sklearn OneHotEncoder "sparse" parameter renaming to "sparse_output"

phygnn/utilities/pre_processing.py

@@ -3,10 +3,11 @@
 Data pre-processing module.
 """
 import logging
+from warnings import warn
+
 import numpy as np
 import pandas as pd
 from sklearn.preprocessing import OneHotEncoder
-from warnings import warn
 
 logger = logging.getLogger(__name__)
 
@@ -168,9 +169,7 @@ def _is_one_hot(arr, convert_int=False):
 
         one_hot = False
 
-        if isinstance(sample, str):
-            one_hot = True
-        elif np.issubdtype(type(sample), np.integer) and convert_int:
+        if isinstance(sample, str) or np.issubdtype(type(sample), np.integer) and convert_int:
             one_hot = True
 
         return one_hot
@@ -277,9 +276,10 @@ def _get_one_hot_data(self, convert_int=False, categories=None):
                     cats = [categories[name]]
                     logger.debug('Using categories {} for column {}'
                                  ''.format(cats, name))
-                    oh_obj = OneHotEncoder(sparse=False, categories=cats)
+                    oh_obj = OneHotEncoder(sparse_output=False,
+                                           categories=cats)
                 else:
-                    oh_obj = OneHotEncoder(sparse=False)
+                    oh_obj = OneHotEncoder(sparse_output=False)
 
                 oh_obj.fit(col)
                 one_hot_data.append(oh_obj.transform(col))

phygnn/version.py

@@ -1,4 +1,4 @@
 # -*- coding: utf-8 -*-
 """Physics Guided Neural Network version."""
 
-__version__ = '0.0.26'
+__version__ = '0.0.27'

requirements.txt

@@ -3,5 +3,5 @@ NREL-rex
 numpy>=1.16
 pandas>=0.25
 pytest>=5.2
-scikit-learn>=0.22
+scikit-learn>=1.2
 tensorflow