add version without kwargs

JuliaReach · Oct 13, 2018 · 3fbf13a · 3fbf13a
1 parent b2cf366
commit 3fbf13a
Show file tree

Hide file tree

Showing 5 changed files with 76 additions and 28 deletions.
diff --git a/src/CartesianProduct.jl b/src/CartesianProduct.jl
@@ -111,11 +111,9 @@ end
 
 @inline function ρ_helper(d::AbstractVector{N},
                           cp::CartesianProduct{N},
-                          ρ_rec::Function;
-                          kwargs...) where {N<:Real}
+                          ρ_rec::Function) where {N<:Real}
     n1 = dim(cp.X)
-    return ρ_rec(d[1:n1], cp.X; kwargs...) +
-           ρ_rec(d[n1+1:length(d)], cp.Y; kwargs...)
+    return ρ_rec(d[1:n1], cp.X) + ρ_rec(d[n1+1:length(d)], cp.Y)
 end
 
 """
@@ -348,13 +346,12 @@ end
 
 @inline function ρ_helper(d::AbstractVector{N},
                           cpa::CartesianProductArray{N},
-                          ρ_rec::Function;
-                          kwargs...) where {N<:Real}
+                          ρ_rec::Function) where {N<:Real}
     sfun = zero(N)
     i0 = 1
     for Xi in cpa.array
         i1 = i0 + dim(Xi) - 1
-        sfun += ρ_rec(d[i0:i1], Xi; kwargs...)
+        sfun += ρ_rec(d[i0:i1], Xi)
         i0 = i1 + 1
     end
     return sfun

diff --git a/src/ConvexHull.jl b/src/ConvexHull.jl
@@ -103,9 +103,8 @@ end
 
 @inline function ρ_helper(d::AbstractVector{N},
                           ch::ConvexHull{N},
-                          ρ_rec::Function;
-                          kwargs...) where {N<:Real}
-    return max(ρ_rec(d, ch.X; kwargs...), ρ_rec(d, ch.Y; kwargs...))
+                          ρ_rec::Function) where {N<:Real}
+    return max(ρ_rec(d, ch.X), ρ_rec(d, ch.Y))
 end
 
 """
@@ -277,9 +276,8 @@ end
 
 @inline function ρ_helper(d::AbstractVector{N},
                           cha::ConvexHullArray{N},
-                          ρ_rec::Function;
-                          kwargs...) where {N<:Real}
-    return maximum([ρ_rec(d, Xi; kwargs...) for Xi in array(cha)])
+                          ρ_rec::Function) where {N<:Real}
+    return maximum([ρ_rec(d, Xi) for Xi in array(cha)])
 end
 
 """

diff --git a/src/ExponentialMap.jl b/src/ExponentialMap.jl
@@ -249,11 +249,10 @@ end
 
 @inline function ρ_helper(d::AbstractVector{N},
                           em::ExponentialMap{N},
-                          ρ_rec::Function;
-                          kwargs...) where {N<:Real}
+                          ρ_rec::Function) where {N<:Real}
     d_dense = d isa Vector ? d : Vector(d)
     v = expmv(one(N), transpose(em.spmexp.M), d_dense) # v <- exp(M^T) * d
-    return ρ_rec(v, em.X; kwargs...)
+    return ρ_rec(v, em.X)
 end
 
 """

diff --git a/src/LazySet.jl b/src/LazySet.jl
@@ -60,6 +60,39 @@ abstract type LazySet{N} end
 # --- common LazySet functions ---
 
 
+@inline function ρ_helper(d::AbstractVector{N},
+                          S::LazySet{N},
+                          ρ_rec::Function)::N where {N<:Real}
+    return dot(d, σ(d, S))
+end
+
+ρ_args(kwargs...) = (d, X) -> ρ(d, X, kwargs...)
+
+ρ_upper_bound_args(kwargs...) = (d, X) -> ρ_upper_bound(d, X, kwargs...)
+
+"""
+    ρ(d::AbstractVector{N}, S::LazySet{N})::N where {N<:Real}
+
+Evaluate the support function of a set in a given direction.
+
+### Input
+
+- `d`      -- direction
+- `S`      -- convex set
+
+### Output
+
+The support function of the set `S` in the direction `d`.
+
+### Algorithm
+
+This is the default implementation that relies on the computation of the support
+vector, `σ`.
+"""
+function ρ(d::AbstractVector{N}, X::LazySet{N}) where {N<:Real}
+    return ρ_helper(d, X, ρ)
+end
+
 """
     ρ(d::AbstractVector{N}, S::LazySet{N}; kwargs...)::N where {N<:Real}
 
@@ -80,8 +113,30 @@ The support function of the set `S` in the direction `d`.
 This is the default implementation that relies on the computation of the support
 vector, `σ`.
 """
-function ρ(d::AbstractVector{N}, S::LazySet{N}; kwargs...)::N where {N<:Real}
-    return dot(d, σ(d, S))
+function ρ(d::AbstractVector{N}, X::LazySet{N}, kwargs...) where {N<:Real}
+    return ρ_helper(d, X, ρ_args(kwargs...))
+end
+
+"""
+    ρ_upper_bound(d::AbstractVector{N}, X::LazySet{N}) where {N<:Real}
+
+Return an upper bound of the support function of a given set.
+
+### Input
+
+- `d` -- direction
+- `X` -- set
+
+### Output
+
+An upper bound of the support function of the given set.
+
+### Algorithm
+
+The default implementation of `ρ_upper_bound` is the exact `ρ(d, X)`.
+"""
+function ρ_upper_bound(d::AbstractVector{N}, X::LazySet{N}) where {N<:Real}
+    return ρ_helper(d, X, ρ_upper_bound)
 end
 
 """
@@ -93,8 +148,9 @@ Return an upper bound of the support function of a given set.
 
 ### Input
 
-- `d` -- direction
-- `X` -- set
+- `d`      -- direction
+- `X`      -- set
+- `kwargs` -- additional keyword arguments
 
 ### Output
 
@@ -105,9 +161,9 @@ An upper bound of the support function of the given set.
 The default implementation of `ρ_upper_bound` is the exact `ρ(d, X)`.
 """
 function ρ_upper_bound(d::AbstractVector{N},
-                       X::LazySet{N};
+                       X::LazySet{N},
                        kwargs...) where {N<:Real}
-    return ρ(d, X)
+    return ρ_helper(d, X, ρ_upper_bound_args(kwargs...))
 end
 
 """

diff --git a/src/MinkowskiSum.jl b/src/MinkowskiSum.jl
@@ -112,9 +112,8 @@ end
 
 @inline function ρ_helper(d::AbstractVector{N},
                           ms::MinkowskiSum{N},
-                          ρ_rec::Function;
-                          kwargs...) where {N<:Real}
-    return ρ_rec(d, ms.X; kwargs...) + ρ_rec(d, ms.Y; kwargs...)
+                          ρ_rec::Function) where {N<:Real}
+    return ρ_rec(d, ms.X) + ρ_rec(d, ms.Y)
 end
 
 """
@@ -273,9 +272,8 @@ end
 
 @inline function ρ_helper(d::AbstractVector{N},
                           msa::MinkowskiSumArray{N},
-                          ρ_rec::Function;
-                          kwargs...) where {N<:Real}
-    return sum([ρ_rec(d, Xi; kwargs...) for Xi in msa.array])
+                          ρ_rec::Function) where {N<:Real}
+    return sum([ρ_rec(d, Xi) for Xi in msa.array])
 end
 
 """