build based on 8ceffc6

previews/PR175/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.10.1","generation_timestamp":"2024-02-26T14:20:49","documenter_version":"1.2.1"}}
+{"documenter":{"julia_version":"1.10.1","generation_timestamp":"2024-02-26T14:48:44","documenter_version":"1.2.1"}}

previews/PR175/HowTo/custom_solvers/index.html

@@ -18,4 +18,4 @@
 m = Unfold.fit(UnfoldModel, designDict, evts,dat_3d; solver=b2b_solver)
 results = coeftable(m)
 
-plot_erp(results)</code></pre><p>These are the decoding-results for <code>conditionA</code> while taking into account <code>conditionB</code> - and vice versa. </p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../standarderrors/">« Standard errors</a><a class="docs-footer-nextpage" href="../../generated/HowTo/juliacall_unfold/">🐍 Calling Unfold.jl directly from Python »</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="Monday 26 February 2024 14:20">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+plot_erp(results)</code></pre><p>These are the decoding-results for <code>conditionA</code> while taking into account <code>conditionB</code> - and vice versa. </p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../standarderrors/">« Standard errors</a><a class="docs-footer-nextpage" href="../../generated/HowTo/juliacall_unfold/">🐍 Calling Unfold.jl directly from Python »</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="Monday 26 February 2024 14:48">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR175/HowTo/lmm_pvalues/index.html

@@ -100,4 +100,4 @@
 scatter(f[2,1],times,df.walds)
 scatter(f[2,2],times,df.lrt)
 
-f</code></pre><img src="64397379.png" alt="Example block output"/><p>Look pretty similar! note that the Walds-T is typically too liberal (LRT also, but to a lesser exted). Best is to use the forthcoming MixedModelsPermutations.jl or go the route via R and use KenwardRoger (data not yet published)</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../generated/HowTo/juliacall_unfold/">« 🐍 Calling Unfold.jl directly from Python</a><a class="docs-footer-nextpage" href="../../generated/HowTo/effects/">Marginal effects (focus on non-linear predictors) »</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="Monday 26 February 2024 14:20">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+f</code></pre><img src="64397379.png" alt="Example block output"/><p>Look pretty similar! note that the Walds-T is typically too liberal (LRT also, but to a lesser exted). Best is to use the forthcoming MixedModelsPermutations.jl or go the route via R and use KenwardRoger (data not yet published)</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../generated/HowTo/juliacall_unfold/">« 🐍 Calling Unfold.jl directly from Python</a><a class="docs-footer-nextpage" href="../../generated/HowTo/effects/">Marginal effects (focus on non-linear predictors) »</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="Monday 26 February 2024 14:48">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR175/HowTo/multiple_events/index.html

@@ -24,4 +24,4 @@
   "eventA" => (0 ~ 1, name: stimulusA…
   &quot;eventB&quot; =&gt; (0 ~ 1, name: stimulusB…</code></pre><p>Finally, fitting &amp; plotting works the same way as always</p><pre><code class="language-julia hljs">m = Unfold.fit(UnfoldModel,bfDict,evts,dat,solver=(x,y) -&gt; Unfold.solver_default(x,y;stderror=true),eventcolumn=&quot;type&quot;)
 results = coeftable(m)
-plot_erp(results;stderror=true,mapping=(;col=:group))</code></pre><img src="3d2674ad.png" alt="Example block output"/></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../tutorials/lmm_overlap/">« LMM + overlap correction</a><a class="docs-footer-nextpage" href="../pymne/">Import EEG with 🐍 PyMNE.jl »</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="Monday 26 February 2024 14:20">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+plot_erp(results;stderror=true,mapping=(;col=:group))</code></pre><img src="3d2674ad.png" alt="Example block output"/></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../tutorials/lmm_overlap/">« LMM + overlap correction</a><a class="docs-footer-nextpage" href="../pymne/">Import EEG with 🐍 PyMNE.jl »</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="Monday 26 February 2024 14:48">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR175/HowTo/pymne/index.html

