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This page was generated on 2024-05-04 11:40:19 -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 kunpeng2


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.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results


Summary

Package: BufferedMatrix
Version: 1.68.0
Command: /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz
StartedAt: 2024-05-04 05:34:01 -0000 (Sat, 04 May 2024)
EndedAt: 2024-05-04 05:34:26 -0000 (Sat, 04 May 2024)
EllapsedTime: 25.0 seconds
RetCode: 0
Status:   OK  
CheckDir: BufferedMatrix.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 beta (2024-04-15 r86425)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    gcc (GCC) 10.3.1
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* 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 for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (GCC) 10.3.1’
* 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
   209 |     $x^{power}$ elementwise of the matrix
       |        ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking 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
  ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.


Installation output

BufferedMatrix.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (GCC) 10.3.1’
gcc -I"/home/biocbuild/R/R-beta-2024-04-15_r86425/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/R/R-beta-2024-04-15_r86425/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -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){
      |       ^~~~~~~~~~~~~~~~~~~
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"/home/biocbuild/R/R-beta-2024-04-15_r86425/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/R/R-beta-2024-04-15_r86425/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/R/R-beta-2024-04-15_r86425/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-beta-2024-04-15_r86425/lib -lR
installing to /home/biocbuild/R/R-beta-2024-04-15_r86425/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)

Tests output

BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout


R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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 
  0.332   0.030   0.347 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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] "/home/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 471778 25.2    1026212 54.9   643448 34.4
Vcells 872066  6.7    8388608 64.0  2045060 15.7
> 
> 
> 
> 
> ##
> ## 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 05:34:20 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 05:34:20 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: 0x19b04ed0>
> 
> 
> 
> 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 05:34:21 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 05:34:21 2024"
> 
> ColMode(tmp2)
<pointer: 0x19b04ed0>
> 
> 
> 
> ### 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,] 100.4680889 -0.4452851 -0.49323946 -0.6230645
[2,]   0.6126193  0.7308491  0.17820573  1.5790213
[3,]   1.3514504 -0.4540252 -0.06055187 -1.1952946
[4,]  -0.2194139 -1.1620313 -0.59396826 -1.0383918
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
            [,1]      [,2]       [,3]      [,4]
[1,] 100.4680889 0.4452851 0.49323946 0.6230645
[2,]   0.6126193 0.7308491 0.17820573 1.5790213
[3,]   1.3514504 0.4540252 0.06055187 1.1952946
[4,]   0.2194139 1.1620313 0.59396826 1.0383918
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]      [,3]      [,4]
[1,] 10.0233771 0.6672968 0.7023101 0.7893444
[2,]  0.7827000 0.8548971 0.4221442 1.2565911
[3,]  1.1625190 0.6738139 0.2460729 1.0932953
[4,]  0.4684164 1.0779755 0.7706934 1.0190151
> 
> 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:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 225.70186 32.11825 32.51634 33.51651
[2,]  33.43962 34.27982 29.39965 39.14493
[3,]  37.97664 32.19216 27.52128 37.12825
[4,]  29.90358 36.94179 33.30090 36.22854
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x191abb90>
> exp(tmp5)
<pointer: 0x191abb90>
> log(tmp5,2)
<pointer: 0x191abb90>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.7689
> Min(tmp5)
[1] 52.86886
> mean(tmp5)
[1] 72.81966
> Sum(tmp5)
[1] 14563.93
> Var(tmp5)
[1] 856.7321
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 92.05115 69.58629 72.36161 70.66549 71.71074 70.55566 70.52459 71.27833
 [9] 70.62302 68.83971
> rowSums(tmp5)
 [1] 1841.023 1391.726 1447.232 1413.310 1434.215 1411.113 1410.492 1425.567
 [9] 1412.460 1376.794
> rowVars(tmp5)
 [1] 7935.18392   36.48379   75.88438   40.66825   87.67641   84.08940
 [7]   85.48011   29.37531   87.52137   68.86431
> rowSd(tmp5)
 [1] 89.079649  6.040182  8.711164  6.377166  9.363568  9.170027  9.245545
 [8]  5.419899  9.355286  8.298452
> rowMax(tmp5)
 [1] 469.76885  81.47505  86.52465  87.44324  87.03668  86.50439  84.68741
 [8]  81.57681  85.72992  87.77240
> rowMin(tmp5)
 [1] 65.32556 57.85192 57.28194 61.76295 57.67022 53.54635 52.86886 59.74510
 [9] 55.11824 56.57582
> 
> colMeans(tmp5)
 [1] 108.62871  72.74602  71.72512  70.38731  70.99831  68.21728  70.28642
 [8]  70.94590  71.79077  68.64485  72.47530  71.26085  69.76789  70.74046
[15]  71.13582  70.30203  73.43446  71.54632  71.24599  70.11335
> colSums(tmp5)
 [1] 1086.2871  727.4602  717.2512  703.8731  709.9831  682.1728  702.8642
 [8]  709.4590  717.9077  686.4485  724.7530  712.6085  697.6789  707.4046
[15]  711.3582  703.0203  734.3446  715.4632  712.4599  701.1335
> colVars(tmp5)
 [1] 16164.61335    26.64596   112.66100    64.56357    39.60421    70.72032
 [7]    76.27868    65.03810    33.32285    68.08925    43.18762    54.33052
[13]   103.50713   100.71292    83.67758    83.01679    71.85170    73.83286
