gher-ulg
@GHER_ULiege
0000-0002-0265-1021
Data
Interpolating
Variational
Analysis
= n dimensional version of DIVA
≠ not a new release of DIVA,
but a brand new code
Get gridded field from in situ data
Mathematical formulation
Programming language
User interface
and a few others since 1991
Multiple dispatch
Math-friendly syntax
Unicode support: π, η, ∫ϵα
julia> 🌊 = 1./3.
julia> cos(🌊*π)
0.5000000000000001
Just-in-time (JIT) compiled
Parallelism
function fib(n::Int)
f=Vector{Int}(undef, n+1)
f[1]=f[2]=1;
for i=3:n+1
f[i]=f[i-1]+f[i-2]
end
return f
end
ff = @time fib(400000000);
1.158971 seconds (18.52 k allocations: 2.981 GiB, 0.84% gc time)
Metaprogramming:
Julia programs can read, analyse, generate other Julia programs
"Easy" interfacing: R, Python, ...
@pyimport numpy.random as nr
nr.rand(3,4)
Learning a new and evolving language
Transition from 0.6 to 1.0
SeaDataCloud regional leaders, creating climatologies
https://www.seadatanet.org/Products/ClimatologiesEMODnet Chemistry regional leaders
http://www.emodnet-chemistry.eu/productsEMODnet Biology (specific products)
http://www.emodnet-biology.eu/data-productsDIVA (2D) within Ocean Data View
http://odv.awi.de/DIVA-on-Web (2D)
http://ec.oceanbrowser.net/emodnet/diva.htmlJupyter notebooks inside the Virtual Research Environment
DIVAnd REST API (2D)
Hofstadter's Law:
even when you take into account Hofstadter's Law.
Barth, A., Beckers, J.-M., Troupin, C., Alvera-Azcárate, A., and Vandenbulcke, L.: DIVAnd-1.0: n-dimensional variational data analysis for ocean observations, Geosci. Model Dev., 7, 225-241, doi:10.5194/gmd-7-225-2014, 2014.
Julia Child (1912-2004)