def __init__(self, n_input=1):
self.n_input = n_input
self.plotter = utils.Plotter()
self.roc = utils.Roccer()
environ["CUDA_VISIBLE_DEVICES"] = ""
import numpy as np
import extra_vars
from subtlenet import config, utils
from subtlenet.backend import obj
from subtlenet.generators.gen import make_coll
basedir = environ['BASEDIR']
figsdir = environ['FIGSDIR']
n_batches = 500
partition = 'test'
p = utils.Plotter()
r1 = utils.Roccer(y_range=range(-5, 1))
r2 = utils.Roccer(y_range=range(-4, 1))
OUTPUT = figsdir + '/'
system('mkdir -p %s' % OUTPUT)
components = [
'singletons',
'shallow',
'baseline2_7_100',
'kltest_7_100',
'categorical_crossentropy2_7_100',
'categorical_crossentropytest2_7_100',
'categorical_crossentropytesttest2_7_100',
]
bkg_hists['N2'] = roccer_hists_SS['N2'][BKG]
#sig_hists['deepTagZqq'] = roccer_hists_SS['deepTagZqq'][SIG]
#bkg_hists['deepTagZqq'] = roccer_hists_SS['deepTagZqq'][BKG]
for model in models:
for i in xrange(len(samples) if MULTICLASS else 2):
roccer_hists = plot(np.linspace(0, 1, 50),
lambda s, i=i: s.Yhat[model][s.vidx, i],
samples,
figsdir + 'class_%i_%s' % (i, model),
xlabel='Class %i %s' % (i, model))
sig_hists[model] = roccer_hists[SIG]
bkg_hists[model] = roccer_hists[BKG]
r1 = utils.Roccer(
y_range=range(0, 1),
axis=[0, 1, 0, 1],
)
#r1.clear()
r1.add_vars(sig_hists, bkg_hists, {
'Dense': 'Dense',
'GRU': 'GRU',
'N2': 'N2',
}
#'deepZqq':'deepZqq'}
)
r1.plot(figsdir + 'class_%s_ROC' % (str(args.version)))
environ['KERAS_BACKEND'] = 'tensorflow'
environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
environ["CUDA_VISIBLE_DEVICES"] = ""
import numpy as np
from subtlenet import config, utils
from subtlenet.backend import obj
from subtlenet.generators.gen import make_coll
n_batches = 500
partition = 'test'
p = utils.Plotter()
r = utils.Roccer()
OUTPUT = environ['FIGSDIR'] + '/'
system('mkdir -p %s'%OUTPUT)
components = [
'singletons',
'shallow_best',
# 'trunc4_limit50_best',
'trunc7_limit100_best',
]
components_gen = [
'singletons',
'shallow_best',
# 'baseline_trunc4_limit50_best',
'baseline_Adam_7_100',
environ["CUDA_VISIBLE_DEVICES"] = ""
import numpy as np
import extra_vars
from subtlenet import config, utils
from subtlenet.backend import obj
from subtlenet.generators.gen import make_coll
basedir = environ['BASEDIR']
figsdir = environ['FIGSDIR']
n_batches = 500
partition = 'test'
p = utils.Plotter()
r = utils.Roccer(y_range=range(-4, 1))
OUTPUT = figsdir + '/'
system('mkdir -p %s' % OUTPUT)
components = [
'singletons',
'shallow',
# 'baseline_trunc4_limit50_clf_best',
# 'decorrelated_trunc4_limit50_clf_best',
# 'mse_decorrelated_trunc4_limit50_clf_best',
# 'emd_decorrelated_trunc4_limit50_clf_best',
# 'baseline_4_50',
# 'baseline_Adam_4_10',
'baseline_Adam_4_50',
'baseline_Adam_4_100',
def __init__(self, n_input=2, n_output=1):
self.n_input = n_input
self.n_output = n_output
self.plotter = utils.Plotter()
self.roc = utils.Roccer(y_range=range(-1,1))