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This page was generated on 2024-03-27 11:35:43 -0400 (Wed, 27 Mar 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 22.04.3 LTS)x86_644.3.3 (2024-02-29) -- "Angel Food Cake" 4667
palomino4Windows Server 2022 Datacenterx644.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" 4403
merida1macOS 12.7.1 Montereyx86_644.3.3 (2024-02-29) -- "Angel Food Cake" 4426
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 246/2266HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.66.0  (landing page)
Ben Bolstad
Snapshot Date: 2024-03-25 14:05:07 -0400 (Mon, 25 Mar 2024)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: RELEASE_3_18
git_last_commit: 1feca44
git_last_commit_date: 2023-10-24 09:37:50 -0400 (Tue, 24 Oct 2023)
nebbiolo2Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino4Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.1 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.1 Ventura / arm64see weekly results here

CHECK results for BufferedMatrix on nebbiolo2


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

raw results


Summary

Package: BufferedMatrix
Version: 1.66.0
Command: /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings BufferedMatrix_1.66.0.tar.gz
StartedAt: 2024-03-25 20:36:14 -0400 (Mon, 25 Mar 2024)
EndedAt: 2024-03-25 20:36:36 -0400 (Mon, 25 Mar 2024)
EllapsedTime: 22.0 seconds
RetCode: 0
Status:   OK  
CheckDir: BufferedMatrix.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings BufferedMatrix_1.66.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.66.0’
* 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 (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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
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 in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
  ‘BufferedMatrix.Rnw’... OK
 OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.



Installation output

BufferedMatrix.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.18-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
gcc -I"/home/biocbuild/bbs-3.18-bioc/R/include" -DNDEBUG   -I/usr/local/include    -fpic  -g -O2  -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.18-bioc/R/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/bbs-3.18-bioc/R/include" -DNDEBUG   -I/usr/local/include    -fpic  -g -O2  -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.18-bioc/R/include" -DNDEBUG   -I/usr/local/include    -fpic  -g -O2  -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.18-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.18-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.18-bioc/R/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 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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 
  0.271   0.020   0.281 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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-3.18-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 457988 24.5     983265 52.6   650542 34.8
Vcells 843172  6.5    8388608 64.0  2057435 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] "Mon Mar 25 20:36:29 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] "Mon Mar 25 20:36:29 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: 0x563e985ec010>
> 
> 
> 
> 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] "Mon Mar 25 20:36:29 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] "Mon Mar 25 20:36:29 2024"
> 
> ColMode(tmp2)
<pointer: 0x563e985ec010>
> 
> 
> 
> ### 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,] 100.3770283 -0.1718021 -0.6510584  0.7580530
[2,]   1.0352393  0.2642558 -1.3848437 -1.3842744
[3,]   0.4940285  1.0262911  1.3044409  1.8273867
[4,]  -0.4354030  1.0765401 -0.5673600 -0.1355474
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.18-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,] 100.3770283 0.1718021 0.6510584 0.7580530
[2,]   1.0352393 0.2642558 1.3848437 1.3842744
[3,]   0.4940285 1.0262911 1.3044409 1.8273867
[4,]   0.4354030 1.0765401 0.5673600 0.1355474
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.18-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,] 10.0188337 0.4144902 0.8068819 0.8706624
[2,]  1.0174671 0.5140582 1.1767938 1.1765519
[3,]  0.7028716 1.0130603 1.1421212 1.3518087
[4,]  0.6598508 1.0375645 0.7532330 0.3681676
> 
> 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-3.18-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,] 225.56537 29.31670 33.71988 34.46468
[2,]  36.20991 30.40484 38.15278 38.14979
[3,]  32.52274 36.15689 37.72565 40.34547
[4,]  32.03391 36.45219 33.09969 28.81722
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x563e989b26a0>
> exp(tmp5)
<pointer: 0x563e989b26a0>
> log(tmp5,2)
<pointer: 0x563e989b26a0>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.4848
> Min(tmp5)
[1] 54.17032
> mean(tmp5)
[1] 72.04182
> Sum(tmp5)
[1] 14408.36
> Var(tmp5)
[1] 860.4563
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 88.42796 69.55181 70.28102 67.04676 69.84777 69.87748 71.53202 72.57846
 [9] 71.40748 69.86746
> rowSums(tmp5)
 [1] 1768.559 1391.036 1405.620 1340.935 1396.955 1397.550 1430.640 1451.569
 [9] 1428.150 1397.349
> rowVars(tmp5)
 [1] 8112.49010   61.30210   40.89514   46.10895   75.47960   71.66690
 [7]   63.80768   55.46630   68.51259   81.75202
> rowSd(tmp5)
 [1] 90.069363  7.829566  6.394931  6.790357  8.687900  8.465631  7.987971
 [8]  7.447570  8.277233  9.041682
> rowMax(tmp5)
 [1] 469.48475  83.22881  83.97382  79.33066  83.62566  88.27489  84.66642
 [8]  86.58130  85.62783  87.26893
> rowMin(tmp5)
 [1] 55.99556 57.90885 54.35508 54.17032 56.33279 54.76191 54.59723 58.77009
 [9] 58.06984 55.79092
> 
> colMeans(tmp5)
 [1] 111.31450  66.43163  74.26558  70.48851  71.18415  75.37658  67.07808
 [8]  71.54966  68.34590  71.57513  67.17618  70.00112  70.40103  70.84617
[15]  65.68906  72.25613  66.65988  73.88603  65.74230  70.56881
> colSums(tmp5)
 [1] 1113.1450  664.3163  742.6558  704.8851  711.8415  753.7658  670.7808
 [8]  715.4966  683.4590  715.7513  671.7618  700.0112  704.0103  708.4617
[15]  656.8906  722.5613  666.5988  738.8603  657.4230  705.6881
> colVars(tmp5)
 [1] 15884.55729    50.60888    48.77292    72.28283    55.13292    78.74995
 [7]    36.56775    74.75652    26.74727    34.06804    68.69493    55.73026
[13]   116.89779    53.21933    33.25328    60.74875    70.90355    76.53052
[19]    47.14942   104.30174
> colSd(tmp5)
 [1] 126.033953   7.113992   6.983761   8.501931   7.425155   8.874117
 [7]   6.047128   8.646186   5.171777   5.836784   8.288241   7.465270
[13]  10.811928   7.295158   5.766566   7.794148   8.420424   8.748172
[19]   6.866543  10.212823
> colMax(tmp5)
 [1] 469.48475  75.87045  85.62783  83.97382  82.49395  87.26893  75.68953
 [8]  89.92201  78.80052  80.26869  78.71035  80.59341  85.58428  85.22966
[15]  77.22257  83.62566  83.22881  88.27489  77.08615  86.58130
> colMin(tmp5)
 [1] 59.24665 54.76191 65.09357 59.23973 60.11332 62.22573 58.77009 58.06984
 [9] 60.89745 63.52510 54.17032 55.79092 56.49951 60.27770 57.85856 57.90885
[17] 54.35508 59.03386 56.33279 54.59723
> 
> 
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
> 
> 
> which.row <- sample(1:10,1,replace=TRUE)
> which.col  <- sample(1:20,1,replace=TRUE)
> 
> tmp5[which.row,which.col] <- NA
> 
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
> 
> rowMeans(tmp5)
 [1] 88.42796 69.55181 70.28102 67.04676 69.84777 69.87748       NA 72.57846
 [9] 71.40748 69.86746
> rowSums(tmp5)
 [1] 1768.559 1391.036 1405.620 1340.935 1396.955 1397.550       NA 1451.569
 [9] 1428.150 1397.349
> rowVars(tmp5)
 [1] 8112.49010   61.30210   40.89514   46.10895   75.47960   71.66690
 [7]   64.77497   55.46630   68.51259   81.75202
> rowSd(tmp5)
 [1] 90.069363  7.829566  6.394931  6.790357  8.687900  8.465631  8.048290
 [8]  7.447570  8.277233  9.041682
> rowMax(tmp5)
 [1] 469.48475  83.22881  83.97382  79.33066  83.62566  88.27489        NA
 [8]  86.58130  85.62783  87.26893
> rowMin(tmp5)
 [1] 55.99556 57.90885 54.35508 54.17032 56.33279 54.76191       NA 58.77009
 [9] 58.06984 55.79092
> 
> colMeans(tmp5)
 [1] 111.31450  66.43163  74.26558  70.48851  71.18415  75.37658  67.07808
 [8]  71.54966  68.34590        NA  67.17618  70.00112  70.40103  70.84617
[15]  65.68906  72.25613  66.65988  73.88603  65.74230  70.56881
> colSums(tmp5)
 [1] 1113.1450  664.3163  742.6558  704.8851  711.8415  753.7658  670.7808
 [8]  715.4966  683.4590        NA  671.7618  700.0112  704.0103  708.4617
[15]  656.8906  722.5613  666.5988  738.8603  657.4230  705.6881
> colVars(tmp5)
 [1] 15884.55729    50.60888    48.77292    72.28283    55.13292    78.74995
 [7]    36.56775    74.75652    26.74727          NA    68.69493    55.73026
[13]   116.89779    53.21933    33.25328    60.74875    70.90355    76.53052
[19]    47.14942   104.30174
> colSd(tmp5)
 [1] 126.033953   7.113992   6.983761   8.501931   7.425155   8.874117
 [7]   6.047128   8.646186   5.171777         NA   8.288241   7.465270
[13]  10.811928   7.295158   5.766566   7.794148   8.420424   8.748172
[19]   6.866543  10.212823
> colMax(tmp5)
 [1] 469.48475  75.87045  85.62783  83.97382  82.49395  87.26893  75.68953
 [8]  89.92201  78.80052        NA  78.71035  80.59341  85.58428  85.22966
[15]  77.22257  83.62566  83.22881  88.27489  77.08615  86.58130
> colMin(tmp5)
 [1] 59.24665 54.76191 65.09357 59.23973 60.11332 62.22573 58.77009 58.06984
 [9] 60.89745       NA 54.17032 55.79092 56.49951 60.27770 57.85856 57.90885
[17] 54.35508 59.03386 56.33279 54.59723
> 
> Max(tmp5,na.rm=TRUE)
[1] 469.4848
> Min(tmp5,na.rm=TRUE)
[1] 54.17032
> mean(tmp5,na.rm=TRUE)
[1] 72.01102
> Sum(tmp5,na.rm=TRUE)
[1] 14330.19
> Var(tmp5,na.rm=TRUE)
[1] 864.6114
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 88.42796 69.55181 70.28102 67.04676 69.84777 69.87748 71.18260 72.57846
 [9] 71.40748 69.86746
> rowSums(tmp5,na.rm=TRUE)
 [1] 1768.559 1391.036 1405.620 1340.935 1396.955 1397.550 1352.469 1451.569
 [9] 1428.150 1397.349
> rowVars(tmp5,na.rm=TRUE)
 [1] 8112.49010   61.30210   40.89514   46.10895   75.47960   71.66690
 [7]   64.77497   55.46630   68.51259   81.75202
> rowSd(tmp5,na.rm=TRUE)
 [1] 90.069363  7.829566  6.394931  6.790357  8.687900  8.465631  8.048290
 [8]  7.447570  8.277233  9.041682
> rowMax(tmp5,na.rm=TRUE)
 [1] 469.48475  83.22881  83.97382  79.33066  83.62566  88.27489  84.66642
 [8]  86.58130  85.62783  87.26893
> rowMin(tmp5,na.rm=TRUE)
 [1] 55.99556 57.90885 54.35508 54.17032 56.33279 54.76191 54.59723 58.77009
 [9] 58.06984 55.79092
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.31450  66.43163  74.26558  70.48851  71.18415  75.37658  67.07808
 [8]  71.54966  68.34590  70.84225  67.17618  70.00112  70.40103  70.84617
[15]  65.68906  72.25613  66.65988  73.88603  65.74230  70.56881
> colSums(tmp5,na.rm=TRUE)
 [1] 1113.1450  664.3163  742.6558  704.8851  711.8415  753.7658  670.7808
 [8]  715.4966  683.4590  637.5803  671.7618  700.0112  704.0103  708.4617
[15]  656.8906  722.5613  666.5988  738.8603  657.4230  705.6881
> colVars(tmp5,na.rm=TRUE)
 [1] 15884.55729    50.60888    48.77292    72.28283    55.13292    78.74995
 [7]    36.56775    74.75652    26.74727    32.28401    68.69493    55.73026
[13]   116.89779    53.21933    33.25328    60.74875    70.90355    76.53052
[19]    47.14942   104.30174
> colSd(tmp5,na.rm=TRUE)
 [1] 126.033953   7.113992   6.983761   8.501931   7.425155   8.874117
 [7]   6.047128   8.646186   5.171777   5.681902   8.288241   7.465270
[13]  10.811928   7.295158   5.766566   7.794148   8.420424   8.748172
[19]   6.866543  10.212823
> colMax(tmp5,na.rm=TRUE)
 [1] 469.48475  75.87045  85.62783  83.97382  82.49395  87.26893  75.68953
 [8]  89.92201  78.80052  80.26869  78.71035  80.59341  85.58428  85.22966
[15]  77.22257  83.62566  83.22881  88.27489  77.08615  86.58130
> colMin(tmp5,na.rm=TRUE)
 [1] 59.24665 54.76191 65.09357 59.23973 60.11332 62.22573 58.77009 58.06984
 [9] 60.89745 63.52510 54.17032 55.79092 56.49951 60.27770 57.85856 57.90885
[17] 54.35508 59.03386 56.33279 54.59723
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 88.42796 69.55181 70.28102 67.04676 69.84777 69.87748      NaN 72.57846
 [9] 71.40748 69.86746
> rowSums(tmp5,na.rm=TRUE)
 [1] 1768.559 1391.036 1405.620 1340.935 1396.955 1397.550    0.000 1451.569
 [9] 1428.150 1397.349
> rowVars(tmp5,na.rm=TRUE)
 [1] 8112.49010   61.30210   40.89514   46.10895   75.47960   71.66690
 [7]         NA   55.46630   68.51259   81.75202
> rowSd(tmp5,na.rm=TRUE)
 [1] 90.069363  7.829566  6.394931  6.790357  8.687900  8.465631        NA
 [8]  7.447570  8.277233  9.041682
> rowMax(tmp5,na.rm=TRUE)
 [1] 469.48475  83.22881  83.97382  79.33066  83.62566  88.27489        NA
 [8]  86.58130  85.62783  87.26893
> rowMin(tmp5,na.rm=TRUE)
 [1] 55.99556 57.90885 54.35508 54.17032 56.33279 54.76191       NA 58.77009
 [9] 58.06984 55.79092
