From 36d25ff96b7d296ccd2d61ca1a411f18398720ab Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Thu, 12 Sep 2024 19:03:12 -0400 Subject: [PATCH 01/15] testing my interactive visualizer docs --- ...tive-brusselator-tutorial-markdown-full.md | 273 ++++++++++++++++++ 1 file changed, 273 insertions(+) create mode 100644 docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md diff --git a/docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md b/docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md new file mode 100644 index 0000000000..f8b59f8aac --- /dev/null +++ b/docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md @@ -0,0 +1,273 @@ +# Interactive Visualization of the Brusselator Model + +In this tutorial, we'll create an interactive visualization of the Brusselator model using Catalyst.jl for model definition, OrdinaryDiffEq.jl for solving the ODE system, and GLMakie.jl for interactive plotting. We'll build this visualization step by step, explaining each part along the way. + +## Introduction + +The Brusselator is a theoretical model for a type of autocatalytic reaction. It's a classic example of a system that can exhibit oscillatory behavior and is often used to study dynamical systems. + +[Here you would embed a short video demonstrating the final interactive visualization] + +```julia +# This code block would contain instructions for embedding the video +# For example: +# ```@raw html +# +# ``` +``` + +## Step 1: Setting up the Environment + +First, let's import the necessary packages and define our Brusselator model: + +```julia +using Catalyst +using OrdinaryDiffEq +using GLMakie + +# 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 => 3.0] +u0 = [:X => 1.0, :Y => 1.0] +tspan = (0.0, 50.0) + +oprob = ODEProblem(brusselator, u0, tspan, p) +``` + +This code sets up our Brusselator model using Catalyst.jl's `@reaction_network` macro. We also define initial parameters, initial conditions, and create an `ODEProblem`. + +## Step 2: Creating a Basic Plot + +Let's start by creating a basic plot of our Brusselator model: + +```julia +# 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(oprob, Tsit5()) + +# Plot the solution +lines!(ax, sol.t, sol[:X], label = "X", color = :blue) +lines!(ax, sol.t, sol[:Y], label = "Y", color = :red) + +# Add a legend +axislegend(ax, position = :rt) + +# Display the figure +display(fig) +``` + +This will produce a basic time series plot of the Brusselator model: + +[Insert image of basic plot here] + +## Step 3: Adding Interactivity with Observables + +Now, let's add interactivity to our plot. We'll do this step-by-step, explaining each addition as we go. + +### 3.1 Setting up the layout + +First, we'll set up a layout that includes space for our plot and for sliders: + +```julia +# 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 an axis for the plot +ax = Axis(plot_layout[1, 1], + title = "Brusselator Model", + xlabel = "Time", + ylabel = "Concentration") +``` + +This code creates a figure with two main areas: one for our plot and one for our soon-to-be-added sliders. + +### 3.2 Creating Observables + +Next, we'll create Observables for our parameters and initial conditions. Observables are a key concept in reactive programming and are central to how Makie.jl creates interactive visualizations. + +```julia +# Create observables for parameters and initial conditions +A = Observable(1.0) +B = Observable(3.0) +X0 = Observable(1.0) +Y0 = Observable(1.0) +``` + +An Observable is a container for a value that can change over time. When the value changes, any dependent computations are automatically updated. + +### 3.3 Adding Sliders + +Now, let's add sliders that will control our Observables: + +```julia +# Create sliders +slider_A = Slider(slider_layout[1, 1], range = 0.1:0.1:5.0, startvalue = 1.0) +slider_B = Slider(slider_layout[2, 1], range = 0.1:0.1:5.0, startvalue = 3.0) +slider_X0 = Slider(slider_layout[3, 1], range = 0.1:0.1:5.0, startvalue = 1.0) +slider_Y0 = Slider(slider_layout[4, 1], range = 0.1:0.1:5.0, startvalue = 1.0) + +# 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") +``` + +These sliders will allow us to interactively change the values of our parameters and initial conditions. + +### 3.4 Connecting Sliders to Observables + +To make our sliders actually control the Observables, we need to connect them: + +```julia +# Connect sliders to observables +connect!(A, slider_A.value) +connect!(B, slider_B.value) +connect!(X0, slider_X0.value) +connect!(Y0, slider_Y0.value) +``` + +Now, when a slider is moved, it will update its corresponding Observable. + +### 3.5 Creating a Reactive Solution + +We want our ODE solution to update whenever our parameters or initial conditions change. We can do this by creating a function that solves the ODE and an Observable that depends on our parameter Observables: + +```julia +# Function to solve the ODE +function solve_brusselator(A, B, X0, Y0) + p = [:A => A, :B => B] + u0 = [:X => X0, :Y => Y0] + prob = remake(oprob, p=p, u0=u0) + solve(prob, Tsit5()) +end + +# Create an observable for the solution +solution = @lift(solve_brusselator($A, $B, $X0, $Y0)) +``` + +The `@lift` macro creates a new Observable that depends on other Observables. Whenever A, B, X0, or Y0 change, `solution` will automatically update. + +### 3.6 Plotting the Reactive Solution + +Finally, we can plot our reactive solution: + +```julia +# Plot the solution +lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue) +lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:Y], solution), label = "Y", color = :red) + +# Add a legend +axislegend(ax, position = :rt) + +# Display the figure +display(fig) +``` + +Here, we use `lift` again to create Observables for our plot data that depend on the `solution` Observable. This means our plot will automatically update whenever the solution changes. + +The resulting figure should look like this: + +[Insert image of interactive plot with sliders here] + +### Understanding the Reactivity + +When a slider is moved, it triggers a chain reaction: +1. The slider updates its corresponding Observable (A, B, X0, or Y0). +2. This causes the `solution` Observable to recompute. +3. The lifted Observables for plotting update because `solution` changed. +4. The plot automatically updates to reflect these changes. + +This reactive approach allows for smooth, efficient updates to our visualization as parameters change. You can now interact with the sliders and see the Brusselator model's behavior change in real-time! + +## Step 4: Adding a Phase Plot + +Let's enhance our visualization by adding a phase plot: + +```julia +# 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") + +# ... [previous code for sliders and observables] ... + +# Plot the time series +lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue) +lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:Y], solution), label = "Y", color = :red) + +# 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) + +# Display the figure +display(fig) +``` + +This will create a visualization with both time series and phase plots: + +[Insert image of plot with time series and phase plot here] + +## Conclusion + +In this tutorial, we've created an interactive visualization of the Brusselator model using Catalyst.jl, OrdinaryDiffEq.jl, and GLMakie.jl. We've learned how to: + +1. Define a reaction network using Catalyst.jl +2. Solve the resulting ODE system using OrdinaryDiffEq.jl +3. Create interactive plots with GLMakie.jl +4. Use Observables to create reactive, interactive visualizations +5. Add multiple plot types to enhance understanding of system dynamics + +This interactive visualization allows for easy exploration of the Brusselator model's behavior under different conditions, making it a powerful tool for understanding complex dynamical systems. + +For further exploration, you could: +- Add more parameters to interact with +- Implement different ODE solvers and compare their performance +- Add additional plot types or analyses +- Extend this approach to other reaction networks + +Remember, the power of this approach lies in its interactivity. Experiment with different parameter values and initial conditions to gain insights into the Brusselator's behavior! From bf4150e43cd05677d9e3c18b4b13cd920c578142 Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Thu, 12 Sep 2024 22:46:39 -0400 Subject: [PATCH 02/15] added interactive brusselator doc --- docs/pages.jl | 1 + docs/src/assets/brusselator_basic_plot.svg | 300 ++ .../assets/brusselator_interactive_plot.svg | 350 ++ .../brusselator_interactive_plot_full.svg | 3421 +++++++++++++++++ ...tive-brusselator-tutorial-markdown-full.md | 273 -- .../interactive_brusselator_simulation.md | 292 ++ 6 files changed, 4364 insertions(+), 273 deletions(-) create mode 100644 docs/src/assets/brusselator_basic_plot.svg create mode 100644 docs/src/assets/brusselator_interactive_plot.svg create mode 100644 docs/src/assets/brusselator_interactive_plot_full.svg delete mode 100644 docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md create mode 100644 docs/src/model_simulation/interactive_brusselator_simulation.md diff --git a/docs/pages.jl b/docs/pages.jl index 7f6181a11d..dc255e9365 100644 --- a/docs/pages.jl +++ b/docs/pages.jl @@ -28,6 +28,7 @@ pages = Any[ "Model simulation" => Any[ "model_simulation/simulation_introduction.md", "model_simulation/simulation_plotting.md", + "model_simulation/interactive_brusselator_simulation.md", "model_simulation/simulation_structure_interfacing.md", "model_simulation/ensemble_simulations.md", "model_simulation/ode_simulation_performance.md", diff --git a/docs/src/assets/brusselator_basic_plot.svg b/docs/src/assets/brusselator_basic_plot.svg new file mode 100644 index 0000000000..07fb20ca2d --- /dev/null +++ b/docs/src/assets/brusselator_basic_plot.svg @@ -0,0 +1,300 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md b/docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md deleted file mode 100644 index f8b59f8aac..0000000000 --- a/docs/src/model_simulation/interactive-brusselator-tutorial-markdown-full.md +++ /dev/null @@ -1,273 +0,0 @@ -# Interactive Visualization of the Brusselator Model - -In this tutorial, we'll create an interactive visualization of the Brusselator model using Catalyst.jl for model definition, OrdinaryDiffEq.jl for solving the ODE system, and GLMakie.jl for interactive plotting. We'll build this visualization step by step, explaining each part along the way. - -## Introduction - -The Brusselator is a theoretical model for a type of autocatalytic reaction. It's a classic example of a system that can exhibit oscillatory behavior and is often used to study dynamical systems. - -[Here you would embed a short video demonstrating the final interactive visualization] - -```julia -# This code block would contain instructions for embedding the video -# For example: -# ```@raw html -# -# ``` -``` - -## Step 1: Setting up the Environment - -First, let's import the necessary packages and define our Brusselator model: - -```julia -using Catalyst -using OrdinaryDiffEq -using GLMakie - -# 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 => 3.0] -u0 = [:X => 1.0, :Y => 1.0] -tspan = (0.0, 50.0) - -oprob = ODEProblem(brusselator, u0, tspan, p) -``` - -This code sets up our Brusselator model using Catalyst.jl's `@reaction_network` macro. We also define initial parameters, initial conditions, and create an `ODEProblem`. - -## Step 2: Creating a Basic Plot - -Let's start by creating a basic plot of our Brusselator model: - -```julia -# 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(oprob, Tsit5()) - -# Plot the solution -lines!