The vector of constant terms b contains all ones, except that the first and last elements are zero. You can use td to find that x1= −0.10557. The following code format should help: def td(l, m, u, b):   '''Solve a linear system Ax = b where A is tridiagonal

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IN PYTHON I want a code in python and no need to post work on paper Iwant a screenshot of the code

A tridiagonal matrix is one where the only nonzero elements are the ones on the main diagonal and the ones immediately above and below it.Write a function that solves a linear system whose coefficient matrix is tridiag- onal. In this case, Gauss elimination can be made much more efficient because most elements are already zero and don't need to be modified or added. As an example, consider a linear system Ax = b with 100,000 unknowns and the same number of equations. The coefficient matrix A is tridiagonal, with all elements on the main diagonal equal to 3 and all elements on the diagonals above and below it equal to 1. The vector of constant terms b contains all ones, except that the first and last elements are zero. You can use td to find that x1= −0.10557.

The following code format should help:

def td(l, m, u, b):

  '''Solve a linear system Ax = b where A is tridiagonal
  
    Inputs: l, lower diagonal of A, n-1 vector
            m, main diagonal of A, n vector
            u, upper diagonal of A, n-1 vector
            b, right-hand constant in each equation, n vector
    Output: x, vector of unknowns, n vector
  
  Example: if A =    2  -2   0   0
                    -1   4  -2   0
                     0  -1   6  -2
                     0   0  -1   8
   and b = [24; 12; -98; 55],
   then l = [-1; -1; -1], m = [2; 4; 6; 8], u = [-2; -2; -2],
   and x = [10; -2; -15; 5]'''

THANK YOU!

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