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This page was generated on 2024-05-04 11:37:30 -0400 (Sat, 04 May 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_644.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" 4753
palomino3Windows Server 2022 Datacenterx644.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" 4486
lconwaymacOS 12.7.1 Montereyx86_644.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" 4519
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch644.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" 4479
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 249/2300HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.68.0  (landing page)
Ben Bolstad
Snapshot Date: 2024-05-03 14:00:19 -0400 (Fri, 03 May 2024)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: RELEASE_3_19
git_last_commit: af6c73d
git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024)
nebbiolo1Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  
kjohnson3macOS 13.6.5 Ventura / arm64see weekly results here

CHECK results for BufferedMatrix on palomino3


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: 1.68.0
Command: F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz
StartedAt: 2024-05-04 01:17:10 -0400 (Sat, 04 May 2024)
EndedAt: 2024-05-04 01:18:42 -0400 (Sat, 04 May 2024)
EllapsedTime: 91.8 seconds
RetCode: 0
Status:   OK  
CheckDir: BufferedMatrix.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck'
* using R version 4.4.0 beta (2024-04-15 r86425 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'BufferedMatrix/DESCRIPTION' ... OK
* this is package 'BufferedMatrix' version '1.68.0'
* 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 whether package 'BufferedMatrix' can be installed ... OK
* used C compiler: 'gcc.exe (GCC) 13.2.0'
* 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 for x64 is not available
File 'F:/biocbuild/bbs-3.19-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll':
  Found '_exit', possibly from '_exit' (C)
  Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran)

Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs nor [v]sprintf. The detected symbols are linked into
the code but might come from libraries and not actually be called.

See 'Writing portable packages' in the 'Writing R Extensions' manual.
* 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: 2 NOTEs
See
  'F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.


Installation output

BufferedMatrix.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library 'F:/biocbuild/bbs-3.19-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 13.2.0'
gcc  -I"F:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG     -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include"     -O2 -Wall  -mfpmath=sse -msse2 -mstackrealign  -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc  -I"F:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG     -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include"     -O2 -Wall  -mfpmath=sse -msse2 -mstackrealign  -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function 'dbm_ReadOnlyMode':
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of '!' or change '&' to '&&' or '!' to '~' [-Wparentheses]
 1580 |   if (!(Matrix->readonly) & setting){
      |       ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: 'sort_double' defined but not used [-Wunused-function]
 3327 | static int sort_double(const double *a1,const double *a2){
      |            ^~~~~~~~~~~
gcc  -I"F:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG     -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include"     -O2 -Wall  -mfpmath=sse -msse2 -mstackrealign  -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc  -I"F:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG     -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include"     -O2 -Wall  -mfpmath=sse -msse2 -mstackrealign  -c init_package.c -o init_package.o
gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib/x64 -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib -LF:/biocbuild/bbs-3.19-bioc/R/bin/x64 -lR
installing to F:/biocbuild/bbs-3.19-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs/x64
** 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
** 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 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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 
   0.26    0.20    0.78 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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] "F:/biocbuild/bbs-3.19-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) max used (Mb)
Ncells 468463 25.1    1021758 54.6   633414 33.9
Vcells 853869  6.6    8388608 64.0  2003140 15.3
> 
> 
> 
> 
> ##
> ## 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] "Sat May  4 01:17:43 2024"
> 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] "Sat May  4 01:17:44 2024"
> 
> 
> 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: 0x00000254122fd3b0>
> 
> 
> 
> 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] "Sat May  4 01:18:03 2024"
> 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] "Sat May  4 01:18:09 2024"
> 
> ColMode(tmp2)
<pointer: 0x00000254122fd3b0>
> 
> 
> 
> ### 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,] 99.3866428  0.3226289 -1.2534143 -0.1045686
[2,]  0.3370124  0.4539006 -0.9416086 -1.5922354
[3,] -0.9516990  0.8671715  0.5426823  1.7595980
[4,]  0.1407967 -0.5341710  0.4222778  1.3434267
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    F:/biocbuild/bbs-3.19-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,] 99.3866428 0.3226289 1.2534143 0.1045686
[2,]  0.3370124 0.4539006 0.9416086 1.5922354
[3,]  0.9516990 0.8671715 0.5426823 1.7595980
[4,]  0.1407967 0.5341710 0.4222778 1.3434267
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    F:/biocbuild/bbs-3.19-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,] 9.9692850 0.5680043 1.1195599 0.3233707
[2,] 0.5805277 0.6737215 0.9703652 1.2618381
[3,] 0.9755506 0.9312204 0.7366697 1.3264984
[4,] 0.3752288 0.7308701 0.6498291 1.1590628
> 
> 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:    F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 224.07949 31.00267 37.44901 28.33828
[2,]  31.14229 32.19112 35.64526 39.21062
[3,]  35.70720 35.17938 32.90938 40.02458
[4,]  28.89309 32.84287 31.92057 37.93406
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x00000254122fd410>
> exp(tmp5)
<pointer: 0x00000254122fd410>
> log(tmp5,2)
<pointer: 0x00000254122fd410>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.3921
