build based on 8474867

previews/PR391/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.10.0","generation_timestamp":"2024-02-13T15:03:46","documenter_version":"1.2.1"}}
+{"documenter":{"julia_version":"1.10.0","generation_timestamp":"2024-02-13T16:42:39","documenter_version":"1.2.1"}}

previews/PR391/concrete_features/index.html

@@ -18,9 +18,9 @@
 plot!([plot, ]x::AbstractVector, f::FiniteGP; ribbon_scale=1, kwargs...)</code></pre><p>Plot the predictive mean for the projection <code>f</code> of a Gaussian process and a ribbon of <code>ribbon_scale</code> standard deviations around it versus <code>x</code>.</p><div class="admonition is-info"><header class="admonition-header">Note</header><div class="admonition-body"><p>Make sure to load <a href="https://github.com/JuliaPlots/Plots.jl">Plots.jl</a> before you use this function.</p></div></div><p><strong>Examples</strong></p><p>Plot the mean and a ribbon of 3 standard deviations:</p><pre><code class="language-julia hljs">using Plots
 
 gp = GP(SqExponentialKernel())
-plot(gp(rand(5)); ribbon_scale=3)</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/26579ef398d40d5be31949b235840e318baf6a85/src/util/plotting.jl#L18-L39">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="RecipesBase.plot-Tuple{AbstractGPs.FiniteGP}" href="#RecipesBase.plot-Tuple{AbstractGPs.FiniteGP}"><code>RecipesBase.plot</code></a> — <span class="docstring-category">Method</span></header><section><div><pre><code class="language-julia hljs">plot(f::FiniteGP; kwargs...)
-plot!([plot, ]f::FiniteGP; kwargs...)</code></pre><p>Plot the predictive mean and a ribbon around it for the projection <code>f</code> of a Gaussian process versus <code>f.x</code>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/26579ef398d40d5be31949b235840e318baf6a85/src/util/plotting.jl#L48-L54">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="RecipesBase.plot-Tuple{AbstractVector, AbstractGPs.AbstractGP}" href="#RecipesBase.plot-Tuple{AbstractVector, AbstractGPs.AbstractGP}"><code>RecipesBase.plot</code></a> — <span class="docstring-category">Method</span></header><section><div><pre><code class="language-julia hljs">plot(x::AbstractVector, gp::AbstractGP; kwargs...)
-plot!([plot, ]x::AbstractVector, gp::AbstractGP; kwargs...)</code></pre><p>Plot the predictive mean and a ribbon around it for the projection <code>gp(x)</code> of the Gaussian process <code>gp</code>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/26579ef398d40d5be31949b235840e318baf6a85/src/util/plotting.jl#L61-L67">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="AbstractGPs.sampleplot" href="#AbstractGPs.sampleplot"><code>AbstractGPs.sampleplot</code></a> — <span class="docstring-category">Function</span></header><section><div><pre><code class="language-julia hljs">sampleplot([x::AbstractVector=f.x, ]f::FiniteGP; samples=1, kwargs...)</code></pre><p>Plot samples from the projection <code>f</code> of a Gaussian process versus <code>x</code>.</p><div class="admonition is-info"><header class="admonition-header">Note</header><div class="admonition-body"><p>Make sure to load <a href="https://github.com/JuliaPlots/Plots.jl">Plots.jl</a> before you use this function.</p></div></div><p>When plotting multiple samples, these are treated as a <em>single</em> series (i.e., only a single entry will be added to the legend when providing a <code>label</code>).</p><p><strong>Example</strong></p><pre><code class="language-julia hljs">using Plots
+plot(gp(rand(5)); ribbon_scale=3)</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/847486726d6c70f533fccb10b3243a608fa0fa8d/src/util/plotting.jl#L18-L39">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="RecipesBase.plot-Tuple{AbstractGPs.FiniteGP}" href="#RecipesBase.plot-Tuple{AbstractGPs.FiniteGP}"><code>RecipesBase.plot</code></a> — <span class="docstring-category">Method</span></header><section><div><pre><code class="language-julia hljs">plot(f::FiniteGP; kwargs...)
+plot!([plot, ]f::FiniteGP; kwargs...)</code></pre><p>Plot the predictive mean and a ribbon around it for the projection <code>f</code> of a Gaussian process versus <code>f.x</code>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/847486726d6c70f533fccb10b3243a608fa0fa8d/src/util/plotting.jl#L48-L54">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="RecipesBase.plot-Tuple{AbstractVector, AbstractGPs.AbstractGP}" href="#RecipesBase.plot-Tuple{AbstractVector, AbstractGPs.AbstractGP}"><code>RecipesBase.plot</code></a> — <span class="docstring-category">Method</span></header><section><div><pre><code class="language-julia hljs">plot(x::AbstractVector, gp::AbstractGP; kwargs...)
+plot!([plot, ]x::AbstractVector, gp::AbstractGP; kwargs...)</code></pre><p>Plot the predictive mean and a ribbon around it for the projection <code>gp(x)</code> of the Gaussian process <code>gp</code>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/847486726d6c70f533fccb10b3243a608fa0fa8d/src/util/plotting.jl#L61-L67">source</a></section></article><article class="docstring"><header><a class="docstring-article-toggle-button fa-solid fa-chevron-down" href="javascript:;" title="Collapse docstring"></a><a class="docstring-binding" id="AbstractGPs.sampleplot" href="#AbstractGPs.sampleplot"><code>AbstractGPs.sampleplot</code></a> — <span class="docstring-category">Function</span></header><section><div><pre><code class="language-julia hljs">sampleplot([x::AbstractVector=f.x, ]f::FiniteGP; samples=1, kwargs...)</code></pre><p>Plot samples from the projection <code>f</code> of a Gaussian process versus <code>x</code>.</p><div class="admonition is-info"><header class="admonition-header">Note</header><div class="admonition-body"><p>Make sure to load <a href="https://github.com/JuliaPlots/Plots.jl">Plots.jl</a> before you use this function.</p></div></div><p>When plotting multiple samples, these are treated as a <em>single</em> series (i.e., only a single entry will be added to the legend when providing a <code>label</code>).</p><p><strong>Example</strong></p><pre><code class="language-julia hljs">using Plots
 
