alesantuz / musclesynergies Goto Github PK

> SYNS_classified <- lapply(RAW_DATA, filtEMG) |>
+     lapply(function(x) normEMG(x, cycle_div = c(100, 100))) |>
+     lapply(synsNMF) |>
+     classify_kmeans()
Error in if (stats::sd(points) != 0) { : 
  missing value where TRUE/FALSE needed

> goodpractice::gp("musclesyneRgies")
[....]

It is good practice to

  ✖ write unit tests for all functions, and all package code in
    general. 72% of code lines are covered by test cases.

    R/classify_kmeans.R:56:NA
    R/classify_kmeans.R:57:NA
    R/classify_kmeans.R:58:NA
    R/classify_kmeans.R:59:NA
    R/classify_kmeans.R:67:NA
    ... and 340 more lines

  ✖ write short and simple functions. These functions have high
    cyclomatic complexity:classify_kmeans (103).
  ✖ avoid long code lines, it is bad for readability. Also,
    many people prefer editor windows that are about 80 characters
    wide. Try make your lines shorter than 80 characters

    R/classify_kmeans.R:4:1
    R/classify_kmeans.R:5:1
    R/classify_kmeans.R:6:1
    R/classify_kmeans.R:9:1
    R/classify_kmeans.R:10:1
    ... and 173 more lines

  ✖ avoid 1:length(...), 1:nrow(...), 1:ncol(...), 1:NROW(...)
    and 1:NCOL(...) expressions. They are error prone and result 1:0 if
    the expression on the right hand side is zero. Use seq_len() or
    seq_along() instead.

    R/classify_kmeans.R:226:16
    R/classify_kmeans.R:318:37
    R/classify_kmeans.R:319:37
    R/classify_kmeans.R:353:15
    R/classify_kmeans.R:404:48
    ... and 10 more lines

  ✖ avoid 'T' and 'F', as they are just variables which are set
    to the logicals 'TRUE' and 'FALSE' by default, but are not reserved
    words and hence can be overwritten by the user.  Hence, one should
    always use 'TRUE' and 'FALSE' for the logicals.

    R/classify_kmeans.R:NA:NA
    R/classify_kmeans.R:NA:NA
    R/classify_kmeans.R:NA:NA
    R/classify_kmeans.R:NA:NA
    R/classify_kmeans.R:NA:NA
    ... and 5 more lines