Various utilities to neaten word objects by removing fixed elements
Object of class
trim() takes a
word and, starting from the right,
strips off columns corresponding to fixed elements until it finds a
non-fixed element. This makes no sense for
cycle objects; if
x is of class
cycle, an error is returned.
tidy() is more aggressive. This firstly removes
all fixed elements, then renames the non-fixed ones to match the
new column numbers. The map is an isomorphism (sic) with respect to
Returns an object of class
Results in empty (that is, zero-column) words if a vector of identity permutations is given
Robin K. S. Hankin
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tidy(as.cycle(5:3)+as.cycle(7:9)) as.cycle(tidy(c(as.cycle(1:2),as.cycle(6:7)))) nicify_cyclist(list(c(4,6), c(7), c(2,5,1), c(8,3))) data(megaminx) tidy(megaminx) # has 120 columns, not 129 stopifnot(all(unique(sort(unlist(as.cycle(tidy(megaminx)),recursive=TRUE)))==1:120)) jj <- megaminx*megaminx stopifnot(identical(shape(jj),shape(tidy(jj)))) #tidy() does not change shape
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