tests/testthat/test-classify_kmeans.R

In musclesyneRgies: Extract Muscle Synergies from Electromyography

test_that("k-means classification is robust", {
  data("SYNS")

  for (tt in 1:5) {
    SYNS_classified <- musclesyneRgies::classify_kmeans(SYNS)
    ranks <- unique(
      unlist(
        lapply(
          SYNS_classified, function(x) {
            syns <- colnames(x$M)
            if (any(grepl("Syncombined", syns))) syns <- syns[-grep("Syncombined", syns)]
            return(max(as.numeric(gsub("Syn", "", syns))))
          }
        )
      )
    )
    expect_length(unique(ranks), 1)
    expect_equal(unique(ranks), 4)
  }

# Check for same amount of normalisation points
rnd_trial <- sample(seq_len(length(SYNS)), size = 1)
SYNS_err <- SYNS
SYNS_err[[rnd_trial]]$P <- SYNS_err[[rnd_trial]]$P[-which(SYNS_err[[rnd_trial]]$P$time > 150), ]
expect_error(musclesyneRgies::classify_kmeans(SYNS_err))

# Check for same amount of muscles
rnd_trial <- sample(seq_len(length(SYNS)), size = 1)
SYNS_err <- SYNS
SYNS_err[[rnd_trial]]$P$MA <- NULL
SYNS_err[[rnd_trial]]$M <- SYNS_err[[rnd_trial]]$M[-grep("MA", rownames(SYNS_err[[rnd_trial]]$M)), ]
expect_error(musclesyneRgies::classify_kmeans(SYNS_err))

})