# depreacated, use pipelines.batched_sobo.sobo_pipeline()

# import os
# import bo
# import ptycho

# def sobo_pipeline(config):

#     result_dir = config['io']['result_dir']
#     os.makedirs(result_dir, exist_ok=True)

#     RANDOM_ITERS = config['job'].get('random_iters', 0)
#     SOBO_ITERS   = config['job'].get('sobo_iters')
#     METRIC = config['bo']['metric']
#     PTYCHOENGINE = ptycho.engines[config['ptycho']['engine']]


#     randombo = bo.RandomBOEngine(config)

#     bo_txt = os.path.join(result_dir, "bo.txt")
#     with open(bo_txt, "w") as f:
#         f.write(f"    iter\tmetric\t{"\t".join([p[:7] for p in randombo.params])}\n")

#     for j in range(RANDOM_ITERS):
#         print(f"RANDOM sampling; iteration {j}")
#         job_config = randombo.ask()
#         ptycho_engine = PTYCHOENGINE(job_config)
#         ptycho_engine.run(run_id=f"bo-{j:03d}")
#         y_value = ptycho_engine.metric(METRIC)
#         randombo.tell(job_config, y_value)
#         with open(bo_txt, "a") as f:
#             p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in randombo.params]
#             f.write(f"{j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")


#     sobo = bo.SingleObjectiveBOEngine(config)
#     sobo.train_x = randombo.train_x
#     sobo.train_y = randombo.train_y

#     for j in range(SOBO_ITERS):
#         print(f"SOBO sampling; iteration {RANDOM_ITERS + j}")
#         job_config = sobo.ask()
#         ptycho_engine = PTYCHOENGINE(job_config)
#         ptycho_engine.run(run_id=f"bo-{RANDOM_ITERS + j:03d}")
#         y_value = ptycho_engine.metric(METRIC)
#         sobo.tell(job_config, y_value)
#         with open(bo_txt, "a") as f:
#             p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in sobo.params]
#             f.write(f"{RANDOM_ITERS + j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")