def __init__(self, algoDir):
"""Initialize the Algorithm class.
Algorithm used to solve the transport of intensity equation to get
normal/ annular Zernike polynomials.
Parameters
----------
algoDir : str
Algorithm configuration directory.
"""
self.algoDir = algoDir
self.algoParamFile = ParamReader()
self._inst = Instrument("")
# Show the calculation message based on this value
# 0 means no message will be showed
self.debugLevel = 0
# Image has the problem or not from the over-compensation
self.caustic = False
# Record the Zk coefficients in each outer-loop iteration
# The actual total outer-loop iteration time is Num_of_outer_itr + 1
self.converge = np.array([])
# Current number of outer-loop iteration
self.currentItr = 0
# Record the coefficients of normal/ annular Zernike polynomials after
# z4 in unit of nm
self.zer4UpNm = np.array([])
# Converged wavefront.
self.wcomp = np.array([])
# Calculated wavefront in previous outer-loop iteration.
self.West = np.array([])
# Converged Zk coefficients
self.zcomp = np.array([])
# Calculated Zk coefficients in previous outer-loop iteration
self.zc = np.array([])
# Padded mask for use at the offset planes
self.pMask = None
# Non-padded mask corresponding to aperture
self.cMask = None
# Change the dimension of mask for fft to use
self.pMaskPad = None
self.cMaskPad = None
def setUp(self):
self.instDir = os.path.join(getConfigDir(), "cwfs", "instData")
self.inst = Instrument(self.instDir)
self.dimOfDonutOnSensor = 120
self.inst.config(CamType.LsstCam,
self.dimOfDonutOnSensor,
announcedDefocalDisInMm=1.5)
def __init__(self, instDir, algoDir):
self.inst = Instrument(instDir)
self.algo = Algorithm(algoDir)
self.imgIntra = CompensableImage()
self.imgExtra = CompensableImage()
self.opticalModel = ""
self.sizeInPix = 0
def __init__(self, algoDir):
self.algoDir = algoDir
self.algoParamFile = ParamReader()
self._inst = Instrument("")
# Show the calculation message based on this value
# 0 means no message will be showed
self.debugLevel = 0
# Image has the problem or not from the over-compensation
self.caustic = False
# Record the Zk coefficients in each outer-loop iteration
# The actual total outer-loop iteration time is Num_of_outer_itr + 1
self.converge = np.array([])
# Current number of outer-loop iteration
self.currentItr = 0
# Record the coefficients of normal/ annular Zernike polynomials after
# z4 in unit of nm
self.zer4UpNm = np.array([])
# Converged wavefront.
self.wcomp = np.array([])
# Calculated wavefront in previous outer-loop iteration.
self.West = np.array([])
# Converged Zk coefficients
self.zcomp = np.array([])
# Calculated Zk coefficients in previous outer-loop iteration
self.zc = np.array([])
# Padded mask for use at the offset planes
self.mask_comp = None
# Non-padded mask corresponding to aperture
self.mask_pupil = None
# Change the dimension of mask for fft to use
self.mask_comp_pad = None
self.mask_pupil_pad = None
# Cache annular Zernike evaluations
self._zk = None
# Cache evaluations of X and Y annular Zernike gradients
self._dzkdx = None
self._dzkdy = None
def testDataAuxTelZWO(self):
inst = Instrument(self.instDir)
inst.config(CamType.AuxTelZWO, 160, announcedDefocalDisInMm=0.5)
self.assertEqual(inst.getObscuration(), 0.3525)
self.assertEqual(inst.getFocalLength(), 21.6)
self.assertEqual(inst.getApertureDiameter(), 1.2)
self.assertEqual(inst.getDefocalDisOffset(), 0.0205)
self.assertEqual(inst.getCamPixelSize(), 15.2e-6)
self.assertAlmostEqual(inst.calcSizeOfDonutExpected(),
74.92690058,
places=7)
def setUp(self):
# Get the path of module
self.modulePath = getModulePath()
# Define the instrument folder
instruFolder = os.path.join(self.modulePath, "configData", "cwfs",
"instruData")
# Define the algorithm folder
algoFolderPath = os.path.join(self.modulePath, "configData", "cwfs",
"algo")
# Define the instrument name
instruName = "lsst"
# Define the algorithm being used: "exp" or "fft"
useAlgorithm = "fft"
