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This page was generated on 2025-08-21 12:06 -0400 (Thu, 21 Aug 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4819
lconwaymacOS 12.7.1 Montereyx86_644.5.1 (2025-06-13) -- "Great Square Root" 4597
kjohnson3macOS 13.7.7 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4539
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4536
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 251/2318HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.73.0  (landing page)
Ben Bolstad
Snapshot Date: 2025-08-20 13:45 -0400 (Wed, 20 Aug 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 12.7.1 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 kjohnson3

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: 2025-08-20 18:27:17 -0400 (Wed, 20 Aug 2025)
EndedAt: 2025-08-20 18:27:34 -0400 (Wed, 20 Aug 2025)
EllapsedTime: 17.2 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 (2025-06-14 r88325)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.7
* 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 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.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-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/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 arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/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-arm64/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 (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

> library(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 
  0.123   0.039   0.155 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

> library(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 480828 25.7    1056621 56.5         NA   634345 33.9
Vcells 891019  6.8    8388608 64.0     196608  2109860 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] "Wed Aug 20 18:27:27 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] "Wed Aug 20 18:27:27 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: 0x600002ee0000>
> 
> 
> 
> 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] "Wed Aug 20 18:27:28 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] "Wed Aug 20 18:27:29 2025"
> 
> ColMode(tmp2)
<pointer: 0x600002ee0000>
> 
> 
> 
> ### 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,] 99.6647133  0.3122969 -0.06651384  1.4260505
[2,] -0.4074112 -0.4881573  0.68581499 -2.1091920
[3,]  0.2861787 -0.4147090  0.17100793  0.1748535
[4,]  0.2349386  0.3482072  0.74958635  0.3279353
> 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 :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]       [,3]      [,4]
[1,] 99.6647133 0.3122969 0.06651384 1.4260505
[2,]  0.4074112 0.4881573 0.68581499 2.1091920
[3,]  0.2861787 0.4147090 0.17100793 0.1748535
[4,]  0.2349386 0.3482072 0.74958635 0.3279353
> 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 :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]      [,2]      [,3]      [,4]
[1,] 9.9832216 0.5588353 0.2579028 1.1941735
[2,] 0.6382877 0.6986825 0.8281395 1.4523058
[3,] 0.5349567 0.6439790 0.4135311 0.4181549
[4,] 0.4847046 0.5900909 0.8657865 0.5726564
> 
> 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 :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 224.49693 30.90065 27.64554 38.36779
[2,]  31.79029 32.47498 33.96721 41.63225
[3,]  30.63575 31.85450 29.30632 29.35640
[4,]  30.08198 31.24912 34.40745 31.05450
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002eec000>
> exp(tmp5)
<pointer: 0x600002eec000>
> log(tmp5,2)
<pointer: 0x600002eec000>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.2609
> Min(tmp5)
[1] 54.05971
> mean(tmp5)
[1] 72.07794
> Sum(tmp5)
[1] 14415.59
> Var(tmp5)
[1] 856.2539
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 89.48213 72.78856 69.74086 67.85108 69.15811 70.42051 70.03436 70.30472
 [9] 70.49672 70.50233
> rowSums(tmp5)
 [1] 1789.643 1455.771 1394.817 1357.022 1383.162 1408.410 1400.687 1406.094
 [9] 1409.934 1410.047
> rowVars(tmp5)
 [1] 7974.07872   80.08652   62.61833   69.89663   47.79931   43.98650
 [7]   78.77558   82.81565   85.20973   74.11387
> rowSd(tmp5)
 [1] 89.297697  8.949107  7.913174  8.360420  6.913704  6.632232  8.875561
 [8]  9.100311  9.230912  8.608941
> rowMax(tmp5)
 [1] 467.26094  86.65207  84.55844  84.75233  82.80390  82.19484  92.77781
 [8]  87.51030  90.82898  90.04660
> rowMin(tmp5)
 [1] 56.82243 54.05971 58.85633 55.12418 58.96993 57.07571 58.00822 56.87379
 [9] 56.49099 60.53339
> 
> colMeans(tmp5)
 [1] 107.61052  64.48921  67.25472  71.40972  67.51884  73.17126  72.56784
 [8]  70.50605  71.13846  69.58469  70.68371  68.35528  73.54252  71.13296
[15]  69.00104  66.24896  72.41833  68.85381  73.20854  72.86237
> colSums(tmp5)
 [1] 1076.1052  644.8921  672.5472  714.0972  675.1884  731.7126  725.6784
 [8]  705.0605  711.3846  695.8469  706.8371  683.5528  735.4252  711.3296
[15]  690.0104  662.4896  724.1833  688.5381  732.0854  728.6237
> colVars(tmp5)
 [1] 16015.92536    44.55609    72.42396    67.90039    32.70580   126.02529
 [7]   108.86924    49.24834    44.09675    76.45229   119.47551    17.28624
[13]    59.84695    75.93215    82.44106    39.85251    49.87463    63.24167
[19]    41.99916   133.08117
> colSd(tmp5)
 [1] 126.554041   6.675035   8.510227   8.240169   5.718899  11.226099
 [7]  10.434042   7.017716   6.640538   8.743700  10.930485   4.157673
[13]   7.736081   8.713906   9.079706   6.312885   7.062197   7.952463
[19]   6.480676  11.536081
> colMax(tmp5)
 [1] 467.26094  76.22956  81.14094  86.65207  75.68628  86.34017  88.23766
 [8]  83.82024  80.56032  85.69897  90.82898  74.28525  84.55844  87.51030
[15]  90.04660  74.16641  82.89231  84.11756  84.75233  92.77781
> colMin(tmp5)
 [1] 59.42767 56.49099 57.54057 61.10150 56.82243 55.12418 58.91484 61.47009
 [9] 59.83124 58.24030 57.07571 60.72712 64.91136 60.17377 59.78207 54.05971
