diff --git a/pes_to_spec/model.py b/pes_to_spec/model.py
index 141591def848bd5ef2018c6adda9dcc1e0b7849c..e271aab5d70b1a19dc63a23b21932c91743c930b 100644
--- a/pes_to_spec/model.py
+++ b/pes_to_spec/model.py
@@ -114,7 +114,7 @@ class Model(object):
         low_pca = self.lr_pca.fit_transform(low_res)
         high_pca = self.hr_pca.fit_transform(high_res)
         # split in train and test for PCA uncertainty evaluation
-        low_pca_train, low_pca_test, high_pca_train, high_pca_test = train_test_split(low_pca, high_pca, test_size=self.test_size)
+        low_pca_train, low_pca_test, high_pca_train, high_pca_test = train_test_split(low_pca, high_pca, test_size=self.test_size, random_state=42)
         # fit the linear model
         self.fit_model.fit(low_pca_train, high_pca_train, low_pca_test, high_pca_test)
 
diff --git a/scripts/test_analysis.py b/scripts/test_analysis.py
index 56b422c8f0be0d584c4dfe5d9a715a99a1a61ae8..53e074d9220dcc66c659979b6c12059648dec65c 100755
--- a/scripts/test_analysis.py
+++ b/scripts/test_analysis.py
@@ -87,7 +87,7 @@ def main():
     # plot
     for tid in test_tids:
         idx = np.where(tid==tids)[0][0]
-        plot_result(f"test_{tid}.png", spec_pred[idx, :, :], spec_smooth[idx, :], spec_raw_pe[idx, :], eps)
+        plot_result(f"test_{tid}.png", spec_pred[idx, :, :], spec_smooth[idx, :], spec_raw_pe[idx, :])
 
 if __name__ == '__main__':
     main()