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16 changes: 16 additions & 0 deletions lib/DiffEqDevTools/src/DiffEqDevTools.jl
Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,7 @@ const ALL_ERRORS = union([:final],
include("benchmark.jl")
include("convergence.jl")
include("plotrecipes.jl")
include("autoplot.jl")
include("test_solution.jl")
include("ode_tableaus.jl")
include("tableau_info.jl")
Expand All @@ -45,6 +46,21 @@ export test_convergence, analyticless_test_convergence, appxtrue!, appxtrue

export get_sample_errors

#Tagging and Filtering
export filter_by_tags, exclude_by_tags, get_tags, unique_tags, merge_wp_sets

#Multi-error-mode
export available_errors

#Best-of-family helpers
export best_by_tag, best_of_families, wp_area

#AutoDiff comparison helpers
export with_autodiff_variants

#Autoplot
export autoplot

#Tab Functions
export stability_region, residual_order_condition, check_tableau, imaginary_stability_interval

Expand Down
81 changes: 81 additions & 0 deletions lib/DiffEqDevTools/src/autoplot.jl
Original file line number Diff line number Diff line change
@@ -0,0 +1,81 @@
"""
autoplot(wp_set; families=nothing, reference_tags=nothing, best_n=2)

Generate a collection of WorkPrecisionSets for standard comparison plots.

Returns a `Dict{String, WorkPrecisionSet}` with:
- `"family_<tag>"` for each family
- `"best_of_families"` with top methods per family
- `"all"` containing the original set
"""
function autoplot(wp_set::WorkPrecisionSet;
families = nothing,
reference_tags = nothing,
best_n::Int = 2)
results = Dict{String, WorkPrecisionSet}()

# Determine families
if families === nothing
families = _auto_detect_families(wp_set)
end

# Per-family plots
for fam in families
subset = filter_by_tags(wp_set, fam)
if reference_tags !== nothing
ref_tags = reference_tags isa Symbol ? (reference_tags,) : Tuple(reference_tags)
ref = filter_by_tags(wp_set, ref_tags...)
# Deduplicate
seen = Set(wp.name for wp in subset.wps)
extra_wps = [wp for wp in ref.wps if wp.name ∉ seen]
if !isempty(extra_wps)
subset = merge_wp_sets(subset,
WorkPrecisionSet(extra_wps, length(extra_wps),
wp_set.abstols, wp_set.reltols, wp_set.prob,
wp_set.setups, [wp.name for wp in extra_wps],
wp_set.error_estimate, wp_set.numruns))
end
end
length(subset) > 0 && (results["family_$(fam)"] = subset)
end

# Best-of-families
if !isempty(families)
best_wps = WorkPrecision[]
seen = Set{String}()
for fam in families
subset = filter_by_tags(wp_set, fam)
length(subset) == 0 && continue
ranked = sort(collect(1:length(subset.wps)),
by = i -> let t = filter(!isnan, subset.wps[i].times)
isempty(t) ? Inf : mean(t)
end)
for idx in ranked[1:min(best_n, length(ranked))]
wp = subset.wps[idx]
if wp.name ∉ seen
push!(seen, wp.name)
push!(best_wps, wp)
end
end
end
if !isempty(best_wps)
names = [wp.name for wp in best_wps]
results["best_of_families"] = WorkPrecisionSet(
best_wps, length(best_wps), wp_set.abstols, wp_set.reltols,
wp_set.prob, wp_set.setups, names, wp_set.error_estimate, wp_set.numruns)
end
end

results["all"] = wp_set
return results
end

function _auto_detect_families(wp_set::WorkPrecisionSet)
all_tags = unique_tags(wp_set)
n_methods = length(wp_set.wps)
n_methods == 0 && return Symbol[]
# Filter out tags that appear on >80% of methods (likely category tags)
return filter(all_tags) do tag
count(wp -> tag in wp.tags, wp_set.wps) <= 0.8 * n_methods
end
end
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