mirror of
https://github.com/kalmarek/PropertyT.jl.git
synced 2024-11-19 07:20:28 +01:00
simplify PropertyT.solve due to changes in MOI
This commit is contained in:
parent
5199189e5f
commit
689bae035e
142
src/sos_sdps.jl
142
src/sos_sdps.jl
@ -172,157 +172,37 @@ end
|
||||
# Low-level solve
|
||||
#
|
||||
###############################################################################
|
||||
using MathProgBase
|
||||
|
||||
function solve(m::JuMP.Model, varλ::JuMP.Variable, varP, warmstart=nothing)
|
||||
|
||||
traits = JuMP.ProblemTraits(m, relaxation=false)
|
||||
function solve(m::JuMP.Model, with_optimizer::JuMP.OptimizerFactory, warmstart=nothing)
|
||||
|
||||
set_optimizer(m, with_optimizer)
|
||||
MOIU.attach_optimizer(m)
|
||||
|
||||
JuMP.build(m, traits=traits)
|
||||
if warmstart != nothing
|
||||
p_sol, d_sol, s = warmstart
|
||||
MathProgBase.SolverInterface.setwarmstart!(m.internalModel, p_sol;
|
||||
dual_sol=d_sol, slack=s);
|
||||
end
|
||||
|
||||
MathProgBase.optimize!(m.internalModel)
|
||||
status = MathProgBase.status(m.internalModel)
|
||||
|
||||
λ = MathProgBase.getobjval(m.internalModel)
|
||||
|
||||
warmstart = (m.internalModel.primal_sol, m.internalModel.dual_sol,
|
||||
m.internalModel.slack)
|
||||
|
||||
fillfrominternal!(m, traits)
|
||||
|
||||
P = JuMP.getvalue(varP)
|
||||
λ = JuMP.getvalue(varλ)
|
||||
optimize!(m)
|
||||
status = termination_status(m)
|
||||
|
||||
return status, (λ, P, warmstart)
|
||||
end
|
||||
|
||||
function solve(solverlog::String, model::JuMP.Model, varλ::JuMP.Variable, varP, warmstart=nothing)
|
||||
function solve(solverlog::String, m::JuMP.Model, with_optimizer::JuMP.OptimizerFactory, warmstart=nothing)
|
||||
|
||||
isdir(dirname(solverlog)) || mkpath(dirname(solverlog))
|
||||
|
||||
Base.flush(Base.stdout)
|
||||
status, (λ, P, warmstart) = open(solverlog, "a+") do logfile
|
||||
status, warmstart = open(solverlog, "a+") do logfile
|
||||
redirect_stdout(logfile) do
|
||||
status, (λ, P, warmstart) = PropertyT.solve(model, varλ, varP, warmstart)
|
||||
status, warmstart = PropertyT.solve(m, with_optimizer, warmstart)
|
||||
Base.Libc.flush_cstdio()
|
||||
status, (λ, P, warmstart)
|
||||
status, warmstart
|
||||
end
|
||||
end
|
||||
|
||||
return status, (λ, P, warmstart)
|
||||
end
|
||||
|
||||
###############################################################################
|
||||
#
|
||||
# Copied from JuMP/src/solvers.jl:178
|
||||
#
|
||||
###############################################################################
|
||||
|
||||
function fillfrominternal!(m::JuMP.Model, traits)
|
||||
|
||||
stat::Symbol = MathProgBase.status(m.internalModel)
|
||||
|
||||
numRows, numCols = length(m.linconstr), m.numCols
|
||||
m.objBound = NaN
|
||||
m.objVal = NaN
|
||||
m.colVal = fill(NaN, numCols)
|
||||
m.linconstrDuals = Array{Float64}(undef, 0)
|
||||
|
||||
discrete = (traits.int || traits.sos)
|
||||
|
||||
if stat == :Optimal
|
||||
# If we think dual information might be available, try to get it
|
||||
# If not, return an array of the correct length
|
||||
if discrete
|
||||
m.redCosts = fill(NaN, numCols)
|
||||
m.linconstrDuals = fill(NaN, numRows)
|
||||
else
|
||||
if !traits.conic
|
||||
m.redCosts = try
|
||||
MathProgBase.getreducedcosts(m.internalModel)[1:numCols]
|
||||
catch
|
||||
fill(NaN, numCols)
|
||||
end
|
||||
|
||||
m.linconstrDuals = try
|
||||
MathProgBase.getconstrduals(m.internalModel)[1:numRows]
|
||||
catch
|
||||
fill(NaN, numRows)
|
||||
end
|
||||
elseif !traits.qp && !traits.qc
|
||||
JuMP.fillConicDuals(m)
|
||||
end
|
||||
end
|
||||
else
|
||||
# Problem was not solved to optimality, attempt to extract useful
|
||||
# information anyway
|
||||
|
||||
if traits.lin
|
||||
if stat == :Infeasible
|
||||
m.linconstrDuals = try
|
||||
infray = MathProgBase.getinfeasibilityray(m.internalModel)
|
||||
@assert length(infray) == numRows
|
||||
infray
|
||||
catch
|
||||
@warn("Infeasibility ray (Farkas proof) not available")
|
||||
fill(NaN, numRows)
|
||||
end
|
||||
elseif stat == :Unbounded
|
||||
m.colVal = try
|
||||
unbdray = MathProgBase.getunboundedray(m.internalModel)
|
||||
@assert length(unbdray) == numCols
|
||||
unbdray
|
||||
catch
|
||||
@warn("Unbounded ray not available")
|
||||
fill(NaN, numCols)
|
||||
end
|
||||
end
|
||||
end
|
||||
# conic duals (currently, SOC and SDP only)
|
||||
if !discrete && traits.conic && !traits.qp && !traits.qc
|
||||
if stat == :Infeasible
|
||||
JuMP.fillConicDuals(m)
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
# If the problem was solved, or if it terminated prematurely, try
|
||||
# to extract a solution anyway. This commonly occurs when a time
|
||||
# limit or tolerance is set (:UserLimit)
|
||||
if !(stat == :Infeasible || stat == :Unbounded)
|
||||
try
|
||||
# Do a separate try since getobjval could work while getobjbound does not and vice versa
|
||||
objBound = MathProgBase.getobjbound(m.internalModel) + m.obj.aff.constant
|
||||
m.objBound = objBound
|
||||
catch
|
||||
@warn("objBound could not be obtained")
|
||||
end
|
||||
|
||||
try
|
||||
objVal = MathProgBase.getobjval(m.internalModel) + m.obj.aff.constant
|
||||
colVal = MathProgBase.getsolution(m.internalModel)[1:numCols]
|
||||
# Rescale off-diagonal terms of SDP variables
|
||||
if traits.sdp
|
||||
offdiagvars = JuMP.offdiagsdpvars(m)
|
||||
colVal[offdiagvars] /= sqrt(2)
|
||||
end
|
||||
# Don't corrupt the answers if one of the above two calls fails
|
||||
m.objVal = objVal
|
||||
m.colVal = colVal
|
||||
catch
|
||||
@warn("objVal/colVal could not be obtained")
|
||||
end
|
||||
end
|
||||
|
||||
if traits.conic && m.objSense == :Max
|
||||
m.objBound = -1 * (m.objBound - m.obj.aff.constant) + m.obj.aff.constant
|
||||
m.objVal = -1 * (m.objVal - m.obj.aff.constant) + m.obj.aff.constant
|
||||
end
|
||||
|
||||
return stat
|
||||
return status, warmstart
|
||||
end
|
||||
|
Loading…
Reference in New Issue
Block a user