diff --git a/Transduction_office/prueba.py b/Transduction/prueba.py
similarity index 97%
rename from Transduction_office/prueba.py
rename to Transduction/prueba.py
index 5e05315..78f20a2 100644
--- a/Transduction_office/prueba.py
+++ b/Transduction/prueba.py
@@ -1,20 +1,16 @@
 import itertools
-from functools import cache
+from typing import Iterable
 
-import numpy as np
 from densratio import densratio
 from scipy.sparse import issparse, vstack
 from scipy.stats import multivariate_normal
 from sklearn.linear_model import LogisticRegression
 from sklearn.model_selection import GridSearchCV
 
-import quapy as qp
-from Transduction_office.pykliep import DensityRatioEstimator
+from Transduction.pykliep import DensityRatioEstimator
 from quapy.protocol import AbstractStochasticSeededProtocol, OnLabelledCollectionProtocol
-from quapy.data import LabelledCollection
 from quapy.method.aggregative import *
 import quapy.functional as F
-from time import time
 
 
 def gaussian(mean, cov=1., label=0, size=100, random_state=0):
@@ -43,7 +39,7 @@ def gaussian(mean, cov=1., label=0, size=100, random_state=0):
 # ------------------------------------------------------------------------------------
 class CovPriorShift(AbstractStochasticSeededProtocol):
 
-    def __init__(self, domains: list[LabelledCollection], sample_size=None, repeats=100, min_support=0, random_state=0,
+    def __init__(self, domains: Iterable[LabelledCollection], sample_size=None, repeats=100, min_support=0, random_state=0,
                  return_type='sample_prev'):
         super(CovPriorShift, self).__init__(random_state)
         self.domains = list(itertools.chain.from_iterable(lc.separate() for lc in domains))
diff --git a/Transduction_office/pykliep.py b/Transduction/pykliep.py
similarity index 100%
rename from Transduction_office/pykliep.py
rename to Transduction/pykliep.py