[19]    52.11171    22.77640
> colSd(tmp5)
 [1] 127.140133   5.161973  10.614189   8.035146   6.293188   8.409537
 [7]   8.733767   8.064620   5.772595   8.251621   6.571729   7.370924
[13]  10.173845  10.035582   9.147545   9.111355   8.476538   8.592605
[19]   7.218844   4.772463
> colMax(tmp5)
 [1] 469.76885  83.45737  85.83997  81.47505  78.96389  84.32762  87.77240
 [8]  85.82677  80.68390  81.36715  79.82846  82.23020  87.44324  84.77831
[15]  86.50439  84.68741  86.52465  85.49814  87.03668  78.88591
> colMin(tmp5)
 [1] 59.74510 66.84994 57.28194 55.11824 62.39668 53.54635 56.20180 59.21284
 [9] 61.54520 55.87246 57.85192 61.63153 52.86886 56.57582 60.54947 58.05923
[17] 60.79885 57.23851 63.93505 64.11238
> 
> 
> ### 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]       NA 69.58629 72.36161 70.66549 71.71074 70.55566 70.52459 71.27833
 [9] 70.62302 68.83971
> rowSums(tmp5)
 [1]       NA 1391.726 1447.232 1413.310 1434.215 1411.113 1410.492 1425.567
 [9] 1412.460 1376.794
> rowVars(tmp5)
 [1] 8371.45113   36.48379   75.88438   40.66825   87.67641   84.08940
 [7]   85.48011   29.37531   87.52137   68.86431
> rowSd(tmp5)
 [1] 91.495635  6.040182  8.711164  6.377166  9.363568  9.170027  9.245545
 [8]  5.419899  9.355286  8.298452
> rowMax(tmp5)
 [1]       NA 81.47505 86.52465 87.44324 87.03668 86.50439 84.68741 81.57681
 [9] 85.72992 87.77240
> rowMin(tmp5)
 [1]       NA 57.85192 57.28194 61.76295 57.67022 53.54635 52.86886 59.74510
 [9] 55.11824 56.57582
> 
> colMeans(tmp5)
 [1] 108.62871  72.74602  71.72512  70.38731  70.99831  68.21728  70.28642
 [8]  70.94590  71.79077  68.64485  72.47530  71.26085  69.76789  70.74046
[15]  71.13582        NA  73.43446  71.54632  71.24599  70.11335
> colSums(tmp5)
 [1] 1086.2871  727.4602  717.2512  703.8731  709.9831  682.1728  702.8642
 [8]  709.4590  717.9077  686.4485  724.7530  712.6085  697.6789  707.4046
[15]  711.3582        NA  734.3446  715.4632  712.4599  701.1335
> colVars(tmp5)
 [1] 16164.61335    26.64596   112.66100    64.56357    39.60421    70.72032
 [7]    76.27868    65.03810    33.32285    68.08925    43.18762    54.33052
[13]   103.50713   100.71292    83.67758          NA    71.85170    73.83286
[19]    52.11171    22.77640
> colSd(tmp5)
 [1] 127.140133   5.161973  10.614189   8.035146   6.293188   8.409537
 [7]   8.733767   8.064620   5.772595   8.251621   6.571729   7.370924
[13]  10.173845  10.035582   9.147545         NA   8.476538   8.592605
[19]   7.218844   4.772463
> colMax(tmp5)
 [1] 469.76885  83.45737  85.83997  81.47505  78.96389  84.32762  87.77240
 [8]  85.82677  80.68390  81.36715  79.82846  82.23020  87.44324  84.77831
[15]  86.50439        NA  86.52465  85.49814  87.03668  78.88591
> colMin(tmp5)
 [1] 59.74510 66.84994 57.28194 55.11824 62.39668 53.54635 56.20180 59.21284
 [9] 61.54520 55.87246 57.85192 61.63153 52.86886 56.57582 60.54947       NA
[17] 60.79885 57.23851 63.93505 64.11238
> 
> Max(tmp5,na.rm=TRUE)
[1] 469.7689
> Min(tmp5,na.rm=TRUE)
[1] 52.86886
> mean(tmp5,na.rm=TRUE)
[1] 72.76747
> Sum(tmp5,na.rm=TRUE)
[1] 14480.73
> Var(tmp5,na.rm=TRUE)
[1] 860.5116
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 92.51674 69.58629 72.36161 70.66549 71.71074 70.55566 70.52459 71.27833
 [9] 70.62302 68.83971
> rowSums(tmp5,na.rm=TRUE)
 [1] 1757.818 1391.726 1447.232 1413.310 1434.215 1411.113 1410.492 1425.567
 [9] 1412.460 1376.794
> rowVars(tmp5,na.rm=TRUE)
 [1] 8371.45113   36.48379   75.88438   40.66825   87.67641   84.08940
 [7]   85.48011   29.37531   87.52137   68.86431
> rowSd(tmp5,na.rm=TRUE)
 [1] 91.495635  6.040182  8.711164  6.377166  9.363568  9.170027  9.245545
 [8]  5.419899  9.355286  8.298452
> rowMax(tmp5,na.rm=TRUE)
 [1] 469.76885  81.47505  86.52465  87.44324  87.03668  86.50439  84.68741
 [8]  81.57681  85.72992  87.77240
> rowMin(tmp5,na.rm=TRUE)
 [1] 65.32556 57.85192 57.28194 61.76295 57.67022 53.54635 52.86886 59.74510
 [9] 55.11824 56.57582
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 108.62871  72.74602  71.72512  70.38731  70.99831  68.21728  70.28642
 [8]  70.94590  71.79077  68.64485  72.47530  71.26085  69.76789  70.74046
[15]  71.13582  68.86837  73.43446  71.54632  71.24599  70.11335
> colSums(tmp5,na.rm=TRUE)
 [1] 1086.2871  727.4602  717.2512  703.8731  709.9831  682.1728  702.8642
 [8]  709.4590  717.9077  686.4485  724.7530  712.6085  697.6789  707.4046
[15]  711.3582  619.8153  734.3446  715.4632  712.4599  701.1335
> colVars(tmp5,na.rm=TRUE)
 [1] 16164.61335    26.64596   112.66100    64.56357    39.60421    70.72032
 [7]    76.27868    65.03810    33.32285    68.08925    43.18762    54.33052
[13]   103.50713   100.71292    83.67758    70.27093    71.85170    73.83286
[19]    52.11171    22.77640
> colSd(tmp5,na.rm=TRUE)
 [1] 127.140133   5.161973  10.614189   8.035146   6.293188   8.409537
 [7]   8.733767   8.064620   5.772595   8.251621   6.571729   7.370924
[13]  10.173845  10.035582   9.147545   8.382776   8.476538   8.592605
[19]   7.218844   4.772463
> colMax(tmp5,na.rm=TRUE)
 [1] 469.76885  83.45737  85.83997  81.47505  78.96389  84.32762  87.77240
 [8]  85.82677  80.68390  81.36715  79.82846  82.23020  87.44324  84.77831
[15]  86.50439  84.68741  86.52465  85.49814  87.03668  78.88591
> colMin(tmp5,na.rm=TRUE)
 [1] 59.74510 66.84994 57.28194 55.11824 62.39668 53.54635 56.20180 59.21284
 [9] 61.54520 55.87246 57.85192 61.63153 52.86886 56.57582 60.54947 58.05923
[17] 60.79885 57.23851 63.93505 64.11238
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1]      NaN 69.58629 72.36161 70.66549 71.71074 70.55566 70.52459 71.27833
 [9] 70.62302 68.83971
> rowSums(tmp5,na.rm=TRUE)
 [1]    0.000 1391.726 1447.232 1413.310 1434.215 1411.113 1410.492 1425.567
 [9] 1412.460 1376.794
> rowVars(tmp5,na.rm=TRUE)
