Methods for ISDMmetrics Objects

Objects of class ISDMmetrics are returned by compute_metrics. These methods provide structured ways to view, summarize and manipulate the evaluation results.

get_background is a helper function to extract the BackgroundPoints object from an ISDMmetrics object.

Usage

# S3 method for class 'ISDMmetrics'
as.data.frame(x, ...)

# S3 method for class 'ISDMmetrics'
print(x, ...)

# S3 method for class 'ISDMmetrics'
summary(object, ...)

# S3 method for class 'ISDMmetrics'
plot(x, include_composite = TRUE, ...)

# S3 method for class 'ISDMmetrics'
x[...]

get_background(x)

Arguments

x

An object of class ISDMmetrics.

...

Additional arguments passed on to the method.

object

An object of class ISDMmetrics.

include_composite

Logical. Should the weighted composite scores be included in the plot? Defaults to TRUE.

Value

• as.data.frame: Returns a tidy data.frame in long format.

• print: Invisibly returns the original object.

• summary: Invisibly returns NULL.

• plot: Returns a ggplot2 object.

• [: Returns a subset of ISDMmetrics object.

The BackgroundPoints object if present, otherwise NULL.

See also

Other ISDM evaluation methods: compute_metrics()

Examples

if (FALSE) { # \dontrun{
#--- Compute metrics for an Integrated SDM
# This object will contain metrics for e.g., Presence-only and Count data
eval_results <- compute_metrics(
  test_data = test_data,
  prob_raster = suitability_raster,
  expected_response = expected_raster,
  n_background = 1000,
  metrics = c("rmse", "mae", "auc", "tss"),
  is_pred_rate = TRUE, # model with offset
  exposure = "area" # standardized exposure name across the counts data
)

#--- Quick view of the results
print(eval_results)

#--- Generate a full replication report
# summary.ISDMmetrics shows seeds, threshold logic, and prediction type
summary(eval_results)

#--- Visual comparison of metrics
plot(eval_results, include_composite = TRUE)

#--- Background visualization (for Presence-Only data)
bg_data <- get_background(eval_results)
if (!is.null(bg_data)) {
  plot(bg_data)
}

#--- Export to tabular format for external reports
results_df <- as.data.frame(eval_results)
head(results_df)

#--- Subset specific metrics for custom analysis
auc_only <- eval_results[grep("AUC", names(eval_results))]
} # }