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Merged
amontoison merged 1 commit into from
Aug 8, 2025
Merged

Update moi_nls_model.jl #214

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182 changes: 173 additions & 9 deletions src/moi_nls_model.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -271,13 +271,35 @@ function NLPModels.cons_nln!(nls::MathOptNLSModel, x::AbstractVector, c::Abstrac
return c
end

function NLPModels.cons!(nls::MathOptNLSModel, x::AbstractVector, c::AbstractVector)
increment!(nls, :neval_cons)
if nls.meta.nlin > 0
coo_prod!(nls.lincon.jacobian.rows, nls.lincon.jacobian.cols, nls.lincon.jacobian.vals, x, c)
end
if nls.meta.nnln > 0
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
c[nls.meta.nlin + i] =
0.5 * coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, x) + dot(qcon.b, x)
end
end
if nls.meta.nnln > nls.quadcon.nquad
index_nnln = (nls.meta.nlin + nls.quadcon.nquad + 1):(nls.meta.ncon)
MOI.eval_constraint(nls.ceval, view(c, index_nnln), x)
end
end
return c
end

function NLPModels.jac_lin_structure!(
nls::MathOptNLSModel,
rows::AbstractVector{<:Integer},
cols::AbstractVector{<:Integer},
)
view(rows, 1:(nls.lincon.nnzj)) .= nls.lincon.jacobian.rows
view(cols, 1:(nls.lincon.nnzj)) .= nls.lincon.jacobian.cols
index_lin = 1:(nls.lincon.nnzj)
view(rows, index_lin) .= nls.lincon.jacobian.rows
view(cols, index_lin) .= nls.lincon.jacobian.cols
return rows, cols
end

Expand All @@ -289,9 +311,11 @@ function NLPModels.jac_nln_structure!(
if nls.quadcon.nquad > 0
index = 0
for i = 1:(nls.quadcon.nquad)
# qcon.g is the sparsity pattern of the gradient of the quadratic constraint qcon
qcon = nls.quadcon.constraints[i]
view(rows, (index + 1):(index + qcon.nnzg)) .= i
view(cols, (index + 1):(index + qcon.nnzg)) .= qcon.g
ind_quad = (index + 1):(index + qcon.nnzg)
view(rows, ind_quad) .= i
view(cols, ind_quad) .= qcon.g
index += qcon.nnzg
end
end
Expand All @@ -303,17 +327,50 @@ function NLPModels.jac_nln_structure!(
return rows, cols
end

function NLPModels.jac_structure!(
nls::MathOptNLSModel,
rows::AbstractVector{<:Integer},
cols::AbstractVector{<:Integer},
)
if nls.meta.nlin > 0
index_lin = 1:(nls.lincon.nnzj)
view(rows, index_lin) .= nls.lincon.jacobian.rows
view(cols, index_lin) .= nls.lincon.jacobian.cols
end
if nls.meta.nnln > 0
if nls.quadcon.nquad > 0
index = 0
for i = 1:(nls.quadcon.nquad)
# qcon.g is the sparsity pattern of the gradient of the quadratic constraint qcon
qcon = nls.quadcon.constraints[i]
ind_quad = (nls.lincon.nnzj + index + 1):(nls.lincon.nnzj + index + qcon.nnzg)
view(rows, ind_quad) .= nls.meta.nlin .+ i
view(cols, ind_quad) .= qcon.g
index += qcon.nnzg
end
end
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.lincon.nnzj + nls.quadcon.nnzj + 1):(nls.meta.nnzj)
view(rows, ind_nnln) .= nls.meta.nlin .+ nls.quadcon.nquad .+ nls.nlcon.jac_rows
view(cols, ind_nnln) .= nls.nlcon.jac_cols
end
end
return rows, cols
end

function NLPModels.jac_lin_coord!(nls::MathOptNLSModel, x::AbstractVector, vals::AbstractVector)
increment!(nls, :neval_jac_lin)
view(vals, 1:(nls.lincon.nnzj)) .= nls.lincon.jacobian.vals
index_lin = 1:(nls.lincon.nnzj)
view(vals, index_lin) .= nls.lincon.jacobian.vals
return vals
end

function NLPModels.jac_nln_coord!(nls::MathOptNLSModel, x::AbstractVector, vals::AbstractVector)
increment!(nls, :neval_jac_nln)
if nls.quadcon.nquad > 0
index = 0
view(vals, 1:(nls.quadcon.nnzj)) .= 0.0
ind_quad = 1:(nls.quadcon.nnzj)
view(vals, ind_quad) .= 0.0
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
for (j, ind) in enumerate(qcon.b.nzind)
Expand Down Expand Up @@ -341,6 +398,45 @@ function NLPModels.jac_nln_coord!(nls::MathOptNLSModel, x::AbstractVector, vals:
return vals
end

