## Example 0: melt iris data with literal alternatives -> chr columns.
ichr <- nc::capture_melt_single(
iris[1,],
part="Sepal|Petal",
"[.]",
dim="Length|Width")
factor(ichr$part)#default factor levels are alphabetical.
## Example 1: melt iris data with alevels() -> factor columns.
(ifac <- nc::capture_melt_single(
iris[1,],
part=nc::alevels("Sepal","Petal"),
"[.]",
dim=nc::alevels("Length","Width")))
ifac$part #factor with levels in same order as given in alevels().
## Example 2: alevels(literals_to_match="levels_to_use_in_output").
tv_wide <- data.frame(
id=0,
train.classif.logloss = 1, train.classif.ce = 2,
valid.classif.logloss = 3, valid.classif.ce = 4)
nc::capture_melt_single(
tv_wide,
set=nc::alevels(valid="validation", train="subtrain"),
"[.]classif[.]",
measure=nc::alevels(ce="error_prop", auc="AUC", "logloss"))
## Example 3: additional groups which output character columns.
nc::capture_melt_single(
tv_wide,
set_chr=list(set_fac=nc::alevels(valid="validation", train="subtrain")),
"[.]classif[.]",
measure_chr=list(measure_fac=nc::alevels(ce="error_prop", auc="AUC", "logloss")))
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