Python 如何解决稀疏矩阵运算

import numpy as np
from scipy import linalg
import os
#输入矩阵维数
print("你好，这里是计算稀疏矩阵线性方程组的地方，非诚勿扰！")
dism_num = input("你的A矩阵维数是：")
dism_num = int(dism_num)
print("接下来请你依次输入矩阵的行向量(注意只能输入英文逗号,):")
A =[]
#X =[]
for i in range(1,dism_num+1):
    a=input("第"+str(i)+"行向量是：")
    alist = a.split(",")
    alist = [int(alist[j]) for j in range(len(alist))]
    A.append(alist)
print("你所输入的矩阵行向量是:")
print(A)
#记录输入的X矩阵

#输入向量b
print("输入b向量")
b = input("b向量是：")
b_list = b.split(",")
b_list = [int(b_list[j]) for j in range(len(b_list))]
print("你输入的b向量是：")
print(b_list)
#记录b向量

#询问是否计算单个答案（单元素）
ask = input("是否只需求解单个值：（是或否）")
while(True):
    if ask == '是':
        ask_a = 'T'
        ask_num = input("请继续输入你所需要的答案序号：")
        ask_num = int(ask_num)
        if ask_num<=dism_num and ask_num>0:
            print("OK,马上帮你计算")
            break
        else:
            print("输入的值超出矩阵维数，请重新输入：")
    if ask == '否':
        ask_a = 'F'
        break
#询问完成,只有当用户输入正确的序号才可以进行计算，否则重新询问

#开始计算x向量了
A = np.array(A)
b = np.array(b_list)
x = linalg.solve(A,b)
print("计算的结果的：")
if ask_a == 'F':
    print(x)
if ask_a =='T':
    print(x[ask_num-1])
#计算完x向量了

os.system("pause")
#用于py文件结束玩暂停显示结果

import threading, time
import numpy as np
res = []
class MyThread(threading.Thread):
    def __init__(self,i,j,m1,m2):
        threading.Thread.__init__(self)
        self.x, self.y = i,j
        self.m1, self.m2 = m1, m2
    def run(self):
        global res, lock
        if lock.acquire():
            m1 = self.m1[self.m1[:,0]==self.x]
            m2 = self.m2[self.m2[:,1]==self.y]
            value = 0.
            for item1 in m1:
                for item2 in m2:
                    if item1[1] == item2[0]:
                        value += item1[2]*item2[2]
            res.append([self.x,self.y,value])
            lock.release()
if "__main__" == __name__:
    m1 = [[2,2],[0,0,1],[0,1,2],[1,0,3],[1,1,4]]
    m2 = [[2,3],[0,0,2],[0,2,1],[1,2,3],[1,1,4]]
    s1, s2 = m1[0], m2[0]
    assert s1[1]==s2[0], 'mismatch'
    m1_value = np.array(m1[1:])
    m2_value = np.array(m2[1:])
    rows, cols = s1[0], s2[1]
    res.append([rows, cols])
    ThreadList = []
    lock = threading.Lock()
    for i in range(rows):
        for j in range(cols):
            t = MyThread(i,j,m1_value,m2_value)
            ThreadList.append(t)
    for t in ThreadList:
        t.start()
    for t in ThreadList:
        t.join()
    print (res)