This folder contains data sets for making informed decisions regarding rule optimization for Midnight Riders. Custom data packs can be created with dice-mechanic-sim.
This is an example of a plot from a csv:
Each data pack includes:
- Individual csv files are a simulation of an entire game. csv files are named with a timestamp of when they were created.
- Plotted graph in png file.
- dicemechanicsim.py pyhon script with the same settings as the data.
What is a CSV file? CSV stands for comma separated values. It is a very simple spreadsheet with each row being a new line and each column separated by commas. This is an example of one csv file.
This repository assumes you are familiar with the rules for Midnight Riders.
1R is the Reputation score for Player 1.
1M is the Madness score for Player 1.
3R is the Reputation score for Player 3.
Download and extract a data pack for example data.
Ways to view and analyze the data:
- A plain text editor can also view the files quickly.
- The csv files can be opened with popular spreadsheet software such as LibreOffice Calc, Google Sheets, or Microsoft Excel.
- Data can be graphed with spreadsheet software or within python through matplotlib, plotly, networkx, or igraph.
- Data analysis software and programming languages can be used to parse the data.
Goals for the data can be found in the goals.md file.
Observations and findings are recorded in the analysis-observations.
If you have any observations, you can submit them as a pull request or submit a new issue on DMS.
Data packs that are built with early iterations of DMS can be graphed using the rebuilddatapack.sh and plotcsv.py files.