@@ -17,4 +17,4 @@
 rename!(events,2=>:coherence) # negative signs in formulas are not good ;)
 events.face = string.(events.face) # ugly names, but fast
 </code></pre><p>Next fit an Unfold Model</p><pre><code class="language- hljs">uf = fit(UnfoldModel,Dict(Any=&gt;(@formula(0~face+coherence),Float64.(limo_epochs.times))),events,data)
-results = coeftable(uf)</code></pre><pre><code class="language- hljs">plot_results(results)</code></pre><h3 id="Read-some-of-your-own-data"><a class="docs-heading-anchor" href="#Read-some-of-your-own-data">Read some of your own data</a><a id="Read-some-of-your-own-data-1"></a><a class="docs-heading-anchor-permalink" href="#Read-some-of-your-own-data" title="Permalink"></a></h3><p>We can make use of all PyMNE importer functions to load the data. Try it for your own data! Get starting with Unfold in no-time!</p><pre><code class="language- hljs">#eeglabdata = PyMNE.io.read_raw_eeglab(&quot;pathToEEGLabSet.set&quot;)</code></pre><h3 id="Contribute?"><a class="docs-heading-anchor" href="#Contribute?">Contribute?</a><a id="Contribute?-1"></a><a class="docs-heading-anchor-permalink" href="#Contribute?" title="Permalink"></a></h3><p>Some extra conversions are needed to import the data from PyMNE to Unfold (as shown above). We could try putting these in a wrapper function - do you want to tackle this challenge? Would be a great first contribution to the toolbox :-)</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../multiple_events/">« Overlap: Multiple events</a><a class="docs-footer-nextpage" href="../standarderrors/">Standard errors »</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="Monday 26 February 2024 14:20">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+results = coeftable(uf)</code></pre><pre><code class="language- hljs">plot_results(results)</code></pre><h3 id="Read-some-of-your-own-data"><a class="docs-heading-anchor" href="#Read-some-of-your-own-data">Read some of your own data</a><a id="Read-some-of-your-own-data-1"></a><a class="docs-heading-anchor-permalink" href="#Read-some-of-your-own-data" title="Permalink"></a></h3><p>We can make use of all PyMNE importer functions to load the data. Try it for your own data! Get starting with Unfold in no-time!</p><pre><code class="language- hljs">#eeglabdata = PyMNE.io.read_raw_eeglab(&quot;pathToEEGLabSet.set&quot;)</code></pre><h3 id="Contribute?"><a class="docs-heading-anchor" href="#Contribute?">Contribute?</a><a id="Contribute?-1"></a><a class="docs-heading-anchor-permalink" href="#Contribute?" title="Permalink"></a></h3><p>Some extra conversions are needed to import the data from PyMNE to Unfold (as shown above). We could try putting these in a wrapper function - do you want to tackle this challenge? Would be a great first contribution to the toolbox :-)</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../multiple_events/">« Overlap: Multiple events</a><a class="docs-footer-nextpage" href="../standarderrors/">Standard errors »</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="Monday 26 February 2024 14:48">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

previews/PR175/HowTo/standarderrors/index.html

@@ -9,4 +9,4 @@
 </code></pre><p>Similar to @Ref(custom_solver), it is possible to specify a solver than also calculates the standard errors of the (single-subject) estimates.</p><pre><code class="language- hljs">se_solver =(x,y)-&gt;Unfold.solver_default(x,y,stderror=true)
 m = Unfold.fit(UnfoldModel,designDict,evts,dat,solver=se_solver)
 results =coeftable(m)
-plot_erp(results;stderror=true)</code></pre><div class="admonition is-warning"><header class="admonition-header">Warning</header><div class="admonition-body"><p><strong>In case of overlap-correction:</strong> Use single-subject SE on your own risk. Because EEG data are autocorrelated your standarderrors will be typically too small.</p></div></div></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../pymne/">« Import EEG with 🐍 PyMNE.jl</a><a class="docs-footer-nextpage" href="../custom_solvers/">Alternative Solvers (Robust, GPU, B2B) »</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="Monday 26 February 2024 14:20">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+plot_erp(results;stderror=true)</code></pre><div class="admonition is-warning"><header class="admonition-header">Warning</header><div class="admonition-body"><p><strong>In case of overlap-correction:</strong> Use single-subject SE on your own risk. Because EEG data are autocorrelated your standarderrors will be typically too small.</p></div></div></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../pymne/">« Import EEG with 🐍 PyMNE.jl</a><a class="docs-footer-nextpage" href="../custom_solvers/">Alternative Solvers (Robust, GPU, B2B) »</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="Monday 26 February 2024 14:48">Monday 26 February 2024</span>. Using Julia version 1.10.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>