jupyter nootebook python with julia (without cvxpy as cp, numpy as np) 1: Modify your models and coding of Chebyshev center and building a house to get the right anwsers.  # Given matrix A and vector b A = [2 -1 2; -1 2 4; 1 2 -2; -1 0 0; 0 -1 0; 0 0 -1]b = [2; 16; 8; 0; 0; 0]

The point P has coordinates x = -3 m and y = 4 m relative to the origin O. The vector v is v = -4î + 4î m/s. Matlab Mathematica Python SymPy from sympy import * Px = -3 Py = 4 v = Matrix([-4, 4, 0]) copy this text What is the orthogonal projection of v onto the vector û = -ếg associated with the polar coordinates for point P? Proj(t, й) — e î+ e jm/s

Using C++. Assume your development team is tasked with writing a pathfinder ( solution finder ) or the childhood game of 8 sliding tiles game. Your task is to determine whether or not an initial board configuration is or is not solvable. Your algorithm should do this by counting inversions. If the number of inversions is even, then the board is solvable. If the number of inversions is odd, then the board is not solvable (there is NO sequence of moves that will transition from the initial board to the goal board).

Use python

Create a python program that will except a 3x3 matrix and unit for translation, then conduct a basic 2D transformation of translation on the matrix.

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,…

Initialize a vector v1 with the following values: 0 23 -7 8 -22 3 14 Write a MATLAB program from the values in v1. The vector v2 should contain the values in v1 transformed as follows: that uses a for-loop and if-statements to make a new vector v2 multiply each positive even element in v1 by 3, multiply each positive odd element of v1 by -2, and change the sign of the negative elements in v1. Then, output the new vector to the command window as follows: The new vector is: -46 7 24 22 -6 42 Also, compute and output the mean of the values in the new vector: The mean of the new vector is: xxxx Above, xxxx is the mean of the values in the new vector with 1 decimal place.