A data frame characterizing the set wherein predecessors/successors are searched.
p
A preference. Worse tuples in the induced order are successors and better tuples are predecessors.
v
A numeric vector of indices in df. This represents the set of tuples for which predecessors/successors are searched.
intersect
Logical value. If it is FALSE (by default) the union of all predecessors/successors of v is returned.
For intersect = TRUE the intersection of those values is returned.
Details
These functions return the predecessors and successors in the Better-Than-Graph of a preference.
Note that the successors/predecessors can can be plotted via get_btg.
Before any of the successor/predecessor functions can be used the initialization has to be called as follows:
init_pred_succ(p, df)
There p is a preference object and df a data frame.
This statement calculates the Better-Than-Relation on df w.r.t. p.
Afterwards the subsequent predecessor and successor functions can be called.
The value of v is a numeric vector within 1:nrow(df)
and characterizes a subset of tuples in df.
The return value of these functions is again a numeric vector referring to the row numbers in df
and it is always ordered ascending, independently of the order of the indices in v.
all_pred(p, v)
Returns all predecessors of v, i.e., indices of better tuples than v.
all_succ(p, v)
Returns all successors of v, i.e., indices of worse tuples than v.
hasse_pred(p, v)
Returns the direct predecessors of v,
i.e., indices of better tuples than v where the better-than-relation is contained in the transitive reduction.
hasse_succ(p, v)
Returns the direct successors of v,
i.e., indices of worse tuples than v where the better-than-relation is contained in the transitive reduction.
If v has length 1, then the value of intersect does not matter, as there is nothing to intersect or join.
For scalar values x and y the following identities hold, where f is one of the predecessor/successor functions:
# preference on mtcars for high mpg and low weight
p <- high(mpg) * low(wt)
init_pred_succ(mtcars, p)
# helper to show mpg/hp values
show_vals <- function(x) mtcars[x,c('mpg','wt')]
# pick some tuple "in the middle"
show_vals(10)
# show (direct) predecessors/successors of tuple 10
show_vals(hasse_pred(p, 10)) # Next better car
show_vals(hasse_succ(p, 10)) # Next worse car
show_vals(all_pred(p, 10)) # All better cars
show_vals(all_succ(p, 10)) # All worse cars
providing 
.