Merge pull request #1053 from jonathanfischer97/testdocs

Added docs and assets for interactive simulation plotting tutorial

Author: isaacsas

.github/workflows/Documentation.yml

@@ -15,14 +15,17 @@ jobs:
       - uses: julia-actions/setup-julia@latest
         with:
           version: '1'
+      - name: Install xvfb and OpenGL libraries
+        run: sudo apt-get update && sudo apt-get install -y xorg-dev mesa-utils xvfb libgl1 freeglut3-dev libxrandr-dev libxinerama-dev libxcursor-dev libxi-dev libxext-dev
       - name: Install dependencies
         run: julia --project=docs/ -e 'ENV["JULIA_PKG_SERVER"] = ""; using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
       - name: Build and deploy
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
           DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
           GKSwstype: "100" # https://discourse.julialang.org/t/generation-of-documentation-fails-qt-qpa-xcb-could-not-connect-to-display/60988
-        run: julia --project=docs/ --code-coverage=user docs/make.jl
+        run: |
+          DISPLAY=:0 xvfb-run -s '-screen 0 1024x768x24' julia --project=docs/ --code-coverage=user docs/make.jl
       - uses: julia-actions/julia-processcoverage@v1
       - uses: codecov/codecov-action@v4
         with:

docs/Project.toml

@@ -8,6 +8,7 @@ DiffEqParamEstim = "1130ab10-4a5a-5621-a13d-e4788d82bd4c"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DynamicalSystems = "61744808-ddfa-5f27-97ff-6e42cc95d634"
+GLMakie = "e9467ef8-e4e7-5192-8a1a-b1aee30e663a"
 GlobalSensitivity = "af5da776-676b-467e-8baf-acd8249e4f0f"
 GraphMakie = "1ecd5474-83a3-4783-bb4f-06765db800d2"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"

docs/pages.jl

@@ -33,7 +33,8 @@ pages = Any[
         "model_simulation/ode_simulation_performance.md",
         "model_simulation/sde_simulation_performance.md",
         "Model simulation examples" => Any[
-            "model_simulation/examples/periodic_events_simulation.md"
+            "model_simulation/examples/periodic_events_simulation.md",
+            "model_simulation/examples/interactive_brusselator_simulation.md"
         ]
     ],
     "Steady state analysis" => Any[

