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This page was generated on 2024-06-28 17:39 -0400 (Fri, 28 Jun 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_644.4.0 (2024-04-24) -- "Puppy Cup" 4760
palomino3Windows Server 2022 Datacenterx644.4.0 (2024-04-24 ucrt) -- "Puppy Cup" 4494
merida1macOS 12.7.4 Montereyx86_644.4.0 (2024-04-24) -- "Puppy Cup" 4508
kjohnson1macOS 13.6.6 Venturaarm644.4.0 (2024-04-24) -- "Puppy Cup" 4466
palomino7Windows Server 2022 Datacenterx644.4.1 (2024-06-14 ucrt) -- "Race for Your Life" 4362
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 249/2300HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.68.0  (landing page)
Ben Bolstad
Snapshot Date: 2024-06-26 14:00 -0400 (Wed, 26 Jun 2024)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: RELEASE_3_19
git_last_commit: af6c73d
git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024)
nebbiolo1Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.4 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.6 Ventura / arm64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
palomino7Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  


CHECK results for BufferedMatrix on nebbiolo1

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

raw results


Summary

Package: BufferedMatrix
Version: 1.68.0
Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz
StartedAt: 2024-06-26 21:13:27 -0400 (Wed, 26 Jun 2024)
EndedAt: 2024-06-26 21:13:51 -0400 (Wed, 26 Jun 2024)
EllapsedTime: 24.1 seconds
RetCode: 0
Status:   OK  
CheckDir: BufferedMatrix.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-pc-linux-gnu
* 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 ‘1.68.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (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 code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
   209 |     $x^{power}$ elementwise of the matrix
       |        ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘Rcodetesting.R’
  Running ‘c_code_level_tests.R’
  Running ‘objectTesting.R’
  Running ‘rawCalltesting.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.


Installation output

BufferedMatrix.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.19-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-3.19-bioc/R/include" -DNDEBUG   -I/usr/local/include    -fpic  -g -O2  -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.19-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-3.19-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-3.19-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-3.19-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-3.19-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.19-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 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 

Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000 

Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068 
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000 

Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 

Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 

Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000 
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000 
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000 
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000 
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000 

