From 366285f757eaa3911baf568312afeb6a2aada183 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Thu, 14 Aug 2025 15:12:13 +0200 Subject: [PATCH 01/32] initial commit to add code from notebooks --- src/UnfoldSimArtifacts.jl | 297 ++++++++++++++++++++++++++++++++++++++ src/types.jl | 6 + 2 files changed, 303 insertions(+) create mode 100644 src/UnfoldSimArtifacts.jl diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl new file mode 100644 index 00000000..fb94e6fa --- /dev/null +++ b/src/UnfoldSimArtifacts.jl @@ -0,0 +1,297 @@ +#= +TODOs + +- is equiv_dipole_mag() repeating some other function's purpose? + +- check all the packages used and whether they are actually needed +- do we need ___? + - read_new_hartmut() + - pos2dfrom3d() (it's technically just 2 lines. see unfoldsim docs multichannel example) + +- docstrings for all functions +=# + + + +# For helper function to read in the large model +# using HDF5 +# using DataFrames + +# for angle conversion - need to check if we still need this or if the simple angle conversion util code will suffice +# using CartesianFromSpherical + + +""" +TODO docstring +Construct the gaze vector in 3-D world coordinates, given the gaze angle (in degrees) as measured from the center gaze (looking straight ahead) in the world x-y plane. Z-component is always 0. +""" +function gazevec_from_angle(angle_deg) + # just x,y plane for now. gaze angle measured from front neutral gaze, not from x-axis + return [sind(angle_deg) cosd(angle_deg) 0] +end + +""" +TODO docstring +Calculate the gaze vector in 3-D world coordinates, given the horizontal and vertical angles (in degrees) from center gaze direction i.e. looking straight ahead. +""" +function gazevec_from_angle_3d(angle_H, angle_V) + # angles measured from center gaze position => use complementary angle for θ + return Array{Float32}(CartesianFromSpherical()(Spherical(1, deg2rad(90-angle_H), deg2rad(angle_V)))) +end + + +""" + read_eyemodel(;p::String = "HArtMuT_NYhead_extra_eyemodel.mat") + +Read and return the HArtMuT eye model from the given file path. + +# Fields +- `p::String` (optional): Path of the file from which to read the eye model. + +# Returns +- `model`: Eye model read from the specified file path. +""" +function read_eyemodel(;p::String = "HArtMuT_NYhead_extra_eyemodel.mat") + file = matopen(p); + hartmut = read(file,"eyemodel") + close(file) + hartmut["label"] = hartmut["labels"] + delete!(hartmut,"labels") + hartmut +end + +""" +TODO docstring + +For each of a given set of labels, find the indices of all the sources in the given model which have that label. + +Arguments: +- `headmodel`: Head model containing the sources in which to search for labels +- `labels::Vector{String}`: Labels to search for. + +Returns: +- `labelsourceindices::Dict`: Dict with the keys being the label and the values being the indices of sources with that label in the given model. +""" +function hart_indices_from_labels(headmodel,labels::Vector{String}=["dummy"]) + labelsourceindices = Dict() + for l in labels + labelsourceindices[l] = findall(k->occursin(l,k),headmodel["label"][:]) + end + return labelsourceindices +end + + +""" +TODO docstring +Calculate orientations from the given positions with respect to the reference. `direction` is by default "towards" the reference point; if a different value is given, orientations are calculated away from the reference point. +""" +function calc_orientations(reference, positions; direction="towards") + if direction == "towards" + orientation_vecs = reference .- positions + else + orientation_vecs = positions .- reference + end + return orientation_vecs ./ norm.(eachrow(orientation_vecs)) +end + + +""" +TODO docstring +Calculate the angle between two 3-D vectors. +""" +function angle_between(a,b) + return acosd.(dot(a, b)/(norm(a)*norm(b))) +end + +# """ +# TODO docstring +# For the given gaze direction, return a weight value for each source point in the model: 1 for a cornea source, 0 for retina sources and all other points in the model. + +# # Arguments +# - `model`: Head model. +# - `sim_idx`: Indices of the (eye) source points for which weights should be calculated. +# - `gazedir`: The gaze direction vector. +# - `max_cornea_angle_deg`: Angle (in degrees) made by the radial vector containing the cornea point farthest from the cornea center with the radial vector containing the cornea center. + +# # Returns +# - `eyeweights`: Weights of the source points: 1 for a cornea source, 0 for retina sources and all other points in the model. +# """ +# function weights_from_gazedir(model, sim_idx, gazedir, max_cornea_angle_deg) +# eyeweights = zeros(size(model["pos"])[1]) # all sources other than those defined by sim_idx will be set to zero magnitude +# eyeweights[sim_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), model["orientation"][sim_idx,:],dims=2) +# return eyeweights +# end + + +""" + is_corneapoint(orientation::Vector{Float64}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) + + +""" +function is_corneapoint(orientation::Vector{Float64}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) + if(angle_between(orientation,gazedir)<=max_cornea_angle_deg) + return 1 + else + return -1 + end +end + + +""" +TODO docstring +""" +function leadfield_from_gazedir(model, sim_idx, gazedir, max_cornea_angle_deg) + mag_model = magnitude(model["leadfield"],model["orientation"]) + source_weights = zeros(size(model["pos"])[1]) # all sources other than those defined by sim_idx will be set to zero magnitude + source_weights[sim_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), model["orientation"][sim_idx,:],dims=2) + + weighted_sum = sum(mag_model[:,idx].* source_weights[idx] for idx in sim_idx,dims=2) + return weighted_sum +end + + +""" +TODO docstring +Take just a selected subset of points in the model, along with new orientations for those points, +and calculate the sum of leadfields of just these points with the new orientations. +""" +function equiv_dipole_mag(model,idx,equiv_orientations) + equiv_ori_model = model["orientation"] + equiv_ori_model[idx,:] .= equiv_orientations[1:length(idx),:] + mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],equiv_ori_model) + mag = sum(mag_eyemodel_equiv[:,ii] for ii in idx) +end + + +""" +TODO docstring +Simulate eye movement start to end using ensemble method +""" +function sim_gazevecs_ensemble() # TODO rename this and turn it into a proper function. For now, moved here from pluto notebook +# simulate for gazevectors - ensemble method + + sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. + + # leadfield for centre, to subtract for B-A method + lf_center = leadfield_from_gazedir(eyemodel, sim_srcs_idx, gazevec_from_angle(0), 54.0384).*10e3 + + # leadfields: matrix of dimensions [electrodes x n_gazepoints] + leadfields_ensemble = zeros(227,length(gazevectors)) + for ix in eachindex((gazevectors)) # 1:length(gazevectors) #TODO delete this comment once it's proven to work + # for each gazepoint, calculate the leadfield and store it in the corresponding column + leadfields_ensemble[:,ix] = leadfield_from_gazedir(eyemodel, sim_srcs_idx, + gazevectors[ix], 54.0384) + end +end + + +""" +TODO docstring +Return imported model, electrode positions, labelsourceindices of eyemodel +""" +function import_model() + + # labels for which to find source indices + labels = [ + r"EyeRetina_Choroid_Sclera_left$" # match the end of the search term, or else it also matches "leftright" sources. + ,r"EyeRetina_Choroid_Sclera_right$" + ,"EyeCornea_left" # new spherical eyemodel - only one set of sources per eye and the labels are different + ,"EyeCornea_right" # same as above + ,"EyeCenter_right" + ,"EyeCenter_left" + ] + + eyemodel = read_eyemodel(; p="HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat") + remove_indices = [164, 165, 166, 167] # since eyemodel structure doesn't exactly correspond to the main hartmut mat structure expected by the read_new_hartmut function, just get the indices of the electrodes that it drops & drop the same indices from eyemodel directly + eyemodel["leadfield"] = eyemodel["leadfield"][Not(remove_indices), :, :] + + lsi_eyemodel = hart_indices_from_labels(eyemodel,labels) + + # import small headmodel temporarily for electrode positions, since eyemodel does not include them + hart_small = UnfoldSim.headmodel() + pos3d = hart_small.electrodes["pos"] + electrode_pos = pos2dfrom3d(pos3d) + eyemodel["electrodes"] = deepcopy(hart_small.electrodes) + eyemodel["electrodes"]["pos2d"] = pos2dfrom3d(pos3d) + + return eyemodel, electrode_pos, lsi_eyemodel +end + + +""" +Calculate left/right eye indices, eye centers, orientations and add them to the eyemodel as properties +""" +function setup_eyemodel(eyemodel, lsi_eyemodel) + + eyemodel_left_idx = [ lsi_eyemodel["EyeCornea_left"] ; lsi_eyemodel[r"EyeRetina_Choroid_Sclera_left$"] ] + eyemodel_right_idx = [ lsi_eyemodel["EyeCornea_right"] ; lsi_eyemodel[r"EyeRetina_Choroid_Sclera_right$"] ] + + # For calculating orientations: get positions of left and right eye points in eyemodel, and their center (provided directly in spherical model) + em_positions_L = eyemodel["pos"][eyemodel_left_idx,:] + em_positions_R = eyemodel["pos"][eyemodel_right_idx,:] + + eye_center_L = eyemodel["pos"][lsi_eyemodel["EyeCenter_left"],:] + eye_center_R = eyemodel["pos"][lsi_eyemodel["EyeCenter_right"],:] + + # calculate orientations away from center, later use negative weightage for the points where the source dipole points towards the center. + eyemodel["orientation"] = zeros(size(eyemodel["pos"])) + eyemodel["orientation"][eyemodel_right_idx,:] = calc_orientations(eye_center_R, em_positions_R; direction="away") + eyemodel["orientation"][eyemodel_left_idx,:] = calc_orientations(eye_center_L, em_positions_L; direction="away") + + # add some more eyemodel-properties to the model + eyemodel["eyeleft_idx"] = eyemodel_left_idx + eyemodel["eyeright_idx"] = eyemodel_right_idx + eyemodel["eyecenter_left_pos"] = eye_center_L + eyemodel["eyecenter_right_pos"] = eye_center_R + + return eyemodel + +end + + +""" +TODO docstring +""" +function simulate_crd(eyemodel, gazevectors) # TODO add type & dimensions + leadfields_crd = zeros(227,length(gazevectors)) # TODO replace hardcoded 227 with number of channels in model? + eyecenter_idx = [lsi_eyemodel["EyeCenter_left"][1],lsi_eyemodel["EyeCenter_right"][1]] #TODO remove duplication of calculating center indices + + for ix in eachindex(gazevectors) # 1:length(gazevectors) #TODO delete this comment once it's proven to work + # calculate leadfield due to 2 individual CRD sources and add + leadfields_crd[:,ix] = ( + leadfield_specific_sources_orientations(deepcopy(eyemodel),eyecenter_idx,gazevectors[ix]) + ) + end + + return leadfields_crd +end + + +""" +TODO docstring +""" +function leadfield_specific_sources_orientations(model,idx,equiv_orientations) + # take just a selected subset of points in the model, along with a new orientation for those points, and calculate the sum of leadfields of just these points with the given orientation. + equiv_ori_model = model["orientation"] + + for ii in idx + equiv_ori_model[ii,:] = equiv_orientations[:] + end + + mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],equiv_ori_model) + mag = sum(mag_eyemodel_equiv[:,ii] for ii in idx) + return mag +end + +#TODO add dandelion plot as utility function + + +function find_avg_gazedir() + # finding cornea centers and approximate gaze direction (as mean of cornea orientations) + cornea_center_R = Statistics.mean(eyemodel["pos"][lsi_eyemodel["EyeCornea_right"],:],dims=1) + cornea_center_L = Statistics.mean(eyemodel["pos"][lsi_eyemodel["EyeCornea_left"],:],dims=1) + gazedir_R = mean(eyemodel["orientation"][lsi_eyemodel["EyeCornea_right"],:], dims=1).*10 + gazedir_L = mean(eyemodel["orientation"][lsi_eyemodel["EyeCornea_left"],:], dims=1).*10 +end + +#TODO auto-find cornea max. angle from center and cornea point positions diff --git a/src/types.jl b/src/types.jl index 314f32ef..8419f4fa 100644 --- a/src/types.jl +++ b/src/types.jl @@ -5,6 +5,8 @@ abstract type AbstractDesign end abstract type AbstractComponent end +abstract type AbstractContinuousSignal end + # find other types in onset.jl and noise.jl # and in design.jl and component.jl @@ -69,3 +71,7 @@ struct Simulation onset::AbstractOnset noisetype::AbstractNoise end + +struct EyeMovement <: AbstractContinuousSignal + controlsignal +end \ No newline at end of file From e17ef7d8c4f6c30d2c2db9ee00b46f0332629434 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Sat, 16 Aug 2025 18:46:08 +0200 Subject: [PATCH 02/32] clean up & merge functions for intermediate steps; add general function for eyemovement sim --- src/UnfoldSimArtifacts.jl | 181 ++++++++++++++++++++++++-------------- 1 file changed, 117 insertions(+), 64 deletions(-) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index fb94e6fa..389dbb00 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -1,8 +1,6 @@ #= TODOs -- is equiv_dipole_mag() repeating some other function's purpose? - - check all the packages used and whether they are actually needed - do we need ___? - read_new_hartmut() @@ -140,128 +138,129 @@ end """ TODO docstring """ -function leadfield_from_gazedir(model, sim_idx, gazedir, max_cornea_angle_deg) - mag_model = magnitude(model["leadfield"],model["orientation"]) - source_weights = zeros(size(model["pos"])[1]) # all sources other than those defined by sim_idx will be set to zero magnitude - source_weights[sim_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), model["orientation"][sim_idx,:],dims=2) +function ensemble_leadfield(eyemodel, sim_idx::Vector{Int}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) + mag_model = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) + source_weights = zeros(size(eyemodel["pos"])[1]) # all sources other than those defined by sim_idx will be set to zero magnitude + source_weights[sim_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), eyemodel["orientation"][sim_idx,:],dims=2) weighted_sum = sum(mag_model[:,idx].* source_weights[idx] for idx in sim_idx,dims=2) return weighted_sum end -""" -TODO docstring -Take just a selected subset of points in the model, along with new orientations for those points, -and calculate the sum of leadfields of just these points with the new orientations. -""" -function equiv_dipole_mag(model,idx,equiv_orientations) - equiv_ori_model = model["orientation"] - equiv_ori_model[idx,:] .= equiv_orientations[1:length(idx),:] - mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],equiv_ori_model) - mag = sum(mag_eyemodel_equiv[:,ii] for ii in idx) -end - - """ TODO docstring Simulate eye movement start to end using ensemble method """ -function sim_gazevecs_ensemble() # TODO rename this and turn it into a proper function. For now, moved here from pluto notebook +function sim_gazevecs_ensemble(gazevectors::Vector{Vector{Float64}}) # TODO rename this and turn it into a proper function. For now, moved here from pluto notebook # simulate for gazevectors - ensemble method sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. - # leadfield for centre, to subtract for B-A method - lf_center = leadfield_from_gazedir(eyemodel, sim_srcs_idx, gazevec_from_angle(0), 54.0384).*10e3 - - # leadfields: matrix of dimensions [electrodes x n_gazepoints] + # leadfields: matrix of dimensions [electrodes x n_gazepoints] leadfields_ensemble = zeros(227,length(gazevectors)) for ix in eachindex((gazevectors)) # 1:length(gazevectors) #TODO delete this comment once it's proven to work # for each gazepoint, calculate the leadfield and store it in the corresponding column - leadfields_ensemble[:,ix] = leadfield_from_gazedir(eyemodel, sim_srcs_idx, - gazevectors[ix], 54.0384) + leadfields_ensemble[:,ix] = ensemble_leadfield(eyemodel, sim_srcs_idx, + gazevectors[ix], 54.0384) #leadfield_from_gazedir end end """ TODO docstring -Return imported model, electrode positions, labelsourceindices of eyemodel +Read the eye model from a mat file, remove channels Nk1-Nk4, and calculate left/right eye indices, eye centers, orientations and add them to the eyemodel as properties. +Return imported model, labelsourceindices of eyemodel """ -function import_model() +function import_eyemodel(; labels=[ + r"EyeRetina_Choroid_Sclera_left$" # match the end of the search term, or else it also matches "leftright" sources. + ,r"EyeRetina_Choroid_Sclera_right$" + ,"EyeCornea_left" # eyemodel - only one set of sources per eye, and the labels are different, compared to the full HArtMuT model + ,"EyeCornea_right" + ,"EyeCenter_left" + ,"EyeCenter_right" +], modelpath="HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat" +) # labels for which to find source indices - labels = [ - r"EyeRetina_Choroid_Sclera_left$" # match the end of the search term, or else it also matches "leftright" sources. - ,r"EyeRetina_Choroid_Sclera_right$" - ,"EyeCornea_left" # new spherical eyemodel - only one set of sources per eye and the labels are different - ,"EyeCornea_right" # same as above - ,"EyeCenter_right" - ,"EyeCenter_left" - ] + # labels = [ + # r"EyeRetina_Choroid_Sclera_left$" # match the end of the search term, or else it also matches "leftright" sources. + # ,r"EyeRetina_Choroid_Sclera_right$" + # ,"EyeCornea_left" # new spherical eyemodel - only one set of sources per eye and the labels are different + # ,"EyeCornea_right" # same as above + # ,"EyeCenter_right" + # ,"EyeCenter_left" + # ] - eyemodel = read_eyemodel(; p="HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat") + eyemodel = read_eyemodel(; p=modelpath) remove_indices = [164, 165, 166, 167] # since eyemodel structure doesn't exactly correspond to the main hartmut mat structure expected by the read_new_hartmut function, just get the indices of the electrodes that it drops & drop the same indices from eyemodel directly eyemodel["leadfield"] = eyemodel["leadfield"][Not(remove_indices), :, :] lsi_eyemodel = hart_indices_from_labels(eyemodel,labels) - # import small headmodel temporarily for electrode positions, since eyemodel does not include them - hart_small = UnfoldSim.headmodel() + # add electrode positions to eyemodel - import small headmodel temporarily since the eyemodel does not contain them + hart_small = Hartmut() pos3d = hart_small.electrodes["pos"] - electrode_pos = pos2dfrom3d(pos3d) eyemodel["electrodes"] = deepcopy(hart_small.electrodes) eyemodel["electrodes"]["pos2d"] = pos2dfrom3d(pos3d) - return eyemodel, electrode_pos, lsi_eyemodel + # add indices and positions of certain sets of sources, to make them easier to access + eyemodel["eyeleft_idx"] = [ lsi_eyemodel["EyeCornea_left"] ; lsi_eyemodel[r"EyeRetina_Choroid_Sclera_left$"] ] # eyemodel_left_idx + eyemodel["eyeright_idx"] = [ lsi_eyemodel["EyeCornea_right"] ; lsi_eyemodel[r"EyeRetina_Choroid_Sclera_right$"] ] # eyemodel_right_idx + eyemodel["eyecenter_left_pos"] = eyemodel["pos"][lsi_eyemodel["EyeCenter_left"],:] # eye_center_L + eyemodel["eyecenter_right_pos"] = eyemodel["pos"][lsi_eyemodel["EyeCenter_right"],:] # eye_center_R + eyemodel["eyecenter_left_idx"] = lsi_eyemodel["EyeCenter_left"] + eyemodel["eyecenter_right_idx"] = lsi_eyemodel["EyeCenter_right"] + + # add orientations (by default all set to zero) + eyemodel["orientation"] = zeros(size(eyemodel["pos"])) + + return eyemodel, lsi_eyemodel end """ Calculate left/right eye indices, eye centers, orientations and add them to the eyemodel as properties """ -function setup_eyemodel(eyemodel, lsi_eyemodel) +function setup_ensemble_model(eyemodel, lsi_eyemodel) - eyemodel_left_idx = [ lsi_eyemodel["EyeCornea_left"] ; lsi_eyemodel[r"EyeRetina_Choroid_Sclera_left$"] ] - eyemodel_right_idx = [ lsi_eyemodel["EyeCornea_right"] ; lsi_eyemodel[r"EyeRetina_Choroid_Sclera_right$"] ] + eyemodel_left_idx = eyemodel["eyeleft_idx"] + eyemodel_right_idx = eyemodel["eyeright_idx"] # For calculating orientations: get positions of left and right eye points in eyemodel, and their center (provided directly in spherical model) - em_positions_L = eyemodel["pos"][eyemodel_left_idx,:] - em_positions_R = eyemodel["pos"][eyemodel_right_idx,:] + em_positions_L = eyemodel["pos"][eyemodel["eyeleft_idx"],:] + em_positions_R = eyemodel["pos"][eyemodel["eyeright_idx"],:] eye_center_L = eyemodel["pos"][lsi_eyemodel["EyeCenter_left"],:] eye_center_R = eyemodel["pos"][lsi_eyemodel["EyeCenter_right"],:] # calculate orientations away from center, later use negative weightage for the points where the source dipole points towards the center. - eyemodel["orientation"] = zeros(size(eyemodel["pos"])) - eyemodel["orientation"][eyemodel_right_idx,:] = calc_orientations(eye_center_R, em_positions_R; direction="away") - eyemodel["orientation"][eyemodel_left_idx,:] = calc_orientations(eye_center_L, em_positions_L; direction="away") - - # add some more eyemodel-properties to the model - eyemodel["eyeleft_idx"] = eyemodel_left_idx - eyemodel["eyeright_idx"] = eyemodel_right_idx - eyemodel["eyecenter_left_pos"] = eye_center_L - eyemodel["eyecenter_right_pos"] = eye_center_R - + eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]; direction="away") + eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]; direction="away") return eyemodel - end """ TODO docstring """ -function simulate_crd(eyemodel, gazevectors) # TODO add type & dimensions +function simulate_crd(eyemodel, gazevectors::Vector{Vector{Float64}}) # TODO add type & dimensions leadfields_crd = zeros(227,length(gazevectors)) # TODO replace hardcoded 227 with number of channels in model? eyecenter_idx = [lsi_eyemodel["EyeCenter_left"][1],lsi_eyemodel["EyeCenter_right"][1]] #TODO remove duplication of calculating center indices - for ix in eachindex(gazevectors) # 1:length(gazevectors) #TODO delete this comment once it's proven to work - # calculate leadfield due to 2 individual CRD sources and add - leadfields_crd[:,ix] = ( + + #original from notebook + # for ix in eachindex(gazevectors) + # # calculate leadfield due to 2 individual CRD sources and add + # leadfields_crd[:,ix] = ( + # leadfield_specific_sources_orientations(deepcopy(eyemodel),eyecenter_idx,gazevectors[ix]) + # ) + # end + + # not yet tested + leadfields_crd[:,ix] = ( leadfield_specific_sources_orientations(deepcopy(eyemodel),eyecenter_idx,gazevectors[ix]) - ) - end + for ix in eachindex(gazevectors) ) return leadfields_crd end @@ -283,7 +282,18 @@ function leadfield_specific_sources_orientations(model,idx,equiv_orientations) return mag end -#TODO add dandelion plot as utility function + +""" +TODO docstring +Take just a selected subset of points in the model, along with new orientations for those points, +and calculate the sum of leadfields of just these points with the new orientations. +""" +function equiv_dipole_mag(model,idx,equiv_orientations) + equiv_ori_model = model["orientation"] + equiv_ori_model[idx,:] .