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The curse of dimensionality is a blessing in disguise. Although multi-dimensional arrays in R are restricted to the six basic types, many programming languages vectors and arrays as a template, which means that you can make such compound objects from any type of object that you like.

This becomes especially handy when it comes to organisation of high-dimensional, spatial data.

The package

The base class VirtualArray is defined, which acts as a wrapper around lists allowing users to fold arbitrary sequential data into n-dimensional, R-style virtual arrays. The derived XArray class is defined to be used for homogeneous lists that contain a single class of objects. The RasterArray, SfcArray and SfArray classes enable the use of stacked spatial data instead of lists.



The functions here were originally developed and published as part of the chronosphere R package. For better compliance with UNIX philosophy and more efficient distribution/development, the original chronosphere has been broken up to three R packages:

  • rgplates: functions related to tectonic reconstructions.
  • via: Virtual Arrays for efficient organisation of high-dimenional data.
  • chronosphere: version-controlled data distribution.

This is a pre-alpha version, and like R, comes with absolutely no warranty.