[[1]]
[1] 0

> 
> proc.time()
   user  system elapsed 
  0.257   0.045   0.290 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> 
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
> 
> 
> ## test creation and some simple assignments and subsetting operations
> 
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
> 
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
> 
> 
> 
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
> 
> 
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
       [,1]    [,2]
 [1,]  0.00 0.00000
 [2,]  0.00 0.00000
 [3,] 51.34 0.00000
 [4,]  0.00 0.00000
 [5,]  0.00 0.00000
 [6,]  0.00 0.00000
 [7,]  0.00 0.00000
 [8,]  0.00 0.00000
 [9,]  0.00 9.87654
[10,]  0.00 0.00000
> tmp2[,-(3:20)]
       [,1]    [,2]
 [1,]  0.00 0.00000
 [2,]  0.00 0.00000
 [3,] 51.34 0.00000
 [4,]  0.00 0.00000
 [5,]  0.00 0.00000
 [6,]  0.00 0.00000
 [7,]  0.00 0.00000
 [8,]  0.00 0.00000
 [9,]  0.00 9.87654
[10,]  0.00 0.00000
> tmp2[3,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34    0    0    0    0    0    0    0    0     0     0     0     0
     [,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,]     0     0     0     0     0     0     0
> tmp2[-3,]
      [,1]    [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [2,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [3,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [4,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [5,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [6,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [7,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [8,]    0 9.87654    0    0    0    0    0    0    0     0     0     0     0
 [9,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
      [,14] [,15] [,16] [,17] [,18] [,19] [,20]
 [1,]     0     0     0     0     0     0     0
 [2,]     0     0     0     0     0     0     0
 [3,]     0     0     0     0     0     0     0
 [4,]     0     0     0     0     0     0     0
 [5,]     0     0     0     0     0     0     0
 [6,]     0     0     0     0     0     0     0
 [7,]     0     0     0     0     0     0     0
 [8,]     0     0     0     0     0     0     0
 [9,]     0     0     0     0     0     0     0
> tmp2[2,1:3]
     [,1] [,2] [,3]
[1,]    0    0    0
> tmp2[3:9,1:3]
      [,1]    [,2] [,3]
[1,] 51.34 0.00000    0
[2,]  0.00 0.00000    0
[3,]  0.00 0.00000    0
[4,]  0.00 0.00000    0
[5,]  0.00 0.00000    0
[6,]  0.00 0.00000    0
[7,]  0.00 9.87654    0
> tmp2[-4,-4]
       [,1]    [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [2,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [3,] 51.34 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [4,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [5,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [6,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [7,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [8,]  0.00 9.87654    0    0    0    0    0    0    0     0     0     0     0
 [9,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
      [,14] [,15] [,16] [,17] [,18] [,19]
 [1,]     0     0     0     0     0     0
 [2,]     0     0     0     0     0     0
 [3,]     0     0     0     0     0     0
 [4,]     0     0     0     0     0     0
 [5,]     0     0     0     0     0     0
 [6,]     0     0     0     0     0     0
 [7,]     0     0     0     0     0     0
 [8,]     0     0     0     0     0     0
 [9,]     0     0     0     0     0     0
> 
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
> 
> for (i in 1:10){
+   for (j in 1:10){
+     tmp3[i,j] <- (j-1)*10 + i
+   }
+ }
> 
> tmp3[2:4,2:4]
     [,1] [,2] [,3]
[1,]   12   22   32
[2,]   13   23   33
[3,]   14   24   34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]   11   21   31   11   21   31   91    1   11     1    11    21    31
 [2,]   12   22   32   12   22   32   92    2   12     2    12    22    32
 [3,]   13   23   33   13   23   33   93    3   13     3    13    23    33
 [4,]   14   24   34   14   24   34   94    4   14     4    14    24    34
 [5,]   15   25   35   15   25   35   95    5   15     5    15    25    35
 [6,]   16   26   36   16   26   36   96    6   16     6    16    26    36
 [7,]   17   27   37   17   27   37   97    7   17     7    17    27    37
 [8,]   18   28   38   18   28   38   98    8   18     8    18    28    38
 [9,]   19   29   39   19   29   39   99    9   19     9    19    29    39
      [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
 [1,]    41    51    61    71    81    91    91    81    71    61    51    41
 [2,]    42    52    62    72    82    92    92    82    72    62    52    42
 [3,]    43    53    63    73    83    93    93    83    73    63    53    43
 [4,]    44    54    64    74    84    94    94    84    74    64    54    44
 [5,]    45    55    65    75    85    95    95    85    75    65    55    45
 [6,]    46    56    66    76    86    96    96    86    76    66    56    46
 [7,]    47    57    67    77    87    97    97    87    77    67    57    47
 [8,]    48    58    68    78    88    98    98    88    78    68    58    48
 [9,]    49    59    69    79    89    99    99    89    79    69    59    49
      [,26] [,27] [,28] [,29]
 [1,]    31    21    11     1
 [2,]    32    22    12     2
 [3,]    33    23    13     3
 [4,]    34    24    14     4
 [5,]    35    25    15     5
 [6,]    36    26    16     6
 [7,]    37    27    17     7
 [8,]    38    28    18     8
 [9,]    39    29    19     9
> tmp3[-c(1:5),-c(6:10)]
     [,1] [,2] [,3] [,4] [,5]
[1,]    6   16   26   36   46
[2,]    7   17   27   37   47
[3,]    8   18   28   38   48
[4,]    9   19   29   39   49
[5,]   10   20   30   40   50
> 
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
      [,1]  [,2]
 [1,] 1100 1e+04
 [2,] 1200 2e+04
 [3,] 1300 3e+04
 [4,] 1400 4e+04
 [5,] 1500 5e+04
 [6,] 1600 6e+04
 [7,] 1700 7e+04
 [8,] 1800 8e+04
 [9,] 1900 9e+04
[10,] 2000 1e+05
> 
> 
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
      [,1] [,2]  [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,] 1100 1100 1e+04   21   31   41   51   61   71    81
 [2,] 1200 1200 2e+04   22   32   42   52   62   72    82
 [3,] 1300 1300 3e+04   23   33   43   53   63   73    83
 [4,] 1400 1400 4e+04   24   34   44   54   64   74    84
 [5,] 1500 1500 5e+04   25   35   45   55   65   75    85
 [6,] 1600 1600 6e+04   26   36   46   56   66   76    86
 [7,] 1700 1700 7e+04   27   37   47   57   67   77    87
 [8,] 1800 1800 8e+04   28   38   48   58   68   78    88
 [9,] 1900 1900 9e+04   29   39   49   59   69   79    89
[10,] 2000 2000 1e+05   30   40   50   60   70   80    90
> 
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
> 
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
> 
> tmp3[1,] <- 1:10
> tmp3[1,]
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    1    2    3    4    5    6    7    8    9    10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1    2    3    4    5    6    7    8    9    10
 [2,]    1    2    1    2    1    2    1    2    1     2
 [3,]    2    1    2    1    2    1    2    1    2     1
 [4,]    1    2    1    2    1    2    1    2    1     2
 [5,]    2    1    2    1    2    1    2    1    2     1
 [6,]    1    2    1    2    1    2    1    2    1     2
 [7,]    2    1    2    1    2    1    2    1    2     1
 [8,]    1    2    1    2    1    2    1    2    1     2
 [9,]    2    1    2    1    2    1    2    1    2     1
[10,]    1    2    1    2    1    2    1    2    1     2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1    2    3    4    5    6    7    8    9    10
 [2,]    1    2    1    2    1    2    1    2    1     2
 [3,]    2    1    2    1    2    1    2    1    2     1
 [4,]    1    2    1    2    1    2    1    2    1     2
 [5,]    2    1    2    1    2    1    2    1    2     1
 [6,]    1    2    1    2    1    2    1    2    1     2
 [7,]    2    1    2    1    2    1    2    1    2     1
 [8,]    1    2    1    2    1    2    1    2    1     2
 [9,]    1    3    5    2    4    1    3    5    2     4
[10,]    2    4    1    3    5    2    4    1    3     5
> 
> 
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
