CRAN Package Check Results for Package rabhit

Last updated on 2020-07-06 19:49:26 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.4 19.93 171.06 190.99 ERROR
r-devel-linux-x86_64-debian-gcc 0.1.4 15.28 122.59 137.87 ERROR
r-devel-linux-x86_64-fedora-clang 0.1.4 230.28 ERROR
r-devel-linux-x86_64-fedora-gcc 0.1.4 221.22 ERROR
r-devel-windows-ix86+x86_64 0.1.4 63.00 157.00 220.00 ERROR
r-patched-linux-x86_64 0.1.4 16.43 157.65 174.08 ERROR
r-patched-solaris-x86 0.1.4 302.40 ERROR
r-release-linux-x86_64 0.1.4 19.34 158.25 177.59 ERROR
r-release-osx-x86_64 0.1.4 WARN
r-release-windows-ix86+x86_64 0.1.4 44.00 156.00 200.00 ERROR
r-oldrel-osx-x86_64 0.1.4 WARN
r-oldrel-windows-ix86+x86_64 0.1.4 52.00 215.00 267.00 ERROR

Check Details

Version: 0.1.4
Check: examples
Result: ERROR
    Running examples in 'rabhit-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: hapDendo
    > ### Title: Hierarchical clustering of haplotypes graphical output
    > ### Aliases: hapDendo
    >
    > ### ** Examples
    >
    > # Plotting haplotype hierarchical clustering based on the Jaccard distance
    > hapDendo(samplesHaplotype)
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.50 1.00 1.00 NaN 0.00
    [31] 1.00 0.75 1.00 0.50 1.00 0.50 1.00 1.00 0.50 0.50 1.00 0.50 1.00 1.00 0.25
    [46] 0.00 0.50 1.00 0.50 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.50 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.00 1.00 0.50 NaN 0.50
    [31] 0.50 0.25 0.00 0.00 1.00 0.50 0.50 0.00 0.00 0.00 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 0.50 0.00 0.00 0.50 1.00 0.00 0.50 0.00 1.00 0.50 1.00 0.00
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.00 0.00 1.00 0.00
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 0.50 NaN 0.50
    [31] 1.00 0.25 0.00 0.50 1.00 0.00 0.50 0.00 0.50 0.50 1.00 1.00 1.00 1.00 0.75
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.00
    [61] 1.00 1.00 0.50 1.00 1.00 1.00 1.00 0.00 1.00 0.50 0.50 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 0.50 1.00 0.50 0.50 1.00 0.50 NaN 0.00
    [31] 0.75 0.00 0.00 0.50 1.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.50
    [46] 1.00 0.50 1.00 0.50 0.50 0.00 0.50 0.50 0.00 0.00 0.00 1.00 0.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 1.00 0.75 NaN 0.00 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 0.00 0.25 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 0.50 NaN 1.00
    [31] 0.50 0.00 0.00 0.00 1.00 0.50 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.75
    [46] 0.00 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 0.00
    [61] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 0.50 0.75 1.00 0.00 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 NaN 0.50
    [31] 0.25 0.00 1.00 0.50 1.00 0.00 0.50 1.00 0.50 0.50 1.00 1.00 1.00 0.50 1.00
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 0.50 0.00 0.50 1.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.00 0.50 1.00 1.00 1.00 1.00 0.50 0.75 0.00 0.50 0.25 1.00 0.50
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 0.5000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 0.5000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 0.0000000 0.5000000 0.0000000 0.0000000 0.5000000 0.5000000
    [57] 1.0000000 0.5000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 0.7500000 NaN
    [71] 0.5000000 0.7500000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 0.00 0.25 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 0.00 0.50 0.50 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 0.75 0.50 0.50 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 0.00 0.50 1.00 0.00 1.00 0.00 0.50 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 0.75 0.00 0.00 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 0.75 0.25 1.00 0.50 1.00 0.50 0.00 1.00 0.50 0.50 1.00 0.00 1.00 0.50 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 0.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 1.00
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 1.0000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 1.0000000 0.5000000 0.0000000 NaN 0.5000000 0.5000000
    [57] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 NaN NaN
    [71] 1.0000000 1.0000000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 1.00 0.50 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 NaN 0.50 0.75 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 1.00 1.00 1.00 0.00 1.00 0.00 1.00 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 1.00 0.50 0.00 NaN 1.00 0.25 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 NaN NaN 0.00 1.00 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 1.50 0.50 1.00 0.50 1.00 0.50 0.50 1.00 0.50 0.50 1.00 0.00 1.00 2.00 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 NaN 0.50 0.25 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [31] 1.00 0.75 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [46] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 NaN 1.00 0.75 1.00 1.00 1.00 1.00
    [61] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 NaN NaN 1.00 1.50 1.00 1.00
    Error: Can't combine `..1$SUBJECT` <logical> and `..2$SUBJECT` <character>.
