def img2vector(filename):
  imgVec = zeros((1,1024))
  file = open(filename)
  for i in range(32):
    lines = file.readline()
    for j in range(32):
      imgVec[0,32*i+j] = lines[j]
  return imgVec

def handWriteNumClassTest():
  NumLabels = []
  TrainingDirfile = listdir(r'D:\ipython\num_recognize\trainingDigits')#文件目录
  L = len(TrainingDirfile)  #该目录中有多少文件
  TrainMat = zeros((L,1024))
  for i in range(L):
    file_n = TrainingDirfile[i]
    fileName = file_n.split('.')[0]
    ClassName = int(file_n.split('_')[0])
    NumLabels.append(ClassName)
    TrainMat[i,:] = img2vector(r'D:\ipython\num_recognize\trainingDigits\%s'%file_n)
  TestfileDir = listdir(r'D:\ipython\num_recognize\testDigits')
  error_cnt = 0.0
  M = len(TestfileDir)
  for j in range(M):
    Testfile = TestfileDir[j]
    TestfileName = Testfile.split('.')[0]
    TestClassName = int(Testfile.split('_')[0])
    TestVector = img2vector(r'D:\ipython\num_recognize\testDigits\%s'%Testfile)
    result = classify0(TestVector,TrainMat,NumLabels,3)
    print('the result is %d,the real answer is %d\n'%(result,TestClassName))
    if result!=TestClassName:
      error_cnt+=1
  print('the total num of errors is %f\n'%error_cnt)
  print('the error rate is %f\n'%(error_cnt/float(M)))