> 
> 
> 
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
> 
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
         used (Mb) gc trigger (Mb) max used (Mb)
Ncells 471778 25.2    1026221 54.9   643431 34.4
Vcells 871899  6.7    8388608 64.0  2046580 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] "Wed Jun 26 21:13:42 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] "Wed Jun 26 21:13:42 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: 0x557e0160e440>
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   which.col <- sample(1:20,1)
+   if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> date()
[1] "Wed Jun 26 21:13:43 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] "Wed Jun 26 21:13:43 2024"
> 
> ColMode(tmp2)
<pointer: 0x557e0160e440>
> 
> 
> 
> ### 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,] 98.128076  1.29993358  0.7165912 -0.3213029
[2,] -1.703297 -0.04883745 -0.3610706  0.2479757
[3,]  1.175908  1.46838215 -0.2464409  0.3634658
[4,]  0.946488  0.01235557 -0.5447740  0.4865162
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]       [,2]      [,3]      [,4]
[1,] 98.128076 1.29993358 0.7165912 0.3213029
[2,]  1.703297 0.04883745 0.3610706 0.2479757
[3,]  1.175908 1.46838215 0.2464409 0.3634658
[4,]  0.946488 0.01235557 0.5447740 0.4865162
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]      [,2]      [,3]      [,4]
[1,] 9.9059617 1.1401463 0.8465171 0.5668358
[2,] 1.3051044 0.2209920 0.6008915 0.4979716
[3,] 1.0843928 1.2117682 0.4964282 0.6028812
[4,] 0.9728762 0.1111556 0.7380881 0.6975071
> 
> my.function <- function(x,power){
+   (x+5)^power
+ }
> 
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 222.18769 37.70140 34.18176 30.98966
[2,]  39.75434 27.25876 31.36999 30.22769
[3,]  37.01984 38.58606 30.21072 31.39228
[4,]  35.67525 26.12391 32.92566 32.46159
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x557e011803b0>
> exp(tmp5)
<pointer: 0x557e011803b0>
> log(tmp5,2)
<pointer: 0x557e011803b0>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 462.4546
> Min(tmp5)
[1] 53.34354
> mean(tmp5)
[1] 71.86558
> Sum(tmp5)
[1] 14373.12
> Var(tmp5)
[1] 840.7847
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 85.71089 69.52724 70.12736 71.09549 68.48577 70.48827 72.14850 71.33142
 [9] 70.52864 69.21226
> rowSums(tmp5)
 [1] 1714.218 1390.545 1402.547 1421.910 1369.715 1409.765 1442.970 1426.628
 [9] 1410.573 1384.245
> rowVars(tmp5)
 [1] 7905.82165   43.53105   64.59957   80.21487   72.29752   93.74045
 [7]   57.63862  100.18674   84.45736   68.58540
> rowSd(tmp5)
 [1] 88.914687  6.597807  8.037386  8.956276  8.502795  9.681965  7.592010
 [8] 10.009333  9.190069  8.281630
> rowMax(tmp5)
 [1] 462.45457  82.74345  88.08163  86.29615  84.48248  90.14023  89.06012
 [8]  92.24273  89.92445  84.28614
> rowMin(tmp5)
 [1] 53.94763 56.73553 58.47321 54.37350 54.12502 56.63315 60.17438 53.34354
 [9] 55.76599 59.09232
> 
> colMeans(tmp5)
 [1] 111.43750  69.38914  67.22416  68.25115  70.79520  66.72230  70.36205
 [8]  71.79602  64.97738  67.76061  71.43156  69.47718  73.04703  72.54610
[15]  68.58514  67.39691  72.31174  70.52291  68.57750  74.70008
> colSums(tmp5)
 [1] 1114.3750  693.8914  672.2416  682.5115  707.9520  667.2230  703.6205
 [8]  717.9602  649.7738  677.6061  714.3156  694.7718  730.4703  725.4610
[15]  685.8514  673.9691  723.1174  705.2291  685.7750  747.0008
> colVars(tmp5)
 [1] 15314.02267    80.27677    54.19242    27.47161    62.28259    42.89737
 [7]   132.31948    83.85311    63.17054    38.95074    94.08356    79.78637
[13]    54.03159    78.37197    88.61406    37.95651   108.58614    80.01137
[19]    30.75284    83.30874
> colSd(tmp5)
 [1] 123.749839   8.959731   7.361550   5.241337   7.891932   6.549608
 [7]  11.503020   9.157134   7.947990   6.241052   9.699668   8.932322
[13]   7.350618   8.852794   9.413504   6.160885  10.420467   8.944907
[19]   5.545525   9.127362
> colMax(tmp5)
 [1] 462.45457  80.31184  81.46316  79.15406  81.08830  73.69268  85.06774
 [8]  86.29615  78.15673  74.12539  84.48248  90.14023  84.86683  87.86257
[15]  89.92445  77.64222  92.24273  88.08163  78.42319  89.06012
> colMin(tmp5)
 [1] 57.77062 54.37350 58.96375 62.91498 58.35480 55.76599 53.34354 54.34408
 [9] 58.07365 54.12502 60.17438 62.14366 62.38722 59.55240 58.07183 58.47321
[17] 61.05177 57.22658 58.10106 57.90320
> 
> 
> ### 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] 85.71089 69.52724 70.12736 71.09549 68.48577 70.48827 72.14850 71.33142
 [9] 70.52864       NA
> rowSums(tmp5)
 [1] 1714.218 1390.545 1402.547 1421.910 1369.715 1409.765 1442.970 1426.628
 [9] 1410.573       NA
> rowVars(tmp5)
 [1] 7905.82165   43.53105   64.59957   80.21487   72.29752   93.74045
 [7]   57.63862  100.18674   84.45736   68.50134
> rowSd(tmp5)
 [1] 88.914687  6.597807  8.037386  8.956276  8.502795  9.681965  7.592010
 [8] 10.009333  9.190069  8.276553
> rowMax(tmp5)
 [1] 462.45457  82.74345  88.08163  86.29615  84.48248  90.14023  89.06012
 [8]  92.24273  89.92445        NA
> rowMin(tmp5)
 [1] 53.94763 56.73553 58.47321 54.37350 54.12502 56.63315 60.17438 53.34354
 [9] 55.76599       NA
> 
> colMeans(tmp5)
 [1] 111.43750  69.38914  67.22416  68.25115  70.79520  66.72230  70.36205
 [8]  71.79602  64.97738  67.76061  71.43156  69.47718  73.04703  72.54610
[15]  68.58514  67.39691        NA  70.52291  68.57750  74.70008
> colSums(tmp5)
 [1] 1114.3750  693.8914  672.2416  682.5115  707.9520  667.2230  703.6205
 [8]  717.9602  649.7738  677.6061  714.3156  694.7718  730.4703  725.4610
[15]  685.8514  673.9691        NA  705.2291  685.7750  747.0008
> colVars(tmp5)
 [1] 15314.02267    80.27677    54.19242    27.47161    62.28259    42.89737
 [7]   132.31948    83.85311    63.17054    38.95074    94.08356    79.78637
[13]    54.03159    78.37197    88.61406    37.95651          NA    80.01137
[19]    30.75284    83.30874
> colSd(tmp5)
 [1] 123.749839   8.959731   7.361550   5.241337   7.891932   6.549608
 [7]  11.503020   9.157134   7.947990   6.241052   9.699668   8.932322
[13]   7.350618   8.852794   9.413504   6.160885         NA   8.944907
[19]   5.545525   9.127362
> colMax(tmp5)
 [1] 462.45457  80.31184  81.46316  79.15406  81.08830  73.69268  85.06774
 [8]  86.29615  78.15673  74.12539  84.48248  90.14023  84.86683  87.86257
[15]  89.92445  77.64222        NA  88.08163  78.42319  89.06012
> colMin(tmp5)
 [1] 57.77062 54.37350 58.96375 62.91498 58.35480 55.76599 53.34354 54.34408
 [9] 58.07365 54.12502 60.17438 62.14366 62.38722 59.55240 58.07183 58.47321
[17]       NA 57.22658 58.10106 57.90320
> 
> Max(tmp5,na.rm=TRUE)
[1] 462.4546
> Min(tmp5,na.rm=TRUE)
[1] 53.34354
> mean(tmp5,na.rm=TRUE)
[1] 71.91992
> Sum(tmp5,na.rm=TRUE)
[1] 14312.06
> Var(tmp5,na.rm=TRUE)
[1] 844.4375
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 85.71089 69.52724 70.12736 71.09549 68.48577 70.48827 72.14850 71.33142
 [9] 70.52864 69.64176
> rowSums(tmp5,na.rm=TRUE)
 [1] 1714.218 1390.545 1402.547 1421.910 1369.715 1409.765 1442.970 1426.628
 [9] 1410.573 1323.193
> rowVars(tmp5,na.rm=TRUE)
 [1] 7905.82165   43.53105   64.59957   80.21487   72.29752   93.74045
 [7]   57.63862  100.18674   84.45736   68.50134
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.914687  6.597807  8.037386  8.956276  8.502795  9.681965  7.592010
 [8] 10.009333  9.190069  8.276553
> rowMax(tmp5,na.rm=TRUE)
 [1] 462.45457  82.74345  88.08163  86.29615  84.48248  90.14023  89.06012
 [8]  92.24273  89.92445  84.28614
> rowMin(tmp5,na.rm=TRUE)
 [1] 53.94763 56.73553 58.47321 54.37350 54.12502 56.63315 60.17438 53.34354
 [9] 55.76599 59.09232
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.43750  69.38914  67.22416  68.25115  70.79520  66.72230  70.36205
 [8]  71.79602  64.97738  67.76061  71.43156  69.47718  73.04703  72.54610
[15]  68.58514  67.39691  73.56285  70.52291  68.57750  74.70008
> colSums(tmp5,na.rm=TRUE)
 [1] 1114.3750  693.8914  672.2416  682.5115  707.9520  667.2230  703.6205
 [8]  717.9602  649.7738  677.6061  714.3156  694.7718  730.4703  725.4610
[15]  685.8514  673.9691  662.0657  705.2291  685.7750  747.0008
> colVars(tmp5,na.rm=TRUE)
 [1] 15314.02267    80.27677    54.19242    27.47161    62.28259    42.89737
