Merge pull request #86 from SciML/simplehally

Halley -> SimpleHalley
SciML · Oct 17, 2023 · 7c92a08 · 7c92a08
2 parents e2f84c6 + ebb501f
commit 7c92a08
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diff --git a/lib/SimpleNonlinearSolve/src/SimpleNonlinearSolve.jl b/lib/SimpleNonlinearSolve/src/SimpleNonlinearSolve.jl
@@ -64,7 +64,7 @@ import PrecompileTools
 PrecompileTools.@compile_workload begin
     for T in (Float32, Float64)
         prob_no_brack = NonlinearProblem{false}((u, p) -> u .* u .- p, T(0.1), T(2))
-        for alg in (SimpleNewtonRaphson, Halley, Broyden, Klement, SimpleTrustRegion,
+        for alg in (SimpleNewtonRaphson, SimpleHalley, Broyden, Klement, SimpleTrustRegion,
             SimpleDFSane)
             solve(prob_no_brack, alg(), abstol = T(1e-2))
         end
@@ -88,8 +88,7 @@ PrecompileTools.@compile_workload begin
     end
 end
 
-# DiffEq styled algorithms
-export Bisection, Brent, Broyden, LBroyden, SimpleDFSane, Falsi, Halley, Klement,
+export Bisection, Brent, Broyden, LBroyden, SimpleDFSane, Falsi, SimpleHalley, Klement,
     Ridder, SimpleNewtonRaphson, SimpleTrustRegion, Alefeld, ITP
 export BatchedBroyden, BatchedSimpleNewtonRaphson, BatchedSimpleDFSane
 

diff --git a/lib/SimpleNonlinearSolve/src/halley.jl b/lib/SimpleNonlinearSolve/src/halley.jl
@@ -1,10 +1,10 @@
 """
 ```julia
-Halley(; chunk_size = Val{0}(), autodiff = Val{true}(),
+SimpleHalley(; chunk_size = Val{0}(), autodiff = Val{true}(),
                                  diff_type = Val{:forward})
 ```
 
-A low-overhead implementation of Halley's Method. This method is non-allocating on scalar
+A low-overhead implementation of SimpleHalley's Method. This method is non-allocating on scalar
 and static array problems.
 
 !!! note
@@ -28,16 +28,16 @@ and static array problems.
   `Val{:forward}` for forward finite differences. For more details on the choices, see the
   [FiniteDiff.jl](https://github.com/JuliaDiff/FiniteDiff.jl) documentation.
 """
-struct Halley{CS, AD, FDT} <: AbstractNewtonAlgorithm{CS, AD, FDT}
-    function Halley(; chunk_size = Val{0}(), autodiff = Val{true}(),
+struct SimpleHalley{CS, AD, FDT} <: AbstractNewtonAlgorithm{CS, AD, FDT}
+    function SimpleHalley(; chunk_size = Val{0}(), autodiff = Val{true}(),
         diff_type = Val{:forward})
         new{SciMLBase._unwrap_val(chunk_size), SciMLBase._unwrap_val(autodiff),
             SciMLBase._unwrap_val(diff_type)}()
     end
 end
 
 function SciMLBase.__solve(prob::NonlinearProblem,
-    alg::Halley, args...; abstol = nothing,
+    alg::SimpleHalley, args...; abstol = nothing,
     reltol = nothing,
     maxiters = 1000, kwargs...)
     f = Base.Fix2(prob.f, prob.p)
@@ -49,7 +49,7 @@ function SciMLBase.__solve(prob::NonlinearProblem,
     T = typeof(x)
 
     if SciMLBase.isinplace(prob)
-        error("Halley currently only supports out-of-place nonlinear problems")
+        error("SimpleHalley currently only supports out-of-place nonlinear problems")
     end
 
     atol = abstol !== nothing ? abstol :

diff --git a/lib/SimpleNonlinearSolve/test/basictests.jl b/lib/SimpleNonlinearSolve/test/basictests.jl
@@ -56,10 +56,10 @@ if VERSION >= v"1.7"
     @test (@ballocated benchmark_scalar(sf, csu0)) == 0
 end
 
-# Halley
+# SimpleHalley
 function benchmark_scalar(f, u0)
     probN = NonlinearProblem{false}(f, u0)
-    sol = (solve(probN, Halley()))
+    sol = (solve(probN, SimpleHalley()))
 end
 
 function ff(u, p)
@@ -139,7 +139,7 @@ using ForwardDiff
 f, u0 = (u, p) -> u .* u .- p, @SVector[1.0, 1.0]
 
 for alg in (SimpleNewtonRaphson(), LBroyden(), Klement(), SimpleTrustRegion(),
-    SimpleDFSane(), Halley(), BROYDEN_SOLVERS...)
+    SimpleDFSane(), SimpleHalley(), BROYDEN_SOLVERS...)
     g = function (p)
         probN = NonlinearProblem{false}(f, csu0, p)
         sol = solve(probN, alg, abstol = 1e-9)
@@ -162,7 +162,7 @@ end
 # Scalar
 f, u0 = (u, p) -> u * u - p, 1.0
 for alg in (SimpleNewtonRaphson(), Klement(), SimpleTrustRegion(),
-    SimpleDFSane(), Halley(), BROYDEN_SOLVERS..., LBROYDEN_SOLVERS...)
+    SimpleDFSane(), SimpleHalley(), BROYDEN_SOLVERS..., LBROYDEN_SOLVERS...)
     g = function (p)
         probN = NonlinearProblem{false}(f, oftype(p, u0), p)
         sol = solve(probN, alg)
@@ -271,7 +271,7 @@ for alg in [Bisection(), Falsi(), Ridder(), Brent(), ITP()]
 end
 
 for alg in (SimpleNewtonRaphson(), Klement(), SimpleTrustRegion(),
-    SimpleDFSane(), Halley(), BROYDEN_SOLVERS..., LBROYDEN_SOLVERS...)
+    SimpleDFSane(), SimpleHalley(), BROYDEN_SOLVERS..., LBROYDEN_SOLVERS...)
     global g, p
     g = function (p)
         probN = NonlinearProblem{false}(f, 0.5, p)
@@ -288,7 +288,7 @@ probN = NonlinearProblem(f, u0)
 
 for alg in (SimpleNewtonRaphson(), SimpleNewtonRaphson(; autodiff = false),
     SimpleTrustRegion(),
-    SimpleTrustRegion(; autodiff = false), Halley(), Halley(; autodiff = false),
+    SimpleTrustRegion(; autodiff = false), SimpleHalley(), SimpleHalley(; autodiff = false),
     Klement(), SimpleDFSane(),
     BROYDEN_SOLVERS..., LBROYDEN_SOLVERS...)
     sol = solve(probN, alg)