DyND is a C++ library for dynamic, multidimensional arrays. It is inspired by NumPy, the Python array programming library at the core of the scientific Python stack, but tries to address a number of obstacles encountered by some of its users. Examples of this are support for variable-sized string, ragged array types, and convenient usage from C++. The library is in a preview development state, and can be thought of as a sandbox where features are being tried and tweaked to gain experience with them.
The core DyND developer team consists of Mark Wiebe, Irwin Zaid, and Ian Henriksen. Much of the funding that made this project possible came through Continuum Analytics and DARPA-BAA-12-38, part of XDATA.