samc (version 1.3.0)

check: Check landscape data

Description

Check that landscape inputs have valid values and matching properties.

Usage

check(a, b)
# S4 method for RasterLayer,missing
check(a)
# S4 method for matrix,missing
check(a)
# S4 method for RasterLayer,RasterLayer
check(a, b)
# S4 method for matrix,matrix
check(a, b)
# S4 method for samc,RasterLayer
check(a, b)
# S4 method for samc,matrix
check(a, b)

Arguments

a

A samc-class, matrix, or RasterLayer-class object

b

A matrix or RasterLayer-class object

Value

See Details section.

Details

This function is used to ensure that landscape inputs (resistance, absorption, fidelity, and occupancy) have valid values and the same properties. This includes checking the CRS (if using RasterLayer inputs), dimensions, and locations of cells with NA data. It can be used to directly compare two matrices or two RasterLayers, or it can be used to check a samc-class object against a matrix or RasterLayer.

The function returns TRUE if the inputs have matching properties. Otherwise, it will stop execution and print the error message generated by the compareRaster() function from the raster package. This error will provide some details about the difference between the two inputs.

Note that the package assumes the different landscape inputs will be the same type, either matrices or RasterLayers. Mixing RasterLayer data and matrix data is not supported.

Examples

# NOT RUN {
# "Load" the data. In this case we are using data built into the package.
# In practice, users will likely load raster data using the raster() function
# from the raster package.
res_data <- samc::ex_res_data
abs_data <- samc::ex_abs_data
occ_data <- samc::ex_occ_data


# Make sure our data meets the basic input requirements of the package using
# the check() function.
check(res_data, abs_data)
check(res_data, occ_data)


# Create a `samc-class` object with the resistance and absorption data using
# the samc() function. We use the recipricol of the arithmetic mean for
# calculating the transition matrix. Note, the input data here are matrices,
# not RasterLayers. If using RasterLayers, the latlon parameter must be set.
samc_obj <- samc(res_data, abs_data, tr_fun = function(x) 1/mean(x))


# Convert the occupancy data to probability of occurrence
occ_prob_data <- occ_data / sum(occ_data, na.rm = TRUE)


# Calculate short- and long-term metrics using the analytical functions
short_mort <- mortality(samc_obj, occ_prob_data, time = 50)
short_dist <- distribution(samc_obj, origin = 3, time = 50)
long_disp <- dispersal(samc_obj, occ_prob_data)
visit <- visitation(samc_obj, dest = 4)
surv <- survival(samc_obj)


# Use the map() function to turn vector results into RasterLayer objects.
short_mort_map <- map(samc_obj, short_mort)
short_dist_map <- map(samc_obj, short_dist)
long_disp_map <- map(samc_obj, long_disp)
visit_map <- map(samc_obj, visit)
surv_map <- map(samc_obj, surv)
# }