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 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 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 __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 _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 __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 testFFT(self):
# Define the algorithm folder
algoFolderPath = os.path.join(self.modulePath, "configData", "cwfs",
"algo")
# Define the algorithm being used: "exp" or "fft"
useAlgorithm = "fft"
# Define the algorithm to be used.
algo = Algorithm(algoFolderPath)
algo.config(useAlgorithm, self.inst, debugLevel=0)
# Run it
algo.runIt(self.inst, self.I1, self.I2, self.opticalModel, tol=1e-3)
# Check the value
Zk = algo.zer4UpNm
self.assertEqual(int(Zk[7]), -192)
class WfEstimator(object):
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 getAlgo(self):
"""Get the algorithm object.
Returns
-------
Algorithm
Algorithm object.
"""
return self.algo
def getInst(self):
"""Get the instrument object.
Returns
-------
Instrument
Instrument object.
"""
return self.inst
def getIntraImg(self):
"""Get the intra-focal donut image.
Returns
-------
CompensableImage
Intra-focal donut image.
"""
return self.imgIntra
def getExtraImg(self):
"""Get the extra-focal donut image.
Returns
-------
CompensableImage
Extra-focal donut image.
"""
return self.imgExtra
def getOptModel(self):
"""Get the optical model.
Returns
-------
str
Optical model.
"""
return self.opticalModel
def getSizeInPix(self):
"""Get the donut image size in pixel defined by the config() function.
Returns
-------
int
Donut image size in pixel
"""
return self.sizeInPix
def reset(self):
"""
Reset the calculation for the new input images with the same algorithm
settings.
"""
self.algo.reset()
def config(
self,
solver="exp",
camType=CamType.LsstCam,
opticalModel="offAxis",
defocalDisInMm=1.5,
sizeInPix=120,
centroidFindType=CentroidFindType.RandomWalk,
debugLevel=0,
):
"""Configure the TIE solver.
Parameters
----------
solver : str, optional
Algorithm to solve the Poisson's equation in the transport of
intensity equation (TIE). It can be "fft" or "exp" here. (the
default is "exp".)
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".)
defocalDisInMm : float, optional
Defocal distance in mm. (the default is 1.5.)
sizeInPix : int, optional
Wavefront image pixel size. (the default is 120.)
centroidFindType : enum 'CentroidFindType', optional
Algorithm to find the centroid of donut. (the default is
CentroidFindType.RandomWalk.)
debugLevel : int, optional
Show the information under the running. If the value is higher,
the information shows more. It can be 0, 1, 2, or 3. (the default
is 0.)
Raises
------
ValueError
Wrong Poisson solver name.
ValueError
Wrong optical model.
"""
if solver not in ("exp", "fft"):
raise ValueError("Poisson solver can not be '%s'." % solver)
if opticalModel not in ("paraxial", "onAxis", "offAxis"):
raise ValueError("Optical model can not be '%s'." % opticalModel)
else:
self.opticalModel = opticalModel
# Update the instrument name
self.sizeInPix = int(sizeInPix)
self.inst.config(camType,
self.sizeInPix,
announcedDefocalDisInMm=defocalDisInMm)
self.algo.config(solver, self.inst, debugLevel=debugLevel)
# Reset the centroid find algorithm if not the default one
if centroidFindType != CentroidFindType.RandomWalk:
self.imgIntra = CompensableImage(centroidFindType=centroidFindType)
self.imgExtra = CompensableImage(centroidFindType=centroidFindType)
def setImg(self, fieldXY, defocalType, image=None, imageFile=None):
"""Set the wavefront image.
Parameters
----------
fieldXY : tuple or list
Position of donut on the focal plane in degree for intra- and
extra-focal images.
defocalType : enum 'DefocalType'
Defocal type of image.
image : numpy.ndarray, optional
Array of image. (the default is None.)
imageFile : str, optional
Path of image file. (the default is None.)
"""
if defocalType == DefocalType.Intra:
img = self.imgIntra
elif defocalType == DefocalType.Extra:
img = self.imgExtra
img.setImg(fieldXY, defocalType, image=image, imageFile=imageFile)
def calWfsErr(self, tol=1e-3, showZer=False, showPlot=False):
"""Calculate the wavefront error.
