"] * F / pixelSize) < 1.:
print("makedonut: ERROR pupil doesn't fit!!!")
print(
" value = ", self.paramDict["pixelOverSample"] *
self.paramDict["scaleFactor"] *
(self.paramDict["waveLength"] * F / pixelSize))
#sys.exit(2)
# for WFM, need to turn gridCalcMode to False for donutengine
#if self.paramDict["useWFM"]:
# self.paramDict["gridCalcMode"] = False
#
# don't do this by default, may need it if Zemax is used, but not if correct bins sizes are used.
# and it isn't coded with c++ donutengine yet either...
# declare fit function
self.gFitFunc = donutengine(**self.paramDict)
# DECam info
self.dinfo = decaminfo()
# set random seed
numpy.random.seed(self.paramDict["randomSeed"])
def __init__(self,**inputDict):
# init contains all initializations which are done only once for all fits
# parameters in fixParamArray1 are nEle,rzero,bkgd,Z2,Z3,Z4,....Z11
self.paramDict = {"nZernikeTerms":11,
"nFits":1,
"fixedParamArray1":[0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1], #need defaults up to quadrefoil
"debugFlag":False,
"outputWavefront":False,
"outputDiff":True,
"outputChi2":False,
"printLevel":1,
"maxIterations":1000}
# search for key in inputDict, change defaults
self.paramDict.update(inputDict)
# setup the fit engine
self.gFitFunc = donutengine(**self.paramDict)
# need dummy versions before calling self.chisq
self.imgarray = numpy.zeros(1)
self.weight = numpy.ones(1)
self.sigmasq = numpy.ones(1)
# get decam info
self.decamInfo = decaminfo()
# setup MINUIT
self.gMinuit = ROOT.TMinuit(self.gFitFunc.npar)
self.gMinuit.SetFCN( self.chisq )
# arglist is for the parameters in Minuit commands
arglist = array( 'd', 10*[0.] )
ierflg = ROOT.Long(1982)
# set the definition of 1sigma
arglist[0] = 1.0
self.gMinuit.mnexcm( "SET ERR", arglist, 1, ierflg )
# turn off Warnings
arglist[0] = 0
self.gMinuit.mnexcm("SET NOWARNINGS", arglist,0,ierflg)
# set printlevel
arglist[0] = self.paramDict["printLevel"]
self.gMinuit.mnexcm("SET PRINTOUT", arglist,1,ierflg)
# do initial setup of Minuit parameters
# status/limit arrays for Minuit parameters
self.startingParam = numpy.zeros(self.gFitFunc.npar)
self.errorParam = numpy.ones(self.gFitFunc.npar)
self.loParam = numpy.zeros(self.gFitFunc.npar)
self.hiParam = numpy.zeros(self.gFitFunc.npar)
self.paramStatusArray = numpy.zeros(self.gFitFunc.npar) # store =0 Floating, =1 Fixed
# Set starting values and step sizes for parameters
# (note that one can redefine the parameters, so this method can be called multiple times)
for ipar in range(self.gFitFunc.npar):
self.gMinuit.DefineParameter(ipar,self.gFitFunc.parNames[ipar],self.startingParam[ipar],self.errorParam[ipar],self.loParam[ipar],self.hiParam[ipar])
def __init__(self,**inputDict):
""" initialize
"""
# initialize the parameter Dictionary, and update defaults from inputDict
self.paramDict = {"inputFile":"",
"wfmFile":"",
"wfmArray":None,
"writeToFits":False,
"outputPrefix":"testone",
"xDECam":0.0,
"yDECam":0.0,
"debugFlag":False,
"rootFlag":False,
"iTelescope":0,
"waveLength":700.0e-9,
"nZernikeTerms":37,
"nbin":512,
"nPixels":64,
"gridCalcMode":True,
"pixelOverSample":8,
"scaleFactor":1.,
"rzero":0.125,
"nEle":1.0e6,
"background":4000.,
"randomFlag":False,
"randomSeed":209823, # if this is an invalid integer, crazy errors will ensue
"gain":1.0,
"flipFlag":False,
"ZernikeArray":[]}
self.paramDict.update(inputDict)
# check parameters are ok
if self.paramDict["nbin"] != self.paramDict["nPixels"]*self.paramDict["pixelOverSample"]:
print "makedonut: nbin must = nPixels * pixelOverSample !!!"
sys.exit(1)
# also require that _Lu > 2R, ie. that pupil fits in pupil plane
# this translates into requiring that (Lambda F / pixelSize) * pixelOverSample * scaleFactor > 1
# Why does this depend on scaleFactor, but not Z4?? Answer: scaleFactor effectively changes the wavelength, so
# it must be included. It is also possible that Z4 is too big for the nPixels - buts that another limit than this one
F = 2.9 # hardcode for DECam for now
pixelSize = 15.e-6
if self.paramDict["pixelOverSample"] * self.paramDict["scaleFactor"] * (self.paramDict["waveLength"] * F / pixelSize) < 1. :
print "makedonut: ERROR pupil doesn't fit!!!"
print " value = ",self.paramDict["pixelOverSample"] * self.paramDict["scaleFactor"] * (self.paramDict["waveLength"] * F / pixelSize)
#sys.exit(2)
# for WFM, need to turn gridCalcMode to False for donutengine
#if self.paramDict["useWFM"]:
# self.paramDict["gridCalcMode"] = False
#
# don't do this by default, may need it if Zemax is used, but not if correct bins sizes are used.
# and it isn't coded with c++ donutengine yet either...
# declare fit function
self.gFitFunc = donutengine(**self.paramDict)
# DECam info
self.dinfo = decaminfo()
# set random seed
numpy.random.seed(self.paramDict["randomSeed"])
"nPixels": 64,
"gridCalcMode": True,
"pixelOverSample": 8,
"scaleFactor": 1.,
"rzero": 0.125,
"nEle": 1.0e6,
"background": 4000.,
"randomFlag": False,
"randomSeed":
209823, # if this is an invalid integer, crazy errors will ensue
"gain": 1.0,
"flipFlag": False,
"iTelescope": 5, # 5 stands for the DESI configuration
"ZernikeArray": []
}
gFitFunc = donutengine(**paramDict)
parArr = np.zeros(gFitFunc.npar)
parArr[gFitFunc.ipar_bkgd] = 4000.
parArr[gFitFunc.ipar_nEle] = 1.e6
parArr[gFitFunc.ipar_rzero] = 0.15
parArr[gFitFunc.ipar_ZernikeFirst + 2] = 7.4
# Set the angle (in degrees, Zemax Echo 22 coordinate system)
# See angles for the test fields inside 00README in the testpupils directory
gFitFunc.setXYDESI(1.325, 0.89)
#calculate and get the pupil mask
gFitFunc.calcAll(parArr)
data = gFitFunc.getvImage()
pupil = gFitFunc.getvPupilMask()
