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Add tolerances in deserialization #703

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merged 7 commits into from
Aug 8, 2023
Merged

Add tolerances in deserialization #703

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1a30e85
support passing tolerances to restoreoptsum!
palday Aug 8, 2023
0c9e2b9
test
palday Aug 8, 2023
1aa2a58
NEWS
palday Aug 8, 2023
e7699ca
version bump
palday Aug 8, 2023
74ede15
JuliaFormatter
palday Aug 8, 2023
3886f7a
Update src/serialization.jl
palday Aug 8, 2023
2d58011
Update src/serialization.jl
palday Aug 8, 2023
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5 changes: 5 additions & 0 deletions NEWS.md
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Original file line number Diff line number Diff line change
@@ -1,3 +1,7 @@
MixedModels v4.16.0 Release Notes
==============================
* Support for check tolerances in deserialization. [#703]

MixedModels v4.15.0 Release Notes
==============================
* Support for different optimization criteria during the bootstrap. [#694]
Expand Down Expand Up @@ -442,3 +446,4 @@ Package dependencies
[#681]: https://github.com/JuliaStats/MixedModels.jl/issues/681
[#682]: https://github.com/JuliaStats/MixedModels.jl/issues/682
[#694]: https://github.com/JuliaStats/MixedModels.jl/issues/694
[#703]: https://github.com/JuliaStats/MixedModels.jl/issues/703
2 changes: 1 addition & 1 deletion Project.toml
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@@ -1,7 +1,7 @@
name = "MixedModels"
uuid = "ff71e718-51f3-5ec2-a782-8ffcbfa3c316"
author = ["Phillip Alday <me@phillipalday.com>", "Douglas Bates <dmbates@gmail.com>", "Jose Bayoan Santiago Calderon <jbs3hp@virginia.edu>"]
version = "4.15.0"
version = "4.16.0"

[deps]
Arrow = "69666777-d1a9-59fb-9406-91d4454c9d45"
Expand Down
16 changes: 10 additions & 6 deletions src/serialization.jl
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@@ -1,10 +1,12 @@
"""
restoreoptsum!(m::LinearMixedModel, io::IO)
restoreoptsum!(m::LinearMixedModel, filename)
restoreoptsum!(m::LinearMixedModel, io::IO; atol::Real=0, rtol::Real=atol>0 ? 0 : √eps)
restoreoptsum!(m::LinearMixedModel, filename; atol::Real=0, rtol::Real=atol>0 ? 0 : √eps)

Read, check, and restore the `optsum` field from a JSON stream or filename.
"""
function restoreoptsum!(m::LinearMixedModel{T}, io::IO) where {T}
function restoreoptsum!(
m::LinearMixedModel{T}, io::IO; atol::Real=0, rtol::Real=atol > 0 ? 0 : √eps(T)
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) where {T}
dict = JSON3.read(io)
ops = m.optsum
okay =
Expand All @@ -22,7 +24,9 @@ function restoreoptsum!(m::LinearMixedModel{T}, io::IO) where {T}
copyto!(ops.initial, dict.initial)
copyto!(ops.final, dict.final)
for (v, f) in (:initial => :finitial, :final => :fmin)
if !isapprox(objective(updateL!(setθ!(m, getfield(ops, v)))), getfield(ops, f))
if !isapprox(
objective(updateL!(setθ!(m, getfield(ops, v)))), getfield(ops, f); rtol, atol
)
throw(ArgumentError("model m at $v does not give stored $f"))
end
end
Expand All @@ -40,9 +44,9 @@ function restoreoptsum!(m::LinearMixedModel{T}, io::IO) where {T}
return m
end

function restoreoptsum!(m::LinearMixedModel{T}, filename) where {T}
function restoreoptsum!(m::LinearMixedModel{T}, filename; kwargs...) where {T}
open(filename, "r") do io
restoreoptsum!(m, io)
restoreoptsum!(m, io; kwargs...)
end
end

Expand Down
16 changes: 13 additions & 3 deletions test/pls.jl
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Expand Up @@ -167,7 +167,7 @@ end
sigma0row = only(filter(r -> r.p == :σ && iszero(r.ζ), dspr01.tbl))
@test sigma0row.σ ≈ dspr01.m.σ
@test sigma0row.β1 ≈ only(dspr01.m.β)
@test sigma0row.θ1 ≈ only(dspr01.m.θ)
@test sigma0row.θ1 ≈ only(dspr01.m.θ)
end
end

Expand Down Expand Up @@ -500,14 +500,23 @@ end

@testset "optsumJSON" begin
fm = last(models(:sleepstudy))
# using a IOBuffer for saving JSON
# using a IOBuffer for saving JSON
saveoptsum(seekstart(io), fm)
m = LinearMixedModel(fm.formula, MixedModels.dataset(:sleepstudy))
restoreoptsum!(m, seekstart(io))
@test loglikelihood(fm) ≈ loglikelihood(m)
@test bic(fm) ≈ bic(m)
@test coef(fm) ≈ coef(m)
# using a temporary file for saving JSON

fm_mod = deepcopy(fm)
fm_mod.optsum.fmin += 1
saveoptsum(seekstart(io), fm_mod)
@test_throws(ArgumentError("model m at final does not give stored fmin"),
restoreoptsum!(m, seekstart(io)))
restoreoptsum!(m, seekstart(io); atol=1)
@test m.optsum.fmin - fm.optsum.fmin ≈ 1

# using a temporary file for saving JSON
fnm = first(mktemp())
saveoptsum(fnm, fm)
m = LinearMixedModel(fm.formula, MixedModels.dataset(:sleepstudy))
Expand All @@ -516,6 +525,7 @@ end
@test bic(fm) ≈ bic(m)
@test coef(fm) ≈ coef(m)
end

@testset "profile" begin
pr = profile(last(models(:sleepstudy)))
tbl = pr.tbl
Expand Down
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