Parameters
----------
tol : float, optional
[description] (the default is 1e-3.)
showZer : bool, optional
Decide to show the annular Zernike polynomails or not. (the default
is False.)
showPlot : bool, optional
Decide to show the plot or not. (the default is False.)
Returns
-------
numpy.ndarray
Coefficients of Zernike polynomials (z4 - z22).
Raises
------
RuntimeError
Input image shape is wrong.
"""
# Check the image size
for img in (self.imgIntra, self.imgExtra):
d1, d2 = img.getImg().shape
if (d1 != self.sizeInPix) or (d2 != self.sizeInPix):
raise RuntimeError(
"Input image shape is (%d, %d), not required (%d, %d)" %
(d1, d2, self.sizeInPix, self.sizeInPix))
# Calculate the wavefront error.
# Run cwfs
self.algo.runIt(self.imgIntra,
self.imgExtra,
self.opticalModel,
tol=tol)
# Show the Zernikes Zn (n>=4)
if showZer:
self.algo.outZer4Up(showPlot=showPlot)
return self.algo.getZer4UpInNm()
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()
class TestAlgorithm(unittest.TestCase):
"""Test the Algorithm class."""
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 testGetDebugLevel(self):
self.assertEqual(self.algoExp.getDebugLevel(), 0)
def testSetDebugLevel(self):
self.algoExp.config("exp", self.inst, debugLevel=3)
self.assertEqual(self.algoExp.getDebugLevel(), 3)
self.algoExp.setDebugLevel(0)
self.assertEqual(self.algoExp.getDebugLevel(), 0)
def testGetZer4UpInNm(self):
zer4UpNm = self.algoExp.getZer4UpInNm()
self.assertTrue(isinstance(zer4UpNm, np.ndarray))
def testGetPoissonSolverName(self):
self.assertEqual(self.algoExp.getPoissonSolverName(), "exp")
self.assertEqual(self.algoFft.getPoissonSolverName(), "fft")
def testGetNumOfZernikes(self):
self.assertEqual(self.algoExp.getNumOfZernikes(), 22)
self.assertEqual(self.algoFft.getNumOfZernikes(), 22)
def testGetZernikeTerms(self):
zTerms = self.algoExp.getZernikeTerms()
self.assertTrue(type(zTerms[0]), int)
self.assertEqual(len(zTerms), self.algoExp.getNumOfZernikes())
self.assertEqual(zTerms[1], 1)
self.assertEqual(zTerms[-1], self.algoExp.getNumOfZernikes() - 1)
zTerms = self.algoFft.getZernikeTerms()
self.assertTrue(type(zTerms[0]), int)
self.assertEqual(len(zTerms), self.algoExp.getNumOfZernikes())
def testGetObsOfZernikes(self):
self.assertEqual(self.algoExp.getObsOfZernikes(),
self.inst.getObscuration())
self.assertEqual(self.algoFft.getObsOfZernikes(),
self.inst.getObscuration())
def testGetNumOfOuterItr(self):
self.assertEqual(self.algoExp.getNumOfOuterItr(), 14)
self.assertEqual(self.algoFft.getNumOfOuterItr(), 14)
def testGetNumOfInnerItr(self):
self.assertEqual(self.algoFft.getNumOfInnerItr(), 6)
def testGetFeedbackGain(self):
self.assertEqual(self.algoExp.getFeedbackGain(), 0.6)
self.assertEqual(self.algoFft.getFeedbackGain(), 0.6)
def testGetOffAxisPolyOrder(self):
self.assertEqual(self.algoExp.getOffAxisPolyOrder(), 10)
self.assertEqual(self.algoFft.getOffAxisPolyOrder(), 10)
def testGetCompensatorMode(self):
self.assertEqual(self.algoExp.getCompensatorMode(), "zer")
self.assertEqual(self.algoFft.getCompensatorMode(), "zer")
def testGetCompSequence(self):
compSequence = self.algoExp.getCompSequence()
self.assertTrue(isinstance(compSequence, np.ndarray))
self.assertEqual(compSequence.dtype, int)
self.assertEqual(len(compSequence), self.algoExp.getNumOfOuterItr())
self.assertEqual(compSequence[0], 4)
self.assertEqual(compSequence[-1], 22)
compSequence = self.algoFft.getCompSequence()
self.assertEqual(len(compSequence), self.algoFft.getNumOfOuterItr())
def testGetBoundaryThickness(self):
