Merge branch 'master' into c-cate

Author: Riera Auge

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -72,7 +72,7 @@ body:
         ```python
         import platform; print(platform.platform())
         import sys; print("Python", sys.version)
-        import doubleml; print("DoubleML", sklearn.__version__)
+        import doubleml; print("DoubleML", doubleml.__version__)
         import sklearn; print("Scikit-Learn", sklearn.__version__)
         ```
     validations:

README.md

@@ -98,21 +98,23 @@ and our
 
 If you use the DoubleML package a citation is highly appreciated:
 
-Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M. (2021), DoubleML - An
+Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M. (2022), DoubleML - An
 Object-Oriented Implementation of Double Machine Learning in Python,
-arXiv:[2104.03220](https://arxiv.org/abs/2104.03220).
+Journal of Machine Learning Research, 23(53): 1-6,
+[https://www.jmlr.org/papers/v23/21-0862.html](https://www.jmlr.org/papers/v23/21-0862.html).
 
 Bibtex-entry:
 
 ```
-@misc{DoubleML2021,
-      title={{DoubleML} -- {A}n Object-Oriented Implementation of Double Machine Learning in {P}ython}, 
-      author={Philipp Bach and Victor Chernozhukov and Malte S. Kurz and Martin Spindler},
-      year={2021},
-      eprint={2104.03220},
-      archivePrefix={arXiv},
-      primaryClass={stat.ML},
-      note={arXiv:\href{https://arxiv.org/abs/2104.03220}{2104.03220} [stat.ML]}
+@article{DoubleML2022,
+      title   = {{DoubleML} -- {A}n Object-Oriented Implementation of Double Machine Learning in {P}ython}, 
+      author  = {Philipp Bach and Victor Chernozhukov and Malte S. Kurz and Martin Spindler},
+      journal = {Journal of Machine Learning Research},
+      year    = {2022},
+      volume  = {23},
+      number  = {53},
+      pages   = {1--6},
+      url     = {http://jmlr.org/papers/v23/21-0862.html}
 }
 ```
 

doc/conf.py

@@ -22,7 +22,7 @@
 author = 'Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M.'
 
 # The full version, including alpha/beta/rc tags
-release = '0.2.dev0'
+release = '0.5.dev0'
 
 
 # -- General configuration ---------------------------------------------------

doubleml/datasets.py

@@ -104,7 +104,7 @@ def fetch_bonus(return_type='DoubleMLData', polynomial_features=False):
     if polynomial_features:
         poly = PolynomialFeatures(2, include_bias=False)
         data_transf = poly.fit_transform(data[x_cols])
-        x_cols = poly.get_feature_names(x_cols)
+        x_cols = list(poly.get_feature_names_out(x_cols))
 
         data_transf = pd.DataFrame(data_transf, columns=x_cols)
         data = pd.concat((data[[y_col] + d_cols], data_transf),

doubleml/double_ml_iivm.py

@@ -308,7 +308,9 @@ def _score_elements(self, y, z, d, g_hat0, g_hat1, m_hat, r_hat0, r_hat1, smpls)
                         - np.divide(np.multiply(1.0-z, w_hat0), 1.0 - m_hat))
         else:
             assert callable(self.score)
-            psi_a, psi_b = self.score(y, z, d, g_hat0, g_hat1, m_hat, r_hat0, r_hat1, smpls)
+            psi_a, psi_b = self.score(y=y, z=z, d=d,
+                                      g_hat0=g_hat0, g_hat1=g_hat1, m_hat=m_hat, r_hat0=r_hat0, r_hat1=r_hat1,
+                                      smpls=smpls)
 
         return psi_a, psi_b
 

doubleml/double_ml_irm.py

@@ -404,7 +404,9 @@ def _score_elements(self, y, d, g_hat0, g_hat1, m_hat, smpls):
                 psi_a = - np.divide(d, p_hat)
         else:
             assert callable(self.score)
-            psi_a, psi_b = self.score(y, d, g_hat0, g_hat1, m_hat, smpls)
+            psi_a, psi_b = self.score(y=y, d=d,
+                                      g_hat0=g_hat0, g_hat1=g_hat1, m_hat=m_hat,
+                                      smpls=smpls)
 
         return psi_a, psi_b