def test_plotgrid():
# histogram creation and manipulation
from coffea import hist
# matplotlib
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
lepton_kinematics = fill_lepton_kinematics()
# Let's stack them, after defining some nice styling
stack_fill_opts = {'alpha': 0.8, 'edgecolor': (0, 0, 0, .5)}
stack_error_opts = {
'label': 'Stat. Unc.',
'hatch': '///',
'facecolor': 'none',
'edgecolor': (0, 0, 0, .5),
'linewidth': 0
}
# maybe we want to compare different eta regions
# plotgrid accepts row and column axes, and creates a grid of 1d plots as appropriate
fig, ax = hist.plotgrid(
lepton_kinematics,
row="eta",
overlay="flavor",
stack=True,
fill_opts=stack_fill_opts,
error_opts=stack_error_opts,
)
def test_plotgrid():
# histogram creation and manipulation
from coffea import hist
# matplotlib
import matplotlib.pyplot as plt
plt.switch_backend("agg")
lepton_kinematics = fill_lepton_kinematics()
# Let's stack them, after defining some nice styling
stack_fill_opts = {"alpha": 0.8, "edgecolor": (0, 0, 0, 0.5)}
stack_error_opts = {
"label": "Stat. Unc.",
"hatch": "///",
"facecolor": "none",
"edgecolor": (0, 0, 0, 0.5),
"linewidth": 0,
}
# maybe we want to compare different eta regions
# plotgrid accepts row and column axes, and creates a grid of 1d plots as appropriate
axs = hist.plotgrid(
lepton_kinematics,
row="eta",
overlay="flavor",
stack=True,
fill_opts=stack_fill_opts,
error_opts=stack_error_opts,
)
return axs.flatten()[0].figure
}
histo.scale(scales, axis='sample')
#display(histo.identifiers('sample'))
#display(histo.identifiers('x'))
## Write root files
'''
import uproot
import os
if os.path.exists("output.root"):
os.remove("output.root")
outputfile = uproot.create("output.root")
h = histo.sum('x', 'y')
for sample in h.identifiers('sample'):
print(sample)
outputfile[sample.name] = hist.export1d(h.integrate('sample', sample))
outputfile.close()
'''
## Plotting
hnew = (histo.rebin("y",
hist.Bin("ynew", "rebinned y value", [0, 3, 5])).rebin(
"z", hist.Bin("znew", "rebinned z value", [5, 8, 10])))
hist.plotgrid(hnew, row='ynew', col='znew', overlay='sample')
plt.show()