create_indicator | R Documentation |
Computation, significance assessment and display of trends of a custom, user-defined indicator.
create_indicator(fun, taskname = as.character(substitute(fun))) compute_indicator(mat, fun, taskname = as.character(substitute(fun)), ...)
fun |
A function that takes a matrix as input and returns a vector of numerical values. If the function returns a named vector, then the names will be used in plots and summaries. The function may also accept extra arguments. |
taskname |
The task name. A character string used used for plots and
textual summaries that describes the indicator (or set of indicators)
being computed. If a task name cannot be derived from |
mat |
A matrix or a list of matrices. |
... |
Additional arguments being passed to the function |
spatialwarnings
provides "workflow functions", named *_sews
,
that assist the user in computing, displaying and assessing the
significance of indicator values. The functions create_indicator
and
compute_indicator
provides such workflow for any arbitrary function.
create_indicator
takes a function 'fun' and returns another function
that can be used as an indicator similar to the *_sews
functions. The
results of this function can be assessed for significance using
indictest
and trends can be displayed using
plot
, summary
, etc. (see Examples). compute_indicator
does the same but without needing an intermediate indicator function.
create_indicator
returns a function that can be used in the same way
than the other *_sews
functions (e.g. generic_sews
). This
function as well as compute_indicator
will return
simple_sews_*
objects.
simple_sews
# Use the maximum patch size as indicator of degradation maxpatchsize <- function(mat) { max(patchsizes(mat)) } # Create the indicator function maxpatch_sews <- create_indicator(maxpatchsize) # Then work with this function as if it were a function from the *_sews # family. mp_indic <- maxpatch_sews(forestgap) summary(mp_indic) ## Not run: # Assess significance and display trends mp_test <- indictest(mp_indic, nulln = 49) plot(mp_test) ## End(Not run) # Try spatial coefficient of variation as a spatial EWS. This function can # have arguments. spatial_cv <- function(mat, subsize) { matc <- coarse_grain(mat, subsize) return( sd(matc) / mean(matc) ) } # Create indicator function cv_sews <- create_indicator(spatial_cv) # Compute and display trends cv_indic <- cv_sews(serengeti, subsize = 3) plot(cv_indic, along = serengeti.rain) # We can do the same work in one run using compute_indicator cv_indic2 <- compute_indicator(serengeti, spatial_cv, subsize = 3) plot(cv_indic2, along = serengeti.rain) ## Not run: indictest(cv_indic, nulln = 99) ## End(Not run)
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