Merge pull request #56 from s-ccs/tests

Configs and bumps

Author: vladdez

.github/workflows/CI.yml

@@ -55,9 +55,9 @@ jobs:
       - run: |
           julia --project=docs -e '
             using Documenter: DocMeta, doctest
-            using UnfoldMakie
-            DocMeta.setdocmeta!(UnfoldMakie, :DocTestSetup, :(using UnfoldMakie); recursive=true)
-            doctest(UnfoldMakie)'
+            using ERPgnostics
+            DocMeta.setdocmeta!(ERPgnostics, :DocTestSetup, :(using ERPgnostics); recursive=true)
+            doctest(ERPgnostics)'
       - run: julia --project=docs docs/make.jl
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.gitignore

@@ -0,0 +1,3 @@
+runner.jl
+test/drafts (to be ignored).jl
+Manifest.toml

Project.toml

@@ -37,12 +37,12 @@ WGLMakie = "276b4fcb-3e11-5398-bf8b-a0c2d153d008"
 
 [compat]
 BenchmarkTools = "1"
-CairoMakie = "0.12"
 CSV = "0.10"
+CairoMakie = "0.12, 0.13"
 ComputationalResources = "0.3"
+DSP = "0.7, 0.8"
 DataFrames = "1"
 Distributions = "0.25"
-DSP = "0.7"
 FileIO = "1"
 HDF5 = "0.17"
 ImageFiltering = "0.7"
@@ -56,8 +56,7 @@ Revise = "3"
 Statistics = "1"
 StatsBase = "0.34"
 TopoPlots = "0.2"
-Unfold = "0.7"
+Unfold = "0.8"
 UnfoldMakie = "0.5"
 UnfoldSim = "0.3"
-WGLMakie = "0.10"
-
+WGLMakie = "0.10, 0.11"

docs/example_data.jl

@@ -22,14 +22,14 @@ function example_data(example = "pattern_detection_values"; mode = 1)
     else
         datapath = dirname(Base.current_project()) * "/data/evts_d.csv"
     end
+    evts_d = CSV.read(datapath, DataFrame)
+    evts_d.channel = 1:nrow(evts_d)
     if example == "pattern_detection_values"
-        evts_d = CSV.read(datapath, DataFrame)
         pattern_detection_values = stack(evts_d)
         rename!(pattern_detection_values, :variable => :condition, :value => :estimate)
         evts_d = nothing
         return pattern_detection_values
     elseif example == "pattern_detection_values_32"
-        evts_d = CSV.read(datapath, DataFrame)
         pattern_detection_values = stack(evts_d[1:32, :])
         rename!(pattern_detection_values, :variable => :condition, :value => :estimate)
         evts_d = nothing

src/ERPgnostics.jl

@@ -20,6 +20,7 @@ using WGLMakie
 using Revise
 using ProgressBars
 
+include("configs.jl")
 include("interactive_heatmap.jl")
 include("interactive_topoplots.jl")
 include("pattern_detection.jl")

src/configs.jl

@@ -0,0 +1,39 @@
+
+"""
+    supportive_defaults(cfg_symb::Symbol)
+
+Default configurations for the supporting axis. Similar to PlotConfig, but these configurations are not shared by all plots.\\
+Such supporting axes allow users to flexibly see defaults in docstrings and manipulate them using corresponding axes.
+    
+For developers: to make them updateable in the function, use `update_axis`.\\
+**Return value:** `NamedTuple`.
+"""
+function supportive_defaults(cfg_symb::Symbol)
+    # plot_splines
+    if cfg_symb == :toposeries_default
+        return (;
+            nrows = 1,
+            mapping = (; col = :condition),
+            axis = (; xlabel = "Conditions", xlabelvisible = false),
+            visual = (
+                label_scatter = (markersize = 10, strokewidth = 2),
+                contours = (; levels = 0),
+                colormap = Reverse(:RdGy_4),
+            ),
+            colorbar = (; label = "Pattern detection function value", height = 300),
+            layout = (; use_colorbar = true),
+        )
+    elseif cfg_symb == :erpimage_defaults
+        return (; show_sortval = true, meanplot = true, axis = (; title = "ERP image"))
+    end
+end
+
+"""
+    update_axis(support_axis::NamedTuple; kwargs...)
+Update values of `NamedTuple{key = value}`.\\
+Used for supportive axes to make users be able to flexibly change them.
+"""
+function update_axis(support_axis::NamedTuple; kwargs...)
+    support_axis = (; support_axis..., kwargs...)
+    return support_axis
+end

src/interactive_topoplots.jl

@@ -7,6 +7,13 @@ Plot interactive topoplot series.
 
