build based on d58560b

dev/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-11-02T04:36:27","documenter_version":"1.1.2"}}
+{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-11-02T07:29:46","documenter_version":"1.1.2"}}

dev/getting_started/find_root/index.html

@@ -69,4 +69,4 @@
  0.0
  0.0
  0.0</code></pre><h3 id="Step-5:-Analyze-the-Solution"><a class="docs-heading-anchor" href="#Step-5:-Analyze-the-Solution">Step 5: Analyze the Solution</a><a id="Step-5:-Analyze-the-Solution-1"></a><a class="docs-heading-anchor-permalink" href="#Step-5:-Analyze-the-Solution" title="Permalink"></a></h3><p>Now let&#39;s check out the solution. First of all, what kind of thing is the <code>sol</code>? We can see that by asking for its type:</p><pre><code class="language-julia hljs">typeof(sol)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">SciMLBase.NonlinearSolution{Float64, 1, Vector{Float64}, Vector{Float64}, SciMLBase.NonlinearProblem{Vector{Float64}, true, Vector{Float64}, SciMLBase.NonlinearFunction{true, SciMLBase.FullSpecialize, ModelingToolkit.var&quot;#f#733&quot;{RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋arg1, :ˍ₋arg2), ModelingToolkit.var&quot;#_RGF_ModTag&quot;, ModelingToolkit.var&quot;#_RGF_ModTag&quot;, (0x892348f8, 0xa22abdbe, 0xa285f9d8, 0x95831967, 0xeaff7cf7), Nothing}, RuntimeGeneratedFunctions.RuntimeGeneratedFunction{(:ˍ₋out, :ˍ₋arg1, :ˍ₋arg2), ModelingToolkit.var&quot;#_RGF_ModTag&quot;, ModelingToolkit.var&quot;#_RGF_ModTag&quot;, (0x2a5931a9, 0x19d9b662, 0x2773c77d, 0x8f1eafb9, 0xd485c91b), Nothing}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Vector{Symbol}, Vector{Symbol}, ModelingToolkit.var&quot;#generated_observed#736&quot;{ModelingToolkit.NonlinearSystem, Dict{Any, Any}}, Nothing, ModelingToolkit.NonlinearSystem, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardNonlinearProblem}, NonlinearSolve.NewtonRaphson{0, true, Val{:forward}, Nothing, typeof(NonlinearSolve.DEFAULT_PRECS), true, nothing}, Nothing, Nothing, SciMLBase.NLStats}</code></pre><p>From this, we can see that it is an <code>NonlinearSolution</code>. We can see the documentation for how to use the <code>NonlinearSolution</code> by checking the <a href="https://docs.sciml.ai/NonlinearSolve/stable/basics/NonlinearSolution/">NonlinearSolve.jl solution type page.</a> For example, the solution is stored as <code>.u</code>. What is the solution to our nonlinear system, and what is the final residual value? We can check it as follows:</p><pre><code class="language-julia hljs"># Analyze the solution
-@show sol.u, sol.resid</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">([0.0, 0.0, 0.0], [0.0, 0.0, 0.0])</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../fit_simulation/">« Fit a simulation to a dataset</a><a class="docs-footer-nextpage" href="../../comparisons/python/">Getting Started with Julia&#39;s SciML for the Python User »</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 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 04:36">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+@show sol.u, sol.resid</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">([0.0, 0.0, 0.0], [0.0, 0.0, 0.0])</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../fit_simulation/">« Fit a simulation to a dataset</a><a class="docs-footer-nextpage" href="../../comparisons/python/">Getting Started with Julia&#39;s SciML for the Python User »</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 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 07:29">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/getting_started/first_optimization/index.html

@@ -28,4 +28,4 @@
 sol = solve(prob, NLopt.LD_LBFGS())</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">u: 2-element Vector{Float64}:
  1.0
  1.0</code></pre><h3 id="Step-4:-Analyze-the-Solution"><a class="docs-heading-anchor" href="#Step-4:-Analyze-the-Solution">Step 4: Analyze the Solution</a><a id="Step-4:-Analyze-the-Solution-1"></a><a class="docs-heading-anchor-permalink" href="#Step-4:-Analyze-the-Solution" title="Permalink"></a></h3><p>Now let&#39;s check out the solution. First of all, what kind of thing is the <code>sol</code>? We can see that by asking for its type:</p><pre><code class="language-julia hljs">typeof(sol)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">SciMLBase.OptimizationSolution{Float64, 1, Vector{Float64}, Optimization.OptimizationCache{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), OptimizationForwardDiffExt.var&quot;#38#56&quot;{ForwardDiff.GradientConfig{ForwardDiff.Tag{OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, Float64}, Float64, 2, Vector{ForwardDiff.Dual{ForwardDiff.Tag{OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, Float64}, Float64, 2}}}, OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}}, OptimizationForwardDiffExt.var&quot;#41#59&quot;{ForwardDiff.HessianConfig{ForwardDiff.Tag{OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, Float64}, Float64, 2, Vector{ForwardDiff.Dual{ForwardDiff.Tag{OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, Float64}, ForwardDiff.Dual{ForwardDiff.Tag{OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, Float64}, Float64, 2}, 2}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, Float64}, Float64, 2}}}, OptimizationForwardDiffExt.var&quot;#37#55&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}}, OptimizationForwardDiffExt.var&quot;#44#62&quot;, Nothing, OptimizationForwardDiffExt.var&quot;#48#66&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, OptimizationForwardDiffExt.var&quot;#53#71&quot;{SciMLBase.OptimizationFunction{true, ADTypes.AutoForwardDiff{nothing, Nothing}, typeof(Main.L), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED_NO_TIME), Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, Optimization.ReInitCache{Vector{Float64}, Vector{Float64}}, Vector{Float64}, Vector{Float64}, Nothing, Nothing, Nothing, NLopt.Algorithm, Base.Iterators.Cycle{Tuple{Optimization.NullData}}, Bool, Optimization.NullCallback}, NLopt.Algorithm, Float64, NLopt.Opt, Float64, Nothing}</code></pre><p>From this, we can see that it is an <code>OptimizationSolution</code>. We can see the documentation for how to use the <code>OptimizationSolution</code> by checking the <a href="https://docs.sciml.ai/Optimization/stable/API/optimization_solution/">Optimization.jl solution type page</a>. For example, the solution is stored as <code>.u</code>. What is the solution to our optimization, and what is the final loss value? We can check it as follows:</p><pre><code class="language-julia hljs"># Analyze the solution
-@show sol.u, L(sol.u, p)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">([1.0, 1.0], 0.0)</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../first_simulation/">« Build and run your first simulation with Julia&#39;s SciML</a><a class="docs-footer-nextpage" href="../fit_simulation/">Fit a simulation to a dataset »</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 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 04:36">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+@show sol.u, L(sol.u, p)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">([1.0, 1.0], 0.0)</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../first_simulation/">« Build and run your first simulation with Julia&#39;s SciML</a><a class="docs-footer-nextpage" href="../fit_simulation/">Fit a simulation to a dataset »</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 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 07:29">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>