self.assertEqual(self.algoExp.getBoundaryThickness(), 8)
self.assertEqual(self.algoFft.getBoundaryThickness(), 1)
def testGetFftDimension(self):
self.assertEqual(self.algoFft.getFftDimension(), 128)
def testGetSignalClipSequence(self):
sumclipSequence = self.algoFft.getSignalClipSequence()
self.assertTrue(isinstance(sumclipSequence, np.ndarray))
self.assertEqual(len(sumclipSequence),
self.algoExp.getNumOfOuterItr() + 1)
self.assertEqual(sumclipSequence[0], 0.33)
self.assertEqual(sumclipSequence[-1], 0.51)
def testGetMaskScalingFactor(self):
self.assertAlmostEqual(self.algoExp.getMaskScalingFactor(),
1.0939,
places=4)
self.assertAlmostEqual(self.algoFft.getMaskScalingFactor(),
1.0939,
places=4)
def testGetWavefrontMapEstiInIter0(self):
self.assertRaises(RuntimeError, self.algoExp.getWavefrontMapEsti)
def testGetWavefrontMapEstiAndResidual(self):
self.algoExp.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
wavefrontMapEsti = self.algoExp.getWavefrontMapEsti()
wavefrontMapEsti[np.isnan(wavefrontMapEsti)] = 0
self.assertGreater(np.sum(np.abs(wavefrontMapEsti)), 4.8e-4)
wavefrontMapResidual = self.algoExp.getWavefrontMapResidual()
wavefrontMapResidual[np.isnan(wavefrontMapResidual)] = 0
self.assertLess(np.sum(np.abs(wavefrontMapResidual)), 2.5e-6)
def testItr0(self):
self.algoExp.itr0(self.I1, self.I2, self.opticalModel)
zer4UpNm = self.algoExp.getZer4UpInNm()
self.assertEqual(
np.sum(np.abs(np.rint(zer4UpNm) - self._getAnsItr0())), 0)
def _getAnsItr0(self):
return [
31,
-69,
-21,
84,
44,
-53,
48,
-146,
6,
10,
13,
-5,
1,
-12,
-8,
7,
0,
-6,
11,
]
def testNextItrWithOneIter(self):
self.algoExp.nextItr(self.I1, self.I2, self.opticalModel, nItr=1)
zer4UpNm = self.algoExp.getZer4UpInNm()
self.assertEqual(
np.sum(np.abs(np.rint(zer4UpNm) - self._getAnsItr0())), 0)
def testNextItrWithTwoIter(self):
self.algoExp.nextItr(self.I1, self.I2, self.opticalModel, nItr=2)
zer4UpNm = self.algoExp.getZer4UpInNm()
ansRint = [
40,
-80,
-18,
92,
44.0,
-52,
54,
-146,
5,
10,
15,
-3,
-0,
-12,
-8,
7,
1,
-3,
12,
]
self.assertEqual(np.sum(np.abs(np.rint(zer4UpNm) - ansRint)), 0)
def testIter0AndNextIterToCheckReset(self):
self.algoExp.itr0(self.I1, self.I2, self.opticalModel)
tmp1 = self.algoExp.getZer4UpInNm()
self.algoExp.nextItr(self.I1, self.I2, self.opticalModel, nItr=2)
# itr0() should reset the images and ignore the effect from nextItr()
self.algoExp.itr0(self.I1, self.I2, self.opticalModel)
tmp2 = self.algoExp.getZer4UpInNm()
difference = np.sum(np.abs(tmp1 - tmp2))
self.assertEqual(difference, 0)
def testRunItOfExp(self):
self.algoExp.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
# Check the value
zk = self.algoExp.getZer4UpInNm()
self.assertEqual(int(zk[7]), -192)
def testResetAfterFullCalc(self):
self.algoExp.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
# Reset and check the calculation again
fieldXY = [self.I1.fieldX, self.I1.fieldY]
self.I1.setImg(fieldXY,
self.I1.getDefocalType(),
image=self.I1.getImgInit())
self.I2.setImg(fieldXY,
self.I2.getDefocalType(),
image=self.I2.getImgInit())
self.algoExp.reset()
self.algoExp.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
zk = self.algoExp.getZer4UpInNm()
self.assertEqual(int(zk[7]), -192)
def testRunItOfFft(self):
self.algoFft.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
zk = self.algoFft.getZer4UpInNm()
self.assertEqual(int(zk[7]), -192)
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()
class WfEstimator(object):
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 getAlgo(self):
"""Get the algorithm object.
