Coverage for src/pycse/sklearn/lr_uq.py: 0.00%

1""" 

2A Linear regressor with uncertainty quantification. 

3""" 

4 

5import numpy as np 

6from pycse import regress 

7from pycse import predict as _predict 

8from sklearn.base import BaseEstimator, RegressorMixin 

9 

10 

11class LinearRegressionUQ(BaseEstimator, RegressorMixin): 

12 def fit(self, X, y): 

13 self.xtrain = np.array(X) 

14 self.ytrain = np.array(y) 

15 self.coefs_, self.pars_cint, self.pars_se = regress(X, y, rcond=None) 

16 return self 

17 

18 def predict(self, X, return_std=False): 

19 y, _, se = _predict(self.xtrain, self.ytrain, self.coefs_, X) 

20 if return_std: 

21 return y, se 

22 else: 

23 return y