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This page was generated on 2025-10-16 12:05 -0400 (Thu, 16 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" 4867
lconwaymacOS 12.7.6 Montereyx86_644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4655
kjohnson3macOS 13.7.7 Venturaarm644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4600
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4610
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 255/2346HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.73.0  (landing page)
Ben Bolstad
Snapshot Date: 2025-10-15 13:45 -0400 (Wed, 15 Oct 2025)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: devel
git_last_commit: 0147962
git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025)
nebbiolo2Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.6 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kjohnson3macOS 13.7.7 Ventura / arm64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
taishanLinux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for BufferedMatrix on 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: 2025-10-15 18:35:51 -0400 (Wed, 15 Oct 2025)
EndedAt: 2025-10-15 18:36:07 -0400 (Wed, 15 Oct 2025)
EllapsedTime: 16.2 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 (2025-09-10 r88807)
* 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: ‘MacOSX11.3.1.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
   209 |     $x^{power}$ elementwise of the matrix
       |        ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘Rcodetesting.R’
  Running ‘c_code_level_tests.R’
  Running ‘objectTesting.R’
  Running ‘rawCalltesting.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 WARNING, 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.


Installation output

BufferedMatrix.Rcheck/00install.out

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-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: ‘MacOSX11.3.1.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 (2025-09-10 r88807) -- "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 
  0.108   0.036   0.140 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: 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    1056624 56.5         NA   634340 33.9
Vcells 891019  6.8    8388608 64.0     196608  2109889 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 Oct 15 18:36:00 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 Oct 15 18:36:00 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: 0x600002f84000>
> 
> 
> 
> 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 Oct 15 18:36:01 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 Oct 15 18:36:01 2025"
> 
> ColMode(tmp2)
<pointer: 0x600002f84000>
> 
> 
> 
> ### 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,] 99.1707827  0.8904548 -0.1002564  0.0458632
[2,] -0.7769350  0.3384607  1.3982161 -0.1476692
[3,]  0.5450194 -0.2140863 -0.3608478 -1.2342241
[4,] -0.8008290 -1.6878772 -0.6345588  0.6028851
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]      [,3]      [,4]
[1,] 99.1707827 0.8904548 0.1002564 0.0458632
[2,]  0.7769350 0.3384607 1.3982161 0.1476692
[3,]  0.5450194 0.2140863 0.3608478 1.2342241
[4,]  0.8008290 1.6878772 0.6345588 0.6028851
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]      [,2]      [,3]      [,4]
[1,] 9.9584528 0.9436391 0.3166329 0.2141570
[2,] 0.8814391 0.5817738 1.1824619 0.3842775
[3,] 0.7382543 0.4626946 0.6007061 1.1109564
[4,] 0.8948905 1.2991833 0.7965920 0.7764568
> 
> my.function <- function(x,power){
+   (x+5)^power
+ }
> 
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 223.75531 35.32685 28.26659 27.18743
[2,]  34.59133 31.15620 38.22283 28.99044
[3,]  32.92756 29.84103 31.36791 37.34379
[4,]  34.74973 39.67971 33.60048 33.36745
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002f80000>
> exp(tmp5)
<pointer: 0x600002f80000>
> log(tmp5,2)
<pointer: 0x600002f80000>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.7174
> Min(tmp5)
[1] 52.55886
> mean(tmp5)
[1] 72.28458
> Sum(tmp5)
[1] 14456.92
> Var(tmp5)
[1] 854.8097
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 88.16071 71.56053 70.37964 70.22195 69.95400 71.68608 69.49218 72.44086
 [9] 67.83420 71.11561
> rowSums(tmp5)
 [1] 1763.214 1431.211 1407.593 1404.439 1399.080 1433.722 1389.844 1448.817
 [9] 1356.684 1422.312
> rowVars(tmp5)
 [1] 7986.87832   90.52160   41.39244   56.47304  112.94250   96.31705
 [7]   75.08964   44.20621   53.37091   85.03341
> rowSd(tmp5)
 [1] 89.369337  9.514284  6.433696  7.514855 10.627441  9.814125  8.665428
 [8]  6.648775  7.305540  9.221356
> rowMax(tmp5)
 [1] 465.71736  86.39166  83.20524  86.68307  90.73065  88.12168  94.94732
 [8]  83.84891  88.05773  85.11387
> rowMin(tmp5)
 [1] 54.36872 54.84574 58.18839 57.65941 54.11009 58.06696 58.06534 52.55886
 [9] 54.70082 53.30482
> 
> colMeans(tmp5)
 [1] 110.25740  71.35782  68.79505  66.96338  73.64564  69.25421  71.42430
 [8]  70.21135  67.40169  74.12194  66.58693  72.99143  66.41568  71.61201
[15]  68.35721  73.78502  72.89905  71.14994  64.48282  73.97867
> colSums(tmp5)
 [1] 1102.5740  713.5782  687.9505  669.6338  736.4564  692.5421  714.2430
 [8]  702.1135  674.0169  741.2194  665.8693  729.9143  664.1568  716.1201
[15]  683.5721  737.8502  728.9905  711.4994  644.8282  739.7867
> colVars(tmp5)
 [1] 15642.13463   115.61056    72.72182    96.27244    43.04698    65.14736
 [7]    26.58767    49.02581   135.90489    77.87871    65.40156    37.61887
[13]    87.58069    47.34060    79.36949    56.59909   106.38746   107.61775
[19]    37.58473    87.05571
> colSd(tmp5)
 [1] 125.068520  10.752235   8.527709   9.811852   6.561019   8.071391
 [7]   5.156323   7.001844  11.657825   8.824891   8.087123   6.133422
[13]   9.358456   6.880450   8.908955   7.523237  10.314430  10.373898
[19]   6.130638   9.330365
> colMax(tmp5)
 [1] 465.71736  94.94732  79.55582  83.76264  83.20524  81.43694  79.23539
 [8]  82.52014  90.73065  87.23769  79.19225  82.35456  82.00598  85.12327
[15]  82.51050  87.89234  88.05773  89.55173  73.82801  88.12168
> colMin(tmp5)
 [1] 55.17194 61.60437 56.99933 53.30482 63.15568 54.70082 63.76799 60.34996
 [9] 54.84574 62.83705 54.35398 62.39967 52.55886 61.29732 56.00267 61.82002
[17] 60.11296 54.11009 57.37821 64.16999
> 
> 
> ### 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] 88.16071 71.56053       NA 70.22195 69.95400 71.68608 69.49218 72.44086
 [9] 67.83420 71.11561
> rowSums(tmp5)
