Creates figures specified in a rptyaml file
Usage
build_figures(
obnd = NULL,
fit = NULL,
rptdetails = NULL,
cat_covars = NULL,
cont_covars = NULL,
verbose = TRUE
)Arguments
- obnd
onbrandreport object to have report elements appended to- fit
nlmixr2fit object to be reported- rptdetails
Object created when reading in rptyaml file
- cat_covars
character vector of categorical covariates to overwrite defaults in yaml file
- cont_covars
character vector of continuous covariates to overwrite defaults in yaml file
- verbose
Boolean variable when set to TRUE (default) messages will be displayed on the terminal
Value
List containing the figures with the following structure:
"rptfigs"- List of figures with names corresponding to the figure ids in the yaml file. Each figure ID contains the following elements:"figure"- list of figure file names for the current fid"orientation"- Figure orientation ("portrait" or "landscape")"isgood"- Boolean variable indicating success or failure"skip"- Boolean variable indicating whether the figure should be skipped during reporting"fmsgs"- Vector of messages"cmd"- Original plot generation command"cmd_proc"- Plot generation command after processing for placeholders"height"- Figure height"width"- Figure width"caption"- Caption for Word"caption_proc"- Caption for Word after processing for placeholders"title"- Slide title for PowerPoint"title_proc"- Slide title for PowerPoint after processing for placeholders
"isgood"- Boolean variable indicating success or failure"msgs"- Vector of messages
Examples
# We need an onbrand object to use below
library(onbrand)
obnd = read_template(
template = system.file(package="nlmixr2rpt", "templates","nlmixr_obnd_template.docx"),
mapping = system.file(package="nlmixr2rpt", "templates","nlmixr_obnd_template.yaml"))
# We also need an nlmixr fit object
fit = fetch_fit_example()
# This reads in the report details as well
rptdetails = yaml_read_fit(
obnd = obnd,
rptyaml = system.file(package="nlmixr2rpt", "examples", "report_fit_test.yaml"),
fit = fit)$rptdetails
# Now we will build the figures
bfres = build_figures(obnd = obnd,
fit = fit,
rptdetails = rptdetails)
#>
#> Attaching package: ‘xpose’
#> The following object is masked from ‘package:stats’:
#>
#> filter
#>
#> ── Building report figures
#> → dv_vs_pred
#> `geom_smooth()` using formula = 'y ~ x'
#> Warning: is.na() applied to non-(list or vector) of type 'object'
#> `geom_smooth()` using formula = 'y ~ x'
#> •
#> /var/folders/pq/7srbf_fx3rd3k706hgxkg61r0000gp/T//Rtmpp05fZU/RUNN/dv_vs_pred-Word.png
#> → bad_figure
#>
#> ── Figure generation failed
#> → figure id: bad_figure
#> → Unable to generate figure
#> → -> call: eval, parse(text = finfo[["cmd_proc"]])
#> → -> message: object 'bad_figure_command' not found
#> → command run:
#> → bad_figure_command
#> Warning: is.na() applied to non-(list or vector) of type 'object'
#> •
#> /var/folders/pq/7srbf_fx3rd3k706hgxkg61r0000gp/T//Rtmpp05fZU/RUNN/bad_figure-Word.png
#> → skip_figure