Merge pull request #3292 from JuliaReach/schillic/solvers

Outsource solver code to separate file

src/Initialization/init_Polyhedra.jl

@@ -4,14 +4,6 @@ eval(quote
     using .Polyhedra: HRep, VRep,
                       removehredundancy!, removevredundancy!
 
-    function default_polyhedra_backend(P::LazySet{N}) where {N}
-        if LazySets.dim(P) == 1
-            return default_polyhedra_backend_1d(N)
-        else
-            return default_polyhedra_backend_nd(N)
-        end
-    end
-
     function default_polyhedra_backend_1d(N::Type{<:Number}, solver=nothing)
         return Polyhedra.IntervalLibrary{N}()
     end

src/Interfaces/AbstractPolyhedron_functions.jl

@@ -8,39 +8,6 @@ export constrained_dimensions,
        an_element,
        vertices_list
 
-# default LP solver for floating-point numbers
-function default_lp_solver(N::Type{<:AbstractFloat})
-    JuMP.optimizer_with_attributes(() -> GLPK.Optimizer(method=GLPK.SIMPLEX))
-end
-
-# default LP solver for rational numbers
-function default_lp_solver(N::Type{<:Rational})
-    JuMP.optimizer_with_attributes(() -> GLPK.Optimizer(method=GLPK.EXACT))
-end
-
-# helper function given two possibly different numeric types
-function default_lp_solver(M::Type{<:Number}, N::Type{<:Number})
-    return default_lp_solver(promote_type(M, N))
-end
-
-# Polyhedra backend (fallback method)
-function default_polyhedra_backend(P::LazySet{N}) where {N}
-    require(@__MODULE__, :Polyhedra; fun_name="default_polyhedra_backend")
-    error("no default backend for numeric type $N")
-end
-
-# default LP solver for Polyhedra (fallback method)
-# NOTE: exists in parallel to `default_lp_solver` because we use different
-# interfaces (see #1493)
-function default_lp_solver_polyhedra(N; kwargs...)
-    require(@__MODULE__, :Polyhedra; fun_name="default_lp_solver_polyhedra")
-    error("no default solver for numeric type $N")
-end
-
-function _is_polyhedra_backend(backend)
-    return false
-end
-
 isconvextype(::Type{<:AbstractPolyhedron}) = true
 
 is_polyhedral(::AbstractPolyhedron) = true

src/Interfaces/LazySet.jl

@@ -212,6 +212,16 @@ true
 """
 isconvextype(X::Type{<:LazySet}) = false
 
+# Polyhedra backend (fallback method)
+function default_polyhedra_backend(P::LazySet{N}) where {N}
+    require(@__MODULE__, :Polyhedra; fun_name="default_polyhedra_backend")
+    if LazySets.dim(P) == 1
+        return default_polyhedra_backend_1d(N)
+    else
+        return default_polyhedra_backend_nd(N)
+    end
+end
+
 # Note: this method cannot be documented due to a bug in Julia
 function low(X::LazySet, i::Int)
     return _low(X, i)

src/LazySets.jl

@@ -52,6 +52,7 @@ include("Utils/numbers.jl")
 include("Utils/helper_functions.jl")
 include("Utils/macros.jl")
 include("Utils/matrix_exponential.jl")
+include("Utils/lp_solvers.jl")
 include("Utils/file_formats.jl")
 
 # ==================

src/Utils/lp_solvers.jl

@@ -0,0 +1,27 @@
+# default LP solver for floating-point numbers
+function default_lp_solver(::Type{<:AbstractFloat})
+    JuMP.optimizer_with_attributes(() -> GLPK.Optimizer(method=GLPK.SIMPLEX))
+end
+
+# default LP solver for rational numbers
+function default_lp_solver(::Type{<:Rational})
+    JuMP.optimizer_with_attributes(() -> GLPK.Optimizer(method=GLPK.EXACT))
+end
+
+# default LP solver given two possibly different numeric types
+function default_lp_solver(M::Type{<:Number}, N::Type{<:Number})
+    return default_lp_solver(promote_type(M, N))
+end
+
+# check for Polyhedra backend (fallback method)
+function _is_polyhedra_backend(backend)
+    return false
+end
+
+# default LP solver for Polyhedra (fallback method)
+# NOTE: exists in parallel to `default_lp_solver` because we use different
+# interfaces (see #1493)
+function default_lp_solver_polyhedra(N, kwargs...)
+    require(@__MODULE__, :Polyhedra; fun_name="default_lp_solver_polyhedra")
+    error("no default solver for numeric type $N")
+end