 - `pattern_detection_values::DataFrame`\\
     DataFrame with columns condition and estimate. Each condition is resposible for a topoplot. Estimates will be projected across channels. 
+- `figure_configs::NamedTuple = (;)`\\
+    Here you can flexibly change configurations of the Figure axis.\\
+    To see all options just type `?Figure` in REPL.\\
+- `toposeries_configs::NamedTuple  = (;)`\\
+    Here you can flexibly change configurations of the topoplot series.\\
+    To see all options just type `?plot_topoplotseries` in REPL.\\
+    Defaults: $(supportive_defaults(:toposeries_default))
 - `kwargs...`\\
     Additional styling behavior. \\
 
@@ -20,7 +27,7 @@ function inter_toposeries(
     pattern_detection_values::DataFrame;
     positions::Vector{Point{2,Float64}} = positions_128,
     figure_configs = (; size = (1500, 400)),
-    toposeries_configs = (; nrows = 1,),
+    toposeries_configs = (;),
 )
 
     names = unique(pattern_detection_values.condition)
@@ -51,15 +58,14 @@ function inter_toposeries(
     end
     hidespines!(ax)
     hidedecorations!(ax)
+
+    toposeries_configs =
+        update_axis(supportive_defaults(:toposeries_default); toposeries_configs...)
     plot_topoplotseries!( # make configurable
         f[1, 1],
         pattern_detection_values;
-        mapping = (; col = :condition),
         positions = positions,
-        nrows = nrows,
         interactive_scatter = obs_tuple,
-        visual = (label_scatter = (markersize = 10, strokewidth = 2),),
-        layout = (; use_colorbar = true),
         toposeries_configs...,
     )
 
@@ -84,6 +90,17 @@ ERP image will have trials on y-axis and time on x-axis
     3-dimensional Array of voltages of Event-related potentials. Dimensions: channels, time of recording, trials. 
 - `timing::?`\\
     Timing of recording. Should be similar to y-value of erps. 
+- `figure_configs::NamedTuple = (;)`\\
+    Here you can flexibly change configurations of the Figure axis.\\
+    To see all options just type `?Figure` in REPL.\\
+- `toposeries_configs::NamedTuple  = (;)`\\
+    Here you can flexibly change configurations of the topoplot series.\\
+    To see all options just type `?plot_topoplotseries` in REPL.\\
+    Defaults: $(supportive_defaults(:toposeries_default))
+- `erpimage_configs::NamedTuple  = (;)`\\
+    Here you can flexibly change configurations of the ERP image plot.\\
+    To see all options just type `?plot_erpimage` in REPL.\\
+    Defaults: $(supportive_defaults(:erpimage_defaults))
 - `kwargs...`\\
     Additional styling behavior. \\
 
@@ -98,8 +115,10 @@ function inter_toposeries_image(
     events,
     erps, #::Array{Float64,3},
     timing;
-    figure_configs = (; size = (1500, 400)),
     positions = positions_128,
+    figure_configs = (; size = (1500, 400)),
+    toposeries_configs = (;),
+    erpimage_configs = (;),
 )
 
     cond_names = unique(pattern_detection_values.condition)
@@ -116,24 +135,18 @@ function inter_toposeries_image(
     hidespines!(ax)
     hidedecorations!(ax)
 
