PR addressing Issue #161

[Max-Bladen]

User has dataframe (72 x 48) with some NAs. When they attempt to use tune.pca(), works fine. When they attempt the below call:

grid.keepX<-c(seq(5,30,5))
tune.spca.result<-tune.spca(X, ncomp=3, folds=4, test.keepX=grid.keepX, nrepeat=10)

The follow error is raised:
Error: Unexpected error while trying to choose the optimum number of components. Please check the inputs and if problem persists submit an issue ...

Worked when nrepeat = 2 or less, but more than that and it breaks.

suppressMessages(library(mixOmics))
data(nutrimouse)

grid.keepX<-c(seq(5,30,5)) # recreate grid from issue #161

## run tuning with no NAs
X <- nutrimouse$gene
tune.spca.result.full <- tune.spca(X, ncomp=3, folds=4, nrepeat=10,
                                   test.keepX = grid.keepX)

## introduce a single NA to ~15% of rows in the data frame
for (r in sample(nrow(X), floor(0.15*nrow(X)))) {
  X[r, sample(ncol(X), 1)] <- NA
}

## run tuning with NAs
tune.spca.result.NAs <- tune.spca(X, ncomp=3, folds=4, nrepeat=10,
                                  test.keepX = grid.keepX)
#> Error: Unexpected error while trying to choose the optimum number of components. Please check the inputs and if problem persists submit an issue to https://github.com/mixOmicsTeam/mixOmics/issues

^{Created on 2022-03-08 by the reprex package (v2.0.1)}

Session info

sessioninfo::session_info()
#> - Session info ---------------------------------------------------------------
#>  setting  value
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#>  ui       RTerm
#>  language (EN)
#>  collate  English_Australia.1252
#>  ctype    English_Australia.1252
#>  tz       Australia/Sydney
#>  date     2022-03-08
#>  pandoc   2.14.2 @ C:/Users/Work/AppData/Local/Pandoc/ (via rmarkdown)
#> 
#> - Packages -------------------------------------------------------------------
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#>  igraph         1.2.11  2022-01-04 [1] CRAN (R 4.1.2)
#>  knitr          1.37    2021-12-16 [1] CRAN (R 4.1.2)
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#> 
#> ------------------------------------------------------------------------------

SOLUTION:
Adjusted lines 78-93 involved removing the rows of any X.train, X.test and t.comp.pred rows which had an NA within them. This is done within the repeat_cv_j function such that no data at the global level is lost. Allows cross product to be calculated within inducing any NA's

[aljabadi]

Hi @Max-Bladen, I run the reproducible example using the latest version of mixOmics and R and I get no errors. Can you please confirm if you still face this issue?

[Max-Bladen]

I am also now unable to reproduce this issue on the latest builds. Potentially one of our previous merges resolved this unintentionally? I believe this is fine to close, though I couldn't tell you specifically why I cannot reproduce it anymore

[Max-Bladen]

Cleaner and better implementation of a solution to this issue provided by PR #276