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This page was generated on 2025-10-18 12:04 -0400 (Sat, 18 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" 4887
lconwaymacOS 12.7.6 Montereyx86_644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4677
kjohnson3macOS 13.7.7 Venturaarm644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4622
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4632
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 256/2353HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.73.0  (landing page)
Ben Bolstad
Snapshot Date: 2025-10-17 13:45 -0400 (Fri, 17 Oct 2025)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: devel
git_last_commit: 0147962
git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025)
nebbiolo2Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.6 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kjohnson3macOS 13.7.7 Ventura / arm64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
taishanLinux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for BufferedMatrix on lconway

To the developers/maintainers of the BufferedMatrix package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results


Summary

Package: BufferedMatrix
Version: 1.73.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
StartedAt: 2025-10-17 20:42:02 -0400 (Fri, 17 Oct 2025)
EndedAt: 2025-10-17 20:43:15 -0400 (Fri, 17 Oct 2025)
EllapsedTime: 73.0 seconds
RetCode: 0
Status:   WARNINGS  
CheckDir: BufferedMatrix.Rcheck
Warnings: 1

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* 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 ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
  doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* used SDK: ‘MacOSX11.3.1.sdk’
* 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 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 ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
   209 |     $x^{power}$ elementwise of the matrix
       |        ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* 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 line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘Rcodetesting.R’
  Running ‘c_code_level_tests.R’
  Running ‘objectTesting.R’
  Running ‘rawCalltesting.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 WARNING, 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.


Installation output

BufferedMatrix.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.1.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
  if (!(Matrix->readonly) & setting){
      ^                   ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
  if (!(Matrix->readonly) & setting){
      ^
       (                           )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
  if (!(Matrix->readonly) & setting){
      ^
      (                  )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
           ^
2 warnings generated.
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)

Tests output

BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 

Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000 

Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068 
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000 

Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 

Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 

Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000 
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000 
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000 
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000 
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000 