(ax, sol.t, sol[:X], label = "X", color = :blue) -lines!(ax, sol.t, sol[:Y], label = "Y", color = :red) - -# Add a legend -axislegend(ax, position = :rt) - -# Display the figure -display(fig) -``` - -This will produce a basic time series plot of the Brusselator model: - -[Insert image of basic plot here] - -## Step 3: Adding Interactivity with Observables - -Now, let's add interactivity to our plot. We'll do this step-by-step, explaining each addition as we go. - -### 3.1 Setting up the layout - -First, we'll set up a layout that includes space for our plot and for sliders: - -```julia -# 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 an axis for the plot -ax = Axis(plot_layout[1, 1], - title = "Brusselator Model", - xlabel = "Time", - ylabel = "Concentration") -``` - -This code creates a figure with two main areas: one for our plot and one for our soon-to-be-added sliders. - -### 3.2 Creating Observables - -Next, we'll create Observables for our parameters and initial conditions. Observables are a key concept in reactive programming and are central to how Makie.jl creates interactive visualizations. - -```julia -# Create observables for parameters and initial conditions -A = Observable(1.0) -B = Observable(3.0) -X0 = Observable(1.0) -Y0 = Observable(1.0) -``` - -An Observable is a container for a value that can change over time. When the value changes, any dependent computations are automatically updated. - -### 3.3 Adding Sliders - -Now, let's add sliders that will control our Observables: - -```julia -# Create sliders -slider_A = Slider(slider_layout[1, 1], range = 0.1:0.1:5.0, startvalue = 1.0) -slider_B = Slider(slider_layout[2, 1], range = 0.1:0.1:5.0, startvalue = 3.0) -slider_X0 = Slider(slider_layout[3, 1], range = 0.1:0.1:5.0, startvalue = 1.0) -slider_Y0 = Slider(slider_layout[4, 1], range = 0.1:0.1:5.0, startvalue = 1.0) - -# 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") -``` - -These sliders will allow us to interactively change the values of our parameters and initial conditions. - -### 3.4 Connecting Sliders to Observables - -To make our sliders actually control the Observables, we need to connect them: - -```julia -# Connect sliders to observables -connect!(A, slider_A.value) -connect!(B, slider_B.value) -connect!(X0, slider_X0.value) -connect!(Y0, slider_Y0.value) -``` - -Now, when a slider is moved, it will update its corresponding Observable. - -### 3.5 Creating a Reactive Solution - -We want our ODE solution to update whenever our parameters or initial conditions change. We can do this by creating a function that solves the ODE and an Observable that depends on our parameter Observables: - -```julia -# Function to solve the ODE -function solve_brusselator(A, B, X0, Y0) - p = [:A => A, :B => B] - u0 = [:X => X0, :Y => Y0] - prob = remake(oprob, p=p, u0=u0) - solve(prob, Tsit5()) -end - -# Create an observable for the solution -solution = @lift(solve_brusselator($A, $B, $X0, $Y0)) -``` - -The `@lift` macro creates a new Observable that depends on other Observables. Whenever A, B, X0, or Y0 change, `solution` will automatically update. - -### 3.6 Plotting the Reactive Solution - -Finally, we can plot our reactive solution: - -```julia -# Plot the solution -lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue) -lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:Y], solution), label = "Y", color = :red) - -# Add a legend -axislegend(ax, position = :rt) - -# Display the figure -display(fig) -``` - -Here, we use `lift` again to create Observables for our plot data that depend on the `solution` Observable. This means our plot will automatically update whenever the solution changes. - -The resulting figure should look like this: - -[Insert image of interactive plot with sliders here] - -### Understanding the Reactivity - -When a slider is moved, it triggers a chain reaction: -1. The slider updates its corresponding Observable (A, B, X0, or Y0). -2. This causes the `solution` Observable to recompute. -3. The lifted Observables for plotting update because `solution` changed. -4. The plot automatically updates to reflect these changes. - -This reactive approach allows for smooth, efficient updates to our visualization as parameters change. You can now interact with the sliders and see the Brusselator model's behavior change in real-time! - -## Step 4: Adding a Phase Plot - -Let's enhance our visualization by adding a phase plot: - -```julia -# 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") - -# ... [previous code for sliders and observables] ... - -# Plot the time series -lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue) -lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:Y], solution), label = "Y", color = :red) - -# 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) - -# Display the