 [7]   132.31948    83.85311    63.17054    38.95074    94.08356    79.78637
[13]    54.03159    78.37197    88.61406    37.95651   104.55009    80.01137
[19]    30.75284    83.30874
> colSd(tmp5,na.rm=TRUE)
 [1] 123.749839   8.959731   7.361550   5.241337   7.891932   6.549608
 [7]  11.503020   9.157134   7.947990   6.241052   9.699668   8.932322
[13]   7.350618   8.852794   9.413504   6.160885  10.224974   8.944907
[19]   5.545525   9.127362
> colMax(tmp5,na.rm=TRUE)
 [1] 462.45457  80.31184  81.46316  79.15406  81.08830  73.69268  85.06774
 [8]  86.29615  78.15673  74.12539  84.48248  90.14023  84.86683  87.86257
[15]  89.92445  77.64222  92.24273  88.08163  78.42319  89.06012
> colMin(tmp5,na.rm=TRUE)
 [1] 57.77062 54.37350 58.96375 62.91498 58.35480 55.76599 53.34354 54.34408
 [9] 58.07365 54.12502 60.17438 62.14366 62.38722 59.55240 58.07183 58.47321
[17] 63.96149 57.22658 58.10106 57.90320
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 85.71089 69.52724 70.12736 71.09549 68.48577 70.48827 72.14850 71.33142
 [9] 70.52864      NaN
> rowSums(tmp5,na.rm=TRUE)
 [1] 1714.218 1390.545 1402.547 1421.910 1369.715 1409.765 1442.970 1426.628
 [9] 1410.573    0.000
> rowVars(tmp5,na.rm=TRUE)
 [1] 7905.82165   43.53105   64.59957   80.21487   72.29752   93.74045
 [7]   57.63862  100.18674   84.45736         NA
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.914687  6.597807  8.037386  8.956276  8.502795  9.681965  7.592010
 [8] 10.009333  9.190069        NA
> rowMax(tmp5,na.rm=TRUE)
 [1] 462.45457  82.74345  88.08163  86.29615  84.48248  90.14023  89.06012
 [8]  92.24273  89.92445        NA
> rowMin(tmp5,na.rm=TRUE)
 [1] 53.94763 56.73553 58.47321 54.37350 54.12502 56.63315 60.17438 53.34354
 [9] 55.76599       NA
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 117.17024  70.13880  68.12770  67.41254  70.73640  65.94781  70.77268
 [8]  71.65349  63.67130  68.39143  72.64808  70.26687  71.89641  71.86556
[15]  69.57495  66.84476       NaN  69.91158  68.97953  73.63496
> colSums(tmp5,na.rm=TRUE)
 [1] 1054.5321  631.2492  613.1493  606.7129  636.6276  593.5303  636.9541
 [8]  644.8814  573.0417  615.5229  653.8327  632.4019  647.0677  646.7900
[15]  626.1745  601.6028    0.0000  629.2042  620.8158  662.7147
> colVars(tmp5,na.rm=TRUE)
 [1] 16858.55196    83.98901    51.78218    22.99383    70.02902    41.51144
 [7]   146.96250    94.10621    51.87616    39.34279    89.19493    82.74401
[13]    45.89143    82.95814    88.66899    39.27121          NA    85.80834
[19]    32.77864    80.95948
> colSd(tmp5,na.rm=TRUE)
 [1] 129.840487   9.164552   7.195984   4.795189   8.368334   6.442938
 [7]  12.122809   9.700836   7.202511   6.272383   9.444307   9.096374
[13]   6.774322   9.108136   9.416421   6.266675         NA   9.263279
[19]   5.725263   8.997748
> colMax(tmp5,na.rm=TRUE)
 [1] 462.45457  80.31184  81.46316  79.15406  81.08830  73.58141  85.06774
 [8]  86.29615  78.15673  74.12539  84.48248  90.14023  84.86683  87.86257
[15]  89.92445  77.64222      -Inf  88.08163  78.42319  89.06012
> colMin(tmp5,na.rm=TRUE)
 [1] 57.77062 54.37350 58.96375 62.91498 58.35480 55.76599 53.34354 54.34408
 [9] 58.07365 54.12502 60.17438 62.14366 62.38722 59.55240 58.07183 58.47321
[17]      Inf 57.22658 58.10106 57.90320
> 
> 
> 
> 
> 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] 271.7774 191.7606 232.1663 124.9190 193.3034 154.5165 321.2738 389.6992
 [9] 158.8390 183.1604
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 271.7774 191.7606 232.1663 124.9190 193.3034 154.5165 321.2738 389.6992
 [9] 158.8390 183.1604
> 
> 
> 
> 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]  8.526513e-14 -9.947598e-14 -2.842171e-14  1.136868e-13  0.000000e+00
 [6]  2.842171e-13 -1.136868e-13  1.136868e-13 -5.684342e-14  0.000000e+00
[11]  1.705303e-13 -5.684342e-14  1.136868e-13  1.705303e-13  0.000000e+00
[16]  5.684342e-14  0.000000e+00 -1.989520e-13  5.684342e-14  5.684342e-14
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## making sure these things agree
> ##
> ## first when there is no NA
> 
> 
> 
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+ 
+   if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Max")
+   }
+   
+ 
+   if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Min")
+   }
+ 
+ 
+   if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+ 
+     cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+     cat(sum(r.matrix,na.rm=TRUE),"\n")
+     cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+     
+     stop("No agreement in Sum")
+   }
+   
+   if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+     stop("No agreement in mean")
+   }
+   
+   
+   if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+     stop("No agreement in Var")
+   }
+   
+   
+ 
+   if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowMeans")
+   }
+   
+   
+   if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colMeans")
+   }
+   
+   
+   if(any(abs(rowSums(buff.matrix,na.rm=TRUE)  -  apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in rowSums")
+   }
+   
+   
+   if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colSums")
+   }
+   
+   ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when 
+   ### computing variance
+   my.Var <- function(x,na.rm=FALSE){
+    if (all(is.na(x))){
+      return(NA)
+    } else {
+      var(x,na.rm=na.rm)
+    }
+ 
+   }
+   
+   if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+   
+   
+   if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+ 
+ 
+   if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+ 
+   if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+   
+   
+   if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+   
+ 
+   if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+ 
+   if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMedian")
+   }
+ 
+   if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colRanges")
+   }
+ 
+ 
+   
+ }
> 
> 
> 
> 
> 
> 
> 
> 
> 
> for (rep in 1:20){
+   copymatrix <- matrix(rnorm(200,150,15),10,20)
+   
+   tmp5[1:10,1:20] <- copymatrix
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ## now lets assign some NA values and check agreement
+ 
+   which.row <- sample(1:10,1,replace=TRUE)
+   which.col  <- sample(1:20,1,replace=TRUE)
+   
+   cat(which.row," ",which.col,"\n")
+   
+   tmp5[which.row,which.col] <- NA
+   copymatrix[which.row,which.col] <- NA
+   
+   agree.checks(tmp5,copymatrix)
+ 
+   ## make an entire row NA
+   tmp5[which.row,] <- NA
+   copymatrix[which.row,] <- NA
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ### also make an entire col NA
+   tmp5[,which.col] <- NA
+   copymatrix[,which.col] <- NA
+ 
+   agree.checks(tmp5,copymatrix)
+ 
+   ### now make 1 element non NA with NA in the rest of row and column
+ 
+   tmp5[which.row,which.col] <- rnorm(1,150,15)
+   copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+ 
+   agree.checks(tmp5,copymatrix)
+ }
9   5 
4   18 
1   8 
5   5 
3   14 
2   12 
7   20 
1   2 
10   2 
3   9 
10   1 
5   12 
8   14 
8   12 
8   4 
2   15 
6   10 
10   10 
1   1 
2   18 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> ### now test 1 by n and n by 1 matrix
> 
> 
> err.tol <- 1e-12
> 
> rm(tmp5)
> 
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
> 
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
> 
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
> 
> 
> 
> 
> 
> Max(tmp)
[1] 2.519074
> Min(tmp)
[1] -3.578609
> mean(tmp)
[1] -0.05473623
> Sum(tmp)
[1] -5.473623
> Var(tmp)
[1] 1.205853
> 
> rowMeans(tmp)
[1] -0.05473623
> rowSums(tmp)
[1] -5.473623
> rowVars(tmp)
[1] 1.205853
> rowSd(tmp)
[1] 1.098113
> rowMax(tmp)
[1] 2.519074
> rowMin(tmp)
[1] -3.578609
> 
> colMeans(tmp)
  [1] -0.893510373 -1.406917781  1.480850210 -1.596825146  0.126353849
  [6] -0.729089291 -1.043840085  0.810958587 -0.682850025  0.101008147
 [11] -0.245541386  0.682835605 -0.156529265 -0.981570643 -1.125753636
 [16]  0.462357406  0.342090867  1.079926084  0.031969173  1.058184151
 [21] -0.569204412 -0.598110115  1.556023881 -0.497832639 -1.438766416
 [26] -0.923379875  0.063270935  0.113370793  0.913479863 -1.237495183
