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 np
import matplotlib.pyplot as plt
%matplotlib inline
data= np.loadtxt('/home/robot_lcl/lcl_file/train_log/train.log.test')
#print data
x=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 plt
fig = 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()

画多子图结构

from matplotlib import pyplot as plt
import numpy as np

t=np.arange(0, 5, 0.2) #类似python里的range

fig=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 plt
import numpy as np

t=np.arange(0, 5, 0.2) #类似python里的range

fig=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
b210
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 np

feat = [0.6,0.8,0.4]
print feat

plt.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 size
plt.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 plt

data = [5, 20, 15, 25, 10]

plt.figure(num=1,figsize=(2.5, 2))
plt.barh(range(len(data)), data)

plt.show()