def applyCTICorrection(self):
"""
Applies a CTI correction in electrons using CDM03 CTI model.
Converts the data to electrons using the gain value given in self.values.
The number of forward reads is defined by self.values['order'] parameter.
Bristow & Alexov (2003) algorithm further developed for HST data
processing by Massey, Rhodes et al.
There is probably an excess of .copy() calls here, but I had some problems
when calling the Fortran code so I added them for now.
"""
self.instrument['trapfile'] = self.instrument['ctifile']
if self.instrument['order'] < 1:
self.log.warning(
'Order < 1, no CTI correction (forward modeling) applied!')
return
#multiply with the gain
self.log.info(
'Multiplying the data with the gain factor = %.3f to convert electrons'
% self.instrument['gain'])
self.data *= self.instrument['gain']
#make a copy, not necessary...?
out = self.data.copy()
if out.shape[0] < 2500:
#this must be quadrant
self.log.info(
'Applying %i forward reads to a quadrant to perform a CTI correction'
% self.instrument['order'])
for x in range(self.instrument['order']):
rd = CTI.CDM03(self.instrument, [], self.log)
damaged = rd.applyRadiationDamage(
out.copy(), iquadrant=self.hdu['QUADRANT'])
out += self.data.copy() - damaged
self.log.info('Forward read %i performed' % (x + 1))
del (rd)
else:
self.log.info(
'Applying %i forward reads to the full CCD to perform a CTI correction'
% self.instrument['order'])
for x in range(self.instrument['order']):
rd = CTI.CDM03(self.instrument, out.copy(), self.log)
damaged = rd.radiateFullCCD2()
out += self.data.copy() - damaged
self.log.info('Forward read %i performed' % (x + 1))
del (rd)
#divide with the gain
self.log.info(
'Dividing the data with the gain factor = %.3f to convert ADUs' %
self.instrument['gain'])
self.data = out / self.instrument['gain']
def currentValues(parallel='cdm_euclid_parallel.dat',
serial='cdm_euclid_serial.dat',
chargeInjection=43500.):
#set up the charge injection chargeInjection positions
lines = dict(xstart1=577,
xstop1=588,
ystart1=1064,
ystop1=1075,
xstart2=4096 - 588,
xstop2=4096 - 577,
ystart2=4132 - 1075,
ystop2=4132 - 1064)
#create two CCD files
CCDhor = np.zeros((4132, 4096), dtype=np.float32)
CCDver = np.zeros((4132, 4096), dtype=np.float32)
#add horizontal charge injection lines
CCDhor[lines['ystart1']:lines['ystop1'], :] = chargeInjection
CCDhor[lines['ystart2']:lines['ystop2'], :] = chargeInjection
#add vertical charge injection lines
CCDver[:, lines['xstart1']:lines['xstop1']] = chargeInjection
CCDver[:, lines['xstart2']:lines['xstop2']] = chargeInjection
#write output files
writeFITSfile(CCDhor,
'ChargeInjectionsHorizontal.fits',
unsigned16bit=False)
writeFITSfile(CCDver, 'ChargeInjectionsVertical.fits', unsigned16bit=False)
#radiate the CCDs
params = MSSLCDM03params()
params.update(
dict(parallelTrapfile=parallel, serialTrapfile=serial, rdose=1.6e10))
CCDCTIhor = CTI.CDM03bidir(params, CCDhor).radiateFullCCD()
CCDCTIver = CTI.CDM03bidir(params, CCDver).radiateFullCCD()
#write output files
writeFITSfile(CCDCTIhor,
'ChargeInjectionsHorizontalCTI.fits',
unsigned16bit=False)
writeFITSfile(CCDCTIver,
'ChargeInjectionsVerticalCTI.fits',
unsigned16bit=False)
#plot profiles
plotProfiles(CCDCTIver, CCDCTIhor, lines)
def generateSimpleTestData(lines, level=(100, 1000, 10000)):
"""
"""
params = MSSLCDM03params()
params.update(
dict(
parallelTrapfile=
'/Users/sammy/EUCLID/CTItesting/Reconciliation/singletrap/cdm_test_parallel.dat',
serialTrapfile=
'/Users/sammy/EUCLID/CTItesting/Reconciliation/singletrap/cdm_test_serial.dat',
rdose=1.6e10,
serial=0,
parallel=1,
quadrant=0))
for i, l in enumerate(level):
print i, l
#create a quadrant
CCD = np.zeros((2066, 2048), dtype=np.float64)
#add horizontal charge injection lines
CCD[lines['ystart1']:lines['ystop1'], :] = l
writeFITSfile(CCD.copy(),
'ChargeInjectionParallelSingle%i.fits' % i,
unsigned16bit=False)
#radiate CTI to plot initial set trails
c = CTI.CDM03bidir(params, [])
CCDCTIhor = c.applyRadiationDamage(CCD.copy().transpose()).transpose()
writeFITSfile(CCDCTIhor, 'CTISingle%i.fits' % i, unsigned16bit=False)
def addCTI(file, loc=1900, bcgr=72.2, thibautCDM03=False, beta=True, serial=1, parallel=1):
"""
Add CTI trails to a FITS file or input data.
