website rerender

.quarto/idx/index.qmd.json

@@ -1 +1 @@
-{"title":"Course overview","markdown":{"yaml":{"title":"Course overview","number-sections":false},"headingText":"Core aims","containsRefs":false,"markdown":"\n\nWelcome to the wonderful world of generalised linear models!\n\nThese sessions are intended to enable you to construct and use generalised linear models confidently.\n\nAs with all of our statistics courses our focus is not on mathematical derivations, but on developing an intuitive understanding of the underlying statistical concepts.\n\nAt the same time this is also *not* a \"how to mindlessly use a stats program\" course! We hope that at the end of this course you feel like you have a better grasp on what it is we're trying to do, and gained sufficient confidence in your coding skills to implement these statistical concepts in your own research!\n\n\nTo introduce sufficient understanding and coding experience for analysing data with non-continuous response variables.\n\n::: callout-note\n## Course aims\n\nTo know what to do when presented with an arbitrary data set e.g.\n\n1.  Construct\n    a.  a logistic model for binary response variables\n    b.  a logistic model for proportion response variables\n    c.  a Poisson model for count response variables\n    d.  ~~a Negative Binomial model for count response variables~~ (to be added later)\n2.  Plot the data and the fitted curve in each case for both continuous and categorical predictors\n3.  Assess the significance of fit\n4.  Assess assumption of the model\n:::\n"},"formats":{"courseformat-html":{"execute":{"fig-width":7,"fig-height":5,"fig-format":"retina","fig-dpi":96,"df-print":"default","error":false,"eval":true,"cache":null,"freeze":"auto","echo":true,"output":true,"warning":true,"include":true,"keep-md":false,"keep-ipynb":false,"ipynb":null,"enabled":null,"daemon":null,"daemon-restart":false,"debug":false,"ipynb-filters":[],"engine":"markdown"},"render":{"keep-tex":false,"keep-yaml":false,"keep-source":false,"keep-hidden":false,"prefer-html":false,"output-divs":true,"output-ext":"html","fig-align":"default","fig-pos":null,"fig-env":null,"code-fold":"none","code-overflow":"scroll","code-link":true,"code-line-numbers":false,"code-tools":false,"tbl-colwidths":"auto","merge-includes":true,"latex-auto-mk":true,"latex-auto-install":true,"latex-clean":true,"latex-max-runs":10,"latex-makeindex":"makeindex","latex-makeindex-opts":[],"latex-tlmgr-opts":[],"latex-input-paths":[],"latex-output-dir":null,"link-external-icon":false,"link-external-newwindow":false,"self-contained-math":false,"format-resources":[],"shortcodes":[]},"pandoc":{"standalone":true,"wrap":"none","default-image-extension":"png","to":"html","toc":true,"number-sections":false,"filters":[],"output-file":"index.html"},"language":{},"metadata":{"lang":"en","fig-responsive":true,"quarto-version":"1.2.134","theme":["default","_extensions/cambiotraining/courseformat/theme.scss"],"number-depth":3,"code-copy":true,"revealjs-plugins":[],"bibliography":["references.bib"],"knitr":{"opts_knit":{"cache.path":".knitr_cache"}},"title":"Course overview"},"extensions":{"book":{"multiFile":true}}}}}
+{"title":"Course overview","markdown":{"yaml":{"title":"Course overview","number-sections":false},"headingText":"Core aims","containsRefs":false,"markdown":"\n\nWelcome to the wonderful world of generalised linear models!\n\nThese sessions are intended to enable you to construct and use generalised linear models confidently.\n\nAs with all of our statistics courses our focus is not on mathematical derivations, but on developing an intuitive understanding of the underlying statistical concepts.\n\nAt the same time this is also *not* a \"how to mindlessly use a stats program\" course! We hope that at the end of this course you feel like you have a better grasp on what it is we're trying to do, and gained sufficient confidence in your coding skills to implement these statistical concepts in your own research!\n\n\nTo introduce sufficient understanding and coding experience for analysing data with non-continuous response variables.\n\n::: callout-note\n## Course aims\n\nTo know what to do when presented with an arbitrary data set e.g.\n\n1.  Construct\n    a.  a logistic model for binary response variables\n    b.  a logistic model for proportion response variables\n    c.  a Poisson model for count response variables\n    d.  ~~a Negative Binomial model for count response variables~~ (to be added later)\n2.  Plot the data and the fitted curve in each case for both continuous and categorical predictors\n3.  Assess the significance of fit\n4.  Assess assumption of the model\n:::\n","srcMarkdownNoYaml":"\n\nWelcome to the wonderful world of generalised linear models!\n\nThese sessions are intended to enable you to construct and use generalised linear models confidently.\n\nAs with all of our statistics courses our focus is not on mathematical derivations, but on developing an intuitive understanding of the underlying statistical concepts.\n\nAt the same time this is also *not* a \"how to mindlessly use a stats program\" course! We hope that at the end of this course you feel like you have a better grasp on what it is we're trying to do, and gained sufficient confidence in your coding skills to implement these statistical concepts in your own research!\n\n## Core aims\n\nTo introduce sufficient understanding and coding experience for analysing data with non-continuous response variables.\n\n::: callout-note\n## Course aims\n\nTo know what to do when presented with an arbitrary data set e.g.\n\n1.  Construct\n    a.  a logistic model for binary response variables\n    b.  a logistic model for proportion response variables\n    c.  a Poisson model for count response variables\n    d.  ~~a Negative Binomial model for count response variables~~ (to be added later)\n2.  Plot the data and the fitted curve in each case for both continuous and categorical predictors\n3.  Assess the significance of fit\n4.  