Ben Bolstad
| Snapshot Date: 2026-05-20 13:45 -0400 (Wed, 20 May 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 2d99771 |
| git_last_commit_date: 2026-04-28 08:32:08 -0400 (Tue, 28 Apr 2026) |
| Back to Build/check report for BioC 3.24: simplified long |
|
This page was generated on 2026-05-21 11:33 -0400 (Thu, 21 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4936 |
| 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 259/2378 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.77.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
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. |
| Package: BufferedMatrix |
| Version: 1.77.0 |
| Command: /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings BufferedMatrix_1.77.0.tar.gz |
| StartedAt: 2026-05-20 21:58:40 -0400 (Wed, 20 May 2026) |
| EndedAt: 2026-05-20 21:59:04 -0400 (Wed, 20 May 2026) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings BufferedMatrix_1.77.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-21 01:58:41 UTC
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.77.0’
* 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 13.3.0-6ubuntu2~24.04.1) 13.3.0’
* 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 ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ...* 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: 1 NOTE
See
‘/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.77.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.24-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.24-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.24-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.24-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.24-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-3.24-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.24-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)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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
0.245 0.038 0.272
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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-3.24-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 480233 25.7 1053308 56.3 637571 34.1
Vcells 887253 6.8 8388608 64.0 2083896 15.9
>
>
>
>
> ##
> ## 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 May 20 21:58:56 2026"
> 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 May 20 21:58:56 2026"
>
>
> 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: 0x587fdd001520>
>
>
>
> 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 May 20 21:58:56 2026"
> 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 May 20 21:58:56 2026"
>
> ColMode(tmp2)
<pointer: 0x587fdd001520>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.9432684 -0.6317843 -0.4256373 0.09090355
[2,] 0.6420287 0.4103068 -0.5630367 -1.03029726
[3,] -0.9759818 -0.5674987 -0.8532136 0.40319947
[4,] -0.8331290 -0.8942566 -0.2161136 -1.08730432
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.9432684 0.6317843 0.4256373 0.09090355
[2,] 0.6420287 0.4103068 0.5630367 1.03029726
[3,] 0.9759818 0.5674987 0.8532136 0.40319947
[4,] 0.8331290 0.8942566 0.2161136 1.08730432
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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,] 9.9971630 0.7948486 0.6524089 0.3015022
[2,] 0.8012669 0.6405520 0.7503577 1.0150356
[3,] 0.9879179 0.7533251 0.9236956 0.6349799
[4,] 0.9127590 0.9456514 0.4648802 1.0427389
>
> 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-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.91490 33.58027 31.94973 28.10593
[2,] 33.65470 31.81583 33.06661 36.18065
[3,] 35.85516 33.10075 35.09017 31.75300
[4,] 34.96072 35.35077 29.86492 36.51469
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x587fdddec8f0>
> exp(tmp5)
<pointer: 0x587fdddec8f0>
> log(tmp5,2)
<pointer: 0x587fdddec8f0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.1309
> Min(tmp5)
[1] 52.46856
> mean(tmp5)
[1] 72.71088
> Sum(tmp5)
[1] 14542.18
> Var(tmp5)
[1] 861.9454
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.54697 70.42192 70.14871 68.52061 70.10895 72.73546 69.27390 72.38558
[9] 70.25841 75.70829
> rowSums(tmp5)
[1] 1750.939 1408.438 1402.974 1370.412 1402.179 1454.709 1385.478 1447.712
[9] 1405.168 1514.166
> rowVars(tmp5)
[1] 8077.06403 62.64237 70.51021 61.89339 116.47365 103.03569
[7] 40.77051 58.17556 73.16795 65.94664
> rowSd(tmp5)
[1] 89.872488 7.914693 8.397036 7.867235 10.792296 10.150650 6.385179
[8] 7.627291 8.553826 8.120754
> rowMax(tmp5)
[1] 468.13089 85.88665 88.40725 84.61836 95.91755 88.58263 77.46873
[8] 88.16974 85.58418 91.96780
> rowMin(tmp5)
[1] 57.84902 60.02693 54.54617 55.26392 53.96026 54.64938 52.46856 60.59256
[9] 55.17787 59.13776
>
> colMeans(tmp5)
[1] 109.81593 72.35803 67.86300 72.51356 69.28992 73.53120 71.13930
[8] 76.48207 72.35947 66.14591 66.10715 72.46390 70.59356 72.70727
[15] 70.63081 75.30957 70.11166 69.45144 65.51371 69.83015
> colSums(tmp5)
[1] 1098.1593 723.5803 678.6300 725.1356 692.8992 735.3120 711.3930
[8] 764.8207 723.5947 661.4591 661.0715 724.6390 705.9356 727.0727
[15] 706.3081 753.0957 701.1166 694.5144 655.1371 698.3015
> colVars(tmp5)
[1] 15919.36306 34.12535 48.76204 103.09546 87.66069 28.40591
[7] 88.58346 70.90075 64.88781 95.26441 35.59082 69.74128
[13] 89.04303 82.04644 172.94537 65.44854 45.71857 68.23343
[19] 46.43274 54.04211
> colSd(tmp5)
