from numpy import *
    import operator


    def createDataSet():
        group = array([[1.0, 1, 1], [1.0, 1.0], [0, 0], [0, 0.1]])
        labels = ['A', 'A', 'B', 'B']
        return group, labels


    def classify0(inX, dataSet, labels, k):
        '''得到数组的形状和其行数 '''
        dataSetSize = dataSet.shape[0]
        '''将其填充和数据集一样形状，并求差 '''

        a = tile(inX, (dataSetSize, 1))

        diffMat = a - dataSet
        '''求差后，每一个元素平方'''
        sqDiffMat = diffMat ** 2
        '''求距离数组中每一组元素的和，即实际距离的平方'''
        sqDistances = sqDiffMat.sum(axis=1)
        '''距离开方'''
        distances = sqDistances ** 0.5
        '''距离排序'''
        sortedDistIndicies = distances.argsort()

        classCount = {}
        for i in range(k):
            voteIlabel = labels[sortedDistIndicies[i]]
            classCount[voteIlabel] = classCount.get(voteIlabel, 0) + 1

        sortedClassCount = sorted(classCount.items(), key=operator.itemgetter(1), reverse=True)
        return sortedClassCount[0][0]


    if __name__ == '__main__':
        group, labels = createDataSet()
        classify0([0, 0], group, labels, 3)