Running ‘euclidian-relational-test.R’ [1s/2s]
  Running ‘prediction-test.R’ [2s/2s]
Running the tests in ‘tests/prediction-test.R’ failed.
Complete output:
  > ## Check that predict.somRes works fine
  > # (i.e., predictions are identical to the final clustering for training data)
  > 
  > library(SOMbrero)
  Loading required package: knitr
  Loading required package: igraph
  
  Attaching package: 'igraph'
  
  The following objects are masked from 'package:stats':
  
      decompose, spectrum
  
  The following object is masked from 'package:base':
  
      union
  
  
  ***********************************************************
  
        This is 'SOMbrero' package, v 1.2
  
  Citation details with citation('SOMbrero')
  
  Further information with help(SOMbrero)...
  
  Use sombreroGUI() to start the Graphical Interface.
  
  Warning! This package has been implemented (mostly) by girls.
  Default colors may not be suited for men.
  
  ***********************************************************
  > data(lesmis)
  > data(presidentielles2002)
  > 
  > nsom <- trainSOM(iris[1:30,1:4], maxit=10, scaling= "none")
  > stopifnot(identical(predict(nsom, iris[1:30,1:4]), nsom$clustering))
  > stopifnot(predict(nsom, iris[1,1:4])==nsom$clustering[1])
  > stopifnot(identical(predict(nsom), nsom$clustering))
  > 
  > nsom <- trainSOM(iris[1:30,1:4], maxit=10, scaling= "center")
  > stopifnot(identical(predict(nsom, iris[1:30,1:4]), nsom$clustering))
  > stopifnot(predict(nsom, iris[1,1:4])==nsom$clustering[1])
  > stopifnot(identical(predict(nsom), nsom$clustering))
  > 
  > nsom <- trainSOM(iris[1:30,1:4], maxit=10, scaling= "unitvar")
  > stopifnot(identical(predict(nsom, iris[1:30,1:4]), nsom$clustering))
  > stopifnot(predict(nsom, iris[1,1:4])==nsom$clustering[1])
  > stopifnot(identical(predict(nsom), nsom$clustering))
  > 
  > rsom <- trainSOM(dissim.lesmis, type="relational", maxit=10, scaling= "none")
  > stopifnot(identical(predict(rsom, dissim.lesmis), rsom$clustering))
  > stopifnot(predict(rsom, dissim.lesmis[1,])==rsom$clustering[1])
  > stopifnot(identical(predict(rsom), rsom$clustering))
  > 
  > rsom <- trainSOM(dissim.lesmis, type="relational", maxit=10, 
  +                  radius.type="letremy")
  > stopifnot(identical(predict(rsom, dissim.lesmis), rsom$clustering))
  > stopifnot(predict(rsom, dissim.lesmis[1,])==rsom$clustering[1])
  > stopifnot(identical(predict(rsom), rsom$clustering))
  > 
  > rsom <- trainSOM(dissim.lesmis, type="relational", maxit=10, 
  +                  affectation="heskes")
  > stopifnot(identical(predict(rsom, dissim.lesmis), rsom$clustering))
  > stopifnot(predict(rsom, dissim.lesmis[1,])==rsom$clustering[1])
  > stopifnot(identical(predict(rsom), rsom$clustering))
  > 
  > rsom <- trainSOM(dissim.lesmis, type="relational", maxit=10, 
  +                  affectation="heskes", radius.type="letremy")
  > stopifnot(identical(predict(rsom, dissim.lesmis), rsom$clustering))
  Error: identical(predict(rsom, dissim.lesmis), rsom$clustering) is not TRUE
  Execution halted