def _mean_regress(self, scatter, r, fit):
if hasattr(scatter, 'yerror'):
if r is None or not isinstance(r, WeightedMeanRegressor):
r = WeightedMeanRegressor()
else:
if r is None or not isinstance(r, MeanRegressor):
r = MeanRegressor()
self._set_regressor(scatter, r)
r.trait_set(fit=fit, trait_change_notify=False)
r.calculate()
self._set_excluded(scatter, r)
return r
def _mean_regress(self, scatter, r, fit):
if hasattr(scatter, 'yerror'):
if r is None or not isinstance(r, WeightedMeanRegressor):
r = WeightedMeanRegressor()
else:
if r is None or not isinstance(r, MeanRegressor):
r = MeanRegressor()
self._set_regressor(scatter, r)
r.trait_set(fit=fit, trait_change_notify=False)
r.calculate()
self._set_excluded(scatter, r)
return r
def _mean_regress(self, scatter, r, fit):
from pychron.core.regression.mean_regressor import MeanRegressor, WeightedMeanRegressor
if hasattr(scatter, 'yerror') and fit=='weighted mean':
if r is None or not isinstance(r, WeightedMeanRegressor):
r = WeightedMeanRegressor()
else:
if r is None or not isinstance(r, MeanRegressor):
r = MeanRegressor()
self._set_regressor(scatter, r)
# r.trait_setq(fit=fit)
r.calculate()
self._set_excluded(scatter, r)
return r
def _mean_regress(self, scatter, r, fit):
from pychron.core.regression.mean_regressor import MeanRegressor, WeightedMeanRegressor
if hasattr(scatter, 'yerror') and fit == 'weighted mean':
if r is None or not isinstance(r, WeightedMeanRegressor):
r = WeightedMeanRegressor()
else:
if r is None or not isinstance(r, MeanRegressor):
r = MeanRegressor()
self._set_regressor(scatter, r)
# r.trait_setq(fit=fit)
r.calculate()
self._set_excluded(scatter, r)
return r