[1] 126.171958 5.841691 6.982982 10.153594 9.362729 5.329719
[7] 9.411879 8.420258 8.055297 9.760349 5.965804 8.351124
[13] 9.436261 9.057949 13.150870 8.090027 6.761551 8.260353
[19] 6.814157 7.351334
> colMax(tmp5)
[1] 468.13089 85.00202 79.22740 95.91755 88.40725 81.84043 86.81946
[8] 88.58263 84.24513 84.61836 77.46873 85.58418 88.16974 83.87933
[15] 91.96780 86.01261 80.70105 81.47373 81.97600 82.77714
> colMin(tmp5)
[1] 58.78075 65.03275 57.30457 58.49880 54.64938 65.42973 57.84902 64.23576
[9] 59.84034 53.96026 60.30603 61.57070 58.97462 56.82008 52.46856 61.75691
[17] 61.21756 56.75608 55.26392 60.39528
>
>
> ### 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] 87.54697 70.42192 70.14871 68.52061 70.10895 72.73546 NA 72.38558
[9] 70.25841 75.70829
> rowSums(tmp5)
[1] 1750.939 1408.438 1402.974 1370.412 1402.179 1454.709 NA 1447.712
[9] 1405.168 1514.166
> rowVars(tmp5)
[1] 8077.06403 62.64237 70.51021 61.89339 116.47365 103.03569
[7] 42.05029 58.17556 73.16795 65.94664
> rowSd(tmp5)
[1] 89.872488 7.914693 8.397036 7.867235 10.792296 10.150650 6.484620
[8] 7.627291 8.553826 8.120754
> rowMax(tmp5)
[1] 468.13089 85.88665 88.40725 84.61836 95.91755 88.58263 NA
[8] 88.16974 85.58418 91.96780
> rowMin(tmp5)
[1] 57.84902 60.02693 54.54617 55.26392 53.96026 54.64938 NA 60.59256
[9] 55.17787 59.13776
>
> colMeans(tmp5)
[1] 109.81593 72.35803 67.86300 72.51356 69.28992 73.53120 71.13930
[8] 76.48207 72.35947 66.14591 66.10715 72.46390 70.59356 72.70727
[15] 70.63081 75.30957 NA 69.45144 65.51371 69.83015
> colSums(tmp5)
[1] 1098.1593 723.5803 678.6300 725.1356 692.8992 735.3120 711.3930
[8] 764.8207 723.5947 661.4591 661.0715 724.6390 705.9356 727.0727
[15] 706.3081 753.0957 NA 694.5144 655.1371 698.3015
> colVars(tmp5)
[1] 15919.36306 34.12535 48.76204 103.09546 87.66069 28.40591
[7] 88.58346 70.90075 64.88781 95.26441 35.59082 69.74128
[13] 89.04303 82.04644 172.94537 65.44854 NA 68.23343
[19] 46.43274 54.04211
> colSd(tmp5)
[1] 126.171958 5.841691 6.982982 10.153594 9.362729 5.329719
[7] 9.411879 8.420258 8.055297 9.760349 5.965804 8.351124
[13] 9.436261 9.057949 13.150870 8.090027 NA 8.260353
[19] 6.814157 7.351334
> colMax(tmp5)
[1] 468.13089 85.00202 79.22740 95.91755 88.40725 81.84043 86.81946
[8] 88.58263 84.24513 84.61836 77.46873 85.58418 88.16974 83.87933
[15] 91.96780 86.01261 NA 81.47373 81.97600 82.77714
> colMin(tmp5)
[1] 58.78075 65.03275 57.30457 58.49880 54.64938 65.42973 57.84902 64.23576
[9] 59.84034 53.96026 60.30603 61.57070 58.97462 56.82008 52.46856 61.75691
[17] NA 56.75608 55.26392 60.39528
>
> Max(tmp5,na.rm=TRUE)
[1] 468.1309
> Min(tmp5,na.rm=TRUE)
[1] 52.46856
> mean(tmp5,na.rm=TRUE)
[1] 72.70753
> Sum(tmp5,na.rm=TRUE)
[1] 14468.8
> Var(tmp5,na.rm=TRUE)
[1] 866.2964
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.54697 70.42192 70.14871 68.52061 70.10895 72.73546 69.05787 72.38558
[9] 70.25841 75.70829
> rowSums(tmp5,na.rm=TRUE)
[1] 1750.939 1408.438 1402.974 1370.412 1402.179 1454.709 1312.099 1447.712
[9] 1405.168 1514.166
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.06403 62.64237 70.51021 61.89339 116.47365 103.03569
[7] 42.05029 58.17556 73.16795 65.94664
> rowSd(tmp5,na.rm=TRUE)
[1] 89.872488 7.914693 8.397036 7.867235 10.792296 10.150650 6.484620
[8] 7.627291 8.553826 8.120754
> rowMax(tmp5,na.rm=TRUE)
[1] 468.13089 85.88665 88.40725 84.61836 95.91755 88.58263 77.46873
[8] 88.16974 85.58418 91.96780
> rowMin(tmp5,na.rm=TRUE)
[1] 57.84902 60.02693 54.54617 55.26392 53.96026 54.64938 52.46856 60.59256
[9] 55.17787 59.13776
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.81593 72.35803 67.86300 72.51356 69.28992 73.53120 71.13930
[8] 76.48207 72.35947 66.14591 66.10715 72.46390 70.59356 72.70727
[15] 70.63081 75.30957 69.74868 69.45144 65.51371 69.83015
> colSums(tmp5,na.rm=TRUE)
[1] 1098.1593 723.5803 678.6300 725.1356 692.8992 735.3120 711.3930
[8] 764.8207 723.5947 661.4591 661.0715 724.6390 705.9356 727.0727
[15] 706.3081 753.0957 627.7381 694.5144 655.1371 698.3015
> colVars(tmp5,na.rm=TRUE)
[1] 15919.36306 34.12535 48.76204 103.09546 87.66069 28.40591
[7] 88.58346 70.90075 64.88781 95.26441 35.59082 69.74128
[13] 89.04303 82.04644 172.94537 65.44854 49.95113 68.23343
[19] 46.43274 54.04211
> colSd(tmp5,na.rm=TRUE)
[1] 126.171958 5.841691 6.982982 10.153594 9.362729 5.329719
[7] 9.411879 8.420258 8.055297 9.760349 5.965804 8.351124
[13] 9.436261 9.057949 13.150870 8.090027 7.067612 8.260353
[19] 6.814157 7.351334
> colMax(tmp5,na.rm=TRUE)
[1] 468.13089 85.00202 79.22740 95.91755 88.40725 81.84043 86.81946
[8] 88.58263 84.24513 84.61836 77.46873 85.58418 88.16974 83.87933
[15] 91.96780 86.01261 80.70105 81.47373 81.97600 82.77714
> colMin(tmp5,na.rm=TRUE)
[1] 58.78075 65.03275 57.30457 58.49880 54.64938 65.42973 57.84902 64.23576
[9] 59.84034 53.96026 60.30603 61.57070 58.97462 56.82008 52.46856 61.75691
[17] 61.21756 56.75608 55.26392 60.39528
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.54697 70.42192 70.14871 68.52061 70.10895 72.73546 NaN 72.38558
[9] 70.25841 75.70829
> rowSums(tmp5,na.rm=TRUE)
[1] 1750.939 1408.438 1402.974 1370.412 1402.179 1454.709 0.000 1447.712
[9] 1405.168 1514.166
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.06403 62.64237 70.51021 61.89339 116.47365 103.03569
[7] NA 58.17556 73.16795 65.94664
> rowSd(tmp5,na.rm=TRUE)
[1] 89.872488 7.914693 8.397036 7.867235 10.792296 10.150650 NA
[8] 7.627291 8.553826 8.120754
> rowMax(tmp5,na.rm=TRUE)
