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Following on from #338, when we transferred all of our sampling methods over to QuasiMonteCarlo.jl, we encountered the issue that QuasiMonteCarlo.jl outputs samples as a $d\times n$Matrix, where $d$ is the dimension of the problem and $n$ is the number of samples, while Surrogates expects samples as a length-$n$ Vector of length-d Tuples. Converting Surrogates.jl to the former representation might improve speed and would allow us to remove the one remaining sampling-related bit of code, but would be a breaking change.
The text was updated successfully, but these errors were encountered:
Following on from #338, when we transferred all of our sampling methods over to$d\times n$ $d$ is the dimension of the problem and $n$ is the number of samples, while
QuasiMonteCarlo.jl
, we encountered the issue thatQuasiMonteCarlo.jl
outputs samples as aMatrix
, whereSurrogates
expects samples as a length-$n$Vector
of length-dTuples
. ConvertingSurrogates.jl
to the former representation might improve speed and would allow us to remove the one remaining sampling-related bit of code, but would be a breaking change.The text was updated successfully, but these errors were encountered: