Ben Bolstad
| Snapshot Date: 2026-02-24 13:40 -0500 (Tue, 24 Feb 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-02-25 11:32 -0500 (Wed, 25 Feb 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences" | 4874 |
| 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 255/2354 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 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: 1.75.0 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz |
| StartedAt: 2026-02-24 22:03:25 -0500 (Tue, 24 Feb 2026) |
| EndedAt: 2026-02-24 22:03:53 -0500 (Tue, 24 Feb 2026) |
| EllapsedTime: 28.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.75.0’
* 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) 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-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-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-3.23-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-3.23-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-3.23-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-3.23-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-3.23-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.23-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 Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
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
0.248 0.048 0.284
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
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-3.23-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 478920 25.6 1048721 56.1 639242 34.2
Vcells 885815 6.8 8388608 64.0 2083259 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] "Tue Feb 24 22:03:43 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] "Tue Feb 24 22:03:43 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: 0x631a413e7c10>
>
>
>
> 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] "Tue Feb 24 22:03:44 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] "Tue Feb 24 22:03:44 2026"
>
> ColMode(tmp2)
<pointer: 0x631a413e7c10>
>
>
>
> ### 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,] 99.9692698 1.9326549 0.6308153 0.7841571
[2,] 0.8972725 -0.1373272 1.2489409 -1.6530720
[3,] -1.3397841 0.1006721 -0.2877064 1.4716186
[4,] -1.7055592 0.3491616 -0.8985088 -3.2800185
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.9692698 1.9326549 0.6308153 0.7841571
[2,] 0.8972725 0.1373272 1.2489409 1.6530720
[3,] 1.3397841 0.1006721 0.2877064 1.4716186
[4,] 1.7055592 0.3491616 0.8985088 3.2800185
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9984634 1.3901996 0.7942388 0.8855264
[2,] 0.9472447 0.3705768 1.1175603 1.2857185
[3,] 1.1574904 0.3172887 0.5363827 1.2131029
[4,] 1.3059706 0.5908990 0.9478971 1.8110821
>
> 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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.95390 40.83465 33.57320 34.63942
[2,] 35.36972 28.84310 37.42454 39.51026
[3,] 37.91469 28.27356 30.65153 38.60265
[4,] 39.76527 31.25815 35.37748 46.39084
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x631a4223eff0>
> exp(tmp5)
<pointer: 0x631a4223eff0>
> log(tmp5,2)
<pointer: 0x631a4223eff0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.2121
> Min(tmp5)
[1] 54.07814
> mean(tmp5)
[1] 73.04799
> Sum(tmp5)
[1] 14609.6
> Var(tmp5)
[1] 872.1303
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 94.93191 69.27517 70.57867 72.65807 74.59814 68.43367 70.43579 69.42213
[9] 70.69626 69.45010
> rowSums(tmp5)
[1] 1898.638 1385.503 1411.573 1453.161 1491.963 1368.673 1408.716 1388.443
[9] 1413.925 1389.002
> rowVars(tmp5)
[1] 7792.24851 64.30722 114.97012 115.08886 61.11062 82.87298
[7] 122.81368 62.32717 62.90707 64.68663
> rowSd(tmp5)
[1] 88.273714 8.019178 10.722412 10.727948 7.817328 9.103460 11.082133
[8] 7.894756 7.931398 8.042800
> rowMax(tmp5)
[1] 468.21208 82.23542 92.95280 96.55645 86.25864 88.27340 93.90424
[8] 82.65827 88.09815 86.46515
> rowMin(tmp5)
[1] 64.82667 54.45661 54.51379 56.62568 62.20071 54.81845 54.07814 55.26556
