matplotlib

Matplotlib Figure, Axis and Legend

Written on May 07, 2017 | Tags: matplotlib python

Convention

For convenience, we usually shorten the matplotlib.pyplot as plt. And you need to import the package in python before you can use it. Best environment is to use jupyter notebook, which you can run your python code and see the result. Import following two pacakge to start.

import matplotlib.pyplot as plt
import numpy as np

Basic

x = np.linspace(-1,1,50) # put 50 points in [-1, 1]
y = 2 * x # our function
plt.plot(x, y) # plot the graph / create matplotlib object
plt.show() # show it

In jupyter notebook, one thing to mention is you can put %matplotlib inline alongside with other import statment. Then jupyter notebook will automatically show the graph. Instand of typing plt.show(), to actually show it.

Figure

In matplotlib, figure is the container for our graph. Continue with previous example, if we want to plot two different functions in two different graph. Or graph two different function in same figure

x = np.linspace(-3, 3, 50)
y1 = 2 * x + 1
y2 = x ** 2
y3 = x ** 3

# create a figure, when not numbered with `num=1`
# system will automatically name it by 1, 2, 3, 4...
# set figure, and all following will be graph in same figure
plt.figure(num=1)
plt.plot(x, y1)

# create another figure
# setting figure size by using `figsize`
plt.figure(num=2, figsize=(8,5))
plt.plot(x, y2)
# set color, line width, and line style `--` is dash line
plt.plot(x, y3, color='red', linewidth=3.0, linestyle='--')

Axis

x = np.linspace(-3, 3, 50)
y1 = 2 * x + 1
y2 = x ** 2

plt.figure()
plt.plot(x,y1)
plt.plot(x,y2)

# set x, y shown value range
plt.xlim((-1,2))
plt.ylim((-2,3))

# show x, y axis label
plt.xlabel("X label")
plt.ylabel("Y label")

# show ticks, or matching with text
plt.xticks([-1,0,1,2])
# divide y axis [-2,3] to 5 pa
plt.yticks(np.linspace(-2,3,5),['really bad','bad','normal','good','really good'])

# Moving axis
# gca: get current axis
ax = plt.gca()

# do not show frame/spine of our graph
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

# set ticks position to left and bottom spine
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

# move x-axis start with y=-1 position
# move y-axis start with x=0 position
ax.spines['bottom'].set_position(('data',-1))
ax.spines['left'].set_position(('data',0))

Legend

x = np.linspace(-10, 10, 100)
y1 = 2 * x + 1
y2 = x ** 2

plt.figure()
plt.xlim((-1,2))
plt.ylim((-2,3))
l1, = plt.plot(x, y1, label='y1')
l2, = plt.plot(x, y2, linestyle='--', label='y2')

# loc can let matplotlib chose best `loc='best'`
plt.legend(handles=[l1,l2],labels=['2x+1','x^2'],loc='lower right')