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 116.31405  66.15504  73.23455  71.73837  70.23037  74.93328  66.12125
 [8]  71.97890  68.48028       NaN  66.03954  70.26034  68.81599  71.42160
[15]  65.89221  72.72129  66.21340  73.75131  64.48187  72.34343
> colSums(tmp5,na.rm=TRUE)
 [1] 1046.8265  595.3954  659.1109  645.6453  632.0734  674.3995  595.0913
 [8]  647.8101  616.3225    0.0000  594.3558  632.3430  619.3439  642.7944
[15]  593.0299  654.4916  595.9206  663.7618  580.3368  651.0909
> colVars(tmp5,na.rm=TRUE)
 [1] 17588.92710    56.07437    42.91048    63.74388    51.79056    86.38296
 [7]    30.83913    82.02828    29.88754          NA    62.74719    61.94063
[13]   103.24595    56.14671    36.94566    65.90820    77.52387    85.89265
[19]    35.17046    81.91009
> colSd(tmp5,na.rm=TRUE)
 [1] 132.623253   7.488282   6.550609   7.983977   7.196566   9.294243
 [7]   5.553299   9.056946   5.466950         NA   7.921312   7.870237
[13]  10.161002   7.493111   6.078295   8.118387   8.804764   9.267829
[19]   5.930469   9.050420
> colMax(tmp5,na.rm=TRUE)
 [1] 469.48475  75.87045  85.62783  83.97382  82.49395  87.26893  74.31362
 [8]  89.92201  78.80052      -Inf  78.71035  80.59341  85.58428  85.22966
[15]  77.22257  83.62566  83.22881  88.27489  73.90865  86.58130
> colMin(tmp5,na.rm=TRUE)
 [1] 59.24665 54.76191 65.09357 59.97928 60.11332 62.22573 58.77009 58.06984
 [9] 60.89745      Inf 54.17032 55.79092 56.49951 60.27770 57.85856 57.90885
[17] 54.35508 59.03386 56.33279 56.93028
> 
> 
> 
> 
> 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] 159.8961 136.4030 157.4480 285.8796 202.3999 206.0569 172.1108 201.8115
 [9] 185.2543 208.1282
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 159.8961 136.4030 157.4480 285.8796 202.3999 206.0569 172.1108 201.8115
 [9] 185.2543 208.1282
> 
> 
> 
> 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] -1.421085e-13  5.684342e-14  8.526513e-14  2.273737e-13  0.000000e+00
 [6] -5.684342e-14 -1.705303e-13  0.000000e+00 -1.136868e-13 -2.273737e-13
[11] -5.684342e-14 -5.684342e-14 -2.273737e-13 -8.526513e-14 -1.705303e-13
[16]  5.684342e-14 -5.684342e-14 -5.684342e-14  1.421085e-14  0.000000e+00
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## making sure these things agree
> ##
> ## first when there is no NA
> 
> 
> 
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+ 
+   if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Max")
+   }
+   
+ 
+   if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Min")
+   }
+ 
+ 
+   if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+ 
+     cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+     cat(sum(r.matrix,na.rm=TRUE),"\n")
+     cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+     
+     stop("No agreement in Sum")
+   }
+   
+   if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+     stop("No agreement in mean")
+   }
+   
+   
+   if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+     stop("No agreement in Var")
+   }
+   
+   
+ 
+   if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowMeans")
+   }
+   
+   
+   if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colMeans")
+   }
+   
+   
+   if(any(abs(rowSums(buff.matrix,na.rm=TRUE)  -  apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in rowSums")
+   }
+   
+   
+   if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colSums")
+   }
+   
+   ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when 
+   ### computing variance
+   my.Var <- function(x,na.rm=FALSE){
+    if (all(is.na(x))){
+      return(NA)
+    } else {
+      var(x,na.rm=na.rm)
+    }
+ 
+   }
+   
+   if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+   
+   
+   if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+ 
+ 
+   if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+ 
+   if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+   
+   
+   if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+   
+ 
+   if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+ 
+   if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMedian")
+   }
+ 
+   if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colRanges")
+   }
+ 
+ 
+   
+ }
> 
> 
> 
> 
> 
> 
> 
> 
> 
> for (rep in 1:20){
+   copymatrix <- matrix(rnorm(200,150,15),10,20)
+   
+   tmp5[1:10,1:20] <- copymatrix
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ## now lets assign some NA values and check agreement
+ 
+   which.row <- sample(1:10,1,replace=TRUE)
+   which.col  <- sample(1:20,1,replace=TRUE)
+   
+   cat(which.row," ",which.col,"\n")
+   
+   tmp5[which.row,which.col] <- NA
+   copymatrix[which.row,which.col] <- NA
+   
+   agree.checks(tmp5,copymatrix)
+ 
+   ## make an entire row NA
+   tmp5[which.row,] <- NA
+   copymatrix[which.row,] <- NA
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ### also make an entire col NA
+   tmp5[,which.col] <- NA
+   copymatrix[,which.col] <- NA
+ 
+   agree.checks(tmp5,copymatrix)
+ 
+   ### now make 1 element non NA with NA in the rest of row and column
+ 
+   tmp5[which.row,which.col] <- rnorm(1,150,15)
+   copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+ 
+   agree.checks(tmp5,copymatrix)
+ }
2   5 
3   9 
3   7 
3   2 
2   15 
5   16 
1   10 
6   6 
6   3 
5   16 
3   13 
3   10 
9   11 
8   9 
7   5 
9   2 
2   7 
9   6 
6   20 
1   10 
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] 3.226733
> Min(tmp)
[1] -2.100497
> mean(tmp)
[1] -0.09820297
> Sum(tmp)
[1] -9.820297
> Var(tmp)
[1] 1.221796
> 
> rowMeans(tmp)
[1] -0.09820297
> rowSums(tmp)
[1] -9.820297
> rowVars(tmp)
[1] 1.221796
> rowSd(tmp)
[1] 1.105349
> rowMax(tmp)
[1] 3.226733
> rowMin(tmp)
[1] -2.100497
> 
> colMeans(tmp)
  [1]  0.162567214 -0.584307739  0.047649531 -0.737198336 -0.071963094
  [6]  0.188574344  0.358329647 -0.721316319 -0.054422256 -0.270622704
 [11]  0.452081369 -0.023421766  0.702353684 -1.150030262 -0.213145122
 [16]  0.232710485 -2.100497229 -0.751190650  0.545988237  0.140422952
 [21] -1.080085905 -0.487232404 -1.371708934 -0.221604267 -1.387604624
 [26] -0.200438726 -1.936406867 -1.234290660  2.544334543 -0.107207423
 [31]  2.074731230  1.697285682 -0.173000258 -0.707881780 -1.097850330
 [36] -0.089012188  2.507008275  0.180777640  1.762682406 -0.567730901
 [41] -0.600425610  1.174497663 -0.339569523 -0.219322053 -0.486937405
 [46]  0.541565618  0.556263163  0.064808342 -0.617065995  0.288734429
 [51]  0.374695305  0.690402508  1.765563543 -0.708822799  0.248101130
