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<h1 class="title">Bilan semaine 20 2025 : 12 mai - 16 mai</h1>
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<div class="quarto-categories">
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<div class="quarto-category">colBiSBM</div>
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<div class="quarto-category">inférence</div>
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<div class="quarto-category">GNN</div>
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<div class="quarto-title-meta-heading">Auteur·rice</div>
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<div class="quarto-title-meta-heading">Affiliation</div>
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<p class="author">Louis Lacoste <a href="mailto:louis.lacoste@agroparistech.fr" class="quarto-title-author-email"><i class="bi bi-envelope"></i></a> <a href="https://orcid.org/0009-0004-0178-9821" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
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</div>
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<div class="quarto-title-meta-contents">
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<p class="affiliation">
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MIA Paris-Saclay, INRAE, AgroParisTech, Université Paris-Saclay
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</p>
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<div class="quarto-title-meta-heading">Date de publication</div>
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<p class="date">16 mai 2025</p>
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<div class="quarto-title-meta-heading">Modifié</div>
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<p class="date-modified">10 février 2026</p>
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<h2 id="toc-title">Sur cette page</h2>
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<ul>
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<li><a href="#top-priorité" id="toc-top-priorité" class="nav-link active" data-scroll-target="#top-priorité">TOP PRIORITÉ</a>
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<ul class="collapse">
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<li><a href="#présentations-lsd-jds-et-mlaussois" id="toc-présentations-lsd-jds-et-mlaussois" class="nav-link" data-scroll-target="#présentations-lsd-jds-et-mlaussois">Présentations LSD, JdS et ML@Aussois</a></li>
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<li><a href="#applications" id="toc-applications" class="nav-link" data-scroll-target="#applications">Applications</a></li>
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<li><a href="#inférence-et-microbes" id="toc-inférence-et-microbes" class="nav-link" data-scroll-target="#inférence-et-microbes">Inférence et microbes</a></li>
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</ul></li>
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<li><a href="#a-discuter" id="toc-a-discuter" class="nav-link" data-scroll-target="#a-discuter">A discuter</a></li>
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<li><a href="#a-faire" id="toc-a-faire" class="nav-link" data-scroll-target="#a-faire">A faire</a>
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<li><a href="#inférence" id="toc-inférence" class="nav-link" data-scroll-target="#inférence">Inférence</a></li>
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<li><a href="#rédaction-article" id="toc-rédaction-article" class="nav-link" data-scroll-target="#rédaction-article">Rédaction article</a></li>
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<li><a href="#jai-fait" id="toc-jai-fait" class="nav-link" data-scroll-target="#jai-fait">J’ai fait</a>
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<li><a href="#présentations-lsd-jds-et-mlaussois-1" id="toc-présentations-lsd-jds-et-mlaussois-1" class="nav-link" data-scroll-target="#présentations-lsd-jds-et-mlaussois-1">Présentations LSD, JdS et ML@Aussois</a></li>
