def runcwfs(argList):
I1File = argList[0]
I1Field = argList[1]
I2File = argList[2]
I2Field = argList[3]
inst = argList[4]
algo = argList[5]
model = argList[6]
I1 = Image(readFile(I1File), I1Field, 'intra')
I2 = Image(readFile(I2File), I2Field, 'extra')
algo.reset(I1, I2)
algo.runIt(inst, I1, I2, model)
return np.append(algo.zer4UpNm*1e-3, algo.caustic)
def testMatlab(self):
global doPlot
if doPlot:
fig = plt.figure(figsize=(10, 10))
j = 0 # counter for matlab outputs, self.matlabZFile_Tol
for imgDir, filenameFmt, fldxy, algorithms, model in self.tests:
imgDir = os.path.join(str(self.rootdir), imgDir)
intraFile = os.path.join(imgDir, filenameFmt % "intra")
I1 = Image(readFile(intraFile), fldxy, Image.INTRA)
extraFile = os.path.join(imgDir, filenameFmt % "extra")
I2 = Image(readFile(extraFile), fldxy, Image.EXTRA)
inst = Instrument(self.myinst, I1.sizeinPix)
for algorithm in algorithms:
matlabZFile, tol = self.matlabZFile_Tol[j]; j += 1
algo = Algorithm(algorithm, inst, 1)
algo.runIt(inst, I1, I2, model)
zer = algo.zer4UpNm
matZ = np.loadtxt(os.path.join(self.validationDir, matlabZFile))
aerr = np.abs(matZ - zer)
print("%-31s max(abs(err)) = %8.3g median(abs(err)) = %8.3g [Z_%d]" %
(matlabZFile, np.max(aerr), np.median(aerr), self.Zernike0 + np.argmax(aerr)))
if doPlot:
ax = plt.subplot(self.nTest, 1, j)
plt.plot(self.x, matZ, label='Matlab', marker='o', color='r', markersize=10)
plt.plot(self.x, zer, label='Python', marker='.', color='b', markersize=10)
plt.axvline(self.Zernike0 + np.argmax(aerr), ls=':', color='black')
plt.legend(loc="best", shadow=True, title=matlabZFile, fancybox=True)
ax.get_legend().get_title().set_color("red")
plt.xlim(self.x[0] - 0.5, self.x[-1] + 0.5)
assert np.max(aerr) < tol
if doPlot:
plt.show()
def testMatlab(self):
global doPlot
if doPlot:
fig = plt.figure(figsize=(10, 10))
j = 0 # counter for matlab outputs, self.matlabZFile_Tol
for imgDir, filenameFmt, fldxy, algorithms, model in self.tests:
imgDir = os.path.join(str(self.rootdir), imgDir)
intraFile = os.path.join(imgDir, filenameFmt % "intra")
I1 = Image(readFile(intraFile), fldxy, Image.INTRA)
extraFile = os.path.join(imgDir, filenameFmt % "extra")
I2 = Image(readFile(extraFile), fldxy, Image.EXTRA)
inst = Instrument(self.myinst, I1.sizeinPix)
for algorithm in algorithms:
matlabZFile, tol = self.matlabZFile_Tol[j]; j += 1
algo = Algorithm(algorithm, inst, 1)
algo.runIt(inst, I1, I2, model)
zer = algo.zer4UpNm
matZ = np.loadtxt(os.path.join(self.validationDir, matlabZFile))
aerr = np.abs(matZ - zer)
print("%-31s max(abs(err)) = %8.3g median(abs(err)) = %8.3g [Z_%d], tol=%.0f nm" %
(matlabZFile, np.max(aerr), np.median(aerr), self.Zernike0 + np.argmax(aerr), tol))
if doPlot:
ax = plt.subplot(self.nTest, 1, j)
plt.plot(self.x, matZ, label='Matlab', marker='o', color='r', markersize=10)
plt.plot(self.x, zer, label='Python', marker='.', color='b', markersize=10)
plt.axvline(self.Zernike0 + np.argmax(aerr), ls=':', color='black')
plt.legend(loc="best", shadow=True, title=matlabZFile, fancybox=True)
ax.get_legend().get_title().set_color("red")
plt.xlim(self.x[0] - 0.5, self.x[-1] + 0.5)
assert np.max(aerr) < tol
if doPlot:
plt.show()
def runcwfs(argList):
"""
Calculate the wavefront error in sigle processor.
