def get_match_score(self, service_matching_props):
s = service_matching_props
service = get_service_key(service_matching_props)
unit = s['gps_car_id']
corrected_error = env.get_corrected_error(s['mean_time_error'])
close_match = s['total_matching'] > 8 and \
abs(corrected_error) < 1.0 and \
s['variance_time_error'] < 2.0
# intentionally coerces to int to form buckets
total_matching_score = int(s['total_matching'] / 5)
error_score = int(abs(corrected_error) / 0.4)
matched_over_total = float(s['total_matching']) / self.tracker.get_total_for_service(service)
matched_over_total_score = int(matched_over_total / 0.25) # 4 buckets essentially
meets_low = s['variance_time_error'] < 3.0 or \
(s['variance_time_error'] < 5.0 and s['total_matching'] < 6)
return (
-int(close_match), # descending
-int(total_matching_score), # descending
int(error_score), # ascending
-int(matched_over_total_score), # descending
-int(meets_low) # descending
)
def is_likely_match(self, service_matching_props):
s = service_matching_props
service = get_service_key(s)
unit = s['gps_car_id']
if self.allocations.was_planned(service, unit):
return True
interval = s['end'] - s['start']
corrected_error = env.get_corrected_error(s['mean_time_error'])
matched_over_total = float(s['total_matching']) / self.tracker.get_total_for_service(service)
low_error_if_few_reports = s['total_matching'] > 5 or (s['variance_time_error'] < 2.0 and abs(corrected_error) < 1.0)
insignificant = matched_over_total < 0.35 and interval < timedelta(minutes=15)
return s['total_matching'] > 2 and \
s['variance_time_error'] < 6.0 and \
abs(corrected_error) < 1.5 and \
low_error_if_few_reports and \
not insignificant
