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v0.2.1 (#13)
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* scimlsensitivity update

* minor adjustment
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@ThummeTo
ThummeTo committed Sep 4, 2024
1 parent 8c3fb0c commit 985e86e
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Showing 2 changed files with 28 additions and 26 deletions.
4 changes: 2 additions & 2 deletions Project.toml
View file
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "FMISensitivity"
uuid = "3e748fe5-cd7f-4615-8419-3159287187d2"
authors = ["TT <[email protected]>", "LM <[email protected]>"]
version = "0.2.0"
version = "0.2.1"

[deps]
FMIBase = "900ee838-d029-460e-b485-d98a826ceef2"
Expand All @@ -11,5 +11,5 @@ SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
[compat]
FMIBase = "1.0.0"
ForwardDiffChainRules = "0.2.0"
SciMLSensitivity = "7.0 - 7.59"
SciMLSensitivity = "7.0 - 7.66"
julia = "1.6"
50 changes: 26 additions & 24 deletions src/sense.jl
View file
Original file line number Diff line number Diff line change
Expand Up @@ -331,7 +331,9 @@ function ChainRulesCore.rrule(::typeof(FMIBase.eval!),
# because they are evaluated at different points in time during ODE solving.
if length(c.solution.snapshots) > 0
sn = getSnapshot(c.solution, t)
apply!(c, sn)
if !isnothing(sn) # sometimes it is -Inf (whyever...)
apply!(c, sn)
end
end

Ω = FMIBase.eval!(cRef, dx, dx_refs, y, y_refs, x, u, u_refs, p, p_refs, ec, ec_idcs, t)
Expand Down Expand Up @@ -1003,7 +1005,7 @@ abstract type FMUSensitivities end
mutable struct FMUJacobian{C, T, F} <: FMUSensitivities
valid::Bool
colored::Bool
component::C
instance::C

mtx::Matrix{T}
jvp::Vector{T}
Expand All @@ -1021,7 +1023,7 @@ mutable struct FMUJacobian{C, T, F} <: FMUSensitivities
validations::Int
colorings::Int

function FMUJacobian{T}(component::C, f_refs::Union{Vector{UInt32}, Tuple{Symbol, Vector{UInt32}}}, x_refs::Union{Vector{UInt32}, Symbol}) where {C, T}
function FMUJacobian{T}(instance::C, f_refs::Union{Vector{UInt32}, Tuple{Symbol, Vector{UInt32}}}, x_refs::Union{Vector{UInt32}, Symbol}) where {C, T}

@assert !isa(f_refs, Tuple) || f_refs[1] == :indicators "`f_refs` is Tuple, it must be `:indicators`"
@assert !isa(x_refs, Symbol) || x_refs == :time "`x_refs` is Symbol, it must be `:time`"
Expand All @@ -1046,7 +1048,7 @@ mutable struct FMUJacobian{C, T, F} <: FMUSensitivities

inst = new{C, T, F}()
inst.f = f
inst.component = component
inst.instance = instance
inst.f_refs = f_refs
inst.f_refs_set = f_refs_set
inst.x_refs = x_refs
Expand All @@ -1068,7 +1070,7 @@ end
mutable struct FMUGradient{C, T, F} <: FMUSensitivities
valid::Bool
colored::Bool
component::C
instance::C

vec::Vector{T}
gvp::Vector{T}
Expand All @@ -1086,7 +1088,7 @@ mutable struct FMUGradient{C, T, F} <: FMUSensitivities
validations::Int
colorings::Int

function FMUGradient{T}(component::C, f_refs::Union{Vector{UInt32}, Tuple{Symbol, Vector{UInt32}}}, x_refs::Union{UInt32, Symbol}) where {C, T}
function FMUGradient{T}(instance::C, f_refs::Union{Vector{UInt32}, Tuple{Symbol, Vector{UInt32}}}, x_refs::Union{UInt32, Symbol}) where {C, T}

@assert !isa(f_refs, Tuple) || f_refs[1] == :indicators "`f_refs` is Tuple, it must be `:indicators`"
@assert !isa(x_refs, Symbol) || x_refs == :time "`x_refs` is Symbol, it must be `:time`"
Expand All @@ -1109,7 +1111,7 @@ mutable struct FMUGradient{C, T, F} <: FMUSensitivities

inst = new{C, T, F}()
inst.f = f
inst.component = component
inst.instance = instance
inst.f_refs = f_refs
inst.f_refs_set = f_refs_set
inst.x_refs = x_refs
Expand All @@ -1129,26 +1131,26 @@ mutable struct FMUGradient{C, T, F} <: FMUSensitivities
end

function f_∂v_∂v(jac::FMUJacobian, dx, x)
setReal(jac.component, jac.x_refs, x; track=false)
getReal!(jac.component, jac.f_refs, dx)
setReal(jac.instance, jac.x_refs, x; track=false)
getReal!(jac.instance, jac.f_refs, dx)
return dx
end

function f_∂e_∂v(jac::FMUJacobian, dx, x)
setReal(jac.component, jac.x_refs, x; track=false)
getEventIndicators!(jac.component, dx, jac.f_refs[2])
setReal(jac.instance, jac.x_refs, x; track=false)
getEventIndicators!(jac.instance, dx, jac.f_refs[2])
return dx
end

function f_∂e_∂t(jac::FMUGradient, dx, x)
setTime(jac.component, x; track=false)
getEventIndicators!(jac.component, dx, jac.f_refs[2])
setTime(jac.instance, x; track=false)
getEventIndicators!(jac.instance, dx, jac.f_refs[2])
return dx
end

function f_∂v_∂t(jac::FMUGradient, dx, x)
setTime(jac.component, x; track=false)
getReal!(jac.component, jac.f_refs, dx)
setTime(jac.instance, x; track=false)
getReal!(jac.instance, jac.f_refs, dx)
return dx
end