 [1] 1763.214 1431.211       NA 1404.439 1399.080 1433.722 1389.844 1448.817
 [9] 1356.684 1422.312
> rowVars(tmp5)
 [1] 7986.87832   90.52160   42.17607   56.47304  112.94250   96.31705
 [7]   75.08964   44.20621   53.37091   85.03341
> rowSd(tmp5)
 [1] 89.369337  9.514284  6.494310  7.514855 10.627441  9.814125  8.665428
 [8]  6.648775  7.305540  9.221356
> rowMax(tmp5)
 [1] 465.71736  86.39166        NA  86.68307  90.73065  88.12168  94.94732
 [8]  83.84891  88.05773  85.11387
> rowMin(tmp5)
 [1] 54.36872 54.84574       NA 57.65941 54.11009 58.06696 58.06534 52.55886
 [9] 54.70082 53.30482
> 
> colMeans(tmp5)
 [1] 110.25740  71.35782        NA  66.96338  73.64564  69.25421  71.42430
 [8]  70.21135  67.40169  74.12194  66.58693  72.99143  66.41568  71.61201
[15]  68.35721  73.78502  72.89905  71.14994  64.48282  73.97867
> colSums(tmp5)
 [1] 1102.5740  713.5782        NA  669.6338  736.4564  692.5421  714.2430
 [8]  702.1135  674.0169  741.2194  665.8693  729.9143  664.1568  716.1201
[15]  683.5721  737.8502  728.9905  711.4994  644.8282  739.7867
> colVars(tmp5)
 [1] 15642.13463   115.61056          NA    96.27244    43.04698    65.14736
 [7]    26.58767    49.02581   135.90489    77.87871    65.40156    37.61887
[13]    87.58069    47.34060    79.36949    56.59909   106.38746   107.61775
[19]    37.58473    87.05571
> colSd(tmp5)
 [1] 125.068520  10.752235         NA   9.811852   6.561019   8.071391
 [7]   5.156323   7.001844  11.657825   8.824891   8.087123   6.133422
[13]   9.358456   6.880450   8.908955   7.523237  10.314430  10.373898
[19]   6.130638   9.330365
> colMax(tmp5)
 [1] 465.71736  94.94732        NA  83.76264  83.20524  81.43694  79.23539
 [8]  82.52014  90.73065  87.23769  79.19225  82.35456  82.00598  85.12327
[15]  82.51050  87.89234  88.05773  89.55173  73.82801  88.12168
> colMin(tmp5)
 [1] 55.17194 61.60437       NA 53.30482 63.15568 54.70082 63.76799 60.34996
 [9] 54.84574 62.83705 54.35398 62.39967 52.55886 61.29732 56.00267 61.82002
[17] 60.11296 54.11009 57.37821 64.16999
> 
> Max(tmp5,na.rm=TRUE)
[1] 465.7174
> Min(tmp5,na.rm=TRUE)
[1] 52.55886
> mean(tmp5,na.rm=TRUE)
[1] 72.31974
> Sum(tmp5,na.rm=TRUE)
[1] 14391.63
> Var(tmp5,na.rm=TRUE)
[1] 858.8785
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 88.16071 71.56053 70.64761 70.22195 69.95400 71.68608 69.49218 72.44086
 [9] 67.83420 71.11561
> rowSums(tmp5,na.rm=TRUE)
 [1] 1763.214 1431.211 1342.305 1404.439 1399.080 1433.722 1389.844 1448.817
 [9] 1356.684 1422.312
> rowVars(tmp5,na.rm=TRUE)
 [1] 7986.87832   90.52160   42.17607   56.47304  112.94250   96.31705
 [7]   75.08964   44.20621   53.37091   85.03341
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.369337  9.514284  6.494310  7.514855 10.627441  9.814125  8.665428
 [8]  6.648775  7.305540  9.221356
> rowMax(tmp5,na.rm=TRUE)
 [1] 465.71736  86.39166  83.20524  86.68307  90.73065  88.12168  94.94732
 [8]  83.84891  88.05773  85.11387
> rowMin(tmp5,na.rm=TRUE)
 [1] 54.36872 54.84574 58.18839 57.65941 54.11009 58.06696 58.06534 52.55886
 [9] 54.70082 53.30482
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 110.25740  71.35782  69.18470  66.96338  73.64564  69.25421  71.42430
 [8]  70.21135  67.40169  74.12194  66.58693  72.99143  66.41568  71.61201
[15]  68.35721  73.78502  72.89905  71.14994  64.48282  73.97867
> colSums(tmp5,na.rm=TRUE)
 [1] 1102.5740  713.5782  622.6623  669.6338  736.4564  692.5421  714.2430
 [8]  702.1135  674.0169  741.2194  665.8693  729.9143  664.1568  716.1201
[15]  683.5721  737.8502  728.9905  711.4994  644.8282  739.7867
> colVars(tmp5,na.rm=TRUE)
 [1] 15642.13463   115.61056    80.10399    96.27244    43.04698    65.14736
 [7]    26.58767    49.02581   135.90489    77.87871    65.40156    37.61887
[13]    87.58069    47.34060    79.36949    56.59909   106.38746   107.61775
[19]    37.58473    87.05571
> colSd(tmp5,na.rm=TRUE)
 [1] 125.068520  10.752235   8.950083   9.811852   6.561019   8.071391
 [7]   5.156323   7.001844  11.657825   8.824891   8.087123   6.133422
[13]   9.358456   6.880450   8.908955   7.523237  10.314430  10.373898
[19]   6.130638   9.330365
> colMax(tmp5,na.rm=TRUE)
 [1] 465.71736  94.94732  79.55582  83.76264  83.20524  81.43694  79.23539
 [8]  82.52014  90.73065  87.23769  79.19225  82.35456  82.00598  85.12327
[15]  82.51050  87.89234  88.05773  89.55173  73.82801  88.12168
> colMin(tmp5,na.rm=TRUE)
 [1] 55.17194 61.60437 56.99933 53.30482 63.15568 54.70082 63.76799 60.34996
 [9] 54.84574 62.83705 54.35398 62.39967 52.55886 61.29732 56.00267 61.82002
[17] 60.11296 54.11009 57.37821 64.16999
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 88.16071 71.56053      NaN 70.22195 69.95400 71.68608 69.49218 72.44086
 [9] 67.83420 71.11561
> rowSums(tmp5,na.rm=TRUE)
 [1] 1763.214 1431.211    0.000 1404.439 1399.080 1433.722 1389.844 1448.817
 [9] 1356.684 1422.312
> rowVars(tmp5,na.rm=TRUE)
 [1] 7986.87832   90.52160         NA   56.47304  112.94250   96.31705
 [7]   75.08964   44.20621   53.37091   85.03341
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.369337  9.514284        NA  7.514855 10.627441  9.814125  8.665428
 [8]  6.648775  7.305540  9.221356
> rowMax(tmp5,na.rm=TRUE)
 [1] 465.71736  86.39166        NA  86.68307  90.73065  88.12168  94.94732
 [8]  83.84891  88.05773  85.11387
> rowMin(tmp5,na.rm=TRUE)
 [1] 54.36872 54.84574       NA 57.65941 54.11009 58.06696 58.06534 52.55886
 [9] 54.70082 53.30482
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 114.89329  72.38533       NaN  65.76751  72.58346  67.90057  70.55640
 [8]  70.31838  68.42539  74.69380  66.43168  73.08779  66.40070  72.13033
[15]  68.47806  73.63440  73.56784  70.99030  63.54410  74.95071
> colSums(tmp5,na.rm=TRUE)
 [1] 1034.0396  651.4680    0.0000  591.9076  653.2511  611.1052  635.0076
 [8]  632.8654  615.8285  672.2442  597.8851  657.7901  597.6063  649.1729
[15]  616.3026  662.7096  662.1105  638.9127  571.8969  674.5564
> colVars(tmp5,na.rm=TRUE)
 [1] 17355.62255   118.18432          NA    92.21784    35.73534    52.67704
 [7]    21.43707    55.02517   141.10344    83.93460    73.30558    42.21676
[13]    98.52575    50.23584    89.12636    63.41877   114.65410   120.78325
[19]    32.36934    87.30804
> colSd(tmp5,na.rm=TRUE)
 [1] 131.740740  10.871261         NA   9.603012   5.977904   7.257895
 [7]   4.630019   7.417895  11.878697   9.161583   8.561868   6.497442
[13]   9.926014   7.087725   9.440676   7.963591  10.707665  10.990143
[19]   5.689406   9.343877