[9] 57.61718 56.60867
>
> colMeans(tmp5)
[1] 111.42248 71.99019 70.77283 76.95240 69.38243 71.35024 72.95528
[8] 73.54591 67.24308 73.12433 71.90858 70.05125 68.01128 68.92302
[15] 69.61125 68.39858 76.58001 71.92872 66.84742 69.96054
> colSums(tmp5)
[1] 1114.2248 719.9019 707.7283 769.5240 693.8243 713.5024 729.5528
[8] 735.4591 672.4308 731.2433 719.0858 700.5125 680.1128 689.2302
[15] 696.1125 683.9858 765.8001 719.2872 668.4742 699.6054
> colVars(tmp5)
[1] 15820.63773 78.15947 28.73560 98.89234 137.29612 71.41411
[7] 86.73047 76.53291 74.71613 54.18392 82.33701 81.09499
[13] 18.94458 79.93405 121.58654 57.13726 160.06849 64.60381
[19] 69.78401 140.73956
> colSd(tmp5)
[1] 125.780117 8.840784 5.360560 9.944463 11.717343 8.450687
[7] 9.312919 8.748309 8.643849 7.360973 9.073974 9.005276
[13] 4.352538 8.940585 11.026629 7.558919 12.651818 8.037650
[19] 8.353683 11.863371
> colMax(tmp5)
[1] 468.21208 84.99198 77.89428 96.55645 90.84109 87.15917 84.82090
[8] 83.54699 79.49050 85.44913 86.25864 91.01974 73.35911 88.10614
[15] 92.95280 78.99259 94.57829 88.27340 83.15405 86.17928
> colMin(tmp5)
[1] 56.60867 58.84771 62.20071 66.35359 54.81845 56.62568 56.68217 58.86949
[9] 54.45661 59.32896 54.07814 59.32573 60.67986 57.22091 57.47087 54.51379
[17] 60.38051 60.98928 55.26556 54.51439
>
>
> ### 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] 94.93191 69.27517 70.57867 72.65807 NA 68.43367 70.43579 69.42213
[9] 70.69626 69.45010
> rowSums(tmp5)
[1] 1898.638 1385.503 1411.573 1453.161 NA 1368.673 1408.716 1388.443
[9] 1413.925 1389.002
> rowVars(tmp5)
[1] 7792.24851 64.30722 114.97012 115.08886 61.45374 82.87298
[7] 122.81368 62.32717 62.90707 64.68663
> rowSd(tmp5)
[1] 88.273714 8.019178 10.722412 10.727948 7.839244 9.103460 11.082133
[8] 7.894756 7.931398 8.042800
> rowMax(tmp5)
[1] 468.21208 82.23542 92.95280 96.55645 NA 88.27340 93.90424
[8] 82.65827 88.09815 86.46515
> rowMin(tmp5)
[1] 64.82667 54.45661 54.51379 56.62568 NA 54.81845 54.07814 55.26556
[9] 57.61718 56.60867
>
> colMeans(tmp5)
[1] 111.42248 71.99019 70.77283 76.95240 69.38243 71.35024 72.95528
[8] 73.54591 67.24308 73.12433 71.90858 70.05125 68.01128 NA
[15] 69.61125 68.39858 76.58001 71.92872 66.84742 69.96054
> colSums(tmp5)
[1] 1114.2248 719.9019 707.7283 769.5240 693.8243 713.5024 729.5528
[8] 735.4591 672.4308 731.2433 719.0858 700.5125 680.1128 NA
[15] 696.1125 683.9858 765.8001 719.2872 668.4742 699.6054
> colVars(tmp5)
[1] 15820.63773 78.15947 28.73560 98.89234 137.29612 71.41411
[7] 86.73047 76.53291 74.71613 54.18392 82.33701 81.09499
[13] 18.94458 NA 121.58654 57.13726 160.06849 64.60381
[19] 69.78401 140.73956
> colSd(tmp5)
[1] 125.780117 8.840784 5.360560 9.944463 11.717343 8.450687
[7] 9.312919 8.748309 8.643849 7.360973 9.073974 9.005276
[13] 4.352538 NA 11.026629 7.558919 12.651818 8.037650
[19] 8.353683 11.863371
> colMax(tmp5)
[1] 468.21208 84.99198 77.89428 96.55645 90.84109 87.15917 84.82090
[8] 83.54699 79.49050 85.44913 86.25864 91.01974 73.35911 NA
[15] 92.95280 78.99259 94.57829 88.27340 83.15405 86.17928
> colMin(tmp5)
[1] 56.60867 58.84771 62.20071 66.35359 54.81845 56.62568 56.68217 58.86949
[9] 54.45661 59.32896 54.07814 59.32573 60.67986 NA 57.47087 54.51379
[17] 60.38051 60.98928 55.26556 54.51439
>
> Max(tmp5,na.rm=TRUE)
[1] 468.2121
> Min(tmp5,na.rm=TRUE)
[1] 54.07814
> mean(tmp5,na.rm=TRUE)
[1] 73.0765
> Sum(tmp5,na.rm=TRUE)
[1] 14542.22
> Var(tmp5,na.rm=TRUE)
[1] 876.3716
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 94.93191 69.27517 70.57867 72.65807 74.97836 68.43367 70.43579 69.42213
[9] 70.69626 69.45010
> rowSums(tmp5,na.rm=TRUE)
[1] 1898.638 1385.503 1411.573 1453.161 1424.589 1368.673 1408.716 1388.443
[9] 1413.925 1389.002
> rowVars(tmp5,na.rm=TRUE)
[1] 7792.24851 64.30722 114.97012 115.08886 61.45374 82.87298
[7] 122.81368 62.32717 62.90707 64.68663
> rowSd(tmp5,na.rm=TRUE)
[1] 88.273714 8.019178 10.722412 10.727948 7.839244 9.103460 11.082133
[8] 7.894756 7.931398 8.042800
