This will occur if the check() function detects that
different sources of landscape data have mismatched properties. This
could be for a variety of reasons, including differing coordinate
reference systems (CRS) if using RasterLayers, differing dimensions, and
differing locations of NA data. An important thing to be aware of is
that the package does not support mixing landscape data in different
types of objects; all landscape data used in an analysis must either be
in matrices or RasterLayers. This includes occupancy data that is not
part of the creation of the samc-class object.
# Working example
r1 <- res_data
r2 <- res_data
check(r1, r2)
#> [1] TRUE
# Remove the NA's in r2 by overwriting all the elements with the number 1.
# check() doesn't check the actual values of the data, but it does check the
# location of NA's
r1 <- res_data
r2 <- res_data
r2[1] <- 1
check(r1, r2)
#> Error: NA mismatch in input data
# Change the dimensions of r2 by subsetting it. check() ensures that the data
# inputs have the same number of rows and columns
r1 <- res_data
r2 <- res_data
r2 <- r2[1:5, 1:5]
check(r1, r2)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'a' in selecting a method for function 'check': [rast] extents do not matchThe SAMC package makes use of R’s S4 method dispatch system to
enforce how the different versions of each function can be used.
Hopefully, this will ensure that users are not unintentionally misusing
functions by producing an error rather than letting the code run and
returning a result that may not be obviously incorrect. If this error
appears, it means that the combination of arguments provided to the
function are not valid. This could be for a couple different reasons.
The first is that an optional parameter is skipped without specifying
argument names for the subsequent arguments. The second is that a user
is passing the wrong type of data to an argument (e.g., passing a
numeric when the function expects a
RasterLayer or a matrix).
# Example: Skipping optional arguments. In this case, the `fidelity` argument is
# optional, so we skip it. The model argument, however, is always required,
# so we pass the relevant to it. But because we don't specify which
# argument it is, R is trying to find a version of the function that expects it
# as the third argument, but this version does not exist.
samc_obj <- samc(res_data, abs_data, list(fun = function(x) 1/mean(x), dir = 8, sym = TRUE))
#> Error in (function (classes, fdef, mtable) : unable to find an inherited method for function 'samc' for signature '"matrix", "matrix", "list", "missing"'
# Solution
samc_obj <- samc(res_data, abs_data, model = list(fun = function(x) 1/mean(x), dir = 8, sym = TRUE))
# Example: Incorrect input types. In this case, we are attempting to pass a
# single numeric value as absorption data. However, the absorption data must
# always be in a matrix or RasterLayer object
samc_obj <- samc(res_data, 0.01, model = list(fun = function(x) 1/mean(x), dir = 8, sym = TRUE))
#> Error in (function (classes, fdef, mtable) : unable to find an inherited method for function 'samc' for signature '"matrix", "numeric", "missing", "list"'
# Solution
samc_obj <- samc(res_data, abs_data, model = list(fun = function(x) 1/mean(x), dir = 8, sym = TRUE))See the Disconnected Data vignette.
See the Disconnected Data vignette.
Update the Rcpp package. Then make sure to unload all of your
packages and reload them again. You do not need to load the Rcpp package
(i.e, do not library(Rcpp)).