def getGalaxyModel(params):
"""Return the image of a single galaxy optionally drawn with a psf.
Look at :mod:`analysis.models` to figure out which galaxy models and psf
models are supported as well as their corresponding implemented
parameters. You can even add your own galaxies if desired.
Args:
params(dict): Dictionary containing the information of a single
galaxy where the keys is the name(str) of the parameter and the
values are the values of the parametes.
Returns:
A :class:`galsim.GSObject`
"""
galaxy_model = params['galaxy_model']
gal_cls = models.getModelCls(galaxy_model)
gal_model = gal_cls(params)
final = gal_model.gal
if params.get('psf_flux', 0) != 0:
if params.get('psf_flux', 1) != 1:
raise ValueError('I do not think you want a psf of flux not 1')
psf_cls = models.getPsfModelCls(params['psf_model'])
psf_model = psf_cls(params)
final = galsim.Convolve([final, psf_model.psf])
return final
def getOmitFit(id_params, omit):
omit_fit = {}
for gal_id in id_params:
params_omit = omit.get(gal_id,[])
params = id_params[gal_id]
galaxy_model = params['galaxy_model']
cls = models.getModelCls(galaxy_model)
obj = cls(params_omit=params_omit)
omit_fit[gal_id] = obj.omit_fit
return omit_fit
def sortModelParamsNames(self):
"""Return the keys of :attr:`params` in an ordered specified by
the class parameters. And when having more than one galaxy, all the
parameters from one of the galaxies are ordered together.
"""
param_names = []
for gal_id in self.id_params:
galaxy_model = self.id_params[gal_id]['galaxy_model']
cls = models.getModelCls(galaxy_model)
for name in cls.parameters:
for param in self.id_params[gal_id]:
if param not in self.omit_fit.get(gal_id, []):
if param == name:
param_names.append(param + '_' + str(gal_id))
return param_names
