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import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

def keynote_style(ax=None):
    if ax is None:
        ax = plt.gca()
    ax.grid(which="major", axis="y")
    ax.set_axisbelow(True)
    for k in ["left", "right", "top"]:

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# requires
# numpy, PIL (and IPython, if you keep in the HTML repr stuff)

import itertools
import numpy as np

def _image_from_clipboard(algo="png"):
    if algo == "jpeg":
        from PIL import ImageGrab
        im = ImageGrab.grabclipboard().convert("RGB")

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Tree information

Open data DoubleMuon dataset: ~62M events, 150M muons, ~2GB with zlib

Converted to uncompressed, LZ4, LZMA versions with

hadd -O -f0 uncompressed_Run2012BC_DoubleMuParked_Muons.root Run2012BC_DoubleMuParked_Muons.root

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This macro will pass through definitions of FHist histograms and make a dictionary encapsulating them.

macro histcollection(ex)
    hists = Symbol[]
    for line in ex.args
        !hasproperty(line, :head) && continue
        line.head !== :(=) && continue
        varname, varbody = line.args[1:2]
        varbody.args[1] ∉ (:Hist1D, :Hist2D) && continue
 push!(hists, varname)

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