added possibility to deactivate warnings for simulations, fixed literate move

Author: behinger

docs/make.jl

@@ -26,15 +26,15 @@ makedocs(;
     pages=[
         "Home" => "index.md",
         "Tutorials" => [
-            "An EEG Example" => "tutorials/generated/eeg.md",
-            "EEG Example - Multichannel data" => "tutorials/generated/eeg-multichannel.md",
+            "An EEG Example" => "generated/tutorials/eeg.md",
+            "EEG Example - Multichannel data" => "generated/tutorials/eeg-multichannel.md",
         ],
         "HowTo" => [
             "R: Between groups" => "howto/R_betweengroups.md",
         ],
         "Reference" => [
-            "Clusterdepth FWER" => "reference/generated/type1.md",
-            "Troendle FWER" => "reference/generated/type1_troendle.md",
+            "Clusterdepth FWER" => "generated/reference/type1.md",
+            "Troendle FWER" => "generated/reference/type1_troendle.md",
         ],
     ],
 )

docs/src/reference/type1.jl

@@ -37,7 +37,7 @@ signal = MixedModelComponent(;
 # Let's move the actual simulation into a function, so we can call it many times.
 # Note that we use (`RedNoise`)[https://unfoldtoolbox.github.io/UnfoldSim.jl/dev/literate/reference/noisetypes/] which has lot's of Autocorrelation between timepoints. nice!
 function run_fun(r)
-    data, events = simulate(
+    data, evts = simulate(
         MersenneTwister(r),
         design,
         signal,
@@ -46,10 +46,10 @@ function run_fun(r)
         return_epoched=true,
     )
     data = reshape(data, size(data, 1), :)
-    data = data[:, events.condition.=="small"] .- data[:, events.condition.=="large"]
+    data = data[:, evts.condition.=="small"] .- data[:, evts.condition.=="large"]
 
     return data,
-    clusterdepth(data'; τ=quantile(TDist(n_subjects - 1), 0.95), nperm=1000)
+    clusterdepth(data'; τ=quantile(TDist(n_subjects - 1), 0.975), nperm=1000, show_warnings=false)
 end;
 
 # ## Understanding the simulation
@@ -68,7 +68,6 @@ sig = pval_uncorrected .<= 0.025;
 # For the uncorrected p-values based on the t-distribution, we get a type1 error over "time":
 mean(sig)
 
-# this is the type 1 error of 5% we expected.
 
 # !!! note
 #       Type-I error is not the FWER (family wise error rate). FWER is the property of a set of tests (in this case tests per time-point), we can calculate it by repeating such tests,
@@ -97,7 +96,7 @@ reps = 500
 res = fill(NaN, reps, 2)
 Threads.@threads for r = 1:reps
     data, pvals = run_fun(r)
-    res[r, 1] = mean(pvals .<= 0.05)
+    res[r, 1] = mean(pvals .<= 0.05 / 2)
     res[r, 2] =
         mean(abs.(ClusterDepth.studentt(data)) .>= quantile(TDist(n_subjects - 1), 0.975))
 end;

src/cluster.jl

@@ -18,7 +18,7 @@ Optional
 - `statfun` / `statfun!` a function that either takes one or two arguments and aggregates over last dimension. in the two argument case we expect the first argument to be modified inplace and provide a suitable Vector/Matrix.
 - `sidefun`: default `abs`. Provide a function to be applied on each element of the output of  `statfun`. 
 - `permfun` function to permute the data, should accept an RNG-object and the data. can be inplace, the data is copied, but the same array is shared between permutations
-
+- `show_warnings`: default `true` - function to suppress warnings, useful for simulations
 """
 clusterdepth(data::AbstractArray, args...; kwargs...) =
     clusterdepth(MersenneTwister(1), data, args...; kwargs...)
@@ -34,6 +34,7 @@ function clusterdepth(
     (statfun!)=nothing,
     statfun=nothing,
     permfun=nothing,
+    show_warnings=false,
 )
     if stat_type == :onesample_ttest && isnothing(statfun!) && isnothing(statfun)
         statfun! = studentt!
@@ -57,7 +58,7 @@ function clusterdepth(
     end
     data_obs = sidefun.(statfun(data))
 
-    if any(data_obs[:, 1] .> τ) || any(data_obs[:, end] .> τ)
+    if show_warnings && (any(data_obs[:, 1] .> τ) || any(data_obs[:, end] .> τ))
         @warn "Your data shows a cluster that starts before the first sample, or ends after the last sample. There exists a fundamental limit in the ClusterDepth method, that the clusterdepth for such a cluster cannot be determined. Maybe you can extend the epoch to include more samples?"
     end
     cdmTuple = perm_clusterdepths_both(