python画图

#仅画图
import numpy as np
import matplotlib.pyplot as plt
#matplotlib inline
from matplotlib import image
from matplotlib import pyplot as plt
#单纯画图
def loadDataSet(fileName):  
    dataMat = []              # 初始化一个空列表，文件的最后一个字段是类别标签
    fr = open(fileName)       # 读取文件
    for line in fr.readlines():   # 循环遍历文件所有行
        curLine = line.strip().split(' ')   # 切割每一行的数据
        fltLine = list(map(float, curLine))  # 映射所有的元素为 float（浮点数）类型
        dataMat.append(fltLine)   # 将数据追加到dataMat
    return dataMat       # 返回dataMat


datMat1 = np.mat(loadDataSet('./nolabel.txt'))
#datMat1 = np.mat(loadDataSet('./after_label_training_center_expand.txt'))

data = image.imread('地图.png')
plt.figure(1)
plt.imshow(data,extent=(0, data.shape[1], 0, data.shape[0]))
nolabel_x = []
nolabel_y = []
yeslabel_x = []
yeslabel_y = []
x = list((datMat1)[:,0])

for i in range(0,len(x)-10,1):
    nolabel_x.append(x[i])
print(len(nolabel_x))

for i in range(len(x)-10,len(x),1):
    yeslabel_x.append(x[i])
print(yeslabel_x)

y = list((datMat1)[:,1])
for i in range(0,len(y)-10,1):
    nolabel_y.append(y[i])
for i in range(len(y)-10,len(y),1):
    yeslabel_y.append(y[i])

#画图形状可参考http://t.csdn.cn/wDfGc
plt.scatter(nolabel_x, nolabel_y,marker = 'x',s=10)
plt.scatter(yeslabel_x, yeslabel_y,marker = 'P',s=100)
plt.show()