def test_set_nested_symbol(self):
"""set nested symbol in table"""
self.s.set_symbol("_main.foo.bar.baz", value=1)
self.assert_(hasattr(self.s._main, "foo"))
self.assert_(isgroup(getattr(self.s._main, "foo")))
self.assert_(hasattr(self.s._main.foo, "bar"))
self.assert_(isgroup(getattr(self.s._main.foo, "bar")))
self.assert_(hasattr(self.s._main.foo.bar, "baz"))
self.assert_(self.s._main.foo.bar.baz == 1)
def prepare_fit(self):
"""prepare parameters for fit
determine which parameters are actually variables
and which are defined expressions.
"""
if self.__prepared:
return
if not isgroup(self.paramgroup):
return 'param group is not a Larch Group'
self.nfev_calls = 0
self.var_names = []
self.defvars = []
self.vars = []
for name in dir(self.paramgroup):
par = getattr(self.paramgroup, name)
if not isinstance(par, Parameter):
continue
if par.expr is not None:
par.defvar = DefinedVariable(par.expr, _larch=self._larch)
par.vary = False
self.defvars.append(name)
elif par.vary:
self.var_names.append(name)
self.vars.append(par.value)
if par.name is None:
par.name = name
self.nvarys = len(self.vars)
# now evaluate make sure initial values are set
# are used to set values of the defined expressions.
# this also acts as a check of expression syntax.
self.__prepared = True
def minimize(fcn,
group,
args=None,
kws=None,
scale_covar=True,
iter_cb=None,
_larch=None,
**fit_kws):
"""simple minimization function,
finding the values for the params which give the
minimal sum-of-squares of the array return by fcn
"""
if not isgroup(group):
return 'param group is not a Larch Group'
fitter = Minimizer(fcn,
group,
fcn_args=args,
fcn_kws=kws,
iter_cb=iter_cb,
scale_covar=scale_covar,
_larch=_larch,
**fit_kws)
return fitter.leastsq()
def prepare_fit(self):
"""prepare parameters for fit
determine which parameters are actually variables
and which are defined expressions.
"""
if self.__prepared:
return
if not isgroup(self.paramgroup):
return 'param group is not a Larch Group'
self.nfev_calls = 0
self.var_names = []
self.defvars = []
self.vars = []
for name in dir(self.paramgroup):
par = getattr(self.paramgroup, name)
if not isinstance(par, Parameter):
continue
if par.expr is not None:
par.defvar = DefinedVariable(par.expr, _larch=self._larch)
par.vary = False
self.defvars.append(name)
elif par.vary:
self.var_names.append(name)
self.vars.append(par.value)
if par.name is None:
par.name = name
self.nvarys = len(self.vars)
# now evaluate make sure initial values are set
# are used to set values of the defined expressions.
# this also acts as a check of expression syntax.
self.__prepared = True
def minimize(fcn, group, args=None, kws=None,
scale_covar=True, iter_cb=None, _larch=None, **fit_kws):
"""simple minimization function,
finding the values for the params which give the
minimal sum-of-squares of the array return by fcn
"""
if not isgroup(group):
return 'param group is not a Larch Group'
fitter = Minimizer(fcn, group, fcn_args=args, fcn_kws=kws,
iter_cb=iter_cb, scale_covar=scale_covar,
_larch=_larch, **fit_kws)
return fitter.leastsq()
def test_group(self):
'''group builtin'''
self.eval('g = group()')
self.assert_(isgroup(self.li.symtable.g))
