Style and plotting tools for matplotlib.
Download this repository and run:
python3 ./setup.py develop --user
In the case this fails it is also possible to install it using
python3 -m pip install -U .
If neither of the methods succeed for you can contact @hsvidras on rocket chat, or [email protected]
The matplotlib style can be installed in the stylelib folder:
./stylelib/install_mlp_style.sh
After installation you can use the style with matplotlib:
import matplotlib.pyplot as plt
plt.style.use('belle2')One of the main features is the hist function, which can be used like matplotlib analogon, but has additional features, such as remembering the x-axis binning.
import b2plot
b2plot.hist(np.random.normal(0, 0.5, 1000))
b2plot.labels("O", "Entries", "Unit")As the x-axis is stored, once you plot multible histograms or error bars on the same plot, all share the binning of the first.
import b2plot as bp
bp.hist(np.random.normal(0, 0.5, 1000), label="Pseudo Simulation")
bp.errorhist(np.random.normal(0, 0.5, 1000), label="Pseudo Data", color='black')
bp.labels("O", "Entries", "Unit")
plt.legend()
Predefined styles make it easy to plot different histogram into one plot.
bp.hist(np.random.normal(0, 0.4, 1000), range=(-1, 8), label="None")
for i in range(6):
bp.hist(np.random.normal(1+i, 0.4, 1000), style=i, label="Style %d"%i)
Another feature is to create stacked histograms easily.
# Assuming a dataframe with columns "mass" and "exp"
bp.stacked(df, col="mass", by='exp', bins=50,)