This function performs thinning of spatial points by rounding their coordinates to a specified precision and removing duplicates. It can perform multiple trials of this process and return the results for all or just the best trial.
Usage
precision_thinning(
coordinates,
precision = 4,
trials = 10,
all_trials = FALSE,
priority = NULL
)Arguments
- coordinates
A numeric matrix or data frame with two columns representing the longitude and latitude of points.
- precision
A positive integer specifying the number of decimal places to which coordinates should be rounded. Default is 4.
- trials
A positive integer specifying the number of thinning trials to perform. Default is 10.
- all_trials
A logical value indicating whether to return results for all trials (`TRUE`) or just the first/best trial (`FALSE`). Default is `FALSE`.
- priority
A numeric vector of the same length as the number of points, specifying a priority weight for each point. Higher values indicate higher importance and are favored when selecting which points to retain. Priority is used to guide selection when multiple candidate points are otherwise equally valid (e.g., points in the same grid cell, with the same rounded coordinates, or with the same number of neighbors).
Value
If `all_trials` is `FALSE`, returns a logical vector indicating which points were kept in the first trial. If `all_trials` is `TRUE`, returns a list of logical vectors, one for each trial.
Details
The function performs multiple trials to account for randomness in the order of point selection. By default, it returns the first trial, but setting `all_trials = TRUE` will return the results of all trials.
Examples
# Example usage
coords <- matrix(c(-123.3656, 48.4284, -123.3657, 48.4285, -123.3658, 48.4286), ncol = 2)
result <- precision_thinning(coords, precision = 3, trials = 5, all_trials = TRUE)
print(result)
#> [[1]]
#> [1] TRUE TRUE TRUE
#>
#> [[2]]
#> [1] TRUE TRUE TRUE
#>
#> [[3]]
#> [1] TRUE TRUE TRUE
#>
#> [[4]]
#> [1] TRUE TRUE TRUE
#>
#> [[5]]
#> [1] TRUE TRUE TRUE
#>
# Example with a single trial and lower precision
result_single <- precision_thinning(coords, precision = 2, trials = 1, all_trials = FALSE)
print(result_single)
#> [[1]]
#> [1] TRUE TRUE FALSE
#>