figure -display(fig) -``` - -This will create a visualization with both time series and phase plots: - -[Insert image of plot with time series and phase plot here] - -## Conclusion - -In this tutorial, we've created an interactive visualization of the Brusselator model using Catalyst.jl, OrdinaryDiffEq.jl, and GLMakie.jl. We've learned how to: - -1. Define a reaction network using Catalyst.jl -2. Solve the resulting ODE system using OrdinaryDiffEq.jl -3. Create interactive plots with GLMakie.jl -4. Use Observables to create reactive, interactive visualizations -5. Add multiple plot types to enhance understanding of system dynamics - -This interactive visualization allows for easy exploration of the Brusselator model's behavior under different conditions, making it a powerful tool for understanding complex dynamical systems. - -For further exploration, you could: -- Add more parameters to interact with -- Implement different ODE solvers and compare their performance -- Add additional plot types or analyses -- Extend this approach to other reaction networks - -Remember, the power of this approach lies in its interactivity. Experiment with different parameter values and initial conditions to gain insights into the Brusselator's behavior! diff --git a/docs/src/model_simulation/interactive_brusselator_simulation.md b/docs/src/model_simulation/interactive_brusselator_simulation.md new file mode 100644 index 0000000000..c0d873d26d --- /dev/null +++ b/docs/src/model_simulation/interactive_brusselator_simulation.md @@ -0,0 +1,292 @@ +# [Interactive Visualization of the Brusselator Model](@id interactive_brusselator) + +```@contents +Pages = ["interactive_brusselator.md"] +Depth = 3 +``` + +Catalyst can utilize the [GLMakie.jl](https://github.com/JuliaPlots/GLMakie.jl) package for creating interactive visualizations. 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. + +!!! note + This tutorial assumes you have GLMakie.jl installed. If not, you can install it by running `using Pkg; Pkg.add("GLMakie")` in your Julia REPL. + +## [Background: The Brusselator Model](@id brusselator_background) + +The Brusselator is a theoretical model for autocatalytic reactions, proposed by Ilya Prigogine and his collaborators. It is described by the following set of differential equations: + +```math +\begin{aligned} +\frac{dX}{dt} &= A + X^2Y - BX - X \\ +\frac{dY}{dt} &= BX - X^2Y +\end{aligned} +``` + +Where X and Y are chemical species, and A and B are parameters. This system can exhibit oscillatory behavior for certain parameter values, making it an interesting subject for study in nonlinear dynamics and chemical kinetics. + +## [Setting up the Brusselator model](@id setup_brusselator) + +First, let's import the necessary packages and define our Brusselator model: + +```julia +using Catalyst +using OrdinaryDiffEq +using GLMakie + +# 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 => 3.0] +u0 = [:X => 1.0, :Y => 1.0] +tspan = (0.0, 50.0) + +oprob = ODEProblem(brusselator, u0, tspan, p) + +# Function to solve the ODE +function solve_brusselator(A, B, X0, Y0) + p = [:A => A, :B => B] + u0 = [:X => X0, :Y => Y0] + prob = remake(oprob, p=p, u0=u0) + solve(prob, 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. + +## [Basic static plotting](@id basic_static_plotting) + +Let's start by creating a basic plot of our Brusselator model: + +```julia +# 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, 3.0, 1.0, 1.0) + +# 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 +display(fig) +``` + +This will produce a basic time series plot of the Brusselator model: + +![Basic Brusselator Plot](../assets/brusselator_basic_plot.svg) + +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. + +```julia +# Create observables for parameters and initial conditions +A = Observable(1.0) +B = Observable(3.0) +X0 = Observable(1.0) +Y0 = Observable(1.0) +``` + +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 that will control our Observables: + +```julia +# 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 = 0.1:0.1:5.0, startvalue = 1.0) +slider_B = Slider(slider_layout[2, 1], range = 0.1:0.1:5.0, startvalue = 3.0) +slider_X0 = Slider(slider_layout[3, 1], range = 0.1:0.1:5.0, startvalue = 1.0) +slider_Y0 = Slider(slider_layout[4, 1], range = 0.1:0.1:5.0, startvalue = 1.0) + +# 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 sliders to 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: + +```julia +# 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 +solution = @lift(solve_brusselator($A, $B, $X0, $Y0)) + +# Plot the solution +lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue, linewidth = 3) +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 +display(fig) +``` + +The resulting figure should look like this: + +![Interactive Brusselator Plot](../assets/brusselator_interactive_plot.svg) + +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. + +## [Enhanced visualization with 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: + +```julia +# 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 sliders with labels and group titles +Label(param_grid[1, 1:2], "Parameters", fontsize = 22) +slider_A = Slider(param_grid[2, 2], range = 0.1:0.1:5.0, startvalue = 1.0) +slider_B = Slider(param_grid[3, 2], range = 0.1:0.1:5.0, startvalue = 3.0) +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 = 0.1:0.1:5.0, startvalue = 1.0) +slider_Y0 = Slider(ic_grid[3, 2], range = 0.1:0.1:5.0, startvalue = 1.0) +Label(ic_grid[2, 1], "X₀") +Label(ic_grid[3, 1], "Y₀") + +# Connect sliders to observables +A = Observable(1.0) +B = Observable(3.0) +X0 = Observable(1.0) +Y0 = Observable(1.0) +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 +colgap!