Returns
-------
Algorithm
Algorithm object.
"""
return self.algo
def getInst(self):
"""Get the instrument object.
Returns
-------
Instrument
Instrument object.
"""
return self.inst
def getIntraImg(self):
"""Get the intra-focal donut image.
Returns
-------
CompensationImageDecorator
Intra-focal donut image.
"""
return self.ImgIntra
def getExtraImg(self):
"""Get the extra-focal donut image.
Returns
-------
CompensationImageDecorator
Extra-focal donut image.
"""
return self.ImgExtra
def getOptModel(self):
"""Get the optical model.
Returns
-------
str
Optical model.
"""
return self.opticalModel
def getSizeInPix(self):
"""Get the donut image size in pixel defined by the config() function.
Returns
-------
int
Donut image size in pixel
"""
return self.sizeInPix
def reset(self):
"""
Reset the calculation for the new input images with the same algorithm
settings.
"""
self.algo.reset()
def config(self,
solver="exp",
instName="lsst",
opticalModel="offAxis",
defocalDisInMm=None,
sizeInPix=120,
debugLevel=0):
"""
Configure the TIE solver.
Keyword Arguments:
solver {[str]} -- Algorithm to solve the Poisson's equation in the transport of
intensity equation (TIE). It can be "fft" or "exp" here.
(default: {"exp"})
instName {[str]} -- Instrument name. It is "lsst" in the baseline. (default: {"lsst"})
opticalModel {[str]} -- Optical model. It can be "paraxial", "onAxis", or "offAxis".
(default: {"offAxis"})
defocalDisInMm {[float]} -- Defocal distance in mm. (default: {None})
sizeInPix {[int]} -- Wavefront image pixel size. (default: {120})
debugLevel {[int]} -- Show the information under the running. If the value is higher,
the information shows more. It can be 0, 1, 2, or 3.
(default: {0})
Raises:
ValueError -- Wrong instrument name.
ValueError -- No intra-focal image.
ValueError -- Wrong Poisson solver name.
ValueError -- Wrong optical model.
"""
# Check the inputs and assign the parameters used in the TIE
# Need to change the way to hold the instance of Instrument and Algorithm
# Update the isnstrument name
if (defocalDisInMm is not None):
instName = instName + str(int(10 * defocalDisInMm))
if instName not in ("lsst", "lsst05", "lsst10", "lsst15", "lsst20",
"lsst25", "comcam10", "comcam15", "comcam20"):
raise ValueError("Instrument can not be '%s'." % instName)
# Set the available wavefront image size (n x n)
self.sizeInPix = int(sizeInPix)
# Configurate the instrument
self.inst.config(instName, self.sizeInPix)
if solver not in ("exp", "fft"):
raise ValueError("Poisson solver can not be '%s'." % solver)
else:
self.algo.config(solver, self.inst, debugLevel=debugLevel)
if opticalModel not in ("paraxial", "onAxis", "offAxis"):
raise ValueError("Optical model can not be '%s'." % opticalModel)
else:
self.opticalModel = opticalModel
def setImg(self, fieldXY, image=None, imageFile=None, defocalType=None):
"""
Set the wavefront image.
Arguments:
fieldXY {[float]} -- Position of donut on the focal plane in degree for intra-
and extra-focal images.
Keyword Arguments:
image {[float]} -- Array of image. (default: {None})
imageFile {[str]} -- Path of image file. (default: {None})
defocalType {[str]} -- Type of image. It should be "intra" or "extra".
(default: {None})
Raises:
ValueError -- Wrong defocal type.