[[1]]
[1] 0

> 
> proc.time()
   user  system elapsed 
  0.357   0.164   0.513 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> 
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
> 
> 
> ## test creation and some simple assignments and subsetting operations
> 
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
> 
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
> 
> 
> 
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
> 
> 
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
       [,1]    [,2]
 [1,]  0.00 0.00000
 [2,]  0.00 0.00000
 [3,] 51.34 0.00000
 [4,]  0.00 0.00000
 [5,]  0.00 0.00000
 [6,]  0.00 0.00000
 [7,]  0.00 0.00000
 [8,]  0.00 0.00000
 [9,]  0.00 9.87654
[10,]  0.00 0.00000
> tmp2[,-(3:20)]
       [,1]    [,2]
 [1,]  0.00 0.00000
 [2,]  0.00 0.00000
 [3,] 51.34 0.00000
 [4,]  0.00 0.00000
 [5,]  0.00 0.00000
 [6,]  0.00 0.00000
 [7,]  0.00 0.00000
 [8,]  0.00 0.00000
 [9,]  0.00 9.87654
[10,]  0.00 0.00000
> tmp2[3,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34    0    0    0    0    0    0    0    0     0     0     0     0
     [,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,]     0     0     0     0     0     0     0
> tmp2[-3,]
      [,1]    [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [2,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [3,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [4,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [5,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [6,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [7,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [8,]    0 9.87654    0    0    0    0    0    0    0     0     0     0     0
 [9,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
      [,14] [,15] [,16] [,17] [,18] [,19] [,20]
 [1,]     0     0     0     0     0     0     0
 [2,]     0     0     0     0     0     0     0
 [3,]     0     0     0     0     0     0     0
 [4,]     0     0     0     0     0     0     0
 [5,]     0     0     0     0     0     0     0
 [6,]     0     0     0     0     0     0     0
 [7,]     0     0     0     0     0     0     0
 [8,]     0     0     0     0     0     0     0
 [9,]     0     0     0     0     0     0     0
> tmp2[2,1:3]
     [,1] [,2] [,3]
[1,]    0    0    0
> tmp2[3:9,1:3]
      [,1]    [,2] [,3]
[1,] 51.34 0.00000    0
[2,]  0.00 0.00000    0
[3,]  0.00 0.00000    0
[4,]  0.00 0.00000    0
[5,]  0.00 0.00000    0
[6,]  0.00 0.00000    0
[7,]  0.00 9.87654    0
> tmp2[-4,-4]
       [,1]    [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [2,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [3,] 51.34 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [4,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [5,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [6,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [7,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [8,]  0.00 9.87654    0    0    0    0    0    0    0     0     0     0     0
 [9,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
      [,14] [,15] [,16] [,17] [,18] [,19]
 [1,]     0     0     0     0     0     0
 [2,]     0     0     0     0     0     0
 [3,]     0     0     0     0     0     0
 [4,]     0     0     0     0     0     0
 [5,]     0     0     0     0     0     0
 [6,]     0     0     0     0     0     0
 [7,]     0     0     0     0     0     0
 [8,]     0     0     0     0     0     0
 [9,]     0     0     0     0     0     0
> 
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
> 
> for (i in 1:10){
+   for (j in 1:10){
+     tmp3[i,j] <- (j-1)*10 + i
+   }
+ }
> 
> tmp3[2:4,2:4]
     [,1] [,2] [,3]
[1,]   12   22   32
[2,]   13   23   33
[3,]   14   24   34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]   11   21   31   11   21   31   91    1   11     1    11    21    31
 [2,]   12   22   32   12   22   32   92    2   12     2    12    22    32
 [3,]   13   23   33   13   23   33   93    3   13     3    13    23    33
 [4,]   14   24   34   14   24   34   94    4   14     4    14    24    34
 [5,]   15   25   35   15   25   35   95    5   15     5    15    25    35
 [6,]   16   26   36   16   26   36   96    6   16     6    16    26    36
 [7,]   17   27   37   17   27   37   97    7   17     7    17    27    37
 [8,]   18   28   38   18   28   38   98    8   18     8    18    28    38
 [9,]   19   29   39   19   29   39   99    9   19     9    19    29    39
      [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
 [1,]    41    51    61    71    81    91    91    81    71    61    51    41
 [2,]    42    52    62    72    82    92    92    82    72    62    52    42
 [3,]    43    53    63    73    83    93    93    83    73    63    53    43
 [4,]    44    54    64    74    84    94    94    84    74    64    54    44
 [5,]    45    55    65    75    85    95    95    85    75    65    55    45
 [6,]    46    56    66    76    86    96    96    86    76    66    56    46
 [7,]    47    57    67    77    87    97    97    87    77    67    57    47
 [8,]    48    58    68    78    88    98    98    88    78    68    58    48
 [9,]    49    59    69    79    89    99    99    89    79    69    59    49
      [,26] [,27] [,28] [,29]
 [1,]    31    21    11     1
 [2,]    32    22    12     2
 [3,]    33    23    13     3
 [4,]    34    24    14     4
 [5,]    35    25    15     5
 [6,]    36    26    16     6
 [7,]    37    27    17     7
 [8,]    38    28    18     8
 [9,]    39    29    19     9
> tmp3[-c(1:5),-c(6:10)]
     [,1] [,2] [,3] [,4] [,5]
[1,]    6   16   26   36   46
[2,]    7   17   27   37   47
[3,]    8   18   28   38   48
[4,]    9   19   29   39   49
[5,]   10   20   30   40   50
> 
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
      [,1]  [,2]
 [1,] 1100 1e+04
 [2,] 1200 2e+04
 [3,] 1300 3e+04
 [4,] 1400 4e+04
 [5,] 1500 5e+04
 [6,] 1600 6e+04
 [7,] 1700 7e+04
 [8,] 1800 8e+04
 [9,] 1900 9e+04
[10,] 2000 1e+05
> 
> 
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
      [,1] [,2]  [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,] 1100 1100 1e+04   21   31   41   51   61   71    81
 [2,] 1200 1200 2e+04   22   32   42   52   62   72    82
 [3,] 1300 1300 3e+04   23   33   43   53   63   73    83
 [4,] 1400 1400 4e+04   24   34   44   54   64   74    84
 [5,] 1500 1500 5e+04   25   35   45   55   65   75    85
 [6,] 1600 1600 6e+04   26   36   46   56   66   76    86
 [7,] 1700 1700 7e+04   27   37   47   57   67   77    87
 [8,] 1800 1800 8e+04   28   38   48   58   68   78    88
 [9,] 1900 1900 9e+04   29   39   49   59   69   79    89
[10,] 2000 2000 1e+05   30   40   50   60   70   80    90
> 
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
> 
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
> 
> tmp3[1,] <- 1:10
> tmp3[1,]
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    1    2    3    4    5    6    7    8    9    10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1    2    3    4    5    6    7    8    9    10
 [2,]    1    2    1    2    1    2    1    2    1     2
 [3,]    2    1    2    1    2    1    2    1    2     1
 [4,]    1    2    1    2    1    2    1    2    1     2
 [5,]    2    1    2    1    2    1    2    1    2     1
 [6,]    1    2    1    2    1    2    1    2    1     2
 [7,]    2    1    2    1    2    1    2    1    2     1
 [8,]    1    2    1    2    1    2    1    2    1     2
 [9,]    2    1    2    1    2    1    2    1    2     1
[10,]    1    2    1    2    1    2    1    2    1     2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1    2    3    4    5    6    7    8    9    10
 [2,]    1    2    1    2    1    2    1    2    1     2
 [3,]    2    1    2    1    2    1    2    1    2     1
 [4,]    1    2    1    2    1    2    1    2    1     2
 [5,]    2    1    2    1    2    1    2    1    2     1
 [6,]    1    2    1    2    1    2    1    2    1     2
 [7,]    2    1    2    1    2    1    2    1    2     1
 [8,]    1    2    1    2    1    2    1    2    1     2
 [9,]    1    3    5    2    4    1    3    5    2     4
[10,]    2    4    1    3    5    2    4    1    3     5
> 
> 
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
> 
> 
> 
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
> 
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
         used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480848 25.7    1056620 56.5         NA   634462 33.9
Vcells 891079  6.8    8388608 64.0      98304  2108714 16.1
> 
> 
> 
> 
> ##
> ## checking reads
> ##
> 
> tmp2 <- createBufferedMatrix(10,20)
> 
> test.sample <- rnorm(10*20)
> 
> tmp2[1:10,1:20] <- test.sample
> 
> test.matrix <- matrix(test.sample,10,20)
> 
> ## testing reads
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   which.col <- sample(1:20,1)
