Matplotlib画图基础

Matplotlib画图
目录：
１．根据数据画曲线图
２．带箭头图
３．3D立体图
４．多子图结构
５．饼状图
６．柱状图

import numpy as npimport matplotlib.pyplot as plt%matplotlib inlinedata= np.loadtxt('/home/robot_lcl/lcl_file/train_log/train.log.test')#print datax=data[:,0]y1=data[:,3]y2=data[:,2]#plt.figure(1,figsize=(3,2))fig = plt.figure(figsize=(3,2))ax1 = fig.add_subplot(111)plot1, = ax1.plot(x, y1, 'b', label='$loss')ax1.set_ylabel('test loss')ax1.set_xlabel('iteration')ax2 = ax1.twinx()plot2, = ax2.plot(x, y2, 'r',label='$accuracy')ax2.set_ylabel('test accuracy')plt.legend([plot1, plot2], ( 'loss','accuracy' ) , 'upper center',bbox_to_anchor=(0.85, -0.05),shadow=True, ncol=2)#plt.legend(loc='upper center', bbox_to_anchor=(0.8, -0.05),  shadow=True, ncol=2)plt.savefig('/home/robot_lcl/lcl_file/train_log/accu.png',format='png')plt.show()

２．===annotat格式可参阅网上资料。在通过annotate（）函数画一个标注的箭头；其中的两个位置是箭头和箭尾的坐标，后面是颜色等信息

import matplotlib.pyplot as pltfig = plt.figure(5)plt.figure(1,figsize=(3,2))   #控制宽度和高度；ax = plt.subplot(111)ann = ax.annotate("Test",                 xy=(0.2,0.2),                 xytext=(0.8,0.8),                 size=20, va="center", ha="center",                 bbox=dict(boxstyle="round4", fc="w"),  #字体大小，位置，边框以及前景色                 arrowprops=dict(arrowstyle="-|>",connectionstyle="arc3,rad=0.2",fc="r") #曲线，箭头红色                 )ax.grid(True)plt.show()

<matplotlib.figure.Figure at 0x7ff31dee1e90>

3．　　　3D立体图

import numpy as np  import matplotlib.pyplot as plt  import mpl_toolkits.mplot3d  x,y=np.mgrid[-2:2:20j,-2:2:20j]  z=x*np.exp(-x**2-y**2)  ax=plt.subplot(111,projection='3d')  ax.plot_surface(x,y,z,rstride=2,cstride=1,cmap=plt.cm.coolwarm,alpha=0.8)  ax.set_xlabel('x')  ax.set_ylabel('y')  ax.set_zlabel('z')  plt.show()  

1. 画多子图结构

from matplotlib import pyplot as pltimport numpy as npt=np.arange(0, 5, 0.2) #类似python里的rangefig=plt.figure()#行，列，序号ax1 = fig.add_subplot(221)ax2 = fig.add_subplot(222)ax3 = fig.add_subplot(212)ax1.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')ax1.grid(True)ax1.set_title("plot")ax2.semilogy(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')ax2.grid(True)ax2.set_title("ylog")ax3.semilogy(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')ax3.grid(True)ax3.set_title('loglog')fig.suptitle('normal vs ylog vs loglog')   #大图的标题fig.subplots_adjust(hspace=0.4)   #控制图３和上两个图间距；plt.show()

多子图结构画法：

from matplotlib import pyplot as pltimport numpy as npt=np.arange(0, 5, 0.2) #类似python里的rangefig=plt.figure()#行，列，序号ax1 = fig.add_subplot(321)ax2 = fig.add_subplot(322)ax3 = fig.add_subplot(312)ax4 = fig.add_subplot(325)ax5 = fig.add_subplot(326)

５．画饼状图

plt.figure(1,figsize=(3, 3))sizes = [120,30,59]labels = 'GL', 'GR', 'GS'colors = ['red','yellowgreen','lightskyblue']explode=(0.06, 0, 0)patches, l_texts, p_texts = plt.pie(sizes, explode=explode, labels=labels, colors=colors,labeldistance=1.1,autopct='%2.1f%%', shadow=True,        startangle=90, pctdistance=0.6)#　labeldistance　标签距圆心１．１倍半径，　autopct　２位整数，１位小数；　　startangle第一块起始角度，逆时针９０开始；#　pctdistance百分比距离圆心位置；plt.axis('equal')#设置　ＸＹ轴刻度一致，保证图是圆的；#plt.legend()  #　图例#patches, l_texts, p_texts=  设置标签，比例数字显示的大小；for t in l_texts:    t.set_size(10)for t in p_texts:     t.set_size(10)plt.show()

６．画柱状图

import matplotlib.pyplot as plt; import numpy as npfeat = [0.6,0.8,0.4]print featplt.figure(num=1,figsize=(2.5, 2)) method = ('Left','Right', 'Go')x_pos = np.arange(3)#plt.barh(range(len(feat)), feat)plt.bar(x_pos,feat,align = 'center', alpha = 0.5,color='r',width=0.3)  plt.xticks(x_pos,method,fontsize =8)  plt.yticks(fontsize =8)   # change the num axis sizeplt.title('Output',size=8) #plt.ylabel("prob")plt.grid(True)  #网格线for x, y in zip(x_pos,feat):    plt.text(x,y+0.02, '%.2f' % y, ha='center', va='bottom')  # 将数字加在各个柱状图上；plt.ylim(0,1.1)    #plt.savefig('/home/robot_lcl/Desktop/picture/p.png',format='png')plt.show()  

[0.6, 0.8, 0.4]

import matplotlib.pyplot as pltdata = [5, 20, 15, 25, 10]plt.figure(num=1,figsize=(2.5, 2)) plt.barh(range(len(data)), data)plt.show()