> Min(tmp5)
[1] 55.52697
> mean(tmp5)
[1] 73.25444
> Sum(tmp5)
[1] 14650.89
> Var(tmp5)
[1] 844.8916
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 90.05197 71.64838 71.12709 72.81619 70.39543 67.36832 74.92158 72.89224
 [9] 72.58563 68.73759
> rowSums(tmp5)
 [1] 1801.039 1432.968 1422.542 1456.324 1407.909 1347.366 1498.432 1457.845
 [9] 1451.713 1374.752
> rowVars(tmp5)
 [1] 7884.79719   81.95713   47.74118   42.80405   72.02221   49.22337
 [7]   77.71969   62.14469   75.35485   80.59046
> rowSd(tmp5)
 [1] 88.796380  9.053018  6.909499  6.542480  8.486590  7.015937  8.815877
 [8]  7.883190  8.680717  8.977219
> rowMax(tmp5)
 [1] 466.39211  91.08330  86.57735  82.96506  86.32681  76.70871  93.10330
 [8]  84.44183  90.60514  88.67739
> rowMin(tmp5)
 [1] 58.46806 57.05171 56.60355 60.13717 56.63032 56.06599 57.25348 55.52697
 [9] 58.92230 55.62707
> 
> colMeans(tmp5)
 [1] 108.31313  68.71934  71.99941  74.19102  68.00338  74.66821  74.62979
 [8]  69.67490  66.92019  67.09632  71.22851  75.76554  70.24958  68.95391
[15]  72.14171  71.63646  77.49843  72.18016  70.40079  70.81807
> colSums(tmp5)
 [1] 1083.1313  687.1934  719.9941  741.9102  680.0338  746.6821  746.2979
 [8]  696.7490  669.2019  670.9632  712.2851  757.6554  702.4958  689.5391
[15]  721.4171  716.3646  774.9843  721.8016  704.0079  708.1807
> colVars(tmp5)
 [1] 15849.76397    48.51083    51.52218    94.33478    79.03498    42.65606
 [7]    58.68365    56.42276    37.89645    70.45041    53.50704    73.04333
[13]    45.80433    86.72288   122.11471    72.84007    73.61613    37.96726
[19]    29.06748    86.99080
> colSd(tmp5)
 [1] 125.895846   6.964972   7.177895   9.712609   8.890162   6.531161
 [7]   7.660525   7.511508   6.156009   8.393474   7.314851   8.546539
[13]   6.767889   9.312512  11.050552   8.534639   8.579984   6.161758
[19]   5.391427   9.326886
> colMax(tmp5)
 [1] 466.39211  80.78002  80.10820  84.48874  82.96506  84.67482  88.67739
 [8]  84.44940  75.12139  84.44183  81.50707  93.10330  81.73751  82.37163
[15]  84.42086  90.60514  91.08330  81.22908  80.19298  87.06284
> colMin(tmp5)
 [1] 60.13717 56.61543 56.82377 56.06599 58.07081 64.95725 60.81923 58.00636
 [9] 55.52697 56.60355 56.63032 65.27016 57.05171 55.62707 56.46081 61.72994
[17] 65.98419 62.37823 63.92270 56.17934
> 
> 
> ### 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] 90.05197 71.64838 71.12709 72.81619 70.39543 67.36832 74.92158 72.89224
 [9] 72.58563       NA
> rowSums(tmp5)
 [1] 1801.039 1432.968 1422.542 1456.324 1407.909 1347.366 1498.432 1457.845
 [9] 1451.713       NA
> rowVars(tmp5)
 [1] 7884.79719   81.95713   47.74118   42.80405   72.02221   49.22337
 [7]   77.71969   62.14469   75.35485   73.12038
> rowSd(tmp5)
 [1] 88.796380  9.053018  6.909499  6.542480  8.486590  7.015937  8.815877
 [8]  7.883190  8.680717  8.551046
> rowMax(tmp5)
 [1] 466.39211  91.08330  86.57735  82.96506  86.32681  76.70871  93.10330
 [8]  84.44183  90.60514        NA
> rowMin(tmp5)
 [1] 58.46806 57.05171 56.60355 60.13717 56.63032 56.06599 57.25348 55.52697
 [9] 58.92230       NA
> 
> colMeans(tmp5)
 [1] 108.31313  68.71934  71.99941  74.19102  68.00338  74.66821  74.62979
 [8]  69.67490  66.92019  67.09632  71.22851  75.76554  70.24958  68.95391
[15]  72.14171  71.63646        NA  72.18016  70.40079  70.81807
> colSums(tmp5)
 [1] 1083.1313  687.1934  719.9941  741.9102  680.0338  746.6821  746.2979
 [8]  696.7490  669.2019  670.9632  712.2851  757.6554  702.4958  689.5391
[15]  721.4171  716.3646        NA  721.8016  704.0079  708.1807
> colVars(tmp5)
 [1] 15849.76397    48.51083    51.52218    94.33478    79.03498    42.65606
 [7]    58.68365    56.42276    37.89645    70.45041    53.50704    73.04333
[13]    45.80433    86.72288   122.11471    72.84007          NA    37.96726
[19]    29.06748    86.99080
> colSd(tmp5)
 [1] 125.895846   6.964972   7.177895   9.712609   8.890162   6.531161
 [7]   7.660525   7.511508   6.156009   8.393474   7.314851   8.546539
[13]   6.767889   9.312512  11.050552   8.534639         NA   6.161758
[19]   5.391427   9.326886
> colMax(tmp5)
 [1] 466.39211  80.78002  80.10820  84.48874  82.96506  84.67482  88.67739
 [8]  84.44940  75.12139  84.44183  81.50707  93.10330  81.73751  82.37163
[15]  84.42086  90.60514        NA  81.22908  80.19298  87.06284
> colMin(tmp5)
 [1] 60.13717 56.61543 56.82377 56.06599 58.07081 64.95725 60.81923 58.00636
 [9] 55.52697 56.60355 56.63032 65.27016 57.05171 55.62707 56.46081 61.72994
[17]       NA 62.37823 63.92270 56.17934
> 
> Max(tmp5,na.rm=TRUE)
[1] 466.3921
> Min(tmp5,na.rm=TRUE)
[1] 55.52697
> mean(tmp5,na.rm=TRUE)
[1] 73.20531
> Sum(tmp5,na.rm=TRUE)
[1] 14567.86
> Var(tmp5,na.rm=TRUE)
[1] 848.6736
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 90.05197 71.64838 71.12709 72.81619 70.39543 67.36832 74.92158 72.89224
 [9] 72.58563 67.98531
> rowSums(tmp5,na.rm=TRUE)
 [1] 1801.039 1432.968 1422.542 1456.324 1407.909 1347.366 1498.432 1457.845
 [9] 1451.713 1291.721
> rowVars(tmp5,na.rm=TRUE)
 [1] 7884.79719   81.95713   47.74118   42.80405   72.02221   49.22337
 [7]   77.71969   62.14469   75.35485   73.12038
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.796380  9.053018  6.909499  6.542480  8.486590  7.015937  8.815877
 [8]  7.883190  8.680717  8.551046
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.39211  91.08330  86.57735  82.96506  86.32681  76.70871  93.10330
 [8]  84.44183  90.60514  88.67739
> rowMin(tmp5,na.rm=TRUE)
 [1] 58.46806 57.05171 56.60355 60.13717 56.63032 56.06599 57.25348 55.52697
 [9] 58.92230 55.62707
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 108.31313  68.71934  71.99941  74.19102  68.00338  74.66821  74.62979
 [8]  69.67490  66.92019  67.09632  71.22851  75.76554  70.24958  68.95391
[15]  72.14171  71.63646  76.88371  72.18016  70.40079  70.81807
> colSums(tmp5,na.rm=TRUE)
 [1] 1083.1313  687.1934  719.9941  741.9102  680.0338  746.6821  746.2979
 [8]  696.7490  669.2019  670.9632  712.2851  757.6554  702.4958  689.5391
[15]  721.4171  716.3646  691.9534  721.8016  704.0079  708.1807
> colVars(tmp5,na.rm=TRUE)
 [1] 15849.76397    48.51083    51.52218    94.33478    79.03498    42.65606
 [7]    58.68365    56.42276    37.89645    70.45041    53.50704    73.04333
[13]    45.80433    86.72288   122.11471    72.84007    78.56697    37.96726
[19]    29.06748    86.99080
> colSd(tmp5,na.rm=TRUE)
 [1] 125.895846   6.964972   7.177895   9.712609   8.890162   6.531161
 [7]   7.660525   7.511508   6.156009   8.393474   7.314851   8.546539
[13]   6.767889   9.312512  11.050552   8.534639   8.863801   6.161758
[19]   5.391427   9.326886
> colMax(tmp5,na.rm=TRUE)