= equiv_orientations[1:length(idx),:] + mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],equiv_ori_model) + mag = sum(mag_eyemodel_equiv[:,ii] for ii in idx) +end function find_avg_gazedir() @@ -295,3 +305,46 @@ function find_avg_gazedir() end #TODO auto-find cornea max. angle from center and cornea point positions + + +""" +TODO docstring +""" +function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; time::Vector{Number}, samplingrate::Number, crd=false, ensemble=false) + if (!crd && !ensemble) + @warn "Neither CRD nor Ensemble model selected. No simulation performed." + return [] + end + eyemodel, lsi_eyemodel = import_eyemodel() + # leadfields: matrix of dimensions [electrodes x n_gazepoints] + leadfields = zeros(227,length(gazevectors)) # TODO replace hardcoded 227 with number of channels in model + + if crd + # select eye centers as points + # set orientation = gazedir + leadfields = simulate_crd(eyemodel,gazevectors) + elseif ensemble + # select cornea and retina + # set orientation, weightage + + sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. + + # calculate eyeball source orientations away from center, later use negative weightage for the points where the source dipole points towards the center (i.e. the retina points). + eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]; direction="away") + eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]; direction="away") + + # leadfields: matrix of dimensions [electrodes x n_gazepoints] + leadfields_ensemble = zeros(227,length(gazevectors)) + for ix in eachindex((gazevectors)) # 1:length(gazevectors) #TODO delete this comment once it's proven to work + # for each gazepoint, calculate the leadfield and store it in the corresponding column + leadfields_ensemble[:,ix] = ensemble_leadfield(eyemodel, sim_srcs_idx, + gazevectors[ix], 54.0384) #leadfield_from_gazedir + end + + + end + + # placeholder: matching the simulated leadfields with time points? + + leadfields +end \ No newline at end of file From bdb1bca8eb6703038dfe41264461d157ad85d58b Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Sat, 16 Aug 2025 19:00:46 +0200 Subject: [PATCH 03/32] simplify ensemble simulation --- src/UnfoldSimArtifacts.jl | 36 +++++------------------------------- 1 file changed, 5 insertions(+), 31 deletions(-) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 389dbb00..555814f9 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -216,28 +216,6 @@ function import_eyemodel(; labels=[ eyemodel["orientation"] = zeros(size(eyemodel["pos"])) return eyemodel, lsi_eyemodel -end - - -""" -Calculate left/right eye indices, eye centers, orientations and add them to the eyemodel as properties -""" -function setup_ensemble_model(eyemodel, lsi_eyemodel) - - eyemodel_left_idx = eyemodel["eyeleft_idx"] - eyemodel_right_idx = eyemodel["eyeright_idx"] - - # For calculating orientations: get positions of left and right eye points in eyemodel, and their center (provided directly in spherical model) - em_positions_L = eyemodel["pos"][eyemodel["eyeleft_idx"],:] - em_positions_R = eyemodel["pos"][eyemodel["eyeright_idx"],:] - - eye_center_L = eyemodel["pos"][lsi_eyemodel["EyeCenter_left"],:] - eye_center_R = eyemodel["pos"][lsi_eyemodel["EyeCenter_right"],:] - - # calculate orientations away from center, later use negative weightage for the points where the source dipole points towards the center. - eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]; direction="away") - eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]; direction="away") - return eyemodel end @@ -317,15 +295,14 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti end eyemodel, lsi_eyemodel = import_eyemodel() # leadfields: matrix of dimensions [electrodes x n_gazepoints] - leadfields = zeros(227,length(gazevectors)) # TODO replace hardcoded 227 with number of channels in model + leadfields = zeros(size(eyemodel["pos"])[1],length(gazevectors)) if crd # select eye centers as points # set orientation = gazedir leadfields = simulate_crd(eyemodel,gazevectors) elseif ensemble - # select cornea and retina - # set orientation, weightage + # select cornea and retina sources to simulate; set orientation; simulate EEG for each of the gaze vectors sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. @@ -333,15 +310,12 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]; direction="away") eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]; direction="away") - # leadfields: matrix of dimensions [electrodes x n_gazepoints] - leadfields_ensemble = zeros(227,length(gazevectors)) - for ix in eachindex((gazevectors)) # 1:length(gazevectors) #TODO delete this comment once it's proven to work + # leadfields: matrix with dimensions [electrodes x n_gazepoints] + for ix in eachindex((gazevectors)) # for each gazepoint, calculate the leadfield and store it in the corresponding column - leadfields_ensemble[:,ix] = ensemble_leadfield(eyemodel, sim_srcs_idx, - gazevectors[ix], 54.0384) #leadfield_from_gazedir + leadfields[:,ix] = ensemble_leadfield(eyemodel, sim_srcs_idx, gazevectors[ix], 54.0384) end - end # placeholder: matching the simulated leadfields with time points? From f9559b41b80cd6eaa287e1b304201b58133baf6c Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Sat, 16 Aug 2025 19:37:58 +0200 Subject: [PATCH 04/32] simplify crd simulation; clean up --- src/UnfoldSimArtifacts.jl | 99 +++++++-------------------------------- 1 file changed, 16 insertions(+), 83 deletions(-) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 555814f9..8a1baa49 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -148,25 +148,6 @@ function ensemble_leadfield(eyemodel, sim_idx::Vector{Int}, gazedir::Vector{Floa end -""" -TODO docstring -Simulate eye movement start to end using ensemble method -""" -function sim_gazevecs_ensemble(gazevectors::Vector{Vector{Float64}}) # TODO rename this and turn it into a proper function. For now, moved here from pluto notebook -# simulate for gazevectors - ensemble method - - sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. - - # leadfields: matrix of dimensions [electrodes x n_gazepoints] - leadfields_ensemble = zeros(227,length(gazevectors)) - for ix in eachindex((gazevectors)) # 1:length(gazevectors) #TODO delete this comment once it's proven to work - # for each gazepoint, calculate the leadfield and store it in the corresponding column - leadfields_ensemble[:,ix] = ensemble_leadfield(eyemodel, sim_srcs_idx, - gazevectors[ix], 54.0384) #leadfield_from_gazedir - end -end - - """ TODO docstring Read the eye model from a mat file, remove channels Nk1-Nk4, and calculate left/right eye indices, eye centers, orientations and add them to the eyemodel as properties. @@ -180,18 +161,7 @@ function import_eyemodel(; labels=[ ,"EyeCenter_left" ,"EyeCenter_right" ], modelpath="HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat" -) - - # labels for which to find source indices - # labels = [ - # r"EyeRetina_Choroid_Sclera_left$" # match the end of the search term, or else it also matches "leftright" sources. - # ,r"EyeRetina_Choroid_Sclera_right$" - # ,"EyeCornea_left" # new spherical eyemodel - only one set of sources per eye and the labels are different - # ,"EyeCornea_right" # same as above - # ,"EyeCenter_right" - # ,"EyeCenter_left" - # ] - +) eyemodel = read_eyemodel(; p=modelpath) remove_indices = [164, 165, 166, 167] # since eyemodel structure doesn't exactly correspond to the main hartmut mat structure expected by the read_new_hartmut function, just get the indices of the electrodes that it drops & drop the same indices from eyemodel directly eyemodel["leadfield"] = eyemodel["leadfield"][Not(remove_indices), :, :] @@ -221,56 +191,13 @@ end """ TODO docstring +Calculate the sum of leadfields of just the source points at the given indices. """ -function simulate_crd(eyemodel, gazevectors::Vector{Vector{Float64}}) # TODO add type & dimensions - leadfields_crd = zeros(227,length(gazevectors)) # TODO replace hardcoded 227 with number of channels in model? - eyecenter_idx = [lsi_eyemodel["EyeCenter_left"][1],lsi_eyemodel["EyeCenter_right"][1]] #TODO remove duplication of calculating center indices - - - #original from notebook - # for ix in eachindex(gazevectors) - # # calculate leadfield due to 2 individual CRD sources and add - # leadfields_crd[:,ix] = ( - # leadfield_specific_sources_orientations(deepcopy(eyemodel),eyecenter_idx,gazevectors[ix]) - # ) - # end - - # not yet tested - leadfields_crd[:,ix] = ( - leadfield_specific_sources_orientations(deepcopy(eyemodel),eyecenter_idx,gazevectors[ix]) - for ix in eachindex(gazevectors) ) - - return leadfields_crd -end - - -""" -TODO docstring -""" -function leadfield_specific_sources_orientations(model,idx,equiv_orientations) - # take just a selected subset of points in the model, along with a new orientation for those points, and calculate the sum of leadfields of just these points with the given orientation. - equiv_ori_model = model["orientation"] - - for ii in idx - equiv_ori_model[ii,:] = equiv_orientations[:] - end - - mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],equiv_ori_model) - mag = sum(mag_eyemodel_equiv[:,ii] for ii in idx) - return mag -end - - -""" -TODO docstring -Take just a selected subset of points in the model, along with new orientations for those points, -and calculate the sum of leadfields of just these points with the new orientations. -""" -function equiv_dipole_mag(model,idx,equiv_orientations) - equiv_ori_model = model["orientation"] - equiv_ori_model[idx,:] .= equiv_orientations[1:length(idx),:] - mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],equiv_ori_model) - mag = sum(mag_eyemodel_equiv[:,ii] for ii in idx) +function selected_sources_eeg(eyemodel,src_idx,equiv_orientations) + # equiv_ori_model = model["orientation"] + # equiv_ori_model[idx,:] .= equiv_orientations[1:length(idx),:] + mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) + mag = sum(mag_eyemodel_equiv[:,ii] for ii in src_idx) end @@ -293,14 +220,20 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti @warn "Neither CRD nor Ensemble model selected. No simulation performed." return [] end + eyemodel, lsi_eyemodel = import_eyemodel() + # leadfields: matrix of dimensions [electrodes x n_gazepoints] leadfields = zeros(size(eyemodel["pos"])[1],length(gazevectors)) if crd - # select eye centers as points - # set orientation = gazedir - leadfields = simulate_crd(eyemodel,gazevectors) + # select eye centers as source points; set orientation = gazevector; simulate + for ix in eachindex(gazevectors) + eyemodel["orientation"][eyemodel["eyecenter_left_idx"]] = gazevectors[ix] + eyemodel["orientation"][eyemodel["eyecenter_right_idx"]] = gazevectors[ix] + leadfields_crd[:,ix] = selected_sources_eeg(eyemodel,[eyemodel["eyecenter_left_idx"] eyemodel["eyecenter_right_idx"]],gazevectors[ix]) + end + elseif ensemble # select cornea and retina sources to simulate; set orientation; simulate EEG for each of the gaze vectors From 4af595427e55c93614d31c5becb9c58830b3e1e3 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Sat, 16 Aug 2025 19:48:08 +0200 Subject: [PATCH 05/32] fix calculate_orientation direction parameter --- src/UnfoldSimArtifacts.jl | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 8a1baa49..da82c632 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -81,10 +81,10 @@ end """ TODO docstring -Calculate orientations from the given positions with respect to the reference. `direction` is by default "towards" the reference point; if a different value is given, orientations are calculated away from the reference point. +Calculate orientations from the given positions with respect to the reference. `direction` is by default "away" from the reference point; set `towards` to calculate orientations away from the reference point. """ -function calc_orientations(reference, positions; direction="towards") - if direction == "towards" +function calc_orientations(reference, positions; towards=false, away=true) + if towards orientation_vecs = reference .- positions else orientation_vecs = positions .- reference @@ -223,7 +223,7 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti eyemodel, lsi_eyemodel = import_eyemodel() - # leadfields: matrix of dimensions [electrodes x n_gazepoints] + # leadfields: matrix with dimensions [electrodes x n_gazepoints] leadfields = zeros(size(eyemodel["pos"])[1],length(gazevectors)) if crd @@ -240,10 +240,9 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. # calculate eyeball source orientations away from center, later use negative weightage for the points where the source dipole points towards the center (i.e. the retina points). - eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]; direction="away") - eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]; direction="away") + eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]; towards=true) + eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]; towards=true) - # leadfields: matrix with dimensions [electrodes x n_gazepoints] for ix in eachindex((gazevectors)) # for each gazepoint, calculate the leadfield and store it in the corresponding column leadfields[:,ix] = ensemble_leadfield(eyemodel, sim_srcs_idx, gazevectors[ix], 54.0384) From afc45a6e2caa85a2bd0b8324fa6256b1636cd8c1 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 19 Aug 2025 20:26:31 +0200 Subject: [PATCH 06/32] cleanup --- src/UnfoldSimArtifacts.jl | 63 ++++++++++----------------------------- 1 file changed, 15 insertions(+), 48 deletions(-) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index da82c632..ea17fc5a 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -1,16 +1,3 @@ -#= -TODOs - -- check all the packages used and whether they are actually needed -- do we need ___? - - read_new_hartmut() - - pos2dfrom3d() (it's technically just 2 lines. see unfoldsim docs multichannel example) - -- docstrings for all functions -=# - - - # For helper function to read in the large model # using HDF5 # using DataFrames @@ -24,7 +11,7 @@ TODO docstring Construct the gaze vector in 3-D world coordinates, given the gaze angle (in degrees) as measured from the center gaze (looking straight ahead) in the world x-y plane. Z-component is always 0. """ function gazevec_from_angle(angle_deg) - # just x,y plane for now. gaze angle measured from front neutral gaze, not from x-axis + # just x,y plane. gaze angle measured from front neutral gaze, not from x-axis return [sind(angle_deg) cosd(angle_deg) 0] end @@ -101,25 +88,6 @@ function angle_between(a,b) return acosd.(dot(a, b)/(norm(a)*norm(b))) end -# """ -# TODO docstring -# For the given gaze direction, return a weight value for each source point in the model: 1 for a cornea source, 0 for retina sources and all other points in the model. - -# # Arguments -# - `model`: Head model. -# - `sim_idx`: Indices of the (eye) source points for which weights should be calculated. -# - `gazedir`: The gaze direction vector. -# - `max_cornea_angle_deg`: Angle (in degrees) made by the radial vector containing the cornea point farthest from the cornea center with the radial vector containing the cornea center. - -# # Returns -# - `eyeweights`: Weights of the source points: 1 for a cornea source, 0 for retina sources and all other points in the model. -# """ -# function weights_from_gazedir(model, sim_idx, gazedir, max_cornea_angle_deg) -# eyeweights = zeros(size(model["pos"])[1]) # all sources other than those defined by sim_idx will be set to zero magnitude -# eyeweights[sim_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), model["orientation"][sim_idx,:],dims=2) -# return eyeweights -# end - """ is_corneapoint(orientation::Vector{Float64}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) @@ -148,6 +116,16 @@ function ensemble_leadfield(eyemodel, sim_idx::Vector{Int}, gazedir::Vector{Floa end +""" +TODO docstring +Calculate the sum of leadfields of just the source points at the given indices. +""" +function selected_sources_eeg(eyemodel,src_idx,equiv_orientations) + mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) + mag = sum(mag_eyemodel_equiv[:,ii] for ii in src_idx) +end + + """ TODO docstring Read the eye model from a mat file, remove channels Nk1-Nk4, and calculate left/right eye indices, eye centers, orientations and add them to the eyemodel as properties. @@ -188,19 +166,10 @@ function import_eyemodel(; labels=[ return eyemodel, lsi_eyemodel end - """ TODO docstring -Calculate the sum of leadfields of just the source points at the given indices. -""" -function selected_sources_eeg(eyemodel,src_idx,equiv_orientations) - # equiv_ori_model = model["orientation"] - # equiv_ori_model[idx,:] .