matplotlib 常用操作

Posted 2020-10-21 所有的遗憾都是成全

标准的Python中用列表(list)保存一组值，可以当作数组使用。但由于列表的元素可以是任何对象，因此列表中保存的是对象的指针。这样一来，为了保存一个简单的列表[1,2,3]，就需 
要有三个指针和三个整数对象。对于数值运算来说，这种结构显然比较浪费内存和 CPU 计算时间。

使用numpy的array模块可以解决这个问题。细节不在此赘述。这里主要记录一些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()