Write a python function to perform the following tasks:

1. set the seed of the numpy random number generator to 1234

2. define Q to be a 200 x 200 matric with normally distributed random entries having zero mean and unit variance (use numpy.random.normal)

3. loop through each element of Q (remember that there are two dimensions). If the element is negative, make it positive by replacing it with its square (i.e. set Q|i,j| to Q|i,j|^2 if Q|i,j| < 0). But don't change the positive entries of Q. (use for and if. could you perform the same operation using only one line of code?)

4. now define r to be a 200 x 1 column vector of uniformly distributed numbers between 0 and 1 (using numpy.random.uniform)

5. now define 200 x 1 vector z = Q * r (using matrix-vector product)

6. define p to be the mean value of the element-wise product between r and z^2 (i.e. the average over j or r|j| z|j|^2). You should be able to do this in one line. use the built-in function, numpy.mean, to take the mean.

you should get a single positive number as the result