def init_function_pars():
global FUNCTION_PAR_NAMES
global FUNCTION_NORM_PARS
global FUNCTION_DEFAULT_PARS
FUNCTION_PAR_NAMES = {}
FUNCTION_NORM_PARS = {}
funcFactory = pyLike.SourceFactory_funcFactory()
names = pyLike.StringVector()
funcFactory.getFunctionNames(names)
for fname in names:
pars = FUNCTION_DEFAULT_PARS.setdefault(fname, {})
par_names = FUNCTION_PAR_NAMES.setdefault(fname, [])
if 'EblAtten' in fname and fname[len('EblAtten::'
):] in FUNCTION_DEFAULT_PARS:
pars.update(FUNCTION_DEFAULT_PARS[fname[len('EblAtten::'):]])
fn = funcFactory.create(fname)
try:
FUNCTION_NORM_PARS[fname] = fn.normPar().getName()
except Exception:
FUNCTION_NORM_PARS[fname] = None
params = pyLike.ParameterVector()
fn.getParams(params)
for i, p in enumerate(params):
pname = p.getName()
par_names += [pname]
if pname == 'Scale':
pars.setdefault(pname, DEFAULT_SCALE_DICT)
elif pname == 'Prefactor':
pars.setdefault(pname, DEFAULT_NORM_DICT)
else:
pars.setdefault(pname, {})
bounds = p.getBounds()
par_dict = dict(name=pname,
value=p.getValue(),
min=bounds[0],
max=bounds[1],
scale=1.0,
free=False)
par_dict.update(copy.deepcopy(pars[pname]))
par_dict['name'] = pname
pars[pname] = par_dict
def constrain_params(self, srcNames, cov_scale=1.0):
for name in srcNames:
free_pars = pyLike.ParameterVector()
self.srcs[name].funcs["Spectrum"].getFreeParams(free_pars)
for i in range(free_pars.size()):
par = free_pars[i]
err = par.error()
val = par.getValue()
if par.error() == 0.0 or not par.isFree():
continue
self.addGaussianPrior(name, par.getName(), val, err * cov_scale)
def minosError(self, component, srcname, parname, level=1):
freeParams = pyLike.ParameterVector()
self.composite.getFreeParams(freeParams)
saved_values = [par.getValue() for par in freeParams]
indx = self._compositeIndex(component, srcname, parname)
if indx == -1:
raise RuntimeError("Invalid parameter specification.")
try:
errors = self.optObject.Minos(indx, level)
self.composite.setFreeParamValues(saved_values)
return errors
except RuntimeError, message:
print "Minos error encountered for parameter %i." % indx
self.composite.setFreeParamValues(saved_values)
def gtlike_spectrum_to_dict(spectrum):
""" Convert a pyLikelihood object to a python dictionary which can
be easily saved to a file."""
parameters = pyLike.ParameterVector()
spectrum.getParams(parameters)
d = dict(spectrum_type=spectrum.genericName())
for p in parameters:
pname = p.getName()
pval = p.getTrueValue()
perr = abs(p.error() * p.getScale()) if p.isFree() else np.nan
d[pname] = np.array([pval, perr])
if d['spectrum_type'] == 'FileFunction':
ff = pyLike.FileFunction_cast(spectrum)
d['file'] = ff.filename()
return d
def __init__(self, like):
self.like = like
self.sources = dict()
all_names = like.sourceNames()
self.covariance = like.covariance
for name in all_names:
spectrum = like[name].src.spectrum()
parameters = pyLikelihood.ParameterVector()
spectrum.getParams(parameters)
self.sources[name] = d = dict(parameters=dict(), spectrum=spectrum)
for p in parameters:
d['parameters'][p.getName()] = _Parameter(p)
def gtlike_spectrum_to_vectors(spectrum):
""" Convert a pyLikelihood object to a python dictionary which can
be easily saved to a file."""
o = {'param_names': np.zeros(10, dtype='S32'),
'param_values': np.empty(10, dtype=float) * np.nan,
'param_errors': np.empty(10, dtype=float) * np.nan,
}
parameters = pyLike.ParameterVector()
spectrum.getParams(parameters)
for i, p in enumerate(parameters):
o['param_names'][i] = p.getName()
o['param_values'][i] = p.getTrueValue()
perr = abs(p.error() * p.getScale()) if p.isFree() else np.nan
o['param_errors'][i] = perr
return o
def minosError(self, component_name, srcname, parname, level=1):
freeParams = pyLike.ParameterVector()
self.composite.getFreeParams(freeParams)
saved_values = [par.getValue() for par in freeParams]
indx = self._compositeIndex(component_name, srcname, parname)
if indx == -1:
raise RuntimeError("Invalid parameter specification")
try:
errors = self.optObject.Minos(indx, level)
self.composite.setFreeParamValues(saved_values)
return errors
except RuntimeError, message:
print "Minos error encountered for parameter %i." % par_index
print "Attempting to reset free parameters."
for tiedName, component in zip(self.srcNames, self.components):
if component_name == tiedName:
component.thaw(component.par_index(srcname, parname))
break
self.composite.setFreeParamValues(saved_values)
raise RuntimeError(message)
