All functions

AttributeSpace-class

AttributeSpace: An S4 class to represent an attribute space.

AttributeSpace()

Create new AttributeSpace object

AttributeSpaces-class

AttributeSpaces: An S4 class to represent a collection of attribute spaces for different species.

AttributeSpaces()

Create new AttributeSpaces object

DemandPoints-class

DemandPoints: An S4 class to represent demand points

DemandPoints()

Create new DemandPoints object

GurobiOpts-class

GurobiOpts: An S4 class to represent Gurobi parameters

GurobiOpts()

Create GurobiOpts object

ManualOpts-class

ManualOpts: An S4 class to represent parameters for manually specified solutions

ManualOpts()

Create ManualOpts object

PlanningUnitPoints-class

PlanningUnitPoints: An S4 class to represent planning units in an attribute space

PlanningUnitPoints()

Create new PlanningUnitPoints object

PolySet-class

PolySet

RapData-class

RapData: An S4 class to represent RAP input data

RapData()

Create new RapData object

RapOpts-class

RapOpts class

RapReliableOpts-class

RapReliableOpts: An S4 class to represent input parameters for the reliable formulation of RAP.

RapReliableOpts()

Create RapReliableOpts object

RapResults-class

RapResults: An S4 class to represent RAP results

RapResults()

Create RapResults object

RapSolved-class

RapSolved: An S4 class to represent RAP inputs and outputs

RapSolved()

Create new RapSolved object

RapUnreliableOpts-class

RapUnreliableOpts: An S4 class to represent parameters for the unreliable RAP problem

RapUnreliableOpts()

Create RapUnreliableOpts object

RapUnsolved-class

RapUnsolved: An S4 class to represent RAP inputs

RapUnsolved()

Create a new RapUnsolved object

SolverOpts-class

SolverOpts class

SpatialPolygons2PolySet()

Convert SpatialPolygons to PolySet data

amount.held()

Extract amount held for a solution

amount.target() `amount.target<-`()

Amount targets

as.list(<GurobiOpts>)

Convert object to list

blank.raster()

Blank raster

calcBoundaryData()

Calculate boundary data for planning units

calcSpeciesAverageInPus()

Calculate average value for species data in planning units

casestudy_data

Case-study dataset for a conservation planning exercise

dp.subset()

Subset demand points

is.GurobiInstalled()

Test if Gurobi is installed

is.gdalInstalled()

Test if GDAL is installed on computer

logging.file()

Log file

make.DemandPoints()

Generate demand points for RAP

make.RapData()

Make data for RAP using minimal inputs

maximum.targets()

Maximum targets

`names<-`(<RapData>) names(<RapData>) `names<-`(<RapUnsolOrSol>) names(<RapUnsolOrSol>)

Names

plot(<RapSolved>,<numeric>) plot(<RapSolved>,<missing>) plot(<RapSolved>,<RapSolved>)

Plot object

print(<AttributeSpace>) print(<AttributeSpaces>) print(<GurobiOpts>) print(<ManualOpts>) print(<RapData>) print(<RapReliableOpts>) print(<RapResults>) print(<RapUnreliableOpts>) print(<RapUnsolved>) print(<RapSolved>)

Print objects

prob.subset()

Subset probabilities above a threshold

pu.subset()

Subset planning units

randomPoints()

Sample random points from a RasterLayer

rap()

Generate prioritizations using RAP

raptr

raptr: Representative and Adequate Prioritization Toolkit in R

rasterizeGDAL()

Rasterize polygon data using GDAL

rrap.proportion.held()

Proportion held using reliable RAP formulation.

score()

Solution score

selections()

Extract solution selections

show(<GurobiOpts>) show(<ManualOpts>) show(<RapData>) show(<RapReliableOpts>) show(<RapResults>) show(<RapUnreliableOpts>) show(<RapUnsolved>) show(<RapSolved>)

Show objects

sim.pus()

Simulate planning units

sim.space()

Simulate attribute space data for RAP

sim.species()

Simulate species distribution data for RAP

simulated_data

Simulated dataset for a conservation planning exercise

solve(<RapUnsolOrSol>,<missing>) solve(<RapUnsolOrSol>,<GurobiOpts>) solve(<RapUnsolOrSol>,<matrix>) solve(<RapUnsolOrSol>,<numeric>) solve(<RapUnsolOrSol>,<logical>)

Solve RAP object

space.held()

Extract attribute space held for a solution

space.plot()

Plot space

space.target() `space.target<-`()

Attribute space targets

spp.plot()

Plot species

spp.subset()

Subset species

summary

Summary of solutions

update(<GurobiOpts>) update(<ManualOpts>) update(<RapData>) update(<RapReliableOpts>) update(<RapUnreliableOpts>) update(<RapUnsolOrSol>)

Update object

urap.proportion.held()

Proportion held using unreliable RAP formulation.