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<li><a href="#vgae" id="toc-vgae" class="nav-link" data-scroll-target="#vgae">VGAE</a></li>
|
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<li><a href="#inférence-et-microbes-1" id="toc-inférence-et-microbes-1" class="nav-link" data-scroll-target="#inférence-et-microbes-1">Inférence et microbes</a></li>
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<li><a href="#applications-1" id="toc-applications-1" class="nav-link" data-scroll-target="#applications-1">Applications</a></li>
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<li><a href="#axe-inférence" id="toc-axe-inférence" class="nav-link" data-scroll-target="#axe-inférence">Axe inférence</a></li>
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</ul></li>
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<li><a href="#repoussés-ou-abandonnés" id="toc-repoussés-ou-abandonnés" class="nav-link" data-scroll-target="#repoussés-ou-abandonnés">Repoussés ou abandonnés</a></li>
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<section id="top-priorité" class="level2">
|
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<h2 class="anchored" data-anchor-id="top-priorité">TOP PRIORITÉ</h2>
|
||
<ul>
|
||
<li><p>Pour clustering de collections sur données réelles :</p>
|
||
<ul>
|
||
<li><del>Relâcher la pénalité pour les coupes pour proposer modèles.</del></li>
|
||
</ul>
|
||
<p>→ L’intuition de Pierre semble être confirmé, les dissimilarités semblent arrêter de varier sensiblement pour de grandes valeurs <span class="math inline">(Q_1,Q_2)</span>.</p>
|
||
<ul>
|
||
<li>Faire le <code>hclust</code> avec diverses distances et voir si les coupes proposées diffèrent sensiblement</li>
|
||
<li>Si plusieurs clustering possibles les tester et sélectionner le meilleur</li>
|
||
<li>Ré-ajuster les bonnes partitions.</li>
|
||
</ul></li>
|
||
<li><p>Données simulées tester diverses distances.</p></li>
|
||
<li><p>Dé-bugger les simulations :</p>
|
||
<ul>
|
||
<li>Inférence : Relancer simus d’inférence avec n = 240 pour voir si la qualité augmenter (se rassurer). En fait on est déjà à 240, j’ai relancé avec M = 4 au lieu de M = 2. En attente résultats MIGALE -> BUG, dois creuser mais juste des problèmes techniques -> Visiblement il y a d’autres problèmes que juste le plan de parallélisation.</li>
|
||
</ul></li>
|
||
<li><p>Vérifier si problème de version tidyverse pour vapply sur l’<strong>inférence</strong>.</p></li>
|
||
<li><p>Si problème de parallélisation vient de pb de version <em>future.callr</em> le signaler à MIGALE.</p></li>
|
||
</ul>
|
||
<section id="présentations-lsd-jds-et-mlaussois" class="level3">
|
||
<h3 class="anchored" data-anchor-id="présentations-lsd-jds-et-mlaussois">Présentations LSD, JdS et ML@Aussois</h3>
|
||
<ul>
|
||
<li><del>PRÉSENTATION JDS (LSD), durée introuvable, adapter en anglais les slides</del> et voir avec PB et SD.</li>
|
||
<li>Quel plan ?</li>
|
||
<li>Quels résultats ? Baldock, Traveset … (sub-Doré)</li>
|
||
<li>Pas la peine de préciser l’algo de clustering</li>
|
||
<li>Indiquer sur une slide le problème de support pour <span class="math inline">\pi\rho</span> à faire s’il y a le temps.</li>
|
||
<li>Résultats sur les réseaux Baldock, regarder le positionnement par bloc des espèces communes, regarder les probas d’appartenance aux blocs par espèces communes et par réseau.</li>
|
||
</ul>
|
||
</section>
|
||
<section id="applications" class="level3">
|
||
<h3 class="anchored" data-anchor-id="applications">Applications</h3>
|
||
<ul>
|
||
<li>Kmeans sur la densité des réseaux subdoré pour pré-partitionner et <em>clusteriser</em>. Car densités déséquilibrées.</li>
|
||
</ul>
|
||
<div id="ref-kmeans-vae" class="quarto-float quarto-figure quarto-figure-center anchored">
|
||
<figure class="quarto-float quarto-float-ref figure">
|
||
<div aria-describedby="ref-kmeans-vae-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
|