function NLPModels.jac_coord!(nls::MathOptNLSModel, x::AbstractVector, vals::AbstractVector)
increment!(nls, :neval_jac)
if nls.meta.nlin > 0
index_lin = 1:(nls.lincon.nnzj)
view(vals, index_lin) .= nls.lincon.jacobian.vals
end
if nls.meta.nnln > 0
if nls.quadcon.nquad > 0
ind_quad = (nls.lincon.nnzj + 1):(nls.lincon.nnzj + nls.quadcon.nnzj)
view(vals, ind_quad) .= 0.0
index = nls.lincon.nnzj
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
for (j, ind) in enumerate(qcon.b.nzind)
k = qcon.dg[ind]
vals[index + k] += qcon.b.nzval[j]
end
for j = 1:(qcon.nnzh)
row = qcon.A.rows[j]
col = qcon.A.cols[j]
val = qcon.A.vals[j]
k1 = qcon.dg[row]
vals[index + k1] += val * x[col]
if row != col
k2 = qcon.dg[col]
vals[index + k2] += val * x[row]
end
end
index += qcon.nnzg
end
end
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.lincon.nnzj + nls.quadcon.nnzj + 1):(nls.meta.nnzj)
MOI.eval_constraint_jacobian(nls.ceval, view(vals, ind_nnln), x)
end
end
return vals
end

function NLPModels.jprod_lin!(
nls::MathOptNLSModel,
x::AbstractVector,
Expand All @@ -366,18 +462,52 @@ function NLPModels.jprod_nln!(
Jv::AbstractVector,
)
increment!(nls, :neval_jprod_nln)
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
# Jv[i] += (Aᵢ * x + bᵢ)ᵀ * v
qcon = nls.quadcon.constraints[i]
Jv[i] = coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, v) + dot(qcon.b, v)
end
end
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.quadcon.nquad + 1):(nls.meta.nnln)
MOI.eval_constraint_jacobian_product(nls.ceval, view(Jv, ind_nnln), x, v)
end
(nls.meta.nnln == nls.quadcon.nquad) && (Jv .= 0.0)
return Jv
end

function NLPModels.jprod!(
nls::MathOptNLSModel,
x::AbstractVector,
v::AbstractVector,
Jv::AbstractVector,
)
increment!(nls, :neval_jprod)
if nls.meta.nlin > 0
view(Jv, nls.meta.lin) .= 0.0
transpose = false
coo_unsym_add_mul!(
transpose,
nls.lincon.jacobian.rows,
nls.lincon.jacobian.cols,
nls.lincon.jacobian.vals,
v,
Jv,
1.0,
)
end
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
# Jv[i] = (Aᵢ * x + bᵢ)ᵀ * v
qcon = nls.quadcon.constraints[i]
Jv[i] += coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, v) + dot(qcon.b, v)
Jv[nls.meta.nlin + i] =
coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, v) + dot(qcon.b, v)
end
end
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.meta.nlin + nls.quadcon.nquad + 1):(nls.meta.ncon)
MOI.eval_constraint_jacobian_product(nls.ceval, view(Jv, ind_nnln), x, v)
end
return Jv
end

Expand Down Expand Up @@ -410,7 +540,7 @@ function NLPModels.jtprod_nln!(
ind_nnln = (nls.quadcon.nquad + 1):(nls.meta.nnln)
MOI.eval_constraint_jacobian_transpose_product(nls.ceval, Jtv, x, view(v, ind_nnln))
end
(nls.meta.nnln == nls.quadcon.nquad) && (Jtv .= 0.0)
(nls.quadcon.nquad == nls.meta.nnln) && (Jtv .= 0.0)
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
# Jtv += v[i] * (Aᵢ * x + bᵢ)
Expand All @@ -422,6 +552,40 @@ function NLPModels.jtprod_nln!(
return Jtv
end

function NLPModels.jtprod!(
nls::MathOptNLSModel,
x::AbstractVector,
v::AbstractVector,
Jtv::AbstractVector,
)
increment!(nls, :neval_jtprod)
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.meta.nlin + nls.quadcon.nquad + 1):(nls.meta.ncon)
MOI.eval_constraint_jacobian_transpose_product(nls.ceval, Jtv, x, view(v, ind_nnln))
end
(nls.quadcon.nquad == nls.meta.nnln) && (Jtv .= 0.0)
if nls.meta.nlin > 0
transpose = true
coo_unsym_add_mul!(
transpose,
nls.lincon.jacobian.rows,
nls.lincon.jacobian.cols,
nls.lincon.jacobian.vals,
v,
Jtv,
1.0,
)
end
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
coo_sym_add_mul!(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, Jtv, v[nls.meta.nlin + i])
Jtv .+= v[nls.meta.nlin + i] .* qcon.b
end
end
return Jtv
end

function NLPModels.hess_structure!(
nls::MathOptNLSModel,
rows::AbstractVector{<:Integer},
Expand Down
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