Create Sankey Diagram

[russelljjarvis]

PlotlyJS has a good sankey, but it tries to take over your whole plotting environment/backend.
Firstly not a registered project, so this line is required

import Pkg; Pkg.add(url="https://github.com/russelljjarvis/SankeyMakie.jl")

[russelljjarvis]

Sankey Network diagrams with cyclic graphs (recursive connections) is only supported by plotly-JS Sankey diagrams.

I think this is a really good way for debugging connectivity issues, as you only want to see the proportions of connectivity between populations of cells, rather than wanting to view all one-to-one connections.

For now the node labels are wrong, but at least the approach seems to produce a useable output. The graph is interactive too, with nice mouse over labels appearing.

Inside the code file test/multilayer_potjans-diesmann2015.jl

    connections = Dict()
    conn_map_pre_density = Dict()
    conn_map_post_density = Dict()

    for i in eachindex(pre_layer_names)
        for j in eachindex(post_layer_names)
            pre = pre_layer_names[i]
            post = post_layer_names[j]
            p = conn_probs[j, i]
            J = conn_j[j, i]
            sym = J>=0 ? :ge : :gi
            μ = abs(J)
            if J>=0      
                s = SNN.SpikingSynapse(neurons[pre], neurons[post], sym; μ = μ, p=p, σ=0, delay_dist=delay_dist_exc)
            else
                s = SNN.SpikingSynapse(neurons[pre], neurons[post], sym; μ = -μ, p=p, σ=0, delay_dist=delay_dist_inh)
            
            end
            keyed = Symbol(string(pre,post))
            if haskey(conn_map_pre_density, keyed)
                conn_map_pre_density[keyed] += length(s.I)
                conn_map_post_density[keyed] += length(s.J)

            else
                conn_map_pre_density[keyed] = length(s.I)  # or set to some default value
                conn_map_post_density[keyed] = length(s.J)

            end
            conn_map_pre_density[Symbol(string(pre,post))] += length(s.I)
            connections[Symbol(string(i,"_",pre,"_",j,"_",post))] = s
        end
    end

function sankey_applied(pre_layer_names,post_layer_names,conn_map_pre_density)
    labels = []
    connections = []
    for i in eachindex(pre_layer_names)
        for j in eachindex(post_layer_names)
            pre = pre_layer_names[i]
            post = post_layer_names[j]
            push!(labels,string(pre))
            push!(connections,(i,j,conn_map_pre_density[Symbol(string(pre,post))]))
        end
    end
    @save "sankey_data.jld" pre_layer_names post_layer_names connections labels
end

In its own seperate file called sankey_only.jl to stop imports from messing with the standard plotting backends of SNN.jl

using PlotlyJS # messes with Plots/Makie backends so compartmentalise by keeping in its own file.
using ElectronDisplay
using JLD2
function sankey_applied()
    @load "sankey_data.jld" pre_layer_names post_layer_names connections labels
    sankey_trace = sankey(
        arrangement = "snap",
        node = attr(
            label    = labels,
            pad      = 15,
            thickness = 20,
            line     = attr(color = "black", width = 0.5)
        ),
        link = attr(
            source = [i[1] for i in connections],
            target = [i[2] for i in connections],
            value  = [i[3] for i in connections]
        )
    )
    plt = plot(sankey_trace)
    ElectronDisplay.display(plt)  # opens a new Electron window
end
sankey_applied()

@aquaresima