> colMax(tmp5,na.rm=TRUE)
 [1] 465.71736  94.94732      -Inf  83.76264  79.30712  80.79956  77.06964
 [8]  82.52014  90.73065  87.23769  79.19225  82.35456  82.00598  85.12327
[15]  82.51050  87.89234  88.05773  89.55173  73.82801  88.12168
> colMin(tmp5,na.rm=TRUE)
 [1] 55.17194 61.60437      Inf 53.30482 63.15568 54.70082 63.76799 60.34996
 [9] 54.84574 62.83705 54.35398 62.39967 52.55886 61.29732 56.00267 61.82002
[17] 60.11296 54.11009 57.37821 64.16999
> 
> 
> 
> 
> 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]  92.42906 252.16183 208.63598 238.11705 187.68022 138.93736 183.00370
 [8] 134.73945 252.21623 198.33570
> apply(copymatrix,1,var,na.rm=TRUE)
 [1]  92.42906 252.16183 208.63598 238.11705 187.68022 138.93736 183.00370
 [8] 134.73945 252.21623 198.33570
> 
> 
> 
> 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] -2.842171e-14 -1.705303e-13  0.000000e+00 -2.842171e-13 -1.989520e-13
 [6] -1.136868e-13  4.547474e-13  5.684342e-14 -1.705303e-13 -1.136868e-13
[11]  1.421085e-14 -4.263256e-14  0.000000e+00 -2.842171e-14 -8.526513e-14
[16]  0.000000e+00  2.842171e-14  1.989520e-13  0.000000e+00  0.000000e+00
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## making sure these things agree
> ##
> ## first when there is no NA
> 
> 
> 
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+ 
+   if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Max")
+   }
+   
+ 
+   if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Min")
+   }
+ 
+ 
+   if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+ 
+     cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+     cat(sum(r.matrix,na.rm=TRUE),"\n")
+     cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+     
+     stop("No agreement in Sum")
+   }
+   
+   if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+     stop("No agreement in mean")
+   }
+   
+   
+   if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+     stop("No agreement in Var")
+   }
+   
+   
+ 
+   if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowMeans")
+   }
+   
+   
+   if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colMeans")
+   }
+   
+   
+   if(any(abs(rowSums(buff.matrix,na.rm=TRUE)  -  apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in rowSums")
+   }
+   
+   
+   if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colSums")
+   }
+   
+   ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when 
+   ### computing variance
+   my.Var <- function(x,na.rm=FALSE){
+    if (all(is.na(x))){
+      return(NA)
+    } else {
+      var(x,na.rm=na.rm)
+    }
+ 
+   }
+   
+   if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+   
+   
+   if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+ 
+ 
+   if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+ 
+   if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+   
+   
+   if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+   
+ 
+   if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+ 
+   if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMedian")
+   }
+ 
+   if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colRanges")
+   }
+ 
+ 
+   
+ }
> 
> 
> 
> 
> 
> 
> 
> 
> 
> for (rep in 1:20){
+   copymatrix <- matrix(rnorm(200,150,15),10,20)
+   
+   tmp5[1:10,1:20] <- copymatrix
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ## now lets assign some NA values and check agreement
+ 
+   which.row <- sample(1:10,1,replace=TRUE)
+   which.col  <- sample(1:20,1,replace=TRUE)
+   
+   cat(which.row," ",which.col,"\n")
+   
+   tmp5[which.row,which.col] <- NA
+   copymatrix[which.row,which.col] <- NA
+   
+   agree.checks(tmp5,copymatrix)
+ 
+   ## make an entire row NA
+   tmp5[which.row,] <- NA
+   copymatrix[which.row,] <- NA
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ### also make an entire col NA
+   tmp5[,which.col] <- NA
+   copymatrix[,which.col] <- NA
+ 
+   agree.checks(tmp5,copymatrix)
+ 
+   ### now make 1 element non NA with NA in the rest of row and column
+ 
+   tmp5[which.row,which.col] <- rnorm(1,150,15)
+   copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+ 
+   agree.checks(tmp5,copymatrix)
+ }
3   2 
9   5 
6   20 
7   10 
7   9 
10   5 
9   18 
3   13 
6   14 
1   10 
3   1 
9   6 
4   5 
2   12 
7   16 
8   18 
5   8 
7   9 
7   17 
4   19 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> ### now test 1 by n and n by 1 matrix
> 
> 
> err.tol <- 1e-12
> 
> rm(tmp5)
> 
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
> 
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
> 
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
> 
> 
> 
> 
> 
> Max(tmp)
[1] 2.449615
> Min(tmp)
[1] -1.940858
> mean(tmp)
[1] 0.1566841
> Sum(tmp)
[1] 15.66841
> Var(tmp)
[1] 0.8559142
> 
> rowMeans(tmp)
[1] 0.1566841
> rowSums(tmp)
[1] 15.66841
> rowVars(tmp)
[1] 0.8559142
> rowSd(tmp)
[1] 0.9251563
> rowMax(tmp)
[1] 2.449615
> rowMin(tmp)
[1] -1.940858
> 
> colMeans(tmp)
  [1]  0.0966762071  0.8160358113 -1.2715836825  0.5359378477 -0.6932101890
  [6] -0.2869556456 -0.5675047061 -0.2269890866  0.5176011817 -0.7395116672
 [11] -0.5451937892  1.0253166426 -0.6738651620  0.4037992202  1.7514742014
 [16]  0.6754281427 -0.7176242697  0.1507880402 -1.1317077273  1.2112223503
 [21]  2.4496153259  1.0400143112 -0.9843058164 -1.8069474769  1.2450288965
 [26] -0.4862186069 -0.8717502026  1.0572125052 -0.4642148338  1.3326089609
 [31]  1.7618013694  0.2960023742 -0.8166370971 -0.8424016614  0.6422386555
 [36]  2.1422728888 -0.8505193961  0.3953205631  0.2077763684 -1.6259738820
 [41]  0.8948332141  0.4584596076  0.0031449707 -0.9977160216 -1.6276642503
 [46] -0.0265674695 -0.0735492297  0.6674950022  0.3410759179  0.8150430894
 [51] -0.8736387584  0.4699806725 -0.3504680354  1.5476512630  2.4197081557
 [56] -0.5176514726  0.0937852503  0.4883559863  0.1268602369 -0.1336044431
 [61] -0.9349795332  0.2987328983 -0.1126699624  0.7836022931  0.6826260872
 [66]  0.7470992854  0.0881578309  1.9416386803  2.4410651539  0.2642076753
 [71]  0.4107522861 -0.4931228670 -1.8439203266 -0.1384477032  0.4539018569
 [76]  0.8180876545  1.2725700093  0.4869562137 -0.2414558024  0.2403020820
 [81]  0.7502529700  0.1799106568 -0.2776238130 -0.6196272713  0.0651427356
 [86] -0.4612713625  1.5073900339 -0.0007586617 -0.3545790559  0.7347639316
 [91]  0.3312424615 -0.0777367915  0.2885385096 -0.4688847424  0.5184125435
 [96] -0.2183134056 -1.9408575498  0.3860546259  0.4421397825 -0.1574823824