 [31]  0.075883734  0.196959785 -0.627714635 -0.624941002 -3.222886261
 [36] -1.750730870  0.450863532  0.022262532  0.662681173  0.504107014
 [41] -0.658281004  0.384304827 -0.008500207  1.010567324 -0.429678756
 [46]  0.173876420  0.082645606  1.313453480 -0.423275634  1.036786529
 [51] -0.522788146 -1.574743482 -0.246883523  1.462457415  0.639219862
 [56]  0.306261381 -1.988427746 -0.346345760 -0.272625070 -0.595711265
 [61]  0.843043183  2.519074239  1.317445036  0.701762099 -1.024176708
 [66] -0.233889401  0.460071967 -1.312369032  1.456480212  2.119896271
 [71] -0.317352721  0.205314814  1.717844144  1.400037449  1.394602230
 [76]  1.234619380  1.940103305 -0.052803393 -0.316237740  1.464392026
 [81] -3.578608815  0.044152633 -1.839403950  2.072674344 -1.010596654
 [86]  0.688560676 -1.638731458 -1.635833674 -0.966836477 -0.810107714
 [91]  0.448712566 -0.795202114 -0.858666689  0.501381604 -0.665367658
 [96] -0.121452973  0.181158194 -0.695402577 -0.324043190  0.287872979
> colSums(tmp)
  [1] -0.893510373 -1.406917781  1.480850210 -1.596825146  0.126353849
  [6] -0.729089291 -1.043840085  0.810958587 -0.682850025  0.101008147
 [11] -0.245541386  0.682835605 -0.156529265 -0.981570643 -1.125753636
 [16]  0.462357406  0.342090867  1.079926084  0.031969173  1.058184151
 [21] -0.569204412 -0.598110115  1.556023881 -0.497832639 -1.438766416
 [26] -0.923379875  0.063270935  0.113370793  0.913479863 -1.237495183
 [31]  0.075883734  0.196959785 -0.627714635 -0.624941002 -3.222886261
 [36] -1.750730870  0.450863532  0.022262532  0.662681173  0.504107014
 [41] -0.658281004  0.384304827 -0.008500207  1.010567324 -0.429678756
 [46]  0.173876420  0.082645606  1.313453480 -0.423275634  1.036786529
 [51] -0.522788146 -1.574743482 -0.246883523  1.462457415  0.639219862
 [56]  0.306261381 -1.988427746 -0.346345760 -0.272625070 -0.595711265
 [61]  0.843043183  2.519074239  1.317445036  0.701762099 -1.024176708
 [66] -0.233889401  0.460071967 -1.312369032  1.456480212  2.119896271
 [71] -0.317352721  0.205314814  1.717844144  1.400037449  1.394602230
 [76]  1.234619380  1.940103305 -0.052803393 -0.316237740  1.464392026
 [81] -3.578608815  0.044152633 -1.839403950  2.072674344 -1.010596654
 [86]  0.688560676 -1.638731458 -1.635833674 -0.966836477 -0.810107714
 [91]  0.448712566 -0.795202114 -0.858666689  0.501381604 -0.665367658
 [96] -0.121452973  0.181158194 -0.695402577 -0.324043190  0.287872979
> 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] -0.893510373 -1.406917781  1.480850210 -1.596825146  0.126353849
  [6] -0.729089291 -1.043840085  0.810958587 -0.682850025  0.101008147
 [11] -0.245541386  0.682835605 -0.156529265 -0.981570643 -1.125753636
 [16]  0.462357406  0.342090867  1.079926084  0.031969173  1.058184151
 [21] -0.569204412 -0.598110115  1.556023881 -0.497832639 -1.438766416
 [26] -0.923379875  0.063270935  0.113370793  0.913479863 -1.237495183
 [31]  0.075883734  0.196959785 -0.627714635 -0.624941002 -3.222886261
 [36] -1.750730870  0.450863532  0.022262532  0.662681173  0.504107014
 [41] -0.658281004  0.384304827 -0.008500207  1.010567324 -0.429678756
 [46]  0.173876420  0.082645606  1.313453480 -0.423275634  1.036786529
 [51] -0.522788146 -1.574743482 -0.246883523  1.462457415  0.639219862
 [56]  0.306261381 -1.988427746 -0.346345760 -0.272625070 -0.595711265
 [61]  0.843043183  2.519074239  1.317445036  0.701762099 -1.024176708
 [66] -0.233889401  0.460071967 -1.312369032  1.456480212  2.119896271
 [71] -0.317352721  0.205314814  1.717844144  1.400037449  1.394602230
 [76]  1.234619380  1.940103305 -0.052803393 -0.316237740  1.464392026
 [81] -3.578608815  0.044152633 -1.839403950  2.072674344 -1.010596654
 [86]  0.688560676 -1.638731458 -1.635833674 -0.966836477 -0.810107714
 [91]  0.448712566 -0.795202114 -0.858666689  0.501381604 -0.665367658
 [96] -0.121452973  0.181158194 -0.695402577 -0.324043190  0.287872979
> colMin(tmp)
  [1] -0.893510373 -1.406917781  1.480850210 -1.596825146  0.126353849
  [6] -0.729089291 -1.043840085  0.810958587 -0.682850025  0.101008147
 [11] -0.245541386  0.682835605 -0.156529265 -0.981570643 -1.125753636
 [16]  0.462357406  0.342090867  1.079926084  0.031969173  1.058184151
 [21] -0.569204412 -0.598110115  1.556023881 -0.497832639 -1.438766416
 [26] -0.923379875  0.063270935  0.113370793  0.913479863 -1.237495183
 [31]  0.075883734  0.196959785 -0.627714635 -0.624941002 -3.222886261
 [36] -1.750730870  0.450863532  0.022262532  0.662681173  0.504107014
 [41] -0.658281004  0.384304827 -0.008500207  1.010567324 -0.429678756
 [46]  0.173876420  0.082645606  1.313453480 -0.423275634  1.036786529
 [51] -0.522788146 -1.574743482 -0.246883523  1.462457415  0.639219862
 [56]  0.306261381 -1.988427746 -0.346345760 -0.272625070 -0.595711265
 [61]  0.843043183  2.519074239  1.317445036  0.701762099 -1.024176708
 [66] -0.233889401  0.460071967 -1.312369032  1.456480212  2.119896271
 [71] -0.317352721  0.205314814  1.717844144  1.400037449  1.394602230
 [76]  1.234619380  1.940103305 -0.052803393 -0.316237740  1.464392026
 [81] -3.578608815  0.044152633 -1.839403950  2.072674344 -1.010596654
 [86]  0.688560676 -1.638731458 -1.635833674 -0.966836477 -0.810107714
 [91]  0.448712566 -0.795202114 -0.858666689  0.501381604 -0.665367658
 [96] -0.121452973  0.181158194 -0.695402577 -0.324043190  0.287872979
> colMedians(tmp)
  [1] -0.893510373 -1.406917781  1.480850210 -1.596825146  0.126353849
  [6] -0.729089291 -1.043840085  0.810958587 -0.682850025  0.101008147
 [11] -0.245541386  0.682835605 -0.156529265 -0.981570643 -1.125753636
 [16]  0.462357406  0.342090867  1.079926084  0.031969173  1.058184151
 [21] -0.569204412 -0.598110115  1.556023881 -0.497832639 -1.438766416
 [26] -0.923379875  0.063270935  0.113370793  0.913479863 -1.237495183
 [31]  0.075883734  0.196959785 -0.627714635 -0.624941002 -3.222886261
 [36] -1.750730870  0.450863532  0.022262532  0.662681173  0.504107014
 [41] -0.658281004  0.384304827 -0.008500207  1.010567324 -0.429678756
 [46]  0.173876420  0.082645606  1.313453480 -0.423275634  1.036786529
 [51] -0.522788146 -1.574743482 -0.246883523  1.462457415  0.639219862
 [56]  0.306261381 -1.988427746 -0.346345760 -0.272625070 -0.595711265
 [61]  0.843043183  2.519074239  1.317445036  0.701762099 -1.024176708
 [66] -0.233889401  0.460071967 -1.312369032  1.456480212  2.119896271
 [71] -0.317352721  0.205314814  1.717844144  1.400037449  1.394602230
 [76]  1.234619380  1.940103305 -0.052803393 -0.316237740  1.464392026
 [81] -3.578608815  0.044152633 -1.839403950  2.072674344 -1.010596654
 [86]  0.688560676 -1.638731458 -1.635833674 -0.966836477 -0.810107714
 [91]  0.448712566 -0.795202114 -0.858666689  0.501381604 -0.665367658
 [96] -0.121452973  0.181158194 -0.695402577 -0.324043190  0.287872979
> colRanges(tmp)
           [,1]      [,2]    [,3]      [,4]      [,5]       [,6]     [,7]
[1,] -0.8935104 -1.406918 1.48085 -1.596825 0.1263538 -0.7290893 -1.04384
[2,] -0.8935104 -1.406918 1.48085 -1.596825 0.1263538 -0.7290893 -1.04384
          [,8]     [,9]     [,10]      [,11]     [,12]      [,13]      [,14]
[1,] 0.8109586 -0.68285 0.1010081 -0.2455414 0.6828356 -0.1565293 -0.9815706
[2,] 0.8109586 -0.68285 0.1010081 -0.2455414 0.6828356 -0.1565293 -0.9815706
         [,15]     [,16]     [,17]    [,18]      [,19]    [,20]      [,21]
[1,] -1.125754 0.4623574 0.3420909 1.079926 0.03196917 1.058184 -0.5692044
[2,] -1.125754 0.4623574 0.3420909 1.079926 0.03196917 1.058184 -0.5692044
          [,22]    [,23]      [,24]     [,25]      [,26]      [,27]     [,28]
[1,] -0.5981101 1.556024 -0.4978326 -1.438766 -0.9233799 0.06327093 0.1133708
[2,] -0.5981101 1.556024 -0.4978326 -1.438766 -0.9233799 0.06327093 0.1133708
         [,29]     [,30]      [,31]     [,32]      [,33]     [,34]     [,35]
[1,] 0.9134799 -1.237495 0.07588373 0.1969598 -0.6277146 -0.624941 -3.222886
[2,] 0.9134799 -1.237495 0.07588373 0.1969598 -0.6277146 -0.624941 -3.222886
         [,36]     [,37]      [,38]     [,39]    [,40]     [,41]     [,42]
[1,] -1.750731 0.4508635 0.02226253 0.6626812 0.504107 -0.658281 0.3843048
[2,] -1.750731 0.4508635 0.02226253 0.6626812 0.504107 -0.658281 0.3843048
