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### Running command:
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###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:mistyR.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings mistyR_1.15.0.tar.gz
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* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/mistyR.Rcheck’
* using R Under development (unstable) (2024-11-20 r87352)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘mistyR/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘mistyR’ version ‘1.15.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 21 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable.  Move as many as possible to Suggests and
use conditionally.
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘mistyR’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
aggregate_results: no visible binding for global variable ‘measure’
aggregate_results: no visible binding for global variable ‘target’
aggregate_results: no visible binding for global variable ‘value’
aggregate_results: no visible binding for global variable ‘sd’
aggregate_results: no visible binding for global variable ‘view’
aggregate_results: no visible binding for global variable ‘.PT’
aggregate_results: no visible binding for global variable ‘Importance’
aggregate_results_subset: no visible binding for global variable ‘view’
aggregate_results_subset: no visible binding for global variable ‘.PT’
aggregate_results_subset: no visible binding for global variable
  ‘Importance’
bagged_mars_model: no visible binding for global variable ‘index’
bagged_mars_model: no visible binding for global variable ‘prediction’
collect_results : <anonymous>: no visible binding for global variable
  ‘intra.RMSE’
collect_results : <anonymous>: no visible binding for global variable
  ‘multi.RMSE’
collect_results : <anonymous>: no visible binding for global variable
  ‘multi.R2’
collect_results : <anonymous>: no visible binding for global variable
  ‘intra.R2’
collect_results: no visible binding for global variable ‘target’
collect_results : <anonymous>: no visible binding for global variable
  ‘target’
collect_results : <anonymous>: no visible binding for global variable
  ‘view’
collect_results : <anonymous> : <anonymous>: no visible binding for
  global variable ‘value’
collect_results : <anonymous> : <anonymous>: no visible binding for
  global variable ‘Predictor’
collect_results : <anonymous> : <anonymous>: no visible binding for
  global variable ‘Importance’
extract_signature: no visible binding for global variable ‘measure’
extract_signature: no visible binding for global variable ‘target’
extract_signature: no visible binding for global variable ‘ts’
extract_signature: no visible binding for global variable ‘view’
extract_signature: no visible binding for global variable ‘value’
extract_signature : <anonymous>: no visible binding for global variable
  ‘Importance’
extract_signature : <anonymous>: no visible binding for global variable
  ‘Target’
extract_signature : <anonymous>: no visible binding for global variable
  ‘ts’
extract_signature : <anonymous>: no visible binding for global variable
  ‘Predictor’
gradient_boosting_model: no visible binding for global variable ‘index’
linear_model: no visible binding for global variable ‘index’
mars_model: no visible binding for global variable ‘index’
mlp_model: no visible binding for global variable ‘index’
plot_contrast_heatmap: no visible binding for global variable ‘view’
plot_contrast_heatmap: no visible binding for global variable ‘measure’
plot_contrast_heatmap: no visible binding for global variable ‘target’
plot_contrast_heatmap: no visible binding for global variable ‘Target’
plot_contrast_heatmap: no visible binding for global variable
  ‘nsamples’
plot_contrast_heatmap: no visible binding for global variable
  ‘Predictor’
plot_contrast_heatmap: no visible binding for global variable
  ‘Importance’
plot_contrast_results: no visible binding for global variable ‘view’
plot_contrast_results : <anonymous>: no visible binding for global
  variable ‘view’
plot_contrast_results : <anonymous>: no visible binding for global
  variable ‘Predictor’
plot_contrast_results : <anonymous>: no visible binding for global
  variable ‘Target’
plot_contrast_results: no visible binding for global variable ‘measure’
plot_contrast_results: no visible binding for global variable ‘target’
plot_contrast_results : <anonymous>: no visible binding for global
  variable ‘nsamples’
plot_contrast_results : <anonymous>: no visible binding for global
  variable ‘Importance’
plot_improvement_stats: no visible binding for global variable ‘target’
plot_improvement_stats: no visible binding for global variable ‘sd’
plot_interaction_communities: no visible binding for global variable
  ‘nsamples’
plot_interaction_communities: no visible binding for global variable
  ‘Predictor’
plot_interaction_heatmap: no visible binding for global variable
  ‘measure’
plot_interaction_heatmap: no visible binding for global variable
  ‘target’
plot_interaction_heatmap: no visible binding for global variable
  ‘Target’
plot_interaction_heatmap: no visible binding for global variable
  ‘Importance’
plot_interaction_heatmap: no visible binding for global variable
  ‘Predictor’
plot_interaction_heatmap: no visible binding for global variable
  ‘total’
plot_view_contributions: no visible binding for global variable
  ‘measure’
plot_view_contributions: no visible binding for global variable
  ‘target’
plot_view_contributions: no visible binding for global variable
  ‘fraction’
plot_view_contributions: no visible binding for global variable ‘view’
run_misty : <anonymous>: no visible binding for global variable ‘p’
run_misty : <anonymous>: no visible binding for global variable
  ‘intra.RMSE’
run_misty : <anonymous>: no visible binding for global variable
  ‘multi.RMSE’
run_misty : <anonymous>: no visible binding for global variable
  ‘intra.R2’
run_misty : <anonymous>: no visible binding for global variable
  ‘multi.R2’
svm_model: no visible binding for global variable ‘index’
Undefined global functions or variables:
  .PT Importance Predictor Target fraction index intra.R2 intra.RMSE
  measure multi.R2 multi.RMSE nsamples p prediction sd target total ts
  value view
Consider adding
  importFrom("stats", "sd", "ts")
to your NAMESPACE file.
* checking Rd files ... NOTE
checkRd: (-1) collect_results.Rd:32: Lost braces; missing escapes or markup?
    32 |             for all performance measures for each {target} over all samples.}
       |                                                   ^
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... ERROR
Running examples in ‘mistyR-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: add_juxtaview
> ### Title: Generate and add a juxtaview to the current view composition
> ### Aliases: add_juxtaview
> 
> ### ** Examples
> 
> # Create a view composition of an intraview and a juxtaview.
> 
> library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