[1] 468.13089 85.88665 88.40725 84.61836 95.91755 88.58263 NA
[8] 88.16974 85.58418 91.96780
> rowMin(tmp5,na.rm=TRUE)
[1] 57.84902 60.02693 54.54617 55.26392 53.96026 54.64938 NA 60.59256
[9] 55.17787 59.13776
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.32336 73.17195 67.60104 72.27365 69.75362 73.16641 71.06865
[8] 77.74360 72.59121 65.13908 64.84475 73.42118 70.92121 72.17956
[15] 72.64884 75.93039 NaN 68.85768 66.05431 70.41616
> colSums(tmp5,na.rm=TRUE)
[1] 1028.9103 658.5476 608.4093 650.4628 627.7826 658.4977 639.6178
[8] 699.6924 653.3209 586.2517 583.6028 660.7906 638.2909 649.6161
[15] 653.8395 683.3735 0.0000 619.7191 594.4888 633.7455
> colVars(tmp5,na.rm=TRUE)
[1] 17680.71733 30.93827 54.08528 115.33487 96.19928 30.45959
[7] 99.60023 61.85938 72.39459 95.76811 22.11113 68.14952
[13] 98.96568 89.16935 148.74864 69.29367 NA 72.79647
[19] 48.94900 56.93399
> colSd(tmp5,na.rm=TRUE)
[1] 132.968858 5.562218 7.354270 10.739407 9.808123 5.519021
[7] 9.979991 7.865074 8.508501 9.786118 4.702248 8.255272
[13] 9.948149 9.442952 12.196255 8.324282 NA 8.532085
[19] 6.996356 7.545462
> colMax(tmp5,na.rm=TRUE)
[1] 468.13089 85.00202 79.22740 95.91755 88.40725 81.84043 86.81946
[8] 88.58263 84.24513 84.61836 72.06917 85.58418 88.16974 83.87933
[15] 91.96780 86.01261 -Inf 81.47373 81.97600 82.77714
> colMin(tmp5,na.rm=TRUE)
[1] 58.78075 66.22047 57.30457 58.49880 54.64938 65.42973 57.84902 64.23576
[9] 59.84034 53.96026 60.30603 61.57070 58.97462 56.82008 55.17787 61.75691
[17] Inf 56.75608 55.26392 60.39528
>
>
>
>
> 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] 171.1175 307.0238 149.4534 151.7881 250.2487 295.2757 164.7263 288.8294
[9] 355.9944 462.0359
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 171.1175 307.0238 149.4534 151.7881 250.2487 295.2757 164.7263 288.8294
[9] 355.9944 462.0359
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.136868e-13 -3.126388e-13 0.000000e+00 -2.842171e-13 5.684342e-14
[6] 1.705303e-13 -2.842171e-14 0.000000e+00 1.705303e-13 -2.842171e-14
[11] 2.273737e-13 -1.705303e-13 1.705303e-13 2.842171e-14 0.000000e+00
[16] -1.136868e-13 5.684342e-14 1.421085e-13 1.136868e-13 -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)
+ }
4 9
4 5
2 11
6 16
6 6
6 3
4 12
6 2
2 13
4 2
7 10
6 17
3 10
2 18
9 18
9 6
10 20
10 17
4 3
7 12
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.388635
> Min(tmp)
[1] -2.623331
> mean(tmp)
[1] -0.05669824
> Sum(tmp)
[1] -5.669824
> Var(tmp)
[1] 0.9527887
>
> rowMeans(tmp)
[1] -0.05669824
> rowSums(tmp)
[1] -5.669824
> rowVars(tmp)
[1] 0.9527887
> rowSd(tmp)
[1] 0.976109
> rowMax(tmp)
[1] 2.388635
> rowMin(tmp)
[1] -2.623331
>
> colMeans(tmp)
[1] -0.071370154 -0.097286024 1.756243345 0.192031762 -0.451501480
[6] -1.448053669 -0.102987642 -0.084906969 0.391735163 -0.553810734
[11] -0.099004537 -0.309514531 -0.248807134 1.153196833 0.970144207
[16] -0.396177715 -0.235425887 0.630470746 0.533419778 -0.171259188
[21] 0.186589198 -0.326224772 -1.372379646 -0.693697654 0.077018275
[26] -0.293952806 -1.286861584 1.394214698 0.363999284 -0.992281368
[31] -1.718509599 0.716475993 -0.568243844 -0.645038679 -0.618546061
[36] 0.239763706 -2.623331118 -1.420421770 0.235252664 1.105258325
[41] -1.203347179 0.772193916 0.699983753 0.898863128 -0.026422586
[46] -0.962345136 0.952130496 1.210759150 0.340965070 -0.933151394
[51] -1.630226058 -0.020429566 -0.626371299 -0.813733276 0.130431311
[56] -0.180373963 1.707895264 -0.603058723 0.652369529 -0.601588693
[61] 2.081192078 0.496876679 -1.541153522 1.579068586 0.569082256
[66] -0.409077064 -0.398221892 -1.558330391 -0.610943869 1.417856959
[71] -1.318516775 -1.252594919 0.009302059 -1.903505535 -2.022239027
[76] -0.098900184 1.767696769 -0.888331433 0.634316371 -1.263522656
[81] 0.027048324 -0.025518853 0.774812105 -0.829780266 -0.836974583
[86] -0.445643303 -0.135506479 1.084923557 2.388634904 1.214617209
[91] -1.446941215 0.250908867 0.487739765 0.303911782 0.469414457
[96] 0.926038539 1.046660606 -0.111816545 0.798119014 0.218710107
> colSums(tmp)
[1] -0.071370154 -0.097286024 1.756243345 0.192031762 -0.451501480
[6] -1.448053669 -0.102987642 -0.084906969 0.391735163 -0.553810734
[11] -0.099004537 -0.309514531 -0.248807134 1.153196833 0.970144207
[16] -0.396177715 -0.235425887 0.630470746 0.533419778 -0.171259188
[21] 0.186589198 -0.326224772 -1.372379646 -0.693697654 0.077018275
[26] -0.293952806 -1.286861584 1.394214698 0.363999284 -0.992281368
[31] -1.718509599 0.716475993 -0.568243844 -0.645038679 -0.618546061
[36] 0.239763706 -2.623331118 -1.420421770 0.235252664 1.105258325
[41] -1.203347179 0.772193916 0.699983753 0.898863128 -0.026422586
[46] -0.962345136 0.952130496 1.210759150 0.340965070 -0.933151394
[51] -1.630226058 -0.020429566 -0.626371299 -0.813733276 0.130431311
[56] -0.180373963 1.707895264 -0.603058723 0.652369529 -0.601588693
[61] 2.081192078 0.496876679 -1.541153522 1.579068586 0.569082256
[66] -0.409077064 -0.398221892 -1.558330391 -0.610943869 1.417856959
[71] -1.318516775 -1.252594919 0.009302059 -1.903505535 -2.022239027
[76] -0.098900184 1.767696769 -0.888331433 0.634316371 -1.263522656
[81] 0.027048324 -0.025518853 0.774812105 -0.829780266 -0.836974583
[86] -0.445643303 -0.135506479 1.084923557 2.388634904 1.214617209
[91] -1.446941215 0.250908867 0.487739765 0.303911782 0.469414457
[96] 0.926038539 1.046660606 -0.111816545 0.798119014 0.218710107