(plot_grid, 20) +rowgap!(fig.layout, 20) +colgap!(param_grid, 10) +colgap!(ic_grid, 10) + +# Display the figure +display(fig) +``` + +This will create a visualization with both time series and phase plots: + +![Interactive Brusselator Plot with Time Series and Phase Plot](../assets/brusselator_interactive_plot_full.svg) + + +## [Performance considerations](@id interactive_performance_considerations) + +When working with interactive visualizations, especially for more complex models, performance can become an issue. Here are some tips to improve performance: + +1. Use appropriate ODE solvers. For stiff systems, consider using `Rodas4()` instead of `Tsit5()`. +2. Adjust the `saveat` parameter in the `solve` function to reduce the number of points plotted. +3. For very large systems, consider using `GLMakie.jl` instead of `Makie.jl` for better performance. + +## [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 colours. +- `label`: Determines label texts. + +For example: + +```julia +lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), + label = "X", color = :blue, 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 or dropdowns to control different aspects of the simulation or visualization. +- Adding additonal axes to the plot. + + From 22f253f5b1ba4692bc89c8c6fddff6d889fe4225 Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Fri, 13 Sep 2024 18:39:48 -0400 Subject: [PATCH 03/15] Added mp4 demo --- docs/pages.jl | 4 +- docs/src/assets/interactive_brusselator.mp4 | Bin 0 -> 1660956 bytes .../interactive_brusselator_simulation.md | 119 ++++++++---------- 3 files changed, 52 insertions(+), 71 deletions(-) create mode 100644 docs/src/assets/interactive_brusselator.mp4 rename docs/src/model_simulation/{ => examples}/interactive_brusselator_simulation.md (62%) diff --git a/docs/pages.jl b/docs/pages.jl index dc255e9365..e03bd16f1f 100644 --- a/docs/pages.jl +++ b/docs/pages.jl @@ -28,13 +28,13 @@ pages = Any[ "Model simulation" => Any[ "model_simulation/simulation_introduction.md", "model_simulation/simulation_plotting.md", - "model_simulation/interactive_brusselator_simulation.md", "model_simulation/simulation_structure_interfacing.md", "model_simulation/ensemble_simulations.md", "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[ diff --git a/docs/src/assets/interactive_brusselator.mp4 b/docs/src/assets/interactive_brusselator.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..72130c2221f947a9bc3668ea28d51c7d26925734 GIT binary patch literal 1660956 zcmYJZ19T=$)GhqPwl%SB+qUtFum0DuDi>%VUnBX<*KJ4ZHV0001O?rdfTz~MEtGc|Jk##BN= ze0`N}h@bQvu1d9~(yb7!l3reUvT(2w(G!_CIGYhMv$GR9vv4zW5-}NZv6*sneLJKW zz5$H#O5&3AY(&BuqTfhUGm~$JsDq=It(mzi5epL&D?JMn^M7bdS64?KMn(@04+eKD zQ!@u!BYOr1XA8#vW?`^&wX^-kI5@gmIoP}K5SbVm8=3Gk6FHlif48P)#3hg`Lu6;= zX=V!ikMCPH13DYoTYRHAh)gV<9qf#N|1;Fp+053~%H>J`A0r2mi>;N(_gemsfr-f8`G4jxv9dFA{VxP7dsj1OTcdB#x82y*&DqEcXyRb! zX!IYs$@d1iIvZKpe^Yz|osIs(m^&NUnSD=4WDIol`j)Ls`B}bYBU2;C|DrGk8e19t z7niA(v)TW|TKp>`90j(gx|#3oXF1jdmq2kL-eiiv#>HS5jp+0czz}Z zj&ITNKcfHXjXe1|xW5f9u4az>Y(!R$-%0sS|98&5xgCxFug3bFa;NXy|CdWZAOPU^ z!z>~cfcmxn1+o2k&kICk{(KwtxB4aGvdZx8=8$k{FseTQ0D%3!3)Gm!E61z9>J@+9 z!&+!xIUR6{@h)~&bSSejOA+(7q5YdX#27m-(_@A}dfyr}4J0`B%|ysg1%x}vy|?(m zm=Isf3LRYP1N5%$MkdqYCU^y9>CLjCesNR{`(MJN1@#+M!M??*iNhumh_fXDrfD-{5`jw#rMN~J zJ{m`Gx>rJ%58RSv*X$%_oQ&l=y(ir;)<0^?v1S#*g)k zn_u7Z9P`3pCBt0_0_!M3SDl~8Fwd#tb-4cbh?*NRh;ka7beGdV->RH!W?~kRi81u$ixjs8;sMO`J>poK~lJD z0r89Liv%9nj6Y5H{sXgsX%YF15UX#l!D#2ef~tO%-H?``e2cTbEM%eKAMXd6=FOq= z$`o?T;<^zv(s;T&3fEY|V16CzoIp7J?<_S+`ro~2d6USW=;9h_t z@gFT$uDxz(G;0a}`7;RCwDh}LYfeJS7z{(66ILU*5?qv$&XdQi8&e zpzGc#G~$0Lm~)L8Mi&K+dMw{Hyi)AR+0ye5kr`4m+a;*Y&p#VB7cTr^1Hzp;_SKX_ zxlmGrVgguKf<-Tcy9nFnE3^^TxT+!aYoo-vwvnF^!8Lv+*XaJ(qn95G9**5ZpV+I# zZDx1-x$@&!vD07DM{1;3SbfP{gKJK(rnL$$dw3@wENj%Vn8VwWd zxjp3^RH-y-?T4tjTCKrd9?KOQbtD

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b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md similarity index 62% rename from docs/src/model_simulation/interactive_brusselator_simulation.md rename to docs/src/model_simulation/examples/interactive_brusselator_simulation.md index c0d873d26d..3118ad93d3 100644 --- a/docs/src/model_simulation/interactive_brusselator_simulation.md +++ b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md @@ -1,31 +1,13 @@ -# [Interactive Visualization of the Brusselator Model](@id interactive_brusselator) +# [Interactive Simulation and Plotting](@id interactive_brusselator) -```@contents -Pages = ["interactive_brusselator.md"] -Depth = 3 -``` - -Catalyst can utilize the [GLMakie.jl](https://github.com/JuliaPlots/GLMakie.jl) package for creating interactive visualizations. 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. +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. !!! note This tutorial assumes you have GLMakie.jl installed. If not, you can install it by running `using Pkg; Pkg.add("GLMakie")` in your Julia REPL. -## [Background: The Brusselator Model](@id brusselator_background) - -The Brusselator is a theoretical model for autocatalytic reactions, proposed by Ilya Prigogine and his collaborators. It is described by the following set of differential equations: - -```math -\begin{aligned} -\frac{dX}{dt} &= A + X^2Y - BX - X \\ -\frac{dY}{dt} &= BX - X^2Y -\end{aligned} -``` - -Where X and Y are chemical species, and A and B are parameters. This system can exhibit oscillatory behavior for certain parameter values, making it an interesting subject for study in nonlinear dynamics and chemical kinetics. - ## [Setting up the Brusselator model](@id setup_brusselator) -First, let's import the necessary packages and define our Brusselator model: +Let's again use the oscillating Brusselator model, extending the basic simulation [plotting](@ref simulation_plotting) workflow we saw earlier. ```julia using Catalyst @@ -41,22 +23,25 @@ brusselator = @reaction_network begin end # Initial parameter values and conditions -p = [:A => 1.0, :B => 3.0] -u0 = [:X => 1.0, :Y => 1.0] +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) +function solve_brusselator(A, B, X0, Y0, prob = oprob) p = [:A => A, :B => B] u0 = [:X => X0, :Y => Y0] - prob = remake(oprob, p=p, u0=u0) - solve(prob, Tsit5(), saveat = 0.1) + newprob = remake(prob, p=p, u0=u0) + solve(newprob, Tsit5(), saveat = 0.1) # saveat = 0.1 saves the solution every 0.1 time units. It's important to set this so that the size of the solution doesn't change during interactivity. 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. +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. + +!!! tip + 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) @@ -64,7 +49,7 @@ Let's start by creating a basic plot of our Brusselator model: ```julia # Create the main figure -fig = Figure(size = (800, 600), fontsize = 18) +fig = Figure(size = (800, 600), fontsize = 18); # Create an axis for the plot ax = Axis(fig[1, 1], @@ -73,7 +58,7 @@ ax = Axis(fig[1, 1], ylabel = "Concentration") # Solve the ODE -sol = solve_brusselator(1.0, 3.0, 1.0, 1.0) +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) @@ -88,7 +73,7 @@ display(fig) This will produce a basic time series plot of the Brusselator model: -![Basic Brusselator Plot](../assets/brusselator_basic_plot.svg) +![Basic Brusselator Plot](../../assets/brusselator_basic_plot.svg) The plot shows the concentrations of species X and Y over time. Notice the oscillatory behavior characteristic of the Brusselator model. @@ -98,14 +83,14 @@ Now, let's add interactivity to our plot using Observables and sliders. We'll bu ### [Creating Observables](@id creating_observables) -Observables are a key concept in reactive programming and are central to how Makie.jl creates interactive visualizations. +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). ```julia # Create observables for parameters and initial conditions A = Observable(1.0) -B = Observable(3.0) +B = Observable(4.0) X0 = Observable(1.0) -Y0 = 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. @@ -116,17 +101,17 @@ Let's add sliders that will control our Observables: ```julia # Create the main figure -fig = Figure(size = (800, 600), fontsize = 18) +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 = 0.1:0.1:5.0, startvalue = 1.0) -slider_B = Slider(slider_layout[2, 1], range = 0.1:0.1:5.0, startvalue = 3.0) -slider_X0 = Slider(slider_layout[3, 1], range = 0.1:0.1:5.0, startvalue = 1.0) -slider_Y0 = Slider(slider_layout[4, 1], range = 0.1:0.1:5.0, startvalue = 1.0) +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") @@ -134,7 +119,7 @@ Label(slider_layout[2, 1, Left()], "B") Label(slider_layout[3, 1, Left()], "X₀") Label(slider_layout[4, 1, Left()], "Y₀") -# Connect sliders to observables +# Connect the values of the sliders to the observables connect!(A, slider_A.value) connect!(B, slider_B.value) connect!(X0, slider_X0.value) @@ -155,10 +140,12 @@ ax = Axis(plot_layout[1, 1], 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 -lines!(ax, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), label = "X", color = :blue, linewidth = 3) +# 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 @@ -170,17 +157,17 @@ display(fig) The resulting figure should look like this: -![Interactive Brusselator Plot](../assets/brusselator_interactive_plot.svg) +![Interactive Brusselator Plot](../../assets/brusselator_interactive_plot.svg) 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. -## [Enhanced visualization with phase plot](@id adding_phase_plot) +## [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: +To gain more insight into the system's behavior, let's enhance our visualization by adding a phase plot, along with some other improvements: ```julia # Create the main figure -fig = Figure(size = (1200, 800), fontsize = 18) +fig = Figure(size = (1200, 800), fontsize = 18); # Create main layout: plots on top, sliders at bottom plot_grid = fig[1, 1] = GridLayout() @@ -205,34 +192,36 @@ ax_phase = Axis(phase_plot[1, 1], 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 = 0.1:0.1:5.0, startvalue = 1.0) -slider_B = Slider(param_grid[3, 2], range = 0.1:0.1:5.0, startvalue = 3.0) +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 = 0.1:0.1:5.0, startvalue = 1.0) -slider_Y0 = Slider(ic_grid[3, 2], range = 0.1:0.1:5.0, startvalue = 1.0) +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 -A = Observable(1.0) -B = Observable(3.0) -X0 = Observable(1.0) -Y0 = Observable(1.0) 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 +# 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[: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 @@ -245,7 +234,7 @@ Colorbar(phase_plot[1, 2], phase_plot_obj, label = "Time") # Add legends axislegend(ax_time, position = :rt) -# Adjust layout +# Adjust layout to your liking colgap!(plot_grid, 20) rowgap!(fig.layout, 20) colgap!(param_grid, 10) @@ -257,36 +246,28 @@ display(fig) This will create a visualization with both time series and phase plots: -![Interactive Brusselator Plot with Time Series and Phase Plot](../assets/brusselator_interactive_plot_full.svg) - - -## [Performance considerations](@id interactive_performance_considerations) - -When working with interactive visualizations, especially for more complex models, performance can become an issue. Here are some tips to improve performance: - -1. Use appropriate ODE solvers. For stiff systems, consider using `Rodas4()` instead of `Tsit5()`. -2. Adjust the `saveat` parameter in the `solve` function to reduce the number of points plotted. -3. For very large systems, consider using `GLMakie.jl` instead of `Makie.jl` for better performance. +![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 colours. -- `label`: Determines label texts. +- `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 = :blue, linewidth = 2, linestyle = :dash) + 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 or dropdowns to control different aspects of the simulation or visualization. -- Adding additonal axes to the plot. +- 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. From 54b81c3961fae943f321d810809466e264ef2bc7 Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Tue, 24 Sep 2024 11:57:42 -0400 Subject: [PATCH 04/15] removed initial setup note, changed saveat tipe to note, added Makie links for sliders,buttons, menus --- .../examples/interactive_brusselator_simulation.md | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md index 3118ad93d3..0d976098d1 100644 --- a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md +++ b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md @@ -2,8 +2,6 @@ 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. -!!! note - This tutorial assumes you have GLMakie.jl installed. If not, you can install it by running `using Pkg; Pkg.add("GLMakie")` in your Julia REPL. ## [Setting up the Brusselator model](@id setup_brusselator) @@ -34,13 +32,13 @@ 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) # saveat = 0.1 saves the solution every 0.1 time units. It's important to set this so that the size of the solution doesn't change during interactivity. + solve(newprob, Tsit5(), saveat = 0.1) # saveat = 0.1 saves the solution every 0.1 time units. It's important to set this so that the solution is saved at regular intervals. 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. -!!! tip +!!! 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) @@ -97,7 +95,7 @@ An Observable is a container for a value that can change over time. When the val ### [Adding sliders and connecting to Observables](@id adding_sliders) -Let's add sliders that will control our Observables: +Let's add [sliders](https://docs.makie.org/stable/reference/blocks/slider) that will control our Observables: ```julia # Create the main figure @@ -266,7 +264,7 @@ lines!(ax_time, lift(sol -> sol.t, solution), lift(sol -> sol[:X], solution), ## [Extending the interactive visualization](@id extending_interactive_visualization) You can further extend this visualization by: -- Adding other interactive elements, such as buttons or dropdowns to control different aspects of the simulation or visualization. +- 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. From 33b60e60eedc068641c47bedb893341432f9fbbb Mon Sep 17 00:00:00 2001 From: Jonathan Fischer Date: Tue, 24 Sep 2024 11:59:43 -0400 Subject: [PATCH 05/15] Update docs/src/model_simulation/examples/interactive_brusselator_simulation.md Co-authored-by: Sam Isaacson --- .../examples/interactive_brusselator_simulation.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md index 0d976098d1..c6ebcc07ef 100644 --- a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md +++ b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md @@ -35,8 +35,7 @@ function solve_brusselator(A, B, X0, Y0, prob = oprob) solve(newprob, Tsit5(), saveat = 0.1) # saveat = 0.1 saves the solution every 0.1 time units. It's important to set this so that the solution is saved at regular intervals. 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. +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. From 5557e553353b569b9bda28d06464c82892e116ec Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Tue, 24 Sep 2024 12:00:18 -0400 Subject: [PATCH 06/15] removed saveat comment --- .../examples/interactive_brusselator_simulation.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md index 0d976098d1..026a71ec35 100644 --- a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md +++ b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md @@ -32,7 +32,7 @@ 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) # saveat = 0.1 saves the solution every 0.1 time units. It's important to set this so that the solution is saved at regular intervals. + solve(newprob, Tsit5(), saveat = 0.1) end ``` From 1fc79dfda3062a2f63f844b3907465a46ced71d2 Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Tue, 24 Sep 2024 12:29:41 -0400 Subject: [PATCH 07/15] changed code blocks to run dynamically --- .../interactive_brusselator_simulation.md | 20 +++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md index 1d856710ca..89c7ba6086 100644 --- a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md +++ b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md @@ -7,10 +7,10 @@ Catalyst can utilize the [GLMakie.jl](https://github.com/JuliaPlots/GLMakie.jl) Let's again use the oscillating Brusselator model, extending the basic simulation [plotting](@ref simulation_plotting) workflow we saw earlier. -```julia +```@example interactive_brusselator using Catalyst using OrdinaryDiffEq -using GLMakie +using GLMakie; GLMakie.activate!