Builds the per-visit metric matrix and wraps it as an
MSKLongitudinalTracker (its activation_series), so
PhysioMSKNet's mskMinimalDetectableChange() and
mskRecoveryTrajectoryFit() can consume the container output directly
(metrics play the role of "muscles", visits the role of timepoints).
Arguments
- long
A
PhysioLongitudinal.- metric_fn, metric_name
As in
changeScores.
Examples
mk <- function(m) PhysioExperiment(
S4Vectors::SimpleList(raw = matrix(m, 10, 2)), samplingRate = 100)
pl <- PhysioLongitudinal(baseline = mk(1), mid = mk(2), discharge = mk(3))
tr <- asMSKTracker(pl, function(e) mean(SummarizedExperiment::assay(e, "raw")))
dim(tr$activation_series)
#> [1] 1 3