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README.md

Synopsis

Try Randvizer online - Visualize Random Number Sequences To Detect Anomalies.

Status

Current version is 0.0.4

Motivation

If one is working on an pseudo-random number generator algorithm (PRNGA), he or she will eventually need to evaluate how well the algorithm works.

It's not easy to say whether a PRNGA performs well or not just by looking at several numbers from the sequence. Of course, there are various mathematical ways to assess the performance. However, it's often easier for human beings to perceive a visualized result to get some intuition about the subject of the study.

Here are two images which explain two visualized random sequences. It's easy to see how the first picture contains some regularities which make it worse compared to the second picture.

Weak Randomness Strong Randomness
Weak Randomness Strong Randomness

Installation

  1. Clone the repository

  2. Run the following commands

npm install
ng serve
  1. Open the project in browser

Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.

Tests

Unit Tests

Run ng test to execute the unit tests via Karma.

End-to-End Tests [Not Available]

Run ng e2e to execute the end-to-end tests via Protractor. Before running the tests make sure you are serving the app via ng serve.

Deployment

ng build --prod --base-href "https://another-guy.github.io/randvizer/"
angular-cli-ghpages

License

The code is distributed under the MIT license.

Reporting an Issue

Reporting an issue, proposing a feature, or asking a question are all great ways to improve software quality.

Here are a few important things that package contributors will expect to see in a new born GitHub issue:

  • the relevant version of the package;
  • the steps to reproduce;
  • the expected result;
  • the observed result;
  • some code samples illustrating current inconveniences and/or proposed improvements.

Contributing

Contribution is the best way to improve any project!

  1. Fork it!
  2. Create your feature branch (git checkout -b my-new-feature).
  3. Commit your changes (git commit -am 'Added some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

...or follow steps described in a nice fork guide by Karl Broman

Acknowledgements

This project is build via Angular and D3.js.

Number-to-color mapping algorithm is a port of code from this SO answer which in turn originates from efg2.com.