Expand Down Expand Up @@ -1191,25 +1193,25 @@ function validate!(jac::FMUJacobian, x::AbstractVector)
rows = length(jac.f_refs)
cols = length(jac.x_refs)

if jac.component.fmu.executionConfig.sensitivity_strategy == :FMIDirectionalDerivative && providesDirectionalDerivatives(jac.component.fmu) && !isa(jac.f_refs, Tuple) && !isa(jac.x_refs, Symbol)
if jac.instance.fmu.executionConfig.sensitivity_strategy == :FMIDirectionalDerivative && providesDirectionalDerivatives(jac.instance.fmu) && !isa(jac.f_refs, Tuple) && !isa(jac.x_refs, Symbol)
# ToDo: use directional derivatives with sparsitiy information!
# ToDo: Optimize allocation (onehot)
# [Note] Jacobian is sampled column by column
for i in 1:cols
getDirectionalDerivative!(jac.component, jac.f_refs, jac.x_refs, onehot(jac.component, cols, i), view(jac.mtx, 1:rows, i))
getDirectionalDerivative!(jac.instance, jac.f_refs, jac.x_refs, onehot(jac.instance, cols, i), view(jac.mtx, 1:rows, i))
end
elseif jac.component.fmu.executionConfig.sensitivity_strategy == :FMIAdjointDerivative && providesAdjointDerivatives(jac.component.fmu) && !isa(jac.f_refs, Tuple) && !isa(jac.x_refs, Symbol)
elseif jac.instance.fmu.executionConfig.sensitivity_strategy == :FMIAdjointDerivative && providesAdjointDerivatives(jac.instance.fmu) && !isa(jac.f_refs, Tuple) && !isa(jac.x_refs, Symbol)
# ToDo: use directional derivatives with sparsitiy information!
# ToDo: Optimize allocation (onehot)
# [Note] Jacobian is sampled row by row
for i in 1:rows
getAdjointDerivative!(jac.component, jac.f_refs, jac.x_refs, onehot(jac.component, rows, i), view(jac.mtx, 1:cols, i))
getAdjointDerivative!(jac.instance, jac.f_refs, jac.x_refs, onehot(jac.instance, rows, i), view(jac.mtx, 1:cols, i))
end
else #if jac.component.fmu.executionConfig.sensitivity_strategy == :FiniteDiff
else #if jac.instance.fmu.executionConfig.sensitivity_strategy == :FiniteDiff
# cache = FiniteDiff.JacobianCache(x)
FiniteDiff.finite_difference_jacobian!(jac.mtx, (_x, _dx) -> (jac.f(jac, _x, _dx)), x) # , cache)
# else
# @assert false "Unknown sensitivity strategy `$(jac.component.fmu.executionConfig.sensitivity_strategy)`."
# @assert false "Unknown sensitivity strategy `$(jac.instance.fmu.executionConfig.sensitivity_strategy)`."
end

jac.validations += 1
Expand All @@ -1219,10 +1221,10 @@ end

function validate!(grad::FMUGradient, x::Real)

if grad.component.fmu.executionConfig.sensitivity_strategy == :FMIDirectionalDerivative && providesDirectionalDerivatives(grad.component.fmu) && !isa(grad.f_refs, Tuple) && !isa(grad.x_refs, Symbol)
if grad.instance.fmu.executionConfig.sensitivity_strategy == :FMIDirectionalDerivative && providesDirectionalDerivatives(grad.instance.fmu) && !isa(grad.f_refs, Tuple) && !isa(grad.x_refs, Symbol)
# ToDo: use directional derivatives with sparsitiy information!
getDirectionalDerivative!(grad.component, grad.f_refs, grad.x_refs, ones(length(jac.f_refs)), grad.vec)
else #if grad.component.fmu.executionConfig.sensitivity_strategy == :FiniteDiff
getDirectionalDerivative!(grad.instance, grad.f_refs, grad.x_refs, ones(length(jac.f_refs)), grad.vec)
else #if grad.instance.fmu.executionConfig.sensitivity_strategy == :FiniteDiff
# cache = FiniteDiff.GradientCache(x)
FiniteDiff.finite_difference_gradient!(grad.vec, (_x, _dx) -> (grad.f(grad, _x, _dx)), x) # , cache)
end
Expand Down

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Registration pull request created: JuliaRegistries/General/114553

Tip: Release Notes

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Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.2.1 -m "<description of version>" 985e86ebd1b1d50aabc01b8d145e1a5d6df9fb48
git push origin v0.2.1

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