def eval_args(updated_args, model, tasks, servers, repeat):
"""
Evaluates the arguments by updating the arguments and then testing the model, tasks, servers and repeat are
equalled to the parsed arguments
:param updated_args: List of updated args
:param model: Value for the model location
:param tasks: Value for the number of tasks
:param servers: Value for the number of servers
:param repeat: Value for the number of repeats
"""
sys.argv = ['location'] + updated_args
args = parse_args()
assert args.model == model and args.tasks == tasks and args.servers == servers and args.repeat == repeat, \
f'Expects: {args.model}, {args.tasks}, {args.servers}, {args.repeat}, ' \
f'actual: {model}, {tasks}, {servers}, {repeat}'
price_change=price_change,
initial_price=initial_price)
for auction_repeat in range(auction_repeats):
reset_model(tasks, servers)
auction_result = optimal_decentralised_iterative_auction(
tasks, servers, time_limit=time_limit)
auction_result.pretty_print()
repeat_results[f'repeat {auction_repeat}'] = auction_result.store()
model_results.append(repeat_results)
# Save all of the results to a file
with open(filename, 'w') as file:
json.dump(model_results, file)
print('Finished running')
if __name__ == "__main__":
args = parse_args()
if args.extra == '' or args.extra == 'task mutation':
full_task_mutation(get_model(args.model, args.tasks, args.servers))
elif args.extra == 'mutation grid search':
mutation_grid_search(get_model(args.model, args.tasks, args.servers))
elif args.extra == 'value only':
value_only_mutation(get_model(args.model, args.tasks, args.servers))
elif args.extra == 'dia repeat':
dia_repeat(get_model(args.model, args.tasks, args.servers))
else:
raise Exception(f'Unknown extra argument: {args.extra}')