= equiv_orientations[1:length(idx),:] - mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) - mag = sum(mag_eyemodel_equiv[:,ii] for ii in src_idx) -end - +""" function find_avg_gazedir() # finding cornea centers and approximate gaze direction (as mean of cornea orientations) cornea_center_R = Statistics.mean(eyemodel["pos"][lsi_eyemodel["EyeCornea_right"],:],dims=1) @@ -220,8 +189,6 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti @warn "Neither CRD nor Ensemble model selected. No simulation performed." return [] end - - eyemodel, lsi_eyemodel = import_eyemodel() # leadfields: matrix with dimensions [electrodes x n_gazepoints] leadfields = zeros(size(eyemodel["pos"])[1],length(gazevectors)) @@ -231,7 +198,7 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti for ix in eachindex(gazevectors) eyemodel["orientation"][eyemodel["eyecenter_left_idx"]] = gazevectors[ix] eyemodel["orientation"][eyemodel["eyecenter_right_idx"]] = gazevectors[ix] - leadfields_crd[:,ix] = selected_sources_eeg(eyemodel,[eyemodel["eyecenter_left_idx"] eyemodel["eyecenter_right_idx"]],gazevectors[ix]) + leadfields[:,ix] = selected_sources_eeg(eyemodel,[eyemodel["eyecenter_left_idx"] eyemodel["eyecenter_right_idx"]],gazevectors[ix]) end elseif ensemble @@ -240,8 +207,8 @@ function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; ti sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. # calculate eyeball source orientations away from center, later use negative weightage for the points where the source dipole points towards the center (i.e. the retina points). - eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]; towards=true) - eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]; towards=true) + eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]) + eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]) for ix in eachindex((gazevectors)) # for each gazepoint, calculate the leadfield and store it in the corresponding column From 0b95b2e4b38abc407080715f2a7b6fba3fa649e6 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 2 Sep 2025 14:19:53 +0200 Subject: [PATCH 07/32] bring simulation functions to the same level --- src/UnfoldSimArtifacts.jl | 129 ++++++++++++++++++++++++-------------- 1 file changed, 81 insertions(+), 48 deletions(-) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index ea17fc5a..59d7328c 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -68,7 +68,7 @@ end """ TODO docstring -Calculate orientations from the given positions with respect to the reference. `direction` is by default "away" from the reference point; set `towards` to calculate orientations away from the reference point. +Calculate orientations from the given positions with respect to the reference. `direction` is by default "away" from the reference point; set `towards=true` to calculate orientations away from the reference point. """ function calc_orientations(reference, positions; towards=false, away=true) if towards @@ -111,18 +111,88 @@ function ensemble_leadfield(eyemodel, sim_idx::Vector{Int}, gazedir::Vector{Floa source_weights = zeros(size(eyemodel["pos"])[1]) # all sources other than those defined by sim_idx will be set to zero magnitude source_weights[sim_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), eyemodel["orientation"][sim_idx,:],dims=2) - weighted_sum = sum(mag_model[:,idx].* source_weights[idx] for idx in sim_idx,dims=2) + weighted_sum = sum(mag_model[:,idx].* source_weights[idx] for idx in sim_idx) return weighted_sum end """ TODO docstring -Calculate the sum of leadfields of just the source points at the given indices. +Multiple gaze direction vectors. Assumes orientations are already set in eyemodel """ -function selected_sources_eeg(eyemodel,src_idx,equiv_orientations) - mag_eyemodel_equiv = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) - mag = sum(mag_eyemodel_equiv[:,ii] for ii in src_idx) +function eyegaze_eeg(eyemodel, src_idx::Vector{Int}, gazedir::Vector{Vector{Float64}}, weights) + + signal = zeros(size(eyemodel["pos"])[1],length(gazedir)) + for ix in eachindex(gazedir) + signal[:,ix] = eyegaze_eeg(eyemodel, src_idx, weights[ix]) + end + + return signal +end + + +""" +TODO docstring +Single gaze direction. Assumes orientations are already set in eyemodel +""" +function eyegaze_eeg(eyemodel, src_idx::Vector{Int}, weights::Vector{Int}) + + mag = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) + signal = sum(mag[:,idx].* weights[idx] for idx in src_idx) + + return signal +end + + +""" +TODO docstring +""" +function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; time::Vector{Number}, samplingrate::Number, crd=false, ensemble=false) + if (!crd && !ensemble) + @warn "Neither CRD nor Ensemble model selected. No simulation performed." + return [] + end + + # when gaze direction changes, + # CRD: orientation changes, weight stays the same + # Ensemble: orientation stays the same, weight changes + + # signal: matrix with dimensions [electrodes x n_gazepoints] + signal = zeros(size(eyemodel["pos"])[1],length(gazevectors)) + + # weights: n_channel x n_gazevec + + if crd + weights = ones(size(eyemodel["pos"])[1]) + src_idx = [eyemodel["eyecenter_left_idx"] eyemodel["eyecenter_right_idx"]] + # select eye centers as source points; set orientation = gazevector + for ix in eachindex(gazevectors) + eyemodel["orientation"][eyemodel["eyecenter_left_idx"]] = gazevectors[ix] + eyemodel["orientation"][eyemodel["eyecenter_right_idx"]] = gazevectors[ix] + # or just use src_idx - will help later if we want to simulate just for one eye or so + + signal[:,ix] = eyegaze_eeg(eyemodel, src_idx, weights) + end + + elseif ensemble + weights = zeros(size(eyemodel["pos"])[1]) + # select cornea and retina sources to simulate; set orientation; simulate EEG for each of the gaze vectors + + # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. + src_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] + + + for ix in eachindex((gazevectors)) + # weight changes depending on retina/cornea type based on current gazevector + weights[src_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), eyemodel["orientation"][src_idx,:]) + # change the above line to separately calculate weights for left and right eye if giving gazepoints and calculating gaze vectors separately. or just run simulate_eyemovement twice, once with gazevectors based on left eye and once with right eye? + + signal[:,ix] = eyegaze_eeg(eyemodel, src_idx, weights) + end + + end + + return signal end @@ -163,6 +233,11 @@ function import_eyemodel(; labels=[ # add orientations (by default all set to zero) eyemodel["orientation"] = zeros(size(eyemodel["pos"])) + # calculate eye surface sources' orientations away from the respective eye centers + # later use negative weightage for the points where the source dipole points towards the center (i.e. the retina points). + eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]) + eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]) + return eyemodel, lsi_eyemodel end @@ -179,45 +254,3 @@ function find_avg_gazedir() end #TODO auto-find cornea max. angle from center and cornea point positions - - -""" -TODO docstring -""" -function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; time::Vector{Number}, samplingrate::Number, crd=false, ensemble=false) - if (!crd && !ensemble) - @warn "Neither CRD nor Ensemble model selected. No simulation performed." - return [] - end - - # leadfields: matrix with dimensions [electrodes x n_gazepoints] - leadfields = zeros(size(eyemodel["pos"])[1],length(gazevectors)) - - if crd - # select eye centers as source points; set orientation = gazevector; simulate - for ix in eachindex(gazevectors) - eyemodel["orientation"][eyemodel["eyecenter_left_idx"]] = gazevectors[ix] - eyemodel["orientation"][eyemodel["eyecenter_right_idx"]] = gazevectors[ix] - leadfields[:,ix] = selected_sources_eeg(eyemodel,[eyemodel["eyecenter_left_idx"] eyemodel["eyecenter_right_idx"]],gazevectors[ix]) - end - - elseif ensemble - # select cornea and retina sources to simulate; set orientation; simulate EEG for each of the gaze vectors - - sim_srcs_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. - - # calculate eyeball source orientations away from center, later use negative weightage for the points where the source dipole points towards the center (i.e. the retina points). - eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]) - eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]) - - for ix in eachindex((gazevectors)) - # for each gazepoint, calculate the leadfield and store it in the corresponding column - leadfields[:,ix] = ensemble_leadfield(eyemodel, sim_srcs_idx, gazevectors[ix], 54.0384) - end - - end - - # placeholder: matching the simulated leadfields with time points? - - leadfields -end \ No newline at end of file From 1483628f2e156d6916e7c4d568f50f76fafc3dbd Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 2 Sep 2025 14:20:25 +0200 Subject: [PATCH 08/32] add first tests for eyemovement --- test/helper.jl | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/test/helper.jl b/test/helper.jl index 053941d0..a2dab43a 100644 --- a/test/helper.jl +++ b/test/helper.jl @@ -18,4 +18,13 @@ end + + @testset "gazevec_from_angle_3d" begin + @test UnfoldSim.gazevec_from_angle_3d(0, 0) ≈ [0; 1; 0] + @test UnfoldSim.gazevec_from_angle_3d(0,90) ≈ [0; 0; 1] + @test UnfoldSim.gazevec_from_angle_3d(90,0) ≈ [1; 0; 0] + # @test isapprox(UnfoldSim.gazevec_from_angle_3d(0,0), [0; 1; 0]) + # @test isapprox(UnfoldSim.gazevec_from_angle_3d(0,90), [0; 0; 1]) + # @test isapprox(UnfoldSim.gazevec_from_angle_3d(90,0), [1; 0; 0]) + end end From 1152943ea23072bbfdfa8f27b228c4edaef943ea Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 2 Sep 2025 19:49:38 +0200 Subject: [PATCH 09/32] import package for eyemovement --- Project.toml | 2 ++ src/UnfoldSim.jl | 7 +++++++ 2 files changed, 9 insertions(+) diff --git a/Project.toml b/Project.toml index 889f5c68..367c1169 100644 --- a/Project.toml +++ b/Project.toml @@ -5,6 +5,7 @@ version = "0.4.1" [deps] Artifacts = "56f22d72-fd6d-98f1-02f0-08ddc0907c33" +CoordinateTransformations = "150eb455-5306-5404-9cee-2592286d6298" DSP = "717857b8-e6f2-59f4-9121-6e50c889abd2" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f" @@ -23,6 +24,7 @@ ToeplitzMatrices = "c751599d-da0a-543b-9d20-d0a503d91d24" [compat] Artifacts = "1" +CoordinateTransformations = "0.6.4" DSP = "0.7,0.8" DataFrames = "1" Distributions = "0.25" diff --git a/src/UnfoldSim.jl b/src/UnfoldSim.jl index 80944294..14d73f60 100644 --- a/src/UnfoldSim.jl +++ b/src/UnfoldSim.jl @@ -17,6 +17,9 @@ using HDF5, Artifacts, FileIO using LinearAlgebra # headmodel +using CoordinateTransformations +import CoordinateTransformations.CartesianFromSpherical # artifacts - gaze direction vector + import DSP.hanning import Base.length import Base.size @@ -31,6 +34,7 @@ include("predefinedSimulations.jl") include("headmodel.jl") include("helper.jl") include("bases.jl") +include("UnfoldSimArtifacts.jl") export size, length export AbstractComponent, AbstractNoise, AbstractOnset, AbstractDesign @@ -78,3 +82,6 @@ export AbstractHeadmodel, Hartmut, headmodel, leadfield, orientation, magnitude # multichannel export MultichannelComponent end + +# artifacts +export simulate_eyemovement \ No newline at end of file From 0c90b8496eda9e637f6ba326394a1324fe410d7f Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 2 Sep 2025 22:07:45 +0200 Subject: [PATCH 10/32] move artifact-related tests to a separate test file --- test/UnfoldSimArtifacts.jl | 5 +++++ test/helper.jl | 9 --------- test/runtests.jl | 1 + 3 files changed, 6 insertions(+), 9 deletions(-) create mode 100644 test/UnfoldSimArtifacts.jl diff --git a/test/UnfoldSimArtifacts.jl b/test/UnfoldSimArtifacts.jl new file mode 100644 index 00000000..3096c41a --- /dev/null +++ b/test/UnfoldSimArtifacts.jl @@ -0,0 +1,5 @@ +@testset "gazevec_from_angle_3d" begin + @test UnfoldSim.gazevec_from_angle_3d(0, 0) ≈ [0; 1; 0] + @test UnfoldSim.gazevec_from_angle_3d(0,90) ≈ [0; 0; 1] + @test UnfoldSim.gazevec_from_angle_3d(90,0) ≈ [1; 0; 0] +end \ No newline at end of file diff --git a/test/helper.jl b/test/helper.jl index a2dab43a..053941d0 100644 --- a/test/helper.jl +++ b/test/helper.jl @@ -18,13 +18,4 @@ end - - @testset "gazevec_from_angle_3d" begin - @test UnfoldSim.gazevec_from_angle_3d(0, 0) ≈ [0; 1; 0] - @test UnfoldSim.gazevec_from_angle_3d(0,90) ≈ [0; 0; 1] - @test UnfoldSim.gazevec_from_angle_3d(90,0) ≈ [1; 0; 0] - # @test isapprox(UnfoldSim.gazevec_from_angle_3d(0,0), [0; 1; 0]) - # @test isapprox(UnfoldSim.gazevec_from_angle_3d(0,90), [0; 0; 1]) - # @test isapprox(UnfoldSim.gazevec_from_angle_3d(90,0), [1; 0; 0]) - end end diff --git a/test/runtests.jl b/test/runtests.jl index 723fc891..f5dc8520 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -8,4 +8,5 @@ include("setup.jl") include("onset.jl") include("simulation.jl") include("helper.jl") + include("UnfoldSimArtifacts.jl") end From e9172231097f8695e54db60d21c95fb4e3cd2ae7 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 2 Sep 2025 22:46:19 +0200 Subject: [PATCH 11/32] rename some variables and functions; edit docstrings --- src/UnfoldSimArtifacts.jl | 98 ++++++++++++++++++++------------------- 1 file changed, 51 insertions(+), 47 deletions(-) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 59d7328c..e13b76ff 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -20,7 +20,8 @@ TODO docstring Calculate the gaze vector in 3-D world coordinates, given the horizontal and vertical angles (in degrees) from center gaze direction i.e. looking straight ahead. """ function gazevec_from_angle_3d(angle_H, angle_V) - # angles measured from center gaze position => use complementary angle for θ + # angles measured from center gaze position => use complementary angle for θ; + # ϕ is already measured upwards from the x-y plane, according to the conventions of CoordinateTransformations.jl return Array{Float32}(CartesianFromSpherical()(Spherical(1, deg2rad(90-angle_H), deg2rad(angle_V)))) end @@ -68,12 +69,13 @@ end """ TODO docstring -Calculate orientations from the given positions with respect to the reference. `direction` is by default "away" from the reference point; set `towards=true` to calculate orientations away from the reference point. +Calculate orientation vectors from the given positions with respect to the reference. The vectors are normalized to have length 1. +`direction` is by default "away" from the reference point; set `direction="towards"` to calculate orientations towards the reference point. """ -function calc_orientations(reference, positions; towards=false, away=true) - if towards +function calc_orientations(reference, positions; direction::String="away") + if direction=="towards" orientation_vecs = reference .- positions - else + else orientation_vecs = positions .- reference end return orientation_vecs ./ norm.(eachrow(orientation_vecs)) @@ -82,7 +84,7 @@ end """ TODO docstring -Calculate the angle between two 3-D vectors. +Return the angle (in degrees) between two 3-D vectors in Cartesian coordinates. """ function angle_between(a,b) return acosd.(dot(a, b)/(norm(a)*norm(b))) @@ -92,6 +94,7 @@ end """ is_corneapoint(orientation::Vector{Float64}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) +Return 1 if the angle between the given orientation vector and the gaze direction vector is less than or equal to the given maximum cornea angle; else return -1. """ function is_corneapoint(orientation::Vector{Float64}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) @@ -116,26 +119,11 @@ function ensemble_leadfield(eyemodel, sim_idx::Vector{Int}, gazedir::Vector{Floa end -""" -TODO docstring -Multiple gaze direction vectors. Assumes orientations are already set in eyemodel -""" -function eyegaze_eeg(eyemodel, src_idx::Vector{Int}, gazedir::Vector{Vector{Float64}}, weights) - - signal = zeros(size(eyemodel["pos"])[1],length(gazedir)) - for ix in eachindex(gazedir) - signal[:,ix] = eyegaze_eeg(eyemodel, src_idx, weights[ix]) - end - - return signal -end - - """ TODO docstring Single gaze direction. Assumes orientations are already set in eyemodel """ -function eyegaze_eeg(eyemodel, src_idx::Vector{Int}, weights::Vector{Int}) +function generate_eyegaze_eeg(eyemodel, src_idx::Vector{Int}, weights::Vector{Int}) mag = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) signal = sum(mag[:,idx].* weights[idx] for idx in src_idx) @@ -145,54 +133,70 @@ end """ -TODO docstring +Simulate the eye movement and return the corresponding scalp potentials at each of the channels, +given a head model, an array of gaze direction vectors defining the eye movement, and optionally an eye-model type. + +# Arguments +- `headmodel`: Head model to be used. +- `gazevectors::Vector{Vector{Float64}}`: Vector of gaze direction vectors (in Cartesian coordinates) to define the eye movement trajectory. The vector should point from the eyes towards the point at which the gaze is directed. +- `eye_model::String` (optional): Choice of model to use for the eye. Options available are "crd" (default) and "ensemble". + +# Returns +- + +TODO docstring; type for headmodel; auto-conversion from x,y angles to gaze direction vectors """ -function simulate_eyemovement(eyemodel, gazevectors::Vector{Vector{Float64}}; time::Vector{Number}, samplingrate::Number, crd=false, ensemble=false) - if (!crd && !ensemble) - @warn "Neither CRD nor Ensemble model selected. No simulation performed." - return [] - end +function simulate_eyemovement(headmodel, gazevectors::Vector{Vector{Float64}}; eye_model::String="crd") - # when gaze direction changes, - # CRD: orientation changes, weight stays the same - # Ensemble: orientation stays the same, weight changes + # if (x,y) angles have been passed in, convert them to cartesian coordinates + # if(size(gazevectors)[2]==2) + # hcat(gazevec_from_angle_3d.(gd_realdata[1,:],gd_realdata[2,:])) + # end - # signal: matrix with dimensions [electrodes x n_gazepoints] - signal = zeros(size(eyemodel["pos"])[1],length(gazevectors)) - # weights: n_channel x n_gazevec + # when gaze direction vector changes, + # CRD: orientation changes, weight stays the same (=1 for all points) + # Ensemble: orientation stays the same, weight changes (=1 for cornea points, -1 for retina points, calculated based on gaze direction) - if crd - weights = ones(size(eyemodel["pos"])[1]) - src_idx = [eyemodel["eyecenter_left_idx"] eyemodel["eyecenter_right_idx"]] + # leadfields: matrix with dimensions [electrodes x n_gazepoints] + leadfields = zeros(size(headmodel["pos"])[1],length(gazevectors)) + + # weights: matrix of dimensions [n_channel x n_gazevec] + + if eye_model=="crd" + weights = ones(size(headmodel["pos"])[1]) + src_idx = [headmodel["eyecenter_left_idx"] headmodel["eyecenter_right_idx"]] # select eye centers as source points; set orientation = gazevector for ix in eachindex(gazevectors) - eyemodel["orientation"][eyemodel["eyecenter_left_idx"]] = gazevectors[ix] - eyemodel["orientation"][eyemodel["eyecenter_right_idx"]] = gazevectors[ix] + headmodel["orientation"][headmodel["eyecenter_left_idx"]] = gazevectors[ix] + headmodel["orientation"][headmodel["eyecenter_right_idx"]] = gazevectors[ix] # or just use src_idx - will help later if we want to simulate just for one eye or so - signal[:,ix] = eyegaze_eeg(eyemodel, src_idx, weights) + leadfields[:,ix] = generate_eyegaze_eeg(headmodel, src_idx, weights) end - elseif ensemble - weights = zeros(size(eyemodel["pos"])[1]) + elseif eye_model=="ensemble" + weights = zeros(size(headmodel["pos"])[1]) + # select cornea and retina sources to simulate; set orientation; simulate EEG for each of the gaze vectors - # indices in eyemodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. - src_idx = [eyemodel["eyeleft_idx"]; eyemodel["eyeright_idx"]] + # indices in headmodel, of the points which we want to use to simulate data, i.e. retina & cornea. used for ensemble simulation. + src_idx = [headmodel["eyeleft_idx"]; headmodel["eyeright_idx"]] for ix in eachindex((gazevectors)) # weight changes depending on retina/cornea type based on current gazevector - weights[src_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), eyemodel["orientation"][src_idx,:]) + weights[src_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), headmodel["orientation"][src_idx,:]) # change the above line to separately calculate weights for left and right eye if giving gazepoints and calculating gaze vectors separately. or just run simulate_eyemovement twice, once with gazevectors based on left eye and once with right eye? - signal[:,ix] = eyegaze_eeg(eyemodel, src_idx, weights) + leadfields[:,ix] = generate_eyegaze_eeg(headmodel, src_idx, weights) end + else + @error "Neither CRD nor Ensemble model selected. No eye movement simulation performed." end - return signal + return leadfields end From 58aeb99a58b2230e5974bf49dcf93319357c152f Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 16 Sep 2025 13:43:26 +0200 Subject: [PATCH 12/32] add example data from real dataset --- src/helper.jl | 7 ++ src/sample_eeg_eyemovements.csv | 137 ++++++++++++++++++++++++++++++++ test/helper.jl | 5 ++ 3 files changed, 149 insertions(+) create mode 100644 src/sample_eeg_eyemovements.csv diff --git a/src/helper.jl b/src/helper.jl index 098d035b..68d625db 100755 --- a/src/helper.jl +++ b/src/helper.jl @@ -273,3 +273,10 @@ function