Introduction

Three months of GSoC 2014 term was over this week and finally I released my product Nyaplot as a gem. This blog post was written to introduce Nyaplot version 0.1.1.

Features

There are various plotting libraries in the world as ggplot2 from R community and Plotrb and Rubyvis from Ruby. The features of Nyaplot compared with those libraries are interactivity, simplicity, and extensibility.

Interactivity is the main theme of my D3 project in GSoC 2014. You can soon find the aforementioned interactivity by clicking plots with your mouse or trackpad. This feature is also available on browsers bundled with Android or iOS thanks to technologies like SVG and WebGL.

However, the word ‘interactivity’ is not limited to situations like the above. You can explore that for yourself by using Nyaplot in IRuby notebook. Various modules prepared by Nyaplot help you to create plots interactively in the notebook. You can also publish the result quickly by uploading the notebook to your Dropbox storage, a gist or pastebin, or somewhere else. Here is an example which Mauricio Giraldo created and published on gist.

Simplicity is also an important element. Many plotting libraries has MATLAB-like function-based API but Nyaplot does not. Nyaplot is designed in a more Ruby-like object-oriented style, and its plots consist of various objects created from different classes. But Nyaplot has simple shortcut methods and users may avoid the more complex API.

Nyaplot can be easily and dramatically extended with some JavaScript code. It bundles 3 extension libraries in its gem package: Nyaplot3D for 3D plots, Mapnya for map visualization, and Bionya for circular plots inspired by circos. Their structure is very simple and you can write the extension easily if you have a little experience in JavaScript and Ruby. For example, the Ruby part of Bionya has only about a hundred lines, even though the graphic’s style is far from that of standard plots.

Quick start

You can install Nyaplot by simply running gem install nyaplot. After that, find example code from path_to_gems/nyaplot-0.1.1/examples/rb and run some of them using ruby command. These scripts will generate some plots with Nyaplot and export them as html files to current directory.

In addition, I strongly recommend you to install IRuby notebook at the same time. IRuby is a web-based, interactive Ruby environment and is useful for quickly creating plots with Nyaplot. The introduction video embedded at the top of this post was also created on IRuby.

IRuby depends on some software outside of Ruby-ecosystem, so its installation method is a bit complicated. Please read the description in the readme to learn more.

Usage

I already wrote tutorials, so I’d like to limit the role of this paragraph to the introduction of the basic usage. You can skip reading this paragraph and find details in the nbviewer tutorial and documentation.

The minimum code to create a scatter plot is as shown below:

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plot = Nyaplot::Plot.new
sc = plot.add(:scatter, [0,1,2,3,4], [-1,2,-3,4,-5])

Nyaplot::Plot is the base class to create plots and Nyaplot::Plot#add is the method to add diagram to its instance. The first argument is to specify the type of diagram, and the second and third are for data mapped into x and y axes. Plot#add returns an instance of Nyaplot::Diagram and you can change attributes like color and stroke of each diagram component.

For example you can change its color by running the code below.

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color = Nyaplot::Colors.qual
sc.color(color)

Nyaplot::Colors is the simple wrapper for Colorbrewer, and one of its methods Nyaplot::Colors.qual randomly returns colorset suitable for qualitative data.

If you execute this code in IRuby notebook, you can check if you favor the colorset through html-table based interface. See the tutorial to learn more.

The plot generated from the code can be exported with two lines below.

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plot.show # show plot on IRuby notebook
plot.export_html # export plot to the current directory as a html file

We cannot explain Nyaplot without Nyaplot::DataFrame. Example code above does not contain the word ‘DataFrame’, but the software internally create an instance of Nyaplot:DataFrame and creates plots based on it.

To create the same scatter plot as above, run the code below.

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df = Nyaplot::DataFrame.new({a: [0,1,2,3,4], b: [-1,2,-3,4,-5]})
plot.add_with_df(df, :scatter, :a, :b)

You may not feel any advantage of using Plot#add_with_df instead of Plot#add, but the former is useful when creating more complicated plots. Have a look at the tutorial to learn more.

Conclusion

My GSoC term has concluded, but that do not mean the end of development. There are still many things to do for improvement of this project. For example Mapnya and Bionya are both experimental implementation, and the functionality of Nyaplot::DataFrame is relatively limited. If you are interested in this project, please fork either or both of the two repositories below and send me pull-requests.

• Nyaplot on GitHub
• Nyaplotjs on GitHub

Any form of contribution is welcome.

At last I’d like to express my gratitude to my mentor Pjotr Prins and other members of SciRuby community. I would not have been able to finish my GSoC term without great help from them. Feedback from people outside of the community also helped me a lot. I had a great summer thanks to all people related to this project.