From c31f04d06e03e7876b4d5f9415ca89d62b320566 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Tue, 1 Oct 2024 16:13:16 -0500 Subject: [PATCH 01/19] Add paper --- _pkgdown.yml | 2 +- paper.md | 34 +++++++++++++++++++ pkgdown/favicon/apple-touch-icon-120x120.png | Bin 0 -> 11626 bytes pkgdown/favicon/apple-touch-icon-152x152.png | Bin 0 -> 15976 bytes pkgdown/favicon/apple-touch-icon-180x180.png | Bin 0 -> 20433 bytes pkgdown/favicon/apple-touch-icon-60x60.png | Bin 0 -> 4476 bytes pkgdown/favicon/apple-touch-icon-76x76.png | Bin 0 -> 5958 bytes pkgdown/favicon/apple-touch-icon.png | Bin 0 -> 20433 bytes pkgdown/favicon/favicon-16x16.png | Bin 0 -> 1113 bytes pkgdown/favicon/favicon-32x32.png | Bin 0 -> 2137 bytes pkgdown/favicon/favicon.ico | Bin 0 -> 15086 bytes 11 files changed, 35 insertions(+), 1 deletion(-) create mode 100644 paper.md create mode 100644 pkgdown/favicon/apple-touch-icon-120x120.png create mode 100644 pkgdown/favicon/apple-touch-icon-152x152.png create mode 100644 pkgdown/favicon/apple-touch-icon-180x180.png create mode 100644 pkgdown/favicon/apple-touch-icon-60x60.png create mode 100644 pkgdown/favicon/apple-touch-icon-76x76.png create mode 100644 pkgdown/favicon/apple-touch-icon.png create mode 100644 pkgdown/favicon/favicon-16x16.png create mode 100644 pkgdown/favicon/favicon-32x32.png create mode 100644 pkgdown/favicon/favicon.ico diff --git a/_pkgdown.yml b/_pkgdown.yml index 6916ce1..8fd811e 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -2,7 +2,7 @@ url: https://jeffreyrstevens.github.io/cocoon/ template: bootstrap: 5 bootswatch: minty - theme: nord + theme: zenburn bslib: bg: "#212529" fg: "#f8f9fa" diff --git a/paper.md b/paper.md new file mode 100644 index 0000000..a5d1ca3 --- /dev/null +++ b/paper.md @@ -0,0 +1,34 @@ +--- +title: 'cocoon: An R package for extracting, formatting, and printing statistical output' +tags: + - R + - formatting + - LaTeX + - Markdown + - statistical objects +authors: + - name: Jeffrey R. Stevens + orcid: 0000-0003-2375-1360 + affiliation: 1 +affiliations: + - name: Department of Psychology, Center for Brain, Biology & Behavior, University of Nebraska-Lincoln + index: 1 +date: 2024-03-19 +# bibliography: paper.bib +--- + +# Summary + +Collecting survey data online can result in low-quality data. Survey participants may not complete the survey, may complete the survey too quickly or slowly, may not reside in the country they claim, or may use unacceptable screen types. Also, online surveys are plagued by automated bots attempting to complete the surveys while offering worthless data. Researchers collecting online data may want to check their data for these and other potential criteria to exclude problematic data entries. The `excluder` package uses three main function types to mark, check, and exclude data based on seven different exclusion criteria. + +# Statement of need + +Researchers who conduct online surveys may use [Qualtrics](https://qualtrics.com) or other online systems to collect data from participants. Those participants may be recruited directly via listservs or through third party vendors that connect researchers and participants, such as [Amazon Mechanical Turk](https://www.mturk.com/) and [Prolific](https://prolific.co/). Ensuring good data quality from these participants can be tricky [@Aruguete.etal.2019;@Chmielewski.Kucker.2020;@Gupta.etal.2021;@Eyal.etal.2021]. For instance, while Mechanical Turk in theory screens workers based on location (e.g., if you want to restrict your participant pool to workers in the United States), this is not necessarily represented in the data when participant IP addresses are recorded. Also, automated bots are constantly trying to complete online surveys with worthless data. Therefore, researchers may want to screen their data for certain exclusion criteria. + +Finding the tools to screen for IP address location can be difficult, and the `excluder` package simplifies working with exclusion criteria based on data that Qualtrics reports, including geolocation, IP address, duplicate records from the same location, participant screen resolution, participant progress through the survey, and survey completion duration. `excluder` is an R [@RCoreTeam.2021] package based on the `tidyverse` [@Wickham.etal.2019] framework that use three primary functions to (1) mark existing files with new columns that flag data rows meeting exclusion criteria, (2) view the subset of data rows that meet exclusion criteria, and (3) exclude data rows that meet exclusion criteria from the data. In addition, `excluder` helps prepare Qualtrics data for analysis and can deidentify the data by removing columns with potentially identifiable information. Though the functionality focuses on data collected by Qualtrics and imported by the `qualtRics` [@Ginn.Silge.2021] package, it is flexible enough for researchers using any source of online survey data. + +# Acknowledgments + +I thank [Francine Goh](https://orcid.org/0000-0002-7364-4398) and Billy Lim for comments on an early version of the package, as well as the insightful feedback from rOpenSci staff [Mauro Lepore](https://orcid.org/0000-0002-1986-7988), [Joseph O'Brien](https://orcid.org/0000-0001-9851-5077), and [Julia Silge](https://orcid.org/0000-0002-3671-836X). This work was funded by US National Science Foundation grant NSF-1658837. + +# References diff --git a/pkgdown/favicon/apple-touch-icon-120x120.png b/pkgdown/favicon/apple-touch-icon-120x120.png new file mode 100644 index 0000000000000000000000000000000000000000..d9c7050cfdf46176fc8698602c5bddc9e55f9c2c GIT binary patch literal 11626 zcmZ{KWmH>j&~0!pTA;WDiUfD3xE3!^+@ZL;Qz%|S30f#nyaWiv-3k;d#ibA&iaQj$ z=e_IRAK#B}Wsz`_bsm}7v-iw-CSLosG660XE(io7P*qXT1wI4*`@_Zr-oiF9S$GO2D3|V zX@WZ{TJ78e^`Dy-Vk<|1*r7yR4Br)AR+lRB%`bIGN&V4Pe%ig|Tm10QAW%nJN8Cor zSFBT$BQYhf^ZOu4VTz<<{)>tb|PSK;k?vPJgvo>J{fOb*rBgB@?A4?*?FJd$&e2l#8wg9bSQlT~I z2(JWVnRJHn)TO)u4_CuCL`OfEhfBbzdg@IMjQx8fS!le>Qneq~Ep|&{nj=X-GqH*E3OdHBtmM>zHoeQ4mZdg7V z9VUe8=u7mxvgA3DvdsL(7IYqK-YA2J%U^Q)L5k0ir=Hpjg`{hhQig1prAR$-ocGya z53+;qBA>9^QOMr36%|m-sMW?w9NyB^5~||PeHW|?T$Q@`6Hc)fO9_%QU18%?B|%kr zJ$BNA_cR(;a}OK6XKI$Z$!wMi0@WI}ts5r1V>Ut!ij+a4LwkEa$-D2r`U8e_TxO*y z0fkry*U<+zgV*MTr^;eQ|1FQ?J^Z=*38o5ao4-1tn_cnb>{QtmI6T;Keu1M39b$!vUjAF6xhtDfNz!DB 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Stevens" Date: Fri, 11 Oct 2024 15:08:54 -0500 Subject: [PATCH 02/19] Complete first draft of paper --- paper.Rmd | 44 ++++++++++++++++++++ paper.bib | 118 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ paper.md | 24 +++++++---- 3 files changed, 179 insertions(+), 7 deletions(-) create mode 100644 paper.Rmd create mode 100644 paper.bib diff --git a/paper.Rmd b/paper.Rmd new file mode 100644 index 0000000..8580848 --- /dev/null +++ b/paper.Rmd @@ -0,0 +1,44 @@ +--- +title: 'cocoon: An R package for extracting, formatting, and printing statistical output' +tags: + - R + - formatting + - LaTeX + - Markdown + - statistical objects +authors: + - name: Jeffrey R. Stevens + orcid: 0000-0003-2375-1360 + affiliation: 1 +affiliations: + - name: Department of Psychology, Center for Brain, Biology & Behavior, University of Nebraska-Lincoln + index: 1 +date: "`r Sys.Date()`" +bibliography: paper.bib +output: + html_document: + keep_md: yes +--- + +# Summary + +Formatting statistics from R statistical objects can be troublesome. One must first find, extract, and include the relevant statistical values, format the values properly with leading zeros and appropriate rounding, and format the statistical labels to match norms or style guides. Doing this with inline code can be messy and hard to read with mulitple functions working in tandem to complete the formatting. Existing packages can extract and format statistics, but they often return output formatted for specific style guides and lack flexibility to precisely control the formatting in other ways. The `{cocoon}` package allows for flexible formatting of statistical objects, statistical values, and numbers more generally to allow users to easily embed statistical information in their reproducible research documents. + + +# Statement of need + +Converting the output of statistical software into a format that can be communicated in documents and presentations can be complicated. Researchers must extract the relevant information from the statistical output then format it in a way to clearly communicate it. Literate programming [@Knuth.1992] involves interweaving code snippets into text, embedding the output of the code to be inserted into the text. A key advantage of literate programming is that the analyses can be reproducible [@Marwick.etal.2018a; @Stodden.etal.2018]. When readers can access the analysis code and see where it is embedded in the text, they are able to directly reproduce the analyses to verify accuracy and explore other possibilities. + +In the R community, the `{knitr}` package [@Xie.2014; @Xie.2015] allows users to embed R code into R Markdown and Quarto documents. However, statistical objects in R are often complicated nested lists that can make it difficult to extract the relevant statistics and values that authors want to report in their documents. Functions have been created that extract commonly used values from statistical objects and return them formatted in a way that can be inserted in inline code. For instance, in the `{papaja}` package [@Aust.Barth.2023], the `apa_print()` function can be applied to a range of statistical objects such as correlations and t-tests to extract test statistics, means, confidence intervals, degrees of freedom, and p-values and return character strings that can be embedded in documents to communicate the statistics. + +In the field of psychology, a number of packages have been developed to extract and return common statistics for integration in documents [e.g., `{apa}` @Gromer.2023; `{insight}` @Ludecke.etal.2019; `{papaja}` @Aust.Barth.2023]. A key limitation of these packages though, is that they tend to only format statistics using the American Psychological Association (APA) Style Guide. This means that the formatting is very specific in how statistics are presented. For instance, APA style requires that the leading zero before values that can only range between -1 and 1 must be removed. So correlations and p-values do not have a leading zero (e.g., _r_ = -.15, _p_ = .05). Many scientific journals and other outlets of research have different style guides. The existing packages for formatting statistics are relatively inflexible in how those statistics are formatted. Moreover, some of those packages output only LaTeX-formatted statistics. Though this is fine for producing PDF documents, LaTeX syntax produces undesirable symbols and mathematical objects when producing HTML and Word documents. Thus, the existing statistical formatting packages lack flexibility in how statistics are formatted and output. + +The aim of the `{cocoon}` package is to provide functions that flexibly format statistical output in a way that can be inserted into R Markdown or Quarto documents. The `{cocoon}` package uses APA style as the default, but it allows more flexible formatting of which statistics are included, how the labels are formatted, and how the values are formatted. All functions also output Markdown syntax by default but can be modified to output LaTeX syntax. + +The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., `r cocoon::format_stats(cor.test(mtcars$mpg, mtcars$cyl))`). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., `r cocoon::format_bf(12.3)`). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., `r cocoon::format_meanci(x = mtcars$mpg)` OR `r cocoon::format_meanci(values = c(12.55, 12.48, 12.63))`). + + +The suite of functions in `{cocoon}` allows users to control numbers of digits, leading zeros, cutoff minima/maxima, the presence of means, confidence intervals, and degrees of freedom, statistical labels, italics, and output format (Markdown or LaTeX). These options give users control over the formatting of their statistics, thereby facilitating a flexible, consistent way of communicating their statistics. + + +# References diff --git a/paper.bib b/paper.bib new file mode 100644 index 0000000..e2e34be --- /dev/null +++ b/paper.bib @@ -0,0 +1,118 @@ +@manual{Aust.Barth.2023, + type = {manual}, + title = {{{papaja}}: {{Prepare}} reproducible {{APA}} journal articles with {{R Markdown}}}, + author = {Aust, Frederik and Barth, Marius}, + year = {2023} +} + +@manual{Gromer.2023, + type = {manual}, + title = {apa: {{Format}} outputs of statistical tests according to {{APA}} guidelines}, + author = {Gromer, Daniel}, + year = {2023} +} + +@book{Knuth.1992, + title = {Literate {{Programming}}}, + author = {Knuth, Donald E.}, + year = {1992}, + month = mar, + publisher = {Cambridge University Press}, + abstract = {Literate programming is a programming methodology that combines a programming language with a documentation language, making programs more robust, more portable, and more easily maintained than programs written only in a high-level language. Computer programmers already know both kinds of languages; they need only learn a few conventions about alternating between languages to create programs that are works of literature. A literate programmer is an essayist who writes programs for humans to understand, instead of primarily writing instructions for machines to follow. When programs are written in the recommended style they can be transformed into documents by a document compiler and into efficient code by an algebraic compiler. This anthology of essays from the inventor of literate programming includes Knuth's early papers on related topics such as structured programming, as well as the Computer Journal article that launched literate programming itself.}, + googlebooks = {fqPIPgAACAAJ}, + isbn = {978-0-937073-80-3}, + langid = {english}, + keywords = {Computers / Social Aspects} +} + +@article{Ludecke.etal.2019, + title = {{{insight}}: a unified interface to access information from model objects in {{R}}}, + author = {L{\"u}decke, Daniel and Waggoner, Philip and Makowski, Dominique}, + year = {2019}, + journal = {Journal of Open Source Software}, + volume = {4}, + number = {38}, + pages = {1412}, + doi = {10.21105/joss.01412} +} + +@article{Makowski.etal.2020, + title = {Methods and algorithms for correlation analysis in {{R}}}, + author = {Makowski, Dominique and {Ben-Shachar}, Mattan S. and Patil, Indrajeet and L{\"u}decke, Daniel}, + year = {2020}, + journal = {Journal of Open Source Software}, + volume = {5}, + number = {51}, + pages = {2306}, + doi = {10.21105/joss.02306} +} + +@misc{Makowski.etal.2022, + title = {{{correlation}}: {{Methods}} for correlation analysis}, + shorttitle = {{{correlation}}}, + author = {Makowski, Dominique and Wiernik, Brenton M. and Patil, Indrajeet and L{\"u}decke, Daniel and {Ben-Shachar}, Mattan S.}, + year = {2022}, + month = oct +} + +@article{Marwick.etal.2018a, + title = {Packaging data analytical work reproducibly using {{R}} (and friends)}, + author = {Marwick, Ben and Boettiger, Carl and Mullen, Lincoln}, + year = {2018}, + month = jan, + journal = {The American Statistician}, + volume = {72}, + number = {1}, + pages = {80--88}, + publisher = {Taylor \& Francis}, + issn = {0003-1305}, + doi = {10.1080/00031305.2017.1375986}, + urldate = {2021-12-30}, + abstract = {Computers are a central tool in the research process, enabling complex and large-scale data analysis. As computer-based research has increased in complexity, so have the challenges of ensuring that this research is reproducible. To address this challenge, we review the concept of the research compendium as a solution for providing a standard and easily recognizable way for organizing the digital materials of a research project to enable other researchers to inspect, reproduce, and extend the research. We investigate how the structure and tooling of software packages of the R programming language are being used to produce research compendia in a variety of disciplines. We also describe how software engineering tools and services are being used by researchers to streamline working with research compendia. Using real-world examples, we show how researchers can improve the reproducibility of their work using research compendia based on R packages and related tools.}, + keywords = {Computational science,Data science,Open source software,Reproducible research}, + file = {/home/jstevens/zotero-library/Marwick et al/marwick_et_al_2018_packaging_data_analytical_work_reproducibly_using_r_(and_friends)2.pdf} +} + +@manual{Morey.Rouder.2024, + type = {manual}, + title = {{{BayesFactor}}: {{Computation}} of bayes factors for common designs}, + author = {Morey, Richard D. and Rouder, Jeffrey N.}, + year = {2024} +} + +@book{Stodden.etal.2018, + title = {Implementing reproducible research}, + editor = {Stodden, Victoria and Leisch, Friedrich and Peng, Roger D.}, + year = {2018}, + month = dec, + publisher = {{Chapman and Hall/CRC}}, + address = {New York}, + doi = {10.1201/9781315373461}, + abstract = {In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.}, + isbn = {978-1-315-37346-1}, + file = {/home/jstevens/zotero-library/Stodden et al/stodden_et_al_2018_implementing_reproducible_research.pdf;/home/jstevens/zotero-library/Stodden et al/stodden_et_al_2018_implementing_reproducible_research2.pdf} +} + +@incollection{Xie.2014, + title = {knitr: {{A Comprehensive Tool}} for {{Reproducible Research}} in {{R}}}, + booktitle = {Implementing {{Reproducible Research}}}, + author = {Xie, Yihui}, + editor = {Stodden, V and Leisch, F and Peng, R D}, + year = {2014}, + pages = {3--32}, + publisher = {CRC Press}, + address = {Boca Raton, FL}, + file = {/home/jstevens/zotero-library/Xie/xie_2014_knitr_-_a_comprehensive_tool_for_reproducible_research_in_r.pdf} +} + +@book{Xie.2015, + title = {Dynamic {{Documents}} with {{R}} and knitr}, + author = {Xie, Yihui}, + year = {2015}, + month = jun, + edition = {2nd}, + publisher = {CRC Press}, + address = {Boca Raton, FL}, + urldate = {2017-06-28}, + abstract = {Quickly and Easily Write Dynamic Documents Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams, books, blogs, and web} +} diff --git a/paper.md b/paper.md index a5d1ca3..ed7cf05 100644 --- a/paper.md +++ b/paper.md @@ -13,22 +13,32 @@ authors: affiliations: - name: Department of Psychology, Center for Brain, Biology & Behavior, University of Nebraska-Lincoln index: 1 -date: 2024-03-19 -# bibliography: paper.bib +date: "2024-10-11" +bibliography: paper.bib +output: + html_document: + keep_md: yes --- # Summary -Collecting survey data online can result in low-quality data. Survey participants may not complete the survey, may complete the survey too quickly or slowly, may not reside in the country they claim, or may use unacceptable screen types. Also, online surveys are plagued by automated bots attempting to complete the surveys while offering worthless data. Researchers collecting online data may want to check their data for these and other potential criteria to exclude problematic data entries. The `excluder` package uses three main function types to mark, check, and exclude data based on seven different exclusion criteria. +Formatting statistics from R statistical objects can be troublesome. One must first find, extract, and include the relevant statistical values, format the values properly with leading zeros and appropriate rounding, and format the statistical labels to match norms or style guides. Doing this with inline code can be messy and hard to read with mulitple functions working in tandem to complete the formatting. Existing packages can extract and format statistics, but they often return output formatted for specific style guides and lack flexibility to precisely control the formatting in other ways. The `{cocoon}` package allows for flexible formatting of statistical objects, statistical values, and numbers more generally to allow users to easily embed statistical information in their reproducible research documents. + # Statement of need -Researchers who conduct online surveys may use [Qualtrics](https://qualtrics.com) or other online systems to collect data from participants. Those participants may be recruited directly via listservs or through third party vendors that connect researchers and participants, such as [Amazon Mechanical Turk](https://www.mturk.com/) and [Prolific](https://prolific.co/). Ensuring good data quality from these participants can be tricky [@Aruguete.etal.2019;@Chmielewski.Kucker.2020;@Gupta.etal.2021;@Eyal.etal.2021]. For instance, while Mechanical Turk in theory screens workers based on location (e.g., if you want to restrict your participant pool to workers in the United States), this is not necessarily represented in the data when participant IP addresses are recorded. Also, automated bots are constantly trying to complete online surveys with worthless data. Therefore, researchers may want to screen their data for certain exclusion criteria. +Converting the output of statistical software into a format that can be communicated in documents and presentations can be complicated. Researchers must extract the relevant information from the statistical output then format it in a way to clearly communicate it. Literate programming [@Knuth.1992] involves interweaving code snippets into text, embedding the output of the code to be inserted into the text. A key advantage of literate programming is that the analyses can be reproducible [@Marwick.etal.2018a; @Stodden.etal.2018]. When readers can access the analysis code and see where it is embedded in the text, they are able to directly reproduce the analyses to verify accuracy and explore other possibilities. + +In the R community, the `{knitr}` package [@Xie.2014; @Xie.2015] allows users to embed R code into R Markdown and Quarto documents. However, statistical objects in R are often complicated nested lists that can make it difficult to extract the relevant statistics and values that authors want to report in their documents. Functions have been created that extract commonly used values from statistical objects and return them formatted in a way that can be inserted in inline code. For instance, in the `{papaja}` package [@Aust.Barth.2023], the `apa_print()` function can be applied to a range of statistical objects such as correlations and t-tests to extract test statistics, means, confidence intervals, degrees of freedom, and p-values and return character strings that can be embedded in documents to communicate the statistics. + +In the field of psychology, a number of packages have been developed to extract and return common statistics for integration in documents [e.g., `{apa}` @Gromer.2023; `{insight}` @Ludecke.etal.2019; `{papaja}` @Aust.Barth.2023]. A key limitation of these packages though, is that they tend to only format statistics using the American Psychological Association (APA) Style Guide. This means that the formatting is very specific in how statistics are presented. For instance, APA style requires that the leading zero before values that can only range between -1 and 1 must be removed. So correlations and p-values do not have a leading zero (e.g., _r_ = -.15, _p_ = .05). Many scientific journals and other outlets of research have different style guides. The existing packages for formatting statistics are relatively inflexible in how those statistics are formatted. Moreover, some of those packages output only LaTeX-formatted statistics. Though this is fine for producing PDF documents, LaTeX syntax produces undesirable symbols and mathematical objects when producing HTML and Word documents. Thus, the existing statistical formatting packages lack flexibility in how statistics are formatted and output. + +The aim of the `{cocoon}` package is to provide functions that flexibly format statistical output in a way that can be inserted into R Markdown or Quarto documents. The `{cocoon}` package uses APA style as the default, but it allows more flexible formatting of which statistics are included, how the labels are formatted, and how the values are formatted. All functions also output Markdown syntax by default but can be modified to output LaTeX syntax. + +The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., _r_ = -.85, 95% CI [-0.93, -0.72], _p_ < .001). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., _BF_~10~ = 12.3). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., _M_ = 20.1, 95% CI [17.9, 22.3] OR _M_ = 12.6, 95% CI [12.5, 12.6]). -Finding the tools to screen for IP address location can be difficult, and the `excluder` package simplifies working with exclusion criteria based on data that Qualtrics reports, including geolocation, IP address, duplicate records from the same location, participant screen resolution, participant progress through the survey, and survey completion duration. `excluder` is an R [@RCoreTeam.2021] package based on the `tidyverse` [@Wickham.etal.2019] framework that use three primary functions to (1) mark existing files with new columns that flag data rows meeting exclusion criteria, (2) view the subset of data rows that meet exclusion criteria, and (3) exclude data rows that meet exclusion criteria from the data. In addition, `excluder` helps prepare Qualtrics data for analysis and can deidentify the data by removing columns with potentially identifiable information. Though the functionality focuses on data collected by Qualtrics and imported by the `qualtRics` [@Ginn.Silge.2021] package, it is flexible enough for researchers using any source of online survey data. -# Acknowledgments +The suite of functions in `{cocoon}` allows users to control numbers of digits, leading zeros, cutoff minima/maxima, the presence of means, confidence intervals, and degrees of freedom, statistical labels, italics, and output format (Markdown or LaTeX). These options give users control over the formatting of their statistics, thereby facilitating a flexible, consistent way of communicating their statistics. -I thank [Francine Goh](https://orcid.org/0000-0002-7364-4398) and Billy Lim for comments on an early version of the package, as well as the insightful feedback from rOpenSci staff [Mauro Lepore](https://orcid.org/0000-0002-1986-7988), [Joseph O'Brien](https://orcid.org/0000-0001-9851-5077), and [Julia Silge](https://orcid.org/0000-0002-3671-836X). This work was funded by US National Science Foundation grant NSF-1658837. # References From fb3077e0260a7082bafb21212894bfd4b1a7fb9f Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Fri, 11 Oct 2024 15:22:06 -0500 Subject: [PATCH 03/19] Add draft PDF to GitHub Actions workflow --- .github/workflows/draft-pdf.yml | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) create mode 100644 .github/workflows/draft-pdf.yml diff --git a/.github/workflows/draft-pdf.yml b/.github/workflows/draft-pdf.yml new file mode 100644 index 0000000..a7c762c --- /dev/null +++ b/.github/workflows/draft-pdf.yml @@ -0,0 +1,24 @@ +name: Draft PDF +on: [push] + +jobs: + paper: + runs-on: ubuntu-latest +name: Paper Draft +steps: + - name: Checkout +uses: actions/checkout@v4 +- name: Build draft PDF +uses: openjournals/openjournals-draft-action@master +with: + journal: joss +# This should be the path to the paper within your repo. +paper-path: paper.md +- name: Upload +uses: actions/upload-artifact@v4 +with: + name: paper +# This is the output path where Pandoc will write the compiled +# PDF. Note, this should be the same directory as the input +# paper.md +path: paper.pdf From 69d2eab4ad9ea68ab17fa8d7ced8ce4ad7fac3db Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Fri, 11 Oct 2024 15:22:22 -0500 Subject: [PATCH 04/19] Update paper --- paper.Rmd | 2 +- paper.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/paper.Rmd b/paper.Rmd index 8580848..c7cc4ab 100644 --- a/paper.Rmd +++ b/paper.Rmd @@ -35,7 +35,7 @@ In the field of psychology, a number of packages have been developed to extract The aim of the `{cocoon}` package is to provide functions that flexibly format statistical output in a way that can be inserted into R Markdown or Quarto documents. The `{cocoon}` package uses APA style as the default, but it allows more flexible formatting of which statistics are included, how the labels are formatted, and how the values are formatted. All functions also output Markdown syntax by default but can be modified to output LaTeX syntax. -The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., `r cocoon::format_stats(cor.test(mtcars$mpg, mtcars$cyl))`). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., `r cocoon::format_bf(12.3)`). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., `r cocoon::format_meanci(x = mtcars$mpg)` OR `r cocoon::format_meanci(values = c(12.55, 12.48, 12.63))`). +The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., `r cocoon::format_stats(cor.test(mtcars$mpg, mtcars$cyl))`). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., `r cocoon::format_bf(12.3)`). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., `r cocoon::format_meanci(x = mtcars$mpg)` OR `r cocoon::format_meanci(values = c(12.55, 12.48, 12.63))`). The suite of functions in `{cocoon}` allows users to control numbers of digits, leading zeros, cutoff minima/maxima, the presence of means, confidence intervals, and degrees of freedom, statistical labels, italics, and output format (Markdown or LaTeX). These options give users control over the formatting of their statistics, thereby facilitating a flexible, consistent way of communicating their statistics. diff --git a/paper.md b/paper.md index ed7cf05..89462c3 100644 --- a/paper.md +++ b/paper.md @@ -35,7 +35,7 @@ In the field of psychology, a number of packages have been developed to extract The aim of the `{cocoon}` package is to provide functions that flexibly format statistical output in a way that can be inserted into R Markdown or Quarto documents. The `{cocoon}` package uses APA style as the default, but it allows more flexible formatting of which statistics are included, how the labels are formatted, and how the values are formatted. All functions also output Markdown syntax by default but can be modified to output LaTeX syntax. -The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., _r_ = -.85, 95% CI [-0.93, -0.72], _p_ < .001). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., _BF_~10~ = 12.3). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., _M_ = 20.1, 95% CI [17.9, 22.3] OR _M_ = 12.6, 95% CI [12.5, 12.6]). +The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., _r_ = -.85, 95% CI [-0.93, -0.72], _p_ < .001). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., _BF_~10~ = 12.3). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., _M_ = 20.1, 95% CI [17.9, 22.3] OR _M_ = 12.6, 95% CI [12.5, 12.6]). The suite of functions in `{cocoon}` allows users to control numbers of digits, leading zeros, cutoff minima/maxima, the presence of means, confidence intervals, and degrees of freedom, statistical labels, italics, and output format (Markdown or LaTeX). These options give users control over the formatting of their statistics, thereby facilitating a flexible, consistent way of communicating their statistics. From 196a11672683e42df3801cc2485ee8ddb26f393e Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Fri, 11 Oct 2024 15:24:21 -0500 Subject: [PATCH 05/19] Fix YAML tabs --- .github/workflows/draft-pdf.yml | 36 ++++++++++++++++----------------- 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/.github/workflows/draft-pdf.yml b/.github/workflows/draft-pdf.yml index a7c762c..2cc9b53 100644 --- a/.github/workflows/draft-pdf.yml +++ b/.github/workflows/draft-pdf.yml @@ -4,21 +4,21 @@ on: [push] jobs: paper: runs-on: ubuntu-latest -name: Paper Draft -steps: - - name: Checkout -uses: actions/checkout@v4 -- name: Build draft PDF -uses: openjournals/openjournals-draft-action@master -with: - journal: joss -# This should be the path to the paper within your repo. -paper-path: paper.md -- name: Upload -uses: actions/upload-artifact@v4 -with: - name: paper -# This is the output path where Pandoc will write the compiled -# PDF. Note, this should be the same directory as the input -# paper.md -path: paper.pdf + name: Paper Draft + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: Build draft PDF + uses: openjournals/openjournals-draft-action@master + with: + journal: joss + # This should be the path to the paper within your repo. + paper-path: paper.md + - name: Upload + uses: actions/upload-artifact@v4 + with: + name: paper + # This is the output path where Pandoc will write the compiled + # PDF. Note, this should be the same directory as the input + # paper.md + path: paper.pdf From 3dbfad84fb10621efc435c6de5b68caab54d8c5e Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Fri, 11 Oct 2024 15:25:57 -0500 Subject: [PATCH 06/19] Replace YAML with new text --- .github/workflows/draft-pdf.yml | 38 ++++++++++++++++----------------- 1 file changed, 19 insertions(+), 19 deletions(-) diff --git a/.github/workflows/draft-pdf.yml b/.github/workflows/draft-pdf.yml index 2cc9b53..1d7dc44 100644 --- a/.github/workflows/draft-pdf.yml +++ b/.github/workflows/draft-pdf.yml @@ -3,22 +3,22 @@ on: [push] jobs: paper: - runs-on: ubuntu-latest - name: Paper Draft - steps: - - name: Checkout - uses: actions/checkout@v4 - - name: Build draft PDF - uses: openjournals/openjournals-draft-action@master - with: - journal: joss - # This should be the path to the paper within your repo. - paper-path: paper.md - - name: Upload - uses: actions/upload-artifact@v4 - with: - name: paper - # This is the output path where Pandoc will write the compiled - # PDF. Note, this should be the same directory as the input - # paper.md - path: paper.pdf + runs-on: ubuntu-latest + name: Paper Draft + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: Build draft PDF + uses: openjournals/openjournals-draft-action@master + with: + journal: joss + # This should be the path to the paper within your repo. + paper-path: paper.md + - name: Upload + uses: actions/upload-artifact@v4 + with: + name: paper + # This is the output path where Pandoc will write the compiled + # PDF. Note, this should be the same directory as the input + # paper.md + path: paper.pdf From 058d4050ae61b659f0a9c0c77a7d3923600e5889 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Tue, 26 Nov 2024 15:01:31 -0600 Subject: [PATCH 07/19] Remove paper --- paper.Rmd | 44 -------------------- paper.bib | 118 ------------------------------------------------------ paper.md | 44 -------------------- 3 files changed, 206 deletions(-) delete mode 100644 paper.Rmd delete mode 100644 paper.bib delete mode 100644 paper.md diff --git a/paper.Rmd b/paper.Rmd deleted file mode 100644 index c7cc4ab..0000000 --- a/paper.Rmd +++ /dev/null @@ -1,44 +0,0 @@ ---- -title: 'cocoon: An R package for extracting, formatting, and printing statistical output' -tags: - - R - - formatting - - LaTeX - - Markdown - - statistical objects -authors: - - name: Jeffrey R. Stevens - orcid: 0000-0003-2375-1360 - affiliation: 1 -affiliations: - - name: Department of Psychology, Center for Brain, Biology & Behavior, University of Nebraska-Lincoln - index: 1 -date: "`r Sys.Date()`" -bibliography: paper.bib -output: - html_document: - keep_md: yes ---- - -# Summary - -Formatting statistics from R statistical objects can be troublesome. One must first find, extract, and include the relevant statistical values, format the values properly with leading zeros and appropriate rounding, and format the statistical labels to match norms or style guides. Doing this with inline code can be messy and hard to read with mulitple functions working in tandem to complete the formatting. Existing packages can extract and format statistics, but they often return output formatted for specific style guides and lack flexibility to precisely control the formatting in other ways. The `{cocoon}` package allows for flexible formatting of statistical objects, statistical values, and numbers more generally to allow users to easily embed statistical information in their reproducible research documents. - - -# Statement of need - -Converting the output of statistical software into a format that can be communicated in documents and presentations can be complicated. Researchers must extract the relevant information from the statistical output then format it in a way to clearly communicate it. Literate programming [@Knuth.1992] involves interweaving code snippets into text, embedding the output of the code to be inserted into the text. A key advantage of literate programming is that the analyses can be reproducible [@Marwick.etal.2018a; @Stodden.etal.2018]. When readers can access the analysis code and see where it is embedded in the text, they are able to directly reproduce the analyses to verify accuracy and explore other possibilities. - -In the R community, the `{knitr}` package [@Xie.2014; @Xie.2015] allows users to embed R code into R Markdown and Quarto documents. However, statistical objects in R are often complicated nested lists that can make it difficult to extract the relevant statistics and values that authors want to report in their documents. Functions have been created that extract commonly used values from statistical objects and return them formatted in a way that can be inserted in inline code. For instance, in the `{papaja}` package [@Aust.Barth.2023], the `apa_print()` function can be applied to a range of statistical objects such as correlations and t-tests to extract test statistics, means, confidence intervals, degrees of freedom, and p-values and return character strings that can be embedded in documents to communicate the statistics. - -In the field of psychology, a number of packages have been developed to extract and return common statistics for integration in documents [e.g., `{apa}` @Gromer.2023; `{insight}` @Ludecke.etal.2019; `{papaja}` @Aust.Barth.2023]. A key limitation of these packages though, is that they tend to only format statistics using the American Psychological Association (APA) Style Guide. This means that the formatting is very specific in how statistics are presented. For instance, APA style requires that the leading zero before values that can only range between -1 and 1 must be removed. So correlations and p-values do not have a leading zero (e.g., _r_ = -.15, _p_ = .05). Many scientific journals and other outlets of research have different style guides. The existing packages for formatting statistics are relatively inflexible in how those statistics are formatted. Moreover, some of those packages output only LaTeX-formatted statistics. Though this is fine for producing PDF documents, LaTeX syntax produces undesirable symbols and mathematical objects when producing HTML and Word documents. Thus, the existing statistical formatting packages lack flexibility in how statistics are formatted and output. - -The aim of the `{cocoon}` package is to provide functions that flexibly format statistical output in a way that can be inserted into R Markdown or Quarto documents. The `{cocoon}` package uses APA style as the default, but it allows more flexible formatting of which statistics are included, how the labels are formatted, and how the values are formatted. All functions also output Markdown syntax by default but can be modified to output LaTeX syntax. - -The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., `r cocoon::format_stats(cor.test(mtcars$mpg, mtcars$cyl))`). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., `r cocoon::format_bf(12.3)`). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., `r cocoon::format_meanci(x = mtcars$mpg)` OR `r cocoon::format_meanci(values = c(12.55, 12.48, 12.63))`). - - -The suite of functions in `{cocoon}` allows users to control numbers of digits, leading zeros, cutoff minima/maxima, the presence of means, confidence intervals, and degrees of freedom, statistical labels, italics, and output format (Markdown or LaTeX). These options give users control over the formatting of their statistics, thereby facilitating a flexible, consistent way of communicating their statistics. - - -# References diff --git a/paper.bib b/paper.bib deleted file mode 100644 index e2e34be..0000000 --- a/paper.bib +++ /dev/null @@ -1,118 +0,0 @@ -@manual{Aust.Barth.2023, - type = {manual}, - title = {{{papaja}}: {{Prepare}} reproducible {{APA}} journal articles with {{R Markdown}}}, - author = {Aust, Frederik and Barth, Marius}, - year = {2023} -} - -@manual{Gromer.2023, - type = {manual}, - title = {apa: {{Format}} outputs of statistical tests according to {{APA}} guidelines}, - author = {Gromer, Daniel}, - year = {2023} -} - -@book{Knuth.1992, - title = {Literate {{Programming}}}, - author = {Knuth, Donald E.}, - year = {1992}, - month = mar, - publisher = {Cambridge University Press}, - abstract = {Literate programming is a programming methodology that combines a programming language with a documentation language, making programs more robust, more portable, and more easily maintained than programs written only in a high-level language. Computer programmers already know both kinds of languages; they need only learn a few conventions about alternating between languages to create programs that are works of literature. A literate programmer is an essayist who writes programs for humans to understand, instead of primarily writing instructions for machines to follow. When programs are written in the recommended style they can be transformed into documents by a document compiler and into efficient code by an algebraic compiler. This anthology of essays from the inventor of literate programming includes Knuth's early papers on related topics such as structured programming, as well as the Computer Journal article that launched literate programming itself.}, - googlebooks = {fqPIPgAACAAJ}, - isbn = {978-0-937073-80-3}, - langid = {english}, - keywords = {Computers / Social Aspects} -} - -@article{Ludecke.etal.2019, - title = {{{insight}}: a unified interface to access information from model objects in {{R}}}, - author = {L{\"u}decke, Daniel and Waggoner, Philip and Makowski, Dominique}, - year = {2019}, - journal = {Journal of Open Source Software}, - volume = {4}, - number = {38}, - pages = {1412}, - doi = {10.21105/joss.01412} -} - -@article{Makowski.etal.2020, - title = {Methods and algorithms for correlation analysis in {{R}}}, - author = {Makowski, Dominique and {Ben-Shachar}, Mattan S. and Patil, Indrajeet and L{\"u}decke, Daniel}, - year = {2020}, - journal = {Journal of Open Source Software}, - volume = {5}, - number = {51}, - pages = {2306}, - doi = {10.21105/joss.02306} -} - -@misc{Makowski.etal.2022, - title = {{{correlation}}: {{Methods}} for correlation analysis}, - shorttitle = {{{correlation}}}, - author = {Makowski, Dominique and Wiernik, Brenton M. and Patil, Indrajeet and L{\"u}decke, Daniel and {Ben-Shachar}, Mattan S.}, - year = {2022}, - month = oct -} - -@article{Marwick.etal.2018a, - title = {Packaging data analytical work reproducibly using {{R}} (and friends)}, - author = {Marwick, Ben and Boettiger, Carl and Mullen, Lincoln}, - year = {2018}, - month = jan, - journal = {The American Statistician}, - volume = {72}, - number = {1}, - pages = {80--88}, - publisher = {Taylor \& Francis}, - issn = {0003-1305}, - doi = {10.1080/00031305.2017.1375986}, - urldate = {2021-12-30}, - abstract = {Computers are a central tool in the research process, enabling complex and large-scale data analysis. As computer-based research has increased in complexity, so have the challenges of ensuring that this research is reproducible. To address this challenge, we review the concept of the research compendium as a solution for providing a standard and easily recognizable way for organizing the digital materials of a research project to enable other researchers to inspect, reproduce, and extend the research. We investigate how the structure and tooling of software packages of the R programming language are being used to produce research compendia in a variety of disciplines. We also describe how software engineering tools and services are being used by researchers to streamline working with research compendia. Using real-world examples, we show how researchers can improve the reproducibility of their work using research compendia based on R packages and related tools.