> 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] -0.071370154 -0.097286024 1.756243345 0.192031762 -0.451501480
[6] -1.448053669 -0.102987642 -0.084906969 0.391735163 -0.553810734
[11] -0.099004537 -0.309514531 -0.248807134 1.153196833 0.970144207
[16] -0.396177715 -0.235425887 0.630470746 0.533419778 -0.171259188
[21] 0.186589198 -0.326224772 -1.372379646 -0.693697654 0.077018275
[26] -0.293952806 -1.286861584 1.394214698 0.363999284 -0.992281368
[31] -1.718509599 0.716475993 -0.568243844 -0.645038679 -0.618546061
[36] 0.239763706 -2.623331118 -1.420421770 0.235252664 1.105258325
[41] -1.203347179 0.772193916 0.699983753 0.898863128 -0.026422586
[46] -0.962345136 0.952130496 1.210759150 0.340965070 -0.933151394
[51] -1.630226058 -0.020429566 -0.626371299 -0.813733276 0.130431311
[56] -0.180373963 1.707895264 -0.603058723 0.652369529 -0.601588693
[61] 2.081192078 0.496876679 -1.541153522 1.579068586 0.569082256
[66] -0.409077064 -0.398221892 -1.558330391 -0.610943869 1.417856959
[71] -1.318516775 -1.252594919 0.009302059 -1.903505535 -2.022239027
[76] -0.098900184 1.767696769 -0.888331433 0.634316371 -1.263522656
[81] 0.027048324 -0.025518853 0.774812105 -0.829780266 -0.836974583
[86] -0.445643303 -0.135506479 1.084923557 2.388634904 1.214617209
[91] -1.446941215 0.250908867 0.487739765 0.303911782 0.469414457
[96] 0.926038539 1.046660606 -0.111816545 0.798119014 0.218710107
> colMin(tmp)
[1] -0.071370154 -0.097286024 1.756243345 0.192031762 -0.451501480
[6] -1.448053669 -0.102987642 -0.084906969 0.391735163 -0.553810734
[11] -0.099004537 -0.309514531 -0.248807134 1.153196833 0.970144207
[16] -0.396177715 -0.235425887 0.630470746 0.533419778 -0.171259188
[21] 0.186589198 -0.326224772 -1.372379646 -0.693697654 0.077018275
[26] -0.293952806 -1.286861584 1.394214698 0.363999284 -0.992281368
[31] -1.718509599 0.716475993 -0.568243844 -0.645038679 -0.618546061
[36] 0.239763706 -2.623331118 -1.420421770 0.235252664 1.105258325
[41] -1.203347179 0.772193916 0.699983753 0.898863128 -0.026422586
[46] -0.962345136 0.952130496 1.210759150 0.340965070 -0.933151394
[51] -1.630226058 -0.020429566 -0.626371299 -0.813733276 0.130431311
[56] -0.180373963 1.707895264 -0.603058723 0.652369529 -0.601588693
[61] 2.081192078 0.496876679 -1.541153522 1.579068586 0.569082256
[66] -0.409077064 -0.398221892 -1.558330391 -0.610943869 1.417856959
[71] -1.318516775 -1.252594919 0.009302059 -1.903505535 -2.022239027
[76] -0.098900184 1.767696769 -0.888331433 0.634316371 -1.263522656
[81] 0.027048324 -0.025518853 0.774812105 -0.829780266 -0.836974583
[86] -0.445643303 -0.135506479 1.084923557 2.388634904 1.214617209
[91] -1.446941215 0.250908867 0.487739765 0.303911782 0.469414457
[96] 0.926038539 1.046660606 -0.111816545 0.798119014 0.218710107
> colMedians(tmp)
[1] -0.071370154 -0.097286024 1.756243345 0.192031762 -0.451501480
[6] -1.448053669 -0.102987642 -0.084906969 0.391735163 -0.553810734
[11] -0.099004537 -0.309514531 -0.248807134 1.153196833 0.970144207
[16] -0.396177715 -0.235425887 0.630470746 0.533419778 -0.171259188
[21] 0.186589198 -0.326224772 -1.372379646 -0.693697654 0.077018275
[26] -0.293952806 -1.286861584 1.394214698 0.363999284 -0.992281368
[31] -1.718509599 0.716475993 -0.568243844 -0.645038679 -0.618546061
[36] 0.239763706 -2.623331118 -1.420421770 0.235252664 1.105258325
[41] -1.203347179 0.772193916 0.699983753 0.898863128 -0.026422586
[46] -0.962345136 0.952130496 1.210759150 0.340965070 -0.933151394
[51] -1.630226058 -0.020429566 -0.626371299 -0.813733276 0.130431311
[56] -0.180373963 1.707895264 -0.603058723 0.652369529 -0.601588693
[61] 2.081192078 0.496876679 -1.541153522 1.579068586 0.569082256
[66] -0.409077064 -0.398221892 -1.558330391 -0.610943869 1.417856959
[71] -1.318516775 -1.252594919 0.009302059 -1.903505535 -2.022239027
[76] -0.098900184 1.767696769 -0.888331433 0.634316371 -1.263522656
[81] 0.027048324 -0.025518853 0.774812105 -0.829780266 -0.836974583
[86] -0.445643303 -0.135506479 1.084923557 2.388634904 1.214617209
[91] -1.446941215 0.250908867 0.487739765 0.303911782 0.469414457
[96] 0.926038539 1.046660606 -0.111816545 0.798119014 0.218710107
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.07137015 -0.09728602 1.756243 0.1920318 -0.4515015 -1.448054 -0.1029876
[2,] -0.07137015 -0.09728602 1.756243 0.1920318 -0.4515015 -1.448054 -0.1029876
[,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.08490697 0.3917352 -0.5538107 -0.09900454 -0.3095145 -0.2488071
[2,] -0.08490697 0.3917352 -0.5538107 -0.09900454 -0.3095145 -0.2488071
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 1.153197 0.9701442 -0.3961777 -0.2354259 0.6304707 0.5334198 -0.1712592
[2,] 1.153197 0.9701442 -0.3961777 -0.2354259 0.6304707 0.5334198 -0.1712592
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] 0.1865892 -0.3262248 -1.37238 -0.6936977 0.07701828 -0.2939528 -1.286862
[2,] 0.1865892 -0.3262248 -1.37238 -0.6936977 0.07701828 -0.2939528 -1.286862
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 1.394215 0.3639993 -0.9922814 -1.71851 0.716476 -0.5682438 -0.6450387
[2,] 1.394215 0.3639993 -0.9922814 -1.71851 0.716476 -0.5682438 -0.6450387
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.6185461 0.2397637 -2.623331 -1.420422 0.2352527 1.105258 -1.203347
[2,] -0.6185461 0.2397637 -2.623331 -1.420422 0.2352527 1.105258 -1.203347
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.7721939 0.6999838 0.8988631 -0.02642259 -0.9623451 0.9521305 1.210759
