# Set up output dir
assert (config.match_model == 'pr4a' or config.match_model == 'pr4a-i1')
config.experiment_out_dir = os.path.join(config.experiment_out_dir,
config.dataset_name,
config.match_model,
'ms=%s' % config.makespan, ts)
output_dir = config.experiment_out_dir
copy_source_to_dir(output_dir, config)
output_dir = os.path.join(output_dir, 'results')
n_rev = np.size(scores, axis=0)
n_pap = np.size(scores, axis=1)
mkdir_p(output_dir)
# Output files.
assignment_file = os.path.join(output_dir, 'assignment')
time_file = os.path.join(output_dir, 'time.tsv')
time_limit = None
iter_limit = config.iter_limit
bm = PR4A(scores, covs, loads, iter_limit=iter_limit)
s = time.time()
bm.fair_assignment()
t = time.time() - s
f = open(time_file, 'w')
f.write(str(t))
f.close()
# Set up output dir
assert(config.match_model == 'irda-lb' or config.match_model == 'irda')
config.experiment_out_dir = os.path.join(
config.experiment_out_dir, config.dataset_name, config.match_model,
'ms=%s' % config.makespan, ts)
output_dir = config.experiment_out_dir
copy_source_to_dir(output_dir, config)
output_dir = os.path.join(output_dir, 'results')
n_rev = np.size(scores, axis=0)
n_pap = np.size(scores, axis=1)
mkdir_p(output_dir)
# Output files.
assignment_file = os.path.join(output_dir, 'assignment')
time_file = os.path.join(output_dir, 'time.tsv')
if config.match_model == 'irda':
bm = IRDALB(loads, None, covs, scores, makespan=ms)
else:
bm = IRDALB(loads, loads_lb, covs, scores, makespan=ms)
s = time.time()
bm.solve()
t = time.time() - s
f = open(time_file, 'w')
f.write(str(t))