epoch(data::AbstractVector, args...; kwargs...) ep = epoch(data_r, args...; kwargs...) return dropdims(ep; dims = 1) end + +function example_data_eyemovements() + return Matrix(CSV.read("src/sample_eeg_eyemovements.csv",DataFrame)) + # Eye tracking and EEG combined dataset + # channels 1,2 are eye tracking values: HREF angles; 3 is pupil size. + # channels 4-6: same but for other eye +end \ No newline at end of file diff --git a/src/sample_eeg_eyemovements.csv b/src/sample_eeg_eyemovements.csv new file mode 100644 index 00000000..aa0aa226 --- /dev/null +++ b/src/sample_eeg_eyemovements.csv @@ -0,0 +1,137 @@ 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901078016e6,5.098902126592e6,5.098903175168e6,5.098904223743999e6,5.0989052723199995e6,5.098906320896e6,5.098907369472e6,5.098908418048e6,5.098909466624e6,5.098910515199999e6,5.098911039488e6,5.098912088064e6,5.09891313664e6,5.098914185215999e6,5.0989152337919995e6,5.098916282368e6 diff --git a/test/helper.jl b/test/helper.jl index 053941d0..0127dc18 100644 --- a/test/helper.jl +++ b/test/helper.jl @@ -18,4 +18,9 @@ end + + @testset "example_data_eyemovements" begin + example_data = UnfoldSim.example_data_eyemovements() + @test size(example_data) == (136, 2000) + end end From 6ebb1e7106f970ee2e93842a467d81e4a39ff201 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 16 Sep 2025 13:58:43 +0200 Subject: [PATCH 13/32] add CSV --- Project.toml | 2 ++ src/UnfoldSim.jl | 2 ++ 2 files changed, 4 insertions(+) diff --git a/Project.toml b/Project.toml index 367c1169..91f79b6a 100644 --- a/Project.toml +++ b/Project.toml @@ -5,6 +5,7 @@ version = "0.4.1" [deps] Artifacts = "56f22d72-fd6d-98f1-02f0-08ddc0907c33" +CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" CoordinateTransformations = "150eb455-5306-5404-9cee-2592286d6298" DSP = "717857b8-e6f2-59f4-9121-6e50c889abd2" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" @@ -24,6 +25,7 @@ ToeplitzMatrices = "c751599d-da0a-543b-9d20-d0a503d91d24" [compat] Artifacts = "1" +CSV = "0.10.15" CoordinateTransformations = "0.6.4" DSP = "0.7,0.8" DataFrames = "1" diff --git a/src/UnfoldSim.jl b/src/UnfoldSim.jl index 14d73f60..f638f5d5 100644 --- a/src/UnfoldSim.jl +++ b/src/UnfoldSim.jl @@ -19,6 +19,7 @@ using LinearAlgebra # headmodel using CoordinateTransformations import CoordinateTransformations.CartesianFromSpherical # artifacts - gaze direction vector +using CSV # artifacts - importing sample data from csv file import DSP.hanning import Base.length @@ -35,6 +36,7 @@ include("headmodel.jl") include("helper.jl") include("bases.jl") include("UnfoldSimArtifacts.jl") +include("AbstractContinuousSignal.jl") export size, length export AbstractComponent, AbstractNoise, AbstractOnset, AbstractDesign From 0a7779789f21d1929dff8da12117b37ebb6ec6a7 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 16 Sep 2025 14:00:05 +0200 Subject: [PATCH 14/32] add AbstractContinuousSignal, a-z simulation beginnings --- src/AbstractContinuousSignal.jl | 62 +++++++++++++++++++++++++++++++++ src/UnfoldSimArtifacts.jl | 31 ++++++++++++----- src/simulation.jl | 7 ++++ src/types.jl | 6 ---- 4 files changed, 91 insertions(+), 15 deletions(-) create mode 100644 src/AbstractContinuousSignal.jl diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl new file mode 100644 index 00000000..a3a4ad97 --- /dev/null +++ b/src/AbstractContinuousSignal.jl @@ -0,0 +1,62 @@ +abstract type AbstractContinuousSignal end + +struct EyeMovement <: AbstractContinuousSignal + controlsignal + headmodel + # events # <-- from realdata (or from controlsignal?) or passed in by user. will be added into the events dataframe returned by simulation function +end + +struct TRF <: AbstractContinuousSignal + controlsignal + # TBD +end + +struct PowerLineNoise <: AbstractContinuousSignal + controlsignal + base_freq::Float64 = 50 + harmonics::Array{Int} = [1 3 5] + sampling_rate::Float64 = 500 +end + +""" +controlsignal: +2 x n_timepoints Matrix containing x,y angles specifying n gaze direction vectors (measured from center gaze reference) +TODO docstring +""" +function simulate_continuoussignal(rng::AbstractRNG,s::EyeMovement,controlsignal::HREFCoordinates, headmodel::AbstractHeadmodel, eye_model="crd") + return simulate_eyemovement(headmodel,gazevec_from_angle_3d.(controlsignal[1,:],controlsignal[2,:]); eye_model=eye_model) +end + +function simulate_continuoussignal(rng::AbstractRNG,s::PowerLineNoise,controlsignal::AbstractArray, base_freq::Float64, harmonics::Array{Int} = [1 3 5], sampling_rate::Float64 = 500.0) + k = 0:1:size(controlsignal)-1 # assumes controlsignal is just 1D + # TODO add check for nyquist criterion? sampling rate & freq -> warn or error? + + n_samples = sampling_rate*length(controlsignal) + 1 # TODO check if we need the +1 or not depending on UnfoldSim conventions + # TODO generate sinusoids at each harmonic + + # not sure yet if controlsignal should be multidimensional (e.g. different magnitudes for different channels => n_chan x time) + # or if we just take the simplest case: the same vector will be used for all channels. + # weight the values at each point, if we need to have different relative strengths of harmonics or if we want to switch on/off the PLN +end + +# function simulate_continuoussignal(rng, s::TRF, controlsignal::) +# # TBD +# end + + + +# sketching possibilities for generate_controlsignal + +function generate_controlsignal(rng::AbstractRNG, c::GazeDirectionVectors) + return c +end + +function generate_controlsignal(rng::AbstractRNG, c::HREFCoordinates) + return gazevec_from_angle_3d.(c[1,:],c[2,:]) +end + +abstract type AbstractControlSignal end + +struct HREFCoordinates <: AbstractControlSignal end + +struct GazeDirectionVectors <: AbstractControlSignal end \ No newline at end of file diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index e13b76ff..1c5c55a1 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -146,14 +146,7 @@ given a head model, an array of gaze direction vectors defining the eye movement TODO docstring; type for headmodel; auto-conversion from x,y angles to gaze direction vectors """ -function simulate_eyemovement(headmodel, gazevectors::Vector{Vector{Float64}}; eye_model::String="crd") - - # if (x,y) angles have been passed in, convert them to cartesian coordinates - # if(size(gazevectors)[2]==2) - # hcat(gazevec_from_angle_3d.(gd_realdata[1,:],gd_realdata[2,:])) - # end - - +function simulate_eyemovement(headmodel, gazevectors::GazeDirectionVectors; eye_model::String="crd") # when gaze direction vector changes, # CRD: orientation changes, weight stays the same (=1 for all points) # Ensemble: orientation stays the same, weight changes (=1 for cornea points, -1 for retina points, calculated based on gaze direction) @@ -242,7 +235,7 @@ function import_eyemodel(; labels=[ eyemodel["orientation"][eyemodel["eyeleft_idx"],:] = calc_orientations(eyemodel["eyecenter_left_pos"], eyemodel["pos"][eyemodel["eyeleft_idx"],:]) eyemodel["orientation"][eyemodel["eyeright_idx"],:] = calc_orientations(eyemodel["eyecenter_right_pos"], eyemodel["pos"][eyemodel["eyeright_idx"],:]) - return eyemodel, lsi_eyemodel + return eyemodel end """ @@ -258,3 +251,23 @@ function find_avg_gazedir() end #TODO auto-find cornea max. angle from center and cornea point positions + + +function a_z_simulation() + # import hartmut model - modified with new eye points + eyemodel::AbstractHeadmodel = import_eyemodel() + + # import href gaze coordinates + sample_data = example_data_eyemovements() + href_trajectory::HREFCoordinates = sample_data[1:2,:] + + # setup basic ingredients for simulate + # design, .... , noise + + # Ques: should it be possible to simulate just for eyemovement, without specifying any design etc? Just passing in the eye trajectory? + + # call simulate with href coords + simulate(d, c, o, [EyeMovement(href_trajectory, eyemodel, nothing) NoNoise()]) # TODO clarify! + + # plot simulated data +end \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index 07539dc0..8b2f74a9 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -183,6 +183,13 @@ function simulate(rng::AbstractRNG, simulation::Simulation; return_epoched::Bool end +function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::AbstractOnset,s::Vector{Union{AbstractContinuousSignal, AbstractNoise}}) + controlsignal::Matrix = generate_controlsignal(deepcopy(rng),s) # Matrix (feat x time) + signal::Matrix = simulate_continuoussignal(deepcopy(rng),s,controlsignal) # --> contains all the different noise-related signals. ((feat x time?)) + # so here we do the normal simulation and then add the prev result to the result of normal simulation? + + # TODO see Ref syntax from pseudocode +end """ create_continuous_signal(rng, responses, simulation) diff --git a/src/types.jl b/src/types.jl index 8419f4fa..314f32ef 100644 --- a/src/types.jl +++ b/src/types.jl @@ -5,8 +5,6 @@ abstract type AbstractDesign end abstract type AbstractComponent end -abstract type AbstractContinuousSignal end - # find other types in onset.jl and noise.jl # and in design.jl and component.jl @@ -71,7 +69,3 @@ struct Simulation onset::AbstractOnset noisetype::AbstractNoise end - -struct EyeMovement <: AbstractContinuousSignal - controlsignal -end \ No newline at end of file From b3c6544b3dac8a7a9c47bcfb55dd6c3487737780 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Fri, 19 Sep 2025 16:46:36 +0200 Subject: [PATCH 15/32] added dependency & mat files for eyemodel import --- Project.toml | 2 ++ ...d_extra_eyemodel_hull_mesh8_2025-03-01.mat | Bin 0 -> 6675471 bytes ...extra_eyemodel_sphere_mesh8_2025-03-01.mat | Bin 0 -> 6684010 bytes 3 files changed, 2 insertions(+) create mode 100644 src/HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat create mode 100644 src/HArtMuT_NYhead_extra_eyemodel_sphere_mesh8_2025-03-01.mat diff --git a/Project.toml b/Project.toml index 91f79b6a..c2862c4b 100644 --- a/Project.toml +++ b/Project.toml @@ -14,6 +14,7 @@ FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549" HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f" ImageFiltering = "6a3955dd-da59-5b1f-98d4-e7296123deb5" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" +MAT = "23992714-dd62-5051-b70f-ba57cb901cac" MixedModels = "ff71e718-51f3-5ec2-a782-8ffcbfa3c316" MixedModelsSim = "d5ae56c5-23ca-4a1f-b505-9fc4796fc1fe" Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a" @@ -34,6 +35,7 @@ FileIO = "1" HDF5 = "0.17" ImageFiltering = "0.7" LinearAlgebra = "1" +MAT = "0.10.7" MixedModels = 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diff --git a/src/UnfoldSim.jl b/src/UnfoldSim.jl index f638f5d5..02c4ac72 100644 --- a/src/UnfoldSim.jl +++ b/src/UnfoldSim.jl @@ -20,6 +20,7 @@ using LinearAlgebra # headmodel using CoordinateTransformations import CoordinateTransformations.CartesianFromSpherical # artifacts - gaze direction vector using CSV # artifacts - importing sample data from csv file +using MAT # artifacts - loading model from .mat file import DSP.hanning import Base.length @@ -35,8 +36,8 @@ include("predefinedSimulations.jl") include("headmodel.jl") include("helper.jl") include("bases.jl") -include("UnfoldSimArtifacts.jl") include("AbstractContinuousSignal.jl") +include("UnfoldSimArtifacts.jl") export size, length export AbstractComponent, AbstractNoise, AbstractOnset, AbstractDesign @@ -86,4 +87,4 @@ export MultichannelComponent end # artifacts -export simulate_eyemovement \ No newline at end of file +export simulate_eyemovement, GazeDirectionVectors, HREFCoordinates, AbstractControlSignal, import_eyemodel, AbstractContinuousSignal, EyeMovement \ No newline at end of file diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 1c5c55a1..dd8b0b59 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -58,7 +58,7 @@ Arguments: Returns: - `labelsourceindices::Dict`: Dict with the keys being the label and the values being the indices of sources with that label in the given model. """ -function hart_indices_from_labels(headmodel,labels::Vector{String}=["dummy"]) +function hart_indices_from_labels(headmodel,labels::AbstractVector=["dummy"]) labelsourceindices = Dict() for l in labels labelsourceindices[l] = findall(k->occursin(l,k),headmodel["label"][:]) @@ -144,7 +144,7 @@ given a head model, an array of gaze direction vectors defining the eye movement # Returns - -TODO docstring; type for headmodel; auto-conversion from x,y angles to gaze direction vectors +TODO docstring; type for headmodel; always takes in gaze direction vectors as controlsignal """ function simulate_eyemovement(headmodel, gazevectors::GazeDirectionVectors; eye_model::String="crd") # when gaze direction vector changes, @@ -205,7 +205,7 @@ function import_eyemodel(; labels=[ ,"EyeCornea_right" ,"EyeCenter_left" ,"EyeCenter_right" -], modelpath="HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat" +], modelpath="src/HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat" ) eyemodel = read_eyemodel(; p=modelpath) remove_indices = [164, 165, 166, 167] # since eyemodel structure doesn't exactly correspond to the main hartmut mat structure expected by the read_new_hartmut function, just get the indices of the electrodes that it drops & drop the same indices from eyemodel directly @@ -217,7 +217,6 @@ function import_eyemodel(; labels=[ hart_small = Hartmut() pos3d = hart_small.electrodes["pos"] eyemodel["electrodes"] = deepcopy(hart_small.electrodes) - eyemodel["electrodes"]["pos2d"] = pos2dfrom3d(pos3d) # add indices and positions of certain sets of sources, to make them easier to access eyemodel["eyeleft_idx"] = [ lsi_eyemodel["EyeCornea_left"] ; lsi_eyemodel[r"EyeRetina_Choroid_Sclera_left$"] ] # eyemodel_left_idx @@ -253,21 +252,29 @@ end #TODO auto-find cornea max. angle from center and cornea point positions -function a_z_simulation() +function az_simulation() # import hartmut model - modified with new eye points - eyemodel::AbstractHeadmodel = import_eyemodel() + eyemodel = import_eyemodel() # import href gaze coordinates sample_data = example_data_eyemovements() - href_trajectory::HREFCoordinates = sample_data[1:2,:] + href_trajectory = sample_data[1:2,:] # setup basic ingredients for simulate - # design, .... , noise - - # Ques: should it be possible to simulate just for eyemovement, without specifying any design etc? Just passing in the eye trajectory? + design = SingleSubjectDesign(; conditions = Dict(:cond_A => ["level_A", "level_B"])) |> x -> RepeatDesign(x, 10); + signal = LinearModelComponent(; + basis = [0, 0, 0, 0.5, 1, 1, 0.5, 0, 0], + formula = @formula(0 ~ 1 + cond_A), + β = [1, 0.5], + ); + onset = UniformOnset(; width = 20, offset = 4); + noise = PinkNoise(; noiselevel = 0.2); # call simulate with href coords - simulate(d, c, o, [EyeMovement(href_trajectory, eyemodel, nothing) NoNoise()]) # TODO clarify! + + println("Calling simulate...") + data, events = simulate(MersenneTwister(1), design, signal, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise]); + # simulate(d, c, o, [EyeMovement(href_trajectory, eyemodel) NoNoise()]) # plot simulated data end \ No newline at end of file diff --git a/src/types.jl b/src/types.jl index 314f32ef..14d05e5c 100644 --- a/src/types.jl +++ b/src/types.jl @@ -69,3 +69,40 @@ struct Simulation onset::AbstractOnset noisetype::AbstractNoise end + + +# Eye Movement +abstract type AbstractControlSignal{T} end + +struct HREFCoordinates{T} <: AbstractControlSignal{T} + val::Matrix{T} +end + +struct GazeDirectionVectors{T} <: AbstractControlSignal{T} + val::Matrix{T} +end + + + +# Artifacts + +abstract type AbstractContinuousSignal end + +struct EyeMovement{T} <: AbstractContinuousSignal + controlsignal::T + headmodel + # events # <-- from realdata (or from controlsignal?) or passed in by user. will be added into the events dataframe returned by simulation function +end + +struct TRF <: AbstractContinuousSignal + controlsignal + # TBD +end + +@with_kw struct PowerLineNoise <: AbstractContinuousSignal + controlsignal + base_freq::Float64 = 50 + harmonics::Array{Int} = [1 3 5] + sampling_rate::Float64 = 500 +end + From 9ece1b7bad2f041860ae0565fbc0f9f6aa840341 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Fri, 19 Sep 2025 16:52:06 +0200 Subject: [PATCH 17/32] update a-z simulation & corresponding fixes in other files --- src/AbstractContinuousSignal.jl | 62 ++++++++++++++++----------------- src/simulation.jl | 20 ++++++++--- 2 files changed, 46 insertions(+), 36 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index a3a4ad97..a384b5ec 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -1,33 +1,20 @@ -abstract type AbstractContinuousSignal end - -struct EyeMovement <: AbstractContinuousSignal - controlsignal - headmodel - # events # <-- from realdata (or from controlsignal?) or passed in by user. will be added into the events dataframe returned by simulation function -end - -struct TRF <: AbstractContinuousSignal - controlsignal - # TBD -end - -struct PowerLineNoise <: AbstractContinuousSignal - controlsignal - base_freq::Float64 = 50 - harmonics::Array{Int} = [1 3 5] - sampling_rate::Float64 = 500 -end - """ controlsignal: 2 x n_timepoints Matrix containing x,y angles specifying n gaze direction vectors (measured from center gaze reference) TODO docstring """ -function simulate_continuoussignal(rng::AbstractRNG,s::EyeMovement,controlsignal::HREFCoordinates, headmodel::AbstractHeadmodel, eye_model="crd") - return simulate_eyemovement(headmodel,gazevec_from_angle_3d.(controlsignal[1,:],controlsignal[2,:]); eye_model=eye_model) +# -> also takes the simulation object since it might influence the generated controlsignal +# always take controlsignal only of GazeDirectionVectors +function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsignal::GazeDirectionVectors, sim::Simulation) + headmodel = s.headmodel + return simulate_eyemovement(headmodel,controlsignal.coords; eye_model=s.eye_model) end -function simulate_continuoussignal(rng::AbstractRNG,s::PowerLineNoise,controlsignal::AbstractArray, base_freq::Float64, harmonics::Array{Int} = [1 3 5], sampling_rate::Float64 = 500.0) +function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractArray, sim::Simulation;) + base_freq = s.base_freq + harmonics = s.harmonics + sampling_rate = s.sampling_rate + k = 0:1:size(controlsignal)-1 # assumes controlsignal is just 1D # TODO add check for nyquist criterion? sampling rate & freq -> warn or error? @@ -39,6 +26,11 @@ function simulate_continuoussignal(rng::AbstractRNG,s::PowerLineNoise,controlsig # weight the values at each point, if we need to have different relative strengths of harmonics or if we want to switch on/off the PLN end +# AbstractNoise: doesn't simulate anything, returns empty Array. Since noise simulation will be handled separately in artifact-aware simulate() +function simulate_continuoussignal(rng::AbstractRNG, s::AbstractNoise, controlsignal::AbstractArray, sim::Simulation) + +end + # function simulate_continuoussignal(rng, s::TRF, controlsignal::) # # TBD # end @@ -47,16 +39,24 @@ end # sketching possibilities for generate_controlsignal -function generate_controlsignal(rng::AbstractRNG, c::GazeDirectionVectors) - return c -end +# generate_controlsignal - returns controlsignal for the specified type of AbstractContinuousSignal +# -> also takes the simulation object since it might influence the generated controlsignal (e.g. generate blinks right after event A -> controlsignal depends on the design) + +# for EyeMovement, always return GazeDirectionVectors -function generate_controlsignal(rng::AbstractRNG, c::HREFCoordinates) - return gazevec_from_angle_3d.