Hello
I attempt to use Surrogate.jl
to build a surrogate model of a set of measurement data, coming from a csv file. For the model, there will be 5 inputs and 1 output. I review the user manual of Surrogate.jl
and I find that there is no tutorial for importing sample from a file. So I wonder if this is supported with Julia. In this case, what sampling method is recommended to use?
Besides, lower bound and upper bound should be indicated in the surrogate model. I want to set the min and max of the columns in the csv, is this correct?
It’s supported. You wouldn’t use a sampling method but instead would use the direct constructor. You just use for example radial_basis = RadialBasis(xys, zs, lower_bound, upper_bound)
where xyz
and zs
match the format that the sampling methods generate.
If you open an issue we can probably add a tutorial.
Another question about format convertion. I have a dataframe of 2 columns reading from csv file, how can I convert each line of dataframe into a tuple, and combine all the tuples to form like Array{Tuple{Float64, Float64}} or Vector{Tuple{Float64, Float64}}?
map(x->Tuple(x...),eachrow(A))
or something of the sort. That should put you at least in the right direction. Do DataFrames iterate by row? They might.
Thanks! eachrow()
is available with DataFrames.jl
, not for Pandas.jl
. Anyway, it works.