"""
# Check the defocal type
if defocalType not in (self.ImgIntra.INTRA, self.ImgIntra.EXTRA):
raise ValueError("Defocal type can not be '%s'." % defocalType)
# Read the image and assign the type
if (defocalType == self.ImgIntra.INTRA):
self.ImgIntra.setImg(fieldXY,
image=image,
imageFile=imageFile,
atype=defocalType)
elif (defocalType == self.ImgIntra.EXTRA):
self.ImgExtra.setImg(fieldXY,
image=image,
imageFile=imageFile,
atype=defocalType)
def calWfsErr(self, tol=1e-3, showZer=False, showPlot=False):
"""
Calculate the wavefront error.
Keyword Arguments:
tol {number} -- Tolerance of difference of coefficients of Zk polynomials compared
with the previours iteration. (default: {1e-3})
showZer {bool} -- Decide to show the annular Zernike polynomails or not.
(default: {False})
showPlot {bool} -- Decide to show the plot or not. (default: {False})
Returns:
[float] -- Coefficients of Zernike polynomials (z4 - z22).
"""
# Check the image size
for img in (self.ImgIntra, self.ImgExtra):
d1, d2 = img.image.shape
if (d1 != self.sizeInPix) or (d2 != self.sizeInPix):
raise RuntimeError(
"Input image shape is (%d, %d), not required (%d, %d)" %
(d1, d2, self.sizeInPix, self.sizeInPix))
# Calculate the wavefront error.
# Run cwfs
self.algo.runIt(self.inst,
self.ImgIntra,
self.ImgExtra,
self.opticalModel,
tol=tol)
# Show the Zernikes Zn (n>=4)
if (showZer):
self.algo.outZer4Up(showPlot=showPlot)
return self.algo.zer4UpNm
def outParam(self, filename=None):
"""
Put the information of images, instrument, and algorithm on terminal or file.
Keyword Arguments:
filename {[str]} -- Name of output file. (default: {None})
"""
# Write the parameters into a file if needed.
if (filename is not None):
fout = open(filename, "w")
else:
fout = sys.stdout
# Write the information of image and optical model
if (self.ImgIntra.name is not None):
fout.write("Intra image: \t %s\n" % self.ImgIntra.name)
if (self.ImgIntra.fieldX is not None):
fout.write("Intra image field in deg =(%6.3f, %6.3f)\n" %
(self.ImgIntra.fieldX, self.ImgIntra.fieldY))
if (self.ImgExtra.name is not None):
fout.write("Extra image: \t %s\n" % self.ImgExtra.name)
if (self.ImgExtra.fieldX is not None):
fout.write("Extra image field in deg =(%6.3f, %6.3f)\n" %
(self.ImgExtra.fieldX, self.ImgExtra.fieldY))
if (self.opticalModel is not None):
fout.write("Using optical model:\t %s\n" % self.opticalModel)
# Read the instrument file
if (self.inst.filename is not None):
self.__readConfigFile(fout, self.inst, "instrument")
# Read the algorithm file
if (self.algo.filename is not None):
self.__readConfigFile(fout, self.algo, "algorithm")
# Close the file
if (filename is not None):
fout.close()
def __readConfigFile(self, fout, config, configName):
"""
Read the configuration file
Arguments:
fout {[file]} -- File instance.
config {[metadata]} -- Instance of configuration. It is Instrument or Algorithm
here.
configName {[str]} -- Name of configuration.
"""
# Create a new line
fout.write("\n")
# Open the file
fconfig = open(config.filename)
fout.write("---" + configName +
" file: --- %s ----------\n" % config.filename)
# Read the file information
iscomment = False
for line in fconfig:
line = line.strip()
if (line.startswith("###")):
iscomment = ~iscomment
if (not (line.startswith("#")) and (not iscomment)
and len(line) > 0):
fout.write(line + "\n")
# Close the file
fconfig.close()
class WfEstimator(object):
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 getAlgo(self):
"""Get the algorithm object.
Returns
-------
Algorithm
Algorithm object.
"""
return self.algo
def getInst(self):
"""Get the instrument object.
Returns
-------
Instrument
Instrument object.