docs/src/assets/interactive_brusselator.mp4

@@ -0,0 +1,263 @@
+# [Interactive Simulation and Plotting](@id interactive_brusselator)
+
+Catalyst can utilize the [GLMakie.jl](https://github.com/JuliaPlots/GLMakie.jl) package for creating interactive visualizations of your reaction network dynamics. This tutorial provides a step-by-step guide to creating an interactive visualization of the Brusselator model, building upon the basic [Brusselator](@ref basic_CRN_library_brusselator) example.
+
+
+## [Setting up the Brusselator model](@id setup_brusselator)
+
+Let's again use the oscillating Brusselator model, extending the basic simulation [plotting](@ref simulation_plotting) workflow we saw earlier.
+
+```@example interactive_brusselator; continued = true
+using Catalyst
+using OrdinaryDiffEq
+using GLMakie
+GLMakie.activate!(inline = true, visible = false) # hide
+
+# Define the Brusselator model
+brusselator = @reaction_network begin
+    A, ∅ → X
+    1, 2X + Y → 3X
+    B, X → Y
+    1, X → ∅
+end
+
+# Initial parameter values and conditions
+p = [:A => 1.0, :B => 4.0]
+u0 = [:X => 1.0, :Y => 0.0]
+tspan = (0.0, 50.0)
+
+oprob = ODEProblem(brusselator, u0, tspan, p)
+
+# Function to solve the ODE
+function solve_brusselator(A, B, X0, Y0, prob = oprob)
+    p = [:A => A, :B => B]
+    u0 = [:X => X0, :Y => Y0]
+    newprob = remake(prob, p=p, u0=u0)
+    solve(newprob, Tsit5(), saveat = 0.1) 
+end
+```
+This code sets up our Brusselator model using Catalyst.jl's `@reaction_network` macro. We also define initial parameters, initial conditions, create an `ODEProblem`, and define a function to solve the ODE with given parameters.  Setting `saveat = 0.1` in the call to `solve` ensures the solution is saved with the desired temporal frequency we want for our later plots.
+
+!!! note
+    Be sure to set `saveat` to a value that is appropriate for your system; otherwise, the size of the solution can change during interactivity, which will cause dimension mismatch errors once we add our interactive elements.
+
+## [Basic static plotting](@id basic_static_plotting)
+
+Let's start by creating a basic plot of our Brusselator model:
+
+```@example interactive_brusselator
+# Create the main figure
+fig = Figure(size = (800, 600), fontsize = 18);
+
+# Create an axis for the plot
+ax = Axis(fig[1, 1], 
+    title = "Brusselator Model", 
+    xlabel = "Time", 
+    ylabel = "Concentration")
+
+# Solve the ODE
+sol = solve_brusselator(1.0, 4.0, 1.0, 0.0)
+
+# Plot the solution
+lines!(ax, sol.t, sol[:X], label = "X", color = :blue, linewidth = 3)
+lines!(ax, sol.t, sol[:Y], label = "Y", color = :red, linewidth = 3)
+
+# Add a legend
+axislegend(ax, position = :rt)
+
+# Display the figure
+fig
+```
+
+The plot shows the concentrations of species X and Y over time. Notice the oscillatory behavior characteristic of the Brusselator model.
+
+## [Adding interactivity](@id adding_interactivity)
+
+Now, let's add interactivity to our plot using Observables and sliders. We'll build this up step by step.
+
+### [Creating Observables](@id creating_observables)
+
+Observables are a key concept in reactive programming and are central to how Makie.jl creates interactive visualizations. You can read more about them [here](https://docs.makie.org/stable/explanations/observables).
+
+```@example interactive_brusselator; continued = true
+# Create observables for parameters and initial conditions
+A = Observable(1.0)
+B = Observable(4.0)
+X0 = Observable(1.0)
+Y0 = Observable(0.0)
+```
+
+An Observable is a container for a value that can change over time. When the value changes, any dependent computations are automatically updated.
+
+### [Adding sliders and connecting to Observables](@id adding_sliders)
+
+Let's add [sliders](https://docs.makie.org/stable/reference/blocks/slider) that will control our Observables:
+
+```@example interactive_brusselator; continued = true
+# Create the main figure
+fig = Figure(size = (800, 600), fontsize = 18);
+
+# Create layout for plot and sliders
+plot_layout = fig[1, 1] = GridLayout()
+slider_layout = fig[2, 1] = GridLayout()
+
+# Create sliders
+slider_A = Slider(slider_layout[1, 1], range = 0.0:0.01:5.0, startvalue = to_value(A)) # to_value(A) unwraps the Observable to a value
+slider_B = Slider(slider_layout[2, 1], range = 0.0:0.01:5.0, startvalue = to_value(B))
+slider_X0 = Slider(slider_layout[3, 1], range = 0.0:0.01:5.0, startvalue = to_value(X0))
+slider_Y0 = Slider(slider_layout[4, 1], range = 0.0:0.01:5.0, startvalue = to_value(Y0))
+
+# Add labels for sliders
+Label(slider_layout[1, 1, Left()], "A")
+Label(slider_layout[2, 1, Left()], "B")
+Label(slider_layout[3, 1, Left()], "X₀")
+Label(slider_layout[4, 1, Left()], "Y₀")
+
+# Connect the values of the sliders to the observables
+connect!(A, slider_A.value)
+connect!(B, slider_B.value)
+connect!(X0, slider_X0.value)
+connect!(Y0, slider_Y0.value)
+```
+
+These sliders allow us to interactively change the parameters A and B, as well as the initial conditions X₀ and Y₀.
+
+### [Creating a reactive plot](@id reactive_plot)
+
+Now, let's create a plot that reacts to changes in our sliders:
+
+```@example interactive_brusselator
+# Create an axis for the plot
+ax = Axis(plot_layout[1, 1], 
+    title = "Brusselator Model", 
