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