    Backtrace:
     x
     1. +-rabhit::hapDendo(samplesHaplotype)
     2. | \-dplyr::bind_rows(haplo_db_clust_texture, tmp_point)
     3. | \-vctrs::vec_rbind(!!!dots, .names_to = .id)
     4. +-vctrs:::vec_ptype2.data.frame.grouped_df(...)
     5. | \-vctrs:::gdf_ptype2(x, y, ...)
     6. | \-vctrs::df_ptype2(x, y, ...)
     7. \-vctrs::vec_default_ptype2(...)
     8. \-vctrs::stop_incompatible_type(...)
     9. \-vctrs:::stop_incompatible(...)
     10. \-vctrs:::stop_vctrs(...)
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1.4
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'RAbHIT-vignette.Rmd' using rmarkdown
    Loading required package: ggplot2
    RAbHIT version: 0.1.4
    Quitting from lines 198-200 (RAbHIT-vignette.Rmd)
    Error: processing vignette 'RAbHIT-vignette.Rmd' failed with diagnostics:
    Can't combine `..1$SUBJECT` <logical> and `..2$SUBJECT` <character>.
    --- failed re-building 'RAbHIT-vignette.Rmd'
    
    SUMMARY: processing the following file failed:
     'RAbHIT-vignette.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.1.4
Check: examples
Result: ERROR
    Running examples in ‘rabhit-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: hapDendo
    > ### Title: Hierarchical clustering of haplotypes graphical output
    > ### Aliases: hapDendo
    >
    > ### ** Examples
    >
    > # Plotting haplotype hierarchical clustering based on the Jaccard distance
    > hapDendo(samplesHaplotype)
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.50 1.00 1.00 NaN 0.00
    [31] 1.00 0.75 1.00 0.50 1.00 0.50 1.00 1.00 0.50 0.50 1.00 0.50 1.00 1.00 0.25
    [46] 0.00 0.50 1.00 0.50 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.50 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.00 1.00 0.50 NaN 0.50
    [31] 0.50 0.25 0.00 0.00 1.00 0.50 0.50 0.00 0.00 0.00 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 0.50 0.00 0.00 0.50 1.00 0.00 0.50 0.00 1.00 0.50 1.00 0.00
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.00 0.00 1.00 0.00
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 0.50 NaN 0.50
    [31] 1.00 0.25 0.00 0.50 1.00 0.00 0.50 0.00 0.50 0.50 1.00 1.00 1.00 1.00 0.75
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.00
    [61] 1.00 1.00 0.50 1.00 1.00 1.00 1.00 0.00 1.00 0.50 0.50 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 0.50 1.00 0.50 0.50 1.00 0.50 NaN 0.00
    [31] 0.75 0.00 0.00 0.50 1.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.50
    [46] 1.00 0.50 1.00 0.50 0.50 0.00 0.50 0.50 0.00 0.00 0.00 1.00 0.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 1.00 0.75 NaN 0.00 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 0.00 0.25 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 0.50 NaN 1.00
    [31] 0.50 0.00 0.00 0.00 1.00 0.50 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.75
    [46] 0.00 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 0.00
    [61] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 0.50 0.75 1.00 0.00 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 NaN 0.50
    [31] 0.25 0.00 1.00 0.50 1.00 0.00 0.50 1.00 0.50 0.50 1.00 1.00 1.00 0.50 1.00
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 0.50 0.00 0.50 1.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.00 0.50 1.00 1.00 1.00 1.00 0.50 0.75 0.00 0.50 0.25 1.00 0.50
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 0.5000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 0.5000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 0.0000000 0.5000000 0.0000000 0.0000000 0.5000000 0.5000000
    [57] 1.0000000 0.5000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 0.7500000 NaN
    [71] 0.5000000 0.7500000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 0.00 0.25 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 0.00 0.50 0.50 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 0.75 0.50 0.50 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 0.00 0.50 1.00 0.00 1.00 0.00 0.50 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 0.75 0.00 0.00 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 0.75 0.25 1.00 0.50 1.00 0.50 0.00 1.00 0.50 0.50 1.00 0.00 1.00 0.50 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 0.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 1.00
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 1.0000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 1.0000000 0.5000000 0.0000000 NaN 0.5000000 0.5000000
    [57] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 NaN NaN
    [71] 1.0000000 1.0000000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 1.00 0.50 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 NaN 0.50 0.75 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 1.00 1.00 1.00 0.00 1.00 0.00 1.00 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 1.00 0.50 0.00 NaN 1.00 0.25 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 NaN NaN 0.00 1.00 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 1.50 0.50 1.00 0.50 1.00 0.50 0.50 1.00 0.50 0.50 1.00 0.00 1.00 2.00 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 NaN 0.50 0.25 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [31] 1.00 0.75 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [46] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 NaN 1.00 0.75 1.00 1.00 1.00 1.00
    [61] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 NaN NaN 1.00 1.50 1.00 1.00
    Error: Can't combine `..1$SUBJECT` <logical> and `..2$SUBJECT` <character>.
    Backtrace:
     █
     1. ├─rabhit::hapDendo(samplesHaplotype)
     2. │ └─dplyr::bind_rows(haplo_db_clust_texture, tmp_point)
     3. │ └─vctrs::vec_rbind(!!!dots, .names_to = .id)
     4. ├─vctrs:::vec_ptype2.data.frame.grouped_df(...)
     5. │ └─vctrs:::gdf_ptype2(x, y, ...)
     6. │ └─vctrs::df_ptype2(x, y, ...)
     7. └─vctrs::vec_default_ptype2(...)
     8. └─vctrs::stop_incompatible_type(...)
     9. └─vctrs:::stop_incompatible(...)
     10. └─vctrs:::stop_vctrs(...)
    Execution halted
Flavors: r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.1.4
Check: examples
Result: ERROR
    Running examples in ‘rabhit-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: hapDendo
    > ### Title: Hierarchical clustering of haplotypes graphical output
    > ### Aliases: hapDendo
    >
    > ### ** Examples
    >
    > # Plotting haplotype hierarchical clustering based on the Jaccard distance
    > hapDendo(samplesHaplotype)
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.50 1.00 1.00 NaN 0.00
    [31] 1.00 0.75 1.00 0.50 1.00 0.50 1.00 1.00 0.50 0.50 1.00 0.50 1.00 1.00 0.25
    [46] 0.00 0.50 1.00 0.50 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.50 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.00 1.00 0.50 NaN 0.50
    [31] 0.50 0.25 0.00 0.00 1.00 0.50 0.50 0.00 0.00 0.00 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 0.50 0.00 0.00 0.50 1.00 0.00 0.50 0.00 1.00 0.50 1.00 0.00
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.00 0.00 1.00 0.00
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 0.50 NaN 0.50
    [31] 1.00 0.25 0.00 0.50 1.00 0.00 0.50 0.00 0.50 0.50 1.00 1.00 1.00 1.00 0.75
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.00
    [61] 1.00 1.00 0.50 1.00 1.00 1.00 1.00 0.00 1.00 0.50 0.50 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 0.50 1.00 0.50 0.50 1.00 0.50 NaN 0.00
    [31] 0.75 0.00 0.00 0.50 1.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.50
    [46] 1.00 0.50 1.00 0.50 0.50 0.00 0.50 0.50 0.00 0.00 0.00 1.00 0.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 1.00 0.75 NaN 0.00 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 0.00 0.25 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 0.50 NaN 1.00
