def run(self, rinput):
# Basic processing
self.logger.info('start focus spectrograph')
flow = self.create_flow(rinput.master_bias,
rinput.obresult.configuration.values)
ever = []
focci = []
# FIXME: use tagger here
vphs = []
for frame in rinput.obresult.images:
hdulist = frame.open()
focus_val = hdulist[0].header['focus']
vph_name = hdulist[0].header['VPH']
focci.append(focus_val)
self.logger.info('processing frame %s', frame)
hdulist = flow(hdulist)
self.logger.info('extract fibers')
rssdata = apextract_tracemap(hdulist[0].data, rinput.tracemap)
self.logger.info('find lines and compute FWHM')
lines_rss_fwhm = self.run_on_image(rssdata, rinput.tracemap, vph_name)
ever.append(lines_rss_fwhm)
self.logger.info('pair lines in images')
line_fibers = self.filter_lines(ever)
focus_wavelength = self.generateJSON(ever,
self.get_wlcalib(rinput.wlcalib),
rinput.obresult.images)
self.logger.info('fit FWHM of lines')
final = self.reorder_and_fit(line_fibers, focci)
focus_median = numpy.median(final[:, 2])
self.logger.info('median focus value is %5.2f', focus_median)
self.logger.info('generate focus image')
image = self.generate_image(final)
focus_image_hdu = fits.PrimaryHDU(image)
focus_image = fits.HDUList([focus_image_hdu])
self.logger.info('end focus spectrograph')
return self.create_result(focus_table=final, focus_image=focus_image,
focus_wavelength=focus_wavelength)
def run(self, rinput):
# Basic processing
self.logger.info('twilight fiber flat reduction started')
parameters = self.get_parameters(rinput)
reduced = self.bias_process_common(rinput.obresult, parameters)
_logger.info('extract fibers')
rssdata = apextract_tracemap(reduced[0].data, rinput.tracemap)
# FIXME: we are ignoring here all the possible bad pixels
# and WL distortion when doing the normalization
# rssdata /= rssdata.mean() #Originally uncomment
template_header = reduced[0].header
rsshdu = fits.PrimaryHDU(rssdata, header=template_header)
rss = fits.HDUList([rsshdu])
self.logger.info('extraction completed')
_logger.info('resampling spectra')
final, wcsdata = self.resample_rss_flux(rsshdu.data, self.get_wlcalib(rinput.wlcalib))
# This value was ~0.4% and now is 4e-6 %
# (abs(final.sum()-hdu_t.data.sum())/hdu_t.data.sum()*100)
# Measure values in final
start = 200
end = 2100
_logger.info('doing mean between columns %d-%d', start, end)
colapse = final[:,start:end].mean(axis=1)
normalized = numpy.tile(colapse[:, numpy.newaxis], 4096)
master_t_hdu = fits.PrimaryHDU(normalized, header=template_header)
header_list = self.getHeaderList([reduced, rinput.obresult.images[0].open()])
master_t = fits.HDUList([master_t_hdu]+header_list)
_logger.info('twilight fiber flat reduction ended')
result = self.create_result(reduced_frame=reduced, reduced_rss=rss,
master_twilight_flat=master_t)
return result