 [56] -0.725156081 -1.877588842 -2.082069766  0.889095691  0.034283053
 [61]  2.448819929  1.410693159  0.209752301 -0.812222727 -0.495624387
 [66]  0.398531683 -0.049089680 -1.593120420  0.382034090 -1.753390028
 [71] -1.152228009  0.282701202 -1.213459973  0.699091868 -0.154305677
 [76]  1.198569287  0.195065523 -1.969420599 -1.462482993  1.856936872
 [81] -0.004221221 -0.078423346  0.519020022 -1.749714841 -0.091729516
 [86] -0.669304723 -0.407831893 -2.036644009 -1.733519947 -0.815702611
 [91] -0.957140135  3.226733302  0.916653055 -0.747107882  0.867019014
 [96] -0.012904518 -0.006320283 -0.846846173 -0.936923738  2.089381771
> colSums(tmp)
  [1]  0.162567214 -0.584307739  0.047649531 -0.737198336 -0.071963094
  [6]  0.188574344  0.358329647 -0.721316319 -0.054422256 -0.270622704
 [11]  0.452081369 -0.023421766  0.702353684 -1.150030262 -0.213145122
 [16]  0.232710485 -2.100497229 -0.751190650  0.545988237  0.140422952
 [21] -1.080085905 -0.487232404 -1.371708934 -0.221604267 -1.387604624
 [26] -0.200438726 -1.936406867 -1.234290660  2.544334543 -0.107207423
 [31]  2.074731230  1.697285682 -0.173000258 -0.707881780 -1.097850330
 [36] -0.089012188  2.507008275  0.180777640  1.762682406 -0.567730901
 [41] -0.600425610  1.174497663 -0.339569523 -0.219322053 -0.486937405
 [46]  0.541565618  0.556263163  0.064808342 -0.617065995  0.288734429
 [51]  0.374695305  0.690402508  1.765563543 -0.708822799  0.248101130
 [56] -0.725156081 -1.877588842 -2.082069766  0.889095691  0.034283053
 [61]  2.448819929  1.410693159  0.209752301 -0.812222727 -0.495624387
 [66]  0.398531683 -0.049089680 -1.593120420  0.382034090 -1.753390028
 [71] -1.152228009  0.282701202 -1.213459973  0.699091868 -0.154305677
 [76]  1.198569287  0.195065523 -1.969420599 -1.462482993  1.856936872
 [81] -0.004221221 -0.078423346  0.519020022 -1.749714841 -0.091729516
 [86] -0.669304723 -0.407831893 -2.036644009 -1.733519947 -0.815702611
 [91] -0.957140135  3.226733302  0.916653055 -0.747107882  0.867019014
 [96] -0.012904518 -0.006320283 -0.846846173 -0.936923738  2.089381771
> 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]  0.162567214 -0.584307739  0.047649531 -0.737198336 -0.071963094
  [6]  0.188574344  0.358329647 -0.721316319 -0.054422256 -0.270622704
 [11]  0.452081369 -0.023421766  0.702353684 -1.150030262 -0.213145122
 [16]  0.232710485 -2.100497229 -0.751190650  0.545988237  0.140422952
 [21] -1.080085905 -0.487232404 -1.371708934 -0.221604267 -1.387604624
 [26] -0.200438726 -1.936406867 -1.234290660  2.544334543 -0.107207423
 [31]  2.074731230  1.697285682 -0.173000258 -0.707881780 -1.097850330
 [36] -0.089012188  2.507008275  0.180777640  1.762682406 -0.567730901
 [41] -0.600425610  1.174497663 -0.339569523 -0.219322053 -0.486937405
 [46]  0.541565618  0.556263163  0.064808342 -0.617065995  0.288734429
 [51]  0.374695305  0.690402508  1.765563543 -0.708822799  0.248101130
 [56] -0.725156081 -1.877588842 -2.082069766  0.889095691  0.034283053
 [61]  2.448819929  1.410693159  0.209752301 -0.812222727 -0.495624387
 [66]  0.398531683 -0.049089680 -1.593120420  0.382034090 -1.753390028
 [71] -1.152228009  0.282701202 -1.213459973  0.699091868 -0.154305677
 [76]  1.198569287  0.195065523 -1.969420599 -1.462482993  1.856936872
 [81] -0.004221221 -0.078423346  0.519020022 -1.749714841 -0.091729516
 [86] -0.669304723 -0.407831893 -2.036644009 -1.733519947 -0.815702611
 [91] -0.957140135  3.226733302  0.916653055 -0.747107882  0.867019014
 [96] -0.012904518 -0.006320283 -0.846846173 -0.936923738  2.089381771
> colMin(tmp)
  [1]  0.162567214 -0.584307739  0.047649531 -0.737198336 -0.071963094
  [6]  0.188574344  0.358329647 -0.721316319 -0.054422256 -0.270622704
 [11]  0.452081369 -0.023421766  0.702353684 -1.150030262 -0.213145122
 [16]  0.232710485 -2.100497229 -0.751190650  0.545988237  0.140422952
 [21] -1.080085905 -0.487232404 -1.371708934 -0.221604267 -1.387604624
 [26] -0.200438726 -1.936406867 -1.234290660  2.544334543 -0.107207423
 [31]  2.074731230  1.697285682 -0.173000258 -0.707881780 -1.097850330
 [36] -0.089012188  2.507008275  0.180777640  1.762682406 -0.567730901
 [41] -0.600425610  1.174497663 -0.339569523 -0.219322053 -0.486937405
 [46]  0.541565618  0.556263163  0.064808342 -0.617065995  0.288734429
 [51]  0.374695305  0.690402508  1.765563543 -0.708822799  0.248101130
 [56] -0.725156081 -1.877588842 -2.082069766  0.889095691  0.034283053
 [61]  2.448819929  1.410693159  0.209752301 -0.812222727 -0.495624387
 [66]  0.398531683 -0.049089680 -1.593120420  0.382034090 -1.753390028
 [71] -1.152228009  0.282701202 -1.213459973  0.699091868 -0.154305677
 [76]  1.198569287  0.195065523 -1.969420599 -1.462482993  1.856936872
 [81] -0.004221221 -0.078423346  0.519020022 -1.749714841 -0.091729516
 [86] -0.669304723 -0.407831893 -2.036644009 -1.733519947 -0.815702611
 [91] -0.957140135  3.226733302  0.916653055 -0.747107882  0.867019014
 [96] -0.012904518 -0.006320283 -0.846846173 -0.936923738  2.089381771
> colMedians(tmp)
  [1]  0.162567214 -0.584307739  0.047649531 -0.737198336 -0.071963094
  [6]  0.188574344  0.358329647 -0.721316319 -0.054422256 -0.270622704
 [11]  0.452081369 -0.023421766  0.702353684 -1.150030262 -0.213145122
 [16]  0.232710485 -2.100497229 -0.751190650  0.545988237  0.140422952
 [21] -1.080085905 -0.487232404 -1.371708934 -0.221604267 -1.387604624
 [26] -0.200438726 -1.936406867 -1.234290660  2.544334543 -0.107207423
 [31]  2.074731230  1.697285682 -0.173000258 -0.707881780 -1.097850330
 [36] -0.089012188  2.507008275  0.180777640  1.762682406 -0.567730901
 [41] -0.600425610  1.174497663 -0.339569523 -0.219322053 -0.486937405
 [46]  0.541565618  0.556263163  0.064808342 -0.617065995  0.288734429
 [51]  0.374695305  0.690402508  1.765563543 -0.708822799  0.248101130
 [56] -0.725156081 -1.877588842 -2.082069766  0.889095691  0.034283053
 [61]  2.448819929  1.410693159  0.209752301 -0.812222727 -0.495624387
 [66]  0.398531683 -0.049089680 -1.593120420  0.382034090 -1.753390028
 [71] -1.152228009  0.282701202 -1.213459973  0.699091868 -0.154305677
 [76]  1.198569287  0.195065523 -1.969420599 -1.462482993  1.856936872
 [81] -0.004221221 -0.078423346  0.519020022 -1.749714841 -0.091729516
 [86] -0.669304723 -0.407831893 -2.036644009 -1.733519947 -0.815702611
 [91] -0.957140135  3.226733302  0.916653055 -0.747107882  0.867019014
 [96] -0.012904518 -0.006320283 -0.846846173 -0.936923738  2.089381771
> colRanges(tmp)
          [,1]       [,2]       [,3]       [,4]        [,5]      [,6]      [,7]