[17] 62.59255 58.61064 63.23209 59.43617
> 
> 
> ### 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] 89.48213 72.78856 69.74086 67.85108 69.15811 70.42051 70.03436 70.30472
 [9]       NA 70.50233
> rowSums(tmp5)
 [1] 1789.643 1455.771 1394.817 1357.022 1383.162 1408.410 1400.687 1406.094
 [9]       NA 1410.047
> rowVars(tmp5)
 [1] 7974.07872   80.08652   62.61833   69.89663   47.79931   43.98650
 [7]   78.77558   82.81565   78.47223   74.11387
> rowSd(tmp5)
 [1] 89.297697  8.949107  7.913174  8.360420  6.913704  6.632232  8.875561
 [8]  9.100311  8.858455  8.608941
> rowMax(tmp5)
 [1] 467.26094  86.65207  84.55844  84.75233  82.80390  82.19484  92.77781
 [8]  87.51030        NA  90.04660
> rowMin(tmp5)
 [1] 56.82243 54.05971 58.85633 55.12418 58.96993 57.07571 58.00822 56.87379
 [9]       NA 60.53339
> 
> colMeans(tmp5)
 [1] 107.61052        NA  67.25472  71.40972  67.51884  73.17126  72.56784
 [8]  70.50605  71.13846  69.58469  70.68371  68.35528  73.54252  71.13296
[15]  69.00104  66.24896  72.41833  68.85381  73.20854  72.86237
> colSums(tmp5)
 [1] 1076.1052        NA  672.5472  714.0972  675.1884  731.7126  725.6784
 [8]  705.0605  711.3846  695.8469  706.8371  683.5528  735.4252  711.3296
[15]  690.0104  662.4896  724.1833  688.5381  732.0854  728.6237
> colVars(tmp5)
 [1] 16015.92536          NA    72.42396    67.90039    32.70580   126.02529
 [7]   108.86924    49.24834    44.09675    76.45229   119.47551    17.28624
[13]    59.84695    75.93215    82.44106    39.85251    49.87463    63.24167
[19]    41.99916   133.08117
> colSd(tmp5)
 [1] 126.554041         NA   8.510227   8.240169   5.718899  11.226099
 [7]  10.434042   7.017716   6.640538   8.743700  10.930485   4.157673
[13]   7.736081   8.713906   9.079706   6.312885   7.062197   7.952463
[19]   6.480676  11.536081
> colMax(tmp5)
 [1] 467.26094        NA  81.14094  86.65207  75.68628  86.34017  88.23766
 [8]  83.82024  80.56032  85.69897  90.82898  74.28525  84.55844  87.51030
[15]  90.04660  74.16641  82.89231  84.11756  84.75233  92.77781
> colMin(tmp5)
 [1] 59.42767       NA 57.54057 61.10150 56.82243 55.12418 58.91484 61.47009
 [9] 59.83124 58.24030 57.07571 60.72712 64.91136 60.17377 59.78207 54.05971
[17] 62.59255 58.61064 63.23209 59.43617
> 
> Max(tmp5,na.rm=TRUE)
[1] 467.2609
> Min(tmp5,na.rm=TRUE)
[1] 54.05971
> mean(tmp5,na.rm=TRUE)
[1] 72.15627
> Sum(tmp5,na.rm=TRUE)
[1] 14359.1
> Var(tmp5,na.rm=TRUE)
[1] 859.3453
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.48213 72.78856 69.74086 67.85108 69.15811 70.42051 70.03436 70.30472
 [9] 71.23387 70.50233
> rowSums(tmp5,na.rm=TRUE)
 [1] 1789.643 1455.771 1394.817 1357.022 1383.162 1408.410 1400.687 1406.094
 [9] 1353.443 1410.047
> rowVars(tmp5,na.rm=TRUE)
 [1] 7974.07872   80.08652   62.61833   69.89663   47.79931   43.98650
 [7]   78.77558   82.81565   78.47223   74.11387
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.297697  8.949107  7.913174  8.360420  6.913704  6.632232  8.875561
 [8]  9.100311  8.858455  8.608941
> rowMax(tmp5,na.rm=TRUE)
 [1] 467.26094  86.65207  84.55844  84.75233  82.80390  82.19484  92.77781
 [8]  87.51030  90.82898  90.04660
> rowMin(tmp5,na.rm=TRUE)
 [1] 56.82243 54.05971 58.85633 55.12418 58.96993 57.07571 58.00822 56.87379
 [9] 58.24030 60.53339
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 107.61052  65.37790  67.25472  71.40972  67.51884  73.17126  72.56784
 [8]  70.50605  71.13846  69.58469  70.68371  68.35528  73.54252  71.13296
[15]  69.00104  66.24896  72.41833  68.85381  73.20854  72.86237
> colSums(tmp5,na.rm=TRUE)
 [1] 1076.1052  588.4011  672.5472  714.0972  675.1884  731.7126  725.6784
 [8]  705.0605  711.3846  695.8469  706.8371  683.5528  735.4252  711.3296
[15]  690.0104  662.4896  724.1833  688.5381  732.0854  728.6237
> colVars(tmp5,na.rm=TRUE)
 [1] 16015.92536    41.24069    72.42396    67.90039    32.70580   126.02529
 [7]   108.86924    49.24834    44.09675    76.45229   119.47551    17.28624
[13]    59.84695    75.93215    82.44106    39.85251    49.87463    63.24167
[19]    41.99916   133.08117
> colSd(tmp5,na.rm=TRUE)
 [1] 126.554041   6.421891   8.510227   8.240169   5.718899  11.226099
 [7]  10.434042   7.017716   6.640538   8.743700  10.930485   4.157673
[13]   7.736081   8.713906   9.079706   6.312885   7.062197   7.952463
[19]   6.480676  11.536081
> colMax(tmp5,na.rm=TRUE)
 [1] 467.26094  76.22956  81.14094  86.65207  75.68628  86.34017  88.23766
 [8]  83.82024  80.56032  85.69897  90.82898  74.28525  84.55844  87.51030
[15]  90.04660  74.16641  82.89231  84.11756  84.75233  92.77781
> colMin(tmp5,na.rm=TRUE)
 [1] 59.42767 56.87379 57.54057 61.10150 56.82243 55.12418 58.91484 61.47009
 [9] 59.83124 58.24030 57.07571 60.72712 64.91136 60.17377 59.78207 54.05971
[17] 62.59255 58.61064 63.23209 59.43617
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.48213 72.78856 69.74086 67.85108 69.15811 70.42051 70.03436 70.30472
 [9]      NaN 70.50233
> rowSums(tmp5,na.rm=TRUE)
 [1] 1789.643 1455.771 1394.817 1357.022 1383.162 1408.410 1400.687 1406.094
 [9]    0.000 1410.047
> rowVars(tmp5,na.rm=TRUE)
 [1] 7974.07872   80.08652   62.61833   69.89663   47.79931   43.98650
 [7]   78.77558   82.81565         NA   74.11387
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.297697  8.949107  7.913174  8.360420  6.913704  6.632232  8.875561
 [8]  9.100311        NA  8.608941
> rowMax(tmp5,na.rm=TRUE)
 [1] 467.26094  86.65207  84.55844  84.75233  82.80390  82.19484  92.77781
 [8]  87.51030        NA  90.04660
> rowMin(tmp5,na.rm=TRUE)
 [1] 56.82243 54.05971 58.85633 55.12418 58.96993 57.07571 58.00822 56.87379
 [9]       NA 60.53339
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 112.38888       NaN  68.19632  72.33677  66.81199  73.45508  70.82675
 [8]  70.85372  71.30514  70.84517  68.44534  67.69639  74.33020  70.90742
[15]  69.40201  65.86067  72.35493  68.21943  73.89049  71.56801
> colSums(tmp5,na.rm=TRUE)