Assess assumption of the model\n:::\n"},"formats":{"courseformat-html":{"identifier":{"display-name":"HTML","target-format":"courseformat-html","base-format":"html","extension-name":"courseformat"},"execute":{"fig-width":7,"fig-height":5,"fig-format":"retina","fig-dpi":96,"df-print":"default","error":false,"eval":true,"cache":null,"freeze":"auto","echo":true,"output":true,"warning":true,"include":true,"keep-md":false,"keep-ipynb":false,"ipynb":null,"enabled":null,"daemon":null,"daemon-restart":false,"debug":false,"ipynb-filters":[],"ipynb-shell-interactivity":null,"plotly-connected":true,"engine":"markdown"},"render":{"keep-tex":false,"keep-typ":false,"keep-source":false,"keep-hidden":false,"prefer-html":false,"output-divs":true,"output-ext":"html","fig-align":"default","fig-pos":null,"fig-env":null,"code-fold":"none","code-overflow":"scroll","code-link":true,"code-line-numbers":false,"code-tools":false,"tbl-colwidths":"auto","merge-includes":true,"inline-includes":false,"preserve-yaml":false,"latex-auto-mk":true,"latex-auto-install":true,"latex-clean":true,"latex-min-runs":1,"latex-max-runs":10,"latex-makeindex":"makeindex","latex-makeindex-opts":[],"latex-tlmgr-opts":[],"latex-input-paths":[],"latex-output-dir":null,"link-external-icon":false,"link-external-newwindow":false,"self-contained-math":false,"format-resources":[],"notebook-links":true,"shortcodes":[]},"pandoc":{"standalone":true,"wrap":"none","default-image-extension":"png","to":"html","toc":true,"number-sections":false,"filters":[],"output-file":"index.html"},"language":{"toc-title-document":"Table of contents","toc-title-website":"On this page","related-formats-title":"Other Formats","related-notebooks-title":"Notebooks","source-notebooks-prefix":"Source","other-links-title":"Other Links","code-links-title":"Code Links","launch-dev-container-title":"Launch Dev Container","launch-binder-title":"Launch Binder","article-notebook-label":"Article Notebook","notebook-preview-download":"Download Notebook","notebook-preview-download-src":"Download Source","notebook-preview-back":"Back to Article","manuscript-meca-bundle":"MECA Bundle","section-title-abstract":"Abstract","section-title-appendices":"Appendices","section-title-footnotes":"Footnotes","section-title-references":"References","section-title-reuse":"Reuse","section-title-copyright":"Copyright","section-title-citation":"Citation","appendix-attribution-cite-as":"For attribution, please cite this work as:","appendix-attribution-bibtex":"BibTeX citation:","title-block-author-single":"Author","title-block-author-plural":"Authors","title-block-affiliation-single":"Affiliation","title-block-affiliation-plural":"Affiliations","title-block-published":"Published","title-block-modified":"Modified","title-block-keywords":"Keywords","callout-tip-title":"Tip","callout-note-title":"Note","callout-warning-title":"Warning","callout-important-title":"Important","callout-caution-title":"Caution","code-summary":"Code","code-tools-menu-caption":"Code","code-tools-show-all-code":"Show All Code","code-tools-hide-all-code":"Hide All Code","code-tools-view-source":"View Source","code-tools-source-code":"Source Code","code-line":"Line","code-lines":"Lines","copy-button-tooltip":"Copy to Clipboard","copy-button-tooltip-success":"Copied!","repo-action-links-edit":"Edit this page","repo-action-links-source":"View source","repo-action-links-issue":"Report an issue","back-to-top":"Back to top","search-no-results-text":"No results","search-matching-documents-text":"matching documents","search-copy-link-title":"Copy link to search","search-hide-matches-text":"Hide additional matches","search-more-match-text":"more match in this document","search-more-matches-text":"more matches in this document","search-clear-button-title":"Clear","search-text-placeholder":"","search-detached-cancel-button-title":"Cancel","search-submit-button-title":"Submit","search-label":"Search","toggle-section":"Toggle section","toggle-sidebar":"Toggle sidebar navigation","toggle-dark-mode":"Toggle dark mode","toggle-reader-mode":"Toggle reader mode","toggle-navigation":"Toggle navigation","crossref-fig-title":"Figure","crossref-tbl-title":"Table","crossref-lst-title":"Listing","crossref-thm-title":"Theorem","crossref-lem-title":"Lemma","crossref-cor-title":"Corollary","crossref-prp-title":"Proposition","crossref-cnj-title":"Conjecture","crossref-def-title":"Definition","crossref-exm-title":"Example","crossref-exr-title":"Exercise","crossref-ch-prefix":"Chapter","crossref-apx-prefix":"Appendix","crossref-sec-prefix":"Section","crossref-eq-prefix":"Equation","crossref-lof-title":"List of Figures","crossref-lot-title":"List of Tables","crossref-lol-title":"List of Listings","environment-proof-title":"Proof","environment-remark-title":"Remark","environment-solution-title":"Solution","listing-page-order-by":"Order By","listing-page-order-by-default":"Default","listing-page-order-by-date-asc":"Oldest","listing-page-order-by-date-desc":"Newest","listing-page-order-by-number-desc":"High to Low","listing-page-order-by-number-asc":"Low to High","listing-page-field-date":"Date","listing-page-field-title":"Title","listing-page-field-description":"Description","listing-page-field-author":"Author","listing-page-field-filename":"File Name","listing-page-field-filemodified":"Modified","listing-page-field-subtitle":"Subtitle","listing-page-field-readingtime":"Reading Time","listing-page-field-wordcount":"Word Count","listing-page-field-categories":"Categories","listing-page-minutes-compact":"{0} min","listing-page-category-all":"All","listing-page-no-matches":"No matching items","listing-page-words":"{0} words"},"metadata":{"lang":"en","fig-responsive":true,"quarto-version":"1.4.531","theme":["default","_extensions/cambiotraining/courseformat/theme.scss"],"number-depth":3,"code-copy":true,"revealjs-plugins":[],"bibliography":["references.bib"],"knitr":{"opts_knit":{"cache.path":".knitr_cache"}},"title":"Course overview"},"extensions":{"book":{"multiFile":true}}}},"projectFormats":["courseformat-html"]}

