Last modified: Oct, 2015

General info
A typical plotting script using Matplotlib
This script tries to do the similar task with the example script in Matlab .

import numpy as np
import matplotlib.pyplot as plt
#plt.close()
plt . figure ( 1 , figsize = ( 10 , 8 )) # figure size 10" by 8"
ax = plt . subplot ( 111 )
x = np . linspace ( 0 , 2 * np . pi , 100 )
y1 = np . sin ( x )
y2 = np . cos ( x )
lines = plt . plot ( x , y1 , 'b-' , x , y2 , 'r--' )
plt . setp ( lines , 'linewidth' , 3 )
plt . xlabel ( 'x' )
plt . ylabel ( 'y' )
plt . xlim ([ 0 , 2 * np . pi ])
plt . ylim ([ - 2 , 2 ])
ax . xaxis . label . set_fontsize ( 18 ) # set x-axis label font size
ax . yaxis . label . set_fontsize ( 18 ) # set y-axis label font size
for item in ( ax . get_xticklabels () + ax . get_yticklabels ()):
item . set_fontsize ( 18 ) # set axis tick font size
plt . legend ([ 'sin(x)' , 'cos(x)' ], loc = 'lower left' , prop = { 'size' : '20' }) # loc: legend location
plt . show ()

Plot multiple y axes/scales in a single plot
See the official example here , using ax.twinx(). My example:

plt . figure ( 1 , figsize = ( 10 , 8 ))
ax = plt . subplot ( 111 )
plt . plot ( t1 , f1 )
plt . xlabel ( 't' )
plt . ylabel ( 'f' )
plt . ylim ([ 0 , 1000 ])
plt . legend ([ "f1" ], loc = "upper left" )
ax . xaxis . label . set_fontsize ( 18 ) # set x-axis label font size
ax . yaxis . label . set_fontsize ( 18 ) # set y-axis label font size
for item in ( ax . get_xticklabels () + ax . get_yticklabels ()):
item . set_fontsize ( 18 ) # set axis tick font size
ax2 = ax . twinx ()
plt . plot ( t1 , T1 , '--r' )
plt . legend ([ "T" ], loc = "upper right" )
plt . ylabel ( 'T' )
plt . ylim ([ - 5 , 60 ])
ax2 . xaxis . label . set_fontsize ( 18 ) # set x-axis label font size
ax2 . yaxis . label . set_fontsize ( 18 ) # set y-axis label font size
for item in ( ax2 . get_xticklabels () + ax2 . get_yticklabels ()):
item . set_fontsize ( 18 ) # set axis tick font size

Import data
Alternative to the “importdata” function in Matlab, Numpy has “loadtxt”. For exapmle:
import numpy as np
data = np . loadtxt ( 'data.dat' , skiprows = 1 ) # skip the first row during the import

Add text to plots
Usually there are two ways:

Use matplotlib.pyplot.text(xpos, ypos, string). For example:
import numpy as np
import matplotlib.pyplot as plt
plt . text ( 1 , 2 , 'this is text' )

Extra manipulation such as text wrapping can be found here .

Use matplotlib.pyplot.annotate. Refer to this link .
Use TeX for rendering text
import matplotlib.pyplot as plt
plt . rc ( 'text' , usetex = True )

Working with directory
Sometimes one needs to import many data files to the workspace and plot. This can be realized with the help of package “glob” which is capable of matching wildcards in path patterns. For example,

import numpy as np
import matplotlib.pyplot as plt
import glob
data_files = glob . glob ( 'data*.dat' )
# data_files will be a string array containing all files matching 'data*.dat' pattern
plt . figure ( 1 )
for d in data_files :
data = np . loadtxt ( d )
plt . loglog ( data [:, 0 ], data [:, 1 ]) # assuming data is a 2D array
plt . show ()