 [1] 466.39211  80.78002  80.10820  84.48874  82.96506  84.67482  88.67739
 [8]  84.44940  75.12139  84.44183  81.50707  93.10330  81.73751  82.37163
[15]  84.42086  90.60514  91.08330  81.22908  80.19298  87.06284
> colMin(tmp5,na.rm=TRUE)
 [1] 60.13717 56.61543 56.82377 56.06599 58.07081 64.95725 60.81923 58.00636
 [9] 55.52697 56.60355 56.63032 65.27016 57.05171 55.62707 56.46081 61.72994
[17] 65.98419 62.37823 63.92270 56.17934
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 90.05197 71.64838 71.12709 72.81619 70.39543 67.36832 74.92158 72.89224
 [9] 72.58563      NaN
> rowSums(tmp5,na.rm=TRUE)
 [1] 1801.039 1432.968 1422.542 1456.324 1407.909 1347.366 1498.432 1457.845
 [9] 1451.713    0.000
> rowVars(tmp5,na.rm=TRUE)
 [1] 7884.79719   81.95713   47.74118   42.80405   72.02221   49.22337
 [7]   77.71969   62.14469   75.35485         NA
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.796380  9.053018  6.909499  6.542480  8.486590  7.015937  8.815877
 [8]  7.883190  8.680717        NA
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.39211  91.08330  86.57735  82.96506  86.32681  76.70871  93.10330
 [8]  84.44183  90.60514        NA
> rowMin(tmp5,na.rm=TRUE)
 [1] 58.46806 57.05171 56.60355 60.13717 56.63032 56.06599 57.25348 55.52697
 [9] 58.92230       NA
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 112.78040  70.06421  72.29225  74.17018  68.99311  75.08264  73.06894
 [8]  69.94417  67.07960  67.73870  70.08645  75.99798  70.96157  70.43467
[15]  71.84999  72.08107       NaN  72.75877  70.41328  72.44460
> colSums(tmp5,na.rm=TRUE)
 [1] 1015.0236  630.5779  650.6303  667.5316  620.9380  675.7437  657.6205
 [8]  629.4975  603.7164  609.6483  630.7781  683.9818  638.6541  633.9121
[15]  646.6499  648.7297    0.0000  654.8289  633.7195  652.0014
> colVars(tmp5,na.rm=TRUE)
 [1] 17606.47381    34.22682    56.99765   106.12174    77.89420    46.05591
 [7]    38.61143    62.65989    42.34762    74.61445    45.52199    81.56592
[13]    45.82703    72.89590   136.42171    79.72112          NA    38.94684
[19]    32.69917    68.10180
> colSd(tmp5,na.rm=TRUE)
 [1] 132.689388   5.850369   7.549679  10.301541   8.825769   6.786450
 [7]   6.213810   7.915800   6.507505   8.637965   6.746999   9.031385
[13]   6.769567   8.537910  11.679970   8.928669         NA   6.240740
[19]   5.718319   8.252381
> colMax(tmp5,na.rm=TRUE)
 [1] 466.39211  80.78002  80.10820  84.48874  82.96506  84.67482  84.01031
 [8]  84.44940  75.12139  84.44183  79.77099  93.10330  81.73751  82.37163
[15]  84.42086  90.60514      -Inf  81.22908  80.19298  87.06284
> colMin(tmp5,na.rm=TRUE)
 [1] 60.13717 63.82605 56.82377 56.06599 58.07081 64.95725 60.81923 58.00636
 [9] 55.52697 56.60355 56.63032 65.27016 57.05171 57.25348 56.46081 61.72994
[17]      Inf 62.37823 63.92270 59.31062
> 
> 
> 
> 
> 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] 248.6857 254.0194 223.6248 239.6683 184.3317 230.2690 456.2258 185.8747
 [9] 159.4195 214.5584
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 248.6857 254.0194 223.6248 239.6683 184.3317 230.2690 456.2258 185.8747
 [9] 159.4195 214.5584
> 
> 
> 
> 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  0.000000e+00 -8.526513e-14 -1.136868e-13  2.842171e-14
 [6]  2.842171e-14 -5.684342e-14 -2.842171e-14 -1.136868e-13  0.000000e+00
[11] -4.263256e-14  2.842171e-14 -1.989520e-13 -2.842171e-13 -8.526513e-14
[16] -5.684342e-14  0.000000e+00  1.136868e-13 -4.263256e-14 -5.684342e-14
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## making sure these things agree
> ##
> ## first when there is no NA
> 
> 
> 
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+ 
+   if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Max")
+   }
+   
+ 
+   if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Min")
+   }
+ 
+ 
+   if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+ 
+     cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+     cat(sum(r.matrix,na.rm=TRUE),"\n")
+     cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+     
+     stop("No agreement in Sum")
+   }
+   
+   if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+     stop("No agreement in mean")
+   }
+   
+   
+   if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+     stop("No agreement in Var")
+   }
+   
+   
+ 
+   if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowMeans")
+   }
+   
+   
+   if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colMeans")
+   }
+   
+   
+   if(any(abs(rowSums(buff.matrix,na.rm=TRUE)  -  apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in rowSums")
+   }
+   
+   
+   if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colSums")
+   }
+   
+   ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when 
+   ### computing variance
+   my.Var <- function(x,na.rm=FALSE){
+    if (all(is.na(x))){
+      return(NA)
+    } else {
+      var(x,na.rm=na.rm)
+    }
+ 
+   }
+   
+   if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+   
+   
+   if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+ 
+ 
+   if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+ 
+   if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+   
+   
+   if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+   
+ 
+   if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+ 
+   if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMedian")
+   }
+ 
+   if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colRanges")
+   }
+ 
+ 
+   
+ }
> 
> 
> 
> 
> 
> 
> 
> 
> 
> for (rep in 1:20){
+   copymatrix <- matrix(rnorm(200,150,15),10,20)
+   
+   tmp5[1:10,1:20] <- copymatrix
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ## now lets assign some NA values and check agreement
+ 
+   which.row <- sample(1:10,1,replace=TRUE)
+   which.col  <- sample(1:20,1,replace=TRUE)
+   
+   cat(which.row," ",which.col,"\n")
+   
+   tmp5[which.row,which.col] <- NA
+   copymatrix[which.row,which.col] <- NA
+   
+   agree.checks(tmp5,copymatrix)
+ 
+   ## make an entire row NA
+   tmp5[which.row,] <- NA
+   copymatrix[which.row,] <- NA
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ### also make an entire col NA
+   tmp5[,which.col] <- NA
+   copymatrix[,which.col] <- NA
+ 
+   agree.checks(tmp5,copymatrix)
+ 
+   ### now make 1 element non NA with NA in the rest of row and column
+ 
+   tmp5[which.row,which.col] <- rnorm(1,150,15)
+   copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+ 
+   agree.checks(tmp5,copymatrix)
+ }
1   10 
2   20 
7   19 
3   15 
10   19 
7   7 
1   19 
3   18 
2   20 
8   4 
2   13 
4   20 
3   9 
7   7 
3   4 
10   3 
2   17 
1   16 
6   4 
3   5 
