matplotlib 經常使用操做

標準的Python中用列表(list)保存一組值，能夠看成數組使用。但因爲列表的元素能夠是任何對象，所以列表中保存的是對象的指針。這樣一來，爲了保存一個簡單的列表[1,2,3]，就需 
要有三個指針和三個整數對象。對於數值運算來講，這種結構顯然比較浪費內存和 CPU 計算時間。

使用numpy的array模塊能夠解決這個問題。細節不在此贅述。這裏主要記錄一些matplotlib的基本使用方法

first plot

#first plot with matplotlib import matplotlib.pyplot as plt plt.plot([1,3,2,4]) plt.show()

in order to avoid pollution of global namespace, it is strongly recommended to never import like:

from import *

simple plot

import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np x = np.arange(0.0,6.0,0.1) plt.plot(x, [xi**2 for xi in x],label = 'First',linewidth = 4,color = 'black') plt.plot(x, [xi**2+2 for xi in x],label = 'second',color = 'red') plt.plot(x, [xi**2+5 for xi in x],label = 'third') plt.axis([0,7,-1,50]) plt.xlabel(r"$\alpha$",fontsize=20) plt.ylabel(r'y') plt.title('simple plot') plt.legend(loc = 'upper left') plt.grid(True) plt.savefig('simple plot.pdf',dpi = 200) print mpl.rcParams['figure.figsize'] #return 8.0,6.0 print mpl.rcParams['savefig.dpi'] #default to 100 the size of the pic will be 800*600 #print mpl.rcParams['interactive'] plt.show()

Python-3

Decorate plot with styles and types

import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np x = np.arange(0.0,6.0,0.1) plt.plot(x, [xi**2 for xi in x],label = 'First',linewidth = 4,color = 'black') #using color string to specify color plt.plot(x, [xi**2+2 for xi in x],'r',label = 'second') #using abbreviation to specify color plt.plot(x, [xi**2+5 for xi in x],color = (1,0,1,1),label = 'Third') #using color tuple to specify color plt.plot(x, [xi**2+9 for xi in x],color = '#BCD2EE',label = 'Fourth') #using hex string to specify color plt.xticks(np.arange(0.0,6.0,2.5)) plt.xlabel(r"$\alpha$",fontsize=20) plt.ylabel(r'y') plt.title('simple plot') plt.legend(loc = 'upper left') plt.grid(True) plt.savefig('simple plot.pdf',dpi = 200) print mpl.rcParams['figure.figsize'] #return 8.0,6.0 print mpl.rcParams['savefig.dpi'] #default to 100 the size of the pic will be 800*600 #print mpl.rcParams['interactive'] plt.show(

 
image

types of graph

• 2

image

Bars

import matplotlib.pyplot as plt 

import numpy as np 

dict = {'A': 40, 'B': 70, 'C': 30, 'D': 85} 

for i, key in enumerate(dict): plt.bar(i, dict[key]);

plt.xticks(np.arange(len(dict))+0.4, dict.keys());

plt.yticks(dict.values());

plt.grid(True)

plt.show()

image_1

Pies

import matplotlib.pyplot as plt 

plt.figure(figsize=(10,10));

x = [4, 9, 21, 55, 30, 18] 

labels = ['Swiss', 'Austria', 'Spain', 'Italy', 'France', 

'Benelux'] 

explode = [0.2, 0.1, 0, 0, 0.1, 0] 

plt.pie(x, labels=labels, explode=explode, autopct='%1.1f%%'); 

plt.show()

image_2

Scatter

import matplotlib.pyplot as plt

import numpy as np

x = np.random.randn(12,20)

y = np.random.randn(12,20)

mark = ['s','o','^','v','>','<','d','p','h','8','+','*']

for i in range(0,12):

    plt.scatter(x[i],y[i],marker = mark[i],color =(np.random.rand(1,3)),s=50,label = str(i+1))

plt.legend()

plt.show()