Bump matminer from 0.8.0 to 0.9.0

modnet/featurizers/utils.py

@@ -3,20 +3,22 @@
 __all__ = ("clean_df",)
 
 
-def clean_df(df):
+def clean_df(df, drop_allnan: bool = True):
     """Cleans dataframe by dropping missing values, replacing NaN's and infinities
     and selecting only columns containing numerical data.
 
     Args:
         df (pd.DataFrame): the dataframe to clean.
+        drop_allnan: if True, clean_df will remove features that are fully NaNs.
 
     Returns:
         pandas.DataFrame: the cleaned dataframe.
 
     """
 
     df = df.select_dtypes(include="number")
-    df = df.dropna(axis=1, how="all")
+    if drop_allnan:
+        df = df.dropna(axis=1, how="all")
     df = df.replace([np.inf, -np.inf, np.nan], np.nan)
 
     return df

modnet/models/vanilla.py

@@ -846,6 +846,11 @@ def _restore_model(self):
                     fill_value=-1,
                 ).fit(np.zeros((1, self.n_feat))),
             )
+        if not hasattr(self, "targets_groups"):
+            self.targets_groups = [x for subl in self.targets for x in subl]
+            LOG.warning(
+                "Installed modnet version (v>=0.4.0) does not match loaded model (v<0.4.0) and may result in errors. Please retrain or change your modnet version !"
+            )
 
     def save(self, filename: str) -> None:
         """Save the `MODNetModel` to filename:

requirements.txt

@@ -2,7 +2,7 @@ tensorflow==2.11.0
 tensorflow-probability==0.19.0
 pandas==1.5.2
 pymatgen==2023.1.30
-matminer==0.8.0
+matminer==0.9.0
 numpy>=1.20
 scikit-learn==1.2.0
 emmet-core<0.57  # Can remove after https://github.com/materialsproject/api/issues/819