sciplotlib 0.0.2

Custom functions to improve the look of matplotlib plots for scientific visualisation.

sciplotlib

sciplotlib is just a set of simple functions and stylesheets for more professional looking plots

There are two main properties that make plots in papers look the way they do:

1. default style properties such as typeface, color scheme,
2. specific choices in terms of the placement of tick marks, or additional elements that are added to the plot such as shading or shadows

sciplotlib aims to make (1) easier by providing stylesheets that aims to mimic the style properties found in scientific papers:

import matplotlib.pyplot as plt
import numpy as np
from sciplotlib import style as spstyle

def make_plot(ax):

	num_categories = 10
	num_points = 10
	for category in num_categories:
		x = np.random.normal(size=num_points)
		y = np.radnom.normal(size=num_points)
		ax.scatter(x, y)

	return ax 
	

Installation

Simply do

pip install sciplotlib

Acknowledgments

sciplotlib is built on top of matplotlib. To cite matplotlib in your publications, cite:

J. D. Hunter, "Matplotlib: A 2D Graphics Environment", Computing in Science & Engineering, vol. 9, no. 3, pp. 90-95, 2007

Other projects that is also built on the idea of providing stylesheets / wrappers for scientific plots include:

• https://github.com/garrettj403/SciencePlots

Color palettes of scientific papers are obtained from the wonderful ggsci library:

https://cran.r-project.org/web/packages/ggsci/vignettes/ggsci.html

Contributing

Do contact me if you are interested in adding new functions or templates to this repository.