build based on f30c8d4

dev/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-11-14T14:00:42","documenter_version":"1.8.0"}}
+{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-11-26T15:52:26","documenter_version":"1.8.0"}}

dev/generated/examples/compressed_sensing/index.html

@@ -5,25 +5,25 @@
 size(image)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">(256, 256)</code></pre><p>This produces a 256x256 image of a Shepp-Logan phantom.</p><p>In this example, we consider a problem in which we randomly sample a third of the pixels in the image. Such a problem and the corresponding measurement can be constructed with the packages LinearOperatorCollection and Random:</p><p>We first randomly shuffle the indices of the image and then select the first third of the indices to sample.</p><pre><code class="language-julia hljs">using Random, LinearOperatorCollection
 randomIndices = shuffle(eachindex(image))
 sampledIndices = sort(randomIndices[1:div(end, 3)])</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">21845-element Vector{Int64}:
+     4
+     7
      9
-    10
-    19
-    24
+    11
+    15
+    18
+    20
     25
     26
-    28
-    35
-    36
-    37
+    27
      ⋮
- 65509
- 65512
- 65514
- 65515
- 65520
- 65521
+ 65492
+ 65500
+ 65516
+ 65522
  65523
- 65527
+ 65524
+ 65528
+ 65530
  65535</code></pre><p>Afterwards we build a sampling operator which samples the image at the selected indices.</p><pre><code class="language-julia hljs">A = SamplingOp(eltype(image), pattern = sampledIndices , shape = size(image));</code></pre><p>Then we apply the sampling operator to the vectorized image to obtain the sampled measurement vector</p><pre><code class="language-julia hljs">b = A*vec(image);</code></pre><p>To visualize our image we can use CairoMakie:</p><pre><code class="language-julia hljs">using CairoMakie
 function plot_image(figPos, img; title = &quot;&quot;, width = 150, height = 150)
   ax = CairoMakie.Axis(figPos; yreversed=true, title, width, height)
@@ -36,30 +36,30 @@
 samplingMask[sampledIndices] .= true
 plot_image(fig[1,2], image .* samplingMask, title = &quot;Sampled Image&quot;)
 resize_to_layout!(fig)
-fig</code></pre><img src="82a9b3c3.png" alt="Example block output"/><p>As we can see in the right image, only a third of the pixels are sampled. The goal of the inverse problem is to recover the original image from this measurement vector.</p><h2 id="Solving-the-Inverse-Problem"><a class="docs-heading-anchor" href="#Solving-the-Inverse-Problem">Solving the Inverse Problem</a><a id="Solving-the-Inverse-Problem-1"></a><a class="docs-heading-anchor-permalink" href="#Solving-the-Inverse-Problem" title="Permalink"></a></h2><p>To recover the image from the measurement vector, we solve the TV-regularized least squares problem:</p><p class="math-container">\[\begin{equation}
+fig</code></pre><img src="7fb3e75a.png" alt="Example block output"/><p>As we can see in the right image, only a third of the pixels are sampled. The goal of the inverse problem is to recover the original image from this measurement vector.</p><h2 id="Solving-the-Inverse-Problem"><a class="docs-heading-anchor" href="#Solving-the-Inverse-Problem">Solving the Inverse Problem</a><a id="Solving-the-Inverse-Problem-1"></a><a class="docs-heading-anchor-permalink" href="#Solving-the-Inverse-Problem" title="Permalink"></a></h2><p>To recover the image from the measurement vector, we solve the TV-regularized least squares problem:</p><p class="math-container">\[\begin{equation}
   \underset{\mathbf{x}}{argmin} \frac{1}{2}\vert\vert \mathbf{A}\mathbf{x}-\mathbf{b} \vert\vert_2^2 + \lambda\vert\vert\mathbf{x}\vert\vert_{\text{TV}} .
 \end{equation}\]</p><p>For this purpose we build a TV regularizer with regularization parameter <span>$λ=0.01$</span></p><pre><code class="language-julia hljs">using RegularizedLeastSquares
 reg = TVRegularization(0.01; shape=size(image));</code></pre><p>We will use the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) to solve our inverse problem. Thus, we build the corresponding solver</p><pre><code class="language-julia hljs">solver = createLinearSolver(FISTA, A; reg=reg, iterations=20);</code></pre><p>and apply it to our measurement vector</p><pre><code class="language-julia hljs">img_approx = solve!(solver,b)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">65536-element Vector{Float32}:
- 1.7268512f-18
- 2.767287f-18
- 5.302688f-18
- 1.0522765f-17
- 2.1176763f-17
- 4.4012232f-17
- 9.5682496f-17
- 2.1162977f-16
- 4.494324f-16
- 8.933863f-16
+ 4.475941f-19
+ 9.203197f-19
+ 2.1954707f-18
+ 5.0659254f-18
+ 1.1152266f-17
+ 2.390461f-17
+ 5.0998504f-17
+ 1.070807f-16
+ 2.1490663f-16
+ 4.1222092f-16
  ⋮
- 4.0347837f-16
- 1.8988034f-16
- 8.902884f-17
- 4.230316f-17
- 1.9907461f-17
- 8.953272f-18
- 3.7583915f-18
- 1.524718f-18
- 7.5730536f-19</code></pre><p>To visualize the reconstructed image, we need to reshape the result vector to the correct shape. Afterwards we can use CairoMakie again:</p><pre><code class="language-julia hljs">img_approx = reshape(img_approx,size(image));
+ 2.364637f-16
+ 1.1878623f-16
+ 5.4425447f-17
+ 2.3837499f-17
+ 1.1017589f-17
+ 5.440978f-18
+ 2.628318f-18
+ 1.2022713f-18
+ 6.2830215f-19</code></pre><p>To visualize the reconstructed image, we need to reshape the result vector to the correct shape. Afterwards we can use CairoMakie again:</p><pre><code class="language-julia hljs">img_approx = reshape(img_approx,size(image));
 plot_image(fig[1,3], img_approx, title = &quot;Reconstructed Image&quot;)
 resize_to_layout!(fig)
-fig</code></pre><img src="82751606.png" alt="Example block output"/><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../getting_started/">« Getting Started</a><a class="docs-footer-nextpage" href="../computed_tomography/">Computed Tomography »</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><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Thursday 14 November 2024 14:00">Thursday 14 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+fig</code></pre><img src="2c4e4ab0.png" alt="Example block output"/><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../getting_started/">« Getting Started</a><a class="docs-footer-nextpage" href="../computed_tomography/">Computed Tomography »</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><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Tuesday 26 November 2024 15:52">Tuesday 26 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/generated/examples/computed_tomography/index.html

