def test_append(self):
"""Also tests layered=False"""
cut = ROOT.TCut('bar<0')
self.splice.make_splice('bar', cut)
cut = ROOT.TCut('bar>=0')
# this should add the rest of the entries
tree = self.splice.make_splice('bar', cut, append=True)
self.assertEqual(self.nentries, nplotted(tree, 'bar'))
def test_make_splice(self):
cut = ROOT.TCut('foo>10')
nexpected = nplotted(self.splice.reset(), 'foo', cut)
tree = self.splice.make_splice('foo_gt_10', cut)
self.assertEqual(nexpected, nplotted(tree, 'foo'))
cut = ROOT.TCut('bar<0')
nexpected = nplotted(self.splice.reset(), 'bar', cut)
tree = self.splice.make_splice('nve_bar', cut)
self.assertEqual(nexpected, nplotted(tree, 'bar'))
def test_elistarray_splice(self):
# entries with 5 elements in data are guaranteed to pass, for
# other entries, it passes when the passing element is < size,
# which happens 3/5 times (when it is b/w 0-2), it is always
# found for size = 5. Therefore, it is found for at least 4/5
# entries.
cut = ROOT.TCut('(data[]%5)>3')
tree = self.splice.make_splice('data_mod_5',
cut,
listtype='entrylistarray')
expected = nplotted(tree, 'data')
# print self.ndata, self.nentries, expected, 4*self.nentries/5
self.assertLess(expected, self.ndata)
self.assertLess(expected, self.nentries)
self.assertGreater(expected, 4 * self.nentries / 5)
# get tree and perform branch name mappings if necessary
factory.AddSignalTree(tree_s, 1.0)
factory.AddBackgroundTree(tree_b, 1.0)
# apply event weights if necessary
if session.bkgwt:
factory.SetBackgroundWeightExpression(session.bkgwt)
if session.sigwt:
# FIXME: correct weights for ignored events, since sweights:
# MVA weight = sw - (∑sw(M<5310 && M>5430))/entries(M<5310 && M>5430)
factory.SetSignalWeightExpression(session.sigwt)
# selection cuts, if any
session.training_opts += ['!V']
factory.PrepareTrainingAndTestTree(ROOT.TCut(''),
':'.join(session.training_opts))
# book methods
map(lambda method: factory.BookMethod(TMVAType(method), method, '!H:!V:' +
':'.join(getattr(session, method))),
session.methods)
# train, test, evaluate
factory.TrainAllMethods()
factory.TestAllMethods()
factory.EvaluateAllMethods()
ofile.Close()
print '::: Training MVAs done!'
def get_estimate(mva, cut, tree=tree):
cut = ROOT.TCut('{}>{}'.format(mva, cut))
# NOTE: only process 200,000 entries
tree.Draw('{0}>>h{0}'.format(mva), cut, 'goff', options.maxentries)
hist = ROOT.gDirectory.Get('h{}'.format(mva))
return hist.GetEntries()
def test_get_splice(self):
cut = ROOT.TCut('sz==4')
self.splice.make_splice('sz_eq_4', cut)
nexpected = nplotted(self.splice.reset(), 'sz', cut)
tree = self.splice.get_splice('sz_eq_4')
self.assertEqual(nexpected, nplotted(tree, 'sz'))
def test_set_splice(self):
cut = ROOT.TCut('bar>0')
self.splice.make_splice('pve_bar', cut)
nexpected = nplotted(self.splice.reset(), 'bar', cut)
tree = self.splice.set_splice(self.splice.elists['pve_bar'])
self.assertEqual(nexpected, nplotted(tree, 'bar'))
def test_reset(self):
self.splice.make_splice('sz_gt_5', ROOT.TCut('sz>5')) # zero
self.assertEqual(nplotted(self.splice.reset(), 'sz'), self.nentries)
def test_get_entries(self):
tree = self.splice.make_splice('sz_gt_3', ROOT.TCut('sz>3')) # 2/3
self.assertEqual(self.splice.get_entries(), nplotted(tree, 'sz'))