> 
> # get the expression data
> data("synthetic")
> expr <- synthetic[[1]] %>% select(-c(row, col, type))
> # get the coordinates for each cell
> pos <- synthetic[[1]] %>% select(row, col)
> 
> # compose
> misty.views <- create_initial_view(expr) %>% add_juxtaview(pos, neighbor.thr = 1.5)

Computing triangulation
Line from midpoint to circumcenter
does not intersect rectangle boundary!
But it HAS to!!!
Error in deldir::deldir(as.data.frame(positions)) : 
  Bailing out of dirseg.
Calls: %>% -> add_juxtaview -> <Anonymous>
Execution halted
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR, 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.21-bioc/meat/mistyR.Rcheck/00check.log’
for details.

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### Running command:
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###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL mistyR
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* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘mistyR’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (mistyR)

R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(mistyR)
mistyR is able to run computationally intensive functions
  in parallel. Please consider specifying a future::plan(). For example by running
  future::plan(future::multisession) before calling mistyR functions.
> 
> test_check("mistyR")

Generating paraview

Attaching package: 'purrr'

The following object is masked from 'package:testthat':

    is_null


Training models

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Training models

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Collecting importances

Aggregating

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Aggregating

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Collecting improvements

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Aggregating

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Aggregating

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Aggregating

Generating paraview

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Generating paraview

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Computing triangulation

Generating juxtaview

Generating paraview

Generating paraview using 20 nearest neighbors per unit

Approximating RBF matrix using the Nystrom method

Computing triangulation

Generating juxtaview

Generating paraview

Computing triangulation

Generating juxtaview

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Computing triangulation

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Generating paraview

Generating paraview using 2 nearest neighbors per unit

Generating paraview

Generating paraview
[ FAIL 0 | WARN 4 | SKIP 0 | PASS 173 ]

[ FAIL 0 | WARN 4 | SKIP 0 | PASS 173 ]
> 
> proc.time()
   user  system elapsed 
 92.065   2.237  94.775