Description Usage Arguments Details Author(s)
Group PALM/iPALM localizations based on their physical separation distance
1 2 3 4 5 6 7 8 9 10 | .perform_partitioning(
input,
critDist,
use_prog_bar = TRUE,
run_parallel = FALSE,
num_cores = NULL,
partition_req = 5000,
parallel_call_depth = 3,
min_gap = NULL
)
|
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. |
min_gap |
The minimum width of any dimension created during partitioning. |
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
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