def config_test(key):
cfg = treedict.TreeDict()
cfg.exp.expname = key[1]
cfg.exp.key = key
cfg.exp.stage = 'primary' if key[0] == names.kPrimaryTest else 'secondary'
cfg.test.res = 20
cfg.test.freq = 100
cfg.test.max = 10001
seed = random.randint(0, sys.maxint)
cfg.hardware.seed.test = seed
datakey = (names.kPrimaryData if key[0] == names.kPrimaryTest else
names.kSecondaryData, ) + key[1:]
cfg.hardware.datafile = names.key2jobname(datakey)
datacfg = datafile.load_config(cfg.hardware.datafile)
cfg.test.fixed_dim = None
if datacfg.sim.sensors == 'toy':
cfg.test.fixed_dim = [None, None, 1.0]
cfg.hardware.testfile = names.key2jobname(key)
cfg.hardware.configfile = names.key2jobname(key) + '.cfg'
jobgraph.add_job(cfg.hardware.testfile, cfg, [cfg.hardware.datafile])
return cfg
def config_test(key):
cfg = treedict.TreeDict()
cfg.exp.expname = key[1]
cfg.exp.key = key
cfg.exp.stage = 'primary' if key[0] == names.kPrimaryTest else 'secondary'
cfg.test.res = 20
cfg.test.freq = 100
cfg.test.max = 10001
seed = random.randint(0, sys.maxint)
cfg.hardware.seed.test = seed
datakey = (names.kPrimaryData if key[0] == names.kPrimaryTest else names.kSecondaryData,) + key[1:]
cfg.hardware.datafile = names.key2jobname(datakey)
datacfg = datafile.load_config(cfg.hardware.datafile)
cfg.test.fixed_dim = None
if datacfg.sim.sensors == 'toy':
cfg.test.fixed_dim = [None, None, 1.0]
cfg.hardware.testfile = names.key2jobname(key)
cfg.hardware.configfile = names.key2jobname(key) + '.cfg'
jobgraph.add_job(cfg.hardware.testfile, cfg, [cfg.hardware.datafile])
return cfg
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)
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)
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)
def config_data(key):
cfg_id = key[-2]
cfg = config.exps[cfg_id]
cfg.exp.expname = key[1]
cfg.exp.key = key
cfg.exp.stage = 'primary' if key[0] == names.kPrimaryData else 'secondary'
cfg.hardware.datafile = names.key2jobname(key)
cfg.hardware.configfile = names.key2jobname(key) + '.cfg'
if cfg.exp.stage == 'primary':
jobgraph.add_job(cfg.hardware.datafile, cfg)
else:
assert cfg.exp.stage == 'secondary'
cat, primname, prim_id, secname, sec_id, rep = key
cfg.hardware.primaryfile = names.key2jobname((names.kPrimaryData, primname, prim_id, rep))
jobgraph.add_job(cfg.hardware.datafile, cfg, [cfg.hardware.primaryfile])
return cfg
def config_data(key):
cfg_id = key[-2]
cfg = config.exps[cfg_id]
cfg.exp.expname = key[1]
cfg.exp.key = key
cfg.exp.stage = 'primary' if key[0] == names.kPrimaryData else 'secondary'
cfg.hardware.datafile = names.key2jobname(key)
cfg.hardware.configfile = names.key2jobname(key) + '.cfg'
if cfg.exp.stage == 'primary':
jobgraph.add_job(cfg.hardware.datafile, cfg)
else:
assert cfg.exp.stage == 'secondary'
cat, primname, prim_id, secname, sec_id, rep = key
cfg.hardware.primaryfile = names.key2jobname(
(names.kPrimaryData, primname, prim_id, rep))
jobgraph.add_job(cfg.hardware.datafile, cfg,
[cfg.hardware.primaryfile])
return cfg
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)
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)
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)
def omega(t_max, exp_id):
tick_p, avg_p, std_p = prim_res[exp_id]
tick_s, avg_s, std_s = sec_res[exp_id]
assert tick_s == tick_p
err_p = sum(a for t, a in zip(tick_p, avg_p) if t <= t_max)
err_s = sum(a for t, a in zip(tick_s, avg_s) if t <= t_max)
#print err_p/err_s
return (err_p-err_s)/err_p
if __name__ == '__main__':
prim_res = datafile.load_results(names.key2jobname((names.kPrimaryResults, primname)))['results']
sec_res = datafile.load_results(names.key2jobname((names.kSecondaryResults, primname, source, secname)))['results']
labels = ['source', 'symmetric', 'bigger', 'distal',
'heavy cube', 'light cube', 'corner base', 'center base',
'source', 'distal']
for i in range(10):
# print("Omega 1000 {} = {:2.3f}".format(i, omega( 700, i)))
print("Omega 2000 {} = {:+2.3f} ({})".format(i, omega( 2000, i), labels[i]))
print("Omega10000 {} = {:+2.3f} ({})".format(i, omega(10000, i), labels[i]))
# negative transfer of corner base
tick_p, avg_p, std_p = prim_res[6]
def config_results(key, jobdep):
cfg = treedict.TreeDict()
cfg.exp.key = key
cfg.hardware.configfile = names.key2jobname(key) + '.cfg'
jobgraph.add_job(names.key2jobname(key), cfg, dependencies = jobdep)
return cfg
def config_results(key, jobdep):
cfg = treedict.TreeDict()
cfg.exp.key = key
cfg.hardware.configfile = names.key2jobname(key) + '.cfg'
jobgraph.add_job(names.key2jobname(key), cfg, dependencies=jobdep)
return cfg