            [,43]    [,44]      [,45]     [,46]      [,47]    [,48]      [,49]
[1,] -0.008500207 1.010567 -0.4296788 0.1738764 0.08264561 1.313453 -0.4232756
[2,] -0.008500207 1.010567 -0.4296788 0.1738764 0.08264561 1.313453 -0.4232756
        [,50]      [,51]     [,52]      [,53]    [,54]     [,55]     [,56]
[1,] 1.036787 -0.5227881 -1.574743 -0.2468835 1.462457 0.6392199 0.3062614
[2,] 1.036787 -0.5227881 -1.574743 -0.2468835 1.462457 0.6392199 0.3062614
         [,57]      [,58]      [,59]      [,60]     [,61]    [,62]    [,63]
[1,] -1.988428 -0.3463458 -0.2726251 -0.5957113 0.8430432 2.519074 1.317445
[2,] -1.988428 -0.3463458 -0.2726251 -0.5957113 0.8430432 2.519074 1.317445
         [,64]     [,65]      [,66]    [,67]     [,68]   [,69]    [,70]
[1,] 0.7017621 -1.024177 -0.2338894 0.460072 -1.312369 1.45648 2.119896
[2,] 0.7017621 -1.024177 -0.2338894 0.460072 -1.312369 1.45648 2.119896
          [,71]     [,72]    [,73]    [,74]    [,75]    [,76]    [,77]
[1,] -0.3173527 0.2053148 1.717844 1.400037 1.394602 1.234619 1.940103
[2,] -0.3173527 0.2053148 1.717844 1.400037 1.394602 1.234619 1.940103
           [,78]      [,79]    [,80]     [,81]      [,82]     [,83]    [,84]
[1,] -0.05280339 -0.3162377 1.464392 -3.578609 0.04415263 -1.839404 2.072674
[2,] -0.05280339 -0.3162377 1.464392 -3.578609 0.04415263 -1.839404 2.072674
         [,85]     [,86]     [,87]     [,88]      [,89]      [,90]     [,91]
[1,] -1.010597 0.6885607 -1.638731 -1.635834 -0.9668365 -0.8101077 0.4487126
[2,] -1.010597 0.6885607 -1.638731 -1.635834 -0.9668365 -0.8101077 0.4487126
          [,92]      [,93]     [,94]      [,95]     [,96]     [,97]      [,98]
[1,] -0.7952021 -0.8586667 0.5013816 -0.6653677 -0.121453 0.1811582 -0.6954026
[2,] -0.7952021 -0.8586667 0.5013816 -0.6653677 -0.121453 0.1811582 -0.6954026
          [,99]   [,100]
[1,] -0.3240432 0.287873
[2,] -0.3240432 0.287873
> 
> 
> Max(tmp2)
[1] 2.265421
> Min(tmp2)
[1] -2.887667
> mean(tmp2)
[1] 0.02955143
> Sum(tmp2)
[1] 2.955143
> Var(tmp2)
[1] 0.9408342
> 
> rowMeans(tmp2)
  [1] -0.68497097  1.46006818 -0.53238919  2.24400989 -0.04860129 -0.29416456
  [7] -1.44978189  0.89093824 -0.90036433 -1.03768713 -0.57283235 -1.09684875
 [13]  1.38984199 -0.21971234 -0.68378754  1.30322530  0.26979562  0.38444934
 [19] -0.74306979 -0.72785705  1.64210466 -0.28506666  1.56040998 -1.17669004
 [25]  0.13632741  1.36541129  0.38228625  0.15285755  1.14600428  0.46318445
 [31] -1.62834301  1.15597419 -0.17666786  0.85782311  2.17608758  0.83280805
 [37] -0.81210504  1.02841510 -0.53497169 -0.34414872  0.89055330 -0.66571680
 [43] -0.36986037  0.01035013  0.43180041 -1.38451660 -1.56853307 -0.76936272
 [49]  0.25855082 -0.09909284  1.06344937  1.09024674  0.61553547 -1.04196656
 [55] -0.26213994 -1.45780036  0.39707956  0.14525400  0.32425919  0.64537404
 [61] -0.25855944  0.70876093 -0.10373997  0.33888030 -0.59165502  0.15482112
 [67]  0.94474586 -1.29925092  1.12899681  0.39380322 -0.12714013  0.68978112
 [73] -0.44229162 -0.02740709  0.12707797 -0.09512242  1.00466226  1.14630801
 [79] -0.92499943 -0.88718559 -0.43009231 -1.20587709  1.25210405 -0.50903861
 [85] -1.35474724 -2.88766716 -0.60799269  1.23056825  1.08140805 -0.35872737
 [91] -0.50185363 -0.12563443 -0.54601379  0.60878237  0.46015293  0.46988338
 [97] -1.45499914  2.26542077 -1.57434143  0.11789587
> rowSums(tmp2)
  [1] -0.68497097  1.46006818 -0.53238919  2.24400989 -0.04860129 -0.29416456
  [7] -1.44978189  0.89093824 -0.90036433 -1.03768713 -0.57283235 -1.09684875
 [13]  1.38984199 -0.21971234 -0.68378754  1.30322530  0.26979562  0.38444934
 [19] -0.74306979 -0.72785705  1.64210466 -0.28506666  1.56040998 -1.17669004
 [25]  0.13632741  1.36541129  0.38228625  0.15285755  1.14600428  0.46318445
 [31] -1.62834301  1.15597419 -0.17666786  0.85782311  2.17608758  0.83280805
 [37] -0.81210504  1.02841510 -0.53497169 -0.34414872  0.89055330 -0.66571680
 [43] -0.36986037  0.01035013  0.43180041 -1.38451660 -1.56853307 -0.76936272
 [49]  0.25855082 -0.09909284  1.06344937  1.09024674  0.61553547 -1.04196656
 [55] -0.26213994 -1.45780036  0.39707956  0.14525400  0.32425919  0.64537404
 [61] -0.25855944  0.70876093 -0.10373997  0.33888030 -0.59165502  0.15482112
 [67]  0.94474586 -1.29925092  1.12899681  0.39380322 -0.12714013  0.68978112
 [73] -0.44229162 -0.02740709  0.12707797 -0.09512242  1.00466226  1.14630801
 [79] -0.92499943 -0.88718559 -0.43009231 -1.20587709  1.25210405 -0.50903861
 [85] -1.35474724 -2.88766716 -0.60799269  1.23056825  1.08140805 -0.35872737
 [91] -0.50185363 -0.12563443 -0.54601379  0.60878237  0.46015293  0.46988338
 [97] -1.45499914  2.26542077 -1.57434143  0.11789587
> 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] -0.68497097  1.46006818 -0.53238919  2.24400989 -0.04860129 -0.29416456
  [7] -1.44978189  0.89093824 -0.90036433 -1.03768713 -0.57283235 -1.09684875
 [13]  1.38984199 -0.21971234 -0.68378754  1.30322530  0.26979562  0.38444934
 [19] -0.74306979 -0.72785705  1.64210466 -0.28506666  1.56040998 -1.17669004
 [25]  0.13632741  1.36541129  0.38228625  0.15285755  1.14600428  0.46318445
 [31] -1.62834301  1.15597419 -0.17666786  0.85782311  2.17608758  0.83280805
 [37] -0.81210504  1.02841510 -0.53497169 -0.34414872  0.89055330 -0.66571680
 [43] -0.36986037  0.01035013  0.43180041 -1.38451660 -1.56853307 -0.76936272
 [49]  0.25855082 -0.09909284  1.06344937  1.09024674  0.61553547 -1.04196656
 [55] -0.26213994 -1.45780036  0.39707956  0.14525400  0.32425919  0.64537404
 [61] -0.25855944  0.70876093 -0.10373997  0.33888030 -0.59165502  0.15482112
 [67]  0.94474586 -1.29925092  1.12899681  0.39380322 -0.12714013  0.68978112
 [73] -0.44229162 -0.02740709  0.12707797 -0.09512242  1.00466226  1.14630801
 [79] -0.92499943 -0.88718559 -0.43009231 -1.20587709  1.25210405 -0.50903861
 [85] -1.35474724 -2.88766716 -0.60799269  1.23056825  1.08140805 -0.35872737
 [91] -0.50185363 -0.12563443 -0.54601379  0.60878237  0.46015293  0.46988338
 [97] -1.45499914  2.26542077 -1.57434143  0.11789587
> rowMin(tmp2)
  [1] -0.68497097  1.46006818 -0.53238919  2.24400989 -0.04860129 -0.29416456
  [7] -1.44978189  0.89093824 -0.90036433 -1.03768713 -0.57283235 -1.09684875
 [13]  1.38984199 -0.21971234 -0.68378754  1.30322530  0.26979562  0.38444934
 [19] -0.74306979 -0.72785705  1.64210466 -0.28506666  1.56040998 -1.17669004
 [25]  0.13632741  1.36541129  0.38228625  0.15285755  1.14600428  0.46318445
 [31] -1.62834301  1.15597419 -0.17666786  0.85782311  2.17608758  0.83280805
 [37] -0.81210504  1.02841510 -0.53497169 -0.34414872  0.89055330 -0.66571680
 [43] -0.36986037  0.01035013  0.43180041 -1.38451660 -1.56853307 -0.76936272
 [49]  0.25855082 -0.09909284  1.06344937  1.09024674  0.61553547 -1.04196656
 [55] -0.26213994 -1.45780036  0.39707956  0.14525400  0.32425919  0.64537404
 [61] -0.25855944  0.70876093 -0.10373997  0.33888030 -0.59165502  0.15482112
 [67]  0.94474586 -1.29925092  1.12899681  0.39380322 -0.12714013  0.68978112
 [73] -0.44229162 -0.02740709  0.12707797 -0.09512242  1.00466226  1.14630801
 [79] -0.92499943 -0.88718559 -0.43009231 -1.20587709  1.25210405 -0.50903861
 [85] -1.35474724 -2.88766716 -0.60799269  1.23056825  1.08140805 -0.35872737
 [91] -0.50185363 -0.12563443 -0.54601379  0.60878237  0.46015293  0.46988338
 [97] -1.45499914  2.26542077 -1.57434143  0.11789587
> 
> colMeans(tmp2)
[1] 0.02955143
> colSums(tmp2)
[1] 2.955143
> colVars(tmp2)
[1] 0.9408342
> colSd(tmp2)
[1] 0.9699661
> colMax(tmp2)
[1] 2.265421
> colMin(tmp2)
[1] -2.887667
> colMedians(tmp2)
[1] -0.03800419
> colRanges(tmp2)
          [,1]
[1,] -2.887667
[2,]  2.265421
> 
> dataset1 <- matrix(dataset1,1,100)
> 
> agree.checks(tmp,dataset1)
> 
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>   
> 
> tmp <- createBufferedMatrix(10,10)
> 
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
 [1] -1.8976831 -4.6790177  5.9152885  2.0523701 -4.1253474  2.2863526
 [7]  3.3821454  3.0418564  0.5561972 -3.1988190
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.4310565
[2,] -0.7419885
[3,] -0.1238176
[4,]  0.1434086
[5,]  1.6026313
> 
> rowApply(tmp,sum)
 [1]  1.1601339  1.2820638  5.2225633 -2.2610654 -2.0449950 -3.8236352
