unit testing for page_ranker.py

[mzargham]

The page_ranker.py file contains methods for imposing heuristics on graphs to create in and out weights in accordance with a large class of pagerank variations including but not limited personal page rank via seed selection and the lazy random walk. This tool is intended to provide a highly generalized method supporting A/B testing and parameter sweeps to hone in on a preferred pagerank algorithm in a scientific manner.

https://github.com/sourcecred/research/blob/mz-exploratory/exploratory/mZargham/pre-infra/page_ranker.py

@mzargham requesting help to set up proper unit tests prior to submitting pull request to master as 'infra'

@BrianLitwin ~ I set up a gitcoin bounty for this. Two ways you can help:

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[satyaki-mallick]

Hi @mzargham , have you gone to any extent on this, the test cases .. ? Anything that you have started working on.

[mzargham]

@satyaki-mallick
Ideally we'd match the test cases from the javascript implementation.
https://github.com/sourcecred/odyssey-hackathon/blob/master/src/core/pagerankGraph.test.js
https://github.com/sourcecred/odyssey-hackathon/blob/master/src/core/attribution/markovChain.test.js
To the extent that they apply.

I am a researcher much more so than a dev, but this python method is intended to be a much more verbose version of the pagerank algorithm in js so we can do scientific experiments over the choices alpha, seed, edge weights, etc.

I haven't worked on this file recently; currently trying to get the
https://github.com/sourcecred/research/tree/graph-generators-for-testing
cleaned up so I can use it alongside the pageranker code for running experiments.

[satyaki-mallick]

Okay. Cool.

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Issue Status: 1. Open 2. Cancelled

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[mzargham]

I removed the bounty. Its own me to make sure the Issue is better defined before opening it up to the public. Will continue to use bounties though.