    [31] 0.50 0.00 0.00 0.00 1.00 0.50 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.75
    [46] 0.00 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 0.00
    [61] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 0.50 0.75 1.00 0.00 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 NaN 0.50
    [31] 0.25 0.00 1.00 0.50 1.00 0.00 0.50 1.00 0.50 0.50 1.00 1.00 1.00 0.50 1.00
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 0.50 0.00 0.50 1.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.00 0.50 1.00 1.00 1.00 1.00 0.50 0.75 0.00 0.50 0.25 1.00 0.50
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 0.5000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 0.5000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 0.0000000 0.5000000 0.0000000 0.0000000 0.5000000 0.5000000
    [57] 1.0000000 0.5000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 0.7500000 NaN
    [71] 0.5000000 0.7500000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 0.00 0.25 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 0.00 0.50 0.50 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 0.75 0.50 0.50 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 0.00 0.50 1.00 0.00 1.00 0.00 0.50 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 0.75 0.00 0.00 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 0.75 0.25 1.00 0.50 1.00 0.50 0.00 1.00 0.50 0.50 1.00 0.00 1.00 0.50 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 0.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 1.00
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 1.0000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 1.0000000 0.5000000 0.0000000 NaN 0.5000000 0.5000000
    [57] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 NaN NaN
    [71] 1.0000000 1.0000000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 1.00 0.50 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 NaN 0.50 0.75 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 1.00 1.00 1.00 0.00 1.00 0.00 1.00 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 1.00 0.50 0.00 NaN 1.00 0.25 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 NaN NaN 0.00 1.00 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 1.50 0.50 1.00 0.50 1.00 0.50 0.50 1.00 0.50 0.50 1.00 0.00 1.00 2.00 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 NaN 0.50 0.25 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [31] 1.00 0.75 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [46] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 NaN 1.00 0.75 1.00 1.00 1.00 1.00
    [61] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 NaN NaN 1.00 1.50 1.00 1.00
    Error: Can't combine `..1$SUBJECT` <logical> and `..2$SUBJECT` <character>.
    Backtrace:
     █
     1. ├─rabhit::hapDendo(samplesHaplotype)
     2. │ └─dplyr::bind_rows(haplo_db_clust_texture, tmp_point)
     3. │ └─vctrs::vec_rbind(!!!dots, .names_to = .id)
     4. ├─vctrs:::vec_ptype2.data.frame.grouped_df(...)
     5. │ └─vctrs:::gdf_ptype2(x, y, ...)
     6. │ └─vctrs::df_ptype2(x, y, ...)
     7. └─vctrs::vec_default_ptype2(...)
     8. └─vctrs::stop_incompatible_type(...)
     9. └─vctrs:::stop_incompatible(...)
     10. └─vctrs:::stop_vctrs(...)
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86

Version: 0.1.4
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building ‘RAbHIT-vignette.Rmd’ using rmarkdown
    Loading required package: ggplot2
    RAbHIT version: 0.1.4
    Quitting from lines 198-200 (RAbHIT-vignette.Rmd)
    Error: processing vignette 'RAbHIT-vignette.Rmd' failed with diagnostics:
    Can't combine `..1$SUBJECT` <logical> and `..2$SUBJECT` <character>.
    --- failed re-building ‘RAbHIT-vignette.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘RAbHIT-vignette.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.1.4
Check: examples
Result: ERROR
    Running examples in 'rabhit-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: hapDendo
    > ### Title: Hierarchical clustering of haplotypes graphical output
    > ### Aliases: hapDendo
    >
    > ### ** Examples
    >
    > # Plotting haplotype hierarchical clustering based on the Jaccard distance
    > hapDendo(samplesHaplotype)
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.50 1.00 1.00 NaN 0.00
    [31] 1.00 0.75 1.00 0.50 1.00 0.50 1.00 1.00 0.50 0.50 1.00 0.50 1.00 1.00 0.25
    [46] 0.00 0.50 1.00 0.50 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.00 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.50 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 1.00 0.50 0.00 1.00 0.50 NaN 0.50
    [31] 0.50 0.25 0.00 0.00 1.00 0.50 0.50 0.00 0.00 0.00 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 0.50 0.00 0.00 0.50 1.00 0.00 0.50 0.00 1.00 0.50 1.00 0.00
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.50 1.00 NaN 0.00 0.00 1.00 0.00
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.00 1.00 0.50 NaN 0.50
    [31] 1.00 0.25 0.00 0.50 1.00 0.00 0.50 0.00 0.50 0.50 1.00 1.00 1.00 1.00 0.75
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 1.00 0.50 0.50 0.50 1.00 0.50 1.00 0.00
    [61] 1.00 1.00 0.50 1.00 1.00 1.00 1.00 0.00 1.00 0.50 0.50 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 0.00 0.50 1.00 0.50 0.50 1.00 0.50 NaN 0.00
    [31] 0.75 0.00 0.00 0.50 1.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.50
    [46] 1.00 0.50 1.00 0.50 0.50 0.00 0.50 0.50 0.00 0.00 0.00 1.00 0.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 0.50 1.00 1.00 0.75 NaN 0.00 0.75 1.00 0.50
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 0.00 0.25 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 0.50 NaN 1.00
    [31] 0.50 0.00 0.00 0.00 1.00 0.50 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.50 0.75
    [46] 0.00 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 0.00
    [61] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 0.50 0.75 1.00 0.00 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 NaN 0.50
    [31] 0.25 0.00 1.00 0.50 1.00 0.00 0.50 1.00 0.50 0.50 1.00 1.00 1.00 0.50 1.00
    [46] 0.50 1.00 1.00 1.00 0.50 0.50 0.00 0.50 0.00 0.50 1.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.00 0.50 1.00 1.00 1.00 1.00 0.50 0.75 0.00 0.50 0.25 1.00 0.50
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 0.5000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 0.5000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 0.0000000 0.5000000 0.0000000 0.0000000 0.5000000 0.5000000
    [57] 1.0000000 0.5000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 0.7500000 NaN
    [71] 0.5000000 0.7500000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 0.00 0.25 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 0.00 0.50 0.50 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 0.75 0.50 0.50 1.00 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 0.00 0.50 1.00 0.00 1.00 0.00 0.50 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 0.50 0.00 0.00 0.50 1.00 0.00 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 0.75 0.00 0.00 0.25 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 0.75 0.25 1.00 0.50 1.00 0.50 0.00 1.00 0.50 0.50 1.00 0.00 1.00 0.50 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 0.00 1.00 0.50 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 1.00 1.00 0.50 1.00 1.00 1.00
     [1] 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 1.0000000
     [8] 0.2500000 1.0000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [15] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
    [22] 0.0000000 0.5000000 1.0000000 1.0000000 0.5000000 1.0000000 1.0000000
    [29] NaN 0.5000000 1.0000000 0.2500000 0.0000000 1.0000000 1.0000000
    [36] 0.5000000 0.5000000 0.0000000 0.5000000 0.5000000 1.0000000 0.0000000
    [43] 1.0000000 1.0000000 0.6666667 0.5000000 1.0000000 1.0000000 0.5000000
    [50] 0.5000000 1.0000000 0.5000000 0.0000000 NaN 0.5000000 0.5000000
    [57] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.5000000
    [64] 1.0000000 1.0000000 0.5000000 1.0000000 0.5000000 NaN NaN
    [71] 1.0000000 1.0000000 1.0000000 0.5000000
     [1] 1.00 1.00 1.00 0.50 1.00 1.00 0.50 0.75 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00 1.00 1.00 NaN 0.50
    [31] 1.00 0.50 0.00 0.50 1.00 1.00 0.50 0.00 0.50 0.50 1.00 0.50 1.00 1.00 0.50
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 0.50 0.00 NaN 0.50 0.75 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 0.50 1.00 0.50 1.00 0.25 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 0.00 1.00 0.50 NaN 1.00
    [31] 1.00 1.00 1.00 0.00 1.00 0.00 1.00 1.00 0.00 0.00 1.00 0.50 1.00 1.00 0.75
    [46] 1.00 0.50 1.00 1.00 0.50 1.00 0.50 0.00 NaN 1.00 0.25 1.00 1.00 1.00 0.00
    [61] 1.00 0.50 1.00 0.50 1.00 1.00 1.00 0.00 NaN NaN 0.00 1.00 1.00 0.50
     [1] 1.00 1.00 1.00 1.00 1.00 0.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 0.50 NaN 0.50
    [31] 1.50 0.50 1.00 0.50 1.00 0.50 0.50 1.00 0.50 0.50 1.00 0.00 1.00 2.00 0.75
    [46] 0.50 0.50 1.00 1.00 1.00 1.00 1.00 0.50 NaN 0.50 0.25 1.00 1.00 1.00 0.50
    [61] 1.00 0.50 0.50 0.50 1.00 1.00 1.00 0.50 NaN NaN 0.50 1.50 1.00 1.00
     [1] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [16] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
    [31] 1.00 0.75 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 1.00 1.00 1.00
    [46] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.50 NaN 1.00 0.75 1.00 1.00 1.00 1.00
    [61] 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 NaN NaN 1.00 1.50 1.00 1.00
    Error: Can't combine `..1$SUBJECT` <logical> and `..2$SUBJECT` <character>.
