build based on 8bbebe6

previews/PR1034/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.10.3","generation_timestamp":"2024-05-12T23:50:04","documenter_version":"1.4.1"}}
+{"documenter":{"julia_version":"1.10.4","generation_timestamp":"2024-06-08T14:49:33","documenter_version":"1.4.1"}}

previews/PR1034/examples/celllistmap/index.html

@@ -113,4 +113,4 @@
     agent_color=p -> p.k
 )</code></pre><video width="auto" controls autoplay loop>
 <source src="../celllistmap.mp4" type="video/mp4">
-</video></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../measurements/">« Measurements.jl</a><a class="docs-footer-nextpage" href="../../performance_tips/">Performance Tips »</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="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.4.1 on <span class="colophon-date" title="Sunday 12 May 2024 23:50">Sunday 12 May 2024</span>. Using Julia version 1.10.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+</video></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../measurements/">« Measurements.jl</a><a class="docs-footer-nextpage" href="../../performance_tips/">Performance Tips »</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="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.4.1 on <span class="colophon-date" title="Saturday 8 June 2024 14:49">Saturday 8 June 2024</span>. Using Julia version 1.10.4.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR1034/examples/diffeq/index.html

@@ -60,7 +60,7 @@
         title = "Fishery Inventory",
     )
 lines!(ax, results.stock, linewidth = 2, color = :blue)
-f</code></pre><img src="5486f47a.png" alt="Example block output"/><h3 id="Add-in-some-bureaucracy"><a class="docs-heading-anchor" href="#Add-in-some-bureaucracy">Add in some bureaucracy</a><a id="Add-in-some-bureaucracy-1"></a><a class="docs-heading-anchor-permalink" href="#Add-in-some-bureaucracy" title="Permalink"></a></h3><p>OK, so let&#39;s add in some annoyances for the fishers. Of course, they wish to go out and catch regularly, but regulators only want to do their job once a year! Since it&#39;s the regulators who will monitor the total stock condition and advise fishers as to whether or not they can continue fishing, a systematic blind spot is inadvertently introduced into the system. Yearly catch and regulation occur on one day a year, whilst the stock will of course grow on a daily basis.</p><p>To achieve this, we extend the model like so:</p><pre><code class="language-julia hljs">function agent_step!(agent, model)
+f</code></pre><img src="a640716e.png" alt="Example block output"/><h3 id="Add-in-some-bureaucracy"><a class="docs-heading-anchor" href="#Add-in-some-bureaucracy">Add in some bureaucracy</a><a id="Add-in-some-bureaucracy-1"></a><a class="docs-heading-anchor-permalink" href="#Add-in-some-bureaucracy" title="Permalink"></a></h3><p>OK, so let&#39;s add in some annoyances for the fishers. Of course, they wish to go out and catch regularly, but regulators only want to do their job once a year! Since it&#39;s the regulators who will monitor the total stock condition and advise fishers as to whether or not they can continue fishing, a systematic blind spot is inadvertently introduced into the system. Yearly catch and regulation occur on one day a year, whilst the stock will of course grow on a daily basis.</p><p>To achieve this, we extend the model like so:</p><pre><code class="language-julia hljs">function agent_step!(agent, model)
     if model.tick % 365 == 0
         agent.yearly_catch = rand(abmrng(model), Poisson(agent.competence))
     end
@@ -114,7 +114,7 @@
         title = &quot;Fishery Inventory&quot;,
     )
 lines!(ax, results.stock, linewidth = 2, color = :blue)
-f</code></pre><img src="e4390ef0.png" alt="Example block output"/><h3 id="Baseline-benchmark"><a class="docs-heading-anchor" href="#Baseline-benchmark">Baseline benchmark</a><a id="Baseline-benchmark-1"></a><a class="docs-heading-anchor-permalink" href="#Baseline-benchmark" title="Permalink"></a></h3><p>Lets get a baseline performance result for our model.</p><pre><code class="language-julia hljs">using BenchmarkTools
+f</code></pre><img src="6f69a20c.png" alt="Example block output"/><h3 id="Baseline-benchmark"><a class="docs-heading-anchor" href="#Baseline-benchmark">Baseline benchmark</a><a id="Baseline-benchmark-1"></a><a class="docs-heading-anchor-permalink" href="#Baseline-benchmark" title="Permalink"></a></h3><p>Lets get a baseline performance result for our model.</p><pre><code class="language-julia hljs">using BenchmarkTools
 
