Candela¶

Candela is an open-source suite of interoperable web visualization components for Kitware’s Resonant platform. Candela focuses on making scalable, rich visualizations available with a normalized API for use in real-world data science applications. Integrated components include:

LineUp component: LineUp dynamic ranking by the Harvard University Visual Computing Group and the Caleydo project.
UpSet component: UpSet set visualization by the Harvard University Visual Computing Group and the Caleydo project.
OnSet component: OnSet set visualization by the Georgia Institute of Technology Information Interfaces Group.
Vega visualizations by the University of Washington Interactive Data Lab. Example component: ScatterPlot.
GeoJS geospatial visualizations by Kitware’s Resonant platform. Example component: GeoDots.

Getting started¶

Quick start - JavaScript¶

Enter the following in a text file named index.html:

<body>
<div id="vis"></div>
<script src="//unpkg.com/candela/dist/candela.min.js"></script>
<script>

  var data = [
    {x: 1, y: 3},
    {x: 2, y: 4},
    {x: 2, y: 3},
    {x: 0, y: 1}
  ];

  var el = document.getElementById('vis');
  var vis = new candela.components.ScatterPlot(el, {
    data: data,
    x: 'x',
    y: 'y'
  });
  vis.render();

</script>
</body>

Open index.html in your browser to display the resulting visualization.

Quick start - Python¶

Make sure you have Python 2.7 and pip installed (on Linux and OS X systems, your local package manager should do the trick; for Windows, see here).
Open a shell (e.g. Terminal on OS X; Bash on Linux; or Command Prompt on Windows) and issue this command to install the Candela package and the Requests library for obtaining sample data from the web:
```
pip install pycandela requests
```
(On UNIX systems you may need to do this as root, or with sudo.)
Issue this command to start Jupyter notebook server in your browser:
```
jupyter-notebook
```

Create a notebook from the New menu and enter the following in a cell, followed by Shift-Enter to execute the cell and display the visualization:

import requests
data = requests.get(
    'https://raw.githubusercontent.com/vega/vega-datasets/gh-pages/data/iris.json'
).json()

import pycandela
pycandela.components.ScatterPlot(
    data=data, color='species', x='sepalLength', y='sepalWidth')

Quick start - R¶

Download and install RStudio.

Run the following commands to install Candela:

install.packages('devtools')
devtools::install_github('Kitware/candela', subdir='R/candela')

Issue these commands to display a scatter plot of the mtcars dataset:

library(candela)
candela('ScatterPlot', data=mtcars, x='mpg', y='wt', color='disp')

Using Candela

Components¶

API documentation

Developer documentation