Supply datasets:

atmospheres: Bclust, Hclust.match, Plot.phylocl, Updist
dolbli: Coml, Infill
drosera: Pleiad
eq, eq_l, eq_s: Boxplots, K
hwc, hwc2, hwc3: pairwise.Eff
moldino: Bclabels, Jclust, PlotBest.mdist
salix_leaves: Missing.map
distances.nts from example(Read.tri.nts): probably, create file like in example(Read.fasta)

MRH() to make two MRPs (by k's and by h's) plus MRC (cophenetic); handle 'phylo' with ape::chronos()

Classif2tree(): 2 var (num_rank + taxon_id) df, then factor(num_rank), dif, if dif = 0, make comma
(or parenthesis if delinearise); if > 0, then open parenthesis and remember rank and name in stack;
if < 0, closing parenthesis, times equal to reach dif, then add colon and name from stack equal to next rank.

Also Rank2num() to assist in convesion characters into numbers: use English and Latin, lowercase, remove non-letters,
RecodeR4() and stop with report if not entirely converted.

Key2tree() to use standardized key, df with this_id, char and next_id columns. Probably, could be converted to dendrogramm.

Fill() to fill down empty values (see examples)

===

Tree2classif(): e.g., cut based on numerous h, then find peaks; on bootstrap with Bclust(Hcl2mat())

Misstats() to take Misclass() output and print it like Misclass() replacing "0" with "-";
to print also 'binom.test(sum(diag(x)), sum(x))$conf.int' and 'mcnemar.test(x)$p.value',

BestMisclass() -- similar but mODuch simpler then BestOverlap(), good for "whibo"

Misplot() based on Dotchart3() with CIs and double obs/pred labels

Life(): decrease borders in image()

Check how alternatives of shipunov::pairwise.Table2.test() and shipunov::Rro.test() work
and change help files accordingly

Try parallel::mclapply() for BestOverlap()

Life(): try to add interactive filling with locator() like in Miney()

Dotchart1(): send this as dotchart() correction to R base

Gap.code(): try to optimize more; possible alternative: rle() each sequence, then extract pos/len of gaps and match
(and check inclusions) sequence gaps in the union of all gaps

Re-structure Boot...() functions to use Class.sample() and Misclass() (their reduced versions are using internally)

Think how extract 'clipper' and adjacent polygon functions from PBSmapping:: sources and make them work from within
shiopunov::; however, in that case Windows distribution will become more complicated
