build based on 07fb34a

previews/PR299/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-04-05T01:24:08","documenter_version":"1.3.0"}}
+{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-04-05T01:56:26","documenter_version":"1.3.0"}}

previews/PR299/API/Emulators/index.html

@@ -48,4 +48,4 @@
     σ2::AbstractVector,
     decomposition::LinearAlgebra.SVD
 ) -> Tuple{Any, Any}
-</code></pre><p>Transform the mean and covariance back to the original (correlated) coordinate system</p><ul><li><code>μ</code> - predicted mean; size <em>output_dim</em> × <em>N_predicted_points</em>.</li><li><code>σ2</code> - predicted variance; size <em>output_dim</em> × <em>N_predicted_points</em>.      - predicted covariance; size <em>N_predicted_points</em> array of size <em>output_dim</em> × <em>output_dim</em>.</li><li><code>decomposition</code> - SVD decomposition of <em>obs_noise_cov</em>.</li></ul><p>Returns the transformed mean (size <em>output_dim</em> × <em>N_predicted_points</em>) and variance.  Note that transforming the variance back to the original coordinate system results in non-zero off-diagonal elements, so instead of just returning the  elements on the main diagonal (i.e., the variances), we return the full  covariance at each point, as a vector of length <em>N_predicted_points</em>, where  each element is a matrix of size <em>output_dim</em> × <em>output_dim</em>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/Emulator.jl#L467">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../glossary/">« Glossary</a><a class="docs-footer-nextpage" href="../GaussianProcess/">Gaussian Process »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:24">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+</code></pre><p>Transform the mean and covariance back to the original (correlated) coordinate system</p><ul><li><code>μ</code> - predicted mean; size <em>output_dim</em> × <em>N_predicted_points</em>.</li><li><code>σ2</code> - predicted variance; size <em>output_dim</em> × <em>N_predicted_points</em>.      - predicted covariance; size <em>N_predicted_points</em> array of size <em>output_dim</em> × <em>output_dim</em>.</li><li><code>decomposition</code> - SVD decomposition of <em>obs_noise_cov</em>.</li></ul><p>Returns the transformed mean (size <em>output_dim</em> × <em>N_predicted_points</em>) and variance.  Note that transforming the variance back to the original coordinate system results in non-zero off-diagonal elements, so instead of just returning the  elements on the main diagonal (i.e., the variances), we return the full  covariance at each point, as a vector of length <em>N_predicted_points</em>, where  each element is a matrix of size <em>output_dim</em> × <em>output_dim</em>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/Emulator.jl#L467">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../glossary/">« Glossary</a><a class="docs-footer-nextpage" href="../GaussianProcess/">Gaussian Process »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:56">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR299/API/GaussianProcess/index.html

@@ -19,4 +19,4 @@
     gp::CalibrateEmulateSample.Emulators.GaussianProcess{CalibrateEmulateSample.Emulators.GPJL},
     new_inputs::AbstractArray{FT<:AbstractFloat, 2}
 ) -> Tuple{Any, Any}
-</code></pre><p>Predict means and covariances in decorrelated output space using Gaussian process models.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/GaussianProcess.jl#L211">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../Emulators/">« General Interface</a><a class="docs-footer-nextpage" href="../RandomFeatures/">Random Features »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:24">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+</code></pre><p>Predict means and covariances in decorrelated output space using Gaussian process models.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/GaussianProcess.jl#L211">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../Emulators/">« General Interface</a><a class="docs-footer-nextpage" href="../RandomFeatures/">Random Features »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:56">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR299/API/MarkovChainMonteCarlo/index.html

