def _least_square_regress(self, scatter, r, fit):
fitfunc, errfunc = fit
if r is None or not isinstance(r, LeastSquaresRegressor):
r = LeastSquaresRegressor()
self._set_regressor(scatter, r)
r.trait_set(fitfunc=fitfunc,
errfunc=errfunc,
trait_change_notify=False)
r.calculate()
self._set_excluded(scatter, r)
return r
def _least_square_regress(self, scatter, r, fit):
fitfunc, errfunc = fit
if r is None or not isinstance(r, LeastSquaresRegressor):
r = LeastSquaresRegressor()
self._set_regressor(scatter, r)
r.trait_set(fitfunc=fitfunc,
errfunc=errfunc,
trait_change_notify=False)
r.calculate()
self._set_excluded(scatter, r)
return r
def _least_square_regress(self, r, x, y, ox, oy, index, fit, fod,
apply_filter):
fitfunc, errfunc = fit
if r is None or not isinstance(r, LeastSquaresRegressor):
r = LeastSquaresRegressor()
r.trait_set(xs=x, ys=y, fitfunc=fitfunc, errfunc=errfunc)
if apply_filter:
r = self._apply_outlier_filter(r, ox, oy, index, fod)
return r
def _least_square_regress(self, scatter, r, fit):
from pychron.core.regression.least_squares_regressor import LeastSquaresRegressor
func, initial_guess = fit
if r is None or not isinstance(r, LeastSquaresRegressor):
r = LeastSquaresRegressor()
self._set_regressor(scatter, r)
r.trait_set(fitfunc=func,
initial_guess=initial_guess,
trait_change_notify=False)
r.calculate()
self._set_excluded(scatter, r)
return r
def _least_square_regress(self, scatter, r, fit):
from pychron.core.regression.least_squares_regressor import LeastSquaresRegressor
func, initial_guess = fit
if r is None or not isinstance(r, LeastSquaresRegressor):
r = LeastSquaresRegressor()
self._set_regressor(scatter, r)
r.trait_set(fitfunc=func,
initial_guess=initial_guess,
trait_change_notify=False)
r.calculate()
self._set_excluded(scatter, r)
return r
def _least_square_regress(self, r, x, y, ox, oy, index,
fit, fod, apply_filter):
fitfunc, errfunc = fit
if r is None or not isinstance(r, LeastSquaresRegressor):
r = LeastSquaresRegressor()
r.trait_set(xs=x, ys=y,
fitfunc=fitfunc,
errfunc=errfunc)
if apply_filter:
r = self._apply_outlier_filter(r, ox, oy, index, fod)
return r
