Is there a reason to use this file format over NRRD [1]? To borrow a wise phrasing: I wonder if the world needs another lightweight raw data format ;)
For what it's worth, NRRD is already supported by JuliaIO/Images.jl, and I believe addresses the use-cases identified in your readme, but with a number of technical and non-technical advantages (not least: a number of independent implementations, and a substantial user base, at least as far as these things go). I say this -- very selfishly I admit -- as someone who has been on the receiving end of far too many files in home-brewed formats. [1] http://teem.sourceforge.net/nrrd/descformat.html On Sunday, September 25, 2016, David Smith <[email protected]> wrote: > Hi, all: > > I finally pushed this out, and it might satisfy some of your needs for a > simple way to store N-d arrays to disk. Hope you enjoy it. > > RawArray (.ra) is a simple file format for storing n-dimensional arrays. > RawArray was designed to be portable, fast, storage efficient, and future > proof. Basically it writes the binary array data directly to disk with a > short header that is used to recreate type and dimension information. > > RawArray is faster than HDF5 and supports complex numbers out of the box, > which HDF5 does not. RawArray supports all basic `Int`, `UInt`, `Float`, > and `Complex{}` types, and more can be easily added in the future, such as > Rational or Big*. It can also handle derived types, but the serialization > of them is currently left up to the user. > > A system of version numbers and flags are implemented to future-proof the > data files as well, in case the implementation needs to change for some > reason. > > You can grab it with `Pkg.add("RawArray")`. A minimum of Julia 0.4 is > required. > > Repository: https://github.com/davidssmith/RawArray.jl > > Cheers, > Dave >
