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Add availability flags in NLPModelMeta
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‎docs/src/index.md‎

Lines changed: 39 additions & 34 deletions
Original file line numberDiff line numberDiff line change
@@ -79,40 +79,45 @@ See the [Models](@ref), the [Tools](@ref tools-section), or the [API](@ref).
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`NLPModelMeta` objects have the following attributes (with `S <: AbstractVector`):
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82-
Attribute | Type | Notes
83-
------------|--------------------|------------------------------------
84-
`nvar` | `Int ` | number of variables
85-
`x0 ` | `S` | initial guess
86-
`lvar` | `S` | vector of lower bounds
87-
`uvar` | `S` | vector of upper bounds
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`ifix` | `Vector{Int}` | indices of fixed variables
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`ilow` | `Vector{Int}` | indices of variables with lower bound only
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`iupp` | `Vector{Int}` | indices of variables with upper bound only
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`irng` | `Vector{Int}` | indices of variables with lower and upper bound (range)
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`ifree` | `Vector{Int}` | indices of free variables
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`iinf` | `Vector{Int}` | indices of visibly infeasible bounds
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`ncon` | `Int ` | total number of general constraints
95-
`nlin ` | `Int ` | number of linear constraints
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`nnln` | `Int ` | number of nonlinear general constraints
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`y0 ` | `S` | initial Lagrange multipliers
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`lcon` | `S` | vector of constraint lower bounds
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`ucon` | `S` | vector of constraint upper bounds
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`lin ` | `Vector{Int}` | indices of linear constraints
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`nln` | `Vector{Int}` | indices of nonlinear constraints
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`jfix` | `Vector{Int}` | indices of equality constraints
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`jlow` | `Vector{Int}` | indices of constraints of the form c(x) ≥ cl
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`jupp` | `Vector{Int}` | indices of constraints of the form c(x) ≤ cu
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`jrng` | `Vector{Int}` | indices of constraints of the form cl ≤ c(x) ≤ cu
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`jfree` | `Vector{Int}` | indices of "free" constraints (there shouldn't be any)
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`jinf` | `Vector{Int}` | indices of the visibly infeasible constraints
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`nnzo` | `Int ` | number of nonzeros in the gradient
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`nnzj` | `Int ` | number of nonzeros in the sparse Jacobian
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`lin_nnzj` | `Int ` | number of nonzeros in the sparse linear constraints Jacobian
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`nln_nnzj` | `Int ` | number of nonzeros in the sparse nonlinear constraints Jacobian
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`nnzh` | `Int ` | number of nonzeros in the lower triangular part of the sparse Hessian of the Lagrangian
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`minimize` | `Bool ` | true if `optimize == minimize`
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`islp` | `Bool ` | true if the problem is a linear program
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`name` | `String` | problem name
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Attribute | Type | Notes
83+
---------------------|---------------|------------------------------------
84+
`nvar` | `Int` | number of variables
85+
`x0 ` | `S` | initial guess
86+
`lvar` | `S` | vector of lower bounds
87+
`uvar` | `S` | vector of upper bounds
88+
`ifix` | `Vector{Int}` | indices of fixed variables
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`ilow` | `Vector{Int}` | indices of variables with lower bound only
90+
`iupp` | `Vector{Int}` | indices of variables with upper bound only
91+
`irng` | `Vector{Int}` | indices of variables with lower and upper bound (range)
92+
`ifree` | `Vector{Int}` | indices of free variables
93+
`iinf` | `Vector{Int}` | indices of visibly infeasible bounds
94+
`ncon` | `Int` | total number of general constraints
95+
`nlin ` | `Int` | number of linear constraints
96+
`nnln` | `Int` | number of nonlinear general constraints
97+
`y0 ` | `S` | initial Lagrange multipliers
98+
`lcon` | `S` | vector of constraint lower bounds
99+
`ucon` | `S` | vector of constraint upper bounds
100+
`lin ` | `Vector{Int}` | indices of linear constraints
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`nln` | `Vector{Int}` | indices of nonlinear constraints
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`jfix` | `Vector{Int}` | indices of equality constraints
103+
`jlow` | `Vector{Int}` | indices of constraints of the form c(x) ≥ cl
104+
`jupp` | `Vector{Int}` | indices of constraints of the form c(x) ≤ cu
105+
`jrng` | `Vector{Int}` | indices of constraints of the form cl ≤ c(x) ≤ cu
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`jfree` | `Vector{Int}` | indices of "free" constraints (there shouldn't be any)
107+
`jinf` | `Vector{Int}` | indices of the visibly infeasible constraints
108+
`nnzo` | `Int` | number of nonzeros in the gradient
109+
`nnzj` | `Int` | number of nonzeros in the sparse Jacobian
110+
`lin_nnzj` | `Int` | number of nonzeros in the sparse linear constraints Jacobian
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`nln_nnzj` | `Int` | number of nonzeros in the sparse nonlinear constraints Jacobian
