def fit(self, **kwargs):
if len(self._set_xdata)==<NUM_LIT:0> or len(self._set_ydata)==<NUM_LIT:0>:<EOL><INDENT>return self._error("<STR_LIT>")<EOL><DEDENT>if self._f_raw is None:<EOL><INDENT>return self._error("<STR_LIT>")<EOL><DEDENT>self._massage_data()<EOL>self.set(**kwargs)<EOL>self.results = _opt.leastsq(self._studentized_residuals_concatenated, self._pguess, full_output=<NUM_LIT:1>)<EOL>if self['<STR_LIT>']: self.plot()<EOL>return self<EOL>
This will try to determine fit parameters using scipy.optimize.leastsq
algorithm. This function relies on a previous call of set_data() and 
set_functions().

Notes
-----
results of the fit algorithm are stored in self.results. 
See scipy.optimize.leastsq for more information.

Optional keyword arguments are sent to self.set() prior to
fitting.