Please provide screenshots of code in Spyder

2. Given the following linear system of equations: 0.0003x1+3.0000x2=2.00011.0000x1+1.0000x2=1.0000 a. Can you solve this linear system by the nave Gaussian Elimination that you just coded? If yes, justify it. If not, propose a solution. b. Can you solve using the built-in function: np. linalg. solve (A,B) and the My_GE_naive_pivot? If yes, justify it. If not, propose a solution. c. Perform an LU decomposition of the system matrix and discuss the result Determine the solution to the flowing system of linear equations (r using the naive Gaussian Elimination that you implemented. 10x1+2x2x33x16x2+2x3x1+x2+5x3=27=61.5=21.5 a. Is there any difference in the solution using the naive GE and b. Run the same problem using Python's the built-in function np.linalg. solve (A,B) and the My_GE_naive_pivot provided to you and compare results. c. Use the Python clock function (time ()) to time the calculations What do you observe? Which method is the fastest? Why? d. Perform an LU decomposition of the system matrix and discuss the results. What is the relation of the L and U factors with the system's multipliers? Solve the linear system by the LU factors. Is there any difference with the previous solvers