+   if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> date()
[1] "Fri Oct 17 20:42:28 2025"
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> date()
[1] "Fri Oct 17 20:42:29 2025"
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> 
> 
> RowMode(tmp2)
<pointer: 0x600000a880c0>
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   which.col <- sample(1:20,1)
+   if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> date()
[1] "Fri Oct 17 20:42:34 2025"
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col <- sample(1:20,5,replace=TRUE)
+   if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> date()
[1] "Fri Oct 17 20:42:37 2025"
> 
> ColMode(tmp2)
<pointer: 0x600000a880c0>
> 
> 
> 
> ### Now testing assignments
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+ 
+   new.data <- rnorm(20)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,] <- new.data
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   new.data <- rnorm(10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+ 
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col  <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(25),5,5)
+   tmp2[which.row,which.col] <- new.data
+   test.matrix[which.row,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> ###
> ###
> ### testing some more functions
> ###
> 
> 
> 
> ## duplication function
> tmp5 <- duplicate(tmp2)
> 
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
> 
> if (tmp5[1,1] == tmp2[1,1]){
+   stop("Problem with duplication")
+ }
> 
> 
> 
> 
> ### testing elementwise applying of functions
> 
> tmp5[1:4,1:4]
           [,1]       [,2]       [,3]       [,4]
[1,] 99.5381700 -0.9507048 -0.2323922 -0.6000422
[2,] -1.4527306  1.5913016 -0.3440142 -0.8820534
[3,]  0.2044241  0.5341052 -0.3994639  1.9587741
[4,] -0.3865978 -0.1650762 -0.2456617  0.6396328
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]      [,3]      [,4]
[1,] 99.5381700 0.9507048 0.2323922 0.6000422
[2,]  1.4527306 1.5913016 0.3440142 0.8820534
[3,]  0.2044241 0.5341052 0.3994639 1.9587741
[4,]  0.3865978 0.1650762 0.2456617 0.6396328
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]      [,2]      [,3]      [,4]
[1,] 9.9768818 0.9750409 0.4820708 0.7746239
[2,] 1.2052928 1.2614680 0.5865272 0.9391770
[3,] 0.4521328 0.7308250 0.6320316 1.3995621
[4,] 0.6217699 0.4062957 0.4956427 0.7997705
> 
> my.function <- function(x,power){
+   (x+5)^power
+ }
> 
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 224.30699 35.70111 30.05310 33.34628
[2,]  38.50566 39.20598 31.20929 35.27382
[3,]  29.72575 32.84236 31.71978 40.95440
[4,]  31.60430 29.22803 30.20209 33.63734
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000a94000>
> exp(tmp5)
<pointer: 0x600000a94000>
> log(tmp5,2)
<pointer: 0x600000a94000>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.8656
> Min(tmp5)
[1] 53.63495
> mean(tmp5)
[1] 72.99881
> Sum(tmp5)
[1] 14599.76
> Var(tmp5)
[1] 858.9286
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 91.71937 71.33217 67.79334 68.63687 71.39814 73.87632 68.87072 72.96973
 [9] 70.68973 72.70173
> rowSums(tmp5)
 [1] 1834.387 1426.643 1355.867 1372.737 1427.963 1477.526 1377.414 1459.395
 [9] 1413.795 1454.035
> rowVars(tmp5)
 [1] 7853.58503   98.10672   91.58841   51.07439   82.10875   67.39373
 [7]   92.64250   74.33372   45.32455   92.45775
> rowSd(tmp5)
 [1] 88.620455  9.904883  9.570183  7.146635  9.061388  8.209368  9.625097
 [8]  8.621701  6.732351  9.615495
> rowMax(tmp5)
 [1] 466.86561  91.29578  85.82699  82.42419  89.92097  90.52077  84.59118
 [8]  92.28979  81.82230  93.01259
> rowMin(tmp5)
 [1] 56.33617 56.97525 53.80605 56.12881 57.24512 62.53844 53.74250 56.30984
 [9] 58.01050 53.63495
> 
> colMeans(tmp5)
 [1] 111.98298  69.20567  70.48140  77.54761  69.63202  75.97644  69.35865
 [8]  71.73165  72.60325  71.17663  70.43190  71.67585  67.52454  65.60265
[15]  70.77787  70.03943  70.67744  67.80948  74.09131  71.64947
> colSums(tmp5)
 [1] 1119.8298  692.0567  704.8140  775.4761  696.3202  759.7644  693.5865
 [8]  717.3165  726.0325  711.7663  704.3190  716.7585  675.2454  656.0265
[15]  707.7787  700.3943  706.7744  678.0948  740.9131  716.4947
> colVars(tmp5)
 [1] 15604.68817    65.16360    64.04069    51.27683   102.56053   100.13814
 [7]    92.06839    72.58785    95.02241   118.55195    60.13247    49.64655
[13]    77.38137   121.41487    64.44422    57.42801    45.26431    88.38596
[19]    45.40140    80.98933
> colSd(tmp5)
 [1] 124.918726   8.072397   8.002543   7.160784  10.127217  10.006904
 [7]   9.595227   8.519850   9.747944  10.888157   7.754513   7.046031
[13]   8.796668  11.018841   8.027716   7.578127   6.727876   9.401381
[19]   6.738056   8.999407
> colMax(tmp5)
 [1] 466.86561  81.60211  84.88008  93.01259  89.92097  90.00506  80.68028
 [8]  86.72278  91.29578  88.42545  85.82699  80.27697  81.82230  90.52077
[15]  81.02524  81.21745  87.54397  78.98626  83.93678  92.28979
> colMin(tmp5)
 [1] 61.87026 59.02324 62.55159 69.40591 53.91807 61.93588 56.12881 62.53844
 [9] 56.33617 53.63495 60.98585 58.03816 56.39710 56.30984 57.63095 59.87138
[17] 63.25584 53.74250 60.79962 59.18185
> 
> 
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
> 
> 
> which.row <- sample(1:10,1,replace=TRUE)
> which.col  <- sample(1:20,1,replace=TRUE)
> 
> tmp5[which.row,which.col] <- NA
> 
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
> 
> rowMeans(tmp5)
 [1] 91.71937 71.33217 67.79334       NA 71.39814 73.87632 68.87072 72.96973
 [9] 70.68973 72.70173
> rowSums(tmp5)
 [1] 1834.387 1426.643 1355.867       NA 1427.963 1477.526 1377.414 1459.395
 [9] 1413.795 1454.035
> rowVars(tmp5)
 [1] 7853.58503   98.10672   91.58841   48.68393   82.10875   67.39373
 [7]   92.64250   74.33372   45.32455   92.45775
> rowSd(tmp5)
 [1] 88.620455  9.904883  9.570183  6.977387  9.061388  8.209368  9.625097
 [8]  8.621701  6.732351  9.615495
> rowMax(tmp5)
 [1] 466.86561  91.29578  85.82699        NA  89.92097  90.52077  84.59118
 [8]  92.28979  81.82230  93.01259
> rowMin(tmp5)
 [1] 56.33617 56.97525 53.80605       NA 57.24512 62.53844 53.74250 56.30984
 [9] 58.01050 53.63495
> 
> colMeans(tmp5)
 [1] 111.98298  69.20567  70.48140  77.54761  69.63202  75.97644  69.35865
 [8]  71.73165  72.60325  71.17663  70.43190  71.67585  67.52454  65.60265
[15]  70.77787  70.03943  70.67744  67.80948  74.09131        NA
> colSums(tmp5)
 [1] 1119.8298  692.0567  704.8140  775.4761  696.3202  759.7644  693.5865
 [8]  717.3165  726.0325  711.7663  704.3190  716.7585  675.2454  656.0265
[15]  707.7787  700.3943  706.7744  678.0948  740.9131        NA
> colVars(tmp5)
 [1] 15604.68817    65.16360    64.04069    51.27683   102.56053   100.13814
 [7]    92.06839    72.58785    95.02241   118.55195    60.13247    49.64655
[13]    77.38137   121.41487    64.44422    57.42801    45.26431    88.38596
[19]    45.40140          NA
> colSd(tmp5)
 [1] 124.918726   8.072397   8.002543   7.160784  10.127217  10.006904
 [7]   9.595227   8.519850   9.747944  10.888157   7.754513   7.046031
[13]   8.796668  11.018841   8.027716   7.578127   6.727876   9.401381
[19]   6.738056         NA
> colMax(tmp5)
 [1] 466.86561  81.60211  84.88008  93.01259  89.92097  90.00506  80.68028
 [8]  86.72278  91.29578  88.42545  85.82699  80.27697  81.82230  90.52077
[15]  81.02524  81.21745  87.54397  78.98626  83.93678        NA
> colMin(tmp5)
 [1] 61.87026 59.02324 62.55159 69.40591 53.91807 61.93588 56.12881 62.53844
 [9] 56.33617 53.63495 60.98585 58.03816 56.39710 56.30984 57.63095 59.87138
[17] 63.25584 53.74250 60.79962       NA
> 
> Max(tmp5,na.rm=TRUE)
[1] 466.8656
> Min(tmp5,na.rm=TRUE)
[1] 53.63495
> mean(tmp5,na.rm=TRUE)
[1] 73.06824
> Sum(tmp5,na.rm=TRUE)
[1] 14540.58
> Var(tmp5,na.rm=TRUE)
[1] 862.2976
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.71937 71.33217 67.79334 69.13451 71.39814 73.87632 68.87072 72.96973
 [9] 70.68973 72.70173
> rowSums(tmp5,na.rm=TRUE)
 [1] 1834.387 1426.643 1355.867 1313.556 1427.963 1477.526 1377.414 1459.395
 [9] 1413.795 1454.035
> rowVars(tmp5,na.rm=TRUE)
 [1] 7853.58503   98.10672   91.58841   48.68393   82.10875   67.39373
 [7]   92.64250   74.33372   45.32455   92.45775
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.620455  9.904883  9.570183  6.977387  9.061388  8.209368  9.625097
 [8]  8.621701  6.732351  9.615495
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.86561  91.29578  85.82699  82.42419  89.92097  90.52077  84.59118
 [8]  92.28979  81.82230  93.01259
> rowMin(tmp5,na.rm=TRUE)
 [1] 56.33617 56.97525 53.80605 56.12881 57.24512 62.53844 53.74250 56.30984
 [9] 58.01050 53.63495
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.98298  69.20567  70.48140  77.54761  69.63202  75.97644  69.35865
 [8]  71.73165  72.60325  71.17663  70.43190  71.67585  67.52454  65.60265
[15]  70.77787  70.03943  70.67744  67.80948  74.09131  73.03476
> colSums(tmp5,na.rm=TRUE)
 [1] 1119.8298  692.0567  704.8140  775.4761  696.3202  759.7644  693.5865
 [8]  717.3165  726.0325  711.7663  704.3190  716.7585  675.2454  656.0265
[15]  707.7787  700.3943  706.7744  678.0948  740.9131  657.3128
> colVars(tmp5,na.rm=TRUE)
 [1] 15604.68817    65.16360    64.04069    51.27683   102.56053   100.13814
 [7]    92.06839    72.58785    95.02241   118.55195    60.13247    49.64655
[13]    77.38137   121.41487    64.44422    57.42801    45.26431    88.38596
[19]    45.40140    69.52391
> colSd(tmp5,na.rm=TRUE)
 [1] 124.918726   8.072397   8.002543   7.160784  10.127217  10.006904
 [7]   9.595227   8.519850   9.747944  10.888157   7.754513   7.046031
[13]   8.796668  11.018841   8.027716   7.578127   6.727876   9.401381
[19]   6.738056   8.338100
> colMax(tmp5,na.rm=TRUE)
 [1] 466.86561  81.60211  84.88008  93.01259  89.92097  90.00506  80.68028
 [8]  86.72278  91.29578  88.42545  85.82699  80.27697  81.82230  90.52077
[15]  81.02524  81.21745  87.54397  78.98626  83.93678  92.28979
> colMin(tmp5,na.rm=TRUE)
 [1] 61.87026 59.02324 62.55159 69.40591 53.91807 61.93588 56.12881 62.53844
 [9] 56.33617 53.63495 60.98585 58.03816 56.39710 56.30984 57.63095 59.87138
[17] 63.25584 53.74250 60.79962 65.85113
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.71937 71.33217 67.79334      NaN 71.39814 73.87632 68.87072 72.96973
 [9] 70.68973 72.70173
> rowSums(tmp5,na.rm=TRUE)
 [1] 1834.387 1426.643 1355.867    0.000 1427.963 1477.526 1377.414 1459.395
 [9] 1413.795 1454.035
> rowVars(tmp5,na.rm=TRUE)
 [1] 7853.58503   98.10672   91.58841         NA   82.10875   67.39373
 [7]   92.64250   74.33372   45.32455   92.45775
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.620455  9.904883  9.570183        NA  9.061388  8.209368  9.625097
 [8]  8.621701  6.732351  9.615495
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.86561  91.29578  85.82699        NA  89.92097  90.52077  84.59118
 [8]  92.28979  81.82230  93.01259
> rowMin(tmp5,na.rm=TRUE)
 [1] 56.33617 56.97525 53.80605       NA 57.24512 62.53844 53.74250 56.30984
 [9] 58.01050 53.63495
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 117.11663  70.13582  71.32804  78.38493  69.53165  76.93612  70.82863
 [8]  72.54207  73.10644  69.92690  70.75604  70.72017  67.86754  65.67626
[15]  69.84332  69.01036  70.70244  67.38478  74.83656       NaN
> colSums(tmp5,na.rm=TRUE)
 [1] 1054.0496  631.2224  641.9523  705.4644  625.7848  692.4251  637.4577
 [8]  652.8787  657.9580  629.3421  636.8043  636.4815  610.8078  591.0864
[15]  628.5899  621.0932  636.3219  606.4630  673.5291    0.0000
> colVars(tmp5,na.rm=TRUE)
 [1] 17258.78848    63.57579    63.98189    49.79896   115.26726   102.29426
 [7]    79.26740    74.27246   104.05171   115.80045    66.46707    45.57748
[13]    85.73053   136.53077    62.67413    52.69297    50.91532    97.40498
[19]    44.82836          NA
> colSd(tmp5,na.rm=TRUE)
 [1] 131.372708   7.973443   7.998868   7.056838  10.736259  10.114063
 [7]   8.903224   8.618147  10.200574  10.761062   8.152734   6.751110
[13]   9.259078  11.684638   7.916699   7.258992   7.135497   9.869396
[19]   6.695399         NA
> colMax(tmp5,na.rm=TRUE)
 [1] 466.86561  81.60211  84.88008  93.01259  89.92097  90.00506  80.68028
 [8]  86.72278  91.29578  88.42545  85.82699  77.03679  81.82230  90.52077
[15]  81.02524  81.21745  87.54397  78.98626  83.93678      -Inf
> colMin(tmp5,na.rm=TRUE)
 [1] 61.87026 59.02324 62.55159 69.40591 53.91807 61.93588 56.97525 62.53844
 [9] 56.33617 53.63495 60.98585 58.03816 56.39710 56.30984 57.63095 59.87138
[17] 63.25584 53.74250 60.79962      Inf
> 
> 
> 
> 
> copymatrix <- matrix(rnorm(200,150,15),10,20)
> 
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col  <- 1
> cat(which.row," ",which.col,"\n")
3   1 
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
> 
> rowVars(tmp5,na.rm=TRUE)
 [1] 366.0464 205.0505 236.1161 145.2982 229.2272 209.6012 283.2792 135.2621
 [9] 269.1541 215.6350
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 366.0464 205.0505 236.1161 145.2982 229.2272 209.6012 283.2792 135.2621
 [9] 269.1541 215.6350
> 
> 
> 
> copymatrix <- matrix(rnorm(200,150,15),10,20)
> 
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col  <- 3
> cat(which.row," ",which.col,"\n")
1   3 
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
> 
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
 [1]  0.000000e+00  1.705303e-13  8.526513e-14  7.105427e-14 -1.136868e-13
 [6]  5.684342e-14 -8.526513e-14  0.000000e+00  1.705303e-13  0.000000e+00
[11]  2.842171e-14 -1.136868e-13 -3.410605e-13  5.684342e-14  2.842171e-14
[16]  1.705303e-13  5.684342e-14 -2.842171e-14  1.136868e-13  5.684342e-14
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## making sure these things agree
> ##
> ## first when there is no NA
> 
> 
> 
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+ 
+   if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Max")
+   }
+   
+ 
+   if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Min")
+   }
+ 
+ 
+   if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+ 
+     cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+     cat(sum(r.matrix,na.rm=TRUE),"\n")
+     cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+     
+     stop("No agreement in Sum")
+   }
+   
+   if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+     stop("No agreement in mean")
+   }
+   
+   
+   if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+     stop("No agreement in Var")
+   }
+   
+   
+ 
+   if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowMeans")
+   }
+   
+   
+   if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colMeans")
+   }
+   
+   
+   if(any(abs(rowSums(buff.matrix,na.rm=TRUE)  -  apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in rowSums")
+   }
+   
+   
+   if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colSums")
+   }
+   
+   ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when 
+   ### computing variance
+   my.Var <- function(x,na.rm=FALSE){
+    if (all(is.na(x))){
+      return(NA)
+    } else {
+      var(x,na.rm=na.rm)
+    }
+ 
+   }
+   
+   if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+   
+   
+   if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+ 
+ 
+   if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+ 
+   if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+   
+   
+   if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+   
+ 
+   if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+ 
+   if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMedian")
+   }
+ 
+   if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colRanges")
+   }
+ 
+ 
+   
+ }
> 
> 
> 
> 
> 
> 
> 
> 
> 
> for (rep in 1:20){
+   copymatrix <- matrix(rnorm(200,150,15),10,20)
+   
+   tmp5[1:10,1:20] <- copymatrix
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ## now lets assign some NA values and check agreement
+ 
+   which.row <- sample(1:10,1,replace=TRUE)
+   which.col  <- sample(1:20,1,replace=TRUE)
+   
+   cat(which.row," ",which.col,"\n")
+   
+   tmp5[which.row,which.col] <- NA
+   copymatrix[which.row,which.col] <- NA
+   
+   agree.checks(tmp5,copymatrix)
+ 
+   ## make an entire row NA
+   tmp5[which.row,] <- NA
+   copymatrix[which.row,] <- NA
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ### also make an entire col NA
+   tmp5[,which.col] <- NA
+   copymatrix[,which.col] <- NA
+ 
+   agree.checks(tmp5,copymatrix)
+ 
+   ### now make 1 element non NA with NA in the rest of row and column
+ 
+   tmp5[which.row,which.col] <- rnorm(1,150,15)
+   copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+ 
+   agree.checks(tmp5,copymatrix)
+ }
3   7 
4   1 
9   1 
8   12 
6   17 
3   2 
9   19 
6   11 
8   16 
9   12 
4   14 
2   18 
5   1 
3   1 
1   10 
2   20 
2   14 
2   14 
4   16 
6   16 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> ### now test 1 by n and n by 1 matrix
> 
> 
> err.tol <- 1e-12
> 
> rm(tmp5)
> 
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
> 
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
> 
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
> 
> 
> 
> 
> 
> Max(tmp)
[1] 2.017961
> Min(tmp)
[1] -2.474488
> mean(tmp)
[1] 0.004864573
> Sum(tmp)
[1] 0.4864573
> Var(tmp)
[1] 0.8432637
> 
> rowMeans(tmp)
[1] 0.004864573
> rowSums(tmp)
[1] 0.4864573
> rowVars(tmp)
[1] 0.8432637
> rowSd(tmp)
[1] 0.9182939
> rowMax(tmp)
[1] 2.017961
> rowMin(tmp)
[1] -2.474488
> 
> colMeans(tmp)
  [1]  0.388298131 -0.829118903 -0.722350413  0.730371690  0.275962186
  [6] -0.207321618  0.002604093 -1.018983243  0.529474690  1.003035619
 [11]  0.989312549 -1.755287322 -0.049128144 -0.138525136  0.176382439
 [16] -0.337241279 -1.924364702 -0.253297232 -0.020249173  0.310184470
 [21]  1.369130702  0.311327800  0.139810364  1.848236831 -0.166978536
 [26]  1.339765861 -0.152063264  0.759845867  1.295334224  1.597372862
 [31] -0.229508798  1.158464406 -0.372645669  0.559392100  0.425616942
 [36]  1.620586944  0.529574337  0.853859268  0.526883888 -1.731924382
 [41]  0.456138279 -0.322552495  0.158458391 -0.247548069 -0.465287252
 [46] -0.178068604  0.359052682  0.836241189  0.365320087  1.704594915
 [51]  0.205280396 -0.285824132  0.094906305 -0.799560372  0.894557104
 [56]  0.327603907  0.562726259  1.375300020 -0.601405051 -0.750348059
 [61]  0.102445385 -0.423581900 -1.458303644 -0.434878963  0.843263615
 [66]  0.314664336 -0.730052835 -0.489773884  0.294508946 -1.545477207
 [71] -0.819769217  1.718275503 -1.413191079  0.070862290 -0.399412587
 [76]  2.017960706  0.155826006 -0.141438359 -0.494643644 -0.414121175
 [81] -1.004134709  0.211019671  0.617642918 -2.043800809 -0.109026996
 [86]  0.013108128  0.718363423 -1.926593506  0.939762020 -0.745712127
 [91] -0.912665186  0.650109440  0.088486346 -0.169247637  0.834670764
 [96] -2.474487611 -1.705794122 -1.126548366 -0.495124773 -0.148157776
> colSums(tmp)
  [1]  0.388298131 -0.829118903 -0.722350413  0.730371690  0.275962186
  [6] -0.207321618  0.002604093 -1.018983243  0.529474690  1.003035619
 [11]  0.989312549 -1.755287322 -0.049128144 -0.138525136  0.176382439
 [16] -0.337241279 -1.924364702 -0.253297232 -0.020249173  0.310184470
 [21]  1.369130702  0.311327800  0.139810364  1.848236831 -0.166978536
 [26]  1.339765861 -0.152063264  0.759845867  1.295334224  1.597372862
 [31] -0.229508798  1.158464406 -0.372645669  0.559392100  0.425616942
 [36]  1.620586944  0.529574337  0.853859268  0.526883888 -1.731924382
 [41]  0.456138279 -0.322552495  0.158458391 -0.247548069 -0.465287252
 [46] -0.178068604  0.359052682  0.836241189  0.365320087  1.704594915
 [51]  0.205280396 -0.285824132  0.094906305 -0.799560372  0.894557104
 [56]  0.327603907  0.562726259  1.375300020 -0.601405051 -0.750348059
 [61]  0.102445385 -0.423581900 -1.458303644 -0.434878963  0.843263615
 [66]  0.314664336 -0.730052835 -0.489773884  0.294508946 -1.545477207
 [71] -0.819769217  1.718275503 -1.413191079  0.070862290 -0.399412587
 [76]  2.017960706  0.155826006 -0.141438359 -0.494643644 -0.414121175
 [81] -1.004134709  0.211019671  0.617642918 -2.043800809 -0.109026996
 [86]  0.013108128  0.718363423 -1.926593506  0.939762020 -0.745712127
 [91] -0.912665186  0.650109440  0.088486346 -0.169247637  0.834670764
 [96] -2.474487611 -1.705794122 -1.126548366 -0.495124773 -0.148157776
> colVars(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
  [1]  0.388298131 -0.829118903 -0.722350413  0.730371690  0.275962186
  [6] -0.207321618  0.002604093 -1.018983243  0.529474690  1.003035619
 [11]  0.989312549 -1.755287322 -0.049128144 -0.138525136  0.176382439
 [16] -0.337241279 -1.924364702 -0.253297232 -0.020249173  0.310184470
 [21]  1.369130702  0.311327800  0.139810364  1.848236831 -0.166978536
 [26]  1.339765861 -0.152063264  0.759845867  1.295334224  1.597372862
 [31] -0.229508798  1.158464406 -0.372645669  0.559392100  0.425616942
 [36]  1.620586944  0.529574337  0.853859268  0.526883888 -1.731924382
 [41]  0.456138279 -0.322552495  0.158458391 -0.247548069 -0.465287252
 [46] -0.178068604  0.359052682  0.836241189  0.365320087  1.704594915
 [51]  0.205280396 -0.285824132  0.094906305 -0.799560372  0.894557104
 [56]  0.327603907  0.562726259  1.375300020 -0.601405051 -0.750348059
 [61]  0.102445385 -0.423581900 -1.458303644 -0.434878963  0.843263615
 [66]  0.314664336 -0.730052835 -0.489773884  0.294508946 -1.545477207
 [71] -0.819769217  1.718275503 -1.413191079  0.070862290 -0.399412587
 [76]  2.017960706  0.155826006 -0.141438359 -0.494643644 -0.414121175
 [81] -1.004134709  0.211019671  0.617642918 -2.043800809 -0.109026996
 [86]  0.013108128  0.718363423 -1.926593506  0.939762020 -0.745712127
 [91] -0.912665186  0.650109440  0.088486346 -0.169247637  0.834670764
 [96] -2.474487611 -1.705794122 -1.126548366 -0.495124773 -0.148157776
> colMin(tmp)
  [1]  0.388298131 -0.829118903 -0.722350413  0.730371690  0.275962186
  [6] -0.207321618  0.002604093 -1.018983243  0.529474690  1.003035619
 [11]  0.989312549 -1.755287322 -0.049128144 -0.138525136  0.176382439
 [16] -0.337241279 -1.924364702 -0.253297232 -0.020249173  0.310184470
 [21]  1.369130702  0.311327800  0.139810364  1.848236831 -0.166978536
 [26]  1.339765861 -0.152063264  0.759845867  1.295334224  1.597372862
 [31] -0.229508798  1.158464406 -0.372645669  0.559392100  0.425616942
 [36]  1.620586944  0.529574337  0.853859268  0.526883888 -1.731924382
 [41]  0.456138279 -0.322552495  0.158458391 -0.247548069 -0.465287252
 [46] -0.178068604  0.359052682  0.836241189  0.365320087  1.704594915
 [51]  0.205280396 -0.285824132  0.094906305 -0.799560372  0.894557104
 [56]  0.327603907  0.562726259  1.375300020 -0.601405051 -0.750348059
 [61]  0.102445385 -0.423581900 -1.458303644 -0.434878963  0.843263615
 [66]  0.314664336 -0.730052835 -0.489773884  0.294508946 -1.545477207
 [71] -0.819769217  1.718275503 -1.413191079  0.070862290 -0.399412587
 [76]  2.017960706  0.155826006 -0.141438359 -0.494643644 -0.414121175
 [81] -1.004134709  0.211019671  0.617642918 -2.043800809 -0.109026996
 [86]  0.013108128  0.718363423 -1.926593506  0.939762020 -0.745712127
 [91] -0.912665186  0.650109440  0.088486346 -0.169247637  0.834670764
 [96] -2.474487611 -1.705794122 -1.126548366 -0.495124773 -0.148157776
> colMedians(tmp)
  [1]  0.388298131 -0.829118903 -0.722350413  0.730371690  0.275962186
  [6] -0.207321618  0.002604093 -1.018983243  0.529474690  1.003035619
 [11]  0.989312549 -1.755287322 -0.049128144 -0.138525136  0.176382439
 [16] -0.337241279 -1.924364702 -0.253297232 -0.020249173  0.310184470
 [21]  1.369130702  0.311327800  0.139810364  1.848236831 -0.166978536
 [26]  1.339765861 -0.152063264  0.759845867  1.295334224  1.597372862
 [31] -0.229508798  1.158464406 -0.372645669  0.559392100  0.425616942
 [36]  1.620586944  0.529574337  0.853859268  0.526883888 -1.731924382
 [41]  0.456138279 -0.322552495  0.158458391 -0.247548069 -0.465287252
 [46] -0.178068604  0.359052682  0.836241189  0.365320087  1.704594915
 [51]  0.205280396 -0.285824132  0.094906305 -0.799560372  0.894557104
 [56]  0.327603907  0.562726259  1.375300020 -0.601405051 -0.750348059
 [61]  0.102445385 -0.423581900 -1.458303644 -0.434878963  0.843263615
 [66]  0.314664336 -0.730052835 -0.489773884  0.294508946 -1.545477207
 [71] -0.819769217  1.718275503 -1.413191079  0.070862290 -0.399412587
 [76]  2.017960706  0.155826006 -0.141438359 -0.494643644 -0.414121175
 [81] -1.004134709  0.211019671  0.617642918 -2.043800809 -0.109026996
 [86]  0.013108128  0.718363423 -1.926593506  0.939762020 -0.745712127
 [91] -0.912665186  0.650109440  0.088486346 -0.169247637  0.834670764
 [96] -2.474487611 -1.705794122 -1.126548366 -0.495124773 -0.148157776
> colRanges(tmp)
          [,1]       [,2]       [,3]      [,4]      [,5]       [,6]        [,7]
[1,] 0.3882981 -0.8291189 -0.7223504 0.7303717 0.2759622 -0.2073216 0.002604093
[2,] 0.3882981 -0.8291189 -0.7223504 0.7303717 0.2759622 -0.2073216 0.002604093
          [,8]      [,9]    [,10]     [,11]     [,12]       [,13]      [,14]
[1,] -1.018983 0.5294747 1.003036 0.9893125 -1.755287 -0.04912814 -0.1385251
[2,] -1.018983 0.5294747 1.003036 0.9893125 -1.755287 -0.04912814 -0.1385251
         [,15]      [,16]     [,17]      [,18]       [,19]     [,20]    [,21]
[1,] 0.1763824 -0.3372413 -1.924365 -0.2532972 -0.02024917 0.3101845 1.369131
[2,] 0.1763824 -0.3372413 -1.924365 -0.2532972 -0.02024917 0.3101845 1.369131
         [,22]     [,23]    [,24]      [,25]    [,26]      [,27]     [,28]
[1,] 0.3113278 0.1398104 1.848237 -0.1669785 1.339766 -0.1520633 0.7598459
[2,] 0.3113278 0.1398104 1.848237 -0.1669785 1.339766 -0.1520633 0.7598459
        [,29]    [,30]      [,31]    [,32]      [,33]     [,34]     [,35]
[1,] 1.295334 1.597373 -0.2295088 1.158464 -0.3726457 0.5593921 0.4256169
[2,] 1.295334 1.597373 -0.2295088 1.158464 -0.3726457 0.5593921 0.4256169
        [,36]     [,37]     [,38]     [,39]     [,40]     [,41]      [,42]
[1,] 1.620587 0.5295743 0.8538593 0.5268839 -1.731924 0.4561383 -0.3225525
[2,] 1.620587 0.5295743 0.8538593 0.5268839 -1.731924 0.4561383 -0.3225525
         [,43]      [,44]      [,45]      [,46]     [,47]     [,48]     [,49]
[1,] 0.1584584 -0.2475481 -0.4652873 -0.1780686 0.3590527 0.8362412 0.3653201
[2,] 0.1584584 -0.2475481 -0.4652873 -0.1780686 0.3590527 0.8362412 0.3653201
        [,50]     [,51]      [,52]      [,53]      [,54]     [,55]     [,56]
[1,] 1.704595 0.2052804 -0.2858241 0.09490631 -0.7995604 0.8945571 0.3276039
[2,] 1.704595 0.2052804 -0.2858241 0.09490631 -0.7995604 0.8945571 0.3276039
         [,57]  [,58]      [,59]      [,60]     [,61]      [,62]     [,63]
[1,] 0.5627263 1.3753 -0.6014051 -0.7503481 0.1024454 -0.4235819 -1.458304
[2,] 0.5627263 1.3753 -0.6014051 -0.7503481 0.1024454 -0.4235819 -1.458304
         [,64]     [,65]     [,66]      [,67]      [,68]     [,69]     [,70]
[1,] -0.434879 0.8432636 0.3146643 -0.7300528 -0.4897739 0.2945089 -1.545477
[2,] -0.434879 0.8432636 0.3146643 -0.7300528 -0.4897739 0.2945089 -1.545477
          [,71]    [,72]     [,73]      [,74]      [,75]    [,76]    [,77]
[1,] -0.8197692 1.718276 -1.413191 0.07086229 -0.3994126 2.017961 0.155826
[2,] -0.8197692 1.718276 -1.413191 0.07086229 -0.3994126 2.017961 0.155826
          [,78]      [,79]      [,80]     [,81]     [,82]     [,83]     [,84]
[1,] -0.1414384 -0.4946436 -0.4141212 -1.004135 0.2110197 0.6176429 -2.043801
[2,] -0.1414384 -0.4946436 -0.4141212 -1.004135 0.2110197 0.6176429 -2.043801
         [,85]      [,86]     [,87]     [,88]    [,89]      [,90]      [,91]
[1,] -0.109027 0.01310813 0.7183634 -1.926594 0.939762 -0.7457121 -0.9126652
[2,] -0.109027 0.01310813 0.7183634 -1.926594 0.939762 -0.7457121 -0.9126652
         [,92]      [,93]      [,94]     [,95]     [,96]     [,97]     [,98]
[1,] 0.6501094 0.08848635 -0.1692476 0.8346708 -2.474488 -1.705794 -1.126548
[2,] 0.6501094 0.08848635 -0.1692476 0.8346708 -2.474488 -1.705794 -1.126548
          [,99]     [,100]
[1,] -0.4951248 -0.1481578
[2,] -0.4951248 -0.1481578
> 
> 
> Max(tmp2)
[1] 2.162894
> Min(tmp2)
[1] -2.501066
> mean(tmp2)
[1] -0.07926129
> Sum(tmp2)
[1] -7.926129
> Var(tmp2)
[1] 1.093321
> 
> rowMeans(tmp2)
  [1]  0.243180494 -0.598707884 -0.523509397 -0.344683994  1.258691985
  [6]  0.034464642 -0.246497982  1.594628915 -0.968010880 -0.306443361
 [11]  0.668240237 -0.418741373 -0.888095536 -0.192606267  0.633915450
 [16] -1.313338436  0.872978282 -0.720814390 -0.449594972 -1.173218852
 [21] -0.001219281 -1.562668566 -0.423280298  1.106383157  1.065212016
 [26]  0.040910296 -0.348782451  0.483000802  1.682365074 -0.781233859
 [31] -2.501065940 -0.132006161  1.423902631 -0.172396818  1.893714739
 [36] -0.992984076  0.016055169  2.136162778 -0.395876557 -0.668453727
 [41]  1.183567510 -0.875640699 -1.687396208 -1.356436152 -0.954440280
 [46] -1.968921137 -0.594293106  1.169696004  1.605314385  0.005120101
 [51]  1.014785282  0.466361030  1.597575096 -0.525677740  0.700451862
 [56]  0.505115125  0.875738124 -1.893429829 -0.515817349 -1.528631409
 [61] -0.129773626 -1.545539514  0.143295874 -1.460524080  0.405120408
 [66]  2.162893813  0.019842560 -1.533953035  1.132682340 -0.878942138
 [71]  0.086730368 -1.815008367 -0.049956208 -0.679955121  1.726704752
 [76]  0.723802695  1.607878695  0.337718880 -0.024121557 -0.518042773
 [81] -0.006450828  1.897407012 -0.669741834 -0.506640204  0.267245459
 [86]  0.501737428 -1.186867132 -0.862923176 -1.172870542 -1.259195275
 [91]  0.390154451  2.035429694 -1.350602247 -0.819260036 -0.354356388
 [96]  0.077521697  0.555989275 -0.757930257 -0.422522538 -0.245723713
> rowSums(tmp2)
  [1]  0.243180494 -0.598707884 -0.523509397 -0.344683994  1.258691985
  [6]  0.034464642 -0.246497982  1.594628915 -0.968010880 -0.306443361
 [11]  0.668240237 -0.418741373 -0.888095536 -0.192606267  0.633915450
 [16] -1.313338436  0.872978282 -0.720814390 -0.449594972 -1.173218852
 [21] -0.001219281 -1.562668566 -0.423280298  1.106383157  1.065212016
 [26]  0.040910296 -0.348782451  0.483000802  1.682365074 -0.781233859
 [31] -2.501065940 -0.132006161  1.423902631 -0.172396818  1.893714739
 [36] -0.992984076  0.016055169  2.136162778 -0.395876557 -0.668453727
 [41]  1.183567510 -0.875640699 -1.687396208 -1.356436152 -0.954440280
 [46] -1.968921137 -0.594293106  1.169696004  1.605314385  0.005120101
 [51]  1.014785282  0.466361030  1.597575096 -0.525677740  0.700451862
 [56]  0.505115125  0.875738124 -1.893429829 -0.515817349 -1.528631409
 [61] -0.129773626 -1.545539514  0.143295874 -1.460524080  0.405120408
 [66]  2.162893813  0.019842560 -1.533953035  1.132682340 -0.878942138
 [71]  0.086730368 -1.815008367 -0.049956208 -0.679955121  1.726704752
 [76]  0.723802695  1.607878695  0.337718880 -0.024121557 -0.518042773
 [81] -0.006450828  1.897407012 -0.669741834 -0.506640204  0.267245459
 [86]  0.501737428 -1.186867132 -0.862923176 -1.172870542 -1.259195275
 [91]  0.390154451  2.035429694 -1.350602247 -0.819260036 -0.354356388
 [96]  0.077521697  0.555989275 -0.757930257 -0.422522538 -0.245723713
> rowVars(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
  [1]  0.243180494 -0.598707884 -0.523509397 -0.344683994  1.258691985
  [6]  0.034464642 -0.246497982  1.594628915 -0.968010880 -0.306443361
 [11]  0.668240237 -0.418741373 -0.888095536 -0.192606267  0.633915450
 [16] -1.313338436  0.872978282 -0.720814390 -0.449594972 -1.173218852
 [21] -0.001219281 -1.562668566 -0.423280298  1.106383157  1.065212016
 [26]  0.040910296 -0.348782451  0.483000802  1.682365074 -0.781233859
 [31] -2.501065940 -0.132006161  1.423902631 -0.172396818  1.893714739
 [36] -0.992984076  0.016055169  2.136162778 -0.395876557 -0.668453727
 [41]  1.183567510 -0.875640699 -1.687396208 -1.356436152 -0.954440280
 [46] -1.968921137 -0.594293106  1.169696004  1.605314385  0.005120101
 [51]  1.014785282  0.466361030  1.597575096 -0.525677740  0.700451862
 [56]  0.505115125  0.875738124 -1.893429829 -0.515817349 -1.528631409
 [61] -0.129773626 -1.545539514  0.143295874 -1.460524080  0.405120408
 [66]  2.162893813  0.019842560 -1.533953035  1.132682340 -0.878942138
 [71]  0.086730368 -1.815008367 -0.049956208 -0.679955121  1.726704752
 [76]  0.723802695  1.607878695  0.337718880 -0.024121557 -0.518042773
 [81] -0.006450828  1.897407012 -0.669741834 -0.506640204  0.267245459
 [86]  0.501737428 -1.186867132 -0.862923176 -1.172870542 -1.259195275
 [91]  0.390154451  2.035429694 -1.350602247 -0.819260036 -0.354356388
 [96]  0.077521697  0.555989275 -0.757930257 -0.422522538 -0.245723713
> rowMin(tmp2)
  [1]  0.243180494 -0.598707884 -0.523509397 -0.344683994  1.258691985
  [6]  0.034464642 -0.246497982  1.594628915 -0.968010880 -0.306443361
 [11]  0.668240237 -0.418741373 -0.888095536 -0.192606267  0.633915450
 [16] -1.313338436  0.872978282 -0.720814390 -0.449594972 -1.173218852
 [21] -0.001219281 -1.562668566 -0.423280298  1.106383157  1.065212016
 [26]  0.040910296 -0.348782451  0.483000802  1.682365074 -0.781233859
 [31] -2.501065940 -0.132006161  1.423902631 -0.172396818  1.893714739
 [36] -0.992984076  0.016055169  2.136162778 -0.395876557 -0.668453727
 [41]  1.183567510 -0.875640699 -1.687396208 -1.356436152 -0.954440280
 [46] -1.968921137 -0.594293106  1.169696004  1.605314385  0.005120101
 [51]  1.014785282  0.466361030  1.597575096 -0.525677740  0.700451862
 [56]  0.505115125  0.875738124 -1.893429829 -0.515817349 -1.528631409
 [61] -0.129773626 -1.545539514  0.143295874 -1.460524080  0.405120408
 [66]  2.162893813  0.019842560 -1.533953035  1.132682340 -0.878942138
 [71]  0.086730368 -1.815008367 -0.049956208 -0.679955121  1.726704752
 [76]  0.723802695  1.607878695  0.337718880 -0.024121557 -0.518042773
 [81] -0.006450828  1.897407012 -0.669741834 -0.506640204  0.267245459
 [86]  0.501737428 -1.186867132 -0.862923176 -1.172870542 -1.259195275
 [91]  0.390154451  2.035429694 -1.350602247 -0.819260036 -0.354356388
 [96]  0.077521697  0.555989275 -0.757930257 -0.422522538 -0.245723713
> 
> colMeans(tmp2)
[1] -0.07926129
> colSums(tmp2)
[1] -7.926129
> colVars(tmp2)
[1] 1.093321
> colSd(tmp2)
[1] 1.04562
> colMax(tmp2)
[1] 2.162894
> colMin(tmp2)
[1] -2.501066
> colMedians(tmp2)
[1] -0.1825015
> colRanges(tmp2)
          [,1]
[1,] -2.501066
[2,]  2.162894
> 
> dataset1 <- matrix(dataset1,1,100)
> 
> agree.checks(tmp,dataset1)
> 
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>   
> 
> tmp <- createBufferedMatrix(10,10)
> 
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
 [1]  0.8101832 -7.3238786 -2.5343781  6.0882263  0.5489007  2.0925742
 [7]  0.2584282  2.8763343  0.9396649 -1.1490886
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -1.00861861
[2,] -0.70852544
[3,] -0.02369848
[4,]  0.41196401
[5,]  1.81841508
> 
> rowApply(tmp,sum)
 [1]  0.4785746 -0.4634977  2.6272203  0.7435411 -0.5439789 -1.3255446
 [7]  5.1587405 -1.6297346 -1.8415706 -0.5967837
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    9    4    9    2    3    3    7    7    2     8
 [2,]    1    5    1    3    5    2    8    1    1     2
 [3,]    6    1   10    5    1    8    4    2    5     7
 [4,]   10    6    7    9    6    9    5    5   10     1