Arguments:
argList {[list]} -- Inputs of cwfs to calulate the wavefront front.
Returns:
[ndarray] -- z4-zn and flag of calculation.
"""
# Intra-focal image and related field x, y
I1File = argList[0]
I1Field = argList[1]
# Extra-focal image and related field x, y
I2File = argList[2]
I2Field = argList[3]
# Instrument
inst = argList[4]
# Algorithm
algo = argList[5]
# Optical model
model = argList[6]
# Set the images
I1 = Image(readFile(I1File), I1Field, "intra")
I2 = Image(readFile(I2File), I2Field, "extra")
# Run the algorithm to solve the TIE
algo.reset(I1, I2)
algo.runIt(inst, I1, I2, model)
return np.append(algo.zer4UpNm * 1e-3, algo.caustic)
def main():
parser = argparse.ArgumentParser(
description='-----This is cwfs (Curvature Wavefront Sensing) code----')
parser.add_argument('intra', help='intra focal image file name (no path)')
parser.add_argument('extra', help='extra focal image file name (no path)')
parser.add_argument('-dir', dest='imgDir',
help='relative or absolute path for input images')
parser.add_argument('-ixy', dest='intra_xy', nargs=2,
type=float, default=[0, 0],
help='intra focal field (x,y) in deg, default=[0 0]')
parser.add_argument('-exy', dest='extra_xy', nargs=2,
type=float, default=[0, 0],
help='extra focal field (x,y) in deg, default=[0 0]')
parser.add_argument('-i', dest='instruFile', default='lsst',
help='instrument parameter file, default=lsst,\
".param" is appended automatically \
default path is data/lsst/')
parser.add_argument('-a', dest='algoFile', default='fft',
help='algorithm parameter file, default=fft,\
".algo" is appended automatically\
default path is data/algo/')
parser.add_argument('-m', dest='model',
choices=('paraxial', 'onAxis', 'offAxis'),
default='paraxial',
help='Optical model to be used, default=paraxial')
parser.add_argument('-op', dest='outputParam', default='',
help='file name for dumping all parameters, \
default=no output')
parser.add_argument('-oz', dest='outputZerFile', default='',
help='file name for output Zernikes (in unit of nm), \
default=no output')
parser.add_argument('-v', '--version', action='version',
version='%(prog)s 1.0')
parser.add_argument('-d', dest='debugLevel', type=int,
default=0, choices=(-1, 0, 1, 2, 3),
help='debug level, -1=quiet, 0=Zernikes, \
1=operator, 2=expert, 3=everything, default=0')
args = parser.parse_args()
if args.debugLevel >= 1:
print(args)
# load intra and extra focal images
intraFile, extraFile = args.intra, args.extra
if args.imgDir:
intraFile = os.path.join(args.imgDir, intraFile)
extraFile = os.path.join(args.imgDir, extraFile)
I1 = Image(readFile(intraFile), args.intra_xy, Image.INTRA, intraFile)
I2 = Image(readFile(extraFile), args.extra_xy, Image.EXTRA, intraFile)
# load instrument and algorithm parameters
inst = Instrument(args.instruFile, I1.sizeinPix)
algo = Algorithm(args.algoFile, inst, args.debugLevel)
# run it
algo.runIt(inst, I1, I2, args.model)
# output Zernikes 4 and up
if not(args.outputZerFile == '') or args.debugLevel >= 0:
outZer4Up(algo.zer4UpNm, 'nm', args.outputZerFile)
# output parameters
if not(args.outputParam == '') or args.debugLevel >= 1:
outParam(args.outputParam, algo, inst, I1, I2, args.model)