@@ -34,4 +34,4 @@
     data::AbstractArray{FT<:AbstractFloat, 2},
     em::CalibrateEmulateSample.Emulators.Emulator{FT<:AbstractFloat}
 ) -> Any
-</code></pre><p>Transform samples from the original (correlated) coordinate system to the SVD-decorrelated coordinate system used by <a href="../Emulators/#CalibrateEmulateSample.Emulators.Emulator"><code>Emulator</code></a>. Used in the constructor for <a href="#CalibrateEmulateSample.MarkovChainMonteCarlo.MCMCWrapper"><code>MCMCWrapper</code></a>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/MarkovChainMonteCarlo.jl#L36">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../RandomFeatures/">« Random Features</a><a class="docs-footer-nextpage" href="../Utilities/">Utilities »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:24">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+</code></pre><p>Transform samples from the original (correlated) coordinate system to the SVD-decorrelated coordinate system used by <a href="../Emulators/#CalibrateEmulateSample.Emulators.Emulator"><code>Emulator</code></a>. Used in the constructor for <a href="#CalibrateEmulateSample.MarkovChainMonteCarlo.MCMCWrapper"><code>MCMCWrapper</code></a>.</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/MarkovChainMonteCarlo.jl#L36">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../RandomFeatures/">« Random Features</a><a class="docs-footer-nextpage" href="../Utilities/">Utilities »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:56">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR299/API/RandomFeatures/index.html

@@ -117,4 +117,4 @@
     kwargs...
 )
 </code></pre><p>Empty method, as optimization takes place within the build_models stage</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/VectorRandomFeature.jl#L616">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="CalibrateEmulateSample.Emulators.shrinkage_cov" href="#CalibrateEmulateSample.Emulators.shrinkage_cov"><code>CalibrateEmulateSample.Emulators.shrinkage_cov</code></a> — <span class="docstring-category">Function</span></header><section><div><pre><code class="language-julia hljs">shrinkage_cov(sample_mat::AbstractMatrix) -&gt; Any
-</code></pre><p>Calculate the empirical covariance, additionally applying a shrinkage operator (here the Ledoit Wolf 2004 shrinkage operation). Known to have better stability properties than Monte-Carlo for low sample sizes</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/RandomFeature.jl#L511">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../GaussianProcess/">« Gaussian Process</a><a class="docs-footer-nextpage" href="../MarkovChainMonteCarlo/">MarkovChainMonteCarlo »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:24">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+</code></pre><p>Calculate the empirical covariance, additionally applying a shrinkage operator (here the Ledoit Wolf 2004 shrinkage operation). Known to have better stability properties than Monte-Carlo for low sample sizes</p></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/RandomFeature.jl#L511">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../GaussianProcess/">« Gaussian Process</a><a class="docs-footer-nextpage" href="../MarkovChainMonteCarlo/">MarkovChainMonteCarlo »</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:56">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR299/API/Utilities/index.html

@@ -8,4 +8,4 @@
     ekp::EnsembleKalmanProcesses.EnsembleKalmanProcess{FT, IT, P},
     train_iterations::Union{AbstractVector{IT}, IT} where IT
 ) -> EnsembleKalmanProcesses.DataContainers.PairedDataContainer
-</code></pre><p>Extract the training points needed to train the Gaussian process regression.</p><ul><li><code>ekp</code> - EnsembleKalmanProcess holding the parameters and the data that were produced during the Ensemble Kalman (EK) process.</li><li><code>train_iterations</code> - Number (or indices) EK layers/iterations to train on.</li></ul></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/Utilities.jl#L17">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../MarkovChainMonteCarlo/">« MarkovChainMonteCarlo</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:24">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+</code></pre><p>Extract the training points needed to train the Gaussian process regression.</p><ul><li><code>ekp</code> - EnsembleKalmanProcess holding the parameters and the data that were produced during the Ensemble Kalman (EK) process.</li><li><code>train_iterations</code> - Number (or indices) EK layers/iterations to train on.</li></ul></div><a class="docs-sourcelink" target="_blank" href="https://github.com/CliMA/CalibrateEmulateSample.jl/blob/v0.5.0/src/Utilities.jl#L17">source</a></section></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../MarkovChainMonteCarlo/">« MarkovChainMonteCarlo</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 1.3.0 on <span class="colophon-date" title="Friday 5 April 2024 01:56">Friday 5 April 2024</span>. Using Julia version 1.10.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>