"""
#trap parameters: parallel
if thibautCDM03:
f1 = '/Users/sammy/EUCLID/vissim-python/data/cdm_thibaut_parallel.dat'
f2 = '/Users/sammy/EUCLID/vissim-python/data/cdm_thibaut_serial.dat'
params = ThibautsCDM03params()
params.update(dict(parallelTrapfile=f1, serialTrapfile=f2, rdose=8.0e9, serial=serial, parallel=parallel))
else:
f1 = '/Users/sammy/EUCLID/vissim-python/data/cdm_euclid_parallel.dat'
f2 = '/Users/sammy/EUCLID/vissim-python/data/cdm_euclid_serial.dat'
params = MSSLCDM03params()
params.update(dict(parallelTrapfile=f1, serialTrapfile=f2, rdose=8.0e9, serial=serial, parallel=parallel))
if beta:
params.update(dict(beta_p=0.6, beta_s=0.6))
print f1, f2
#load data
if type(file) is str:
nocti = pf.getdata(file)
else:
nocti = file.copy()
#place it on canvas
tmp = np.zeros((2066, 2048))
ysize, xsize = nocti.shape
ysize /= 2
xsize /= 2
tmp[loc-ysize:loc+ysize, loc-xsize:loc+xsize] = nocti.copy()
#add background
tmp += bcgr
#run CDM03
c = CTI.CDM03bidir(params, [])
tmp = c.applyRadiationDamage(tmp)
#remove background and make a cutout
CTIdata = tmp[loc-ysize:loc+ysize, loc-xsize:loc+xsize]
CTIdata -= bcgr
CTIdata[CTIdata < 0.] = 0.
return CTIdata
def useThibautsData(log, output, bcgr=72.2, sigma=0.75, iterations=4, loc=1900, galaxies=1000,
datadir='/Users/smn2/EUCLID/CTItesting/uniform/',
thibautCDM03=False, beta=False, serial=1, parallel=1):
"""
Test the impact of CTI in case of no noise and no correction.
