'Generate indices to split data into training and test set.
Parameters
X : object
Always ignored, exists for compatibility.
y : object
Always ignored, exists for compatibility.
groups : object
Always ignored, exists for compatibility.
Returns
train : ndarray
The training set indices for that split.
test : ndarray
The testing set indices for that split.'

def split(self, X=None, y=None, groups=None):

    ind = np.arange(len(self.test_fold))
    for test_index in self._iter_test_masks():
        train_index = ind[np.logical_not(test_index)]
        test_index = ind[test_index]
        (yield (train_index, test_index))