[2,] 0.7721939 0.6999838 0.8988631 -0.02642259 -0.9623451 0.9521305 1.210759
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 0.3409651 -0.9331514 -1.630226 -0.02042957 -0.6263713 -0.8137333 0.1304313
[2,] 0.3409651 -0.9331514 -1.630226 -0.02042957 -0.6263713 -0.8137333 0.1304313
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.180374 1.707895 -0.6030587 0.6523695 -0.6015887 2.081192 0.4968767
[2,] -0.180374 1.707895 -0.6030587 0.6523695 -0.6015887 2.081192 0.4968767
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -1.541154 1.579069 0.5690823 -0.4090771 -0.3982219 -1.55833 -0.6109439
[2,] -1.541154 1.579069 0.5690823 -0.4090771 -0.3982219 -1.55833 -0.6109439
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.417857 -1.318517 -1.252595 0.009302059 -1.903506 -2.022239 -0.09890018
[2,] 1.417857 -1.318517 -1.252595 0.009302059 -1.903506 -2.022239 -0.09890018
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 1.767697 -0.8883314 0.6343164 -1.263523 0.02704832 -0.02551885 0.7748121
[2,] 1.767697 -0.8883314 0.6343164 -1.263523 0.02704832 -0.02551885 0.7748121
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.8297803 -0.8369746 -0.4456433 -0.1355065 1.084924 2.388635 1.214617
[2,] -0.8297803 -0.8369746 -0.4456433 -0.1355065 1.084924 2.388635 1.214617
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -1.446941 0.2509089 0.4877398 0.3039118 0.4694145 0.9260385 1.046661
[2,] -1.446941 0.2509089 0.4877398 0.3039118 0.4694145 0.9260385 1.046661
[,98] [,99] [,100]
[1,] -0.1118165 0.798119 0.2187101
[2,] -0.1118165 0.798119 0.2187101
>
>
> Max(tmp2)
[1] 1.929186
> Min(tmp2)
[1] -2.582259
> mean(tmp2)
[1] 0.02479307
> Sum(tmp2)
[1] 2.479307
> Var(tmp2)
[1] 0.9404489
>
> rowMeans(tmp2)
[1] 1.58554623 1.12143609 0.74374564 1.61104029 0.73635449 -0.91373221
[7] 0.25175487 -0.72876290 0.69090886 -0.17428749 -1.38566630 1.89807017
[13] 1.21409844 1.57392065 0.61943248 0.72326609 0.16982180 0.13576169
[19] -1.04073402 0.73053910 -1.71341231 -0.70983375 -0.97428860 1.25683110
[25] -0.14431161 1.15377923 0.76170621 0.46037206 -0.90497936 -0.64808276
[31] 0.79873324 -0.40786653 1.23178506 -0.97910414 0.87464549 -1.00185330
[37] -0.12850838 0.64172839 -1.00325506 0.46827300 -0.28299513 -0.91296341
[43] 0.05342211 -1.99227633 -0.96227787 0.36852348 -0.87825969 -0.32113783
[49] -0.25034841 -1.89405989 0.77952594 -0.05002770 -1.59858680 1.81781392
[55] 1.67663595 -0.56019391 -0.95218222 -1.03644330 0.17162146 -0.52979448
[61] -0.13320162 1.92918642 0.83638130 -0.26717057 0.61504980 -0.19681763
[67] 0.11103672 0.79690994 -1.46773681 -0.60231408 -2.58225853 0.10765582
[73] -1.71182145 0.90156715 -0.02037528 1.12593342 -0.42500932 -0.78138362
[79] 1.11859623 -0.32902848 0.57491687 -0.50616938 -0.35806753 -1.06487802
[85] -0.35536159 0.63834005 0.41876226 1.39278960 -0.42056195 1.92145770
[91] -1.12919206 -0.20320164 0.32629769 -0.05621281 -0.18574017 0.61852440
[97] 1.02877114 -0.16452137 -0.28197135 0.01925775
> rowSums(tmp2)
[1] 1.58554623 1.12143609 0.74374564 1.61104029 0.73635449 -0.91373221
[7] 0.25175487 -0.72876290 0.69090886 -0.17428749 -1.38566630 1.89807017
[13] 1.21409844 1.57392065 0.61943248 0.72326609 0.16982180 0.13576169
[19] -1.04073402 0.73053910 -1.71341231 -0.70983375 -0.97428860 1.25683110
[25] -0.14431161 1.15377923 0.76170621 0.46037206 -0.90497936 -0.64808276
[31] 0.79873324 -0.40786653 1.23178506 -0.97910414 0.87464549 -1.00185330
[37] -0.12850838 0.64172839 -1.00325506 0.46827300 -0.28299513 -0.91296341
[43] 0.05342211 -1.99227633 -0.96227787 0.36852348 -0.87825969 -0.32113783
[49] -0.25034841 -1.89405989 0.77952594 -0.05002770 -1.59858680 1.81781392
[55] 1.67663595 -0.56019391 -0.95218222 -1.03644330 0.17162146 -0.52979448
[61] -0.13320162 1.92918642 0.83638130 -0.26717057 0.61504980 -0.19681763
[67] 0.11103672 0.79690994 -1.46773681 -0.60231408 -2.58225853 0.10765582
[73] -1.71182145 0.90156715 -0.02037528 1.12593342 -0.42500932 -0.78138362
[79] 1.11859623 -0.32902848 0.57491687 -0.50616938 -0.35806753 -1.06487802
[85] -0.35536159 0.63834005 0.41876226 1.39278960 -0.42056195 1.92145770
[91] -1.12919206 -0.20320164 0.32629769 -0.05621281 -0.18574017 0.61852440
[97] 1.02877114 -0.16452137 -0.28197135 0.01925775
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.58554623 1.12143609 0.74374564 1.61104029 0.73635449 -0.91373221
[7] 0.25175487 -0.72876290 0.69090886 -0.17428749 -1.38566630 1.89807017
[13] 1.21409844 1.57392065 0.61943248 0.72326609 0.16982180 0.13576169
[19] -1.04073402 0.73053910 -1.71341231 -0.70983375 -0.97428860 1.25683110
[25] -0.14431161 1.15377923 0.76170621 0.46037206 -0.90497936 -0.64808276
[31] 0.79873324 -0.40786653 1.23178506 -0.97910414 0.87464549 -1.00185330
[37] -0.12850838 0.64172839 -1.00325506 0.46827300 -0.28299513 -0.91296341
[43] 0.05342211 -1.99227633 -0.96227787 0.36852348 -0.87825969 -0.32113783
[49] -0.25034841 -1.89405989 0.77952594 -0.05002770 -1.59858680 1.81781392
[55] 1.67663595 -0.56019391 -0.95218222 -1.03644330 0.17162146 -0.52979448
[61] -0.13320162 1.92918642 0.83638130 -0.26717057 0.61504980 -0.19681763
[67] 0.11103672 0.79690994 -1.46773681 -0.60231408 -2.58225853 0.10765582
[73] -1.71182145 0.90156715 -0.02037528 1.12593342 -0.42500932 -0.78138362
[79] 1.11859623 -0.32902848 0.57491687 -0.50616938 -0.35806753 -1.06487802
[85] -0.35536159 0.63834005 0.41876226 1.39278960 -0.42056195 1.92145770