 [1] 1011.5000    0.0000  613.7669  651.0309  601.3079  661.0958  637.4407
 [8]  637.6835  641.7462  637.6066  616.0081  609.2675  668.9718  638.1667
[15]  624.6181  592.7460  651.1944  613.9749  665.0144  644.1121
> colVars(tmp5,na.rm=TRUE)
 [1] 17761.04705          NA    71.50252    66.71940    31.17312   140.87219
 [7]    88.37466    54.04449    49.29631    68.13450    78.04438    14.56306
[13]    60.34790    84.85138    90.93747    43.13789    56.06374    66.61950
[19]    42.01709   130.86840
> colSd(tmp5,na.rm=TRUE)
 [1] 133.270578         NA   8.455916   8.168194   5.583289  11.868959
 [7]   9.400780   7.351496   7.021133   8.254363   8.834273   3.816158
[13]   7.768391   9.211481   9.536114   6.567944   7.487573   8.162077
[19]   6.482059  11.439773
> colMax(tmp5,na.rm=TRUE)
 [1] 467.26094      -Inf  81.14094  86.65207  75.68628  86.34017  82.80390
 [8]  83.82024  80.56032  85.69897  80.48092  73.73248  84.55844  87.51030
[15]  90.04660  74.16641  82.89231  84.11756  84.75233  92.77781
> colMin(tmp5,na.rm=TRUE)
 [1] 59.42767      Inf 57.54057 61.10150 56.82243 55.12418 58.91484 61.47009
 [9] 59.83124 59.91292 57.07571 60.72712 64.91136 60.17377 59.78207 54.05971
[17] 62.59255 58.61064 63.23209 59.43617
> 
> 
> 
> 
> 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] 197.5523 420.6898 202.7396 284.3233 288.6322 313.6761 141.1286 135.3738
 [9] 261.3674 352.8952
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 197.5523 420.6898 202.7396 284.3233 288.6322 313.6761 141.1286 135.3738
 [9] 261.3674 352.8952
> 
> 
> 
> 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]  5.684342e-14 -5.684342e-14  5.684342e-14  0.000000e+00  2.842171e-14
 [6]  1.421085e-14 -2.842171e-14  1.136868e-13  0.000000e+00 -5.684342e-14
[11]  2.842171e-14  0.000000e+00 -5.684342e-14 -1.136868e-13  5.684342e-14
[16] -2.842171e-14  1.421085e-14 -1.136868e-13  2.842171e-14 -2.842171e-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)
+ }
6   6 
2   9 
8   3 
7   6 
9   5 
10   6 
9   13 
8   8 
8   5 
3   15 
8   20 
8   7 
3   3 
5   9 
9   14 
5   19 
5   3 
5   1 
1   17 
7   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] 1.953334
> Min(tmp)
[1] -1.762098
> mean(tmp)
[1] 0.2624679
> Sum(tmp)
[1] 26.24679
> Var(tmp)
[1] 0.6878305
> 
> rowMeans(tmp)
[1] 0.2624679
> rowSums(tmp)
[1] 26.24679
> rowVars(tmp)
[1] 0.6878305
> rowSd(tmp)
[1] 0.8293555
> rowMax(tmp)
[1] 1.953334
> rowMin(tmp)
[1] -1.762098
> 
> colMeans(tmp)
  [1] -1.255707755  0.589392391  1.128666697 -0.032013565  1.642956890
  [6] -0.348710299  0.029227959  1.501925246  0.202996674  0.529633247
 [11] -1.205949825  0.775972627  1.556423506 -0.009869488 -0.426003972
 [16] -0.102954558 -0.890369451  0.253690233  0.410414053  0.011324734
 [21] -0.733097293  1.953333917  1.049959324  0.837845467  1.714503435
 [26] -0.056997400 -0.176646426 -0.518723584  0.703384855  1.284840768
 [31]  0.749667779  1.547010079 -0.199687747  1.869935743 -0.216602261
 [36]  1.166806339  0.205940979  0.387477398  0.178702712  1.133001008
 [41]  0.720174858 -1.762097520 -1.120370147  0.039402116  1.335775707
 [46]  1.687994069  1.308582146 -0.154007723 -0.349197347  0.106241433
 [51] -0.158237993 -0.049174344  0.215438700 -0.254620664 -0.337623727
 [56]  1.251349957  1.598264307 -0.685417156 -0.439605949  1.429195409
 [61] -0.739436614  0.059748047  0.302489820  0.217329661  0.258243049
 [66]  0.996465187 -1.222297838 -0.592096846  0.141037390  0.847553806
 [71]  0.181688349 -0.816399375 -0.065393055  0.303150888 -0.166205453
 [76]  0.777151762  0.687885757  0.605786513 -0.669760584  0.553433325
 [81]  0.198170491  0.796742230  0.183291887 -0.434049446 -0.225065060
 [86]  1.116337858 -0.832257535 -0.392786723  0.220793207  1.242879551
 [91] -1.466122796  0.503594528  1.793640584 -0.716820219  0.661041812
 [96] -1.287607215  0.758442754  0.675721799  0.009938979  0.156762677
> colSums(tmp)
  [1] -1.255707755  0.589392391  1.128666697 -0.032013565  1.642956890
  [6] -0.348710299  0.029227959  1.501925246  0.202996674  0.529633247
 [11] -1.205949825  0.775972627  1.556423506 -0.009869488 -0.426003972
 [16] -0.102954558 -0.890369451  0.253690233  0.410414053  0.011324734
 [21] -0.733097293  1.953333917  1.049959324  0.837845467  1.714503435
 [26] -0.056997400 -0.176646426 -0.518723584  0.703384855  1.284840768
 [31]  0.749667779  1.547010079 -0.199687747  1.869935743 -0.216602261
 [36]  1.166806339  0.205940979  0.387477398  0.178702712  1.133001008
 [41]  0.720174858 -1.762097520 -1.120370147  0.039402116  1.335775707
 [46]  1.687994069  1.308582146 -0.154007723 -0.349197347  0.106241433
 [51] -0.158237993 -0.049174344  0.215438700 -0.254620664 -0.337623727
 [56]  1.251349957  1.598264307 -0.685417156 -0.439605949  1.429195409
 [61] -0.739436614  0.059748047  0.302489820  0.217329661  0.258243049
 [66]  0.996465187 -1.222297838 -0.592096846  0.141037390  0.847553806
 [71]  0.181688349 -0.816399375 -0.065393055  0.303150888 -0.166205453
 [76]  0.777151762  0.687885757  0.605786513 -0.669760584  0.553433325
 [81]  0.198170491  0.796742230  0.183291887 -0.434049446 -0.225065060
 [86]  1.116337858 -0.832257535 -0.392786723  0.220793207  1.242879551
 [91] -1.466122796  0.503594528  1.793640584 -0.716820219  0.661041812
 [96] -1.287607215  0.758442754  0.675721799  0.009938979  0.156762677
> 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] -1.255707755  0.589392391  1.128666697 -0.032013565  1.642956890
  [6] -0.348710299  0.029227959  1.501925246  0.202996674  0.529633247
 [11] -1.205949825  0.775972627  1.556423506 -0.009869488 -0.426003972
 [16] -0.102954558 -0.890369451  0.253690233  0.410414053  0.011324734
 [21] -0.733097293  1.953333917  1.049959324  0.837845467  1.714503435
 [26] -0.056997400 -0.176646426 -0.518723584  0.703384855  1.284840768
 [31]  0.749667779  1.547010079 -0.199687747  1.869935743 -0.216602261
 [36]  1.166806339  0.205940979  0.387477398  0.178702712  1.133001008