> colSums(tmp)
  [1]  0.0966762071  0.8160358113 -1.2715836825  0.5359378477 -0.6932101890
  [6] -0.2869556456 -0.5675047061 -0.2269890866  0.5176011817 -0.7395116672
 [11] -0.5451937892  1.0253166426 -0.6738651620  0.4037992202  1.7514742014
 [16]  0.6754281427 -0.7176242697  0.1507880402 -1.1317077273  1.2112223503
 [21]  2.4496153259  1.0400143112 -0.9843058164 -1.8069474769  1.2450288965
 [26] -0.4862186069 -0.8717502026  1.0572125052 -0.4642148338  1.3326089609
 [31]  1.7618013694  0.2960023742 -0.8166370971 -0.8424016614  0.6422386555
 [36]  2.1422728888 -0.8505193961  0.3953205631  0.2077763684 -1.6259738820
 [41]  0.8948332141  0.4584596076  0.0031449707 -0.9977160216 -1.6276642503
 [46] -0.0265674695 -0.0735492297  0.6674950022  0.3410759179  0.8150430894
 [51] -0.8736387584  0.4699806725 -0.3504680354  1.5476512630  2.4197081557
 [56] -0.5176514726  0.0937852503  0.4883559863  0.1268602369 -0.1336044431
 [61] -0.9349795332  0.2987328983 -0.1126699624  0.7836022931  0.6826260872
 [66]  0.7470992854  0.0881578309  1.9416386803  2.4410651539  0.2642076753
 [71]  0.4107522861 -0.4931228670 -1.8439203266 -0.1384477032  0.4539018569
 [76]  0.8180876545  1.2725700093  0.4869562137 -0.2414558024  0.2403020820
 [81]  0.7502529700  0.1799106568 -0.2776238130 -0.6196272713  0.0651427356
 [86] -0.4612713625  1.5073900339 -0.0007586617 -0.3545790559  0.7347639316
 [91]  0.3312424615 -0.0777367915  0.2885385096 -0.4688847424  0.5184125435
 [96] -0.2183134056 -1.9408575498  0.3860546259  0.4421397825 -0.1574823824
> colVars(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
  [1]  0.0966762071  0.8160358113 -1.2715836825  0.5359378477 -0.6932101890
  [6] -0.2869556456 -0.5675047061 -0.2269890866  0.5176011817 -0.7395116672
 [11] -0.5451937892  1.0253166426 -0.6738651620  0.4037992202  1.7514742014
 [16]  0.6754281427 -0.7176242697  0.1507880402 -1.1317077273  1.2112223503
 [21]  2.4496153259  1.0400143112 -0.9843058164 -1.8069474769  1.2450288965
 [26] -0.4862186069 -0.8717502026  1.0572125052 -0.4642148338  1.3326089609
 [31]  1.7618013694  0.2960023742 -0.8166370971 -0.8424016614  0.6422386555
 [36]  2.1422728888 -0.8505193961  0.3953205631  0.2077763684 -1.6259738820
 [41]  0.8948332141  0.4584596076  0.0031449707 -0.9977160216 -1.6276642503
 [46] -0.0265674695 -0.0735492297  0.6674950022  0.3410759179  0.8150430894
 [51] -0.8736387584  0.4699806725 -0.3504680354  1.5476512630  2.4197081557
 [56] -0.5176514726  0.0937852503  0.4883559863  0.1268602369 -0.1336044431
 [61] -0.9349795332  0.2987328983 -0.1126699624  0.7836022931  0.6826260872
 [66]  0.7470992854  0.0881578309  1.9416386803  2.4410651539  0.2642076753
 [71]  0.4107522861 -0.4931228670 -1.8439203266 -0.1384477032  0.4539018569
 [76]  0.8180876545  1.2725700093  0.4869562137 -0.2414558024  0.2403020820
 [81]  0.7502529700  0.1799106568 -0.2776238130 -0.6196272713  0.0651427356
 [86] -0.4612713625  1.5073900339 -0.0007586617 -0.3545790559  0.7347639316
 [91]  0.3312424615 -0.0777367915  0.2885385096 -0.4688847424  0.5184125435
 [96] -0.2183134056 -1.9408575498  0.3860546259  0.4421397825 -0.1574823824
> colMin(tmp)
  [1]  0.0966762071  0.8160358113 -1.2715836825  0.5359378477 -0.6932101890
  [6] -0.2869556456 -0.5675047061 -0.2269890866  0.5176011817 -0.7395116672
 [11] -0.5451937892  1.0253166426 -0.6738651620  0.4037992202  1.7514742014
 [16]  0.6754281427 -0.7176242697  0.1507880402 -1.1317077273  1.2112223503
 [21]  2.4496153259  1.0400143112 -0.9843058164 -1.8069474769  1.2450288965
 [26] -0.4862186069 -0.8717502026  1.0572125052 -0.4642148338  1.3326089609
 [31]  1.7618013694  0.2960023742 -0.8166370971 -0.8424016614  0.6422386555
 [36]  2.1422728888 -0.8505193961  0.3953205631  0.2077763684 -1.6259738820
 [41]  0.8948332141  0.4584596076  0.0031449707 -0.9977160216 -1.6276642503
 [46] -0.0265674695 -0.0735492297  0.6674950022  0.3410759179  0.8150430894
 [51] -0.8736387584  0.4699806725 -0.3504680354  1.5476512630  2.4197081557
 [56] -0.5176514726  0.0937852503  0.4883559863  0.1268602369 -0.1336044431
 [61] -0.9349795332  0.2987328983 -0.1126699624  0.7836022931  0.6826260872
 [66]  0.7470992854  0.0881578309  1.9416386803  2.4410651539  0.2642076753
 [71]  0.4107522861 -0.4931228670 -1.8439203266 -0.1384477032  0.4539018569
 [76]  0.8180876545  1.2725700093  0.4869562137 -0.2414558024  0.2403020820
 [81]  0.7502529700  0.1799106568 -0.2776238130 -0.6196272713  0.0651427356
 [86] -0.4612713625  1.5073900339 -0.0007586617 -0.3545790559  0.7347639316
 [91]  0.3312424615 -0.0777367915  0.2885385096 -0.4688847424  0.5184125435
 [96] -0.2183134056 -1.9408575498  0.3860546259  0.4421397825 -0.1574823824
> colMedians(tmp)
  [1]  0.0966762071  0.8160358113 -1.2715836825  0.5359378477 -0.6932101890
  [6] -0.2869556456 -0.5675047061 -0.2269890866  0.5176011817 -0.7395116672
 [11] -0.5451937892  1.0253166426 -0.6738651620  0.4037992202  1.7514742014
 [16]  0.6754281427 -0.7176242697  0.1507880402 -1.1317077273  1.2112223503
 [21]  2.4496153259  1.0400143112 -0.9843058164 -1.8069474769  1.2450288965
 [26] -0.4862186069 -0.8717502026  1.0572125052 -0.4642148338  1.3326089609
 [31]  1.7618013694  0.2960023742 -0.8166370971 -0.8424016614  0.6422386555
 [36]  2.1422728888 -0.8505193961  0.3953205631  0.2077763684 -1.6259738820
 [41]  0.8948332141  0.4584596076  0.0031449707 -0.9977160216 -1.6276642503
 [46] -0.0265674695 -0.0735492297  0.6674950022  0.3410759179  0.8150430894
 [51] -0.8736387584  0.4699806725 -0.3504680354  1.5476512630  2.4197081557
 [56] -0.5176514726  0.0937852503  0.4883559863  0.1268602369 -0.1336044431
 [61] -0.9349795332  0.2987328983 -0.1126699624  0.7836022931  0.6826260872
 [66]  0.7470992854  0.0881578309  1.9416386803  2.4410651539  0.2642076753
 [71]  0.4107522861 -0.4931228670 -1.8439203266 -0.1384477032  0.4539018569
 [76]  0.8180876545  1.2725700093  0.4869562137 -0.2414558024  0.2403020820
 [81]  0.7502529700  0.1799106568 -0.2776238130 -0.6196272713  0.0651427356
 [86] -0.4612713625  1.5073900339 -0.0007586617 -0.3545790559  0.7347639316
 [91]  0.3312424615 -0.0777367915  0.2885385096 -0.4688847424  0.5184125435
 [96] -0.2183134056 -1.9408575498  0.3860546259  0.4421397825 -0.1574823824
> colRanges(tmp)
           [,1]      [,2]      [,3]      [,4]       [,5]       [,6]       [,7]
[1,] 0.09667621 0.8160358 -1.271584 0.5359378 -0.6932102 -0.2869556 -0.5675047
[2,] 0.09667621 0.8160358 -1.271584 0.5359378 -0.6932102 -0.2869556 -0.5675047