 @btime Agents.step!(model, 20 * 365) setup = (model = initialise())</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">StandardABM with 50 agents of type Fisher
  agents container: Dict
@@ -185,7 +185,7 @@
         title = &quot;Fishery Inventory&quot;,
     )
 lines!(ax, resultsdeq.stock, linewidth = 2, color = :blue)
-f</code></pre><img src="4c6eb0b4.png" alt="Example block output"/><p>The small complexity addition yields us a generous speed up of around 4.5x.</p><pre><code class="language-julia hljs">@btime Agents.step!(model, 20) setup = (model = initialise_diffeq())</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">StandardABM with 50 agents of type Fisher
+f</code></pre><img src="1d278aec.png" alt="Example block output"/><p>The small complexity addition yields us a generous speed up of around 4.5x.</p><pre><code class="language-julia hljs">@btime Agents.step!(model, 20) setup = (model = initialise_diffeq())</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">StandardABM with 50 agents of type Fisher
  agents container: Dict
  space: nothing (no spatial structure)
  scheduler: fastest
@@ -200,7 +200,7 @@
 lineE = lines!(ax, results.stock, linewidth = 2, color = :blue)
 lineTS = lines!(ax, resultsdeq.stock, linewidth = 2, color = :red)
 leg = f[1, end+1] = Legend(f, [lineE, lineTS], [&quot;Euler&quot;, &quot;TSit5&quot;])
-f</code></pre><img src="19f07096.png" alt="Example block output"/><p>That&#39;s an average discrepancy of 30 fish! Optimising the step size in the Euler method can close this gap, but this is yet more analysis overhead we&#39;d prefer to avoid by using better solutions.</p><p>In addition, the ODE solver will be faster most of the time, regardless of how many steps it needs to take. If not, there are other, more effective solvers that can be used for your particular case.</p><h2 id="Coupling-Agents.jl-to-DifferentialEquations.jl"><a class="docs-heading-anchor" href="#Coupling-Agents.jl-to-DifferentialEquations.jl">Coupling Agents.jl to DifferentialEquations.jl</a><a id="Coupling-Agents.jl-to-DifferentialEquations.jl-1"></a><a class="docs-heading-anchor-permalink" href="#Coupling-Agents.jl-to-DifferentialEquations.jl" title="Permalink"></a></h2><p>Perhaps you&#39;re more familiar to the <code>DifferentialEquations</code> <code>solve</code> interface and you&#39;re new to <code>Agents</code>?</p><p>We can also couple the two systems the other way. Let&#39;s use <a href="https://docs.sciml.ai/stable/features/callback_functions/#Using-Callbacks-1">callbacks</a> to handle the agent based aspects of our problem.</p><pre><code class="language-julia hljs">function agent_cb_step!(agent, model)
+f</code></pre><img src="f32e6c3c.png" alt="Example block output"/><p>That&#39;s an average discrepancy of 30 fish! Optimising the step size in the Euler method can close this gap, but this is yet more analysis overhead we&#39;d prefer to avoid by using better solutions.</p><p>In addition, the ODE solver will be faster most of the time, regardless of how many steps it needs to take. If not, there are other, more effective solvers that can be used for your particular case.</p><h2 id="Coupling-Agents.jl-to-DifferentialEquations.jl"><a class="docs-heading-anchor" href="#Coupling-Agents.jl-to-DifferentialEquations.jl">Coupling Agents.jl to DifferentialEquations.jl</a><a id="Coupling-Agents.jl-to-DifferentialEquations.jl-1"></a><a class="docs-heading-anchor-permalink" href="#Coupling-Agents.jl-to-DifferentialEquations.jl" title="Permalink"></a></h2><p>Perhaps you&#39;re more familiar to the <code>DifferentialEquations</code> <code>solve</code> interface and you&#39;re new to <code>Agents</code>?</p><p>We can also couple the two systems the other way. Let&#39;s use <a href="https://docs.sciml.ai/stable/features/callback_functions/#Using-Callbacks-1">callbacks</a> to handle the agent based aspects of our problem.</p><pre><code class="language-julia hljs">function agent_cb_step!(agent, model)
     agent.yearly_catch = rand(abmrng(model), Poisson(agent.competence))
 end
 
@@ -255,4 +255,4 @@
         title = &quot;Fishery Inventory&quot;,
     )
 lines!(ax, discrete, linewidth = 2, color = :blue)
-f</code></pre><p>The results are different here, since the construction of this version and the one above are quite different and cannot be randomly seeded in the same manner.</p><p>However, as you can see, it is for the most part just a re-arranged implementation of the integrator method - giving users flexibility in their architecture choices.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../optim/">« BlackBoxOptim.jl</a><a class="docs-footer-nextpage" href="../schoolyard/">Graphs.jl »</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="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.4.1 on <span class="colophon-date" title="Sunday 12 May 2024 23:50">Sunday 12 May 2024</span>. Using Julia version 1.10.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+f</code></pre><p>The results are different here, since the construction of this version and the one above are quite different and cannot be randomly seeded in the same manner.</p><p>However, as you can see, it is for the most part just a re-arranged implementation of the integrator method - giving users flexibility in their architecture choices.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../optim/">« BlackBoxOptim.jl</a><a class="docs-footer-nextpage" href="../schoolyard/">Graphs.jl »</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="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.4.1 on <span class="colophon-date" title="Saturday 8 June 2024 14:49">Saturday 8 June 2024</span>. Using Julia version 1.10.4.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>