Add POI.Parameters #40
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@@ Coverage Diff @@
## master #40 +/- ##
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+ Coverage 90.71% 90.94% +0.22%
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Files 4 4
Lines 528 541 +13
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+ Hits 479 492 +13
Misses 49 49
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Not sure we should create another set for this. Maybe @odow has a suggestion for this... If JuMP is doing something really different we should re-think the way forward and not add much complexity here. |
joaquimg
reviewed
Jul 21, 2021
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@joaquimg indeed there is this version. It works on MOI but it does not work in JuMP, at least the way I tried. using JuMP, ParametricOptInterface, MathOptInterface, GLPK
const POI = ParametricOptInterface
const MOI = MathOptInterface
n = 100
model = Model(() -> POI.ParametricOptimizer(GLPK.Optimizer()))
@variable(model, x[i=1:2] >= 0)
@variable(model, y[i=1:3] in POI.Parameter.(zeros(3)))leads to ERROR: MethodError: no method matching build_variable(::JuMP.var"#_error#108"{LineNumberNode}, ::Vector{ScalarVariable{Float64, Float64, Float64, Float64}}, ::Vector{ParametricOptInterface.Parameter})
Closest candidates are:
build_variable(::Function, ::Vector{var"#s142"} where var"#s142"<:ScalarVariable, ::AbstractVectorSet) at C:\Users\guilhermebodin\.julia\packages\JuMP\Xrr7O\src\sets.jl:14
build_variable(::Function, ::VariableInfo, ::Any...; kwargs...) at C:\Users\guilhermebodin\.julia\packages\JuMP\Xrr7O\src\macros.jl:1340
build_variable(::Function, ::Vector{var"#s142"} where var"#s142"<:ScalarVariable, ::MathOptInterface.AbstractVectorSet) at C:\Users\guilhermebodin\.julia\packages\JuMP\Xrr7O\src\macros.jl:1356
...
Stacktrace:
[1] macro expansion
@ C:\Users\guilhermebodin\.julia\packages\JuMP\Xrr7O\src\macros.jl:142 [inlined]
[2] top-level scope
@ REPL[25]:1 |
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@joaquimg Alternatively we can also make this work by adding these two methods using JuMP, ParametricOptInterface, MathOptInterface, GLPK
const POI = ParametricOptInterface
const MOI = MathOptInterface
n = 100
function JuMP.build_variable(
_error::Function,
variables::Vector{<:ScalarVariable},
sets::Vector{<:MOI.AbstractScalarSet},
)
v = Vector{VariableConstrainedOnCreation}(undef, length(sets))
for i in eachindex(variables)
v[i] = VariableConstrainedOnCreation(variables[i], sets[i])
end
return v
end
function JuMP.add_variable(
model::Model,
variables::Vector{VariableConstrainedOnCreation},
names,
)
var_indices = Vector{MOI.VariableIndex}(undef, length(variables))
for (i, variable) in enumerate(variables)
var_indices[i] = JuMP._moi_add_constrained_variable(
JuMP.backend(model),
variable.scalar_variable,
variable.set,
names[i],
)
end
return [JuMP.VariableRef(model, var_index) for var_index in var_indices]
end
model = Model(() -> POI.ParametricOptimizer(GLPK.Optimizer()))
@variable(model, x[i=1:2] >= 0)
@variable(model, y[i=1:3] in POI.Parameter.(zeros(3)))
@constraint(model, 2*x[1] + x[2] + y[1] <= 4)
@constraint(model, 1*x[1] + 2*x[2] + y[3] <= 4)
@objective(model, Max, 4*x[1] + 3*x[2] + y[2])
optimize!(model)And this would also be possible @variable(model, z[i=1:3] in MOI.LessThan.(zeros(3))) |
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It might be that JuMP is missing those functions. I just don't know if they are not there on purpose. |
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strongly related discussion: jump-dev/JuMP.jl#2148 |
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@joaquimg it works on your branch of JuMP (ParametricOptInterface) pkg> st
Project ParametricOptInterface v0.1.1
Status `C:\Users\guilhermebodin\Documents\Github\ParametricOptInterface.jl\Project.toml`
[4076af6c] JuMP v0.21.9 `https://github.com/jump-dev/JuMP.jl.git#jg/at_var`
[b8f27783] MathOptInterface v0.9.22
julia>
julia> model = Model(() -> POI.ParametricOptimizer(GLPK.Optimizer()));
julia>
julia> @variable(model, x[i=1:2] >= 0)
2-element Vector{VariableRef}:
x[1]
x[2]
julia> @variable(model, y[i=1:3] in POI.Parameter.([1.0, 2.0, 3.0]))
3-element Vector{VariableRef}:
y[1]
y[2]
y[3]
julia>
julia> @constraint(model, 2*x[1] + x[2] + y[1] <= 4)
2 x[1] + x[2] + y[1] <= 4.0
julia> @constraint(model, 1*x[1] + 2*x[2] + y[3] <= 4)
x[1] + 2 x[2] + y[3] <= 4.0
julia>
julia> @objective(model, Max, 4*x[1] + 3*x[2] + y[2])
4 x[1] + 3 x[2] + y[2]
julia>
julia> optimize!(model) |
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Closing this because either we go on with jump-dev/JuMP.jl#2657 or define it outside the package for now. |
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This is a step towards solving #20
Now this works
but this does not
The model gives the following error: