CRAN Package Check Results for Package liayson

Last updated on 2019-04-13 01:58:08 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.1 18.44 196.79 215.23 ERROR
r-devel-linux-x86_64-debian-gcc 1.0.1 16.21 154.12 170.33 ERROR
r-devel-linux-x86_64-fedora-clang 1.0.1 258.42 ERROR
r-devel-linux-x86_64-fedora-gcc 1.0.1 246.63 ERROR
r-devel-windows-ix86+x86_64 1.0.1 49.00 287.00 336.00 ERROR
r-patched-linux-x86_64 1.0.1 17.13 192.48 209.61 ERROR
r-patched-solaris-x86 1.0.1 401.80 ERROR
r-release-linux-x86_64 1.0.1 12.51 188.72 201.23 OK
r-release-windows-ix86+x86_64 1.0.1 32.00 203.00 235.00 OK
r-release-osx-x86_64 1.0.1 OK
r-oldrel-windows-ix86+x86_64 1.0.1 20.00 244.00 264.00 OK
r-oldrel-osx-x86_64 1.0.1 OK

Check Details

Version: 1.0.1
Check: examples
Result: ERROR
    Running examples in 'liayson-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: clusterCells
    > ### Title: Grouping cells into clones.
    > ### Aliases: clusterCells
    >
    > ### ** Examples
    >
    > data(cnps)
    > set.seed(2)
    > rcells = sample(colnames(cnps), 120)
    > outc = clusterCells(cnps[apply(cnps, 1, var)>0, rcells])
    [1] "Neither k nor h is set."
    [1] "Using Akaike information criterion to decide number of clusters..."
    Error in kmeans(t(cnps), centers = x) :
     more cluster centers than distinct data points.
    Calls: clusterCells ... sapply -> lapply -> FUN -> .kmeansAIC -> ncol -> kmeans
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64

Version: 1.0.1
Check: examples
Result: ERROR
    Running examples in ‘liayson-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: clusterCells
    > ### Title: Grouping cells into clones.
    > ### Aliases: clusterCells
    >
    > ### ** Examples
    >
    > data(cnps)
    > set.seed(2)
    > rcells = sample(colnames(cnps), 120)
    > outc = clusterCells(cnps[apply(cnps, 1, var)>0, rcells])
    [1] "Neither k nor h is set."
    [1] "Using Akaike information criterion to decide number of clusters..."
    Error in kmeans(t(cnps), centers = x) :
     more cluster centers than distinct data points.
    Calls: clusterCells ... sapply -> lapply -> FUN -> .kmeansAIC -> ncol -> kmeans
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-solaris-x86