import pandas as pd
import seaborn as sns

from nnfwtbn import Variable, Process, Cut, hist, McStack, DataStack, Stack, \
                    RangeBlindingStrategy
from nnfwtbn import toydata

df = toydata.get()

Cannot find cached data. Recreating toy data. This might take some time...

Processes

p_ztt = Process(r"$Z\rightarrow\tau\tau$", range=(0, 0))
p_sig = Process(r"Signal", range=(1, 1))

p_asimov = Process(r"Asimov", selection=lambda d: d.fpid >= 0)

Stacks

colors = ["windows blue", "amber", "greyish", "faded green", "dusty purple"]
s_mc = McStack(p_ztt, p_sig, palette=sns.xkcd_palette(colors))
s_data = DataStack(p_asimov)

Blinding

b_higgs_m = RangeBlindingStrategy(99, 150)

Variables

v_higgs_m = Variable(r"$m^H$", "higgs_m", "GeV", blinding=b_higgs_m)

Actual plot

Stacks passed to blind argument will be blinded according to blind strategy of variable v_higgs_m.

Blind data stack

hist(df, v_higgs_m, 20, [s_mc, s_data], range=(0, 200),
     weight="weight",  ratio_label="Data / SM", blind=s_data, diff=True)
None

Blind MC stack

hist(df, v_higgs_m, 20, [s_mc, s_data], range=(0, 200),
     weight="weight",  ratio_label="Data / SM", blind=s_mc)
None

Blind both stacks

blind argument can be a single stack or a list of stacks.

hist(df, v_higgs_m, 20, [s_mc, s_data], range=(0, 200),
     weight="weight",  ratio_label="Data / SM", blind=[s_mc, s_data])
None