示例#1
0
文件: exp_bias.py 项目: humm/l2l
def bias_exp( repeat = 3, primname = 'mbab01K'):

    expname = 'imbias'

    for rep in range(repeat):

        # secondary data for every possibilities
        for prim in range(10):
            for sec in range(10):
                cfg = config_data((names.kSecondaryData, primname, prim, expname, sec, rep))
                cfg.exp.bias = expname
                if write_configs:
                    datafile.save_config(cfg)

        # tests
        for prim in range(10):
            for sec in range(10):
                cfg = config_test((names.kSecondaryTest, primname, prim, expname, sec, rep))
                if write_configs:
                    datafile.save_config(cfg)

    # results
    for prim in range(10):
        jobdep = []
        for sec in range(10):
            for rep in range(repeat):
                jobdep.append(names.key2jobname((names.kSecondaryTest, primname, prim, expname, sec, rep)))
        cfg = config_results((names.kSecondaryResults, primname, prim, expname), jobdep)
        if write_configs:
            datafile.save_config(cfg)
示例#2
0
文件: exp_bias.py 项目: humm/l2l
def sec_param_exp(min_orderbabble, repeat = 3):

    if min_orderbabble >= 1000 and min_orderbabble % 1000 == 0:
        n_babble = '{:02d}K'.format(min_orderbabble/1000)
    else:
        n_babble = '{:03d}'.format(min_orderbabble)
    primname = 'mbab{}'.format(n_babble)
    secname  = '{}{}'.format('imbias', n_babble)

    prim = 0
    for rep in range(repeat):
        # secondary data
        for sec in range(10):
            cfg = config_data((names.kSecondaryData, primname, prim, secname, sec, rep))
            cfg.goals.guide.min_orderbabble = min_orderbabble
            cfg.exp.bias = 'imbias'
            if write_configs:
                datafile.save_config(cfg)

        # secondary test
        for sec in range(10):
            cfg = config_test((names.kSecondaryTest, primname, prim, secname, sec, rep))
            if write_configs:
                datafile.save_config(cfg)

    # results
    jobdep = []
    for sec in range(10):
        for rep in range(repeat):
            jobdep.append(names.key2jobname((names.kSecondaryTest, primname, prim, secname, sec, rep)))
    cfg = config_results((names.kSecondaryResults, primname, prim, secname), jobdep)
    if write_configs:
        datafile.save_config(cfg)
示例#3
0
def bias_exp(repeat=3, primname='mbab01K'):

    expname = 'imbias'

    for rep in range(repeat):

        # secondary data for every possibilities
        for prim in range(10):
            for sec in range(10):
                cfg = config_data(
                    (names.kSecondaryData, primname, prim, expname, sec, rep))
                cfg.exp.bias = expname
                if write_configs:
                    datafile.save_config(cfg)

        # tests
        for prim in range(10):
            for sec in range(10):
                cfg = config_test(
                    (names.kSecondaryTest, primname, prim, expname, sec, rep))
                if write_configs:
                    datafile.save_config(cfg)

    # results
    for prim in range(10):
        jobdep = []
        for sec in range(10):
            for rep in range(repeat):
                jobdep.append(
                    names.key2jobname((names.kSecondaryTest, primname, prim,
                                       expname, sec, rep)))
        cfg = config_results(
            (names.kSecondaryResults, primname, prim, expname), jobdep)
        if write_configs:
            datafile.save_config(cfg)
示例#4
0
def prim_param_exp(min_orderbabble, repeat=3):

    if min_orderbabble >= 1000 and min_orderbabble % 1000 == 0:
        n_babble = '{:02d}K'.format(min_orderbabble / 1000)
    else:
        n_babble = '{:03d}'.format(min_orderbabble)
    primname = 'mbab{}'.format(n_babble)

    learn_seeds = [
        7155156840889203871, 5690355778091957505, 4227221844763982751,
        1077203299390958199, 742764988813620150, 5189664138391362084,
        8242855154472905725, 730853595070848367, 2536789960665647998,
        7200813046020147260, 4676635650031838608, 7064174268753147830,
        4193293326361042609, 8572800867951405795, 7598963578664304146,
        2316684008784354120, 9152028930354691119, 7200627669525538061,
        4500226611609739185, 4050985011484108118
    ]
    assert repeat <= len(learn_seeds)

    for rep in range(repeat):
        # primary data
        for prim in range(10):
            cfg = config_data((names.kPrimaryData, primname, prim, rep))
            cfg.goals.guide.min_orderbabble = min_orderbabble
            cfg.hardware.seed.primary = learn_seeds[rep]
            if write_configs:
                datafile.save_config(cfg)