:param log: logger instance
:param bcgr: background in electrons for the CTI modelling
:param sigma: size of the weighting function for the quadrupole moment
:param iterations: number of iterations in the quadrupole moments estimation
:param loc: location to which the galaxy will be placed [default=1900]
:param galaxies: number of galaxies to use (< 10000)
:param datadir: directory pointing to the galaxy images
:return:
"""
files = g.glob(datadir + '*.fits')
#pick randomly
files = np.random.choice(files, galaxies, replace=False)
#trap parameters: parallel
if thibautCDM03:
f1 = '/Users/smn2/EUCLID/vissim-python/data/cdm_thibaut_parallel.dat'
f2 = '/Users/smn2/EUCLID/vissim-python/data/cdm_thibaut_serial.dat'
params = ThibautsCDM03params()
params.update(dict(parallelTrapfile=f1, serialTrapfile=f2, rdose=8.0e9, serial=serial, parallel=parallel))
else:
f1 = '/Users/smn2/EUCLID/vissim-python/data/cdm_euclid_parallel.dat'
f2 = '/Users/smn2/EUCLID/vissim-python/data/cdm_euclid_serial.dat'
params = MSSLCDM03params()
params.update(dict(parallelTrapfile=f1, serialTrapfile=f2, rdose=8.0e9, serial=serial, parallel=parallel))
if beta:
params.update(dict(beta_p=0.6, beta_s=0.6))
print f1, f2
#store shapes
eclean = []
e1clean = []
e2clean = []
R2clean = []
xclean = []
yclean = []
eCTI = []
e1CTI = []
e2CTI = []
R2CTI = []
xCTI = []
yCTI = []
eCTIfixed = []
e1CTIfixed = []
e2CTIfixed = []
R2CTIfixed = []
xCTIfixed = []
yCTIfixed = []
fh = open(output.replace('.pk', '.csv'), 'w')
fh.write('#files: %s and %s\n' % (f1, f2))
for key in params:
print key, params[key]
fh.write('# %s = %s\n' % (key, str(params[key])))
fh.write('#file, delta_e, delta_e1, delta_e2, delta_R2, delta_x, delta_y\n')
for f in files:
print 'Processing: ', f
#load data
nocti = pf.getdata(f)
#scale to SNR about 10 (average galaxy, a single exposure)
nocti /= np.sum(nocti)
nocti *= 1500.
#place it on canvas
tmp = np.zeros((2066, 2048))
ysize, xsize = nocti.shape
ysize /= 2
xsize /= 2
tmp[loc-ysize:loc+ysize, loc-xsize:loc+xsize] = nocti.copy()
#add background
tmp += bcgr
#run CDM03
c = CTI.CDM03bidir(params, [])
tmp = c.applyRadiationDamage(tmp.copy().transpose()).transpose()
#remove background and make a cutout
CTIdata = tmp[loc-ysize:loc+ysize, loc-xsize:loc+xsize]
CTIdata -= bcgr
CTIdata[CTIdata < 0.] = 0.
#write files
#fileIO.writeFITS(nocti, f.replace('.fits', 'noCTI.fits'), int=False)
#fileIO.writeFITS(CTI, f.replace('.fits', 'CTI.fits'), int=False)
#reset settings
settings = dict(sigma=sigma, iterations=iterations)
#calculate shapes
sh = shape.shapeMeasurement(nocti.copy(), log, **settings)
results = sh.measureRefinedEllipticity()
eclean.append(results['ellipticity'])
e1clean.append(results['e1'])
e2clean.append(results['e2'])
R2clean.append(results['R2'])
xclean.append(results['centreX'])
yclean.append(results['centreY'])
#CTI, fitted centroid
sh = shape.shapeMeasurement(CTIdata.copy(), log, **settings)
results2 = sh.measureRefinedEllipticity()
eCTI.append(results2['ellipticity'])
e1CTI.append(results2['e1'])
e2CTI.append(results2['e2'])
R2CTI.append(results2['R2'])
xCTI.append(results2['centreX'])
yCTI.append(results2['centreY'])
#fixed centroid
settings['fixedPosition'] = True
settings['fixedX'] = results['centreX']
settings['fixedY'] = results['centreY']
settings['iterations'] = 1
sh = shape.shapeMeasurement(CTIdata.copy(), log, **settings)
results3 = sh.measureRefinedEllipticity()
eCTIfixed.append(results3['ellipticity'])
e1CTIfixed.append(results3['e1'])
e2CTIfixed.append(results3['e2'])
R2CTIfixed.append(results3['R2'])
xCTIfixed.append(results3['centreX'])
yCTIfixed.append(results3['centreY'])
text = '%s,%e,%e,%e,%e,%e,%e\n' % (f, results['ellipticity'] - results2['ellipticity'],
results['e1'] - results2['e1'], results['e2'] - results2['e2'],
results['R2'] - results2['R2'],
results['centreX'] - results2['centreX'],
results['centreY'] - results2['centreY'])
fh.write(text)
print text
fh.close()
results = {'eclean': np.asarray(eclean),
'e1clean': np.asarray(e1clean),
'e2clean': np.asarray(e2clean),
'R2clean': np.asarray(R2clean),
'xclean': np.asarray(xclean),
'yclean': np.asarray(yclean),
'eCTI': np.asarray(eCTI),
'e1CTI': np.asarray(e1CTI),
'e2CTI': np.asarray(e2CTI),
'R2CTI': np.asarray(R2CTI),
'xCTI': np.asarray(xCTI),
'yCTI': np.asarray(yCTI),
'eCTIfixed': np.asarray(eCTIfixed),
'e1CTIfixed': np.asarray(e1CTIfixed),
'e2CTIfixed': np.asarray(e2CTIfixed),
'R2CTIfixed': np.asarray(R2CTIfixed),
'xCTIfixed': np.asarray(xCTIfixed),
'yCTIfixed': np.asarray(yCTIfixed)}
#save to a file
fileIO.cPickleDumpDictionary(results, output)
return results
def testCTIcorrectionNonoise(log, files, output, sigma=0.75, iterations=4):
"""
Calculates PSF properties such as ellipticity and size from data w/ and w/o CTI.
