sorted erp added to docs

docs/src/tutorials/erpimage.md

@@ -14,24 +14,23 @@ include("../../example_data.jl")
 ```
 
 
-## Plot ERP Images
+## Plot ERP image
 
 The following code will result in the default configuration. 
 ```@example main
 data, evts = UnfoldSim.predef_eeg(; noiselevel=10, return_epoched=true)
 plot_erpimage(data)
 ```
 
-## Column Mappings for ERP Images
+## Column Mappings for ERP image
 
 Since ERP images use a `Matrix` as an input, the library does not need any informations about the mapping.
 
-- erpblur (number, 10) - Is a number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module. Negative values deactivate the blur.
-
-- sortvalues - Indicating whether the data is sorted; using sortperm() of Base Julia.
-(sortperm() computes a permutation of the array's indices that puts the array into sorted order). 
-
-- meanplot (bool, false) - Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data. If limits are set in the axis values both plots will be aligned.
+- `erpblur` (Number, `10`): number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module.
+Non-Positive values deactivate the blur.
+- `sortvalues` (bool, `false`): parameter over which plot will be sorted. Using sortperm() of Base Julia. 
+    - sortperm() computes a permutation of the array's indices that puts the array into sorted order. 
+- `meanplot` (bool, `false`): Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data.
 
 ```@example main
 plot_erpimage(data;
@@ -40,3 +39,20 @@ plot_erpimage(data;
     visual = (colormap = :viridis, colorrange = (-40, 40)))
 
 ```
+
+## Sorted ERP image
+
+First, generate a data. Second, specify the necessary sorting parameter. 
+
+```@example main
+    dat, evts = UnfoldSim.predef_eeg(; 
+        onset=LogNormalOnset(μ=3.5, σ=0.4), 
+        noiselevel=5
+    )
+    dat_e, times = Unfold.epoch(dat, evts, [-0.1,1], 100)
+    evts, dat_e = Unfold.dropMissingEpochs(evts, dat_e)
+    evts.Δlatency =  diff(vcat(evts.latency, 0))
+    dat_e = dat_e[1,:,:]
+
+    plot_erpimage(times, dat_e; sortvalues=evts.Δlatency)
+```

src/plot_erpimage.jl

@@ -11,12 +11,12 @@ Plot an ERP image.
 - `plot::Matrix{Float64}`: Data for the plot visualization
         
 ## Keyword Arguments
-- `erpblur` (Number, `10`) - Number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module.
+- `erpblur` (Number, `10`): number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module.
 Non-Positive values deactivate the blur.
 - `sortix` (default: `nothing`): .
-- `sortvalues` (bool, `false`) - parameter over which plot will be sorted. Using sortperm() of Base Julia. 
+- `sortvalues` (bool, `false`): parameter over which plot will be sorted. Using sortperm() of Base Julia. 
     - sortperm() computes a permutation of the array's indices that puts the array into sorted order. 
-- `meanplot`: (bool, `false`) - Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data.
+- `meanplot` (bool, `false`): Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data.
 
 $(_docstring(:erpimage))
 

test/Project.toml

@@ -1,5 +1,6 @@
 [deps]
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
+Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 GeometryBasics = "5c1252a2-5f33-56bf-86c9-59e7332b4326"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

test/test_butterfly.jl

@@ -1,7 +1,6 @@
 
 include("../docs/example_data.jl")
 data, pos = example_data("TopoPlots.jl")
-using Colors
 
 @testset "basic" begin
     plot_butterfly(data; positions = pos)