def compute_performance(scenario, G, index, demand, no_damage_travel_time, no_damage_vmt):
import time
import pickle
import pdb
import networkx
import util
from travel_main_simple_simplev3 import damage_bridges
from travel_main_simple_simplev3 import measure_performance
from travel_main_simple_simplev3 import damage_network
from travel_main_simple_simplev3 import get_graph
start_time = time.time()
if G == None:
G = get_graph()
#figure out bridge damage for each scenario
damaged_bridges_internal, damaged_bridges_new, num_damaged_bridges = damage_bridges(scenario) #e.g., [1, 89, 598] #num_bridges_out is highway bridges only
# #figure out network damage and output Cube files to this effect
G = damage_network(damaged_bridges_internal, damaged_bridges_new, G, time.strftime("%Y%m%d")+'_filesForCube/', index)
# #figure out impact (performance metrics)
flow, shortest_paths, travel_time, vmt = measure_performance(G, num_damaged_bridges, demand, no_damage_travel_time, no_damage_vmt)
G = util.clean_up_graph(G)
print 'total scenario time: ', time.time() - start_time
return damaged_bridges_internal, damaged_bridges_new, num_damaged_bridges, flow, shortest_paths, travel_time, vmt
def main():
'''can change the number of epsilons below'''
seed(0) #set seed
simple = False #simple is just %bridges out, which is computationally efficient
number_of_highway_bridges = 1743
numeps = 3 #the number of epsilons
tol = 0.00001 #the minimum annual rate that you care about in the original event set (the weight now is the original annual rate / number of epsilons per event)
demand = bd.build_demand('input/BATS2000_34SuperD_TripTableData.csv', 'input/superdistricts_centroids_dummies.csv') #we just take a percentage in ita.py, namely #to get morning flows, take 5.3% of daily driver values. 11.5/(4.5*6+11.5*10+14*4+4.5*4) from Figure S10 of http://www.nature.com/srep/2012/121220/srep01001/extref/srep01001-s1.pdf
#figure out ground motions
# lnsas, weights = ground_motions(numeps, tol, 'input/SF2_mtc_total_3909scenarios_1743bridgesPlusBART_1epsFake.txt')
lnsas, weights, magnitudes = ground_motions(numeps, tol, 'input/SF2_mtc_total_3909scenarios_1743bridgesPlusBART_3eps.txt')
# with open ('input/20140114_lnsas_1epsFake.pkl', 'wb') as f:
# pickle.dump(lnsas, f)
with open ('input/20140114_magnitudes_3eps.pkl', 'wb') as f:
pickle.dump(magnitudes, f)
with open('input/20140114_lnsas_3eps.pkl','rb') as f:
lnsas = pickle.load(f)
# with open('input/20140114_lnsas_1epsFake.pkl','rb') as f:
# lnsas = pickle.load(f)
print 'the number of ground motion events we are considering: ', len(lnsas)
print 'first length: ', len(lnsas[0])
bart_dict = transit_to_damage.make_bart_dict()
muni_dict = transit_to_damage.make_muni_dict()
bridge_array_new = []
bridge_array_internal = []
travel_index_times = []
# G = nx.read_gpickle("input/graphMTC_noCentroidsLength15.gpickle")
G = get_graph()
print 'am I a multi graph? I really do not want to be!', G.is_multigraph() #An undirected graph class that can store multiedges. Multiedges are multiple edges between two nodes. Each edge can hold optional data or attributes.A MultiGraph holds undirected edges. Self loops are allowed.
no_damage_travel_time, no_damage_vmt = compute_tt_vmt(G, demand)
G = util.clean_up_graph(G)
# make_directories(range(len(lnsas)))
# transit_to_damage.set_main_path('input/trn/transit_lines/', 'input/trncopy/transit_lines/') #TODO: need to change THREE file paths (these plus bart)
# run in SERIES
#---------------------------------------------
# targets = [0, 5000]
# # targets = range(len(lnsas))
# for i in targets:
# print i
# start = time.time()
# damaged_bridges_internal, damaged_bridges_new, num_damaged_bridges, flow, shortest_paths, travel_time, vmt = compute_performance(lnsas[i], G, i, demand, no_damage_travel_time, no_damage_vmt)
# bridge_array_internal.append(damaged_bridges_internal)
# bridge_array_new.append(damaged_bridges_new)
# travel_index_times.append((i, num_damaged_bridges, flow, shortest_paths, travel_time, vmt, num_damaged_bridges/float(number_of_highway_bridges), magnitudes[i]))
# print 'time for one: ', time.time() - start
# if i%3909 == 0:
# save_results(bridge_array_internal, bridge_array_new, travel_index_times, int((i + 1)/float(3909)))
# # scenario = lnsas[i]
# # #figure out bridge damage for each scenario
# # damaged_bridges_internal, damaged_bridges_new, num_damaged_bridges = damage_bridges(scenario) #e.g., [1, 89, 598] #num_bridges_out is highway bridges only
# # bridge_array_internal.append(damaged_bridges_internal)
# # bridge_array_new.append(damaged_bridges_new)
# # #figure out network damage and output Cube files to this effect
# # G = damage_network(damaged_bridges_internal, damaged_bridges_new, G, time.strftime("%Y%m%d")+'_filesForCube/', i)
# # #figure out impact (performance metrics)
# # flow, shortest_paths, travel_time, vmt = measure_performance(G, num_damaged_bridges, demand, no_damage_travel_time, no_damage_vmt)
# # travel_index_times.append((i, num_damaged_bridges, flow, shortest_paths, travel_time, vmt, num_damaged_bridges/float(number_of_highway_bridges), magnitudes[i]))
# # G = util.clean_up_graph(G)
# # # if i%3909 == 0:
# # if i%1 == 0:
# # save_results(bridge_array_internal, bridge_array_new, travel_index_times, int(i/float(3909)))
# # #---------------------------------------------
# # # run in PARALLEL
# # # #---------------------------------------------
ppservers = ()
# Creates jobserver with automatically detected number of workers
job_server = pp.Server(ppservers=ppservers)
print "Starting pp with", job_server.get_ncpus(), "workers"
start_time = time.time()
# set up jobs
jobs = []
targets = range(3909, len(lnsas)) #len(lnsas)) 7818,
# targets = [0, 33, 5000]
# for i in range(len(lnsas)):
for i in targets:
jobs.append(job_server.submit(compute_performance, (lnsas[i], None, i, demand, no_damage_travel_time, no_damage_vmt, ), modules = ('networkx', ))) # functions, modules
# get results
# if len(jobs) != len(lnsas):
# pdb.set_trace() # error checking!
index = 0
for job in jobs:
(damaged_bridges_internal, damaged_bridges_new, num_damaged_bridges, flow, shortest_paths, travel_time, vmt) = job()
i = targets[index]
print 'target id: ', i
bridge_array_internal.append(damaged_bridges_internal)
bridge_array_new.append(damaged_bridges_new)
travel_index_times.append((i, num_damaged_bridges, flow, shortest_paths, travel_time, vmt, num_damaged_bridges/float(number_of_highway_bridges), magnitudes[i]))
if i%3909 == 0:
save_results(bridge_array_internal, bridge_array_new, travel_index_times, int((i + 1)/float(3909)))
index += 1
# #---------------------------------------------
save_results(bridge_array_internal, bridge_array_new, travel_index_times, int((i + 1)/float(3909)))
