Generating random numbers with a seed

One of the major assumptions about option theory is that stock prices follow a log-normal distribution and returns follow a normal distribution. The following lines of code show an example of this:

>>>importscipy as sp
>>>x=sp.random.rand(10) 	# 10 random numbers from [0,1)
>>>y=sp.random.rand(5,2) # random numbers 5 by 2 array
>>>z=sp.random.rand.norm(100) from a standard normal 
>>>

After issuing the preceding function, the software would pick up a set of random numbers depending on a user's computer time. However, sometimes we need a fixed set of random numbers, and this is especially true when testing our models and code, and for teaching. To satisfy this need, we will have to set up the seed value before generating our random numbers, as shown in the following lines of code:

>>>importscipy as sp
>>>sp.random.seed(12456)
>>>sp.random.rand(5)
[0.92961609, 0.3163755, 0.18391881...