euclidean_linker {Bioi} | R Documentation |
Group PALM/iPALM localizations based on their physical separation distance
euclidean_linker( input, critDist, use_prog_bar = TRUE, run_parallel = FALSE, num_cores = NULL, partition_req = 5000, parallel_call_depth = 3, ... )
input |
A numeric matrix where each row is a localization and each column is a spatial axis. |
critDist |
The critical distance for which localizations nearer than this distance are deemed part of the same group. |
use_prog_bar |
TRUE/FALSE indicating whether a progress bar should be used. This is only available when run_parallel is FALSE. |
run_parallel |
TRUE/FALSE indicating whether operations should be performed in parallel. This is only valid if partitioning is performed. |
num_cores |
The number of cores to use if running in parallel. |
partition_req |
The minimum number of points required to create a new partition. |
parallel_call_depth |
The number of levels of partitioning that should be performed before terminating calls to run operations in parallel. The number of threads opened when running in parallel is equal to 2^(parallel_call_depth)*num_cores. |
... |
Additional parameters passed to euclidean_linker (i.e. finding_blobs). |
PALM/iPALM data results in a list of spatial coordinates for fluorophore localizations. This function groups nearby localizations if they are within the provided critical distance from each other.
Zach Colburn
# Generate random data. #set.seed(10) #input <- as.matrix(data.frame(x=rnorm(10),y=rnorm(10))) # Perform linking. #euclidean_linker(input, 0.4)