112+
`nnzh` | `Int` | number of nonzeros in the lower triangular part of the sparse Hessian of the Lagrangian
113+
`minimize` | `Bool` | true if `optimize == minimize`
114+
`islp` | `Bool` | true if the problem is a linear program
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`name` | `String` | problem name
116+
`jacobian_available` | `Bool` | true if the sparse Jacobian of the constraints is available
117+
`hessian_available` | `Bool` | true if the sparse Hessian of the Lagrangian is available
118+
`Jv_available` | `Bool` | true if the Jacobian-vector product `J * v` is available
119+
`Jtv_available` | `Bool` | true if the transpose Jacobian-vector product `J' * v` is available
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`Hv_available` | `Bool` | true if the Hessian-vector product of the objective or Lagrangian `H * v` is available
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## License
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‎src/nlp/meta.jl‎

Lines changed: 35 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -51,6 +51,11 @@ The following keyword arguments are accepted:
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- `minimize`: true if optimize == minimize
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- `islp`: true if the problem is a linear program
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- `name`: problem name
54+
- `jacobian_available`: indicates whether the sparse Jacobian of the constraints is available
55+
- `hessian_available`: indicates whether the sparse Hessian of the Lagrangian is available
56+
- `Jv_available`: indicates whether the Jacobian-vector product `J * v` is available
57+
- `Jtv_available`: indicates whether the transpose Jacobian-vector product `J' * v` is available
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- `Hv_available`: indicates whether the Hessian-vector product of the objective or Lagrangian `H * v` is available
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`NLPModelMeta` also contains the following attributes, which are computed from the variables above:
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- `nvar`: number of variables
@@ -114,6 +119,12 @@ struct NLPModelMeta{T, S} <: AbstractNLPModelMeta{T, S}
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minimize::Bool
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islp::Bool
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name::String
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123+
jacobian_available::Bool
124+
hessian_available::Bool
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Jv_available::Bool
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Jtv_available::Bool
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Hv_available::Bool
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end
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119130
function NLPModelMeta{T, S}(
@@ -134,9 +145,14 @@ function NLPModelMeta{T, S}(
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nln_nnzj = nnzj - lin_nnzj,
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nnzh = nvar * (nvar + 1) / 2,
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lin = Int[],
137-
minimize = true,
138-
islp = false,
148+
minimize::Bool = true,
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islp::Bool = false,
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name = "Generic",
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jacobian_available::Bool = true,
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hessian_available::Bool = true,
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Jv_available::Bool = true,
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Jtv_available::Bool = true,
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Hv_available::Bool = true,
140156
) where {T, S}
141157
if (nvar < 1) || (ncon < 0)
142158
error("Nonsensical dimensions")
@@ -213,6 +229,11 @@ function NLPModelMeta{T, S}(
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minimize,
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islp,
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name,
232+
jacobian_available,
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hessian_available,
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Jv_available,
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Jtv_available,
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Hv_available,
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)
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end
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@@ -238,9 +259,14 @@ function NLPModelMeta(
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nln_nnzj = meta.nln_nnzj,
239260
nnzh = meta.nnzh,
240261
lin = meta.lin,
241-
minimize = meta.minimize,
242-
islp = meta.islp,
262+
minimize::Bool = meta.minimize,
263+
islp::Bool = meta.islp,
243264
name = meta.name,
265+
jacobian_available::Bool = meta.jacobian_available,
266+
hessian_available::Bool = meta.hessian_available,
267+
Jv_available::Bool = meta.Jv_available,
268+
Jtv_available::Bool = meta.Jtv_available,
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Hv_available::Bool = meta.Hv_available,
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) where {T, S}
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NLPModelMeta{T, S}(
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nvar,
@@ -263,6 +289,11 @@ function NLPModelMeta(
263289
minimize = minimize,
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islp = islp,
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name = name,
292+
jacobian_available = jacobian_available,
293+
hessian_available = hessian_available,
294+
Jv_available = Jv_available,
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Jtv_available = Jtv_available,
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Hv_available = Hv_available,
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)
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end
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