[91] -1.12919206 -0.20320164 0.32629769 -0.05621281 -0.18574017 0.61852440
[97] 1.02877114 -0.16452137 -0.28197135 0.01925775
> rowMin(tmp2)
[1] 1.58554623 1.12143609 0.74374564 1.61104029 0.73635449 -0.91373221
[7] 0.25175487 -0.72876290 0.69090886 -0.17428749 -1.38566630 1.89807017
[13] 1.21409844 1.57392065 0.61943248 0.72326609 0.16982180 0.13576169
[19] -1.04073402 0.73053910 -1.71341231 -0.70983375 -0.97428860 1.25683110
[25] -0.14431161 1.15377923 0.76170621 0.46037206 -0.90497936 -0.64808276
[31] 0.79873324 -0.40786653 1.23178506 -0.97910414 0.87464549 -1.00185330
[37] -0.12850838 0.64172839 -1.00325506 0.46827300 -0.28299513 -0.91296341
[43] 0.05342211 -1.99227633 -0.96227787 0.36852348 -0.87825969 -0.32113783
[49] -0.25034841 -1.89405989 0.77952594 -0.05002770 -1.59858680 1.81781392
[55] 1.67663595 -0.56019391 -0.95218222 -1.03644330 0.17162146 -0.52979448
[61] -0.13320162 1.92918642 0.83638130 -0.26717057 0.61504980 -0.19681763
[67] 0.11103672 0.79690994 -1.46773681 -0.60231408 -2.58225853 0.10765582
[73] -1.71182145 0.90156715 -0.02037528 1.12593342 -0.42500932 -0.78138362
[79] 1.11859623 -0.32902848 0.57491687 -0.50616938 -0.35806753 -1.06487802
[85] -0.35536159 0.63834005 0.41876226 1.39278960 -0.42056195 1.92145770
[91] -1.12919206 -0.20320164 0.32629769 -0.05621281 -0.18574017 0.61852440
[97] 1.02877114 -0.16452137 -0.28197135 0.01925775
>
> colMeans(tmp2)
[1] 0.02479307
> colSums(tmp2)
[1] 2.479307
> colVars(tmp2)
[1] 0.9404489
> colSd(tmp2)
[1] 0.9697674
> colMax(tmp2)
[1] 1.929186
> colMin(tmp2)
[1] -2.582259
> colMedians(tmp2)
[1] -0.05312025
> colRanges(tmp2)
[,1]
[1,] -2.582259
[2,] 1.929186
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.8613256 -2.4587055 1.2130296 -2.5580228 -1.3452758 2.2333010
[7] 3.9583312 -1.9514949 0.6563882 5.3465323
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8672609
[2,] -0.6452924
[3,] -0.1835633
[4,] 0.7658220
[5,] 1.5053508
>
> rowApply(tmp,sum)
[1] -1.4315891 3.9146998 -1.3596244 0.2506319 1.0424042 2.2991939
[7] 1.3305915 2.5842179 -6.0006371 1.6028692
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 1 1 5 6 8 9 9 6 8
[2,] 5 2 2 9 8 1 1 5 9 6
[3,] 4 6 6 4 7 7 10 8 1 7
[4,] 1 10 9 3 2 4 3 2 3 9
[5,] 9 9 8 1 1 6 6 4 2 4
[6,] 10 4 5 6 5 9 4 1 8 5
[7,] 6 7 7 2 10 2 8 10 10 2
[8,] 2 5 4 8 4 5 7 3 7 3
[9,] 3 3 3 7 9 3 2 7 5 10
[10,] 8 8 10 10 3 10 5 6 4 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.415402571 0.984914244 4.137296886 2.550942635 0.005689505
[6] 2.984863205 5.008387435 -1.811138574 -1.443486624 0.109781841
[11] -3.971511731 -1.916013105 -6.914334085 1.268335529 -0.572034865
[16] 3.000039418 -0.870409707 -0.927934406 -2.044567652 1.619129587
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.02221191
[2,] 0.24107643
[3,] 0.44521942
[4,] 0.83115790
[5,] 0.87573691
>
> rowApply(tmp,sum)
[1] 2.3454582 -5.0949569 0.3300646 -1.7773104 7.8100966
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 12 17 10 16 15
[2,] 13 10 7 3 19
[3,] 18 15 9 6 20
[4,] 17 14 16 13 8
[5,] 10 8 11 9 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.24107643 0.4842137 1.204353059 0.96393308 0.06217076 1.5007620
[2,] 0.87573691 -0.2053028 0.638808704 0.29671140 -0.70180855 -0.7286929
[3,] 0.02221191 -0.3726130 0.009397884 0.97942110 0.18861530 1.2236534
[4,] 0.44521942 -1.3378772 -0.815544277 0.32407365 -0.24232667 0.5280070
[5,] 0.83115790 2.4164935 3.100281515 -0.01319659 0.69903865 0.4611337
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.0746821 0.7079964 -1.29232931 0.6436703 -0.3091647 -0.3648297
[2,] 1.6746605 -1.8234711 -1.21045672 0.9165228 -1.0678578 -1.1004623
[3,] 0.9832584 0.2846733 1.26629600 0.3665981 -1.3061172 1.2005498
[4,] 1.7028525 -1.7032558 -0.25681785 -0.7976901 0.1232793 -0.8901500
[5,] 1.7222982 0.7229186 0.04982126 -1.0193192 -1.4116513 -0.7611209
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.0017224 0.01097932 -1.0164285 1.7484109 -0.5083446 0.09256876
[2,] -2.7186761 1.00062638 0.1920694 -0.1924253 -0.2271079 -1.34888492
[3,] -2.0033825 -0.13273098 -0.8915038 0.4933949 0.6418134 -0.77227919
[4,] -0.8983928 0.36024713 0.3345514 1.0926406 -0.1117337 0.24162312
[5,] -0.2921604 0.02921368 0.8092766 -0.1419817 -0.6650368 0.85903782
[,19] [,20]
[1,] 0.8407003 -0.58787548
[2,] 0.7079320 -0.07287856
[3,] -1.3437674 -0.50742484
[4,] -1.6990343 1.82301816
[5,] -0.5503983 0.96429031
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 648 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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-3.24-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 1.629963 0.9784756 0.1264526 1.758438 -0.7760992 -0.1441366 -0.4726626
col8 col9 col10 col11 col12 col13 col14
row1 0.5408941 0.4011144 2.094507 1.081973 -1.161585 0.630277 0.03089093
col15 col16 col17 col18 col19 col20
row1 0.03357393 0.9608 0.6514134 -1.181169 -0.6426526 -1.508182
> tmp[,"col10"]
col10
row1 2.0945069
row2 0.2197461
row3 0.1052607
row4 1.7051131
row5 0.7413958
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.6299633 0.9784756 0.1264526 1.7584379 -0.7760992 -0.14413665 -0.4726626
row5 0.5974029 -0.4136364 0.5619862 0.9143954 0.2592765 0.01579904 -0.3268539
col8 col9 col10 col11 col12 col13 col14
row1 0.5408941 0.4011144 2.0945069 1.081973 -1.1615851 0.630277 0.03089093
row5 0.1206226 0.6177983 0.7413958 2.081742 -0.1566517 -1.266657 0.71457559
col15 col16 col17 col18 col19 col20
row1 0.03357393 0.9608000 0.6514134 -1.1811692 -0.6426526 -1.5081820
