"""
Tests the assignment algorithm.
Assignment algorithm: find all flights that arrive at the virtual hub within a
certain time window of each other and group them by maximizing the available
slack.
"""
from lib.intervals import Interval, group
if __name__ == "__main__":
print group(
[
Interval("G", 0, 2),
Interval("B", 2, 4),
Interval("C", 1, 3),
Interval("D", 3, 5),
Interval("A", 1, 3),
Interval("E", 4, 6),
Interval("F", 2, 4),
]
)
def allocate(self, aircraft):
p('debug', 'Starting formation allocation for %s' % aircraft)
# Do not perform allocation if no hub exists in the flight route.
if len(aircraft.route.segments) == 0:
return
self.formations = []
intervals = []
candidates = self.aircraft_queue
hub = aircraft.route.waypoints[0]
# This is bad. We don't want to filter anything.
# @todo: pre-process at a higher level.
# Only consider other aircraft flying to the same hub
candidates = filter(lambda a: a.route.waypoints[0] is hub,
candidates)
p('debug', 'Full candidate set: %s' % candidates)
# Only consider aircraft having a maximum heading difference between
# the hub and their destination
segment = Segment(aircraft.hub, aircraft.destination)
leader_heading = segment.get_initial_bearing()
def heading_filter(buddy):
segment = Segment(buddy.hub, buddy.destination)
buddy_heading = segment.get_initial_bearing()
phi_obs = abs(leader_heading - buddy_heading)
p(
'debug',
'delta phi observed for %s (phi: %.2f) against %s (phi: %.2f)'
': %.2f degrees' % (
aircraft, leader_heading, buddy, buddy_heading, phi_obs
)
)
return phi_obs <= (config.phi_max/2)
candidates = filter(heading_filter, candidates)
# Other interesting filters
if 'same-airline' in config.restrictions:
airline = aircraft.label[0:2]
candidates = filter(lambda a: a.label[0:2] == airline,
candidates)
if 'same-aircraft-type' in config.restrictions:
aircraft_type = aircraft.aircraft_type
candidates = filter(lambda a: a.aircraft_type == aircraft_type,
candidates)
p('debug', 'Reduced candidate set: %s' % candidates)
for candidate in candidates:
# Quick and dirty: recalc position. Instead, pull eta from var.
candidate.controller.update_position()
tth = candidate.time_to_waypoint() # time to hub
hub_eta = sim.time + tth
# From the moment the aircraft enters the lock area, the slack
# decreases linearly to zero upon hub arrival.
if tth < config.lock_time:
slack = tth * config.etah_slack / config.lock_time
else:
slack = config.etah_slack
p('Time = %s, Hub (= %s) eta %s for candidate %s' %\
(sim.time, hub, hub_eta, candidate))
intervals.append(Interval(
candidate,
int(hub_eta) - slack,
int(hub_eta) + slack
))
for interval_group in group(intervals):
formation = Formation()
for interval in interval_group:
formation.append(interval.obj)
self.formations.append(formation)
"""
Tests the assignment algorithm.
Assignment algorithm: find all flights that arrive at the virtual hub within a
certain time window of each other and group them by maximizing the available
slack.
"""
from lib.intervals import Interval, group
if __name__ == '__main__':
print group([
Interval('G', 0, 2),
Interval('B', 2, 4),
Interval('C', 1, 3),
Interval('D', 3, 5),
Interval('A', 1, 3),
Interval('E', 4, 6),
Interval('F', 2, 4),
])
def allocate(self, aircraft):
p('debug', 'Starting formation allocation for %s' % aircraft)
# Do not perform allocation if no hub exists in the flight route.
if len(aircraft.route.segments) == 0:
return
self.formations = []
intervals = []
candidates = self.aircraft_queue
hub = aircraft.route.waypoints[0]
# This is bad. We don't want to filter anything.
# @todo: pre-process at a higher level.
# Only consider other aircraft flying to the same hub
candidates = filter(lambda a: a.route.waypoints[0] is hub, candidates)
p('debug', 'Full candidate set: %s' % candidates)
# Only consider aircraft having a maximum heading difference between
# the hub and their destination
segment = Segment(aircraft.hub, aircraft.destination)
leader_heading = segment.get_initial_bearing()
def heading_filter(buddy):
segment = Segment(buddy.hub, buddy.destination)
buddy_heading = segment.get_initial_bearing()
phi_obs = abs(leader_heading - buddy_heading)
p(
'debug',
'delta phi observed for %s (phi: %.2f) against %s (phi: %.2f)'
': %.2f degrees' %
(aircraft, leader_heading, buddy, buddy_heading, phi_obs))
return phi_obs <= (config.phi_max / 2)
candidates = filter(heading_filter, candidates)
# Other interesting filters
if 'same-airline' in config.restrictions:
airline = aircraft.label[0:2]
candidates = filter(lambda a: a.label[0:2] == airline, candidates)
if 'same-aircraft-type' in config.restrictions:
aircraft_type = aircraft.aircraft_type
candidates = filter(lambda a: a.aircraft_type == aircraft_type,
candidates)
p('debug', 'Reduced candidate set: %s' % candidates)
for candidate in candidates:
# Quick and dirty: recalc position. Instead, pull eta from var.
candidate.controller.update_position()
tth = candidate.time_to_waypoint() # time to hub
hub_eta = sim.time + tth
# From the moment the aircraft enters the lock area, the slack
# decreases linearly to zero upon hub arrival.
if tth < config.lock_time:
slack = tth * config.etah_slack / config.lock_time
else:
slack = config.etah_slack
p('Time = %s, Hub (= %s) eta %s for candidate %s' %\
(sim.time, hub, hub_eta, candidate))
intervals.append(
Interval(candidate,
int(hub_eta) - slack,
int(hub_eta) + slack))
for interval_group in group(intervals):
formation = Formation()
for interval in interval_group:
formation.append(interval.obj)
self.formations.append(formation)