Ejemplo n.º 1
0
def _calculate_resources(data, args, resources):
    parallel = clargs.to_parallel(args)
    config = data[0][0]['config']
    config['resources'].update({resources['name']: {'memory': "%sg" % resources['mem'], 'cores': resources['cores']}})
    parallel.update({'progs': [resources['name']]})
    # parallel = log.create_base_logger(config, parallel)
    # log.setup_local_logging(config, parallel)
    log.setup_log(config, parallel)
    dirs = {'work': os.path.abspath(os.getcwd())}
    system.write_info(dirs, parallel, config)
    sysinfo = system.machine_info()[0]
    log.logger.info("Number of items %s" % len(data))
    parallel = res.calculate(parallel, data, sysinfo, config)
    log.logger.info(parallel)
    # print parallel
    # raise
    return parallel
Ejemplo n.º 2
0
def machine_info(*args):
    args = ipython.unzip_args(args)
    return ipython.zip_args(system.machine_info())
Ejemplo n.º 3
0
def machine_info(*args):
    args = ipython.unzip_args(args)
    return ipython.zip_args(system.machine_info())
                                     "bcbio_system.yaml")
    except ValueError as err:
        print(err)
        print(
            "WARNING: Attempting to read bcbio_system.yaml in the current directory."
        )
        system_config = "bcbio_system.yaml"

    with open(system_config) as in_handle:
        config = yaml.load(in_handle)
        res = {'cores': args.cores_per_job}
        config["algorithm"] = {"num_cores": args.cores_per_job}
        config["resources"].update({'sambamba': res, 'samtools': res})
        config["log_dir"] = os.path.join(os.path.abspath(os.getcwd()), "log")
    parallel = clargs.to_parallel(args)
    parallel.update({'progs': ['samtools', 'sambamba']})
    parallel = log.create_base_logger(config, parallel)
    log.setup_local_logging(config, parallel)
    dirs = {'work': os.path.abspath(os.getcwd())}
    system.write_info(dirs, parallel, config)
    sysinfo = system.machine_info()[0]
    samples = _get_samples_to_process(args.csv, out_dir, config,
                                      args.force_single, args.separators)
    parallel = resources.calculate(parallel, [samples], sysinfo, config)

    with prun.start(parallel, samples, config, dirs) as run_parallel:
        with profile.report("prepare bcbio samples", dirs):
            samples = run_parallel("prepare_bcbio_samples", samples)

    create_new_csv(samples, args)
Ejemplo n.º 5
0
def machine_info(*args):
    return system.machine_info()
Ejemplo n.º 6
0
    parser.add_argument("-p", "--tag", help="Tag name to label jobs on the cluster", default="bcb-prep")
    parser.add_argument("-t", "--paralleltype",
                        choices=["local", "ipython"],
                        default="local", help="Run with iptyhon")

    args = parser.parse_args()
    out_dir = os.path.abspath(args.out)
    utils.safe_makedir(out_dir)
    system_config = os.path.join(_get_data_dir(), "galaxy", "bcbio_system.yaml")
    with open(system_config) as in_handle:
        config = yaml.load(in_handle)
        res = {'cores': args.cores_per_job}
        config["algorithm"] = {"num_cores": args.cores_per_job}
        config["resources"].update({'sambamba': res,
                                    'samtools': res})
    parallel = clargs.to_parallel(args)
    parallel.update({'progs': ['samtools', 'sambamba']})
    parallel = log.create_base_logger(config, parallel)
    log.setup_local_logging(config, parallel)
    dirs = {'work': os.path.abspath(os.getcwd())}
    system.write_info(dirs, parallel, config)
    sysinfo = system.machine_info()[0]
    samples = _get_samples_to_process(args.csv, out_dir, config)
    parallel = resources.calculate(parallel, [samples], sysinfo, config)

    with prun.start(parallel, samples, config, dirs) as run_parallel:
        with profile.report("prepare bcbio samples", dirs):
            samples = run_parallel("prepare_bcbio_samples", samples)

    create_new_csv(samples, args)
Ejemplo n.º 7
0
def machine_info(*args):
    return system.machine_info()