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abexp/core/planning.py

@@ -1,17 +1,17 @@
 # MIT License
-# 
+#
 # Copyright (c) 2021 Playtika Ltd.
-# 
+#
 # Permission is hereby granted, free of charge, to any person obtaining a copy
 # of this software and associated documentation files (the "Software"), to deal
 # in the Software without restriction, including without limitation the rights
 # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 # copies of the Software, and to permit persons to whom the Software is
 # furnished to do so, subject to the following conditions:
-# 
+#
 # The above copyright notice and this permission notice shall be included in all
 # copies or substantial portions of the Software.
-# 
+#
 # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
@@ -26,9 +26,10 @@
 
 
 class Planning:
-
     @staticmethod
-    def planning_diff_mean(avg_n_users_per_day, mean_contr, mean_treat, std_contr, alpha=0.05, power=0.8):
+    def planning_diff_mean(
+        avg_n_users_per_day, mean_contr, mean_treat, std_contr, alpha=0.05, power=0.8
+    ):
         """
         Use the sample size determination with means comparison from the core.design.SampleSize class
         to estimate the number of days that a test must run to achieve the desired significance and power level.
@@ -66,12 +67,16 @@ def planning_diff_mean(avg_n_users_per_day, mean_contr, mean_treat, std_contr, a
             return np.Inf
 
         # Compute required sample size
-        sample_size = SampleSize.ssd_mean(mean_contr, mean_treat, std_contr, alpha, power)
+        sample_size = SampleSize.ssd_mean(
+            mean_contr, mean_treat, std_contr, alpha, power
+        )
 
-        return int(np.ceil(sample_size/avg_n_users_per_day))
+        return int(np.ceil(sample_size / avg_n_users_per_day))
 
     @staticmethod
-    def planning_diff_prop(avg_n_users_per_day, prop_contr, prop_treat, alpha=0.05, power=0.8):
+    def planning_diff_prop(
+        avg_n_users_per_day, prop_contr, prop_treat, alpha=0.05, power=0.8
+    ):
         """
         Use the sample size determination with proportions comparison from the core.design.SampleSize class
         to estimate the number of days that a test must run to achieve the desired significance and power level.
@@ -109,3 +114,6 @@ def planning_diff_prop(avg_n_users_per_day, prop_contr, prop_treat, alpha=0.05,
         sample_size = SampleSize.ssd_prop(prop_contr, prop_treat, alpha, power)
 
         return int(np.ceil(sample_size / avg_n_users_per_day))
+
+
+# comment