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))