https://github.com/another-guy/randvizer
Visualize Random Number Sequences To Detect Anomalies
https://github.com/another-guy/randvizer
data-visualization random random-generation random-number-generators randomization randvizer visualization visualizer
Last synced: 7 months ago
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Visualize Random Number Sequences To Detect Anomalies
- Host: GitHub
- URL: https://github.com/another-guy/randvizer
- Owner: another-guy
- Created: 2017-05-14T03:28:33.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2017-05-17T07:56:00.000Z (almost 9 years ago)
- Last Synced: 2025-05-28T14:03:17.454Z (10 months ago)
- Topics: data-visualization, random, random-generation, random-number-generators, randomization, randvizer, visualization, visualizer
- Language: TypeScript
- Homepage: http://soloydenko.com/randvizer/
- Size: 917 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Synopsis
Try [Randvizer](http://soloydenko.com/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 |
|:-------------:|:-------------:|
|  |  |
## Installation
1. Clone the repository
2. Run the following commands
```
npm install
ng serve
```
3. 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](https://karma-runner.github.io).
### End-to-End Tests [Not Available]
Run `ng e2e` to execute the end-to-end tests via [Protractor](http://www.protractortest.org/).
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](http://kbroman.org/github_tutorial/pages/fork.html) by Karl Broman
## Acknowledgements
This project is build via [Angular](https://angular.io/) and [D3.js](https://d3js.org/).
Number-to-color mapping algorithm is a port of code from [this SO answer](http://stackoverflow.com/a/2376159/482868) which in turn originates from [efg2.com](http://www.efg2.com/Lab/ScienceAndEngineering/Spectra.htm).