}, - keywords = {Computational science,Data science,Open source software,Reproducible research}, - file = {/home/jstevens/zotero-library/Marwick et al/marwick_et_al_2018_packaging_data_analytical_work_reproducibly_using_r_(and_friends)2.pdf} -} - -@manual{Morey.Rouder.2024, - type = {manual}, - title = {{{BayesFactor}}: {{Computation}} of bayes factors for common designs}, - author = {Morey, Richard D. and Rouder, Jeffrey N.}, - year = {2024} -} - -@book{Stodden.etal.2018, - title = {Implementing reproducible research}, - editor = {Stodden, Victoria and Leisch, Friedrich and Peng, Roger D.}, - year = {2018}, - month = dec, - publisher = {{Chapman and Hall/CRC}}, - address = {New York}, - doi = {10.1201/9781315373461}, - abstract = {In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.}, - isbn = {978-1-315-37346-1}, - file = {/home/jstevens/zotero-library/Stodden et al/stodden_et_al_2018_implementing_reproducible_research.pdf;/home/jstevens/zotero-library/Stodden et al/stodden_et_al_2018_implementing_reproducible_research2.pdf} -} - -@incollection{Xie.2014, - title = {knitr: {{A Comprehensive Tool}} for {{Reproducible Research}} in {{R}}}, - booktitle = {Implementing {{Reproducible Research}}}, - author = {Xie, Yihui}, - editor = {Stodden, V and Leisch, F and Peng, R D}, - year = {2014}, - pages = {3--32}, - publisher = {CRC Press}, - address = {Boca Raton, FL}, - file = {/home/jstevens/zotero-library/Xie/xie_2014_knitr_-_a_comprehensive_tool_for_reproducible_research_in_r.pdf} -} - -@book{Xie.2015, - title = {Dynamic {{Documents}} with {{R}} and knitr}, - author = {Xie, Yihui}, - year = {2015}, - month = jun, - edition = {2nd}, - publisher = {CRC Press}, - address = {Boca Raton, FL}, - urldate = {2017-06-28}, - abstract = {Quickly and Easily Write Dynamic Documents Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams, books, blogs, and web} -} diff --git a/paper.md b/paper.md deleted file mode 100644 index 89462c3..0000000 --- a/paper.md +++ /dev/null @@ -1,44 +0,0 @@ ---- -title: 'cocoon: An R package for extracting, formatting, and printing statistical output' -tags: - - R - - formatting - - LaTeX - - Markdown - - statistical objects -authors: - - name: Jeffrey R. Stevens - orcid: 0000-0003-2375-1360 - affiliation: 1 -affiliations: - - name: Department of Psychology, Center for Brain, Biology & Behavior, University of Nebraska-Lincoln - index: 1 -date: "2024-10-11" -bibliography: paper.bib -output: - html_document: - keep_md: yes ---- - -# Summary - -Formatting statistics from R statistical objects can be troublesome. One must first find, extract, and include the relevant statistical values, format the values properly with leading zeros and appropriate rounding, and format the statistical labels to match norms or style guides. Doing this with inline code can be messy and hard to read with mulitple functions working in tandem to complete the formatting. Existing packages can extract and format statistics, but they often return output formatted for specific style guides and lack flexibility to precisely control the formatting in other ways. The `{cocoon}` package allows for flexible formatting of statistical objects, statistical values, and numbers more generally to allow users to easily embed statistical information in their reproducible research documents. - - -# Statement of need - -Converting the output of statistical software into a format that can be communicated in documents and presentations can be complicated. Researchers must extract the relevant information from the statistical output then format it in a way to clearly communicate it. Literate programming [@Knuth.1992] involves interweaving code snippets into text, embedding the output of the code to be inserted into the text. A key advantage of literate programming is that the analyses can be reproducible [@Marwick.etal.2018a; @Stodden.etal.2018]. When readers can access the analysis code and see where it is embedded in the text, they are able to directly reproduce the analyses to verify accuracy and explore other possibilities. - -In the R community, the `{knitr}` package [@Xie.2014; @Xie.2015] allows users to embed R code into R Markdown and Quarto documents. However, statistical objects in R are often complicated nested lists that can make it difficult to extract the relevant statistics and values that authors want to report in their documents. Functions have been created that extract commonly used values from statistical objects and return them formatted in a way that can be inserted in inline code. For instance, in the `{papaja}` package [@Aust.Barth.2023], the `apa_print()` function can be applied to a range of statistical objects such as correlations and t-tests to extract test statistics, means, confidence intervals, degrees of freedom, and p-values and return character strings that can be embedded in documents to communicate the statistics. - -In the field of psychology, a number of packages have been developed to extract and return common statistics for integration in documents [e.g., `{apa}` @Gromer.2023; `{insight}` @Ludecke.etal.2019; `{papaja}` @Aust.Barth.2023]. A key limitation of these packages though, is that they tend to only format statistics using the American Psychological Association (APA) Style Guide. This means that the formatting is very specific in how statistics are presented. For instance, APA style requires that the leading zero before values that can only range between -1 and 1 must be removed. So correlations and p-values do not have a leading zero (e.g., _r_ = -.15, _p_ = .05). Many scientific journals and other outlets of research have different style guides. The existing packages for formatting statistics are relatively inflexible in how those statistics are formatted. Moreover, some of those packages output only LaTeX-formatted statistics. Though this is fine for producing PDF documents, LaTeX syntax produces undesirable symbols and mathematical objects when producing HTML and Word documents. Thus, the existing statistical formatting packages lack flexibility in how statistics are formatted and output. - -The aim of the `{cocoon}` package is to provide functions that flexibly format statistical output in a way that can be inserted into R Markdown or Quarto documents. The `{cocoon}` package uses APA style as the default, but it allows more flexible formatting of which statistics are included, how the labels are formatted, and how the values are formatted. All functions also output Markdown syntax by default but can be modified to output LaTeX syntax. - -The `{cocoon}` package includes a number of functions to format different kinds of inputs. The `format_stats()` generic function applies methods for specific object classes to extract relevant statistics. For instance, applying `format_stats()` to an object returned by `cor.test()` will extract correlation coefficients, confidence intervals, and p-values from the object and generate a character string than can be embedded inline in an R Markdown or Quarto document (e.g., _r_ = -.85, 95% CI [-0.93, -0.72], _p_ < .001). In addition, other functions can be applied directly to numeric values themselves to format them appropriately. For example, the `format_bf()` function can take a numeric value representing a Bayes factor and prepend it will a label and equals sign (e.g., _BF_~10~ = 12.3). The `format_summary()` functions can either calculate summary statistics from a data vector or directly format a vector of central tendency and upper and lower error bounds (e.g., _M_ = 20.1, 95% CI [17.9, 22.3] OR _M_ = 12.6, 95% CI [12.5, 12.6]). - - -The suite of functions in `{cocoon}` allows users to control numbers of digits, leading zeros, cutoff minima/maxima, the presence of means, confidence intervals, and degrees of freedom, statistical labels, italics, and output format (Markdown or LaTeX). These options give users control over the formatting of their statistics, thereby facilitating a flexible, consistent way of communicating their statistics. - - -# References From 91bd090085dba00a7617402d7908372cd4f37b68 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Tue, 26 Nov 2024 15:32:18 -0600 Subject: [PATCH 08/19] Add format_stats.aov() method --- NAMESPACE | 1 + R/format_stats.R | 100 ++++++++++++++++++++++++++++ man/format_bf.Rd | 1 + man/format_corr.Rd | 1 + man/format_stats.BFBayesFactor.Rd | 1 + man/format_stats.Rd | 1 + man/format_stats.easycorrelation.Rd | 1 + man/format_stats.htest.Rd | 1 + man/format_ttest.Rd | 1 + 9 files changed, 108 insertions(+) diff --git a/NAMESPACE b/NAMESPACE index b42d8fc..c33c846 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,6 +1,7 @@ # Generated by roxygen2: do not edit by hand S3method(format_stats,BFBayesFactor) +S3method(format_stats,aov) S3method(format_stats,default) S3method(format_stats,easycorrelation) S3method(format_stats,htest) diff --git a/R/format_stats.R b/R/format_stats.R index 9a7c6c0..58e711c 100644 --- a/R/format_stats.R +++ b/R/format_stats.R @@ -288,6 +288,106 @@ format_stats.easycorrelation <- function(x, type = type) } +#' Title +#' +#' @param x An `aov` object +#' @param term Character string for row name of term to extract statistics for. +#' This must be the exact string returned in the `summary()` output from the +#' `aov` object +#' @param digits Number of digits after the decimal for means, confidence +#' intervals, and test statistics +#' @param pdigits Number of digits after the decimal for p-values, ranging +#' between 1-5 (also controls cutoff for small p-values) +#' @param pzero Logical value (default = FALSE) for whether to include +#' leading zero for p-values +#' @param italics Logical value (default = TRUE) for whether _p_ label should be +#' italicized +#' @param dfs Formatting for degrees of freedom ("par" = parenthetical, +#' "sub" = subscript, "none" = do not print degrees of freedom) +#' @param type Type of formatting ("md" = markdown, "latex" = LaTeX) +#' @param ... Additional arguments passed to methods. +#' +#' @return +#' A character string of statistical information formatted in Markdown or LaTeX. +#' +#' @method format_stats aov +#' @family functions for printing statistical objects + +#' @export +#' +#' @examples +#' test_aov <- aov(mpg ~ cyl, data = mtcars) +format_stats.aov <- function(x, + term, + digits = 1, + pdigits = 3, + pzero = FALSE, + # full = TRUE, + italics = TRUE, + dfs = "par", + # mean = "abbr", + type = "md", + ...) { + # Validate arguments + if (!is.null(digits)) { + stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) + stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) + } + stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = is.numeric(pdigits)) + stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits > 0) + stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits < 6) + stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) + # stopifnot("Argument `full` must be TRUE or FALSE." = is.logical(full)) + stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) + stopifnot("Argument `dfs` must be 'par', 'sub', or 'none'." = dfs %in% c("par", "sub", "none")) + # stopifnot("Argument `mean` must be 'abbr' or 'word'." = mean %in% c("abbr", "word")) + stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + + terms <- attr(x$terms, "term.labels") + stopifnot("Argument `term` not found in model terms." = term %in% terms) + term_num <- which(terms == term) + + summ <- summary(x) + + f_stat <- summ[[1]][["F value"]][term_num] + df1 <- summ[[1]][["Df"]][term_num] + df2 <- x$df.residual + p_value <- summ[[1]][["Pr(>F)"]][term_num] + + stat_value <- format_num(f_stat, digits = digits, pzero = TRUE) + pvalue <- format_p(p_value, + digits = pdigits, pzero = pzero, + italics = italics, type = type + ) + + # Build label + statlab <- "F" + stat_label <- dplyr::case_when( + !italics ~ paste0(statlab), + identical(type, "md") ~ paste0("_", statlab, "_"), + identical(type, "latex") ~ paste0("$", statlab, "$") + ) + stat_label <- dplyr::case_when(identical(dfs, "par") ~ paste0(stat_label, "(", df1, ", ", df2, ")"), + identical(dfs, "sub") & identical(type, "md") ~ paste0(stat_label, "~", df1, ", ", df2, "~"), + identical(dfs, "sub") & identical(type, "latex") ~ paste0(stat_label, "$_{", df1, ", ", df2, "}$"), + .default = stat_label + )[1] + + # Create statistics string + + build_string(mean_label = NULL, + mean_value = NULL, + cis = FALSE, + stat_label = stat_label, + stat_value = stat_value, + pvalue = pvalue, + full = FALSE) +} + + + + + #' Format Bayes factors #' #' This method formats Bayes factors from the diff --git a/man/format_bf.Rd b/man/format_bf.Rd index 76bd647..461fde7 100644 --- a/man/format_bf.Rd +++ b/man/format_bf.Rd @@ -92,6 +92,7 @@ Other functions for printing statistical objects: \code{\link{format_corr}()}, \code{\link{format_stats}()}, \code{\link{format_stats.BFBayesFactor}()}, +\code{\link{format_stats.aov}()}, \code{\link{format_stats.easycorrelation}()}, \code{\link{format_stats.htest}()}, \code{\link{format_ttest}()} diff --git a/man/format_corr.Rd b/man/format_corr.Rd index fec7ade..9980c7c 100644 --- a/man/format_corr.Rd +++ b/man/format_corr.Rd @@ -48,6 +48,7 @@ Other functions for printing statistical objects: \code{\link{format_bf}()}, \code{\link{format_stats}()}, \code{\link{format_stats.BFBayesFactor}()}, +\code{\link{format_stats.aov}()}, \code{\link{format_stats.easycorrelation}()}, \code{\link{format_stats.htest}()}, \code{\link{format_ttest}()} diff --git a/man/format_stats.BFBayesFactor.Rd b/man/format_stats.BFBayesFactor.Rd index 1080e5c..bac790e 100644 --- a/man/format_stats.BFBayesFactor.Rd +++ b/man/format_stats.BFBayesFactor.Rd @@ -77,6 +77,7 @@ Other functions for printing statistical objects: \code{\link{format_bf}()}, \code{\link{format_corr}()}, \code{\link{format_stats}()}, +\code{\link{format_stats.aov}()}, \code{\link{format_stats.easycorrelation}()}, \code{\link{format_stats.htest}()}, \code{\link{format_ttest}()} diff --git a/man/format_stats.Rd b/man/format_stats.Rd index f11d09b..bdea406 100644 --- a/man/format_stats.Rd +++ b/man/format_stats.Rd @@ -49,6 +49,7 @@ Other functions for printing statistical objects: \code{\link{format_bf}()}, \code{\link{format_corr}()}, \code{\link{format_stats.BFBayesFactor}()}, +\code{\link{format_stats.aov}()}, \code{\link{format_stats.easycorrelation}()}, \code{\link{format_stats.htest}()}, \code{\link{format_ttest}()} diff --git a/man/format_stats.easycorrelation.Rd b/man/format_stats.easycorrelation.Rd index dbb6259..c9697a2 100644 --- a/man/format_stats.easycorrelation.Rd +++ b/man/format_stats.easycorrelation.Rd @@ -72,6 +72,7 @@ Other functions for printing statistical objects: \code{\link{format_corr}()}, \code{\link{format_stats}()}, \code{\link{format_stats.BFBayesFactor}()}, +\code{\link{format_stats.aov}()}, \code{\link{format_stats.htest}()}, \code{\link{format_ttest}()} } diff --git a/man/format_stats.htest.Rd b/man/format_stats.htest.Rd index 77ba07a..e9107de 100644 --- a/man/format_stats.htest.Rd +++ b/man/format_stats.htest.Rd @@ -96,6 +96,7 @@ Other functions for printing statistical objects: \code{\link{format_corr}()}, \code{\link{format_stats}()}, \code{\link{format_stats.BFBayesFactor}()}, +\code{\link{format_stats.aov}()}, \code{\link{format_stats.easycorrelation}()}, \code{\link{format_ttest}()} } diff --git a/man/format_ttest.Rd b/man/format_ttest.Rd index ac1fc4e..20868ba 100644 --- a/man/format_ttest.Rd +++ b/man/format_ttest.Rd @@ -51,6 +51,7 @@ Other functions for printing statistical objects: \code{\link{format_corr}()}, \code{\link{format_stats}()}, \code{\link{format_stats.BFBayesFactor}()}, +\code{\link{format_stats.aov}()}, \code{\link{format_stats.easycorrelation}()}, \code{\link{format_stats.htest}()} } From 93ba860c4ef60d66bfd2eaa5b038c19b1d02892a Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Tue, 26 Nov 2024 15:32:34 -0600 Subject: [PATCH 09/19] Add format_stats.aov() tests --- tests/testthat/helper.R | 1 + tests/testthat/test-format_stats.R | 75 +++++++++++++++++++++++++++--- 2 files changed, 69 insertions(+), 7 deletions(-) diff --git a/tests/testthat/helper.R b/tests/testthat/helper.R index 849f0fe..27cf0f1 100644 --- a/tests/testthat/helper.R +++ b/tests/testthat/helper.R @@ -11,5 +11,6 @@ test_ttest3 <- suppressWarnings(wilcox.test(df$a, mu = 5)) test_ttest4 <- suppressWarnings(wilcox.test(df$a, df$b)) test_ttest5 <- suppressWarnings(wilcox.test(df$a, c(df$b, 120))) test_chisq <- chisq.test(as.table(rbind(c(762, 327, 468), c(484, 239, 477)))) +test_aov <- aov(c ~ a, data = df) test_bf <- BayesFactor::ttestBF(df$a, mu = 5) diff --git a/tests/testthat/test-format_stats.R b/tests/testthat/test-format_stats.R index 6a63e39..73f191c 100644 --- a/tests/testthat/test-format_stats.R +++ b/tests/testthat/test-format_stats.R @@ -22,6 +22,18 @@ test_that("unavailable format_stats() methods are aborted", { }) + +test_that("format_stats() works properly for accepted objects", { + expect_no_error(format_stats(test_ttest)) + expect_no_error(format_stats(test_corr)) + expect_no_error(format_stats(test_easycorr)) + expect_no_error(format_stats(test_easycorr2)) + expect_no_error(format_stats(test_easycorr3)) + expect_no_error(format_stats(test_aov, "a")) + expect_no_error(format_stats(test_bf)) +}) + + test_that("htest correlations are validated properly", { suppressMessages(expect_error( format_stats(test_corr, digits = "xxx"), @@ -61,6 +73,7 @@ test_that("htest correlations are validated properly", { )) }) + test_that("correlation correlations are validated properly", { suppressMessages(expect_error( format_stats(test_easycorr, digits = "xxx"), @@ -100,6 +113,7 @@ test_that("correlation correlations are validated properly", { )) }) + test_that("formatting correlations works properly", { expect_equal(format_stats(test_corr), "_r_ = 1.00, 95% CI [1.00, 1.00], _p_ < .001") expect_equal(format_stats(test_corr, digits = 3), "_r_ = 1.000, 95% CI [1.000, 1.000], _p_ < .001") @@ -114,6 +128,7 @@ test_that("formatting correlations works properly", { expect_equal(format_stats(cor.test(df$a, df$b, method = "spearman")), "_ρ_ = 1.00, _p_ < .001") }) + test_that("htest t-tests are validated properly", { suppressMessages(expect_error( format_stats(test_ttest, digits = "xxx"), @@ -161,6 +176,7 @@ test_that("htest t-tests are validated properly", { )) }) + test_that("formatting t-tests works properly", { expect_equal(format_stats(test_ttest1), "_M_ = 5.5, 95% CI [3.3, 7.7], _t_(9) = 0.5, _p_ = .614") expect_equal(format_stats(test_ttest), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = .470") @@ -180,15 +196,60 @@ test_that("formatting t-tests works properly", { suppressMessages(expect_equal(format_stats(test_ttest5), "_W_ = 40.5, _p_ = .323")) }) -test_that("format_stats() works properly for htest and BayesFactor objects", { - expect_no_error(format_stats(test_ttest)) - expect_no_error(format_stats(test_corr)) - expect_no_error(format_stats(test_easycorr)) - expect_no_error(format_stats(test_easycorr2)) - expect_no_error(format_stats(test_easycorr3)) - expect_no_error(format_stats(test_bf)) + +test_that("aov ANOVAs are validated properly", { + suppressMessages(expect_error( + format_stats(test_aov, digits = "xxx"), + "Argument `digits` must be a non-negative numeric vector" + )) + suppressMessages(expect_error( + format_stats(test_aov, digits = -1), + "Argument `digits` must be a non-negative numeric vector" + )) + suppressMessages(expect_error( + format_stats(test_aov, pdigits = "xxx"), + "Argument `pdigits` must be a numeric between 1 and 5" + )) + suppressMessages(expect_error( + format_stats(test_aov, pdigits = 0), + "Argument `pdigits` must be a numeric between 1 and 5" + )) + suppressMessages(expect_error( + format_stats(test_aov, pdigits = 7), + "Argument `pdigits` must be a numeric between 1 and 5" + )) + suppressMessages(expect_error( + format_stats(test_aov, pzero = "xxx"), + "Argument `pzero` must be TRUE or FALSE" + )) + suppressMessages(expect_error( + format_stats(test_aov, italics = "xxx"), + "Argument `italics` must be TRUE or FALSE" + )) + suppressMessages(expect_error( + format_stats(test_aov, dfs = "xxx"), + "Argument `dfs` must be 'par', 'sub', or 'none'" + )) + suppressMessages(expect_error( + format_stats(test_aov, type = "xxx"), + "Argument `type` must be 'md' or 'latex'" + )) +}) + + +test_that("formatting ANOVAs works properly", { + expect_equal(format_stats(test_aov, "a"), "_F_(1, 8) = 0.1, _p_ = .748") + expect_equal(format_stats(test_aov, "a", digits = 2), "_F_(1, 8) = 0.11, _p_ = .748") + expect_equal(format_stats(test_aov, "a", pdigits = 2), "_F_(1, 8) = 0.1, _p_ = .75") + expect_equal(format_stats(test_aov, "a", pzero = TRUE), "_F_(1, 8) = 0.1, _p_ = 0.748") + expect_equal(format_stats(test_aov, "a", italics = FALSE), "F(1, 8) = 0.1, p = .748") + expect_equal(format_stats(test_aov, "a", dfs = "sub"), "_F_~1, 8~ = 0.1, _p_ = .748") + expect_equal(format_stats(test_aov, "a", dfs = "none"), "_F_ = 0.1, _p_ = .748") + expect_equal(format_stats(test_aov, "a", type = "latex"), "$F$(1, 8) = 0.1, $p$ = .748") + expect_equal(format_stats(test_aov, "a", type = "latex", dfs = "sub"), "$F$$_{1, 8}$ = 0.1, $p$ = .748") }) + test_that("format_stats.BFBayesFactor() validates arguments properly", { suppressMessages(expect_error( format_stats(test_bf, digits1 = "xxx"), From 848a73b779aa0662062d0910c16d0928b60e2441 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Tue, 26 Nov 2024 15:32:56 -0600 Subject: [PATCH 10/19] Add format_stats.aov() documentation --- man/format_stats.aov.Rd | 64 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 64 insertions(+) create mode 100644 man/format_stats.aov.Rd diff --git a/man/format_stats.aov.Rd b/man/format_stats.aov.Rd new file mode 100644 index 0000000..9784167 --- /dev/null +++ b/man/format_stats.aov.Rd @@ -0,0 +1,64 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/format_stats.R +\name{format_stats.aov} +\alias{format_stats.aov} +\title{Title} +\usage{ +\method{format_stats}{aov}( + x, + term, + digits = 1, + pdigits = 3, + pzero = FALSE, + italics = TRUE, + dfs = "par", + type = "md", + ... +) +} +\arguments{ +\item{x}{An \code{aov} object} + +\item{term}{Character string for row name of term to extract statistics for. +This must be the exact string returned in the \code{summary()} output from the +\code{aov} object} + +\item{digits}{Number of digits after the decimal for means, confidence +intervals, and test statistics} + +\item{pdigits}{Number of digits after the decimal for p-values, ranging +between 1-5 (also controls cutoff for small p-values)} + +\item{pzero}{Logical value (default = FALSE) for whether to include +leading zero for p-values} + +\item{italics}{Logical value (default = TRUE) for whether \emph{p} label should be +italicized} + +\item{dfs}{Formatting for degrees of freedom ("par" = parenthetical, +"sub" = subscript, "none" = do not print degrees of freedom)} + +\item{type}{Type of formatting ("md" = markdown, "latex" = LaTeX)} + +\item{...}{Additional arguments passed to methods.} +} +\value{ +A character string of statistical information formatted in Markdown or LaTeX. +} +\description{ +Title +} +\examples{ +test_aov <- aov(mpg ~ cyl, data = mtcars) +} +\seealso{ +Other functions for printing statistical objects: +\code{\link{format_bf}()}, +\code{\link{format_corr}()}, +\code{\link{format_stats}()}, +\code{\link{format_stats.BFBayesFactor}()}, +\code{\link{format_stats.easycorrelation}()}, +\code{\link{format_stats.htest}()}, +\code{\link{format_ttest}()} +} +\concept{functions for printing statistical objects} From c0350a76976b470b3f2fcb60c0f1f36f100dc28e Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Wed, 27 Nov 2024 10:40:18 -0600 Subject: [PATCH 11/19] Use rlang standalone checks --- DESCRIPTION | 3 +- NAMESPACE | 2 + R/cocoon-package.R | 2 + R/format_numbers.R | 22 +- R/format_stats.R | 63 +-- R/format_statvalues.R | 69 ++- R/format_summary.R | 17 +- R/import-standalone-obj-type.R | 366 ++++++++++++++ R/import-standalone-types-check.R | 619 ++++++++++++++++++++++++ tests/testthat/helper.R | 1 + tests/testthat/test-format_numbers.R | 26 +- tests/testthat/test-format_stats.R | 143 +++--- tests/testthat/test-format_statvalues.R | 35 +- tests/testthat/test-format_summary.R | 24 +- vignettes/cocoon.Rmd | 1 + 15 files changed, 1208 insertions(+), 185 deletions(-) create mode 100644 R/import-standalone-obj-type.R create mode 100644 R/import-standalone-types-check.R diff --git a/DESCRIPTION b/DESCRIPTION index 8d81765..4517dc9 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -23,7 +23,8 @@ Suggests: Config/testthat/edition: 3 Imports: dplyr, - lifecycle + lifecycle, + rlang (>= 1.1.0) URL: https://github.com/JeffreyRStevens/cocoon, https://jeffreyrstevens.github.io/cocoon/ BugReports: https://github.com/JeffreyRStevens/cocoon/issues VignetteBuilder: knitr diff --git a/NAMESPACE b/NAMESPACE index c33c846..ba73d2d 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -22,3 +22,5 @@ export(format_sub) export(format_summary) export(format_ttest) importFrom(lifecycle,deprecated) +importFrom(rlang,ffi_standalone_check_number_1.0.7) +importFrom(rlang,ffi_standalone_is_bool_1.0.7) diff --git a/R/cocoon-package.R b/R/cocoon-package.R index 425b3c1..79fd574 100644 --- a/R/cocoon-package.R +++ b/R/cocoon-package.R @@ -3,5 +3,7 @@ ## usethis namespace: start #' @importFrom lifecycle deprecated +#' @importFrom rlang ffi_standalone_check_number_1.0.7 +#' @importFrom rlang ffi_standalone_is_bool_1.0.7 ## usethis namespace: end NULL diff --git a/R/format_numbers.R b/R/format_numbers.R index ca7accf..102e1a4 100644 --- a/R/format_numbers.R +++ b/R/format_numbers.R @@ -17,9 +17,8 @@ format_num <- function(x, digits = 1, pzero = TRUE) { # Check arguments - stopifnot("Input must be a numeric vector." = is.numeric(x)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) + check_numeric(x) + check_number_whole(digits, min = 0) # Format number dplyr::case_when( @@ -48,10 +47,9 @@ format_scientific <- function(x, digits = 1, type = "md") { # Check arguments - stopifnot("Input must be a numeric vector." = is.numeric(x)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_numeric(x) + check_number_whole(digits, min = 1) + check_match(type, c("md", "latex")) # Format number num <- formatC(x, digits = digits, format = "e") @@ -91,9 +89,9 @@ format_chr <- function(x, italics = TRUE, type = "md") { # Check arguments - stopifnot("Input must be a character string." = is.character(x)) - stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_string(x) + check_bool(italics) + check_match(type, c("md", "latex")) dplyr::case_when( italics & type == "md" ~ paste0("_", x, "_"), italics & type == "latex" ~ paste0("$", x, "$"), @@ -119,8 +117,8 @@ format_chr <- function(x, format_sub <- function(subscript = NULL, type = "md") { # Check arguments - stopifnot("Input must be a character string or NULL." = is.character(subscript) | is.null(subscript)) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_string(subscript, allow_null = TRUE) + check_match(type, c("md", "latex")) dplyr::case_when( subscript == "" ~ "", !is.null(subscript) & type == "md" ~ paste0("~", subscript, "~"), diff --git a/R/format_stats.R b/R/format_stats.R index 58e711c..9df399e 100644 --- a/R/format_stats.R +++ b/R/format_stats.R @@ -148,19 +148,15 @@ format_stats.htest <- function(x, type = "md", ...) { # Validate arguments - if (!is.null(digits)) { - stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) - } - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = is.numeric(pdigits)) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits > 0) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits < 6) - stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) - stopifnot("Argument `full` must be TRUE or FALSE." = is.logical(full)) - stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - stopifnot("Argument `dfs` must be 'par', 'sub', or 'none'." = dfs %in% c("par", "sub", "none")) - stopifnot("Argument `mean` must be 'abbr' or 'word'." = mean %in% c("abbr", "word")) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_number_whole(digits, min = 0, allow_null = TRUE) + check_number_whole(pdigits, min = 1, max = 5) + check_bool(pzero) + check_bool(full) + check_bool(italics) + check_match(dfs, c("par", "sub", "none")) + check_match(mean, c("abbr", "word")) + check_string(type) + check_match(type, c("md", "latex")) if (grepl("correlation", x$method)) { if (is.null(digits)) { @@ -247,17 +243,13 @@ format_stats.easycorrelation <- function(x, type = "md", ...) { # Validate arguments - if (!is.null(digits)) { - stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) - } - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = is.numeric(pdigits)) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits > 0) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits < 6) - stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) - stopifnot("Argument `full` must be TRUE or FALSE." = is.logical(full)) - stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_number_whole(digits, min = 0, allow_null = TRUE) + check_number_whole(pdigits, min = 1, max = 5) + check_bool(pzero) + check_bool(full) + check_bool(italics) + check_string(type) + check_match(type, c("md", "latex")) if ("r" %in% names(x)) { method <- "Pearson correlation" @@ -322,26 +314,19 @@ format_stats.aov <- function(x, digits = 1, pdigits = 3, pzero = FALSE, - # full = TRUE, italics = TRUE, dfs = "par", - # mean = "abbr", type = "md", ...) { # Validate arguments - if (!is.null(digits)) { - stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) - } - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = is.numeric(pdigits)) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits > 0) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits < 6) - stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) - # stopifnot("Argument `full` must be TRUE or FALSE." = is.logical(full)) - stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - stopifnot("Argument `dfs` must be 'par', 'sub', or 'none'." = dfs %in% c("par", "sub", "none")) - # stopifnot("Argument `mean` must be 'abbr' or 'word'." = mean %in% c("abbr", "word")) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_character(term) + check_number_whole(digits, min = 0, allow_null = TRUE) + check_number_whole(pdigits, min = 1, max = 5) + check_bool(pzero) + check_bool(italics) + check_match(dfs, c("par", "sub", "none")) + check_string(type) + check_match(type, c("md", "latex")) terms <- attr(x$terms, "term.labels") stopifnot("Argument `term` not found in model terms." = term %in% terms) diff --git a/R/format_statvalues.R b/R/format_statvalues.R index 577e8c5..87177ef 100644 --- a/R/format_statvalues.R +++ b/R/format_statvalues.R @@ -33,15 +33,22 @@ format_corr <- function(x, # Validate arguments stopifnot("Input must be a correlation object." = inherits(x, what = "htest") && grepl("correlation", x$method)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) - stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = is.numeric(pdigits)) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits > 0) - stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits < 6) - stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) - stopifnot("Argument `full` must be TRUE or FALSE." = is.logical(full)) - stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_number_whole(digits, min = 0, allow_null = TRUE) + check_number_whole(pdigits, min = 1, max = 5) + check_bool(pzero) + check_bool(full) + check_bool(italics) + check_string(type) + check_match(type, c("md", "latex")) + # stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) + # stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) + # stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = is.numeric(pdigits)) + # stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits > 0) + # stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits < 6) + # stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) + # stopifnot("Argument `full` must be TRUE or FALSE." = is.logical(full)) + # stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) + # stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) # Format numbers corr_method <- dplyr::case_when( @@ -246,14 +253,22 @@ format_bf <- function(x, } # Validate arguments - stopifnot("Argument `digits1` must be a non-negative numeric vector." = is.numeric(digits1)) - stopifnot("Argument `digits1` must be a non-negative numeric vector." = digits1 >= 0) - stopifnot("Argument `digits2` must be a non-negative numeric vector." = is.numeric(digits2)) - stopifnot("Argument `digits2` must be a non-negative numeric vector." = digits2 >= 0) - stopifnot("Argument `cutoff` must be a numeric vector greater than 1 or NULL." = (is.numeric(cutoff) & cutoff > 1) | is.null(cutoff)) - stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - stopifnot("Argument `subscript` must be a character string (usually '10', '01', or '')." = is.character(subscript)) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_number_whole(digits1, min = 0, allow_null = TRUE) + check_number_whole(digits2, min = 0, allow_null = TRUE) + check_number_decimal(cutoff, min = 1, allow_null = TRUE) + check_bool(italics) + check_string(subscript) + check_string(type) + check_match(type, c("md", "latex")) + + # stopifnot("Argument `digits1` must be a non-negative numeric vector." = is.numeric(digits1)) + # stopifnot("Argument `digits1` must be a non-negative numeric vector." = digits1 >= 0) + # stopifnot("Argument `digits2` must be a non-negative numeric vector." = is.numeric(digits2)) + # stopifnot("Argument `digits2` must be a non-negative numeric vector." = digits2 >= 0) + # stopifnot("Argument `cutoff` must be a numeric vector greater than 1 or NULL." = (is.numeric(cutoff) & cutoff > 1) | is.null(cutoff)) + # stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) + # stopifnot("Argument `subscript` must be a character string (usually '10', '01', or '')." = is.character(subscript)) + # stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) # Build label if (label != "") { @@ -350,13 +365,19 @@ format_p <- function(x, italics = TRUE, type = "md") { # Check arguments - stopifnot("Input must be a numeric vector." = is.numeric(x)) - stopifnot("Argument `digits` must be a numeric between 1 and 5." = is.numeric(digits)) - stopifnot("Argument `digits` must be a numeric between 1 and 5." = digits > 0) - stopifnot("Argument `digits` must be a numeric between 1 and 5." = digits < 6) - stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) - stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) + check_numeric(x) + check_number_whole(digits, min = 1, max = 5, allow_null = TRUE) + check_bool(pzero) + check_bool(italics) + check_string(type) + check_match(type, c("md", "latex")) + # stopifnot("Input must be a numeric vector." = is.numeric(x)) + # stopifnot("Argument `digits` must be a numeric between 1 and 5." = is.numeric(digits)) + # stopifnot("Argument `digits` must be a numeric between 1 and 5." = digits > 0) + # stopifnot("Argument `digits` must be a numeric between 1 and 5." = digits < 6) + # stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) + # stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) + # stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) # Build label if (label != "") { diff --git a/R/format_summary.R b/R/format_summary.R index a5fc713..1bd45f4 100644 --- a/R/format_summary.R +++ b/R/format_summary.R @@ -78,15 +78,15 @@ format_summary <- function(x = NULL, type = "md") { # Check arguments if (!is.null(x)) { - stopifnot("Argument `x` must be a numeric vector." = is.numeric(x)) - stopifnot('Specify `tendency` as "mean" or "median".' = tendency %in% c("mean", "median")) - stopifnot('Specify `error` as "ci", "sd", "se", or "iqr".' = error %in% c("ci", "sd", "se", "iqr")) + check_numeric(x) + check_match(tendency, c("mean", "median")) + check_match(error, c("ci", "sd", "se", "iqr")) xtendency <- dplyr::case_when( identical(tendency, "mean") ~ mean(x, na.rm = TRUE), identical(tendency, "median") ~ median(x, na.rm = TRUE) ) xn <- sum(!is.na(x)) - stopifnot("Less than two non-missing values in vector, so no confidence interval can be computed." = xn > 1) + stopifnot("Less than two values in vector, so no confidence interval can be computed." = xn > 1) xlimit <- 1 - (1 - cilevel) / 2 xsd <- stats::sd(x, na.rm = TRUE) xse <- xsd / sqrt(xn) @@ -106,7 +106,7 @@ format_summary <- function(x = NULL, ) xinterval <- xtendency - xlower } else if (!is.null(values)) { - stopifnot("Argument `values` must be a numeric vector." = is.numeric(values)) + check_numeric(values) stopifnot("Argument `values` must be a vector with two or three elements." = length(values) %in% c(2, 3)) if (length(values) == 2) { xtendency <- values[1] @@ -123,12 +123,11 @@ format_summary <- function(x = NULL, } else { stop("You must include either the `x` or `values` argument.") } - stopifnot('Specify `tendlabel` as "abbr", "word", or "none".' = tendlabel %in% c("abbr", "word", "none")) - stopifnot("The `units` argument must be a character vector or NULL" = is.character(units) | is.null(units)) - stopifnot('Specify `display` as "limits", "pm", "par", or "none".' = display %in% c("limits", "pm", "par", "none")) + check_match(tendlabel, c("abbr", "word", "none")) + check_character(units, allow_null = TRUE) + check_match(display, c("limits", "pm", "par", "none")) # Build mean - # subname <- ifelse(!is.null(subscript), subscript, "") unit <- dplyr::case_when( !is.null(units) ~ paste0(" ", units), .default = "" diff --git a/R/import-standalone-obj-type.R b/R/import-standalone-obj-type.R new file mode 100644 index 0000000..31b5db9 --- /dev/null +++ b/R/import-standalone-obj-type.R @@ -0,0 +1,366 @@ +# Standalone file: do not edit by hand +# Source: https://github.com/r-lib/rlang/blob/HEAD/R/standalone-obj-type.R +# Generated by: usethis::use_standalone("r-lib/rlang", "obj-type") +# ---------------------------------------------------------------------- +# +# --- +# repo: r-lib/rlang +# file: standalone-obj-type.R +# last-updated: 2024-02-14 +# license: https://unlicense.org +# imports: rlang (>= 1.1.0) +# --- +# +# ## Changelog +# +# 2024-02-14: +# - `obj_type_friendly()` now works for S7 objects. +# +# 2023-05-01: +# - `obj_type_friendly()` now only displays the first class of S3 objects. +# +# 2023-03-30: +# - `stop_input_type()` now handles `I()` input literally in `arg`. +# +# 2022-10-04: +# - `obj_type_friendly(value = TRUE)` now shows numeric scalars +# literally. +# - `stop_friendly_type()` now takes `show_value`, passed to +# `obj_type_friendly()` as the `value` argument. +# +# 2022-10-03: +# - Added `allow_na` and `allow_null` arguments. +# - `NULL` is now backticked. +# - Better friendly type for infinities and `NaN`. +# +# 2022-09-16: +# - Unprefixed usage of rlang functions with `rlang::` to +# avoid onLoad issues when called from rlang (#1482). +# +# 2022-08-11: +# - Prefixed usage of rlang functions with `rlang::`. +# +# 2022-06-22: +# - `friendly_type_of()` is now `obj_type_friendly()`. +# - Added `obj_type_oo()`. +# +# 2021-12-20: +# - Added support for scalar values and empty vectors. +# - Added `stop_input_type()` +# +# 2021-06-30: +# - Added support for missing arguments. +# +# 2021-04-19: +# - Added support for matrices and arrays (#141). +# - Added documentation. +# - Added changelog. +# +# nocov start + +library(rlang) + +#' Return English-friendly type +#' @param x Any R object. +#' @param value Whether to describe the value of `x`. Special values +#' like `NA` or `""` are always described. +#' @param length Whether to mention the length of vectors and lists. +#' @return A string describing the type. Starts with an indefinite +#' article, e.g. "an integer vector". +#' @noRd +obj_type_friendly <- function(x, value = TRUE) { + if (rlang::is_missing(x)) { + return("absent") + } + + if (is.object(x)) { + if (inherits(x, "quosure")) { + type <- "quosure" + } else { + type <- class(x)[[1L]] + } + return(sprintf("a <%s> object", type)) + } + + if (!rlang::is_vector(x)) { + return(.rlang_as_friendly_type(typeof(x))) + } + + n_dim <- length(dim(x)) + + if (!n_dim) { + if (!rlang::is_list(x) && length(x) == 1) { + if (rlang::is_na(x)) { + return(switch( + typeof(x), + logical = "`NA`", + integer = "an integer `NA`", + double = + if (is.nan(x)) { + "`NaN`" + } else { + "a numeric `NA`" + }, + complex = "a complex `NA`", + character = "a character `NA`", + .rlang_stop_unexpected_typeof(x) + )) + } + + show_infinites <- function(x) { + if (x > 0) { + "`Inf`" + } else { + "`-Inf`" + } + } + str_encode <- function(x, width = 30, ...) { + if (nchar(x) > width) { + x <- substr(x, 1, width - 3) + x <- paste0(x, "...") + } + encodeString(x, ...) + } + + if (value) { + if (is.numeric(x) && is.infinite(x)) { + return(show_infinites(x)) + } + + if (is.numeric(x) || is.complex(x)) { + number <- as.character(round(x, 2)) + what <- if (is.complex(x)) "the complex number" else "the number" + return(paste(what, number)) + } + + return(switch( + typeof(x), + logical = if (x) "`TRUE`" else "`FALSE`", + character = { + what <- if (nzchar(x)) "the string" else "the empty string" + paste(what, str_encode(x, quote = "\"")) + }, + raw = paste("the raw value", as.character(x)), + .rlang_stop_unexpected_typeof(x) + )) + } + + return(switch( + typeof(x), + logical = "a logical value", + integer = "an integer", + double = if (is.infinite(x)) show_infinites(x) else "a number", + complex = "a complex number", + character = if (nzchar(x)) "a string" else "\"\"", + raw = "a raw value", + .rlang_stop_unexpected_typeof(x) + )) + } + + if (length(x) == 0) { + return(switch( + typeof(x), + logical = "an empty logical vector", + integer = "an empty integer vector", + double = "an empty numeric vector", + complex = "an empty complex vector", + character = "an empty character vector", + raw = "an empty raw vector", + list = "an empty list", + .rlang_stop_unexpected_typeof(x) + )) + } + } + + vec_type_friendly(x) +} + +vec_type_friendly <- function(x, length = FALSE) { + if (!rlang::is_vector(x)) { + rlang::abort("`x` must be a vector.") + } + type <- typeof(x) + n_dim <- length(dim(x)) + + add_length <- function(type) { + if (length && !n_dim) { + paste0(type, sprintf(" of length %s", length(x))) + } else { + type + } + } + + if (type == "list") { + if (n_dim < 2) { + return(add_length("a list")) + } else if (is.data.frame(x)) { + return("a data frame") + } else if (n_dim == 2) { + return("a list matrix") + } else { + return("a list array") + } + } + + type <- switch( + type, + logical = "a logical %s", + integer = "an integer %s", + numeric = , + double = "a double %s", + complex = "a complex %s", + character = "a character %s", + raw = "a raw %s", + type = paste0("a ", type, " %s") + ) + + if (n_dim < 2) { + kind <- "vector" + } else if (n_dim == 2) { + kind <- "matrix" + } else { + kind <- "array" + } + out <- sprintf(type, kind) + + if (n_dim >= 2) { + out + } else { + add_length(out) + } +} + +.rlang_as_friendly_type <- function(type) { + switch( + type, + + list = "a list", + + NULL = "`NULL`", + environment = "an environment", + externalptr = "a pointer", + weakref = "a weak reference", + S4 = "an S4 object", + + name = , + symbol = "a symbol", + language = "a call", + pairlist = "a pairlist node", + expression = "an expression vector", + + char = "an internal string", + promise = "an internal promise", + ... = "an internal dots object", + any = "an internal `any` object", + bytecode = "an internal bytecode object", + + primitive = , + builtin = , + special = "a primitive function", + closure = "a function", + + type + ) +} + +.rlang_stop_unexpected_typeof <- function(x, call = rlang::caller_env()) { + rlang::abort( + sprintf("Unexpected type <%s>.", typeof(x)), + call = call + ) +} + +#' Return OO type +#' @param x Any R object. +#' @return One of `"bare"` (for non-OO objects), `"S3"`, `"S4"`, +#' `"R6"`, or `"S7"`. +#' @noRd +obj_type_oo <- function(x) { + if (!is.object(x)) { + return("bare") + } + + class <- inherits(x, c("R6", "S7_object"), which = TRUE) + + if (class[[1]]) { + "R6" + } else if (class[[2]]) { + "S7" + } else if (isS4(x)) { + "S4" + } else { + "S3" + } +} + +#' @param x The object type which does not conform to `what`. Its +#' `obj_type_friendly()` is taken and mentioned in the error message. +#' @param what The friendly expected type as a string. Can be a +#' character vector of expected types, in which case the error +#' message mentions all of them in an "or" enumeration. +#' @param show_value Passed to `value` argument of `obj_type_friendly()`. +#' @param ... Arguments passed to [abort()]. +#' @inheritParams args_error_context +#' @noRd +stop_input_type <- function(x, + what, + ..., + allow_na = FALSE, + allow_null = FALSE, + show_value = TRUE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + # From standalone-cli.R + cli <- rlang::env_get_list( + nms = c("format_arg", "format_code"), + last = topenv(), + default = function(x) sprintf("`%s`", x), + inherit = TRUE + ) + + if (allow_na) { + what <- c(what, cli$format_code("NA")) + } + if (allow_null) { + what <- c(what, cli$format_code("NULL")) + } + if (length(what)) { + what <- oxford_comma(what) + } + if (inherits(arg, "AsIs")) { + format_arg <- identity + } else { + format_arg <- cli$format_arg + } + + message <- sprintf( + "%s must be %s, not %s.", + format_arg(arg), + what, + obj_type_friendly(x, value = show_value) + ) + + rlang::abort(message, ..., call = call, arg = arg) +} + +oxford_comma <- function(chr, sep = ", ", final = "or") { + n <- length(chr) + + if (n < 2) { + return(chr) + } + + head <- chr[seq_len(n - 1)] + last <- chr[n] + + head <- paste(head, collapse = sep) + + # Write a or b. But a, b, or c. + if (n > 2) { + paste0(head, sep, final, " ", last) + } else { + paste0(head, " ", final, " ", last) + } +} + +# nocov end diff --git a/R/import-standalone-types-check.R b/R/import-standalone-types-check.R new file mode 100644 index 0000000..a019510 --- /dev/null +++ b/R/import-standalone-types-check.R @@ -0,0 +1,619 @@ +# Standalone file: do not edit by hand +# Source: https://github.com/r-lib/rlang/blob/HEAD/R/standalone-types-check.R +# Generated by: usethis::use_standalone("r-lib/rlang", "types-check") +# ---------------------------------------------------------------------- +# +# --- +# repo: r-lib/rlang +# file: standalone-types-check.R +# last-updated: 2023-03-13 +# license: https://unlicense.org +# dependencies: standalone-obj-type.R +# imports: rlang (>= 1.1.0) +# --- +# +# ## Changelog +# +# 2024-08-15: +# - `check_character()` gains an `allow_na` argument (@martaalcalde, #1724) +# +# 2023-03-13: +# - Improved error messages of number checkers (@teunbrand) +# - Added `allow_infinite` argument to `check_number_whole()` (@mgirlich). +# - Added `check_data_frame()` (@mgirlich). +# +# 2023-03-07: +# - Added dependency on rlang (>= 1.1.0). +# +# 2023-02-15: +# - Added `check_logical()`. +# +# - `check_bool()`, `check_number_whole()`, and +# `check_number_decimal()` are now implemented in C. +# +# - For efficiency, `check_number_whole()` and +# `check_number_decimal()` now take a `NULL` default for `min` and +# `max`. This makes it possible to bypass unnecessary type-checking +# and comparisons in the default case of no bounds checks. +# +# 2022-10-07: +# - `check_number_whole()` and `_decimal()` no longer treat +# non-numeric types such as factors or dates as numbers. Numeric +# types are detected with `is.numeric()`. +# +# 2022-10-04: +# - Added `check_name()` that forbids the empty string. +# `check_string()` allows the empty string by default. +# +# 2022-09-28: +# - Removed `what` arguments. +# - Added `allow_na` and `allow_null` arguments. +# - Added `allow_decimal` and `allow_infinite` arguments. +# - Improved errors with absent arguments. +# +# +# 2022-09-16: +# - Unprefixed usage of rlang functions with `rlang::` to +# avoid onLoad issues when called from rlang (#1482). +# +# 2022-08-11: +# - Added changelog. +# +# nocov start + +# Scalars ----------------------------------------------------------------- + +.standalone_types_check_dot_call <- .Call + +check_bool <- function(x, + ..., + allow_na = FALSE, + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x) && .standalone_types_check_dot_call(ffi_standalone_is_bool_1.0.7, x, allow_na, allow_null)) { + return(invisible(NULL)) + } + + stop_input_type( + x, + c("`TRUE`", "`FALSE`"), + ..., + allow_na = allow_na, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_string <- function(x, + ..., + allow_empty = TRUE, + allow_na = FALSE, + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + is_string <- .rlang_check_is_string( + x, + allow_empty = allow_empty, + allow_na = allow_na, + allow_null = allow_null + ) + if (is_string) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a single string", + ..., + allow_na = allow_na, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +.rlang_check_is_string <- function(x, + allow_empty, + allow_na, + allow_null) { + if (rlang::is_string(x)) { + if (allow_empty || !rlang::is_string(x, "")) { + return(TRUE) + } + } + + if (allow_null && rlang::is_null(x)) { + return(TRUE) + } + + if (allow_na && (identical(x, NA) || identical(x, rlang::na_chr))) { + return(TRUE) + } + + FALSE +} + +check_name <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + is_string <- .rlang_check_is_string( + x, + allow_empty = FALSE, + allow_na = FALSE, + allow_null = allow_null + ) + if (is_string) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a valid name", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +IS_NUMBER_true <- 0 +IS_NUMBER_false <- 1 +IS_NUMBER_oob <- 2 + +check_number_decimal <- function(x, + ..., + min = NULL, + max = NULL, + allow_infinite = TRUE, + allow_na = FALSE, + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (missing(x)) { + exit_code <- IS_NUMBER_false + } else if (0 == (exit_code <- .standalone_types_check_dot_call( + ffi_standalone_check_number_1.0.7, + x, + allow_decimal = TRUE, + min, + max, + allow_infinite, + allow_na, + allow_null + ))) { + return(invisible(NULL)) + } + + .stop_not_number( + x, + ..., + exit_code = exit_code, + allow_decimal = TRUE, + min = min, + max = max, + allow_na = allow_na, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_number_whole <- function(x, + ..., + min = NULL, + max = NULL, + allow_infinite = FALSE, + allow_na = FALSE, + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (missing(x)) { + exit_code <- IS_NUMBER_false + } else if (0 == (exit_code <- .standalone_types_check_dot_call( + ffi_standalone_check_number_1.0.7, + x, + allow_decimal = FALSE, + min, + max, + allow_infinite, + allow_na, + allow_null + ))) { + return(invisible(NULL)) + } + + .stop_not_number( + x, + ..., + exit_code = exit_code, + allow_decimal = FALSE, + min = min, + max = max, + allow_na = allow_na, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +.stop_not_number <- function(x, + ..., + exit_code, + allow_decimal, + min, + max, + allow_na, + allow_null, + arg, + call) { + if (allow_decimal) { + what <- "a number" + } else { + what <- "a whole number" + } + + if (exit_code == IS_NUMBER_oob) { + min <- min %||% -Inf + max <- max %||% Inf + + if (min > -Inf && max < Inf) { + what <- sprintf("%s between %s and %s", what, min, max) + } else if (x < min) { + what <- sprintf("%s larger than or equal to %s", what, min) + } else if (x > max) { + what <- sprintf("%s smaller than or equal to %s", what, max) + } else { + rlang::abort("Unexpected state in OOB check", .internal = TRUE) + } + } + + stop_input_type( + x, + what, + ..., + allow_na = allow_na, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_symbol <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_symbol(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a symbol", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_arg <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_symbol(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "an argument name", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_call <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_call(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a defused call", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_environment <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_environment(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "an environment", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_function <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_function(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a function", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_closure <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_closure(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "an R function", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_formula <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_formula(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a formula", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + + +check_match <- function(x, + vec, + ..., + allow_empty = TRUE, + allow_na = FALSE, + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (x %in% vec) { + return(invisible(NULL)) + } + } + if (is.character(vec)) { + vec <- paste0("\"", vec, "\"") + } + + stop_input_type( + x, + vec, + ..., + allow_na = allow_na, + allow_null = allow_null, + arg = arg, + call = call + ) +} + + +# Vectors ----------------------------------------------------------------- + +# TODO: Figure out what to do with logical `NA` and `allow_na = TRUE` + +check_numeric <- function(x, + ..., + allow_na = TRUE, + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + + if (!missing(x)) { + if (is.numeric(x)) { + if (!allow_na && any(is.na(x))) { + rlang::abort( + sprintf("`%s` can't contain NA values.", arg), + arg = arg, + call = call + ) + } + + return(invisible(NULL)) + } + + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a numeric vector", + ..., + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_character <- function(x, + ..., + allow_na = TRUE, + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + + if (!missing(x)) { + if (rlang::is_character(x)) { + if (!allow_na && any(is.na(x))) { + rlang::abort( + sprintf("`%s` can't contain NA values.", arg), + arg = arg, + call = call + ) + } + + return(invisible(NULL)) + } + + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a character vector", + ..., + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_logical <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (rlang::is_logical(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a logical vector", + ..., + allow_na = FALSE, + allow_null = allow_null, + arg = arg, + call = call + ) +} + +check_data_frame <- function(x, + ..., + allow_null = FALSE, + arg = rlang::caller_arg(x), + call = rlang::caller_env()) { + if (!missing(x)) { + if (is.data.frame(x)) { + return(invisible(NULL)) + } + if (allow_null && rlang::is_null(x)) { + return(invisible(NULL)) + } + } + + stop_input_type( + x, + "a data frame", + ..., + allow_null = allow_null, + arg = arg, + call = call + ) +} + +# nocov end + diff --git a/tests/testthat/helper.R b/tests/testthat/helper.R index 27cf0f1..8662778 100644 --- a/tests/testthat/helper.R +++ b/tests/testthat/helper.R @@ -14,3 +14,4 @@ test_chisq <- chisq.test(as.table(rbind(c(762, 327, 468), c(484, 239, 477)))) test_aov <- aov(c ~ a, data = df) test_bf <- BayesFactor::ttestBF(df$a, mu = 5) +library(rlang) diff --git a/tests/testthat/test-format_numbers.R b/tests/testthat/test-format_numbers.R index 7339f79..0e8e3c0 100644 --- a/tests/testthat/test-format_numbers.R +++ b/tests/testthat/test-format_numbers.R @@ -1,15 +1,15 @@ test_that("format_num() rounds properly", { suppressMessages(expect_error( format_num("xxx"), - "Input must be a numeric vector" + '`x` must be a numeric vector, not the string "xxx"' )) suppressMessages(expect_error( format_num(123.456, digits = "xxx"), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number, not the string "xxx"' )) suppressMessages(expect_error( format_num(123.456, digits = -1), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number larger than or equal to 0, not the number -1' )) expect_equal(format_num(123.456), "123.5") expect_equal(format_num(123.456, digits = 2), "123.46") @@ -19,19 +19,19 @@ test_that("format_num() rounds properly", { test_that("format_scientific() works properly", { suppressMessages(expect_error( format_scientific("xxx"), - "Input must be a numeric vector" + '`x` must be a numeric vector, not the string "xxx"' )) suppressMessages(expect_error( format_scientific(123.456, digits = "xxx"), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number, not the string "xxx"' )) suppressMessages(expect_error( format_scientific(123.456, digits = -1), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number larger than or equal to 1, not the number -1' )) suppressMessages(expect_error( - format_bf(123.4567, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + format_scientific(123.4567, type = "xxx"), + '`type` must be "md" or "latex", not the string "xxx"' )) expect_equal(format_scientific(1000), "1.0×10^3^") expect_equal(format_scientific(0.00123), "1.2×10^-3^") @@ -43,15 +43,15 @@ test_that("format_scientific() works properly", { test_that("format_chr() formats properly", { suppressMessages(expect_error( format_chr(3), - "Input must be a character string" + '`x` must be a single string, not the number 3' )) suppressMessages(expect_error( format_chr("xxx", italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_chr("xxx", type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) expect_equal(format_chr("Hello world!"), "_Hello world!_") expect_equal(format_chr("Hello world!", italics = FALSE), "Hello world!") @@ -62,11 +62,11 @@ test_that("format_chr() formats properly", { test_that("format_sub() formats properly", { suppressMessages(expect_error( format_sub(3), - "Input must be a character string" + '`subscript` must be a single string or `NULL`, not the number 3' )) suppressMessages(expect_error( format_sub("xxx", type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) expect_equal(format_sub("10"), "~10~") expect_equal(format_sub("10", type = "latex"), "$_{10}$") diff --git a/tests/testthat/test-format_stats.R b/tests/testthat/test-format_stats.R index 73f191c..ffaf890 100644 --- a/tests/testthat/test-format_stats.R +++ b/tests/testthat/test-format_stats.R @@ -1,23 +1,23 @@ test_that("unavailable format_stats() methods are aborted", { suppressMessages(expect_error( format_stats(123), - "Numerics are not supported by" + 'Numerics are not supported by' )) suppressMessages(expect_error( format_stats("xxx"), - "Character strings are not supported by" + 'Character strings are not supported by' )) suppressMessages(expect_error( format_stats(df), - "Data frames are not supported by" + 'Data frames are not supported by' )) suppressMessages(expect_error( format_stats(TRUE), - "Objects of class" + 'Objects of class' )) suppressMessages(expect_error( format_stats(test_chisq), - "Objects of method" + 'Objects of method' )) }) @@ -37,39 +37,43 @@ test_that("format_stats() works properly for accepted objects", { test_that("htest correlations are validated properly", { suppressMessages(expect_error( format_stats(test_corr, digits = "xxx"), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_corr, digits = -1), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_corr, digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' )) suppressMessages(expect_error( format_stats(test_corr, pdigits = "xxx"), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_corr, pdigits = 0), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number between 1 and 5, not the number 0' )) suppressMessages(expect_error( format_stats(test_corr, pdigits = 7), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number between 1 and 5, not the number 7' )) suppressMessages(expect_error( format_stats(test_corr, pzero = "xxx"), - "Argument `pzero` must be TRUE or FALSE" + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_corr, full = "xxx"), - "Argument `full` must be TRUE or FALSE" + '`full` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_corr, italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_corr, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) }) @@ -77,39 +81,43 @@ test_that("htest correlations are validated properly", { test_that("correlation correlations are validated properly", { suppressMessages(expect_error( format_stats(test_easycorr, digits = "xxx"), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_easycorr, digits = -1), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' )) suppressMessages(expect_error( format_stats(test_easycorr, pdigits = "xxx"), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_easycorr, pdigits = 0), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number between 1 and 5, not the number 0' )) suppressMessages(expect_error( format_stats(test_easycorr, pdigits = 7), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number between 1 and 5, not the number 7' )) suppressMessages(expect_error( format_stats(test_easycorr, pzero = "xxx"), - "Argument `pzero` must be TRUE or FALSE" + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_easycorr, full = "xxx"), - "Argument `full` must be TRUE or FALSE" + '`full` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_easycorr, italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_easycorr, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) }) @@ -132,47 +140,51 @@ test_that("formatting correlations works properly", { test_that("htest t-tests are validated properly", { suppressMessages(expect_error( format_stats(test_ttest, digits = "xxx"), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_ttest, digits = -1), - "Argument `digits` must be a non-negative numeric vector" + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_ttest, digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' )) suppressMessages(expect_error( format_stats(test_ttest, pdigits = "xxx"), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_ttest, pdigits = 0), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number between 1 and 5, not the number 0' )) suppressMessages(expect_error( format_stats(test_ttest, pdigits = 7), - "Argument `pdigits` must be a numeric between 1 and 5" + '`pdigits` must be a whole number between 1 and 5, not the number 7' )) suppressMessages(expect_error( format_stats(test_ttest, pzero = "xxx"), - "Argument `pzero` must be TRUE or FALSE" + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_ttest, full = "xxx"), - "Argument `full` must be TRUE or FALSE" + '`full` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_ttest, italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_ttest, dfs = "xxx"), - "Argument `dfs` must be 'par', 'sub', or 'none'" + '`dfs` must be "par", "sub", or "none", not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_ttest, mean = "xxx"), - "Argument `mean` must be 'abbr' or 'word'" + '`mean` must be "abbr" or "word", not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_ttest, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) }) @@ -199,41 +211,52 @@ test_that("formatting t-tests works properly", { test_that("aov ANOVAs are validated properly", { suppressMessages(expect_error( - format_stats(test_aov, digits = "xxx"), - "Argument `digits` must be a non-negative numeric vector" + format_stats(test_aov), + '`term` must be a character vector, not absent' )) suppressMessages(expect_error( - format_stats(test_aov, digits = -1), - "Argument `digits` must be a non-negative numeric vector" + format_stats(test_aov, term = "c", digits = "xxx"), + '`digits` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( - format_stats(test_aov, pdigits = "xxx"), - "Argument `pdigits` must be a numeric between 1 and 5" + format_stats(test_aov, term = "c", digits = -1), + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' )) suppressMessages(expect_error( - format_stats(test_aov, pdigits = 0), - "Argument `pdigits` must be a numeric between 1 and 5" + format_stats(test_aov, term = "c", digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' )) suppressMessages(expect_error( - format_stats(test_aov, pdigits = 7), - "Argument `pdigits` must be a numeric between 1 and 5" + format_stats(test_aov, term = "c", pdigits = "xxx"), + '`pdigits` must be a whole number, not the string "xxx"' )) suppressMessages(expect_error( - format_stats(test_aov, pzero = "xxx"), - "Argument `pzero` must be TRUE or FALSE" + format_stats(test_aov, term = "c", pdigits = 0), + '`pdigits` must be a whole number between 1 and 5, not the number 0' )) suppressMessages(expect_error( - format_stats(test_aov, italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + format_stats(test_aov, term = "c", pdigits = 7), + '`pdigits` must be a whole number between 1 and 5, not the number 7' )) suppressMessages(expect_error( - format_stats(test_aov, dfs = "xxx"), - "Argument `dfs` must be 'par', 'sub', or 'none'" + format_stats(test_aov, term = "c", pzero = "xxx"), + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( - format_stats(test_aov, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + format_stats(test_aov, term = "c", italics = "xxx"), + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", dfs = "xxx"), + '`dfs` must be "par", "sub", or "none", not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", type = "xxx"), + '`type` must be "md" or "latex", not the string "xxx"' + )) + + + }) @@ -253,35 +276,35 @@ test_that("formatting ANOVAs works properly", { test_that("format_stats.BFBayesFactor() validates arguments properly", { suppressMessages(expect_error( format_stats(test_bf, digits1 = "xxx"), - "Argument `digits1` must be a non-negative numeric vector" + '`digits1` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_bf, digits1 = -1), - "Argument `digits1` must be a non-negative numeric vector" + '`digits1` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' )) suppressMessages(expect_error( format_stats(test_bf, digits2 = "xxx"), - "Argument `digits2` must be a non-negative numeric vector" + '`digits2` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_bf, digits2 = -1), - "Argument `digits2` must be a non-negative numeric vector" + '`digits2` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' )) suppressMessages(expect_error( format_stats(test_bf, cutoff = 0.5), - "Argument `cutoff` must be a numeric vector greater than 1 or NULL" + '`cutoff` must be a number larger than or equal to 1 or `NULL`, not the number 0.5' )) suppressMessages(expect_error( format_stats(test_bf, cutoff = "xxx"), - "Argument `cutoff` must be a numeric vector greater than 1 or NULL" + '`cutoff` must be a number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_bf, italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_stats(test_bf, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) }) diff --git a/tests/testthat/test-format_statvalues.R b/tests/testthat/test-format_statvalues.R index 2e73963..bd11fc9 100644 --- a/tests/testthat/test-format_statvalues.R +++ b/tests/testthat/test-format_statvalues.R @@ -1,43 +1,43 @@ test_that("format_bf() validates arguments properly", { suppressMessages(expect_error( format_bf("0.0012"), - "Input is not numeric or of class BFBayesFactor" + 'Input is not numeric or of class BFBayesFactor' )) suppressMessages(expect_error( format_bf(test_corr), - "Input is not numeric or of class BFBayesFactor" + 'Input is not numeric or of class BFBayesFactor' )) suppressMessages(expect_error( format_bf(123.4567, digits1 = "xxx"), - "Argument `digits1` must be a non-negative numeric vector" + '`digits1` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_bf(123.4567, digits1 = -1), - "Argument `digits1` must be a non-negative numeric vector" + '`digits1` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' )) suppressMessages(expect_error( format_bf(123.4567, digits2 = "xxx"), - "Argument `digits2` must be a non-negative numeric vector" + '`digits2` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_bf(123.4567, digits2 = -1), - "Argument `digits2` must be a non-negative numeric vector" + '`digits2` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' )) suppressMessages(expect_error( format_bf(123.4567, cutoff = 0.5), - "Argument `cutoff` must be a numeric vector greater than 1 or NULL" + '`cutoff` must be a number larger than or equal to 1 or `NULL`, not the number 0.5' )) suppressMessages(expect_error( format_bf(123.4567, cutoff = "xxx"), - "Argument `cutoff` must be a numeric vector greater than 1 or NULL" + '`cutoff` must be a number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_bf(123.4567, italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_bf(123.4567, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) }) @@ -70,32 +70,33 @@ test_that("format_bf() works properly", { test_that("format_p() works properly", { suppressMessages(expect_error( format_p("xxx"), - "Input must be a numeric vector" + '`x` must be a numeric vector, not the string "xxx"' )) suppressMessages(expect_error( format_p(0.0012, digits = "xxx"), - "Argument `digits` must be a numeric between 1 and 5" + '`digits` must be a whole number or `NULL`, not the string "xxx"' )) suppressMessages(expect_error( format_p(0.0012, digits = 0), - "Argument `digits` must be a numeric between 1 and 5" + '`digits` must be a whole number between 1 and 5 or `NULL`, not the number 0' )) suppressMessages(expect_error( format_p(0.0012, digits = 7), - "Argument `digits` must be a numeric between 1 and 5" + '`digits` must be a whole number between 1 and 5 or `NULL`, not the number 7' )) suppressMessages(expect_error( format_p(0.0012, pzero = "xxx"), - "Argument `pzero` must be TRUE or FALSE" + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_p(0.0012, italics = "xxx"), - "Argument `italics` must be TRUE or FALSE" + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' )) suppressMessages(expect_error( format_p(0.0012, type = "xxx"), - "Argument `type` must be 'md' or 'latex'" + '`type` must be "md" or "latex", not the string "xxx"' )) + expect_equal(format_p(c(0.0012, 0.444)), c("_p_ = .001", "_p_ = .444")) expect_equal(format_p(0.0012), "_p_ = .001") expect_equal(format_p(0.0012, digits = 2), "_p_ < .01") expect_equal(format_p(0.0012, pzero = TRUE), "_p_ = 0.001") diff --git a/tests/testthat/test-format_summary.R b/tests/testthat/test-format_summary.R index 8edfee3..22ed471 100644 --- a/tests/testthat/test-format_summary.R +++ b/tests/testthat/test-format_summary.R @@ -1,39 +1,43 @@ test_that("format_summary() works properly", { suppressMessages(expect_error( format_summary(x = "xxx"), - "Argument `x` must be a numeric vector" + '`x` must be a numeric vector, not the string "xxx"' )) suppressMessages(expect_error( - format_summary(error = "xxx"), - "You must include either the `x` or `values` argument" + format_summary(tendency = "xxx"), + 'You must include either the `x` or `values` argument' + )) + suppressMessages(expect_error( + format_summary(x = 1:3, tendency = "xxx"), + '`tendency` must be "mean" or "median", not the string "xxx"' )) suppressMessages(expect_error( format_summary(x = 1:3, error = "xxx"), - 'Specify `error` as "ci", "sd", "se", or "iqr"' + '`error` must be "ci", "sd", "se", or "iqr", not the string "xxx"' )) suppressMessages(expect_error( format_summary(values = "xxx"), - "Argument `values` must be a numeric vector" + '`values` must be a numeric vector, not the string "xxx"' )) suppressMessages(expect_error( format_summary(values = 1:4), - "Argument `values` must be a vector with two or three elements" + 'Argument `values` must be a vector with two or three elements' )) suppressMessages(expect_error( format_summary(values = c(2, 4, 1)), - "Argument `values` must include the mean followed by the lower CI limit then the upper CI limit" + 'Argument `values` must include the mean followed by the lower CI limit then the upper CI limit' )) suppressMessages(expect_error( format_summary(x = 1:3, tendlabel = "xxx"), - 'Specify `tendlabel` as "abbr", "word", or "none"' + '`tendlabel` must be "abbr", "word", or "none", not the string "xxx"' )) suppressMessages(expect_error( format_summary(x = 1:3, units = 2), - "The `units` argument must be a character vector or NULL" + '`units` must be a character vector or `NULL`, not the number 2' )) suppressMessages(expect_error( format_summary(x = 1:3, display = "xxx"), - 'Specify `display` as "limits", "pm", "par", or "none"' + '`display` must be "limits", "pm", "par", or "none", not the string "xxx"' )) expect_equal(format_summary(x = 1:10), "_M_ = 5.5, 95% CI [3.3, 7.7]") expect_equal(format_summary(values = c(5.5, 1.2)), "_M_ = 5.5, 95% CI [4.3, 6.7]") diff --git a/vignettes/cocoon.Rmd b/vignettes/cocoon.Rmd index 631dd60..2bbcb44 100644 --- a/vignettes/cocoon.Rmd +++ b/vignettes/cocoon.Rmd @@ -12,6 +12,7 @@ knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) +library(rlang) ``` ```{r setup-real, echo = FALSE, message = FALSE} From 73847c80d1bf68adab6f8e29fdd16de0680b1348 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Wed, 27 Nov 2024 11:59:01 -0600 Subject: [PATCH 12/19] Update vignette to Quarto --- DESCRIPTION | 4 +- vignettes/cocoon.Rmd | 62 +- vignettes/cocoon.qmd | 272 +++ ...p-93d79d5d413ef011dde10b33346a7d31.min.css | 12 + .../libs/bootstrap/bootstrap-icons.css | 2078 +++++++++++++++++ .../libs/bootstrap/bootstrap-icons.woff | Bin 0 -> 176200 bytes .../libs/bootstrap/bootstrap.min.js | 7 + .../libs/clipboard/clipboard.min.js | 7 + .../libs/quarto-html/anchor.min.js | 9 + .../libs/quarto-html/popper.min.js | 6 + ...hting-29e2c20b02301cfff04dc8050bf30c7e.css | 205 ++ .../cocoon_files/libs/quarto-html/quarto.js | 911 ++++++++ .../cocoon_files/libs/quarto-html/tippy.css | 1 + .../libs/quarto-html/tippy.umd.min.js | 2 + 14 files changed, 3556 insertions(+), 20 deletions(-) create mode 100644 vignettes/cocoon.qmd create mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css create mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.css create mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.woff create mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap.min.js create mode 100644 vignettes/cocoon_files/libs/clipboard/clipboard.min.js create mode 100644 vignettes/cocoon_files/libs/quarto-html/anchor.min.js create mode 100644 vignettes/cocoon_files/libs/quarto-html/popper.min.js create mode 100644 vignettes/cocoon_files/libs/quarto-html/quarto-syntax-highlighting-29e2c20b02301cfff04dc8050bf30c7e.css create mode 100644 vignettes/cocoon_files/libs/quarto-html/quarto.js create mode 100644 vignettes/cocoon_files/libs/quarto-html/tippy.css create mode 100644 vignettes/cocoon_files/libs/quarto-html/tippy.umd.min.js diff --git a/DESCRIPTION b/DESCRIPTION index 4517dc9..7000434 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -18,6 +18,7 @@ Suggests: BayesFactor, correlation, knitr, + quarto, rmarkdown, testthat (>= 3.0.0) Config/testthat/edition: 3 @@ -27,4 +28,5 @@ Imports: rlang (>= 1.1.0) URL: https://github.com/JeffreyRStevens/cocoon, https://jeffreyrstevens.github.io/cocoon/ BugReports: https://github.com/JeffreyRStevens/cocoon/issues -VignetteBuilder: knitr +VignetteBuilder: + quarto diff --git a/vignettes/cocoon.Rmd b/vignettes/cocoon.Rmd index 2bbcb44..3c10ba9 100644 --- a/vignettes/cocoon.Rmd +++ b/vignettes/cocoon.Rmd @@ -74,36 +74,60 @@ The `format_stats()` function can also input objects returned by the `t.test()` Let's start by creating a few different t-tests ```{r} -mpg_disp_ttest_gear_carb <- t.test(mtcars$gear, mtcars$carb) -mpg_disp_ttest_gear_carb_paired <- t.test(mtcars$gear, mtcars$carb, paired = TRUE) -mpg_disp_ttest_gear_carb_onesample <- t.test(mtcars$gear, mu = 4) -mpg_disp_wtest_gear_carb <- wilcox.test(mtcars$gear, mtcars$carb, exact = FALSE) -mpg_disp_wtest_gear_carb_paired <- wilcox.test(mtcars$gear, mtcars$carb, paired = TRUE, exact = FALSE) -mpg_disp_wtest_gear_carb_onesample <- wilcox.test(mtcars$gear, mu = 4, exact = FALSE) +ttest_gear_carb <- t.test(mtcars$gear, mtcars$carb) +ttest_gear_carb_paired <- t.test(mtcars$gear, mtcars$carb, paired = TRUE) +ttest_gear_carb_onesample <- t.test(mtcars$gear, mu = 4) +wtest_gear_carb <- wilcox.test(mtcars$gear, mtcars$carb, exact = FALSE) +wtest_gear_carb_paired <- wilcox.test(mtcars$gear, mtcars$carb, paired = TRUE, exact = FALSE) +wtest_gear_carb_onesample <- wilcox.test(mtcars$gear, mu = 4, exact = FALSE) ``` For Student's t-tests, we get the mean value or difference and the confidence intervals. Means and confidence intervals can be omitted by setting `full = FALSE`. | Code | Output | |-------|-----| -| `format_stats(mpg_disp_ttest_gear_carb)` | `r format_stats(mpg_disp_ttest_gear_carb)` | -| `format_stats(mpg_disp_ttest_gear_carb_paired)` | `r format_stats(mpg_disp_ttest_gear_carb_paired)` | -| `format_stats(mpg_disp_ttest_gear_carb_onesample)` | `r format_stats(mpg_disp_ttest_gear_carb_onesample)` | -| `format_stats(mpg_disp_ttest_gear_carb_onesample, full = FALSE)` | `r format_stats(mpg_disp_ttest_gear_carb_onesample, full = FALSE)` | -| `format_stats(mpg_disp_wtest_gear_carb)` | `r format_stats(mpg_disp_wtest_gear_carb)` | -| `format_stats(mpg_disp_wtest_gear_carb_paired)` | `r format_stats(mpg_disp_wtest_gear_carb_paired)` | -| `format_stats(mpg_disp_wtest_gear_carb_onesample)` | `r format_stats(mpg_disp_wtest_gear_carb_onesample)` | +| `format_stats(ttest_gear_carb)` | `r format_stats(ttest_gear_carb)` | +| `format_stats(ttest_gear_carb_paired)` | `r format_stats(ttest_gear_carb_paired)` | +| `format_stats(ttest_gear_carb_onesample)` | `r format_stats(ttest_gear_carb_onesample)` | +| `format_stats(ttest_gear_carb_onesample, full = FALSE)` | `r format_stats(ttest_gear_carb_onesample, full = FALSE)` | +| `format_stats(wtest_gear_carb)` | `r format_stats(wtest_gear_carb)` | +| `format_stats(wtest_gear_carb_paired)` | `r format_stats(wtest_gear_carb_paired)` | +| `format_stats(wtest_gear_carb_onesample)` | `r format_stats(wtest_gear_carb_onesample)` | Format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. | Code | Output | |---------|------| -| `format_stats(mpg_disp_ttest_gear_carb)` | `r format_stats(mpg_disp_ttest_gear_carb)` | -| `format_stats(mpg_disp_ttest_gear_carb, digits = 2, pdigits = 2)` | `r format_stats(mpg_disp_ttest_gear_carb, digits = 2, pdigits = 2)` | -| `format_stats(mpg_disp_ttest_gear_carb, pzero = TRUE)` | `r format_stats(mpg_disp_ttest_gear_carb, pzero = TRUE)` | -| `format_stats(mpg_disp_ttest_gear_carb, italics = FALSE)` | `r format_stats(mpg_disp_ttest_gear_carb, italics = FALSE)` | -| `format_stats(mpg_disp_wtest_gear_carb)` | `r format_stats(mpg_disp_wtest_gear_carb)` | -| `format_stats(mpg_disp_wtest_gear_carb, italics = FALSE)` | `r format_stats(mpg_disp_wtest_gear_carb, italics = FALSE)` | +| `format_stats(ttest_gear_carb)` | `r format_stats(ttest_gear_carb)` | +| `format_stats(ttest_gear_carb, digits = 2, pdigits = 2)` | `r format_stats(ttest_gear_carb, digits = 2, pdigits = 2)` | +| `format_stats(ttest_gear_carb, pzero = TRUE)` | `r format_stats(ttest_gear_carb, pzero = TRUE)` | +| `format_stats(ttest_gear_carb, italics = FALSE)` | `r format_stats(ttest_gear_carb, italics = FALSE)` | +| `format_stats(wtest_gear_carb)` | `r format_stats(wtest_gear_carb)` | +| `format_stats(wtest_gear_carb, italics = FALSE)` | `r format_stats(wtest_gear_carb, italics = FALSE)` | + +### ANOVAs + +The `format_stats()` function can also input objects returned by the `aov()` function. It then reports and formats the F statistic, degrees of freedom, and p-value. + +Let's start by creating an ANOVA + +```{r} +aov_mpg_cyl_hp <- aov(mpg ~ cyl * hp, data = mtcars) +summary(aov_mpg_cyl_hp) +``` + +To use `format_stats()` on ANOVAs, you must pass the `aov` object and a character string describing which term to extract. Apply `summary()` to your `aov` object and copy the text of the term you want to extract. Then you can format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. With `dfs`, format degrees of freedom as parenthetical (`par`) or subscripts (`sub`) or remove them (`none`). + +| Code | Output | +|-------------|------| +| `format_stats(aov_mpg_cyl_hp, term = "cyl")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl")` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl:hp")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl:hp")` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", digits = 2, pdigits = 2)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", digits = 2, pdigits = 2)` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", pzero = TRUE)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", pzero = TRUE)` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", italics = FALSE)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", italics = FALSE)` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", dfs = "sub")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", dfs = "sub")` | + +F~1, 28~ = 92.5, p < .001 ### Bayes factors diff --git a/vignettes/cocoon.qmd b/vignettes/cocoon.qmd new file mode 100644 index 0000000..e737af8 --- /dev/null +++ b/vignettes/cocoon.qmd @@ -0,0 +1,272 @@ +--- +title: "cocoon" +format: + html: + toc: true + html-math-method: mathjax +vignette: > + %\VignetteIndexEntry{cocoon} + %\VignetteEngine{quarto::html} + %\VignetteEncoding{UTF-8} +--- + +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>" +) +library(rlang) +``` + +```{r setup-real, echo = FALSE, message = FALSE} +library(cocoon) +# devtools::load_all(".") +``` + +```{r setup-show, eval = FALSE} +library(cocoon) +``` + +One of the many useful features of the [`{papaja}`](https://github.com/crsh/papaja) package is the [`apa_print()`](https://frederikaust.com/papaja_man/reporting.html#statistical-models-and-tests) +function, which takes a statistical object and formats the output to print the statistical information inline in R Markdown documents. The `apa_print()` function is an easy way to extract and format this statistical information for documents following APA style. However, APA style has some rather strange quirks, and users may want some flexibility in how their statistics are formatted. Moreover, `apa_print()` uses LaTeX syntax, which works great for PDFs but generates images for mathematical symbols when outputting to Word documents. + +The `{cocoon}` package uses APA style as the default, but allows more flexible formatting such as including the leading 0 before numbers with maximum values of 1. All functions accept a `type` argument that specifies either `"md"` for Markdown (default) or `"latex"` for LaTeX. This package can format statistical objects, statistical values, and numbers more generally. + + +## Formatting statistical objects + +Running a statistical test in R typically returns a list with lots of information about the test, often including things like statistical test values and p-values. The aim of the `format_stats()` function is to extract and format statistics for a suite of commonly used statistical objects (correlation and t-tests). + +### Correlations + +The `format_stats()` function can input objects returned by the `cor.test()` or `correlation::correlation()` function and detects whether the object is from a Pearson, Kendall, or Spearman correlation. It then reports and formats the appropriate correlation coefficient and p-value. + +Let's start by creating a few different correlations. + +```{r} +mpg_disp_corr_pearson <- cor.test(mtcars$mpg, mtcars$disp, method = "pearson") +mpg_disp_corr_spearman <- cor.test(mtcars$mpg, mtcars$disp, method = "spearman", exact = FALSE) +mpg_disp_corr_kendall <- cor.test(mtcars$mpg, mtcars$disp, method = "kendall", exact = FALSE) +``` + +For Pearson correlations, we get the correlation coefficient and the confidence intervals. Since Spearman and Kendall correlations are non-parametric, confidence intervals are not returned. Confidence intervals can be omitted from Pearson correlations by setting `full = FALSE`. + +| Code | Output | +|-------|-----| +| `format_stats(mpg_disp_corr_pearson)` | `r format_stats(mpg_disp_corr_pearson)` | +| `format_stats(mpg_disp_corr_pearson, full = FALSE)` | `r format_stats(mpg_disp_corr_pearson, full = FALSE)` | +| `format_stats(mpg_disp_corr_spearman)` | `r format_stats(mpg_disp_corr_spearman)` | +| `format_stats(mpg_disp_corr_kendall)` | `r format_stats(mpg_disp_corr_kendall)` | + +Format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. + +| Code | Output | +|---------|------| +| `format_stats(mpg_disp_corr_pearson)` | `r format_stats(mpg_disp_corr_pearson)` | +| `format_stats(mpg_disp_corr_pearson, digits = 1, pdigits = 2)` | `r format_stats(mpg_disp_corr_pearson, digits = 1, pdigits = 2)` | +| `format_stats(mpg_disp_corr_pearson, pzero = TRUE)` | `r format_stats(mpg_disp_corr_pearson, pzero = TRUE)` | +| `format_stats(mpg_disp_corr_pearson, italics = FALSE)` | `r format_stats(mpg_disp_corr_pearson, italics = FALSE)` | +| `format_stats(mpg_disp_corr_spearman, italics = FALSE)` | `r format_stats(mpg_disp_corr_spearman, italics = FALSE)` | +| `format_stats(mpg_disp_corr_kendall, italics = FALSE)` | `r format_stats(mpg_disp_corr_kendall, italics = FALSE)` | + + +### T-tests + +The `format_stats()` function can also input objects returned by the `t.test()` or `wilcox.test()` functions and detect whether the object is from a Student's or Wilcoxon t-test, including one-sample, independent-sample, and paired-sample versions. It then reports and formats the mean value (or mean difference), confidence intervals for mean value/difference, appropriate test statistic, degrees of freedom (for parametric tests), and p-value. + +Let's start by creating a few different t-tests + +```{r} +ttest_gear_carb <- t.test(mtcars$gear, mtcars$carb) +ttest_gear_carb_paired <- t.test(mtcars$gear, mtcars$carb, paired = TRUE) +ttest_gear_carb_onesample <- t.test(mtcars$gear, mu = 4) +wtest_gear_carb <- wilcox.test(mtcars$gear, mtcars$carb, exact = FALSE) +wtest_gear_carb_paired <- wilcox.test(mtcars$gear, mtcars$carb, paired = TRUE, exact = FALSE) +wtest_gear_carb_onesample <- wilcox.test(mtcars$gear, mu = 4, exact = FALSE) +``` + +For Student's t-tests, we get the mean value or difference and the confidence intervals. Means and confidence intervals can be omitted by setting `full = FALSE`. + +| Code | Output | +|-------|-----| +| `format_stats(ttest_gear_carb)` | `r format_stats(ttest_gear_carb)` | +| `format_stats(ttest_gear_carb_paired)` | `r format_stats(ttest_gear_carb_paired)` | +| `format_stats(ttest_gear_carb_onesample)` | `r format_stats(ttest_gear_carb_onesample)` | +| `format_stats(ttest_gear_carb_onesample, full = FALSE)` | `r format_stats(ttest_gear_carb_onesample, full = FALSE)` | +| `format_stats(wtest_gear_carb)` | `r format_stats(wtest_gear_carb)` | +| `format_stats(wtest_gear_carb_paired)` | `r format_stats(wtest_gear_carb_paired)` | +| `format_stats(wtest_gear_carb_onesample)` | `r format_stats(wtest_gear_carb_onesample)` | + +Format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. + +| Code | Output | +|---------|------| +| `format_stats(ttest_gear_carb)` | `r format_stats(ttest_gear_carb)` | +| `format_stats(ttest_gear_carb, digits = 2, pdigits = 2)` | `r format_stats(ttest_gear_carb, digits = 2, pdigits = 2)` | +| `format_stats(ttest_gear_carb, pzero = TRUE)` | `r format_stats(ttest_gear_carb, pzero = TRUE)` | +| `format_stats(ttest_gear_carb, italics = FALSE)` | `r format_stats(ttest_gear_carb, italics = FALSE)` | +| `format_stats(wtest_gear_carb)` | `r format_stats(wtest_gear_carb)` | +| `format_stats(wtest_gear_carb, italics = FALSE)` | `r format_stats(wtest_gear_carb, italics = FALSE)` | + +### ANOVAs + +The `format_stats()` function can also input objects returned by the `aov()` function. It then reports and formats the F statistic, degrees of freedom, and p-value. + +Let's start by creating an ANOVA + +```{r} +aov_mpg_cyl_hp <- aov(mpg ~ cyl * hp, data = mtcars) +summary(aov_mpg_cyl_hp) +``` + +To use `format_stats()` on ANOVAs, you must pass the `aov` object and a character string describing which term to extract. Apply `summary()` to your `aov` object and copy the text of the term you want to extract. Then you can format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. With `dfs`, format degrees of freedom as parenthetical (`par`) or subscripts (`sub`) or remove them (`none`). + +| Code | Output | +|-------------|------| +| `format_stats(aov_mpg_cyl_hp, term = "cyl")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl")` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl:hp")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl:hp")` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", digits = 2, pdigits = 2)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", digits = 2, pdigits = 2)` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", pzero = TRUE)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", pzero = TRUE)` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", italics = FALSE)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", italics = FALSE)` | +| `format_stats(aov_mpg_cyl_hp, term = "cyl", dfs = "sub")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", dfs = "sub")` | + + +### Bayes factors + +The `format_stats()` function can also extract and format Bayes factors from a `BFBayesFactor` object from the [`{BayesFactor}`](https://cran.r-project.org/package=BayesFactor) package. Bayes factors are not as standardized in how they are formatted. One issue is that Bayes factors can be referenced from either the alternative hypothesis (H~1~) or the null hypothesis (H~0~). Also, as a ratio, digits after the decimal are more important below 1 than above 1. + +To respond to the digits issue, the `format_stats()` function controls digits for Bayes factors less than 1 (`digits1`) separately from those greater than 1 (`digits2`). In fact, the defaults are different for these two arguments. Further, Bayes factors can be very large or very small when evidence strongly favors one hypothesis over another. Therefore, the `cutoff` argument set a threshold above which (or below 1/cutoff) the returned value is truncated (e.g., BF > 1000). + +```{r} +bf_corr <- BayesFactor::correlationBF(mtcars$mpg, mtcars$disp) +bf_ttest <- BayesFactor::ttestBF(mtcars$vs, mtcars$am) +bf_lm <- BayesFactor::lmBF(mpg ~ am, data = mtcars) +``` + + +| Code | Output | +|--------|------| +| `format_stats(bf_lm)` | `r format_stats(bf_lm)` | +| `format_stats(bf_lm, digits1 = 2)` | `r format_stats(bf_lm, digits1 = 2)` | +| `format_stats(bf_corr)` | `r format_stats(bf_corr)` | +| `format_stats(bf_corr, cutoff = 1000)` | `r format_stats(bf_corr, cutoff = 1000)` | +| `format_stats(bf_ttest)` | `r format_stats(bf_ttest)` | +| `format_stats(bf_ttest, digits2 = 3)` | `r format_stats(bf_ttest, digits2 = 3)` | +| `format_stats(bf_ttest, cutoff = 3)` | `r format_stats(bf_ttest, cutoff = 3)` | + +The default label for Bayes factors is _BF_~10~. The text of the label can be changed with the `label` argument, where setting `label = ""` omits the label. Italics can be removed with `italics = FALSE`, and the subscript can be set to 01 (`subscript = "01"`) or removed (`subscript = ""`). + +| Code | Output | +|--------|-----| +| `format_stats(bf_lm)` | `r format_stats(bf_lm)` | +| `format_stats(bf_lm, italics = FALSE)` | `r format_stats(bf_lm, italics = FALSE)` | +| `format_stats(bf_lm, subscript = "")` | `r format_stats(bf_lm, subscript = "")` | +| `format_stats(bf_lm, label = "Bayes factor", italics = FALSE, subscript = "")` | `r format_stats(bf_lm, label = "Bayes factor", italics = FALSE, subscript = "")` | +| `format_stats(bf_lm, label = "")` | `r format_stats(bf_lm, label = "")` | + + +## Formatting statistical values + +### Central tendency and error + +#### Data vectors +Often, we need to include simple descriptive statistics in our documents, such as measures of central tendency and error. `{cocoon}` includes a suite of functions that can calculate different summary measures of central tendency (mean or median) and error (confidence interval, standard error, standard deviation, interquartile range) from a numeric data vector. With the base function `format_summary()`, you can specify central tendency with the `summary` argument and error with the `error` argument. For instance, `format_summary(vec, summary = "mean", error = "se")` calculates mean and standard error. + +`{cocoon}` includes a number of wrapper functions that cover common measures of central tendency and error including: + +* `format_meanci()` +* `format_meanse()` +* `format_meansd()` +* `format_medianiqr()` + +And if you don't want to include error, use `format_mean()` or `format_median()`. + +| Code | Output | +|------|--------| +| `format_summary(mtcars$mpg, error = "ci")` | `r format_summary(mtcars$mpg, error = "ci")` | +| `format_meanci(mtcars$mpg)` | `r format_meanci(mtcars$mpg)` | +| `format_medianiqr(mtcars$mpg)` | `r format_medianiqr(mtcars$mpg)` | +| `format_mean(mtcars$mpg)` | `r format_mean(mtcars$mpg)` | + +#### Pre-calculated summaries + +In addition to calculating values directly from the vectors, these functions can format already-calculated measures. So if you already have your mean and error calculated, just pass the vector of central tendency, lower error limit, and upper error limit to the `values` argument to format them. For instance, `format_meanci(values = c(12.5, 11.2, 13.7))` produces `r format_meanci(values = c(12.5, 11.2, 13.7))`. Make sure you pass the arguments in this order, as the function checks whether the send argument is less than or equal to the first and the third is greater than or equal to the first. + +#### Formatting output +These functions can control many aspects of formatting for the values and labels of summary statistics. Digits after the decimal are controlled with `digits` (default is 1). The `tendlabel` argument defines whether the default abbreviation is used ("M" or "Mdn"), the full word ("Mean" or "Median"), or no label is provided. Each of these can be italicized or not with the `italics` argument, subscripts can be included with the `subscript` argument, and units added with the `units` argument. + +| Code | Output | +|------|--------| +| `format_mean(mtcars$mpg)` | `r format_mean(mtcars$mpg)` | +| `format_mean(mtcars$mpg, tendlabel = "word")` | `r format_mean(mtcars$mpg, tendlabel = "word")` | +| `format_mean(mtcars$mpg, tendlabel = "none")` | `r format_mean(mtcars$mpg, tendlabel = "none")` | +| `format_mean(mtcars$mpg, italics = FALSE)` | `r format_mean(mtcars$mpg, italics = FALSE)` | +| `format_mean(mtcars$mpg, subscript = "A")` | `r format_mean(mtcars$mpg, subscript = "A")` | +| `format_mean(mtcars$mpg, units = "m")` | `r format_mean(mtcars$mpg, units = "m")` | + +Error can be displayed in a number of different ways. Setting the `display` argument to `"limits"` (default) includes upper and lower limits in brackets. If intervals rather than limits are preferred, they can be appended after the mean/median with ± using `"pm"` or in parentheses with `"par"`. Error is not displayed if `display = "none"`. The presence of the error label is controlled by the logical argument `errorlabel`. When set to `FALSE`, no error label is included. For confidence intervals, the `cilevel` argument takes a numeric scalar from 0-1 to define the confidence level. + +| Code | Output | +|--------|------| +| `format_meanci(mtcars$mpg)` | `r format_meanci(mtcars$mpg)` | +| `format_meanci(mtcars$mpg, display = "pm")` | `r format_meanci(mtcars$mpg, display = "pm")` | +| `format_meanci(mtcars$mpg, display = "par")` | `r format_meanci(mtcars$mpg, display = "par")` | +| `format_meanci(mtcars$mpg, display = "none")` | `r format_meanci(mtcars$mpg, display = "none")` | +| `format_meanci(mtcars$mpg, errorlabel = FALSE)` | `r format_meanci(mtcars$mpg, errorlabel = FALSE)` | +| `format_meanci(mtcars$mpg, cilevel = 0.90)` | `r format_meanci(mtcars$mpg, cilevel = 0.90)` | + + +### P-values + +P-values are pretty easy to format with `format_p()`. The `digits` argument controls the number of digits after the decimal, and if the value is lower, `p <` is used. Unfortunately, APA style involves lopping off the leading zero in p-values, but setting `pzero = TRUE` turns off this silly setting. The p-value label is controlled by `label`, where the user can specify the exact label text. By default, this is a lower case, italicized _p_. Non-italicized can be defined with `italics = FALSE`. P-value labels can be omitted by setting `label = ""`. + +| Code | Output | +|------|--------| +| `format_p(0.001)` | `r format_p(0.001)` | +| `format_p(0.001, digits = 2)` | `r format_p(0.001, digits = 2)` | +| `format_p(0.321, digits = 2)` | `r format_p(0.321, digits = 2)` | +| `format_p(0.001, pzero = TRUE)` | `r format_p(0.001, pzero = TRUE)` | +| `format_p(0.001, label = "P")` | `r format_p(0.001, label = "P")` | +| `format_p(0.001, italics = FALSE)` | `r format_p(0.001, italics = FALSE)` | +| `format_p(0.001, label = "")` | `r format_p(0.001, label = "")` | + + +### Bayes factors + +Though the `format_stats()` function extracts and formats Bayes factors from the [`{BayesFactor}`](https://cran.r-project.org/package=BayesFactor) package, sometimes you may have Bayes factors from other sources. The `format_bf()` function formats Bayes factors from numeric values (either single scalar elements or vectors). + +| Code | Output | +|--------|------| +| `format_bf(4321)` | `r format_bf(4321)` | +| `format_bf(4321, digits1 = 2)` | `r format_bf(4321, digits1 = 2)` | +| `format_bf(4321, cutoff = 1000)` | `r format_bf(4321, cutoff = 1000)` | +| `format_bf(0.04321)` | `r format_bf(0.04321)` | +| `format_bf(0.04321, digits2 = 3)` | `r format_bf(0.04321, digits2 = 3)` | +| `format_bf(0.04321, cutoff = 10)` | `r format_bf(0.04321, cutoff = 10)` | +| `format_bf(4321, italics = FALSE)` | `r format_bf(4321, italics = FALSE)` | +| `format_bf(4321, subscript = "")` | `r format_bf(4321, subscript = "")` | +| `format_bf(4321, label = "Bayes factor", italics = FALSE, subscript = "")` | `r format_bf(4321, label = "Bayes factor", italics = FALSE, subscript = "")` | +| `format_bf(4321, label = "")` | `r format_bf(4321, label = "")` | +| `format_bf(c(4321, 0.04321))` | `r format_bf(c(4321, 0.04321))` | + + +## Formatting numbers + +In addition to formatting specific statistics, this package can format numbers more generally. The `format_num()` function controls general formatting of numbers of digits with `digits` and the presence of the leading zero with `pzero`. + +| Code | Output | +|---------|------| +| `format_num(0.1234)` | `r format_num(0.1234)` | +| `format_num(0.1234, digits = 2)` | `r format_num(0.1234, digits = 2)` | +| `format_num(0.1234, pzero = FALSE)` | `r format_num(0.1234, pzero = FALSE)` | + +For large or small values, using scientific notation may be a more useful way to format the numbers. The `format_scientific()` function converts to scientific notation, again offering control of the number of `digits` as well as whether output `type` is Markdown or LaTeX. + +| Code | Output | +|---------|------| +| `format_scientific(1234)` | `r format_scientific(1234)` | +| `format_scientific(0.0000001234)` | `r format_scientific(0.0000001234)` | +| `format_scientific(0.0000001234, digits = 2)` | `r format_scientific(0.0000001234, digits = 2)` | + + + diff --git a/vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css b/vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css new file mode 100644 index 0000000..04c15c5 --- /dev/null +++ b/vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css @@ -0,0 +1,12 @@ +/*! + * Bootstrap v5.3.1 (https://getbootstrap.com/) + * Copyright 2011-2023 The Bootstrap Authors + * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) + 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.offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex 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var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 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var(--bs-breadcrumb-divider, ">") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #0d6efd;--bs-pagination-bg: #ffffff;--bs-pagination-border-width: 1px;--bs-pagination-border-color: white;--bs-pagination-border-radius: 0.375rem;--bs-pagination-hover-color: #0a58ca;--bs-pagination-hover-bg: #f8f9fa;--bs-pagination-hover-border-color: white;--bs-pagination-focus-color: #0a58ca;--bs-pagination-focus-bg: #e9ecef;--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-pagination-active-color: #ffffff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: rgba(33, 37, 41, 0.75);--bs-pagination-disabled-bg: #e9ecef;--bs-pagination-disabled-border-color: white;display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(1px*-1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: 0.5rem}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: 0.25rem}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #ffffff;--bs-badge-border-radius: 0.375rem;display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 1px solid var(--bs-alert-border-color);--bs-alert-border-radius: 0.375rem;--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: #e9ecef;--bs-progress-border-radius: 0.375rem;--bs-progress-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075);--bs-progress-bar-color: #ffffff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: #212529;--bs-list-group-bg: #ffffff;--bs-list-group-border-color: white;--bs-list-group-border-width: 1px;--bs-list-group-border-radius: 0.375rem;--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: rgba(33, 37, 41, 0.75);--bs-list-group-action-hover-color: #000;--bs-list-group-action-hover-bg: #f8f9fa;--bs-list-group-action-active-color: #212529;--bs-list-group-action-active-bg: #e9ecef;--bs-list-group-disabled-color: rgba(33, 37, 41, 0.75);--bs-list-group-disabled-bg: #ffffff;--bs-list-group-active-color: #ffffff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: #0d6efd;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item:first-child{border-top-left-radius:inherit;border-top-right-radius:inherit}.list-group-item:last-child{border-bottom-right-radius:inherit;border-bottom-left-radius:inherit}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1*var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media(min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xxl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: 0.5;--bs-btn-close-hover-opacity: 0.75;--bs-btn-close-focus-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: 0.25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:rgba(0,0,0,0) var(--bs-btn-close-bg) center/1em auto 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#cc9a06;--quarto-scss-export-yellow-700: #997404;--quarto-scss-export-yellow-800: #664d03;--quarto-scss-export-yellow-900: #332701;--quarto-scss-export-green-100: #d1e7dd;--quarto-scss-export-green-200: #a3cfbb;--quarto-scss-export-green-300: #75b798;--quarto-scss-export-green-400: #479f76;--quarto-scss-export-green-500: #198754;--quarto-scss-export-green-600: #146c43;--quarto-scss-export-green-700: #0f5132;--quarto-scss-export-green-800: #0a3622;--quarto-scss-export-green-900: #051b11;--quarto-scss-export-teal-100: #d2f4ea;--quarto-scss-export-teal-200: #a6e9d5;--quarto-scss-export-teal-300: #79dfc1;--quarto-scss-export-teal-400: #4dd4ac;--quarto-scss-export-teal-500: #20c997;--quarto-scss-export-teal-600: #1aa179;--quarto-scss-export-teal-700: #13795b;--quarto-scss-export-teal-800: #0d503c;--quarto-scss-export-teal-900: #06281e;--quarto-scss-export-cyan-100: #cff4fc;--quarto-scss-export-cyan-200: #9eeaf9;--quarto-scss-export-cyan-300: #6edff6;--quarto-scss-export-cyan-400: #3dd5f3;--quarto-scss-export-cyan-500: #0dcaf0;--quarto-scss-export-cyan-600: #0aa2c0;--quarto-scss-export-cyan-700: #087990;--quarto-scss-export-cyan-800: #055160;--quarto-scss-export-cyan-900: #032830;--quarto-scss-export-default: #dee2e6;--quarto-scss-export-secondary: #6c757d;--quarto-scss-export-success: #198754;--quarto-scss-export-info: #0dcaf0;--quarto-scss-export-warning: #ffc107;--quarto-scss-export-danger: #dc3545;--quarto-scss-export-light: #f8f9fa;--quarto-scss-export-dark: #212529;--quarto-scss-export-primary-text-emphasis: #052c65;--quarto-scss-export-secondary-text-emphasis: #2b2f32;--quarto-scss-export-success-text-emphasis: #0a3622;--quarto-scss-export-info-text-emphasis: #055160;--quarto-scss-export-warning-text-emphasis: #664d03;--quarto-scss-export-danger-text-emphasis: #58151c;--quarto-scss-export-light-text-emphasis: #495057;--quarto-scss-export-dark-text-emphasis: #495057;--quarto-scss-export-primary-bg-subtle: #cfe2ff;--quarto-scss-export-secondary-bg-subtle: #e2e3e5;--quarto-scss-export-success-bg-subtle: #d1e7dd;--quarto-scss-export-info-bg-subtle: #cff4fc;--quarto-scss-export-warning-bg-subtle: #fff3cd;--quarto-scss-export-danger-bg-subtle: #f8d7da;--quarto-scss-export-light-bg-subtle: #fcfcfd;--quarto-scss-export-dark-bg-subtle: #ced4da;--quarto-scss-export-primary-border-subtle: #9ec5fe;--quarto-scss-export-secondary-border-subtle: #c4c8cb;--quarto-scss-export-success-border-subtle: #a3cfbb;--quarto-scss-export-info-border-subtle: #9eeaf9;--quarto-scss-export-warning-border-subtle: #ffe69c;--quarto-scss-export-danger-border-subtle: #f1aeb5;--quarto-scss-export-light-border-subtle: #e9ecef;--quarto-scss-export-dark-border-subtle: #adb5bd;--quarto-scss-export-body-text-align: ;--quarto-scss-export-body-color: #212529;--quarto-scss-export-body-bg: #ffffff;--quarto-scss-export-body-secondary-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-body-secondary-bg: #e9ecef;--quarto-scss-export-body-tertiary-color: rgba(33, 37, 41, 0.5);--quarto-scss-export-body-tertiary-bg: #f8f9fa;--quarto-scss-export-body-emphasis-color: #000;--quarto-scss-export-link-hover-color: #0a58ca;--quarto-scss-export-link-hover-decoration: ;--quarto-scss-export-border-color-translucent: rgba(0, 0, 0, 0.175);--quarto-scss-export-component-active-bg: #0d6efd;--quarto-scss-export-component-active-color: #ffffff;--quarto-scss-export-focus-ring-color: rgba(13, 110, 253, 0.25);--quarto-scss-export-headings-font-family: ;--quarto-scss-export-headings-font-style: ;--quarto-scss-export-display-font-family: ;--quarto-scss-export-display-font-style: ;--quarto-scss-export-text-muted: rgba(33, 37, 41, 0.75);--quarto-scss-export-blockquote-footer-color: #6c757d;--quarto-scss-export-blockquote-border-color: #e9ecef;--quarto-scss-export-hr-bg-color: ;--quarto-scss-export-hr-height: ;--quarto-scss-export-hr-border-color: ;--quarto-scss-export-legend-font-weight: ;--quarto-scss-export-mark-bg: #fff3cd;--quarto-scss-export-table-color: #212529;--quarto-scss-export-table-bg: #ffffff;--quarto-scss-export-table-accent-bg: transparent;--quarto-scss-export-table-th-font-weight: ;--quarto-scss-export-table-striped-color: #212529;--quarto-scss-export-table-striped-bg: rgba(0, 0, 0, 0.05);--quarto-scss-export-table-active-color: #212529;--quarto-scss-export-table-active-bg: rgba(0, 0, 0, 0.1);--quarto-scss-export-table-hover-color: #212529;--quarto-scss-export-table-hover-bg: rgba(0, 0, 0, 0.075);--quarto-scss-export-table-caption-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-input-btn-font-family: ;--quarto-scss-export-input-btn-focus-color: rgba(13, 110, 253, 0.25);--quarto-scss-export-btn-color: #212529;--quarto-scss-export-btn-font-family: ;--quarto-scss-export-btn-white-space: ;--quarto-scss-export-btn-link-color: #0d6efd;--quarto-scss-export-btn-link-hover-color: #0a58ca;--quarto-scss-export-btn-link-disabled-color: #6c757d;--quarto-scss-export-form-text-font-style: ;--quarto-scss-export-form-text-font-weight: ;--quarto-scss-export-form-text-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-form-label-font-size: ;--quarto-scss-export-form-label-font-style: ;--quarto-scss-export-form-label-font-weight: ;--quarto-scss-export-form-label-color: ;--quarto-scss-export-input-font-family: ;--quarto-scss-export-input-disabled-color: ;--quarto-scss-export-input-disabled-bg: #e9ecef;--quarto-scss-export-input-disabled-border-color: ;--quarto-scss-export-input-color: #212529;--quarto-scss-export-input-focus-bg: #ffffff;--quarto-scss-export-input-focus-border-color: #86b7fe;--quarto-scss-export-input-focus-color: #212529;--quarto-scss-export-input-placeholder-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-input-plaintext-color: #212529;--quarto-scss-export-form-check-label-color: ;--quarto-scss-export-form-check-transition: ;--quarto-scss-export-form-check-input-bg: #ffffff;--quarto-scss-export-form-check-input-focus-border: #86b7fe;--quarto-scss-export-form-check-input-checked-color: #ffffff;--quarto-scss-export-form-check-input-checked-bg-color: #0d6efd;--quarto-scss-export-form-check-input-checked-border-color: #0d6efd;--quarto-scss-export-form-check-input-indeterminate-color: #ffffff;--quarto-scss-export-form-check-input-indeterminate-bg-color: #0d6efd;--quarto-scss-export-form-check-input-indeterminate-border-color: #0d6efd;--quarto-scss-export-form-switch-color: rgba(0, 0, 0, 0.25);--quarto-scss-export-form-switch-focus-color: #86b7fe;--quarto-scss-export-form-switch-checked-color: #ffffff;--quarto-scss-export-input-group-addon-color: #212529;--quarto-scss-export-input-group-addon-bg: #f8f9fa;--quarto-scss-export-input-group-addon-border-color: white;--quarto-scss-export-form-select-font-family: ;--quarto-scss-export-form-select-color: #212529;--quarto-scss-export-form-select-bg: #ffffff;--quarto-scss-export-form-select-disabled-color: ;--quarto-scss-export-form-select-disabled-bg: #e9ecef;--quarto-scss-export-form-select-disabled-border-color: ;--quarto-scss-export-form-select-indicator-color: #343a40;--quarto-scss-export-form-select-border-color: white;--quarto-scss-export-form-select-focus-border-color: #86b7fe;--quarto-scss-export-form-range-track-bg: #f8f9fa;--quarto-scss-export-form-range-thumb-bg: #0d6efd;--quarto-scss-export-form-range-thumb-active-bg: #b6d4fe;--quarto-scss-export-form-range-thumb-disabled-bg: rgba(33, 37, 41, 0.75);--quarto-scss-export-form-file-button-color: #212529;--quarto-scss-export-form-file-button-bg: #f8f9fa;--quarto-scss-export-form-file-button-hover-bg: #e9ecef;--quarto-scss-export-form-floating-label-disabled-color: #6c757d;--quarto-scss-export-form-feedback-font-style: ;--quarto-scss-export-form-feedback-valid-color: #198754;--quarto-scss-export-form-feedback-invalid-color: #dc3545;--quarto-scss-export-form-feedback-icon-valid-color: #198754;--quarto-scss-export-form-feedback-icon-invalid-color: #dc3545;--quarto-scss-export-form-valid-color: #198754;--quarto-scss-export-form-valid-border-color: #198754;--quarto-scss-export-form-invalid-color: #dc3545;--quarto-scss-export-form-invalid-border-color: #dc3545;--quarto-scss-export-nav-link-font-size: ;--quarto-scss-export-nav-link-font-weight: ;--quarto-scss-export-nav-link-color: #0d6efd;--quarto-scss-export-nav-link-hover-color: #0a58ca;--quarto-scss-export-nav-link-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-nav-tabs-border-color: white;--quarto-scss-export-nav-tabs-link-hover-border-color: #e9ecef #e9ecef white;--quarto-scss-export-nav-tabs-link-active-color: #000;--quarto-scss-export-nav-tabs-link-active-bg: #ffffff;--quarto-scss-export-nav-pills-link-active-bg: #0d6efd;--quarto-scss-export-nav-pills-link-active-color: #ffffff;--quarto-scss-export-nav-underline-link-active-color: #000;--quarto-scss-export-navbar-padding-x: ;--quarto-scss-export-navbar-light-contrast: #ffffff;--quarto-scss-export-navbar-dark-contrast: #ffffff;--quarto-scss-export-navbar-light-icon-color: rgba(255, 255, 255, 0.75);--quarto-scss-export-navbar-dark-icon-color: rgba(255, 255, 255, 0.75);--quarto-scss-export-dropdown-color: #212529;--quarto-scss-export-dropdown-bg: #ffffff;--quarto-scss-export-dropdown-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-divider-bg: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-link-color: #212529;--quarto-scss-export-dropdown-link-hover-color: #212529;--quarto-scss-export-dropdown-link-hover-bg: #f8f9fa;--quarto-scss-export-dropdown-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-link-active-color: #ffffff;--quarto-scss-export-dropdown-link-disabled-color: rgba(33, 37, 41, 0.5);--quarto-scss-export-dropdown-header-color: #6c757d;--quarto-scss-export-dropdown-dark-color: #dee2e6;--quarto-scss-export-dropdown-dark-bg: #343a40;--quarto-scss-export-dropdown-dark-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-dark-divider-bg: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-dark-box-shadow: ;--quarto-scss-export-dropdown-dark-link-color: #dee2e6;--quarto-scss-export-dropdown-dark-link-hover-color: #ffffff;--quarto-scss-export-dropdown-dark-link-hover-bg: rgba(255, 255, 255, 0.15);--quarto-scss-export-dropdown-dark-link-active-color: #ffffff;--quarto-scss-export-dropdown-dark-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-dark-link-disabled-color: #adb5bd;--quarto-scss-export-dropdown-dark-header-color: #adb5bd;--quarto-scss-export-pagination-color: #0d6efd;--quarto-scss-export-pagination-bg: #ffffff;--quarto-scss-export-pagination-border-color: white;--quarto-scss-export-pagination-focus-color: #0a58ca;--quarto-scss-export-pagination-focus-bg: #e9ecef;--quarto-scss-export-pagination-hover-color: #0a58ca;--quarto-scss-export-pagination-hover-bg: #f8f9fa;--quarto-scss-export-pagination-hover-border-color: white;--quarto-scss-export-pagination-active-color: #ffffff;--quarto-scss-export-pagination-active-bg: #0d6efd;--quarto-scss-export-pagination-active-border-color: #0d6efd;--quarto-scss-export-pagination-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-pagination-disabled-bg: #e9ecef;--quarto-scss-export-pagination-disabled-border-color: white;--quarto-scss-export-card-title-color: ;--quarto-scss-export-card-subtitle-color: ;--quarto-scss-export-card-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-card-box-shadow: ;--quarto-scss-export-card-cap-bg: rgba(33, 37, 41, 0.03);--quarto-scss-export-card-cap-color: ;--quarto-scss-export-card-height: ;--quarto-scss-export-card-color: ;--quarto-scss-export-card-bg: #ffffff;--quarto-scss-export-accordion-color: #212529;--quarto-scss-export-accordion-bg: #ffffff;--quarto-scss-export-accordion-border-color: white;--quarto-scss-export-accordion-button-color: #212529;--quarto-scss-export-accordion-button-bg: #ffffff;--quarto-scss-export-accordion-button-active-bg: #cfe2ff;--quarto-scss-export-accordion-button-active-color: #052c65;--quarto-scss-export-accordion-button-focus-border-color: #86b7fe;--quarto-scss-export-accordion-icon-color: #212529;--quarto-scss-export-accordion-icon-active-color: #052c65;--quarto-scss-export-tooltip-color: #ffffff;--quarto-scss-export-tooltip-bg: #000;--quarto-scss-export-tooltip-margin: ;--quarto-scss-export-tooltip-arrow-color: ;--quarto-scss-export-form-feedback-tooltip-line-height: ;--quarto-scss-export-popover-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-popover-header-bg: #e9ecef;--quarto-scss-export-popover-body-color: #212529;--quarto-scss-export-popover-arrow-color: #ffffff;--quarto-scss-export-popover-arrow-outer-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-color: ;--quarto-scss-export-toast-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-header-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-toast-header-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-header-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-badge-color: #ffffff;--quarto-scss-export-modal-content-color: ;--quarto-scss-export-modal-content-bg: #ffffff;--quarto-scss-export-modal-content-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-modal-backdrop-bg: #000;--quarto-scss-export-modal-header-border-color: white;--quarto-scss-export-modal-footer-bg: ;--quarto-scss-export-modal-footer-border-color: white;--quarto-scss-export-progress-bg: #e9ecef;--quarto-scss-export-progress-bar-color: #ffffff;--quarto-scss-export-progress-bar-bg: #0d6efd;--quarto-scss-export-list-group-color: #212529;--quarto-scss-export-list-group-bg: #ffffff;--quarto-scss-export-list-group-border-color: white;--quarto-scss-export-list-group-hover-bg: #f8f9fa;--quarto-scss-export-list-group-active-bg: #0d6efd;--quarto-scss-export-list-group-active-color: #ffffff;--quarto-scss-export-list-group-active-border-color: #0d6efd;--quarto-scss-export-list-group-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-disabled-bg: #ffffff;--quarto-scss-export-list-group-action-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-action-hover-color: #000;--quarto-scss-export-list-group-action-active-color: #212529;--quarto-scss-export-list-group-action-active-bg: #e9ecef;--quarto-scss-export-thumbnail-bg: #ffffff;--quarto-scss-export-thumbnail-border-color: white;--quarto-scss-export-figure-caption-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-font-size: ;--quarto-scss-export-breadcrumb-bg: ;--quarto-scss-export-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-active-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-border-radius: ;--quarto-scss-export-carousel-control-color: #ffffff;--quarto-scss-export-carousel-indicator-active-bg: #ffffff;--quarto-scss-export-carousel-caption-color: #ffffff;--quarto-scss-export-carousel-dark-indicator-active-bg: #000;--quarto-scss-export-carousel-dark-caption-color: #000;--quarto-scss-export-btn-close-color: #000;--quarto-scss-export-offcanvas-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-offcanvas-bg-color: #ffffff;--quarto-scss-export-offcanvas-color: #212529;--quarto-scss-export-offcanvas-backdrop-bg: #000;--quarto-scss-export-code-color-dark: white;--quarto-scss-export-kbd-color: #ffffff;--quarto-scss-export-kbd-bg: #212529;--quarto-scss-export-nested-kbd-font-weight: ;--quarto-scss-export-pre-bg: #f8f9fa;--quarto-scss-export-pre-color: #000;--quarto-scss-export-bslib-sidebar-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.05);--quarto-scss-export-bslib-sidebar-toggle-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.1);--quarto-scss-export-bslib-page-sidebar-title-bg: #517699;--quarto-scss-export-bslib-page-sidebar-title-color: #ffffff;--quarto-scss-export-mermaid-bg-color: #ffffff;--quarto-scss-export-mermaid-edge-color: #6c757d;--quarto-scss-export-mermaid-node-fg-color: #212529;--quarto-scss-export-mermaid-fg-color: #212529;--quarto-scss-export-mermaid-fg-color--lighter: #383f45;--quarto-scss-export-mermaid-fg-color--lightest: #4e5862;--quarto-scss-export-mermaid-label-bg-color: #ffffff;--quarto-scss-export-mermaid-label-fg-color: #0d6efd;--quarto-scss-export-mermaid-node-bg-color: rgba(13, 110, 253, 0.1);--quarto-scss-export-code-block-border-left-color: white;--quarto-scss-export-callout-color-note: #0d6efd;--quarto-scss-export-callout-color-tip: #198754;--quarto-scss-export-callout-color-important: #dc3545;--quarto-scss-export-callout-color-caution: #fd7e14;--quarto-scss-export-callout-color-warning: #ffc107} \ No newline at end of file diff --git a/vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.css b/vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.css new file mode 100644 index 0000000..285e444 --- /dev/null +++ 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W{static get NAME(){return"button"}toggle(){this._element.setAttribute("aria-pressed",this._element.classList.toggle("active"))}static jQueryInterface(t){return this.each((function(){const e=Y.getOrCreateInstance(this);"toggle"===t&&e[t]()}))}}N.on(document,"click.bs.button.data-api",X,(t=>{t.preventDefault();const e=t.target.closest(X);Y.getOrCreateInstance(e).toggle()})),m(Y);const U=".bs.swipe",G=`touchstart${U}`,J=`touchmove${U}`,Z=`touchend${U}`,tt=`pointerdown${U}`,et=`pointerup${U}`,it={endCallback:null,leftCallback:null,rightCallback:null},nt={endCallback:"(function|null)",leftCallback:"(function|null)",rightCallback:"(function|null)"};class st extends H{constructor(t,e){super(),this._element=t,t&&st.isSupported()&&(this._config=this._getConfig(e),this._deltaX=0,this._supportPointerEvents=Boolean(window.PointerEvent),this._initEvents())}static get Default(){return it}static get DefaultType(){return nt}static get 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t.defaultInterval=t.interval,t}_addEventListeners(){this._config.keyboard&&N.on(this._element,ft,(t=>this._keydown(t))),"hover"===this._config.pause&&(N.on(this._element,pt,(()=>this.pause())),N.on(this._element,mt,(()=>this._maybeEnableCycle()))),this._config.touch&&st.isSupported()&&this._addTouchEventListeners()}_addTouchEventListeners(){for(const t of z.find(".carousel-item img",this._element))N.on(t,gt,(t=>t.preventDefault()));const t={leftCallback:()=>this._slide(this._directionToOrder(ct)),rightCallback:()=>this._slide(this._directionToOrder(ht)),endCallback:()=>{"hover"===this._config.pause&&(this.pause(),this.touchTimeout&&clearTimeout(this.touchTimeout),this.touchTimeout=setTimeout((()=>this._maybeEnableCycle()),500+this._config.interval))}};this._swipeHelper=new st(this._element,t)}_keydown(t){if(/input|textarea/i.test(t.target.tagName))return;const e=Tt[t.key];e&&(t.preventDefault(),this._slide(this._directionToOrder(e)))}_getItemIndex(t){return this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=z.findOne(wt,this._indicatorsElement);e.classList.remove(yt),e.removeAttribute("aria-current");const i=z.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(yt),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===at,s=e||b(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>N.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(dt).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const 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t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"

"},Un={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Gn={entry:"(string|element|function|null)",selector:"(string|element)"};class Jn extends H{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Yn}static get DefaultType(){return Un}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return bi(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return g(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...g(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)N.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");N.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),N.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},N.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=F.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},ds={...cs.DefaultType,content:"(null|string|element|function)"};class us extends cs{static get Default(){return hs}static get DefaultType(){return ds}static get 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b/vignettes/cocoon_files/libs/quarto-html/quarto-syntax-highlighting-29e2c20b02301cfff04dc8050bf30c7e.css new file mode 100644 index 0000000..49514bd --- /dev/null +++ b/vignettes/cocoon_files/libs/quarto-html/quarto-syntax-highlighting-29e2c20b02301cfff04dc8050bf30c7e.css @@ -0,0 +1,205 @@ +/* quarto syntax highlight colors */ +:root { + --quarto-hl-ot-color: #003B4F; + --quarto-hl-at-color: #657422; + --quarto-hl-ss-color: #20794D; + --quarto-hl-an-color: #5E5E5E; + --quarto-hl-fu-color: #4758AB; + --quarto-hl-st-color: #20794D; + --quarto-hl-cf-color: #003B4F; + --quarto-hl-op-color: #5E5E5E; + --quarto-hl-er-color: #AD0000; + --quarto-hl-bn-color: #AD0000; + --quarto-hl-al-color: #AD0000; + --quarto-hl-va-color: #111111; + --quarto-hl-bu-color: inherit; + --quarto-hl-ex-color: inherit; + --quarto-hl-pp-color: #AD0000; + --quarto-hl-in-color: #5E5E5E; + --quarto-hl-vs-color: #20794D; + --quarto-hl-wa-color: #5E5E5E; + --quarto-hl-do-color: #5E5E5E; + --quarto-hl-im-color: #00769E; + --quarto-hl-ch-color: #20794D; + --quarto-hl-dt-color: #AD0000; + --quarto-hl-fl-color: #AD0000; + --quarto-hl-co-color: #5E5E5E; + --quarto-hl-cv-color: #5E5E5E; + --quarto-hl-cn-color: #8f5902; + --quarto-hl-sc-color: #5E5E5E; + --quarto-hl-dv-color: #AD0000; + --quarto-hl-kw-color: #003B4F; +} + +/* other quarto variables */ +:root { + --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; +} + +pre > code.sourceCode > span { + color: #003B4F; +} + +code span { + color: #003B4F; +} + +code.sourceCode > span { + color: #003B4F; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #003B4F; +} + +code span.ot { + color: #003B4F; + font-style: inherit; +} + +code span.at { + color: #657422; + font-style: inherit; +} + +code span.ss { + color: #20794D; + font-style: inherit; +} + +code span.an { + color: #5E5E5E; + font-style: inherit; +} + +code span.fu { + color: #4758AB; + font-style: inherit; +} + +code span.st { + color: #20794D; + font-style: inherit; +} + +code span.cf { + color: #003B4F; + font-weight: bold; + font-style: inherit; +} + +code span.op { + color: #5E5E5E; + font-style: inherit; +} + +code span.er { + color: #AD0000; + font-style: inherit; +} + +code span.bn { + color: #AD0000; + font-style: inherit; +} + +code span.al { + color: #AD0000; + font-style: inherit; +} + +code span.va { + color: #111111; + font-style: inherit; +} + +code span.bu { + font-style: inherit; +} + +code span.ex { + font-style: inherit; +} + +code span.pp { + color: #AD0000; + font-style: inherit; +} + +code span.in { + color: #5E5E5E; + font-style: inherit; +} + +code span.vs { + color: #20794D; + font-style: inherit; +} + +code span.wa { + color: #5E5E5E; + font-style: italic; +} + +code span.do { + color: #5E5E5E; + font-style: italic; +} + +code span.im { + color: #00769E; + font-style: inherit; +} + +code span.ch { + color: #20794D; + font-style: inherit; +} + +code span.dt { + color: #AD0000; + font-style: inherit; +} + +code span.fl { + color: #AD0000; + font-style: inherit; +} + +code span.co { + color: #5E5E5E; + font-style: inherit; +} + +code span.cv { + color: #5E5E5E; + font-style: italic; +} + +code span.cn { + color: #8f5902; + font-style: inherit; +} + +code span.sc { + color: #5E5E5E; + font-style: inherit; +} + +code span.dv { + color: #AD0000; + font-style: inherit; +} + +code span.kw { + color: #003B4F; + font-weight: bold; + font-style: inherit; +} + +.prevent-inlining { + content: " { + // Find any conflicting margin elements and add margins to the + // top to prevent overlap + const marginChildren = window.document.querySelectorAll( + ".column-margin.column-container > *, .margin-caption, .aside" + ); + + let lastBottom = 0; + for (const marginChild of marginChildren) { + if (marginChild.offsetParent !== null) { + // clear the top margin so we recompute it + marginChild.style.marginTop = null; + const top = marginChild.getBoundingClientRect().top + window.scrollY; + if (top < lastBottom) { + const marginChildStyle = window.getComputedStyle(marginChild); + const marginBottom = parseFloat(marginChildStyle["marginBottom"]); + const margin = lastBottom - top + marginBottom; + marginChild.style.marginTop = `${margin}px`; + } + const styles = window.getComputedStyle(marginChild); + const marginTop = parseFloat(styles["marginTop"]); + lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; + } + } +}; + +window.document.addEventListener("DOMContentLoaded", function (_event) { + // Recompute the position of margin elements anytime the body size changes + if (window.ResizeObserver) { + const resizeObserver = new window.ResizeObserver( + throttle(() => { + layoutMarginEls(); + if ( + window.document.body.getBoundingClientRect().width < 990 && + isReaderMode() + ) { + quartoToggleReader(); + } + }, 50) + ); + resizeObserver.observe(window.document.body); + } + + const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]'); + const sidebarEl = window.document.getElementById("quarto-sidebar"); + const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left"); + const marginSidebarEl = window.document.getElementById( + "quarto-margin-sidebar" + ); + // function to determine whether the element has a previous sibling that is active + const prevSiblingIsActiveLink = (el) => { + const sibling = el.previousElementSibling; + if (sibling && sibling.tagName === "A") { + return sibling.classList.contains("active"); + } else { + return false; + } + }; + + // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior) + function fireSlideEnter(e) { + const event = window.document.createEvent("Event"); + event.initEvent("slideenter", true, true); + window.document.dispatchEvent(event); + } + const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); + tabs.forEach((tab) => { + tab.addEventListener("shown.bs.tab", fireSlideEnter); + }); + + // fire slideEnter for tabby tab activations (for htmlwidget resize behavior) + document.addEventListener("tabby", fireSlideEnter, false); + + // Track scrolling and mark TOC links as active + // get table of contents and sidebar (bail if we don't have at least one) + const tocLinks = tocEl + ? [...tocEl.querySelectorAll("a[data-scroll-target]")] + : []; + const makeActive = (link) => tocLinks[link].classList.add("active"); + const removeActive = (link) => tocLinks[link].classList.remove("active"); + const removeAllActive = () => + [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); + + // activate the anchor for a section associated with this TOC entry + tocLinks.forEach((link) => { + link.addEventListener("click", () => { + if (link.href.indexOf("#") !== -1) { + const anchor = link.href.split("#")[1]; + const heading = window.document.querySelector( + `[data-anchor-id="${anchor}"]` + ); + if (heading) { + // Add the class + heading.classList.add("reveal-anchorjs-link"); + + // function to show the anchor + const handleMouseout = () => { + heading.classList.remove("reveal-anchorjs-link"); + heading.removeEventListener("mouseout", handleMouseout); + }; + + // add a function to clear the anchor when the user mouses out of it + heading.addEventListener("mouseout", handleMouseout); + } + } + }); + }); + + const sections = tocLinks.map((link) => { + const target = link.getAttribute("data-scroll-target"); + if (target.startsWith("#")) { + return window.document.getElementById(decodeURI(`${target.slice(1)}`)); + } else { + return window.document.querySelector(decodeURI(`${target}`)); + } + }); + + const sectionMargin = 200; + let currentActive = 0; + // track whether we've initialized state the first time + let init = false; + + const updateActiveLink = () => { + // The index from bottom to top (e.g. reversed list) + let sectionIndex = -1; + if ( + window.innerHeight + window.pageYOffset >= + window.document.body.offsetHeight + ) { + // This is the no-scroll case where last section should be the active one + sectionIndex = 0; + } else { + // This finds the last section visible on screen that should be made active + sectionIndex = [...sections].reverse().findIndex((section) => { + if (section) { + return window.pageYOffset >= section.offsetTop - sectionMargin; + } else { + return false; + } + }); + } + if (sectionIndex > -1) { + const current = sections.length - sectionIndex - 1; + if (current !== currentActive) { + removeAllActive(); + currentActive = current; + makeActive(current); + if (init) { + window.dispatchEvent(sectionChanged); + } + init = true; + } + } + }; + + const inHiddenRegion = (top, bottom, hiddenRegions) => { + for (const region of hiddenRegions) { + if (top <= region.bottom && bottom >= region.top) { + return true; + } + } + return false; + }; + + const categorySelector = "header.quarto-title-block .quarto-category"; + const activateCategories = (href) => { + // Find any categories + // Surround them with a link pointing back to: + // #category=Authoring + try { + const categoryEls = window.document.querySelectorAll(categorySelector); + for (const categoryEl of categoryEls) { + const categoryText = categoryEl.textContent; + if (categoryText) { + const link = `${href}#category=${encodeURIComponent(categoryText)}`; + const linkEl = window.document.createElement("a"); + linkEl.setAttribute("href", link); + for (const child of categoryEl.childNodes) { + linkEl.append(child); + } + categoryEl.appendChild(linkEl); + } + } + } catch { + // Ignore errors + } + }; + function hasTitleCategories() { + return window.document.querySelector(categorySelector) !