           [,8]      [,9]      [,10]      [,11]    [,12]      [,13]     [,14]
[1,] -0.2269891 0.5176012 -0.7395117 -0.5451938 1.025317 -0.6738652 0.4037992
[2,] -0.2269891 0.5176012 -0.7395117 -0.5451938 1.025317 -0.6738652 0.4037992
        [,15]     [,16]      [,17]    [,18]     [,19]    [,20]    [,21]
[1,] 1.751474 0.6754281 -0.7176243 0.150788 -1.131708 1.211222 2.449615
[2,] 1.751474 0.6754281 -0.7176243 0.150788 -1.131708 1.211222 2.449615
        [,22]      [,23]     [,24]    [,25]      [,26]      [,27]    [,28]
[1,] 1.040014 -0.9843058 -1.806947 1.245029 -0.4862186 -0.8717502 1.057213
[2,] 1.040014 -0.9843058 -1.806947 1.245029 -0.4862186 -0.8717502 1.057213
          [,29]    [,30]    [,31]     [,32]      [,33]      [,34]     [,35]
[1,] -0.4642148 1.332609 1.761801 0.2960024 -0.8166371 -0.8424017 0.6422387
[2,] -0.4642148 1.332609 1.761801 0.2960024 -0.8166371 -0.8424017 0.6422387
        [,36]      [,37]     [,38]     [,39]     [,40]     [,41]     [,42]
[1,] 2.142273 -0.8505194 0.3953206 0.2077764 -1.625974 0.8948332 0.4584596
[2,] 2.142273 -0.8505194 0.3953206 0.2077764 -1.625974 0.8948332 0.4584596
           [,43]     [,44]     [,45]       [,46]       [,47]    [,48]     [,49]
[1,] 0.003144971 -0.997716 -1.627664 -0.02656747 -0.07354923 0.667495 0.3410759
[2,] 0.003144971 -0.997716 -1.627664 -0.02656747 -0.07354923 0.667495 0.3410759
         [,50]      [,51]     [,52]     [,53]    [,54]    [,55]      [,56]
[1,] 0.8150431 -0.8736388 0.4699807 -0.350468 1.547651 2.419708 -0.5176515
[2,] 0.8150431 -0.8736388 0.4699807 -0.350468 1.547651 2.419708 -0.5176515
          [,57]    [,58]     [,59]      [,60]      [,61]     [,62]    [,63]
[1,] 0.09378525 0.488356 0.1268602 -0.1336044 -0.9349795 0.2987329 -0.11267
[2,] 0.09378525 0.488356 0.1268602 -0.1336044 -0.9349795 0.2987329 -0.11267
         [,64]     [,65]     [,66]      [,67]    [,68]    [,69]     [,70]
[1,] 0.7836023 0.6826261 0.7470993 0.08815783 1.941639 2.441065 0.2642077
[2,] 0.7836023 0.6826261 0.7470993 0.08815783 1.941639 2.441065 0.2642077
         [,71]      [,72]    [,73]      [,74]     [,75]     [,76]   [,77]
[1,] 0.4107523 -0.4931229 -1.84392 -0.1384477 0.4539019 0.8180877 1.27257
[2,] 0.4107523 -0.4931229 -1.84392 -0.1384477 0.4539019 0.8180877 1.27257
         [,78]      [,79]     [,80]    [,81]     [,82]      [,83]      [,84]
[1,] 0.4869562 -0.2414558 0.2403021 0.750253 0.1799107 -0.2776238 -0.6196273
[2,] 0.4869562 -0.2414558 0.2403021 0.750253 0.1799107 -0.2776238 -0.6196273
          [,85]      [,86]   [,87]         [,88]      [,89]     [,90]     [,91]
[1,] 0.06514274 -0.4612714 1.50739 -0.0007586617 -0.3545791 0.7347639 0.3312425
[2,] 0.06514274 -0.4612714 1.50739 -0.0007586617 -0.3545791 0.7347639 0.3312425
           [,92]     [,93]      [,94]     [,95]      [,96]     [,97]     [,98]
[1,] -0.07773679 0.2885385 -0.4688847 0.5184125 -0.2183134 -1.940858 0.3860546
[2,] -0.07773679 0.2885385 -0.4688847 0.5184125 -0.2183134 -1.940858 0.3860546
         [,99]     [,100]
[1,] 0.4421398 -0.1574824
[2,] 0.4421398 -0.1574824
> 
> 
> Max(tmp2)
[1] 2.404904
> Min(tmp2)
[1] -2.719074
> mean(tmp2)
[1] -0.153059
> Sum(tmp2)
[1] -15.3059
> Var(tmp2)
[1] 1.066
> 
> rowMeans(tmp2)
  [1] -1.165372139 -0.666796937 -0.298665870  1.298881321  0.557003855
  [6]  0.072498758 -0.933832427 -1.221577771 -1.135054791  2.048257952
 [11] -0.822950632  0.331771338  1.019512595 -0.477627035 -2.055076374
 [16]  0.835090978 -1.684841322  1.819842162 -0.495288662 -2.065742577
 [21] -0.316536369  1.001498224  0.619854179 -0.889461242  2.404903829
 [26]  1.681950801  1.361280466  1.121318524 -0.810917426 -1.050275287
 [31]  0.102560455  1.442550064 -0.531475101 -0.464880244 -0.056595493
 [36]  0.532954467 -0.230321650 -0.700764200 -0.846821010  0.154653480
 [41] -0.016825474 -0.226877435 -1.387860715  2.090237087  0.217134249
 [46] -0.046804045 -0.058754504  1.070065233  1.488787095 -0.607694807
 [51] -0.888241341 -1.822942411  1.626721643  0.458669796 -0.243951571
 [56]  0.505696206  0.109210684 -1.013793530 -0.608896140 -1.113980819
 [61] -1.174237843  0.066377258 -0.928597195  0.292738902  0.926226135
 [66] -0.184547730 -0.934440981 -0.604814358 -1.583552648  0.084731957
 [71] -1.251578631 -0.367668246 -0.866963836 -0.420343634 -2.719074458
 [76]  0.441537597  0.031040666  1.523761974 -0.253744142 -0.503616681
 [81] -0.440992020  0.546139260 -0.684540250  0.661355228 -0.409168713
 [86] -0.417120386  1.438555755 -0.868273768 -0.326036887 -0.932878153
 [91]  0.412057601  0.392474603  0.538786875 -0.001315633  0.231644530
 [96] -1.814684999 -2.399415156 -0.108127101 -1.839330949  0.126331235
> rowSums(tmp2)
  [1] -1.165372139 -0.666796937 -0.298665870  1.298881321  0.557003855
  [6]  0.072498758 -0.933832427 -1.221577771 -1.135054791  2.048257952
 [11] -0.822950632  0.331771338  1.019512595 -0.477627035 -2.055076374
 [16]  0.835090978 -1.684841322  1.819842162 -0.495288662 -2.065742577
 [21] -0.316536369  1.001498224  0.619854179 -0.889461242  2.404903829
 [26]  1.681950801  1.361280466  1.121318524 -0.810917426 -1.050275287
 [31]  0.102560455  1.442550064 -0.531475101 -0.464880244 -0.056595493
 [36]  0.532954467 -0.230321650 -0.700764200 -0.846821010  0.154653480
 [41] -0.016825474 -0.226877435 -1.387860715  2.090237087  0.217134249
 [46] -0.046804045 -0.058754504  1.070065233  1.488787095 -0.607694807
 [51] -0.888241341 -1.822942411  1.626721643  0.458669796 -0.243951571
 [56]  0.505696206  0.109210684 -1.013793530 -0.608896140 -1.113980819
 [61] -1.174237843  0.066377258 -0.928597195  0.292738902  0.926226135
 [66] -0.184547730 -0.934440981 -0.604814358 -1.583552648  0.084731957
 [71] -1.251578631 -0.367668246 -0.866963836 -0.420343634 -2.719074458
 [76]  0.441537597  0.031040666  1.523761974 -0.253744142 -0.503616681
 [81] -0.440992020  0.546139260 -0.684540250  0.661355228 -0.409168713
 [86] -0.417120386  1.438555755 -0.868273768 -0.326036887 -0.932878153
 [91]  0.412057601  0.392474603  0.538786875 -0.001315633  0.231644530
 [96] -1.814684999 -2.399415156 -0.108127101 -1.839330949  0.126331235
> 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] -1.165372139 -0.666796937 -0.298665870  1.298881321  0.557003855
  [6]  0.072498758 -0.933832427 -1.221577771 -1.135054791  2.048257952
 [11] -0.822950632  0.331771338  1.019512595 -0.477627035 -2.055076374
 [16]  0.835090978 -1.684841322  1.819842162 -0.495288662 -2.065742577
 [21] -0.316536369  1.001498224  0.619854179 -0.889461242  2.404903829
 [26]  1.681950801  1.361280466  1.121318524 -0.810917426 -1.050275287
