def run_replanning_loop(settings, forecast_year):
replan_iters = settings['replan_iters']
replan_hh_samp_size = settings['replan_hh_samp_size']
activity_demand_model = settings['activity_demand_model']
image_names = settings['docker_images']
activity_demand_image = image_names[activity_demand_model]
region = settings['region']
asim_subdir = settings['region_to_asim_subdir'][region]
asim_workdir = os.path.join('/activitysim', asim_subdir)
asim_docker_vols = get_asim_docker_vols(settings)
base_asim_cmd = get_base_asim_cmd(settings, replan_hh_samp_size)
docker_stdout = settings.get('docker_stdout', False)
last_asim_step = settings['replan_after']
for i in range(replan_iters):
replanning_iteration_number = i + 1
print_str = (
'Replanning Iteration {0}'.format(replanning_iteration_number))
formatted_print(print_str)
# a) format new skims for asim
asim_pre.create_skims_from_beam(settings, year, overwrite=True)
# b) replan with asim
print_str = (
"Replanning {0} households with ActivitySim".format(
replan_hh_samp_size))
formatted_print(print_str)
asim = client.containers.run(
activity_demand_image, working_dir=asim_workdir,
volumes=asim_docker_vols,
command=base_asim_cmd + ' -r ' + last_asim_step,
stdout=docker_stdout,
stderr=True,
detach=True,
remove=True)
for log in asim.logs(
stream=True, stderr=True, stdout=docker_stdout):
print(log)
# e) run BEAM
run_traffic_assignment(
settings, year, client, replanning_iteration_number)
return
def generate_activity_plans(
settings, year, forecast_year, client,
resume_after=None,
warm_start=False,
overwrite_skims=True):
"""
Parameters
----------
year : int
Start year for the simulation iteration.
forecast_year : int
Simulation year for which activities are generated. If `forecast_year`
is the start year of the whole simulation, then we are probably
generating warm start activities based on the base year input data in
order to generate "warm start" skims.
"""
# 1. PARSE SETTINGS
activity_demand_model = settings['activity_demand_model']
land_use_model = settings['land_use_model']
image_names = settings['docker_images']
activity_demand_image = image_names[activity_demand_model]
region = settings['region']
asim_subdir = settings['region_to_asim_subdir'][region]
asim_workdir = os.path.join('/activitysim', asim_subdir)
asim_docker_vols = get_asim_docker_vols(settings)
asim_cmd = get_base_asim_cmd(settings)
docker_stdout = settings.get('docker_stdout', False)
# If this is the first iteration, skims should only exist because
# they were created during the warm start activities step. The skims
# haven't been updated since then so we don't need to re-create them.
if year == settings['start_year']:
overwrite_skims = False
# 2. PREPROCESS DATA FOR ACTIVITY DEMAND MODEL
print_str = "Creating {0} input data from {1} outputs".format(
activity_demand_model,
land_use_model)
formatted_print(print_str)
asim_pre.create_skims_from_beam(settings, year, overwrite=overwrite_skims)
asim_pre.create_asim_data_from_h5(
settings, year=forecast_year, warm_start=warm_start)
# 3. GENERATE ACTIVITY PLANS
print_str = (
"Generating activity plans for the year "
"{0} with {1}".format(
forecast_year, activity_demand_model))
formatted_print(print_str)
if resume_after:
asim_cmd += ' -r {0}'.format(resume_after)
asim = client.containers.run(
activity_demand_image,
working_dir=asim_workdir,
volumes=asim_docker_vols,
command=asim_cmd,
stdout=docker_stdout,
stderr=True,
detach=True)
for log in asim.logs(
stream=True, stderr=True, stdout=docker_stdout):
print(log)
# 4. COPY ACTIVITY DEMAND OUTPUTS --> LAND USE INPUTS
# If generating activities for the base year (i.e. warm start),
# then we don't want to overwrite urbansim input data. Otherwise
# we want to set up urbansim for the next simulation iteration
if (settings['land_use_enabled']) and (not warm_start):
print_str = (
"Generating {0} {1} input data from "
"{2} outputs".format(
forecast_year, land_use_model, activity_demand_model))
formatted_print(print_str)
asim_post.create_next_iter_inputs(settings, year, forecast_year)
# 6. CLEANUP
asim.remove()
logger.info('Done!')
return
def warm_start_activities(settings, year, client):
"""
Run ActivitySim to update UrbanSim inputs with long-term
choices it needs: workplace location, school location, and
auto ownership.
"""
# 1. PARSE SETTINGS
activity_demand_model = settings['activity_demand_model']
land_use_model = settings['land_use_model']
travel_model = settings['travel_model']
image_names = settings['docker_images']
activity_demand_image = image_names[activity_demand_model]
region = settings['region']
asim_subdir = settings['region_to_asim_subdir'][region]
asim_workdir = os.path.join('/activitysim', asim_subdir)
asim_docker_vols = get_asim_docker_vols(settings)
base_asim_cmd = get_base_asim_cmd(settings)
docker_stdout = settings.get('docker_stdout', False)
print_str = "Initializing {0} warm start sequence".format(
activity_demand_model)
formatted_print(print_str)
# 2. CREATE DATA FROM BASE YEAR SKIMS AND URBANSIM INPUTS
# skims
logger.info("Creating {0} skims from {1}".format(
activity_demand_model,
travel_model).upper())
asim_pre.create_skims_from_beam(settings, year)
# data tables
logger.info("Creating {0} input data from {1} outputs".format(
activity_demand_model,
land_use_model).upper())
asim_pre.create_asim_data_from_h5(settings, year, warm_start=True)
# 3. RUN ACTIVITYSIM IN WARM START MODE
logger.info("Running {0} in warm start mode".format(
activity_demand_model).upper())
ws_asim_cmd = base_asim_cmd + ' -w' # warm start flag
asim = client.containers.run(
activity_demand_image,
working_dir=asim_workdir,
volumes=asim_docker_vols,
command=ws_asim_cmd,
stdout=docker_stdout,
stderr=True,
detach=True)
for log in asim.logs(stream=True, stderr=True, stdout=docker_stdout):
print(log)
# 4. UPDATE URBANSIM BASE YEAR INPUT DATA
logger.info((
"Appending warm start activities/choices to "
" {0} base year input data").format(land_use_model).upper())
asim_post.update_usim_inputs_after_warm_start(settings)
# 5. CLEANUP
asim.remove()
logger.info('Done!')
return