Produce publication-level quality images on top of Matplotlib
Project description
Erwan Pannier - EM2C Laboratory, CentraleSupélec / CNRS UPR 288
Description
Produce publication-level quality images on top of Matplotlib, with a simple call to couple functions at the start and end of your script.
For similar librairies, see seaborn, which also add neat high-end API to Matplotlib function calls.
Use
At the beginning of the script, call:
set_style()
After each new axe is plotted, call:
fix_style()
Note that importing publib will already load the basic style.
A few more styles (‘poster’, ‘article’, etc.) can be selected with the function set_style()
Because some matplotlib parameters cannot be changed before the lines are plotted, they are called through the function fix_style() which:
changes the minor ticks
remove the spines
turn the legend draggable by default
Examples
import numpy as np
import matplotlib.pyplot as plt
A default Matplotlib plot:
x = np.linspace(0,5,250)
y = np.cos(x)**2+np.random.normal(scale=0.5,size=len(x))
yav = np.cos(x)**2
plt.figure()
ax = plt.subplot()
ax.plot(x,y,'o',label='normal distribution')
ax.plot(x,yav,zorder=-1,label='average')
plt.xlabel(r'$x$')
plt.ylabel(r'$\cos^2 x$+noise')
plt.title('matplotlib')
plt.legend(loc='upper left')
plt.ylim((-1.5,3.5))
plt.show()
And now the same code with the two new lines calling the publib functions
from publib import set_style, fix_style
set_style('article') # before the first plot
x = np.linspace(0,5,250)
y = np.cos(x)**2+np.random.normal(scale=0.5,size=len(x))
yav = np.cos(x)**2
plt.figure()
ax = plt.subplot()
ax.plot(x,y,'o',label='normal distribution')
ax.plot(x,yav,zorder=-1,label='average')
plt.xlabel(r'$x$')
plt.ylabel(r'$\cos^2 x$+noise')
plt.title('article')
plt.legend(loc='upper left')
plt.ylim((-1.5,3.5))
plt.show()
fix_style('article') # after the axe has been created
plt.show()
Run the _test() routine in publib.py for more examples.
Changes
0.1.6 : improve Readme 0.1.5 : changed those buff_style functions in fix_style
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