[1,] 0.1625672 -0.5843077 0.04764953 -0.7371983 -0.07196309 0.1885743 0.3583296
[2,] 0.1625672 -0.5843077 0.04764953 -0.7371983 -0.07196309 0.1885743 0.3583296
           [,8]        [,9]      [,10]     [,11]       [,12]     [,13]    [,14]
[1,] -0.7213163 -0.05442226 -0.2706227 0.4520814 -0.02342177 0.7023537 -1.15003
[2,] -0.7213163 -0.05442226 -0.2706227 0.4520814 -0.02342177 0.7023537 -1.15003
          [,15]     [,16]     [,17]      [,18]     [,19]    [,20]     [,21]
[1,] -0.2131451 0.2327105 -2.100497 -0.7511907 0.5459882 0.140423 -1.080086
[2,] -0.2131451 0.2327105 -2.100497 -0.7511907 0.5459882 0.140423 -1.080086
          [,22]     [,23]      [,24]     [,25]      [,26]     [,27]     [,28]
[1,] -0.4872324 -1.371709 -0.2216043 -1.387605 -0.2004387 -1.936407 -1.234291
[2,] -0.4872324 -1.371709 -0.2216043 -1.387605 -0.2004387 -1.936407 -1.234291
        [,29]      [,30]    [,31]    [,32]      [,33]      [,34]    [,35]
[1,] 2.544335 -0.1072074 2.074731 1.697286 -0.1730003 -0.7078818 -1.09785
[2,] 2.544335 -0.1072074 2.074731 1.697286 -0.1730003 -0.7078818 -1.09785
           [,36]    [,37]     [,38]    [,39]      [,40]      [,41]    [,42]
[1,] -0.08901219 2.507008 0.1807776 1.762682 -0.5677309 -0.6004256 1.174498
[2,] -0.08901219 2.507008 0.1807776 1.762682 -0.5677309 -0.6004256 1.174498
          [,43]      [,44]      [,45]     [,46]     [,47]      [,48]     [,49]
[1,] -0.3395695 -0.2193221 -0.4869374 0.5415656 0.5562632 0.06480834 -0.617066
[2,] -0.3395695 -0.2193221 -0.4869374 0.5415656 0.5562632 0.06480834 -0.617066
         [,50]     [,51]     [,52]    [,53]      [,54]     [,55]      [,56]
[1,] 0.2887344 0.3746953 0.6904025 1.765564 -0.7088228 0.2481011 -0.7251561
[2,] 0.2887344 0.3746953 0.6904025 1.765564 -0.7088228 0.2481011 -0.7251561
         [,57]    [,58]     [,59]      [,60]   [,61]    [,62]     [,63]
[1,] -1.877589 -2.08207 0.8890957 0.03428305 2.44882 1.410693 0.2097523
[2,] -1.877589 -2.08207 0.8890957 0.03428305 2.44882 1.410693 0.2097523
          [,64]      [,65]     [,66]       [,67]    [,68]     [,69]    [,70]
[1,] -0.8122227 -0.4956244 0.3985317 -0.04908968 -1.59312 0.3820341 -1.75339
[2,] -0.8122227 -0.4956244 0.3985317 -0.04908968 -1.59312 0.3820341 -1.75339
         [,71]     [,72]    [,73]     [,74]      [,75]    [,76]     [,77]
[1,] -1.152228 0.2827012 -1.21346 0.6990919 -0.1543057 1.198569 0.1950655
[2,] -1.152228 0.2827012 -1.21346 0.6990919 -0.1543057 1.198569 0.1950655
         [,78]     [,79]    [,80]        [,81]       [,82]   [,83]     [,84]
[1,] -1.969421 -1.462483 1.856937 -0.004221221 -0.07842335 0.51902 -1.749715
[2,] -1.969421 -1.462483 1.856937 -0.004221221 -0.07842335 0.51902 -1.749715
           [,85]      [,86]      [,87]     [,88]    [,89]      [,90]      [,91]
[1,] -0.09172952 -0.6693047 -0.4078319 -2.036644 -1.73352 -0.8157026 -0.9571401
[2,] -0.09172952 -0.6693047 -0.4078319 -2.036644 -1.73352 -0.8157026 -0.9571401
        [,92]     [,93]      [,94]    [,95]       [,96]        [,97]      [,98]
[1,] 3.226733 0.9166531 -0.7471079 0.867019 -0.01290452 -0.006320283 -0.8468462
[2,] 3.226733 0.9166531 -0.7471079 0.867019 -0.01290452 -0.006320283 -0.8468462
          [,99]   [,100]
[1,] -0.9369237 2.089382
[2,] -0.9369237 2.089382
> 
> 
> Max(tmp2)
[1] 2.660869
> Min(tmp2)
[1] -2.271214
> mean(tmp2)
[1] 0.07302326
> Sum(tmp2)
[1] 7.302326
> Var(tmp2)
[1] 1.015322
> 
> rowMeans(tmp2)
  [1] -0.544561137 -0.431788008 -1.321432930 -0.786996529  0.700334627
  [6]  0.381091436  0.422574127 -1.420527055  0.726248650  1.425197887
 [11]  0.881530902  0.400702550  0.251600070 -1.871714269  0.034080187
 [16] -0.159544409 -1.113244259  0.085279781  1.434395253  0.545311480
 [21]  0.886008644  1.832223557  0.938428477  0.882211704 -0.350634468
 [26]  0.948554692 -0.012140000 -1.184195548  0.230771336 -0.493863509
 [31] -0.411108501 -0.291825814 -0.425715628 -1.347366490  0.809121373
 [36]  1.361370178  0.615994404 -0.803175525 -0.657327726 -1.084020336
 [41] -0.866070249  0.148448249 -1.940656383  0.283511088  1.321646428
 [46] -1.728614391  0.111176473  0.965293100  0.687306624  0.480265123
 [51] -0.051392876  0.748321879 -0.401566002 -0.205590701 -0.671694473
 [56] -0.563586306 -0.469252817 -1.425342941 -0.330352766  0.025752954
 [61] -0.943765902  0.110013854 -1.781963977 -0.007380445  0.448798089
 [66]  2.045630178  0.295102054  0.728984655  1.705783453  1.801023602
 [71]  1.151423766 -0.855657247 -0.193518817  2.660868864  1.351430607
 [76] -0.052251045  0.433892536 -0.625718061  0.043965568 -1.970231425
 [81]  0.429158035  0.470148711 -0.765558090  0.030346543  0.646727742
 [86]  0.522423614  0.212275646  2.143105567 -0.432707942  1.413995061
 [91]  0.812346765 -2.271213596 -1.441421036  0.176542435  1.121688410
 [96]  0.809135008 -0.083652927  1.441771731  0.165094669 -1.643761399
> rowSums(tmp2)
  [1] -0.544561137 -0.431788008 -1.321432930 -0.786996529  0.700334627
  [6]  0.381091436  0.422574127 -1.420527055  0.726248650  1.425197887
 [11]  0.881530902  0.400702550  0.251600070 -1.871714269  0.034080187
 [16] -0.159544409 -1.113244259  0.085279781  1.434395253  0.545311480
 [21]  0.886008644  1.832223557  0.938428477  0.882211704 -0.350634468
 [26]  0.948554692 -0.012140000 -1.184195548  0.230771336 -0.493863509
 [31] -0.411108501 -0.291825814 -0.425715628 -1.347366490  0.809121373
 [36]  1.361370178  0.615994404 -0.803175525 -0.657327726 -1.084020336
 [41] -0.866070249  0.148448249 -1.940656383  0.283511088  1.321646428
 [46] -1.728614391  0.111176473  0.965293100  0.687306624  0.480265123
 [51] -0.051392876  0.748321879 -0.401566002 -0.205590701 -0.671694473
 [56] -0.563586306 -0.469252817 -1.425342941 -0.330352766  0.025752954
 [61] -0.943765902  0.110013854 -1.781963977 -0.007380445  0.448798089
 [66]  2.045630178  0.295102054  0.728984655  1.705783453  1.801023602
 [71]  1.151423766 -0.855657247 -0.193518817  2.660868864  1.351430607
 [76] -0.052251045  0.433892536 -0.625718061  0.043965568 -1.970231425
 [81]  0.429158035  0.470148711 -0.765558090  0.030346543  0.646727742
 [86]  0.522423614  0.212275646  2.143105567 -0.432707942  1.413995061
 [91]  0.812346765 -2.271213596 -1.441421036  0.176542435  1.121688410
 [96]  0.809135008 -0.083652927  1.441771731  0.165094669 -1.643761399
> rowVars(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
  [1] -0.544561137 -0.431788008 -1.321432930 -0.786996529  0.700334627
  [6]  0.381091436  0.422574127 -1.420527055  0.726248650  1.425197887
 [11]  0.881530902  0.400702550  0.251600070 -1.871714269  0.034080187