 [1]       NA 36.48379 75.88438 40.66825 87.67641 84.08940 85.48011 29.37531
 [9] 87.52137 68.86431
> rowSd(tmp5,na.rm=TRUE)
 [1]       NA 6.040182 8.711164 6.377166 9.363568 9.170027 9.245545 5.419899
 [9] 9.355286 8.298452
> rowMax(tmp5,na.rm=TRUE)
 [1]       NA 81.47505 86.52465 87.44324 87.03668 86.50439 84.68741 81.57681
 [9] 85.72992 87.77240
> rowMin(tmp5,na.rm=TRUE)
 [1]       NA 57.85192 57.28194 61.76295 57.67022 53.54635 52.86886 59.74510
 [9] 55.11824 56.57582
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 68.50202 73.40114 72.17474 70.45699 70.47718 67.83546 70.83763 70.80199
 [9] 71.46042 68.53493 72.02292 71.72805 68.68585 69.18070 70.77304      NaN
[17] 73.85845 71.80322 71.83983 70.41354
> colSums(tmp5,na.rm=TRUE)
 [1] 616.5182 660.6103 649.5727 634.1129 634.2947 610.5192 637.5387 637.2179
 [9] 643.1438 616.8144 648.2063 645.5525 618.1726 622.6263 636.9574   0.0000
[17] 664.7260 646.2290 646.5585 633.7219
> colVars(tmp5,na.rm=TRUE)
 [1]  70.99504  25.14840 124.46930  72.57940  41.49952  77.92027  82.39544
 [8]  72.93485  36.26055  76.46448  46.28386  58.66613 103.27388  85.93244
[15]  92.65673        NA  78.81086  82.31946  54.65838  24.60963
> colSd(tmp5,na.rm=TRUE)
 [1]  8.425856  5.014818 11.156581  8.519354  6.442012  8.827246  9.077193
 [8]  8.540190  6.021674  8.744397  6.803224  7.659382 10.162376  9.269975
[15]  9.625836        NA  8.877548  9.073007  7.393131  4.960810
> colMax(tmp5,na.rm=TRUE)
 [1] 82.19889 83.45737 85.83997 81.47505 78.96389 84.32762 87.77240 85.82677
 [9] 80.68390 81.36715 79.82846 82.23020 87.44324 83.23540 86.50439     -Inf
[17] 86.52465 85.49814 87.03668 78.88591
> colMin(tmp5,na.rm=TRUE)
 [1] 59.74510 67.00377 57.28194 55.11824 62.39668 53.54635 56.20180 59.21284
 [9] 61.54520 55.87246 57.85192 61.63153 52.86886 56.57582 60.54947      Inf
[17] 60.79885 57.23851 63.93505 64.11238
> 
> 
> 
> 
> 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] 269.5714 319.5000 171.2762 287.8408 266.4857 172.2271 314.7419 312.4041
 [9] 237.8906 230.3943
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 269.5714 319.5000 171.2762 287.8408 266.4857 172.2271 314.7419 312.4041
 [9] 237.8906 230.3943
> 
> 
> 
> 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]  1.136868e-13 -5.684342e-14  0.000000e+00  7.105427e-14  1.421085e-14
 [6] -2.842171e-14  5.684342e-14  1.136868e-13  0.000000e+00 -1.421085e-13
[11]  0.000000e+00  1.421085e-13 -1.989520e-13  5.684342e-14  5.684342e-14
[16]  0.000000e+00 -1.421085e-13  2.842171e-14  5.684342e-14 -2.842171e-13
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## 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)
+ }
4   9 
3   19 
9   8 
2   6 
4   19 
9   5 
7   18 
2   8 
6   9 
6   9 
1   20 
4   14 
3   10 
2   20 
5   11 
2   1 
6   4 
7   19 
3   3 
2   12 
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] 2.215006
> Min(tmp)
[1] -3.035438
> mean(tmp)
[1] -0.08192893
> Sum(tmp)
[1] -8.192893
> Var(tmp)
[1] 0.9848143
> 
> rowMeans(tmp)
[1] -0.08192893
> rowSums(tmp)
[1] -8.192893
> rowVars(tmp)
[1] 0.9848143
> rowSd(tmp)
[1] 0.9923781
> rowMax(tmp)
[1] 2.215006
> rowMin(tmp)
[1] -3.035438
> 
> colMeans(tmp)
  [1] -0.890312479  0.986659819  1.614931594  0.162277738  0.069283017
  [6] -0.145152142 -0.695392779 -0.351915272 -0.147305494  0.891955879
 [11] -2.301978909  0.102642382  0.839576516 -0.021335671  0.163465981
 [16] -0.807503435  0.137893117  0.305052626 -1.618874936 -0.883077106
 [21] -0.524165928  0.863545199 -0.658709066  1.740575047 -1.060640656
 [26] -0.010554454  1.221588425 -0.225604690 -0.204647764  0.563353603
 [31] -0.183300627 -0.341057800  1.186912190  1.084676042 -0.529524113
 [36]  0.684288475  0.319132902 -0.680864280 -0.405608849 -1.401320150
 [41] -0.276645161  1.211291158 -1.792915773 -3.035437626 -0.022364175
 [46]  1.027549548  0.739521432 -0.305445648 -0.777987951  0.771570420
 [51] -0.871003977 -1.205544164  0.917283914  0.861259741 -0.671202550
 [56]  0.495447564  0.086334140 -0.950082848  2.166610761 -1.120223012
 [61]  0.029302646  0.468824829 -1.147519060  0.612241406 -0.009628447
 [66] -1.404924785 -0.803645414 -1.426167351  1.687049500 -0.595533271
 [71]  0.647058952 -0.302737767 -0.594917143 -0.178130022 -1.303854182
 [76]  1.454947285  0.105578895 -0.994937657  0.270250201  1.268699958
 [81]  2.215006493 -1.893380502  1.205122458 -1.145303967  1.037625404
 [86] -1.392426178 -0.616838793 -0.270211039  0.658996137 -1.041747460
 [91] -0.012556569  0.384904476  0.827089151  0.935957614 -1.842657254
 [96]  0.539691998  0.184035753 -0.354860554 -0.999441817 -0.490837113
> colSums(tmp)
  [1] -0.890312479  0.986659819  1.614931594  0.162277738  0.069283017
  [6] -0.145152142 -0.695392779 -0.351915272 -0.147305494  0.891955879
 [11] -2.301978909  0.102642382  0.839576516 -0.021335671  0.163465981
 [16] -0.807503435  0.137893117  0.305052626 -1.618874936 -0.883077106
 [21] -0.524165928  0.863545199 -0.658709066  1.740575047 -1.060640656
 [26] -0.010554454  1.221588425 -0.225604690 -0.204647764  0.563353603
 [31] -0.183300627 -0.341057800  1.186912190  1.084676042 -0.529524113
 [36]  0.684288475  0.319132902 -0.680864280 -0.405608849 -1.401320150
 [41] -0.276645161  1.211291158 -1.792915773 -3.035437626 -0.022364175
 [46]  1.027549548  0.739521432 -0.305445648 -0.777987951  0.771570420
 [51] -0.871003977 -1.205544164  0.917283914  0.861259741 -0.671202550
 [56]  0.495447564  0.086334140 -0.950082848  2.166610761 -1.120223012
 [61]  0.029302646  0.468824829 -1.147519060  0.612241406 -0.009628447
 [66] -1.404924785 -0.803645414 -1.426167351  1.687049500 -0.595533271
 [71]  0.647058952 -0.302737767 -0.594917143 -0.178130022 -1.303854182
 [76]  1.454947285  0.105578895 -0.994937657  0.270250201  1.268699958
 [81]  2.215006493 -1.893380502  1.205122458 -1.145303967  1.037625404