# Define the image folder and image names
# Image data -- Don't know the final image format.
# It is noted that image.readFile inuts is based on the txt file
imageFolderPath = os.path.join(self.modulePath, "tests", "testData",
"testImages", "LSST_NE_SN25")
intra_image_name = "z11_0.25_intra.txt"
extra_image_name = "z11_0.25_extra.txt"
# Define fieldXY: [1.185, 1.185] or [0, 0]
# This is the position of donut on the focal plane in degree
fieldXY = [1.185, 1.185]
# Define the optical model: "paraxial", "onAxis", "offAxis"
self.opticalModel = "offAxis"
# Image files Path
intra_image_file = os.path.join(imageFolderPath, intra_image_name)
extra_image_file = os.path.join(imageFolderPath, extra_image_name)
# Theree is the difference between intra and extra images
# I1: intra_focal images, I2: extra_focal Images
# self.I1 = Image.Image()
# self.I2 = Image.Image()
self.I1 = CompensationImageDecorator()
self.I2 = CompensationImageDecorator()
self.I1.setImg(fieldXY, imageFile=intra_image_file, atype="intra")
self.I2.setImg(fieldXY, imageFile=extra_image_file, atype="extra")
self.inst = Instrument(instruFolder)
self.inst.config(instruName, self.I1.sizeinPix)
def _runWep(self, imgIntraName, imgExtraName, offset, model):
# Cut the donut image from input files
centroidFindType = CentroidFindType.Otsu
imgIntra = Image(centroidFindType=centroidFindType)
imgExtra = Image(centroidFindType=centroidFindType)
imgIntraPath = os.path.join(self.testImgDir, imgIntraName)
imgExtraPath = os.path.join(self.testImgDir, imgExtraName)
imgIntra.setImg(imageFile=imgIntraPath)
imgExtra.setImg(imageFile=imgExtraPath)
xIntra, yIntra, _ = imgIntra.getCenterAndR()
imgIntraArray = imgIntra.getImg()[int(yIntra) - offset:int(yIntra) +
offset,
int(xIntra) - offset:int(xIntra) +
offset, ]
xExtra, yExtra, _ = imgExtra.getCenterAndR()
imgExtraArray = imgExtra.getImg()[int(yExtra) - offset:int(yExtra) +
offset,
int(xExtra) - offset:int(xExtra) +
offset, ]
# Set the images
fieldXY = (0, 0)
imgCompIntra = CompensableImage(centroidFindType=centroidFindType)
imgCompIntra.setImg(fieldXY, DefocalType.Intra, image=imgIntraArray)
imgCompExtra = CompensableImage(centroidFindType=centroidFindType)
imgCompExtra.setImg(fieldXY, DefocalType.Extra, image=imgExtraArray)
# Calculate the wavefront error
# Set the instrument
instDir = os.path.join(getConfigDir(), "cwfs", "instData")
instAuxTel = Instrument(instDir)
instAuxTel.config(CamType.AuxTel,
imgCompIntra.getImgSizeInPix(),
announcedDefocalDisInMm=0.8)
# Set the algorithm
algoFolderPath = os.path.join(getConfigDir(), "cwfs", "algo")
algoAuxTel = Algorithm(algoFolderPath)
algoAuxTel.config("exp", instAuxTel)
algoAuxTel.runIt(imgCompIntra, imgCompExtra, model)
return algoAuxTel.getZer4UpInNm()
def setUp(self):
# Get the path of module
self.modulePath = getModulePath()
