Made a fix for error occuring when generalized library is used with t…

…ensor arrays and ensembling.

pysindy/feature_library/generalized_library.py

@@ -163,6 +163,7 @@ def __init__(
                     )
         self.tensor_array_ = tensor_array
         self.inputs_per_library_ = inputs_per_library
+        self.libraries_full_ = self.libraries_
 
     def fit(self, x, y=None):
         """
@@ -227,7 +228,7 @@ def fit(self, x, y=None):
         self.n_output_features_ = sum([lib.n_output_features_ for lib in fitted_libs])
 
         # Save fitted libs
-        self.libraries_ = fitted_libs
+        self.libraries_full_ = fitted_libs
 
         return self
 
@@ -246,7 +247,7 @@ def transform(self, x):
             generated from applying the custom functions to the inputs.
 
         """
-        for lib in self.libraries_:
+        for lib in self.libraries_full_:
             check_is_fitted(lib)
 
         n_samples, n_features = x.shape
@@ -262,7 +263,7 @@ def transform(self, x):
         xp = np.zeros((n_samples, self.n_output_features_))
 
         current_feat = 0
-        for i, lib in enumerate(self.libraries_):
+        for i, lib in enumerate(self.libraries_full_):
 
             # retrieve num output features from lib
             lib_n_output_features = lib.n_output_features_
@@ -296,7 +297,7 @@ def get_feature_names(self, input_features=None):
         output_feature_names : list of string, length n_output_features
         """
         feature_names = list()
-        for i, lib in enumerate(self.libraries_):
+        for i, lib in enumerate(self.libraries_full_):
             if i < self.inputs_per_library_.shape[0]:
                 if input_features is None:
                     input_features_i = [