    Backtrace:
     x
     1. +-rabhit::hapDendo(samplesHaplotype)
     2. | \-dplyr::bind_rows(haplo_db_clust_texture, tmp_point)
     3. | \-vctrs::vec_rbind(!!!dots, .names_to = .id)
     4. +-vctrs:::vec_ptype2.data.frame.grouped_df(...)
     5. | \-vctrs:::gdf_ptype2(x, y, ...)
     6. | \-vctrs::df_ptype2(x, y, ...)
     7. \-vctrs::vec_default_ptype2(...)
     8. \-vctrs::stop_incompatible_type(...)
     9. \-vctrs:::stop_incompatible(...)
     10. \-vctrs:::stop_vctrs(...)
    Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.1.4
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘RAbHIT-vignette.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Loading required package: ggplot2
    RAbHIT version: 0.1.4
    Quitting from lines 198-200 (RAbHIT-vignette.Rmd)
    Error: processing vignette 'RAbHIT-vignette.Rmd' failed with diagnostics:
    Can't combine `..1$SUBJECT` <logical> and `..2$SUBJECT` <character>.
    --- failed re-building ‘RAbHIT-vignette.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘RAbHIT-vignette.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-patched-solaris-x86

Version: 0.1.4
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘RAbHIT-vignette.Rmd’ using rmarkdown
    Loading required package: ggplot2
    RAbHIT version: 0.1.4
    Fontconfig error: Cannot load default config file
    PhantomJS not found. You can install it with webshot::install_phantomjs(). If it is installed, please make sure the phantomjs executable can be found via the PATH variable.
    dyld: lazy symbol binding failed: Symbol not found: ____chkstk_darwin
     Referenced from: /usr/local/bin/pandoc (which was built for Mac OS X 10.15)
     Expected in: /usr/lib/libSystem.B.dylib
    
    dyld: Symbol not found: ____chkstk_darwin
     Referenced from: /usr/local/bin/pandoc (which was built for Mac OS X 10.15)
     Expected in: /usr/lib/libSystem.B.dylib
    
    Error: processing vignette 'RAbHIT-vignette.Rmd' failed with diagnostics:
    pandoc document conversion failed with error 6
    --- failed re-building ‘RAbHIT-vignette.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘RAbHIT-vignette.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-release-osx-x86_64

Version: 0.1.4
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘RAbHIT-vignette.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Loading required package: ggplot2
    RAbHIT version: 0.1.4
    Warning: Ignoring unknown aesthetics: text
    Warning: Ignoring unknown aesthetics: text
    PhantomJS not found. You can install it with webshot::install_phantomjs(). If it is installed, please make sure the phantomjs executable can be found via the PATH variable.
    Quitting from lines 299-301 (RAbHIT-vignette.Rmd)
    Error: processing vignette 'RAbHIT-vignette.Rmd' failed with diagnostics:
    cannot open the connection
    --- failed re-building ‘RAbHIT-vignette.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘RAbHIT-vignette.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-oldrel-osx-x86_64