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我遇到的e问题是行减法的正确答案,但是,当是 set a[j] = e,然后a[j]变成[0,0,0]而不是[0,0.5,0.5].

import numpy as np

def naive_gauss(a,b):
    n = len(a)

    for i in range(n-1):
        for j in range(i+1, n):
            print("a is: ,",a,"\n")
            factor = a[j][i] / a[i][i]
            e = a[j] - (a[i] * factor)
            print("e is", e)
            print("a[j] is: ,", a[j], "\n")
            a[j] = e
            print("a[j] is:, ", a[j])
            print("-----------------------------------")
            b[j] = b[j] - (b[i] * factor)
            print("new a is: ", a)
            print("new b is: ", b, "\n")
     print("new matrix is:", a)
     return b

d = np.array([8,-11,-3])
f = np.array([[2,1,-1],[-3,-1,2],[-2,1,2]])


print(naive_gauss(f,d))
4

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