Update jac_lin_coord methods

docs/src/guidelines.md

@@ -68,7 +68,7 @@ The following functions should be defined:
   - `cons_nln!(nlp, x, c)`
   - `jac_lin_structure!(nlp, jrows, jcols)`
   - `jac_nln_structure!(nlp, jrows, jcols)`
-  - `jac_lin_coord!(nlp, x, jvals)`
+  - `jac_lin_coord!(nlp, jvals)`
   - `jac_nln_coord!(nlp, x, jvals)`
   - `jprod_lin!(nlp, x, v, Jv)`
   - `jprod_nln!(nlp, x, v, Jv)`

src/nlp/api.jl

@@ -1,3 +1,5 @@
+using Base: @deprecate
+
 export obj, grad, grad!, objgrad, objgrad!, objcons, objcons!
 export cons, cons!, cons_lin, cons_lin!, cons_nln, cons_nln!
 export jth_con, jth_congrad, jth_congrad!, jth_sparse_congrad
@@ -307,36 +309,43 @@ function jac(nlp::AbstractNLPModel, x::AbstractVector)
 end
 
 """
-    vals = jac_lin_coord!(nlp, x, vals)
+    vals = jac_lin_coord!(nlp, vals)
 
-Evaluate ``J(x)``, the linear constraints Jacobian at `x` in sparse coordinate format,
+Evaluate the linear constraints Jacobian in sparse coordinate format,
 overwriting `vals`.
 """
 function jac_lin_coord! end
 
+# Deprecated version with x parameter
+@deprecate jac_lin_coord!(nlp::AbstractNLPModel, x::AbstractVector, vals::AbstractVector) jac_lin_coord!(nlp, vals)
+
 """
-    vals = jac_lin_coord(nlp, x)
+    vals = jac_lin_coord(nlp)
 
-Evaluate ``J(x)``, the linear constraints Jacobian at `x` in sparse coordinate format.
+Evaluate the linear constraints Jacobian in sparse coordinate format.
 """
-function jac_lin_coord(nlp::AbstractNLPModel{T, S}, x::AbstractVector) where {T, S}
-  @lencheck nlp.meta.nvar x
+function jac_lin_coord(nlp::AbstractNLPModel{T, S}) where {T, S}
   vals = S(undef, nlp.meta.lin_nnzj)
-  return jac_lin_coord!(nlp, x, vals)
+  return jac_lin_coord!(nlp, vals)
 end
 
+# Deprecated version with x parameter
+@deprecate jac_lin_coord(nlp::AbstractNLPModel, x::AbstractVector) jac_lin_coord(nlp)
+
 """
-    Jx = jac_lin(nlp, x)
+    Jx = jac_lin(nlp)
 
-Evaluate ``J(x)``, the linear constraints Jacobian at `x` as a sparse matrix.
+Evaluate the linear constraints Jacobian as a sparse matrix.
 """
-function jac_lin(nlp::AbstractNLPModel, x::AbstractVector)
-  @lencheck nlp.meta.nvar x
+function jac_lin(nlp::AbstractNLPModel)
   rows, cols = jac_lin_structure(nlp)
-  vals = jac_lin_coord(nlp, x)
+  vals = jac_lin_coord(nlp)
   sparse(rows, cols, vals, nlp.meta.nlin, nlp.meta.nvar)
 end
 
+# Deprecated version with x parameter
+@deprecate jac_lin(nlp::AbstractNLPModel, x::AbstractVector) jac_lin(nlp)
+
 """
     vals = jac_nln_coord!(nlp, x, vals)
 
@@ -736,37 +745,40 @@ function jac_op!(
 end
 
 """
-    J = jac_lin_op(nlp, x)
+    J = jac_lin_op(nlp)
 
-Return the linear Jacobian at `x` as a linear operator.
+Return the linear Jacobian as a linear operator.
 The resulting object may be used as if it were a matrix, e.g., `J * v` or
 `J' * v`.
 """
-function jac_lin_op(nlp::AbstractNLPModel{T, S}, x::AbstractVector) where {T, S}
-  @lencheck nlp.meta.nvar x
+function jac_lin_op(nlp::AbstractNLPModel{T, S}) where {T, S}
   Jv = S(undef, nlp.meta.nlin)
   Jtv = S(undef, nlp.meta.nvar)
-  return jac_lin_op!(nlp, x, Jv, Jtv)
+  return jac_lin_op!(nlp, Jv, Jtv)
 end
 
+# Deprecated version with x parameter
+@deprecate jac_lin_op(nlp::AbstractNLPModel, x::AbstractVector) jac_lin_op(nlp)
+
 """
-    J = jac_lin_op!(nlp, x, Jv, Jtv)
+    J = jac_lin_op!(nlp, Jv, Jtv)
 