 [86] -1.392426178 -0.616838793 -0.270211039  0.658996137 -1.041747460
 [91] -0.012556569  0.384904476  0.827089151  0.935957614 -1.842657254
 [96]  0.539691998  0.184035753 -0.354860554 -0.999441817 -0.490837113
> 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] -0.890312479  0.986659819  1.614931594  0.162277738  0.069283017
  [6] -0.145152142 -0.695392779 -0.351915272 -0.147305494  0.891955879
 [11] -2.301978909  0.102642382  0.839576516 -0.021335671  0.163465981
 [16] -0.807503435  0.137893117  0.305052626 -1.618874936 -0.883077106
 [21] -0.524165928  0.863545199 -0.658709066  1.740575047 -1.060640656
 [26] -0.010554454  1.221588425 -0.225604690 -0.204647764  0.563353603
 [31] -0.183300627 -0.341057800  1.186912190  1.084676042 -0.529524113
 [36]  0.684288475  0.319132902 -0.680864280 -0.405608849 -1.401320150
 [41] -0.276645161  1.211291158 -1.792915773 -3.035437626 -0.022364175
 [46]  1.027549548  0.739521432 -0.305445648 -0.777987951  0.771570420
 [51] -0.871003977 -1.205544164  0.917283914  0.861259741 -0.671202550
 [56]  0.495447564  0.086334140 -0.950082848  2.166610761 -1.120223012
 [61]  0.029302646  0.468824829 -1.147519060  0.612241406 -0.009628447
 [66] -1.404924785 -0.803645414 -1.426167351  1.687049500 -0.595533271
 [71]  0.647058952 -0.302737767 -0.594917143 -0.178130022 -1.303854182
 [76]  1.454947285  0.105578895 -0.994937657  0.270250201  1.268699958
 [81]  2.215006493 -1.893380502  1.205122458 -1.145303967  1.037625404
 [86] -1.392426178 -0.616838793 -0.270211039  0.658996137 -1.041747460
 [91] -0.012556569  0.384904476  0.827089151  0.935957614 -1.842657254
 [96]  0.539691998  0.184035753 -0.354860554 -0.999441817 -0.490837113
> colMin(tmp)
  [1] -0.890312479  0.986659819  1.614931594  0.162277738  0.069283017
  [6] -0.145152142 -0.695392779 -0.351915272 -0.147305494  0.891955879
 [11] -2.301978909  0.102642382  0.839576516 -0.021335671  0.163465981
 [16] -0.807503435  0.137893117  0.305052626 -1.618874936 -0.883077106
 [21] -0.524165928  0.863545199 -0.658709066  1.740575047 -1.060640656
 [26] -0.010554454  1.221588425 -0.225604690 -0.204647764  0.563353603
 [31] -0.183300627 -0.341057800  1.186912190  1.084676042 -0.529524113
 [36]  0.684288475  0.319132902 -0.680864280 -0.405608849 -1.401320150
 [41] -0.276645161  1.211291158 -1.792915773 -3.035437626 -0.022364175
 [46]  1.027549548  0.739521432 -0.305445648 -0.777987951  0.771570420
 [51] -0.871003977 -1.205544164  0.917283914  0.861259741 -0.671202550
 [56]  0.495447564  0.086334140 -0.950082848  2.166610761 -1.120223012
 [61]  0.029302646  0.468824829 -1.147519060  0.612241406 -0.009628447
 [66] -1.404924785 -0.803645414 -1.426167351  1.687049500 -0.595533271
 [71]  0.647058952 -0.302737767 -0.594917143 -0.178130022 -1.303854182
 [76]  1.454947285  0.105578895 -0.994937657  0.270250201  1.268699958
 [81]  2.215006493 -1.893380502  1.205122458 -1.145303967  1.037625404
 [86] -1.392426178 -0.616838793 -0.270211039  0.658996137 -1.041747460
 [91] -0.012556569  0.384904476  0.827089151  0.935957614 -1.842657254
 [96]  0.539691998  0.184035753 -0.354860554 -0.999441817 -0.490837113
> colMedians(tmp)
  [1] -0.890312479  0.986659819  1.614931594  0.162277738  0.069283017
  [6] -0.145152142 -0.695392779 -0.351915272 -0.147305494  0.891955879
 [11] -2.301978909  0.102642382  0.839576516 -0.021335671  0.163465981
 [16] -0.807503435  0.137893117  0.305052626 -1.618874936 -0.883077106
 [21] -0.524165928  0.863545199 -0.658709066  1.740575047 -1.060640656
 [26] -0.010554454  1.221588425 -0.225604690 -0.204647764  0.563353603
 [31] -0.183300627 -0.341057800  1.186912190  1.084676042 -0.529524113
 [36]  0.684288475  0.319132902 -0.680864280 -0.405608849 -1.401320150
 [41] -0.276645161  1.211291158 -1.792915773 -3.035437626 -0.022364175
 [46]  1.027549548  0.739521432 -0.305445648 -0.777987951  0.771570420
 [51] -0.871003977 -1.205544164  0.917283914  0.861259741 -0.671202550
 [56]  0.495447564  0.086334140 -0.950082848  2.166610761 -1.120223012
 [61]  0.029302646  0.468824829 -1.147519060  0.612241406 -0.009628447
 [66] -1.404924785 -0.803645414 -1.426167351  1.687049500 -0.595533271
 [71]  0.647058952 -0.302737767 -0.594917143 -0.178130022 -1.303854182
 [76]  1.454947285  0.105578895 -0.994937657  0.270250201  1.268699958
 [81]  2.215006493 -1.893380502  1.205122458 -1.145303967  1.037625404
 [86] -1.392426178 -0.616838793 -0.270211039  0.658996137 -1.041747460
 [91] -0.012556569  0.384904476  0.827089151  0.935957614 -1.842657254
 [96]  0.539691998  0.184035753 -0.354860554 -0.999441817 -0.490837113
> colRanges(tmp)
           [,1]      [,2]     [,3]      [,4]       [,5]       [,6]       [,7]
[1,] -0.8903125 0.9866598 1.614932 0.1622777 0.06928302 -0.1451521 -0.6953928
[2,] -0.8903125 0.9866598 1.614932 0.1622777 0.06928302 -0.1451521 -0.6953928
           [,8]       [,9]     [,10]     [,11]     [,12]     [,13]       [,14]
[1,] -0.3519153 -0.1473055 0.8919559 -2.301979 0.1026424 0.8395765 -0.02133567
[2,] -0.3519153 -0.1473055 0.8919559 -2.301979 0.1026424 0.8395765 -0.02133567
        [,15]      [,16]     [,17]     [,18]     [,19]      [,20]      [,21]
[1,] 0.163466 -0.8075034 0.1378931 0.3050526 -1.618875 -0.8830771 -0.5241659
[2,] 0.163466 -0.8075034 0.1378931 0.3050526 -1.618875 -0.8830771 -0.5241659
         [,22]      [,23]    [,24]     [,25]       [,26]    [,27]      [,28]
[1,] 0.8635452 -0.6587091 1.740575 -1.060641 -0.01055445 1.221588 -0.2256047
[2,] 0.8635452 -0.6587091 1.740575 -1.060641 -0.01055445 1.221588 -0.2256047
          [,29]     [,30]      [,31]      [,32]    [,33]    [,34]      [,35]
[1,] -0.2046478 0.5633536 -0.1833006 -0.3410578 1.186912 1.084676 -0.5295241
[2,] -0.2046478 0.5633536 -0.1833006 -0.3410578 1.186912 1.084676 -0.5295241
         [,36]     [,37]      [,38]      [,39]    [,40]      [,41]    [,42]
