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Merge pull request #1115 from vyudu/GraphMakie
GraphMakie update
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‎ext/CatalystGraphMakieExtension.jl

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module CatalystGraphMakieExtension
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# Fetch packages.
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using Catalyst, GraphMakie
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import Catalyst: lattice_plot, lattice_animation, extract_vals
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import Graphs: AbstractGraph, SimpleGraph
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using Catalyst, GraphMakie, Graphs, Symbolics
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using Symbolics: get_variables!
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import Catalyst: species_reaction_graph, incidencematgraph, lattice_plot, lattice_animation
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# Creates and exports hc_steady_states function.
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# Creates and exports graph plotting functions.
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include("CatalystGraphMakieExtension/graph_makie_extension_spatial_modelling.jl")
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include("CatalystGraphMakieExtension/rn_graph_plot.jl")
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end

‎ext/CatalystGraphMakieExtension/rn_graph_plot.jl

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#############
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# Adapted from https://github.com/MakieOrg/GraphMakie.jl/issues/52#issuecomment-1018527479
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#############
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"""
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SRGraphWrap{T}
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Wrapper for the species-reaction graph containing edges for rate-dependence on species. Intended to allow plotting of multiple edges.
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"""
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struct SRGraphWrap{T} <: Graphs.AbstractGraph{T}
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g::SimpleDiGraph{T}
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rateedges::Vector{Graphs.SimpleEdge{T}}
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edgeorder::Vector{Int64}
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end
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# Create the SimpleDiGraph corresponding to the species and reactions
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function SRGraphWrap(rn::ReactionSystem)
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srg = species_reaction_graph(rn)
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rateedges = Vector{Graphs.SimpleEdge{Int}}()
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sm = speciesmap(rn); specs = species(rn)
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deps = Set()
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for (i, rx) in enumerate(reactions(rn))
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empty!(deps)
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get_variables!(deps, rx.rate, specs)
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if !isempty(deps)
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for spec in deps
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specidx = sm[spec]
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push!(rateedges, Graphs.SimpleEdge(specidx, i + length(specs)))
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end
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end
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end
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edgelist = vcat(collect(Graphs.edges(srg)), rateedges)
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edgeorder = sortperm(edgelist)
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SRGraphWrap(srg, rateedges, edgeorder)
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end
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Base.eltype(g::SRGraphWrap) = eltype(g.g)
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Graphs.edgetype(g::SRGraphWrap) = edgetype(g.g)
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Graphs.has_edge(g::SRGraphWrap, s, d) = has_edge(g.g, s, d)
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Graphs.has_vertex(g::SRGraphWrap, i) = has_vertex(g.g, i)
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Graphs.inneighbors(g::SRGraphWrap{T}, i) where T = inneighbors(g.g, i)
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Graphs.outneighbors(g::SRGraphWrap{T}, i) where T = outneighbors(g.g, i)
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Graphs.ne(g::SRGraphWrap) = length(g.rateedges) + length(Graphs.edges(g.g))
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Graphs.nv(g::SRGraphWrap) = nv(g.g)
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Graphs.vertices(g::SRGraphWrap) = vertices(g.g)
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Graphs.is_directed(g::SRGraphWrap) = is_directed(g.g)
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function Graphs.edges(g::SRGraphWrap)
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edgelist = vcat(collect(Graphs.edges(g.g)), g.rateedges)[g.edgeorder]
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end
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function gen_distances(g::SRGraphWrap; inc = 0.2)
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edgelist = edges(g)
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distances = zeros(length(edgelist))
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for i in 2:Base.length(edgelist)
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edgelist[i] == edgelist[i-1] && (distances[i] = inc)
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end
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distances
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end
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"""
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plot_network(rn::ReactionSystem; interactive=false)
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Converts a [`ReactionSystem`](@ref) into a GraphMakie plot of the species reaction graph
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(or Petri net representation). Reactions correspond to small green circles, and
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species to blue circles.
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Notes:
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- Black arrows from species to reactions indicate reactants, and are labelled
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with their input stoichiometry.
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- Black arrows from reactions to species indicate products, and are labelled
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with their output stoichiometry.
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- Red arrows from species to reactions indicate that species is used within the
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rate expression. For example, in the reaction `k*A, B --> C`, there would be a
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red arrow from `A` to the reaction node. In `k*A, A+B --> C`, there would be
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red and black arrows from `A` to the reaction node.
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"""
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# TODO: update docs for interacting with plots. The `interactive` flag sets the ability to interactively drag nodes and edges in the generated plot. Only allowed if `GLMakie` is the loaded Makie backend.
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function Catalyst.plot_network(rn::ReactionSystem)
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srg = SRGraphWrap(rn)
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ns = length(species(rn))
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nodecolors = vcat([:skyblue3 for i in 1:ns],
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[:green for i in ns+1:nv(srg)])
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ilabels = vcat(map(s -> String(tosymbol(s, escape=false)), species(rn)),
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fill("", nv(srg.g) - ns))
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nodesizes = vcat([30 for i in 1:ns],
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[10 for i in ns+1:nv(srg)])
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ssm = substoichmat(rn); psm = prodstoichmat(rn)
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# Get stoichiometry of reaction
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edgelabels = map(Graphs.edges(srg.g)) do e
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string(src(e) > ns ?
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psm[dst(e), src(e)-ns] :
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ssm[src(e), dst(e)-ns])
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end
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edgecolors = [:black for i in 1:ne(srg)]
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num_e = ne(srg.g)
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for i in 1:length(srg.edgeorder)
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if srg.edgeorder[i] > num_e
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edgecolors[i] = :red
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insert!(edgelabels, i, "")
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end
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end
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graphplot(srg;
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edge_color = edgecolors,
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elabels = edgelabels,
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elabels_rotation = 0,
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ilabels = ilabels,
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node_color = nodecolors,
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node_size = nodesizes,
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arrow_shift = :end,
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arrow_size = 20,
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curve_distance_usage = true,
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curve_distance = gen_distances(srg)
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)
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end
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"""
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plot_complexes(rn::ReactionSystem; interactive=false)
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Creates a GraphMakie plot of the [`ReactionComplex`](@ref)s in `rn`. Reactions
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correspond to arrows and reaction complexes to blue circles.
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Notes:
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- Black arrows from complexes to complexes indicate reactions whose rate is a
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parameter or a `Number`. i.e. `k, A --> B`.
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- Red arrows from complexes to complexes indicate reactions whose rate
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depends on species. i.e. `k*C, A --> B` for `C` a species.
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"""
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function Catalyst.plot_complexes(rn::ReactionSystem)
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img = incidencematgraph(rn)
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specs = species(rn); rxs = reactions(rn)
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edgecolors = [:black for i in 1:ne(img)]
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nodelabels = complexlabels(rn)
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edgelabels = [repr(rx.rate) for rx in rxs]
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deps = Set()
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for (i, rx) in enumerate(rxs)
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empty!(deps)
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get_variables!(deps, rx.rate, specs)
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(!isempty(deps)) && (edgecolors[i] = :red)
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end
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graphplot(img;
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edge_color = edgecolors,
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elabels = edgelabels,
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ilabels = complexlabels(rn),
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node_color = :skyblue3,
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elabels_rotation = 0,
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arrow_shift = :end,
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curve_distance = 0.2
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)
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end
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function complexelem_tostr(e::Catalyst.ReactionComplexElement, specstrs)
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if e.speciesstoich == 1
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return "$(specstrs[e.speciesid])"
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else
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return "$(e.speciesstoich)$(specstrs[e.speciesid])"
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end
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end
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# Get the strings corresponding to the reaction complexes
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function complexlabels(rn::ReactionSystem)
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labels = String[]
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specstrs = map(s -> String(tosymbol(s, escape=false)), species(rn))
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complexes, B = reactioncomplexes(rn)
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for complex in complexes
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if isempty(complex)
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push!(labels, "∅")
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elseif length(complex) == 1
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push!(labels, complexelem_tostr(complex[1], specstrs))
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else
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elems = map(c -> complexelem_tostr(c, specstrs), complex)
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str = reduce((e1, e2) -> *(e1, " + ", e2), @view elems[2:end]; init = elems[1])
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push!(labels, str)
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end
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end
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labels
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end