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] 2.069931
> Min(tmp)
[1] -2.215155
> mean(tmp)
[1] -0.00246735
> Sum(tmp)
[1] -0.246735
> Var(tmp)
[1] 0.9141906
> 
> rowMeans(tmp)
[1] -0.00246735
> rowSums(tmp)
[1] -0.246735
> rowVars(tmp)
[1] 0.9141906
> rowSd(tmp)
[1] 0.9561331
> rowMax(tmp)
[1] 2.069931
> rowMin(tmp)
[1] -2.215155
> 
> colMeans(tmp)
  [1]  0.719625641  1.213930729 -1.071193301  1.204916569 -0.261050436
  [6] -0.397643724 -1.189913273 -0.399449937 -0.148934840 -0.385016507
 [11] -0.176923055 -1.135181885 -2.215154761  0.852684146 -1.663375505
 [16]  1.528836800  1.034011625  1.524482890 -0.392973609 -0.047548303
 [21] -0.347860814  0.510709512 -0.002397400 -0.658621344  0.286728620
 [26] -0.196676277 -0.641801524  1.596034923 -0.369020997  0.107955863
 [31] -0.104173228  0.101696810 -0.283743019 -1.021236034  0.003786366
 [36]  0.333554537 -0.607569724  1.031695665  0.092158145  2.069930772
 [41] -0.045576462 -1.783563022 -0.645770242  1.548194488 -0.535522520
 [46]  1.252187871 -0.532944697 -1.982116085 -0.402671882  0.079940769
 [51]  1.335891310 -0.542844258  0.099300476  0.529725057  0.184697290
 [56] -0.502921126  0.994150958 -0.635487440 -1.081809037 -1.150536857
 [61] -2.050771470  0.866907980  0.480666461 -0.538866061 -0.489146597
 [66] -1.575565333  0.209122957  1.933157286  0.167803195  0.661841194
 [71]  1.382059122  0.683316829  0.828869743 -1.289821609  1.885800872
 [76] -1.634543136  0.630529489  1.013357982 -0.478828239 -0.272760071
 [81] -0.242493356  0.355575422 -0.521891173  1.632359852  0.541252092
 [86]  1.203300055  0.337898545 -0.638075333 -0.186016176 -0.763989819
 [91] -0.506404816 -0.212720108 -0.343572209 -0.766362857  1.251239696
 [96] -0.315148337 -1.235280545 -0.159066226 -0.483225039  1.715149997
> colSums(tmp)
  [1]  0.719625641  1.213930729 -1.071193301  1.204916569 -0.261050436
  [6] -0.397643724 -1.189913273 -0.399449937 -0.148934840 -0.385016507
 [11] -0.176923055 -1.135181885 -2.215154761  0.852684146 -1.663375505
 [16]  1.528836800  1.034011625  1.524482890 -0.392973609 -0.047548303
 [21] -0.347860814  0.510709512 -0.002397400 -0.658621344  0.286728620
 [26] -0.196676277 -0.641801524  1.596034923 -0.369020997  0.107955863
 [31] -0.104173228  0.101696810 -0.283743019 -1.021236034  0.003786366
 [36]  0.333554537 -0.607569724  1.031695665  0.092158145  2.069930772
 [41] -0.045576462 -1.783563022 -0.645770242  1.548194488 -0.535522520
 [46]  1.252187871 -0.532944697 -1.982116085 -0.402671882  0.079940769
 [51]  1.335891310 -0.542844258  0.099300476  0.529725057  0.184697290
 [56] -0.502921126  0.994150958 -0.635487440 -1.081809037 -1.150536857
 [61] -2.050771470  0.866907980  0.480666461 -0.538866061 -0.489146597
 [66] -1.575565333  0.209122957  1.933157286  0.167803195  0.661841194
 [71]  1.382059122  0.683316829  0.828869743 -1.289821609  1.885800872
 [76] -1.634543136  0.630529489  1.013357982 -0.478828239 -0.272760071
 [81] -0.242493356  0.355575422 -0.521891173  1.632359852  0.541252092
 [86]  1.203300055  0.337898545 -0.638075333 -0.186016176 -0.763989819
 [91] -0.506404816 -0.212720108 -0.343572209 -0.766362857  1.251239696
 [96] -0.315148337 -1.235280545 -0.159066226 -0.483225039  1.715149997
> 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]  0.719625641  1.213930729 -1.071193301  1.204916569 -0.261050436
  [6] -0.397643724 -1.189913273 -0.399449937 -0.148934840 -0.385016507
 [11] -0.176923055 -1.135181885 -2.215154761  0.852684146 -1.663375505
 [16]  1.528836800  1.034011625  1.524482890 -0.392973609 -0.047548303
 [21] -0.347860814  0.510709512 -0.002397400 -0.658621344  0.286728620
 [26] -0.196676277 -0.641801524  1.596034923 -0.369020997  0.107955863
 [31] -0.104173228  0.101696810 -0.283743019 -1.021236034  0.003786366
 [36]  0.333554537 -0.607569724  1.031695665  0.092158145  2.069930772
 [41] -0.045576462 -1.783563022 -0.645770242  1.548194488 -0.535522520
 [46]  1.252187871 -0.532944697 -1.982116085 -0.402671882  0.079940769
 [51]  1.335891310 -0.542844258  0.099300476  0.529725057  0.184697290
 [56] -0.502921126  0.994150958 -0.635487440 -1.081809037 -1.150536857
 [61] -2.050771470  0.866907980  0.480666461 -0.538866061 -0.489146597
 [66] -1.575565333  0.209122957  1.933157286  0.167803195  0.661841194
 [71]  1.382059122  0.683316829  0.828869743 -1.289821609  1.885800872
 [76] -1.634543136  0.630529489  1.013357982 -0.478828239 -0.272760071
 [81] -0.242493356  0.355575422 -0.521891173  1.632359852  0.541252092
 [86]  1.203300055  0.337898545 -0.638075333 -0.186016176 -0.763989819
 [91] -0.506404816 -0.212720108 -0.343572209 -0.766362857  1.251239696
 [96] -0.315148337 -1.235280545 -0.159066226 -0.483225039  1.715149997
> colMin(tmp)
  [1]  0.719625641  1.213930729 -1.071193301  1.204916569 -0.261050436
  [6] -0.397643724 -1.189913273 -0.399449937 -0.148934840 -0.385016507
 [11] -0.176923055 -1.135181885 -2.215154761  0.852684146 -1.663375505
 [16]  1.528836800  1.034011625  1.524482890 -0.392973609 -0.047548303
 [21] -0.347860814  0.510709512 -0.002397400 -0.658621344  0.286728620
 [26] -0.196676277 -0.641801524  1.596034923 -0.369020997  0.107955863
 [31] -0.104173228  0.101696810 -0.283743019 -1.021236034  0.003786366
 [36]  0.333554537 -0.607569724  1.031695665  0.092158145  2.069930772
 [41] -0.045576462 -1.783563022 -0.645770242  1.548194488 -0.535522520
 [46]  1.252187871 -0.532944697 -1.982116085 -0.402671882  0.079940769
 [51]  1.335891310 -0.542844258  0.099300476  0.529725057  0.184697290
 [56] -0.502921126  0.994150958 -0.635487440 -1.081809037 -1.150536857
 [61] -2.050771470  0.866907980  0.480666461 -0.538866061 -0.489146597
 [66] -1.575565333  0.209122957  1.933157286  0.167803195  0.661841194
 [71]  1.382059122  0.683316829  0.828869743 -1.289821609  1.885800872
 [76] -1.634543136  0.630529489  1.013357982 -0.478828239 -0.272760071
 [81] -0.242493356  0.355575422 -0.521891173  1.632359852  0.541252092
 [86]  1.203300055  0.337898545 -0.638075333 -0.186016176 -0.763989819
 [91] -0.506404816 -0.212720108 -0.343572209 -0.766362857  1.251239696
 [96] -0.315148337 -1.235280545 -0.159066226 -0.483225039  1.715149997
> colMedians(tmp)
  [1]  0.719625641  1.213930729 -1.071193301  1.204916569 -0.261050436
  [6] -0.397643724 -1.189913273 -0.399449937 -0.148934840 -0.385016507
 [11] -0.176923055 -1.135181885 -2.215154761  0.852684146 -1.663375505
 [16]  1.528836800  1.034011625  1.524482890 -0.392973609 -0.047548303
 [21] -0.347860814  0.510709512 -0.002397400 -0.658621344  0.286728620
 [26] -0.196676277 -0.641801524  1.596034923 -0.369020997  0.107955863
 [31] -0.104173228  0.101696810 -0.283743019 -1.021236034  0.003786366
 [36]  0.333554537 -0.607569724  1.031695665  0.092158145  2.069930772
