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Get caching working correctly #28

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ns-rse opened this issue Jul 11, 2024 · 0 comments
Closed

Get caching working correctly #28

ns-rse opened this issue Jul 11, 2024 · 0 comments
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quarto Issues relating to use of Quarto

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ns-rse commented Jul 11, 2024

Ideally we should be using Quarto's caching feature so that only things that change need to be re-run when re-rendering/previewing are executed.

At the document level this requires adding the following to the YAML header...

execute:
  cache: true

If this doesn't work individual code chunks can be cached by adding the option to its header...

#| cache: true
@ns-rse ns-rse added the quarto Issues relating to use of Quarto label Jul 11, 2024
@ns-rse ns-rse self-assigned this Jul 11, 2024
ns-rse added a commit that referenced this issue Jul 11, 2024
Closes #28

**IMPORTANT** Currently there is a [bug in the stable release of
Quarto](quarto-dev/quarto-cli#10196) which prevents rendering of the missing data figures. It
is fixed in development version [`v1.6.1`](https://github.com/quarto-dev/quarto-cli/releases/tag/v1.6.1) (currently
available as pre-release, so if things don't render upgrade to this version).

+ Uses the [mice](https://amices.org/mice/index.html) package to summarise missing data graphically and undertake three
  different methods of multiple imputation. Functions are defined to aid with the plotting of imputed data for
  comparison to the original dataset. Notes on tasks that could be done to augment this such as tabulation.
  This is via the `sections/_interpolation.qmd` file. Includes citation for the mice R package.
+ Moves data dictionary to Appendix.
+ Tidies up tables adding missing captions and removing `print()`
+ Moves tables to [panel-tabset](https://quarto.org/docs/interactive/layout.html#tabset-panel) as document was getting
  long and cluttered. This makes it shorter and easier to navigate. Used for plots that summarise imputation.
+ Introduces caching to the document so that computationally expensive sections of code are not re-run on every render.
+ Some house keeping wrapping lines to 120 characters.
+ Moves summary of missing data patterns to `sections/_missing.qmd`.
+ Removes `dark_theme_minimal()` from plot of final lasso.
+ Tidies up `sections/_logistic.qmd` to explicitly use `family = binomial(link = "logit")` (**NB** Previous work ensured
  the `train` data frame is used in all logistic regression rather the raw `df` which includes individuals with missing
  `final_pathology`).
@ns-rse ns-rse closed this as completed Jul 11, 2024
ns-rse added a commit that referenced this issue Jul 11, 2024
Closes #28

**IMPORTANT** Currently there is a [bug in the stable release of
Quarto](quarto-dev/quarto-cli#10196) which prevents rendering of the missing data figures. It
is fixed in development version [`v1.6.1`](https://github.com/quarto-dev/quarto-cli/releases/tag/v1.6.1) (currently
available as pre-release, so if things don't render upgrade to this version).

+ Uses the [mice](https://amices.org/mice/index.html) package to summarise missing data graphically and undertake three
  different methods of multiple imputation. Functions are defined to aid with the plotting of imputed data for
  comparison to the original dataset. Notes on tasks that could be done to augment this such as tabulation.
  This is via the `sections/_interpolation.qmd` file. Includes citation for the mice R package.
+ Moves data dictionary to Appendix.
+ Tidies up tables adding missing captions and removing `print()`
+ Moves tables to [panel-tabset](https://quarto.org/docs/interactive/layout.html#tabset-panel) as document was getting
  long and cluttered. This makes it shorter and easier to navigate. Used for plots that summarise imputation.
+ Introduces caching to the document so that computationally expensive sections of code are not re-run on every render.
+ Some house keeping wrapping lines to 120 characters.
+ Moves summary of missing data patterns to `sections/_missing.qmd`.
+ Removes `dark_theme_minimal()` from plot of final lasso.
+ Tidies up `sections/_logistic.qmd` to explicitly use `family = binomial(link = "logit")` (**NB** Previous work ensured
  the `train` data frame is used in all logistic regression rather the raw `df` which includes individuals with missing
  `final_pathology`).
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