 [41]  0.720174858 -1.762097520 -1.120370147  0.039402116  1.335775707
 [46]  1.687994069  1.308582146 -0.154007723 -0.349197347  0.106241433
 [51] -0.158237993 -0.049174344  0.215438700 -0.254620664 -0.337623727
 [56]  1.251349957  1.598264307 -0.685417156 -0.439605949  1.429195409
 [61] -0.739436614  0.059748047  0.302489820  0.217329661  0.258243049
 [66]  0.996465187 -1.222297838 -0.592096846  0.141037390  0.847553806
 [71]  0.181688349 -0.816399375 -0.065393055  0.303150888 -0.166205453
 [76]  0.777151762  0.687885757  0.605786513 -0.669760584  0.553433325
 [81]  0.198170491  0.796742230  0.183291887 -0.434049446 -0.225065060
 [86]  1.116337858 -0.832257535 -0.392786723  0.220793207  1.242879551
 [91] -1.466122796  0.503594528  1.793640584 -0.716820219  0.661041812
 [96] -1.287607215  0.758442754  0.675721799  0.009938979  0.156762677
> colMin(tmp)
  [1] -1.255707755  0.589392391  1.128666697 -0.032013565  1.642956890
  [6] -0.348710299  0.029227959  1.501925246  0.202996674  0.529633247
 [11] -1.205949825  0.775972627  1.556423506 -0.009869488 -0.426003972
 [16] -0.102954558 -0.890369451  0.253690233  0.410414053  0.011324734
 [21] -0.733097293  1.953333917  1.049959324  0.837845467  1.714503435
 [26] -0.056997400 -0.176646426 -0.518723584  0.703384855  1.284840768
 [31]  0.749667779  1.547010079 -0.199687747  1.869935743 -0.216602261
 [36]  1.166806339  0.205940979  0.387477398  0.178702712  1.133001008
 [41]  0.720174858 -1.762097520 -1.120370147  0.039402116  1.335775707
 [46]  1.687994069  1.308582146 -0.154007723 -0.349197347  0.106241433
 [51] -0.158237993 -0.049174344  0.215438700 -0.254620664 -0.337623727
 [56]  1.251349957  1.598264307 -0.685417156 -0.439605949  1.429195409
 [61] -0.739436614  0.059748047  0.302489820  0.217329661  0.258243049
 [66]  0.996465187 -1.222297838 -0.592096846  0.141037390  0.847553806
 [71]  0.181688349 -0.816399375 -0.065393055  0.303150888 -0.166205453
 [76]  0.777151762  0.687885757  0.605786513 -0.669760584  0.553433325
 [81]  0.198170491  0.796742230  0.183291887 -0.434049446 -0.225065060
 [86]  1.116337858 -0.832257535 -0.392786723  0.220793207  1.242879551
 [91] -1.466122796  0.503594528  1.793640584 -0.716820219  0.661041812
 [96] -1.287607215  0.758442754  0.675721799  0.009938979  0.156762677
> colMedians(tmp)
  [1] -1.255707755  0.589392391  1.128666697 -0.032013565  1.642956890
  [6] -0.348710299  0.029227959  1.501925246  0.202996674  0.529633247
 [11] -1.205949825  0.775972627  1.556423506 -0.009869488 -0.426003972
 [16] -0.102954558 -0.890369451  0.253690233  0.410414053  0.011324734
 [21] -0.733097293  1.953333917  1.049959324  0.837845467  1.714503435
 [26] -0.056997400 -0.176646426 -0.518723584  0.703384855  1.284840768
 [31]  0.749667779  1.547010079 -0.199687747  1.869935743 -0.216602261
 [36]  1.166806339  0.205940979  0.387477398  0.178702712  1.133001008
 [41]  0.720174858 -1.762097520 -1.120370147  0.039402116  1.335775707
 [46]  1.687994069  1.308582146 -0.154007723 -0.349197347  0.106241433
 [51] -0.158237993 -0.049174344  0.215438700 -0.254620664 -0.337623727
 [56]  1.251349957  1.598264307 -0.685417156 -0.439605949  1.429195409
 [61] -0.739436614  0.059748047  0.302489820  0.217329661  0.258243049
 [66]  0.996465187 -1.222297838 -0.592096846  0.141037390  0.847553806
 [71]  0.181688349 -0.816399375 -0.065393055  0.303150888 -0.166205453
 [76]  0.777151762  0.687885757  0.605786513 -0.669760584  0.553433325
 [81]  0.198170491  0.796742230  0.183291887 -0.434049446 -0.225065060
 [86]  1.116337858 -0.832257535 -0.392786723  0.220793207  1.242879551
 [91] -1.466122796  0.503594528  1.793640584 -0.716820219  0.661041812
 [96] -1.287607215  0.758442754  0.675721799  0.009938979  0.156762677
> colRanges(tmp)
          [,1]      [,2]     [,3]        [,4]     [,5]       [,6]       [,7]
[1,] -1.255708 0.5893924 1.128667 -0.03201356 1.642957 -0.3487103 0.02922796
[2,] -1.255708 0.5893924 1.128667 -0.03201356 1.642957 -0.3487103 0.02922796
         [,8]      [,9]     [,10]    [,11]     [,12]    [,13]        [,14]
[1,] 1.501925 0.2029967 0.5296332 -1.20595 0.7759726 1.556424 -0.009869488
[2,] 1.501925 0.2029967 0.5296332 -1.20595 0.7759726 1.556424 -0.009869488
         [,15]      [,16]      [,17]     [,18]     [,19]      [,20]      [,21]
[1,] -0.426004 -0.1029546 -0.8903695 0.2536902 0.4104141 0.01132473 -0.7330973
[2,] -0.426004 -0.1029546 -0.8903695 0.2536902 0.4104141 0.01132473 -0.7330973
        [,22]    [,23]     [,24]    [,25]      [,26]      [,27]      [,28]
[1,] 1.953334 1.049959 0.8378455 1.714503 -0.0569974 -0.1766464 -0.5187236
[2,] 1.953334 1.049959 0.8378455 1.714503 -0.0569974 -0.1766464 -0.5187236
         [,29]    [,30]     [,31]   [,32]      [,33]    [,34]      [,35]
[1,] 0.7033849 1.284841 0.7496678 1.54701 -0.1996877 1.869936 -0.2166023
[2,] 0.7033849 1.284841 0.7496678 1.54701 -0.1996877 1.869936 -0.2166023
        [,36]    [,37]     [,38]     [,39]    [,40]     [,41]     [,42]
[1,] 1.166806 0.205941 0.3874774 0.1787027 1.133001 0.7201749 -1.762098
[2,] 1.166806 0.205941 0.3874774 0.1787027 1.133001 0.7201749 -1.762098
        [,43]      [,44]    [,45]    [,46]    [,47]      [,48]      [,49]
[1,] -1.12037 0.03940212 1.335776 1.687994 1.308582 -0.1540077 -0.3491973
[2,] -1.12037 0.03940212 1.335776 1.687994 1.308582 -0.1540077 -0.3491973
         [,50]     [,51]       [,52]     [,53]      [,54]      [,55]   [,56]
[1,] 0.1062414 -0.158238 -0.04917434 0.2154387 -0.2546207 -0.3376237 1.25135
[2,] 0.1062414 -0.158238 -0.04917434 0.2154387 -0.2546207 -0.3376237 1.25135
        [,57]      [,58]      [,59]    [,60]      [,61]      [,62]     [,63]
[1,] 1.598264 -0.6854172 -0.4396059 1.429195 -0.7394366 0.05974805 0.3024898
[2,] 1.598264 -0.6854172 -0.4396059 1.429195 -0.7394366 0.05974805 0.3024898
         [,64]    [,65]     [,66]     [,67]      [,68]     [,69]     [,70]
[1,] 0.2173297 0.258243 0.9964652 -1.222298 -0.5920968 0.1410374 0.8475538
