def setpara_bdsm(self, img):
from types import ClassType, TypeType
chain = [
Op_preprocess,
Op_rmsimage(),
Op_threshold(),
Op_islands(),
Op_gausfit(),
Op_gaul2srl(),
Op_make_residimage()
]
opts = img.opts.to_dict()
if img.opts.pi_thresh_isl != None:
opts['thresh_isl'] = img.opts.pi_thresh_isl
if img.opts.pi_thresh_pix != None:
opts['thresh_pix'] = img.opts.pi_thresh_pix
opts['thresh'] = 'hard'
opts['polarisation_do'] = False
opts['filename'] = ''
opts['detection_image'] = ''
ops = []
for op in chain:
if isinstance(op, (ClassType, TypeType)):
ops.append(op())
else:
ops.append(op)
return ops, opts
def setpara_bdsm(self, img):
from types import ClassType, TypeType
chain = [
Op_preprocess,
Op_rmsimage(),
Op_threshold(),
Op_islands(),
Op_gausfit(),
Op_gaul2srl(),
Op_make_residimage()
]
opts = {'thresh': 'hard'}
opts['thresh_pix'] = img.thresh_pix
opts['kappa_clip'] = 3.0
opts['rms_map'] = img.opts.rms_map
opts['mean_map'] = img.opts.mean_map
opts['thresh_isl'] = img.opts.thresh_isl
opts['minpix_isl'] = 6
opts['savefits_rmsim'] = False
opts['savefits_meanim'] = False
opts['savefits_rankim'] = False
opts['savefits_normim'] = False
opts['polarisation_do'] = False
opts['aperture'] = None
opts['group_by_isl'] = img.opts.group_by_isl
opts['quiet'] = img.opts.quiet
opts['ncores'] = img.opts.ncores
opts['flag_smallsrc'] = False
opts['flag_minsnr'] = 0.2
opts['flag_maxsnr'] = 1.2
opts['flag_maxsize_isl'] = 2.5
opts['flag_bordersize'] = 0
opts['flag_maxsize_bm'] = 50.0
opts['flag_minsize_bm'] = 0.2
opts['flag_maxsize_fwhm'] = 0.5
opts['bbs_patches'] = img.opts.bbs_patches
opts['filename'] = ''
opts['output_all'] = img.opts.output_all
opts['verbose_fitting'] = img.opts.verbose_fitting
opts['split_isl'] = False
opts['peak_fit'] = True
opts['peak_maxsize'] = 30.0
opts['detection_image'] = ''
opts['verbose_fitting'] = img.opts.verbose_fitting
ops = []
for op in chain:
if isinstance(op, (ClassType, TypeType)):
ops.append(op())
else:
ops.append(op)
return ops, opts
def setpara_bdsm(self, img, det_file):
from types import ClassType, TypeType
chain=[Op_readimage(), Op_collapse(), Op_preprocess, Op_rmsimage(),
Op_threshold(), Op_islands()]
opts = img.opts.to_dict()
opts['filename'] = det_file
opts['detection_image'] = ''
opts['polarisation_do'] = False
ops = []
for op in chain:
if isinstance(op, (ClassType, TypeType)):
ops.append(op())
else:
ops.append(op)
return ops, opts
from output import Op_outlist
from shapefit import Op_shapelets
from gaul2srl import Op_gaul2srl
from spectralindex import Op_spectralindex
from polarisation import Op_polarisation
from wavelet_atrous import Op_wavelet_atrous
from psf_vary import Op_psf_vary
from cleanup import Op_cleanup
from _version import __version__
import gc
default_chain = [Op_readimage(),
Op_collapse(),
Op_preprocess(),
Op_rmsimage(),
Op_threshold(),
Op_islands(),
Op_gausfit(),
Op_wavelet_atrous(),
Op_shapelets(),
Op_gaul2srl(),
Op_spectralindex(),
Op_polarisation(),
Op_make_residimage(),
Op_psf_vary(),
Op_outlist(),
Op_cleanup()
]
fits_chain = default_chain # for legacy scripts
def execute(chain, opts):