# Define the image folder and image names
# Image data -- Don't know the final image format.
# It is noted that image.readFile inuts is based on the txt file
imageFolderPath = os.path.join(self.modulePath, "tests", "testData",
"testImages", "LSST_NE_SN25")
intra_image_name = "z11_0.25_intra.txt"
extra_image_name = "z11_0.25_extra.txt"
# Define fieldXY: [1.185, 1.185] or [0, 0]
# This is the position of donut on the focal plane in degree
fieldXY = [1.185, 1.185]
# Define the optical model: "paraxial", "onAxis", "offAxis"
self.opticalModel = "offAxis"
# Image files Path
intra_image_file = os.path.join(imageFolderPath, intra_image_name)
extra_image_file = os.path.join(imageFolderPath, extra_image_name)
# Theree is the difference between intra and extra images
# I1: intra_focal images, I2: extra_focal Images
self.I1 = CompensableImage()
self.I2 = CompensableImage()
self.I1.setImg(fieldXY, DefocalType.Intra, imageFile=intra_image_file)
self.I2.setImg(fieldXY, DefocalType.Extra, imageFile=extra_image_file)
# Set up the instrument
cwfsConfigDir = os.path.join(getConfigDir(), "cwfs")
instDir = os.path.join(cwfsConfigDir, "instData")
self.inst = Instrument(instDir)
self.inst.config(CamType.LsstCam,
self.I1.getImgSizeInPix(),
announcedDefocalDisInMm=1.0)
# Set up the algorithm
algoDir = os.path.join(cwfsConfigDir, "algo")
self.algoExp = Algorithm(algoDir)
self.algoExp.config("exp", self.inst)
self.algoFft = Algorithm(algoDir)
self.algoFft.config("fft", self.inst)
def __init__(self, instruFolderPath, algoFolderPath):
"""
Initialize the wavefront estimator class.
Arguments:
instruFolderPath {[str]} -- Path to instrument directory.
algoFolderPath {[str]} -- Path to algorithm directory.
"""
self.algo = Algorithm(algoFolderPath)
self.inst = Instrument(instruFolderPath)
self.ImgIntra = CompensationImageDecorator()
self.ImgExtra = CompensationImageDecorator()
self.opticalModel = ""
self.sizeInPix = 0
def testMakeMasks(self):
donutStamp = DonutStamp(
self.testStamps[0],
lsst.geom.SpherePoint(0.0, 0.0, lsst.geom.degrees),
lsst.geom.Point2D(2047.5, 2001.5),
DefocalType.Extra.value,
"R22_S11",
"LSSTCam",
)
# Set up instrument
instDataPath = os.path.join(getConfigDir(), "cwfs", "instData")
inst = Instrument(instDataPath)
donutWidth = 126
inst.config(CamType.LsstCam, donutWidth)
# Check that masks are empty at start
np.testing.assert_array_equal(np.empty(shape=(0, 0)),
donutStamp.mask_comp.getArray())
np.testing.assert_array_equal(np.empty(shape=(0, 0)),
donutStamp.mask_pupil.getArray())
# Check masks after creation
donutStamp.makeMasks(inst, "offAxis", 0, 1)
self.assertEqual(afwImage.MaskX, type(donutStamp.mask_comp))
self.assertEqual(afwImage.MaskX, type(donutStamp.mask_pupil))
self.assertDictEqual({
"BKGRD": 0,
"DONUT": 1
}, donutStamp.mask_comp.getMaskPlaneDict())
self.assertDictEqual({
"BKGRD": 0,
"DONUT": 1
}, donutStamp.mask_pupil.getMaskPlaneDict())
maskC = donutStamp.mask_comp.getArray()
maskP = donutStamp.mask_pupil.getArray()
# Donut should match
self.assertEqual(np.shape(maskC), (126, 126))
self.assertEqual(np.shape(maskP), (126, 126))
# Make sure not just an empty array
self.assertTrue(np.sum(maskC) > 0.0)
self.assertTrue(np.sum(maskP) > 0.0)
# Donut at center of focal plane should be symmetric
np.testing.assert_array_equal(maskC[:63], maskC[-63:][::-1])
np.testing.assert_array_equal(maskP[:63], maskP[-63:][::-1])
def setUp(self):
# Get the path of module
modulePath = getModulePath()
# Define the instrument folder
instDir = os.path.join(getConfigDir(), "cwfs", "instData")
# Define the instrument name
dimOfDonutOnSensor = 120
self.inst = Instrument(instDir)
self.inst.config(CamType.LsstCam,
dimOfDonutOnSensor,
announcedDefocalDisInMm=1.0)
# Define the image folder and image names
# Image data -- Don't know the final image format.
# It is noted that image.readFile inuts is based on the txt file
imageFolderPath = os.path.join(modulePath, "tests", "testData",
"testImages", "LSST_NE_SN25")
intra_image_name = "z11_0.25_intra.txt"
extra_image_name = "z11_0.25_extra.txt"
self.imgFilePathIntra = os.path.join(imageFolderPath, intra_image_name)
self.imgFilePathExtra = os.path.join(imageFolderPath, extra_image_name)
# This is the position of donut on the focal plane in degree
self.fieldXY = (1.185, 1.185)
# Define the optical model: "paraxial", "onAxis", "offAxis"
self.opticalModel = "offAxis"
# Get the true Zk
zcAnsFilePath = os.path.join(
modulePath,
"tests",
"testData",
"testImages",
"validation",
"simulation",
"LSST_NE_SN25_z11_0.25_exp.txt",
)
self.zcCol = np.loadtxt(zcAnsFilePath)
self.wfsImg = CompensableImage()
def __init__(self, instDir, algoDir):
"""Initialize the wavefront estimator class.
