build based on 310f154

Author: Documenter.jl

dev/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.12.2","generation_timestamp":"2025-12-01T14:15:52","documenter_version":"1.16.1"}}
+{"documenter":{"julia_version":"1.12.2","generation_timestamp":"2025-12-01T14:33:06","documenter_version":"1.16.1"}}

dev/background/loss_functions/index.html

@@ -9,7 +9,7 @@
 
 julia> img_n = poisson(img_b, 300);
 
-julia&gt; res, o = deconvolution(img_n, psf);</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/roflmaostc/DeconvOptim.jl/blob/23b0f5c5d7883443d5eb6e31ae767af5e7c3c2f6/src/deconvolution.jl#L3-L59">source</a></section></details></article><article><details class="docstring" open="true"><summary id="DeconvOptim.richardson_lucy_iterative"><a class="docstring-binding" href="#DeconvOptim.richardson_lucy_iterative"><code>DeconvOptim.richardson_lucy_iterative</code></a> — <span class="docstring-category">Function</span></summary><section><div><pre><code class="language-julia hljs">richardson_lucy_iterative(measured, psf; &lt;keyword arguments&gt;)</code></pre><p>Classical iterative Richardson-Lucy iteration scheme for deconvolution. <code>measured</code> is the measured array and <code>psf</code> the point spread function. Converges slower than the optimization approach of <code>deconvolution</code></p><p><strong>Keyword Arguments</strong></p><ul><li><code>regularizer=GR()</code>: A regularizer function. Can be exchanged</li><li><code>λ=0.05</code>: A float indicating the total weighting of the regularizer with    respect to the global loss function</li><li><code>iterations=100</code>: Specifies number of iterations.</li><li><code>progress</code>: if not <code>nothing</code>, the progress will be monitored in a summary dictionary as obtained by             DeconvOptim.options<em>trace</em>deconv()</li></ul><p><strong>Example</strong></p><pre><code class="language-julia-repl hljs">julia&gt; using DeconvOptim, TestImages, Colors, Noise;
+julia&gt; res, o = deconvolution(img_n, psf);</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/roflmaostc/DeconvOptim.jl/blob/310f154be230dde8d2330b59cc54821772d3f084/src/deconvolution.jl#L3-L59">source</a></section></details></article><article><details class="docstring" open="true"><summary id="DeconvOptim.richardson_lucy_iterative"><a class="docstring-binding" href="#DeconvOptim.richardson_lucy_iterative"><code>DeconvOptim.richardson_lucy_iterative</code></a> — <span class="docstring-category">Function</span></summary><section><div><pre><code class="language-julia hljs">richardson_lucy_iterative(measured, psf; &lt;keyword arguments&gt;)</code></pre><p>Classical iterative Richardson-Lucy iteration scheme for deconvolution. <code>measured</code> is the measured array and <code>psf</code> the point spread function. Converges slower than the optimization approach of <code>deconvolution</code></p><p><strong>Keyword Arguments</strong></p><ul><li><code>regularizer=GR()</code>: A regularizer function. Can be exchanged</li><li><code>λ=0.05</code>: A float indicating the total weighting of the regularizer with    respect to the global loss function</li><li><code>iterations=100</code>: Specifies number of iterations.</li><li><code>progress</code>: if not <code>nothing</code>, the progress will be monitored in a summary dictionary as obtained by             DeconvOptim.options<em>trace</em>deconv()</li></ul><p><strong>Example</strong></p><pre><code class="language-julia-repl hljs">julia&gt; using DeconvOptim, TestImages, Colors, Noise;
 
 julia&gt; img = Float32.(testimage(&quot;resolution_test_512&quot;));
 
@@ -19,4 +19,4 @@
 
 julia&gt; img_n = poisson(img_b, 300);
 