||
<ul>
|
||
<li>Faire GNN-VAE Doré et sub-Doré avec kmeans et clustering sur l’espace latent J’ai commencé à regarder un peu</li>
|
||
</ul>
|
||
</div>
|
||
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-ref quarto-uncaptioned" id="ref-kmeans-vae-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
|
||
Reference 1
|
||
</figcaption>
|
||
</figure>
|
||
</div>
|
||
</section>
|
||
<section id="inférence-et-microbes" class="level3">
|
||
<h3 class="anchored" data-anchor-id="inférence-et-microbes">Inférence et microbes</h3>
|
||
<ul>
|
||
<li>Lancer <em>colBiSBM</em> sur <span class="math inline">OTU\times Sample</span></li>
|
||
<li>Se renseigner techniques d’inférence de réseaux :
|
||
<ul>
|
||
<li>covariance (base corrélation et seuil)</li>
|
||
<li>GraphicalLASSO</li>
|
||
<li>Co-occurence</li>
|
||
</ul></li>
|
||
<li>Lancer <em>colSBM</em> sur <span class="math inline">OTU\times OTU</span></li>
|
||
<li>Creuser <a href="https://raw.githubusercontent.com/cregouby/R-toulouse-tabnet/main/Tabnet_RR2023_fr_pdf.pdf">TabNet</a> de Christophe Regouby et les <a href="https://github.com/cregouby/Tutoriel_torch">exercices</a></li>
|
||
<li>Regarder <strong>SPARTA</strong> Rennes</li>
|
||
<li>Lire Papiers compositional data (Aitchison et al. intro)</li>
|
||
<li>Lire article multi-niveaux Saint-Clair</li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
<section id="a-discuter" class="level2">
|
||
<h2 class="anchored" data-anchor-id="a-discuter">A discuter</h2>
|
||
</section>
|
||
<section id="a-faire" class="level2">
|
||
<h2 class="anchored" data-anchor-id="a-faire">A faire</h2>
|
||
<section id="inférence" class="level3">
|
||
<h3 class="anchored" data-anchor-id="inférence">Inférence</h3>
|
||
<ul>
|
||
<li>Papier pour comprendre données
|
||
<ul>
|
||
<li><del>Faust et al.</del></li>
|
||
<li>Abdill et al.</li>
|
||
<li>Bashan et al.</li>
|
||
</ul></li>
|
||
<li>pbs : variance, bcp de zero, covariables, offset et taxonomie (Reseaux arretes differents niveaux : Genre, OTU …)</li>
|
||
</ul>
|
||
<blockquote class="blockquote">
|
||
<p>Combine networks at different taxonomic levels</p>
|
||
</blockquote>
|
||
<ul>
|
||
<li>Inférence + GREMLINS</li>
|
||
</ul>
|
||
</section>
|
||
<section id="rédaction-article" class="level3">
|
||
<h3 class="anchored" data-anchor-id="rédaction-article">Rédaction article</h3>
|
||
<ul>
|
||
<li>Relire intro St Clair</li>
|
||
<li>S’inspirer structure pour mon intro</li>
|
||
<li>Trouver biblio intro</li>
|
||
<li>Rédiger l’intro</li>
|
||
<li>Dire résultats nettement meilleurs et variabilités inférieures.</li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
<section id="jai-fait" class="level2">
|
||
<h2 class="anchored" data-anchor-id="jai-fait">J’ai fait</h2>
|
||
<ul>
|
||
<li><p>Dé-bugger les simulations :</p>
|
||
<ul>
|
||
<li>Clustering : Relancer simulations de clustering avec <span class="math inline">M = 30</span> où <span class="math inline">M_i = 10, \forall i</span>. En attente retour MIGALE Relancer simus clustering avec VEM steps = 10 000 et plus nombreux init pour spectral. Ajouter simu clustering métriques nb sous-collections obtenues. Vérifier les résultats obtenus si ARI = 0. Et augmenter la taille <span class="math inline">M = 30</span> avec <span class="math inline">M_1 = M_2 = M_3 = 10</span>. <del>-> BUG, dois creuser mais juste des problèmes techniques.</del> Le bug venait probablement d’une inadéquation entre la version de <em>future</em> et <em>future.callr</em>, les résultats temporaires sont encourageants. <strong>J’ai mis les résultats dans l’article</strong>.</li>
|
||
</ul></li>
|
||
</ul>
|
||
<section id="présentations-lsd-jds-et-mlaussois-1" class="level3">
|
||
<h3 class="anchored" data-anchor-id="présentations-lsd-jds-et-mlaussois-1">Présentations LSD, JdS et ML@Aussois</h3>
|
||
<ul>
|
||
<li><p><del>PRÉSENTATION JDS (LSD), durée introuvable, adapter en anglais les slides</del> et voir avec PB et SD.</p></li>
|
||
<li><p>Quel plan ?</p></li>
|
||
<li><p>Quels résultats ? Baldock, Traveset … (sub-Doré)</p></li>
|
||
<li><p>Mettre le détails des formules et des algos pour VE et sélection de modèle en annexe.</p></li>
|
||
<li><p>Préciser simplement que l’on utilise un algo VE et un critère type BIC.</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="vgae" class="level3">
|
||
<h3 class="anchored" data-anchor-id="vgae">VGAE</h3>
|
||
<ul>
|
||
<li><del>Dé-bugger pourquoi <code>BipartiteInnerProductDecoder.forward() -> NaN</code></del> -> <strong>C’était parce que les features en entrée n’était pas normalisée par les couches de convolutions</strong>. Les meilleurs résultats d’AUC et de précisions que j’obtiens par VGAE sont autour de 0.80.</li>
|
||
</ul>
|
||
</section>
|
||
<section id="inférence-et-microbes-1" class="level3">
|
||
<h3 class="anchored" data-anchor-id="inférence-et-microbes-1">Inférence et microbes</h3>
|
||
<ul>
|
||
<li>Human Gut Compendium télécharger et préparé les données. Mises au format <code>edgelist</code> et liste de matrices et extrait les infos supplémentaires. → trop lourd en RAM pour tourner sur machine perso (optim colSBM…) ## A continuer</li>
|
||
</ul>
|
||
</section>
|
||
<section id="applications-1" class="level3">
|
||
<h3 class="anchored" data-anchor-id="applications-1">Applications</h3>
|
||
<ul>
|
||
<li>Idée Sophie: Regarder clustering de données plantes-pollinisateur selon gradient d’urbanisation</li>
|
||
</ul>
|
||
<blockquote class="blockquote">
|
||
<p>Sophie a fait une appli qui marche bien et va dans le sens de l’analyse faite (à savoir pas d’effet du gradien d’urbanisation). À continuer pour l’intégrer dans l’article !</p>
|
||
</blockquote>
|
||
</section>
|
||
<section id="axe-inférence" class="level3">
|
||
<h3 class="anchored" data-anchor-id="axe-inférence">Axe inférence</h3>
|
||
<ul>
|
||
<li>Lire biblio fournie Julie, Inférence de réseaux : co-occurence</li>
|
||
</ul>
|
||
<blockquote class="blockquote">
|
||
<p>J’ai lu Faust et al. Je lis Abdill et al.</p>
|
||
</blockquote>
|
||
</section>
|
||
</section>
|
||
<section id="repoussés-ou-abandonnés" class="level2">
|
||
<h2 class="anchored" data-anchor-id="repoussés-ou-abandonnés">Repoussés ou abandonnés</h2>
|
||
<div class="callout callout-style-default callout-note callout-titled">
|
||
<div class="callout-header d-flex align-content-center" data-bs-toggle="collapse" data-bs-target=".callout-1-contents" aria-controls="callout-1" aria-expanded="false" aria-label="Toggle callout">
|
||
<div class="callout-icon-container">
|
||
<i class="callout-icon"></i>
|
||
</div>
|
||
<div class="callout-title-container flex-fill">
|
||
Déplier pour voir
|
||
</div>
|
||
<div class="callout-btn-toggle d-inline-block border-0 py-1 ps-1 pe-0 float-end"><i class="callout-toggle"></i></div>
|
||
</div>
|
||
<div id="callout-1" class="callout-1-contents callout-collapse collapse">
|
||
<div class="callout-body-container callout-body">
|
||
<ul>
|
||
<li>Résultats simus NA <strong>Erreur pour certaines conditions</strong> : Pour NA robustness générer <code>nb_rep</code> collections de taille <span class="math inline">M=2</span> et prélever <span class="math inline">\epsilon_{max}n_r n_c</span> liens à retirer puis pour les <span class="math inline">\epsilon < \epsilon_{max}</span> prélever dans la liste des indices afin d’avoir des perturbations emboitées. Il faut que j’ajoute un mécanisme pour reprendre des conditions qui ont plantés et que je skip dans le future_lapply les conditions déjà traitées (pour avoir la même seed quand je vais exécuter le code). Implémenté les missing steps.</li>
|
||
</ul>
|
||
<blockquote class="blockquote">
|
||
<p>Je n’arrive pas à comprendre les erreurs qui arrivent</p>
|
||
</blockquote>
|
||
<ul>
|
||
<li><p>Lire Biological Networks - François Képès</p></li>
|
||
<li><p>Regarder les applications pour les collections de réseaux recommender system <em>Pas pertinents et trop gros</em></p></li>
|
||
</ul>
|
||
<div id="lst-reco-systems" class="listing quarto-float quarto-figure quarto-figure-left anchored">