 [31]  0.102560455  1.442550064 -0.531475101 -0.464880244 -0.056595493
 [36]  0.532954467 -0.230321650 -0.700764200 -0.846821010  0.154653480
 [41] -0.016825474 -0.226877435 -1.387860715  2.090237087  0.217134249
 [46] -0.046804045 -0.058754504  1.070065233  1.488787095 -0.607694807
 [51] -0.888241341 -1.822942411  1.626721643  0.458669796 -0.243951571
 [56]  0.505696206  0.109210684 -1.013793530 -0.608896140 -1.113980819
 [61] -1.174237843  0.066377258 -0.928597195  0.292738902  0.926226135
 [66] -0.184547730 -0.934440981 -0.604814358 -1.583552648  0.084731957
 [71] -1.251578631 -0.367668246 -0.866963836 -0.420343634 -2.719074458
 [76]  0.441537597  0.031040666  1.523761974 -0.253744142 -0.503616681
 [81] -0.440992020  0.546139260 -0.684540250  0.661355228 -0.409168713
 [86] -0.417120386  1.438555755 -0.868273768 -0.326036887 -0.932878153
 [91]  0.412057601  0.392474603  0.538786875 -0.001315633  0.231644530
 [96] -1.814684999 -2.399415156 -0.108127101 -1.839330949  0.126331235
> rowMin(tmp2)
  [1] -1.165372139 -0.666796937 -0.298665870  1.298881321  0.557003855
  [6]  0.072498758 -0.933832427 -1.221577771 -1.135054791  2.048257952
 [11] -0.822950632  0.331771338  1.019512595 -0.477627035 -2.055076374
 [16]  0.835090978 -1.684841322  1.819842162 -0.495288662 -2.065742577
 [21] -0.316536369  1.001498224  0.619854179 -0.889461242  2.404903829
 [26]  1.681950801  1.361280466  1.121318524 -0.810917426 -1.050275287
 [31]  0.102560455  1.442550064 -0.531475101 -0.464880244 -0.056595493
 [36]  0.532954467 -0.230321650 -0.700764200 -0.846821010  0.154653480
 [41] -0.016825474 -0.226877435 -1.387860715  2.090237087  0.217134249
 [46] -0.046804045 -0.058754504  1.070065233  1.488787095 -0.607694807
 [51] -0.888241341 -1.822942411  1.626721643  0.458669796 -0.243951571
 [56]  0.505696206  0.109210684 -1.013793530 -0.608896140 -1.113980819
 [61] -1.174237843  0.066377258 -0.928597195  0.292738902  0.926226135
 [66] -0.184547730 -0.934440981 -0.604814358 -1.583552648  0.084731957
 [71] -1.251578631 -0.367668246 -0.866963836 -0.420343634 -2.719074458
 [76]  0.441537597  0.031040666  1.523761974 -0.253744142 -0.503616681
 [81] -0.440992020  0.546139260 -0.684540250  0.661355228 -0.409168713
 [86] -0.417120386  1.438555755 -0.868273768 -0.326036887 -0.932878153
 [91]  0.412057601  0.392474603  0.538786875 -0.001315633  0.231644530
 [96] -1.814684999 -2.399415156 -0.108127101 -1.839330949  0.126331235
> 
> colMeans(tmp2)
[1] -0.153059
> colSums(tmp2)
[1] -15.3059
> colVars(tmp2)
[1] 1.066
> colSd(tmp2)
[1] 1.032473
> colMax(tmp2)
[1] 2.404904
> colMin(tmp2)
[1] -2.719074
> colMedians(tmp2)
[1] -0.2371366
> colRanges(tmp2)
          [,1]
[1,] -2.719074
[2,]  2.404904
> 
> dataset1 <- matrix(dataset1,1,100)
> 
> agree.checks(tmp,dataset1)
> 
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>   
> 
> tmp <- createBufferedMatrix(10,10)
> 
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
 [1] -0.03338753  7.31832259 -2.18655653  4.21767959 -1.80198566 -1.28297243
 [7] -4.21370073  0.86058904  8.04882990  2.09095038
> colApply(tmp,quantile)[,1]
             [,1]
[1,] -0.984372938
[2,] -0.507592916
[3,] -0.004239053
[4,]  0.609017174
[5,]  0.961833710
> 
> rowApply(tmp,sum)
 [1]  1.73783154  2.84868931 -3.27626473  2.96473357  0.01088918  3.88215691
 [7] -5.35192469  3.72523409  3.45992729  3.01649616
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]   10    5    4    2    4    7    5    7    5     2
 [2,]    9    9    8    8    8    9    8    5    9     6
 [3,]    7    7   10    4    5    2    9    4    4     1
 [4,]    8    2    9    3   10    8    7    8    8     5
 [5,]    4    8    2    1    3    4    3    1    7     8
 [6,]    3    6    6    7    2    3    2    9    2     4
 [7,]    1    1    7    5    1    5    1    3    3    10
 [8,]    6    3    3    6    9    6    4   10    6     3
 [9,]    5   10    5   10    7    1   10    2   10     9
[10,]    2    4    1    9    6   10    6    6    1     7
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  1.26659630  3.94125531  5.13688139 -0.74484454  3.15060450 -1.34386254
 [7]  1.62652401 -0.42202689 -2.63970817 -0.89898134  2.48076405  2.13829985
[13]  2.75144550  1.71363469  0.09501112 -1.37350181 -4.04667721 -0.90999171
[19] -1.22688005 -1.50445841
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -0.5436862
[2,] -0.1615766
[3,]  0.0527176
[4,]  0.9523703
[5,]  0.9667712
> 
> rowApply(tmp,sum)
[1]  4.800021  7.975035 -3.543256 -2.212537  2.170820
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]    7   16    6   15    9
[2,]   12   19   16   13   18
[3,]   14   20   18   20    4
[4,]   11   10   17    2    5
[5,]    2    9   20   14   19
> 
> 
> as.matrix(tmp)
           [,1]      [,2]       [,3]       [,4]       [,5]       [,6]
[1,] -0.1615766 0.3368908  0.5480821  0.3105163 -1.0592100 -1.2259415
[2,]  0.9523703 1.6278490  2.1920222  0.2553424  0.2299611 -0.4945709
[3,] -0.5436862 0.6630063  0.8585823  0.6750950  1.8214098 -0.3080876
[4,]  0.9667712 0.2350754  2.0658906 -1.6058465  0.7726338 -0.7729147
[5,]  0.0527176 1.0784337 -0.5276958 -0.3799518  1.3858098  1.4576521
           [,7]       [,8]       [,9]      [,10]       [,11]      [,12]
[1,]  0.5793884 -1.0063986  1.9310325 -0.5599517  0.09685195  1.0175290
[2,]  0.7352194  0.8581102 -1.6017941  1.0688983  1.17980822  0.4587116
[3,] -1.5708512  0.5718180 -2.2458769 -0.6688448 -0.11760707 -0.3003836
[4,]  1.3576619 -0.5572467 -0.9097088 -1.4448024  1.18192270  1.1753674
[5,]  0.5251056 -0.2883098  0.1866391  0.7057193  0.13978824 -0.2129245
          [,13]       [,14]      [,15]      [,16]      [,17]      [,18]
[1,]  1.8721621 -0.02415441  0.3866564  0.1097288 -0.5517791  1.4236339
[2,]  0.1963082  0.60250717 -0.3039970 -0.3588516 -0.3012891  0.1732644
[3,]  0.4618255  0.43313189 -0.4093068  1.4890586 -1.5933633 -2.3772982
[4,] -0.1747769 -0.01975669 -0.1452536 -2.4584899 -0.7247089  1.1027964
[5,]  0.3959266  0.72190674  0.5669121 -0.1549478 -0.8755368 -1.2323883
            [,19]      [,20]
[1,]  1.136231664 -0.3596706
[2,]  0.212343934  0.2928219
[3,] -0.007945325 -0.3739323
[4,] -0.894527163 -1.3626247
[5,] -1.672983161  0.2989474
> 
> 
> 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 :  648  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 :  561  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  480  bytes.
> 
> 
> rm(tmp)
> 
> 
> ###
> ### Testing colnames and rownames
> ###
