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Adding time limit to levenberg_marquardt.jl #204

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Adding time limit to levenberg_marquardt.jl #204

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5f4b166
add time limit in levenberg_marquardt.jl
Dec 6, 2021
57ed9db
define stopped_by_time_limit and print message if show_trace and stop…
Dec 6, 2021
b3d0e4a
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pkofod Sep 2, 2022
2307059
Merge branch 'master' into master
pkofod Sep 3, 2022
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Nov 1, 2022
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12 changes: 11 additions & 1 deletion src/levenberg_marquardt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@ Comp & Applied Math).
* `x_tol::Real=1e-8`: search tolerance in x
* `g_tol::Real=1e-12`: search tolerance in gradient
* `maxIter::Integer=1000`: maximum number of iterations
* `time_limit::Integer=-1`: maximum running time in seconds (-1 for no limit)
* `min_step_quality=1e-3`: for steps below this quality, the trust region is shrinked
* `good_step_quality=0.75`: for steps above this quality, the trust region is expanded
* `lambda::Real=10`: (inverse of) initial trust region radius
Expand All @@ -31,12 +32,14 @@ Comp & Applied Math).
# and the like. This way we could not only merge the two functions, but also have a convenient
# way to provide an autodiff-made acceleration when someone doesn't provide an `avv`.
# it would probably be very inefficient performace-wise for most cases, but it wouldn't hurt to have it somewhere

function levenberg_marquardt(
df::OnceDifferentiable,
initial_x::AbstractVector{T};
x_tol::Real = 1e-8,
g_tol::Real = 1e-12,
maxIter::Integer = 1000,
time_limit::Real=NaN,
lambda = T(10),
tau = T(Inf),
lambda_increase::Real = 10.0,
Expand All @@ -49,6 +52,8 @@ function levenberg_marquardt(
avv!::Union{Function,Nothing,Avv} = nothing,
) where {T}

t0 = time() # Initial time stamp used to control early stopping by time_limit

# First evaluation
value_jacobian!!(df, initial_x)

Expand Down Expand Up @@ -88,6 +93,7 @@ function levenberg_marquardt(
x_converged = false
g_converged = false
iterCt = 0
stopped_by_time_limit = false
x = copy(initial_x)
delta_x = copy(initial_x)
a = similar(x)
Expand Down Expand Up @@ -116,7 +122,7 @@ function levenberg_marquardt(
println(os)
end

while (~converged && iterCt < maxIter)
while (~converged && ~stopped_by_time_limit && iterCt < maxIter)
# jacobian! will check if x is new or not, so it is only actually
# evaluated if x was updated last iteration.
jacobian!(df, x) # has alias J
Expand Down Expand Up @@ -235,6 +241,10 @@ function levenberg_marquardt(
x_converged = true
end
converged = g_converged | x_converged

# Check time_limit; if time_limit=NaN (the default) the condition is false.
stopped_by_time_limit = (time_limit > 0) && (time() - t0 > time_limit)
show_trace && stopped_by_time_limit #&& warn("Stopping due to time limit")
end

LsqFitResults(
Expand Down