CRAN Package Check Results for Package msgl

Last updated on 2014-10-20 23:47:06.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2.0.125.0 16.22 83.78 99.99 NOTE
r-devel-linux-x86_64-debian-gcc 2.0.125.0 18.48 79.23 97.70 OK
r-devel-linux-x86_64-fedora-clang 2.0.125.0 224.62 NOTE
r-devel-linux-x86_64-fedora-gcc 2.0.125.0 217.15 OK
r-devel-osx-x86_64-clang 2.0.125.0 185.21 NOTE
r-devel-windows-ix86+x86_64 2.0.125.0 51.00 187.00 238.00 NOTE
r-patched-linux-x86_64 2.0.125.0 18.98 82.70 101.68 OK
r-patched-solaris-sparc 2.0.125.0 1418.40 OK
r-patched-solaris-x86 2.0.125.0 255.10 ERROR
r-release-linux-ix86 2.0.125.0 23.67 107.02 130.69 OK
r-release-linux-x86_64 2.0.125.0 18.63 80.72 99.35 OK
r-release-osx-x86_64-mavericks 2.0.125.0 OK
r-release-osx-x86_64-snowleopard 2.0.125.0 OK
r-release-windows-ix86+x86_64 2.0.125.0 46.00 203.00 249.00 OK
r-oldrel-windows-ix86+x86_64 2.0.125.0 48.00 196.00 244.00 OK

Check Details

Version: 2.0.125.0
Check: R code for possible problems
Result: NOTE
    SglOptim warning: openmp (multithreading) not supported on this system
    NOTE : openMP (multithreading) is not supported on this system
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-fedora-clang, r-devel-osx-x86_64-clang

Version: 2.0.125.0
Check: R code for possible problems
Result: NOTE
    SglOptim warning: compiled with debugging on -- this may slow down the runtime of the sgl routines
    WARNING : debugging is turned on -- this may increase the runtime
Flavor: r-devel-windows-ix86+x86_64

Version: 2.0.125.0
Check: examples
Result: ERROR
    Running examples in ‘msgl-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: print.msgl
    > ### Title: Print function for msgl
    > ### Aliases: print.msgl
    >
    > ### ** Examples
    >
    > data(SimData)
    > x <- sim.data$x
    > classes <- sim.data$classes
    >
    > ### Estimation
    > lambda <- msgl.lambda.seq(x, classes, alpha = .5, d = 50, lambda.min = 0.05)
    > fit <- msgl(x, classes, alpha = .5, lambda = lambda)
    
    Running msgl (sparse design matrix)
    
     Samples: Features: Classes: Groups: Parameters:
     100 401 10 401 4010
    
    0 %
    |----|----|----|----|----|----|----|----|----|----|
    **************************************************|
    |
    >
    > # Print some information about the estimated models
    > fit
    
    Call:
    msgl(x = x, classes = classes, alpha = 0.5, lambda = lambda)
    
    Models:
    
     Index: Lambda: Features: Parameters:
     10 0.082 4 23
     20 0.072 11 57
     30 0.064 15 82
     40 0.057 21 117
     50 0.050 24 141
    
    >
    > ### Cross validation
    > fit.cv <- msgl.cv(x, classes, alpha = .5, lambda = lambda)
    Running msgl 10 fold cross validation (dense design matrix)
    
     Samples: Features: Classes: Groups: Parameters:
     100 401 10 401 4010
    
    0 %
    |----|----|----|----|----|----|----|----|----|----|
    **************************************************|
    Warning: stack imbalance in '.Call', 36 then 41
    Warning: stack imbalance in '<-', 34 then 39
    >
    > # Print some information
    > fit.cv
    
    Call:
    msgl.cv(x = x, classes = classes, alpha = 0.5, lambda = lambda)
    
    Models:
    
     Index: Lambda: Features: Parameters: Error:
     10 0.082 4 23 0.78
     20 0.072 10 55 0.54
     30 0.064 16 87 0.40
     40 0.057 20 113 0.33
     50 0.050 25 144 0.29
    
    Best model:
    
     Index: Lambda: Features: Parameters: Error:
     50 0.05 25 144 0.29
    
    >
    > ### Subsampling
    > test <- list(1:20, 21:40)
    > train <- lapply(test, function(s) (1:length(classes))[-s])
    >
    > lambda <- msgl.lambda.seq(x, classes, alpha = .5, d = 50, lambda.min = 0.05)
    > fit.sub <- msgl.subsampling(x, classes, alpha = .5, lambda = lambda, training = train, test = test)
    Running msgl subsampling with 2 subsamples (dense design matrix)
    
     Samples: Features: Classes: Groups: Parameters:
     100 401 10 401 4010
    
    0 %
    |----|----|----|----|----|----|----|----|----|----|
    **************************************************|
    >
    > # Print some information
    > fit.sub
    
    Call:
    msgl.subsampling(x = x, classes = classes, alpha = 0.5, lambda = lambda,
     training = train, test = test)
    
    Best models:
    
     Subsample: Model index: Lambda: Features: Parameters: Error:
     1 41 0.056 13 72 0.5
     2 46 0.053 13 67 0.4
    
    >
    >
    >
    > ### * <FOOTER>
    > ###
    > options(digits = 7L)
    > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
    Time elapsed: 74.461 16.899 48.087 0 0
    > grDevices::dev.off()
    null device
     1
    > ###
    > ### Local variables: ***
    > ### mode: outline-minor ***
    > ### outline-regexp: "\\(> \\)?### [*]+" ***
    > ### End: ***
    > quit('no')
    
     *** caught segfault ***
    address 4, cause 'memory not mapped'
    
    Traceback:
     1: quit("no")
    aborting ...
Flavor: r-patched-solaris-x86