row5 0.10706351 0.2289014 -0.3337247 0.4019404 -0.7402944 0.4159396
> tmp[,c("col6","col20")]
col6 col20
row1 -0.14413665 -1.5081820
row2 -0.29705382 0.6100673
row3 -0.67018249 1.1161613
row4 -0.78817568 1.4131762
row5 0.01579904 0.4159396
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.14413665 -1.5081820
row5 0.01579904 0.4159396
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.93939 49.58797 49.92139 48.74946 49.37434 104.2921 50.45109 49.25532
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.82219 50.06225 48.49189 50.29174 49.3186 49.84161 51.6585 49.87225
col17 col18 col19 col20
row1 49.88578 50.37455 50.00854 106.0417
> tmp[,"col10"]
col10
row1 50.06225
row2 30.42364
row3 29.85602
row4 29.94487
row5 50.56703
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.93939 49.58797 49.92139 48.74946 49.37434 104.2921 50.45109 49.25532
row5 51.56528 49.92429 51.93356 51.80631 50.49698 104.2841 48.82899 49.22111
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.82219 50.06225 48.49189 50.29174 49.31860 49.84161 51.6585 49.87225
row5 50.91998 50.56703 49.73403 50.03784 49.18632 49.65013 50.3617 48.25667
col17 col18 col19 col20
row1 49.88578 50.37455 50.00854 106.0417
row5 49.20782 50.05686 49.49537 105.5579
> tmp[,c("col6","col20")]
col6 col20
row1 104.29207 106.04172
row2 74.91628 74.55150
row3 73.29510 73.57043
row4 74.02652 75.71669
row5 104.28408 105.55786
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.2921 106.0417
row5 104.2841 105.5579
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.2921 106.0417
row5 104.2841 105.5579
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.83418764
[2,] 0.02966049
[3,] 0.20045602
[4,] 0.93089106
[5,] -1.31900882
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.8076434 -0.05138926
[2,] 0.4475179 0.52632809
[3,] -1.6925433 -0.86178876
[4,] 1.2651079 0.80535846
[5,] -0.1020957 0.73943323
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.9279764 1.3828819
[2,] -0.6030628 0.8017577
[3,] 0.6583753 0.8048131
[4,] 0.1015889 -1.0294342
[5,] -1.4460636 1.0935658
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.9279764
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.9279764
[2,] -0.6030628
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 1.0588822 -1.387182 -2.143835 0.3768829 1.20741648 0.2215507 -0.9648162
row1 0.6576106 1.340266 -1.922474 1.6267271 -0.07086692 -0.5446877 0.3460042
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.03628968 0.5319667 1.0237936 -0.9354238 -0.02744931 -1.1259522
row1 -1.78940115 0.1130967 -0.1781601 -0.1557148 0.13808864 0.3925367
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.2444148 -0.4713148 0.3368165 1.117394 -0.4493712 -1.6020637 -0.6821472
row1 0.8112162 0.4686057 -0.9069406 -1.443194 0.2834440 0.3043883 0.9339873
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5071853 0.6326854 0.2931718 0.5469164 -1.62876 -0.491638 -1.195207
[,8] [,9] [,10]
row2 0.9514897 0.361662 1.479261
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2473872 -0.2486824 -0.2109174 -0.2231338 0.1936428 1.153904 -0.3045791
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.3732358 -0.2326381 0.08537395 -0.579318 1.678562 -1.421843 0.5116007
[,15] [,16] [,17] [,18] [,19] [,20]
row5 2.268113 0.9938607 -2.921054 -1.930996 0.2061792 0.2765143
>
>
> 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: 0x587fdca16350>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f3a9c9c71"
[2] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f459d2283"
[3] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f1325fe45"
[4] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f20f87e5f"
[5] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f1ac64d66"
[6] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f19a6bb71"
[7] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f5c10f9fb"
[8] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f2142b626"
[9] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f456e338a"
[10] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f2ca06844"
[11] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f6acde0af"
[12] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f61496396"
[13] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f1355fb68"
[14] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09f45efd156"
[15] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e09fe8d4f82"
>
>
> ### 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: 0x587fdf38d5e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x587fdf38d5e0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x587fdf38d5e0>
> rowMedians(tmp)
[1] 0.1284567204 0.6104314292 -0.2480857843 -0.5927803716 0.0156866786
[6] -0.1704907018 0.0475434578 0.2091823899 -0.5179928703 -0.1550974643
[11] -0.1380874985 0.0154175670 -0.0215162956 -0.0128587975 -0.3403660603
[16] -0.1665040098 -0.0863478213 -0.5938083965 0.2036736102 0.0211207642
[21] 0.0900095386 0.0439693398 0.2583897993 0.0736097332 -0.3052764925
[26] -0.5608097729 -0.0996671809 -0.2211877335 0.1068431167 -0.5834458246
[31] 0.2135474638 -0.1413938753 -0.1587135415 -0.0316314181 0.2120563960
[36] 0.1108197411 -0.2713033206 0.0469858028 -0.5099343327 0.1730859113
[41] -0.2020662711 0.1080780864 -0.0943923405 0.0680168948 -0.0694997158
[46] 0.4119513513 -0.1081173610 0.0828253098 -0.0585832255 -0.3859868620
[51] -0.6775144384 -0.4056613351 -0.4761641601 -0.0981136414 -0.0865585719