-Return the linear Jacobian at `x` as a linear operator.
+Return the linear Jacobian as a linear operator.
 The resulting object may be used as if it were a matrix, e.g., `J * v` or
 `J' * v`. The values `Jv` and `Jtv` are used as preallocated storage for the
 operations.
 """
 function jac_lin_op!(
   nlp::AbstractNLPModel{T, S},
-  x::AbstractVector{T},
   Jv::AbstractVector,
   Jtv::AbstractVector,
 ) where {T, S}
-  @lencheck nlp.meta.nvar x Jtv
   @lencheck nlp.meta.nlin Jv
+  @lencheck nlp.meta.nvar Jtv
   prod! = @closure (res, v, α, β) -> begin # res = α * J * v + β * res
-    jprod_lin!(nlp, x, v, Jv)
+    rows, cols = jac_lin_structure(nlp)
+    vals = jac_lin_coord(nlp)
+    jprod_lin!(nlp, rows, cols, vals, v, Jv)
     if β == 0
       res .= α .* Jv
     else
@@ -775,7 +787,9 @@ function jac_lin_op!(
     return res
   end
   ctprod! = @closure (res, v, α, β) -> begin
-    jtprod_lin!(nlp, x, v, Jtv)
+    rows, cols = jac_lin_structure(nlp)
+    vals = jac_lin_coord(nlp)
+    jtprod_lin!(nlp, rows, cols, vals, v, Jtv)
     if β == 0
       res .= α .* Jtv
     else
@@ -786,6 +800,9 @@ function jac_lin_op!(
   return LinearOperator{T}(nlp.meta.nlin, nlp.meta.nvar, false, false, prod!, ctprod!, ctprod!)
 end
 
+# Deprecated version with x parameter  
+@deprecate jac_lin_op!(nlp::AbstractNLPModel, x::AbstractVector, Jv::AbstractVector, Jtv::AbstractVector) jac_lin_op!(nlp, Jv, Jtv)
+
 """
     J = jac_lin_op!(nlp, rows, cols, vals, Jv, Jtv)
 

test/nlp/api.jl

@@ -30,7 +30,7 @@
   @test cons_lin(nlp, x) == c(x)[1:1]
   @test jac(nlp, x) ≈ J(x)
   @test jac_nln(nlp, x) ≈ J(x)[2:2, :]
-  @test jac_lin(nlp, x) ≈ J(x)[1:1, :]
+  @test jac_lin(nlp) ≈ J(x)[1:1, :]
   @test jprod(nlp, x, v) ≈ J(x) * v
   @test jprod_nln(nlp, x, v) ≈ J(x)[2:2, :] * v
   @test jprod_lin(nlp, x, v) ≈ J(x)[1:1, :] * v
@@ -56,12 +56,12 @@
   @test jprod!(nlp, jac_structure(nlp)..., jac_coord(nlp, x), v, Jv) ≈ J(x) * v
   @test jprod_nln!(nlp, jac_nln_structure(nlp)..., jac_nln_coord(nlp, x), v, Jv[2:2]) ≈
         J(x)[2:2, :] * v
-  @test jprod_lin!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp, x), v, Jv[1:1]) ≈
+  @test jprod_lin!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp), v, Jv[1:1]) ≈
         J(x)[1:1, :] * v
   @test jtprod!(nlp, jac_structure(nlp)..., jac_coord(nlp, x), w, Jtw) ≈ J(x)' * w
   @test jtprod_nln!(nlp, jac_nln_structure(nlp)..., jac_nln_coord(nlp, x), w[2:2], Jtw) ≈
         J(x)[2:2, :]' * w[2:2]
-  @test jtprod_lin!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp, x), w[1:1], Jtw) ≈
+  @test jtprod_lin!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp), w[1:1], Jtw) ≈
         J(x)[1:1, :]' * w[1:1]
   Jop = jac_op!(nlp, x, Jv, Jtw)
   @test Jop * v ≈ J(x) * v
@@ -91,14 +91,14 @@
   @test mul!(w[2:2], Jop, v, 1.0, -1.0) ≈ res
   res = J(x)[2:2, :]' * w[2:2] - v
   @test mul!(v, Jop', w[2:2], 1.0, -1.0) ≈ res
-  Jop = jac_lin_op!(nlp, x, Jv[1:1], Jtw)
+  Jop = jac_lin_op!(nlp, Jv[1:1], Jtw)
   @test Jop * v ≈ J(x)[1:1, :] * v
   @test Jop' * w[1:1] ≈ Jtw
   res = J(x)[1:1, :] * v - w[1:1]
   @test mul!(w[1:1], Jop, v, 1.0, -1.0) ≈ res
   res = J(x)[1:1, :]' * w[1:1] - v
   @test mul!(v, Jop', w[1:1], 1.0, -1.0) ≈ res
-  Jop = jac_lin_op!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp, x), Jv[1:1], Jtw)
+  Jop = jac_lin_op!(nlp, jac_lin_structure(nlp)..., jac_lin_coord(nlp), Jv[1:1], Jtw)
   @test Jop * v ≈ J(x)[1:1, :] * v
   @test Jop' * w[1:1] ≈ Jtw
   res = J(x)[1:1, :] * v - w[1:1]

test/nlp/dummy-model.jl

@@ -28,6 +28,6 @@ end
   @test_throws(MethodError, ghjvprod!(model, [0.0], [1.0], [2.0], [3.0]))
   @assert isa(hess_op(model, [0.0]), LinearOperator)
   @assert isa(jac_op(model, [0.0]), LinearOperator)
-  @assert isa(jac_lin_op(model, [0.0]), LinearOperator)
+  @assert isa(jac_lin_op(model), LinearOperator)
   @assert isa(jac_nln_op(model, [0.0]), LinearOperator)
 end

test/nlp/simple-model.jl

@@ -139,8 +139,8 @@ function NLPModels.jac_nln_coord!(nlp::SimpleNLPModel, x::AbstractVector, vals::
   return vals
 end
 
-function NLPModels.jac_lin_coord!(nlp::SimpleNLPModel, x::AbstractVector, vals::AbstractVector)
-  @lencheck 2 x vals
+function NLPModels.jac_lin_coord!(nlp::SimpleNLPModel, vals::AbstractVector)
+  @lencheck 2 vals
   increment!(nlp, :neval_jac_lin)
   vals .= [1, -2]
   return vals