:param log: python logger instance
:type log: instance
:param files: a list of files to be processed
:type files: list
:param sigma: size of the Gaussian weighting function
:type sigma: float
:param iterations: the number of iterations for the moment based shape estimator
:type iterations: int
:return: ellipticity and size
:rtype: dict
"""
eclean = []
e1clean = []
e2clean = []
R2clean = []
xclean = []
yclean = []
eCTI = []
e1CTI = []
e2CTI = []
R2CTI = []
xCTI = []
yCTI = []
eCTIfixed = []
e1CTIfixed = []
e2CTIfixed = []
R2CTIfixed = []
xCTIfixed = []
yCTIfixed = []
fh = open(output.replace('pk', 'csv'), 'w')
fh.write('#file, delta_e, delta_e1, delta_e2, delta_R2, delta_x, delta_y\n')
for f in files:
print 'Processing: ', f
#reset settings
settings = dict(sigma=sigma, iterations=iterations)
#load no cti data
nocti = pf.getdata(f.replace('CUT', 'CUTnoctinonoise'))
#load CTI data
CTI = pf.getdata(f)
sh = shape.shapeMeasurement(nocti, log, **settings)
results = sh.measureRefinedEllipticity()
eclean.append(results['ellipticity'])
e1clean.append(results['e1'])
e2clean.append(results['e2'])
R2clean.append(results['R2'])
xclean.append(results['centreX'])
yclean.append(results['centreY'])
#CTI, fitted centroid
sh = shape.shapeMeasurement(CTI.copy(), log, **settings)
results2 = sh.measureRefinedEllipticity()
eCTI.append(results2['ellipticity'])
e1CTI.append(results2['e1'])
e2CTI.append(results2['e2'])
R2CTI.append(results2['R2'])
xCTI.append(results2['centreX'])
yCTI.append(results2['centreY'])
#fixed centroid
settings['fixedPosition'] = True
settings['fixedX'] = results['centreX']
settings['fixedY'] = results['centreY']
settings['iterations'] = 1
sh = shape.shapeMeasurement(CTI.copy(), log, **settings)
results3 = sh.measureRefinedEllipticity()
eCTIfixed.append(results3['ellipticity'])
e1CTIfixed.append(results3['e1'])
e2CTIfixed.append(results3['e2'])
R2CTIfixed.append(results3['R2'])
xCTIfixed.append(results3['centreX'])
yCTIfixed.append(results3['centreY'])
text = '%s,%e,%e,%e,%e,%e,%e\n' % (f, results['ellipticity'] - results2['ellipticity'],
results['e1'] - results2['e1'], results['e2'] - results2['e2'], results['R2'] - results2['R2'],
results['centreX'] - results2['centreX'], results['centreY'] - results2['centreY'])
fh.write(text)
print text
fh.close()
results = {'eclean' : np.asarray(eclean),
'e1clean' : np.asarray(e1clean),
'e2clean' : np.asarray(e2clean),
'R2clean' : np.asarray(R2clean),
'xclean' : np.asarray(xclean),
'yclean' : np.asarray(yclean),
'eCTI' : np.asarray(eCTI),
'e1CTI' : np.asarray(e1CTI),
'e2CTI' : np.asarray(e2CTI),
'R2CTI' : np.asarray(R2CTI),
'xCTI' : np.asarray(xCTI),
'yCTI' : np.asarray(yCTI),
'eCTIfixed': np.asarray(eCTIfixed),
'e1CTIfixed': np.asarray(e1CTIfixed),
'e2CTIfixed': np.asarray(e2CTIfixed),