‎src/Catalyst.jl

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function make_si_ode end
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export make_si_ode
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# GraphMakie
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function plot_network end
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function plot_complexes end
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export plot_network, plot_complexes
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### Spatial Reaction Networks ###
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# Spatial reactions.

‎src/network_analysis.jl

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@@ -314,6 +314,44 @@ function incidencematgraph(incidencemat::SparseMatrixCSC{Int, Int})
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return graph
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end
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"""
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species_reaction_graph(rn::ReactionSystem)
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Construct a directed simple graph where there are two types of nodes: species and reactions.
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An edge from a species *s* to reaction *r* indicates that *s* is a reactant for *r*, and
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an edge from a reaction *r* to a species *s* indicates that *s* is a product of *r*. By
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default, the species vertices are listed first, so the first *n* indices correspond to
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species nodes.
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Note: this is equivalent to the Petri net representation of a chemical reaction network.
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For example,
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```julia
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sir = @reaction_network SIR begin
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β, S + I --> 2I
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ν, I --> R
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end
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species_reaction_graph(sir)
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"""
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function species_reaction_graph(rn::ReactionSystem)
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specs = species(rn)
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rxs = reactions(rn)
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sm = speciesmap(rn)
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s = length(specs)
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edgelist = Graphs.Edge[]
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for (i, rx) in enumerate(rxs)
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for spec in rx.substrates
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push!(edgelist, Graphs.Edge(sm[spec], s+i))
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end
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for spec in rx.products
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push!(edgelist, Graphs.Edge(s+i, sm[spec]))
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end
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end
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srg = Graphs.SimpleDiGraphFromIterator(edgelist)
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end
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### Linkage, Deficiency, Reversibility ###
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"""

