R Under development (unstable) (2025-11-24 r89059 ucrt) -- "Unsuffered Consequences"
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> 
> ### ceeboo 2015
> 
> library("arulesSequences")
Loading required package: arules
Loading required package: Matrix

Attaching package: 'arules'

The following objects are masked from 'package:base':

    abbreviate, write


Attaching package: 'arulesSequences'

The following object is masked from 'package:arules':

    itemsets

> 
> ## use example
> data(zaki)
> ## IGNORE_RDIFF_BEGIN
> s7 <- cspade(zaki, parameter = list(support = .25), 
+ 	           control   = list(verbose = TRUE, tidLists = TRUE))

parameter specification:
support : 0.25
maxsize :   10
maxlen  :   10

algorithmic control:
bfstype  : FALSE
verbose  :  TRUE
summary  : FALSE
tidLists :  TRUE

preprocessing ... 1 partition(s), 0 MB [0.02s]
mining transactions ... 0.12 MB [0.04s]
reading sequences ... [0.69s]

total elapsed time: 0.75s
> ## IGNORE_RDIFF_END
> 
> ## IGNORE_RDIFF_BEGIN
> k <- support(s7, zaki, control = list(verbose = TRUE))
preprocessing ... [0.02s]
> ## IGNORE_RDIFF_END
> table(size(s7), sign(quality(s7)$support - k))
   
       0
  1   31
  2  328
  3 1353
  4 2205
> 
> ## random atomic sequences
> ## <FIXME>
> ## Remove eventually.
> suppressWarnings(RNGversion("3.5.0"))
> ## </FIXME>
> set.seed(20150921)
> 
> f <- tempfile()
> local({
+ n <- 1000
+ l <- 30
+ k <- 5
+ 
+ s <- lapply(sample(1:l, n, TRUE), function(x)
+        sample(1:k, x, TRUE)
+ )
+ 
+ m <- sapply(s, length)
+ s <- cbind(
+     rep(1:n, m),
+     unlist(lapply(m, seq)),
+     unlist(s)
+ )
+ 
+ write.table(s, file = f, row.names = FALSE, col.names = FALSE)
+ })
> 
> ## use generated data
> t <- read_baskets(con  = f,
+                   info = c("sequenceID", "eventID"))
> unlink(f)
> 
> ## use low support
> ## IGNORE_RDIFF_BEGIN
> s1 <- cspade(t, parameter = list(support = .17), 
+                 control   = list(verbose = TRUE))

parameter specification:
support : 0.17
maxsize :   10
maxlen  :   10

algorithmic control:
bfstype  : FALSE
verbose  :  TRUE
summary  : FALSE
tidLists : FALSE

preprocessing ... 1 partition(s), 0.35 MB [0.04s]
mining transactions ... 0.31 MB [0.25s]
reading sequences ... [1.8s]

total elapsed time: 2.11s
> ## IGNORE_RDIFF_END
> summary(s1)
set of 8616 sequences with

most frequent items:
      2       3       4       1       5 (Other) 
   6594    6354    6171    5582    5352       0 

most frequent elements:
    {2}     {3}     {4}     {1}     {5} (Other) 
   6594    6354    6171    5582    5352       0 

element (sequence) size distribution:
sizes
   1    2    3    4    5    6 
   5   25  125  625 3125 4711 

sequence length distribution:
lengths
   1    2    3    4    5    6 
   5   25  125  625 3125 4711 

summary of quality measures:
    support      
 Min.   :0.1700  
 1st Qu.:0.1740  
 Median :0.1820  
 Mean   :0.2301  
 3rd Qu.:0.2660  
 Max.   :0.8790  

includes transaction ID lists: FALSE 

mining info:
 data ntransactions nsequences support
    t         15391       1000    0.17
> 
> ##
> ## IGNORE_RDIFF_BEGIN
> k <- support(s1, t, control = list(verbose = TRUE))
preprocessing ... [0.01s]
> ## IGNORE_RDIFF_END
> table(size(s1), sign(quality(s1)$support - k))
   
       0
  1    5
  2   25
  3  125
  4  625
  5 3125
  6 4711
> 
> ## internal
> ## IGNORE_RDIFF_BEGIN
> stopifnot(all.equal(
+     .Call(arulesSequences:::R_pnscount, s1@data, s1@data, 
+ 	  s1@elements@items@data, FALSE),
+     .Call(arulesSequences:::R_pnscount, s1@data, s1@data, NULL, TRUE)
+ ))
> ## IGNORE_RDIFF_END
> 
> ## IGNORE_RDIFF_BEGIN
> stopifnot(all.equal(
+     .Call(arulesSequences:::R_pnsclosed, s1@data,
+ 	  s1@elements@items@data, rep(1L, length(s1)), TRUE),
+     is.maximal(s1)
+ ))
> ## IGNORE_RDIFF_END
> 
> 
> ## IGNORE_RDIFF_BEGIN
> stopifnot(all.equal(
+     .Call(arulesSequences:::R_pnsredundant, s1@data,
+ 	  s1@elements@items@data, rep(1L, length(s1)), TRUE),
+     size(s1) > 1L
+ ))
> ## IGNORE_RDIFF_END
> 
> warnings()
> ###
> 
> 
> proc.time()
   user  system elapsed 
   4.79    0.26    5.31