Looking for library/tool to visualise multi-dimensional data [closed]

Question

I'm using Python in an attempt to analyse a large chunk of empiric measurements. In essence, I've two functions transforming the empiric data which also takes 3 'count' parameters - and returns a sequence of floats in each configuration. I'm expecting (hoping) to see some interesting patterns emerge when appropriate parameters are selected. I anticipate that the patterns might be relative between sequences returned for each function - and/or relate to patterns of some kind in the parameters. In case it's relevant, the 3 'count' parameters roughly correspond to:

• A 'window size' on the underlying data over which summary statistics are calculated
• A number of consecutive windows used to compute a single summary statistic (i.e. the trade-off between greater spatial or greater temporal accuracy)
• An 'minimum age' - an offset into history of the underlying data.

The summary statistics (which generate the resulting sequences of floats for each parameter configuration) are non-trivial but will be independently sensitive to all three parameters.

I'm interested in visualisation techniques - suited to RAD/ad-hoc enquiry that will help me experiment with this multi-dimensional data.

So far, I've tinkered with MatPlotLib but find being restricted generating two graphs of 2/3 dimensions in the style of batch processing makes investigation very tedious. Ideally, I'd find a tool that would allow me to visualise more than two dimensions... perhaps allowing me to switch real-time between dimensions in an interactive GUI.

I'd really appreciate hints from any visualisation gurus as to suitable tools I should investigate - ideally to integrate with my existing Python functions - or in other languages. I'd especially like to hear any anecdotes of success with similar visualisation problems.

EDIT to add: One possible approach I'm considering is to use animation on 2 or 3D plots (to capture another dimension... leaving 1 or 2 for manual selection)... though I've found no good tools to help me achieve this, yet.

Answer 1

RGL is a visualization device system for R, using OpenGL as the rendering backend. An rgl device at its core is a real-time 3D engine written in C++. It provides an interactive viewpoint navigation facility (mouse + wheel support) and an R programming interface.

GGobi is an open source visualization program for exploring high-dimensional data. It provides highly dynamic and interactive graphics such as tours, as well as familiar graphics such as the scatterplot, barchart and parallel coordinates plots. Plots are interactive and linked with brushing and identification.

There's a tutorial that covers both of the above systems here.

RPy is a very simple, yet robust, Python interface to the R Programming Language. It can manage all kinds of R objects and can execute arbitrary R functions (including the graphic functions). All errors from the R language are converted to Python exceptions. Any module installed for the R system can be used from within Python.

Answer 2

You might want to look at outputting SVG with animation, in which case this question might interest you. I suspect the animation aspects will require a lot of work on your part. Another option is maybe visualizing the data as a graph, although I'm don't know enough about your data to know whether this would be useful to you. If it is, cytoscape is python scriptable