Get the cluster map object
Source:R/all_generic.R
, R/cluster_array.R
, R/cluster_experiment.R
clusters-methods.Rd
Get the cluster map object
Get the clusters object via generic
Usage
clusters(x, ...)
# S4 method for class 'H5ParcellatedArray'
clusters(x)
# S4 method for class 'H5ParcellatedMultiScan'
clusters(x)
See also
Other H5Parcellated:
$,H5ParcellatedMultiScan-method
,
H5ParcellatedArray-class
,
H5ParcellatedMultiScan
,
H5ParcellatedScan-class
,
H5ParcellatedScanSummary-class
,
close()
,
cluster_metadata,H5ParcellatedMultiScan-method
,
h5file,H5ParcellatedArray-method
,
mask()
,
matrix_concat()
,
n_scans,H5ParcellatedMultiScan-method
,
scan_metadata,H5ParcellatedMultiScan-method
,
scan_names,H5ParcellatedMultiScan-method
,
series_concat()
Examples
if (FALSE) { # \dontrun{
# For H5ParcellatedMultiScan:
if (!is.null(fmristore:::create_minimal_h5_for_H5ParcellatedMultiScan)) {
temp_exp_file <- NULL
exp_obj <- NULL
tryCatch({
temp_exp_file <- fmristore:::create_minimal_h5_for_H5ParcellatedMultiScan(
master_mask_dims = c(4L,4L,3L),
num_master_clusters = 2L
)
exp_obj <- fmristore::H5ParcellatedMultiScan(file_path = temp_exp_file)
# Get the master cluster map from the experiment
cluster_vol <- clusters(exp_obj)
print(cluster_vol)
# if (requireNamespace("neuroim2", quietly=TRUE)) print(is(cluster_vol, "ClusteredNeuroVol"))
# Individual runs also have cluster information, potentially accessible via their own methods
# run1 <- runs(exp_obj)[["Run1_Full"]]
# run1_clusters <- clusters(run1) # Assuming a method for H5ParcellatedScan
# print(run1_clusters)
}, error = function(e) {
message("clusters example for H5ParcellatedMultiScan failed: ", e$message)
}, finally = {
if (!is.null(exp_obj)) try(close(exp_obj), silent = TRUE)
if (!is.null(temp_exp_file) && file.exists(temp_exp_file)) {
unlink(temp_exp_file)
}
})
} else {
message("Skipping clusters example for H5ParcellatedMultiScan: helper not available.")
}
} # }