== null; + } + + function offsetRelativeUrl(url) { + const offset = getMeta("quarto:offset"); + return offset ? offset + url : url; + } + + function offsetAbsoluteUrl(url) { + const offset = getMeta("quarto:offset"); + const baseUrl = new URL(offset, window.location); + + const projRelativeUrl = url.replace(baseUrl, ""); + if (projRelativeUrl.startsWith("/")) { + return projRelativeUrl; + } else { + return "/" + projRelativeUrl; + } + } + + // read a meta tag value + function getMeta(metaName) { + const metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; + } + + async function findAndActivateCategories() { + // Categories search with listing only use path without query + const currentPagePath = offsetAbsoluteUrl( + window.location.origin + window.location.pathname + ); + const response = await fetch(offsetRelativeUrl("listings.json")); + if (response.status == 200) { + return response.json().then(function (listingPaths) { + const listingHrefs = []; + for (const listingPath of listingPaths) { + const pathWithoutLeadingSlash = listingPath.listing.substring(1); + for (const item of listingPath.items) { + if ( + item === currentPagePath || + item === currentPagePath + "index.html" + ) { + // Resolve this path against the offset to be sure + // we already are using the correct path to the listing + // (this adjusts the listing urls to be rooted against + // whatever root the page is actually running against) + const relative = offsetRelativeUrl(pathWithoutLeadingSlash); + const baseUrl = window.location; + const resolvedPath = new URL(relative, baseUrl); + listingHrefs.push(resolvedPath.pathname); + break; + } + } + } + + // Look up the tree for a nearby linting and use that if we find one + const nearestListing = findNearestParentListing( + offsetAbsoluteUrl(window.location.pathname), + listingHrefs + ); + if (nearestListing) { + activateCategories(nearestListing); + } else { + // See if the referrer is a listing page for this item + const referredRelativePath = offsetAbsoluteUrl(document.referrer); + const referrerListing = listingHrefs.find((listingHref) => { + const isListingReferrer = + listingHref === referredRelativePath || + listingHref === referredRelativePath + "index.html"; + return isListingReferrer; + }); + + if (referrerListing) { + // Try to use the referrer if possible + activateCategories(referrerListing); + } else if (listingHrefs.length > 0) { + // Otherwise, just fall back to the first listing + activateCategories(listingHrefs[0]); + } + } + }); + } + } + if (hasTitleCategories()) { + findAndActivateCategories(); + } + + const findNearestParentListing = (href, listingHrefs) => { + if (!href || !listingHrefs) { + return undefined; + } + // Look up the tree for a nearby linting and use that if we find one + const relativeParts = href.substring(1).split("/"); + while (relativeParts.length > 0) { + const path = relativeParts.join("/"); + for (const listingHref of listingHrefs) { + if (listingHref.startsWith(path)) { + return listingHref; + } + } + relativeParts.pop(); + } + + return undefined; + }; + + const manageSidebarVisiblity = (el, placeholderDescriptor) => { + let isVisible = true; + let elRect; + + return (hiddenRegions) => { + if (el === null) { + return; + } + + // Find the last element of the TOC + const lastChildEl = el.lastElementChild; + + if (lastChildEl) { + // Converts the sidebar to a menu + const convertToMenu = () => { + for (const child of el.children) { + child.style.opacity = 0; + child.style.overflow = "hidden"; + child.style.pointerEvents = "none"; + } + + nexttick(() => { + const toggleContainer = window.document.createElement("div"); + toggleContainer.style.width = "100%"; + toggleContainer.classList.add("zindex-over-content"); + toggleContainer.classList.add("quarto-sidebar-toggle"); + toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom + toggleContainer.id = placeholderDescriptor.id; + toggleContainer.style.position = "fixed"; + + const toggleIcon = window.document.createElement("i"); + toggleIcon.classList.add("quarto-sidebar-toggle-icon"); + toggleIcon.classList.add("bi"); + toggleIcon.classList.add("bi-caret-down-fill"); + + const toggleTitle = window.document.createElement("div"); + const titleEl = window.document.body.querySelector( + placeholderDescriptor.titleSelector + ); + if (titleEl) { + toggleTitle.append( + titleEl.textContent || titleEl.innerText, + toggleIcon + ); + } + toggleTitle.classList.add("zindex-over-content"); + toggleTitle.classList.add("quarto-sidebar-toggle-title"); + toggleContainer.append(toggleTitle); + + const toggleContents = window.document.createElement("div"); + toggleContents.classList = el.classList; + toggleContents.classList.add("zindex-over-content"); + toggleContents.classList.add("quarto-sidebar-toggle-contents"); + for (const child of el.children) { + if (child.id === "toc-title") { + continue; + } + + const clone = child.cloneNode(true); + clone.style.opacity = 1; + clone.style.pointerEvents = null; + clone.style.display = null; + toggleContents.append(clone); + } + toggleContents.style.height = "0px"; + const positionToggle = () => { + // position the element (top left of parent, same width as parent) + if (!elRect) { + elRect = el.getBoundingClientRect(); + } + toggleContainer.style.left = `${elRect.left}px`; + toggleContainer.style.top = `${elRect.top}px`; + toggleContainer.style.width = `${elRect.width}px`; + }; + positionToggle(); + + toggleContainer.append(toggleContents); + el.parentElement.prepend(toggleContainer); + + // Process clicks + let tocShowing = false; + // Allow the caller to control whether this is dismissed + // when it is clicked (e.g. sidebar navigation supports + // opening and closing the nav tree, so don't dismiss on click) + const clickEl = placeholderDescriptor.dismissOnClick + ? toggleContainer + : toggleTitle; + + const closeToggle = () => { + if (tocShowing) { + toggleContainer.classList.remove("expanded"); + toggleContents.style.height = "0px"; + tocShowing = false; + } + }; + + // Get rid of any expanded toggle if the user scrolls + window.document.addEventListener( + "scroll", + throttle(() => { + closeToggle(); + }, 50) + ); + + // Handle positioning of the toggle + window.addEventListener( + "resize", + throttle(() => { + elRect = undefined; + positionToggle(); + }, 50) + ); + + window.addEventListener("quarto-hrChanged", () => { + elRect = undefined; + }); + + // Process the click + clickEl.onclick = () => { + if (!tocShowing) { + toggleContainer.classList.add("expanded"); + toggleContents.style.height = null; + tocShowing = true; + } else { + closeToggle(); + } + }; + }); + }; + + // Converts a sidebar from a menu back to a sidebar + const convertToSidebar = () => { + for (const child of el.children) { + child.style.opacity = 1; + child.style.overflow = null; + child.style.pointerEvents = null; + } + + const placeholderEl = window.document.getElementById( + placeholderDescriptor.id + ); + if (placeholderEl) { + placeholderEl.remove(); + } + + el.classList.remove("rollup"); + }; + + if (isReaderMode()) { + convertToMenu(); + isVisible = false; + } else { + // Find the top and bottom o the element that is being managed + const elTop = el.offsetTop; + const elBottom = + elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; + + if (!isVisible) { + // If the element is current not visible reveal if there are + // no conflicts with overlay regions + if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToSidebar(); + isVisible = true; + } + } else { + // If the element is visible, hide it if it conflicts with overlay regions + // and insert a placeholder toggle (or if we're in reader mode) + if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToMenu(); + isVisible = false; + } + } + } + } + }; + }; + + const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]'); + for (const tabEl of tabEls) { + const id = tabEl.getAttribute("data-bs-target"); + if (id) { + const columnEl = document.querySelector( + `${id} .column-margin, .tabset-margin-content` + ); + if (columnEl) + tabEl.addEventListener("shown.bs.tab", function (event) { + const el = event.srcElement; + if (el) { + const visibleCls = `${el.id}-margin-content`; + // walk up until we find a parent tabset + let panelTabsetEl = el.parentElement; + while (panelTabsetEl) { + if (panelTabsetEl.classList.contains("panel-tabset")) { + break; + } + panelTabsetEl = panelTabsetEl.parentElement; + } + + if (panelTabsetEl) { + const prevSib = panelTabsetEl.previousElementSibling; + if ( + prevSib && + prevSib.classList.contains("tabset-margin-container") + ) { + const childNodes = prevSib.querySelectorAll( + ".tabset-margin-content" + ); + for (const childEl of childNodes) { + if (childEl.classList.contains(visibleCls)) { + childEl.classList.remove("collapse"); + } else { + childEl.classList.add("collapse"); + } + } + } + } + } + + layoutMarginEls(); + }); + } + } + + // Manage the visibility of the toc and the sidebar + const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { + id: "quarto-toc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { + id: "quarto-sidebarnav-toggle", + titleSelector: ".title", + dismissOnClick: false, + }); + let tocLeftScrollVisibility; + if (leftTocEl) { + tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { + id: "quarto-lefttoc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + } + + // Find the first element that uses formatting in special columns + const conflictingEls = window.document.body.querySelectorAll( + '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' + ); + + // Filter all the possibly conflicting elements into ones + // the do conflict on the left or ride side + const arrConflictingEls = Array.from(conflictingEls); + const leftSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return false; + } + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + className.startsWith("column-") && + !className.endsWith("right") && + !className.endsWith("container") && + className !== "column-margin" + ); + }); + }); + const rightSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return true; + } + + const hasMarginCaption = Array.from(el.classList).find((className) => { + return className == "margin-caption"; + }); + if (hasMarginCaption) { + return true; + } + + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + !className.endsWith("container") && + className.startsWith("column-") && + !className.endsWith("left") + ); + }); + }); + + const kOverlapPaddingSize = 10; + function toRegions(els) { + return els.map((el) => { + const boundRect = el.getBoundingClientRect(); + const top = + boundRect.top + + document.documentElement.scrollTop - + kOverlapPaddingSize; + return { + top, + bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, + }; + }); + } + + let hasObserved = false; + const visibleItemObserver = (els) => { + let visibleElements = [...els]; + const intersectionObserver = new IntersectionObserver( + (entries, _observer) => { + entries.forEach((entry) => { + if (entry.isIntersecting) { + if (visibleElements.indexOf(entry.target) === -1) { + visibleElements.push(entry.target); + } + } else { + visibleElements = visibleElements.filter((visibleEntry) => { + return visibleEntry !== entry; + }); + } + }); + + if (!hasObserved) { + hideOverlappedSidebars(); + } + hasObserved = true; + }, + {} + ); + els.forEach((el) => { + intersectionObserver.observe(el); + }); + + return { + getVisibleEntries: () => { + return visibleElements; + }, + }; + }; + + const rightElementObserver = visibleItemObserver(rightSideConflictEls); + const leftElementObserver = visibleItemObserver(leftSideConflictEls); + + const hideOverlappedSidebars = () => { + marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries())); + sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries())); + if (tocLeftScrollVisibility) { + tocLeftScrollVisibility( + toRegions(leftElementObserver.getVisibleEntries()) + ); + } + }; + + window.quartoToggleReader = () => { + // Applies a slow class (or removes it) + // to update the transition speed + const slowTransition = (slow) => { + const manageTransition = (id, slow) => { + const el = document.getElementById(id); + if (el) { + if (slow) { + el.classList.add("slow"); + } else { + el.classList.remove("slow"); + } + } + }; + + manageTransition("TOC", slow); + manageTransition("quarto-sidebar", slow); + }; + const readerMode = !isReaderMode(); + setReaderModeValue(readerMode); + + // If we're entering reader mode, slow the transition + if (readerMode) { + slowTransition(readerMode); + } + highlightReaderToggle(readerMode); + hideOverlappedSidebars(); + + // If we're exiting reader mode, restore the non-slow transition + if (!readerMode) { + slowTransition(!readerMode); + } + }; + + const highlightReaderToggle = (readerMode) => { + const els = document.querySelectorAll(".quarto-reader-toggle"); + if (els) { + els.forEach((el) => { + if (readerMode) { + el.classList.add("reader"); + } else { + el.classList.remove("reader"); + } + }); + } + }; + + const setReaderModeValue = (val) => { + if (window.location.protocol !== "file:") { + window.localStorage.setItem("quarto-reader-mode", val); + } else { + localReaderMode = val; + } + }; + + const isReaderMode = () => { + if (window.location.protocol !== "file:") { + return window.localStorage.getItem("quarto-reader-mode") === "true"; + } else { + return localReaderMode; + } + }; + let localReaderMode = null; + + const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded"); + const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1; + + // Walk the TOC and collapse/expand nodes + // Nodes are expanded if: + // - they are top level + // - they have children that are 'active' links + // - they are directly below an link that is 'active' + const walk = (el, depth) => { + // Tick depth when we enter a UL + if (el.tagName === "UL") { + depth = depth + 1; + } + + // It this is active link + let isActiveNode = false; + if (el.tagName === "A" && el.classList.contains("active")) { + isActiveNode = true; + } + + // See if there is an active child to this element + let hasActiveChild = false; + for (child of el.children) { + hasActiveChild = walk(child, depth) || hasActiveChild; + } + + // Process the collapse state if this is an UL + if (el.tagName === "UL") { + if (tocOpenDepth === -1 && depth > 1) { + // toc-expand: false + el.classList.add("collapse"); + } else if ( + depth <= tocOpenDepth || + hasActiveChild || + prevSiblingIsActiveLink(el) + ) { + el.classList.remove("collapse"); + } else { + el.classList.add("collapse"); + } + + // untick depth when we leave a UL + depth = depth - 1; + } + return hasActiveChild || isActiveNode; + }; + + // walk the TOC and expand / collapse any items that should be shown + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + + // Throttle the scroll event and walk peridiocally + window.document.addEventListener( + "scroll", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 5) + ); + window.addEventListener( + "resize", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 10) + ); + hideOverlappedSidebars(); + highlightReaderToggle(isReaderMode()); +}); + +// grouped tabsets +window.addEventListener("pageshow", (_event) => { + function getTabSettings() { + const data = localStorage.getItem("quarto-persistent-tabsets-data"); + if (!data) { + localStorage.setItem("quarto-persistent-tabsets-data", "{}"); + return {}; + } + if (data) { + return JSON.parse(data); + } + } + + function setTabSettings(data) { + localStorage.setItem( + "quarto-persistent-tabsets-data", + JSON.stringify(data) + ); + } + + function setTabState(groupName, groupValue) { + const data = getTabSettings(); + data[groupName] = groupValue; + setTabSettings(data); + } + + function toggleTab(tab, active) { + const tabPanelId = tab.getAttribute("aria-controls"); + const tabPanel = document.getElementById(tabPanelId); + if (active) { + tab.classList.add("active"); + tabPanel.classList.add("active"); + } else { + tab.classList.remove("active"); + tabPanel.classList.remove("active"); + } + } + + function toggleAll(selectedGroup, selectorsToSync) { + for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) { + const active = selectedGroup === thisGroup; + for (const tab of tabs) { + toggleTab(tab, active); + } + } + } + + function findSelectorsToSyncByLanguage() { + const result = {}; + const tabs = Array.from( + document.querySelectorAll(`div[data-group] a[id^='tabset-']`) + ); + for (const item of tabs) { + const div = item.parentElement.parentElement.parentElement; + const group = div.getAttribute("data-group"); + if (!result[group]) { + result[group] = {}; + } + const selectorsToSync = result[group]; + const value = item.innerHTML; + if (!selectorsToSync[value]) { + selectorsToSync[value] = []; + } + selectorsToSync[value].push(item); + } + return result; + } + + function setupSelectorSync() { + const selectorsToSync = findSelectorsToSyncByLanguage(); + Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => { + Object.entries(tabSetsByValue).forEach(([value, items]) => { + items.forEach((item) => { + item.addEventListener("click", (_event) => { + setTabState(group, value); + toggleAll(value, selectorsToSync[group]); + }); + }); + }); + }); + return selectorsToSync; + } + + const selectorsToSync = setupSelectorSync(); + for (const [group, selectedName] of Object.entries(getTabSettings())) { + const selectors = selectorsToSync[group]; + // it's possible that stale state gives us empty selections, so we explicitly check here. + if (selectors) { + toggleAll(selectedName, selectors); + } + } +}); + +function throttle(func, wait) { + let waiting = false; + return function () { + if (!waiting) { + func.apply(this, arguments); + waiting = true; + setTimeout(function () { + waiting = false; + }, wait); + } + }; +} + +function nexttick(func) { + return setTimeout(func, 0); +} diff --git a/vignettes/cocoon_files/libs/quarto-html/tippy.css b/vignettes/cocoon_files/libs/quarto-html/tippy.css new file mode 100644 index 0000000..e6ae635 --- /dev/null +++ b/vignettes/cocoon_files/libs/quarto-html/tippy.css @@ -0,0 +1 @@ +.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 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R. Stevens" Date: Wed, 27 Nov 2024 11:59:15 -0600 Subject: [PATCH 13/19] Update README --- README.Rmd | 1 + README.md | 1 + 2 files changed, 2 insertions(+) diff --git a/README.Rmd b/README.Rmd index 7930f69..7cd12c8 100644 --- a/README.Rmd +++ b/README.Rmd @@ -93,6 +93,7 @@ Fuel efficiency and engine displacement were highly correlated - Student t-tests, Wilcoxon rank sum, and signed rank tests (output from `t.test()` and `wilcox.test()`, including one-sample, two-sample independent, and paired tests) + - ANOVAs from `aov()` - Bayes factors (output from [`{BayesFactor}`](https://cran.r-project.org/package=BayesFactor) package) * `format_summary()`: Means and error (calculates from vector or uses vector of mean and error interval or mean, lower error limit, and upper error limit) diff --git a/README.md b/README.md index 18c0461..df06e06 100644 --- a/README.md +++ b/README.md @@ -98,6 +98,7 @@ Fuel efficiency and engine displacement were highly correlated (r = - Student t-tests, Wilcoxon rank sum, and signed rank tests (output from `t.test()` and `wilcox.test()`, including one-sample, two-sample independent, and paired tests) + - ANOVAs from `aov()` - Bayes factors (output from [`{BayesFactor}`](https://cran.r-project.org/package=BayesFactor) package) From 38872e0699e0ddc9c0309af586326d34e044478e Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Wed, 27 Nov 2024 12:00:26 -0600 Subject: [PATCH 14/19] Separate functions and tests into separate format_stats() methods --- R/format_stats.R | 376 +----------------- R/format_stats_BFBayesFactor.R | 72 ++++ R/format_stats_aov.R | 105 +++++ R/format_stats_easycorrelation.R | 83 ++++ R/format_stats_htest.R | 128 ++++++ man/format_stats.BFBayesFactor.Rd | 2 +- man/format_stats.Rd | 1 + man/format_stats.aov.Rd | 23 +- man/format_stats.easycorrelation.Rd | 2 +- man/format_stats.htest.Rd | 2 +- tests/testthat/test-format_stats.R | 275 ------------- .../test-format_stats_BFBayesFactor.R | 36 ++ tests/testthat/test-format_stats_aov.R | 60 +++ .../test-format_stats_easycorrelation.R | 57 +++ tests/testthat/test-format_stats_htest.R | 130 ++++++ 15 files changed, 695 insertions(+), 657 deletions(-) create mode 100644 R/format_stats_BFBayesFactor.R create mode 100644 R/format_stats_aov.R create mode 100644 R/format_stats_easycorrelation.R create mode 100644 R/format_stats_htest.R create mode 100644 tests/testthat/test-format_stats_BFBayesFactor.R create mode 100644 tests/testthat/test-format_stats_aov.R create mode 100644 tests/testthat/test-format_stats_easycorrelation.R create mode 100644 tests/testthat/test-format_stats_htest.R diff --git a/R/format_stats.R b/R/format_stats.R index 9df399e..4dc667e 100644 --- a/R/format_stats.R +++ b/R/format_stats.R @@ -7,6 +7,7 @@ #' 1. `htest` objects of correlations, t-tests, and Wilcoxon tests #' 1. correlations from the #' \{[correlation](https://cran.r-project.org/package=correlation)\} package. +#' 1. `aov` objects for ANOVAs #' 1. Bayes factors from the #' \{[BayesFactor](https://cran.r-project.org/package=BayesFactor)\} package. #' The function invokes specific methods that depend on the class of the @@ -69,378 +70,3 @@ format_stats.default <- function(x, ...) { ) } } - -#' Format hypothesis test statistics -#' -#' This method formats hypothesis test statistics from the class `htest`. -#' Currently, this includes correlations from [cor.test()] and t-tests and -#' Wilcoxon tests from [t.test()] and [wilcox.test()]. For correlations, the -#' function detects whether the object is from a Pearson, -#' Spearman, or Kendall correlation and reports the appropriate correlation -#' label (r, \eqn{\tau}, \eqn{\rho}). The default output is APA formatted, but -#' this function allows control over numbers of -#' digits, leading zeros, the presence of means and confidence intervals, -#' italics, degrees of freedom, and mean labels, and output format of -#' Markdown or LaTeX. -#' -#' @param x An `htest` object -#' @param digits Number of digits after the decimal for means, confidence -#' intervals, and test statistics -#' @param pdigits Number of digits after the decimal for p-values, ranging -#' between 1-5 (also controls cutoff for small p-values) -#' @param pzero Logical value (default = FALSE) for whether to include -#' leading zero for p-values -#' @param full Logical value (default = TRUE) for whether to include means -#' and confidence intervals or just test statistic and p-value -#' @param italics Logical value (default = TRUE) for whether _p_ label should be -#' italicized -#' @param dfs Formatting for degrees of freedom ("par" = parenthetical, -#' "sub" = subscript, "none" = do not print degrees of freedom) -#' @param mean Formatting for mean label ("abbr" = M, "word" = Mean) -#' @param type Type of formatting ("md" = markdown, "latex" = LaTeX) -#' @param ... Additional arguments passed to methods. -#' -#' @return -#' A character string of statistical information formatted in Markdown or LaTeX. -#' -#' @method format_stats htest -#' @family functions for printing statistical objects -#' @export -#' -#' @examples -#' # Prepare statistical objects -#' test_corr <- cor.test(mtcars$mpg, mtcars$cyl) -#' test_corr2 <- cor.test(mtcars$mpg, mtcars$cyl, method = "kendall") -#' test_ttest <- t.test(mtcars$vs, mtcars$am) -#' test_ttest2 <- wilcox.test(mtcars$vs, mtcars$am) -#' -#' # Format correlation -#' format_stats(test_corr) -#' -#' # Remove confidence intervals and italics -#' format_stats(test_corr, full = FALSE, italics = FALSE) -#' -#' # Change digits and add leading zero to p-value -#' format_stats(test_corr, digits = 3, pdigits = 4, pzero = TRUE) -#' -#' # Format Kendall's tau -#' format_stats(test_corr2) -#' -#' # Format t-test -#' format_stats(test_ttest) -#' -#' # Remove mean and confidence interval -#' format_stats(test_ttest, full = FALSE) -#' -#' # Remove degrees of freedom and spell out "Mean" -#' format_stats(test_ttest, dfs = "none", mean = "word") -#' -#' # Format for LaTeX -#' format_stats(test_ttest2, type = "latex") -format_stats.htest <- function(x, - digits = NULL, - pdigits = 3, - pzero = FALSE, - full = TRUE, - italics = TRUE, - dfs = "par", - mean = "abbr", - type = "md", - ...) { - # Validate arguments - check_number_whole(digits, min = 0, allow_null = TRUE) - check_number_whole(pdigits, min = 1, max = 5) - check_bool(pzero) - check_bool(full) - check_bool(italics) - check_match(dfs, c("par", "sub", "none")) - check_match(mean, c("abbr", "word")) - check_string(type) - check_match(type, c("md", "latex")) - - if (grepl("correlation", x$method)) { - if (is.null(digits)) { - digits <- 2 - } else { - digits <- digits - } - format_corr(x, - digits = digits, - pdigits = pdigits, - pzero = pzero, - full = full, - italics = italics, - type = type) - } else if (grepl("t-test", x$method) | grepl("Wilcoxon", x$method)) { - if (is.null(digits)) { - digits <- 1 - } else { - digits <- digits - } - format_ttest(x, - digits = digits, - pdigits = pdigits, - pzero = pzero, - full = full, - italics = italics, - dfs = dfs, - mean = mean, - type = type) - } else { - stop( - "Objects of method '" - , x$method - , "' are currently not supported." - , "\nVisit https://github.com/JeffreyRStevens/cocoon/issues to request support for this method." - , call. = FALSE - ) - } -} - -#' Format correlation statistics -#' -#' @description -#' This functions formats correlation statistics generated from the -#' \{[correlation](https://cran.r-project.org/package=correlation)\} package. -#' This detects whether the object is from a Pearson, Spearman, or Kendall -#' correlation and reports the appropriate correlation label -#' (r, \eqn{\tau}, \eqn{\rho}). The default output is APA formatted, but -#' numbers of digits, leading zeros, the presence of confidence intervals, -#' and italics are all customizable. - -#' @inheritParams format_stats.htest -#' -#' @return -#' A character string of statistical information formatted in Markdown or LaTeX. -#' -#' @method format_stats easycorrelation -#' @family functions for printing statistical objects - -#' @export -#' -#' @examples -#' # Prepare statistical objects -#' test_corr <- correlation::correlation(mtcars, select = "mpg", select2 = "disp") -#' test_corr2 <- correlation::correlation(mtcars, select = "mpg", select2 = "disp", method = "kendall") -#' -#' # Format correlation -#' format_stats(test_corr) -#' -#' # Remove confidence intervals and italics -#' format_stats(test_corr, full = FALSE, italics = FALSE) -#' -#' # Change digits and add leading zero to p-value -#' format_stats(test_corr, digits = 3, pdigits = 4, pzero = TRUE) -#' -#' # Format Kendall's tau for LaTeX -#' format_stats(test_corr2, type = "latex") -format_stats.easycorrelation <- function(x, - digits = 2, - pdigits = 3, - pzero = FALSE, - full = TRUE, - italics = TRUE, - type = "md", - ...) { - # Validate arguments - check_number_whole(digits, min = 0, allow_null = TRUE) - check_number_whole(pdigits, min = 1, max = 5) - check_bool(pzero) - check_bool(full) - check_bool(italics) - check_string(type) - check_match(type, c("md", "latex")) - - if ("r" %in% names(x)) { - method <- "Pearson correlation" - } else if ("rho" %in% names(x)) { - method <- "Spearman correlation" - x$r <- x$rho - } else if ("tau" %in% names(x)) { - method <- "Kendall correlation" - x$r <- x$tau - } else { - stop("Correlation method is not Pearson, Spearman, or Kendall.") - } - - y <- list(statistic = x$t, - parameter = x$df_error, - p.value = x$p, - estimate = x$r, - data.name = paste0(x$Parameter1, " and ", x$Parameter2), - method = method, - conf.int = c(x$CI_low, x$CI_high)) - class(y) <- "htest" - format_corr(y, - digits = digits, - pdigits = pdigits, - pzero = pzero, - full = full, - italics = italics, - type = type) -} - -#' Title -#' -#' @param x An `aov` object -#' @param term Character string for row name of term to extract statistics for. -#' This must be the exact string returned in the `summary()` output from the -#' `aov` object -#' @param digits Number of digits after the decimal for means, confidence -#' intervals, and test statistics -#' @param pdigits Number of digits after the decimal for p-values, ranging -#' between 1-5 (also controls cutoff for small p-values) -#' @param pzero Logical value (default = FALSE) for whether to include -#' leading zero for p-values -#' @param italics Logical value (default = TRUE) for whether _p_ label should be -#' italicized -#' @param dfs Formatting for degrees of freedom ("par" = parenthetical, -#' "sub" = subscript, "none" = do not print degrees of freedom) -#' @param type Type of formatting ("md" = markdown, "latex" = LaTeX) -#' @param ... Additional arguments passed to methods. -#' -#' @return -#' A character string of statistical information formatted in Markdown or LaTeX. -#' -#' @method format_stats aov -#' @family functions for printing statistical objects - -#' @export -#' -#' @examples -#' test_aov <- aov(mpg ~ cyl, data = mtcars) -format_stats.aov <- function(x, - term, - digits = 1, - pdigits = 3, - pzero = FALSE, - italics = TRUE, - dfs = "par", - type = "md", - ...) { - # Validate arguments - check_character(term) - check_number_whole(digits, min = 0, allow_null = TRUE) - check_number_whole(pdigits, min = 1, max = 5) - check_bool(pzero) - check_bool(italics) - check_match(dfs, c("par", "sub", "none")) - check_string(type) - check_match(type, c("md", "latex")) - - terms <- attr(x$terms, "term.labels") - stopifnot("Argument `term` not found in model terms." = term %in% terms) - term_num <- which(terms == term) - - summ <- summary(x) - - f_stat <- summ[[1]][["F value"]][term_num] - df1 <- summ[[1]][["Df"]][term_num] - df2 <- x$df.residual - p_value <- summ[[1]][["Pr(>F)"]][term_num] - - stat_value <- format_num(f_stat, digits = digits, pzero = TRUE) - pvalue <- format_p(p_value, - digits = pdigits, pzero = pzero, - italics = italics, type = type - ) - - # Build label - statlab <- "F" - stat_label <- dplyr::case_when( - !italics ~ paste0(statlab), - identical(type, "md") ~ paste0("_", statlab, "_"), - identical(type, "latex") ~ paste0("$", statlab, "$") - ) - stat_label <- dplyr::case_when(identical(dfs, "par") ~ paste0(stat_label, "(", df1, ", ", df2, ")"), - identical(dfs, "sub") & identical(type, "md") ~ paste0(stat_label, "~", df1, ", ", df2, "~"), - identical(dfs, "sub") & identical(type, "latex") ~ paste0(stat_label, "$_{", df1, ", ", df2, "}$"), - .default = stat_label - )[1] - - # Create statistics string - - build_string(mean_label = NULL, - mean_value = NULL, - cis = FALSE, - stat_label = stat_label, - stat_value = stat_value, - pvalue = pvalue, - full = FALSE) -} - - - - - -#' Format Bayes factors -#' -#' This method formats Bayes factors from the -#' \{[BayesFactor](https://cran.r-project.org/package=BayesFactor)\} package. -#' By default, this function rounds Bayes factors greater than 1 to one decimal -#' place and Bayes factors less than 1 to two decimal places. Values greater -#' than 1000 or less than 1/1000 are formatted using scientific notation. -#' Cutoffs can be set that format the values as greater than or less than the -#' cutoffs (e.g., BF > 1000 or BF < 0.001). Numbers of digits, cutoffs, -#' italics, and label subscripts are all customizable. -#' -#' @param x BayesFactor object or vector of numeric Bayes factor values -#' @param digits1 Number of digits after the decimal for Bayes factors > 1 -#' @param digits2 Number of digits after the decimal for Bayes factors < 1 -#' @param cutoff Cutoff for using `_BF_~10~ > ` or -#' `_BF_~10~ < 1 / ` (value must be > 1) -#' @param label Character string for label before Bayes factor. Default is BF. -#' Set `label = ""` to return just the formatted Bayes factor value with no -#' label or operator (`=`, `<`, `>`) -#' @param italics Logical value (default = TRUE) for whether label should be -#' italicized (_BF_ or BF) -#' @param subscript Subscript to include with _BF_ label (`"10"`, `"01"`, or -#' `""` for no subscript) -#' @param type Type of formatting (`"md"` = markdown, `"latex"` = LaTeX) -#' @param ... Additional arguments passed to methods. -#' -#' -#' @return -#' A character string of statistical information formatted in Markdown or LaTeX. -#' -#' @method format_stats BFBayesFactor -#' @family functions for printing statistical objects -#' @export -#' -#' @examples -#' # Prepare statistical object -#' test_bf <- BayesFactor::ttestBF(mtcars$vs, mtcars$am) -#' -#' # Format Bayes factor -#' format_stats(test_bf) -#' -#' # Control cutoff for output -#' format_stats(test_bf, cutoff = 3) -#' -#' # Change digits, remove italics and subscript -#' format_stats(test_bf, digits2 = 1, italics = FALSE, subscript = "") -#' -#' # Return only Bayes factor value (no label) -#' format_stats(test_bf, label = "") -#' -#' # Format for LaTeX -#' format_stats(test_bf, type = "latex") -format_stats.BFBayesFactor <- function(x, - digits1 = 1, - digits2 = 2, - cutoff = NULL, - label = "BF", - italics = TRUE, - subscript = "10", - type = "md", - ...) { - - format_bf(x, - digits1 = digits1, - digits2 = digits2, - cutoff = cutoff, - label = label, - italics = italics, - subscript = subscript, - type = type) -} diff --git a/R/format_stats_BFBayesFactor.R b/R/format_stats_BFBayesFactor.R new file mode 100644 index 0000000..0a16212 --- /dev/null +++ b/R/format_stats_BFBayesFactor.R @@ -0,0 +1,72 @@ + +#' Format Bayes factors +#' +#' This method formats Bayes factors from the +#' \{[BayesFactor](https://cran.r-project.org/package=BayesFactor)\} package. +#' By default, this function rounds Bayes factors greater than 1 to one decimal +#' place and Bayes factors less than 1 to two decimal places. Values greater +#' than 1000 or less than 1/1000 are formatted using scientific notation. +#' Cutoffs can be set that format the values as greater than or less than the +#' cutoffs (e.g., BF > 1000 or BF < 0.001). Numbers of digits, cutoffs, +#' italics, and label subscripts are all customizable. +#' +#' @param x BayesFactor object or vector of numeric Bayes factor values +#' @param digits1 Number of digits after the decimal for Bayes factors > 1 +#' @param digits2 Number of digits after the decimal for Bayes factors < 1 +#' @param cutoff Cutoff for using `_BF_~10~ > ` or +#' `_BF_~10~ < 1 / ` (value must be > 1) +#' @param label Character string for label before Bayes factor. Default is BF. +#' Set `label = ""` to return just the formatted Bayes factor value with no +#' label or operator (`=`, `<`, `>`) +#' @param italics Logical value (default = TRUE) for whether label should be +#' italicized (_BF_ or BF) +#' @param subscript Subscript to include with _BF_ label (`"10"`, `"01"`, or +#' `""` for no subscript) +#' @param type Type of formatting (`"md"` = markdown, `"latex"` = LaTeX) +#' @param ... Additional arguments passed to methods. +#' +#' +#' @return +#' A character string of statistical information formatted in Markdown or LaTeX. +#' +#' @method format_stats BFBayesFactor +#' @family functions for printing statistical objects +#' @export +#' +#' @examples +#' # Prepare statistical object +#' test_bf <- BayesFactor::ttestBF(mtcars$vs, mtcars$am) +#' +#' # Format Bayes factor +#' format_stats(test_bf) +#' +#' # Control cutoff for output +#' format_stats(test_bf, cutoff = 3) +#' +#' # Change digits, remove italics and subscript +#' format_stats(test_bf, digits2 = 1, italics = FALSE, subscript = "") +#' +#' # Return only Bayes factor value (no label) +#' format_stats(test_bf, label = "") +#' +#' # Format for LaTeX +#' format_stats(test_bf, type = "latex") +format_stats.BFBayesFactor <- function(x, + digits1 = 1, + digits2 = 2, + cutoff = NULL, + label = "BF", + italics = TRUE, + subscript = "10", + type = "md", + ...) { + + format_bf(x, + digits1 = digits1, + digits2 = digits2, + cutoff = cutoff, + label = label, + italics = italics, + subscript = subscript, + type = type) +} diff --git a/R/format_stats_aov.R b/R/format_stats_aov.R new file mode 100644 index 0000000..3d3d5c6 --- /dev/null +++ b/R/format_stats_aov.R @@ -0,0 +1,105 @@ + +#' Format ANOVA statistics +#' +#' @description +#' This method formats analysis of variance (ANOVA) statistics from the class +#' `aov`. The default output is APA formatted, but this function allows control +#' over numbers of digits, leading zeros, italics, degrees of freedom, +#' and output format of Markdown or LaTeX. +#' +#' @param x An `aov` object +#' @param term Character string for row name of term to extract statistics for. +#' This must be the exact string returned in the `summary()` output from the +#' `aov` object +#' @param digits Number of digits after the decimal for means, confidence +#' intervals, and test statistics +#' @param pdigits Number of digits after the decimal for p-values, ranging +#' between 1-5 (also controls cutoff for small p-values) +#' @param pzero Logical value (default = FALSE) for whether to include +#' leading zero for p-values +#' @param italics Logical value (default = TRUE) for whether _p_ label should be +#' italicized +#' @param dfs Formatting for degrees of freedom ("par" = parenthetical, +#' "sub" = subscript, "none" = do not print degrees of freedom) +#' @param type Type of formatting ("md" = markdown, "latex" = LaTeX) +#' @param ... Additional arguments passed to methods. +#' +#' @return +#' A character string of statistical information formatted in Markdown or LaTeX. +#' +#' @method format_stats aov +#' @family functions for printing statistical objects +#' @export +#' +#' @examples +#' test_aov <- aov(mpg ~ cyl * hp, data = mtcars) +#' +#' # Format ANOVA +#' format_stats(test_aov, term = "cyl") +#' +#' # Remove italics and make degrees of freedom subscripts +#' format_stats(test_aov, term = "cyl", italics = FALSE, dfs = "sub") +#' +#' # Change digits and add leading zero to p-value +#' format_stats(test_aov, term = "hp", digits = 3, pdigits = 4, pzero = TRUE) +#' +#' # Format for LaTeX +#' format_stats(test_aov, term = "hp", type = "latex") +format_stats.aov <- function(x, + term, + digits = 1, + pdigits = 3, + pzero = FALSE, + italics = TRUE, + dfs = "par", + type = "md", + ...) { + # Validate arguments + check_character(term) + check_number_whole(digits, min = 0, allow_null = TRUE) + check_number_whole(pdigits, min = 1, max = 5) + check_bool(pzero) + check_bool(italics) + check_match(dfs, c("par", "sub", "none")) + check_string(type) + check_match(type, c("md", "latex")) + + terms <- attr(x$terms, "term.labels") + stopifnot("Argument `term` not found in model terms." = term %in% terms) + term_num <- which(terms == term) + + summ <- summary(x) + + f_stat <- summ[[1]][["F value"]][term_num] + df1 <- summ[[1]][["Df"]][term_num] + df2 <- x$df.residual + p_value <- summ[[1]][["Pr(>F)"]][term_num] + + stat_value <- format_num(f_stat, digits = digits, pzero = TRUE) + pvalue <- format_p(p_value, + digits = pdigits, pzero = pzero, + italics = italics, type = type + ) + + # Build label + statlab <- "F" + stat_label <- dplyr::case_when( + !italics ~ paste0(statlab), + identical(type, "md") ~ paste0("_", statlab, "_"), + identical(type, "latex") ~ paste0("$", statlab, "$") + ) + stat_label <- dplyr::case_when(identical(dfs, "par") ~ paste0(stat_label, "(", df1, ", ", df2, ")"), + identical(dfs, "sub") & identical(type, "md") ~ paste0(stat_label, "~", df1, ",", df2, "~"), + identical(dfs, "sub") & identical(type, "latex") ~ paste0(stat_label, "$_{", df1, ",", df2, "}$"), + .default = stat_label + )[1] + + # Create statistics string + build_string(mean_label = NULL, + mean_value = NULL, + cis = FALSE, + stat_label = stat_label, + stat_value = stat_value, + pvalue = pvalue, + full = FALSE) +} diff --git a/R/format_stats_easycorrelation.R b/R/format_stats_easycorrelation.R new file mode 100644 index 0000000..e8b2b03 --- /dev/null +++ b/R/format_stats_easycorrelation.R @@ -0,0 +1,83 @@ + +#' Format correlation statistics +#' +#' @description +#' This functions formats correlation statistics generated from the +#' \{[correlation](https://cran.r-project.org/package=correlation)\} package. +#' This detects whether the object is from a Pearson, Spearman, or Kendall +#' correlation and reports the appropriate correlation label +#' (r, \eqn{\tau}, \eqn{\rho}). The default output is APA formatted, but +#' numbers of digits, leading zeros, the presence of confidence intervals, +#' and italics are all customizable. + +#' @inheritParams format_stats.htest +#' +#' @return +#' A character string of statistical information formatted in Markdown or LaTeX. +#' +#' @method format_stats easycorrelation +#' @family functions for printing statistical objects + +#' @export +#' +#' @examples +#' # Prepare statistical objects +#' test_corr <- correlation::correlation(mtcars, select = "mpg", select2 = "disp") +#' test_corr2 <- correlation::correlation(mtcars, select = "mpg", select2 = "disp", method = "kendall") +#' +#' # Format correlation +#' format_stats(test_corr) +#' +#' # Remove confidence intervals and italics +#' format_stats(test_corr, full = FALSE, italics = FALSE) +#' +#' # Change digits and add leading zero to p-value +#' format_stats(test_corr, digits = 3, pdigits = 4, pzero = TRUE) +#' +#' # Format Kendall's tau for LaTeX +#' format_stats(test_corr2, type = "latex") +format_stats.easycorrelation <- function(x, + digits = 2, + pdigits = 3, + pzero = FALSE, + full = TRUE, + italics = TRUE, + type = "md", + ...) { + # Validate arguments + check_number_whole(digits, min = 0, allow_null = TRUE) + check_number_whole(pdigits, min = 1, max = 5) + check_bool(pzero) + check_bool(full) + check_bool(italics) + check_string(type) + check_match(type, c("md", "latex")) + + if ("r" %in% names(x)) { + method <- "Pearson correlation" + } else if ("rho" %in% names(x)) { + method <- "Spearman correlation" + x$r <- x$rho + } else if ("tau" %in% names(x)) { + method <- "Kendall correlation" + x$r <- x$tau + } else { + stop("Correlation method is not Pearson, Spearman, or Kendall.") + } + + y <- list(statistic = x$t, + parameter = x$df_error, + p.value = x$p, + estimate = x$r, + data.name = paste0(x$Parameter1, " and ", x$Parameter2), + method = method, + conf.int = c(x$CI_low, x$CI_high)) + class(y) <- "htest" + format_corr(y, + digits = digits, + pdigits = pdigits, + pzero = pzero, + full = full, + italics = italics, + type = type) +} diff --git a/R/format_stats_htest.R b/R/format_stats_htest.R new file mode 100644 index 0000000..c6f45be --- /dev/null +++ b/R/format_stats_htest.R @@ -0,0 +1,128 @@ + +#' Format hypothesis test statistics +#' +#' This method formats hypothesis test statistics from the class `htest`. +#' Currently, this includes correlations from [cor.test()] and t-tests and +#' Wilcoxon tests from [t.test()] and [wilcox.test()]. For correlations, the +#' function detects whether the object is from a Pearson, +#' Spearman, or Kendall correlation and reports the appropriate correlation +#' label (r, \eqn{\tau}, \eqn{\rho}). The default output is APA formatted, but +#' this function allows control over numbers of +#' digits, leading zeros, the presence of means and confidence intervals, +#' italics, degrees of freedom, and mean labels, and output format of +#' Markdown or LaTeX. +#' +#' @param x An `htest` object +#' @param digits Number of digits after the decimal for means, confidence +#' intervals, and test statistics +#' @param pdigits Number of digits after the decimal for p-values, ranging +#' between 1-5 (also controls cutoff for small p-values) +#' @param pzero Logical value (default = FALSE) for whether to include +#' leading zero for p-values +#' @param full Logical value (default = TRUE) for whether to include means +#' and confidence intervals or just test statistic and p-value +#' @param italics Logical value (default = TRUE) for whether _p_ label should be +#' italicized +#' @param dfs Formatting for degrees of freedom ("par" = parenthetical, +#' "sub" = subscript, "none" = do not print degrees of freedom) +#' @param mean Formatting for mean label ("abbr" = M, "word" = Mean) +#' @param type Type of formatting ("md" = markdown, "latex" = LaTeX) +#' @param ... Additional arguments passed to methods. +#' +#' @return +#' A character string of statistical information formatted in Markdown or LaTeX. +#' +#' @method format_stats htest +#' @family functions for printing statistical objects +#' @export +#' +#' @examples +#' # Prepare statistical objects +#' test_corr <- cor.test(mtcars$mpg, mtcars$cyl) +#' test_corr2 <- cor.test(mtcars$mpg, mtcars$cyl, method = "kendall") +#' test_ttest <- t.test(mtcars$vs, mtcars$am) +#' test_ttest2 <- wilcox.test(mtcars$vs, mtcars$am) +#' +#' # Format correlation +#' format_stats(test_corr) +#' +#' # Remove confidence intervals and italics +#' format_stats(test_corr, full = FALSE, italics = FALSE) +#' +#' # Change digits and add leading zero to p-value +#' format_stats(test_corr, digits = 3, pdigits = 4, pzero = TRUE) +#' +#' # Format Kendall's tau +#' format_stats(test_corr2) +#' +#' # Format t-test +#' format_stats(test_ttest) +#' +#' # Remove mean and confidence interval +#' format_stats(test_ttest, full = FALSE) +#' +#' # Remove degrees of freedom and spell out "Mean" +#' format_stats(test_ttest, dfs = "none", mean = "word") +#' +#' # Format for LaTeX +#' format_stats(test_ttest2, type = "latex") +format_stats.htest <- function(x, + digits = NULL, + pdigits = 3, + pzero = FALSE, + full = TRUE, + italics = TRUE, + dfs = "par", + mean = "abbr", + type = "md", + ...) { + # Validate arguments + check_number_whole(digits, min = 0, allow_null = TRUE) + check_number_whole(pdigits, min = 1, max = 5) + check_bool(pzero) + check_bool(full) + check_bool(italics) + check_match(dfs, c("par", "sub", "none")) + check_match(mean, c("abbr", "word")) + check_string(type) + check_match(type, c("md", "latex")) + + if (grepl("correlation", x$method)) { + if (is.null(digits)) { + digits <- 2 + } else { + digits <- digits + } + format_corr(x, + digits = digits, + pdigits = pdigits, + pzero = pzero, + full = full, + italics = italics, + type = type) + } else if (grepl("t-test", x$method) | grepl("Wilcoxon", x$method)) { + if (is.null(digits)) { + digits <- 1 + } else { + digits <- digits + } + format_ttest(x, + digits = digits, + pdigits = pdigits, + pzero = pzero, + full = full, + italics = italics, + dfs = dfs, + mean = mean, + type = type) + } else { + stop( + "Objects of method '" + , x$method + , "' are currently not supported." + , "\nVisit https://github.com/JeffreyRStevens/cocoon/issues to request support for this method." + , call. = FALSE + ) + } +} + diff --git a/man/format_stats.BFBayesFactor.Rd b/man/format_stats.BFBayesFactor.Rd index bac790e..df3d7bb 100644 --- a/man/format_stats.BFBayesFactor.Rd +++ b/man/format_stats.BFBayesFactor.