def _write_read_noise_dists(outfile, Ntot, Nsys, gains, bias, sysnoise):
output = fits.HDUList()
output.append(fits.PrimaryHDU())
output[0].header['BIASFILE'] = bias
output[0].header['SYSNFILE'] = str(sysnoise)
for amp in Ntot:
sigtot, sigsys = Ntot[amp], Nsys[amp]
nread_col = fits.Column(name="TOTAL_NOISE",
format="E",
unit="e- rms",
array=sigtot)
nsys_col = fits.Column(name="SYSTEM_NOISE",
format="E",
unit="e- rms",
array=sigsys)
output.append(fitsTableFactory((nread_col, nsys_col)))
output[amp].name = "SEGMENT%s" % imutils.channelIds[amp]
output[0].header["GAIN%s" % imutils.channelIds[amp]] = gains[amp]
output[0].header["SIGTOT%s" % imutils.channelIds[amp]] = \
imutils.median(sigtot)
output[0].header["SIGSYS%s" % imutils.channelIds[amp]] = \
imutils.median(sigsys)
fitsWriteto(output, outfile, clobber=True)
def ctesim(infile, pcti=0, scti=0, verbose=False):
input = fits.open(infile)
amps = [
i for i in range(1, len(input))
if input[i].name.upper().startswith('SEGMENT')
]
if not isinstance(pcti, dict):
pcti = {amp: pcti for amp in amps}
if not isinstance(scti, dict):
scti = {amp: scti for amp in amps}
segments = {}
for amp in amps:
if verbose:
print("ctesim: working on amp", amp)
image = afwImage.ImageF(infile, imutils.dm_hdu(amp))
geom = makeAmplifierGeometry(infile)
#
# Temporarily remove readout bias median.
#
bias_med = imutils.median(image.Factory(image, geom.serial_overscan))
image -= bias_med
imarr = image.getArray()
outimage = afwImage.ImageF(image, True)
outarr = outimage.getArray()
if pcti[amp] != 0:
pcte_matrix = cte_matrix(imarr.shape[0], pcti[amp])
for col in range(0, imarr.shape[1]):
outarr[:, col] = np.dot(pcte_matrix, imarr[:, col])
if scti[amp] != 0:
scte_matrix = cte_matrix(imarr.shape[1], scti[amp])
for row in range(0, imarr.shape[0]):
outarr[row, :] = np.dot(scte_matrix, outarr[row, :])
#
# Restore readout bias
#
outarr += bias_med
segments[amp] = outimage
return fitsFile(segments, input)
def run(self,
sensor_id,
bias_files,
gains,
system_noise_files=None,
system_noise=None,
mask_files=(),
use_overscan=False):
all_amps = imutils.allAmps(bias_files[0])
imutils.check_temperatures(bias_files,
self.config.temp_set_point_tol,
setpoint=self.config.temp_set_point,
warn_only=True)
outfiles = []
Ntot = NoiseDistributions(amps=all_amps)
Nsys = NoiseDistributions(amps=all_amps)
if system_noise_files is None:
system_noise_files = [None] * len(bias_files)
for i, bias, sysnoise in zip(range(len(bias_files)), bias_files,
system_noise_files):
outfile = "%s_read_noise_%03i.fits" % (sensor_id, i)
outfile = os.path.join(self.config.output_dir, outfile)
outfiles.append(outfile)
if self.config.verbose:
self.log.info("Processing %s %s -> %s" %
(bias, sysnoise, outfile))
# Determine the nominal imaging region from the bias file.
ccd = MaskedCCD(bias)
if use_overscan:
imaging = ccd.amp_geom.serial_overscan
dx = imaging.getWidth() / 2
dy = self.config.dy
nsamp = self.config.nsamp
else:
imaging = ccd.amp_geom.imaging
dx = self.config.dx
dy = self.config.dy
nsamp = self.config.nsamp
#
# Create a single sub-region sampler so that the same
# sub-regions will be used for both the bias and system
# noise frames.
#
sampler = imutils.SubRegionSampler(dx, dy, nsamp, imaging=imaging)
Ntot_amp = noise_dists(bias, gains, sampler, mask_files=mask_files)
Nsys_amp = noise_dists(sysnoise,
gains,
sampler,
mask_files=mask_files)
_write_read_noise_dists(outfile, Ntot_amp, Nsys_amp, gains, bias,
sysnoise)
#
# Accumulate noise distributions for final median calculation
#
Ntot.append(Ntot_amp)
Nsys.append(Nsys_amp)
results_file = self.config.eotest_results_file
if results_file is None:
results_file = os.path.join(self.config.output_dir,
'%s_eotest_results.fits' % sensor_id)
results = EOTestResults(results_file, namps=len(ccd))
if self.config.verbose:
self.log.info("Amp read noise total noise system noise")
for amp in ccd:
Ntot_med = imutils.median(Ntot[amp])
if system_noise is not None:
Nsys_med = float(system_noise[amp])
else:
Nsys_med = imutils.median(Nsys[amp])
var = Ntot_med**2 - Nsys_med**2
if var >= 0:
Nread = np.sqrt(var)
else:
Nread = -1
line = "%2s %7.4f %7.4f %7.4f" % (
amp, Nread, Ntot_med, Nsys_med)
if self.config.verbose:
self.log.info(line)
results.add_seg_result(amp, 'READ_NOISE', Nread)
results.add_seg_result(amp, 'TOTAL_NOISE', Ntot_med)
results.add_seg_result(amp, 'SYSTEM_NOISE', Nsys_med)
results.write(clobber=True)
seg.add_bias(sigma=4) # CCD read noise
bias_segs.append(seg)
writeFits(bias_segs, bias_file)
#
# Simulate readout system noise.
#
readout_noise_file = 'readout_noise.fits'
noise_segs = []
for amp in gains:
seg = SegmentExposure(exptime=0, gain=gains[amp])
seg.add_bias(level=1e4, sigma=5) # electronic bias and noise
noise_segs.append(seg)
writeFits(noise_segs, readout_noise_file)
#
# Compute the distribution of noise estimates.
#
dx, dy = 100, 100
nsamp = 1000
imaging = imutils.imaging
sampler = imutils.SubRegionSampler(dx, dy, nsamp, imaging)
#mask_files = ('CCD250_DEFECTS_mask.fits',)
mask_files = ()
Ntot = noise_dists(bias_file, gains, sampler, mask_files=mask_files)
Nsys = noise_dists(readout_noise_file, gains, sampler, mask_files)
#
# Read noise distribution.
#
for amp in Ntot:
Nread = np.sqrt(Ntot[amp] * Ntot[amp] - Nsys[amp] * Nsys[amp])
print imutils.median(Nread), imutils.stdev(Nread)