[2,] 0.2173297 0.258243 0.9964652 -1.222298 -0.5920968 0.1410374 0.8475538
         [,71]      [,72]       [,73]     [,74]      [,75]     [,76]     [,77]
[1,] 0.1816883 -0.8163994 -0.06539305 0.3031509 -0.1662055 0.7771518 0.6878858
[2,] 0.1816883 -0.8163994 -0.06539305 0.3031509 -0.1662055 0.7771518 0.6878858
         [,78]      [,79]     [,80]     [,81]     [,82]     [,83]      [,84]
[1,] 0.6057865 -0.6697606 0.5534333 0.1981705 0.7967422 0.1832919 -0.4340494
[2,] 0.6057865 -0.6697606 0.5534333 0.1981705 0.7967422 0.1832919 -0.4340494
          [,85]    [,86]      [,87]      [,88]     [,89]   [,90]     [,91]
[1,] -0.2250651 1.116338 -0.8322575 -0.3927867 0.2207932 1.24288 -1.466123
[2,] -0.2250651 1.116338 -0.8322575 -0.3927867 0.2207932 1.24288 -1.466123
         [,92]    [,93]      [,94]     [,95]     [,96]     [,97]     [,98]
[1,] 0.5035945 1.793641 -0.7168202 0.6610418 -1.287607 0.7584428 0.6757218
[2,] 0.5035945 1.793641 -0.7168202 0.6610418 -1.287607 0.7584428 0.6757218
           [,99]    [,100]
[1,] 0.009938979 0.1567627
[2,] 0.009938979 0.1567627
> 
> 
> Max(tmp2)
[1] 2.981305
> Min(tmp2)
[1] -3.2649
> mean(tmp2)
[1] 0.009608868
> Sum(tmp2)
[1] 0.9608868
> Var(tmp2)
[1] 1.352672
> 
> rowMeans(tmp2)
  [1] -0.745411172 -1.030482800  1.515912564 -0.690763563 -0.978883666
  [6]  0.105134426 -0.579238525  0.117174335  1.203236811  1.112571807
 [11]  1.907525510 -2.612106813 -0.634750899 -1.024588251  0.015289224
 [16]  0.231053326 -1.231083388 -1.453375507 -0.293061420 -0.779736032
 [21] -0.972964409 -0.474477793  1.459833413 -2.412011715  0.329140963
 [26]  0.519212753  0.874608155  1.269300470  0.282860360 -1.462407989
 [31]  0.757215301  0.870926880  0.007713818 -0.667823665 -0.022004777
 [36]  1.337128642  1.066298352 -0.908805027 -0.875489888  0.062833590
 [41]  0.089402544 -0.309623407  1.071472967 -0.952381779  0.447340017
 [46] -0.630616182  0.387732754  2.142335821  2.981304738 -1.913044500
 [51] -0.873712346 -2.068015800  0.715617265 -0.431237552  0.252384387
 [56] -0.326145166 -0.072919601  0.323668423  1.103755148 -0.707822628
 [61]  0.192005875 -0.833257684 -0.507803901  1.480823382  2.329361608
 [66]  1.264331120  2.475412425 -0.173868577  0.740869766 -1.196141077
 [71] -0.107482541 -2.570875767  0.126362229 -1.666745721  0.548950579
 [76] -0.649787275 -0.438566856  0.402377848 -0.409255736 -0.556990352
 [81] -0.191110319 -3.264900426  0.919634264 -0.504844970  1.974331095
 [86] -1.840167192  1.114557281  0.381205592  0.357974453  0.571119571
 [91]  1.237030298 -0.508939301  0.040401904  1.672954421 -0.517965507
 [96]  1.553107339  1.356369381  0.073466799 -1.077992696  0.739936922
> rowSums(tmp2)
  [1] -0.745411172 -1.030482800  1.515912564 -0.690763563 -0.978883666
  [6]  0.105134426 -0.579238525  0.117174335  1.203236811  1.112571807
 [11]  1.907525510 -2.612106813 -0.634750899 -1.024588251  0.015289224
 [16]  0.231053326 -1.231083388 -1.453375507 -0.293061420 -0.779736032
 [21] -0.972964409 -0.474477793  1.459833413 -2.412011715  0.329140963
 [26]  0.519212753  0.874608155  1.269300470  0.282860360 -1.462407989
 [31]  0.757215301  0.870926880  0.007713818 -0.667823665 -0.022004777
 [36]  1.337128642  1.066298352 -0.908805027 -0.875489888  0.062833590
 [41]  0.089402544 -0.309623407  1.071472967 -0.952381779  0.447340017
 [46] -0.630616182  0.387732754  2.142335821  2.981304738 -1.913044500
 [51] -0.873712346 -2.068015800  0.715617265 -0.431237552  0.252384387
 [56] -0.326145166 -0.072919601  0.323668423  1.103755148 -0.707822628
 [61]  0.192005875 -0.833257684 -0.507803901  1.480823382  2.329361608
 [66]  1.264331120  2.475412425 -0.173868577  0.740869766 -1.196141077
 [71] -0.107482541 -2.570875767  0.126362229 -1.666745721  0.548950579
 [76] -0.649787275 -0.438566856  0.402377848 -0.409255736 -0.556990352
 [81] -0.191110319 -3.264900426  0.919634264 -0.504844970  1.974331095
 [86] -1.840167192  1.114557281  0.381205592  0.357974453  0.571119571
 [91]  1.237030298 -0.508939301  0.040401904  1.672954421 -0.517965507
 [96]  1.553107339  1.356369381  0.073466799 -1.077992696  0.739936922
> 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] -0.745411172 -1.030482800  1.515912564 -0.690763563 -0.978883666
  [6]  0.105134426 -0.579238525  0.117174335  1.203236811  1.112571807
 [11]  1.907525510 -2.612106813 -0.634750899 -1.024588251  0.015289224
 [16]  0.231053326 -1.231083388 -1.453375507 -0.293061420 -0.779736032
 [21] -0.972964409 -0.474477793  1.459833413 -2.412011715  0.329140963
 [26]  0.519212753  0.874608155  1.269300470  0.282860360 -1.462407989
 [31]  0.757215301  0.870926880  0.007713818 -0.667823665 -0.022004777
 [36]  1.337128642  1.066298352 -0.908805027 -0.875489888  0.062833590
 [41]  0.089402544 -0.309623407  1.071472967 -0.952381779  0.447340017
 [46] -0.630616182  0.387732754  2.142335821  2.981304738 -1.913044500
 [51] -0.873712346 -2.068015800  0.715617265 -0.431237552  0.252384387
 [56] -0.326145166 -0.072919601  0.323668423  1.103755148 -0.707822628
 [61]  0.192005875 -0.833257684 -0.507803901  1.480823382  2.329361608
 [66]  1.264331120  2.475412425 -0.173868577  0.740869766 -1.196141077
 [71] -0.107482541 -2.570875767  0.126362229 -1.666745721  0.548950579
 [76] -0.649787275 -0.438566856  0.402377848 -0.409255736 -0.556990352
 [81] -0.191110319 -3.264900426  0.919634264 -0.504844970  1.974331095
 [86] -1.840167192  1.114557281  0.381205592  0.357974453  0.571119571
 [91]  1.237030298 -0.508939301  0.040401904  1.672954421 -0.517965507
 [96]  1.553107339  1.356369381  0.073466799 -1.077992696  0.739936922
> rowMin(tmp2)
  [1] -0.745411172 -1.030482800  1.515912564 -0.690763563 -0.978883666
  [6]  0.105134426 -0.579238525  0.117174335  1.203236811  1.112571807
 [11]  1.907525510 -2.612106813 -0.634750899 -1.024588251  0.015289224
 [16]  0.231053326 -1.231083388 -1.453375507 -0.293061420 -0.779736032
 [21] -0.972964409 -0.474477793  1.459833413 -2.412011715  0.329140963