+    toposeries_configs =
+        update_axis(supportive_defaults(:toposeries_default); toposeries_configs...)
+    erpimage_configs =
+        update_axis(supportive_defaults(:erpimage_defaults); erpimage_configs...)
+
     plot_topoplotseries!(
         f[1, 1:5],
         pattern_detection_values;
-        positions = positions,
-        col_labels = true,
         mapping = (; col = :condition),
-        axis = (; xlabel = "Conditions", xlabelvisible = false),
-        visual = (
-            label_scatter = (markersize = 10, strokewidth = 2),
-            contours = (; levels = 0),
-            colormap = Reverse(:RdGy_4),
-        ),
+        positions = positions,
         interactive_scatter = obs_tuple,
-        colorbar = (;
-            label = "Pattern detection function value",
-            colorrange = (0, 1),
-            height = 300,
-        ),
+        toposeries_configs...,
     )
 
     single_channel_erpimage = @lift(erps[$obs_tuple[3], :, :])
@@ -145,10 +158,8 @@ function inter_toposeries_image(
         timing,
         single_channel_erpimage;
         sortvalues = sortval,
-        show_sortval = true,
-        meanplot = true,
         sortval_xlabel = str2,
-        axis = (; title = "ERP image"),
+        erpimage_configs...,
     )
 
     #= on(events(f).mousebutton, priority = 1) do event

src/pattern_detection.jl

@@ -7,23 +7,23 @@ For instance, single EEG channel (sensor) with trials over time.\\
 Method:\\
 - Filter dataset for smearing.\\
 - Use pattern detection function.\\
-- In "plot" mode returns an ERP image with a value of pattern detection. Otherwise - only value.
+- In `mode = "plot"` returns an ERP image with a value of pattern detection. Otherwise - only value.
 
 ## Arguments
 
-- erp_data::Matrix{Float64}`\\
+- `erp_data::Matrix{Float64}`\\
     3-dimensional array of voltages of event-related potentials. Dimensions: channels, recording time, trials. 
-- detector::Function`\\
+- `detector::Function`\\
     Function used for pattern detection.\\
     For example, `Images.entropy` from `Images.jl`.
-- filter::Function`\\
+- `filter::Function`\\
     Function used for smearing.\\
 
 ## Keyword arguments (kwargs)
-- mode::String = "plot"` \\
+- `mode::String = "plot"` \\
     Plot an ERP image with the pattern detection value.
 
-**Return Value:** (Figure with) pattern detection value.
+**Return Value:** (`Figure` with) pattern detection value.
 """
 function pattern_detector(
     erp_data::Matrix{Float64},
@@ -64,17 +64,17 @@ Mode of permuted means:\\
 
 - `erp_data::Array{Float64, 3}`\\
     3-dimensional Array of voltages of Event-related potentials. Dimensions: time of recording, trials, channels. 
-- detector::Function`\\
+- `detector::Function`\\
     Function used for pattern detection.\\
     For example, `Images.entropy` from `Images.jl`.
-- filter::Function`\\
+- `filter::Function`\\
     Function used for smearing.\\- `kwargs...`\\
     Additional styling behavior. \\
 
 ## Keyword arguments (kwargs)
 - `n_permutations::Number = 10` \\
     Number fo permutations. Useful for mode "permuted_means" where it defines number of random permutations before averaging.
-- mode::String = "basic"` \\
+- `mode::String = "basic"` \\
     With the "permuted_means" mode, results are given as the absolute value between the detector result over the given data set and the randomly permuted data set.
 
 **Return Value:** DataFrame with pattern detection values. Dimensions: experimental events, channels.

src/pattern_simulation.jl

@@ -130,7 +130,7 @@ Columns in resulting sim\\_6patterns Data Frame to simulate this patterns: Δlat
 - `σ::Float = 3.2`\\
     Controls standart deviation.
 
-**Return Value:** sim\\_6patterns::Matrix{Float64} with voltages and sim_evts::DataFrame with events. 
+**Return Value:** `sim\\_6patterns::Matrix{Float64}` with voltages and `sim_evts::DataFrame` with events. 
 """
 function simulate_6patterns(μ = 3.2, σ = 0.5; tmp = nothing)
     design = SingleSubjectDesign(;

test/interactive_heatmap_test.jl

@@ -3,7 +3,7 @@ begin
     pattern_detection_values = CSV.read("../data/evts_d.csv", DataFrame)
 end
 
-@testset "inter_heatmap" begin
+@testset "interactive heatmap" begin
     inter_heatmap(pattern_detection_values)
 end
 
@@ -12,7 +12,7 @@ end
 erps_fix = read(fid["data"]["data_fixations.hdf5"])
 close(fid)
 
-@testset "inter_heatmap_image" begin
+@testset "interactive heatmap image" begin
     inter_heatmap_image(pattern_detection_values, events, erps_fix)
 end
- =#
+=#