"""
return self.inst
def getIntraImg(self):
"""Get the intra-focal donut image.
Returns
-------
CompensableImage
Intra-focal donut image.
"""
return self.imgIntra
def getExtraImg(self):
"""Get the extra-focal donut image.
Returns
-------
CompensableImage
Extra-focal donut image.
"""
return self.imgExtra
def getOptModel(self):
"""Get the optical model.
Returns
-------
str
Optical model.
"""
return self.opticalModel
def getSizeInPix(self):
"""Get the donut image size in pixel defined by the config() function.
Returns
-------
int
Donut image size in pixel
"""
return self.sizeInPix
def reset(self):
"""
Reset the calculation for the new input images with the same algorithm
settings.
"""
self.algo.reset()
def config(self, solver="exp", camType=CamType.LsstCam,
opticalModel="offAxis", defocalDisInMm=None, sizeInPix=120,
debugLevel=0):
"""Configure the TIE solver.
Parameters
----------
solver : str, optional
Algorithm to solve the Poisson's equation in the transport of
intensity equation (TIE). It can be "fft" or "exp" here. (the
default is "exp".)
camType : enum 'CamType'
Camera type. (the default is CamType.LsstCam.)
opticalModel : str, optional
Optical model. It can be "paraxial", "onAxis", or "offAxis". (the
default is "offAxis".)
defocalDisInMm : float, optional
Defocal distance in mm. (the default is None.)
sizeInPix : int, optional
Wavefront image pixel size. (the default is 120.)
debugLevel : int, optional
Show the information under the running. If the value is higher,
the information shows more. It can be 0, 1, 2, or 3. (the default
is 0.)
Raises
------
ValueError
Wrong Poisson solver name.
ValueError
Wrong optical model.
"""
if solver not in ("exp", "fft"):
raise ValueError("Poisson solver can not be '%s'." % solver)
if opticalModel not in ("paraxial", "onAxis", "offAxis"):
raise ValueError("Optical model can not be '%s'." % opticalModel)
else:
self.opticalModel = opticalModel
# Update the isnstrument name
if (defocalDisInMm is None):
defocalDisInMm = 1.5
self.sizeInPix = int(sizeInPix)
self.inst.config(camType, self.sizeInPix,
announcedDefocalDisInMm=defocalDisInMm)
self.algo.config(solver, self.inst, debugLevel=debugLevel)
def setImg(self, fieldXY, defocalType, image=None, imageFile=None):
"""Set the wavefront image.
Parameters
----------
fieldXY : tuple or list
Position of donut on the focal plane in degree for intra- and
extra-focal images.
defocalType : enum 'DefocalType'
Defocal type of image.
image : numpy.ndarray, optional
Array of image. (the default is None.)
imageFile : str, optional
Path of image file. (the default is None.)
"""
if (defocalType == DefocalType.Intra):
img = self.imgIntra
elif (defocalType == DefocalType.Extra):
img = self.imgExtra
img.setImg(fieldXY, defocalType, image=image, imageFile=imageFile)
def calWfsErr(self, tol=1e-3, showZer=False, showPlot=False):
"""Calculate the wavefront error.
Parameters
----------
tol : float, optional
[description] (the default is 1e-3.)
showZer : bool, optional
Decide to show the annular Zernike polynomails or not. (the default
is False.)
showPlot : bool, optional
Decide to show the plot or not. (the default is False.)
Returns
-------
numpy.ndarray
Coefficients of Zernike polynomials (z4 - z22).
Raises
------
RuntimeError
Input image shape is wrong.
"""
# Check the image size
for img in (self.imgIntra, self.imgExtra):
d1, d2 = img.getImg().shape
if (d1 != self.sizeInPix) or (d2 != self.sizeInPix):
raise RuntimeError("Input image shape is (%d, %d), not required (%d, %d)" % (
d1, d2, self.sizeInPix, self.sizeInPix))