 [26]  0.519212753  0.874608155  1.269300470  0.282860360 -1.462407989
 [31]  0.757215301  0.870926880  0.007713818 -0.667823665 -0.022004777
 [36]  1.337128642  1.066298352 -0.908805027 -0.875489888  0.062833590
 [41]  0.089402544 -0.309623407  1.071472967 -0.952381779  0.447340017
 [46] -0.630616182  0.387732754  2.142335821  2.981304738 -1.913044500
 [51] -0.873712346 -2.068015800  0.715617265 -0.431237552  0.252384387
 [56] -0.326145166 -0.072919601  0.323668423  1.103755148 -0.707822628
 [61]  0.192005875 -0.833257684 -0.507803901  1.480823382  2.329361608
 [66]  1.264331120  2.475412425 -0.173868577  0.740869766 -1.196141077
 [71] -0.107482541 -2.570875767  0.126362229 -1.666745721  0.548950579
 [76] -0.649787275 -0.438566856  0.402377848 -0.409255736 -0.556990352
 [81] -0.191110319 -3.264900426  0.919634264 -0.504844970  1.974331095
 [86] -1.840167192  1.114557281  0.381205592  0.357974453  0.571119571
 [91]  1.237030298 -0.508939301  0.040401904  1.672954421 -0.517965507
 [96]  1.553107339  1.356369381  0.073466799 -1.077992696  0.739936922
> 
> colMeans(tmp2)
[1] 0.009608868
> colSums(tmp2)
[1] 0.9608868
> colVars(tmp2)
[1] 1.352672
> colSd(tmp2)
[1] 1.163044
> colMax(tmp2)
[1] 2.981305
> colMin(tmp2)
[1] -3.2649
> colMedians(tmp2)
[1] 0.02784556
> colRanges(tmp2)
          [,1]
[1,] -3.264900
[2,]  2.981305
> 
> 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] -2.0022555 -5.9508549  0.2448837  3.3320100  1.7130373 -2.1374354
 [7]  1.0794739  0.7728714 -1.7423895  3.6431927
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -2.7647939
[2,] -0.4988315
[3,]  0.0582581
[4,]  0.3034531
[5,]  1.8905807
> 
> rowApply(tmp,sum)
 [1]  0.5213378  2.0236227 -5.2980458 -6.3029121  2.8655071  2.0168681
 [7] -4.6813308  4.5939037  1.6513672  1.5622158
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    2    4    7    7    3    4   10    5   10     1
 [2,]    7    1    1    1    1    2    2    7    8     8
 [3,]    5    2    5    4    9    6    1    4    9    10
 [4,]    1    9   10   10    4    1    8    9    6     9
 [5,]   10    7    6    2    5    7    4    6    4     6
 [6,]    6    3    8    5    2   10    9    2    2     3
 [7,]    3    6    9    3   10    5    6   10    7     2
 [8,]    4    5    2    9    6    9    7    3    3     7
 [9,]    8   10    4    6    7    3    3    1    1     5
[10,]    9    8    3    8    8    8    5    8    5     4
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1] -2.28396282 -2.05727695  0.30358454 -3.11941298  0.47345970  0.14436735
 [7]  0.07367776  0.20005795 -4.32897691  3.66761433  2.05323379  0.84736216
[13] -0.35543909  4.18051419 -3.18771200  1.84632483 -5.68964529 -3.69430824
[19] -0.67323540  0.85118500
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -1.04541462
[2,] -0.67187040
[3,] -0.54569882
[4,] -0.09355347
[5,]  0.07257448
> 
> rowApply(tmp,sum)
[1]   2.152636   4.162451  -4.509871  -1.804716 -10.749087
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]    7   11   13    6    7
[2,]   11    7   12    3   11
[3,]    4    3    9   15   20
[4,]    1   20   20    7    1
[5,]   16   10    7   17    8
> 
> 
> as.matrix(tmp)
            [,1]        [,2]       [,3]       [,4]        [,5]        [,6]
[1,] -0.54569882  0.09721317 -0.7957205 -1.7373186  0.88136663  2.20021737
[2,]  0.07257448 -0.20744558 -0.8015816  2.3936160  0.03038779 -0.19868940
[3,] -0.09355347 -0.17290317 -0.4005738  1.1063614 -0.46890396 -0.03013146
[4,] -0.67187040 -1.40841323  0.5690904 -0.6310527  0.88399715 -1.45337632
[5,] -1.04541462 -0.36572815  1.7323701 -4.2510191 -0.85338791 -0.37365284
           [,7]        [,8]       [,9]     [,10]       [,11]      [,12]
[1,]  1.3943290  1.81771788 -0.9220502 0.1245062 -0.11230864  0.2997762
[2,]  0.0902457 -1.90890135 -0.6992089 1.2523689  1.38784107  1.7115214
[3,] -0.3970630  0.36243157 -1.0379503 0.8820680  0.52314672 -0.4580431
[4,]  0.9140954  0.06916278 -0.3465712 1.2756489  0.09534568 -0.5739401
[5,] -1.9279294 -0.14035293 -1.3231963 0.1330224  0.15920897 -0.1319521
          [,13]      [,14]      [,15]      [,16]      [,17]      [,18]
[1,]  0.9408196  0.7745057  0.5382636 -0.5489387 -1.3001197 -0.1377108
[2,] -0.3121598  0.1751704 -0.8155698  1.3134558 -0.2753275 -0.0339155
[3,] -0.5746712 -0.3989989 -0.5711575  0.6618222 -1.5060436 -2.0556909
[4,]  0.4281087  1.9698559 -0.5277803 -0.2547193 -0.7053803 -1.4404613
[5,] -0.8375364  1.6599812 -1.8114681  0.6747048 -1.9027741 -0.0265297
          [,19]      [,20]
[1,] -0.6361289 -0.1800845
[2,]  0.7571585  0.2309105
[3,] -0.5512729  0.6712560
[4,]  0.8632384 -0.8596945
[5,] -1.1062305  0.9887975
> 
> 
> 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 :  655  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 :  567  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 -1.58074 0.9979144 0.2066212 1.211563 -1.150258 0.5178354 0.4190822
          col8     col9    col10   col11     col12     col13      col14
row1 0.2282616 1.284519 1.001294 2.27942 0.5341866 -1.027551 -0.2231819
        col15     col16      col17     col18      col19      col20
row1 1.742135 0.6272193 0.02837241 0.3884905 -0.8214127 -0.5555808
> tmp[,"col10"]
          col10
row1  1.0012943
row2  0.5477120
row3 -0.2714901
row4 -0.6104439
row5  1.2562438
> tmp[c("row1","row5"),]
           col1       col2      col3      col4       col5       col6       col7
row1 -1.5807404 0.99791445 0.2066212 1.2115632 -1.1502582  0.5178354  0.4190822
row5  0.8333131 0.04768308 0.8943429 0.1741031  0.6841888 -0.9895242 -0.1009037
           col8       col9    col10     col11     col12      col13      col14
row1  0.2282616 1.28451903 1.001294  2.279420 0.5341866 -1.0275510 -0.2231819
row5 -0.3472598 0.08918039 1.256244 -1.104303 1.3199775  0.6742076  1.9359599
        col15     col16       col17     col18      col19      col20
row1 1.742135 0.6272193  0.02837241 0.3884905 -0.8214127 -0.5555808
row5 1.934684 0.5184094 -0.57925112 1.2350205  0.9437992  0.7610904