Parameters
----------
instDir : str
Path to instrument directory.
algoDir : str
Path to algorithm directory.
"""
self.inst = Instrument(instDir)
self.algo = Algorithm(algoDir)
self.imgIntra = CompensableImage()
self.imgExtra = CompensableImage()
self.opticalModel = ""
self.sizeInPix = 0
def setUp(self):
# Get the path of module
modulePath = getModulePath()
# Define the instrument folder
instruFolder = os.path.join(modulePath, "configData", "cwfs",
"instruData")
# Define the instrument name
instruName = "lsst"
sensorSamples = 120
self.inst = Instrument(instruFolder)
self.inst.config(instruName, sensorSamples)
# Define the image folder and image names
# Image data -- Don't know the final image format.
# It is noted that image.readFile inuts is based on the txt file
imageFolderPath = os.path.join(modulePath, "tests", "testData",
"testImages", "LSST_NE_SN25")
intra_image_name = "z11_0.25_intra.txt"
extra_image_name = "z11_0.25_extra.txt"
self.imgFilePathIntra = os.path.join(imageFolderPath, intra_image_name)
self.imgFilePathExtra = os.path.join(imageFolderPath, extra_image_name)
# Define fieldXY: [1.185, 1.185] or [0, 0]
# This is the position of donut on the focal plane in degree
self.fieldXY = [1.185, 1.185]
# Define the optical model: "paraxial", "onAxis", "offAxis"
self.opticalModel = "offAxis"
# Get the true Zk
zcAnsFilePath = os.path.join(modulePath, "tests", "testData",
"testImages", "validation",
"LSST_NE_SN25_z11_0.25_exp.txt")
self.zcCol = np.loadtxt(zcAnsFilePath)
def _runWEP(
self,
instDir,
algoFolderPath,
useAlgorithm,
imageFolderPath,
intra_image_name,
extra_image_name,
fieldXY,
opticalModel,
showFig=False,
):
# Image files Path
intra_image_file = os.path.join(imageFolderPath, intra_image_name)
extra_image_file = os.path.join(imageFolderPath, extra_image_name)
# There is the difference between intra and extra images
# I1: intra_focal images, I2: extra_focal Images
I1 = CompensableImage()
I2 = CompensableImage()
I1.setImg(fieldXY, DefocalType.Intra, imageFile=intra_image_file)
I2.setImg(fieldXY, DefocalType.Extra, imageFile=extra_image_file)
# Set the instrument
inst = Instrument(instDir)
inst.config(CamType.LsstCam,
I1.getImgSizeInPix(),
announcedDefocalDisInMm=1.0)
# Define the algorithm to be used.
algo = Algorithm(algoFolderPath)
algo.config(useAlgorithm, inst, debugLevel=0)
# Plot the original wavefront images
if showFig:
plotImage(I1.image, title="intra image")
plotImage(I2.image, title="extra image")
# Run it
algo.runIt(I1, I2, opticalModel, tol=1e-3)
# Show the Zernikes Zn (n>=4)
algo.outZer4Up(showPlot=False)
# Plot the final conservated images and wavefront
if showFig:
plotImage(I1.image, title="Compensated intra image")
plotImage(I2.image, title="Compensated extra image")
# Plot the Wavefront
plotImage(algo.wcomp, title="Final wavefront")
plotImage(
algo.wcomp,
title="Final wavefront with pupil mask applied",
mask=algo.pMask,
)
# Return the Zernikes Zn (n>=4)
return algo.getZer4UpInNm()
def calcWfErr(
self,
centroidFindType,
fieldXY,
camType,
algoName,
announcedDefocalDisInMm,
opticalModel,
imageIntra=None,
imageExtra=None,
imageFileIntra=None,
imageFileExtra=None,
):
"""Calculate the wavefront error.
Parameters
----------
centroidFindType : enum 'CentroidFindType'
Algorithm to find the centroid of donut.
fieldXY : tuple or list
Position of donut on the focal plane in degree (field x, field y).
camType : enum 'CamType'
Camera type.
algoName : str
Algorithm configuration file to solve the Poisson's equation in the
transport of intensity equation (TIE). It can be "fft" or "exp"
here.
announcedDefocalDisInMm : float
Announced defocal distance in mm. It is noted that the defocal
distance offset used in calculation might be different from this
value.
opticalModel : str
Optical model. It can be "paraxial", "onAxis", or "offAxis".
imageIntra : numpy.ndarray, optional
Array of intra-focal image. (the default is None.)
imageExtra : numpy.ndarray, optional
Array of extra-focal image. (the default is None.)
imageFileIntra : str, optional
Path of intra-focal image file. (the default is None.)
imageFileExtra : str, optional
Path of extra-focal image file. (the default is None.)
Returns
-------
numpy.ndarray
Zernike polynomials of z4-zn in nm.
"""
# Set the defocal images
imgIntra = CompensableImage(centroidFindType=centroidFindType)
imgExtra = CompensableImage(centroidFindType=centroidFindType)
imgIntra.setImg(
fieldXY, DefocalType.Intra, image=imageIntra, imageFile=imageFileIntra
)
imgExtra.setImg(
fieldXY, DefocalType.Extra, image=imageExtra, imageFile=imageFileExtra
)
# Set the instrument
instDir = os.path.join(getConfigDir(), "cwfs", "instData")
inst = Instrument(instDir)
inst.config(
camType,
imgIntra.getImgSizeInPix(),
announcedDefocalDisInMm=announcedDefocalDisInMm,
)
# Define the algorithm to be used.
algoFolderPath = os.path.join(getConfigDir(), "cwfs", "algo")
algo = Algorithm(algoFolderPath)
algo.config(algoName, inst, debugLevel=0)
# Run it
algo.runIt(imgIntra, imgExtra, opticalModel, tol=1e-3)
# Return the Zernikes Zn (n>=4)
return algo.getZer4UpInNm()
def makeTemplate(
self,
sensorName,
defocalType,
imageSize,
camType=CamType.LsstCam,
opticalModel="offAxis",
pixelScale=0.2,
):
"""Make the donut template image.
Parameters
----------
sensorName : str
The camera detector for which we want to make a template. Should
be in "Rxx_Sxx" format.
defocalType : enum 'DefocalType'
The defocal state of the sensor.
imageSize : int
Size of template in pixels. The template will be a square.
camType : enum 'CamType', optional
Camera type. (Default is CamType.LsstCam)
model : str, optional
Optical model. It can be "paraxial", "onAxis", or "offAxis".
(The default is "offAxis")
pixelScale : float, optional
The pixels to arcseconds conversion factor. (The default is 0.2)
Returns
-------
numpy.ndarray [int]
The donut template as a binary image.
"""
configDir = getConfigDir()
focalPlaneLayout = readPhoSimSettingData(configDir,
"focalplanelayout.txt",
"fieldCenter")
pixelSizeInUm = float(focalPlaneLayout[sensorName][2])
sizeXinPixel = int(focalPlaneLayout[sensorName][3])
sensorXMicron, sensorYMicron = np.array(
focalPlaneLayout[sensorName][:2], dtype=float)
# Correction for wavefront sensors
if sensorName in ("R44_S00_C0", "R00_S22_C1"):
# Shift center to +x direction
sensorXMicron = sensorXMicron + sizeXinPixel / 2 * pixelSizeInUm
elif sensorName in ("R44_S00_C1", "R00_S22_C0"):
# Shift center to -x direction
sensorXMicron = sensorXMicron - sizeXinPixel / 2 * pixelSizeInUm
elif sensorName in ("R04_S20_C1", "R40_S02_C0"):
# Shift center to -y direction
sensorYMicron = sensorYMicron - sizeXinPixel / 2 * pixelSizeInUm
elif sensorName in ("R04_S20_C0", "R40_S02_C1"):
# Shift center to +y direction
sensorYMicron = sensorYMicron + sizeXinPixel / 2 * pixelSizeInUm
# Load Instrument parameters
instDir = os.path.join(configDir, "cwfs", "instData")
inst = Instrument(instDir)
inst.config(camType, imageSize)
# Create image for mask
img = CompensableImage()
# Convert pixel locations to degrees
sensorXPixel = float(sensorXMicron) / pixelSizeInUm
sensorYPixel = float(sensorYMicron) / pixelSizeInUm
# Multiply by pixelScale then divide by 3600 for arcsec -> deg conversion
sensorXDeg = sensorXPixel * pixelScale / 3600
sensorYDeg = sensorYPixel * pixelScale / 3600
fieldXY = [sensorXDeg, sensorYDeg]
# Define position of donut at center of current sensor in degrees
boundaryT = 0
maskScalingFactorLocal = 1
img.setImg(fieldXY,
defocalType,
image=np.zeros((imageSize, imageSize)))
img.makeMask(inst, opticalModel, boundaryT, maskScalingFactorLocal)
return img.getNonPaddedMask()
def testInstrument(self):
inst = Instrument(self.instruFolder)
inst.config(self.instruName, 120)
self.assertEqual(inst.parameter["sensorSamples"], 120)
def makeTemplate(
self,
sensorName,
defocalType,
imageSize,
camType=CamType.LsstCam,
opticalModel="offAxis",
pixelScale=0.2,
):
"""Make the donut template image.