 [16] -0.159544409 -1.113244259  0.085279781  1.434395253  0.545311480
 [21]  0.886008644  1.832223557  0.938428477  0.882211704 -0.350634468
 [26]  0.948554692 -0.012140000 -1.184195548  0.230771336 -0.493863509
 [31] -0.411108501 -0.291825814 -0.425715628 -1.347366490  0.809121373
 [36]  1.361370178  0.615994404 -0.803175525 -0.657327726 -1.084020336
 [41] -0.866070249  0.148448249 -1.940656383  0.283511088  1.321646428
 [46] -1.728614391  0.111176473  0.965293100  0.687306624  0.480265123
 [51] -0.051392876  0.748321879 -0.401566002 -0.205590701 -0.671694473
 [56] -0.563586306 -0.469252817 -1.425342941 -0.330352766  0.025752954
 [61] -0.943765902  0.110013854 -1.781963977 -0.007380445  0.448798089
 [66]  2.045630178  0.295102054  0.728984655  1.705783453  1.801023602
 [71]  1.151423766 -0.855657247 -0.193518817  2.660868864  1.351430607
 [76] -0.052251045  0.433892536 -0.625718061  0.043965568 -1.970231425
 [81]  0.429158035  0.470148711 -0.765558090  0.030346543  0.646727742
 [86]  0.522423614  0.212275646  2.143105567 -0.432707942  1.413995061
 [91]  0.812346765 -2.271213596 -1.441421036  0.176542435  1.121688410
 [96]  0.809135008 -0.083652927  1.441771731  0.165094669 -1.643761399
> rowMin(tmp2)
  [1] -0.544561137 -0.431788008 -1.321432930 -0.786996529  0.700334627
  [6]  0.381091436  0.422574127 -1.420527055  0.726248650  1.425197887
 [11]  0.881530902  0.400702550  0.251600070 -1.871714269  0.034080187
 [16] -0.159544409 -1.113244259  0.085279781  1.434395253  0.545311480
 [21]  0.886008644  1.832223557  0.938428477  0.882211704 -0.350634468
 [26]  0.948554692 -0.012140000 -1.184195548  0.230771336 -0.493863509
 [31] -0.411108501 -0.291825814 -0.425715628 -1.347366490  0.809121373
 [36]  1.361370178  0.615994404 -0.803175525 -0.657327726 -1.084020336
 [41] -0.866070249  0.148448249 -1.940656383  0.283511088  1.321646428
 [46] -1.728614391  0.111176473  0.965293100  0.687306624  0.480265123
 [51] -0.051392876  0.748321879 -0.401566002 -0.205590701 -0.671694473
 [56] -0.563586306 -0.469252817 -1.425342941 -0.330352766  0.025752954
 [61] -0.943765902  0.110013854 -1.781963977 -0.007380445  0.448798089
 [66]  2.045630178  0.295102054  0.728984655  1.705783453  1.801023602
 [71]  1.151423766 -0.855657247 -0.193518817  2.660868864  1.351430607
 [76] -0.052251045  0.433892536 -0.625718061  0.043965568 -1.970231425
 [81]  0.429158035  0.470148711 -0.765558090  0.030346543  0.646727742
 [86]  0.522423614  0.212275646  2.143105567 -0.432707942  1.413995061
 [91]  0.812346765 -2.271213596 -1.441421036  0.176542435  1.121688410
 [96]  0.809135008 -0.083652927  1.441771731  0.165094669 -1.643761399
> 
> colMeans(tmp2)
[1] 0.07302326
> colSums(tmp2)
[1] 7.302326
> colVars(tmp2)
[1] 1.015322
> colSd(tmp2)
[1] 1.007632
> colMax(tmp2)
[1] 2.660869
> colMin(tmp2)
[1] -2.271214
> colMedians(tmp2)
[1] 0.1105952
> colRanges(tmp2)
          [,1]
[1,] -2.271214
[2,]  2.660869
> 
> 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]  3.3280287 -3.0717379 -0.1358745 -4.2059992  0.7745532  0.3594701
 [7] -0.3078845 -0.1618874  2.0966562  2.6078577
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -0.9556247
[2,] -0.5279104
[3,] -0.1542741
[4,]  0.6092336
[5,]  3.1835716
> 
> rowApply(tmp,sum)
 [1] -1.62284785  1.53360654  3.51224923  1.18682613 -0.35628301  0.08497347
 [7] -2.20430773  0.26804829 -0.50643866 -0.61264408
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]   10    2    1   10    5    7    3   10    5     4
 [2,]    6    4    8    1    1    1    4    6    4     9
 [3,]    2    5    2    5    8   10    6    1    9     5
 [4,]    9    1    7    2    6    6    8    2    3     1
 [5,]    3    8    4    7    4    2    9    7    8     6
 [6,]    1    3   10    4    7    8    5    9    7     7
 [7,]    5    9    3    8    2    3    7    3    2     8
 [8,]    8    6    6    3    9    4    2    8    6     3
 [9,]    4   10    9    9   10    5    1    5    1    10
[10,]    7    7    5    6    3    9   10    4   10     2
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  2.39728166 -1.08602117 -2.94932402 -5.15782957 -0.47307237 -4.05085827
 [7]  2.82197417 -1.39781245  0.47822655  2.28664584  0.05771946  4.45639913
[13] -0.58059044 -0.47637791 -0.23087458 -3.22683491  2.10067862 -0.52816760
[19]  0.49223027  3.31198729
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -0.92341939
[2,]  0.08648267
[3,]  0.63511222
[4,]  0.88398249
[5,]  1.71512367
> 
> rowApply(tmp,sum)
[1]  0.6782349 -0.1273296  5.1119057 -4.7889219 -2.6285094
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]   15   17    3   20   12
[2,]    3   18   16    5    5
[3,]    9    2    7   16    4
[4,]    4    1    4   10    6
[5,]   19    4   12    3   14
> 
> 
> as.matrix(tmp)
            [,1]       [,2]       [,3]       [,4]       [,5]       [,6]
[1,]  0.63511222 -1.2097113 -0.3041465 -0.9646290  1.1286621 -0.4065421
[2,]  0.88398249  1.2258366 -1.9773652 -2.5604251 -0.9326746 -1.3635667
[3,] -0.92341939  0.8372364  0.2103882 -0.7397559  0.4129960  0.2560547
[4,]  1.71512367 -0.8597411  0.2466915 -0.1393152 -1.5070915 -2.3706029
[5,]  0.08648267 -1.0796418 -1.1248920 -0.7537043  0.4250356 -0.1662012
          [,7]       [,8]        [,9]      [,10]       [,11]      [,12]
[1,] 0.3663817 -1.2716148  0.28440639  2.3272913 -0.44618728  0.2554226
[2,] 0.3035143  0.2658308  0.49813186  0.1096718  0.58328074  2.5998824
[3,] 1.0090251  1.1904878  0.08118053  0.3261295  0.23026748  0.5487773
[4,] 0.6689070 -0.2185023  0.17706385 -0.5862390  0.01176288 -0.7000875
[5,] 0.4741460 -1.3640139 -0.56255608  0.1097923 -0.32140435  1.7524044
           [,13]      [,14]      [,15]        [,16]      [,17]        [,18]
[1,] -0.42984219 -0.6431484 -1.6799673 -0.001951685  0.8596126  0.471403256
[2,]  0.23312689 -0.6319647  1.2670349  0.243845188  0.8172775 -0.484899265
[3,] -1.74406423 -0.3010622  0.8088149  0.368168191  1.4251839 -1.138817802
[4,] -0.03496223 -0.1240709 -1.7892382 -1.249135177 -0.3864514  0.614571354
[5,]  1.39515131  1.2238682  1.1624811 -2.587761430 -0.6149439  0.009574857
          [,19]      [,20]
[1,]  0.8201186  0.8875647
[2,] -0.5035049 -0.7043446
[3,]  0.6771755  1.5771397
[4,]  1.5172383  0.2251571
[5,] -2.0187972  1.3264703
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.18-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-3.18-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  652  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  565  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.18-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 0.09275054 -0.4720249 0.1437151 -0.4844938 0.3341833 -0.4166722 -1.661966
