Get module names or update which sections are used by an ecological or data-status report. Profiles provide named, reusable selections without moving or duplicating the YAML module files.
Usage
section_names(keep, exclude, object, profile, report_type)
sections(x, n, profile, report_type)Arguments
- keep
An optional character vector of section names to keep.
- exclude
An optional character vector of section names to exclude.
- object
An optional
camReportobject. It is needed to inspect user-defined profiles registered in that object.- profile
An optional profile name or
reportProfileobject.- report_type
Which output selection to use:
"report","status", or, forsection_names(),"all".- x
- n
An optional character vector of modules to include. Qualified names such as
"status::spatial"can select from the other module pool when a profile is being edited.
Value
section_names() and sections(x) return character vectors.
sections(x, n) updates x and returns it invisibly.
Unknown names in a partially valid sections(x, n) selection are ignored
with a warning naming those sections. An entirely unknown selection errors.
Details
section_names() lists modules in a pool or in a profile. Set
report_type = "all" to list both pools. Names from both pools, and names
returned for a profile, use the unambiguous "source::module" notation.
sections() updates the transient module tree used for the next render.
When profile is supplied, it can also inspect or update that registered
profile. Set report_type = "status" to manage the data-status selection.
See also
reportProfile(), report(), status(), listReportSections()
Other report sections:
reportSection,character-method,
testSection,.textSection-method,
updateReportSection()
Examples
section_names()
#> [1] "introduction" "methods"
#> [3] "study_area" "sampling"
#> [5] "location" "location_eow"
#> [7] "effort" "effort_eow"
#> [9] "image_processing" "data_processing"
#> [11] "results" "captures"
#> [13] "abundance_trends" "abundance_trends_eow"
#> [15] "population_density" "population_density_annual"
#> [17] "model_parameters" "model_parameters_eow"
#> [19] "population_densities" "population_densities_eow"
#> [21] "activity_patterns" "activity_patterns_eow"
#> [23] "richness" "co_occurrence"
#> [25] "spatial_density" "habitat_preferences"
#> [27] "species_accumulation" "acknowledgements"
#> [29] "appendix" "appendix_eow"
#> [31] "References" "References_eow"
section_names(profile = "default")
#> [1] "report::introduction" "report::methods"
#> [3] "report::study_area" "report::sampling"
#> [5] "report::location" "report::effort"
#> [7] "report::image_processing" "report::data_processing"
#> [9] "report::results" "report::captures"
#> [11] "report::abundance_trends" "report::population_density"
#> [13] "report::model_parameters" "report::population_densities"
#> [15] "report::activity_patterns" "report::richness"
#> [17] "report::co_occurrence" "report::spatial_density"
#> [19] "report::habitat_preferences" "report::species_accumulation"
#> [21] "report::acknowledgements" "report::appendix"
#> [23] "report::References"
section_names(report_type = "all")
#> [1] "report::introduction" "report::methods"
#> [3] "report::study_area" "report::sampling"
#> [5] "report::location" "report::location_eow"
#> [7] "report::effort" "report::effort_eow"
#> [9] "report::image_processing" "report::data_processing"
#> [11] "report::results" "report::captures"
#> [13] "report::abundance_trends" "report::abundance_trends_eow"
#> [15] "report::population_density" "report::population_density_annual"
#> [17] "report::model_parameters" "report::model_parameters_eow"
#> [19] "report::population_densities" "report::population_densities_eow"
#> [21] "report::activity_patterns" "report::activity_patterns_eow"
#> [23] "report::richness" "report::co_occurrence"
#> [25] "report::spatial_density" "report::habitat_preferences"
#> [27] "report::species_accumulation" "report::acknowledgements"
#> [29] "report::appendix" "report::appendix_eow"
#> [31] "report::References" "report::References_eow"
#> [33] "status::abstract" "status::spatial"
#> [35] "status::temporal" "status::availability"
#> [37] "status::validation" "status::annotation"
#> [39] "status::observation_type" "status::conclusion"
#> [41] "status::acknowledge"
# \donttest{
# Section selection needs only a small imported dataset.
source_dataset <- system.file(
"external", "example-small", package = "camtrapReport"
)
example_dataset <- tempfile("camtrapReport-example-")
dir.create(example_dataset)
invisible(file.copy(
list.files(source_dataset, full.names = TRUE),
example_dataset,
recursive = TRUE
))
cm <- camData(example_dataset)
#> The camReport object is being created...
#> Dataset size: 164.4 KB.
#> File size looks modest, but full object creation may still take several minutes depending on the number of records.
#> Taxonomic class is unavailable for 10 recorded taxa. Class-dependent groups and mammal counts may be incomplete; missing classification does not indicate ecological absence. Supply source classifications or explicitly enable GBIF enrichment and rebuild with update = TRUE.
#> Setup is done!
#> Data loaded successfully in 8 sec.
#> camReport object is ready for GMU8 LEUVEN.
sections(cm, profile = "default")
#> [1] "report::introduction" "report::methods"
#> [3] "report::study_area" "report::sampling"
#> [5] "report::location" "report::effort"
#> [7] "report::image_processing" "report::data_processing"
#> [9] "report::results" "report::captures"
#> [11] "report::abundance_trends" "report::population_density"
#> [13] "report::model_parameters" "report::population_densities"
#> [15] "report::activity_patterns" "report::richness"
#> [17] "report::co_occurrence" "report::spatial_density"
#> [19] "report::habitat_preferences" "report::species_accumulation"
#> [21] "report::acknowledgements" "report::appendix"
#> [23] "report::References"
cm <- sections(cm, c("introduction", "methods"))
#>
#> The report sections are updated.
unlink(example_dataset, recursive = TRUE, force = TRUE)
# }