 gp = GP(SqExponentialKernel())
-sampleplot(gp(rand(5)); samples=10, linealpha=1.0)</code></pre><p>The given example plots 10 samples from the projection of the GP <code>gp</code>. The <code>linealpha</code> is modified from default of 0.35 to 1.</p><hr/><pre><code class="nohighlight hljs">sampleplot(x::AbstractVector, gp::AbstractGP; samples=1, kwargs...)</code></pre><p>Plot samples from the finite projection <code>gp(x, 1e-9)</code> versus <code>x</code>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/26579ef398d40d5be31949b235840e318baf6a85/src/util/plotting.jl#L76-L103">source</a></section></article><h3 id="Makie.jl"><a class="docs-heading-anchor" href="#Makie.jl">Makie.jl</a><a id="Makie.jl-1"></a><a class="docs-heading-anchor-permalink" href="#Makie.jl" title="Permalink"></a></h3><p>You can use the Julia package <a href="https://github.com/JuliaGaussianProcesses/AbstractGPsMakie.jl">AbstractGPsMakie.jl</a> to plot Gaussian processes with <a href="https://github.com/JuliaPlots/Makie.jl">Makie.jl</a>.</p><p><video src="https://juliagaussianprocesses.github.io/AbstractGPsMakie.jl/stable/posterior_animation.mp4" controls="true" title="posterior animation"><a href="https://juliagaussianprocesses.github.io/AbstractGPsMakie.jl/stable/posterior_animation.mp4">posterior animation</a></video></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../api/">« The Main APIs</a><a class="docs-footer-nextpage" href="../examples/0-intro-1d/">Intro to AbstractGPs: one-dimensional regression »</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 1.2.1 on <span class="colophon-date" title="Tuesday 13 February 2024 15:03">Tuesday 13 February 2024</span>. Using Julia version 1.10.0.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+sampleplot(gp(rand(5)); samples=10, linealpha=1.0)</code></pre><p>The given example plots 10 samples from the projection of the GP <code>gp</code>. The <code>linealpha</code> is modified from default of 0.35 to 1.</p><hr/><pre><code class="nohighlight hljs">sampleplot(x::AbstractVector, gp::AbstractGP; samples=1, kwargs...)</code></pre><p>Plot samples from the finite projection <code>gp(x, 1e-9)</code> versus <code>x</code>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/JuliaGaussianProcesses/AbstractGPs.jl/blob/847486726d6c70f533fccb10b3243a608fa0fa8d/src/util/plotting.jl#L76-L103">source</a></section></article><h3 id="Makie.jl"><a class="docs-heading-anchor" href="#Makie.jl">Makie.jl</a><a id="Makie.jl-1"></a><a class="docs-heading-anchor-permalink" href="#Makie.jl" title="Permalink"></a></h3><p>You can use the Julia package <a href="https://github.com/JuliaGaussianProcesses/AbstractGPsMakie.jl">AbstractGPsMakie.jl</a> to plot Gaussian processes with <a href="https://github.com/JuliaPlots/Makie.jl">Makie.jl</a>.</p><p><video src="https://juliagaussianprocesses.github.io/AbstractGPsMakie.jl/stable/posterior_animation.mp4" controls="true" title="posterior animation"><a href="https://juliagaussianprocesses.github.io/AbstractGPsMakie.jl/stable/posterior_animation.mp4">posterior animation</a></video></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../api/">« The Main APIs</a><a class="docs-footer-nextpage" href="../examples/0-intro-1d/">Intro to AbstractGPs: one-dimensional regression »</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 1.2.1 on <span class="colophon-date" title="Tuesday 13 February 2024 16:42">Tuesday 13 February 2024</span>. Using Julia version 1.10.0.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR391/examples/0-intro-1d/Manifest.toml

@@ -6,11 +6,11 @@ project_hash = "f2a4e287233f560750b3481c1f2594a5673c5bf1"
 
 [[deps.AbstractGPs]]
 deps = ["ChainRulesCore", "Distributions", "FillArrays", "IrrationalConstants", "KernelFunctions", "LinearAlgebra", "PDMats", "Random", "RecipesBase", "Reexport", "Statistics", "StatsBase", "Test"]
-git-tree-sha1 = "a61ec1599a10bb775bfaa318f1cf1774d3c39b2f"
-repo-rev = "26579ef398d40d5be31949b235840e318baf6a85"
+git-tree-sha1 = "552e9b69735ce4661d1dda8c697035624ecd7a1b"
+repo-rev = "847486726d6c70f533fccb10b3243a608fa0fa8d"
 repo-url = "/home/runner/work/AbstractGPs.jl/AbstractGPs.jl"
 uuid = "99985d1d-32ba-4be9-9821-2ec096f28918"
-version = "0.5.19"
+version = "0.5.20"
 
 [[deps.AbstractMCMC]]
 deps = ["BangBang", "ConsoleProgressMonitor", "Distributed", "LogDensityProblems", "Logging", "LoggingExtras", "ProgressLogging", "Random", "StatsBase", "TerminalLoggers", "Transducers"]