'R2CTIfixed': np.asarray(R2CTIfixed),
'xCTIfixed': np.asarray(xCTIfixed),
'yCTIfixed': np.asarray(yCTIfixed)}
#save to a file
fileIO.cPickleDumpDictionary(results, output)
return results
def deriveTrails(parallel,
serial,
chargeInjection=44500.,
lines=dict(ystart1=1064, ystop1=1075, xstart1=577,
xstop1=588),
thibaut=False,
beta=False):
"""
Derive CTI trails in both parallel and serial direction separately given the input data files
:param parallel: name of the parallel CTI file
:param serial: name of the serial CTI file
:param chargeInjection: number of electrons to inject
:param lines: positions of the charge injectino lines
:param thibaut: whether or not to scale the capture cross sections from m**2 to cm**2
:return:
"""
#create a quadrant
CCD = np.zeros((2066, 2048), dtype=np.float64)
#add horizontal charge injection lines
CCD[lines['ystart1']:lines['ystop1'], :] = chargeInjection
if thibaut:
writeFITSfile(CCD.copy(), 'ChargeHT.fits', unsigned16bit=False)
else:
writeFITSfile(CCD.copy(), 'ChargeH.fits', unsigned16bit=False)
#radiate CTI to plot initial set trails
if thibaut:
params = ThibautsCDM03params()
params.update(
dict(parallelTrapfile=parallel,
serialTrapfile=serial,
rdose=8.0e9,
serial=0,
parallel=1,
quadrant=0))
c = CTI.CDM03bidir(params, [])
CCDCTIhor = c.applyRadiationDamage(CCD.copy().transpose()).transpose()
writeFITSfile(CCDCTIhor, 'CTIHT.fits', unsigned16bit=False)
else:
if beta:
params = MSSLCDM03params()
params.update(
dict(parallelTrapfile=parallel,
serialTrapfile=serial,
rdose=1.6e10,
beta_s=0.6,
beta_p=0.6,
serial=0,
parallel=1,
quadrant=0))
c = CTI.CDM03bidir(params, [])
CCDCTIhor = c.applyRadiationDamage(
CCD.copy().transpose()).transpose()
writeFITSfile(CCDCTIhor, 'CTIH2.fits', unsigned16bit=False)
else:
params = MSSLCDM03params()
params.update(
dict(parallelTrapfile=parallel,
serialTrapfile=serial,
rdose=1.6e10,
serial=0,
parallel=1,
quadrant=0))
c = CTI.CDM03bidir(params, [])
CCDCTIhor = c.applyRadiationDamage(
CCD.copy().transpose()).transpose()
writeFITSfile(CCDCTIhor, 'CTIH.fits', unsigned16bit=False)
profileParallel = np.average(CCDCTIhor, axis=1)
#now serial
CCD = np.zeros((2066, 2048), dtype=np.float64)
#add horizontal charge injection lines
CCD[:, lines['xstart1']:lines['xstop1']] = chargeInjection
if thibaut:
writeFITSfile(CCD, 'ChargeVT.fits', unsigned16bit=False)
else:
writeFITSfile(CCD, 'ChargeV.fits', unsigned16bit=False)
#radiate CTI to plot initial set trails
if thibaut:
params = ThibautsCDM03params()
params.update(
dict(parallelTrapfile=parallel,
serialTrapfile=serial,
rdose=8.0e9,
parallel=0,
serial=1,
quadrant=0))
c = CTI.CDM03bidir(params, [])
CCDCTI = c.applyRadiationDamage(CCD.copy().transpose()).transpose()
writeFITSfile(CCDCTI, 'CTIVT.fits', unsigned16bit=False)
else:
if beta:
params = MSSLCDM03params()
