style adjusted

epios/sampling_maker.py

@@ -48,7 +48,7 @@ def __init__(self, non_resp_rate=0, keep_track=False, data=None,
         self.keep_track = keep_track
         self.data = data
 
-    def __call__(self, sampling_times, people, post_proc = False):
+    def __call__(self, sampling_times, people, post_proc=False):
 
         '''
         Method to return the results for all the planned tests
@@ -85,7 +85,7 @@ def __call__(self, sampling_times, people, post_proc = False):
                 temp = []
                 for x in res:
                     for n, y in enumerate(temp):
-                        temp[n] = y.drop(columns = x.columns, errors = 'ignore')
+                        temp[n] = y.drop(columns=x.columns, errors='ignore')
                     temp.append(x)
                     result.append(temp.copy())
                     observ.append(list(map(lambda x: (x == 'Positive').mean().mean(), temp)))

epios/tests/test_re_scaler.py

@@ -18,9 +18,10 @@ def test_call(self):
     def test_smooth(self):
         x = [[1.0], [1.0, 2.0], [1.0, 2.0, 3.0]]
         with self.assertRaises(Exception):
-            ReScaler(smoothing=lambda x: 1)(x, tested=[[1],[1,1],[1,1,1]])
+            ReScaler(smoothing=lambda x: 1)(x, tested=[[1], [1, 1], [1, 1, 1]])
         with self.assertRaises(Exception):
             ReScaler(smoothing=lambda x: 1)(x, times=array([0.0, 1.0, 2.0]))
-        self.assertEqual(ReScaler(smoothing=lambda x: 1)(x, times=array([0.0, 1.0, 2.0]), tested=[[1],[1,1],[1,1,1]])[0], 1.0)
-        self.assertEqual(ReScaler(smoothing=lambda x: 1)(x, times=array([0.0, 1.0, 2.0]), tested=[[1],[1,1],[1,1,1]])[1], 2.0)
-        self.assertEqual(ReScaler(smoothing=lambda x: 1)(x, times=array([0.0, 1.0, 2.0]), tested=[[1],[1,1],[1,1,1]])[2], 3.0)
+        result = ReScaler(smoothing=lambda x: 1)(x, times=array([0.0, 1.0, 2.0]), tested=[[1], [1, 1],[1, 1, 1]])
+        self.assertEqual(result[0], 1.0)
+        self.assertEqual(result[1], 2.0)
+        self.assertEqual(result[2], 3.0)

epios/tests/test_sampling_maker.py

@@ -1,10 +1,10 @@
 import pandas as pd
 from unittest import TestCase
 from sampling_maker import SamplingMaker
-from numpy import array
 
 class TestSM(TestCase):
 
+
     def test_positive(self):
         self.assertEqual(SamplingMaker(threshold=1)._testresult(1.1), 'Positive')
         for a in [3, 4, 5, 6, 7, 8]: