From 76bf4f01bd99ea7c01cb7e3d38dabcc2b05701ca Mon Sep 17 00:00:00 2001
From: Daniel Schick <schick@textbausteine.net>
Date: Thu, 2 May 2024 10:43:09 +0200
Subject: [PATCH] Maximum threshold should still be allowed (e.g. 1 hour)

---
 .../validators/validation_rule_functions.py   | 20 +++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/src/server/BreCal/validators/validation_rule_functions.py b/src/server/BreCal/validators/validation_rule_functions.py
index 1c16ce4..9e6df51 100644
--- a/src/server/BreCal/validators/validation_rule_functions.py
+++ b/src/server/BreCal/validators/validation_rule_functions.py
@@ -119,8 +119,8 @@ class ValidationRuleBaseFunctions():
             - there are no matching times for the provided {query} (e.g., "eta_berth")
 
         This method computes the absolute time difference between all time entries. A threshold (in seconds) is used
-        to identify, when the time differences are so large, that participants essentially disagree on the times. 
-        This circumvents previous instabilities, which stem from rounding the pd.Timestamp elements.  
+        to identify, when the time differences are so large, that participants essentially disagree on the times.
+        This circumvents previous instabilities, which stem from rounding the pd.Timestamp elements.
 
         options:
             threshold: integer. Determines the threshold in seconds, when two Timestamps differ 'too much'
@@ -142,7 +142,7 @@ class ValidationRuleBaseFunctions():
         if len(agency_times)==0:
             violation_state = False
             return violation_state
-        
+
         df_times = df_times.loc[df_times["participant_type"].isin(participant_types),:]
         agency_time = [time_ for time_ in agency_times.loc[:,query].tolist() if isinstance(time_, pd.Timestamp)]
 
@@ -154,16 +154,16 @@ class ValidationRuleBaseFunctions():
         if len(estimated_times)==0:
             violation_state = False
             return violation_state
-        
+
         # for the given query, e.g., 'eta_berth', sample all times from the pandas DataFrame
         estimated_times = [time_ for time_ in df_times.loc[:,query].tolist() if isinstance(time_, pd.Timestamp)] # consider only pandas Timestamp objects
 
-        # measure the time difference between all pairs. 
+        # measure the time difference between all pairs.
         # for each pair of times, the absolute timedifference in seconds (float) is measured
         time_absolute_differences = [[abs(time_.to_pydatetime()-time__.to_pydatetime()).total_seconds()  for j_, time__ in enumerate(estimated_times) if j_ != i_] for i_, time_ in enumerate(estimated_times)]
 
         # list of lists: for each element in the list, create a boolean that indicates, whether the threshold is exceeded
-        time_difference_exceeds_threshold = [[time__ >= threshold for time__ in time_] for time_ in time_absolute_differences]
+        time_difference_exceeds_threshold = [[time__ > threshold for time__ in time_] for time_ in time_absolute_differences]
 
         # list of booleans for each time entry separately
         time_difference_exceeds_threshold = [any(time_) for time_ in time_difference_exceeds_threshold]
@@ -180,7 +180,7 @@ class ValidationRuleBaseFunctions():
         # violation_state = difference > pd.Timedelta("15min")
 
         # this solution clamps the times to 15 minute intervals and compares these values. When there is a single time difference, a violation occurs
-        # the drawback is that in some cases if there is a minimal difference say of 1 minute (:22 and :23 minutes after the hour) the violation is 
+        # the drawback is that in some cases if there is a minimal difference say of 1 minute (:22 and :23 minutes after the hour) the violation is
         # triggered even though the times are very close to each other
 
         # apply rounding. For example, the agreement of different participants may be required to match minute-wise
@@ -639,7 +639,7 @@ class ValidationRuleFunctions(ValidationRuleBaseFunctions):
         """
         if self.ignore_terminal_flag: # this feature flag may disable the validation rule for Terminals
             return self.get_no_violation_default_output()
-        
+
         if not shipcall.type in [ShipcallType.OUTGOING.value, ShipcallType.SHIFTING.value]:
             return self.get_no_violation_default_output()
 
@@ -757,7 +757,7 @@ class ValidationRuleFunctions(ValidationRuleBaseFunctions):
         """
         if self.ignore_terminal_flag: # this feature flag may disable the validation rule for Terminals
             return self.get_no_violation_default_output()
-        
+
         if not shipcall.type in [ShipcallType.INCOMING.value]:
             return self.get_no_violation_default_output()
 
@@ -800,7 +800,7 @@ class ValidationRuleFunctions(ValidationRuleBaseFunctions):
         """
         if self.ignore_terminal_flag: # this feature flag may disable the validation rule for Terminals
             return self.get_no_violation_default_output()
-        
+
         if not shipcall.type in [ShipcallType.OUTGOING.value, ShipcallType.SHIFTING.value]:
             return self.get_no_violation_default_output()