def clean_database(simulation):
"""Drop from the database the tables created for the run."""
matrices = functions.get_query('matrices', simulation)
matrices_id = list(matrices.values_list('id', flat=True))
matrices_id.append(simulation.scenario.supply.pttimes.id)
with connection.cursor() as cursor:
for matrice_id in matrices_id:
cursor.execute(
"DROP TABLE IF EXISTS Matrix_{id};"
).format(id=matrice_id)
def clean(self):
"""Checks that no two nodes have the same user_id."""
if any(self.errors):
# Don't bother validating the formset unless each form is valid on
# its own
return
centroids = functions.get_query('centroid', self.simulation)
user_ids = list(centroids.values_list('user_id', flat=True))
for form in self.forms:
user_id = form.cleaned_data['user_id']
delete = form.cleaned_data['DELETE']
if not delete:
if user_id in user_ids:
raise forms.ValidationError(
'Two nodes (zones and intersections) cannot have the '
'same id (id: {}).').format(user_id)
user_ids.append(user_id)
def export_link_results(output, export_file):
# Create a dictionary to map the link ids with the link user ids.
link_mapping = dict()
links = functions.get_query('link', SIMULATION.id)
for link in links:
link_mapping[link.id] = link.user_id
# Check size of network.
large_network = len(output['link_ids']) >= LINK_THRESHOLD
# Write a csv.
with codecs.open(export_file, 'w', encoding='utf8') as f:
writer = csv.writer(f, delimiter='\t')
# Writer a custom header.
if large_network:
labels = ['in-flow_H', 'ttime_H']
else:
labels = ['in-flow_H', 'in-flow_S', 'out-flow_H', 'out-flow_S',
'ttime_H', 'ttime_S']
nb_periods = len(output['phi_in_H'][0])
headers = ['{}_{}'.format(label, i + 1)
for label in labels
for i in range(nb_periods)]
headers = ['link'] + headers
writer.writerow(headers)
# Write rows.
if large_network:
# Large network, only store one type of results (phi_in_H).
output_types = ['phi_in_H', 'ttime_H']
else:
# Small network, we can store everything.
output_types = ['phi_in_H', 'phi_in_S', 'phi_out_H', 'phi_out_S',
'ttime_H', 'ttime_S']
for i, link_id in enumerate(output['link_ids']):
link_id = int(link_id)
link_user_id = link_mapping[link_id]
row = [link_user_id]
for output_type in output_types:
values = output[output_type][i]
row += list(values)
writer.writerow(row)
stopfile = args[13]
simulation_id = int(args[15])
run_id = int(args[17])
# Get the SimulationRun object of the argument.
try:
run = SimulationRun.objects.get(pk=run_id)
except SimulationRun.DoesNotExist:
raise SystemExit('MetroDoesNotExist: No SimulationRun object ' +
'corresponding to the given id.')
# Retrieve Simulation and Link objects.
simulation = run.simulation
links = get_query('link', simulation.id)
# Write dummy MOEs.
moes = SimulationMOEs(
simulation=simulation.id,
runid=run.id,
)
moes.save()
# Wait 2 minutes.
for i in range(30):
if os.path.isfile(stopfile):
break
if i % 10 == 0:
with open(logfile, 'a') as g:
g.write('\n{} seconds remaining.'.format(30 - i))
raise SystemExit('MetroArgError: This script must be executed with the id '
+ 'of the SimulationRun has an argument.')
# Get the SimulationRun object of the argument.
try:
run = SimulationRun.objects.get(pk=run_id)
except SimulationRun.DoesNotExist:
raise SystemExit('MetroDoesNotExist: No SimulationRun object corresponding'
+ ' to the given id.')
simulation = run.simulation
# Output user-specific results only if the population is small.
# I believe that Metropolis does not output the file correctly if the
# population is large.
matrices = get_query('matrices', simulation)
nb_travelers = matrices.aggregate(Sum('total'))['total__sum']
if nb_travelers > TRAVELERS_THRESHOLD:
simulation.outputUsersTimes = 'false'
else:
simulation.outputUsersTimes = 'true'
simulation.save()
# Use the existing network output file if it exists.
simulation_network = (
'{0}/website_files/network_output/network_{1}.json'
.format(settings.BASE_DIR, simulation.id)
)
if simulation.has_changed or not os.path.isfile(simulation_network):
# Generate a new output file.
print('Network file does not exist, generating a new one...')
'of the SimulationRun has an argument.')
# Get the SimulationRun object of the argument.
try:
run = models.SimulationRun.objects.get(pk=run_id)
except models.SimulationRun.DoesNotExist:
raise SystemExit(
'MetroDoesNotExist: No SimulationRun object corresponding' +
' to the given id.')
simulation = run.simulation
# Output user-specific results only if the population is small.
# I believe that Metropolis does not output the file correctly if the
# population is large.
matrices = functions.get_query('matrices', simulation)
nb_travelers = matrices.aggregate(Sum('total'))['total__sum']
if nb_travelers > TRAVELERS_THRESHOLD:
simulation.outputUsersTimes = 'false'
simulation.outputUsersPaths = 'false'
else:
simulation.outputUsersTimes = 'true'
simulation.outputUsersPaths = 'true'
simulation.save()
# Use the existing network output file if it exists.
simulation_network = (
'{0}/website_files/network_output/network_{1}.json'.format(
settings.BASE_DIR, simulation.id))
if simulation.has_changed or not os.path.isfile(simulation_network):
# Generate a new output file.
DB_NAME = settings.DATABASES['default']['NAME']
# Create a tsv file with a readable user-specific cost output.
print('Writing traveler-specific cost output...')
FILE = (
'{0}/metrosim_files/output/metrosim_users_{1}_{2}.txt'
).format(settings.BASE_DIR, DB_NAME, SIMULATION.id)
if os.path.isfile(FILE):
try:
EXPORT_FILE = (
'{0}/website_files/network_output/user_results_{1}_{2}.txt'
).format(settings.BASE_DIR, SIMULATION.id, RUN.id)
# Create a dictionary to map the centroid ids with the centroid user
# ids.
centroid_mapping = dict()
centroids = functions.get_query('centroid', SIMULATION.id)
for centroid in centroids:
centroid_mapping[centroid.id] = centroid.user_id
# Create a dictionary to map the demandsegment ids with the name of the
# usertype.
usertype_mapping = dict()
demandsegments = models.DemandSegment.objects.filter(
demand__scenario__simulation=SIMULATION
)
for demandsegment in demandsegments:
name = demandsegment.usertype.name
if name:
usertype_mapping[demandsegment.id] = name
else:
usertype_mapping[demandsegment.id] = demandsegment.usertype.id
with codecs.open(FILE, 'r', encoding='utf8') as f: