build based on 646a34d

v0.8.2/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.6.7","generation_timestamp":"2023-10-16T13:01:12","documenter_version":"1.1.1"}}
+{"documenter":{"julia_version":"1.6.7","generation_timestamp":"2023-10-16T13:11:54","documenter_version":"1.1.1"}}

v0.8.2/BasicConstructors/index.html

@@ -51,4 +51,4 @@
 edge = ODEEdge(; f=edgefunction!, dim=1, coupling=:undirected)
 edgearr = [edge for e in edges(g)]
 
-nd = network_dynamics(vertexarr, edgearr, g)</code></pre><p>Now we have an <code>ODEFunction</code> <code>nd</code> that can be solved with the tools provided by <a href="https://github.com/SciML/DifferentialEquations.jl">DifferentialEquations.jl</a>.</p><p>For more details check out the Tutorials section.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../">« General</a><a class="docs-footer-nextpage" href="../parameters/">Parameter handling »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.1 on <span class="colophon-date" title="Monday 16 October 2023 13:01">Monday 16 October 2023</span>. Using Julia version 1.6.7.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+nd = network_dynamics(vertexarr, edgearr, g)</code></pre><p>Now we have an <code>ODEFunction</code> <code>nd</code> that can be solved with the tools provided by <a href="https://github.com/SciML/DifferentialEquations.jl">DifferentialEquations.jl</a>.</p><p>For more details check out the Tutorials section.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../">« General</a><a class="docs-footer-nextpage" href="../parameters/">Parameter handling »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.1 on <span class="colophon-date" title="Monday 16 October 2023 13:11">Monday 16 October 2023</span>. Using Julia version 1.6.7.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

v0.8.2/SDEVertex/index.html

@@ -31,10 +31,10 @@
 ode_sol = solve(ode_prob, Tsit5())
 
 using Plots, LaTeXStrings
-plot(ode_sol; vars=syms_containing(nd, &quot;ω&quot;), ylims=(-1.0, 1.0), ylabel=L&quot;\omega&quot;, legend=false, fmt=:png)</code></pre><img src="dbaa6d16.svg" alt="Example block output"/><p>We see that this is in fact a fixpoint solution. We will later use this as an initial condition for the numerical integration of the SDE system.</p><h2 id="Adding-a-Stochastic-Layer"><a class="docs-heading-anchor" href="#Adding-a-Stochastic-Layer">Adding a Stochastic Layer</a><a id="Adding-a-Stochastic-Layer-1"></a><a class="docs-heading-anchor-permalink" href="#Adding-a-Stochastic-Layer" title="Permalink"></a></h2><p>For adding the stochastic part of the dynamics we have to define a second graph layer. In our example, the fluctuations at different nodes are independent of each other. Therefore, we define a second graph with the same number of vertices but without any edges.</p><pre><code class="language-julia hljs">h = SimpleGraph(4, 0)</code></pre><p>The dynamics at the nodes has to have the same dimension as in the deterministic case. In our example we only have fluctuations in the second variable.</p><pre><code class="language-julia hljs">function fluctuation!(dx, x, edges, p, t)
+plot(ode_sol; vars=syms_containing(nd, &quot;ω&quot;), ylims=(-1.0, 1.0), ylabel=L&quot;\omega&quot;, legend=false, fmt=:png)</code></pre><img src="eae58088.svg" alt="Example block output"/><p>We see that this is in fact a fixpoint solution. We will later use this as an initial condition for the numerical integration of the SDE system.</p><h2 id="Adding-a-Stochastic-Layer"><a class="docs-heading-anchor" href="#Adding-a-Stochastic-Layer">Adding a Stochastic Layer</a><a id="Adding-a-Stochastic-Layer-1"></a><a class="docs-heading-anchor-permalink" href="#Adding-a-Stochastic-Layer" title="Permalink"></a></h2><p>For adding the stochastic part of the dynamics we have to define a second graph layer. In our example, the fluctuations at different nodes are independent of each other. Therefore, we define a second graph with the same number of vertices but without any edges.</p><pre><code class="language-julia hljs">h = SimpleGraph(4, 0)</code></pre><p>The dynamics at the nodes has to have the same dimension as in the deterministic case. In our example we only have fluctuations in the second variable.</p><pre><code class="language-julia hljs">function fluctuation!(dx, x, edges, p, t)
     dx[1] = 0.0
     dx[2] = 0.05
 end</code></pre><p>Now we can construct the dynamics of the second layer by using <code>network_dynamics()</code>. Since the graph structure of the stochastic layer has no edges we can take the edge function of the deterministic case as a placeholder.</p><pre><code class="language-julia hljs">fluctuation_vertex = ODEVertex(; f=fluctuation!, dim=2)
 nd_noise = network_dynamics(fluctuation_vertex, powerflow_edge, h)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">[ Info: Reconstructing EdgeFunction with :undefined coupling type..</code></pre><h2 id="Simulating-the-SDE"><a class="docs-heading-anchor" href="#Simulating-the-SDE">Simulating the SDE</a><a id="Simulating-the-SDE-1"></a><a class="docs-heading-anchor-permalink" href="#Simulating-the-SDE" title="Permalink"></a></h2><p>Finally, we can create an <code>SDEProblem</code> and solve it with <code>DifferentialEquations</code>.</p><pre><code class="language-julia hljs">sde_prob = SDEProblem(nd, nd_noise, u0, (0.0, 500.0), p)
 sde_sol = solve(sde_prob, SOSRA())
-plot(sde_sol; vars=syms_containing(nd, &quot;ω&quot;), ylims=(-1.0, 1.0), ylabel=L&quot;\omega&quot;, legend=false, fmt=:png)</code></pre><img src="5474df40.svg" alt="Example block output"/><p>More details on SDE problems, e.g. how to include correlations or how to define an <code>EnsembleProblem</code>, can be found in the <a href="https://diffeq.sciml.ai/stable/types/sde_types/">documentation</a> of <code>DifferentialEquations</code>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../heterogeneous_system/">« Heterogeneous systems</a><a class="docs-footer-nextpage" href="../kuramoto_delay/">Delay differential equations »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.1 on <span class="colophon-date" title="Monday 16 October 2023 13:01">Monday 16 October 2023</span>. Using Julia version 1.6.7.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+plot(sde_sol; vars=syms_containing(nd, &quot;ω&quot;), ylims=(-1.0, 1.0), ylabel=L&quot;\omega&quot;, legend=false, fmt=:png)</code></pre><img src="9ae22bdd.svg" alt="Example block output"/><p>More details on SDE problems, e.g. how to include correlations or how to define an <code>EnsembleProblem</code>, can be found in the <a href="https://diffeq.sciml.ai/stable/types/sde_types/">documentation</a> of <code>DifferentialEquations</code>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../heterogeneous_system/">« Heterogeneous systems</a><a class="docs-footer-nextpage" href="../kuramoto_delay/">Delay differential equations »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.1 on <span class="colophon-date" title="Monday 16 October 2023 13:11">Monday 16 October 2023</span>. Using Julia version 1.6.7.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

v0.8.2/accessing_edge_variables/index.html

@@ -12,4 +12,4 @@
     edgevals
 end
 cb = SavingCallback(saving_func, saved_values)
-sol = solve(prob, Tsit5(); callback=cb)</code></pre><p>The variables <code>saved_values</code> will contain the stored edge values. At the moment this method requires detailed knowledge of the internal data structures. Our plan is to simplify this in a future release.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../Library/">« Library</a><a class="docs-footer-nextpage" href="../getting_started_with_network_dynamics/">Getting started »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.1 on <span class="colophon-date" title="Monday 16 October 2023 13:01">Monday 16 October 2023</span>. Using Julia version 1.6.7.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+sol = solve(prob, Tsit5(); callback=cb)</code></pre><p>The variables <code>saved_values</code> will contain the stored edge values. At the moment this method requires detailed knowledge of the internal data structures. Our plan is to simplify this in a future release.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../Library/">« Library</a><a class="docs-footer-nextpage" href="../getting_started_with_network_dynamics/">Getting started »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.1 on <span class="colophon-date" title="Monday 16 October 2023 13:11">Monday 16 October 2023</span>. Using Julia version 1.6.7.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>