params.update(
dict(parallelTrapfile=parallel,
serialTrapfile=serial,
rdose=1.6e10,
beta_p=0.6,
beta_s=0.6,
parallel=0,
serial=1,
quadrant=0))
c = CTI.CDM03bidir(params, [])
CCDCTI = c.applyRadiationDamage(CCD.copy().transpose()).transpose()
writeFITSfile(CCDCTI, 'CTIV2.fits', unsigned16bit=False)
else:
params = MSSLCDM03params()
params.update(
dict(parallelTrapfile=parallel,
serialTrapfile=serial,
rdose=1.6e10,
parallel=0,
serial=1,
quadrant=0))
c = CTI.CDM03bidir(params, [])
CCDCTI = c.applyRadiationDamage(CCD.copy().transpose()).transpose()
writeFITSfile(CCDCTI, 'CTIV.fits', unsigned16bit=False)
#plot trails
profileSerial = np.average(CCDCTI, axis=0)
return profileParallel, profileSerial
def testPythonCDM03(parallel='cdm_euclid_parallel.dat',
serial='cdm_euclid_serial.dat',
chargeInjection=44500.,
lines=dict(ystart1=1064,
ystop1=1075,
xstart1=577,
xstop1=588)):
from CTI import CTI
trapdata = np.loadtxt(parallel)
nt_p = trapdata[:, 0]
sigma_p = trapdata[:, 1]
taur_p = trapdata[:, 2]
trapdata = np.loadtxt(serial)
nt_s = trapdata[:, 0]
sigma_s = trapdata[:, 1]
taur_s = trapdata[:, 2]
#create a quadrant
CCD = np.zeros((2066, 2048), dtype=np.float32)
#add horizontal charge injection lines
CCD[lines['ystart1']:lines['ystop1'], :] = chargeInjection
writeFITSfile(CCD.copy(), 'ChargeHtest.fits', unsigned16bit=False)
#radiate CTI to plot initial set trails
c = CTI.CDM03Python({}, [])
CCDCTIhor = c.applyRadiationDamage(CCD.copy(),
nt_p,
sigma_p,
taur_p,
nt_s,
sigma_s,
taur_s,
rdose=1.6e10)
writeFITSfile(CCDCTIhor, 'CTIHtest.fits', unsigned16bit=False)
parallel = np.average(CCDCTIhor, axis=1)
#now serial
CCD = np.zeros((2066, 2048), dtype=np.float32)
#add horizontal charge injection lines
CCD[:, lines['xstart1']:lines['xstop1']] = chargeInjection
writeFITSfile(CCD, 'ChargeVtest.fits', unsigned16bit=False)
#radiate CTI to plot initial set trails
c = CTI.CDM03Python({}, [])
CCDCTI = c.applyRadiationDamage(CCD.copy(),
nt_p,
sigma_p,
taur_p,
nt_s,
sigma_s,
taur_s,
rdose=1.6e10)
writeFITSfile(CCDCTI, 'CTIVtest.fits', unsigned16bit=False)
#plot trails
serial = np.average(CCDCTI, axis=0)
#get parallel measurements
indp, parallelValues = parallelMeasurements(returnScale=True)
inds, serialValues = serialMeasurements(returnScale=True)
#mask out irrelevant values
mskp = indp > -5
msks = inds > -5
indp = indp[mskp][:100]
inds = inds[msks][:250]
parallelValues = parallelValues[mskp][:100]
serialValues = serialValues[msks][:250]
#rescale
indp += 185
inds += 10
#cutout right region
shift = 5
profileParallelM = parallel[lines['ystop1'] - shift:lines['ystop1'] -
shift + len(indp)]
profileSerialM = serial[lines['xstop1'] - shift:lines['xstop1'] - shift +
len(inds)]
#set up the charge injection chargeInjection positions
fig = plt.figure()
fig.suptitle(
