JuMP appears unable to recognise that a matrix is positive definite

[ASaragga]

*** Please disregard this issue. I didn't notice that there was already a reply to an identical issue I had posted yesterday.

Running the model

model = Model(COSMO.Optimizer)   # or SCS.Optimizer
@variable(model, w[1:6] >= 0)
@constraint(model, sum(w) == 1)
@constraint(model, w' * pcov * w == 0.038)
@objective(model, Max, sum((pmean[i] * w[i]) for i = 1:6))
optimize!(model)
optimal_solution = value.(w)

with

pmean = [0.006719140992780818 0.011577810667787833 0.01344208119264699 0.005535719592233162 0.026922967360723037 0.00934581295816873]
pcov = [0.018717403832096687 0.005706355121276367 0.006459876807928641 0.0012524618528797894 0.002563861720279623 0.0007671488407868487; 0.005706355121276367 0.006526570285541143 0.004384136499235087 0.0011480135148245983 0.0018044216713121253 0.001154428875412326; 0.006459876807928641 0.004384136499235087 0.0054284300755523115 0.0006596834879959167 0.0016581295100441041 0.0007133949662164625; 0.0012524618528797894 0.0011480135148245983 0.0006596834879959167 0.0026543564006455294 0.00048713871877351897 0.0011206346404939; 0.002563861720279623 0.0018044216713121253 0.0016581295100441041 0.00048713871877351897 0.0023567945429189227 0.00043958950944804554; 0.0007671488407868487 0.001154428875412326 0.0007133949662164625 0.0011206346404939 0.00043958950944804554 0.0020143379751173373]

throws the following error:

ERROR: LoadError: The optimizer supports second-order cone constraints and not quadratic constraints but you entered a quadratic constraint of type: `MathOptInterface.ScalarQuadraticFunction{Float64}`-in-`MathOptInterface.GreaterThan{Float64}`. A bridge attempted to transform the quadratic constraint to a second order cone constraint but the constraint is not strongly convex, i.e., the symmetric matrix of quadratic coefficients is not positive definite. Convex constraints that are not strongly convex, i.e. the matrix is positive semidefinite but not positive definite, are not supported yet.

However, the covariance matrix pcov is positive definite (all eigen values > 0) and so the constraint is strongly convex.

[odow]

I moved jump-dev/MathOptInterface.jl#1259 because it related to MathOptInterface.jl, not JuMP.jl.