ramp: *ra*nge *m*apper *p*ipe line.

In valcu/rangeMapper: A Platform for the Study of Macro-Ecology of Life History Traits

Description

A quick alternative to initiate a project by pipelining several functions.

Usage

ramp(file, dir = tempdir(), gridSize, spdf, bbox = spdf, ID, biotab,
  metadata, FUN, overwrite = FALSE)

Arguments

file	project file name.
dir	project directory.
gridSize	grid resolution (in units previously set by global.bbox.save)
spdf	SpatialPolygonsDataFrame object containing all the ranges.
bbox	the spatial domain of the project (see global.bbox.save )
ID	a character vector of length one. An spdf column name indicating the range ID (e.g. species name).
biotab	character string identifying the ‘BIO’ table to use.
metadata	a named list of functions. See rangeTraits and metadata.update.
FUN	the function to be applied to each pixel. If FUN is missing then species richness (species count) is computed.
overwrite	logical vector, default to FALSE (the file is kept but all tables are dropped).

Value

an sqlite connection to a rangeMapper project

Note

ramp combines all the functions from rangeMap.start() to processRanges() and rangeMap.save() but is less flexible as compared with a step-by-step project building.

See Also

rangeMap.start global.bbox.save gridSize.save canvas.save processRanges bio.save rangeMap.save

Examples

breding_ranges = rgdal::readOGR(system.file(package = "rangeMapper",
     "extdata", "wrens", "vector_combined"), "wrens", verbose = FALSE)[1:50, ]
data(wrens)
d = subset(wrens, select = c('sci_name', 'body_size', 'clutch_size') )
con = ramp("wrens.sqlite", gridSize = 15, spdf = breding_ranges, biotab = d, ID = "sci_name",
            metadata = rangeTraits(), FUN = "median", overwrite = TRUE)
m = rangeMap.fetch(con)
dbDisconnect(con)

valcu/rangeMapper documentation built on Feb. 6, 2021, 8:20 p.m.