Write a function my_num_diff_w_smoothing(x,y,n) with output [dy,X], where x and y are a 1D NumPy…

Write a function my_num_diff_w_smoothing(x,y,n) with output [dy,X], where x and y are a 1D NumPy…
Write a function my_num_diff_w_smoothing(x,y,n) with output [dy,X], where x and y are a 1D NumPy array of the same length, and n is a strictly positive scalar. The function should first create a vector of “smoothed” y data points where y_smooth[i] = np.mean(y[i-n:i+n]). The func?tion should then compute dy, the derivative of the smoothed y-vector, using the central difference method. The function should also output a 1D array X that is the same size as dy and denotes the x-values for which dy is valid. Assume that the data contained in x is in ascending order with no duplicate entries; it is possible that the elements of x will not be evenly spaced. Note that the output dy will have 2n + 2 fewer points than y. Assume that the length of y is much bigger than 2n + 2.May 18 2022 09:58 AM