|
||
<figure class="quarto-float quarto-float-lst figure">
|
||
<figcaption class="quarto-float-caption-top quarto-float-caption quarto-float-lst" id="lst-reco-systems-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
|
||
Listing 1: Recommender systems data
|
||
</figcaption>
|
||
<div aria-describedby="lst-reco-systems-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
|
||
<p>Par exemple :</p>
|
||
<ul>
|
||
<li><a href="https://cseweb.ucsd.edu/~jmcauley/datasets.html">Liste de recommendation data</a></li>
|
||
</ul>
|
||
</div>
|
||
</figure>
|
||
</div>
|
||
<section id="papier-plus-multi-applications" class="level3">
|
||
<h3 class="anchored" data-anchor-id="papier-plus-multi-applications">Papier plus multi-applications</h3>
|
||
<ul>
|
||
<li>Données d’Elisa herbivore ?</li>
|
||
<li>Données urbanisations ?</li>
|
||
</ul>
|
||
</section>
|
||
<section id="autour-de-larticle-et-du-package" class="level3">
|
||
<h3 class="anchored" data-anchor-id="autour-de-larticle-et-du-package">Autour de l’article et du package</h3>
|
||
<ul>
|
||
<li>Créer des vignettes illustrant par exemple des cas de simulations. <strong>Possible de mettre l’exemple d’application de Sophie sur les réseaux avec gradient d’urbanisation</strong>.</li>
|
||
</ul>
|
||
</section>
|
||
<section id="simulations-article" class="level3">
|
||
<h3 class="anchored" data-anchor-id="simulations-article">Simulations article</h3>
|
||
<ul>
|
||
<li><p>Comparer sur clustering unipartite avec versions symétriser des par blocs des matrices d’adjacences.</p></li>
|
||
<li><p>Corriger structure de simus :</p>
|
||
<ul>
|
||
<li>Pour noisy <span class="math inline">\alpha</span> :
|
||
<ul>
|
||
<li>Logit pour envoyer la gaussienne vers (0,1)</li>
|
||
<li>Beta contrainte dans (0,1)</li>
|
||
</ul></li>
|
||
<li>Pour noisy links : Générer <code>nb_clustering</code> collections de taille M puis prélever <span class="math inline">\epsilon_{max}n_r n_c</span> liens à inverser puis pour les <span class="math inline">\epsilon < \epsilon_{max}</span> prélever dans la liste des indices afin d’avoir des perturbations emboitées.</li>
|
||
</ul></li>
|
||
</ul>
|
||
</section>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
|
||
</section>
|
||
|
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// remove the first header
|
||
if (note.children.length > 0 && note.children[0].tagName === "HEADER") {
|
||
note.children[0].remove();
|
||
}
|
||
const html = processXRef(null, note);
|
||
instance.setContent(html);
|
||
}
|
||
}).finally(() => {
|
||
instance.enable();
|
||
instance.show();
|
||
});
|
||
}
|
||
}, function(instance) {
|
||
});
|
||
}
|
||
let selectedAnnoteEl;
|
||
const selectorForAnnotation = ( cell, annotation) => {
|
||
let cellAttr = 'data-code-cell="' + cell + '"';
|
||
let lineAttr = 'data-code-annotation="' + annotation + '"';
|
||
const selector = 'span[' + cellAttr + '][' + lineAttr + ']';
|
||
return selector;
|
||
}
|
||
const selectCodeLines = (annoteEl) => {
|
||
const doc = window.document;
|
||
const targetCell = annoteEl.getAttribute("data-target-cell");
|
||
const targetAnnotation = annoteEl.getAttribute("data-target-annotation");
|
||
const annoteSpan = window.document.querySelector(selectorForAnnotation(targetCell, targetAnnotation));
|
||
const lines = annoteSpan.getAttribute("data-code-lines").split(",");
|
||
const lineIds = lines.map((line) => {
|
||
return targetCell + "-" + line;
|
||
})
|
||
let top = null;
|
||
let height = null;
|
||
let parent = null;
|
||
if (lineIds.length > 0) {
|
||
//compute the position of the single el (top and bottom and make a div)
|
||
const el = window.document.getElementById(lineIds[0]);
|
||
top = el.offsetTop;
|
||
height = el.offsetHeight;
|
||
parent = el.parentElement.parentElement;
|
||
if (lineIds.length > 1) {
|
||
const lastEl = window.document.getElementById(lineIds[lineIds.length - 1]);
|
||
const bottom = lastEl.offsetTop + lastEl.offsetHeight;