 [41] -0.045576462 -1.783563022 -0.645770242  1.548194488 -0.535522520
 [46]  1.252187871 -0.532944697 -1.982116085 -0.402671882  0.079940769
 [51]  1.335891310 -0.542844258  0.099300476  0.529725057  0.184697290
 [56] -0.502921126  0.994150958 -0.635487440 -1.081809037 -1.150536857
 [61] -2.050771470  0.866907980  0.480666461 -0.538866061 -0.489146597
 [66] -1.575565333  0.209122957  1.933157286  0.167803195  0.661841194
 [71]  1.382059122  0.683316829  0.828869743 -1.289821609  1.885800872
 [76] -1.634543136  0.630529489  1.013357982 -0.478828239 -0.272760071
 [81] -0.242493356  0.355575422 -0.521891173  1.632359852  0.541252092
 [86]  1.203300055  0.337898545 -0.638075333 -0.186016176 -0.763989819
 [91] -0.506404816 -0.212720108 -0.343572209 -0.766362857  1.251239696
 [96] -0.315148337 -1.235280545 -0.159066226 -0.483225039  1.715149997
> colRanges(tmp)
          [,1]     [,2]      [,3]     [,4]       [,5]       [,6]      [,7]
[1,] 0.7196256 1.213931 -1.071193 1.204917 -0.2610504 -0.3976437 -1.189913
[2,] 0.7196256 1.213931 -1.071193 1.204917 -0.2610504 -0.3976437 -1.189913
           [,8]       [,9]      [,10]      [,11]     [,12]     [,13]     [,14]
[1,] -0.3994499 -0.1489348 -0.3850165 -0.1769231 -1.135182 -2.215155 0.8526841
[2,] -0.3994499 -0.1489348 -0.3850165 -0.1769231 -1.135182 -2.215155 0.8526841
         [,15]    [,16]    [,17]    [,18]      [,19]      [,20]      [,21]
[1,] -1.663376 1.528837 1.034012 1.524483 -0.3929736 -0.0475483 -0.3478608
[2,] -1.663376 1.528837 1.034012 1.524483 -0.3929736 -0.0475483 -0.3478608
         [,22]      [,23]      [,24]     [,25]      [,26]      [,27]    [,28]
[1,] 0.5107095 -0.0023974 -0.6586213 0.2867286 -0.1966763 -0.6418015 1.596035
[2,] 0.5107095 -0.0023974 -0.6586213 0.2867286 -0.1966763 -0.6418015 1.596035
         [,29]     [,30]      [,31]     [,32]     [,33]     [,34]       [,35]
[1,] -0.369021 0.1079559 -0.1041732 0.1016968 -0.283743 -1.021236 0.003786366
[2,] -0.369021 0.1079559 -0.1041732 0.1016968 -0.283743 -1.021236 0.003786366
         [,36]      [,37]    [,38]      [,39]    [,40]       [,41]     [,42]
[1,] 0.3335545 -0.6075697 1.031696 0.09215814 2.069931 -0.04557646 -1.783563
[2,] 0.3335545 -0.6075697 1.031696 0.09215814 2.069931 -0.04557646 -1.783563
          [,43]    [,44]      [,45]    [,46]      [,47]     [,48]      [,49]
[1,] -0.6457702 1.548194 -0.5355225 1.252188 -0.5329447 -1.982116 -0.4026719
[2,] -0.6457702 1.548194 -0.5355225 1.252188 -0.5329447 -1.982116 -0.4026719
          [,50]    [,51]      [,52]      [,53]     [,54]     [,55]      [,56]
[1,] 0.07994077 1.335891 -0.5428443 0.09930048 0.5297251 0.1846973 -0.5029211
[2,] 0.07994077 1.335891 -0.5428443 0.09930048 0.5297251 0.1846973 -0.5029211
        [,57]      [,58]     [,59]     [,60]     [,61]    [,62]     [,63]
[1,] 0.994151 -0.6354874 -1.081809 -1.150537 -2.050771 0.866908 0.4806665
[2,] 0.994151 -0.6354874 -1.081809 -1.150537 -2.050771 0.866908 0.4806665
          [,64]      [,65]     [,66]    [,67]    [,68]     [,69]     [,70]
[1,] -0.5388661 -0.4891466 -1.575565 0.209123 1.933157 0.1678032 0.6618412
[2,] -0.5388661 -0.4891466 -1.575565 0.209123 1.933157 0.1678032 0.6618412
        [,71]     [,72]     [,73]     [,74]    [,75]     [,76]     [,77]
[1,] 1.382059 0.6833168 0.8288697 -1.289822 1.885801 -1.634543 0.6305295
[2,] 1.382059 0.6833168 0.8288697 -1.289822 1.885801 -1.634543 0.6305295
        [,78]      [,79]      [,80]      [,81]     [,82]      [,83]   [,84]
[1,] 1.013358 -0.4788282 -0.2727601 -0.2424934 0.3555754 -0.5218912 1.63236
[2,] 1.013358 -0.4788282 -0.2727601 -0.2424934 0.3555754 -0.5218912 1.63236
         [,85]  [,86]     [,87]      [,88]      [,89]      [,90]      [,91]
[1,] 0.5412521 1.2033 0.3378985 -0.6380753 -0.1860162 -0.7639898 -0.5064048
[2,] 0.5412521 1.2033 0.3378985 -0.6380753 -0.1860162 -0.7639898 -0.5064048
          [,92]      [,93]      [,94]   [,95]      [,96]     [,97]      [,98]
[1,] -0.2127201 -0.3435722 -0.7663629 1.25124 -0.3151483 -1.235281 -0.1590662
[2,] -0.2127201 -0.3435722 -0.7663629 1.25124 -0.3151483 -1.235281 -0.1590662
         [,99]  [,100]
[1,] -0.483225 1.71515
[2,] -0.483225 1.71515
> 
> 
> Max(tmp2)
[1] 3.035681
> Min(tmp2)
[1] -2.800095
> mean(tmp2)
[1] 0.07245322
> Sum(tmp2)
[1] 7.245322
> Var(tmp2)
[1] 1.285921
> 
> rowMeans(tmp2)
  [1]  0.68564344 -0.36085909  1.51166423  0.78329164 -0.60165194  0.92115733
  [7] -1.37553483  2.35345797  0.26829367 -0.64381240  0.26916210 -2.06133359
 [13] -0.57541817 -1.36326635  0.50058227 -1.46729136  1.18408117  1.88309201
 [19] -0.75108619 -0.90917261  0.16018775 -0.22666467 -1.12728722 -0.78057583
 [25]  0.83014365 -0.23513149 -0.93694634  1.25548878 -0.04719795  1.12436291
 [31]  0.68826510  1.40959510  0.52990780  3.03568131 -1.22303306 -2.80009539
 [37]  0.08868323  1.52735358 -0.43163654  0.09826795  0.24777817 -0.39856093
 [43]  1.53492493 -1.09444324 -0.92724569 -0.54919897 -0.47995375  2.23272057
 [49]  0.08428868 -0.81806073  1.37596515 -0.93502959  0.29602304  0.72219741
 [55]  0.46159160  1.53687380 -0.84252807  0.69960372 -2.16965557 -0.87742915
 [61] -1.28097855  0.20953558  0.46955235 -2.55620633  0.13753914  0.31199043
 [67] -0.38150944 -1.08184100  0.83555219 -0.35173692 -0.71553713  0.11593661
 [73]  1.82119183  0.73875847 -0.68570378  0.02697403 -1.52524303  1.89667380
 [79] -0.85540912  0.83941440  1.41295778  0.58613243 -0.28690883  0.60948984
 [85] -0.01796637 -0.54970050  0.15899146 -1.09273878  1.39912060  0.78643604
 [91]  1.45310548  0.58336490  0.96881069 -1.05614286 -1.14856701  1.12646173
 [97] -1.45154752  0.60620181 -0.64258761  2.54122537
> rowSums(tmp2)
  [1]  0.68564344 -0.36085909  1.51166423  0.78329164 -0.60165194  0.92115733
  [7] -1.37553483  2.35345797  0.26829367 -0.64381240  0.26916210 -2.06133359
 [13] -0.57541817 -1.36326635  0.50058227 -1.46729136  1.18408117  1.88309201
 [19] -0.75108619 -0.90917261  0.16018775 -0.22666467 -1.12728722 -0.78057583
 [25]  0.83014365 -0.23513149 -0.93694634  1.25548878 -0.04719795  1.12436291
 [31]  0.68826510  1.40959510  0.52990780  3.03568131 -1.22303306 -2.80009539
 [37]  0.08868323  1.52735358 -0.43163654  0.09826795  0.24777817 -0.39856093
 [43]  1.53492493 -1.09444324 -0.92724569 -0.54919897 -0.47995375  2.23272057
 [49]  0.08428868 -0.81806073  1.37596515 -0.93502959  0.29602304  0.72219741
 [55]  0.46159160  1.53687380 -0.84252807  0.69960372 -2.16965557 -0.87742915
 [61] -1.28097855  0.20953558  0.46955235 -2.55620633  0.13753914  0.31199043
 [67] -0.38150944 -1.08184100  0.83555219 -0.35173692 -0.71553713  0.11593661
 [73]  1.82119183  0.73875847 -0.68570378  0.02697403 -1.52524303  1.89667380
