templates.set_dynamic_header_table(header, table)
# Let's use a standard DTKConfigBuilder.
config_builder = DTKConfigBuilder()
# ignore_missing is required when using templates
config_builder.ignore_missing = True
# Use the default COMPS 2.10 and the SamplesInput folder for input files
# See examples\AssetManagement\use_custom_executable.py for more information
config_builder.set_exe_collection('EMOD 2.10')
# For the experiment builder in the example, we use a ModBuilder from_combos to run
# each of the configurations for two separate run numbers.
# The first line needs to be the modifier functions coming from the templates
experiment_builder = ModBuilder.from_combos(
templates.get_modifier_functions(), # <-- Do this first!
[
ModFn(DTKConfigBuilder.set_param, 'Run_Number', rn)
for rn in range(2, 4)
])
# This dictionary is used by the `dtk run` command line and allow to pass it some parameters
# If you are running through `python example_templates.py`, this dictionary is unused
run_sim_args = {
'exp_builder': experiment_builder,
'exp_name': 'TemplateDemo',
'config_builder': config_builder
}
# This part is needed if you are running the script through `python example_templates.py`
# It is not used by the command line interface
# Construct the table
table = [list(c.values()) for c in combined]
# Change some things in the config.json
config.set_param('Config_Name', scenario_name)
# Initialize the template
tpl = TemplateHelper()
tpl.set_dynamic_header_table(headers, table)
tpl.active_templates = [
config, campaign_tpl, demog, demog_pfa, demog_asrt, demog_acc
]
# Create an experiment builder
experiment_builder = ModBuilder.from_combos(
tpl.get_modifier_functions())
experiment_manager = ExperimentManagerFactory.from_cb(
config_builder)
COMPS_experiment_name = scenario_name
# COMPS_experiment_name = suite_name # I want hover-over in COMPS to be the suite name
experiment_manager.run_simulations(exp_name=COMPS_experiment_name,
exp_builder=experiment_builder,
suite_id=suite_id)
experiments.append(experiment_manager)
experiments_ids.append(experiment_manager.experiment.exp_id)
# Dump the experiment ids for resume
with open('ids.json', 'w') as out:
json.dump(experiments_ids, out)