diff --git a/pyFTS/common/fts.py b/pyFTS/common/fts.py
index 37cf196..4b11206 100644
--- a/pyFTS/common/fts.py
+++ b/pyFTS/common/fts.py
@@ -76,8 +76,8 @@ class FTS(object):
         else:
             ndata = self.apply_transformations(data)
 
-        if self.uod_clip:
-            ndata = np.clip(ndata, self.original_min, self.original_max)
+            if self.uod_clip:
+                ndata = np.clip(ndata, self.original_min, self.original_max)
 
         if 'distributed' in kwargs:
             distributed = kwargs.pop('distributed')
diff --git a/pyFTS/tests/multivariate.py b/pyFTS/tests/multivariate.py
index e0658a6..02db63e 100644
--- a/pyFTS/tests/multivariate.py
+++ b/pyFTS/tests/multivariate.py
@@ -7,7 +7,7 @@ from pyFTS.common import Transformations
 from pyFTS.data import SONDA
 df = SONDA.get_dataframe()
 train = df.iloc[0:578241] #three years
-#test = df.iloc[1572480:2096640] #ears
+test = df.iloc[1572480:2096640] #one year
 del df
 
 from pyFTS.partitioners import Grid, Util as pUtil
@@ -58,8 +58,10 @@ model1.target_variable = vavg
 
 #model.fit(train, num_batches=60, save=True, batch_save=True, file_path='mvfts_sonda')
 
-model1.fit(train, num_batches=200, save=True, batch_save=True, file_path='mvfts_sonda', distributed=True,
-          nodes=['192.168.0.110'], batch_save_interval=10)
+#model1.fit(train, num_batches=200, save=True, batch_save=True, file_path='mvfts_sonda', distributed=False,
+#          nodes=['192.168.0.110'], batch_save_interval=10)
 
 
-#model = Util.load_obj('mvfts_sonda')
\ No newline at end of file
+model = Util.load_obj('mvfts_sonda')
+
+forecasts = model.predict(test)
\ No newline at end of file