TypeError:-:“列表"和“列表"的不受支持的操作数类型 [英] TypeError: unsupported operand type(s) for -: 'list' and 'list'

问题描述

我正在尝试实现Naive Gauss，并在执行时遇到不受支持的操作数类型错误. 输出:

I am trying to implement the Naive Gauss and getting the unsupported operand type error on execution. Output:

  execfile(filename, namespace)
  File "/media/zax/MYLINUXLIVE/A0N-.py", line 26, in <module>
    print Naive_Gauss([[2,3],[4,5]],[[6],[7]])
  File "/media/zax/MYLINUXLIVE/A0N-.py", line 20, in Naive_Gauss
    b[row] = b[row]-xmult*b[column]
TypeError: unsupported operand type(s) for -: 'list' and 'list'
>>>   

这是代码

def Naive_Gauss(Array,b):
    n = len(Array)

    for column in xrange(n-1):
        for row in xrange(column+1, n):
            xmult = Array[row][column] / Array[column][column]
            Array[row][column] = xmult
            #print Array[row][col]
            for col in xrange(0, n):
                Array[row][col] = Array[row][col] - xmult*Array[column][col]
            b[row] = b[row]-xmult*b[column]


    print Array
    print b

print Naive_Gauss([[2,3],[4,5]],[[6],[7]])

推荐答案

您不能从列表中减去列表.

You can't subtract a list from a list.

>>> [3, 7] - [1, 2]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for -: 'list' and 'list'

简单的方法是使用 numpy :

Simple way to do it is using numpy:

>>> import numpy as np
>>> np.array([3, 7]) - np.array([1, 2])
array([2, 5])

您也可以使用列表推导功能，但是这需要在函数中更改代码:

You can also use list comprehension, but it will require changing code in the function:

>>> [a - b for a, b in zip([3, 7], [1, 2])]
[2, 5]

---

>>> import numpy as np
>>>
>>> def Naive_Gauss(Array,b):
...     n = len(Array)
...     for column in xrange(n-1):
...         for row in xrange(column+1, n):
...             xmult = Array[row][column] / Array[column][column]
...             Array[row][column] = xmult
...             #print Array[row][col]
...             for col in xrange(0, n):
...                 Array[row][col] = Array[row][col] - xmult*Array[column][col]
...             b[row] = b[row]-xmult*b[column]
...     print Array
...     print b
...     return Array, b  # <--- Without this, the function will return `None`.
...
>>> print Naive_Gauss(np.array([[2,3],[4,5]]),
...                   np.array([[6],[7]]))
[[ 2  3]
 [-2 -1]]
[[ 6]
 [-5]]
(array([[ 2,  3],
       [-2, -1]]), array([[ 6],
       [-5]]))

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