diptaparna / b2plot

b2plot

Description

Style and plotting tools for matplotlib.

Installation

Download this repository and run:

python3 ./setup.py develop --user

The matolotlib style can be installed in the sytlelib folder:

./install_mlp_style.sh

Usage

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,)