 [79] -0.85540912  0.83941440  1.41295778  0.58613243 -0.28690883  0.60948984
 [85] -0.01796637 -0.54970050  0.15899146 -1.09273878  1.39912060  0.78643604
 [91]  1.45310548  0.58336490  0.96881069 -1.05614286 -1.14856701  1.12646173
 [97] -1.45154752  0.60620181 -0.64258761  2.54122537
> rowVars(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
  [1]  0.68564344 -0.36085909  1.51166423  0.78329164 -0.60165194  0.92115733
  [7] -1.37553483  2.35345797  0.26829367 -0.64381240  0.26916210 -2.06133359
 [13] -0.57541817 -1.36326635  0.50058227 -1.46729136  1.18408117  1.88309201
 [19] -0.75108619 -0.90917261  0.16018775 -0.22666467 -1.12728722 -0.78057583
 [25]  0.83014365 -0.23513149 -0.93694634  1.25548878 -0.04719795  1.12436291
 [31]  0.68826510  1.40959510  0.52990780  3.03568131 -1.22303306 -2.80009539
 [37]  0.08868323  1.52735358 -0.43163654  0.09826795  0.24777817 -0.39856093
 [43]  1.53492493 -1.09444324 -0.92724569 -0.54919897 -0.47995375  2.23272057
 [49]  0.08428868 -0.81806073  1.37596515 -0.93502959  0.29602304  0.72219741
 [55]  0.46159160  1.53687380 -0.84252807  0.69960372 -2.16965557 -0.87742915
 [61] -1.28097855  0.20953558  0.46955235 -2.55620633  0.13753914  0.31199043
 [67] -0.38150944 -1.08184100  0.83555219 -0.35173692 -0.71553713  0.11593661
 [73]  1.82119183  0.73875847 -0.68570378  0.02697403 -1.52524303  1.89667380
 [79] -0.85540912  0.83941440  1.41295778  0.58613243 -0.28690883  0.60948984
 [85] -0.01796637 -0.54970050  0.15899146 -1.09273878  1.39912060  0.78643604
 [91]  1.45310548  0.58336490  0.96881069 -1.05614286 -1.14856701  1.12646173
 [97] -1.45154752  0.60620181 -0.64258761  2.54122537
> rowMin(tmp2)
  [1]  0.68564344 -0.36085909  1.51166423  0.78329164 -0.60165194  0.92115733
  [7] -1.37553483  2.35345797  0.26829367 -0.64381240  0.26916210 -2.06133359
 [13] -0.57541817 -1.36326635  0.50058227 -1.46729136  1.18408117  1.88309201
 [19] -0.75108619 -0.90917261  0.16018775 -0.22666467 -1.12728722 -0.78057583
 [25]  0.83014365 -0.23513149 -0.93694634  1.25548878 -0.04719795  1.12436291
 [31]  0.68826510  1.40959510  0.52990780  3.03568131 -1.22303306 -2.80009539
 [37]  0.08868323  1.52735358 -0.43163654  0.09826795  0.24777817 -0.39856093
 [43]  1.53492493 -1.09444324 -0.92724569 -0.54919897 -0.47995375  2.23272057
 [49]  0.08428868 -0.81806073  1.37596515 -0.93502959  0.29602304  0.72219741
 [55]  0.46159160  1.53687380 -0.84252807  0.69960372 -2.16965557 -0.87742915
 [61] -1.28097855  0.20953558  0.46955235 -2.55620633  0.13753914  0.31199043
 [67] -0.38150944 -1.08184100  0.83555219 -0.35173692 -0.71553713  0.11593661
 [73]  1.82119183  0.73875847 -0.68570378  0.02697403 -1.52524303  1.89667380
 [79] -0.85540912  0.83941440  1.41295778  0.58613243 -0.28690883  0.60948984
 [85] -0.01796637 -0.54970050  0.15899146 -1.09273878  1.39912060  0.78643604
 [91]  1.45310548  0.58336490  0.96881069 -1.05614286 -1.14856701  1.12646173
 [97] -1.45154752  0.60620181 -0.64258761  2.54122537
> 
> colMeans(tmp2)
[1] 0.07245322
> colSums(tmp2)
[1] 7.245322
> colVars(tmp2)
[1] 1.285921
> colSd(tmp2)
[1] 1.133985
> colMax(tmp2)
[1] 3.035681
> colMin(tmp2)
[1] -2.800095
> colMedians(tmp2)
[1] 0.1071023
> colRanges(tmp2)
          [,1]
[1,] -2.800095
[2,]  3.035681
> 
> 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] -6.4245028 -0.9462800 -3.1064467  4.0009761  3.0025974 -4.6737291
 [7] -2.5558056 -1.8116997  3.8384425 -0.1683924
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -2.24785650
[2,] -1.37964721
[3,] -0.56328721
[4,]  0.09687625
[5,]  1.04058223
> 
> rowApply(tmp,sum)
 [1] -3.3289591  3.2106615 -4.1360413 -0.2601700 -0.2007454  1.4122100
 [7]  0.9450419 -2.9787577  3.8227910 -7.3308711
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    8    2    7    3    1    3    3    1    8     1
 [2,]    5    5    8    1    9    2    1    5    5    10
 [3,]    1    9    1    2    8    5    8    9    6     8
 [4,]    4    7   10    9    7    4    9    6   10     7
 [5,]   10    3    5    5   10    8   10    8    4     9
 [6,]    9    1    9    8    2    1    7    2    1     5
 [7,]    6    6    6    7    3    6    4    3    2     6
 [8,]    2    4    2    6    4   10    2    7    7     2
 [9,]    7    8    4   10    5    9    6   10    9     4
[10,]    3   10    3    4    6    7    5    4    3     3
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  3.45119116 -3.06638168  0.64543126 -0.29046099 -0.46594676 -2.36157745
 [7] -2.53717766 -0.09109211 -1.92053650 -3.14727271 -1.72235599  3.08401424
[13] -1.65036374 -1.52448213  0.27133503  0.29508787  1.73843590 -0.09342664
[19] -0.50107469  1.83563635
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.0214553
[2,] -0.4238874
[3,]  0.0580044
[4,]  1.6549760
[5,]  3.1835535
> 
> rowApply(tmp,sum)
[1] -1.152628  3.435365 -5.419969 -1.129008 -3.784777
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]   12    5   20    4   20
[2,]    2   11   16    5    3
[3,]   10   19   13   17    1
[4,]   11   15    1   13   16
[5,]   15    6   12    8    9
> 
> 
> as.matrix(tmp)
           [,1]       [,2]        [,3]        [,4]        [,5]       [,6]
[1,]  0.0580044 -1.3332182 -0.09984381  0.02306839  0.41042840 -0.3876723
[2,] -0.4238874  0.3274293  1.45729903  0.84855989 -0.04670725  0.2276149
[3,]  3.1835535  0.2523491  0.08705764 -1.94118217 -0.09345492 -1.5088768
[4,] -1.0214553 -0.9156405  0.90453845  0.28923969 -0.43910292  0.3690273
[5,]  1.6549760 -1.3973013 -1.70362004  0.48985321 -0.29711006 -1.0616707
           [,7]       [,8]        [,9]      [,10]      [,11]     [,12]
[1,] -0.6681313  0.4695355  0.42709607 -0.1777017  1.0650823 1.4377361
[2,]  0.7615652  0.8576042 -1.40719114  0.2499665  0.1760904 0.2461428
[3,] -0.9661403 -1.1454952 -0.67734704 -1.4915621 -0.4165705 0.1529736
[4,] -1.8786826  0.6566605 -0.04739672 -1.1029490 -1.4626967 1.1430056
[5,]  0.2142115 -0.9293972 -0.21569768 -0.6250265 -1.0842614 0.1041562
          [,13]      [,14]      [,15]      [,16]      [,17]      [,18]
[1,] -0.3501298 -0.2047868  0.3175055 -0.7241144 -1.6988461  0.2722204
[2,] -3.0992706 -0.4508075  0.9192049  1.7032848  0.4670159 -1.0191968
[3,]  0.1989844 -0.9170101 -0.7948604  0.5142698  0.6910460  0.5878675
[4,]  0.8362834  0.9649679 -0.8579489  0.2847048  2.1002145 -0.2922761
[5,]  0.7637689 -0.9168456  0.6874340 -1.4830571  0.1790057  0.3579585
          [,19]      [,20]
[1,] -0.4355136  0.4466530
[2,]  1.1052764  0.5353716
[3,] -0.8135891 -0.3219816
[4,] -0.7671127  0.1076109
[5,]  0.4098643  1.0679824
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.8  Kilobytes.
Disk usage :  800  bytes.
> 
> 
> 
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size:  5 5 
