def fit(self):
dummy_data = np.zeros(1)
dummy_times = np.arange(1)
ui.load_arrays(1, dummy_times, dummy_data)
ui.set_method(self.method)
ui.get_method().config.update(sherpa_configs.get(self.method, {}))
ui.load_user_model(CalcModel(self.model), 'xijamod') # sets global xijamod
ui.add_user_pars('xijamod', self.model.parnames)
ui.set_model(1, 'xijamod')
calc_stat = CalcStat(self.model, self.child_pipe)
ui.load_user_stat('xijastat', calc_stat, lambda x: np.ones_like(x))
ui.set_stat(xijastat)
# Set frozen, min, and max attributes for each xijamod parameter
for par in self.model.pars:
xijamod_par = getattr(xijamod, par.full_name)
xijamod_par.val = par.val
xijamod_par.frozen = par.frozen
xijamod_par.min = par.min
xijamod_par.max = par.max
if any(not par.frozen for par in self.model.pars):
try:
ui.fit(1)
calc_stat.message['status'] = 'finished'
logging.debug('Fit finished normally')
except FitTerminated as err:
calc_stat.message['status'] = 'terminated'
logging.debug('Got FitTerminated exception {}'.format(err))
self.child_pipe.send(calc_stat.message)
def fit(self, method='simplex'):
"""Initiate a fit of the model using Sherpa.
:param method: Method to be used to fit the model (e.g. simplex, levmar, or moncar)
"""
dummy_data = np.zeros(1)
dummy_times = np.arange(1)
ui.load_arrays(1, dummy_times, dummy_data)
ui.set_method(method)
ui.get_method().config.update(sherpa_configs.get(method, {}))
ui.load_user_model(CalcModel(self.model, self.fit_logger),
'xijamod') # sets global xijamod
ui.add_user_pars('xijamod', self.model.parnames)
ui.set_model(1, 'xijamod')
calc_stat = CalcStat(self.model, self.fit_logger)
ui.load_user_stat('xijastat', calc_stat, lambda x: np.ones_like(x))
ui.set_stat(xijastat)
# Set frozen, min, and max attributes for each xijamod parameter
for par in self.model.pars:
xijamod_par = getattr(xijamod, par.full_name)
xijamod_par.val = par.val
xijamod_par.frozen = par.frozen
xijamod_par.min = par.min
xijamod_par.max = par.max
ui.fit(1)
self.save_snapshot(fit_stat=calc_stat.min_fit_stat, method=method)
def fit(self):
dummy_data = np.zeros(1)
dummy_times = np.arange(1)
ui.load_arrays(1, dummy_times, dummy_data)
ui.set_method(self.method)
ui.get_method().config.update(sherpa_configs.get(self.method, {}))
ui.load_user_model(CalcModel(self.model), 'xijamod') # sets global xijamod
ui.add_user_pars('xijamod', self.model.parnames)
ui.set_model(1, 'xijamod')
calc_stat = CalcStat(self.model, self.child_pipe, self.maxiter)
ui.load_user_stat('xijastat', calc_stat, lambda x: np.ones_like(x))
ui.set_stat(xijastat)
# Set frozen, min, and max attributes for each xijamod parameter
for par in self.model.pars:
xijamod_par = getattr(xijamod, par.full_name)
xijamod_par.val = par.val
xijamod_par.frozen = par.frozen
xijamod_par.min = par.min
xijamod_par.max = par.max
if any(not par.frozen for par in self.model.pars):
try:
ui.fit(1)
calc_stat.message['status'] = 'finished'
fit_logger.info('Fit finished normally')
except FitTerminated as err:
calc_stat.message['status'] = 'terminated'
fit_logger.warning('Got FitTerminated exception {}'.format(err))
self.child_pipe.send(calc_stat.message)
def fit_model(
model,
comm=None,
method='simplex',
config=None,
nofit=None,
freeze_pars=freeze_pars,
thaw_pars=[],
):
dummy_data = np.zeros(1)
dummy_times = np.arange(1)
ui.load_arrays(1, dummy_times, dummy_data)
ui.set_method(method)
ui.get_method().config.update(config or sherpa_configs.get(method, {}))
ui.load_user_model(CalcModel(model, comm), 'xijamod')
ui.add_user_pars('xijamod', model.parnames)
ui.set_model(1, 'xijamod')
fit_parnames = set()
for parname, parval in zip(model.parnames, model.parvals):
getattr(xijamod, parname).val = parval
fit_parnames.add(parname)
if any([re.match(x + '$', parname) for x in freeze_pars]):
fit_logger.info('Freezing ' + parname)
ui.freeze(getattr(xijamod, parname))
fit_parnames.remove(parname)
if any([re.match(x + '$', parname) for x in thaw_pars]):
fit_logger.info('Thawing ' + parname)
ui.thaw(getattr(xijamod, parname))
fit_parnames.add(parname)
if 'tau' in parname:
getattr(xijamod, parname).min = 0.1
calc_stat = CalcStat(model, comm)
ui.load_user_stat('xijastat', calc_stat, lambda x: np.ones_like(x))
ui.set_stat(xijastat)
if fit_parnames and not nofit:
ui.fit(1)
else:
model.calc()
def fit_model(model,
comm=None,
method='simplex',
config=None,
nofit=None,
freeze_pars=freeze_pars,
thaw_pars=[],
):
dummy_data = np.zeros(1)
dummy_times = np.arange(1)
ui.load_arrays(1, dummy_times, dummy_data)
ui.set_method(method)
ui.get_method().config.update(config or sherpa_configs.get(method, {}))
ui.load_user_model(CalcModel(model, comm), 'xijamod')
ui.add_user_pars('xijamod', model.parnames)
ui.set_model(1, 'xijamod')
fit_parnames = set()
for parname, parval in zip(model.parnames, model.parvals):
getattr(xijamod, parname).val = parval
fit_parnames.add(parname)
if any([re.match(x + '$', parname) for x in freeze_pars]):
fit_logger.info('Freezing ' + parname)
ui.freeze(getattr(xijamod, parname))
fit_parnames.remove(parname)
if any([re.match(x + '$', parname) for x in thaw_pars]):
fit_logger.info('Thawing ' + parname)
ui.thaw(getattr(xijamod, parname))
fit_parnames.add(parname)
if 'tau' in parname:
getattr(xijamod, parname).min = 0.1
calc_stat = CalcStat(model, comm)
ui.load_user_stat('xijastat', calc_stat, lambda x: np.ones_like(x))
ui.set_stat(xijastat)
if fit_parnames and not nofit:
ui.fit(1)
else:
model.calc()
