unit test for replicability based on qp.util.temp_seed

quapy/method/aggregative.py

@@ -438,6 +438,7 @@ class PACC(AggregativeProbabilisticQuantifier):
         validation data, or as an integer, indicating that the misclassification rates should be estimated via
         `k`-fold cross validation (this integer stands for the number of folds `k`), or as a
         :class:`quapy.data.base.LabelledCollection` (the split itself).
+    :param n_jobs: number of parallel workers
     """
 
     def __init__(self, learner: BaseEstimator, val_split=0.4, n_jobs=None):

quapy/tests/test_replicability.py

@@ -0,0 +1,30 @@
+import unittest
+import quapy as qp
+from quapy.functional import strprev
+from sklearn.linear_model import LogisticRegression
+
+from method.aggregative import PACC
+
+
+class MyTestCase(unittest.TestCase):
+    def test_replicability(self):
+
+        dataset = qp.datasets.fetch_UCIDataset('yeast')
+
+        with qp.util.temp_seed(0):
+            lr = LogisticRegression(random_state=0, max_iter=10000)
+            pacc = PACC(lr)
+            prev = pacc.fit(dataset.training).quantify(dataset.test.X)
+            str_prev1 = strprev(prev, prec=5)
+
+        with qp.util.temp_seed(0):
+            lr = LogisticRegression(random_state=0, max_iter=10000)
+            pacc = PACC(lr)
+            prev2 = pacc.fit(dataset.training).quantify(dataset.test.X)
+            str_prev2 = strprev(prev2, prec=5)
+
+        self.assertEqual(str_prev1, str_prev2)  # add assertion here
+
+
+if __name__ == '__main__':
+    unittest.main()