          col8     col9      col10      col11    col12       col13     col14
row1 0.1937892 1.745016 0.06345853 0.05245037 0.262642 -0.05414287 0.4106141
         col15     col16      col17    col18      col19      col20
row1 0.9036032 0.6488667 -0.2720576 1.244934 0.04535035 -0.2854411
> tmp[,"col10"]
           col10
row1  0.06345853
row2 -0.60637854
row3 -0.60651159
row4 -1.88164497
row5  1.14664703
> tmp[c("row1","row5"),]
            col1       col2       col3       col4       col5       col6
row1  0.09275054 -0.4720249  0.1437151 -0.4844938 0.33418334 -0.4166722
row5 -1.81085924  1.3504223 -0.5157018 -0.4025538 0.03149348 -2.0627109
           col7       col8     col9      col10      col11     col12       col13
row1 -1.6619656  0.1937892 1.745016 0.06345853 0.05245037 0.2626420 -0.05414287
row5  0.8894515 -0.8484619 0.171939 1.14664703 1.21597550 0.1855152 -1.00713632
         col14     col15        col16      col17    col18       col19
row1 0.4106141 0.9036032  0.648866674 -0.2720576 1.244934  0.04535035
row5 0.4338916 1.2146643 -0.007305511  0.1066988 1.010461 -0.39256859
          col20
row1 -0.2854411
row5  0.1567314
> tmp[,c("col6","col20")]
           col6      col20
row1 -0.4166722 -0.2854411
row2 -0.1732115 -0.5708520
row3  2.3263203 -1.0528198
row4  1.4615553  1.7450634
row5 -2.0627109  0.1567314
> tmp[c("row1","row5"),c("col6","col20")]
           col6      col20
row1 -0.4166722 -0.2854411
row5 -2.0627109  0.1567314
> 
> 
> 
> 
> 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 49.35319 51.62979 49.94651 49.77144 48.5978 103.6454 51.67509 48.48316
         col9    col10    col11    col12    col13    col14    col15    col16
row1 49.91114 51.70905 50.53214 50.01607 51.19952 49.52572 49.12467 49.57155
        col17    col18    col19    col20
row1 49.91798 50.32993 50.34821 104.8873
> tmp[,"col10"]
        col10
row1 51.70905
row2 29.35605
row3 32.25965
row4 29.12576
row5 50.08185
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 49.35319 51.62979 49.94651 49.77144 48.59780 103.6454 51.67509 48.48316
row5 49.32054 50.91990 49.89422 49.71841 49.26871 105.7868 49.72167 48.44067
         col9    col10    col11    col12    col13    col14    col15    col16
row1 49.91114 51.70905 50.53214 50.01607 51.19952 49.52572 49.12467 49.57155
row5 49.73952 50.08185 49.67345 49.76160 49.85746 50.06323 50.00127 49.08639
        col17    col18    col19    col20
row1 49.91798 50.32993 50.34821 104.8873
row5 49.43602 50.23923 51.99143 107.7564
> tmp[,c("col6","col20")]
          col6     col20
row1 103.64541 104.88734
row2  76.15137  74.40497
row3  76.18926  74.41823
row4  75.43734  75.25329
row5 105.78675 107.75640
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 103.6454 104.8873
row5 105.7868 107.7564
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 103.6454 104.8873
row5 105.7868 107.7564
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,] -2.1639917
[2,]  0.9011858
[3,]  1.0368701
[4,] -1.3744750
[5,] -0.2622730
> tmp[,c("col17","col7")]
           col17        col7
[1,] -0.06693832 -0.79685161
[2,] -0.85469237 -0.02090629
[3,] -2.36373437 -0.45995059
[4,]  2.24691224  0.34121407
[5,] -0.83564666  0.62716957
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
           col6       col20
[1,]  1.7030844  0.52397990
[2,] -0.1008612 -1.18351537
[3,]  0.2839226 -0.08539384
[4,] -0.9547772  0.53849911
[5,]  0.3659561  1.13140001
> subBufferedMatrix(tmp,1,c("col6"))[,1]
         col1
[1,] 1.703084
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
           col6
[1,]  1.7030844
[2,] -0.1008612
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> 
> 
> 
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
           [,1]       [,2]       [,3]       [,4]     [,5]      [,6]      [,7]
row3 -0.4228289  1.0404864 -0.6978341  1.6435804 2.038826 0.2156838 -1.937206
row1 -0.9757986 -0.7935525 -1.1822633 -0.9522872 1.973153 0.9806305  1.352953
          [,8]      [,9]     [,10]      [,11]      [,12]     [,13]    [,14]
row3 0.7473793 -1.374052 0.7253138  1.6561572 -1.6231491 -2.733387 1.259781
row1 0.2818399  0.192409 0.6435641 -0.1791212 -0.2886034 -1.075843 2.798360
         [,15]      [,16]      [,17]     [,18]      [,19]      [,20]
row3  1.208305 -0.4642119  1.4870337 0.8989267 0.43940477 -0.3249109
row1 -1.863233 -0.7964451 -0.5779871 1.0372574 0.09246355 -1.5392024
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
           [,1]        [,2]       [,3]      [,4]      [,5]       [,6]
row2 -0.5670421 -0.08558317 -0.6795207 0.3544977 -1.591983 -0.5253287
           [,7]     [,8]      [,9]     [,10]
row2 -0.7544825 1.190469 -0.948438 0.7590648
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
         [,1]      [,2]      [,3]       [,4]      [,5]     [,6]      [,7]
row5 1.295167 0.3703016 -1.530607 -0.1101114 -2.029272 1.553019 0.3993023
        [,8]       [,9]     [,10]      [,11]      [,12]      [,13]    [,14]
row5 1.23462 -0.1974254 -1.312892 -0.3834642 -0.2698716 -0.9535435 1.780416
          [,15]      [,16]    [,17]     [,18]     [,19]      [,20]
row5 -0.4098637 -0.7176078 1.276047 0.5677921 0.2372337 -0.8122356
> 
> 
> 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: 0x563e97ee3050>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a58a27312"
 [2] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a3bfdc1d" 
 [3] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a16a7387c"
 [4] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a266f522f"
 [5] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a7e417950"
 [6] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a48cbebab"
 [7] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a3c340767"
 [8] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a2c82f7be"
 [9] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a73aa20ae"
[10] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a48dd54a4"
[11] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a569d6dab"
[12] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a235a85b1"
[13] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a8ae8449" 
[14] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a1f6e58e4"
[15] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM127c1a66124b9c"
> 
> 
> ### 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: 0x563e998afca0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x563e998afca0>
