def job(place):
try:
s = abm.Sim(sim=sim, place=place)
if s.load_agents():
s.load_agent_meta()
s.init_scenario(scenario=scenario)
print s.agents_file()
sys.stdout.flush()
s.load_result_meta()
detail = []
for d in s.DX_destin.keys():
detail.append({
"type": "Feature",
"properties": {
"name": place,
"destin": d,
'pop': s.n_destin[d],
'D10%': np.percentile(s.DX_destin[d], 10),
'D50%': np.percentile(s.DX_destin[d], 50),
'D90%': np.percentile(s.DX_destin[d], 90),
'T10%': np.percentile(s.T_destin[d], 10),
'T50%': np.percentile(s.T_destin[d], 50),
'T90%': np.percentile(s.T_destin[d], 90),
},
"geometry": mapping(Point(s.h.nodes[d]))
})
overview = [{
"type": "Feature",
"properties": {
"name": place,
"pop": s.n,
"no_of_destins": len(s.DX_destin.keys()),
"video": s.video_file(),
'D10%': np.percentile(s.DX, 10),
'D50%': np.percentile(s.DX, 50),
'D90%': np.percentile(s.DX, 90),
'T10%': np.percentile(s.T, 10),
'T50%': np.percentile(s.T, 50),
'T90%': np.percentile(s.T, 90),
},
"geometry": mapping(s.h.boundary)
}]
print overview
print detail
else:
raise ValueError(
'Output files cannot be initialised for some reason (e.g. no destinations available).'
)
return overview, detail
except KeyboardInterrupt:
print 'KeyboardInterrupt caught in child...'
except (ValueError, AttributeError, NameError, IOError) as e:
print e
print '{}: {}'.format(place, e)
logging.critical(place)
logging.exception(e)
def do_calculations(city):
'''
Multiprocessing runs this subroutine for each city in parallel
Parameters
----------
city : string
A string that describes name of city boundary in OSM.
Returns
-------
return_code: integer
A number that signifies the outcome of the simulation.
0: One of (ValueError, AttributeError, NameError, IOError)
1: Successful
2: Already done
'''
# Number of completed scenarios for this city in this run
return_code = 0
scenario = 'undefined'
try:
simulation = abm.Sim(sim=sim,city=city,p_factor=cities.p_factor,n=None,destins=None,fresh_place=False)
# Iterate through the scenarios
for scenario in simulation.scenarios:
simulation.init_scenario(scenario=scenario)
# If the results cannot be loaded, run simulation
if not simulation.load_results():
simulation.run_sim(fps=20,bitrate=4000,video=True,live_video=False)
else:
print '{0}[{1}]: This scenario has already been simulated with the given parameters!'.format(city, scenario)
sys.stdout.flush()
return_code += 1
return return_code
except KeyboardInterrupt:
print 'KeyboardInterrupt caught in child...'
return
except Exception as e:
logging.critical(city)
logging.exception(e)
print '{0}[{1}]: {2}'.format(city,scenario,e)
print '----------------------------------------------------------------------'
print 'Following has been logged to [{0}]'.format(logfile)
print '----------------------------------------------------------------------'
print traceback.format_exc()
print '----------------------------------------------------------------------'
return return_code
import sys
sys.path.append('core')
import abm
import db
reload(abm)
reload(db)
from matplotlib import pyplot as plt
import numpy as np
import pickle
import os
s = abm.Sim('bristol25', 'City of Bristol')
s.h.init_destins()
s.h.init_route()
s.scenario = 'k5-original'
s.h.init_SG(subgraph='nearest')
# -----------------------------------------
# reading N from tstep folder
# Copy and paste from here
tstep = 0
# Number of bins for that particular destin
]
# self = abm.Sim('flood','Carlisle')
p = db.Population((-2.960970689433074, 54.88321937312177, -2.8861928154524805,
54.91133135582124))
destin_type = {'invdistprob': True, 'nearest': False}
combinations = {
('invdistprob', 'ia'): 'k5-idp',
('invdistprob', 'ff'): 'ff-idp',
('nearest', 'ia'): 'k5',
('nearest', 'ff'): 'ff',
}
sim = abm.Sim('flood', 'Carlisle')
sim.n = int(round(sum(p.pop)))
sim.scenarios = combinations.values()
sim.h.destins = []
for k, v in enumerate(ec):
ec[k]['nearest_node'] = sim.h.nearest_node(*v['approx_coord'])
sim.h.destins.append(ec[k]['nearest_node'])
nodes_not_in_bbox = set(sim.h.G.nodes()).difference(nodes_in_bbox)
for u, v, d in sim.h.G.edges_iter(nodes_not_in_bbox, data=True):
d['pop_dist'] = 0
# sim.fresh=True
sim.run_by_agent(rerun=False)
reload(abm)
reload(db)
import logging
from collections import OrderedDict
sim = 'bristol50'
logging.basicConfig(filename='logs/{0}.log'.format(sim), level=logging.DEBUG)
places = abm.Places(sim).names
description = {'ff': 'Normal Scenario', 'ia': 'Evacuation Scenario'}
city = 'City of Bristol'
self = abm.Sim(sim, city)
# Save each exit to a different file
def do_calculations(city):
try:
return_code = 1
# self = abm.Sim(sim,city)
content = OrderedDict()
t90 = {}
for scenario in ['ff', 'ia']:
self.scenarios = [scenario]
self.run()
content['Video: {0}'.format(
description[scenario])] = '{0}.mp4'.format(self.df_agents_file)
import sys
sys.path.append('core')
import abm, db
reload(abm)
reload(db)
# self = abm.Sim('flood','Carlisle')
self = abm.Sim('test_abm_buffer',(-2.88612967859241, 54.91133135582125, -2.9609706894330743, 54.88327220183169))
self.n = 10000
self.use_buffer = True
self.run_by_agent()
import sys
sys.path.append('core')
import abm, db
reload(abm)
reload(db)
sim = abm.Sim('abm_test', 'City of London')
sim.scenarios = ['k5']
sim.n = 1000
sim.run_by_agent(verbose=False)
# Generate video
import matplotlib.pyplot as plt
plt.close('all')
sim.init_scenario('k5')
sim.load_events()
v = abm.Viewer(sim, video=True)
v.path(which='speed')
import sys
sys.path.append('core')
import abm
import db
reload(abm)
reload(db)
# s=abm_new.Sim('flood','Carlisle')
s = abm.Sim('flood', (-2.88612967859241, 54.91133135582125,
-2.9609706894330743, 54.88327220183169))
s.scenarios = ['ia']
s.n = 100000
s.run_sim()
import abm
reload(abm)
import db
reload(db)
s = abm.Sim('test', 'City of Bristol')
s.n = 500000
properties = s.load_agent_times()
fname = '{0}/time.json'.format(s.agents_file())
s.h.geojson_edges(fname, properties)