Parameters
----------
sensorName : str
The camera detector for which we want to make a template. Should
be in "Rxx_Sxx" format.
defocalType : enum 'DefocalType'
The defocal state of the sensor.
imageSize : int
Size of template in pixels. The template will be a square.
camType : enum 'CamType', optional
Camera type. (The default is CamType.LsstCam)
opticalModel : str, optional
Optical model. It can be "paraxial", "onAxis", or "offAxis".
(The default is "offAxis")
pixelScale : float, optional
The pixels to arcseconds conversion factor. (The default is 0.2)
Returns
-------
numpy.ndarray [int]
The donut template as a binary image.
Raises
------
ValueError
Camera type is not supported.
"""
configDir = getConfigDir()
# Load Instrument parameters
instDir = os.path.join(configDir, "cwfs", "instData")
inst = Instrument(instDir)
if camType in (CamType.LsstCam, CamType.LsstFamCam, CamType.ComCam):
inst.config(camType, imageSize)
focalPlaneLayout = readPhoSimSettingData(configDir,
"focalplanelayout.txt",
"fieldCenter")
pixelSizeInUm = float(focalPlaneLayout[sensorName][2])
sensorXMicron, sensorYMicron = np.array(
focalPlaneLayout[sensorName][:2], dtype=float)
elif camType == CamType.AuxTel:
# AuxTel only works with onAxis sources
if opticalModel != "onAxis":
raise ValueError(
str(f"Optical Model {opticalModel} not supported with AuxTel. "
+ "Must use 'onAxis'."))
# Defocal distance for Latiss in mm
# for LsstCam can use the default
# hence only need to set here
announcedDefocalDisInMm = getDefocalDisInMm("auxTel")
inst.config(camType, imageSize, announcedDefocalDisInMm)
# load the info for auxTel
pixelSizeInMeters = inst.getCamPixelSize() # pixel size in meters.
pixelSizeInUm = pixelSizeInMeters * 1e6
camera = obs_lsst.Latiss.getCamera()
sensorName = list(
camera.getNameIter())[0] # only one detector in latiss
detector = camera.get(sensorName)
xp, yp = detector.getCenter(
cameraGeom.FOCAL_PLANE) # center of CCD in mm
# multiply by 1000 to for mm --> microns conversion
sensorXMicron = yp * 1000
sensorYMicron = xp * 1000
else:
raise ValueError("Camera type (%s) is not supported." % camType)
# Create image for mask
img = CompensableImage()
# Convert pixel locations to degrees
sensorXPixel = float(sensorXMicron) / pixelSizeInUm
sensorYPixel = float(sensorYMicron) / pixelSizeInUm
# Multiply by pixelScale then divide by 3600 for arcsec->deg conversion
sensorXDeg = sensorXPixel * pixelScale / 3600
sensorYDeg = sensorYPixel * pixelScale / 3600
fieldXY = [sensorXDeg, sensorYDeg]
# Define position of donut at center of current sensor in degrees
boundaryT = 0
maskScalingFactorLocal = 1
img.setImg(fieldXY,
defocalType,
image=np.zeros((imageSize, imageSize)))
img.makeMask(inst, opticalModel, boundaryT, maskScalingFactorLocal)
return img.getNonPaddedMask()
