单元4：Matplotlib库入门

matplotlib.pyplot是绘制各类可视化图形的命令子库，相当于快捷方式

import matplotlib.pyplot as plt

#-*- coding: utf-8 -*-

"""Created on Fri Aug 2 10:03:57 2019

@author: ASUS"""

importmatplotlib.pyplot as plt

plt.plot([0,2,4,6,8],[3,1,4,5,2])#x,y轴坐标

plt.ylabel("grade")

plt.xlabel("haha")

plt.axis([0,8,0,6])#x,y轴范围

plt.savefig('test1',dpi=600)

plt.show

plt.subplot(nrows,nclos,plot_number)

#-*- coding: utf-8 -*-

"""Created on Fri Aug 2 10:03:57 2019

@author: ASUS"""

importnumpy as npimportmatplotlib.pyplot as pltdeff(t):return np.exp(-t)*np.cos(2*np.pi*t)

a= np.arange(0.0,5.0,0.02)

plt.subplot(211)

plt.plot(a,f(a))

plt.subplot(2,1,2)

plt.plot(a,np.cos(2*np.pi*a),'r--')

plt.show()

plt.plot(x,y,format_string,**kwargs)

format_string:控制曲线的格式字符串，可选

颜色字符：

风格字符：

标记字符：

color:控制颜色，color='green'

linestyle:线条颜色，linestyle='dashed'

marker:标记风格，marker='o'

markerfacecolor:标记颜色，markerfacecolor='blue'

markersize:标记尺寸

**kwargs：第二组或更多

中文显示：

第一种方法：pyplot并不默认支持中文显示，需要rcParams修改字体实现

#-*- coding: utf-8 -*-

"""Created on Fri Aug 2 10:03:57 2019

@author: ASUS"""

importnumpy as npimportmatplotlib.pyplot as pltimportmatplotlib

matplotlib.rcParams['font.family']='SimHei'

#'font.family'用于显示字体的名字#'font.style'字体风格，正常'normal'或斜体'italic'#'font-size'字体大小，整数字号或者'large'、'x-small'

a = np.arange(10)

plt.plot(a,a*1.5,'go-',a,a*2.5,'rx',a,a*3.5,'*',a,a*4.5,'b-.')

plt.ylabel("纵轴(值)")

plt.show()

第二种办法：

fontproperties

#-*- coding: utf-8 -*-

"""Created on Fri Aug 2 10:03:57 2019

@author: ASUS"""

importnumpy as npimportmatplotlib.pyplot as plt#import matplotlib

a= np.arange(0.0,5.0,0.02)

plt.xlabel("横轴：时间",fontproperties='SimHei',fontsize=20)

plt.ylabel("纵轴：振幅",fontproperties='SimHei',fontsize=10)

plt.plot(a,np.cos(2*np.pi*a),'r--')

plt.show()

#会遇到负号显示乱码

#添加plt.rcParams['axes.unicode_minus'] = False 即可

文本显示函数：

plt.tiltle()  对图形整体增加文本标签

plt.text() 在任意位置增加文本

plt.annotate(s,xy=arrow_crd,xytext=text_crd,arrowprops=dict) 在图形中增加带箭头的注解

importnumpy as npimportmatplotlib.pyplot as plt#import matplotlib

a= np.arange(0.0,5.0,0.02)

plt.plot(a,np.cos(2*np.pi*a),'r--')

plt.rcParams['axes.unicode_minus'] =False

plt.xlabel("横轴：时间",fontproperties='SimHei',fontsize=15,color='green')

plt.ylabel("纵轴：振幅",fontproperties='SimHei',fontsize=15)

plt.title(r'正弦波实例$y=cos(2\pi x)$',fontproperties='SimHei',fontsize=25)

plt.text(2,1,r'$\nu=100$',fontsize=15)#plt.annotate(r'$\mu=100$',xy=(2,1),xytext=(3,1.5),arrowprops=dict(facecolor='black',shrink=0.1,width=2))

plt.axis([-1,6,-2,2])

plt.grid(True)

plt.savefig('test2')

plt.show()

pyplot子绘图区域

plt.subplot2grid(GridSpec,CurSpec,colspan=1,rowspan=1)

或

importmatplotlib.pyplot as pltimportmatplotlib.gridspec as gridspec

gs= gridspec.GridSpec(3,3)

ax1=plt.subplot(gs[0,:])

ax2= plt.subplot(gs[1,:-1])

ax3= plt.subplot(gs[1:,-1])

ax2= plt.subplot(gs[2,0])

ax2= plt.subplot(gs[2,1])

plt.savefig('test3')

单元5：Matplotlib基础绘图函数示例

pyplot饼图的绘制

#-*- coding: utf-8 -*-

"""Spyder Editor

This is a temporary script file."""

importmatplotlib.pyplot as plt

labels= 'Frogs','Hogs','Dogs','Logs'sizes= [15,30,45,10]

explode= (0,0.1,0,0)

plt.pie(sizes,explode=explode,labels = labels,autopct='%1.1f%%',shadow=False,startangle=90)

plt.axis('equal')

plt.show()

pyplot直方图的绘制

#-*- coding: utf-8 -*-

"""Spyder Editor

This is a temporary script file."""

importnumpy as npimportmatplotlib.pyplot as plt

np.random.seed(0)

mu,sigma= 100,20a= np.random.normal(mu,sigma,size=100)

plt.hist(a,40,normed=0,histtype='stepfilled',facecolor='b',alpha=0.75)#直方图的个数

#normed = 1概率，normed = 0,个数

plt.title('Histogram')

plt.show()

pyplot极坐标图

importnumpy as npimportmatplotlib.pyplot as plt

N= 20theta= np.linspace(0.0,2*np.pi,N,endpoint=False)

radii= 10*np.random.rand(N)

width= np.pi / 4*np.random.rand(N)

ax= plt.subplot(111,projection='polar')

bars= ax.bar(theta,radii,width=width,bottom=0.0)#left height width

for r,bar inzip(radii,bars):

bar.set_facecolor(plt.cm.viridis(r/10.))

bar.set_alpha(0.5)

plt.savefig('test')

plt.show()

pyplot散点图绘制

importnumpy as npimportmatplotlib.pyplot as plt

fig,ax=plt.subplots()

ax.plot(10*np.random.randn(100),10*np.random.randn(100),'o')

ax.set_title('Simple Scatter')

plt.show()