# Calculate the wavefront error.
# Run cwfs
self.algo.runIt(self.imgIntra, self.imgExtra, self.opticalModel, tol=tol)
# Show the Zernikes Zn (n>=4)
if (showZer):
self.algo.outZer4Up(showPlot=showPlot)
return self.algo.getZer4UpInNm()
def testExp(self):
# Define the algorithm folder
algoFolderPath = os.path.join(self.modulePath, "configData", "cwfs",
"algo")
# Define the algorithm being used: "exp" or "fft"
useAlgorithm = "exp"
# Define the algorithm to be used.
algo = Algorithm(algoFolderPath)
algo.config(useAlgorithm, self.inst, debugLevel=3)
algo.setDebugLevel(0)
self.assertEqual(algo.debugLevel, 0)
# Test functions: itr0() and nextItr()
algo.itr0(self.inst, self.I1, self.I2, self.opticalModel)
tmp1 = algo.zer4UpNm
algo.nextItr(self.inst, self.I1, self.I2, self.opticalModel, nItr=2)
algo.itr0(self.inst, self.I1, self.I2, self.opticalModel)
tmp2 = algo.zer4UpNm
difference = np.sum(np.abs(tmp1 - tmp2))
self.assertEqual(difference, 0)
# Run it
algo.runIt(self.inst, self.I1, self.I2, self.opticalModel, tol=1e-3)
# Check the value
Zk = algo.zer4UpNm
self.assertEqual(int(Zk[7]), -192)
# Reset and check the calculation again
fieldXY = [self.I1.fieldX, self.I1.fieldY]
self.I1.setImg(fieldXY, image=self.I1.image0, atype=self.I1.atype)
self.I2.setImg(fieldXY, image=self.I2.image0, atype=self.I2.atype)
algo.reset()
algo.runIt(self.inst, self.I1, self.I2, self.opticalModel, tol=1e-3)
Zk = algo.zer4UpNm
self.assertEqual(int(Zk[7]), -192)
def runWEP(instDir, algoFolderPath, useAlgorithm, imageFolderPath,
intra_image_name, extra_image_name, fieldXY, opticalModel,
showFig=False):
"""Calculate the coefficients of normal/ annular Zernike polynomials based
on the provided instrument, algorithm, and optical model.
Parameters
----------
instDir : str
Path to instrument folder.
algoFolderPath : str
Path to algorithm folder.
useAlgorithm : str
Algorithm to solve the Poisson's equation in the transport of intensity
equation (TIE). It can be "fft" or "exp" here.
imageFolderPath : str
Path to image folder.
intra_image_name : str
File name of intra-focal image.
extra_image_name : str
File name of extra-focal image.
fieldXY : tuple
Position of donut on the focal plane in degree for intra- and
extra-focal images.
opticalModel : str
Optical model. It can be "paraxial", "onAxis", or "offAxis".
showFig : bool, optional
Show the wavefront image and compenstated image or not. (the default is
False.)
Returns
-------
numpy.ndarray
Coefficients of Zernike polynomials (z4 - z22).
"""
# 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()
class TestAlgorithm(unittest.TestCase):
"""Test the Algorithm class."""
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 testGetDebugLevel(self):
self.assertEqual(self.algoExp.getDebugLevel(), 0)
def testSetDebugLevel(self):
self.algoExp.config("exp", self.inst, debugLevel=3)
self.assertEqual(self.algoExp.getDebugLevel(), 3)
self.algoExp.setDebugLevel(0)
self.assertEqual(self.algoExp.getDebugLevel(), 0)
def testGetZer4UpInNm(self):
zer4UpNm = self.algoExp.getZer4UpInNm()
self.assertTrue(isinstance(zer4UpNm, np.ndarray))
def testGetPoissonSolverName(self):
self.assertEqual(self.algoExp.getPoissonSolverName(), "exp")
self.assertEqual(self.algoFft.getPoissonSolverName(), "fft")
def testGetNumOfZernikes(self):
self.assertEqual(self.algoExp.getNumOfZernikes(), 22)
self.assertEqual(self.algoFft.getNumOfZernikes(), 22)
def testGetZernikeTerms(self):
zTerms = self.algoExp.getZernikeTerms()