Buffer size:  1 1 
Directory:    F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  622  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  543  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.8  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 -0.7517026 0.8754706 -0.4866183 0.1757386 1.292171 0.2099958 -0.2344583
          col8       col9     col10     col11     col12     col13   col14
row1 0.6158508 -0.4855516 0.8251786 0.9522758 -1.130112 0.2100366 1.63227
         col15      col16      col17      col18      col19   col20
row1 -1.028087 -0.8198322 -0.5070827 -0.8015502 -0.8750125 0.15341
> tmp[,"col10"]
           col10
row1  0.82517862
row2 -0.47937999
row3  0.09692121
row4 -1.93658207
row5  0.50016416
> tmp[c("row1","row5"),]
           col1      col2       col3       col4      col5       col6
row1 -0.7517026 0.8754706 -0.4866183  0.1757386 1.2921708  0.2099958
row5 -1.6770662 0.5626928 -0.7507023 -0.9555897 0.4269318 -1.5284524
            col7      col8       col9     col10      col11     col12     col13
row1 -0.23445834 0.6158508 -0.4855516 0.8251786  0.9522758 -1.130112 0.2100366
row5 -0.09044489 1.6797149 -1.1454127 0.5001642 -0.9857777 -1.025390 0.3001306
        col14     col15      col16      col17      col18      col19     col20
row1 1.632270 -1.028087 -0.8198322 -0.5070827 -0.8015502 -0.8750125 0.1534100
row5 0.723705 -0.283033  1.7729302 -0.7386827  1.4120508 -0.9937189 0.6410027
> tmp[,c("col6","col20")]
            col6        col20
row1  0.20999575  0.153409963
row2 -0.18588042 -0.474535448
row3 -0.09344081 -0.006535874
row4  0.30268061  1.441911031
row5 -1.52845238  0.641002736
> tmp[c("row1","row5"),c("col6","col20")]
           col6     col20
row1  0.2099958 0.1534100
row5 -1.5284524 0.6410027
> 
> 
> 
> 
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")]  <- rnorm(4,mean=105)
> 
> tmp["row1",]
         col1     col2     col3    col4    col5     col6     col7     col8
row1 49.50995 49.00248 51.12079 50.7922 49.7562 105.6151 50.49839 48.56784
         col9    col10    col11   col12    col13    col14    col15    col16
row1 48.27842 48.35327 49.16942 48.4068 51.30337 50.51653 49.91843 51.10238
        col17    col18    col19    col20
row1 50.91431 50.17042 49.23017 104.9092
> tmp[,"col10"]
        col10
row1 48.35327
row2 29.97180
row3 30.31648
row4 29.75312
row5 50.37328
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 49.50995 49.00248 51.12079 50.79220 49.75620 105.6151 50.49839 48.56784
row5 50.52799 50.86339 49.41222 49.46443 50.92377 104.5482 50.29988 50.37244
         col9    col10    col11    col12    col13    col14    col15    col16
row1 48.27842 48.35327 49.16942 48.40680 51.30337 50.51653 49.91843 51.10238
row5 49.25148 50.37328 49.06871 49.58251 50.88907 50.29274 50.36823 50.28712
        col17    col18    col19    col20
row1 50.91431 50.17042 49.23017 104.9092
row5 49.01405 50.37404 50.69512 105.2559
> tmp[,c("col6","col20")]
          col6     col20
row1 105.61509 104.90917
row2  74.44095  75.27007
row3  75.56389  74.37646
row4  76.10834  75.42720
row5 104.54818 105.25594
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 105.6151 104.9092
row5 104.5482 105.2559
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 105.6151 104.9092
row5 104.5482 105.2559
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,] -0.6742334
[2,] -1.4166057
[3,] -0.6409939
[4,] -0.2395388
[5,] -0.6391714
> tmp[,c("col17","col7")]
           col17        col7
[1,]  0.52597964  0.19615118
[2,]  1.02055185  0.05332441
[3,]  1.61909910  1.67244576
[4,] -0.25449485  1.89157096
[5,] -0.02905436 -0.54057437
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
            col6      col20
[1,] -0.03807105  0.5786678
[2,] -1.05398630  0.8284769
[3,] -1.09716326  0.8646771
[4,]  1.49760439  0.4847604
[5,]  1.22263026 -0.6861758
> subBufferedMatrix(tmp,1,c("col6"))[,1]
            col1
[1,] -0.03807105
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
            col6
[1,] -0.03807105
[2,] -1.05398630
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> 
> 
> 
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
           [,1]       [,2]      [,3]       [,4]       [,5]       [,6]     [,7]
row3  0.1851189 -0.6084977 0.1235397 -0.1262611 -1.3761241 -0.4957471 1.055759
row1 -0.4326921  0.9035352 0.0998328 -0.2078872  0.8581415 -0.6337524 0.400925
           [,8]       [,9]      [,10]      [,11]      [,12]     [,13]
row3  1.2682848  1.8471437  0.3553449 -0.5174047 -0.8043694 1.1579090
row1 -0.2977463 -0.7708924 -1.1993453 -0.4032281 -0.1313210 0.2692938
          [,14]      [,15]      [,16]      [,17]      [,18]      [,19]
row3  1.0119913  0.6384653 -0.4459908  0.7196608 -0.4394328 -2.2477061
row1 -0.6927785 -1.5507236  1.3814640 -2.2525270  0.8295410  0.4006577
         [,20]
row3 1.1716491
row1 0.2846633
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
          [,1]      [,2]       [,3]    [,4]      [,5]      [,6]       [,7]
row2 0.2606786 -1.160233 -0.5025152 0.66332 -1.222813 0.8189688 -0.5378378
           [,8]      [,9]     [,10]
row2 -0.3485118 0.6856712 0.1399048
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
           [,1]     [,2]       [,3]     [,4]     [,5]      [,6]     [,7]
row5 -0.4597707 1.516574 -0.9791743 -1.33157 1.607715 0.6702671 1.877521
         [,8]      [,9]    [,10]     [,11]     [,12]     [,13]     [,14]
row5 2.090489 -2.388891 1.427652 0.3909895 0.9464141 0.3807691 -1.431884
        [,15]      [,16]      [,17]      [,18]      [,19]      [,20]
row5 1.450818 -0.5276301 -0.4552728 -0.9772481 -0.1724992 -0.3157691
> 
> 
> 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: 0x00000254122fdd70>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236828bc219a"
 [2] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236821022636"
 [3] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM23688085b36" 
 [4] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236850ec5674"
 [5] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236834932605"
 [6] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM2368666d7e69"
 [7] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM2368248c3acb"
 [8] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM23682546489d"
 [9] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236836f120e1"
[10] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM23684a7c44d4"
[11] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236827ff20da"
[12] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM23684467fd8" 
[13] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236829ed4a65"
