ffreyer / binninganalysis.jl Goto Github PK

Currently (in mean, var, etc) the binning level is 0-based. This means that the binning level corresponds to how often data has been binned, i.e. level 0 is unbinned, level 1 has been binned once, etc. However with Julia having 1-based indexing it might be more natural to have 1-based levels. That would mean level 1 is unbinned, level 2 binned once, etc.

What are your thoughts?

Last entry seems to always be NaN.

Hi @ffreyer,

if you give me administrator rights here I can try to move the issues to https://github.com/crstnbr/BinningAnalysis.jl

Best
Carsten

The means on all levels should be exactly identical (up to rounding erros), right?

Try creating a binner with zero(Int64) and add more than one element. This will fail because the averaging of the first compressor, 0.5 * (C.value + value), will produce a Float64 and there is no method push! for Float64 for this binner.

Make CI (travis and appveyor) work.

AFAICS, currently only Float64 numbers can be handled.

It would be good to have support for other number types (like ComplexF64) and also higher dimensional arrays (numbers being the 0 dimensional case).