[1,] 0.6842885 0.3191329 -0.6808643 -0.4056088 -1.40132 -0.2766452 1.211291
[2,] 0.6842885 0.3191329 -0.6808643 -0.4056088 -1.40132 -0.2766452 1.211291
         [,43]     [,44]       [,45]   [,46]     [,47]      [,48]     [,49]
[1,] -1.792916 -3.035438 -0.02236418 1.02755 0.7395214 -0.3054456 -0.777988
[2,] -1.792916 -3.035438 -0.02236418 1.02755 0.7395214 -0.3054456 -0.777988
         [,50]     [,51]     [,52]     [,53]     [,54]      [,55]     [,56]
[1,] 0.7715704 -0.871004 -1.205544 0.9172839 0.8612597 -0.6712025 0.4954476
[2,] 0.7715704 -0.871004 -1.205544 0.9172839 0.8612597 -0.6712025 0.4954476
          [,57]      [,58]    [,59]     [,60]      [,61]     [,62]     [,63]
[1,] 0.08633414 -0.9500828 2.166611 -1.120223 0.02930265 0.4688248 -1.147519
[2,] 0.08633414 -0.9500828 2.166611 -1.120223 0.02930265 0.4688248 -1.147519
         [,64]        [,65]     [,66]      [,67]     [,68]    [,69]      [,70]
[1,] 0.6122414 -0.009628447 -1.404925 -0.8036454 -1.426167 1.687049 -0.5955333
[2,] 0.6122414 -0.009628447 -1.404925 -0.8036454 -1.426167 1.687049 -0.5955333
        [,71]      [,72]      [,73]    [,74]     [,75]    [,76]     [,77]
[1,] 0.647059 -0.3027378 -0.5949171 -0.17813 -1.303854 1.454947 0.1055789
[2,] 0.647059 -0.3027378 -0.5949171 -0.17813 -1.303854 1.454947 0.1055789
          [,78]     [,79]  [,80]    [,81]     [,82]    [,83]     [,84]    [,85]
[1,] -0.9949377 0.2702502 1.2687 2.215006 -1.893381 1.205122 -1.145304 1.037625
[2,] -0.9949377 0.2702502 1.2687 2.215006 -1.893381 1.205122 -1.145304 1.037625
         [,86]      [,87]     [,88]     [,89]     [,90]       [,91]     [,92]
[1,] -1.392426 -0.6168388 -0.270211 0.6589961 -1.041747 -0.01255657 0.3849045
[2,] -1.392426 -0.6168388 -0.270211 0.6589961 -1.041747 -0.01255657 0.3849045
         [,93]     [,94]     [,95]    [,96]     [,97]      [,98]      [,99]
[1,] 0.8270892 0.9359576 -1.842657 0.539692 0.1840358 -0.3548606 -0.9994418
[2,] 0.8270892 0.9359576 -1.842657 0.539692 0.1840358 -0.3548606 -0.9994418
         [,100]
[1,] -0.4908371
[2,] -0.4908371
> 
> 
> Max(tmp2)
[1] 3.245362
> Min(tmp2)
[1] -2.446327
> mean(tmp2)
[1] 0.01559622
> Sum(tmp2)
[1] 1.559622
> Var(tmp2)
[1] 1.079314
> 
> rowMeans(tmp2)
  [1] -1.583170022  1.087705321  0.617353724  0.263760162  0.663565322
  [6] -0.507027278  0.182476390  0.177874626 -0.640916370 -1.684965517
 [11]  0.972294111 -2.446327291  2.135998561 -0.523751399  0.862537261
 [16]  0.273624090 -0.835348864  0.091376840  0.092958821 -0.275609398
 [21]  0.622033098  0.351171062 -0.047684908 -0.287863264 -0.271751597
 [26] -0.519213479  1.508029526  1.556931693  0.099642168 -0.470764793
 [31] -2.143370787  0.324726454 -0.273014524  0.186041850 -0.935117067
 [36]  0.326142594 -0.168577961 -0.577722538  1.291443614  0.008337845
 [41]  1.125350345 -0.931930458 -0.315582906  1.904028341  0.519067426
 [46]  1.934337483  0.177538325  0.161692397  1.912072974  1.848001269
 [51] -0.268365229  2.311536244 -0.230221008  0.244747981 -0.822508308
 [56]  1.094918172  0.348970583 -0.761185866 -1.040655727 -0.100400188
 [61] -0.982379732  0.402319842  0.873603115 -0.029505057 -0.325930099
 [66] -0.503165769 -0.865178768  0.389463328  3.245361618  0.374982595
 [71] -0.587516315  0.725126988  0.298942753 -0.978834812 -0.008548049
 [76]  0.609436438  0.742141069  0.099093454  0.675895353 -1.210023703
 [81]  0.460363662 -0.563290804 -1.436743028 -2.292282952 -0.703604358
 [86] -1.239996154  0.016827269  0.981418759 -0.817628608 -0.435967049
 [91] -1.096127068 -0.721255958 -1.431717266  0.478811237  1.426531074
 [96] -0.874885048 -1.866968014 -0.749644780 -0.971167352  1.836423949
> rowSums(tmp2)
  [1] -1.583170022  1.087705321  0.617353724  0.263760162  0.663565322
  [6] -0.507027278  0.182476390  0.177874626 -0.640916370 -1.684965517
 [11]  0.972294111 -2.446327291  2.135998561 -0.523751399  0.862537261
 [16]  0.273624090 -0.835348864  0.091376840  0.092958821 -0.275609398
 [21]  0.622033098  0.351171062 -0.047684908 -0.287863264 -0.271751597
 [26] -0.519213479  1.508029526  1.556931693  0.099642168 -0.470764793
 [31] -2.143370787  0.324726454 -0.273014524  0.186041850 -0.935117067
 [36]  0.326142594 -0.168577961 -0.577722538  1.291443614  0.008337845
 [41]  1.125350345 -0.931930458 -0.315582906  1.904028341  0.519067426
 [46]  1.934337483  0.177538325  0.161692397  1.912072974  1.848001269
 [51] -0.268365229  2.311536244 -0.230221008  0.244747981 -0.822508308
 [56]  1.094918172  0.348970583 -0.761185866 -1.040655727 -0.100400188
 [61] -0.982379732  0.402319842  0.873603115 -0.029505057 -0.325930099
 [66] -0.503165769 -0.865178768  0.389463328  3.245361618  0.374982595
 [71] -0.587516315  0.725126988  0.298942753 -0.978834812 -0.008548049
 [76]  0.609436438  0.742141069  0.099093454  0.675895353 -1.210023703
 [81]  0.460363662 -0.563290804 -1.436743028 -2.292282952 -0.703604358
 [86] -1.239996154  0.016827269  0.981418759 -0.817628608 -0.435967049
 [91] -1.096127068 -0.721255958 -1.431717266  0.478811237  1.426531074
 [96] -0.874885048 -1.866968014 -0.749644780 -0.971167352  1.836423949
> rowVars(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
  [1] -1.583170022  1.087705321  0.617353724  0.263760162  0.663565322
  [6] -0.507027278  0.182476390  0.177874626 -0.640916370 -1.684965517
 [11]  0.972294111 -2.446327291  2.135998561 -0.523751399  0.862537261
 [16]  0.273624090 -0.835348864  0.091376840  0.092958821 -0.275609398
 [21]  0.622033098  0.351171062 -0.047684908 -0.287863264 -0.271751597
 [26] -0.519213479  1.508029526  1.556931693  0.099642168 -0.470764793
 [31] -2.143370787  0.324726454 -0.273014524  0.186041850 -0.935117067
 [36]  0.326142594 -0.168577961 -0.577722538  1.291443614  0.008337845
 [41]  1.125350345 -0.931930458 -0.315582906  1.904028341  0.519067426