_extensions/cambiotraining/courseformat/_extension.yml

@@ -1,6 +1,6 @@
 title: Course Page Format
 author: Cambridge Informatics Training
-version: 1.0.5
+version: 1.0.6
 contributes:
   formats:
     html:
@@ -11,4 +11,6 @@ contributes:
       code-link: true
       code-copy: true
   shortcodes:
-    - star_levels.lua
+    - star_levels.lua
+  filters:
+    - callout_exercise.lua

_extensions/cambiotraining/courseformat/callout_exercise.lua

@@ -0,0 +1,45 @@
+function Div(div)
+  -- process exercise
+  if div.classes:includes("callout-exercise") then
+    -- default title
+    local title = "Exercise"
+    -- Use first element of div as title if this is a header
+    if div.content[1] ~= nil and div.content[1].t == "Header" then
+      title = pandoc.utils.stringify(div.content[1])
+      div.content:remove(1)
+    end
+    -- return a callout instead of the Div
+    return quarto.Callout({
+      type = "exercise",
+      content = { pandoc.Div(div) },
+      title = title,
+      collapse = false
+    })
+  end
+
+  -- process answer
+  if div.classes:includes("callout-answer") then
+    -- default title
+    local title = "Answer"
+    -- return a callout instead of the Div
+    return quarto.Callout({
+      type = "answer",
+      content = { pandoc.Div(div) },
+      title = title,
+      collapse = true
+    })
+  end
+
+  -- process hint
+  if div.classes:includes("callout-hint") then
+    -- default title
+    local title = "Hint"
+    -- return a callout instead of the Div
+    return quarto.Callout({
+      type = "hint",
+      content = { pandoc.Div(div) },
+      title = title,
+      collapse = true
+    })
+  end
+end

_extensions/cambiotraining/courseformat/theme.scss

@@ -28,6 +28,7 @@ $callout-color-caution: #D62828;
 $callout-color-warning: #D62828;
 $callout-color-important: #28828A;
 
+
 /*-- scss:rules --*/
 
 // headings colour
@@ -40,13 +41,6 @@ div.sidebar-item-container .active {
   font-weight: bold;
 }
 
-// part titles text bold
-div.sidebar-item-container .text-start {
-  color: #003a41;
-  font-weight: bold;
-  font-size: 0.8rem;
-}
-
 // active links - affects header and TOC navigation bar
 .sidebar .nav-link.active {
   font-weight: bold;