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non mutating gradient #159

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non mutating gradient #159

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30 changes: 29 additions & 1 deletion src/gradients.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -130,7 +130,12 @@ function finite_difference_gradient(
end
end
cache = GradientCache(df, x, fdtype, returntype, inplace)
finite_difference_gradient!(df, f, x, cache, relstep=relstep, absstep=absstep, dir=dir)
if typeof(x) <: AbstractArray && fdtype == Val(:central)
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why the check for AbstractArray? I would think that the non-! call should always do a non-mutating version by default.

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The check for AbstractArray is only because I changed the vector->scalar code and not the scalar->vector code.
Since by #157 , the latter should be replaced with jacobian calls.
Once that is done, x should be restrained to Num.

df = finite_difference_gradient(f, x, cache, relstep=relstep, absstep=absstep, dir=dir)
else
df = finite_difference_gradient!(df,f, x, cache, relstep=relstep, absstep=absstep, dir=dir)
end
return df
end

function finite_difference_gradient!(
Expand Down Expand Up @@ -169,6 +174,29 @@ end

# vector of derivatives of a vector->scalar map by each component of a vector x
# this ignores the value of "inplace", because it doesn't make much sense
function finite_difference_gradient(
f,
x::AbstractVector{<:Number},
cache::GradientCache{T1,T2,T3,T4,fdtype,returntype,inplace};
relstep=default_relstep(fdtype, eltype(x)),
absstep=relstep,
dir=true) where {T1,T2,T3,T4,fdtype,returntype,inplace}

df = deepcopy(x) # how to get correct output type here cache.returntype

if fdtype == Val(:central)
@inbounds for i ∈ eachindex(x)
epsilon = compute_epsilon(fdtype, x[i], relstep, absstep, dir)
c1 = f(setindex(x,x[i]+epsilon ,i))
c2 = f(setindex(x,x[i]-epsilon ,i))
dfi = (c1-c2)/(2epsilon)
df = setindex(df,dfi,i)
end
else
fdtype_error(returntype)
end
df
end
function finite_difference_gradient!(
df,
f,
Expand Down