(c[1,:],c[2,:]) +function generate_controlsignal(rng::AbstractRNG, cs::GazeDirectionVectors, sim::Simulation) + return cs.val end -abstract type AbstractControlSignal end +function generate_controlsignal(rng::AbstractRNG, cs::HREFCoordinates, sim::Simulation) + return gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:]) +end -struct HREFCoordinates <: AbstractControlSignal end +function generate_controlsignal(rng::AbstractRNG, s::EyeMovement, sim::Simulation) + return generate_controlsignal(rng, s.controlsignal, sim) +end -struct GazeDirectionVectors <: AbstractControlSignal end \ No newline at end of file +# AbstractNoise: returns empty Array. Since noise simulation will be handled separately in artifact-aware simulate() +function generate_controlsignal(rng::AbstractRNG, s::AbstractNoise, sim::Simulation) + return [] +end diff --git a/src/simulation.jl b/src/simulation.jl index 8b2f74a9..5af47c74 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -183,12 +183,22 @@ function simulate(rng::AbstractRNG, simulation::Simulation; return_epoched::Bool end -function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::AbstractOnset,s::Vector{Union{AbstractContinuousSignal, AbstractNoise}}) - controlsignal::Matrix = generate_controlsignal(deepcopy(rng),s) # Matrix (feat x time) - signal::Matrix = simulate_continuoussignal(deepcopy(rng),s,controlsignal) # --> contains all the different noise-related signals. ((feat x time?)) - # so here we do the normal simulation and then add the prev result to the result of normal simulation? +"""TODO docstring +s: Vector of AbstractContinuousSignal and/or AbstractNoise +""" +function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::AbstractOnset,s::AbstractVector) + + + sim = Simulation(d, c, o, NoNoise()) # since generated controlsignal might depend on some aspect of the simulation + + println(typeof.(s)) + controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) # Matrix (feat x time) + signal, evts = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)) - # TODO see Ref syntax from pseudocode + # do the normal simulation and then add to the previous result + signal2,evts = simulate(rng,d,c,o,NoNoise()) + # simulate_noise(rng,PinkNoise(3),max(length(signal),length(signal2))) + # return signal .+ signal2,evts # i.e. add the signals eeg & artifact end """ From e0446d8451201632c1acd91f33c36e4c1cc6f7af Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Fri, 19 Sep 2025 22:22:02 +0200 Subject: [PATCH 18/32] PoC simulation just eyemovements, t=1:200 from sample data --- src/AbstractContinuousSignal.jl | 12 +++++++----- src/UnfoldSimArtifacts.jl | 29 ++++++++++++++++------------- src/simulation.jl | 16 ++++++++++------ src/types.jl | 4 ++-- 4 files changed, 35 insertions(+), 26 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index a384b5ec..85c92938 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -4,10 +4,10 @@ controlsignal: TODO docstring """ # -> also takes the simulation object since it might influence the generated controlsignal -# always take controlsignal only of GazeDirectionVectors -function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsignal::GazeDirectionVectors, sim::Simulation) +# always take controlsignal only of Gaze Direction Vectors: Matrix of size 3 x n_timepoints +function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsignal::AbstractMatrix, sim::Simulation) headmodel = s.headmodel - return simulate_eyemovement(headmodel,controlsignal.coords; eye_model=s.eye_model) + return simulate_eyemovement(headmodel,controlsignal) end function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractArray, sim::Simulation;) @@ -28,7 +28,7 @@ end # AbstractNoise: doesn't simulate anything, returns empty Array. Since noise simulation will be handled separately in artifact-aware simulate() function simulate_continuoussignal(rng::AbstractRNG, s::AbstractNoise, controlsignal::AbstractArray, sim::Simulation) - + return [] end # function simulate_continuoussignal(rng, s::TRF, controlsignal::) @@ -45,11 +45,13 @@ end # for EyeMovement, always return GazeDirectionVectors function generate_controlsignal(rng::AbstractRNG, cs::GazeDirectionVectors, sim::Simulation) + @assert size(cs.val)[1] == 3 "Please make sure gaze data has the shape 3 x n_timepoints." return cs.val end function generate_controlsignal(rng::AbstractRNG, cs::HREFCoordinates, sim::Simulation) - return gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:]) + return reduce(hcat,gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:])) # always return a 3 x time_points matrix + end function generate_controlsignal(rng::AbstractRNG, s::EyeMovement, sim::Simulation) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index dd8b0b59..6aa645fb 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -22,7 +22,7 @@ Calculate the gaze vector in 3-D world coordinates, given the horizontal and ver function gazevec_from_angle_3d(angle_H, angle_V) # angles measured from center gaze position => use complementary angle for θ; # ϕ is already measured upwards from the x-y plane, according to the conventions of CoordinateTransformations.jl - return Array{Float32}(CartesianFromSpherical()(Spherical(1, deg2rad(90-angle_H), deg2rad(angle_V)))) + return Vector{Float32}(CartesianFromSpherical()(Spherical(1, deg2rad(90-angle_H), deg2rad(angle_V)))) end @@ -123,7 +123,7 @@ end TODO docstring Single gaze direction. Assumes orientations are already set in eyemodel """ -function generate_eyegaze_eeg(eyemodel, src_idx::Vector{Int}, weights::Vector{Int}) +function generate_eyegaze_eeg(eyemodel, src_idx::AbstractVector, weights::AbstractVector) mag = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) signal = sum(mag[:,idx].* weights[idx] for idx in src_idx) @@ -146,26 +146,31 @@ given a head model, an array of gaze direction vectors defining the eye movement TODO docstring; type for headmodel; always takes in gaze direction vectors as controlsignal """ -function simulate_eyemovement(headmodel, gazevectors::GazeDirectionVectors; eye_model::String="crd") +function simulate_eyemovement(headmodel, gazevectors::AbstractMatrix; eye_model::String="crd") # when gaze direction vector changes, # CRD: orientation changes, weight stays the same (=1 for all points) # Ensemble: orientation stays the same, weight changes (=1 for cornea points, -1 for retina points, calculated based on gaze direction) # leadfields: matrix with dimensions [electrodes x n_gazepoints] - leadfields = zeros(size(headmodel["pos"])[1],length(gazevectors)) + leadfields = zeros(size(headmodel["electrodes"]["pos"])[1],size(gazevectors)[2]) # weights: matrix of dimensions [n_channel x n_gazevec] + println(size(gazevectors)) + if eye_model=="crd" weights = ones(size(headmodel["pos"])[1]) src_idx = [headmodel["eyecenter_left_idx"] headmodel["eyecenter_right_idx"]] - # select eye centers as source points; set orientation = gazevector - for ix in eachindex(gazevectors) - headmodel["orientation"][headmodel["eyecenter_left_idx"]] = gazevectors[ix] - headmodel["orientation"][headmodel["eyecenter_right_idx"]] = gazevectors[ix] + # select eye centers as source points; set orientation = each respective gazevector and find corresponding leadfield + + #TODO: can we make this independent of the headmodel object's orientations, and pass in the corresponding orientations directly to the function instead? + # the problem is that magnitude() will still only work with the model object's orientations. + for ix = 1:size(gazevectors)[2] + headmodel["orientation"][headmodel["eyecenter_left_idx"],:] = gazevectors[:,ix] + headmodel["orientation"][headmodel["eyecenter_right_idx"],:] = gazevectors[:,ix] # or just use src_idx - will help later if we want to simulate just for one eye or so - leadfields[:,ix] = generate_eyegaze_eeg(headmodel, src_idx, weights) + leadfields[:,ix] = generate_eyegaze_eeg(headmodel, vec(src_idx), weights) end elseif eye_model=="ensemble" @@ -258,7 +263,7 @@ function az_simulation() # import href gaze coordinates sample_data = example_data_eyemovements() - href_trajectory = sample_data[1:2,:] + href_trajectory = sample_data[1:2,1:200] # setup basic ingredients for simulate design = SingleSubjectDesign(; conditions = Dict(:cond_A => ["level_A", "level_B"])) |> x -> RepeatDesign(x, 10); @@ -270,11 +275,9 @@ function az_simulation() onset = UniformOnset(; width = 20, offset = 4); noise = PinkNoise(; noiselevel = 0.2); - # call simulate with href coords + # data, events = simulate(MersenneTwister(1), design, signal, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel)]); - println("Calling simulate...") data, events = simulate(MersenneTwister(1), design, signal, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise]); - # simulate(d, c, o, [EyeMovement(href_trajectory, eyemodel) NoNoise()]) # plot simulated data end \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index 5af47c74..c626c4c1 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -187,18 +187,22 @@ end s: Vector of AbstractContinuousSignal and/or AbstractNoise """ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::AbstractOnset,s::AbstractVector) - - + @assert all(x -> x isa AbstractContinuousSignal || x isa AbstractNoise, s) "Artifact-related inputs should all be of type AbstractContinuousSignal or AbstractNoise" sim = Simulation(d, c, o, NoNoise()) # since generated controlsignal might depend on some aspect of the simulation - println(typeof.(s)) - controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) # Matrix (feat x time) - signal, evts = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)) + println("Generating controlsignals...") + controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) # Vector (n_feat) of Matrix (__ x time) + @show size.(controlsignal) + println("Simulating continuous signals...") + signal, evts = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)); # do the normal simulation and then add to the previous result - signal2,evts = simulate(rng,d,c,o,NoNoise()) + println("Simulating EEG with no noise...") + signal2,evts = simulate(rng,d,c,o,NoNoise()); + println("Simulate just noise -->") # simulate_noise(rng,PinkNoise(3),max(length(signal),length(signal2))) # return signal .+ signal2,evts # i.e. add the signals eeg & artifact + return signal, evts end """ diff --git a/src/types.jl b/src/types.jl index 14d05e5c..f7131524 100644 --- a/src/types.jl +++ b/src/types.jl @@ -79,18 +79,18 @@ struct HREFCoordinates{T} <: AbstractControlSignal{T} end struct GazeDirectionVectors{T} <: AbstractControlSignal{T} - val::Matrix{T} + val::Matrix{T} # size 3 x n_timepoints end # Artifacts - abstract type AbstractContinuousSignal end struct EyeMovement{T} <: AbstractContinuousSignal controlsignal::T headmodel + # TODO eye_model? # events # <-- from realdata (or from controlsignal?) or passed in by user. will be added into the events dataframe returned by simulation function end From 62ed12a7586b5166dce34eeac884d2fd7930ad82 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Fri, 19 Sep 2025 22:22:45 +0200 Subject: [PATCH 19/32] add regression test for PoC with previously saved simulation result --- src/simulated_2025-07-17.csv | 228 +++++++++++++++++++++++++++++++++++ test/UnfoldSimArtifacts.jl | 8 ++ 2 files changed, 236 insertions(+) create mode 100644 src/simulated_2025-07-17.csv diff --git a/src/simulated_2025-07-17.csv b/src/simulated_2025-07-17.csv new file mode 100644 index 00000000..d05b7889 --- /dev/null +++ b/src/simulated_2025-07-17.csv @@ -0,0 +1,228 @@ 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diff --git a/test/UnfoldSimArtifacts.jl b/test/UnfoldSimArtifacts.jl index 3096c41a..96311204 100644 --- a/test/UnfoldSimArtifacts.jl +++ b/test/UnfoldSimArtifacts.jl @@ -2,4 +2,12 @@ @test UnfoldSim.gazevec_from_angle_3d(0, 0) ≈ [0; 1; 0] @test UnfoldSim.gazevec_from_angle_3d(0,90) ≈ [0; 0; 1] @test UnfoldSim.gazevec_from_angle_3d(90,0) ≈ [1; 0; 0] +end + +@testset "az_simulation" begin + # test the simulated values of just an eyemovement using the sample data HREF + # compare a previously simulated and saved set of values with the freshly simulated output + leadfields_stepbystep_sim = Matrix(CSV.read("src/simulated_2025-07-17.csv",DataFrame)); + data, events = UnfoldSim.az_simulation(); + @test sum(leadfields[:,1:200] .- data[:,1:200]) == 0.0 end \ No newline at end of file From 4e0faa06370341db7ea807f1ec6279f8b712886f Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 23 Sep 2025 12:05:15 +0200 Subject: [PATCH 20/32] reorder exports --- src/UnfoldSim.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/UnfoldSim.jl b/src/UnfoldSim.jl index 02c4ac72..d2a74c90 100644 --- a/src/UnfoldSim.jl +++ b/src/UnfoldSim.jl @@ -87,4 +87,6 @@ export MultichannelComponent end # artifacts -export simulate_eyemovement, GazeDirectionVectors, HREFCoordinates, AbstractControlSignal, import_eyemodel, AbstractContinuousSignal, EyeMovement \ No newline at end of file +export simulate_eyemovement +export AbstractControlSignal, GazeDirectionVectors, HREFCoordinates +export AbstractContinuousSignal, EyeMovement \ No newline at end of file From e303661b3c728606b3a058448dc27ae1c3a7ab00 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 23 Sep 2025 12:12:03 +0200 Subject: [PATCH 21/32] A-Z change EEG to multichannel; simulate noise; test with multiple EEG+noise inputs --- src/AbstractContinuousSignal.jl | 10 +++++----- src/UnfoldSimArtifacts.jl | 6 +++--- src/simulation.jl | 29 +++++++++++++++++++++-------- test/Project.toml | 1 + 4 files changed, 30 insertions(+), 16 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index 85c92938..4b93fc34 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -27,6 +27,7 @@ function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controls end # AbstractNoise: doesn't simulate anything, returns empty Array. Since noise simulation will be handled separately in artifact-aware simulate() +# TODO: option: select only the AbstractContinuousSignal objects by type when calling simulate_continuoussignal. Then we don't need this method function simulate_continuoussignal(rng::AbstractRNG, s::AbstractNoise, controlsignal::AbstractArray, sim::Simulation) return [] end @@ -51,14 +52,13 @@ end function generate_controlsignal(rng::AbstractRNG, cs::HREFCoordinates, sim::Simulation) return reduce(hcat,gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:])) # always return a 3 x time_points matrix - end -function generate_controlsignal(rng::AbstractRNG, s::EyeMovement, sim::Simulation) - return generate_controlsignal(rng, s.controlsignal, sim) +function generate_controlsignal(rng::AbstractRNG, cs::EyeMovement, sim::Simulation) + return generate_controlsignal(rng, cs.controlsignal, sim) end # AbstractNoise: returns empty Array. Since noise simulation will be handled separately in artifact-aware simulate() -function generate_controlsignal(rng::AbstractRNG, s::AbstractNoise, sim::Simulation) - return [] +function generate_controlsignal(rng::AbstractRNG, cs::AbstractNoise, sim::Simulation) + return zeros(Float64, 0, 0) end diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 6aa645fb..644cac61 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -272,12 +272,12 @@ function az_simulation() formula = @formula(0 ~ 1 + cond_A), β = [1, 0.5], ); + hart = Hartmut(); + mc = UnfoldSim.MultichannelComponent(signal, hart => "Left Postcentral Gyrus"); onset = UniformOnset(; width = 20, offset = 4); noise = PinkNoise(; noiselevel = 0.2); - # data, events = simulate(MersenneTwister(1), design, signal, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel)]); - - data, events = simulate(MersenneTwister(1), design, signal, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise]); + data, events = simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise; RedNoise()]); # plot simulated data end \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index c626c4c1..c67977a1 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -191,18 +191,31 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs sim = Simulation(d, c, o, NoNoise()) # since generated controlsignal might depend on some aspect of the simulation println("Generating controlsignals...") - controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) # Vector (n_feat) of Matrix (__ x time) - @show size.(controlsignal) + controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) # Vector (n_feat) of Matrix (__ x time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact + @show size.(controlsignal) + artifact_lengths = size.(controlsignal,2) + maxtime_artifacts = maximum(artifact_lengths) + padlengths = maxtime_artifacts .- artifact_lengths + println("Simulating continuous signals...") - signal, evts = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)); + artifact_signal, evts = [simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim))]; # do the normal simulation and then add to the previous result println("Simulating EEG with no noise...") - signal2,evts = simulate(rng,d,c,o,NoNoise()); - println("Simulate just noise -->") - # simulate_noise(rng,PinkNoise(3),max(length(signal),length(signal2))) - # return signal .+ signal2,evts # i.e. add the signals eeg & artifact - return signal, evts + eeg_signal,evts = simulate(rng,d,c,o,NoNoise()); + + length_noise = max(maxtime_artifacts,length(eeg_signal)) + #TODO how to handle changing shape of eeg signal for 1D-4D case? specifically how to find the length in the time dimension + # use length of eyemovement only in time dimension. + # PLN will also use the max length in time rather than counting the total number of simulated points across all channels + @show length(artifact_signal),length(eeg_signal), size(artifact_signal) ,size(eeg_signal) + + println("Simulating just noise...") + noise_signal = [simulate_noise(rng,x,max(size(artifact_signal)[2],length(eeg_signal))) for x in s if x isa AbstractNoise] + # for noise simulation, use length(eeg_signal) since we want to generate noise for all channels all timepoints in one go + + # return signal .+ signal2,evts + return artifact_signal, evts, noise_signal, eeg_signal end """ diff --git a/test/Project.toml b/test/Project.toml index e6b8ec6d..1cd244e2 100644 --- a/test/Project.toml +++ b/test/Project.toml @@ -1,4 +1,5 @@ [deps] +CoordinateTransformations = "150eb455-5306-5404-9cee-2592286d6298" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MixedModelsSim = "d5ae56c5-23ca-4a1f-b505-9fc4796fc1fe" From bd44114d8026e9d16992e023c410e25d0b1a4f45 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 23 Sep 2025 13:42:50 +0200 Subject: [PATCH 22/32] remove events from artifact simulation results (temporary, for PoC) --- src/simulation.jl | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/simulation.jl b/src/simulation.jl index c67977a1..404918b3 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -198,7 +198,8 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs padlengths = maxtime_artifacts .- artifact_lengths println("Simulating continuous signals...") - artifact_signal, evts = [simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim))]; + artifact_signal = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)); #TODO handle events: right now for simplicity assume no events are being returned + @show size(artifact_signal), size.(artifact_signal) # do the normal simulation and then add to the previous result println("Simulating EEG with no noise...") @@ -211,7 +212,7 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs @show length(artifact_signal),length(eeg_signal), size(artifact_signal) ,size(eeg_signal) println("Simulating just noise...") - noise_signal = [simulate_noise(rng,x,max(size(artifact_signal)[2],length(eeg_signal))) for x in s if x isa AbstractNoise] + noise_signal = [simulate_noise(rng,x,length(eeg_signal)) for x in s if x isa AbstractNoise] #assumption: length(eeg) will always be more than the artifact length for multichannel simulation. TODO take max. later when addressing single channel eeg sim # for noise simulation, use length(eeg_signal) since we want to generate noise for all channels all timepoints in one go # return signal .