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add div methods for Dual #121

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add div methods for Dual #121

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7 changes: 7 additions & 0 deletions src/forwarddiff.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,13 @@ for PT in (Particles, StaticParticles)
Dual{T}($PT(value(d) .- p.particles), ntuple(i->$PT(0p.particles .+ partials(d)[i]) ,length(partials(d))))
end

function Base.:(/)(p::$PT, d::Dual{T}) where {T}
Dual{T}($PT(p.particles ./ value(d)), ntuple(i->$PT(0p.particles ./ partials(d)[i]) ,length(partials(d))))
end
function Base.:(/)(d::Dual{T}, p::$PT) where {T}
Dual{T}($PT(value(d) ./ p.particles), ntuple(i->$PT(0p.particles .+ partials(d)[i]) ,length(partials(d))))
end

function Base.promote_rule(::Type{ForwardDiff.Dual{T,V,NP}}, ::Type{$PT{S, N}}) where {T, V, NP, S, N}
VS = promote_type(V,S)
Dual{T, $PT{VS, N}, NP}
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6 changes: 5 additions & 1 deletion test/test_forwarddiff.jl
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Expand Up @@ -8,7 +8,7 @@ const FD = ForwardDiff
# In the cost function below, we ensure that $cx+dy > 10 \; ∀ \; c,d ∈ P$ by looking at the worst case
function cost(params)
x,y = params
-(3x+2y) + 10000sum(params .< 0) + 10000*(pmaximum(c*x+d*y) > 10)
-(3x+2y) + 10000sum(params .< 0) + 10000*(pmaximum(c*x+d*y) > 10) + (x/3)*(3/x) - 1
end

params = [1., 2] # Initial guess
Expand Down Expand Up @@ -55,4 +55,8 @@ const FD = ForwardDiff
@test pmean(pmean(r[2])) != ref[2]

unsafe_comparisons(false)

x = paramsp[1]
@test FD.derivative(x -> x/2, x) == 1/2
@test FD.derivative(x -> 2/x, x) ≈ -2/x^2
end