[56] -0.1866466523 -0.0772671793 0.4235886677 0.0085445652 0.1598019829
[61] -0.0095413789 -0.0593645772 0.1762966017 -0.0505815392 0.1894747647
[66] -0.0489756545 0.1059375595 -0.1139058170 0.1818508719 0.3034075406
[71] -0.0870516978 -0.0390512679 0.2562461441 0.4600029955 -0.1944659767
[76] 0.1707535002 0.0049320497 0.2909844301 -0.3035795207 0.0954341418
[81] -0.1837496779 0.3760673728 0.3176597057 -0.0489481783 0.1987390156
[86] 0.8019198687 0.3536035870 -0.0283731126 0.2617446326 -0.2662037561
[91] -0.3092749516 0.1203763655 0.2068147271 0.1320814501 -0.0411084426
[96] -0.5309175920 -0.0667872216 0.1553885645 -0.3140306537 0.4902775741
[101] -0.2344754884 0.1157549777 -0.1274495296 0.2443866670 -0.0026921846
[106] -0.2041384124 -0.1420004632 0.5602907887 -0.4313408887 -0.1343029774
[111] -0.0693034889 -0.0031483061 0.2164516277 0.0259893609 -0.1832080892
[116] 0.2309735273 -0.4875745975 -0.2298023175 -0.4249174802 0.3357096504
[121] -0.8855766052 0.4179645936 0.5102082306 -0.2154533601 0.1017880190
[126] 0.0732853318 -0.3981301768 -0.5096509983 -0.0465835644 -0.0714726511
[131] -0.1366194100 -0.0711865580 -0.2742318461 0.2735380492 -0.2301931233
[136] -0.4257311391 0.4120284370 0.3469767799 -0.4333295453 -0.1104447612
[141] 0.0388710791 0.5031974065 -0.7705177456 0.3691533775 -0.1411578469
[146] 0.3701477564 0.3591012483 0.7220055357 -0.2697284322 0.1438413268
[151] -0.0721871348 0.6301656170 -0.3347015738 0.0234949378 -0.2546191076
[156] -0.1827176243 -0.1684553452 0.2998716319 -0.1033938998 -0.1947298411
[161] -0.5677958257 0.5669872821 -0.4276362624 0.0451741892 0.2082414847
[166] -0.0089466402 0.3851287566 -0.2169946985 -0.0975477170 -0.7141211480
[171] 0.2049581118 0.3504525819 0.2267669403 0.6883663450 -0.2567137517
[176] 0.2435060969 -0.4178668967 -0.2200683104 0.2323738121 0.5112038959
[181] -0.1221911675 0.4610099951 -0.1980871512 -0.3848779699 -0.2115943806
[186] 0.0004644525 0.1064718590 -0.3900041118 -0.0511792499 0.0631059716
[191] -0.3554053222 -0.5030434221 0.3931696072 0.4497938644 0.0016520888
[196] 0.6194644597 -0.0042727273 0.4421380596 -0.0783285199 0.1078646281
[201] 0.0542868148 -0.0270881717 0.2527457396 -0.4958002406 -0.5567232987
[206] 0.2436321122 0.2701247366 -0.0357974925 -0.1894652594 -0.0164823532
[211] -0.0954886606 -0.6894719099 -0.7119712535 -0.4199892179 -0.0269782974
[216] 0.3414337491 -0.0061165069 0.3375494663 0.0890274909 -0.2768485083
[221] 0.4346338409 -0.0101320344 -0.0113777283 0.4229117476 -0.5699546241
[226] -0.1450932489 0.1468990379 -0.0868817613 -0.0944624874 -0.6875603129
>
> proc.time()
user system elapsed
1.250 0.701 1.937
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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: 0x5bcc12b27520>
> .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: 0x5bcc12b27520>
> .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: 0x5bcc12b27520>
> .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: 0x5bcc12b27520>
> 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: 0x5bcc126d0f60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc126d0f60>
> .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: 0x5bcc126d0f60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc126d0f60>
> .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: 0x5bcc126d0f60>
> 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: 0x5bcc1327ab40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc1327ab40>
> .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: 0x5bcc1327ab40>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5bcc1327ab40>
> .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: 0x5bcc1327ab40>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5bcc1327ab40>
> .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: 0x5bcc1327ab40>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5bcc1327ab40>
> .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: 0x5bcc1327ab40>
> 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: 0x5bcc132b7bc0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5bcc132b7bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc132b7bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc132b7bc0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e15a6918d9f8" "BufferedMatrixFile1e15a69c626fd"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e15a6918d9f8" "BufferedMatrixFile1e15a69c626fd"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc13251000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc13251000>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5bcc13251000>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5bcc13251000>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5bcc13251000>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5bcc13251000>
> .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: 0x5bcc12384e30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bcc12384e30>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5bcc12384e30>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5bcc12384e30>
> 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: 0x5bcc129aea50>
> .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: 0x5bcc129aea50>
> rm(P)
>
> proc.time()
user system elapsed
0.249 0.048 0.287
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 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
0.245 0.047 0.280