self.assertTrue(zTerms.dtype, int)
self.assertEqual(len(zTerms), self.algoExp.getNumOfZernikes())
self.assertEqual(zTerms[0], 1)
self.assertEqual(zTerms[-1], self.algoExp.getNumOfZernikes())
zTerms = self.algoFft.getZernikeTerms()
self.assertTrue(zTerms.dtype, int)
self.assertEqual(len(zTerms), self.algoExp.getNumOfZernikes())
def testGetObsOfZernikes(self):
self.assertEqual(self.algoExp.getObsOfZernikes(),
self.inst.getObscuration())
self.assertEqual(self.algoFft.getObsOfZernikes(),
self.inst.getObscuration())
def testGetNumOfOuterItr(self):
self.assertEqual(self.algoExp.getNumOfOuterItr(), 14)
self.assertEqual(self.algoFft.getNumOfOuterItr(), 14)
def testGetNumOfInnerItr(self):
self.assertEqual(self.algoFft.getNumOfInnerItr(), 6)
def testGetFeedbackGain(self):
self.assertEqual(self.algoExp.getFeedbackGain(), 0.6)
self.assertEqual(self.algoFft.getFeedbackGain(), 0.6)
def testGetOffAxisPolyOrder(self):
self.assertEqual(self.algoExp.getOffAxisPolyOrder(), 10)
self.assertEqual(self.algoFft.getOffAxisPolyOrder(), 10)
def testGetCompensatorMode(self):
self.assertEqual(self.algoExp.getCompensatorMode(), "zer")
self.assertEqual(self.algoFft.getCompensatorMode(), "zer")
def testGetCompSequence(self):
compSequence = self.algoExp.getCompSequence()
self.assertTrue(isinstance(compSequence, np.ndarray))
self.assertEqual(compSequence.dtype, int)
self.assertEqual(len(compSequence), self.algoExp.getNumOfOuterItr())
self.assertEqual(compSequence[0], 4)
self.assertEqual(compSequence[-1], 22)
compSequence = self.algoFft.getCompSequence()
self.assertEqual(len(compSequence), self.algoFft.getNumOfOuterItr())
def testGetBoundaryThickness(self):
self.assertEqual(self.algoExp.getBoundaryThickness(), 8)
self.assertEqual(self.algoFft.getBoundaryThickness(), 1)
def testGetFftDimension(self):
self.assertEqual(self.algoFft.getFftDimension(), 128)
def testGetSignalClipSequence(self):
sumclipSequence = self.algoFft.getSignalClipSequence()
self.assertTrue(isinstance(sumclipSequence, np.ndarray))
self.assertEqual(len(sumclipSequence), self.algoExp.getNumOfOuterItr()+1)
self.assertEqual(sumclipSequence[0], 0.33)
self.assertEqual(sumclipSequence[-1], 0.51)
def testGetMaskScalingFactor(self):
self.assertAlmostEqual(self.algoExp.getMaskScalingFactor(), 1.0939,
places=4)
self.assertAlmostEqual(self.algoFft.getMaskScalingFactor(), 1.0939,
places=4)
def testRunItOfExp(self):
# Test functions: itr0() and nextItr()
self.algoExp.itr0(self.I1, self.I2, self.opticalModel)
tmp1 = self.algoExp.getZer4UpInNm()
self.algoExp.nextItr(self.I1, self.I2, self.opticalModel, nItr=2)
self.algoExp.itr0(self.I1, self.I2, self.opticalModel)
tmp2 = self.algoExp.getZer4UpInNm()
difference = np.sum(np.abs(tmp1-tmp2))
self.assertEqual(difference, 0)
# Run it
self.algoExp.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
# Check the value
Zk = self.algoExp.getZer4UpInNm()
self.assertEqual(int(Zk[7]), -192)
# Reset and check the calculation again
fieldXY = [self.I1.fieldX, self.I1.fieldY]
self.I1.setImg(fieldXY, self.I1.getDefocalType(), image=self.I1.getImgInit())
self.I2.setImg(fieldXY, self.I2.getDefocalType(), image=self.I2.getImgInit())
self.algoExp.reset()
self.algoExp.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
Zk = self.algoExp.getZer4UpInNm()
self.assertEqual(int(Zk[7]), -192)
def testRunItOfFft(self):
self.algoFft.runIt(self.I1, self.I2, self.opticalModel, tol=1e-3)
zk = self.algoFft.getZer4UpInNm()
self.assertEqual(int(zk[7]), -192)