> tmp[,c("col6","col20")]
           col6      col20
row1  0.5178354 -0.5555808
row2 -0.5274328 -0.5311647
row3  0.3752505  2.3871765
row4  0.4014896  0.2097543
row5 -0.9895242  0.7610904
> tmp[c("row1","row5"),c("col6","col20")]
           col6      col20
row1  0.5178354 -0.5555808
row5 -0.9895242  0.7610904
> 
> 
> 
> 
> 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 49.54737 50.64612 48.89173 49.91507 50.01981 104.6471 49.30627 50.80114
         col9    col10    col11    col12    col13    col14    col15    col16
row1 48.78383 49.41511 49.04311 49.81354 51.50583 51.63737 51.21129 47.86428
        col17    col18    col19    col20
row1 48.71482 51.06873 49.66226 104.5029
> tmp[,"col10"]
        col10
row1 49.41511
row2 29.66958
row3 31.69368
row4 30.20683
row5 49.78832
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 49.54737 50.64612 48.89173 49.91507 50.01981 104.6471 49.30627 50.80114
row5 49.32303 50.89441 49.90532 49.92769 52.08304 105.3627 50.32738 51.32795
         col9    col10    col11    col12    col13    col14    col15    col16
row1 48.78383 49.41511 49.04311 49.81354 51.50583 51.63737 51.21129 47.86428
row5 49.82314 49.78832 51.54798 48.68424 47.91886 48.90280 50.68602 51.13345
        col17    col18    col19    col20
row1 48.71482 51.06873 49.66226 104.5029
row5 49.73702 48.44403 49.07617 105.1411
> tmp[,c("col6","col20")]
          col6     col20
row1 104.64712 104.50292
row2  74.21975  75.51303
row3  73.55504  74.49519
row4  75.38761  73.20556
row5 105.36272 105.14112
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 104.6471 104.5029
row5 105.3627 105.1411
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 104.6471 104.5029
row5 105.3627 105.1411
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
           col13
[1,] -0.29790001
[2,] -0.07153087
[3,] -0.33054256
[4,]  1.96312265
[5,]  2.16609355
> tmp[,c("col17","col7")]
           col17        col7
[1,] -0.23804209  0.61628093
[2,] -0.19404708 -1.63342259
[3,]  0.50382884 -1.02084849
[4,]  0.42511466 -0.02694993
[5,] -0.00640584 -1.13321796
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
             col6       col20
[1,]  1.502808383  1.07083018
[2,] -0.003816454  0.54711353
[3,]  0.993272094  0.05030241
[4,]  1.315511021  1.03176725
[5,]  0.837654351 -0.99927606
> subBufferedMatrix(tmp,1,c("col6"))[,1]
         col1
[1,] 1.502808
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
             col6
[1,]  1.502808383
[2,] -0.003816454
> 
> 
> 
> 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]       [,7]
row3 0.7917576 -0.7012862 1.0966668 0.02592337 1.26289395 -0.9206334  1.5263413
row1 2.1212671 -0.1936359 0.4013785 1.32028851 0.02302377 -2.1705810 -0.4489104
           [,8]         [,9]      [,10]      [,11]       [,12]      [,13]
row3 -1.3356022  0.006568484 -0.8457200 -0.6650638  0.08900893 -0.6515250
row1 -0.3889981 -1.450986000 -0.8920909 -0.6031456 -0.87885200  0.3180373
          [,14]      [,15]      [,16]      [,17]      [,18]        [,19]
row3 -1.0419804 -0.6121932  0.9361547 -0.3648078 -0.3887736  0.734232551
row1  0.4177689 -2.0066220 -0.3047363  0.3381933 -0.6282916 -0.004190501
           [,20]
row3 1.356060273
row1 0.001636901
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
           [,1]      [,2]     [,3]       [,4]      [,5]       [,6]     [,7]
row2 -0.5438014 0.8868713 1.537689 -0.8677802 -1.537043 -0.8132026 1.182196
          [,8]    [,9]     [,10]
row2 -0.421447 1.63862 0.1167239
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
           [,1]      [,2]       [,3]     [,4]       [,5]     [,6]       [,7]
row5 -0.8214395 0.3066524 -0.1578388 0.428282 -0.9446113 2.097403 -0.6392544
          [,8]      [,9]     [,10]       [,11]     [,12]      [,13]     [,14]
row5 0.4672726 0.1829395 -0.568489 -0.04881642 -1.291415 -0.3519512 -1.308416
        [,15]      [,16]       [,17]       [,18]      [,19]     [,20]
row5 2.496012 0.06257571 -0.04367494 -0.09220678 0.08482485 -1.440276
> 
> 
> 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: 0x600002ef0420>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158322f89c1e2"
 [2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158327d17f4cf"
 [3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158322fc98232"
 [4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158325682b920"
 [5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158322048103f"
 [6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158325b22a8a7"
 [7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM15832406e9aaf"
 [8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158321d6d7835"
 [9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158327deeeeaa"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1583251771b7d"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1583262add553"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM158322906ec2" 
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM15832585783de"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1583259929121"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1583225763b78"
> 
> 
> ### 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: 0x600002efc240>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002efc240>
Warning message:
In dir.create(new.directory) :
  '/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x600002efc240>
> rowMedians(tmp)
  [1] -5.017250e-02  2.014000e-02  2.262894e-01 -1.174532e-01  4.830387e-02
  [6]  7.630525e-05 -4.039295e-01 -1.019339e-01  1.891071e-01 -1.528221e-01
 [11] -2.263049e-01  6.346499e-02  4.267944e-01  5.277279e-02 -8.044223e-02
 [16] -1.366809e-01  3.505637e-01  3.835610e-02 -1.297407e-01 -2.784647e-01
 [21]  1.380544e-01  6.398159e-01  3.321641e-01  2.821799e-01 -8.177145e-02
 [26] -2.582236e-01  3.228943e-01  2.241165e-01 -3.852682e-01  3.456442e-01
 [31]  3.664387e-02 -8.237190e-02  7.756837e-04 -1.393160e-02  5.832907e-02
