CompactGrids: Create compacted environmental grids for AdaptR

In KarelMokany/AdaptR: Species distribution modelling incorporating genetic adaptation

Description

Create compacted environmental grids for AdaptR

Usage

CompactGrids(compactor.parameter.file.name, ncols, nrows, n.env.vars,
  n.time.points, raw.env.grids.name.files, output.env.name.file)

Arguments

compactor.parameter.file.name	A file path to a text file (.txt) to be created by this function, where the grid compactor parameter file will be saved
ncols	The number of columns on the spatial grid
nrows	The number of rows on the spatial grid
n.env.vars	The number of environment variables being considered
n.time.points	The number of time points for which compacted environment grids are to be created
raw.env.grids.name.files	A list of length n.env.vars of filepaths to text files holding the filepaths of individual environment grids to be compacted.
output.env.name.file	A filepath to a text file (.txt) holding the filepaths where the compacted environment grids will be saved.

Value

A set of compacted environment files in the specified location

Examples

## Complete example of the multiple steps in applying AdaptR using data example provided for Drosophila jambulina

# 1. Set the filepath to the example data set
filepath.data <- system.file("extdata", package="AdaptR")

# 2. Create text files to describe the file path to each input variable, and the output variable
write.table((file.path(filepath.data,"Tmax",paste0("Tmax",seq(1:159),".asc"))), file = file.path(filepath.data,"Tmax","Tmax_filenames.txt"), eol = "\n", row.names = FALSE, col.names = FALSE, quote=FALSE )
write.table((file.path(filepath.data,"Habitat",paste0("Habitat",seq(1:159),".asc"))), file = file.path(filepath.data,"Habitat","Habitat_filenames.txt"), eol = "\n", row.names = FALSE, col.names = FALSE, quote=FALSE )
write.table((file.path(filepath.data,"compact_grids",paste0("demo_compact_grids_T",seq(1:159)))), file = file.path(filepath.data,"compact_grids","demo_compact_grids_output_filenames.txt"), eol = "\n", row.names = FALSE, col.names = FALSE, quote=FALSE )

# 3. Run the grid compactor
CompactGrids(compactor.parameter.file.name = file.path(filepath.data,"species_inputs","Jambulina__grid_compactor_parameter_file.txt"),
             ncols = 100,
             nrows = 79,
             n.env.vars = 2,
             n.time.points = 159,
             raw.env.grids.name.files = c(file.path(filepath.data,"Tmax","Tmax_filenames.txt"),file.path(filepath.data,"Habitat","Habitat_filenames.txt")),
             output.env.name.file = file.path(filepath.data,"compact_grids","demo_compact_grids_output_filenames.txt"))

# 4. Generate a dispersal kernel for the drosophila example
filepath.data <- system.file("extdata", package="AdaptR")
Dispersal_Neighbourhood(radius=5, 
                       type="neg.power", 
                       params=c(1,1), 
                       output.name="Dispersal_relfile_L1_K1_rad5",
                       output.directory=file.path(filepath.data,"species_inputs"),
                       dispersal.plot=TRUE)  

# 5. Create text files to describe the file path to the compact grids
write.table(paste0("demo_compact_grids_T",rep(1:159, length.out=159)), file = file.path(filepath.data,"species_inputs","compact_series_names.txt"), eol = "\n", row.names = FALSE, col.names = FALSE, quote=FALSE )

# 6. Run the AdaptR model
AdaptR(run.name = "jambulina_test",
        parameter.file.name = file.path(filepath.data,"outputs","jambulina_test_parameters.txt"),
        ncols = 100,
        nrows = 79,
        output.folder.path = file.path(filepath.data,"outputs"),
        verbose.outputs = FALSE,
        n.time.points = 159,
        n.env.vars = 2,
        env.vars.names = c("MaxTemp", "Other_Maxent"),
        env.grids.folder.path = file.path(filepath.data,"compact_grids"),
        env.grids.name.file = file.path(filepath.data,"species_inputs","compact_series_names.txt"),
        species.initial.grid = file.path(filepath.data,"species_inputs","demo_jambulia_initial_distribution.asc"),
        minimum.survival.percentage = 5,
        resident.population.weighting = 1000,
        dispersal.neighbourhood.file = file.path(filepath.data,"species_inputs","Dispersal_relfile_L1_K1_rad5.dna"),
        species.location.file = file.path(filepath.data,"species_inputs","demo_locations_out.txt"),
        env.lower.thresholds = c(19.47,0.99),
        env.upper.thresholds = c(37.94547,1.01),
        env.low.adaptation = c(FALSE,FALSE),
        env.high.adaptation = c(TRUE,FALSE),
        adapt.limit = c(40,0),
        heritability = c(0.53,0),
        fitness.cost = c(0.05,0),
        adapt.threshold.grids = c(FALSE,FALSE),
        phenotypic.sd.grid = c(FALSE,FALSE),
        phenotypic.sd.value = c(1.106,0),
        plasticity = c(1.106,0))

# 7. Map the predictions of the model (at the last time point)
map.single.run(output.folder.path = file.path(filepath.data,"outputs"), 
               run.name = "jambulina_test")

KarelMokany/AdaptR documentation built on May 8, 2019, 4:48 p.m.