def __init__(self, path, keys, train_frac=0.6, val_frac=0.2):
self._path = path
self._files = glob(path)
self._idx = {'train': 0, 'val': 0, 'test': 0}
self.keys = keys
self._fracs = {
'train': (0, train_frac),
'val': (train_frac, train_frac + val_frac),
'test': (train_frac + val_frac, 1)
}
self.plotter = utils.Plotter()
def plot(binning, fn, samples, outpath, xlabel=None, ylabel=None):
hists = {}
for s in samples:
h = utils.NH1(binning)
if type(fn) == int:
h.fill_array(s.X[s.vidx, fn], weights=s.W[s.vidx])
else:
h.fill_array(fn(s), weights=s.W[s.vidx])
h.scale()
hists[s.name] = h
p = utils.Plotter()
for i, s in enumerate(samples):
p.add_hist(hists[s.name], s.name, i)
_make_parent(outpath)
p.plot(xlabel=xlabel, ylabel=ylabel, output=outpath)
p.plot(xlabel=xlabel, ylabel=ylabel, output=outpath + '_logy', logy=True)
p.clear()
return hists
def __init__(self, n_input=1):
self.n_input = n_input
self.plotter = utils.Plotter()
self.roc = utils.Roccer()
environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
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',
]
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))