 [36]  6.596224e-01 -3.680003e-01  1.285475e-01 -2.156813e-01 -7.599008e-02
 [41] -1.543079e-01  3.719571e-02  2.957496e-01 -1.208998e-01 -9.614170e-03
 [46] -4.613807e-02 -1.489248e-01  1.293554e-01  2.020946e-01 -8.552677e-02
 [51] -2.542210e-01  3.048452e-01  3.013996e-01  2.428399e-01  2.348083e-01
 [56] -4.521149e-02 -6.336937e-02  3.913172e-01 -4.711231e-01 -7.130950e-02
 [61]  1.034008e-01 -2.824729e-01 -4.278545e-01 -1.627716e-01 -1.316666e-01
 [66] -5.154083e-01  1.250842e-01 -1.103484e-01 -2.573869e-01 -5.474250e-01
 [71] -1.021378e-01  2.084859e-01  4.925648e-01 -1.006125e-01 -2.093841e-01
 [76]  4.716525e-01  1.306830e-01 -4.951387e-01  2.491205e-01  2.821239e-03
 [81] -3.627855e-01 -4.447522e-01 -2.985079e-01  1.629173e-01  2.792442e-01
 [86] -3.003855e-01  2.006709e-01 -2.092669e-01 -9.830341e-02 -2.105626e-01
 [91] -2.284392e-02  3.717440e-03 -4.659547e-02  6.032081e-01 -1.814052e-01
 [96] -4.533435e-02  2.712917e-01  2.490122e-01 -2.267053e-01 -2.667174e-01
[101]  3.148500e-01 -1.523149e-01  1.402758e-01 -2.646699e-01 -2.094110e-01
[106]  4.477357e-01 -1.915239e-01 -9.156676e-02  3.249975e-01  2.742054e-01
[111]  1.386674e-01  6.571649e-01 -8.550748e-02 -2.064236e-01  3.153935e-01
[116] -2.118436e-01  5.431349e-01 -2.222561e-01  7.487631e-02 -1.307695e-01
[121]  1.403386e-01  1.528567e-01 -2.153087e-01  4.769723e-02 -8.120699e-02
[126]  2.072523e-01  8.144739e-01  1.746164e-01 -5.004108e-01 -1.513105e-01
[131]  3.944645e-02 -6.195148e-01 -5.857319e-02 -1.014293e-01  4.343220e-01
[136]  3.113112e-01 -6.175015e-01  9.844636e-02  7.054367e-01  3.444859e-01
[141] -4.191049e-01  2.610812e-01  7.584189e-02 -3.097298e-02 -1.383430e-01
[146]  5.583366e-01  3.074603e-02  2.977143e-01 -4.962661e-01  3.141085e-01
[151]  4.703070e-01 -1.856046e-01  2.343949e-01  1.591661e-01 -1.498386e-01
[156]  9.740708e-02 -5.330620e-03 -2.229275e-01  3.727056e-01  2.220132e-01
[161] -4.183493e-01 -3.698459e-01  1.251142e-01  2.008085e-01  1.190398e-01
[166]  2.815910e-01 -2.804117e-01  1.635472e-01 -3.417315e-01  1.255640e-01
[171] -7.609131e-02  1.956616e-01  8.611095e-02 -4.447330e-01 -1.622689e-01
[176] -2.974250e-01  3.678545e-01  1.793089e-02  3.911143e-01  1.828862e-01
[181]  5.716665e-02 -4.683623e-01  6.832460e-02  3.124108e-01 -7.465746e-02
[186] -1.378648e-01  2.392991e-01 -3.223001e-01  2.410190e-01  2.479738e-01
[191]  1.028384e-01 -4.325058e-01  5.248174e-02 -2.612060e-01 -9.835601e-02
[196]  1.225546e-01  3.352326e-01  2.025486e-01  8.065044e-01  3.305202e-01
[201] -1.716485e-01 -5.460940e-01  1.013146e-01 -7.807986e-01  1.201924e-01
[206] -1.571693e-01 -4.250999e-01  1.253526e-01 -8.753107e-02  3.185723e-01
[211]  3.675711e-01  3.216846e-02  6.343672e-01  1.988754e-02  7.818957e-02
[216]  8.102753e-03  7.997204e-02 -1.473886e-01  3.182081e-01 -1.412014e-01
[221]  7.157220e-01  3.595864e-01 -3.916422e-02 -2.374413e-01  7.615351e-02
[226] -3.518389e-01  1.199116e-01  2.144111e-01 -2.597285e-01 -9.635280e-03
> 
> proc.time()
   user  system elapsed 
  0.675   3.249   4.159 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

> library(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: 0x6000033b02a0>
> .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: 0x6000033b02a0>
> .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: 0x6000033b02a0>
> .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: 0x6000033b02a0>
> 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: 0x6000033b4660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4660>
> .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: 0x6000033b4660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4660>
> .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: 0x6000033b4660>
> 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: 0x6000033b4840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4840>
> .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: 0x6000033b4840>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000033b4840>
> .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: 0x6000033b4840>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x6000033b4840>
> .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: 0x6000033b4840>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x6000033b4840>
> .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: 0x6000033b4840>
> 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: 0x6000033b4a20>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000033b4a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4a20>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile15e411b21b64b" "BufferedMatrixFile15e41424703d7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile15e411b21b64b" "BufferedMatrixFile15e41424703d7"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4cc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4cc0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033b4cc0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033b4cc0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000033b4cc0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000033b4cc0>
> .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: 0x6000033b4ea0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033b4ea0>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000033b4ea0>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000033b4ea0>
> 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: 0x6000033b5080>
> .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: 0x6000033b5080>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.112   0.041   0.143 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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

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

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

> library(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 
  0.127   0.028   0.152 

Example timings