 [46]  1.934337483  0.177538325  0.161692397  1.912072974  1.848001269
 [51] -0.268365229  2.311536244 -0.230221008  0.244747981 -0.822508308
 [56]  1.094918172  0.348970583 -0.761185866 -1.040655727 -0.100400188
 [61] -0.982379732  0.402319842  0.873603115 -0.029505057 -0.325930099
 [66] -0.503165769 -0.865178768  0.389463328  3.245361618  0.374982595
 [71] -0.587516315  0.725126988  0.298942753 -0.978834812 -0.008548049
 [76]  0.609436438  0.742141069  0.099093454  0.675895353 -1.210023703
 [81]  0.460363662 -0.563290804 -1.436743028 -2.292282952 -0.703604358
 [86] -1.239996154  0.016827269  0.981418759 -0.817628608 -0.435967049
 [91] -1.096127068 -0.721255958 -1.431717266  0.478811237  1.426531074
 [96] -0.874885048 -1.866968014 -0.749644780 -0.971167352  1.836423949
> rowMin(tmp2)
  [1] -1.583170022  1.087705321  0.617353724  0.263760162  0.663565322
  [6] -0.507027278  0.182476390  0.177874626 -0.640916370 -1.684965517
 [11]  0.972294111 -2.446327291  2.135998561 -0.523751399  0.862537261
 [16]  0.273624090 -0.835348864  0.091376840  0.092958821 -0.275609398
 [21]  0.622033098  0.351171062 -0.047684908 -0.287863264 -0.271751597
 [26] -0.519213479  1.508029526  1.556931693  0.099642168 -0.470764793
 [31] -2.143370787  0.324726454 -0.273014524  0.186041850 -0.935117067
 [36]  0.326142594 -0.168577961 -0.577722538  1.291443614  0.008337845
 [41]  1.125350345 -0.931930458 -0.315582906  1.904028341  0.519067426
 [46]  1.934337483  0.177538325  0.161692397  1.912072974  1.848001269
 [51] -0.268365229  2.311536244 -0.230221008  0.244747981 -0.822508308
 [56]  1.094918172  0.348970583 -0.761185866 -1.040655727 -0.100400188
 [61] -0.982379732  0.402319842  0.873603115 -0.029505057 -0.325930099
 [66] -0.503165769 -0.865178768  0.389463328  3.245361618  0.374982595
 [71] -0.587516315  0.725126988  0.298942753 -0.978834812 -0.008548049
 [76]  0.609436438  0.742141069  0.099093454  0.675895353 -1.210023703
 [81]  0.460363662 -0.563290804 -1.436743028 -2.292282952 -0.703604358
 [86] -1.239996154  0.016827269  0.981418759 -0.817628608 -0.435967049
 [91] -1.096127068 -0.721255958 -1.431717266  0.478811237  1.426531074
 [96] -0.874885048 -1.866968014 -0.749644780 -0.971167352  1.836423949
> 
> colMeans(tmp2)
[1] 0.01559622
> colSums(tmp2)
[1] 1.559622
> colVars(tmp2)
[1] 1.079314
> colSd(tmp2)
[1] 1.0389
> colMax(tmp2)
[1] 3.245362
> colMin(tmp2)
[1] -2.446327
> colMedians(tmp2)
[1] 0.01258256
> colRanges(tmp2)
          [,1]
[1,] -2.446327
[2,]  3.245362
> 
> 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]  1.5083893  4.6506166  1.8559389  8.8284402  2.9275345  0.1167529
 [7]  2.1067661 -3.5726897  8.2918953  4.5720232
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -0.6677884
[2,] -0.3990625
[3,] -0.2110392
[4,]  0.1141179
[5,]  2.8099130
> 
> rowApply(tmp,sum)
 [1] 3.8577507 2.8564920 5.1585743 4.2976528 9.2688297 0.3152049 1.9016976
 [8] 0.9950070 2.4285648 0.2058934
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    2    3    2    2    9    5    2    6    1    10
 [2,]    8    2    7    7    7    8   10    3    2     7
 [3,]    6    8    8    4    2    3    4    8    5     5
 [4,]   10    9    9    5   10    2    6    9    6     6
 [5,]    3    7   10    1    1    6    5    7    7     8
 [6,]    9    6    6    9    3    1    7    4    8     1
 [7,]    7    5    3   10    4    7    8    5    3     3
 [8,]    4    1    4    3    8    4    1    1    4     2
 [9,]    1   10    1    8    5   10    3   10   10     9
[10,]    5    4    5    6    6    9    9    2    9     4
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1] -1.22367482 -2.15605172  1.20237753  1.27718685  1.59287658  1.47119198
 [7]  1.27373993 -2.43918252  1.53330396  1.63242462 -1.96914061 -0.19404317
[13]  4.07395572 -4.76424757  0.29159300 -0.07126138 -1.50074778 -0.13132325
[19]  0.64761414  2.37532170
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.7618388
[2,] -0.7645275
[3,] -0.1547134
[4,]  0.5232016
[5,]  0.9342034
> 
> rowApply(tmp,sum)
[1]  2.215003  6.202926 -8.345103 -1.615230  4.464318
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]    7   14   18    2    6
[2,]   18    4    3    9    1
[3,]    3    6   20   20    8
[4,]    4   20    6   14   12
[5,]   19    9   10   12    9
> 
> 
> as.matrix(tmp)
           [,1]       [,2]       [,3]       [,4]       [,5]       [,6]
[1,] -0.1547134  1.5280599 -1.7090613 -1.4791462  1.8972010  0.8170164
[2,]  0.9342034 -0.9044952 -0.5578296  2.4745133  0.2822689  0.8645221
[3,]  0.5232016 -1.1905786  1.3593426 -0.8605828 -0.5537529 -0.8554307
[4,] -1.7618388 -0.3586442  2.3639024  0.6709456  0.1759056 -0.5206113
[5,] -0.7645275 -1.2303937 -0.2539766  0.4714570 -0.2087460  1.1656954
            [,7]       [,8]       [,9]      [,10]      [,11]      [,12]
[1,] -0.09870791 -0.3895611 -0.0861110  2.0030373 -0.6732632  0.4410245
[2,]  0.30022061 -0.2774812  0.4524011  0.9389216 -0.9562614 -1.2407241
[3,] -0.98067884 -1.3085029  0.3007265 -0.2811666 -1.5445995  0.3839637
[4,] -0.20861071 -1.8644768  0.3766000 -0.1233101  0.8658825  0.9936837
[5,]  2.26151678  1.4008396  0.4896874 -0.9050576  0.3391011 -0.7719910
          [,13]      [,14]      [,15]      [,16]      [,17]       [,18]
[1,]  1.4528993 -2.3179048 -1.8847604 -0.1388414  0.9612158  0.01901885
[2,]  2.0287682 -0.6372622  0.3465262  0.9409375 -0.4737178  1.44343759
[3,] -0.1030551 -1.0347995 -0.5484447 -0.5649781  0.5250749 -0.70179228
[4,]  1.6698973 -0.3594512  0.9561076 -1.5679740 -1.6303354 -1.31798127
[5,] -0.9745539 -0.4148298  1.4221643  1.2595945 -0.8829854  0.42599385
          [,19]      [,20]
[1,]  0.5468021  1.4807981
[2,] -0.9898532  1.2338303
[3,] -0.3817638 -0.5272859
[4,]  0.8336895 -0.8086110
[5,]  0.6387396  0.9965901
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  800  bytes.
