QFI k-means explorations

⚠️ WIP ⚠️

This repo contains experimental code that is used to understand how the popular k-means algorithm could be used in identifying collusion in a quadratic funding round.

Considerations

• When a ballot is at the same distance of two centroids, the first one is the one they are assigned to.

Coefficient Calculation

Coefficients can be calculated in two ways:

1. $1- clusterSize/totalVoters$
2. $clusterSize/totalVoters$

Allocation Calculation

Funds allocation can be calculated in two ways:

1. squaring before applying the coefficient
2. squaring after applying the coefficient

Usage

• clone the repo:
  git@github.com:ctrlc03/qfi-kmeans.git
• install the dependencies:
  yarn
• run tests for the typescript implementation:
  yarn test:ts and yarn test:class
• run tests for the circom implementation: yarn test:circom
• to run all possible combinations of calculations and the elbow method (which can be used to identify the optimal value for k) use: ./plotting.sh (needs execute permissions first)

Please note that this stores a very large amount of files on disk (json and png files)

• to plot the data of a single run of the algorithm you can use the Python scripts inside src/plotting: python3 src/plotting/x.py $k
• Fetch GitCoin round data (you need to fill the .env file first - copy .env.template): yarn gitcoin yarn parse:gitcoin
• Run k-means on Gitcoin round data yarn start:gitcoin