'CCD204 05325-03-02 Hopkinson EPER at 200kHz, with 20.48ms, 8e9 at 10MeV'
)
fig.subplots_adjust(bottom=0.1, right=0.8, top=0.9)
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.set_title('Parallel CTI')
ax2.set_title('Serial CTI')
ax1.semilogy(indp, parallelValues, 'bo', ms=3, label='152.55K')
ax1.semilogy(indp, profileParallelM, 'y-', label='MSSL')
ax2.semilogy(inds, serialValues, 'bs', ms=3, label='152.5K')
ax2.semilogy(inds, profileSerialM, 'y-', label='MSSL')
ax1.set_ylim(1., 60000)
ax2.set_ylim(1., 60000)
ax1.set_xlim(180, 250)
ax2.set_xlim(0, 220)
ax2.set_xlabel('Pixels')
ax1.set_ylabel('Photoelectrons')
ax2.set_ylabel('Photoelectrons')
ax1.legend(fancybox=True, shadow=True, numpoints=1)
ax2.legend(fancybox=True, shadow=True, numpoints=1)
plt.savefig('PythonCDM03.pdf')
plt.close()
def addCTI(file,
locx=200,
locy=200,
bcgr=72.2,
thibautCDM03=False,
test=False,
beta=True,
serial=1,
parallel=0,
quadrant=0,
single=True):
"""
Add CTI trails to a FITS file or input data.
"""
#trap parameters: parallel2
if thibautCDM03:
f1 = '/Users/sammy/EUCLID/vissim-python/data/cdm_thibaut_parallel.dat'
f2 = '/Users/sammy/EUCLID/vissim-python/data/cdm_thibaut_serial.dat'
params = ThibautsCDM03params()
params.update(
dict(parallelTrapfile=f1,
serialTrapfile=f2,
rdose=8.e9,
serial=serial,
parallel=parallel))
elif test:
if single:
f1 = '/Users/sammy/EUCLID/CTItesting/Reconciliation/singletrap/cdm_test_parallel.dat'
f2 = '/Users/sammy/EUCLID/CTItesting/Reconciliation/singletrap/cdm_test_serial.dat'
else:
f1 = '/Users/sammy/EUCLID/CTItesting/Reconciliation/multitrap/cdm_test_parallel.dat'
f2 = '/Users/sammy/EUCLID/CTItesting/Reconciliation/multitrap/cdm_test_serial.dat'
params = TestCDM03params()
params.update(
dict(parallelTrapfile=f1,
serialTrapfile=f2,
rdose=8e9,
serial=serial,
parallel=parallel))
else:
f1 = '/Users/sammy/EUCLID/vissim-python/data/cdm_euclid_parallel.dat'
f2 = '/Users/sammy/EUCLID/vissim-python/data/cdm_euclid_serial.dat'
params = MSSLCDM03params()
params.update(
dict(parallelTrapfile=f1,
serialTrapfile=f2,
rdose=8.e9,
serial=serial,
parallel=parallel))
if beta:
params.update(dict(beta_p=0.6, beta_s=0.6))
#load data
if type(file) is str:
nocti = pf.getdata(file)
else:
nocti = file.copy()
#place it on canvas
if locx is not None:
tmp = np.zeros((2066, 2048))
ysize, xsize = nocti.shape
ysize /= 2
xsize /= 2
tmp[locy - ysize:locy + ysize,
locx - xsize:locx + xsize] = nocti.copy()
else:
tmp = nocti
#add background
if bcgr is not None:
tmp += bcgr
#run CDM03
c = CTI.CDM03bidir(params, [])
tmp = c.applyRadiationDamage(tmp.T, iquadrant=quadrant).T
#make a cutout
if locx is not None:
CTIdata = tmp[locy - ysize:locy + ysize, locx - xsize:locx + xsize]
else:
CTIdata = tmp
#remove background
if bcgr is not None:
CTIdata -= bcgr
CTIdata[CTIdata < 0.] = 0.
return CTIdata