@@ -62,4 +62,4 @@
  0.0</code></pre><p>To visualize the reconstructed image, we need to reshape the result vector to the correct shape. Afterwards we can use CairoMakie again:</p><pre><code class="language-julia hljs">img_approx = reshape(img_approx,size(image));
 plot_image(fig[1,4], img_approx, title = &quot;Reconstructed Image&quot;)
 resize_to_layout!(fig)
-fig</code></pre><img src="97715265.png" alt="Example block output"/><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../compressed_sensing/">« Compressed Sensing</a><a class="docs-footer-nextpage" href="../../../solvers/">Solvers »</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><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Thursday 14 November 2024 14:00">Thursday 14 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+fig</code></pre><img src="97715265.png" alt="Example block output"/><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../compressed_sensing/">« Compressed Sensing</a><a class="docs-footer-nextpage" href="../../../solvers/">Solvers »</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><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Tuesday 26 November 2024 15:52">Tuesday 26 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/generated/examples/getting_started/index.html

@@ -9,4 +9,4 @@
   \underset{\mathbf{x}}{argmin} \frac{1}{2}\vert\vert \mathbf{A}\mathbf{x}-\mathbf{b} \vert\vert_2^2 + \lambda\vert\vert\mathbf{x}\vert\vert^2_2 .
 \end{equation}\]</p><p>The corresponding solver can be built with the <span>$l^2_2$</span>-regularization term:</p><pre><code class="language-julia hljs">solver = createLinearSolver(CGNR, A; reg = L2Regularization(0.0001), iterations=32);
 x_approx = solve!(solver, b)
-isapprox(x, x_approx, rtol = 0.001)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">true</code></pre><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../../">« Home</a><a class="docs-footer-nextpage" href="../compressed_sensing/">Compressed Sensing »</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><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Thursday 14 November 2024 14:00">Thursday 14 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+isapprox(x, x_approx, rtol = 0.001)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">true</code></pre><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../../">« Home</a><a class="docs-footer-nextpage" href="../compressed_sensing/">Compressed Sensing »</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><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Tuesday 26 November 2024 15:52">Tuesday 26 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>