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Minimal changes to jacobian in calculus.jl to allow for nonsquare Jacobians #372

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merged 3 commits into from
Oct 17, 2024
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Minimal changes to jacobian in calculus.jl to allow for nonsquare Jacobians #372

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dfdef84
allowed for nonsquare jacobians now
gaperez64 Oct 16, 2024
42c1cbf
removed comments
gaperez64 Oct 16, 2024
c7e81c0
eachindex instead of hardcoding indices
gaperez64 Oct 17, 2024
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22 changes: 10 additions & 12 deletions src/calculus.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -252,10 +252,9 @@ evaluated at the vector `vals`. If `vals` is omitted, it is evaluated at zero.
"""
function jacobian(vf::Array{TaylorN{T},1}) where {T<:Number}
numVars = get_numvars()
@assert length(vf) == numVars
jac = Array{T}(undef, numVars, numVars)
jac = Array{T}(undef, numVars, length(vf))

@inbounds for comp = 1:numVars
@inbounds for comp in eachindex(vf)
jac[:,comp] = vf[comp][1][1:end]
end

Expand All @@ -264,10 +263,10 @@ end
function jacobian(vf::Array{TaylorN{T},1}, vals::Array{S,1}) where {T<:Number,S<:Number}
R = promote_type(T,S)
numVars = get_numvars()
@assert length(vf) == numVars == length(vals)
jac = Array{R}(undef, numVars, numVars)
@assert numVars == length(vals)
jac = Array{R}(undef, numVars, length(vf))

for comp = 1:numVars
for comp in eachindex(vf)
@inbounds grad = gradient( vf[comp] )
@inbounds for nv = 1:numVars
jac[nv,comp] = evaluate(grad[nv], vals)
Expand All @@ -294,10 +293,9 @@ it is evaluated at zero.
"""
function jacobian!(jac::Array{T,2}, vf::Array{TaylorN{T},1}) where {T<:Number}
numVars = get_numvars()
@assert length(vf) == numVars
@assert (numVars, numVars) == size(jac)
@assert (length(vf), numVars) == size(jac)
for comp2 = 1:numVars
for comp1 = 1:numVars
for comp1 in eachindex(vf)
@inbounds jac[comp1,comp2] = vf[comp1][1][comp2]
end
end
Expand All @@ -306,10 +304,10 @@ end
function jacobian!(jac::Array{T,2}, vf::Array{TaylorN{T},1},
vals::Array{T,1}) where {T<:Number}
numVars = get_numvars()
@assert length(vf) == numVars == length(vals)
@assert (numVars, numVars) == size(jac)
@assert numVars == length(vals)
@assert (length(vf), numVars) == size(jac)
for comp = 1:numVars
@inbounds for nv = 1:numVars
@inbounds for nv in eachindex(vf)
jac[nv,comp] = evaluate(differentiate(vf[nv], comp), vals)
end
end
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