def __init__(self, *args, **kwargs):
TransformationBundleLegacy.__init__(self, *args, **kwargs)
self.init_indices()
if self.idx.ndim() > 1:
raise self.exception('expect 0d/1d index')
self.groups = Categories(self.cfg.get('groups', {}), recursive=True)
class root_histograms_v03(TransformationBundle):
def __init__(self, *args, **kwargs):
TransformationBundle.__init__(self, *args, **kwargs)
self.check_nidx_dim(0, 1, 'major')
self.check_nidx_dim(0, 0, 'minor')
self.groups = Categories(self.cfg.get('groups', {}), recursive=True)
@staticmethod
def _provides(cfg):
return (), (cfg.name, )
def build(self):
file = R.TFile(self.cfg.filename, 'READ')
if file.IsZombie():
raise Exception('Can not read ROOT file ' + file.GetName())
print('Read input file {}:'.format(file.GetName()))
for it in self.nidx.iterate():
if it.ndim() > 0:
subst, = it.current_values()
else:
subst = ''
hname = self.groups.format(subst, self.cfg.format)
h = file.Get(hname)
if not h:
raise Exception('Can not read {hist} from {file}'.format(
hist=hname, file=file.GetName()))
print(' read{}: {}'.format(' ' + subst, hname), end='')
edges = get_bin_edges_axis(h.GetXaxis())
data = get_buffer_hist1(h)
if self.cfg.get('normalize', False):
print(' [normalized]')
data = N.ascontiguousarray(data, dtype='d')
data = data / data.sum()
else:
print()
fmt = self.cfg.get('label', 'hist {name}\n{autoindex}')
hist = Histogram(edges,
data,
labels=it.current_format(fmt, name=self.cfg.name))
self.set_output(self.cfg.name, it, hist.single())
self.context.objects[('hist', subst)] = hist
file.Close()
def __init__(self, *args, **kwargs):
TransformationBundle.__init__(self, *args, **kwargs)
self.check_nidx_dim(0, 1, 'major')
self.check_nidx_dim(0, 0, 'minor')
self.groups = Categories(self.cfg.get('groups', {}), recursive=True)
class root_histograms_v05(TransformationBundle):
"""Load ROOT histograms from ROOT files v05
Updates:
v04 - scale X/Y axes with 'xscale' and 'yscale' options
v05 - Read a bunch of histograms
"""
def __init__(self, *args, **kwargs):
TransformationBundle.__init__(self, *args, **kwargs)
self.check_nidx_dim(0, 1, 'major')
self.check_nidx_dim(0, 0, 'minor')
self.groups = Categories(self.cfg.get('groups', {}), recursive=True)
@staticmethod
def _provides(cfg):
return (), tuple(cfg.names)
def build(self):
file = R.TFile( self.cfg.filename, 'READ' )
if file.IsZombie():
raise Exception('Can not read ROOT file '+file.GetName())
print( 'Read input file {}:'.format(file.GetName()) )
normalize=self.cfg.get('normalize', False)
xscale = self.cfg.get('xscale', None)
yscale = self.cfg.get('yscale', None)
for name, format, labelfmt in I.zip_longest(self.cfg.names, self.cfg.formats, self.cfg.get('labels', [])):
for it in self.nidx.iterate():
if it.ndim()>0:
subst, = it.current_values()
else:
subst = ''
hname = self.groups.format(subst, format)
h = file.Get(hname)
if not h:
raise Exception('Can not read {hist} from {file}'.format(hist=hname, file=file.GetName()))
print( ' read{}: {}'.format(' '+subst if subst else '', hname), end=' ' )
edges = get_bin_edges_axis( h.GetXaxis() )
data = get_buffer_hist1( h )
if normalize:
print( '[normalized]', end=' ' )
data=N.ascontiguousarray(data, dtype='d')
data=data/data.sum()
else:
print()
if xscale is not None:
print( '[xscale]', end=' ' )
edges*=xscale
if yscale is not None:
print( '[yscale]', end=' ' )
data*=yscale
print()
if labelfmt is None:
labelfmt = 'hist {name}\n{autoindex}'
hist=Histogram(edges, data, labels=it.current_format(labelfmt, name=name))
self.set_output(name, it, hist.single())
self.context.objects[('hist',subst)] = hist
file.Close()