example_data.jl

using UnfoldSim
using TopoPlots
using Unfold
"""
Makes use of TopoPlots example data (originating from eegvis matlab toolbox).
type ==
"TopoPlots.jl"(default) Returns tidy DataFrame with two conditions, 64 channels and 800ms of data. This is an average over many subjects.
"""

function example_data(example="TopoPlots.jl")

	if example == "UnfoldLinearModel"
		# load and generate a simulated Unfold Design
		data,evts = UnfoldSim.predef_eeg(;noiselevel=10,return_epoched=true)
		data = reshape(data,1,size(data)...)
		f  = @formula 0~1+condition+continuous
		# generate ModelStruct
		se_solver =(x,y)->Unfold.solver_default(x,y,stderror=true)
		return fit(UnfoldModel,(Dict(Any=>(f,range(0,length=size(data,2),step=1/100)))) ,evts,data;solver=se_solver)
	elseif example == "UnfoldLinearModelMultiChannel"
			# load and generate a simulated Unfold Design
			cAll = DataFrame()
			sfreq = 100
			for ch = 1:5
			data,evts = UnfoldSim.predef_eeg(;p1 = (p100(;sfreq=sfreq), @formula(0~1),[5],Dict()), 
			
			n1 = (n170(;sfreq=sfreq), @formula(0~1+condition),[5,-ch*0.5],Dict()), 
			 p3 = (p300(;sfreq=sfreq), @formula(0~1+continuous),[ch,1],Dict()), 
			return_epoched=true)
			data = reshape(data,1,size(data)...)
			f  = @formula 0~1+condition+continuous
			# generate ModelStruct
		
			m= fit(UnfoldModel,(Dict(Any=>(f,range(0,length=size(data,2),step=1/100)))) ,evts,data)
			d = coeftable(m)
			d.channel .= ch
			cAll = append!(cAll,d)
			end
			return cAll

	elseif example == "UnfoldLinearModelContinuousTime"
		# load and generate a simulated Unfold Design
		data,evts = UnfoldSim.predef_eeg(;)
		data = reshape(data,1,size(data)...)
		f  = @formula 0~1+condition+continuous
		basis = firbasis([0,0.5],100)
		# generate ModelStruct
		return fit(UnfoldModel,Dict(Any=>(f,basis)) ,evts,data)
		
	elseif example == "TopoPlots.jl"
		data,chanlocs = TopoPlots.example_data();
		df = DataFrame(estimate=Float64[],time=Float64[],channel=Int64[],coefname=String[],topoPositions=[],se=Float64[],pval=Float64[])
		pos = TopoPlots.points2mat(chanlocs)
		for ch = 1:size(data,1)
			for t = 1:size(data,2)
				append!(df,DataFrame(estimate=data[ch,t,1],se=data[ch,t,2],pval=data[ch,t,3],time=t,channel=ch,coefname="A",topoPositions=(pos[1,ch],pos[2,ch])))
				
				
			end
		end
		df.time = range(-0.3,0.5,step=1/500)[Int.(df.time)]
		return df,chanlocs
	else
		error("unknown example data")
	end
end