 [7]  0.6002209  2.4953138  2.4065555 -1.7038126
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    6    4    4    3    3    6    1   10    1     7
 [2,]    7    2    5    6    4    2    2    5    7     1
 [3,]    5    9    9   10    6   10    4    7    6     4
 [4,]   10    7    3    2    7    9    9    8    2     3
 [5,]    1    1    1    9    2    3    5    3    5     9
 [6,]    9    3    2    8    9    5    6    6    9     2
 [7,]    3   10    6    4   10    8    8    2    8     5
 [8,]    8    8    7    1    1    7   10    9   10     8
 [9,]    2    6   10    7    5    4    3    4    4    10
[10,]    4    5    8    5    8    1    7    1    3     6
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  1.5215369 -1.8704544  1.4091194 -5.3441076 -3.0336424  1.7949364
 [7] -2.4359946  0.6041238  1.6292974  1.9704832 -2.2747822 -0.9493569
[13]  1.6024805  1.9796877 -3.7203760 -0.5665073  0.1486802  1.9841115
[19] -1.2937505 -1.2406924
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -0.6787913
[2,]  0.1548257
[3,]  0.5754497
[4,]  0.6913576
[5,]  0.7786953
> 
> rowApply(tmp,sum)
[1]  -3.571651 -14.019252  -2.723463   2.621486   9.607672
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]   18   11   16   17    5
[2,]   16    3   13   19    1
[3,]   13   17   10    8   15
[4,]    1    2    3   18    4
[5,]    9    1    1   16    9
> 
> 
> as.matrix(tmp)
           [,1]       [,2]        [,3]       [,4]        [,5]       [,6]
[1,]  0.6913576  0.6403120  0.49629885 -3.3486719  0.05327254  1.3473253
[2,] -0.6787913 -1.6809654  0.07525872 -1.9125917 -2.03110971 -0.6078088
[3,]  0.5754497  0.2433256  0.11858799 -1.2342082 -2.20696844 -1.0628124
[4,]  0.7786953  1.0212838 -0.12776473  1.0099228  0.70186704  1.6174021
[5,]  0.1548257 -2.0944104  0.84673855  0.1414414  0.44929617  0.5008302
            [,7]        [,8]       [,9]     [,10]      [,11]       [,12]
[1,] -1.01128092 -0.18706694  0.6522350 0.8631248  0.5887258  0.09294713
[2,] -1.65715520 -0.03271061 -0.9202168 0.2901488 -1.0782549 -0.78755060
[3,]  0.04661574  0.43960878 -0.3153537 0.1897834 -1.5245117  0.74831480
[4,] -0.39016898 -0.33932403  0.3054315 0.3052195 -0.6523326 -1.16359109
[5,]  0.57599471  0.72361655  1.9072014 0.3222067  0.3915912  0.16052287
          [,13]       [,14]      [,15]      [,16]      [,17]       [,18]
[1,]  0.5601352  0.06111727 -0.4608370 -1.4949874 -1.1228300  0.41911414
[2,] -1.0935459 -1.21603512 -0.8450722  0.5931275 -0.2669998  0.08490432
[3,]  1.7477500  0.88115211 -0.9861928  0.8922675  0.1502846 -0.83497180
[4,] -0.5230787  0.63818060 -0.5578833  0.2183008  0.4973536  0.03100708
[5,]  0.9112199  1.61527287 -0.8703906 -0.7752159  0.8908719  2.28405773
           [,19]      [,20]
[1,] -1.34157780 -1.0703645
[2,] -0.04099485 -0.2128884
[3,]  0.33687337 -0.9284572
[4,] -0.99017886  0.2411440
[5,]  0.74212768  0.7298736
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  800  bytes.
> 
> 
> 
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size:  5 5 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  649  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  561  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  480  bytes.
> 
> 
> rm(tmp)
> 
> 
> ###
> ### Testing colnames and rownames
> ###
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> 
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> tmp["row1",]
           col1      col2      col3       col4      col5       col6       col7
row1 -0.6676995 0.7393984 0.2509851 -0.3939936 -0.655009 -0.4797399 -0.9772393
           col8      col9       col10      col11      col12      col13
row1 -0.1754892 -1.829751 -0.07063634 0.02619364 -0.5091775 -0.1676355
         col14    col15      col16     col17       col18      col19    col20
row1 0.9149108 1.181722 -0.5291536 -0.901548 -0.09864412 -0.3315927 1.092642
> tmp[,"col10"]
           col10
row1 -0.07063634
row2 -0.96321493
row3 -0.30677346
row4 -0.11744792
row5 -1.58426319
> tmp[c("row1","row5"),]
           col1      col2      col3       col4       col5       col6       col7
row1 -0.6676995 0.7393984 0.2509851 -0.3939936 -0.6550090 -0.4797399 -0.9772393
row5  0.8585900 1.1191220 0.4593249  0.6487639 -0.4107521 -0.9219997 -0.7650607
           col8      col9       col10      col11      col12      col13
row1 -0.1754892 -1.829751 -0.07063634 0.02619364 -0.5091775 -0.1676355
row5  2.4357406 -0.353847 -1.58426319 0.34263227  0.6773516 -0.4065248
           col14      col15      col16     col17       col18      col19
row1  0.91491079  1.1817215 -0.5291536 -0.901548 -0.09864412 -0.3315927
row5 -0.09106465 -0.6769843 -0.4220426 -0.963312 -1.01062428 -0.8560792
         col20
row1 1.0926421
row5 0.4638794
> tmp[,c("col6","col20")]
           col6     col20
row1 -0.4797399 1.0926421
row2 -1.2096496 1.2580808
row3  0.2888534 0.6252070
row4 -0.4146441 2.3992116
row5 -0.9219997 0.4638794
> tmp[c("row1","row5"),c("col6","col20")]
           col6     col20
row1 -0.4797399 1.0926421
row5 -0.9219997 0.4638794
> 
> 
> 
> 
> 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 50.45849 50.75331 48.3474 50.06751 49.35606 104.5012 50.09127 49.20486
        col9    col10    col11    col12   col13    col14    col15    col16
row1 49.8946 48.95831 50.70816 51.05191 49.1355 51.10485 50.79022 51.38563
        col17    col18    col19    col20
row1 49.64386 49.62237 48.31123 105.3192
> tmp[,"col10"]
        col10
row1 48.95831
row2 30.41698
row3 29.82019
row4 31.21791
row5 51.93560
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 50.45849 50.75331 48.34740 50.06751 49.35606 104.5012 50.09127 49.20486
row5 49.33125 50.81241 49.51262 51.09060 49.88254 104.9801 49.37121 50.40518
         col9    col10    col11    col12    col13    col14    col15    col16
row1 49.89460 48.95831 50.70816 51.05191 49.13550 51.10485 50.79022 51.38563
row5 50.49843 51.93560 51.42214 49.18696 50.02139 50.60788 51.04207 49.34602
        col17    col18    col19    col20
row1 49.64386 49.62237 48.31123 105.3192
row5 47.58376 50.47915 50.18578 104.5737
> tmp[,c("col6","col20")]
          col6     col20
row1 104.50119 105.31917
row2  74.60627  74.54493
row3  74.32781  75.86716
row4  73.71883  75.44445
row5 104.98005 104.57371
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 104.5012 105.3192
row5 104.9801 104.5737
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 104.5012 105.3192
row5 104.9801 104.5737
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
           col13
[1,]  2.06876682
[2,] -0.15598794
[3,] -3.03009978
[4,] -0.93875993
[5,]  0.06840085
> tmp[,c("col17","col7")]
          col17       col7
[1,] -0.3243236 -0.9002190
[2,]  1.0015478 -0.7462030
[3,] -0.1817125 -0.7866812
[4,]  0.6454991 -1.6347683
[5,] -0.4459683 -0.9509082
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
           col6       col20
[1,]  0.1264306  0.20616290
[2,]  1.0126390  0.22560278
[3,]  1.8158916  0.03385136
[4,] -0.2963280  0.73070544
[5,]  1.5665386 -0.53448812
> subBufferedMatrix(tmp,1,c("col6"))[,1]
          col1
[1,] 0.1264306
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
          col6
[1,] 0.1264306
[2,] 1.0126390
> 
> 
> 
> 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]
row3 -0.1876415 0.69456513 -1.000618 -0.04799789 -0.2875465 -1.341751
row1  0.6455078 0.04176497 -1.835291 -0.47302300  0.1571399 -1.291899
           [,7]      [,8]       [,9]     [,10]     [,11]    [,12]     [,13]
row3 -0.3882909 1.3320668  0.1360087 0.7609870 0.6045881 1.279999 -1.255499
row1  0.9711116 0.1785768 -1.9756379 0.4987786 0.4089700 0.472659 -0.714682
         [,14]      [,15]     [,16]      [,17]      [,18]      [,19]
row3 -1.012811 -0.6053497 0.2568781 -0.7586623 -1.0646892  0.5462559
row1 -1.650666  1.3490874 0.1309460  1.6887882 -0.2140736 -1.6411283
           [,20]
row3  0.02585894
row1 -3.10319427
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
           [,1]       [,2]      [,3]      [,4]      [,5]     [,6]     [,7]
row2 -0.6892174 -0.6074251 0.9257204 0.7308181 0.9894275 2.251508 1.125243
          [,8]      [,9]      [,10]
row2 0.6800166 0.3134272 0.03059488
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
         [,1]      [,2]      [,3]      [,4]      [,5]      [,6]     [,7]