-julia&gt; @time res = richardson_lucy_iterative(img_n, psf);</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/roflmaostc/DeconvOptim.jl/blob/23b0f5c5d7883443d5eb6e31ae767af5e7c3c2f6/src/lucy_richardson.jl#L3-L32">source</a></section></details></article><h2 id="More-generic-alternative"><a class="docs-heading-anchor" href="#More-generic-alternative">More generic alternative</a><a id="More-generic-alternative-1"></a><a class="docs-heading-anchor-permalink" href="#More-generic-alternative" title="Permalink"></a></h2><article><details class="docstring" open="true"><summary id="DeconvOptim.invert"><a class="docstring-binding" href="#DeconvOptim.invert"><code>DeconvOptim.invert</code></a> — <span class="docstring-category">Function</span></summary><section><div><pre><code class="language-julia hljs">invert(measured, rec0, forward; &lt;keyword arguments&gt;)</code></pre><p>Tries to invert the <code>forward</code> model. <code>forward</code> is a function taking  an input with the shape of <code>rec0</code> and returns an object which has the  same shape as <code>measured</code></p><p>Multiple keyword arguments can be specified for different loss functions, regularizers and mappings.</p><p><strong>Arguments</strong></p><ul><li><code>loss=Poisson()</code>: the loss function being compatible to compare with <code>measured</code>.</li><li><code>regularizer=nothing</code>: A regularizer function, same form as <code>loss</code>.</li><li><code>λ=0.05</code>: A float indicating the total weighting of the regularizer with    respect to the global loss function</li><li><code>mapping=Non_negative()</code>: Applies a mapping of the optimizer weight. Default is a              parabola which achieves a non-negativity constraint.</li><li><code>iterations=nothing</code>: Specifies a number of iterations after the optimization.   definitely should stop. Will be overwritten if <code>opt_options</code> is provided. Default: 20</li><li><code>opt_package=Opt_Optim</code>: decides which backend for the optimizer is used.</li><li><code>opt=LBFGS()</code>: The chosen optimizer which must fit to <code>opt_package</code>. </li><li><code>opt_options=nothing</code>: Can be a options file required by Optim.jl. Will overwrite iterations.</li><li><code>debug_f=nothing</code>: A debug function which must take a single argument, the current reconstruction. </li></ul></div><a class="docs-sourcelink" target="_blank" href="https://github.com/roflmaostc/DeconvOptim.jl/blob/23b0f5c5d7883443d5eb6e31ae767af5e7c3c2f6/src/generic_invert.jl#L7-L30">source</a></section></details></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../background/regularizer/">« Regularizer</a><a class="docs-footer-nextpage" href="../loss/">Loss Functions »</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 1.16.1 on <span class="colophon-date" title="Monday 1 December 2025 14:15">Monday 1 December 2025</span>. Using Julia version 1.12.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+julia&gt; @time res = richardson_lucy_iterative(img_n, psf);</code></pre></div><a class="docs-sourcelink" target="_blank" href="https://github.com/roflmaostc/DeconvOptim.jl/blob/310f154be230dde8d2330b59cc54821772d3f084/src/lucy_richardson.jl#L3-L32">source</a></section></details></article><h2 id="More-generic-alternative"><a class="docs-heading-anchor" href="#More-generic-alternative">More generic alternative</a><a id="More-generic-alternative-1"></a><a class="docs-heading-anchor-permalink" href="#More-generic-alternative" title="Permalink"></a></h2><article><details class="docstring" open="true"><summary id="DeconvOptim.invert"><a class="docstring-binding" href="#DeconvOptim.invert"><code>DeconvOptim.invert</code></a> — <span class="docstring-category">Function</span></summary><section><div><pre><code class="language-julia hljs">invert(measured, rec0, forward; &lt;keyword arguments&gt;)</code></pre><p>Tries to invert the <code>forward</code> model. <code>forward</code> is a function taking  an input with the shape of <code>rec0</code> and returns an object which has the  same shape as <code>measured</code></p><p>Multiple keyword arguments can be specified for different loss functions, regularizers and mappings.</p><p><strong>Arguments</strong></p><ul><li><code>loss=Poisson()</code>: the loss function being compatible to compare with <code>measured</code>.</li><li><code>regularizer=nothing</code>: A regularizer function, same form as <code>loss</code>.</li><li><code>λ=0.05</code>: A float indicating the total weighting of the regularizer with    respect to the global loss function</li><li><code>mapping=Non_negative()</code>: Applies a mapping of the optimizer weight. Default is a              parabola which achieves a non-negativity constraint.</li><li><code>iterations=nothing</code>: Specifies a number of iterations after the optimization.   definitely should stop. Will be overwritten if <code>opt_options</code> is provided. Default: 20</li><li><code>opt_package=Opt_Optim</code>: decides which backend for the optimizer is used.</li><li><code>opt=LBFGS()</code>: The chosen optimizer which must fit to <code>opt_package</code>. </li><li><code>opt_options=nothing</code>: Can be a options file required by Optim.jl. Will overwrite iterations.</li><li><code>debug_f=nothing</code>: A debug function which must take a single argument, the current reconstruction. </li></ul></div><a class="docs-sourcelink" target="_blank" href="https://github.com/roflmaostc/DeconvOptim.jl/blob/310f154be230dde8d2330b59cc54821772d3f084/src/generic_invert.jl#L7-L30">source</a></section></details></article></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../background/regularizer/">« Regularizer</a><a class="docs-footer-nextpage" href="../loss/">Loss Functions »</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 1.16.1 on <span class="colophon-date" title="Monday 1 December 2025 14:33">Monday 1 December 2025</span>. Using Julia version 1.12.2.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>