def _poly_regress(self, scatter, r, fit):
if hasattr(scatter, 'yerror'):
if r is None or not isinstance(r, WeightedPolynomialRegressor):
r = WeightedPolynomialRegressor()
else:
if r is None or not isinstance(r, PolynomialRegressor):
r = PolynomialRegressor()
self._set_regressor(scatter, r)
r.trait_set(degree=fit)
r.set_truncate(scatter.truncate)
r.calculate()
if r.ys.shape[0] < fit + 1:
return
self._set_excluded(scatter, r)
return r
def _poly_regress(self, scatter, r, fit):
if hasattr(scatter, 'yerror'):
if r is None or not isinstance(r, WeightedPolynomialRegressor):
r = WeightedPolynomialRegressor()
else:
if r is None or not isinstance(r, PolynomialRegressor):
r = PolynomialRegressor()
self._set_regressor(scatter, r)
r.trait_set(degree=fit)
r.set_truncate(scatter.truncate)
r.calculate()
if r.ys.shape[0] < fit + 1:
return
self._set_excluded(scatter, r)
return r
def _poly_regress(self, scatter, r, fit):
from pychron.core.regression.ols_regressor import PolynomialRegressor
from pychron.core.regression.wls_regressor import WeightedPolynomialRegressor
if hasattr(scatter, 'yerror') and any(scatter.yerror.get_data()):
if r is None or not isinstance(r, WeightedPolynomialRegressor):
r = WeightedPolynomialRegressor()
else:
if r is None or not isinstance(r, PolynomialRegressor):
r = PolynomialRegressor()
self._set_regressor(scatter, r)
r.trait_set(degree=fit)
r.set_truncate(scatter.truncate)
if r.ys.shape[0] < fit + 1:
return
r.calculate()
self._set_excluded(scatter, r)
return r
