2. Cubic Splines. (a) Write a python program to implement the natural cubic splines using Crout Factoriza- (b) Simulate a noisy sin curve between-/2 and /2 with a 0.4 step size. You can use (c) Generate a grid of 100 equally spaced values between-/2 and /2 and use your cubic (d) Compare your results with the splines obtained from the CubicSpline function form tion. np.random.normal to generate white Gaussian noise. spline code to interpolate the values on the grid. scipy.interpolate by plotting both curves on top of the original simulated values 2. Cubic Splines. (a) Write a python program to implement the natural cubic splines using Crout Factoriza- (b) Simulate a noisy sin curve between-/2 and /2 with a 0.4 step size. You can use (c) Generate a grid of 100 equally spaced values between-/2 and /2 and use your cubic (d) Compare your results with the splines obtained from the CubicSpline function form tion. np.random.normal to generate white Gaussian noise. spline code to interpolate the values on the grid. scipy.interpolate by plotting both curves on top of the original simulated values