        #primary test
        for prim in range(10):
            cfg = config_test((names.kPrimaryTest, primname, prim, rep))
            if write_configs:
                datafile.save_config(cfg)

    # results
    jobdep = []
    for prim in range(10):
        for rep in range(repeat):
            jobdep.append(
                names.key2jobname((names.kPrimaryTest, primname, prim, rep)))
    cfg = config_results((names.kPrimaryResults, primname), jobdep)
    if write_configs:
        datafile.save_config(cfg)
示例#5
0
文件: exp_bias.py 项目: humm/l2l
def prim_param_exp(min_orderbabble, repeat = 3):

    if min_orderbabble >= 1000 and min_orderbabble % 1000 == 0:
        n_babble = '{:02d}K'.format(min_orderbabble/1000)
    else:
        n_babble = '{:03d}'.format(min_orderbabble)
    primname = 'mbab{}'.format(n_babble)

    learn_seeds = [7155156840889203871, 5690355778091957505, 4227221844763982751, 1077203299390958199,
                    742764988813620150, 5189664138391362084, 8242855154472905725,  730853595070848367,
                   2536789960665647998, 7200813046020147260, 4676635650031838608, 7064174268753147830,
                   4193293326361042609, 8572800867951405795, 7598963578664304146, 2316684008784354120,
                   9152028930354691119, 7200627669525538061, 4500226611609739185, 4050985011484108118]
    assert repeat <= len(learn_seeds)

    for rep in range(repeat):
        # primary data
        for prim in range(10):
            cfg = config_data((names.kPrimaryData, primname, prim, rep))
            cfg.goals.guide.min_orderbabble = min_orderbabble
            cfg.hardware.seed.primary = learn_seeds[rep]
            if write_configs:
                datafile.save_config(cfg)

        #primary test
        for prim in range(10):
            cfg = config_test((names.kPrimaryTest, primname, prim, rep))
            if write_configs:
                datafile.save_config(cfg)

    # results
    jobdep = []
    for prim in range(10):
        for rep in range(repeat):
            jobdep.append(names.key2jobname((names.kPrimaryTest, primname, prim, rep)))
    cfg = config_results((names.kPrimaryResults, primname), jobdep)
    if write_configs:
        datafile.save_config(cfg)
示例#6
0
def sec_param_exp(min_orderbabble, repeat=3):

    if min_orderbabble >= 1000 and min_orderbabble % 1000 == 0:
        n_babble = '{:02d}K'.format(min_orderbabble / 1000)
    else:
        n_babble = '{:03d}'.format(min_orderbabble)
    primname = 'mbab{}'.format(n_babble)
    secname = '{}{}'.format('imbias', n_babble)

    prim = 0
    for rep in range(repeat):
        # secondary data
        for sec in range(10):
            cfg = config_data(
                (names.kSecondaryData, primname, prim, secname, sec, rep))
            cfg.goals.guide.min_orderbabble = min_orderbabble
            cfg.exp.bias = 'imbias'
            if write_configs:
                datafile.save_config(cfg)

        # secondary test
        for sec in range(10):
            cfg = config_test(
                (names.kSecondaryTest, primname, prim, secname, sec, rep))
            if write_configs:
                datafile.save_config(cfg)

    # results
    jobdep = []
    for sec in range(10):
        for rep in range(repeat):
            jobdep.append(
                names.key2jobname(
                    (names.kSecondaryTest, primname, prim, secname, sec, rep)))
    cfg = config_results((names.kSecondaryResults, primname, prim, secname),
                         jobdep)
    if write_configs:
        datafile.save_config(cfg)