Python parallel_exec Examples

Example #1

def run_parallel(datasets, f, cmp_class_args, preprocess_args, param, metric):
    f_run = functools.partial(f,
                              cmp_class_args=cmp_class_args,
                              preprocess_args=preprocess_args,
                              param=param,
                              metric=metric)
    datasets = map(lambda x: [x], datasets)
    utils.parallel_exec(f_run, datasets)

Example #2

File: spatial_time_correlation.py Project: diegoximenes/master_dissertation

def run_parallel(metric, eps_hours, min_fraction_of_clients):
    dt_ranges = list(utils.iter_dt_range())
    f_localize_events = functools.partial(
        localize_events,
        metric=metric,
        eps_hours=eps_hours,
        min_fraction_of_clients=min_fraction_of_clients)
    utils.parallel_exec(f_localize_events, dt_ranges)

Example #3

def run_parallel(metric, eps_hours):
    dt_ranges = list(utils.iter_dt_range())

    fp_voting = functools.partial(voting,
                                  metric=metric,
                                  in_dir="paths",
                                  eps_hours=eps_hours)
    utils.parallel_exec(fp_voting, dt_ranges)

    fp_voting = functools.partial(voting,
                                  metric=metric,
                                  in_dir="names",
                                  eps_hours=eps_hours)
    utils.parallel_exec(fp_voting, dt_ranges)

Example #4

File: print_cps.py Project: diegoximenes/master_dissertation

def run_parallel(dir_model, metric, preprocess_args):
    dt_ranges = list(utils.iter_dt_range())
    fp_print_cps = functools.partial(print_cps,
                                     dir_model=dir_model,
                                     metric=metric,
                                     preprocess_args=preprocess_args)
    utils.parallel_exec(fp_print_cps, dt_ranges)

    fp_print_per_name = functools.partial(unsupervised_utils.print_per_name,
                                          metric=metric,
                                          file_name="cps_per_mac.csv")
    utils.parallel_exec(fp_print_per_name, dt_ranges)

    fp_print_per_path = functools.partial(unsupervised_utils.print_per_path,
                                          metric=metric,
                                          file_name="cps_per_mac.csv")
    utils.parallel_exec(fp_print_per_path, dt_ranges)

Example #5

File: print_empty_segs.py Project: diegoximenes/master_dissertation

def run_parallel(metric, min_seg_len, filtered):
    dt_ranges = list(utils.iter_dt_range())
    fp_print_empty_segs = functools.partial(print_empty_segs,
                                            metric=metric,
                                            min_seg_len=min_seg_len,
                                            filtered=filtered,
                                            plot=False)
    utils.parallel_exec(fp_print_empty_segs, dt_ranges)

    fp_print_per_name = functools.partial(unsupervised_utils.print_per_name,
                                          metric=metric,
                                          file_name="empty_segs_per_mac.csv")
    utils.parallel_exec(fp_print_per_name, dt_ranges)

    fp_print_per_path = functools.partial(unsupervised_utils.print_per_path,
                                          metric=metric,
                                          file_name="empty_segs_per_mac.csv")
    utils.parallel_exec(fp_print_per_path, dt_ranges)

Example #6

File: plot_names.py Project: diegoximenes/master_dissertation

def run_parallel(metric):
    dt_ranges = list(utils.iter_dt_range())
    f_plot_per_name = functools.partial(plot_per_name,
                                        metric=metric,
                                        preprocess_args=preprocess_args)
    utils.parallel_exec(f_plot_per_name, dt_ranges)

Example #7

File: print_graph.py Project: diegoximenes/master_dissertation

def run_parallel():
    dt_ranges = list(utils.iter_dt_range())
    utils.parallel_exec(process_graphs, dt_ranges)

Example #8

File: traceroute_exploratory_prints.py Project: diegoximenes/master_dissertation

def run_parallel():
    mac_node = read_input.get_mac_node()
    dt_ranges = list(utils.iter_dt_range())
    f_print_all = functools.partial(print_all, mac_node=mac_node)
    utils.parallel_exec(f_print_all, dt_ranges)

Example #9

File: create_dataset_unsupervised.py Project: diegoximenes/master_dissertation

def run_parallel():
    dt_ranges = list(utils.iter_dt_range())
    utils.parallel_exec(create_dataset_unsupervised, dt_ranges)

Example #10

File: plot_latencies_traceroute.py Project: diegoximenes/master_dissertation

def run_parallel(preprocess_args):
    dt_ranges = list(utils.iter_dt_range())
    fp = functools.partial(plot_latencies_traceroute,
                           preprocess_args=preprocess_args)
    utils.parallel_exec(fp, dt_ranges)

Example #11

def run_parallel(metric, only_unique_traceroute):
    dt_ranges = list(utils.iter_dt_range())
    f_plot_per_node = \
        functools.partial(plot_per_node, metric=metric,
                          only_unique_traceroute=only_unique_traceroute)
    utils.parallel_exec(f_plot_per_node, dt_ranges)