Summarize, filter and subset occurrence data

Set of S3 methods to summarize, filter and get unique occurrence data retrieved using occurrences. This uses information based on selections of assertions (quality assurance issues ALA has identified), spatial and temporal data.

# S3 method for occurrences
summary(object, ...)

# S3 method for occurrences
unique(
  x,
  incomparables = FALSE,
  spatial = 0,
  temporal = NULL,
  na.rm = FALSE,
  ...
)

# S3 method for occurrences
subset(
  x,
  remove.fatal = TRUE,
  exclude.spatial = "error",
  exclude.temporal = "error",
  exclude.taxonomic = "error",
  max.spatial.uncertainty,
  keep.missing.spatial.uncertainty = TRUE,
  ...
)

Arguments

object	list: an 'occurrence' object that has been downloaded using occurrences
...	not currently used
x	list: an 'occurrence' object that has been downloaded using occurrences
incomparables	logical/numeric: currently ignored, but needed for S3 method consistency
spatial	numeric: specifies a rounding value in decimal degrees used to create a unique subset of the data. Value of 0 means no rounding and use values as is. Values <0 mean ignore spatial unique parameter
temporal	character: specifies the temporal unit for which to keep unique records; this can be by "year", "month", "yearmonth" or "full" date. NULL means ignore temporal unique parameter
na.rm	logical: keep (FALSE) or remove (TRUE) missing spatial or temporal data
remove.fatal	logical: remove flagged assertion issues that are considered "fatal"; see check_assertions
exclude.spatial	character vector: defining flagged spatial assertion issues to be removed. Values can include 'warnings','error','missing', 'none'; see check_assertions
exclude.temporal	character vector: defining flagged temporal assertion issues to be removed. Values can include 'warnings','error', 'missing','none'; see check_assertions
exclude.taxonomic	character vector: defining flagged taxonomic assertion issues to be removed. Values can include 'warnings','error', 'missing','none'; see check_assertions
max.spatial.uncertainty	numeric: number defining the maximum spatial uncertainty (in meters) one is willing to accept.
keep.missing.spatial.uncertainty	logical: keep (FALSE) or remove (TRUE) information missing spatial uncertainty data.

Details

unique will give the min value for all columns that are not used in the aggregation.

References

https://api.ala.org.au/

http://stat.ethz.ch/R-manual/R-devel/library/methods/html/Methods.html

Examples

if (FALSE) {
#download some observations
x <- occurrences(taxon = "Amblyornis newtonianus",download_reason_id = 10,
email = "ala4r@ala.org.au")

#summarize the occurrences
summary(x)

#keep spatially unique data at 0.01 degrees (latitudeOriginal and longitudeOriginal)
tt <- unique(x,spatial = 0.01)
summary(tt)

#keep spatially unique data that is also unique year/month for the
#collection date
tt <- unique(x,spatial = 0,temporal = 'yearmonth')
summary(tt)

#keep only information for which fatal or "error" assertions do not exist
tt <- subset(x)
summary(tt)
}