Merge pull request #3482 from JuliaReach/schillic/icp

Bring back IntervalConstraintProgramming in tests

Author: schillic

docs/src/man/optional_dependencies.md

@@ -58,8 +58,6 @@ The package [`IntervalLinearAlgebra`](https://github.com/JuliaIntervals/Interval
 |[`IntervalMatrices`](https://github.com/JuliaReach/IntervalMatrices.jl) | Set operations that involve matrices whose coefficients are intervals.|
 |[`TaylorModels`](https://github.com/JuliaIntervals/TaylorModels.jl) |Taylor expansion of functions with rigorous interval remainder.|
 
-Note: `IntervalConstraintProgramming` is currently not tested due to compatibility issues.
-
 ## Optimization algorithms
 
 Some computations require use of external numerical optimization solvers. The modeling language [`JuMP`](https://github.com/jump-dev/JuMP.jl) is loaded by default, together with the [GLPK](https://en.wikipedia.org/wiki/GNU_Linear_Programming_Kit) solver for linear programs (LPs). Other solvers can be loaded on-demand, even commercial ones, provided that you have the appropriate license. See JuMP's [documentation page on supported solvers](https://jump.dev/JuMP.jl/stable/installation/#Supported-solvers) for further details.

src/Approximations/overapproximate.jl

@@ -641,7 +641,7 @@ function load_paving_overapproximation()
         converted into hyperrectangles, and then calculates the support function of the
         set along each  direction in dirs, to compute the `HPolyhedron` constraints.
 
-        ### Requires IntervalConstraintProgramming
+        This algorithm requires the IntervalConstraintProgramming package.
         """
         function overapproximate(p::Paving{L,N}, dirs::AbstractDirections{N,VN}) where {L,N,VN}
             # enclose outer approximation

test/Approximations/overapproximate.jl

@@ -513,13 +513,12 @@ for N in [Float64]
     cap = overapproximate(Z ∩ L, OctDirections)
     @test (L ∩ Z) ⊆ cap
 
-    # NOTE: ICP currently leads to unsatisfiable package requirements
     # overapproximate a nonlinear constraint with an HPolyhedron
-    #     dom = IntervalBox(interval(-2, 2), interval(-2, 2))
-    #     C = @constraint x^2 + y^2 <= 1
-    #     p = pave(C, dom, 0.01)
-    #     dirs = OctDirections(2)
-    #     H = overapproximate(p, dirs)
-    #     B2 = Ball2(N[0, 0], N(1))
-    #     @test B2 ⊆ H
+    dom = IntervalBox(interval(-2, 2), interval(-2, 2))
+    C = ICP.@constraint x^2 + y^2 <= 1
+    p = ICP.pave(C, dom, 0.01)
+    dirs = OctDirections(2)
+    H = overapproximate(p, dirs)
+    B2 = Ball2(N[0, 0], N(1))
+    @test B2 ⊆ H
 end

test/Project.toml

@@ -7,6 +7,7 @@ ExponentialUtilities = "d4d017d3-3776-5f7e-afef-a10c40355c18"
 GLPK = "60bf3e95-4087-53dc-ae20-288a0d20c6a6"
 GR = "28b8d3ca-fb5f-59d9-8090-bfdbd6d07a71"
 IntervalArithmetic = "d1acc4aa-44c8-5952-acd4-ba5d80a2a253"
+IntervalConstraintProgramming = "138f1668-1576-5ad7-91b9-7425abbf3153"
 IntervalMatrices = "5c1f47dc-42dd-5697-8aaa-4d102d140ba9"
 Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
@@ -37,6 +38,7 @@ ExponentialUtilities = "1"
 GLPK = "0.11 - 0.15, 1"
 GR = "0"
 IntervalArithmetic = "0.15 - 0.21, =0.21.2"  # v0.22 removed IntervalBox
+IntervalConstraintProgramming = "0.9 - 0.13"
 IntervalMatrices = "0.8 - 0.10"
 Ipopt = "1"
 JuMP = "0.21 - 0.23, 1"

test/runtests.jl

@@ -10,7 +10,8 @@ Random.seed!(1234)
 # Optional dependencies
 # ========================
 import Distributions, ExponentialUtilities, Expokit, IntervalMatrices, Ipopt,
-       MiniQhull, Optim, RangeEnclosures, SCS, SetProg, TaylorModels
+       MiniQhull, Optim, PkgVersion, RangeEnclosures, SCS, SetProg, TaylorModels
+import IntervalConstraintProgramming as ICP
 import IntervalArithmetic as IA
 using IntervalArithmetic: IntervalBox, interval
 @static if VERSION >= v"1.9"
@@ -23,8 +24,6 @@ else
 end
 using IntervalMatrices: ±, IntervalMatrix
 using TaylorModels: set_variables, TaylorModelN
-# ICP currently leads to unsatisfiable package requirements
-# using IntervalConstraintProgramming
 using Symbolics
 
 # ==============================