+ signal2,evts From 8e96973dc846cf60084adb401a51ff36f21348b5 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Fri, 26 Sep 2025 16:18:39 +0200 Subject: [PATCH 23/32] add eeg, artifact, noise after padding --- src/AbstractContinuousSignal.jl | 8 ++-- src/UnfoldSimArtifacts.jl | 2 +- src/simulation.jl | 65 +++++++++++++++++++++++---------- src/types.jl | 5 +++ 4 files changed, 55 insertions(+), 25 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index 4b93fc34..b25adca8 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -11,6 +11,7 @@ function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsign end function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractArray, sim::Simulation;) + # are different channels of the PLN in phase with each other? base_freq = s.base_freq harmonics = s.harmonics sampling_rate = s.sampling_rate @@ -26,10 +27,9 @@ function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controls # weight the values at each point, if we need to have different relative strengths of harmonics or if we want to switch on/off the PLN end -# AbstractNoise: doesn't simulate anything, returns empty Array. Since noise simulation will be handled separately in artifact-aware simulate() -# TODO: option: select only the AbstractContinuousSignal objects by type when calling simulate_continuoussignal. Then we don't need this method +# AbstractNoise: just returns empty Array - the noise simulation is handled separately in artifact-aware simulate() function simulate_continuoussignal(rng::AbstractRNG, s::AbstractNoise, controlsignal::AbstractArray, sim::Simulation) - return [] + return zeros(Float64, 0, 0) end # function simulate_continuoussignal(rng, s::TRF, controlsignal::) @@ -58,7 +58,7 @@ function generate_controlsignal(rng::AbstractRNG, cs::EyeMovement, sim::Simulati return generate_controlsignal(rng, cs.controlsignal, sim) end -# AbstractNoise: returns empty Array. Since noise simulation will be handled separately in artifact-aware simulate() +# AbstractNoise: returns empty Array for now, however in future the controlsignal for AbstractNoise may depend on the Simulation. function generate_controlsignal(rng::AbstractRNG, cs::AbstractNoise, sim::Simulation) return zeros(Float64, 0, 0) end diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 644cac61..f32ac561 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -263,7 +263,7 @@ function az_simulation() # import href gaze coordinates sample_data = example_data_eyemovements() - href_trajectory = sample_data[1:2,1:200] + href_trajectory = sample_data[1:2,1:20] # setup basic ingredients for simulate design = SingleSubjectDesign(; conditions = Dict(:cond_A => ["level_A", "level_B"])) |> x -> RepeatDesign(x, 10); diff --git a/src/simulation.jl b/src/simulation.jl index 404918b3..971628b3 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -185,38 +185,63 @@ end """TODO docstring s: Vector of AbstractContinuousSignal and/or AbstractNoise +NOTE: +1. It is assumed that `AbstractContinuousSignal.controlsignal` + is defined from the start of the simulation. If you require the artifact to start at + a different time, please take care to pre-pad the controlsignal with zeros. +2. EEG simulation components must be multichannel, and it is assumed that + the number and position of EEG channels are the same as in the artifact head model. """ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::AbstractOnset,s::AbstractVector) @assert all(x -> x isa AbstractContinuousSignal || x isa AbstractNoise, s) "Artifact-related inputs should all be of type AbstractContinuousSignal or AbstractNoise" sim = Simulation(d, c, o, NoNoise()) # since generated controlsignal might depend on some aspect of the simulation + # Current Assumptions: + # events from artifacts - not considered/handled right now + # EEG component is assumed to be multichannel and having the same number and positions of channels as the artifact. + # noise is considered to be independent of EEG/artifacts. + # controlsignals are generated only for AbstractContinuousSignal and not AbstractNoise. + # currently any number of noise components and/or artifacts are allowed. e.g. we can simulate RedNoise as well as PinkNoise and multiple EyeMovements each starting from t=0. + # eeg and artifact signals are simulated separately and then added together, padding to the larger of the two. Then noise is added to this signal. + + + println("Simulating EEG with no noise...") + eeg_signal,evts = simulate(rng,d,c,o,NoNoise()); + @show(size(eeg_signal)) + println("Generating controlsignals...") - controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) # Vector (n_feat) of Matrix (__ x time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact + controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) + # Vector (n_feat) of Matrix (__ x time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact @show size.(controlsignal) - artifact_lengths = size.(controlsignal,2) - maxtime_artifacts = maximum(artifact_lengths) - padlengths = maxtime_artifacts .- artifact_lengths - + println("Simulating continuous signals...") artifact_signal = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)); #TODO handle events: right now for simplicity assume no events are being returned - @show size(artifact_signal), size.(artifact_signal) + + filter!(signal -> size(signal) != (0,0), artifact_signal) # remove the empty arrays (e.g. from AbstractNoise) - # do the normal simulation and then add to the previous result - println("Simulating EEG with no noise...") - eeg_signal,evts = simulate(rng,d,c,o,NoNoise()); + combined_signals = [[eeg_signal] ; artifact_signal] + @info size(combined_signals), size.(combined_signals) - length_noise = max(maxtime_artifacts,length(eeg_signal)) - #TODO how to handle changing shape of eeg signal for 1D-4D case? specifically how to find the length in the time dimension - # use length of eyemovement only in time dimension. - # PLN will also use the max length in time rather than counting the total number of simulated points across all channels - @show length(artifact_signal),length(eeg_signal), size(artifact_signal) ,size(eeg_signal) + row_counts = [size(mat, 1) for mat in combined_signals]; + @show row_counts + if length(unique(row_counts)) > 1 + @warn "Simulated EEG and artifacts do not have the same number of channels: $(row_counts)" + end - println("Simulating just noise...") - noise_signal = [simulate_noise(rng,x,length(eeg_signal)) for x in s if x isa AbstractNoise] #assumption: length(eeg) will always be more than the artifact length for multichannel simulation. TODO take max. later when addressing single channel eeg sim - # for noise simulation, use length(eeg_signal) since we want to generate noise for all channels all timepoints in one go - - # return signal .+ signal2,evts - return artifact_signal, evts, noise_signal, eeg_signal + max_cols = maximum([size(mat, 2) for mat in combined_signals]) + for i in 1:length(combined_signals) + mat = combined_signals[i] + if size(mat, 2) < max_cols + combined_signals[i] = hcat(mat, zeros(size(mat, 1), max_cols - size(mat, 2))) + end + end + + sum_signals = reduce(+, combined_signals) # sum of eeg and artifacts + + println("Adding noise...") + add_noise!.(rng,[x for x in s if x isa AbstractNoise],Ref(sum_signals)) + + return eeg_signal, artifact_signal, combined_signals, sum_signals, evts end """ diff --git a/src/types.jl b/src/types.jl index f7131524..4a0d0d6c 100644 --- a/src/types.jl +++ b/src/types.jl @@ -85,7 +85,12 @@ end # Artifacts +""" +TODO docstring +`controlsignal`: Defines the control signal, always starting from the first time point. +""" abstract type AbstractContinuousSignal end +# in future we may want to allow generating the noise on only a particular channel. struct EyeMovement{T} <: AbstractContinuousSignal controlsignal::T From 9edc2883785580e3261e3b7fab72fd3747e86d4f Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Sun, 28 Sep 2025 17:54:45 +0200 Subject: [PATCH 24/32] update a-z simulation --- src/UnfoldSim.jl | 3 ++- src/UnfoldSimArtifacts.jl | 5 ++--- src/helper.jl | 13 +++++++++---- src/simulation.jl | 4 ++-- 4 files changed, 15 insertions(+), 10 deletions(-) diff --git a/src/UnfoldSim.jl b/src/UnfoldSim.jl index d2a74c90..aff086f2 100644 --- a/src/UnfoldSim.jl +++ b/src/UnfoldSim.jl @@ -89,4 +89,5 @@ end # artifacts export simulate_eyemovement export AbstractControlSignal, GazeDirectionVectors, HREFCoordinates -export AbstractContinuousSignal, EyeMovement \ No newline at end of file +export AbstractContinuousSignal, EyeMovement +export az_simulation \ No newline at end of file diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index f32ac561..58ced791 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -210,7 +210,7 @@ function import_eyemodel(; labels=[ ,"EyeCornea_right" ,"EyeCenter_left" ,"EyeCenter_right" -], modelpath="src/HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat" +], modelpath=joinpath(pkgdir(UnfoldSim),"src/HArtMuT_NYhead_extra_eyemodel_hull_mesh8_2025-03-01.mat") ) eyemodel = read_eyemodel(; p=modelpath) remove_indices = [164, 165, 166, 167] # since eyemodel structure doesn't exactly correspond to the main hartmut mat structure expected by the read_new_hartmut function, just get the indices of the electrodes that it drops & drop the same indices from eyemodel directly @@ -277,7 +277,6 @@ function az_simulation() onset = UniformOnset(; width = 20, offset = 4); noise = PinkNoise(; noiselevel = 0.2); - data, events = simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise; RedNoise()]); + simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise; RedNoise()]); - # plot simulated data end \ No newline at end of file diff --git a/src/helper.jl b/src/helper.jl index 68d625db..19bb8e2d 100755 --- a/src/helper.jl +++ b/src/helper.jl @@ -274,9 +274,14 @@ function epoch(data::AbstractVector, args...; kwargs...) return dropdims(ep; dims = 1) end +""" +Returns example combined EEG-Eyetracking data from a dataset (Gert et al. 2022). +Channels 1,2 are eye tracking values in head-referenced angle coordinates (HREF); channel 3 is the pupil size for that eye. +Channels 4-6 are the same, for the other eye. +The remaining channels contain the corresponding EEG. + +TODO docstring +""" function example_data_eyemovements() - return Matrix(CSV.read("src/sample_eeg_eyemovements.csv",DataFrame)) - # Eye tracking and EEG combined dataset - # channels 1,2 are eye tracking values: HREF angles; 3 is pupil size. - # channels 4-6: same but for other eye + return Matrix(CSV.read(joinpath(pkgdir(UnfoldSim),"src/sample_eeg_eyemovements.csv"),DataFrame)) end \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index 971628b3..9ae680de 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -203,7 +203,7 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs # controlsignals are generated only for AbstractContinuousSignal and not AbstractNoise. # currently any number of noise components and/or artifacts are allowed. e.g. we can simulate RedNoise as well as PinkNoise and multiple EyeMovements each starting from t=0. # eeg and artifact signals are simulated separately and then added together, padding to the larger of the two. Then noise is added to this signal. - + # multiple EyeMovement artifacts are currently allowed. (TODO: check if it makes sense to restrict this. This could be useful if different Eyemovements have different offsets?) println("Simulating EEG with no noise...") eeg_signal,evts = simulate(rng,d,c,o,NoNoise()); @@ -241,7 +241,7 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs println("Adding noise...") add_noise!.(rng,[x for x in s if x isa AbstractNoise],Ref(sum_signals)) - return eeg_signal, artifact_signal, combined_signals, sum_signals, evts + return combined_signals, sum_signals, evts end """ From 00dc199ac543e3fcf0276c801fa46d6a8690fcf9 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Mon, 29 Sep 2025 23:08:59 +0200 Subject: [PATCH 25/32] misc small changes --- src/AbstractContinuousSignal.jl | 3 --- src/UnfoldSimArtifacts.jl | 4 +--- src/helper.jl | 3 +-- 3 files changed, 2 insertions(+), 8 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index b25adca8..756849c9 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -37,9 +37,6 @@ end # end - -# sketching possibilities for generate_controlsignal - # generate_controlsignal - returns controlsignal for the specified type of AbstractContinuousSignal # -> also takes the simulation object since it might influence the generated controlsignal (e.g. generate blinks right after event A -> controlsignal depends on the design) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 58ced791..dec44bc2 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -156,8 +156,6 @@ function simulate_eyemovement(headmodel, gazevectors::AbstractMatrix; eye_model: # weights: matrix of dimensions [n_channel x n_gazevec] - println(size(gazevectors)) - if eye_model=="crd" weights = ones(size(headmodel["pos"])[1]) src_idx = [headmodel["eyecenter_left_idx"] headmodel["eyecenter_right_idx"]] @@ -277,6 +275,6 @@ function az_simulation() onset = UniformOnset(; width = 20, offset = 4); noise = PinkNoise(; noiselevel = 0.2); - simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise; RedNoise()]); + simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise]); end \ No newline at end of file diff --git a/src/helper.jl b/src/helper.jl index 19bb8e2d..1dd64bdd 100755 --- a/src/helper.jl +++ b/src/helper.jl @@ -276,8 +276,7 @@ end """ Returns example combined EEG-Eyetracking data from a dataset (Gert et al. 2022). -Channels 1,2 are eye tracking values in head-referenced angle coordinates (HREF); channel 3 is the pupil size for that eye. -Channels 4-6 are the same, for the other eye. +Channels (rows) 1-7 are eye tracking channels: x/y left, pupil left, x/y right, pupil right, DIN. The remaining channels contain the corresponding EEG. TODO docstring From 0b4fec685ca6d2fc076325363d285c7e9c8633a7 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 30 Sep 2025 02:50:24 +0200 Subject: [PATCH 26/32] add eye_model selection --- src/AbstractContinuousSignal.jl | 3 ++- src/UnfoldSimArtifacts.jl | 12 ++++++------ src/simulation.jl | 5 ++--- src/types.jl | 4 ++-- 4 files changed, 12 insertions(+), 12 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index 756849c9..0400ff62 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -7,7 +7,8 @@ TODO docstring # always take controlsignal only of Gaze Direction Vectors: Matrix of size 3 x n_timepoints function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsignal::AbstractMatrix, sim::Simulation) headmodel = s.headmodel - return simulate_eyemovement(headmodel,controlsignal) + eye_model = s.eye_model + return simulate_eyemovement(headmodel,controlsignal, eye_model) end function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractArray, sim::Simulation;) diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index dec44bc2..f7ce4fa5 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -97,7 +97,7 @@ end Return 1 if the angle between the given orientation vector and the gaze direction vector is less than or equal to the given maximum cornea angle; else return -1. """ -function is_corneapoint(orientation::Vector{Float64}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) +function is_corneapoint(orientation::Vector{Float64}, gazedir::Vector, max_cornea_angle_deg::Float64) if(angle_between(orientation,gazedir)<=max_cornea_angle_deg) return 1 else @@ -138,7 +138,7 @@ given a head model, an array of gaze direction vectors defining the eye movement # Arguments - `headmodel`: Head model to be used. -- `gazevectors::Vector{Vector{Float64}}`: Vector of gaze direction vectors (in Cartesian coordinates) to define the eye movement trajectory. The vector should point from the eyes towards the point at which the gaze is directed. +- `gazevectors`: Gaze direction vectors (in Cartesian coordinates) to define the eye movement trajectory. The vector should point from the eyes towards the gaze target. - `eye_model::String` (optional): Choice of model to use for the eye. Options available are "crd" (default) and "ensemble". # Returns @@ -146,7 +146,7 @@ given a head model, an array of gaze direction vectors defining the eye movement TODO docstring; type for headmodel; always takes in gaze direction vectors as controlsignal """ -function simulate_eyemovement(headmodel, gazevectors::AbstractMatrix; eye_model::String="crd") +function simulate_eyemovement(headmodel, gazevectors::AbstractMatrix, eye_model::String="crd") # when gaze direction vector changes, # CRD: orientation changes, weight stays the same (=1 for all points) # Ensemble: orientation stays the same, weight changes (=1 for cornea points, -1 for retina points, calculated based on gaze direction) @@ -180,9 +180,9 @@ function simulate_eyemovement(headmodel, gazevectors::AbstractMatrix; eye_model: src_idx = [headmodel["eyeleft_idx"]; headmodel["eyeright_idx"]] - for ix in eachindex((gazevectors)) + for ix in 1:size(gazevectors,2) # weight changes depending on retina/cornea type based on current gazevector - weights[src_idx] .= mapslices(x -> is_corneapoint(x,gazedir,max_cornea_angle_deg), headmodel["orientation"][src_idx,:]) + weights[src_idx] .= mapslices(x -> is_corneapoint(x,gazevectors[:,ix],54.0384), headmodel["orientation"][src_idx,:],dims=2) # change the above line to separately calculate weights for left and right eye if giving gazepoints and calculating gaze vectors separately. or just run simulate_eyemovement twice, once with gazevectors based on left eye and once with right eye? leadfields[:,ix] = generate_eyegaze_eeg(headmodel, src_idx, weights) @@ -275,6 +275,6 @@ function az_simulation() onset = UniformOnset(; width = 20, offset = 4); noise = PinkNoise(; noiselevel = 0.2); - simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel); noise]); + simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel, "ensemble"); noise]); end \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index 9ae680de..9570bd72 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -217,13 +217,12 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs println("Simulating continuous signals...") artifact_signal = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)); #TODO handle events: right now for simplicity assume no events are being returned - filter!(signal -> size(signal) != (0,0), artifact_signal) # remove the empty arrays (e.g. from AbstractNoise) + println("Removing empty artifact signals...") + filter!(signal -> size(signal) != (0,0), artifact_signal) # remove the empty arrays (e.g. from AbstractNoise, PowerLineNoise) combined_signals = [[eeg_signal] ; artifact_signal] - @info size(combined_signals), size.(combined_signals) row_counts = [size(mat, 1) for mat in combined_signals]; - @show row_counts if length(unique(row_counts)) > 1 @warn "Simulated EEG and artifacts do not have the same number of channels: $(row_counts)" end diff --git a/src/types.jl b/src/types.jl index 4a0d0d6c..86000bab 100644 --- a/src/types.jl +++ b/src/types.jl @@ -92,10 +92,10 @@ TODO docstring abstract type AbstractContinuousSignal end # in future we may want to allow generating the noise on only a particular channel. -struct EyeMovement{T} <: AbstractContinuousSignal +@with_kw struct EyeMovement{T} <: AbstractContinuousSignal controlsignal::T headmodel - # TODO eye_model? + eye_model::String = "crd" # events # <-- from realdata (or from controlsignal?) or passed in by user. will be added into the events dataframe returned by simulation function end From 38f7a91d95f42b471ddcaec8a39a10226d9d3ba9 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 30 Sep 2025 03:24:11 +0200 Subject: [PATCH 27/32] add basic PLN simulation --- src/AbstractContinuousSignal.jl | 25 ++++++++++++++++++------- src/UnfoldSim.jl | 2 +- src/UnfoldSimArtifacts.jl | 2 +- src/simulation.jl | 24 +++++++++++++----------- src/types.jl | 5 +++-- 5 files changed, 36 insertions(+), 22 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index 0400ff62..ac072796 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -11,21 +11,26 @@ function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsign return simulate_eyemovement(headmodel,controlsignal, eye_model) end +""" +controlsignal: weights to each channel x timepoint? -> user can decide this themselves. +for now as an initial step it can directly be the simulated eeg itself. +#TODO docstring +""" function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractArray, sim::Simulation;) - # are different channels of the PLN in phase with each other? base_freq = s.base_freq harmonics = s.harmonics sampling_rate = s.sampling_rate + weights_harmonics = s.weights_harmonics - k = 0:1:size(controlsignal)-1 # assumes controlsignal is just 1D + n_samples = size(controlsignal,2) + k = 0:1:n_samples-1 # TODO add check for nyquist criterion? sampling rate & freq -> warn or error? - n_samples = sampling_rate*length(controlsignal) + 1 # TODO check if we need the +1 or not depending on UnfoldSim conventions - # TODO generate sinusoids at each harmonic + harmonics_signals = [sin.(2 * pi * (base_freq.*h)/sampling_rate .* k) for h in harmonics].