row5 2.141383 0.5522776 0.7397866 -1.918373 0.7352339 0.0855127 1.050848
           [,8]      [,9]      [,10]      [,11]    [,12]      [,13]    [,14]
row5 0.02615662 0.5167899 -0.3834515 -0.5834113 1.370456 -0.2556535 1.566833
          [,15]     [,16]     [,17]     [,18]    [,19]    [,20]
row5 -0.6321619 0.1615187 0.1320151 -1.217394 1.582021 1.685433
> 
> 
> 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: 0x557e02d37180>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a167518aa"
 [2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a6df49862"
 [3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a6bda04b6"
 [4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a19600259"
 [5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a24b05b8" 
 [6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a6597a0ea"
 [7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a22821105"
 [8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a5131d43e"
 [9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a64fbbb93"
[10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a426993ca"
[11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a23e2f48f"
[12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a2d4e8dfd"
[13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a397f9c9e"
[14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a2ffb3b9e"
[15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMd830a5cb2426f"
> 
> 
> ### 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: 0x557e01239fe0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x557e01239fe0>
Warning message:
In dir.create(new.directory) :
  '/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x557e01239fe0>
> rowMedians(tmp)
  [1] -0.475414602 -0.127663910 -0.143848718  0.277902981 -0.364162376
  [6]  0.358388879 -0.437162266 -0.479344264  0.057035194  0.019872339
 [11] -0.718649312  0.077856054 -0.339133495  0.471975598  0.264002567
 [16] -0.250815440 -0.133109235 -0.008873971 -0.099868232 -0.211731183
 [21] -0.303586157  0.527519652 -0.190250645  0.333563386 -0.287155213
 [26]  0.099909413  0.598431599 -0.290048763  0.135862449  0.435385765
 [31] -0.228470085  0.193020512 -0.146051287  0.747833006 -0.068007892
 [36]  0.061875045 -0.291635217 -0.646035313 -0.048302733  0.194597283
 [41]  0.019048811  0.123567875 -0.295452978 -0.107607158 -0.004766054
 [46] -0.073355559 -0.025037305  0.244712389  0.187403867 -0.118618331
 [51]  0.104316618 -0.006132854 -0.021652416  0.298126947 -0.301844953
 [56]  0.235799620  0.628336465  0.082023713  0.317462277  0.329291947
 [61]  0.097676536  0.185723494 -0.035892895  0.665837171 -0.057989168
 [66] -0.468193172 -0.236117932  0.073337008 -0.240379477 -0.105614861
 [71] -0.098662216  0.544822515 -0.291132878  0.098075014  0.084330863
 [76]  0.294318599 -0.414047436 -0.307701703 -0.666862628 -0.183350173
 [81]  0.418787288 -0.277785357 -0.116283607 -0.367972963 -0.221371768
 [86] -0.251992842 -0.085473759  0.085597015 -0.004448783  0.289305944
 [91]  0.404310726  0.119926177  0.169522641  0.066150481  0.273402822
 [96] -0.116552996  0.021287755  0.171263312 -0.013165881  0.607573443
[101] -0.044732196  0.052975697 -0.067457855 -0.350894282 -0.191193986
[106] -0.689007005 -0.703259472  0.107019851  0.192352870 -0.204628512
[111] -0.032123537  0.337991852 -0.227398162  0.267694483  0.249159122
[116] -0.033478740  0.212919899  0.383846870 -0.589580757 -0.122425171
[121]  0.234651044  0.470991804  0.373987342 -0.517244896 -0.634508494
[126]  0.473863358 -0.304674608 -0.225588930  0.321571987  0.052923459
[131] -0.269426945 -0.564270525  0.015052013 -0.055981892 -0.071071534
[136]  0.007737562  0.046485989 -0.077833889 -0.502707223  0.163686173
[141]  0.401872178  0.087737575 -0.470217861 -0.047290182  0.462367755
[146]  0.623479671 -0.216361704  0.438774312 -0.289655728 -0.045294249
[151]  0.070090337 -0.121323677 -0.001552026  0.030479481 -0.244115398
[156] -0.657122991 -0.566214383 -0.256004652 -0.534842411 -0.108721146
[161] -0.044655997 -0.229284186 -0.343134263  0.130162138  0.297999749
[166]  0.277050848  0.037145526 -0.590202255 -0.347473288 -0.298707755
[171]  0.133862108  0.387828057 -0.114786453  0.121527185  0.035611085
[176] -0.339568102  0.170245722  0.281669065 -0.562720653  0.257928738
[181] -0.203157862 -0.296046356  0.162059910  0.370246032 -0.055706003
[186]  0.310143834  0.306604563  0.014983248  0.317812261 -0.158701756
[191]  0.322614515 -0.238327754  0.446289222  0.006253772 -0.175521623
[196] -0.170761776  0.089932514  0.163864560  0.125803092  0.245131516
[201] -0.265831371  0.132033974  0.028544168  0.057159164 -0.298791267
[206] -0.110604866 -0.611921702 -0.078036610 -0.097651178 -0.292382079
[211]  0.116598559 -0.024002385 -0.198738419  0.263890851  0.254800917
[216]  0.489317975 -0.535404292 -0.088484264  0.233142790 -0.170787616
[221]  0.140271314  0.118901458 -0.124437014 -0.610083602 -0.364972589
[226] -0.114605691 -0.256402288 -0.471635997  0.072660644  0.037851141
> 
> proc.time()
   user  system elapsed 
  1.419   1.791   3.209 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> prefix <- "dbmtest"
> directory <- getwd()
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0x5558e2f47b80>
> .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: 0x5558e2f47b80>
> .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: 0x5558e2f47b80>
> .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: 0x5558e2f47b80>
> 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: 0x5558e25bd290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e25bd290>
> .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: 0x5558e25bd290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e25bd290>
> .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: 0x5558e25bd290>
> 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: 0x5558e337c1a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e337c1a0>
> .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: 0x5558e337c1a0>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5558e337c1a0>
> .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: 0x5558e337c1a0>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x5558e337c1a0>
> .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: 0x5558e337c1a0>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x5558e337c1a0>
> .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: 0x5558e337c1a0>
> 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: 0x5558e2d52440>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5558e2d52440>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e2d52440>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e2d52440>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiled91531d084989" "BufferedMatrixFiled91535edc504e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiled91531d084989" "BufferedMatrixFiled91535edc504e"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e3183aa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e3183aa0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5558e3183aa0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5558e3183aa0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5558e3183aa0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5558e3183aa0>
> .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: 0x5558e345afc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5558e345afc0>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5558e345afc0>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5558e345afc0>
> 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: 0x5558e40c7770>
> .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: 0x5558e40c7770>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.258   0.067   0.316 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

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

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

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

> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100   0
> buffer.dim(Temp)
[1] 1 1
> 
> 
> proc.time()
   user  system elapsed 
  0.259   0.049   0.297 

Example timings