A box contains a 4-sided die, a 6-sided die, an 8-sided die, a 12-sided die, and a 20-sided die. A die is selected at random, and the rest are destroyed.
We would like to determine which die I have selected, given only information of what I roll.
What is the prior associated with choosing any one die?
What is the likelihood function? You should assume that the die are all fair.
Say I roll an 8. After one bayesian update, what are the new priors?
You are to create a class called BayesDice. Implement as many instance methods as you need. The purpose of this class is to run a simulation. The simulation will choose a die, and then roll it repeatedly. Every time you roll the chosen die, you will update the priors. You should be able to figure out which die was chosen after a small number of rolls have occurred.
Here is a small sample of how you could execute your code.
bd = BayesDice()
bd.choose_die()
bd.roll_die()
bd.roll_die()
bd.roll_die()
Put your code under the src directory. Also create a test directory to test out your code, to ensure it is working as expected. Use pytest.
Fork and clone the repository. Use a dev branch. Send a pull request of your final code.