Fix instance of NaNMath.acos

Project.toml

@@ -1,7 +1,7 @@
 name = "McCormick"
 uuid = "53c679d3-6890-5091-8386-c291e8c8aaa1"
 authors = ["Matthew Wilhelm <matthew.wilhelm@uconn.edu>"]
-version = "0.13.9"
+version = "0.13.10"
 
 [deps]
 DiffRules = "b552c78f-8df3-52c6-915a-8e097449b14b"

src/McCormick.jl

@@ -202,8 +202,8 @@ end
 """
 $(TYPEDSIGNATURES)
 
-Takes the concave relaxation gradient 'cc_grad', the convex relaxation gradient
-'cv_grad', and the index of the midpoint returned 'id' and outputs the appropriate
+Takes the concave relaxation gradient `cc_grad`, the convex relaxation gradient
+`cv_grad`, and the index of the midpoint returned `id` and outputs the appropriate
 gradient according to McCormick relaxation rules.
 """
 function mid_grad(cc_grad::SVector{N,Float64}, cv_grad::SVector{N,Float64}, id::Int64) where N
@@ -218,8 +218,8 @@ end
 """
 $(TYPEDSIGNATURES)
 
-Calculates the value of the slope line segment between `(xL, f(xL))` and `(xU, f(xU))`
-defaults to evaluating the derivative of the function if the interval is tight.
+Calculates the value and the slope of the line segment between `(xL, f(xL))` and `(xU, f(xU))`.
+Defaults to evaluating the derivative of the function if the interval is tight.
 """
 @inline function dline_seg(f::Function, df::Function, x::Float64, xL::Float64, xU::Float64)
     delta = xU - xL
@@ -266,7 +266,7 @@ end
 $(TYPEDSIGNATURES)
 
 Refines convex/concave relaxations `cv` and `cc` with associated subgradients
-`cv_grad` and `cc_grad` by intersecting them with the interval boudns `xL`
+`cv_grad` and `cc_grad` by intersecting them with the interval bounds `xL`
 and `xU`.
 """
 function cut(xL::Float64, xU::Float64, cv::Float64, cc::Float64,

src/forward_operators/mixed_convexity.jl

@@ -314,7 +314,7 @@ end
         flag && (p = golden_section(xL, 0.0, acos_env, xU, 0.0))
     end
     (x <= p) && (return NaNMath.acos(x), -1.0/NaNMath.sqrt(1.0-x^2), p)
-    return dline_seg(acos, acos_deriv, x, p, xU)..., p
+    return dline_seg(NaNMath.acos, acos_deriv, x, p, xU)..., p
 end
 
 @inline asinh_deriv(x::Float64) = 1.0/sqrt(1.0 + x^2)