*weights_harmonics + # TODO: use controlsignal as weights for each channel x timepoint? + + return reduce(+,harmonics_signals) - # not sure yet if controlsignal should be multidimensional (e.g. different magnitudes for different channels => n_chan x time) - # or if we just take the simplest case: the same vector will be used for all channels. - # weight the values at each point, if we need to have different relative strengths of harmonics or if we want to switch on/off the PLN end # AbstractNoise: just returns empty Array - the noise simulation is handled separately in artifact-aware simulate() @@ -56,6 +61,12 @@ function generate_controlsignal(rng::AbstractRNG, cs::EyeMovement, sim::Simulati return generate_controlsignal(rng, cs.controlsignal, sim) end +# PowerLineNoise: returns empty Array for now. +# later, maybe weights for each channel x timepoint +function generate_controlsignal(rng::AbstractRNG, cs::PowerLineNoise, sim::Simulation) + return zeros(Float64, 0, 0) +end + # AbstractNoise: returns empty Array for now, however in future the controlsignal for AbstractNoise may depend on the Simulation. function generate_controlsignal(rng::AbstractRNG, cs::AbstractNoise, sim::Simulation) return zeros(Float64, 0, 0) diff --git a/src/UnfoldSim.jl b/src/UnfoldSim.jl index aff086f2..e7d92729 100644 --- a/src/UnfoldSim.jl +++ b/src/UnfoldSim.jl @@ -89,5 +89,5 @@ end # artifacts export simulate_eyemovement export AbstractControlSignal, GazeDirectionVectors, HREFCoordinates -export AbstractContinuousSignal, EyeMovement +export AbstractContinuousSignal, EyeMovement, PowerLineNoise export az_simulation \ No newline at end of file diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index f7ce4fa5..a1a3bebe 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -275,6 +275,6 @@ function az_simulation() onset = UniformOnset(; width = 20, offset = 4); noise = PinkNoise(; noiselevel = 0.2); - simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel, "ensemble"); noise]); + simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel, "ensemble"); noise; PowerLineNoise([0 0; 0 0], 50, [1 3 5], [0.001 0.0005 0], 1000); PowerLineNoise([0 0; 0 0], 60, [1 3 5], [0 0 0], 1000)]); end \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index 9570bd72..007419ce 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -204,29 +204,28 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs # currently any number of noise components and/or artifacts are allowed. e.g. we can simulate RedNoise as well as PinkNoise and multiple EyeMovements each starting from t=0. # eeg and artifact signals are simulated separately and then added together, padding to the larger of the two. Then noise is added to this signal. # multiple EyeMovement artifacts are currently allowed. (TODO: check if it makes sense to restrict this. This could be useful if different Eyemovements have different offsets?) + # PLN simulation assumes that the sampling frequency of the final signal is the same as the sampling frequency of the other signals (eeg/artifacts). TODO: declare this more explicitly in the docstring. println("Simulating EEG with no noise...") eeg_signal,evts = simulate(rng,d,c,o,NoNoise()); - @show(size(eeg_signal)) - println("Generating controlsignals...") - controlsignal = generate_controlsignal.(deepcopy(rng),s,Ref(sim)) - # Vector (n_feat) of Matrix (__ x time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact - @show size.(controlsignal) - - println("Simulating continuous signals...") - artifact_signal = simulate_continuoussignal.(deepcopy(rng),s,controlsignal,Ref(sim)); #TODO handle events: right now for simplicity assume no events are being returned + sim_artifacts = [x for x in s if !(x isa PowerLineNoise)] # ignore PLN for now, it is handled separately since it needs to know the length of the final signal + controlsignal = generate_controlsignal.(deepcopy(rng),sim_artifacts,Ref(sim)) + # Vector (n_feat) of Matrix (__ x time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact + + artifact_signal = simulate_continuoussignal.(deepcopy(rng),sim_artifacts,controlsignal,Ref(sim)); #TODO handle events: right now for simplicity assume no events are being returned println("Removing empty artifact signals...") filter!(signal -> size(signal) != (0,0), artifact_signal) # remove the empty arrays (e.g. from AbstractNoise, PowerLineNoise) combined_signals = [[eeg_signal] ; artifact_signal] - + row_counts = [size(mat, 1) for mat in combined_signals]; if length(unique(row_counts)) > 1 @warn "Simulated EEG and artifacts do not have the same number of channels: $(row_counts)" end + # pad all signals to the same length (max length of all signals) max_cols = maximum([size(mat, 2) for mat in combined_signals]) for i in 1:length(combined_signals) mat = combined_signals[i] @@ -235,12 +234,15 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs end end - sum_signals = reduce(+, combined_signals) # sum of eeg and artifacts + # once all other signals are the same size, pass any one of them to PLN simulation as controlsignal to get the right length + plns = [simulate_continuoussignal(rng,p,combined_signals[1],sim) for p in s if p isa PowerLineNoise] + sum_pln = plns == [] ? zeros(size(combined_signals[1],2)) : reduce(+,plns) + sum_signals = reduce(+, combined_signals) .+ reshape(sum_pln,1,:) println("Adding noise...") add_noise!.(rng,[x for x in s if x isa AbstractNoise],Ref(sum_signals)) - return combined_signals, sum_signals, evts + return combined_signals, sum_signals, sum_pln, evts end """ diff --git a/src/types.jl b/src/types.jl index 86000bab..fa891025 100644 --- a/src/types.jl +++ b/src/types.jl @@ -105,9 +105,10 @@ struct TRF <: AbstractContinuousSignal end @with_kw struct PowerLineNoise <: AbstractContinuousSignal - controlsignal + controlsignal::Matrix{Float64} = zeros(Float64, 0, 0) base_freq::Float64 = 50 harmonics::Array{Int} = [1 3 5] - sampling_rate::Float64 = 500 + weights_harmonics::Array{Float64} = ones(length(harmonics)) + sampling_rate::Float64 = 1000 end From eb71a7e75bc2e70fdbba2bad4cd86360b2e9eb13 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 14 Oct 2025 13:28:24 +0200 Subject: [PATCH 28/32] address PR comments + small changes --- src/UnfoldSim.jl | 3 ++- src/simulation.jl | 4 ++-- src/types.jl | 1 + 3 files changed, 5 insertions(+), 3 deletions(-) diff --git a/src/UnfoldSim.jl b/src/UnfoldSim.jl index e7d92729..add053e2 100644 --- a/src/UnfoldSim.jl +++ b/src/UnfoldSim.jl @@ -90,4 +90,5 @@ end export simulate_eyemovement export AbstractControlSignal, GazeDirectionVectors, HREFCoordinates export AbstractContinuousSignal, EyeMovement, PowerLineNoise -export az_simulation \ No newline at end of file +export az_simulation +export example_data_eyemovements \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index 007419ce..90d507da 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -207,7 +207,7 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs # PLN simulation assumes that the sampling frequency of the final signal is the same as the sampling frequency of the other signals (eeg/artifacts). TODO: declare this more explicitly in the docstring. println("Simulating EEG with no noise...") - eeg_signal,evts = simulate(rng,d,c,o,NoNoise()); + eeg_signal,evts = simulate(deepcopy(rng),sim); sim_artifacts = [x for x in s if !(x isa PowerLineNoise)] # ignore PLN for now, it is handled separately since it needs to know the length of the final signal controlsignal = generate_controlsignal.(deepcopy(rng),sim_artifacts,Ref(sim)) @@ -226,7 +226,7 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs end # pad all signals to the same length (max length of all signals) - max_cols = maximum([size(mat, 2) for mat in combined_signals]) + max_cols = maximum(size.(combined_signals,2)) for i in 1:length(combined_signals) mat = combined_signals[i] if size(mat, 2) < max_cols diff --git a/src/types.jl b/src/types.jl index fa891025..4a612948 100644 --- a/src/types.jl +++ b/src/types.jl @@ -104,6 +104,7 @@ struct TRF <: AbstractContinuousSignal # TBD end +# harmonics are always weighted the same relative to each other @with_kw struct PowerLineNoise <: AbstractContinuousSignal controlsignal::Matrix{Float64} = zeros(Float64, 0, 0) base_freq::Float64 = 50 From b24616dc6b0c654ea6d6ebc09cd880e12677634f Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Sun, 26 Oct 2025 08:36:22 +0100 Subject: [PATCH 29/32] unify flow for pln & noise; intermediate - test deepcopy(rng) broadcast --- src/AbstractContinuousSignal.jl | 79 +++++++++++++++++++++++++-------- src/simulation.jl | 27 +++++------ src/types.jl | 4 +- 3 files changed, 72 insertions(+), 38 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index ac072796..4042b26a 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -6,68 +6,109 @@ TODO docstring # -> also takes the simulation object since it might influence the generated controlsignal # always take controlsignal only of Gaze Direction Vectors: Matrix of size 3 x n_timepoints function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsignal::AbstractMatrix, sim::Simulation) + @show typeof(s), objectid(rng) + println(rand(rng)) headmodel = s.headmodel eye_model = s.eye_model return simulate_eyemovement(headmodel,controlsignal, eye_model) end """ -controlsignal: weights to each channel x timepoint? -> user can decide this themselves. -for now as an initial step it can directly be the simulated eeg itself. +controlsignal: actual weights (channel x time) to be applied to the simulated single-channel PLN + +controlsignal ---> n_channels x n_timepoints #TODO docstring """ -function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractArray, sim::Simulation;) +function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractMatrix, sim::Simulation) + @show typeof(s), objectid(rng) + println(rand(rng)) base_freq = s.base_freq harmonics = s.harmonics sampling_rate = s.sampling_rate weights_harmonics = s.weights_harmonics - n_samples = size(controlsignal,2) + n_samples = size(controlsignal)[end] k = 0:1:n_samples-1 # TODO add check for nyquist criterion? sampling rate & freq -> warn or error? harmonics_signals = [sin.(2 * pi * (base_freq.*h)/sampling_rate .* k) for h in harmonics].*weights_harmonics - # TODO: use controlsignal as weights for each channel x timepoint? - return reduce(+,harmonics_signals) - + # @show typeof(harmonics_signals[1]), size(controlsignal), size(weights_harmonics) + return reduce(+,harmonics_signals)' .*controlsignal end -# AbstractNoise: just returns empty Array - the noise simulation is handled separately in artifact-aware simulate() + function simulate_continuoussignal(rng::AbstractRNG, s::AbstractNoise, controlsignal::AbstractArray, sim::Simulation) - return zeros(Float64, 0, 0) + @show typeof(s), objectid(rng) + println(rand(rng)) + return reshape(simulate_noise(rng,s,length(controlsignal)),size(controlsignal)) .* controlsignal end -# function simulate_continuoussignal(rng, s::TRF, controlsignal::) -# # TBD -# end - # generate_controlsignal - returns controlsignal for the specified type of AbstractContinuousSignal # -> also takes the simulation object since it might influence the generated controlsignal (e.g. generate blinks right after event A -> controlsignal depends on the design) -# for EyeMovement, always return GazeDirectionVectors +# for EyeMovement, always return a matrix containing gaze direction vectors function generate_controlsignal(rng::AbstractRNG, cs::GazeDirectionVectors, sim::Simulation) + @show "gen_cs", typeof(cs), objectid(rng) + println(rand(rng)) @assert size(cs.val)[1] == 3 "Please make sure gaze data has the shape 3 x n_timepoints." return cs.val end function generate_controlsignal(rng::AbstractRNG, cs::HREFCoordinates, sim::Simulation) + @show "gen_cs", typeof(cs), objectid(rng) + println(rand(rng)) return reduce(hcat,gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:])) # always return a 3 x time_points matrix end -function generate_controlsignal(rng::AbstractRNG, cs::EyeMovement, sim::Simulation) - return generate_controlsignal(rng, cs.controlsignal, sim) +function generate_controlsignal(rng::AbstractRNG, cs::AbstractContinuousSignal, sim::Simulation) + @show "gen_cs", typeof(cs), objectid(rng) + println(rand(deepcopy(rng))) + return generate_controlsignal(deepcopy(rng), cs.controlsignal, sim) end + # PowerLineNoise: returns empty Array for now. # later, maybe weights for each channel x timepoint +#function generate_controlsignal(rng::AbstractRNG, cs::PowerLineNoise, sim::Simulation) +# #return cs.controlsignal#zeros(Float64, 0, 0) +# return generate_controlsignal(rng, cs.controlsignal, sim) +#end + function generate_controlsignal(rng::AbstractRNG, cs::PowerLineNoise, sim::Simulation) - return zeros(Float64, 0, 0) + @show "gen_cs", typeof(cs), objectid(rng) + println(rand(rng)) + return nothing end -# AbstractNoise: returns empty Array for now, however in future the controlsignal for AbstractNoise may depend on the Simulation. +# AbstractNoise: returns nothing for now, however in future the controlsignal for AbstractNoise may depend on the Simulation. function generate_controlsignal(rng::AbstractRNG, cs::AbstractNoise, sim::Simulation) - return zeros(Float64, 0, 0) + @show "gen_cs", typeof(cs), objectid(rng) + println(rand(rng)) + return nothing end + +# identity function - in case the user already specified the final controlsignal while creating the artifact +function generate_controlsignal(rng::AbstractRNG, cs::AbstractMatrix, sim::Simulation) + @show "gen_cs", typeof(cs), objectid(rng) + println(rand(rng)) + return cs +end + + +# # for drifts / allowing user to pass in a vector of values for individual channels +# # Dict: channel => weight array +# function generate_controlsignal(rng::AbstractRNG, cs::Dict{Int,Array{Int}}, sim::Simulation) +# # place the given weight arrays together into a common zero matrix at the specified channels. +# # return controlsignal matrix +# end + +# for drifts / allowing user to pass in a function for individual channels +# function generate_controlsignal(rng::AbstractRNG, cs::Dict{Int,function}, sim::Simulation) +# # generate the weight arrays from the function +# # place them into a common zero matrix at the specified channels. +# # return controlsignal matrix +# end + diff --git a/src/simulation.jl b/src/simulation.jl index 90d507da..d7ecf0e1 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -209,20 +209,19 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs println("Simulating EEG with no noise...") eeg_signal,evts = simulate(deepcopy(rng),sim); - sim_artifacts = [x for x in s if !(x isa PowerLineNoise)] # ignore PLN for now, it is handled separately since it needs to know the length of the final signal - controlsignal = generate_controlsignal.(deepcopy(rng),sim_artifacts,Ref(sim)) - # Vector (n_feat) of Matrix (__ x time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact - - artifact_signal = simulate_continuoussignal.(deepcopy(rng),sim_artifacts,controlsignal,Ref(sim)); #TODO handle events: right now for simplicity assume no events are being returned + sim_artifacts = s + controlsignal = generate_controlsignal.(deepcopy.(rng),sim_artifacts,Ref(sim)) # map(x->generate_controlsignal(deepcopy(rng),x,sim),sim_artifacts) + # Vector (n_feat) of Arrays (last dimension time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact - println("Removing empty artifact signals...") - filter!(signal -> size(signal) != (0,0), artifact_signal) # remove the empty arrays (e.g. from AbstractNoise, PowerLineNoise) - + replace!(controlsignal, nothing => ones(size(eeg_signal)[1],max(size(eeg_signal)[end],map(x->size(x)[end],filter(!isnothing,controlsignal))...))) + + artifact_signal = map((x,y)->simulate_continuoussignal(deepcopy(rng),x,y,sim),sim_artifacts,controlsignal); #TODO handle events: right now for simplicity assume no events are being returned + # simulate_continuoussignal.(deepcopy(rng),sim_artifacts,controlsignal, sim) combined_signals = [[eeg_signal] ; artifact_signal] row_counts = [size(mat, 1) for mat in combined_signals]; if length(unique(row_counts)) > 1 - @warn "Simulated EEG and artifacts do not have the same number of channels: $(row_counts)" + error("Simulated EEG and artifacts do not have the same number of channels: $(row_counts)") end # pad all signals to the same length (max length of all signals) @@ -234,15 +233,9 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs end end - # once all other signals are the same size, pass any one of them to PLN simulation as controlsignal to get the right length - plns = [simulate_continuoussignal(rng,p,combined_signals[1],sim) for p in s if p isa PowerLineNoise] - sum_pln = plns == [] ? zeros(size(combined_signals[1],2)) : reduce(+,plns) - sum_signals = reduce(+, combined_signals) .+ reshape(sum_pln,1,:) - - println("Adding noise...") - add_noise!.(rng,[x for x in s if x isa AbstractNoise],Ref(sum_signals)) + sum_signals = reduce(+, combined_signals) - return combined_signals, sum_signals, sum_pln, evts + return combined_signals, sum_signals, evts end """ diff --git a/src/types.jl b/src/types.jl index 4a612948..ee7f1a03 100644 --- a/src/types.jl +++ b/src/types.jl @@ -106,9 +106,9 @@ end # harmonics are always weighted the same relative to each other @with_kw struct PowerLineNoise <: AbstractContinuousSignal - controlsignal::Matrix{Float64} = zeros(Float64, 0, 0) + controlsignal = nothing base_freq::Float64 = 50 - harmonics::Array{Int} = [1 3 5] + harmonics::Array{Int64} = [1 3 5] weights_harmonics::Array{Float64} = ones(length(harmonics)) sampling_rate::Float64 = 1000 end From 1ac745b85b151606f0862b76241560dfb400954c Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 11 Nov 2025 18:38:21 +0100 Subject: [PATCH 30/32] rng testing results --- src/AbstractContinuousSignal.jl | 24 ------------------------ src/UnfoldSimArtifacts.jl | 2 +- src/simulation.jl | 11 ++++++++--- 3 files changed, 9 insertions(+), 28 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index 4042b26a..7aa29ca7 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -20,8 +20,6 @@ controlsignal ---> n_channels x n_timepoints #TODO docstring """ function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractMatrix, sim::Simulation) - @show typeof(s), objectid(rng) - println(rand(rng)) base_freq = s.base_freq harmonics = s.harmonics sampling_rate = s.sampling_rate @@ -39,8 +37,6 @@ end function simulate_continuoussignal(rng::AbstractRNG, s::AbstractNoise, controlsignal::AbstractArray, sim::Simulation) - @show typeof(s), objectid(rng) - println(rand(rng)) return reshape(simulate_noise(rng,s,length(controlsignal)),size(controlsignal)) .* controlsignal end @@ -51,49 +47,29 @@ end # for EyeMovement, always return a matrix containing gaze direction vectors function generate_controlsignal(rng::AbstractRNG, cs::GazeDirectionVectors, sim::Simulation) - @show "gen_cs", typeof(cs), objectid(rng) - println(rand(rng)) @assert size(cs.val)[1] == 3 "Please make sure gaze data has the shape 3 x n_timepoints." return cs.val end function generate_controlsignal(rng::AbstractRNG, cs::HREFCoordinates, sim::Simulation) - @show "gen_cs", typeof(cs), objectid(rng) - println(rand(rng)) return reduce(hcat,gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:])) # always return a 3 x time_points matrix end function generate_controlsignal(rng::AbstractRNG, cs::AbstractContinuousSignal, sim::Simulation) - @show "gen_cs", typeof(cs), objectid(rng) - println(rand(deepcopy(rng))) return generate_controlsignal(deepcopy(rng), cs.controlsignal, sim) end - -# PowerLineNoise: returns empty Array for now. -# later, maybe weights for each channel x timepoint -#function generate_controlsignal(rng::AbstractRNG, cs::PowerLineNoise, sim::Simulation) -# #return cs.controlsignal#zeros(Float64, 0, 0) -# return generate_controlsignal(rng, cs.controlsignal, sim) -#end - function generate_controlsignal(rng::AbstractRNG, cs::PowerLineNoise, sim::Simulation) - @show "gen_cs", typeof(cs), objectid(rng) - println(rand(rng)) return nothing end # AbstractNoise: returns nothing for now, however in future the controlsignal for AbstractNoise may depend on the Simulation. function generate_controlsignal(rng::AbstractRNG, cs::AbstractNoise, sim::Simulation) - @show "gen_cs", typeof(cs), objectid(rng) - println(rand(rng)) return nothing end # identity function - in case the user already specified the final controlsignal while creating the artifact function generate_controlsignal(rng::AbstractRNG, cs::AbstractMatrix, sim::Simulation) - @show "gen_cs", typeof(cs), objectid(rng) - println(rand(rng)) return cs end diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index a1a3bebe..700546d3 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -275,6 +275,6 @@ function az_simulation() onset = UniformOnset(; width = 20, offset = 4); noise = PinkNoise(; noiselevel = 0.2); - simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel, "ensemble"); noise; PowerLineNoise([0 0; 0 0], 50, [1 3 5], [0.001 0.0005 0], 1000); PowerLineNoise([0 0; 0 0], 60, [1 3 5], [0 0 0], 1000)]); + simulate(MersenneTwister(1), design, mc, onset, [EyeMovement(HREFCoordinates(href_trajectory), eyemodel, "ensemble"); noise; PowerLineNoise([0 0; 0 0], 50, [1 3 5], [0.001 0.0005 0], 1000)]); end \ No newline at end of file diff --git a/src/simulation.jl b/src/simulation.jl index d7ecf0e1..05a9a808 100755 --- a/src/simulation.jl +++ b/src/simulation.jl @@ -210,13 +210,18 @@ function simulate(rng::AbstractRNG,d::AbstractDesign,c::AbstractComponent,o::Abs eeg_signal,evts = simulate(deepcopy(rng),sim); sim_artifacts = s - controlsignal = generate_controlsignal.