(inline = true) # Activate the GLMakie backend. Here we set `inline = true` so that the plot is displayed inline for this documentation, but you can leave it out in your own work if you prefer plots displayed in a separate window. # Define the Brusselator model brusselator = @reaction_network begin @@ -44,7 +44,7 @@ This code sets up our Brusselator model using Catalyst.jl's `@reaction_network` Let's start by creating a basic plot of our Brusselator model: -```julia +```@example interactive_brusselator # Create the main figure fig = Figure(size = (800, 600), fontsize = 18); @@ -68,9 +68,9 @@ axislegend(ax, position = :rt) display(fig) ``` -This will produce a basic time series plot of the Brusselator model: + The plot shows the concentrations of species X and Y over time. Notice the oscillatory behavior characteristic of the Brusselator model. @@ -82,7 +82,7 @@ Now, let's add interactivity to our plot using Observables and sliders. We'll bu 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). -```julia +```@example interactive_brusselator # Create observables for parameters and initial conditions A = Observable(1.0) B = Observable(4.0) @@ -129,7 +129,7 @@ These sliders allow us to interactively change the parameters A and B, as well a Now, let's create a plot that reacts to changes in our sliders: -```julia +```@example interactive_brusselator # Create an axis for the plot ax = Axis(plot_layout[1, 1], title = "Brusselator Model", @@ -151,10 +151,10 @@ axislegend(ax, position = :rt) # Display the figure display(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. @@ -162,7 +162,7 @@ This plot will now update in real-time as you move the sliders, allowing for int To gain more insight into the system's behavior, let's enhance our visualization by adding a phase plot, along with some other improvements: -```julia +```@example interactive_brusselator # Create the main figure fig = Figure(size = (1200, 800), fontsize = 18); From 0f19713f0ee063c1f7ff879cfaf89f63c7c0b69a Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Tue, 24 Sep 2024 12:41:22 -0400 Subject: [PATCH 08/15] removed `display`, think it was messing up the inline plots --- .../examples/interactive_brusselator_simulation.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md index 89c7ba6086..9e4e897aae 100644 --- a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md +++ b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md @@ -65,7 +65,7 @@ lines!(ax, sol.t, sol[:Y], label = "Y", color = :red, linewidth = 3) axislegend(ax, position = :rt) # Display the figure -display(fig) +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) @@ -152,10 +148,6 @@ 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. @@ -239,7 +231,7 @@ colgap!(param_grid, 10) colgap!(ic_grid, 10) # Display the figure -fig +#fig ``` This will create a visualization with both time series and phase plots: From 5b25e8f96240ab7a4a09468c773f4c260ff23ae1 Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Tue, 24 Sep 2024 13:53:14 -0400 Subject: [PATCH 13/15] stopped code blocks from executing and returning prior to plotting --- .../examples/interactive_brusselator_simulation.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md index 5047aaae91..380ee78cbd 100644 --- a/docs/src/model_simulation/examples/interactive_brusselator_simulation.md +++ b/docs/src/model_simulation/examples/interactive_brusselator_simulation.md @@ -7,7 +7,7 @@ Catalyst can utilize the [GLMakie.jl](https://github.com/JuliaPlots/GLMakie.jl) Let's again use the oscillating Brusselator model, extending the basic simulation [plotting](@ref simulation_plotting) workflow we saw earlier. -```@example interactive_brusselator +```@example interactive_brusselator; continued = true using Catalyst using OrdinaryDiffEq using GLMakie @@ -79,7 +79,7 @@ Now, let's add interactivity to our plot using Observables and sliders. We'll bu 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 +```@example interactive_brusselator; continued = true # Create observables for parameters and initial conditions A = Observable(1.0) B = Observable(4.0) From 8015ec74ded5e5af55fa429fae0ff8cd99dd175a Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Thu, 10 Oct 2024 18:05:40 -0400 Subject: [PATCH 14/15] added GLMakie dependency to docs env --- docs/Project.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/Project.toml b/docs/Project.toml index a44ca1c2c5..6c66dd72c5 100644 --- a/docs/Project.toml +++ b/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" From 31eae9f77b18efe4146fb5f1c7d5a92b1686706d Mon Sep 17 00:00:00 2001 From: Jonathan Fischer PEPE Date: Mon, 14 Oct 2024 16:52:03 -0400 Subject: [PATCH 15/15] added xvfb to Documentation workflow to allow headless GLMakie doctest to pass --- .github/workflows/Documentation.yml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.github/workflows/Documentation.yml b/.github/workflows/Documentation.yml index a743dd3cc8..7babb259e4 100644 --- a/.github/workflows/Documentation.yml +++ b/.github/workflows/Documentation.yml @@ -15,6 +15,8 @@ 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 @@ -22,7 +24,8 @@ jobs: 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:

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