Returns the Julia code of the save_solution(model, output_dir, data_format)
helper that is embedded in the generated model.jl and called after solving.
Details
The helper is called from within the generated model.jl file. It saves variable values in the same directory structure as input data.
Examples
# Julia source of the save_solution() helper embedded in generated model.jl
cat(write_jump_solution_code())
#>
#> # Function to save solution values
#> function save_solution(model, output_dir, data_format)
#> using Dates
#> using DataFrames
#> using CSV
#> using Arrow
#>
#> if !isdir(output_dir)
#> mkpath(output_dir)
#> end
#>
#> println("\nSaving solution to: ", output_dir)
#>
#> # Determine file extension
#> ext = data_format == "csv" ? ".csv" : ".arrow"
#>
#> # Save each variable
#> for (var_name, var_obj) in object_dict(model)
#> if !(var_obj isa AbstractArray{VariableRef})
#> continue
#> end
#>
#> # Get variable values
#> var_vals = value.(var_obj)
#>
#> # Convert to DataFrame based on dimensions
#> if var_obj isa DenseAxisArray
#> # Get indices
#> indices = axes(var_obj)
#> n_dims = length(indices)
#>
#> if n_dims == 0
#> # Scalar variable
#> df = DataFrame(value = [var_vals])
#> else
#> # Multi-dimensional variable
#> idx_names = [Symbol("dim$i") for i in 1:n_dims]
#> rows = []
#>
#> for idx in Iterators.product(indices...)
#> val = var_vals[idx...]
#> if abs(val) > 1e-10 # Only save non-zero values
#> push!(rows, (idx..., val))
#> end
#> end
#>
#> if !isempty(rows)
#> df = DataFrame(rows, vcat(idx_names, :value))
#> else
#> df = DataFrame()
#> end
#> end
#> else
#> # Default handling
#> df = DataFrame(value = [var_vals])
#> end
#>
#> # Save to file
#> if !isempty(df)
#> var_dir = joinpath(output_dir, string(var_name))
#> mkpath(var_dir)
#> out_file = joinpath(var_dir, "data" * ext)
#>
#> if ext == ".csv"
#> CSV.write(out_file, df)
#> else
#> Arrow.write(out_file, df)
#> end
#>
#> println(" Saved ", string(var_name), ": ", nrow(df), " values")
#> end
#> end
#>
#> println("Solution saved successfully\n")
#> end
#>
#> # Save solution after solving
#> if termination_status(model) == MOI.OPTIMAL ||
#> termination_status(model) == MOI.LOCALLY_SOLVED
#>
#> run_name = Dates.format(now(), "yyyy-mm-dd_HHMMSS")
#> solution_dir = joinpath(@__DIR__, "..", "..", "solutions", run_name)
#> save_solution(model, solution_dir, DATA_FORMAT)
#> end