(deepcopy.(rng),sim_artifacts,Ref(sim)) # map(x->generate_controlsignal(deepcopy(rng),x,sim),sim_artifacts) - # Vector (n_feat) of Arrays (last dimension time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact + controlsignal = generate_controlsignal.(deepcopy.(rng),sim_artifacts,Ref(sim)) + # this is a Vector (size same as s) of Arrays (each with last dimension time) -> each kind of artifact could have a different shape of controlsignal, so keep them as elements of the vector rather than combining to a matrix and losing information of which row(s) corresp. to which artifact + # Note on the use of rng: simply using deepcopy(rng) generates the deepcopy just once and reuses the same object for every call to generate_controlsignal. + # This can be tested by checking the objectid and/or generating a random number inside the called function. + # By using deepcopy.(rng) we ensure a new deepcopied object is provided each time. + # Another option: map(x->generate_controlsignal(deepcopy(rng),x,sim),sim_artifacts) + + # generate controlsignal for those AbstractContinuousSignal types that need to know the signal size first replace!(controlsignal, nothing => ones(size(eeg_signal)[1],max(size(eeg_signal)[end],map(x->size(x)[end],filter(!isnothing,controlsignal))...))) artifact_signal = map((x,y)->simulate_continuoussignal(deepcopy(rng),x,y,sim),sim_artifacts,controlsignal); #TODO handle events: right now for simplicity assume no events are being returned - # simulate_continuoussignal.(deepcopy(rng),sim_artifacts,controlsignal, sim) combined_signals = [[eeg_signal] ; artifact_signal] row_counts = [size(mat, 1) for mat in combined_signals]; From 397956babc06e02dd5037e95e271a95880701859 Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Tue, 11 Nov 2025 18:52:04 +0100 Subject: [PATCH 31/32] basic implementation -- drift + userdefined artifact --- src/AbstractContinuousSignal.jl | 39 +++++++++++++++++++++++++++++++++ src/types.jl | 23 +++++++++++++++++++ 2 files changed, 62 insertions(+) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index 7aa29ca7..5244cff6 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -40,6 +40,9 @@ function simulate_continuoussignal(rng::AbstractRNG, s::AbstractNoise, controlsi return reshape(simulate_noise(rng,s,length(controlsignal)),size(controlsignal)) .* controlsignal end +function simulate_continuoussignal(rng::AbstractRNG, s::UserDefinedContinuousSignal, controlsignal::AbstractArray, sim::Simulation) + return s.signal .* controlsignal # the user has already defined what they want +end # generate_controlsignal - returns controlsignal for the specified type of AbstractContinuousSignal # -> also takes the simulation object since it might influence the generated controlsignal (e.g. generate blinks right after event A -> controlsignal depends on the design) @@ -88,3 +91,39 @@ end # # return controlsignal matrix # end + +#--- +function simulate_continuoussignal(rng::AbstractRNG, s::Union{ARDriftNoise,DCDriftNoise,LinearDriftNoise}, controlsignal::AbstractMatrix, sim::Simulation) + # call the singlechannel simulate_continououssignal(..., controlsignal[i,:]) for each row (channel) of controlsignal + return hcat(map(controlsignal_channelwise->simulate_continuoussignal(rng,s,controlsignal_channelwise,sim), eachrow(controlsignal))...)' +end + +function simulate_continuoussignal(rng::AbstractRNG, s::LinearDriftNoise, controlsignal::AbstractVector, sim::Simulation) + # simulate single-channel drift + n_samples = size(controlsignal)[end] + return range(0,1,length=n_samples).* + (rand((rng))*2-1) .* # slope of the line for this particular channel + s.scaling_factor .* # global scaling factor for the entire current LinearDriftNoise + controlsignal # user-controllable weights (current_channel x timepoint) +end + +function simulate_continuoussignal(rng::AbstractRNG, s::ARDriftNoise, controlsignal::AbstractVector, sim::Simulation) + n_samples = size(controlsignal)[end] + return cumsum(s.σ .* randn((rng),n_samples).*controlsignal) +end + +function simulate_continuoussignal(rng::AbstractRNG, s::DCDriftNoise, controlsignal::AbstractVector, sim::Simulation) + n_samples = size(controlsignal)[end] + return ones(n_samples).*rand((rng)).* s.scaling_factor .*controlsignal +end + + +function simulate_continuoussignal(rng::AbstractRNG, s::DriftNoise, controlsignal::AbstractMatrix, sim::Simulation) + fn = fieldnames(DriftNoise) + all_s = [] + for f in fn + push!(all_s,simulate_continuoussignal(rng,getfield(s,f),controlsignal,sim)) + end + + return sum(all_s) +end \ No newline at end of file diff --git a/src/types.jl b/src/types.jl index ee7f1a03..18954600 100644 --- a/src/types.jl +++ b/src/types.jl @@ -113,3 +113,26 @@ end sampling_rate::Float64 = 1000 end +@with_kw struct UserDefinedContinuousSignal <: AbstractContinuousSignal + controlsignal = nothing + signal::Array +end + +@with_kw struct DCDriftNoise <: AbstractContinuousSignal + controlsignal = nothing + scaling_factor = 1 +end +@with_kw struct ARDriftNoise <: AbstractContinuousSignal + controlsignal = nothing + σ +end +@with_kw struct LinearDriftNoise <: AbstractContinuousSignal + controlsignal = nothing + scaling_factor = 1 +end + +@with_kw struct DriftNoise <: AbstractContinuousSignal + ar::ARDriftNoise = ARDriftNoise(σ=1) + linear::LinearDriftNoise = LinearDriftNoise() + dc::DCDriftNoise = DCDriftNoise() +end From 8602eeeb7ace66f50bd4b213d6dedd36b841e4bb Mon Sep 17 00:00:00 2001 From: maanikmarathe <66105649+maanikmarathe@users.noreply.github.com> Date: Wed, 3 Dec 2025 14:28:57 +0100 Subject: [PATCH 32/32] update docs & comments --- src/AbstractContinuousSignal.jl | 49 +++++++++---------------------- src/UnfoldSimArtifacts.jl | 52 +++++++++++++++------------------ src/helper.jl | 2 -- 3 files changed, 37 insertions(+), 66 deletions(-) diff --git a/src/AbstractContinuousSignal.jl b/src/AbstractContinuousSignal.jl index 5244cff6..8311c696 100644 --- a/src/AbstractContinuousSignal.jl +++ b/src/AbstractContinuousSignal.jl @@ -1,23 +1,12 @@ -""" -controlsignal: -2 x n_timepoints Matrix containing x,y angles specifying n gaze direction vectors (measured from center gaze reference) -TODO docstring -""" -# -> also takes the simulation object since it might influence the generated controlsignal -# always take controlsignal only of Gaze Direction Vectors: Matrix of size 3 x n_timepoints function simulate_continuoussignal(rng::AbstractRNG, s::EyeMovement, controlsignal::AbstractMatrix, sim::Simulation) - @show typeof(s), objectid(rng) - println(rand(rng)) + # at the lowest level, eyemovement simulation takes a controlsignal = Matrix having size 3 x n_timepoints i.e. a set of gaze direction vectors headmodel = s.headmodel eye_model = s.eye_model return simulate_eyemovement(headmodel,controlsignal, eye_model) end """ -controlsignal: actual weights (channel x time) to be applied to the simulated single-channel PLN - -controlsignal ---> n_channels x n_timepoints -#TODO docstring +controlsignal: actual weights (n_channels x n_timepoints) to be applied to the simulated single-channel powerline noise """ function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controlsignal::AbstractMatrix, sim::Simulation) base_freq = s.base_freq @@ -27,11 +16,10 @@ function simulate_continuoussignal(rng::AbstractRNG, s::PowerLineNoise, controls n_samples = size(controlsignal)[end] k = 0:1:n_samples-1 - # TODO add check for nyquist criterion? sampling rate & freq -> warn or error? + # TODO add check for nyquist criterion? -> warn or error? harmonics_signals = [sin.(2 * pi * (base_freq.*h)/sampling_rate .* k) for h in harmonics].*weights_harmonics - # @show typeof(harmonics_signals[1]), size(controlsignal), size(weights_harmonics) return reduce(+,harmonics_signals)' .*controlsignal end @@ -44,10 +32,13 @@ function simulate_continuoussignal(rng::AbstractRNG, s::UserDefinedContinuousSig return s.signal .* controlsignal # the user has already defined what they want end -# generate_controlsignal - returns controlsignal for the specified type of AbstractContinuousSignal -# -> also takes the simulation object since it might influence the generated controlsignal (e.g. generate blinks right after event A -> controlsignal depends on the design) -# for EyeMovement, always return a matrix containing gaze direction vectors + +# generate_controlsignal - returns controlsignal for the specified type of AbstractContinuousSignal. +# also takes the simulation object since it might influence the generated controlsignal (e.g. generate blinks right after event A -> controlsignal depends on the design) + + +# for EyeMovement, always return a 3 x n_timepoints matrix containing gaze direction vectors (n_timepoints number of gaze vectors, in 3 dimensions) function generate_controlsignal(rng::AbstractRNG, cs::GazeDirectionVectors, sim::Simulation) @assert size(cs.val)[1] == 3 "Please make sure gaze data has the shape 3 x n_timepoints." @@ -55,13 +46,14 @@ function generate_controlsignal(rng::AbstractRNG, cs::GazeDirectionVectors, sim: end function generate_controlsignal(rng::AbstractRNG, cs::HREFCoordinates, sim::Simulation) - return reduce(hcat,gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:])) # always return a 3 x time_points matrix + return reduce(hcat,gazevec_from_angle_3d.(cs.val[1,:],cs.val[2,:])) end function generate_controlsignal(rng::AbstractRNG, cs::AbstractContinuousSignal, sim::Simulation) return generate_controlsignal(deepcopy(rng), cs.controlsignal, sim) end + # for PowerLineNoise we do not yet know the required n_timepoints, so we postpone controlsignal generation until the eeg and the known-size artifacts have already been generated function generate_controlsignal(rng::AbstractRNG, cs::PowerLineNoise, sim::Simulation) return nothing end @@ -77,22 +69,9 @@ function generate_controlsignal(rng::AbstractRNG, cs::AbstractMatrix, sim::Simul end -# # for drifts / allowing user to pass in a vector of values for individual channels -# # Dict: channel => weight array -# function generate_controlsignal(rng::AbstractRNG, cs::Dict{Int,Array{Int}}, sim::Simulation) -# # place the given weight arrays together into a common zero matrix at the specified channels. -# # return controlsignal matrix -# end -# for drifts / allowing user to pass in a function for individual channels -# function generate_controlsignal(rng::AbstractRNG, cs::Dict{Int,function}, sim::Simulation) -# # generate the weight arrays from the function -# # place them into a common zero matrix at the specified channels. -# # return controlsignal matrix -# end +# simulate_continououssignal - simulates the continuoussignal based on the signal type and the specified controlsignal. - -#--- function simulate_continuoussignal(rng::AbstractRNG, s::Union{ARDriftNoise,DCDriftNoise,LinearDriftNoise}, controlsignal::AbstractMatrix, sim::Simulation) # call the singlechannel simulate_continououssignal(..., controlsignal[i,:]) for each row (channel) of controlsignal return hcat(map(controlsignal_channelwise->simulate_continuoussignal(rng,s,controlsignal_channelwise,sim), eachrow(controlsignal))...)' @@ -104,7 +83,7 @@ function simulate_continuoussignal(rng::AbstractRNG, s::LinearDriftNoise, contro return range(0,1,length=n_samples).* (rand((rng))*2-1) .* # slope of the line for this particular channel s.scaling_factor .* # global scaling factor for the entire current LinearDriftNoise - controlsignal # user-controllable weights (current_channel x timepoint) + controlsignal # user-controllable weights (1 x timepoint : current_channel vector taken from the entire artifact controlsignal) end function simulate_continuoussignal(rng::AbstractRNG, s::ARDriftNoise, controlsignal::AbstractVector, sim::Simulation) @@ -117,7 +96,7 @@ function simulate_continuoussignal(rng::AbstractRNG, s::DCDriftNoise, controlsig return ones(n_samples).*rand((rng)).* s.scaling_factor .*controlsignal end - +# generic drift noise: contains multiple fields having different driftnoise types. Simulate the artifact for each of these. function simulate_continuoussignal(rng::AbstractRNG, s::DriftNoise, controlsignal::AbstractMatrix, sim::Simulation) fn = fieldnames(DriftNoise) all_s = [] diff --git a/src/UnfoldSimArtifacts.jl b/src/UnfoldSimArtifacts.jl index 700546d3..9a4a099e 100644 --- a/src/UnfoldSimArtifacts.jl +++ b/src/UnfoldSimArtifacts.jl @@ -1,13 +1,6 @@ -# For helper function to read in the large model -# using HDF5 -# using DataFrames - -# for angle conversion - need to check if we still need this or if the simple angle conversion util code will suffice -# using CartesianFromSpherical - +# For helper function to read in the large headmodel, we need HDF5 and DataFrames. """ -TODO docstring Construct the gaze vector in 3-D world coordinates, given the gaze angle (in degrees) as measured from the center gaze (looking straight ahead) in the world x-y plane. Z-component is always 0. """ function gazevec_from_angle(angle_deg) @@ -16,12 +9,11 @@ function gazevec_from_angle(angle_deg) end """ -TODO docstring Calculate the gaze vector in 3-D world coordinates, given the horizontal and vertical angles (in degrees) from center gaze direction i.e. looking straight ahead. """ function gazevec_from_angle_3d(angle_H, angle_V) - # angles measured from center gaze position => use complementary angle for θ; - # ϕ is already measured upwards from the x-y plane, according to the conventions of CoordinateTransformations.jl + # since angles are measured from center gaze position => use complementary angle for θ (horizontal direction); + # ϕ (vertical direction) is already measured upwards from the x-y plane, according to the conventions of CoordinateTransformations.jl return Vector{Float32}(CartesianFromSpherical()(Spherical(1, deg2rad(90-angle_H), deg2rad(angle_V)))) end @@ -47,16 +39,14 @@ function read_eyemodel(;p::String = "HArtMuT_NYhead_extra_eyemodel.mat") end """ -TODO docstring - -For each of a given set of labels, find the indices of all the sources in the given model which have that label. +For each of a given set of labels, find the indices of all the sources in the given hartmut model which have that label. Arguments: - `headmodel`: Head model containing the sources in which to search for labels - `labels::Vector{String}`: Labels to search for. Returns: -- `labelsourceindices::Dict`: Dict with the keys being the label and the values being the indices of sources with that label in the given model. +- `labelsourceindices::Dict`: Dict with the keys being the given labels and the values being the corresponding indices of sources with that label in the given model. """ function hart_indices_from_labels(headmodel,labels::AbstractVector=["dummy"]) labelsourceindices = Dict() @@ -68,7 +58,6 @@ end """ -TODO docstring Calculate orientation vectors from the given positions with respect to the reference. The vectors are normalized to have length 1. `direction` is by default "away" from the reference point; set `direction="towards"` to calculate orientations towards the reference point. """ @@ -83,7 +72,6 @@ end """ -TODO docstring Return the angle (in degrees) between two 3-D vectors in Cartesian coordinates. """ function angle_between(a,b) @@ -107,7 +95,17 @@ end """ -TODO docstring +Calculate the leadfield (assuming ensemble model of the eye) for a given gaze direction. + +# Arguments +- `eyemodel`: Head model containing the sources +- `sim_idx::Vector{Int}`: Indices of the sources which should be included in the calculation. +- `gazedir::Vector{Float64}`: Gaze direction vector in 3-D space, pointing from the eye center to the gaze target. +- `max_cornea_angle_deg::Float64`: Angle defining the cone within which a point will be considered as a cornea point based on the gaze direction. + +# Returns +- Ensemble-model leadfield calculated for the given gaze direction, source indices and cornea angle. + """ function ensemble_leadfield(eyemodel, sim_idx::Vector{Int}, gazedir::Vector{Float64}, max_cornea_angle_deg::Float64) mag_model = magnitude(eyemodel["leadfield"],eyemodel["orientation"]) @@ -120,8 +118,8 @@ end """ -TODO docstring -Single gaze direction. Assumes orientations are already set in eyemodel +Calculate the leadfield resulting from activating only the specified source points, weighted according to the given weight vector. +It is assumed that the orientations for the respective source points are already set in the given head model. """ function generate_eyegaze_eeg(eyemodel, src_idx::AbstractVector, weights::AbstractVector) @@ -142,11 +140,9 @@ given a head model, an array of gaze direction vectors defining the eye movement - `eye_model::String` (optional): Choice of model to use for the eye. Options available are "crd" (default) and "ensemble". # Returns -- - -TODO docstring; type for headmodel; always takes in gaze direction vectors as controlsignal +- Matrix of size n_channels x n_gazepoints containing the eyeball-generated leadfield for each time point based on the corresponding gaze direction vectors. """ -function simulate_eyemovement(headmodel, gazevectors::AbstractMatrix, eye_model::String="crd") +function simulate_eyemovement(headmodel, gazevectors::AbstractMatrix, eye_model::String) # when gaze direction vector changes, # CRD: orientation changes, weight stays the same (=1 for all points) # Ensemble: orientation stays the same, weight changes (=1 for cornea points, -1 for retina points, calculated based on gaze direction) @@ -197,7 +193,6 @@ end """ -TODO docstring Read the eye model from a mat file, remove channels Nk1-Nk4, and calculate left/right eye indices, eye centers, orientations and add them to the eyemodel as properties. Return imported model, labelsourceindices of eyemodel """ @@ -241,10 +236,9 @@ function import_eyemodel(; labels=[ end """ -TODO docstring - +Find the approximate current gaze direction from the orientations of cornea-labelled sources. """ -function find_avg_gazedir() +function find_avg_gazedir(eyemodel) # finding cornea centers and approximate gaze direction (as mean of cornea orientations) cornea_center_R = Statistics.mean(eyemodel["pos"][lsi_eyemodel["EyeCornea_right"],:],dims=1) cornea_center_L = Statistics.mean(eyemodel["pos"][lsi_eyemodel["EyeCornea_left"],:],dims=1) @@ -261,7 +255,7 @@ function az_simulation() # import href gaze coordinates sample_data = example_data_eyemovements() - href_trajectory = sample_data[1:2,1:20] + href_trajectory = sample_data[1:2,1:200] # setup basic ingredients for simulate design = SingleSubjectDesign(; conditions = Dict(:cond_A => ["level_A", "level_B"])) |> x -> RepeatDesign(x, 10); diff --git a/src/helper.jl b/src/helper.jl index 1dd64bdd..4a03c44d 100755 --- a/src/helper.jl +++ b/src/helper.jl @@ -278,8 +278,6 @@ end Returns example combined EEG-Eyetracking data from a dataset (Gert et al. 2022). Channels (rows) 1-7 are eye tracking channels: x/y left, pupil left, x/y right, pupil right, DIN. The remaining channels contain the corresponding EEG. - -TODO docstring """ function example_data_eyemovements() return Matrix(CSV.read(joinpath(pkgdir(UnfoldSim),"src/sample_eeg_eyemovements.csv"),DataFrame))

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