def __init__(
self ,
channel ,
nn_dir ,
year ,
features ,
composed_features ,
base_dir ,
post_fix ,
dir_suffix ,
selection_data_mmm ,
selection_mc_mmm ,
selection_data_mem ,
selection_mc_mem ,
selection_data_eee ,
selection_mc_eee ,
selection_data_eem ,
selection_mc_eem ,
selection_tight ,
lumi ,
epochs=1000 ,
early_stopping=True,
skip_mc=False,
val_fraction=0.3,
scale_mc=1.):
self.channel = channel.split('_')[0]
self.channel_extra = channel.split('_')[1] if len(channel.split('_'))>1 else ''
self.year = year
self.features = features
self.composed_features = composed_features
self.base_dir = base_dir
self.post_fix = post_fix
self.selection_data_mmm = ' & '.join(selection_data_mmm)
self.selection_mc_mmm = ' & '.join(selection_mc_mmm)
self.selection_data_mem = ' & '.join(selection_data_mem)
self.selection_mc_mem = ' & '.join(selection_mc_mem)
self.selection_data_eee = ' & '.join(selection_data_eee)
self.selection_mc_eee = ' & '.join(selection_mc_eee)
self.selection_data_eem = ' & '.join(selection_data_eem)
self.selection_mc_eem = ' & '.join(selection_mc_eem)
self.selection_tight = selection_tight
self.selection_lnt = 'not (%s)' %self.selection_tight
self.lumi = lumi
self.epochs = epochs
self.early_stopping = early_stopping
self.skip_mc = skip_mc
self.val_fraction = val_fraction
self.scale_mc = scale_mc
self.nn_dir = '/'.join([nn_dir, '_'.join([channel, dir_suffix, get_time_str()]) ])
if self.year==2018:
from plotter.samples.samples_2018 import get_data_samples, get_mc_samples, get_signal_samples
if self.year==2017:
from plotter.samples.samples_2017 import get_data_samples, get_mc_samples, get_signal_samples
if self.year==2016:
from plotter.samples.samples_2016 import get_data_samples, get_mc_samples, get_signal_samples
self.get_data_samples = get_data_samples
self.get_mc_samples = get_mc_samples
self.get_signal_samples = get_signal_samples
def __init__(self,
channel,
year,
plot_dir,
base_dir,
post_fix,
selection_data,
selection_mc,
selection_tight,
pandas_selection,
lumi,
model,
transformation,
features,
process_signals,
plot_signals,
blinded,
datacards=[],
mini_signals=False,
do_ratio=True,
mc_subtraction=True,
dir_suffix='',
relaxed_mc_scaling=1.,
data_driven=True):
self.channel = channel.split('_')[0]
self.year = year
self.full_channel = channel
self.plt_dir = '/'.join(
[plot_dir, channel, '_'.join([dir_suffix,
get_time_str()])])
self.base_dir = base_dir
self.post_fix = post_fix
self.selection_data = ' & '.join(selection_data)
self.selection_mc = ' & '.join(selection_mc)
self.selection_tight = selection_tight
self.pandas_selection = pandas_selection
self.lumi = lumi
self.model = model
self.transformation = transformation
self.features = features
self.process_signals = process_signals
self.plot_signals = plot_signals if self.process_signals else []
self.blinded = blinded
self.selection_lnt = 'not (%s)' % self.selection_tight
self.do_ratio = do_ratio
self.mini_signals = mini_signals
self.datacards = datacards
self.mc_subtraction = mc_subtraction
self.relaxed_mc_scaling = relaxed_mc_scaling
self.data_driven = data_driven
if self.year == 2018:
from plotter.samples.samples_2018 import get_data_samples, get_mc_samples, get_signal_samples
if self.year == 2017:
from plotter.samples.samples_2017 import get_data_samples, get_mc_samples, get_signal_samples
if self.year == 2016:
from plotter.samples.samples_2016 import get_data_samples, get_mc_samples, get_signal_samples
self.get_data_samples = get_data_samples
self.get_mc_samples = get_mc_samples
self.get_signal_samples = get_signal_samples