Add warm start (#1)

* Add warm start to wrapper.

* Fix maybe functionality.

* Add tests warm start.

* Better testing warm start.

* Apply suggestions from code review

Co-Authored-By: Lorenzo Stella <lorenzostella@gmail.com>

* Fix random generation.

.gitignore

@@ -0,0 +1,2 @@
+deps/lib/
+deps/deps.jl

src/wrappers.jl

@@ -224,7 +224,24 @@ mutable struct Results
     Results() = new(Float64[], Float64[], QPALM.Info(), Float64[], Float64[])
 end
 
-function solve!(model::QPALM.Model, results::QPALM.Results=Results())
+function warm_start!(model::QPALM.Model;
+                     x_warm_start::Maybe{Vector{Float64}} = nothing,
+                     y_warm_start::Maybe{Vector{Float64}} = nothing)
+    if model.workspace == C_NULL
+        error("QPALM Model not setup")
+    end
+
+    ccall(
+        (:qpalm_warm_start, LIBQPALM_PATH),
+        Cvoid,
+        (Ptr{QPALM.Workspace}, Ptr{Float64}, Ptr{Float64}),
+        model.workspace,
+        x_warm_start != nothing ? pointer(x_warm_start) : C_NULL,
+        y_warm_start != nothing ? pointer(y_warm_start) : C_NULL,
+    )
+end
+
+function solve!(model::QPALM.Model, results::QPALM.Results=Results())::QPALM.Results
     ccall(
         (:qpalm_solve, LIBQPALM_PATH),
         Cvoid,
@@ -272,11 +289,12 @@ function solve!(model::QPALM.Model, results::QPALM.Results=Results())
         end
     end
 
-    if results.info.status == :Non_convex
-        results.info.obj_val = NaN
-    end
+    # An objective value is not calculated at this moment.
+    # if results.info.status == :Non_convex
+    #     results.info.obj_val = NaN
+    # end
 
-    results
+    return results
 end
 
 function cleanup!(model::QPALM.Model)

test/runtests.jl

@@ -1,4 +1,5 @@
 include("feasible.jl")
 include("infeasible.jl")
+include("warm_start.jl")
 include("linear_programs.jl")
 include("update.jl")

test/warm_start.jl

@@ -0,0 +1,55 @@
+using Test
+
+@testset "Warm start" begin
+
+    using QPALM
+    using LinearAlgebra
+    using SparseArrays
+    using Random
+
+    Random.seed!(0)
+
+    n, m = 10, 20
+    act = 5
+    F = randn(n, n-1)
+    Q = sparse(F*F' + 1e-3*I)
+    A = sparse(randn(m, n))
+    x_star = randn(n)
+    y_star = [rand(act); zeros(m-act)]
+    q = -Q*x_star - A'*y_star
+    b = [A[1:act, :]*x_star; A[act+1:end, :]*x_star + rand(m-act)]
+
+    model = QPALM.Model()
+    QPALM.setup!(model, Q=Q, q=q, A=A, bmax=b)
+    results = QPALM.solve!(model)
+    @test results.info.iter > 5
+
+    @testset "Not setup" begin
+        model = QPALM.Model()
+
+        @test_throws ErrorException QPALM.warm_start!(model, x_warm_start=results.x)
+    end
+
+    @testset "Normal usage (1)" begin
+        model = QPALM.Model()
+
+        QPALM.setup!(model, Q=Q, q=q, A=A, bmax=b)
+        QPALM.warm_start!(model, x_warm_start=results.x, y_warm_start=results.y)
+        res = QPALM.solve!(model)
+        @test res.info.status == :Solved
+        @test res.info.iter < results.info.iter
+    end
+
+    @testset "Normal usage (2)" begin
+        model = QPALM.Model()
+
+        QPALM.setup!(model, Q=Q, q=q, A=A, bmax=b)
+        QPALM.warm_start!(model, y_warm_start=results.y)
+        QPALM.warm_start!(model, x_warm_start=results.x)
+
+        res = QPALM.solve!(model)
+        @test res.info.status == :Solved
+        @test res.info.iter < results.info.iter
+    end
+
+end