Gesmann, Markus
2005-Mar-08 11:29 UTC
[R] To convert an adjacency list model into a nested set model
Dear R-help
I am wondering if somebody wrote some code to convert an adjacency list
model into a nested set model.
In principal I want to do the same as John Celko mentioned it here with
SQL:
http://groups.google.co.uk/groups?hl=en&lr=lang_en&selm=8j0n05%24n31%241
%40nnrp1.deja.com
Assume you have a tree structure like this
Albert
/ \
/ \
Bert Chuck
/ | \
/ | \
/ | \
/ | \
Donna Eddie Fred
in an adjacency list model:
> emp=c("Albert", "Bert", "Chuck",
"Donna", "Eddie", "Fred")
> boss=c(NA, "Albert", "Albert", "Chuck",
"Chuck", "Chuck")
> print(Personnel<-data.frame(emp, boss))
emp boss
1 Albert <NA>
2 Bert Albert
3 Chuck Albert
4 Donna Chuck
5 Eddie Chuck
6 Fred Chuck
Then it is quite hard to find the all the supervisors of one employee.
John's suggestion is to convert the adjacency list model into a nested
set model.
The organizational chart would look like this as a directed graph:
Albert (1,12)
/ \
/ \
Bert (2,3) Chuck (4,11)
/ | \
/ | \
/ | \
/ | \
Donna (5,6) Eddie (7,8) Fred (9,10)
The data is than stored in the following form:
> lft=c(1,2,4,5,7,9)
> rgt=c(12,3,11,6,8,10)
> print(Per<-data.frame(emp, lft, rgt))
emp lft rgt
1 Albert 1 12
2 Bert 2 3
3 Chuck 4 11
4 Donna 5 6
5 Eddie 7 8
6 Fred 9 10
To find now the supervisor of an employee all you have to do is to look
where the employees lft figure is between lft and rgt. The supervisors
of Eddie are therefore> subset(Per, lft < 7 & rgt > 7)
emp lft rgt
1 Albert 1 12
3 Chuck 4 11
In the site mentioned above John provides also some code to transform a
adjacency list model into a nested set model.
Does somebody know if there is already a package for this in R?
Kind Regards
Markus Gesmann
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Gabor Grothendieck
2005-Mar-08 17:19 UTC
[R] To convert an adjacency list model into a nested set model
Gesmann, Markus <Markus.Gesmann <at> lloyds.com> writes:
:
: Dear R-help
:
: I am wondering if somebody wrote some code to convert an adjacency list
: model into a nested set model.
: In principal I want to do the same as John Celko mentioned it here with
: SQL:
:
http://groups.google.co.uk/groups?hl=en&lr=lang_en&selm=8j0n05%24n31%241
: %40nnrp1.deja.com
:
: Assume you have a tree structure like this
: Albert
: / \
: / \
: Bert Chuck
: / | \
: / | \
: / | \
: / | \
: Donna Eddie Fred
:
: in an adjacency list model:
:
: > emp=c("Albert", "Bert", "Chuck",
"Donna", "Eddie", "Fred")
: > boss=c(NA, "Albert", "Albert", "Chuck",
"Chuck", "Chuck")
: > print(Personnel<-data.frame(emp, boss))
: emp boss
: 1 Albert <NA>
: 2 Bert Albert
: 3 Chuck Albert
: 4 Donna Chuck
: 5 Eddie Chuck
: 6 Fred Chuck
:
: Then it is quite hard to find the all the supervisors of one employee.
: John's suggestion is to convert the adjacency list model into a nested
: set model.
: The organizational chart would look like this as a directed graph:
:
: Albert (1,12)
: / \
: / \
: Bert (2,3) Chuck (4,11)
: / | \
: / | \
: / | \
: / | \
: Donna (5,6) Eddie (7,8) Fred (9,10)
:
: The data is than stored in the following form:
:
: > lft=c(1,2,4,5,7,9)
: > rgt=c(12,3,11,6,8,10)
: > print(Per<-data.frame(emp, lft, rgt))
: emp lft rgt
: 1 Albert 1 12
: 2 Bert 2 3
: 3 Chuck 4 11
: 4 Donna 5 6
: 5 Eddie 7 8
: 6 Fred 9 10
:
: To find now the supervisor of an employee all you have to do is to look
: where the employees lft figure is between lft and rgt. The supervisors
: of Eddie are therefore
: > subset(Per, lft < 7 & rgt > 7)
: emp lft rgt
: 1 Albert 1 12
: 3 Chuck 4 11
:
: In the site mentioned above John provides also some code to transform a
: adjacency list model into a nested set model.
: Does somebody know if there is already a package for this in R?
:
: Kind Regards
:
: Markus Gesmann
:
This is not a direct answer to getting a nesting from an adjacency
but the following is easy to do and gives all the same info.
Note that if A is the adjacency matrix of children (rows) and ]
parents (columns) then A^n is the matrix defining ancestors n
generations away and exp(A) is a weighted version of that with
A^i weighted by i! (These expressions are mathematics, not R.)
Thus:
empf <- factor(emp, level = union(emp, boss)) # emp as factor
bossf <- factor(boss, level = union(emp, boss)) # ditto for boss
adj <- table(empf, bossf) # i,j is 1 if j is boss of i
library(rmutil) # http://popgen.unimaas.nl/~jlindsey/rcode.html
mexp(adj, type = "series") - diag(length(empf))
giving a matrix whose i,j-th entry is 1/n! if j is n-generations above
i.>From that you can get the info you need.