class_docstr: Base class for time series cross validators
  
  Based on the scikit-learn base cross-validator with alterations to fit the
  time series interface.
class_docstr_tok: ["Base","class","for","time","series","cross","validators","Based","on","the","scikit-learn","base","cross-validator","with","alterations","to","fit","the","time","series","interface","."]
docstr: Generate boolean masks corresponding to test sets
docstr_tok: ["Generate","boolean","masks","corresponding","to","test","sets"]
code: def _iter_train_test_masks(self, y, X):
      """Generate boolean masks corresponding to test sets"""
      for train_index, test_index in self._iter_train_test_indices(
          y, X
      ):
          train_mask = np.zeros(y.shape[0], dtype=bool)
          test_mask = np.zeros(y.shape[0], dtype=bool)
  
          train_mask[train_index] = True
          test_mask[test_index] = True
          yield train_mask, test_mask
  
imports: import abc
  import numpy
  from sklearn.base import BaseEstimator
  from sklearn.utils.validation import indexable
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 4 for calling the BaseTSCrossValidator obj's underlying member method code with example usage: obj._iter_train_test_masks(y, X) without return types