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samc (version 2.0.1)

check: Check landscape data

Description

Check that landscape inputs have valid values and matching properties.

Usage

check(a, b)

# S4 method for Raster,missing check(a)

# S4 method for matrix,missing check(a)

# S4 method for Raster,Raster check(a, b)

# S4 method for matrix,matrix check(a, b)

# S4 method for samc,Raster check(a, b)

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

Value

See Details section.

Arguments

a

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

b

A matrix or RasterLayer-class object

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

Run this code
# "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)

# Setup the details for our transition function
tr <- list(fun = function(x) 1/mean(x), # Function for calculating transition probabilities
           dir = 8, # Directions of the transitions. Either 4 or 8.
           sym = TRUE) # Is the function symmetric?


# 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.
samc_obj <- samc(res_data, abs_data, tr_args = tr)


# 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)

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