KDredX2

KDredX2 [1] is a cross-platform application (kay-dee-kai; a combined initialism of kernel density estimation and reduced chi-squared) to facilitate the visualization of weighted means along with its accompanied reduced chi-squared statistic, and univariate data density. It supports exporting the visualisations in a variety of file formats and provides an extensive customization to produce publication-quality figures. The developed numerical computations provide important insight into the nature and usability of said data. Prior numerical tools developed for this purpose are only available on a single operating system and generally restricted to antiquated programming languages. KDredX2 is designed to perform the aforementioned functions in the robust Java platform.

KDredX2 can run as a web-based or a standalone application. We have tested the application under MacOS and Windows.

MacOS App

KDredX2 macOS app is available here. Make sure that you have installed JRE before running the App.

Code Structure

KDredX2 is a Griffon application with JavaFX as UI toolkit and Java as main language. The project has the following file structure

.
├── build.gradle
├── griffon-app
│   ├── conf
│   ├── controllers
│   ├── i18n
│   ├── lifecycle
│   ├── models
│   ├── resources
│   ├── services
│   └── views
├── pom.xml
└── src
    ├── integration-test
    │   └── java
    ├── main
    │   ├── java
    │   └── resources
    └── test
        ├── java
        └── resources

Compile and Build

You will be able to build your project with

gradle build
gradle test
gradle run

Don't forget to add any extra JAR dependencies to build.gradle!

If you prefer building with Maven then execute the following commands

mvn compile
mvn test
mvn -Prun

Don't forget to add any extra JAR dependencies to pom.xml!

Reference

[1] Spencer, C. J., Yakymchuk, C., & Ghaznavi, M. (2017). Visualising data distributions with kernel density estimation and reduced chi-squared statistic. Geoscience Frontiers, 8(6), 1247-1252.