将列乘以矩阵向量乘以范围为（1,101）的变量项

Question

I want to multiply Matrix AB. To get the vector Y, Where A is 3x4 and B is 4x1 x= range(1,101) B = [2,x,3,x] Since B contains the variable x we will get 100 different vectors for Y. I want to add them to a list so I can use these vectors for computations later on.

This is what i've tried but i get an error messages

AB= list()
for x in range (1,100):
    A = np.matrix('1 9 2 3; 7 2 1 4; 4 2 5 2') 
    B = ('2; x; 3; x')
    AB.append(A @ B)

What am I doing wrong? The error i get is: (that refers to a different file btw)

raise ValueError('malformed node or string: ' + repr(node))

Answer 1

Okay first, you forgot to make B a numpy matrix, second you need to use f-strings to use x as a variable instead of the character x which is an incompatible type.

AB = list()
for x in range (1,100):
   A = np.matrix('1 9 2 3; 7 2 1 4; 4 2 5 2') 
   B = np.matrix(f'2; {x}; 3; {x}')
   AB.append(A @ B)

Answer 2

The preferred way of creating arrays is:

In [146]: A = np.array([[1, 9, 2, 3],[7, 2, 1, 4],[4, 2, 5, 2]])                                                                     
In [147]: A                                                                     
Out[147]: 
array([[1, 9, 2, 3],
       [7, 2, 1, 4],
       [4, 2, 5, 2]])

For small arrays np.matrix with its imitation MATLAB constructor is convenient, but generally discouraged.

In [148]: x=3                                                                   
In [149]: B = np.array([[2],[x],[3],[x]])                                       
In [150]: B                                                                     
Out[150]: 
array([[2],
       [3],
       [3],
       [3]])
# B = np.array([[2,x,3,x]]).T
In [151]: A@B                                                                   
Out[151]: 
array([[44],
       [35],
       [35]])

For multiple values of x :

In [152]: x = np.arange(10)                                                     
In [153]: B = np.empty((4,x.shape[0]), int)                                     
In [154]: B[[1,3]] = x                                                          
In [155]: B[0] = 2                                                              
In [156]: B[2] = 3                                                              
In [157]: B                                                                     
Out[157]: 
array([[2, 2, 2, 2, 2, 2, 2, 2, 2, 2],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [3, 3, 3, 3, 3, 3, 3, 3, 3, 3],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])
In [158]: A@B                                                                   
Out[158]: 
array([[  8,  20,  32,  44,  56,  68,  80,  92, 104, 116],
       [ 17,  23,  29,  35,  41,  47,  53,  59,  65,  71],
       [ 23,  27,  31,  35,  39,  43,  47,  51,  55,  59]])