+    xlabel = "Time", 
+    ylabel = "Concentration")
+
+# Create an observable for the solution
+# The `@lift` macro is used to create an Observable that depends on the observables `A`, `B`, `X0`, and `Y0`, and automatically updates when any of these observables change
+solution = @lift(solve_brusselator($A, $B, $X0, $Y0))
+
+# Plot the solution
+# We don't use the ODESolution plot recipe here, as you've seen in the previous examples where only the solution and an `idxs` argument was passed to the plot method, because we are passing in an Observable wrapping the solution
+lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue, linewidth = 3) # `lift` can either be used as a function or a macro
+lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:Y], solution), label = "Y", color = :red, linewidth = 3)
+
+# Add a legend
+axislegend(ax, position = :rt)
+
+# Display the figure
+fig
+```
+
+This plot will now update in real-time as you move the sliders, allowing for interactive exploration of the Brusselator's behavior under different conditions.
+
+## [Adding a phase plot](@id adding_phase_plot)
+
+To gain more insight into the system's behavior, let's enhance our visualization by adding a phase plot, along with some other improvements:
+
+```@example interactive_brusselator
+# Create the main figure
+fig = Figure(size = (1200, 800), fontsize = 18);
+
+# Create main layout: plots on top, sliders at bottom
+plot_grid = fig[1, 1] = GridLayout()
+slider_grid = fig[2, 1] = GridLayout()
+
+# Create sub-grids for plots
+time_plot = plot_grid[1, 1] = GridLayout()
+phase_plot = plot_grid[1, 2] = GridLayout()
+
+# Create axes for the time series plot and phase plot
+ax_time = Axis(time_plot[1, 1], 
+    title = "Brusselator Model - Time Series", 
+    xlabel = "Time", 
+    ylabel = "Concentration")
+
+ax_phase = Axis(phase_plot[1, 1], 
+    title = "Brusselator Model - Phase Plot", 
+    xlabel = "X", 
+    ylabel = "Y")
+
+# Create sub-grids for sliders
+param_grid = slider_grid[1, 1] = GridLayout()
+ic_grid = slider_grid[1, 2] = GridLayout()
+
+# Create observables for parameters and initial conditions
+A = Observable{Float64}(1.0) # We can specify the type of the Observable value, which can help with type stability and performance
+B = Observable{Float64}(4.0)
+X0 = Observable{Float64}(1.0)
+Y0 = Observable{Float64}(0.0)
+
+# Create sliders with labels and group titles
+Label(param_grid[1, 1:2], "Parameters", fontsize = 22)
+slider_A = Slider(param_grid[2, 2], range = 0.0:0.01:5.0, startvalue = to_value(A))
+slider_B = Slider(param_grid[3, 2], range = 0.0:0.01:5.0, startvalue = to_value(B))
+Label(param_grid[2, 1], "A")
+Label(param_grid[3, 1], "B")
+
+Label(ic_grid[1, 1:2], "Initial Conditions", fontsize = 22)
+slider_X0 = Slider(ic_grid[2, 2], range = 0.0:0.01:5.0, startvalue = to_value(X0))
+slider_Y0 = Slider(ic_grid[3, 2], range = 0.0:0.01:5.0, startvalue = to_value(Y0))
+Label(ic_grid[2, 1], "X₀")
+Label(ic_grid[3, 1], "Y₀")
+
+# Connect sliders to observables
+connect!(A, slider_A.value)
+connect!(B, slider_B.value)
+connect!(X0, slider_X0.value)
+connect!(Y0, slider_Y0.value)
+
+# Create an observable for the solution. 
+solution = @lift(solve_brusselator($A, $B, $X0, $Y0))
+
+# Plot the time series
+lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue, linewidth = 3) 
+lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:Y], solution), label = "Y", color = :red, linewidth = 3)
+
+# Plot the phase plot
+phase_plot_obj = lines!(ax_phase, lift(sol -> sol[:X], solution), lift(sol -> sol[:Y], solution), 
+                        color = lift(sol -> sol.t, solution), colormap = :viridis)
+
+# Add a colorbar for the phase plot
+Colorbar(phase_plot[1, 2], phase_plot_obj, label = "Time")
+
+# Add legends
+axislegend(ax_time, position = :rt)
+
+# Adjust layout to your liking
+colgap!(plot_grid, 20)
+rowgap!(fig.layout, 20)
+colgap!(param_grid, 10)
+colgap!(ic_grid, 10)
+
+# Display the figure
+#fig
+```
+
+This will create a visualization with both time series and phase plots:
+
+![Interactive Brusselator Plot with Time Series and Phase Plot](../../assets/interactive_brusselator.mp4)
+
+## [Common plotting options](@id common_makie_plotting_options)
+
+Various plotting options can be provided as optional arguments to the `lines!` command. Common options include:
+- `linewidth` or `lw`: Determine plot line widths.
+- `linestyle`: Determines plot line style.
+- `color`: Determines the line colors.
+- `label`: Determines label texts displayed in the legend.
+
+For example:
+
+```julia
+lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), 
+       label = "X", color = :green, linewidth = 2, linestyle = :dash)
+```
+
+## [Extending the interactive visualization](@id extending_interactive_visualization)
+
+You can further extend this visualization by:
+- Adding other interactive elements, such as [buttons](https://docs.makie.org/stable/reference/blocks/button) or [dropdown menus](https://docs.makie.org/stable/reference/blocks/menu) to control different aspects of the simulation or visualization.
+- Adding additonal axes to the plot, such as plotting the derivatives of the species.
+- Color coding the slider and slider labels to match the plot colors.
+
+