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> 
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> tmp["row1",]
           col1     col2      col3     col4      col5      col6       col7
row1 -0.6618635 0.625387 -1.322472 0.215453 -1.725876 0.6684454 -0.4756606
          col8        col9      col10     col11    col12     col13   col14
row1 -1.507418 0.000353224 -0.5521397 0.7874646 1.233456 -1.290914 1.18992
          col15    col16     col17     col18    col19      col20
row1 -0.6956476 0.658197 0.9834035 0.1063154 2.307901 -0.4634639
> tmp[,"col10"]
           col10
row1 -0.55213974
row2 -0.34283650
row3  0.23515840
row4 -0.02337678
row5 -0.02836212
> tmp[c("row1","row5"),]
           col1      col2       col3      col4       col5       col6       col7
row1 -0.6618635 0.6253870 -1.3224717 0.2154530 -1.7258762  0.6684454 -0.4756606
row5  1.0138696 0.3210659  0.1127847 0.1623673  0.7542129 -1.4825075  1.1417598
          col8         col9       col10     col11      col12      col13
row1 -1.507418  0.000353224 -0.55213974 0.7874646  1.2334562 -1.2909142
row5  1.082516 -0.548075282 -0.02836212 0.8080317 -0.3951497  0.2575223
          col14      col15      col16      col17      col18     col19
row1  1.1899199 -0.6956476  0.6581970  0.9834035  0.1063154 2.3079010
row5 -0.5082577  1.4594561 -0.4622921 -1.2272188 -0.6979306 0.2373884
          col20
row1 -0.4634639
row5  1.0344604
> tmp[,c("col6","col20")]
           col6      col20
row1  0.6684454 -0.4634639
row2  0.5827822 -0.3689643
row3 -1.3350162 -0.0515202
row4  0.1202983  0.7414074
row5 -1.4825075  1.0344604
> tmp[c("row1","row5"),c("col6","col20")]
           col6      col20
row1  0.6684454 -0.4634639
row5 -1.4825075  1.0344604
> 
> 
> 
> 
> 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 47.39122 50.33443 48.85014 49.11537 50.05355 104.3079 50.41643 50.53215
         col9    col10    col11    col12   col13    col14    col15    col16
row1 49.81242 49.35236 49.35072 51.81567 50.7962 47.86172 49.01387 50.02229
        col17    col18   col19    col20
row1 49.36201 49.47012 48.5138 104.2288
> tmp[,"col10"]
        col10
row1 49.35236
row2 31.16340
row3 28.89860
row4 28.24756
row5 50.66785
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 47.39122 50.33443 48.85014 49.11537 50.05355 104.3079 50.41643 50.53215
row5 49.15300 50.15075 50.81044 50.93472 49.90478 105.4222 50.26255 49.43411
         col9    col10    col11    col12    col13    col14    col15    col16
row1 49.81242 49.35236 49.35072 51.81567 50.79620 47.86172 49.01387 50.02229
row5 50.60644 50.66785 50.32278 49.86469 49.25846 51.00973 52.59131 51.06750
        col17    col18    col19    col20
row1 49.36201 49.47012 48.51380 104.2288
row5 50.72614 51.64471 49.67487 103.9974
> tmp[,c("col6","col20")]
          col6     col20
row1 104.30791 104.22885
row2  75.19928  74.02859
row3  75.42038  75.09832
row4  75.89154  75.26950
row5 105.42217 103.99742
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 104.3079 104.2288
row5 105.4222 103.9974
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 104.3079 104.2288
row5 105.4222 103.9974
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,] -0.6660044
[2,] -0.1625575
[3,]  0.2269506
[4,] -0.3294806
[5,]  0.2995679
> tmp[,c("col17","col7")]
          col17       col7
[1,]  0.9936407 -0.8287116
[2,]  0.4324726 -0.3825174
[3,] -3.1104551  0.9507832
[4,] -1.7943930  1.1374484
[5,] -0.6616147 -0.5659934
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
           col6      col20
[1,]  0.6919330 -0.3874444
[2,] -1.5200480 -0.3988692
[3,] -0.1553765 -0.6042198
[4,] -1.3061131  0.1515694
[5,]  0.3896265  0.8651942
> subBufferedMatrix(tmp,1,c("col6"))[,1]
         col1
[1,] 0.691933
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
          col6
[1,]  0.691933
[2,] -1.520048
> 
> 
> 
> 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  1.155679 1.2613704 0.4623955 -0.5838037 -2.032531 -1.022221 -1.5495457
row1 -0.794993 0.6064364 0.1004492 -0.7681391  1.259424  1.951971  0.4470082
            [,8]       [,9]      [,10]      [,11]      [,12]      [,13]
row3 -2.08309555 -0.8285564  0.3076328 -1.1681404 -0.1017466 -0.1324009
row1  0.03429419 -1.1434779 -1.7688175 -0.8530641 -1.3464674 -1.6016308
          [,14]      [,15]      [,16]      [,17]      [,18]     [,19]     [,20]
row3 -1.1320374  1.0849849 0.00372355 -0.7625573  0.3301598  1.720883  2.256794
row1 -0.4468293 -0.2167161 1.19654587 -0.1103081 -0.9103781 -2.087128 -1.176153
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
          [,1]       [,2]    [,3]       [,4]       [,5]      [,6]      [,7]
row2 -1.107806 -0.2390286 -0.5578 -0.7294327 -0.4083651 0.9282283 -2.302358
           [,8]      [,9]    [,10]
row2 -0.1850339 0.3510502 1.128397
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
           [,1]      [,2]      [,3]      [,4]       [,5]       [,6]      [,7]
row5 -0.1812004 0.7564524 0.9956431 0.4296583 -0.5156892 -0.6742804 0.7611944
           [,8]       [,9]    [,10]      [,11]     [,12]       [,13]      [,14]
row5 -0.1424096 -0.3899406 0.488149 -0.7447689 0.3253446 -0.04874365 -0.4456472
        [,15]     [,16]    [,17]     [,18]     [,19]     [,20]
row5 1.014806 0.9295206 2.400194 0.4120841 0.2230856 0.3235435
> 
> 
> 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: 0x600002f98180>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8141631f848"
 [2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8142aa34a5a"
 [3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc81446667094"
 [4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8146f6928a7"
 [5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc81460ec2515"
 [6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8142f76b769"
 [7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8141b0366d7"
 [8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8147c54bb1b"
 [9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8141ec82962"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8146714f0b7"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc814fc7b340" 
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8147fc936d7"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc814732f9ecb"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8143b625c81"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMc81436a7379c"
> 
> 
> ### 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: 0x600002f88ae0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002f88ae0>