|
||
height = bottom - top;
|
||
}
|
||
if (top !== null && height !== null && parent !== null) {
|
||
// cook up a div (if necessary) and position it
|
||
let div = window.document.getElementById("code-annotation-line-highlight");
|
||
if (div === null) {
|
||
div = window.document.createElement("div");
|
||
div.setAttribute("id", "code-annotation-line-highlight");
|
||
div.style.position = 'absolute';
|
||
parent.appendChild(div);
|
||
}
|
||
div.style.top = top - 2 + "px";
|
||
div.style.height = height + 4 + "px";
|
||
div.style.left = 0;
|
||
let gutterDiv = window.document.getElementById("code-annotation-line-highlight-gutter");
|
||
if (gutterDiv === null) {
|
||
gutterDiv = window.document.createElement("div");
|
||
gutterDiv.setAttribute("id", "code-annotation-line-highlight-gutter");
|
||
gutterDiv.style.position = 'absolute';
|
||
const codeCell = window.document.getElementById(targetCell);
|
||
const gutter = codeCell.querySelector('.code-annotation-gutter');
|
||
gutter.appendChild(gutterDiv);
|
||
}
|
||
gutterDiv.style.top = top - 2 + "px";
|
||
gutterDiv.style.height = height + 4 + "px";
|
||
}
|
||
selectedAnnoteEl = annoteEl;
|
||
}
|
||
};
|
||
const unselectCodeLines = () => {
|
||
const elementsIds = ["code-annotation-line-highlight", "code-annotation-line-highlight-gutter"];
|
||
elementsIds.forEach((elId) => {
|
||
const div = window.document.getElementById(elId);
|
||
if (div) {
|
||
div.remove();
|
||
}
|
||
});
|
||
selectedAnnoteEl = undefined;
|
||
};
|
||
// Handle positioning of the toggle
|
||
window.addEventListener(
|
||
"resize",
|
||
throttle(() => {
|
||
elRect = undefined;
|
||
if (selectedAnnoteEl) {
|
||
selectCodeLines(selectedAnnoteEl);
|
||
}
|
||
}, 10)
|
||
);
|
||
function throttle(fn, ms) {
|
||
let throttle = false;
|
||
let timer;
|
||
return (...args) => {
|
||
if(!throttle) { // first call gets through
|
||
fn.apply(this, args);
|
||
throttle = true;
|
||
} else { // all the others get throttled
|
||
if(timer) clearTimeout(timer); // cancel #2
|
||
timer = setTimeout(() => {
|
||
fn.apply(this, args);
|
||
timer = throttle = false;
|
||
}, ms);
|
||
}
|
||
};
|
||
}
|
||
// Attach click handler to the DT
|
||
const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');
|
||
for (const annoteDlNode of annoteDls) {
|
||
annoteDlNode.addEventListener('click', (event) => {
|
||
const clickedEl = event.target;
|
||
if (clickedEl !== selectedAnnoteEl) {
|
||
unselectCodeLines();
|
||
const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active');
|
||
if (activeEl) {
|
||
activeEl.classList.remove('code-annotation-active');
|
||
}
|
||
selectCodeLines(clickedEl);
|
||
clickedEl.classList.add('code-annotation-active');
|
||
} else {
|
||
// Unselect the line
|
||
unselectCodeLines();
|
||
clickedEl.classList.remove('code-annotation-active');
|
||
}
|
||
});
|
||
}
|
||
const findCites = (el) => {
|
||
const parentEl = el.parentElement;
|
||
if (parentEl) {
|
||
const cites = parentEl.dataset.cites;
|
||
if (cites) {
|
||
return {
|
||
el,
|
||
cites: cites.split(' ')
|
||
};
|
||
} else {
|
||
return findCites(el.parentElement)
|
||
}
|
||
} else {
|
||
return undefined;
|
||
}
|
||
};
|
||
var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
|
||
for (var i=0; i<bibliorefs.length; i++) {
|
||
const ref = bibliorefs[i];
|
||
const citeInfo = findCites(ref);
|
||
if (citeInfo) {
|
||
tippyHover(citeInfo.el, function() {
|
||
var popup = window.document.createElement('div');
|
||
citeInfo.cites.forEach(function(cite) {
|
||
var citeDiv = window.document.createElement('div');
|
||
citeDiv.classList.add('hanging-indent');
|
||
citeDiv.classList.add('csl-entry');
|
||
var biblioDiv = window.document.getElementById('ref-' + cite);
|
||
if (biblioDiv) {
|
||
citeDiv.innerHTML = biblioDiv.innerHTML;
|
||
}
|
||
popup.appendChild(citeDiv);
|
||
});
|
||
return popup.innerHTML;
|
||
});
|
||
}
|
||
}
|
||
});
|
||
</script>
|
||
</div> <!-- /content -->
|
||
|
||
|
||
|
||
|
||
</body></html> |