Try Randvizer online - Visualize Random Number Sequences To Detect Anomalies.
Current version is 0.0.4
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 |
---|---|
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Clone the repository
-
Run the following commands
npm install
ng serve
- Open the project in browser
Navigate to http://localhost:4200/
. The app will automatically reload if you change any of the source files.
Run ng test
to execute the unit tests via Karma.
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
.
ng build --prod --base-href "https://another-guy.github.io/randvizer/"
angular-cli-ghpages
The code is distributed under the MIT license.
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.
Contribution is the best way to improve any project!
- Fork it!
- Create your feature branch (
git checkout -b my-new-feature
). - Commit your changes (
git commit -am 'Added some feature'
) - Push to the branch (
git push origin my-new-feature
) - Create new Pull Request
...or follow steps described in a nice fork guide by Karl Broman
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.