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/format_stats.R +% Please edit documentation in R/format_stats_BFBayesFactor.R \name{format_stats.BFBayesFactor} \alias{format_stats.BFBayesFactor} \title{Format Bayes factors} diff --git a/man/format_stats.Rd b/man/format_stats.Rd index bdea406..090270d 100644 --- a/man/format_stats.Rd +++ b/man/format_stats.Rd @@ -25,6 +25,7 @@ documents. Currently, the generic function works with the following objects: \item \code{htest} objects of correlations, t-tests, and Wilcoxon tests \item correlations from the \{\href{https://cran.r-project.org/package=correlation}{correlation}\} package. +\item \code{aov} objects for ANOVAs \item Bayes factors from the \{\href{https://cran.r-project.org/package=BayesFactor}{BayesFactor}\} package. The function invokes specific methods that depend on the class of the diff --git a/man/format_stats.aov.Rd b/man/format_stats.aov.Rd index 9784167..5380e86 100644 --- a/man/format_stats.aov.Rd +++ b/man/format_stats.aov.Rd @@ -1,8 +1,8 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/format_stats.R +% Please edit documentation in R/format_stats_aov.R \name{format_stats.aov} \alias{format_stats.aov} -\title{Title} +\title{Format ANOVA statistics} \usage{ \method{format_stats}{aov}( x, @@ -46,10 +46,25 @@ italicized} A character string of statistical information formatted in Markdown or LaTeX. } \description{ -Title +This method formats analysis of variance (ANOVA) statistics from the class +\code{aov}. The default output is APA formatted, but this function allows control +over numbers of digits, leading zeros, italics, degrees of freedom, +and output format of Markdown or LaTeX. } \examples{ -test_aov <- aov(mpg ~ cyl, data = mtcars) +test_aov <- aov(mpg ~ cyl * hp, data = mtcars) + +# Format ANOVA +format_stats(test_aov, term = "cyl") + +# Remove italics and make degrees of freedom subscripts +format_stats(test_aov, term = "cyl", italics = FALSE, dfs = "sub") + +# Change digits and add leading zero to p-value +format_stats(test_aov, term = "hp", digits = 3, pdigits = 4, pzero = TRUE) + +# Format for LaTeX +format_stats(test_aov, term = "hp", type = "latex") } \seealso{ Other functions for printing statistical objects: diff --git a/man/format_stats.easycorrelation.Rd b/man/format_stats.easycorrelation.Rd index c9697a2..46d3700 100644 --- a/man/format_stats.easycorrelation.Rd +++ b/man/format_stats.easycorrelation.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/format_stats.R +% Please edit documentation in R/format_stats_easycorrelation.R \name{format_stats.easycorrelation} \alias{format_stats.easycorrelation} \title{Format correlation statistics} diff --git a/man/format_stats.htest.Rd b/man/format_stats.htest.Rd index e9107de..3fab08c 100644 --- a/man/format_stats.htest.Rd +++ b/man/format_stats.htest.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/format_stats.R +% Please edit documentation in R/format_stats_htest.R \name{format_stats.htest} \alias{format_stats.htest} \title{Format hypothesis test statistics} diff --git a/tests/testthat/test-format_stats.R b/tests/testthat/test-format_stats.R index ffaf890..2e21818 100644 --- a/tests/testthat/test-format_stats.R +++ b/tests/testthat/test-format_stats.R @@ -33,278 +33,3 @@ test_that("format_stats() works properly for accepted objects", { expect_no_error(format_stats(test_bf)) }) - -test_that("htest correlations are validated properly", { - suppressMessages(expect_error( - format_stats(test_corr, digits = "xxx"), - '`digits` must be a whole number or `NULL`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_corr, digits = -1), - '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' - )) - suppressMessages(expect_error( - format_stats(test_corr, digits = 1.5), - '`digits` must be a whole number or `NULL`, not the number 1.5' - )) - suppressMessages(expect_error( - format_stats(test_corr, pdigits = "xxx"), - '`pdigits` must be a whole number, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_corr, pdigits = 0), - '`pdigits` must be a whole number between 1 and 5, not the number 0' - )) - suppressMessages(expect_error( - format_stats(test_corr, pdigits = 7), - '`pdigits` must be a whole number between 1 and 5, not the number 7' - )) - suppressMessages(expect_error( - format_stats(test_corr, pzero = "xxx"), - '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_corr, full = "xxx"), - '`full` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_corr, italics = "xxx"), - '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_corr, type = "xxx"), - '`type` must be "md" or "latex", not the string "xxx"' - )) -}) - - -test_that("correlation correlations are validated properly", { - suppressMessages(expect_error( - format_stats(test_easycorr, digits = "xxx"), - '`digits` must be a whole number or `NULL`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, digits = -1), - '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, digits = 1.5), - '`digits` must be a whole number or `NULL`, not the number 1.5' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, pdigits = "xxx"), - '`pdigits` must be a whole number, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, pdigits = 0), - '`pdigits` must be a whole number between 1 and 5, not the number 0' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, pdigits = 7), - '`pdigits` must be a whole number between 1 and 5, not the number 7' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, pzero = "xxx"), - '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, full = "xxx"), - '`full` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, italics = "xxx"), - '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_easycorr, type = "xxx"), - '`type` must be "md" or "latex", not the string "xxx"' - )) -}) - - -test_that("formatting correlations works properly", { - expect_equal(format_stats(test_corr), "_r_ = 1.00, 95% CI [1.00, 1.00], _p_ < .001") - expect_equal(format_stats(test_corr, digits = 3), "_r_ = 1.000, 95% CI [1.000, 1.000], _p_ < .001") - expect_equal(format_stats(test_corr, pdigits = 2), "_r_ = 1.00, 95% CI [1.00, 1.00], _p_ < .01") - expect_equal(format_stats(test_corr, pzero = TRUE), "_r_ = 1.00, 95% CI [1.00, 1.00], _p_ < 0.001") - expect_equal(format_stats(test_corr2), "_r_ = -.12, 95% CI [-0.70, 0.55], _p_ = .748") - expect_equal(format_stats(test_corr2, pzero = TRUE), "_r_ = -0.12, 95% CI [-0.70, 0.55], _p_ = 0.748") - expect_equal(format_stats(test_corr, full = FALSE), "_r_ = 1.00, _p_ < .001") - expect_equal(format_stats(test_corr, italics = FALSE), "r = 1.00, 95% CI [1.00, 1.00], p < .001") - expect_equal(format_stats(test_corr, type = "latex"), "$r$ = 1.00, 95% CI [1.00, 1.00], $p$ < .001") - expect_equal(format_stats(cor.test(df$a, df$b, method = "kendall")), "_τ_ = 1.00, _p_ < .001") - expect_equal(format_stats(cor.test(df$a, df$b, method = "spearman")), "_ρ_ = 1.00, _p_ < .001") -}) - - -test_that("htest t-tests are validated properly", { - suppressMessages(expect_error( - format_stats(test_ttest, digits = "xxx"), - '`digits` must be a whole number or `NULL`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_ttest, digits = -1), - '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' - )) - suppressMessages(expect_error( - format_stats(test_ttest, digits = 1.5), - '`digits` must be a whole number or `NULL`, not the number 1.5' - )) - suppressMessages(expect_error( - format_stats(test_ttest, pdigits = "xxx"), - '`pdigits` must be a whole number, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_ttest, pdigits = 0), - '`pdigits` must be a whole number between 1 and 5, not the number 0' - )) - suppressMessages(expect_error( - format_stats(test_ttest, pdigits = 7), - '`pdigits` must be a whole number between 1 and 5, not the number 7' - )) - suppressMessages(expect_error( - format_stats(test_ttest, pzero = "xxx"), - '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_ttest, full = "xxx"), - '`full` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_ttest, italics = "xxx"), - '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_ttest, dfs = "xxx"), - '`dfs` must be "par", "sub", or "none", not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_ttest, mean = "xxx"), - '`mean` must be "abbr" or "word", not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_ttest, type = "xxx"), - '`type` must be "md" or "latex", not the string "xxx"' - )) -}) - - -test_that("formatting t-tests works properly", { - expect_equal(format_stats(test_ttest1), "_M_ = 5.5, 95% CI [3.3, 7.7], _t_(9) = 0.5, _p_ = .614") - expect_equal(format_stats(test_ttest), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = .470") - expect_equal(format_stats(test_ttest2), "_M_ = -11.3, 95% CI [-34.4, 11.8], _t_(10.2) = -1.1, _p_ = .302") - expect_equal(format_stats(test_ttest, digits = 2), "_M_ = -1.00, 95% CI [-3.84, 1.84], _t_(18) = -0.74, _p_ = .470") - expect_equal(format_stats(test_ttest, pdigits = 2), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = .47") - expect_equal(format_stats(test_ttest, pzero = TRUE), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = 0.470") - expect_equal(format_stats(test_ttest, full = FALSE), "_t_(18) = -0.7, _p_ = .470") - expect_equal(format_stats(test_ttest, italics = FALSE), "M = -1.0, 95% CI [-3.8, 1.8], t(18) = -0.7, p = .470") - expect_equal(format_stats(test_ttest, dfs = "sub"), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_~18~ = -0.7, _p_ = .470") - expect_equal(format_stats(test_ttest, dfs = "none"), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_ = -0.7, _p_ = .470") - expect_equal(format_stats(test_ttest, type = "latex"), "$M$ = -1.0, 95% CI [-3.8, 1.8], $t$(18) = -0.7, $p$ = .470") - expect_equal(format_stats(test_ttest, type = "latex", dfs = "sub"), "$M$ = -1.0, 95% CI [-3.8, 1.8], $t$$_{18}$ = -0.7, $p$ = .470") - expect_equal(format_stats(test_ttest, mean = "word"), "_Mean_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = .470") - suppressMessages(expect_equal(format_stats(test_ttest3), "_V_ = 27.0, _p_ = .634")) - suppressMessages(expect_equal(format_stats(test_ttest4), "_W_ = 40.5, _p_ = .495")) - suppressMessages(expect_equal(format_stats(test_ttest5), "_W_ = 40.5, _p_ = .323")) -}) - - -test_that("aov ANOVAs are validated properly", { - suppressMessages(expect_error( - format_stats(test_aov), - '`term` must be a character vector, not absent' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", digits = "xxx"), - '`digits` must be a whole number or `NULL`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", digits = -1), - '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", digits = 1.5), - '`digits` must be a whole number or `NULL`, not the number 1.5' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", pdigits = "xxx"), - '`pdigits` must be a whole number, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", pdigits = 0), - '`pdigits` must be a whole number between 1 and 5, not the number 0' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", pdigits = 7), - '`pdigits` must be a whole number between 1 and 5, not the number 7' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", pzero = "xxx"), - '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", italics = "xxx"), - '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", dfs = "xxx"), - '`dfs` must be "par", "sub", or "none", not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_aov, term = "c", type = "xxx"), - '`type` must be "md" or "latex", not the string "xxx"' - )) - - - -}) - - -test_that("formatting ANOVAs works properly", { - expect_equal(format_stats(test_aov, "a"), "_F_(1, 8) = 0.1, _p_ = .748") - expect_equal(format_stats(test_aov, "a", digits = 2), "_F_(1, 8) = 0.11, _p_ = .748") - expect_equal(format_stats(test_aov, "a", pdigits = 2), "_F_(1, 8) = 0.1, _p_ = .75") - expect_equal(format_stats(test_aov, "a", pzero = TRUE), "_F_(1, 8) = 0.1, _p_ = 0.748") - expect_equal(format_stats(test_aov, "a", italics = FALSE), "F(1, 8) = 0.1, p = .748") - expect_equal(format_stats(test_aov, "a", dfs = "sub"), "_F_~1, 8~ = 0.1, _p_ = .748") - expect_equal(format_stats(test_aov, "a", dfs = "none"), "_F_ = 0.1, _p_ = .748") - expect_equal(format_stats(test_aov, "a", type = "latex"), "$F$(1, 8) = 0.1, $p$ = .748") - expect_equal(format_stats(test_aov, "a", type = "latex", dfs = "sub"), "$F$$_{1, 8}$ = 0.1, $p$ = .748") -}) - - -test_that("format_stats.BFBayesFactor() validates arguments properly", { - suppressMessages(expect_error( - format_stats(test_bf, digits1 = "xxx"), - '`digits1` must be a whole number or `NULL`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_bf, digits1 = -1), - '`digits1` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' - )) - suppressMessages(expect_error( - format_stats(test_bf, digits2 = "xxx"), - '`digits2` must be a whole number or `NULL`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_bf, digits2 = -1), - '`digits2` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' - )) - suppressMessages(expect_error( - format_stats(test_bf, cutoff = 0.5), - '`cutoff` must be a number larger than or equal to 1 or `NULL`, not the number 0.5' - )) - suppressMessages(expect_error( - format_stats(test_bf, cutoff = "xxx"), - '`cutoff` must be a number or `NULL`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_bf, italics = "xxx"), - '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' - )) - suppressMessages(expect_error( - format_stats(test_bf, type = "xxx"), - '`type` must be "md" or "latex", not the string "xxx"' - )) -}) - diff --git a/tests/testthat/test-format_stats_BFBayesFactor.R b/tests/testthat/test-format_stats_BFBayesFactor.R new file mode 100644 index 0000000..89e095b --- /dev/null +++ b/tests/testthat/test-format_stats_BFBayesFactor.R @@ -0,0 +1,36 @@ + +test_that("format_stats.BFBayesFactor() validates arguments properly", { + suppressMessages(expect_error( + format_stats(test_bf, digits1 = "xxx"), + '`digits1` must be a whole number or `NULL`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_bf, digits1 = -1), + '`digits1` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_bf, digits2 = "xxx"), + '`digits2` must be a whole number or `NULL`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_bf, digits2 = -1), + '`digits2` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_bf, cutoff = 0.5), + '`cutoff` must be a number larger than or equal to 1 or `NULL`, not the number 0.5' + )) + suppressMessages(expect_error( + format_stats(test_bf, cutoff = "xxx"), + '`cutoff` must be a number or `NULL`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_bf, italics = "xxx"), + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_bf, type = "xxx"), + '`type` must be "md" or "latex", not the string "xxx"' + )) +}) + diff --git a/tests/testthat/test-format_stats_aov.R b/tests/testthat/test-format_stats_aov.R new file mode 100644 index 0000000..0883c2d --- /dev/null +++ b/tests/testthat/test-format_stats_aov.R @@ -0,0 +1,60 @@ + +test_that("aov ANOVAs are validated properly", { + suppressMessages(expect_error( + format_stats(test_aov), + '`term` must be a character vector, not absent' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", digits = "xxx"), + '`digits` must be a whole number or `NULL`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", digits = -1), + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", pdigits = "xxx"), + '`pdigits` must be a whole number, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", pdigits = 0), + '`pdigits` must be a whole number between 1 and 5, not the number 0' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", pdigits = 7), + '`pdigits` must be a whole number between 1 and 5, not the number 7' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", pzero = "xxx"), + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", italics = "xxx"), + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", dfs = "xxx"), + '`dfs` must be "par", "sub", or "none", not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_aov, term = "c", type = "xxx"), + '`type` must be "md" or "latex", not the string "xxx"' + )) +}) + + +test_that("formatting ANOVAs works properly", { + expect_equal(format_stats(test_aov, "a"), "_F_(1, 8) = 0.1, _p_ = .748") + expect_equal(format_stats(test_aov, "a", digits = 2), "_F_(1, 8) = 0.11, _p_ = .748") + expect_equal(format_stats(test_aov, "a", pdigits = 2), "_F_(1, 8) = 0.1, _p_ = .75") + expect_equal(format_stats(test_aov, "a", pzero = TRUE), "_F_(1, 8) = 0.1, _p_ = 0.748") + expect_equal(format_stats(test_aov, "a", italics = FALSE), "F(1, 8) = 0.1, p = .748") + expect_equal(format_stats(test_aov, "a", dfs = "sub"), "_F_~1,8~ = 0.1, _p_ = .748") + expect_equal(format_stats(test_aov, "a", dfs = "none"), "_F_ = 0.1, _p_ = .748") + expect_equal(format_stats(test_aov, "a", type = "latex"), "$F$(1, 8) = 0.1, $p$ = .748") + expect_equal(format_stats(test_aov, "a", type = "latex", dfs = "sub"), "$F$$_{1,8}$ = 0.1, $p$ = .748") +}) diff --git a/tests/testthat/test-format_stats_easycorrelation.R b/tests/testthat/test-format_stats_easycorrelation.R new file mode 100644 index 0000000..3ef28a1 --- /dev/null +++ b/tests/testthat/test-format_stats_easycorrelation.R @@ -0,0 +1,57 @@ + +test_that("easycorrelation correlations are validated properly", { + suppressMessages(expect_error( + format_stats(test_easycorr, digits = "xxx"), + '`digits` must be a whole number or `NULL`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, digits = -1), + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, pdigits = "xxx"), + '`pdigits` must be a whole number, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, pdigits = 0), + '`pdigits` must be a whole number between 1 and 5, not the number 0' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, pdigits = 7), + '`pdigits` must be a whole number between 1 and 5, not the number 7' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, pzero = "xxx"), + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, full = "xxx"), + '`full` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, italics = "xxx"), + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_easycorr, type = "xxx"), + '`type` must be "md" or "latex", not the string "xxx"' + )) +}) + + +test_that("formatting easycorrelations works properly", { + expect_equal(format_stats(test_easycorr), "_r_ = -.12, 95% CI [-0.70, 0.55], _p_ = .748") + expect_equal(format_stats(test_easycorr2), "_ρ_ = -.03, _p_ = .933") + expect_equal(format_stats(test_easycorr3), "_τ_ = .00, _p_ = 1.000") + expect_equal(format_stats(test_easycorr, digits = 3), "_r_ = -.117, 95% CI [-0.695, 0.553], _p_ = .748") + expect_equal(format_stats(test_easycorr, pdigits = 2), "_r_ = -.12, 95% CI [-0.70, 0.55], _p_ = .75") + expect_equal(format_stats(test_easycorr, pzero = TRUE), "_r_ = -0.12, 95% CI [-0.70, 0.55], _p_ = 0.748") + expect_equal(format_stats(test_easycorr, full = FALSE), "_r_ = -.12, _p_ = .748") + expect_equal(format_stats(test_easycorr, italics = FALSE), "r = -.12, 95% CI [-0.70, 0.55], p = .748") + expect_equal(format_stats(test_easycorr, type = "latex"), "$r$ = -.12, 95% CI [-0.70, 0.55], $p$ = .748") +}) + diff --git a/tests/testthat/test-format_stats_htest.R b/tests/testthat/test-format_stats_htest.R new file mode 100644 index 0000000..f7cab83 --- /dev/null +++ b/tests/testthat/test-format_stats_htest.R @@ -0,0 +1,130 @@ + +test_that("htest correlations are validated properly", { + suppressMessages(expect_error( + format_stats(test_corr, digits = "xxx"), + '`digits` must be a whole number or `NULL`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_corr, digits = -1), + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_corr, digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' + )) + suppressMessages(expect_error( + format_stats(test_corr, pdigits = "xxx"), + '`pdigits` must be a whole number, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_corr, pdigits = 0), + '`pdigits` must be a whole number between 1 and 5, not the number 0' + )) + suppressMessages(expect_error( + format_stats(test_corr, pdigits = 7), + '`pdigits` must be a whole number between 1 and 5, not the number 7' + )) + suppressMessages(expect_error( + format_stats(test_corr, pzero = "xxx"), + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_corr, full = "xxx"), + '`full` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_corr, italics = "xxx"), + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_corr, type = "xxx"), + '`type` must be "md" or "latex", not the string "xxx"' + )) +}) + + +test_that("formatting correlations works properly", { + expect_equal(format_stats(test_corr), "_r_ = 1.00, 95% CI [1.00, 1.00], _p_ < .001") + expect_equal(format_stats(test_corr, digits = 3), "_r_ = 1.000, 95% CI [1.000, 1.000], _p_ < .001") + expect_equal(format_stats(test_corr, pdigits = 2), "_r_ = 1.00, 95% CI [1.00, 1.00], _p_ < .01") + expect_equal(format_stats(test_corr, pzero = TRUE), "_r_ = 1.00, 95% CI [1.00, 1.00], _p_ < 0.001") + expect_equal(format_stats(test_corr2), "_r_ = -.12, 95% CI [-0.70, 0.55], _p_ = .748") + expect_equal(format_stats(test_corr2, pzero = TRUE), "_r_ = -0.12, 95% CI [-0.70, 0.55], _p_ = 0.748") + expect_equal(format_stats(test_corr, full = FALSE), "_r_ = 1.00, _p_ < .001") + expect_equal(format_stats(test_corr, italics = FALSE), "r = 1.00, 95% CI [1.00, 1.00], p < .001") + expect_equal(format_stats(test_corr, type = "latex"), "$r$ = 1.00, 95% CI [1.00, 1.00], $p$ < .001") + expect_equal(format_stats(cor.test(df$a, df$b, method = "kendall")), "_τ_ = 1.00, _p_ < .001") + expect_equal(format_stats(cor.test(df$a, df$b, method = "spearman")), "_ρ_ = 1.00, _p_ < .001") +}) + + +test_that("htest t-tests are validated properly", { + suppressMessages(expect_error( + format_stats(test_ttest, digits = "xxx"), + '`digits` must be a whole number or `NULL`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_ttest, digits = -1), + '`digits` must be a whole number larger than or equal to 0 or `NULL`, not the number -1' + )) + suppressMessages(expect_error( + format_stats(test_ttest, digits = 1.5), + '`digits` must be a whole number or `NULL`, not the number 1.5' + )) + suppressMessages(expect_error( + format_stats(test_ttest, pdigits = "xxx"), + '`pdigits` must be a whole number, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_ttest, pdigits = 0), + '`pdigits` must be a whole number between 1 and 5, not the number 0' + )) + suppressMessages(expect_error( + format_stats(test_ttest, pdigits = 7), + '`pdigits` must be a whole number between 1 and 5, not the number 7' + )) + suppressMessages(expect_error( + format_stats(test_ttest, pzero = "xxx"), + '`pzero` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_ttest, full = "xxx"), + '`full` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_ttest, italics = "xxx"), + '`italics` must be `TRUE` or `FALSE`, not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_ttest, dfs = "xxx"), + '`dfs` must be "par", "sub", or "none", not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_ttest, mean = "xxx"), + '`mean` must be "abbr" or "word", not the string "xxx"' + )) + suppressMessages(expect_error( + format_stats(test_ttest, type = "xxx"), + '`type` must be "md" or "latex", not the string "xxx"' + )) +}) + + +test_that("formatting t-tests works properly", { + expect_equal(format_stats(test_ttest1), "_M_ = 5.5, 95% CI [3.3, 7.7], _t_(9) = 0.5, _p_ = .614") + expect_equal(format_stats(test_ttest), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = .470") + expect_equal(format_stats(test_ttest2), "_M_ = -11.3, 95% CI [-34.4, 11.8], _t_(10.2) = -1.1, _p_ = .302") + expect_equal(format_stats(test_ttest, digits = 2), "_M_ = -1.00, 95% CI [-3.84, 1.84], _t_(18) = -0.74, _p_ = .470") + expect_equal(format_stats(test_ttest, pdigits = 2), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = .47") + expect_equal(format_stats(test_ttest, pzero = TRUE), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = 0.470") + expect_equal(format_stats(test_ttest, full = FALSE), "_t_(18) = -0.7, _p_ = .470") + expect_equal(format_stats(test_ttest, italics = FALSE), "M = -1.0, 95% CI [-3.8, 1.8], t(18) = -0.7, p = .470") + expect_equal(format_stats(test_ttest, dfs = "sub"), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_~18~ = -0.7, _p_ = .470") + expect_equal(format_stats(test_ttest, dfs = "none"), "_M_ = -1.0, 95% CI [-3.8, 1.8], _t_ = -0.7, _p_ = .470") + expect_equal(format_stats(test_ttest, type = "latex"), "$M$ = -1.0, 95% CI [-3.8, 1.8], $t$(18) = -0.7, $p$ = .470") + expect_equal(format_stats(test_ttest, type = "latex", dfs = "sub"), "$M$ = -1.0, 95% CI [-3.8, 1.8], $t$$_{18}$ = -0.7, $p$ = .470") + expect_equal(format_stats(test_ttest, mean = "word"), "_Mean_ = -1.0, 95% CI [-3.8, 1.8], _t_(18) = -0.7, _p_ = .470") + suppressMessages(expect_equal(format_stats(test_ttest3), "_V_ = 27.0, _p_ = .634")) + suppressMessages(expect_equal(format_stats(test_ttest4), "_W_ = 40.5, _p_ = .495")) + suppressMessages(expect_equal(format_stats(test_ttest5), "_W_ = 40.5, _p_ = .323")) +}) From fcf5dee1efec0588b6c440542d229c949db4a114 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Wed, 27 Nov 2024 12:00:39 -0600 Subject: [PATCH 15/19] Clean up commented code --- R/format_statvalues.R | 25 ------------------------- 1 file changed, 25 deletions(-) diff --git a/R/format_statvalues.R b/R/format_statvalues.R index 87177ef..4b7400c 100644 --- a/R/format_statvalues.R +++ b/R/format_statvalues.R @@ -40,15 +40,6 @@ format_corr <- function(x, check_bool(italics) check_string(type) check_match(type, c("md", "latex")) - # stopifnot("Argument `digits` must be a non-negative numeric vector." = is.numeric(digits)) - # stopifnot("Argument `digits` must be a non-negative numeric vector." = digits >= 0) - # stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = is.numeric(pdigits)) - # stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits > 0) - # stopifnot("Argument `pdigits` must be a numeric between 1 and 5." = pdigits < 6) - # stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) - # stopifnot("Argument `full` must be TRUE or FALSE." = is.logical(full)) - # stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - # stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) # Format numbers corr_method <- dplyr::case_when( @@ -261,15 +252,6 @@ format_bf <- function(x, check_string(type) check_match(type, c("md", "latex")) - # stopifnot("Argument `digits1` must be a non-negative numeric vector." = is.numeric(digits1)) - # stopifnot("Argument `digits1` must be a non-negative numeric vector." = digits1 >= 0) - # stopifnot("Argument `digits2` must be a non-negative numeric vector." = is.numeric(digits2)) - # stopifnot("Argument `digits2` must be a non-negative numeric vector." = digits2 >= 0) - # stopifnot("Argument `cutoff` must be a numeric vector greater than 1 or NULL." = (is.numeric(cutoff) & cutoff > 1) | is.null(cutoff)) - # stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - # stopifnot("Argument `subscript` must be a character string (usually '10', '01', or '')." = is.character(subscript)) - # stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) - # Build label if (label != "") { bf_lab <- paste0(format_chr(label, italics = italics, type = type), format_sub(subscript, type = type)) @@ -371,13 +353,6 @@ format_p <- function(x, check_bool(italics) check_string(type) check_match(type, c("md", "latex")) - # stopifnot("Input must be a numeric vector." = is.numeric(x)) - # stopifnot("Argument `digits` must be a numeric between 1 and 5." = is.numeric(digits)) - # stopifnot("Argument `digits` must be a numeric between 1 and 5." = digits > 0) - # stopifnot("Argument `digits` must be a numeric between 1 and 5." = digits < 6) - # stopifnot("Argument `pzero` must be TRUE or FALSE." = is.logical(pzero)) - # stopifnot("Argument `italics` must be TRUE or FALSE." = is.logical(italics)) - # stopifnot("Argument `type` must be 'md' or 'latex'." = type %in% c("md", "latex")) # Build label if (label != "") { From 49affd7ac51a2af8519e1dcf1cfa1bb9c7b61165 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Wed, 27 Nov 2024 12:04:13 -0600 Subject: [PATCH 16/19] Remove paper workflow --- .github/workflows/draft-pdf.yml | 24 ------------------------ 1 file changed, 24 deletions(-) delete mode 100644 .github/workflows/draft-pdf.yml diff --git a/.github/workflows/draft-pdf.yml b/.github/workflows/draft-pdf.yml deleted file mode 100644 index 1d7dc44..0000000 --- a/.github/workflows/draft-pdf.yml +++ /dev/null @@ -1,24 +0,0 @@ -name: Draft PDF -on: [push] - -jobs: - paper: - runs-on: ubuntu-latest - name: Paper Draft - steps: - - name: Checkout - uses: actions/checkout@v4 - - name: Build draft PDF - uses: openjournals/openjournals-draft-action@master - with: - journal: joss - # This should be the path to the paper within your repo. - paper-path: paper.md - - name: Upload - uses: actions/upload-artifact@v4 - with: - name: paper - # This is the output path where Pandoc will write the compiled - # PDF. Note, this should be the same directory as the input - # paper.md - path: paper.pdf From cf29c35d7f5b66185633613eac41bf5207238642 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Wed, 27 Nov 2024 12:08:13 -0600 Subject: [PATCH 17/19] Remove R Markdown version of vignette --- vignettes/cocoon.Rmd | 270 ------------------------------------------- 1 file changed, 270 deletions(-) delete mode 100644 vignettes/cocoon.Rmd diff --git a/vignettes/cocoon.Rmd b/vignettes/cocoon.Rmd deleted file mode 100644 index 3c10ba9..0000000 --- a/vignettes/cocoon.Rmd +++ /dev/null @@ -1,270 +0,0 @@ ---- -title: "cocoon" -output: rmarkdown::html_vignette -vignette: > - %\VignetteIndexEntry{cocoon} - %\VignetteEngine{knitr::rmarkdown} - %\VignetteEncoding{UTF-8} ---- - -```{r, include = FALSE} -knitr::opts_chunk$set( - collapse = TRUE, - comment = "#>" -) -library(rlang) -``` - -```{r setup-real, echo = FALSE, message = FALSE} -library(cocoon) -# devtools::load_all(".") -``` - -```{r setup-show, eval = FALSE} -library(cocoon) -``` - -One of the many useful features of the [`{papaja}`](https://github.com/crsh/papaja) package is the [`apa_print()`](https://frederikaust.com/papaja_man/reporting.html#statistical-models-and-tests) -function, which takes a statistical object and formats the output to print the statistical information inline in R Markdown documents. The `apa_print()` function is an easy way to extract and format this statistical information for documents following APA style. However, APA style has some rather strange quirks, and users may want some flexibility in how their statistics are formatted. Moreover, `apa_print()` uses LaTeX syntax, which works great for PDFs but generates images for mathematical symbols when outputting to Word documents. - -The `{cocoon}` package uses APA style as the default, but allows more flexible formatting such as including the leading 0 before numbers with maximum values of 1. All functions accept a `type` argument that specifies either `"md"` for Markdown (default) or `"latex"` for LaTeX. This package can format statistical objects, statistical values, and numbers more generally. - - -## Formatting statistical objects - -Running a statistical test in R typically returns a list with lots of information about the test, often including things like statistical test values and p-values. The aim of the `format_stats()` function is to extract and format statistics for a suite of commonly used statistical objects (correlation and t-tests). - -### Correlations - -The `format_stats()` function can input objects returned by the `cor.test()` or `correlation::correlation()` function and detects whether the object is from a Pearson, Kendall, or Spearman correlation. It then reports and formats the appropriate correlation coefficient and p-value. - -Let's start by creating a few different correlations. - -```{r} -mpg_disp_corr_pearson <- cor.test(mtcars$mpg, mtcars$disp, method = "pearson") -mpg_disp_corr_spearman <- cor.test(mtcars$mpg, mtcars$disp, method = "spearman", exact = FALSE) -mpg_disp_corr_kendall <- cor.test(mtcars$mpg, mtcars$disp, method = "kendall", exact = FALSE) -``` - -For Pearson correlations, we get the correlation coefficient and the confidence intervals. Since Spearman and Kendall correlations are non-parametric, confidence intervals are not returned. Confidence intervals can be omitted from Pearson correlations by setting `full = FALSE`. - -| Code | Output | -|-------|-----| -| `format_stats(mpg_disp_corr_pearson)` | `r format_stats(mpg_disp_corr_pearson)` | -| `format_stats(mpg_disp_corr_pearson, full = FALSE)` | `r format_stats(mpg_disp_corr_pearson, full = FALSE)` | -| `format_stats(mpg_disp_corr_spearman)` | `r format_stats(mpg_disp_corr_spearman)` | -| `format_stats(mpg_disp_corr_kendall)` | `r format_stats(mpg_disp_corr_kendall)` | - -Format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. - -| Code | Output | -|---------|------| -| `format_stats(mpg_disp_corr_pearson)` | `r format_stats(mpg_disp_corr_pearson)` | -| `format_stats(mpg_disp_corr_pearson, digits = 1, pdigits = 2)` | `r format_stats(mpg_disp_corr_pearson, digits = 1, pdigits = 2)` | -| `format_stats(mpg_disp_corr_pearson, pzero = TRUE)` | `r format_stats(mpg_disp_corr_pearson, pzero = TRUE)` | -| `format_stats(mpg_disp_corr_pearson, italics = FALSE)` | `r format_stats(mpg_disp_corr_pearson, italics = FALSE)` | -| `format_stats(mpg_disp_corr_spearman, italics = FALSE)` | `r format_stats(mpg_disp_corr_spearman, italics = FALSE)` | -| `format_stats(mpg_disp_corr_kendall, italics = FALSE)` | `r format_stats(mpg_disp_corr_kendall, italics = FALSE)` | - - -### T-tests - -The `format_stats()` function can also input objects returned by the `t.test()` or `wilcox.test()` functions and detect whether the object is from a Student's or Wilcoxon t-test, including one-sample, independent-sample, and paired-sample versions. It then reports and formats the mean value (or mean difference), confidence intervals for mean value/difference, appropriate test statistic, degrees of freedom (for parametric tests), and p-value. - -Let's start by creating a few different t-tests - -```{r} -ttest_gear_carb <- t.test(mtcars$gear, mtcars$carb) -ttest_gear_carb_paired <- t.test(mtcars$gear, mtcars$carb, paired = TRUE) -ttest_gear_carb_onesample <- t.test(mtcars$gear, mu = 4) -wtest_gear_carb <- wilcox.test(mtcars$gear, mtcars$carb, exact = FALSE) -wtest_gear_carb_paired <- wilcox.test(mtcars$gear, mtcars$carb, paired = TRUE, exact = FALSE) -wtest_gear_carb_onesample <- wilcox.test(mtcars$gear, mu = 4, exact = FALSE) -``` - -For Student's t-tests, we get the mean value or difference and the confidence intervals. Means and confidence intervals can be omitted by setting `full = FALSE`. - -| Code | Output | -|-------|-----| -| `format_stats(ttest_gear_carb)` | `r format_stats(ttest_gear_carb)` | -| `format_stats(ttest_gear_carb_paired)` | `r format_stats(ttest_gear_carb_paired)` | -| `format_stats(ttest_gear_carb_onesample)` | `r format_stats(ttest_gear_carb_onesample)` | -| `format_stats(ttest_gear_carb_onesample, full = FALSE)` | `r format_stats(ttest_gear_carb_onesample, full = FALSE)` | -| `format_stats(wtest_gear_carb)` | `r format_stats(wtest_gear_carb)` | -| `format_stats(wtest_gear_carb_paired)` | `r format_stats(wtest_gear_carb_paired)` | -| `format_stats(wtest_gear_carb_onesample)` | `r format_stats(wtest_gear_carb_onesample)` | - -Format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. - -| Code | Output | -|---------|------| -| `format_stats(ttest_gear_carb)` | `r format_stats(ttest_gear_carb)` | -| `format_stats(ttest_gear_carb, digits = 2, pdigits = 2)` | `r format_stats(ttest_gear_carb, digits = 2, pdigits = 2)` | -| `format_stats(ttest_gear_carb, pzero = TRUE)` | `r format_stats(ttest_gear_carb, pzero = TRUE)` | -| `format_stats(ttest_gear_carb, italics = FALSE)` | `r format_stats(ttest_gear_carb, italics = FALSE)` | -| `format_stats(wtest_gear_carb)` | `r format_stats(wtest_gear_carb)` | -| `format_stats(wtest_gear_carb, italics = FALSE)` | `r format_stats(wtest_gear_carb, italics = FALSE)` | - -### ANOVAs - -The `format_stats()` function can also input objects returned by the `aov()` function. It then reports and formats the F statistic, degrees of freedom, and p-value. - -Let's start by creating an ANOVA - -```{r} -aov_mpg_cyl_hp <- aov(mpg ~ cyl * hp, data = mtcars) -summary(aov_mpg_cyl_hp) -``` - -To use `format_stats()` on ANOVAs, you must pass the `aov` object and a character string describing which term to extract. Apply `summary()` to your `aov` object and copy the text of the term you want to extract. Then you can format the number of digits of coefficients with `digits` and digits of p-values with `pdigits`. Include the leading zeros for coefficients and p-values with `pzero = TRUE`. Remove italics with `italics = FALSE`. With `dfs`, format degrees of freedom as parenthetical (`par`) or subscripts (`sub`) or remove them (`none`). - -| Code | Output | -|-------------|------| -| `format_stats(aov_mpg_cyl_hp, term = "cyl")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl")` | -| `format_stats(aov_mpg_cyl_hp, term = "cyl:hp")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl:hp")` | -| `format_stats(aov_mpg_cyl_hp, term = "cyl", digits = 2, pdigits = 2)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", digits = 2, pdigits = 2)` | -| `format_stats(aov_mpg_cyl_hp, term = "cyl", pzero = TRUE)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", pzero = TRUE)` | -| `format_stats(aov_mpg_cyl_hp, term = "cyl", italics = FALSE)` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", italics = FALSE)` | -| `format_stats(aov_mpg_cyl_hp, term = "cyl", dfs = "sub")` | `r format_stats(aov_mpg_cyl_hp, term = "cyl", dfs = "sub")` | - -F~1, 28~ = 92.5, p < .001 - -### Bayes factors - -The `format_stats()` function can also extract and format Bayes factors from a `BFBayesFactor` object from the [`{BayesFactor}`](https://cran.r-project.org/package=BayesFactor) package. Bayes factors are not as standardized in how they are formatted. One issue is that Bayes factors can be referenced from either the alternative hypothesis (H~1~) or the null hypothesis (H~0~). Also, as a ratio, digits after the decimal are more important below 1 than above 1. - -To respond to the digits issue, the `format_stats()` function controls digits for Bayes factors less than 1 (`digits1`) separately from those greater than 1 (`digits2`). In fact, the defaults are different for these two arguments. Further, Bayes factors can be very large or very small when evidence strongly favors one hypothesis over another. Therefore, the `cutoff` argument set a threshold above which (or below 1/cutoff) the returned value is truncated (e.g., BF > 1000). - -```{r} -bf_corr <- BayesFactor::correlationBF(mtcars$mpg, mtcars$disp) -bf_ttest <- BayesFactor::ttestBF(mtcars$vs, mtcars$am) -bf_lm <- BayesFactor::lmBF(mpg ~ am, data = mtcars) -``` - - -| Code | Output | -|--------|------| -| `format_stats(bf_lm)` | `r format_stats(bf_lm)` | -| `format_stats(bf_lm, digits1 = 2)` | `r format_stats(bf_lm, digits1 = 2)` | -| `format_stats(bf_corr)` | `r format_stats(bf_corr)` | -| `format_stats(bf_corr, cutoff = 1000)` | `r format_stats(bf_corr, cutoff = 1000)` | -| `format_stats(bf_ttest)` | `r format_stats(bf_ttest)` | -| `format_stats(bf_ttest, digits2 = 3)` | `r format_stats(bf_ttest, digits2 = 3)` | -| `format_stats(bf_ttest, cutoff = 3)` | `r format_stats(bf_ttest, cutoff = 3)` | - -The default label for Bayes factors is _BF_~10~. The text of the label can be changed with the `label` argument, where setting `label = ""` omits the label. Italics can be removed with `italics = FALSE`, and the subscript can be set to 01 (`subscript = "01"`) or removed (`subscript = ""`). - -| Code | Output | -|--------|-----| -| `format_stats(bf_lm)` | `r format_stats(bf_lm)` | -| `format_stats(bf_lm, italics = FALSE)` | `r format_stats(bf_lm, italics = FALSE)` | -| `format_stats(bf_lm, subscript = "")` | `r format_stats(bf_lm, subscript = "")` | -| `format_stats(bf_lm, label = "Bayes factor", italics = FALSE, subscript = "")` | `r format_stats(bf_lm, label = "Bayes factor", italics = FALSE, subscript = "")` | -| `format_stats(bf_lm, label = "")` | `r format_stats(bf_lm, label = "")` | - - -## Formatting statistical values - -### Central tendency and error - -#### Data vectors -Often, we need to include simple descriptive statistics in our documents, such as measures of central tendency and error. `{cocoon}` includes a suite of functions that can calculate different summary measures of central tendency (mean or median) and error (confidence interval, standard error, standard deviation, interquartile range) from a numeric data vector. With the base function `format_summary()`, you can specify central tendency with the `summary` argument and error with the `error` argument. For instance, `format_summary(vec, summary = "mean", error = "se")` calculates mean and standard error. - -`{cocoon}` includes a number of wrapper functions that cover common measures of central tendency and error including: - -* `format_meanci()` -* `format_meanse()` -* `format_meansd()` -* `format_medianiqr()` - -And if you don't want to include error, use `format_mean()` or `format_median()`. - -| Code | Output | -|------|--------| -| `format_summary(mtcars$mpg, error = "ci")` | `r format_summary(mtcars$mpg, error = "ci")` | -| `format_meanci(mtcars$mpg)` | `r format_meanci(mtcars$mpg)` | -| `format_medianiqr(mtcars$mpg)` | `r format_medianiqr(mtcars$mpg)` | -| `format_mean(mtcars$mpg)` | `r format_mean(mtcars$mpg)` | - -#### Pre-calculated summaries - -In addition to calculating values directly from the vectors, these functions can format already-calculated measures. So if you already have your mean and error calculated, just pass the vector of central tendency, lower error limit, and upper error limit to the `values` argument to format them. For instance, `format_meanci(values = c(12.5, 11.2, 13.7))` produces `r format_meanci(values = c(12.5, 11.2, 13.7))`. Make sure you pass the arguments in this order, as the function checks whether the send argument is less than or equal to the first and the third is greater than or equal to the first. - -#### Formatting output -These functions can control many aspects of formatting for the values and labels of summary statistics. Digits after the decimal are controlled with `digits` (default is 1). The `tendlabel` argument defines whether the default abbreviation is used ("M" or "Mdn"), the full word ("Mean" or "Median"), or no label is provided. Each of these can be italicized or not with the `italics` argument, subscripts can be included with the `subscript` argument, and units added with the `units` argument. - -| Code | Output | -|------|--------| -| `format_mean(mtcars$mpg)` | `r format_mean(mtcars$mpg)` | -| `format_mean(mtcars$mpg, tendlabel = "word")` | `r format_mean(mtcars$mpg, tendlabel = "word")` | -| `format_mean(mtcars$mpg, tendlabel = "none")` | `r format_mean(mtcars$mpg, tendlabel = "none")` | -| `format_mean(mtcars$mpg, italics = FALSE)` | `r format_mean(mtcars$mpg, italics = FALSE)` | -| `format_mean(mtcars$mpg, subscript = "A")` | `r format_mean(mtcars$mpg, subscript = "A")` | -| `format_mean(mtcars$mpg, units = "m")` | `r format_mean(mtcars$mpg, units = "m")` | - -Error can be displayed in a number of different ways. Setting the `display` argument to `"limits"` (default) includes upper and lower limits in brackets. If intervals rather than limits are preferred, they can be appended after the mean/median with ± using `"pm"` or in parentheses with `"par"`. Error is not displayed if `display = "none"`. The presence of the error label is controlled by the logical argument `errorlabel`. When set to `FALSE`, no error label is included. For confidence intervals, the `cilevel` argument takes a numeric scalar from 0-1 to define the confidence level. - -| Code | Output | -|--------|------| -| `format_meanci(mtcars$mpg)` | `r format_meanci(mtcars$mpg)` | -| `format_meanci(mtcars$mpg, display = "pm")` | `r format_meanci(mtcars$mpg, display = "pm")` | -| `format_meanci(mtcars$mpg, display = "par")` | `r format_meanci(mtcars$mpg, display = "par")` | -| `format_meanci(mtcars$mpg, display = "none")` | `r format_meanci(mtcars$mpg, display = "none")` | -| `format_meanci(mtcars$mpg, errorlabel = FALSE)` | `r format_meanci(mtcars$mpg, errorlabel = FALSE)` | -| `format_meanci(mtcars$mpg, cilevel = 0.90)` | `r format_meanci(mtcars$mpg, cilevel = 0.90)` | - - -### P-values - -P-values are pretty easy to format with `format_p()`. The `digits` argument controls the number of digits after the decimal, and if the value is lower, `p <` is used. Unfortunately, APA style involves lopping off the leading zero in p-values, but setting `pzero = TRUE` turns off this silly setting. The p-value label is controlled by `label`, where the user can specify the exact label text. By default, this is a lower case, italicized _p_. Non-italicized can be defined with `italics = FALSE`. P-value labels can be omitted by setting `label = ""`. - -| Code | Output | -|------|--------| -| `format_p(0.001)` | `r format_p(0.001)` | -| `format_p(0.001, digits = 2)` | `r format_p(0.001, digits = 2)` | -| `format_p(0.321, digits = 2)` | `r format_p(0.321, digits = 2)` | -| `format_p(0.001, pzero = TRUE)` | `r format_p(0.001, pzero = TRUE)` | -| `format_p(0.001, label = "P")` | `r format_p(0.001, label = "P")` | -| `format_p(0.001, italics = FALSE)` | `r format_p(0.001, italics = FALSE)` | -| `format_p(0.001, label = "")` | `r format_p(0.001, label = "")` | - - -### Bayes factors - -Though the `format_stats()` function extracts and formats Bayes factors from the [`{BayesFactor}`](https://cran.r-project.org/package=BayesFactor) package, sometimes you may have Bayes factors from other sources. The `format_bf()` function formats Bayes factors from numeric values (either single scalar elements or vectors). - -| Code | Output | -|--------|------| -| `format_bf(4321)` | `r format_bf(4321)` | -| `format_bf(4321, digits1 = 2)` | `r format_bf(4321, digits1 = 2)` | -| `format_bf(4321, cutoff = 1000)` | `r format_bf(4321, cutoff = 1000)` | -| `format_bf(0.04321)` | `r format_bf(0.04321)` | -| `format_bf(0.04321, digits2 = 3)` | `r format_bf(0.04321, digits2 = 3)` | -| `format_bf(0.04321, cutoff = 10)` | `r format_bf(0.04321, cutoff = 10)` | -| `format_bf(4321, italics = FALSE)` | `r format_bf(4321, italics = FALSE)` | -| `format_bf(4321, subscript = "")` | `r format_bf(4321, subscript = "")` | -| `format_bf(4321, label = "Bayes factor", italics = FALSE, subscript = "")` | `r format_bf(4321, label = "Bayes factor", italics = FALSE, subscript = "")` | -| `format_bf(4321, label = "")` | `r format_bf(4321, label = "")` | -| `format_bf(c(4321, 0.04321))` | `r format_bf(c(4321, 0.04321))` | - - -## Formatting numbers - -In addition to formatting specific statistics, this package can format numbers more generally. The `format_num()` function controls general formatting of numbers of digits with `digits` and the presence of the leading zero with `pzero`. - -| Code | Output | -|---------|------| -| `format_num(0.1234)` | `r format_num(0.1234)` | -| `format_num(0.1234, digits = 2)` | `r format_num(0.1234, digits = 2)` | -| `format_num(0.1234, pzero = FALSE)` | `r format_num(0.1234, pzero = FALSE)` | - -For large or small values, using scientific notation may be a more useful way to format the numbers. The `format_scientific()` function converts to scientific notation, again offering control of the number of `digits` as well as whether output `type` is Markdown or LaTeX. - -| Code | Output | -|---------|------| -| `format_scientific(1234)` | `r format_scientific(1234)` | -| `format_scientific(0.0000001234)` | `r format_scientific(0.0000001234)` | -| `format_scientific(0.0000001234, digits = 2)` | `r format_scientific(0.0000001234, digits = 2)` | - - - From 2529c86e4b4635f0078feada8c4da9e1c01c1199 Mon Sep 17 00:00:00 2001 From: "Jeffrey R. Stevens" Date: Wed, 27 Nov 2024 12:15:13 -0600 Subject: [PATCH 18/19] Add format_stats.aov to pkgdown --- _pkgdown.yml | 5 +- vignettes/.gitignore | 2 + ...p-93d79d5d413ef011dde10b33346a7d31.min.css | 12 - .../libs/bootstrap/bootstrap-icons.css | 2078 ----------------- .../libs/bootstrap/bootstrap-icons.woff | Bin 176200 -> 0 bytes .../libs/bootstrap/bootstrap.min.js | 7 - .../libs/clipboard/clipboard.min.js | 7 - .../libs/quarto-html/anchor.min.js | 9 - .../libs/quarto-html/popper.min.js | 6 - ...hting-29e2c20b02301cfff04dc8050bf30c7e.css | 205 -- .../cocoon_files/libs/quarto-html/quarto.js | 911 -------- .../cocoon_files/libs/quarto-html/tippy.css | 1 - .../libs/quarto-html/tippy.umd.min.js | 2 - 13 files changed, 5 insertions(+), 3240 deletions(-) delete mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css delete mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.css delete mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.woff delete mode 100644 vignettes/cocoon_files/libs/bootstrap/bootstrap.min.js delete mode 100644 vignettes/cocoon_files/libs/clipboard/clipboard.min.js delete mode 100644 vignettes/cocoon_files/libs/quarto-html/anchor.min.js delete mode 100644 vignettes/cocoon_files/libs/quarto-html/popper.min.js delete mode 100644 vignettes/cocoon_files/libs/quarto-html/quarto-syntax-highlighting-29e2c20b02301cfff04dc8050bf30c7e.css delete mode 100644 vignettes/cocoon_files/libs/quarto-html/quarto.js delete mode 100644 vignettes/cocoon_files/libs/quarto-html/tippy.css delete mode 100644 vignettes/cocoon_files/libs/quarto-html/tippy.umd.min.js diff --git a/_pkgdown.yml b/_pkgdown.yml index 314058c..f5b0049 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -17,9 +17,10 @@ reference: - title: Format statistical objects contents: - format_stats - - format_stats.htest - - format_stats.easycorrelation + - format_stats.aov - format_stats.BFBayesFactor + - format_stats.easycorrelation + - format_stats.htest - title: Format statistical values contents: - format_summary diff --git a/vignettes/.gitignore b/vignettes/.gitignore index 097b241..9e2bd63 100644 --- a/vignettes/.gitignore +++ b/vignettes/.gitignore @@ -1,2 +1,4 @@ *.html *.R + +/.quarto/ diff --git a/vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css b/vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css deleted file mode 100644 index 04c15c5..0000000 --- a/vignettes/cocoon_files/libs/bootstrap/bootstrap-93d79d5d413ef011dde10b33346a7d31.min.css +++ /dev/null @@ -1,12 +0,0 @@ -/*! - * Bootstrap v5.3.1 (https://getbootstrap.com/) - * Copyright 2011-2023 The Bootstrap Authors - * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) - */:root,[data-bs-theme=light]{--bs-blue: #0d6efd;--bs-indigo: #6610f2;--bs-purple: #6f42c1;--bs-pink: #d63384;--bs-red: #dc3545;--bs-orange: 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1rem;--bs-nav-link-padding-y: 0.5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: #0d6efd;--bs-nav-link-hover-color: #0a58ca;--bs-nav-link-disabled-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) var(--bs-nav-link-padding-x);font-size:var(--bs-nav-link-font-size);font-weight:var(--bs-nav-link-font-weight);color:var(--bs-nav-link-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background:none;border:0;transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out}@media(prefers-reduced-motion: reduce){.nav-link{transition:none}}.nav-link:hover,.nav-link:focus{color:var(--bs-nav-link-hover-color)}.nav-link:focus-visible{outline:0;box-shadow:0 0 0 .25rem 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.offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex 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6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: #86b7fe;--bs-accordion-btn-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: #052c65;--bs-accordion-active-bg: #cfe2ff}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media(prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1*var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--bs-breadcrumb-item-padding-x: 0.5rem;--bs-breadcrumb-item-active-color: rgba(33, 37, 41, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, ">") /* rtl: var(--bs-breadcrumb-divider, ">") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #0d6efd;--bs-pagination-bg: #ffffff;--bs-pagination-border-width: 1px;--bs-pagination-border-color: white;--bs-pagination-border-radius: 0.375rem;--bs-pagination-hover-color: #0a58ca;--bs-pagination-hover-bg: #f8f9fa;--bs-pagination-hover-border-color: white;--bs-pagination-focus-color: #0a58ca;--bs-pagination-focus-bg: #e9ecef;--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-pagination-active-color: #ffffff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: rgba(33, 37, 41, 0.75);--bs-pagination-disabled-bg: #e9ecef;--bs-pagination-disabled-border-color: white;display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(1px*-1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: 0.5rem}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: 0.25rem}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #ffffff;--bs-badge-border-radius: 0.375rem;display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 1px solid var(--bs-alert-border-color);--bs-alert-border-radius: 0.375rem;--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: #e9ecef;--bs-progress-border-radius: 0.375rem;--bs-progress-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075);--bs-progress-bar-color: #ffffff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: #212529;--bs-list-group-bg: #ffffff;--bs-list-group-border-color: white;--bs-list-group-border-width: 1px;--bs-list-group-border-radius: 0.375rem;--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: rgba(33, 37, 41, 0.75);--bs-list-group-action-hover-color: #000;--bs-list-group-action-hover-bg: #f8f9fa;--bs-list-group-action-active-color: #212529;--bs-list-group-action-active-bg: #e9ecef;--bs-list-group-disabled-color: rgba(33, 37, 41, 0.75);--bs-list-group-disabled-bg: #ffffff;--bs-list-group-active-color: #ffffff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: #0d6efd;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item:first-child{border-top-left-radius:inherit;border-top-right-radius:inherit}.list-group-item:last-child{border-bottom-right-radius:inherit;border-bottom-left-radius:inherit}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1*var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media(min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xxl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: 0.5;--bs-btn-close-hover-opacity: 0.75;--bs-btn-close-focus-shadow: 0 0 0 0.25rem rgba(13, 110, 253, 0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: 0.25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:rgba(0,0,0,0) var(--bs-btn-close-bg) center/1em auto no-repeat;border:0;border-radius:.375rem;opacity:var(--bs-btn-close-opacity)}.btn-close:hover{color:var(--bs-btn-close-color);text-decoration:none;opacity:var(--bs-btn-close-hover-opacity)}.btn-close:focus{outline:0;box-shadow:var(--bs-btn-close-focus-shadow);opacity:var(--bs-btn-close-focus-opacity)}.btn-close:disabled,.btn-close.disabled{pointer-events:none;user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;opacity:var(--bs-btn-close-disabled-opacity)}.btn-close-white{filter:var(--bs-btn-close-white-filter)}[data-bs-theme=dark] .btn-close{filter:var(--bs-btn-close-white-filter)}.toast{--bs-toast-zindex: 1090;--bs-toast-padding-x: 0.75rem;--bs-toast-padding-y: 0.5rem;--bs-toast-spacing: 1.5rem;--bs-toast-max-width: 350px;--bs-toast-font-size:0.875rem;--bs-toast-color: ;--bs-toast-bg: rgba(255, 255, 255, 0.85);--bs-toast-border-width: 1px;--bs-toast-border-color: rgba(0, 0, 0, 0.175);--bs-toast-border-radius: 0.375rem;--bs-toast-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15);--bs-toast-header-color: rgba(33, 37, 41, 0.75);--bs-toast-header-bg: rgba(255, 255, 255, 0.85);--bs-toast-header-border-color: rgba(0, 0, 0, 0.175);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow);border-radius:var(--bs-toast-border-radius)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 1090;position:absolute;z-index:var(--bs-toast-zindex);width:max-content;width:-webkit-max-content;width:-moz-max-content;width:-ms-max-content;width:-o-max-content;max-width:100%;pointer-events:none}.toast-container>:not(:last-child){margin-bottom:var(--bs-toast-spacing)}.toast-header{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;padding:var(--bs-toast-padding-y) var(--bs-toast-padding-x);color:var(--bs-toast-header-color);background-color:var(--bs-toast-header-bg);background-clip:padding-box;border-bottom:var(--bs-toast-border-width) solid var(--bs-toast-header-border-color);border-top-left-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width));border-top-right-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width))}.toast-header .btn-close{margin-right:calc(-0.5*var(--bs-toast-padding-x));margin-left:var(--bs-toast-padding-x)}.toast-body{padding:var(--bs-toast-padding-x);word-wrap:break-word}.modal{--bs-modal-zindex: 1055;--bs-modal-width: 500px;--bs-modal-padding: 1rem;--bs-modal-margin: 0.5rem;--bs-modal-color: ;--bs-modal-bg: #ffffff;--bs-modal-border-color: rgba(0, 0, 0, 0.175);--bs-modal-border-width: 1px;--bs-modal-border-radius: 0.5rem;--bs-modal-box-shadow: 0 0.125rem 0.25rem rgba(0, 0, 0, 0.075);--bs-modal-inner-border-radius: calc(0.5rem - 1px);--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1rem 1rem;--bs-modal-header-border-color: white;--bs-modal-header-border-width: 1px;--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: 0.5rem;--bs-modal-footer-bg: ;--bs-modal-footer-border-color: white;--bs-modal-footer-border-width: 1px;position:fixed;top:0;left:0;z-index:var(--bs-modal-zindex);display:none;width:100%;height:100%;overflow-x:hidden;overflow-y:auto;outline:0}.modal-dialog{position:relative;width:auto;margin:var(--bs-modal-margin);pointer-events:none}.modal.fade .modal-dialog{transition:transform .3s ease-out;transform:translate(0, -50px)}@media(prefers-reduced-motion: reduce){.modal.fade .modal-dialog{transition:none}}.modal.show .modal-dialog{transform:none}.modal.modal-static .modal-dialog{transform:scale(1.02)}.modal-dialog-scrollable{height:calc(100% - var(--bs-modal-margin)*2)}.modal-dialog-scrollable .modal-content{max-height:100%;overflow:hidden}.modal-dialog-scrollable .modal-body{overflow-y:auto}.modal-dialog-centered{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;min-height:calc(100% - var(--bs-modal-margin)*2)}.modal-content{position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;width:100%;color:var(--bs-modal-color);pointer-events:auto;background-color:var(--bs-modal-bg);background-clip:padding-box;border:var(--bs-modal-border-width) solid var(--bs-modal-border-color);border-radius:var(--bs-modal-border-radius);outline:0}.modal-backdrop{--bs-backdrop-zindex: 1050;--bs-backdrop-bg: #000;--bs-backdrop-opacity: 0.5;position:fixed;top:0;left:0;z-index:var(--bs-backdrop-zindex);width:100vw;height:100vh;background-color:var(--bs-backdrop-bg)}.modal-backdrop.fade{opacity:0}.modal-backdrop.show{opacity:var(--bs-backdrop-opacity)}.modal-header{display:flex;display:-webkit-flex;flex-shrink:0;-webkit-flex-shrink:0;align-items:center;-webkit-align-items:center;justify-content:space-between;-webkit-justify-content:space-between;padding:var(--bs-modal-header-padding);border-bottom:var(--bs-modal-header-border-width) solid var(--bs-modal-header-border-color);border-top-left-radius:var(--bs-modal-inner-border-radius);border-top-right-radius:var(--bs-modal-inner-border-radius)}.modal-header .btn-close{padding:calc(var(--bs-modal-header-padding-y)*.5) calc(var(--bs-modal-header-padding-x)*.5);margin:calc(-0.5*var(--bs-modal-header-padding-y)) calc(-0.5*var(--bs-modal-header-padding-x)) calc(-0.5*var(--bs-modal-header-padding-y)) auto}.modal-title{margin-bottom:0;line-height:var(--bs-modal-title-line-height)}.modal-body{position:relative;flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-modal-padding)}.modal-footer{display:flex;display:-webkit-flex;flex-shrink:0;-webkit-flex-shrink:0;flex-wrap:wrap;-webkit-flex-wrap:wrap;align-items:center;-webkit-align-items:center;justify-content:flex-end;-webkit-justify-content:flex-end;padding:calc(var(--bs-modal-padding) - var(--bs-modal-footer-gap)*.5);background-color:var(--bs-modal-footer-bg);border-top:var(--bs-modal-footer-border-width) solid 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#ffffff;--quarto-scss-export-form-check-input-checked-bg-color: #0d6efd;--quarto-scss-export-form-check-input-checked-border-color: #0d6efd;--quarto-scss-export-form-check-input-indeterminate-color: #ffffff;--quarto-scss-export-form-check-input-indeterminate-bg-color: #0d6efd;--quarto-scss-export-form-check-input-indeterminate-border-color: #0d6efd;--quarto-scss-export-form-switch-color: rgba(0, 0, 0, 0.25);--quarto-scss-export-form-switch-focus-color: #86b7fe;--quarto-scss-export-form-switch-checked-color: #ffffff;--quarto-scss-export-input-group-addon-color: #212529;--quarto-scss-export-input-group-addon-bg: #f8f9fa;--quarto-scss-export-input-group-addon-border-color: white;--quarto-scss-export-form-select-font-family: ;--quarto-scss-export-form-select-color: #212529;--quarto-scss-export-form-select-bg: #ffffff;--quarto-scss-export-form-select-disabled-color: ;--quarto-scss-export-form-select-disabled-bg: #e9ecef;--quarto-scss-export-form-select-disabled-border-color: ;--quarto-scss-export-form-select-indicator-color: #343a40;--quarto-scss-export-form-select-border-color: white;--quarto-scss-export-form-select-focus-border-color: #86b7fe;--quarto-scss-export-form-range-track-bg: #f8f9fa;--quarto-scss-export-form-range-thumb-bg: #0d6efd;--quarto-scss-export-form-range-thumb-active-bg: #b6d4fe;--quarto-scss-export-form-range-thumb-disabled-bg: rgba(33, 37, 41, 0.75);--quarto-scss-export-form-file-button-color: #212529;--quarto-scss-export-form-file-button-bg: #f8f9fa;--quarto-scss-export-form-file-button-hover-bg: #e9ecef;--quarto-scss-export-form-floating-label-disabled-color: #6c757d;--quarto-scss-export-form-feedback-font-style: ;--quarto-scss-export-form-feedback-valid-color: #198754;--quarto-scss-export-form-feedback-invalid-color: #dc3545;--quarto-scss-export-form-feedback-icon-valid-color: #198754;--quarto-scss-export-form-feedback-icon-invalid-color: #dc3545;--quarto-scss-export-form-valid-color: #198754;--quarto-scss-export-form-valid-border-color: #198754;--quarto-scss-export-form-invalid-color: #dc3545;--quarto-scss-export-form-invalid-border-color: #dc3545;--quarto-scss-export-nav-link-font-size: ;--quarto-scss-export-nav-link-font-weight: ;--quarto-scss-export-nav-link-color: #0d6efd;--quarto-scss-export-nav-link-hover-color: #0a58ca;--quarto-scss-export-nav-link-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-nav-tabs-border-color: white;--quarto-scss-export-nav-tabs-link-hover-border-color: #e9ecef #e9ecef white;--quarto-scss-export-nav-tabs-link-active-color: #000;--quarto-scss-export-nav-tabs-link-active-bg: #ffffff;--quarto-scss-export-nav-pills-link-active-bg: #0d6efd;--quarto-scss-export-nav-pills-link-active-color: #ffffff;--quarto-scss-export-nav-underline-link-active-color: #000;--quarto-scss-export-navbar-padding-x: ;--quarto-scss-export-navbar-light-contrast: #ffffff;--quarto-scss-export-navbar-dark-contrast: #ffffff;--quarto-scss-export-navbar-light-icon-color: rgba(255, 255, 255, 0.75);--quarto-scss-export-navbar-dark-icon-color: rgba(255, 255, 255, 0.75);--quarto-scss-export-dropdown-color: #212529;--quarto-scss-export-dropdown-bg: #ffffff;--quarto-scss-export-dropdown-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-divider-bg: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-link-color: #212529;--quarto-scss-export-dropdown-link-hover-color: #212529;--quarto-scss-export-dropdown-link-hover-bg: #f8f9fa;--quarto-scss-export-dropdown-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-link-active-color: #ffffff;--quarto-scss-export-dropdown-link-disabled-color: rgba(33, 37, 41, 0.5);--quarto-scss-export-dropdown-header-color: #6c757d;--quarto-scss-export-dropdown-dark-color: #dee2e6;--quarto-scss-export-dropdown-dark-bg: #343a40;--quarto-scss-export-dropdown-dark-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-dark-divider-bg: rgba(0, 0, 0, 0.175);--quarto-scss-export-dropdown-dark-box-shadow: ;--quarto-scss-export-dropdown-dark-link-color: #dee2e6;--quarto-scss-export-dropdown-dark-link-hover-color: #ffffff;--quarto-scss-export-dropdown-dark-link-hover-bg: rgba(255, 255, 255, 0.15);--quarto-scss-export-dropdown-dark-link-active-color: #ffffff;--quarto-scss-export-dropdown-dark-link-active-bg: #0d6efd;--quarto-scss-export-dropdown-dark-link-disabled-color: #adb5bd;--quarto-scss-export-dropdown-dark-header-color: #adb5bd;--quarto-scss-export-pagination-color: #0d6efd;--quarto-scss-export-pagination-bg: #ffffff;--quarto-scss-export-pagination-border-color: white;--quarto-scss-export-pagination-focus-color: #0a58ca;--quarto-scss-export-pagination-focus-bg: #e9ecef;--quarto-scss-export-pagination-hover-color: #0a58ca;--quarto-scss-export-pagination-hover-bg: #f8f9fa;--quarto-scss-export-pagination-hover-border-color: white;--quarto-scss-export-pagination-active-color: #ffffff;--quarto-scss-export-pagination-active-bg: #0d6efd;--quarto-scss-export-pagination-active-border-color: #0d6efd;--quarto-scss-export-pagination-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-pagination-disabled-bg: #e9ecef;--quarto-scss-export-pagination-disabled-border-color: white;--quarto-scss-export-card-title-color: ;--quarto-scss-export-card-subtitle-color: ;--quarto-scss-export-card-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-card-box-shadow: ;--quarto-scss-export-card-cap-bg: rgba(33, 37, 41, 0.03);--quarto-scss-export-card-cap-color: ;--quarto-scss-export-card-height: ;--quarto-scss-export-card-color: ;--quarto-scss-export-card-bg: #ffffff;--quarto-scss-export-accordion-color: #212529;--quarto-scss-export-accordion-bg: #ffffff;--quarto-scss-export-accordion-border-color: white;--quarto-scss-export-accordion-button-color: #212529;--quarto-scss-export-accordion-button-bg: #ffffff;--quarto-scss-export-accordion-button-active-bg: #cfe2ff;--quarto-scss-export-accordion-button-active-color: #052c65;--quarto-scss-export-accordion-button-focus-border-color: #86b7fe;--quarto-scss-export-accordion-icon-color: #212529;--quarto-scss-export-accordion-icon-active-color: #052c65;--quarto-scss-export-tooltip-color: #ffffff;--quarto-scss-export-tooltip-bg: #000;--quarto-scss-export-tooltip-margin: ;--quarto-scss-export-tooltip-arrow-color: ;--quarto-scss-export-form-feedback-tooltip-line-height: ;--quarto-scss-export-popover-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-popover-header-bg: #e9ecef;--quarto-scss-export-popover-body-color: #212529;--quarto-scss-export-popover-arrow-color: #ffffff;--quarto-scss-export-popover-arrow-outer-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-color: ;--quarto-scss-export-toast-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-toast-header-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-toast-header-background-color: rgba(255, 255, 255, 0.85);--quarto-scss-export-toast-header-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-badge-color: #ffffff;--quarto-scss-export-modal-content-color: ;--quarto-scss-export-modal-content-bg: #ffffff;--quarto-scss-export-modal-content-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-modal-backdrop-bg: #000;--quarto-scss-export-modal-header-border-color: white;--quarto-scss-export-modal-footer-bg: ;--quarto-scss-export-modal-footer-border-color: white;--quarto-scss-export-progress-bg: #e9ecef;--quarto-scss-export-progress-bar-color: #ffffff;--quarto-scss-export-progress-bar-bg: #0d6efd;--quarto-scss-export-list-group-color: #212529;--quarto-scss-export-list-group-bg: #ffffff;--quarto-scss-export-list-group-border-color: white;--quarto-scss-export-list-group-hover-bg: #f8f9fa;--quarto-scss-export-list-group-active-bg: #0d6efd;--quarto-scss-export-list-group-active-color: #ffffff;--quarto-scss-export-list-group-active-border-color: #0d6efd;--quarto-scss-export-list-group-disabled-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-disabled-bg: #ffffff;--quarto-scss-export-list-group-action-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-list-group-action-hover-color: #000;--quarto-scss-export-list-group-action-active-color: #212529;--quarto-scss-export-list-group-action-active-bg: #e9ecef;--quarto-scss-export-thumbnail-bg: #ffffff;--quarto-scss-export-thumbnail-border-color: white;--quarto-scss-export-figure-caption-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-font-size: ;--quarto-scss-export-breadcrumb-bg: ;--quarto-scss-export-breadcrumb-divider-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-active-color: rgba(33, 37, 41, 0.75);--quarto-scss-export-breadcrumb-border-radius: ;--quarto-scss-export-carousel-control-color: #ffffff;--quarto-scss-export-carousel-indicator-active-bg: #ffffff;--quarto-scss-export-carousel-caption-color: #ffffff;--quarto-scss-export-carousel-dark-indicator-active-bg: #000;--quarto-scss-export-carousel-dark-caption-color: #000;--quarto-scss-export-btn-close-color: #000;--quarto-scss-export-offcanvas-border-color: rgba(0, 0, 0, 0.175);--quarto-scss-export-offcanvas-bg-color: #ffffff;--quarto-scss-export-offcanvas-color: #212529;--quarto-scss-export-offcanvas-backdrop-bg: #000;--quarto-scss-export-code-color-dark: white;--quarto-scss-export-kbd-color: #ffffff;--quarto-scss-export-kbd-bg: #212529;--quarto-scss-export-nested-kbd-font-weight: ;--quarto-scss-export-pre-bg: #f8f9fa;--quarto-scss-export-pre-color: #000;--quarto-scss-export-bslib-sidebar-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.05);--quarto-scss-export-bslib-sidebar-toggle-bg: rgba(var(--bs-emphasis-color-rgb, 0, 0, 0), 0.1);--quarto-scss-export-bslib-page-sidebar-title-bg: #517699;--quarto-scss-export-bslib-page-sidebar-title-color: #ffffff;--quarto-scss-export-mermaid-bg-color: #ffffff;--quarto-scss-export-mermaid-edge-color: #6c757d;--quarto-scss-export-mermaid-node-fg-color: #212529;--quarto-scss-export-mermaid-fg-color: #212529;--quarto-scss-export-mermaid-fg-color--lighter: #383f45;--quarto-scss-export-mermaid-fg-color--lightest: #4e5862;--quarto-scss-export-mermaid-label-bg-color: #ffffff;--quarto-scss-export-mermaid-label-fg-color: #0d6efd;--quarto-scss-export-mermaid-node-bg-color: rgba(13, 110, 253, 0.1);--quarto-scss-export-code-block-border-left-color: white;--quarto-scss-export-callout-color-note: #0d6efd;--quarto-scss-export-callout-color-tip: #198754;--quarto-scss-export-callout-color-important: #dc3545;--quarto-scss-export-callout-color-caution: #fd7e14;--quarto-scss-export-callout-color-warning: #ffc107} \ No newline at end of file diff --git a/vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.css b/vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.css deleted file mode 100644 index 285e444..0000000 --- a/vignettes/cocoon_files/libs/bootstrap/bootstrap-icons.css +++ /dev/null @@ -1,2078 +0,0 @@ -/*! - * Bootstrap Icons v1.11.1 (https://icons.getbootstrap.com/) - * Copyright 2019-2023 The Bootstrap Authors - * Licensed under MIT (https://github.com/twbs/icons/blob/main/LICENSE) - */ - -@font-face { - font-display: block; - font-family: "bootstrap-icons"; - src: -url("./bootstrap-icons.woff?2820a3852bdb9a5832199cc61cec4e65") format("woff"); -} - -.bi::before, -[class^="bi-"]::before, -[class*=" bi-"]::before { - display: inline-block; - font-family: bootstrap-icons !important; - font-style: normal; - font-weight: normal !important; - font-variant: normal; - text-transform: none; - line-height: 1; - vertical-align: -.125em; - -webkit-font-smoothing: antialiased; - -moz-osx-font-smoothing: grayscale; -} - -.bi-123::before { content: "\f67f"; } -.bi-alarm-fill::before { content: "\f101"; } -.bi-alarm::before { content: "\f102"; } -.bi-align-bottom::before { content: "\f103"; } 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} -.bi-badge-cc-fill::before { content: "\f164"; } -.bi-badge-cc::before { content: "\f165"; } -.bi-badge-hd-fill::before { content: "\f166"; } -.bi-badge-hd::before { content: "\f167"; } -.bi-badge-tm-fill::before { content: "\f168"; } -.bi-badge-tm::before { content: "\f169"; } -.bi-badge-vo-fill::before { content: "\f16a"; } -.bi-badge-vo::before { content: "\f16b"; } -.bi-badge-vr-fill::before { content: "\f16c"; } -.bi-badge-vr::before { content: "\f16d"; } -.bi-badge-wc-fill::before { content: "\f16e"; } -.bi-badge-wc::before { content: "\f16f"; } -.bi-bag-check-fill::before { content: "\f170"; } -.bi-bag-check::before { content: "\f171"; } -.bi-bag-dash-fill::before { content: "\f172"; } -.bi-bag-dash::before { content: "\f173"; } -.bi-bag-fill::before { content: "\f174"; } -.bi-bag-plus-fill::before { content: "\f175"; } -.bi-bag-plus::before { content: "\f176"; } -.bi-bag-x-fill::before { content: "\f177"; } -.bi-bag-x::before { content: "\f178"; } -.bi-bag::before { content: 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-.bi-binoculars::before { content: "\f18f"; } -.bi-blockquote-left::before { content: "\f190"; } -.bi-blockquote-right::before { content: "\f191"; } -.bi-book-fill::before { content: "\f192"; } -.bi-book-half::before { content: "\f193"; } -.bi-book::before { content: "\f194"; } -.bi-bookmark-check-fill::before { content: "\f195"; } -.bi-bookmark-check::before { content: "\f196"; } -.bi-bookmark-dash-fill::before { content: "\f197"; } -.bi-bookmark-dash::before { content: "\f198"; } -.bi-bookmark-fill::before { content: "\f199"; } -.bi-bookmark-heart-fill::before { content: "\f19a"; } -.bi-bookmark-heart::before { content: "\f19b"; } -.bi-bookmark-plus-fill::before { content: "\f19c"; } -.bi-bookmark-plus::before { content: "\f19d"; } -.bi-bookmark-star-fill::before { content: "\f19e"; } -.bi-bookmark-star::before { content: "\f19f"; } -.bi-bookmark-x-fill::before { content: "\f1a0"; } -.bi-bookmark-x::before { content: "\f1a1"; } -.bi-bookmark::before { content: "\f1a2"; } -.bi-bookmarks-fill::before { content: "\f1a3"; } -.bi-bookmarks::before { content: "\f1a4"; } -.bi-bookshelf::before { content: "\f1a5"; } -.bi-bootstrap-fill::before { content: "\f1a6"; } -.bi-bootstrap-reboot::before { content: "\f1a7"; } -.bi-bootstrap::before { content: "\f1a8"; } -.bi-border-all::before { content: "\f1a9"; } -.bi-border-bottom::before { content: "\f1aa"; } -.bi-border-center::before { content: "\f1ab"; } -.bi-border-inner::before { content: "\f1ac"; } -.bi-border-left::before { content: "\f1ad"; } -.bi-border-middle::before { content: "\f1ae"; } -.bi-border-outer::before { content: "\f1af"; } -.bi-border-right::before { content: "\f1b0"; } -.bi-border-style::before { content: "\f1b1"; } -.bi-border-top::before { content: "\f1b2"; } -.bi-border-width::before { content: "\f1b3"; } -.bi-border::before { content: "\f1b4"; } -.bi-bounding-box-circles::before { content: "\f1b5"; } -.bi-bounding-box::before { content: "\f1b6"; } -.bi-box-arrow-down-left::before { content: "\f1b7"; } -.bi-box-arrow-down-right::before { content: "\f1b8"; } -.bi-box-arrow-down::before { content: "\f1b9"; } -.bi-box-arrow-in-down-left::before { content: "\f1ba"; } -.bi-box-arrow-in-down-right::before { content: "\f1bb"; } -.bi-box-arrow-in-down::before { content: "\f1bc"; } -.bi-box-arrow-in-left::before { content: "\f1bd"; } -.bi-box-arrow-in-right::before { content: "\f1be"; } -.bi-box-arrow-in-up-left::before { content: "\f1bf"; } -.bi-box-arrow-in-up-right::before { content: "\f1c0"; } -.bi-box-arrow-in-up::before { content: "\f1c1"; } -.bi-box-arrow-left::before { content: "\f1c2"; } -.bi-box-arrow-right::before { content: "\f1c3"; } -.bi-box-arrow-up-left::before { content: "\f1c4"; } -.bi-box-arrow-up-right::before { content: "\f1c5"; } -.bi-box-arrow-up::before { content: "\f1c6"; } -.bi-box-seam::before { content: "\f1c7"; } -.bi-box::before { content: "\f1c8"; } -.bi-braces::before { content: "\f1c9"; } -.bi-bricks::before { content: "\f1ca"; } -.bi-briefcase-fill::before { content: "\f1cb"; } -.bi-briefcase::before { content: "\f1cc"; } -.bi-brightness-alt-high-fill::before { content: "\f1cd"; } -.bi-brightness-alt-high::before { content: "\f1ce"; } -.bi-brightness-alt-low-fill::before { content: "\f1cf"; } -.bi-brightness-alt-low::before { content: "\f1d0"; } -.bi-brightness-high-fill::before { content: "\f1d1"; } -.bi-brightness-high::before { content: "\f1d2"; } -.bi-brightness-low-fill::before { content: "\f1d3"; } -.bi-brightness-low::before { content: "\f1d4"; } -.bi-broadcast-pin::before { content: "\f1d5"; } -.bi-broadcast::before { content: "\f1d6"; } -.bi-brush-fill::before { content: "\f1d7"; } -.bi-brush::before { content: "\f1d8"; } -.bi-bucket-fill::before { content: "\f1d9"; } -.bi-bucket::before { content: "\f1da"; } -.bi-bug-fill::before { content: "\f1db"; } -.bi-bug::before { content: "\f1dc"; } -.bi-building::before { content: "\f1dd"; } -.bi-bullseye::before { content: "\f1de"; } -.bi-calculator-fill::before { content: "\f1df"; } -.bi-calculator::before { content: "\f1e0"; } -.bi-calendar-check-fill::before { content: "\f1e1"; } -.bi-calendar-check::before { content: "\f1e2"; } -.bi-calendar-date-fill::before { content: "\f1e3"; } -.bi-calendar-date::before { content: "\f1e4"; } -.bi-calendar-day-fill::before { content: "\f1e5"; } -.bi-calendar-day::before { content: "\f1e6"; } -.bi-calendar-event-fill::before { content: "\f1e7"; } -.bi-calendar-event::before { content: "\f1e8"; } -.bi-calendar-fill::before { content: "\f1e9"; } -.bi-calendar-minus-fill::before { content: "\f1ea"; } -.bi-calendar-minus::before { content: "\f1eb"; } -.bi-calendar-month-fill::before { content: "\f1ec"; } -.bi-calendar-month::before { content: "\f1ed"; } -.bi-calendar-plus-fill::before { content: "\f1ee"; } -.bi-calendar-plus::before { content: "\f1ef"; } -.bi-calendar-range-fill::before { content: "\f1f0"; } -.bi-calendar-range::before { content: "\f1f1"; } -.bi-calendar-week-fill::before { content: "\f1f2"; } -.bi-calendar-week::before { content: "\f1f3"; } -.bi-calendar-x-fill::before { content: "\f1f4"; } -.bi-calendar-x::before { content: "\f1f5"; } -.bi-calendar::before { content: "\f1f6"; } -.bi-calendar2-check-fill::before { content: "\f1f7"; } -.bi-calendar2-check::before { content: "\f1f8"; } -.bi-calendar2-date-fill::before { content: "\f1f9"; } -.bi-calendar2-date::before { content: "\f1fa"; } -.bi-calendar2-day-fill::before { content: "\f1fb"; } -.bi-calendar2-day::before { content: "\f1fc"; } -.bi-calendar2-event-fill::before { content: "\f1fd"; } -.bi-calendar2-event::before { content: "\f1fe"; } -.bi-calendar2-fill::before { content: "\f1ff"; } -.bi-calendar2-minus-fill::before { content: "\f200"; } -.bi-calendar2-minus::before { content: "\f201"; } -.bi-calendar2-month-fill::before { content: "\f202"; } -.bi-calendar2-month::before { content: "\f203"; } -.bi-calendar2-plus-fill::before { content: "\f204"; } -.bi-calendar2-plus::before { content: "\f205"; } -.bi-calendar2-range-fill::before { content: "\f206"; } -.bi-calendar2-range::before { content: "\f207"; } -.bi-calendar2-week-fill::before { content: "\f208"; } -.bi-calendar2-week::before { content: "\f209"; } -.bi-calendar2-x-fill::before { content: "\f20a"; } -.bi-calendar2-x::before { content: "\f20b"; } -.bi-calendar2::before { content: "\f20c"; } -.bi-calendar3-event-fill::before { content: "\f20d"; } -.bi-calendar3-event::before { content: "\f20e"; } -.bi-calendar3-fill::before { content: "\f20f"; } -.bi-calendar3-range-fill::before { content: "\f210"; } -.bi-calendar3-range::before { content: "\f211"; } -.bi-calendar3-week-fill::before { content: "\f212"; } -.bi-calendar3-week::before { content: "\f213"; } -.bi-calendar3::before { content: "\f214"; } -.bi-calendar4-event::before { content: "\f215"; } -.bi-calendar4-range::before { content: "\f216"; } -.bi-calendar4-week::before { content: "\f217"; } -.bi-calendar4::before { content: "\f218"; } -.bi-camera-fill::before { content: "\f219"; } -.bi-camera-reels-fill::before { content: "\f21a"; } -.bi-camera-reels::before { content: "\f21b"; } -.bi-camera-video-fill::before { content: "\f21c"; } -.bi-camera-video-off-fill::before { content: "\f21d"; } -.bi-camera-video-off::before { content: "\f21e"; } -.bi-camera-video::before { content: "\f21f"; } -.bi-camera::before { content: "\f220"; } -.bi-camera2::before { content: "\f221"; } -.bi-capslock-fill::before { content: "\f222"; } -.bi-capslock::before { content: "\f223"; } -.bi-card-checklist::before { content: "\f224"; } -.bi-card-heading::before { content: "\f225"; } -.bi-card-image::before { content: "\f226"; } -.bi-card-list::before { content: "\f227"; } -.bi-card-text::before { content: "\f228"; } -.bi-caret-down-fill::before { content: "\f229"; } -.bi-caret-down-square-fill::before { content: "\f22a"; } -.bi-caret-down-square::before { content: "\f22b"; } -.bi-caret-down::before { content: "\f22c"; } -.bi-caret-left-fill::before { content: "\f22d"; } -.bi-caret-left-square-fill::before { content: "\f22e"; } -.bi-caret-left-square::before { content: "\f22f"; } -.bi-caret-left::before { content: "\f230"; } -.bi-caret-right-fill::before { content: "\f231"; } -.bi-caret-right-square-fill::before { content: "\f232"; } -.bi-caret-right-square::before { content: "\f233"; } -.bi-caret-right::before { content: "\f234"; } -.bi-caret-up-fill::before { content: "\f235"; } -.bi-caret-up-square-fill::before { content: "\f236"; } -.bi-caret-up-square::before { content: "\f237"; } -.bi-caret-up::before { content: "\f238"; } -.bi-cart-check-fill::before { content: "\f239"; } -.bi-cart-check::before { content: "\f23a"; } -.bi-cart-dash-fill::before { content: "\f23b"; } -.bi-cart-dash::before { content: "\f23c"; } -.bi-cart-fill::before { content: "\f23d"; } -.bi-cart-plus-fill::before { content: "\f23e"; } -.bi-cart-plus::before { content: "\f23f"; } -.bi-cart-x-fill::before { content: "\f240"; } -.bi-cart-x::before { content: "\f241"; } -.bi-cart::before { content: "\f242"; } -.bi-cart2::before { content: "\f243"; } -.bi-cart3::before { content: "\f244"; } -.bi-cart4::before { content: "\f245"; } -.bi-cash-stack::before { content: "\f246"; } -.bi-cash::before { content: "\f247"; } -.bi-cast::before { content: "\f248"; } -.bi-chat-dots-fill::before { content: "\f249"; } -.bi-chat-dots::before { content: "\f24a"; } -.bi-chat-fill::before { content: "\f24b"; } -.bi-chat-left-dots-fill::before { content: "\f24c"; } -.bi-chat-left-dots::before { content: "\f24d"; } -.bi-chat-left-fill::before { content: "\f24e"; } -.bi-chat-left-quote-fill::before { content: "\f24f"; } -.bi-chat-left-quote::before { content: "\f250"; } -.bi-chat-left-text-fill::before { content: "\f251"; } -.bi-chat-left-text::before { content: "\f252"; } -.bi-chat-left::before { content: "\f253"; } -.bi-chat-quote-fill::before { content: "\f254"; } -.bi-chat-quote::before { content: "\f255"; } -.bi-chat-right-dots-fill::before { content: "\f256"; } -.bi-chat-right-dots::before { content: "\f257"; } -.bi-chat-right-fill::before { content: "\f258"; } -.bi-chat-right-quote-fill::before { content: "\f259"; } -.bi-chat-right-quote::before { content: "\f25a"; } -.bi-chat-right-text-fill::before { content: "\f25b"; } -.bi-chat-right-text::before { content: "\f25c"; } -.bi-chat-right::before { content: "\f25d"; } -.bi-chat-square-dots-fill::before { content: "\f25e"; } -.bi-chat-square-dots::before { content: "\f25f"; } -.bi-chat-square-fill::before { content: "\f260"; } -.bi-chat-square-quote-fill::before { content: "\f261"; } -.bi-chat-square-quote::before { content: "\f262"; } -.bi-chat-square-text-fill::before { content: "\f263"; } -.bi-chat-square-text::before { content: "\f264"; } -.bi-chat-square::before { content: "\f265"; } -.bi-chat-text-fill::before { content: "\f266"; } -.bi-chat-text::before { content: "\f267"; } -.bi-chat::before { content: "\f268"; } -.bi-check-all::before { content: "\f269"; } -.bi-check-circle-fill::before { content: "\f26a"; } -.bi-check-circle::before { content: "\f26b"; } -.bi-check-square-fill::before { content: "\f26c"; } -.bi-check-square::before { content: "\f26d"; } -.bi-check::before { content: "\f26e"; } -.bi-check2-all::before { content: "\f26f"; } -.bi-check2-circle::before { content: "\f270"; } -.bi-check2-square::before { content: "\f271"; } -.bi-check2::before { content: "\f272"; } -.bi-chevron-bar-contract::before { content: "\f273"; } -.bi-chevron-bar-down::before { content: "\f274"; } -.bi-chevron-bar-expand::before { content: "\f275"; } -.bi-chevron-bar-left::before { content: "\f276"; } -.bi-chevron-bar-right::before { content: "\f277"; } -.bi-chevron-bar-up::before { content: "\f278"; } -.bi-chevron-compact-down::before { content: "\f279"; } -.bi-chevron-compact-left::before { content: "\f27a"; } -.bi-chevron-compact-right::before { content: "\f27b"; } -.bi-chevron-compact-up::before { content: "\f27c"; } -.bi-chevron-contract::before { content: "\f27d"; } -.bi-chevron-double-down::before { content: "\f27e"; } -.bi-chevron-double-left::before { content: "\f27f"; } -.bi-chevron-double-right::before { content: "\f280"; } -.bi-chevron-double-up::before { content: "\f281"; } -.bi-chevron-down::before { content: "\f282"; } -.bi-chevron-expand::before { content: "\f283"; } -.bi-chevron-left::before { content: "\f284"; } -.bi-chevron-right::before { content: "\f285"; } -.bi-chevron-up::before { content: "\f286"; } -.bi-circle-fill::before { content: "\f287"; } -.bi-circle-half::before { content: "\f288"; } -.bi-circle-square::before { content: "\f289"; } -.bi-circle::before { content: "\f28a"; } -.bi-clipboard-check::before { content: "\f28b"; } -.bi-clipboard-data::before { content: "\f28c"; } -.bi-clipboard-minus::before { content: "\f28d"; } -.bi-clipboard-plus::before { content: "\f28e"; } -.bi-clipboard-x::before { content: "\f28f"; } -.bi-clipboard::before { content: "\f290"; } -.bi-clock-fill::before { content: "\f291"; } -.bi-clock-history::before { content: "\f292"; } -.bi-clock::before { content: "\f293"; } -.bi-cloud-arrow-down-fill::before { content: "\f294"; } -.bi-cloud-arrow-down::before { content: "\f295"; } -.bi-cloud-arrow-up-fill::before { content: "\f296"; } -.bi-cloud-arrow-up::before { content: "\f297"; } -.bi-cloud-check-fill::before { content: "\f298"; } -.bi-cloud-check::before { content: "\f299"; } -.bi-cloud-download-fill::before { content: "\f29a"; } -.bi-cloud-download::before { content: "\f29b"; } -.bi-cloud-drizzle-fill::before { content: "\f29c"; } -.bi-cloud-drizzle::before { content: "\f29d"; } -.bi-cloud-fill::before { content: "\f29e"; } -.bi-cloud-fog-fill::before { content: "\f29f"; } -.bi-cloud-fog::before { content: "\f2a0"; } -.bi-cloud-fog2-fill::before { content: "\f2a1"; } -.bi-cloud-fog2::before { content: "\f2a2"; } -.bi-cloud-hail-fill::before { content: "\f2a3"; } -.bi-cloud-hail::before { content: "\f2a4"; } -.bi-cloud-haze-fill::before { content: "\f2a6"; } -.bi-cloud-haze::before { content: "\f2a7"; } -.bi-cloud-haze2-fill::before { content: "\f2a8"; } -.bi-cloud-lightning-fill::before { content: "\f2a9"; } -.bi-cloud-lightning-rain-fill::before { content: "\f2aa"; } -.bi-cloud-lightning-rain::before { content: "\f2ab"; } -.bi-cloud-lightning::before { content: "\f2ac"; } -.bi-cloud-minus-fill::before { content: "\f2ad"; } -.bi-cloud-minus::before { content: "\f2ae"; } -.bi-cloud-moon-fill::before { content: "\f2af"; } -.bi-cloud-moon::before { content: "\f2b0"; } -.bi-cloud-plus-fill::before { content: "\f2b1"; } -.bi-cloud-plus::before { content: "\f2b2"; } -.bi-cloud-rain-fill::before { content: "\f2b3"; } -.bi-cloud-rain-heavy-fill::before { content: "\f2b4"; } -.bi-cloud-rain-heavy::before { content: "\f2b5"; } -.bi-cloud-rain::before { content: "\f2b6"; } -.bi-cloud-slash-fill::before { content: "\f2b7"; } -.bi-cloud-slash::before { content: "\f2b8"; } -.bi-cloud-sleet-fill::before { content: "\f2b9"; } -.bi-cloud-sleet::before { content: "\f2ba"; } -.bi-cloud-snow-fill::before { content: "\f2bb"; } -.bi-cloud-snow::before { content: "\f2bc"; } -.bi-cloud-sun-fill::before { content: "\f2bd"; } -.bi-cloud-sun::before { content: "\f2be"; } -.bi-cloud-upload-fill::before { content: "\f2bf"; } -.bi-cloud-upload::before { content: "\f2c0"; } -.bi-cloud::before { content: "\f2c1"; } -.bi-clouds-fill::before { content: "\f2c2"; } -.bi-clouds::before { content: "\f2c3"; } -.bi-cloudy-fill::before { content: "\f2c4"; } -.bi-cloudy::before { content: "\f2c5"; } -.bi-code-slash::before { content: "\f2c6"; } -.bi-code-square::before { content: "\f2c7"; } -.bi-code::before { content: "\f2c8"; } -.bi-collection-fill::before { content: "\f2c9"; } -.bi-collection-play-fill::before { content: "\f2ca"; } -.bi-collection-play::before { content: "\f2cb"; } -.bi-collection::before { content: "\f2cc"; } -.bi-columns-gap::before { content: "\f2cd"; } -.bi-columns::before { content: "\f2ce"; } -.bi-command::before { content: "\f2cf"; } -.bi-compass-fill::before { content: "\f2d0"; } -.bi-compass::before { content: "\f2d1"; } -.bi-cone-striped::before { content: "\f2d2"; } -.bi-cone::before { content: "\f2d3"; } -.bi-controller::before { content: "\f2d4"; } -.bi-cpu-fill::before { content: "\f2d5"; } -.bi-cpu::before { content: "\f2d6"; } -.bi-credit-card-2-back-fill::before { content: "\f2d7"; } -.bi-credit-card-2-back::before { content: "\f2d8"; } -.bi-credit-card-2-front-fill::before { content: "\f2d9"; } -.bi-credit-card-2-front::before { content: "\f2da"; } -.bi-credit-card-fill::before { content: "\f2db"; } -.bi-credit-card::before { content: "\f2dc"; } -.bi-crop::before { content: "\f2dd"; } -.bi-cup-fill::before { content: "\f2de"; } -.bi-cup-straw::before { content: "\f2df"; } -.bi-cup::before { content: "\f2e0"; } -.bi-cursor-fill::before { content: "\f2e1"; } -.bi-cursor-text::before { content: "\f2e2"; } -.bi-cursor::before { content: "\f2e3"; } -.bi-dash-circle-dotted::before { content: "\f2e4"; } -.bi-dash-circle-fill::before { content: "\f2e5"; } -.bi-dash-circle::before { content: "\f2e6"; } -.bi-dash-square-dotted::before { content: "\f2e7"; } -.bi-dash-square-fill::before { content: "\f2e8"; } -.bi-dash-square::before { content: "\f2e9"; } -.bi-dash::before { content: "\f2ea"; } -.bi-diagram-2-fill::before { content: "\f2eb"; } -.bi-diagram-2::before { content: "\f2ec"; } -.bi-diagram-3-fill::before { content: "\f2ed"; } -.bi-diagram-3::before { content: "\f2ee"; } -.bi-diamond-fill::before { content: "\f2ef"; } -.bi-diamond-half::before { content: "\f2f0"; } -.bi-diamond::before { content: "\f2f1"; } -.bi-dice-1-fill::before { content: "\f2f2"; } -.bi-dice-1::before { content: "\f2f3"; } -.bi-dice-2-fill::before { content: "\f2f4"; } -.bi-dice-2::before { content: "\f2f5"; } -.bi-dice-3-fill::before { content: "\f2f6"; } -.bi-dice-3::before { content: "\f2f7"; } 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} -.bi-pentagon-fill::before { content: "\f4cc"; } -.bi-pentagon-half::before { content: "\f4cd"; } -.bi-pentagon::before { content: "\f4ce"; } -.bi-people-fill::before { content: "\f4cf"; } -.bi-people::before { content: "\f4d0"; } -.bi-percent::before { content: "\f4d1"; } -.bi-person-badge-fill::before { content: "\f4d2"; } -.bi-person-badge::before { content: "\f4d3"; } -.bi-person-bounding-box::before { content: "\f4d4"; } -.bi-person-check-fill::before { content: "\f4d5"; } -.bi-person-check::before { content: "\f4d6"; } -.bi-person-circle::before { content: "\f4d7"; } -.bi-person-dash-fill::before { content: "\f4d8"; } -.bi-person-dash::before { content: "\f4d9"; } -.bi-person-fill::before { content: "\f4da"; } -.bi-person-lines-fill::before { content: "\f4db"; } -.bi-person-plus-fill::before { content: "\f4dc"; } -.bi-person-plus::before { content: "\f4dd"; } -.bi-person-square::before { content: "\f4de"; } -.bi-person-x-fill::before { content: "\f4df"; } -.bi-person-x::before { content: "\f4e0"; } -.bi-person::before { content: "\f4e1"; } -.bi-phone-fill::before { content: "\f4e2"; } -.bi-phone-landscape-fill::before { content: "\f4e3"; } -.bi-phone-landscape::before { content: "\f4e4"; } -.bi-phone-vibrate-fill::before { content: "\f4e5"; } -.bi-phone-vibrate::before { content: "\f4e6"; } -.bi-phone::before { content: "\f4e7"; } -.bi-pie-chart-fill::before { content: "\f4e8"; } -.bi-pie-chart::before { content: "\f4e9"; } -.bi-pin-angle-fill::before { content: "\f4ea"; } -.bi-pin-angle::before { content: "\f4eb"; } -.bi-pin-fill::before { content: "\f4ec"; } -.bi-pin::before { content: "\f4ed"; } -.bi-pip-fill::before { content: "\f4ee"; } -.bi-pip::before { content: "\f4ef"; } -.bi-play-btn-fill::before { content: "\f4f0"; } -.bi-play-btn::before { content: "\f4f1"; } -.bi-play-circle-fill::before { content: "\f4f2"; } -.bi-play-circle::before { content: "\f4f3"; } -.bi-play-fill::before { content: "\f4f4"; } -.bi-play::before { content: "\f4f5"; } 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-.bi-question-square-fill::before { content: "\f50a"; } -.bi-question-square::before { content: "\f50b"; } -.bi-question::before { content: "\f50c"; } -.bi-rainbow::before { content: "\f50d"; } -.bi-receipt-cutoff::before { content: "\f50e"; } -.bi-receipt::before { content: "\f50f"; } -.bi-reception-0::before { content: "\f510"; } -.bi-reception-1::before { content: "\f511"; } -.bi-reception-2::before { content: "\f512"; } -.bi-reception-3::before { content: "\f513"; } -.bi-reception-4::before { content: "\f514"; } -.bi-record-btn-fill::before { content: "\f515"; } -.bi-record-btn::before { content: "\f516"; } -.bi-record-circle-fill::before { content: "\f517"; } -.bi-record-circle::before { content: "\f518"; } -.bi-record-fill::before { content: "\f519"; } -.bi-record::before { content: "\f51a"; } -.bi-record2-fill::before { content: "\f51b"; } -.bi-record2::before { content: "\f51c"; } -.bi-reply-all-fill::before { content: "\f51d"; } -.bi-reply-all::before { content: "\f51e"; } -.bi-reply-fill::before { content: "\f51f"; } -.bi-reply::before { content: "\f520"; } -.bi-rss-fill::before { content: "\f521"; } -.bi-rss::before { content: "\f522"; } -.bi-rulers::before { content: "\f523"; } -.bi-save-fill::before { content: "\f524"; } -.bi-save::before { content: "\f525"; } -.bi-save2-fill::before { content: "\f526"; } -.bi-save2::before { content: "\f527"; } -.bi-scissors::before { content: "\f528"; } -.bi-screwdriver::before { content: "\f529"; } -.bi-search::before { content: "\f52a"; } -.bi-segmented-nav::before { content: "\f52b"; } -.bi-server::before { content: "\f52c"; } -.bi-share-fill::before { content: "\f52d"; } -.bi-share::before { content: "\f52e"; } -.bi-shield-check::before { content: "\f52f"; } -.bi-shield-exclamation::before { content: "\f530"; } -.bi-shield-fill-check::before { content: "\f531"; } -.bi-shield-fill-exclamation::before { content: "\f532"; } -.bi-shield-fill-minus::before { content: "\f533"; } -.bi-shield-fill-plus::before { content: "\f534"; } -.bi-shield-fill-x::before { content: "\f535"; } -.bi-shield-fill::before { content: "\f536"; } -.bi-shield-lock-fill::before { content: "\f537"; } -.bi-shield-lock::before { content: "\f538"; } -.bi-shield-minus::before { content: "\f539"; } -.bi-shield-plus::before { content: "\f53a"; } -.bi-shield-shaded::before { content: "\f53b"; } -.bi-shield-slash-fill::before { content: "\f53c"; } -.bi-shield-slash::before { content: "\f53d"; } -.bi-shield-x::before { content: "\f53e"; } -.bi-shield::before { content: "\f53f"; } -.bi-shift-fill::before { content: "\f540"; } -.bi-shift::before { content: "\f541"; } -.bi-shop-window::before { content: "\f542"; } -.bi-shop::before { content: "\f543"; } -.bi-shuffle::before { content: "\f544"; } -.bi-signpost-2-fill::before { content: "\f545"; } -.bi-signpost-2::before { content: "\f546"; } -.bi-signpost-fill::before { content: "\f547"; } -.bi-signpost-split-fill::before { content: "\f548"; } -.bi-signpost-split::before { content: "\f549"; } -.bi-signpost::before { content: "\f54a"; } -.bi-sim-fill::before { content: "\f54b"; } -.bi-sim::before { content: "\f54c"; } -.bi-skip-backward-btn-fill::before { content: "\f54d"; } -.bi-skip-backward-btn::before { content: "\f54e"; } -.bi-skip-backward-circle-fill::before { content: "\f54f"; } -.bi-skip-backward-circle::before { content: "\f550"; } -.bi-skip-backward-fill::before { content: "\f551"; } -.bi-skip-backward::before { content: "\f552"; } -.bi-skip-end-btn-fill::before { content: "\f553"; } -.bi-skip-end-btn::before { content: "\f554"; } -.bi-skip-end-circle-fill::before { content: "\f555"; } -.bi-skip-end-circle::before { content: "\f556"; } -.bi-skip-end-fill::before { content: "\f557"; } -.bi-skip-end::before { content: "\f558"; } -.bi-skip-forward-btn-fill::before { content: "\f559"; } -.bi-skip-forward-btn::before { content: "\f55a"; } -.bi-skip-forward-circle-fill::before { content: "\f55b"; } -.bi-skip-forward-circle::before { content: "\f55c"; } -.bi-skip-forward-fill::before { content: "\f55d"; } -.bi-skip-forward::before { content: "\f55e"; } -.bi-skip-start-btn-fill::before { content: "\f55f"; } -.bi-skip-start-btn::before { content: "\f560"; } -.bi-skip-start-circle-fill::before { content: "\f561"; } -.bi-skip-start-circle::before { content: "\f562"; } -.bi-skip-start-fill::before { content: "\f563"; } -.bi-skip-start::before { content: "\f564"; } -.bi-slack::before { content: "\f565"; } -.bi-slash-circle-fill::before { content: "\f566"; } -.bi-slash-circle::before { content: "\f567"; } -.bi-slash-square-fill::before { content: "\f568"; } -.bi-slash-square::before { content: "\f569"; } -.bi-slash::before { content: "\f56a"; } -.bi-sliders::before { content: "\f56b"; } -.bi-smartwatch::before { content: "\f56c"; } -.bi-snow::before { content: "\f56d"; } -.bi-snow2::before { content: "\f56e"; } -.bi-snow3::before { content: "\f56f"; } -.bi-sort-alpha-down-alt::before { content: "\f570"; } -.bi-sort-alpha-down::before { content: "\f571"; } -.bi-sort-alpha-up-alt::before { content: "\f572"; } -.bi-sort-alpha-up::before { content: "\f573"; } -.bi-sort-down-alt::before { content: "\f574"; } -.bi-sort-down::before { content: "\f575"; } -.bi-sort-numeric-down-alt::before { content: "\f576"; } -.bi-sort-numeric-down::before { content: "\f577"; } -.bi-sort-numeric-up-alt::before { content: "\f578"; } -.bi-sort-numeric-up::before { content: "\f579"; } -.bi-sort-up-alt::before { content: "\f57a"; } -.bi-sort-up::before { content: "\f57b"; } -.bi-soundwave::before { content: "\f57c"; } -.bi-speaker-fill::before { content: "\f57d"; } -.bi-speaker::before { content: "\f57e"; } -.bi-speedometer::before { content: "\f57f"; } -.bi-speedometer2::before { content: "\f580"; } -.bi-spellcheck::before { content: "\f581"; } -.bi-square-fill::before { content: "\f582"; } -.bi-square-half::before { content: "\f583"; } -.bi-square::before { content: "\f584"; } -.bi-stack::before { content: "\f585"; } -.bi-star-fill::before { content: "\f586"; } -.bi-star-half::before { content: "\f587"; } -.bi-star::before { content: "\f588"; } -.bi-stars::before { content: "\f589"; } -.bi-stickies-fill::before { content: "\f58a"; } -.bi-stickies::before { content: "\f58b"; } -.bi-sticky-fill::before { content: "\f58c"; } -.bi-sticky::before { content: "\f58d"; } -.bi-stop-btn-fill::before { content: "\f58e"; } -.bi-stop-btn::before { content: "\f58f"; } -.bi-stop-circle-fill::before { content: "\f590"; } -.bi-stop-circle::before { content: "\f591"; } -.bi-stop-fill::before { content: "\f592"; } -.bi-stop::before { content: "\f593"; } -.bi-stoplights-fill::before { content: "\f594"; } -.bi-stoplights::before { content: "\f595"; } -.bi-stopwatch-fill::before { content: "\f596"; } -.bi-stopwatch::before { content: "\f597"; } -.bi-subtract::before { content: "\f598"; } -.bi-suit-club-fill::before { content: "\f599"; } -.bi-suit-club::before { content: "\f59a"; } -.bi-suit-diamond-fill::before { content: "\f59b"; } -.bi-suit-diamond::before { content: "\f59c"; } -.bi-suit-heart-fill::before { content: "\f59d"; } -.bi-suit-heart::before { content: "\f59e"; } -.bi-suit-spade-fill::before { content: "\f59f"; } -.bi-suit-spade::before { content: "\f5a0"; } -.bi-sun-fill::before { content: "\f5a1"; } -.bi-sun::before { content: "\f5a2"; } -.bi-sunglasses::before { content: "\f5a3"; } -.bi-sunrise-fill::before { content: "\f5a4"; } -.bi-sunrise::before { content: "\f5a5"; } -.bi-sunset-fill::before { content: "\f5a6"; } -.bi-sunset::before { content: "\f5a7"; } -.bi-symmetry-horizontal::before { content: "\f5a8"; } -.bi-symmetry-vertical::before { content: "\f5a9"; } -.bi-table::before { content: "\f5aa"; } -.bi-tablet-fill::before { content: "\f5ab"; } -.bi-tablet-landscape-fill::before { content: "\f5ac"; } -.bi-tablet-landscape::before { content: "\f5ad"; } -.bi-tablet::before { content: "\f5ae"; } -.bi-tag-fill::before { content: "\f5af"; } -.bi-tag::before { content: "\f5b0"; } -.bi-tags-fill::before { content: "\f5b1"; } -.bi-tags::before { content: "\f5b2"; } -.bi-telegram::before { content: "\f5b3"; } -.bi-telephone-fill::before { content: "\f5b4"; } -.bi-telephone-forward-fill::before { content: "\f5b5"; } -.bi-telephone-forward::before { content: "\f5b6"; } -.bi-telephone-inbound-fill::before { content: "\f5b7"; } -.bi-telephone-inbound::before { content: "\f5b8"; } -.bi-telephone-minus-fill::before { content: "\f5b9"; } -.bi-telephone-minus::before { content: "\f5ba"; } -.bi-telephone-outbound-fill::before { content: "\f5bb"; } -.bi-telephone-outbound::before { content: "\f5bc"; } -.bi-telephone-plus-fill::before { content: "\f5bd"; } -.bi-telephone-plus::before { content: "\f5be"; } -.bi-telephone-x-fill::before { content: "\f5bf"; } -.bi-telephone-x::before { content: "\f5c0"; } -.bi-telephone::before { content: "\f5c1"; } -.bi-terminal-fill::before { content: "\f5c2"; } -.bi-terminal::before { content: "\f5c3"; } -.bi-text-center::before { content: 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"\f605"; } -.bi-view-stacked::before { content: "\f606"; } -.bi-vinyl-fill::before { content: "\f607"; } -.bi-vinyl::before { content: "\f608"; } -.bi-voicemail::before { content: "\f609"; } -.bi-volume-down-fill::before { content: "\f60a"; } -.bi-volume-down::before { content: "\f60b"; } -.bi-volume-mute-fill::before { content: "\f60c"; } -.bi-volume-mute::before { content: "\f60d"; } -.bi-volume-off-fill::before { content: "\f60e"; } -.bi-volume-off::before { content: "\f60f"; } -.bi-volume-up-fill::before { content: "\f610"; } -.bi-volume-up::before { content: "\f611"; } -.bi-vr::before { content: "\f612"; } -.bi-wallet-fill::before { content: "\f613"; } -.bi-wallet::before { content: "\f614"; } -.bi-wallet2::before { content: "\f615"; } -.bi-watch::before { content: "\f616"; } -.bi-water::before { content: "\f617"; } -.bi-whatsapp::before { content: "\f618"; } -.bi-wifi-1::before { content: "\f619"; } -.bi-wifi-2::before { content: "\f61a"; } -.bi-wifi-off::before { content: 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H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const 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hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return 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sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const 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W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"

"},Un={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Gn={entry:"(string|element|function|null)",selector:"(string|element)"};class Jn extends H{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Yn}static get DefaultType(){return Un}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get 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i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t 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b/vignettes/cocoon_files/libs/quarto-html/quarto-syntax-highlighting-29e2c20b02301cfff04dc8050bf30c7e.css deleted file mode 100644 index 49514bd..0000000 --- a/vignettes/cocoon_files/libs/quarto-html/quarto-syntax-highlighting-29e2c20b02301cfff04dc8050bf30c7e.css +++ /dev/null @@ -1,205 +0,0 @@ -/* quarto syntax highlight colors */ -:root { - --quarto-hl-ot-color: #003B4F; - --quarto-hl-at-color: #657422; - --quarto-hl-ss-color: #20794D; - --quarto-hl-an-color: #5E5E5E; - --quarto-hl-fu-color: #4758AB; - --quarto-hl-st-color: #20794D; - --quarto-hl-cf-color: #003B4F; - --quarto-hl-op-color: #5E5E5E; - --quarto-hl-er-color: #AD0000; - --quarto-hl-bn-color: #AD0000; - --quarto-hl-al-color: #AD0000; - --quarto-hl-va-color: #111111; - --quarto-hl-bu-color: inherit; - --quarto-hl-ex-color: inherit; - --quarto-hl-pp-color: #AD0000; - --quarto-hl-in-color: #5E5E5E; - --quarto-hl-vs-color: #20794D; - --quarto-hl-wa-color: #5E5E5E; - --quarto-hl-do-color: #5E5E5E; - --quarto-hl-im-color: #00769E; - --quarto-hl-ch-color: #20794D; - --quarto-hl-dt-color: #AD0000; - --quarto-hl-fl-color: #AD0000; - --quarto-hl-co-color: #5E5E5E; - --quarto-hl-cv-color: #5E5E5E; - --quarto-hl-cn-color: #8f5902; - --quarto-hl-sc-color: #5E5E5E; - --quarto-hl-dv-color: #AD0000; - --quarto-hl-kw-color: #003B4F; -} - -/* other quarto variables */ -:root { - --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; -} - -pre > code.sourceCode > span { - color: #003B4F; -} - -code span { - color: #003B4F; -} - -code.sourceCode > span { - color: #003B4F; -} - -div.sourceCode, -div.sourceCode pre.sourceCode { - color: #003B4F; -} - -code span.ot { - color: #003B4F; - font-style: inherit; -} - -code span.at { - color: #657422; - font-style: inherit; -} - -code span.ss { - color: #20794D; - font-style: inherit; -} - -code span.an { - color: #5E5E5E; - font-style: inherit; -} - -code span.fu { - color: #4758AB; - font-style: inherit; -} - -code span.st { - color: #20794D; - font-style: inherit; -} - -code span.cf { - color: #003B4F; - font-weight: bold; - font-style: inherit; -} - -code span.op { - color: #5E5E5E; - font-style: inherit; -} - -code span.er { - color: #AD0000; - font-style: inherit; -} - -code span.bn { - color: #AD0000; - font-style: inherit; -} - -code span.al { - color: #AD0000; - font-style: inherit; -} - -code span.va { - color: #111111; - font-style: inherit; -} - -code span.bu { - font-style: inherit; -} - -code span.ex { - font-style: inherit; -} - -code span.pp { - color: #AD0000; - font-style: inherit; -} - -code span.in { - color: #5E5E5E; - font-style: inherit; -} - -code span.vs { - color: #20794D; - font-style: inherit; -} - -code span.wa { - color: #5E5E5E; - font-style: italic; -} - -code span.do { - color: #5E5E5E; - font-style: italic; -} - -code span.im { - color: #00769E; - font-style: inherit; -} - -code span.ch { - color: #20794D; - font-style: inherit; -} - -code span.dt { - color: #AD0000; - font-style: inherit; -} - -code span.fl { - color: #AD0000; - font-style: inherit; -} - -code span.co { - color: #5E5E5E; - font-style: inherit; -} - -code span.cv { - color: #5E5E5E; - font-style: italic; -} - -code span.cn { - color: #8f5902; - font-style: inherit; -} - -code span.sc { - color: #5E5E5E; - font-style: inherit; -} - -code span.dv { - color: #AD0000; - font-style: inherit; -} - -code span.kw { - color: #003B4F; - font-weight: bold; - font-style: inherit; -} - -.prevent-inlining { - content: " { - // Find any conflicting margin elements and add margins to the - // top to prevent overlap - const marginChildren = window.document.querySelectorAll( - ".column-margin.column-container > *, .margin-caption, .aside" - ); - - let lastBottom = 0; - for (const marginChild of marginChildren) { - if (marginChild.offsetParent !== null) { - // clear the top margin so we recompute it - marginChild.style.marginTop = null; - const top = marginChild.getBoundingClientRect().top + window.scrollY; - if (top < lastBottom) { - const marginChildStyle = window.getComputedStyle(marginChild); - const marginBottom = parseFloat(marginChildStyle["marginBottom"]); - const margin = lastBottom - top + marginBottom; - marginChild.style.marginTop = `${margin}px`; - } - const styles = window.getComputedStyle(marginChild); - const marginTop = parseFloat(styles["marginTop"]); - lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; - } - } -}; - -window.document.addEventListener("DOMContentLoaded", function (_event) { - // Recompute the position of margin elements anytime the body size changes - if (window.ResizeObserver) { - const resizeObserver = new window.ResizeObserver( - throttle(() => { - layoutMarginEls(); - if ( - window.document.body.getBoundingClientRect().width < 990 && - isReaderMode() - ) { - quartoToggleReader(); - } - }, 50) - ); - resizeObserver.observe(window.document.body); - } - - const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]'); - const sidebarEl = window.document.getElementById("quarto-sidebar"); - const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left"); - const marginSidebarEl = window.document.getElementById( - "quarto-margin-sidebar" - ); - // function to determine whether the element has a previous sibling that is active - const prevSiblingIsActiveLink = (el) => { - const sibling = el.previousElementSibling; - if (sibling && sibling.tagName === "A") { - return sibling.classList.contains("active"); - } else { - return false; - } - }; - - // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior) - function fireSlideEnter(e) { - const event = window.document.createEvent("Event"); - event.initEvent("slideenter", true, true); - window.document.dispatchEvent(event); - } - const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); - tabs.forEach((tab) => { - tab.addEventListener("shown.bs.tab", fireSlideEnter); - }); - - // fire slideEnter for tabby tab activations (for htmlwidget resize behavior) - document.addEventListener("tabby", fireSlideEnter, false); - - // Track scrolling and mark TOC links as active - // get table of contents and sidebar (bail if we don't have at least one) - const tocLinks = tocEl - ? [...tocEl.querySelectorAll("a[data-scroll-target]")] - : []; - const makeActive = (link) => tocLinks[link].classList.add("active"); - const removeActive = (link) => tocLinks[link].classList.remove("active"); - const removeAllActive = () => - [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); - - // activate the anchor for a section associated with this TOC entry - tocLinks.forEach((link) => { - link.addEventListener("click", () => { - if (link.href.indexOf("#") !== -1) { - const anchor = link.href.split("#")[1]; - const heading = window.document.querySelector( - `[data-anchor-id="${anchor}"]` - ); - if (heading) { - // Add the class - heading.classList.add("reveal-anchorjs-link"); - - // function to show the anchor - const handleMouseout = () => { - heading.classList.remove("reveal-anchorjs-link"); - heading.removeEventListener("mouseout", handleMouseout); - }; - - // add a function to clear the anchor when the user mouses out of it - heading.addEventListener("mouseout", handleMouseout); - } - } - }); - }); - - const sections = tocLinks.map((link) => { - const target = link.getAttribute("data-scroll-target"); - if (target.startsWith("#")) { - return window.document.getElementById(decodeURI(`${target.slice(1)}`)); - } else { - return window.document.querySelector(decodeURI(`${target}`)); - } - }); - - const sectionMargin = 200; - let currentActive = 0; - // track whether we've initialized state the first time - let init = false; - - const updateActiveLink = () => { - // The index from bottom to top (e.g. reversed list) - let sectionIndex = -1; - if ( - window.innerHeight + window.pageYOffset >= - window.document.body.offsetHeight - ) { - // This is the no-scroll case where last section should be the active one - sectionIndex = 0; - } else { - // This finds the last section visible on screen that should be made active - sectionIndex = [...sections].reverse().findIndex((section) => { - if (section) { - return window.pageYOffset >= section.offsetTop - sectionMargin; - } else { - return false; - } - }); - } - if (sectionIndex > -1) { - const current = sections.length - sectionIndex - 1; - if (current !== currentActive) { - removeAllActive(); - currentActive = current; - makeActive(current); - if (init) { - window.dispatchEvent(sectionChanged); - } - init = true; - } - } - }; - - const inHiddenRegion = (top, bottom, hiddenRegions) => { - for (const region of hiddenRegions) { - if (top <= region.bottom && bottom >= region.top) { - return true; - } - } - return false; - }; - - const categorySelector = "header.quarto-title-block .quarto-category"; - const activateCategories = (href) => { - // Find any categories - // Surround them with a link pointing back to: - // #category=Authoring - try { - const categoryEls = window.document.querySelectorAll(categorySelector); - for (const categoryEl of categoryEls) { - const categoryText = categoryEl.textContent; - if (categoryText) { - const link = `${href}#category=${encodeURIComponent(categoryText)}`; - const linkEl = window.document.createElement("a"); - linkEl.setAttribute("href", link); - for (const child of categoryEl.childNodes) { - linkEl.append(child); - } - categoryEl.appendChild(linkEl); - } - } - } catch { - // Ignore errors - } - }; - function hasTitleCategories() { - return window.document.querySelector(categorySelector) !== null; - } - - function offsetRelativeUrl(url) { - const offset = getMeta("quarto:offset"); - return offset ? offset + url : url; - } - - function offsetAbsoluteUrl(url) { - const offset = getMeta("quarto:offset"); - const baseUrl = new URL(offset, window.location); - - const projRelativeUrl = url.replace(baseUrl, ""); - if (projRelativeUrl.startsWith("/")) { - return projRelativeUrl; - } else { - return "/" + projRelativeUrl; - } - } - - // read a meta tag value - function getMeta(metaName) { - const metas = window.document.getElementsByTagName("meta"); - for (let i = 0; i < metas.length; i++) { - if (metas[i].getAttribute("name") === metaName) { - return metas[i].getAttribute("content"); - } - } - return ""; - } - - async function findAndActivateCategories() { - // Categories search with listing only use path without query - const currentPagePath = offsetAbsoluteUrl( - window.location.origin + window.location.pathname - ); - const response = await fetch(offsetRelativeUrl("listings.json")); - if (response.status == 200) { - return response.json().then(function (listingPaths) { - const listingHrefs = []; - for (const listingPath of listingPaths) { - const pathWithoutLeadingSlash = listingPath.listing.substring(1); - for (const item of listingPath.items) { - if ( - item === currentPagePath || - item === currentPagePath + "index.html" - ) { - // Resolve this path against the offset to be sure - // we already are using the correct path to the listing - // (this adjusts the listing urls to be rooted against - // whatever root the page is actually running against) - const relative = offsetRelativeUrl(pathWithoutLeadingSlash); - const baseUrl = window.location; - const resolvedPath = new URL(relative, baseUrl); - listingHrefs.push(resolvedPath.pathname); - break; - } - } - } - - // Look up the tree for a nearby linting and use that if we find one - const nearestListing = findNearestParentListing( - offsetAbsoluteUrl(window.location.pathname), - listingHrefs - ); - if (nearestListing) { - activateCategories(nearestListing); - } else { - // See if the referrer is a listing page for this item - const referredRelativePath = offsetAbsoluteUrl(document.referrer); - const referrerListing = listingHrefs.find((listingHref) => { - const isListingReferrer = - listingHref === referredRelativePath || - listingHref === referredRelativePath + "index.html"; - return isListingReferrer; - }); - - if (referrerListing) { - // Try to use the referrer if possible - activateCategories(referrerListing); - } else if (listingHrefs.length > 0) { - // Otherwise, just fall back to the first listing - activateCategories(listingHrefs[0]); - } - } - }); - } - } - if (hasTitleCategories()) { - findAndActivateCategories(); - } - - const findNearestParentListing = (href, listingHrefs) => { - if (!href || !listingHrefs) { - return undefined; - } - // Look up the tree for a nearby linting and use that if we find one - const relativeParts = href.substring(1).split("/"); - while (relativeParts.length > 0) { - const path = relativeParts.join("/"); - for (const listingHref of listingHrefs) { - if (listingHref.startsWith(path)) { - return listingHref; - } - } - relativeParts.pop(); - } - - return undefined; - }; - - const manageSidebarVisiblity = (el, placeholderDescriptor) => { - let isVisible = true; - let elRect; - - return (hiddenRegions) => { - if (el === null) { - return; - } - - // Find the last element of the TOC - const lastChildEl = el.lastElementChild; - - if (lastChildEl) { - // Converts the sidebar to a menu - const convertToMenu = () => { - for (const child of el.children) { - child.style.opacity = 0; - child.style.overflow = "hidden"; - child.style.pointerEvents = "none"; - } - - nexttick(() => { - const toggleContainer = window.document.createElement("div"); - toggleContainer.style.width = "100%"; - toggleContainer.classList.add("zindex-over-content"); - toggleContainer.classList.add("quarto-sidebar-toggle"); - toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom - toggleContainer.id = placeholderDescriptor.id; - toggleContainer.style.position = "fixed"; - - const toggleIcon = window.document.createElement("i"); - toggleIcon.classList.add("quarto-sidebar-toggle-icon"); - toggleIcon.classList.add("bi"); - toggleIcon.classList.add("bi-caret-down-fill"); - - const toggleTitle = window.document.createElement("div"); - const titleEl = window.document.body.querySelector( - placeholderDescriptor.titleSelector - ); - if (titleEl) { - toggleTitle.append( - titleEl.textContent || titleEl.innerText, - toggleIcon - ); - } - toggleTitle.classList.add("zindex-over-content"); - toggleTitle.classList.add("quarto-sidebar-toggle-title"); - toggleContainer.append(toggleTitle); - - const toggleContents = window.document.createElement("div"); - toggleContents.classList = el.classList; - toggleContents.classList.add("zindex-over-content"); - toggleContents.classList.add("quarto-sidebar-toggle-contents"); - for (const child of el.children) { - if (child.id === "toc-title") { - continue; - } - - const clone = child.cloneNode(true); - clone.style.opacity = 1; - clone.style.pointerEvents = null; - clone.style.display = null; - toggleContents.append(clone); - } - toggleContents.style.height = "0px"; - const positionToggle = () => { - // position the element (top left of parent, same width as parent) - if (!elRect) { - elRect = el.getBoundingClientRect(); - } - toggleContainer.style.left = `${elRect.left}px`; - toggleContainer.style.top = `${elRect.top}px`; - toggleContainer.style.width = `${elRect.width}px`; - }; - positionToggle(); - - toggleContainer.append(toggleContents); - el.parentElement.prepend(toggleContainer); - - // Process clicks - let tocShowing = false; - // Allow the caller to control whether this is dismissed - // when it is clicked (e.g. sidebar navigation supports - // opening and closing the nav tree, so don't dismiss on click) - const clickEl = placeholderDescriptor.dismissOnClick - ? toggleContainer - : toggleTitle; - - const closeToggle = () => { - if (tocShowing) { - toggleContainer.classList.remove("expanded"); - toggleContents.style.height = "0px"; - tocShowing = false; - } - }; - - // Get rid of any expanded toggle if the user scrolls - window.document.addEventListener( - "scroll", - throttle(() => { - closeToggle(); - }, 50) - ); - - // Handle positioning of the toggle - window.addEventListener( - "resize", - throttle(() => { - elRect = undefined; - positionToggle(); - }, 50) - ); - - window.addEventListener("quarto-hrChanged", () => { - elRect = undefined; - }); - - // Process the click - clickEl.onclick = () => { - if (!tocShowing) { - toggleContainer.classList.add("expanded"); - toggleContents.style.height = null; - tocShowing = true; - } else { - closeToggle(); - } - }; - }); - }; - - // Converts a sidebar from a menu back to a sidebar - const convertToSidebar = () => { - for (const child of el.children) { - child.style.opacity = 1; - child.style.overflow = null; - child.style.pointerEvents = null; - } - - const placeholderEl = window.document.getElementById( - placeholderDescriptor.id - ); - if (placeholderEl) { - placeholderEl.remove(); - } - - el.classList.remove("rollup"); - }; - - if (isReaderMode()) { - convertToMenu(); - isVisible = false; - } else { - // Find the top and bottom o the element that is being managed - const elTop = el.offsetTop; - const elBottom = - elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; - - if (!isVisible) { - // If the element is current not visible reveal if there are - // no conflicts with overlay regions - if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { - convertToSidebar(); - isVisible = true; - } - } else { - // If the element is visible, hide it if it conflicts with overlay regions - // and insert a placeholder toggle (or if we're in reader mode) - if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { - convertToMenu(); - isVisible = false; - } - } - } - } - }; - }; - - const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]'); - for (const tabEl of tabEls) { - const id = tabEl.getAttribute("data-bs-target"); - if (id) { - const columnEl = document.querySelector( - `${id} .column-margin, .tabset-margin-content` - ); - if (columnEl) - tabEl.addEventListener("shown.bs.tab", function (event) { - const el = event.srcElement; - if (el) { - const visibleCls = `${el.id}-margin-content`; - // walk up until we find a parent tabset - let panelTabsetEl = el.parentElement; - while (panelTabsetEl) { - if (panelTabsetEl.classList.contains("panel-tabset")) { - break; - } - panelTabsetEl = panelTabsetEl.parentElement; - } - - if (panelTabsetEl) { - const prevSib = panelTabsetEl.previousElementSibling; - if ( - prevSib && - prevSib.classList.contains("tabset-margin-container") - ) { - const childNodes = prevSib.querySelectorAll( - ".tabset-margin-content" - ); - for (const childEl of childNodes) { - if (childEl.classList.contains(visibleCls)) { - childEl.classList.remove("collapse"); - } else { - childEl.classList.add("collapse"); - } - } - } - } - } - - layoutMarginEls(); - }); - } - } - - // Manage the visibility of the toc and the sidebar - const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { - id: "quarto-toc-toggle", - titleSelector: "#toc-title", - dismissOnClick: true, - }); - const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { - id: "quarto-sidebarnav-toggle", - titleSelector: ".title", - dismissOnClick: false, - }); - let tocLeftScrollVisibility; - if (leftTocEl) { - tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { - id: "quarto-lefttoc-toggle", - titleSelector: "#toc-title", - dismissOnClick: true, - }); - } - - // Find the first element that uses formatting in special columns - const conflictingEls = window.document.body.querySelectorAll( - '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' - ); - - // Filter all the possibly conflicting elements into ones - // the do conflict on the left or ride side - const arrConflictingEls = Array.from(conflictingEls); - const leftSideConflictEls = arrConflictingEls.filter((el) => { - if (el.tagName === "ASIDE") { - return false; - } - return Array.from(el.classList).find((className) => { - return ( - className !== "column-body" && - className.startsWith("column-") && - !className.endsWith("right") && - !className.endsWith("container") && - className !== "column-margin" - ); - }); - }); - const rightSideConflictEls = arrConflictingEls.filter((el) => { - if (el.tagName === "ASIDE") { - return true; - } - - const hasMarginCaption = Array.from(el.classList).find((className) => { - return className == "margin-caption"; - }); - if (hasMarginCaption) { - return true; - } - - return Array.from(el.classList).find((className) => { - return ( - className !== "column-body" && - !className.endsWith("container") && - className.startsWith("column-") && - !className.endsWith("left") - ); - }); - }); - - const kOverlapPaddingSize = 10; - function toRegions(els) { - return els.map((el) => { - const boundRect = el.getBoundingClientRect(); - const top = - boundRect.top + - document.documentElement.scrollTop - - kOverlapPaddingSize; - return { - top, - bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, - }; - }); - } - - let hasObserved = false; - const visibleItemObserver = (els) => { - let visibleElements = [...els]; - const intersectionObserver = new IntersectionObserver( - (entries, _observer) => { - entries.forEach((entry) => { - if (entry.isIntersecting) { - if (visibleElements.indexOf(entry.target) === -1) { - visibleElements.push(entry.target); - } - } else { - visibleElements = visibleElements.filter((visibleEntry) => { - return visibleEntry !== entry; - }); - } - }); - - if (!hasObserved) { - hideOverlappedSidebars(); - } - hasObserved = true; - }, - {} - ); - els.forEach((el) => { - intersectionObserver.observe(el); - }); - - return { - getVisibleEntries: () => { - return visibleElements; - }, - }; - }; - - const rightElementObserver = visibleItemObserver(rightSideConflictEls); - const leftElementObserver = visibleItemObserver(leftSideConflictEls); - - const hideOverlappedSidebars = () => { - marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries())); - sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries())); - if (tocLeftScrollVisibility) { - tocLeftScrollVisibility( - toRegions(leftElementObserver.getVisibleEntries()) - ); - } - }; - - window.quartoToggleReader = () => { - // Applies a slow class (or removes it) - // to update the transition speed - const slowTransition = (slow) => { - const manageTransition = (id, slow) => { - const el = document.getElementById(id); - if (el) { - if (slow) { - el.classList.add("slow"); - } else { - el.classList.remove("slow"); - } - } - }; - - manageTransition("TOC", slow); - manageTransition("quarto-sidebar", slow); - }; - const readerMode = !isReaderMode(); - setReaderModeValue(readerMode); - - // If we're entering reader mode, slow the transition - if (readerMode) { - slowTransition(readerMode); - } - highlightReaderToggle(readerMode); - hideOverlappedSidebars(); - - // If we're exiting reader mode, restore the non-slow transition - if (!readerMode) { - slowTransition(!readerMode); - } - }; - - const highlightReaderToggle = (readerMode) => { - const els = document.querySelectorAll(".quarto-reader-toggle"); - if (els) { - els.forEach((el) => { - if (readerMode) { - el.classList.add("reader"); - } else { - el.classList.remove("reader"); - } - }); - } - }; - - const setReaderModeValue = (val) => { - if (window.location.protocol !== "file:") { - window.localStorage.setItem("quarto-reader-mode", val); - } else { - localReaderMode = val; - } - }; - - const isReaderMode = () => { - if (window.location.protocol !== "file:") { - return window.localStorage.getItem("quarto-reader-mode") === "true"; - } else { - return localReaderMode; - } - }; - let localReaderMode = null; - - const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded"); - const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1; - - // Walk the TOC and collapse/expand nodes - // Nodes are expanded if: - // - they are top level - // - they have children that are 'active' links - // - they are directly below an link that is 'active' - const walk = (el, depth) => { - // Tick depth when we enter a UL - if (el.tagName === "UL") { - depth = depth + 1; - } - - // It this is active link - let isActiveNode = false; - if (el.tagName === "A" && el.classList.contains("active")) { - isActiveNode = true; - } - - // See if there is an active child to this element - let hasActiveChild = false; - for (child of el.children) { - hasActiveChild = walk(child, depth) || hasActiveChild; - } - - // Process the collapse state if this is an UL - if (el.tagName === "UL") { - if (tocOpenDepth === -1 && depth > 1) { - // toc-expand: false - el.classList.add("collapse"); - } else if ( - depth <= tocOpenDepth || - hasActiveChild || - prevSiblingIsActiveLink(el) - ) { - el.classList.remove("collapse"); - } else { - el.classList.add("collapse"); - } - - // untick depth when we leave a UL - depth = depth - 1; - } - return hasActiveChild || isActiveNode; - }; - - // walk the TOC and expand / collapse any items that should be shown - if (tocEl) { - updateActiveLink(); - walk(tocEl, 0); - } - - // Throttle the scroll event and walk peridiocally - window.document.addEventListener( - "scroll", - throttle(() => { - if (tocEl) { - updateActiveLink(); - walk(tocEl, 0); - } - if (!isReaderMode()) { - hideOverlappedSidebars(); - } - }, 5) - ); - window.addEventListener( - "resize", - throttle(() => { - if (tocEl) { - updateActiveLink(); - walk(tocEl, 0); - } - if (!isReaderMode()) { - hideOverlappedSidebars(); - } - }, 10) - ); - hideOverlappedSidebars(); - highlightReaderToggle(isReaderMode()); -}); - -// grouped tabsets -window.addEventListener("pageshow", (_event) => { - function getTabSettings() { - const data = localStorage.getItem("quarto-persistent-tabsets-data"); - if (!data) { - localStorage.setItem("quarto-persistent-tabsets-data", "{}"); - return {}; - } - if (data) { - return JSON.parse(data); - } - } - - function setTabSettings(data) { - localStorage.setItem( - "quarto-persistent-tabsets-data", - JSON.stringify(data) - ); - } - - function setTabState(groupName, groupValue) { - const data = getTabSettings(); - data[groupName] = groupValue; - setTabSettings(data); - } - - function toggleTab(tab, active) { - const tabPanelId = tab.getAttribute("aria-controls"); - const tabPanel = document.getElementById(tabPanelId); - if (active) { - tab.classList.add("active"); - tabPanel.classList.add("active"); - } else { - tab.classList.remove("active"); - tabPanel.classList.remove("active"); - } - } - - function toggleAll(selectedGroup, selectorsToSync) { - for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) { - const active = selectedGroup === thisGroup; - for (const tab of tabs) { - toggleTab(tab, active); - } - } - } - - function 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R. Stevens" Date: Wed, 27 Nov 2024 12:28:36 -0600 Subject: [PATCH 19/19] Switch back to R Markdown vignette --- DESCRIPTION | 3 +-- vignettes/{cocoon.qmd => cocoon.Rmd} | 7 ++----- 2 files changed, 3 insertions(+), 7 deletions(-) rename vignettes/{cocoon.qmd => cocoon.Rmd} (99%) diff --git a/DESCRIPTION b/DESCRIPTION index 7000434..ddbfa00 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -18,7 +18,6 @@ Suggests: BayesFactor, correlation, knitr, - quarto, rmarkdown, testthat (>= 3.0.0) Config/testthat/edition: 3 @@ -29,4 +28,4 @@ Imports: URL: https://github.com/JeffreyRStevens/cocoon, https://jeffreyrstevens.github.io/cocoon/ BugReports: https://github.com/JeffreyRStevens/cocoon/issues VignetteBuilder: - quarto + knitr diff --git a/vignettes/cocoon.qmd b/vignettes/cocoon.Rmd similarity index 99% rename from vignettes/cocoon.qmd rename to vignettes/cocoon.Rmd index e737af8..07bf885 100644 --- a/vignettes/cocoon.qmd +++ b/vignettes/cocoon.Rmd @@ -1,12 +1,9 @@ --- title: "cocoon" -format: - html: - toc: true - html-math-method: mathjax +output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{cocoon} - %\VignetteEngine{quarto::html} + %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} ---