> 
> 
> 
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size:  5 5 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  654  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  566  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  480  bytes.
> 
> 
> rm(tmp)
> 
> 
> ###
> ### Testing colnames and rownames
> ###
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> 
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> tmp["row1",]
          col1       col2     col3      col4       col5      col6      col7
row1 0.1162249 -0.8487981 1.143377 -0.942462 -0.1313287 0.1010205 -1.475458
           col8      col9      col10      col11      col12     col13      col14
row1 -0.2852802 -2.317861 -0.4068345 -0.4844734 -0.2166555 -1.282698 -0.6666089
          col15     col16     col17       col18    col19     col20
row1 -0.1720226 -1.461507 -1.083061 -0.02294347 1.043818 -0.321076
> tmp[,"col10"]
            col10
row1 -0.406834540
row2 -0.001671575
row3 -2.743822888
row4 -1.119432432
row5  0.948222765
> tmp[c("row1","row5"),]
          col1       col2      col3       col4       col5       col6       col7
row1 0.1162249 -0.8487981 1.1433771 -0.9424620 -0.1313287  0.1010205 -1.4754582
row5 0.3032657 -1.8502477 0.4920107 -0.8401545  0.8282328 -0.9687764  0.1224417
           col8       col9      col10      col11      col12     col13
row1 -0.2852802 -2.3178607 -0.4068345 -0.4844734 -0.2166555 -1.282698
row5  0.2781013 -0.3023013  0.9482228 -0.6065927 -0.1087187 -2.420122
           col14      col15     col16       col17       col18     col19
row1 -0.66660887 -0.1720226 -1.461507 -1.08306083 -0.02294347 1.0438180
row5 -0.02096362  0.9027950  1.454790 -0.05829389 -0.95108813 0.2214996
          col20
row1 -0.3210760
row5  0.7202403
> tmp[,c("col6","col20")]
           col6      col20
row1  0.1010205 -0.3210760
row2  2.0863784 -0.8233180
row3 -0.1913869  1.8530269
row4  0.1168676 -0.2709252
row5 -0.9687764  0.7202403
> tmp[c("row1","row5"),c("col6","col20")]
           col6      col20
row1  0.1010205 -0.3210760
row5 -0.9687764  0.7202403
> 
> 
> 
> 
> 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 49.07113 49.12514 50.42635 51.46402 50.39781 105.3307 49.38677 49.10163
        col9    col10    col11    col12    col13    col14    col15    col16
row1 50.3038 49.60054 48.84578 48.53622 51.44495 49.74758 48.41401 51.04607
        col17    col18    col19   col20
row1 49.67592 49.50556 49.64118 104.855
> tmp[,"col10"]
        col10
row1 49.60054
row2 31.16970
row3 29.91349
row4 29.04098
row5 49.90242
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 49.07113 49.12514 50.42635 51.46402 50.39781 105.3307 49.38677 49.10163
row5 48.67506 50.40024 50.74577 47.71117 50.36327 104.1525 49.24261 51.89402
         col9    col10    col11    col12    col13    col14    col15    col16
row1 50.30380 49.60054 48.84578 48.53622 51.44495 49.74758 48.41401 51.04607
row5 50.47166 49.90242 49.51140 48.99320 51.63952 48.55189 50.98225 50.68126
        col17    col18    col19    col20
row1 49.67592 49.50556 49.64118 104.8550
row5 47.39910 50.97983 51.06878 104.6616
> tmp[,c("col6","col20")]
          col6     col20
row1 105.33068 104.85505
row2  74.87252  75.76282
row3  74.41380  75.89901
row4  76.15219  75.68277
row5 104.15247 104.66155
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 105.3307 104.8550
row5 104.1525 104.6616
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 105.3307 104.8550
row5 104.1525 104.6616
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,]  0.7344616
[2,]  0.1572993
[3,] -1.5430378
[4,]  0.6724984
[5,] -0.3592926
> tmp[,c("col17","col7")]
           col17        col7
[1,] -0.68926705  0.24286738
[2,]  0.79681377 -0.92572036
[3,]  0.15692469 -1.05188856
[4,]  0.05925496 -0.81872590
[5,]  0.40086598  0.08780571
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
           col6       col20
[1,]  0.9812965 -1.01387738
[2,] -1.0167677  0.08766847
[3,] -0.8053764 -0.81229362
[4,]  1.5435264  1.59315492
[5,] -0.7010947  0.65307525
> subBufferedMatrix(tmp,1,c("col6"))[,1]
          col1
[1,] 0.9812965
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
           col6
[1,]  0.9812965
[2,] -1.0167677
> 
> 
> 
> 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 -2.3215368 -0.7740534 -1.172970 -0.1289311  1.136408 0.8639297  0.04219201
row1 -0.2082514 -1.6627740  1.478631 -1.3537274 -1.044518 0.3549011 -1.37846933
           [,8]      [,9]     [,10]    [,11]     [,12]     [,13]     [,14]
row3  0.8115768 -0.516927  0.419511 1.052297 0.2374094 -1.257615 0.2288823
row1 -0.6852716  1.327880 -1.704550 2.139482 0.6826252 -1.179010 0.5602661
          [,15]    [,16]     [,17]    [,18]    [,19]       [,20]
row3  1.3900246 1.075769 0.3901419 2.109877 1.088752 -0.42196362
row1 -0.2118889 2.059858 0.8725948 1.434681 0.617979  0.09892193
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
          [,1]      [,2]      [,3]      [,4]     [,5]       [,6]       [,7]
row2 0.5672411 0.3065943 0.4155484 -2.140922 1.553069 -0.5919951 -0.2919361
           [,8]       [,9]    [,10]
row2 -0.5233044 -0.2759385 1.512434
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
          [,1]       [,2]      [,3]      [,4]      [,5]     [,6]       [,7]
row5 0.8305194 -0.5439588 -1.086714 0.6067971 -1.214108 1.147301 -0.1432065
           [,8]      [,9]     [,10]   [,11]     [,12]      [,13]     [,14]
row5 -0.5473357 0.1432544 -1.057114 3.02484 -0.018228 -0.6245808 0.6243056
        [,15]      [,16]    [,17]      [,18]    [,19]     [,20]
row5 0.919645 0.04820785 1.037796 0.04044848 2.442351 0.4237901
> 
> 
> 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: 0x1ae9a3a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b444aac00d"
 [2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b463ccb22" 
 [3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b4274746da"
 [4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b42f858117"
 [5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b4a17e5f8" 
 [6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b436a17d44"
 [7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b4664e1328"
 [8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b463f2f633"
 [9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b45af072cf"
[10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b4365ab042"
[11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b44db63d20"
[12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b4302087d6"
