
# pandemonium

<!-- badges: start -->

<img src="man/figures/pandemonium.png" height="300px" align="right"/>
<!-- badges: end -->

pandemonium performs hierarchical cluster analysis within a Shiny GUI.
The data space should be split into two parts, for example input
variables and latent variables for a statistical model. Clustering is
performed using the subset of variables in the *clustering space*, and
cluster assignments are also visualised in the *linked space*.

Within the dynamic GUI pandemonium performs data preparation, clustering
and visualisation with interactive methods. The user can change all
settings without having to to leave the GUI.

## Installation

The latest release version of pandemonium can be installed from
[CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("pandemonium")
```

You can install the development version of pandemonium from
[GitHub](https://github.com/GabrielMccoy/pandemonium) with:

``` r
# install.packages("pak")
pak::pak("GabrielMccoy/pandemonium")
```

## Getting Started

We use the `Bikes` data example to show how the app can be used. To load
the GUI with this data, the following can be used.

``` r
library(pandemonium)
pandemonium(df = Bikes$space1, linked = Bikes$space2, 
                getScore = outsideScore(Bikes$other$res,"Residual"))
```

By loading the app with the clustering space in `df` and the linked
space in `linked` the data is automatically selected in the data page.
From here pressing load app will launch the analysis tab.

Within the analysis tab you can explore different visualisations and
their options in each of the enclosed tabs.