 [5,]    5    9    4    7    9    1    2   10    7     9
 [6,]    8    2    2    4    8    4   10    6    9     3
 [7,]    7    7    6    6    7    7    6    3    6     4
 [8,]    4    3    8   10    4    5    9    8    4     6
 [9,]    2    8    5    8   10   10    1    4    3     5
[10,]    3   10    3    1    2    6    3    9    8    10
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1] -2.9500215  1.7916467 -2.4065231 -1.5725152  0.7736759  1.3175729
 [7]  0.1411892  2.8904583  0.1405575  2.3910914 -2.2531530  1.2685228
[13] -3.9943692  1.7901563 -1.3431002 -0.4732238  2.9167760  3.3902206
[19]  0.8159190 -0.6362984
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.2262160
[2,] -1.1684351
[3,] -1.0545242
[4,] -0.3409403
[5,]  0.8400939
> 
> rowApply(tmp,sum)
[1] -1.4328673 -1.6763222  9.5534998  0.1909124 -2.6366406
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]    4    8   15    2    5
[2,]   18    7    8   13   16
[3,]   16   16    5    3    1
[4,]   15   11    2   12    2
[5,]    7    1   19    8   19
> 
> 
> as.matrix(tmp)
           [,1]         [,2]       [,3]        [,4]       [,5]       [,6]
[1,] -1.0545242  0.846118485  0.7281777  0.59510953 -0.7152826  0.8005353
[2,] -0.3409403 -0.377669411  0.3213578 -0.06099323 -1.4878407 -0.6215555
[3,]  0.8400939 -0.001689981 -0.3897796 -0.94481993  1.9923647  1.7312138
[4,] -1.2262160  0.410810459 -0.9808167  0.37464337 -0.3695683 -0.3675498
[5,] -1.1684351  0.914077169 -2.0854623 -1.53645494  1.3540027 -0.2250710
           [,7]       [,8]       [,9]       [,10]      [,11]      [,12]
[1,] -1.4369682  1.4706556 -0.3655434 -0.83633476  0.2416408 -0.3966737
[2,]  0.1402269 -0.7811499 -0.6336099  1.17242868 -1.0049603 -0.1459915
[3,]  0.7630806 -0.2831088  0.3135136  0.77251046 -1.5181696  0.9899258
[4,]  0.5573992  1.4913785  0.4800141  1.22266921  0.5291327 -0.7686639
[5,]  0.1174508  0.9926829  0.3461831  0.05981779 -0.5007966  1.5899261
          [,13]      [,14]      [,15]      [,16]       [,17]      [,18]
[1,] -1.0939463  1.6860878  0.1887674  0.4169545 -1.56367056 -1.0054907
[2,] -0.5491559  0.1151707  0.1364515 -0.2799037  0.77673981  1.3570536
[3,]  0.6456997 -0.8784107 -0.7506162  0.8098109  3.06046292  1.7841750
[4,] -1.5437966  0.9833537 -0.6935214 -0.5701037 -0.06806139  0.2855525
[5,] -1.4531699 -0.1160453 -0.2241816 -0.8499818  0.71130521  0.9689303
           [,19]      [,20]
[1,] -0.38371491  0.4452349
[2,]  0.32938980  0.2586293
[3,] -0.03855277  0.6557959
[4,]  1.10417838 -0.6599220
[5,] -0.19538155 -1.3360365
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  800  bytes.
> 
> 
> 
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size:  5 5 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  643  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  558  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  480  bytes.
> 
> 
> rm(tmp)
> 
> 
> ###
> ### Testing colnames and rownames
> ###
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> 
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> tmp["row1",]
          col1     col2      col3      col4      col5     col6      col7
row1 0.2658358 1.518363 -1.801001 0.0742698 -1.024368 1.889207 0.1523091
           col8       col9     col10     col11    col12     col13     col14
row1 -0.6989447 -0.1531445 0.6819267 -2.029068 2.310776 -1.266825 -1.701845
         col15      col16     col17     col18       col19      col20
row1 0.2676376 -0.2457559 -1.603232 -1.483972 0.001335041 -0.3620179
> tmp[,"col10"]
           col10
row1  0.68192666
row2 -0.70130898
row3  0.84540172
row4  0.03763114
row5 -1.08361242
> tmp[c("row1","row5"),]
           col1       col2      col3       col4       col5       col6
row1  0.2658358  1.5183634 -1.801001  0.0742698 -1.0243683  1.8892067
row5 -1.4412237 -0.8196483  1.310672 -0.9435499 -0.9961925 -0.1669772
           col7       col8       col9      col10     col11    col12     col13
row1  0.1523091 -0.6989447 -0.1531445  0.6819267 -2.029068 2.310776 -1.266825
row5 -0.5289285  0.6637350 -1.8679281 -1.0836124 -1.491911 1.082868  1.716880
          col14      col15      col16      col17     col18       col19
row1 -1.7018446  0.2676376 -0.2457559 -1.6032321 -1.483972 0.001335041
row5  0.0951304 -0.5657630  0.6364319 -0.3508701  1.840926 1.936989654
          col20
row1 -0.3620179
row5  0.8695541
> tmp[,c("col6","col20")]
            col6      col20
row1  1.88920666 -0.3620179
row2  0.61834648 -0.8006323
row3 -0.15453148 -1.6656892
row4  0.07547116 -1.4789879
row5 -0.16697722  0.8695541
> tmp[c("row1","row5"),c("col6","col20")]
           col6      col20
row1  1.8892067 -0.3620179
row5 -0.1669772  0.8695541
> 
> 
> 
> 
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")]  <- rnorm(4,mean=105)
> 
> tmp["row1",]
        col1     col2     col3     col4     col5     col6     col7     col8
row1 50.9119 48.87514 50.04415 49.82565 49.75082 104.9051 50.53967 49.29491
         col9    col10    col11    col12    col13    col14    col15    col16
row1 50.29463 50.34914 51.09758 51.19911 50.69688 49.17518 48.70036 51.34037
        col17    col18    col19    col20
row1 51.26183 47.31379 50.06559 105.0696
> tmp[,"col10"]
        col10
row1 50.34914
row2 30.47597
row3 28.42333
row4 29.75476
row5 49.98163
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 50.91190 48.87514 50.04415 49.82565 49.75082 104.9051 50.53967 49.29491
row5 51.59985 50.38273 49.59499 50.41144 51.15931 104.3609 50.02766 49.48930
         col9    col10    col11    col12    col13    col14    col15    col16
row1 50.29463 50.34914 51.09758 51.19911 50.69688 49.17518 48.70036 51.34037
row5 48.88004 49.98163 50.99156 50.10501 48.82699 49.23385 49.97024 49.51814
        col17    col18    col19    col20
row1 51.26183 47.31379 50.06559 105.0696
row5 52.45756 48.99519 49.75273 105.2841
> tmp[,c("col6","col20")]
          col6     col20
row1 104.90512 105.06960
row2  74.55601  74.63314
row3  74.30309  76.32959
row4  75.15875  75.45756
row5 104.36093 105.28410
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 104.9051 105.0696
row5 104.3609 105.2841
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 104.9051 105.0696
row5 104.3609 105.2841
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,] -0.1654240
[2,]  0.2572335
[3,] -0.1276917
[4,]  1.9068185
[5,]  1.6786602
> tmp[,c("col17","col7")]
           col17       col7
[1,]  0.20157605 -0.2710607
[2,] -0.20948619 -0.6460538
[3,]  0.17363178  0.9232795
[4,]  0.04730316  1.3499820
[5,]  0.09879285  0.6559636
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
            col6        col20
[1,] -0.09131267  1.021168303
[2,] -1.02413695  0.406405292
[3,] -1.92598169 -0.068289360
[4,]  0.48336006  0.683985951
[5,]  0.08618670 -0.002899625
> subBufferedMatrix(tmp,1,c("col6"))[,1]
            col1
[1,] -0.09131267
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
            col6
[1,] -0.09131267
[2,] -1.02413695
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> 
> 
> 
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
          [,1]       [,2]       [,3]        [,4]       [,5]       [,6]
row3 1.7547810 -0.3847942 -0.7695121 -0.05649153  0.5981458 -0.7328675
row1 0.3421688  0.5214421  0.3654008  1.30549489 -0.7376696 -0.1952980
           [,7]       [,8]       [,9]     [,10]      [,11]    [,12]      [,13]
row3 -0.7914498 -0.6512425 -0.9487691  0.785016 -0.5653958 1.254606 -0.8955213
row1  0.8854214  1.0347519 -1.1085328 -1.178397  0.1679616 1.226007  0.7696713
         [,14]     [,15]      [,16]      [,17]        [,18]     [,19]     [,20]
row3 0.3848422 0.7488353  0.3465036 -0.4063492 -0.004792401  1.319181 0.4986733
row1 1.9922607 0.5350447 -0.9962097 -0.7295692 -1.699998488 -1.756247 2.3742080
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
          [,1]     [,2]       [,3]       [,4]       [,5]       [,6]       [,7]
row2 0.8819376 1.036796 -0.1329206 -0.7815201 -0.9055115 0.02152087 -0.2647634
           [,8]       [,9]     [,10]
row2 -0.3103186 -0.2198884 0.1764901
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
           [,1]      [,2]      [,3]      [,4]        [,5]      [,6]     [,7]
row5 -0.4100117 0.9114131 0.9128061 0.7636108 -0.03699474 0.1800854 1.299676
           [,8]       [,9]      [,10]      [,11]      [,12]      [,13]
row5 -0.4157428 -0.9953653 -0.3684934 -0.5284008 -0.2012807 -0.9253671
           [,14]     [,15]      [,16]    [,17]      [,18]     [,19]     [,20]
row5 -0.01018658 0.4821572 -0.1973441 2.223414 -0.2292721 0.3533396 -1.266423
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> colnames(tmp) <- NULL
> rownames(tmp) <- NULL
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> dimnames(tmp)
[[1]]
[1] "row1" "row2" "row3" "row4" "row5"