[13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b450923518"
[14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b455a5168d"
[15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f91b4446c3f6d"
> 
> 
> ### 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: 0x189f9910>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x189f9910>
Warning message:
In dir.create(new.directory) :
  '/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x189f9910>
> rowMedians(tmp)
  [1] -0.294848448 -0.024905735 -0.262870489 -0.612931636 -0.327724007
  [6] -0.413768952 -0.067347788  0.640575280  0.685553354  0.195027743
 [11] -0.125547222  0.085048364 -0.148665130  0.326959557  0.115203695
 [16] -0.183092196  0.511836062 -0.137820786 -0.223576230 -0.295096365
 [21]  0.114484197 -0.010636617 -0.163868491  0.034903509  0.075347382
 [26] -0.162552371 -0.342879977 -0.383699549 -0.222099684  0.137287886
 [31] -0.106183509 -0.190990117  0.162047865  0.032861769 -0.254477038
 [36]  0.053968192  0.058744303 -0.044734179  0.037511304 -0.551820008
 [41]  0.042517024  0.444271771 -0.119167206  0.126749754 -0.141111853
 [46] -0.127528273 -0.203815011 -0.181763255  0.227007098 -0.204913538
 [51] -0.068053807 -0.157090273 -0.415329291  0.034183592 -0.311052156
 [56] -0.933243573  0.140244347 -0.053666598  0.103533784 -0.274182968
 [61]  0.341851474  0.274440760  0.319708966  0.187673204 -0.447402714
 [66] -0.002004461 -0.546029386  0.572626301  0.598444231 -0.560813420
 [71] -0.063347044 -0.109970233 -0.417494047 -0.168823081 -0.501272687
 [76] -0.085813959 -0.150680717  0.135087152 -0.415382095  0.181228210
 [81] -0.288152183  0.561175943 -0.292302636  0.215322287 -0.412495507
 [86]  0.165417945  0.388824887 -0.001898483  0.098284408  0.156495787
 [91] -0.016301845 -0.269594704  0.286919383 -0.347826817  0.630488524
 [96]  0.241445227  0.240150398  0.038415792  0.108482441  1.036136465
[101] -0.116021662  0.118430120 -0.217345675  0.517915722 -0.620423774
[106]  0.515805360  0.247008349 -0.018075755  0.471424555  0.041660452
[111] -0.416853870 -0.191191686  0.303508633 -0.239976948  0.290518306
[116]  0.005972075 -0.058340504 -0.607220422 -0.031342542 -0.246713449
[121] -0.021724217 -0.546527526  0.376760118  0.341520886 -0.241935092
[126]  0.004002066  0.775404340  0.182090128 -0.107849670 -0.313961569
[131] -0.012101278  0.480414442 -0.728832343 -0.081228711  0.369584559
[136]  0.294969042 -0.484467921 -0.182575065 -0.180937384  0.423943166
[141] -0.021456217 -0.049842885  0.386480497 -0.735032923  0.190057484
[146] -0.437093022 -0.214076569 -0.465724524 -0.318814557 -0.550619261
[151]  0.367408955 -0.220773789  0.208426091 -0.122622102  0.523610351
[156] -0.166485317  0.096835059 -0.162086472  0.662450374  0.264946507
[161] -0.091924577  0.314476940  0.221198626 -0.487227623  0.443298530
[166]  0.403041970 -0.285943139 -0.182328018  0.073656714  0.027543639
[171]  0.020109651 -0.225778918 -0.073854673  0.067756294 -0.205676987
[176] -0.033052437  0.474075760  0.193130870  0.405277009 -0.151160936
[181] -0.197149344 -0.130784529 -0.192379173 -0.344756677  0.298097957
[186] -0.021440062  0.076571721 -0.040868353  0.245767954  0.130611436
[191] -0.145270090  0.261630806 -0.245108145  0.278403145 -0.117447293
[196]  0.112158838  0.607250046 -0.652032188 -0.278974718  0.012929812
[201]  0.102978082  0.020281803  0.528830162 -0.122597430 -0.031270986
[206] -0.267162765 -0.051273574 -0.011240765 -0.194255435 -0.297265344
[211]  0.220156591 -0.104378294  0.462880970 -0.360780357  0.266803932
[216]  0.375395569  0.335982466 -0.548493312  0.245467142 -0.244579359
[221] -0.027843527  0.017776221  0.628438086 -0.101854708  0.118699652
[226] -0.596125197 -0.529550099  0.668565298 -0.474880227  0.124986731
> 
> proc.time()
   user  system elapsed 
  1.973   0.869   2.863 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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: 0x3a905ed0>
> .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: 0x3a905ed0>
> .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: 0x3a905ed0>
> .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: 0x3a905ed0>
> 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: 0x39352fb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39352fb0>
> .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: 0x39352fb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39352fb0>
> .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: 0x39352fb0>
> 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: 0x391ac990>
> .Call("R_bm_AddColumn",P)
<pointer: 0x391ac990>
> .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: 0x391ac990>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x391ac990>
> .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: 0x391ac990>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x391ac990>
> .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: 0x391ac990>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x391ac990>
> .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: 0x391ac990>
> 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: 0x3bb0bcf0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x3bb0bcf0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3bb0bcf0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3bb0bcf0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2f92181e7987d9" "BufferedMatrixFile2f92188a177fa" 
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2f92181e7987d9" "BufferedMatrixFile2f92188a177fa" 
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x398f04f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x398f04f0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x398f04f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x398f04f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x398f04f0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x398f04f0>
> .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: 0x3a1ea180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3a1ea180>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x3a1ea180>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x3a1ea180>
> 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: 0x3a1ee880>
> .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: 0x3a1ee880>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.337   0.037   0.359 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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 
  0.329   0.038   0.351 

Example timings