python 实现矩阵相乘

优势在于，矩阵的数据组织方式适合分布式计算

# coding:utf-8__author__ = 'taohao'import randomclass Matrix(object):    def build_matrix_a(self, row, col):        """        matrix:            1  0  2            -1 3  1        turn to ->Matrix name,rowNum,colNum,elementNum        for example:            A,1,1,1            A,1,2,1            A,1,3,2            A,2,1,-1            A,2,2,3            A,2,3,1        save the matrix to file for hadoop to read data from file        :return:        """        fd = open('MatrixA.txt', 'w')        num = ''        for i in range(row):            for j in range(col):                num += ',' + str(i+1) + ',' + str(j+1) + ','                num += str(random.randint(1, 10))                fd.write('A' + num + '\n')                num = ''        fd.close()    def build_matrix_b(self, row, col):        """        the same as def build_matrix_a        :param row:        :param col:        :return:        """        fd = open('MatrixB.txt', 'w')        num = ''        for i in range(row):            for j in range(col):                num += ',' + str(i+1) + ',' + str(j+1) + ','                num += str(random.randint(1, 10))                fd.write('B' + num + '\n')                num = ''        fd.close()    def matrix_multify(self, row, col):        result = {}        matrix_a = {}        matrix_b = {}        fd_a = open("MatrixA.txt", 'r')        fd_b = open('MatrixB.txt', 'r')        for line_a in fd_a:            line_item = line_a.rstrip('\n').split(r',')            if line_item[1] not in matrix_a:                matrix_a[line_item[1]] = []            matrix_a[line_item[1]].append(line_item[3])        for line_b in fd_b:            line_item_b = line_b.rstrip('\n').split(r',')            if line_item_b[2] not in matrix_b:                matrix_b[line_item_b[2]] = []            matrix_b[line_item_b[2]].append(line_item_b[3])        fd_a.close()        fd_b.close()        # print matrix_a        # print matrix_b        for i in range(row):            row_num = matrix_a.get(str(i+1))            # print 'row', row_num            for j in range(col):                col_num = matrix_b.get(str(j+1))                # print 'col', col_num                k = 0                while k < len(row_num):                    if str(i+1)+str(j+1) not in result:                        result[str(i+1)+str(j+1)] = 0                    result[str(i+1)+str(j+1)] += int(row_num[k]) * int(col_num[k])                    k += 1        print result    # output the resultif __name__ == '__main__':    rowA = 4    colA = 2    rowB = 2    colB = 3    matrix = Matrix()    matrix.build_matrix_a(rowA, colA)    matrix.build_matrix_b(rowB, colB)    matrix.matrix_multify(rowA, colB)