[14] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236831052878"
[15] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM236875d91175"
> 
> 
> ### 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: 0x00000254149ffa10>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x00000254149ffa10>
Warning message:
In dir.create(new.directory) :
  'F:\biocbuild\bbs-3.19-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x00000254149ffa10>
> rowMedians(tmp)
  [1]  0.360358586  0.255074146 -0.217487357  0.624303124  0.186446498
  [6]  0.029522015  0.600336583 -0.436520890 -0.172785141  0.073596550
 [11]  0.405368260  0.124259817  0.204252259 -0.196892058 -0.400845784
 [16] -0.334110494  0.344026046  0.170926454 -0.494469164  0.437143319
 [21]  0.049212931 -0.140604901 -0.370911483 -0.132336493  0.356667907
 [26]  0.050670474 -0.202627410  0.074334059  0.405992290  0.259806336
 [31]  0.021421540 -0.364391789  0.343097150 -0.049424925 -0.247570373
 [36]  0.812779574  0.144242417 -0.674993864  0.269661833 -0.199174944
 [41]  0.035565950  0.059227075  0.120016838  0.314463327  0.351562173
 [46]  0.203932440  0.685250241 -0.104844173  0.247101686 -0.124407326
 [51]  0.084939150  0.189826533  0.239249500 -0.004904704 -0.282397985
 [56]  0.114562443 -0.368467852  0.145685341  0.121584692  0.050271684
 [61]  0.183686177  0.518244068  0.497353790  0.378212038 -0.177977645
 [66] -0.325452691  0.082946508  0.624518822 -0.067472556  0.102708440
 [71]  0.512273165 -0.254635372 -0.338709525 -0.078829161  0.353876143
 [76]  0.289153144 -0.280780132  0.066777538  0.969704258 -0.302493395
 [81]  0.136525471  0.677720240 -0.286169753 -0.017292621  0.505932750
 [86] -0.172529240 -0.524399932  0.542846441 -0.319333949  0.034177634
 [91] -0.232675064 -0.310166355  0.800935900  0.353799578  0.032611621
 [96] -0.063810733 -0.112154392  0.341323910 -0.468080465 -0.117446861
[101]  0.539348906 -0.079117434 -0.509699388 -0.105409292  0.139239346
[106]  0.070894450  0.320801263  0.195183284  0.098895913 -0.011232725
[111] -0.157704306 -0.170864855  0.050150523  0.341763685  0.101967072
[116]  0.241734006  0.195161338 -0.196664727 -0.254366401  0.214149773
[121] -0.475836470  0.229735696 -0.408610649 -0.170971459 -0.045749903
[126] -0.594091734 -0.170011022  0.027498104  0.198673469 -0.511622374
[131] -0.422972863 -0.321451929  0.427565297  0.306161822  0.321882994
[136] -0.218814164  0.024533706 -0.093983822  0.021655323  0.165139162
[141] -0.063859999  0.601392573 -0.230964182  0.135561902  0.415564918
[146] -0.058141178 -0.400378830 -0.058547628 -0.207070305 -0.376614732
[151] -0.187654929  0.222236462  0.087803637  0.427912638  0.066766806
[156]  0.214241158 -0.675511014  0.626362707  0.149442341 -0.252246145
[161] -0.032019074 -0.032630319  0.100031966 -0.223139750  0.423886023
[166] -0.003660397 -0.167205082 -0.437526047  0.145167755  0.442627922
[171]  0.265045672  0.382125119 -0.053368078 -0.343217644  0.070649015
[176]  0.170298183 -0.096730809  0.082405363  0.082317061  0.542375178
[181] -0.097522405 -0.605927929  0.152484839 -0.078604283 -0.014837146
[186] -0.226914727  0.094187254 -0.485547422  0.367813068  0.228257979
[191] -0.048593813  0.057468529  0.227622202  0.058405961 -0.096464214
[196]  0.141588810 -0.433025392 -0.046838681  0.187883219 -0.015030521
[201] -0.264355668  0.831762546  0.047465899  0.550860722  0.615221608
[206]  0.024753948  0.119733390  0.422253306 -0.357424110  0.018957678
[211]  0.045161252  0.355216302  0.285444073  0.288403527 -0.035853332
[216]  0.322491397  0.425848336  0.001080431 -0.156539824  0.612353512
[221]  0.215915733  0.434853836 -0.127571414  0.305531260  0.271667964
[226]  0.070418138 -0.157941387  0.029484177 -0.213008538  0.549696662
> 
> proc.time()
   user  system elapsed 
   3.73   20.01   52.29 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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: 0x000001a5790fd6b0>
> .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: 0x000001a5790fd6b0>
> .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: 0x000001a5790fd6b0>
> .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: 0x000001a5790fd6b0>
> 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: 0x000001a5790fda10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fda10>
> .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: 0x000001a5790fda10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fda10>
> .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: 0x000001a5790fda10>
> 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: 0x000001a5790fd170>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fd170>
> .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: 0x000001a5790fd170>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001a5790fd170>
> .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: 0x000001a5790fd170>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x000001a5790fd170>
> .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: 0x000001a5790fd170>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x000001a5790fd170>
> .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: 0x000001a5790fd170>
> 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: 0x000001a5790fd710>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000001a5790fd710>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fd710>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fd710>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile31ac6b732aea" "BufferedMatrixFile31ac7e953782"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile31ac6b732aea" "BufferedMatrixFile31ac7e953782"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fd530>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fd530>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001a5790fd530>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001a5790fd530>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000001a5790fd530>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000001a5790fd530>
> .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: 0x000001a5790fd950>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a5790fd950>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001a5790fd950>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000001a5790fd950>
> 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: 0x000001a5790fdad0>
> .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: 0x000001a5790fdad0>
> rm(P)
> 
> proc.time()
   user  system elapsed 
   0.39    0.14    0.61 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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 
   0.28    0.12    0.39 

Example timings