Warning message:
In dir.create(new.directory) :
  '/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x600002f88ae0>
> rowMedians(tmp)
  [1] -0.2432192940 -0.6510934101 -0.1431980043  0.1043657164 -0.0389562069
  [6]  0.3003645250  0.3498875796 -0.0287990882 -0.4310555846  0.0072890282
 [11] -0.0681523524 -0.2230624963  0.2113782596 -0.2830035874 -0.1258033270
 [16]  0.0551523608 -0.6912583912 -0.0793834398 -0.1378899148  0.2488811301
 [21] -0.1347665635 -0.3459399287  0.0331414555 -0.0678485500 -0.1155893588
 [26]  0.0025487238 -0.1310105415  0.6687819194 -0.1666139341  0.0348234185
 [31] -0.0254898314  0.0857401089  0.1322752227  1.0710638014  0.0893603334
 [36] -0.3338687274  0.0489264071  0.3691808212  0.7120778950 -0.1612062141
 [41]  0.0361840938  0.1451168655 -0.0729801563 -0.0370695033  0.4861396199
 [46]  0.4705821653  0.0543452025 -0.3155160568  0.4624805748 -0.2272279648
 [51] -0.5263436187 -0.0290577053 -0.4240207903  0.7371802107 -0.3792726400
 [56]  0.0127992217 -0.3289312132  0.4659880097  0.3448295879  0.0029557280
 [61]  0.3011499028  0.2594320569 -0.0649747003  0.1245807574  0.1627250986
 [66]  0.2647912638  0.6018627620  0.2095980011  0.2548671394 -0.2091033557
 [71] -0.0253916393  0.0680394562  0.0156037124  0.0278934190  0.3905284582
 [76] -0.1999112766  0.3297207858 -0.4607412105 -0.5398982793  0.0450685776
 [81]  0.3641147991  0.0815341792  0.1030015649 -0.0442939714 -0.2087591642
 [86]  0.3283361531  0.6601976050 -0.2618679782 -0.2072121792 -0.1675619642
 [91]  0.2745760769  0.1838401026 -0.0972451179  0.3222368354  0.0246580197
 [96] -0.0490467165  0.4794478681 -0.0194632823  0.5331649105  0.0008929163
[101]  0.1815013184 -0.6510633729  0.1165433618  0.0459009974  0.0466496627
[106]  0.0432808768 -0.4456989519 -0.4928746678 -0.1360368844  0.0117790968
[111]  0.5856669642 -0.0267923236  0.1487565524 -0.2405767287 -0.3626263277
[116]  0.3033286794 -0.1178566461 -0.3782289598 -0.2644646683  0.2468347280
[121]  0.0676125468  0.4537965596  0.0861924715  0.0030262193 -0.0264133613
[126] -0.1105625114  0.2892655220 -0.2112613271  0.7343657964  0.0252327717
[131]  0.6720981843  0.2262260151  0.1784448062 -0.0848490302 -0.3959891863
[136]  0.4265194644  0.0168863572 -0.1291579566 -0.0210113554 -0.0050026347
[141]  0.5021153326 -0.0048337119 -0.4533768778  0.3499866618  0.1710192577
[146]  0.3095839890 -0.1273662548  0.4281035117  0.2800316349  0.0544372477
[151] -0.0545809061 -0.1345765480 -0.2971623365  0.1951199439 -0.2326033777
[156] -0.6216081865  0.0519496990  0.4348966553 -0.1298254792 -0.4492456249
[161] -0.1683076642  0.3367463552 -0.4407871631 -0.1091468343 -0.5413978087
[166]  0.4494744494 -0.0568366728 -0.3017698692  0.6875057856 -0.4305553041
[171]  0.3996590358 -0.1951758890 -0.0011088088  0.1197314168 -0.1474956617
[176] -0.3846809308 -0.0348129310  0.2554858027  0.3822103327 -0.2961466786
[181] -0.2627443616  0.2345040911 -0.0094540009 -0.0777514218  0.0505870094
[186] -0.3210410240  0.7693880605  0.1249884416  0.1917819812  0.4057930162
[191]  0.3493679632  0.2987616070 -0.3096035229  0.7324941102  0.2880145555
[196] -0.3216262969  0.4182221986 -0.5658744821 -0.2564812909 -0.0389170915
[201] -0.5645915337 -0.1136831827 -0.3766535982  0.6572517508  0.3543020354
[206] -0.1634037720  0.0986018739 -0.3476067083  0.3019792043  0.3374525247
[211] -0.1602405411 -0.5536474797 -0.2940554319 -0.4345915456  0.1508159770
[216] -0.7214627666 -0.0405799777 -0.0042170592  0.0650431673  0.4617370766
[221] -0.1541887942 -0.3767178949  0.0475993299  0.2144058647 -0.5078348149
[226] -0.6207154560 -0.3370043674 -0.0812510423 -0.2609477468 -0.3706590679
> 
> proc.time()
   user  system elapsed 
  0.621   3.153   3.828 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: 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: 0x600001c14660>
> .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: 0x600001c14660>
> .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: 0x600001c14660>
> .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: 0x600001c14660>
> 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: 0x600001c08420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c08420>
> .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: 0x600001c08420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c08420>
> .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: 0x600001c08420>
> 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: 0x600001c08600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c08600>
> .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: 0x600001c08600>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001c08600>
> .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: 0x600001c08600>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x600001c08600>
> .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: 0x600001c08600>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x600001c08600>
> .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: 0x600001c08600>
> 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: 0x600001c087e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600001c087e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c087e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c087e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilecab44745a12c" "BufferedMatrixFilecab46ec6f22d"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilecab44745a12c" "BufferedMatrixFilecab46ec6f22d"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c08a80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c08a80>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001c08a80>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001c08a80>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600001c08a80>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600001c08a80>
> .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: 0x600001c08c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c08c60>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001c08c60>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600001c08c60>
> 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: 0x600001c08e40>
> .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: 0x600001c08e40>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.108   0.034   0.137 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: 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 
  0.105   0.020   0.122 

Example timings