I am having trouble while joining a matrix and a vector togheter in Python.

Basically, assume I am given a matrix A such that

A = [
    [1,2,3,1,0],
    [3,2,2,0,1],
]

And a bunch of indexes such that

unboundedVarsIndex = [3]

My first task would be to go into index 2 of matrix A, and add a extra column in the matrix such that A[i 1] = -1 * A[i]. I was able to do this with the following code:

B = np.array(A).T

newA = [[]] * (len(B) len(unboundedVarsIndex))

for i in range(len(newA)-1):
    for indexVal in unboundedVarsIndex:
        if i == indexVal-1:
            newA[i 1] = -1*B[i]
    if len(newA[i]) == 0:
        newA[i] = B[i]
    else:
        newA[i 1] = B[i]

boolean = True
k = len(newA)-1
for indexVal in unboundedVarsIndex:
    if k == indexVal:
        boolean = False
        newnewA = [[]] * (len(newA) 1)
        newnewA[len(newnewA-1)] = -1*newA[len(newA)-1]
        for i in range(len(newA)):
            newnewA[i] = newA[i]

if(boolean):
    A = np.array(newA).T
else:
    A = np.array(newnewA).T

With this code, I get the following output:

A = [
    [1,2,3,-3,1,0]
    [3,2,2,-2,0,1]
]

Which is also what I wanted. My first problem is: this code doesn't work If I have more than one unbounbdedVarIndex. If I use, for example,

unboundedVarsIndex = [2,3]

The code gives me the following error:

newA[i 1] = B[i]
IndexError: index 5 is out of bounds for axis 0 with size 5

How would one fix this issue?

Thanks for any help in advance.

CodePudding user response：

This code does what you want:

A = [
    [1,2,3,1,0],
    [3,2,2,0,1],
]
unboundedVarsIndex = [2, 3]
unboundedVarsIndex.sort(reverse=True)
for index in unboundedVarsIndex:
    for each in A:
        each.insert(index, - each[index - 1])
print(unboundedVarsIndex)
print(A)