[[2]]
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"

> 
> dimnames(tmp) <- NULL
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> dimnames(tmp)
[[1]]
NULL

[[2]]
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"

> 
> 
> dimnames(tmp) <- NULL
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> dimnames(tmp)
[[1]]
[1] "row1" "row2" "row3" "row4" "row5"

[[2]]
NULL

> 
> dimnames(tmp) <- list(NULL,c(colnames(tmp,do.NULL=FALSE)))
> dimnames(tmp)
[[1]]
NULL

[[2]]
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"

> 
> 
> 
> ###
> ### Testing logical indexing
> ###
> ###
> 
> tmp <- createBufferedMatrix(230,15)
> tmp[1:230,1:15] <- rnorm(230*15)
> x <-tmp[1:230,1:15]  
> 
> for (rep in 1:10){
+   which.cols <- sample(c(TRUE,FALSE),15,replace=T)
+   which.rows <- sample(c(TRUE,FALSE),230,replace=T)
+   
+   if (!all(tmp[which.rows,which.cols] == x[which.rows,which.cols])){
+     stop("No agreement when logical indexing\n")
+   }
+   
+   if (!all(subBufferedMatrix(tmp,,which.cols)[,1:sum(which.cols)] ==  x[,which.cols])){
+     stop("No agreement when logical indexing in subBufferedMatrix cols\n")
+   }
+   if (!all(subBufferedMatrix(tmp,which.rows,)[1:sum(which.rows),] ==  x[which.rows,])){
+     stop("No agreement when logical indexing in subBufferedMatrix rows\n")
+   }
+   
+   
+   if (!all(subBufferedMatrix(tmp,which.rows,which.cols)[1:sum(which.rows),1:sum(which.cols)]==  x[which.rows,which.cols])){
+     stop("No agreement when logical indexing in subBufferedMatrix rows and columns\n")
+   }
+ }
> 
> 
> ##
> ## Test the ReadOnlyMode
> ##
> 
> ReadOnlyMode(tmp)
<pointer: 0x600000af4000>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8addaee74d" 
 [2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad55d3773f"
 [3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad2e39f51e"
 [4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad5f0b9c47"
 [5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad73412a10"
 [6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad3b30bb8d"
 [7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad7c694456"
 [8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad6305a9e9"
 [9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad8d632c9" 
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad26a02ea7"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad5e56e9c0"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad1c0c6ca3"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad73b04fb7"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad3c41b2b7"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8ad7d3c2b48"
> 
> 
> ### testing coercion functions
> ###
> 
> tmp <- as(tmp,"matrix")
> tmp <- as(tmp,"BufferedMatrix")
> 
> 
> 
> ### testing whether can move storage from one location to another
> 
> MoveStorageDirectory(tmp,"NewDirectory",full.path=FALSE)
<pointer: 0x600000a88120>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600000a88120>
Warning message:
In dir.create(new.directory) :
  '/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x600000a88120>
> rowMedians(tmp)
  [1]  0.092744943  0.254166741 -0.020091654 -0.094561012  0.171572861
  [6] -0.171902379 -0.109307292  0.088945189  0.059809788  0.195993307
 [11] -0.149007331 -0.134619247  0.476212352 -0.240811862 -0.490638588
 [16] -0.018586600  0.013706314 -0.084044371 -0.150494419  0.016603314
 [21] -0.117862114  0.144670972 -0.006846260 -0.100088808 -0.107878493
 [26] -0.390799301  0.046748896 -0.588052382  0.714183856 -0.416237520
 [31]  0.239401037  0.007553035  0.607692812 -0.356067544 -0.197430821
 [36] -0.240247082 -0.255394135 -0.383870030 -0.059415370 -0.318353277
 [41] -0.510738405  0.186018061  0.126164086  0.492195703  0.034219315
 [46] -0.207608296  0.295379819 -0.049483125  0.493800165 -0.329315744
 [51] -0.051501978 -0.257602053  0.042123825  0.024661583  0.297270957
 [56] -0.407790397  0.353865260 -0.173363808 -0.402979461 -0.048765607
 [61] -0.263085527 -0.103306963  0.119000079  0.027802627  0.749380559
 [66] -0.465917939  0.036870282 -0.120735842  0.854967363 -0.060677612
 [71] -0.227426449 -0.260753888 -0.059682945 -0.000667919 -0.186292227
 [76] -0.643839475 -0.104465331  0.559447952 -0.613989572 -0.212872206
 [81] -0.310603926 -0.434612829  0.382544856  0.006369746 -0.142692848
 [86]  0.254313944  0.273902905 -0.157900359 -0.130352020 -0.143965121
 [91] -0.061798798 -0.354132501  0.302211445  0.098482281  0.386056233
 [96]  0.173044258 -0.386741157 -0.668987778 -0.021537807  0.129429823
[101]  0.345149393 -0.676868526 -0.321027085 -0.527297367  0.152079114
[106]  0.195655410  0.604999048 -0.393120211  0.166762026 -0.465692436
[111]  0.143147420  0.491985934 -0.034667417 -0.072494612 -0.490235685
[116] -0.485433922  0.305360617 -0.034394047 -0.205180974  0.151113983
[121]  0.125568003 -0.647636831  0.457887108 -0.018220402 -0.360660530
[126]  0.023075470 -0.256465483 -0.019340558  0.424119029 -0.240763947
[131] -0.426155231  0.375695079 -0.076515992 -0.295461347  0.125885822
[136] -0.051413714  0.078028709  0.361372580  0.095681169  0.486157125
[141] -0.278811722 -0.105242116 -0.424630230 -0.183227398  0.259719296
[146] -0.047558012 -0.484121234 -0.323515359  0.231809374 -0.276717367
[151] -0.080919809  0.415748802 -0.307746146  0.402763666 -0.256057265
[156] -0.230183555 -0.437324222 -0.117721361  0.128038802  0.295486739
[161]  0.226240312 -0.238359599  0.317649573  0.459782088  0.604522054
[166]  0.111829604  0.010237409  0.031776242  0.092582218  0.057630549
[171]  0.474594428  0.204457745 -0.140530661 -0.111970336 -0.011514572
[176]  0.015753081 -0.521432685 -0.344774267 -0.163546108 -0.199758677
[181] -0.231875704 -0.330518365  0.003013235  0.258093428 -0.490861892
[186]  0.534964288 -0.013472972  0.204575985  0.012432586  0.136713530
[191]  0.153336467 -0.079955170 -0.031825962 -0.218151024  0.025508038
[196]  0.303698984  0.240430413  0.237754867  0.223555123 -0.456692000
[201] -0.366564186  0.068661974  0.408940825  0.461995268  0.104844302
[206]  0.013814772  0.034979898 -0.126414289  0.012241432 -0.360401653
[211]  0.226977201 -0.515432641  0.399650481 -0.195477912  0.117016098
[216]  1.009098688  0.028549781 -0.264713857  0.231541284 -0.041307190
[221] -0.034043540  0.138946931 -0.093653532 -0.131818875  0.814986526
[226]  0.091013267 -0.471175941 -0.039505835  0.189113394 -0.196495609
> 
> proc.time()
   user  system elapsed 
  2.798  16.222  35.197 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> prefix <- "dbmtest"
> directory <- getwd()
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0x600000e58480>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0x600000e58480>
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 10
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0x600000e58480>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 10
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 0.000000 0.000000 0.000000 0.000000 

<pointer: 0x600000e58480>
> rm(P)
> 
> #P <- .Call("R_bm_Destroy",P)
> #.Call("R_bm_Destroy",P)
> #.Call("R_bm_Test_C",P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,5)
[1] TRUE
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 0
Buffer Rows: 1
Buffer Cols: 1

Printing Values






<pointer: 0x600000e24000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e24000>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 1
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 
0.000000 
0.000000 
0.000000 
0.000000 

<pointer: 0x600000e24000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e24000>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0x600000e24000>
> rm(P)
> 
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,5)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e6c0c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e6c0c0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0x600000e6c0c0>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000e6c0c0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0x600000e6c0c0>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x600000e6c0c0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0x600000e6c0c0>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x600000e6c0c0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0x600000e6c0c0>
> rm(P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e04120>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600000e04120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e04120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e04120>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile13974af2cae0" "BufferedMatrixFile13979e55e91" 
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile13974af2cae0" "BufferedMatrixFile13979e55e91" 
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e54000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e54000>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000e54000>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000e54000>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600000e54000>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600000e54000>
> .Call("R_bm_isRowMode",P)
[1] FALSE
> rm(P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e2c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000e2c000>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000e2c000>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600000e2c000>
> rm(P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0x600000e44240>
> .Call("R_bm_getValue",P,3,3)
[1] 6
> 
> .Call("R_bm_getValue",P,100000,10000)
[1] NA
> .Call("R_bm_setValue",P,3,3,12345.0)
[1] TRUE
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 12345.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0x600000e44240>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.369   0.207   1.190 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100   0
> buffer.dim(Temp)
[1] 1 1
> 
> 
> proc.time()
   user  system elapsed 
  0.355   0.104   0.462 

Example timings