move fillfrominternal! to SDPs.jl
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src/PropertyT.jl
113
src/PropertyT.jl
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@ -160,120 +160,19 @@ function λandP(name::String, SDP_problem::JuMP.Model, varλ, varP, warmstart=fa
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return λ, P
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end
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function fillfrominternal!(m::JuMP.Model, traits)
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# Copied from JuMP/src/solvers.jl:178
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stat::Symbol = MathProgBase.status(m.internalModel)
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numRows, numCols = length(m.linconstr), m.numCols
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m.objBound = NaN
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m.objVal = NaN
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m.colVal = fill(NaN, numCols)
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m.linconstrDuals = Array{Float64}(0)
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discrete = (traits.int || traits.sos)
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if stat == :Optimal
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# If we think dual information might be available, try to get it
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# If not, return an array of the correct length
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if discrete
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m.redCosts = fill(NaN, numCols)
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m.linconstrDuals = fill(NaN, numRows)
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else
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if !traits.conic
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m.redCosts = try
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MathProgBase.getreducedcosts(m.internalModel)[1:numCols]
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catch
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fill(NaN, numCols)
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end
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m.linconstrDuals = try
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MathProgBase.getconstrduals(m.internalModel)[1:numRows]
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catch
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fill(NaN, numRows)
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end
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elseif !traits.qp && !traits.qc
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JuMP.fillConicDuals(m)
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end
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end
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else
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# Problem was not solved to optimality, attempt to extract useful
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# information anyway
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if traits.lin
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if stat == :Infeasible
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m.linconstrDuals = try
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infray = MathProgBase.getinfeasibilityray(m.internalModel)
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@assert length(infray) == numRows
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infray
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catch
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suppress_warnings || warn("Infeasibility ray (Farkas proof) not available")
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fill(NaN, numRows)
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end
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elseif stat == :Unbounded
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m.colVal = try
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unbdray = MathProgBase.getunboundedray(m.internalModel)
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@assert length(unbdray) == numCols
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unbdray
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catch
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suppress_warnings || warn("Unbounded ray not available")
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fill(NaN, numCols)
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end
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end
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end
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# conic duals (currently, SOC and SDP only)
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if !discrete && traits.conic && !traits.qp && !traits.qc
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if stat == :Infeasible
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JuMP.fillConicDuals(m)
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end
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end
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end
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# If the problem was solved, or if it terminated prematurely, try
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# to extract a solution anyway. This commonly occurs when a time
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# limit or tolerance is set (:UserLimit)
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if !(stat == :Infeasible || stat == :Unbounded)
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try
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# Do a separate try since getobjval could work while getobjbound does not and vice versa
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objBound = MathProgBase.getobjbound(m.internalModel) + m.obj.aff.constant
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m.objBound = objBound
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end
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try
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objVal = MathProgBase.getobjval(m.internalModel) + m.obj.aff.constant
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colVal = MathProgBase.getsolution(m.internalModel)[1:numCols]
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# Rescale off-diagonal terms of SDP variables
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if traits.sdp
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offdiagvars = JuMP.offdiagsdpvars(m)
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colVal[offdiagvars] /= sqrt(2)
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end
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# Don't corrupt the answers if one of the above two calls fails
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m.objVal = objVal
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m.colVal = colVal
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end
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end
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return stat
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end
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function compute_λandP(m, varλ, varP; warmstart=nothing)
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λ = 0.0
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P = nothing
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traits = JuMP.ProblemTraits(m, relaxation=false)
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while λ == 0.0
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try
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JuMP.build(m, traits=traits)
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if warmstart != nothing
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p_sol, d_sol, s = warmstart
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MathProgBase.SolverInterface.setwarmstart!(m.internalModel, p_sol; dual_sol = d_sol, slack=s);
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end
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solve_SDP(m)
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λ = MathProgBase.getobjval(m.internalModel)
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catch y
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warn(LOGGER_SOLVER, y)
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end
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JuMP.build(m, traits=traits)
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if warmstart != nothing
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p_sol, d_sol, s = warmstart
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MathProgBase.SolverInterface.setwarmstart!(m.internalModel, p_sol; dual_sol = d_sol, slack=s);
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end
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solve_SDP(m)
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λ = MathProgBase.getobjval(m.internalModel)
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warmstart = (m.internalModel.primal_sol, m.internalModel.dual_sol,
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m.internalModel.slack)
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95
src/SDPs.jl
95
src/SDPs.jl
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@ -73,3 +73,98 @@ function solve_SDP(SDP_problem)
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return 0
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end
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function fillfrominternal!(m::JuMP.Model, traits)
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# Copied from JuMP/src/solvers.jl:178
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stat::Symbol = MathProgBase.status(m.internalModel)
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numRows, numCols = length(m.linconstr), m.numCols
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m.objBound = NaN
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m.objVal = NaN
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m.colVal = fill(NaN, numCols)
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m.linconstrDuals = Array{Float64}(0)
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discrete = (traits.int || traits.sos)
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if stat == :Optimal
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# If we think dual information might be available, try to get it
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# If not, return an array of the correct length
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if discrete
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m.redCosts = fill(NaN, numCols)
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m.linconstrDuals = fill(NaN, numRows)
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else
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if !traits.conic
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m.redCosts = try
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MathProgBase.getreducedcosts(m.internalModel)[1:numCols]
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catch
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fill(NaN, numCols)
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end
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m.linconstrDuals = try
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MathProgBase.getconstrduals(m.internalModel)[1:numRows]
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catch
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fill(NaN, numRows)
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end
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elseif !traits.qp && !traits.qc
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JuMP.fillConicDuals(m)
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end
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end
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else
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# Problem was not solved to optimality, attempt to extract useful
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# information anyway
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if traits.lin
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if stat == :Infeasible
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m.linconstrDuals = try
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infray = MathProgBase.getinfeasibilityray(m.internalModel)
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@assert length(infray) == numRows
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infray
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catch
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suppress_warnings || warn("Infeasibility ray (Farkas proof) not available")
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fill(NaN, numRows)
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end
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elseif stat == :Unbounded
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m.colVal = try
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unbdray = MathProgBase.getunboundedray(m.internalModel)
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@assert length(unbdray) == numCols
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unbdray
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catch
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suppress_warnings || warn("Unbounded ray not available")
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fill(NaN, numCols)
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end
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end
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end
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# conic duals (currently, SOC and SDP only)
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if !discrete && traits.conic && !traits.qp && !traits.qc
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if stat == :Infeasible
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JuMP.fillConicDuals(m)
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end
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end
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end
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# If the problem was solved, or if it terminated prematurely, try
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# to extract a solution anyway. This commonly occurs when a time
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# limit or tolerance is set (:UserLimit)
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if !(stat == :Infeasible || stat == :Unbounded)
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try
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# Do a separate try since getobjval could work while getobjbound does not and vice versa
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objBound = MathProgBase.getobjbound(m.internalModel) + m.obj.aff.constant
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m.objBound = objBound
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end
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try
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objVal = MathProgBase.getobjval(m.internalModel) + m.obj.aff.constant
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colVal = MathProgBase.getsolution(m.internalModel)[1:numCols]
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# Rescale off-diagonal terms of SDP variables
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if traits.sdp
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offdiagvars = JuMP.offdiagsdpvars(m)
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colVal[offdiagvars] /= sqrt(2)
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end
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# Don't corrupt the answers if one of the above two calls fails
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m.objVal = objVal
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m.colVal = colVal
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end
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end
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return stat
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end
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