In the previous chapter, we used Python to analyze population genetics datasets based on real data. In this chapter, we will see how to use Python to simulate population genetics data. From teaching to developing new statistical methods or to analyze the performance of existing methods, simulated datasets have plenty of applications.

There are two kinds of simulation. One is coalescent simulation that goes backwards in time. Second is forward time. As the name implies, it simulates going forward. The coalescent simulation is computationally less expensive because only the most recent generation of individuals need to be completely rendered; previous generations only need parents of the previous generation to be maintained. On the other hand, this severely limits what can be simulated because we need to complete populations to make decisions on e.g. which individuals mate. Forward time simulations are computationally more demanding and normally more complex to code, but they...