def inverted_estimation_filter_worker(work_queue,done_queue,G,master_sets,choice_set_config):
for trip_id in iter(work_queue.get,'STOP'):
if choice_set_config['allow_duplicates_of_chosen_route']:
chosen_overlap=calc_chosen_overlap(G,master_sets[trip_id][0],master_sets[trip_id][1:],choice_set_config)
choice_set=ds.filter_master(G,None,master_sets[trip_id][1:],choice_set_config)
choice_set=[master_sets[trip_id][0]]+choice_set
done_queue.put((trip_id,choice_set,chosen_overlap))
else:
choice_set,chosen_overlap=ds.filter_master(G,master_sets[trip_id][0],master_sets[trip_id][1:],choice_set_config)
done_queue.put((trip_id,choice_set,chosen_overlap))
done_queue.put('STOP')
return True
def inverted_estimation_filter_worker(work_queue, done_queue, G, master_sets,
choice_set_config):
for trip_id in iter(work_queue.get, 'STOP'):
if choice_set_config['allow_duplicates_of_chosen_route']:
chosen_overlap = calc_chosen_overlap(G, master_sets[trip_id][0],
master_sets[trip_id][1:],
choice_set_config)
choice_set = ds.filter_master(G, None, master_sets[trip_id][1:],
choice_set_config)
choice_set = [master_sets[trip_id][0]] + choice_set
done_queue.put((trip_id, choice_set, chosen_overlap))
else:
choice_set, chosen_overlap = ds.filter_master(
G, master_sets[trip_id][0], master_sets[trip_id][1:],
choice_set_config)
done_queue.put((trip_id, choice_set, chosen_overlap))
done_queue.put('STOP')
return True
def predict_holdback_filter_worker(work_queue,done_queue,G,master_sets,choice_set_config):
for trip_id in iter(work_queue.get,'STOP'):
if choice_set_config['allow_duplicates_of_chosen_route']:
choice_set=ds.filter_master(G,None,master_sets[trip_id][1:],choice_set_config)
chosen_overlap=[1]
for i in range(len(choice_set)):
chosen_overlap.append(calc_chosen_overlap(G,master_sets[trip_id][0],[choice_set[i]],choice_set_config))
choice_set=[master_sets[trip_id][0]]+choice_set
done_queue.put((trip_id,choice_set,chosen_overlap))
else:
raise Exception, 'must allow duplicates of chosen route for predicting a holdback sample'
done_queue.put('STOP')
return True
def inverted_assignment_load_worker(work_queue, done_queue, network,
master_config, ext_bound, matrix_list):
this_network = network
config = master_config.assign_config
idx = 0
for source, the_target in iter(work_queue.get, 'STOP'):
idx = idx + 1
print time.asctime(time.localtime()), "-", current_process(
).name, "-", idx, ". zone: ", source, "Selecting random sample of generated paths..."
if source in the_target:
del the_target[source]
master_sets = {}
for t in the_target:
master_sets[t] = []
to_iter = 1
if master_config.choice_set_config['randomize_after']:
to_iter = master_config.choice_set_config['randomize_after_iters']
while to_iter:
to_iter = to_iter - 1
for fname in glob.glob(
os.path.join(master_config.assign_config['pickle_path'],
str(source) + '_*')):
f = open(fname, 'rb')
target_paths = cPickle.load(f)
f.close()
for t in the_target:
if t in target_paths:
master_sets[t].append(target_paths[t])
filtered_sets = {}
for t in master_sets:
if master_sets[t] != []:
#filter master set
filtered_sets[t] = ds.filter_master(
this_network, None, master_sets[t],
master_config.choice_set_config)
trace_and_load(this_network, filtered_sets, master_config, matrix_list,
source)
done_queue.put(this_network.orig_network)
done_queue.put('STOP')
return True
def inverted_assignment_load_worker(work_queue,done_queue,network,master_config,ext_bound,matrix_list):
this_network=network
config=master_config.assign_config
idx=0
for source,the_target in iter(work_queue.get,'STOP'):
idx=idx+1
print time.asctime(time.localtime()), "-", current_process().name, "-",idx, ". zone: ", source, "Selecting random sample of generated paths..."
if source in the_target:
del the_target[source]
master_sets={}
for t in the_target:
master_sets[t]=[]
to_iter=1
if master_config.choice_set_config['randomize_after']:
to_iter=master_config.choice_set_config['randomize_after_iters']
while to_iter:
to_iter=to_iter-1
for fname in glob.glob(os.path.join(master_config.assign_config['pickle_path'],str(source)+'_*')):
f=open(fname,'rb')
target_paths=cPickle.load(f)
f.close()
for t in the_target:
if t in target_paths:
master_sets[t].append(target_paths[t])
filtered_sets={}
for t in master_sets:
if master_sets[t]!=[]:
#filter master set
filtered_sets[t]=ds.filter_master(this_network,None,master_sets[t],master_config.choice_set_config)
trace_and_load(this_network,filtered_sets,master_config,matrix_list,source)
done_queue.put(this_network.orig_network)
done_queue.put('STOP')
return True
