terpypy/d4-monte-carlo

Monte Carlo simulation to try and estimate the probability of reaching Masterwork level 12 given n number of max attempts. The simulation starts at level 4 since tiers 1-4 have 100% chance to upgrade.

Monte Carlo Simulations for Masterwork Tier Upgrades

This script simulates the process of upgrading masterwork tiers in D4 using Monte Carlo simulations. It includes a function for running the simulation, a helper function for running the simulations in parallel using multiprocessing, and a main function that parses command line arguments and runs the appropriate simulation.

Functions

• upgrade_mw_tier(max_up_attempts=15): Simulates the process of upgrading masterwork tiers in D4. Returns the final masterwork level achieved.

• Sim: A class that wraps the simulation functions. It has two methods for running simulations with and without keyword arguments.

• save_results(results, filename): Saves the results of a simulation to a file.

• pooled_simulation(sim, n, **kargs): A helper function that prepares and runs simulations in parallel using multiprocessing.

Usage

To run the script, use the following command:

python mw_rollout.py <simulation_name>

where <simulation_name> is the name of the simulation you want to runs the name of the simulation you want to run. The available simulations are upgrade_mw_tier and run_mw_batch.

For example, to run the upgrade_mw_tier simulation, use the following command:

python mw_rollout.py upgrade_mw_tier

Output

The script prints the probability of reaching tier 12 and the total run time. It also saves the results of the simulation as pickle files in form results_<num_max_attempts>.pkl.

Requirements

• Python 3.9+
• numpy
• multiprocessing

for notebook:

• matplotlib
• re
• pandas