‎test/extensions/graphmakie.jl

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using Catalyst, GraphMakie, GLMakie, Graphs
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include("../test_networks.jl")
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# Test that speciesreactiongraph is generated correctly
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let
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brusselator = @reaction_network begin
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A, ∅ --> X
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1, 2X + Y --> 3X
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B, X --> Y
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1, X --> ∅
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end
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srg = Catalyst.species_reaction_graph(brusselator)
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s = length(species(brusselator))
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edgel = Graphs.Edge.([(s+1, 1),
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(1, s+2),
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(2, s+2),
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(s+2, 1),
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(s+3, 2),
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(1, s+3),
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(1, s+4)])
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@test all(∈(collect(Graphs.edges(srg))), edgel)
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MAPK = @reaction_network MAPK begin
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(k₁, k₂),KKK + E1 <--> KKKE1
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k₃, KKKE1 --> KKK_ + E1
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(k₄, k₅), KKK_ + E2 <--> KKKE2
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k₆, KKKE2 --> KKK + E2
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(k₇, k₈), KK + KKK_ <--> KK_KKK_
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k₉, KK_KKK_ --> KKP + KKK_
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(k₁₀, k₁₁), KKP + KKK_ <--> KKPKKK_
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k₁₂, KKPKKK_ --> KKPP + KKK_
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(k₁₃, k₁₄), KKP + KKPase <--> KKPKKPase
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k₁₅, KKPPKKPase --> KKP + KKPase
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k₁₆,KKPKKPase --> KK + KKPase
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(k₁₇, k₁₈), KKPP + KKPase <--> KKPPKKPase
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(k₁₉, k₂₀), KKPP + K <--> KKPPK
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k₂₁, KKPPK --> KKPP + KP
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(k₂₂, k₂₃), KKPP + KP <--> KPKKPP
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k₂₄, KPKKPP --> KPP + KKPP
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(k₂₅, k₂₆), KP + KPase <--> KPKPase
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k₂₇, KKPPKPase --> KP + KPase
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k₂₈, KPKPase --> K + KPase
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(k₂₉, k₃₀), KPP + KPase <--> KKPPKPase
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end
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srg = Catalyst.species_reaction_graph(MAPK)
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@test nv(srg) == length(species(MAPK)) + length(reactions(MAPK))
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@test ne(srg) == 90
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# Test that figures are generated properly.
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f = plot_network(MAPK)
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save("fig.png", f)
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@test isfile("fig.png")
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rm("fig.png")
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f = plot_network(brusselator)
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save("fig.png", f)
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@test isfile("fig.png")
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rm("fig.png")
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f = plot_complexes(MAPK); save("fig.png", f)
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@test isfile("fig.png")
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rm("fig.png")
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f = plot_complexes(brusselator); save("fig.png", f)
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@test isfile("fig.png")
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rm("fig.png")
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end
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CGME = Base.get_extension(parentmodule(ReactionSystem), :CatalystGraphMakieExtension)
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# Test that rate edges are inferred correctly. We should see two for the following reaction network.
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let
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# Two rate edges, one to species and one to product
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rn = @reaction_network begin
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k, A --> B
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k * C, A --> C
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k * B, B --> C
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end
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srg = CGME.SRGraphWrap(rn)
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s = length(species(rn))
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@test ne(srg) == 8
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@test Graphs.Edge(3, s+2) ∈ srg.rateedges
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@test Graphs.Edge(2, s+3) ∈ srg.rateedges
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# Since B is both a dep and a reactant
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@test count(==(Graphs.Edge(2, s+3)), edges(srg)) == 2
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f = plot_network(rn)
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save("fig.png", f)
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@test isfile("fig.png")
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rm("fig.png")
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f = plot_complexes(rn); save("fig.png", f)
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@test isfile("fig.png")
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rm("fig.png")
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# Two rate edges, both to reactants
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rn = @reaction_network begin
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k, A --> B
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k * A, A --> C
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k * B, B --> C
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end
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srg = CGME.SRGraphWrap(rn)
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s = length(species(rn))
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@test ne(srg) == 8
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# Since A, B is both a dep and a reactant
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@test count(==(Graphs.Edge(1, s+2)), edges(srg)) == 2
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@test count(==(Graphs.Edge(2, s+3)), edges(srg)) == 2
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end
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