Warning message:
In dir.create(new.directory) :
  '/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x563e998afca0>
> rowMedians(tmp)
  [1] -0.1302970209 -0.0226566016 -0.3189008290 -0.3277161574  0.7420887305
  [6]  0.4696775596  0.1913903559  0.2334437180  0.2618116496 -0.1548893583
 [11] -0.2652124553 -0.2730943547  0.1995544561  0.1470894983  0.2140698676
 [16]  0.0255258227 -0.2777745670  0.1835588527 -0.1762118373 -0.3567452165
 [21]  0.7337645428  0.2716483023  0.5821411503 -0.1022668384  0.6040873126
 [26]  0.0494060035  0.4712887175 -0.1870470831 -0.1338062785 -0.1525824945
 [31]  0.0585035216  0.5765197714  0.3833238341  0.3661553534 -0.3494611099
 [36]  0.0098491661 -0.1615035519  0.1833164486  0.1329584976  0.1700317858
 [41] -0.2243167479 -0.0981979467 -0.3015545947 -0.0710185422 -0.3927052354
 [46] -0.3096530516 -0.4601637390 -0.3330077449  0.0601875651 -0.4223590609
 [51] -0.0288399088  0.6899767315  0.5224384969  0.2993263427  0.3073022571
 [56] -0.0746981979  0.3121427547  0.0945980183 -0.9123254439  0.0158800742
 [61] -0.0700541319  0.3296767191  0.3313415127 -0.2476903051 -0.1675905888
 [66]  0.3825827604  0.1011998728 -0.0235505170 -0.1610884306  0.3413208507
 [71]  0.1758513310 -0.0572794817  0.4809721372  0.0368632528  0.0240747106
 [76]  0.4956932769 -0.3977801326  0.1860499183  0.1679992678 -0.5573583981
 [81] -0.5600725578  0.7578324717 -0.5246242865 -0.0215848357  0.5355718752
 [86] -0.2046664365  0.0855428801  0.0171234480 -0.3592971536  0.0005053341
 [91]  0.3081986373 -0.1954133836  0.0379679132  0.1135763888  0.0543072614
 [96]  0.1423002509 -0.1212413498  0.1735301074  0.3656836059  0.3881618933
[101] -0.0437398030 -0.2243974203  0.1213072350 -0.5850036794  0.0363681560
[106]  0.3826303316 -0.5268247609  0.1458070669 -0.2238209211 -0.1102075280
[111] -0.1852129929 -0.4211446878 -0.4288462002  0.2569567664 -0.1193124638
[116]  0.0716993757 -0.4695405602  0.3501216233  0.0342768792  0.3980497762
[121] -0.2776598966 -0.0452149491 -0.4621978116 -0.2009359290 -0.1138677143
[126]  0.1042901168  0.2058667463  0.2114596527  0.2692038468  0.2404118652
[131]  0.2735397584 -0.4802014882 -0.0982349877 -0.1485119673  0.0665573364
[136]  0.1893481175  0.3336497618  0.2995198200 -0.0804535918 -0.1618992035
[141]  0.1526788646 -0.3757910043 -0.3949748303  0.0292000769  0.0735842090
[146] -0.4621885723  0.2128209828 -0.4445395711 -0.6243750394  0.0594867027
[151] -0.0190390225  0.1682314661 -0.2069868123 -0.1193664715 -0.0576489896
[156] -0.6281463248 -0.0683898004 -0.1217298213 -0.1542343057 -0.1248337535
[161] -0.2728920060 -0.6160381848 -0.1975857526 -0.3438745554  0.1488131243
[166] -0.2218268422 -0.3091640315  0.2804796889  0.3685839019  0.0911327816
[171] -0.2034257128  0.1017557633  0.0721877148 -0.0883148036  0.3059854569
[176]  0.2543308410 -0.5316443980  0.0446232424 -0.1363036129  0.0541453276
[181] -0.4775590953 -0.3971318917 -0.1871422630  0.3436361479  0.1231652028
[186] -0.2612663073  0.7685666515 -0.4975526079 -0.3650780740  0.1992417608
[191]  0.5147371386 -0.6599224571  0.1479181566  0.3190699360 -0.0094184652
[196] -0.0196923147 -0.1278435139 -0.3536389483  0.5879973369 -0.0226686924
[201] -0.1166142338 -0.2893569192 -0.1025188095  0.2244563719  0.2874809020
[206]  0.0992769519  0.3886991092 -0.7008690743  0.3550999890 -0.3543312145
[211] -0.2705925511  0.9121276395  0.4010772937  0.5584224832 -0.5584460197
[216] -0.0167858503 -0.2317220975  0.1433642322  0.0981084837  0.1509071174
[221] -0.5442557736  0.1176977055  0.1595861018  0.6392330531 -0.5338513781
[226]  0.4785649923 -0.0274659436  0.1750681973 -0.1214753045 -0.1858855072
> 
> proc.time()
   user  system elapsed 
  1.352   0.587   1.933 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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: 0x55c8f6908010>
> .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: 0x55c8f6908010>
> .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: 0x55c8f6908010>
> .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: 0x55c8f6908010>
> 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: 0x55c8f6cce6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f6cce6a0>
> .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: 0x55c8f6cce6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f6cce6a0>
> .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: 0x55c8f6cce6a0>
> 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: 0x55c8f5e111c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f5e111c0>
> .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: 0x55c8f5e111c0>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55c8f5e111c0>
> .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: 0x55c8f5e111c0>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x55c8f5e111c0>
> .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: 0x55c8f5e111c0>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x55c8f5e111c0>
> .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: 0x55c8f5e111c0>
> 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: 0x55c8f87385e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55c8f87385e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f87385e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f87385e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile127ddb42976e86" "BufferedMatrixFile127ddb66cd6a68"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile127ddb42976e86" "BufferedMatrixFile127ddb66cd6a68"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f6b75280>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f6b75280>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55c8f6b75280>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55c8f6b75280>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55c8f6b75280>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55c8f6b75280>
> .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: 0x55c8f7dc7920>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c8f7dc7920>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55c8f7dc7920>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55c8f7dc7920>
> 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: 0x55c8f70a5c00>
> .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: 0x55c8f70a5c00>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.255   0.030   0.275 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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 
  0.245   0.042   0.277 

Example timings