> rowMax(tmp5,na.rm=TRUE)
[1] 468.21208 82.23542 92.95280 96.55645 86.25864 88.27340 93.90424
[8] 82.65827 88.09815 86.46515
> rowMin(tmp5,na.rm=TRUE)
[1] 64.82667 54.45661 54.51379 56.62568 62.20071 54.81845 54.07814 55.26556
[9] 57.61718 56.60867
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.42248 71.99019 70.77283 76.95240 69.38243 71.35024 72.95528
[8] 73.54591 67.24308 73.12433 71.90858 70.05125 68.01128 69.09513
[15] 69.61125 68.39858 76.58001 71.92872 66.84742 69.96054
> colSums(tmp5,na.rm=TRUE)
[1] 1114.2248 719.9019 707.7283 769.5240 693.8243 713.5024 729.5528
[8] 735.4591 672.4308 731.2433 719.0858 700.5125 680.1128 621.8562
[15] 696.1125 683.9858 765.8001 719.2872 668.4742 699.6054
> colVars(tmp5,na.rm=TRUE)
[1] 15820.63773 78.15947 28.73560 98.89234 137.29612 71.41411
[7] 86.73047 76.53291 74.71613 54.18392 82.33701 81.09499
[13] 18.94458 89.59257 121.58654 57.13726 160.06849 64.60381
[19] 69.78401 140.73956
> colSd(tmp5,na.rm=TRUE)
[1] 125.780117 8.840784 5.360560 9.944463 11.717343 8.450687
[7] 9.312919 8.748309 8.643849 7.360973 9.073974 9.005276
[13] 4.352538 9.465335 11.026629 7.558919 12.651818 8.037650
[19] 8.353683 11.863371
> colMax(tmp5,na.rm=TRUE)
[1] 468.21208 84.99198 77.89428 96.55645 90.84109 87.15917 84.82090
[8] 83.54699 79.49050 85.44913 86.25864 91.01974 73.35911 88.10614
[15] 92.95280 78.99259 94.57829 88.27340 83.15405 86.17928
> colMin(tmp5,na.rm=TRUE)
[1] 56.60867 58.84771 62.20071 66.35359 54.81845 56.62568 56.68217 58.86949
[9] 54.45661 59.32896 54.07814 59.32573 60.67986 57.22091 57.47087 54.51379
[17] 60.38051 60.98928 55.26556 54.51439
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 94.93191 69.27517 70.57867 72.65807 NaN 68.43367 70.43579 69.42213
[9] 70.69626 69.45010
> rowSums(tmp5,na.rm=TRUE)
[1] 1898.638 1385.503 1411.573 1453.161 0.000 1368.673 1408.716 1388.443
[9] 1413.925 1389.002
> rowVars(tmp5,na.rm=TRUE)
[1] 7792.24851 64.30722 114.97012 115.08886 NA 82.87298
[7] 122.81368 62.32717 62.90707 64.68663
> rowSd(tmp5,na.rm=TRUE)
[1] 88.273714 8.019178 10.722412 10.727948 NA 9.103460 11.082133
[8] 7.894756 7.931398 8.042800
> rowMax(tmp5,na.rm=TRUE)
[1] 468.21208 82.23542 92.95280 96.55645 NA 88.27340 93.90424
[8] 82.65827 88.09815 86.46515
> rowMin(tmp5,na.rm=TRUE)
[1] 64.82667 54.45661 54.51379 56.62568 NA 54.81845 54.07814 55.26556
[9] 57.61718 56.60867
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.75078 71.26098 71.72529 77.96028 67.78684 71.11950 72.16601
[8] 72.55149 66.92881 71.75491 70.31413 70.10352 67.49075 NaN
[15] 69.75768 68.83870 77.76282 72.33339 65.03557 68.77848
> colSums(tmp5,na.rm=TRUE)
[1] 1032.7570 641.3488 645.5276 701.6425 610.0815 640.0755 649.4940
[8] 652.9634 602.3593 645.7941 632.8272 630.9317 607.4167 0.0000
[15] 627.8191 619.5483 699.8654 651.0006 585.3201 619.0063
> colVars(tmp5,na.rm=TRUE)
[1] 17673.59502 81.94733 22.12182 99.82582 125.81669 79.74191
[7] 90.56354 74.97476 82.94451 39.85958 64.02857 91.20113
[13] 18.26437 NA 136.54365 62.10024 164.33788 70.83694
[19] 41.57559 142.61268
> colSd(tmp5,na.rm=TRUE)
[1] 132.942074 9.052476 4.703384 9.991287 11.216804 8.929833
[7] 9.516488 8.658797 9.107387 6.313444 8.001785 9.549928
[13] 4.273683 NA 11.685189 7.880370 12.819434 8.416468
[19] 6.447914 11.942055
> colMax(tmp5,na.rm=TRUE)
[1] 468.21208 84.99198 77.89428 96.55645 90.84109 87.15917 84.82090
[8] 83.54699 79.49050 82.67644 82.13197 91.01974 73.35911 -Inf
[15] 92.95280 78.99259 94.57829 88.27340 71.75651 86.17928
> colMin(tmp5,na.rm=TRUE)
[1] 56.60867 58.84771 63.79715 66.35359 54.81845 56.62568 56.68217 58.86949
[9] 54.45661 59.32896 54.07814 59.32573 60.67986 Inf 57.47087 54.51379
[17] 60.38051 60.98928 55.26556 54.51439
>
>
>
>
> 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] 219.4364 188.5587 209.8708 260.2215 282.4854 199.1304 286.7221 158.7418
[9] 144.0693 199.3411
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 219.4364 188.5587 209.8708 260.2215 282.4854 199.1304 286.7221 158.7418
[9] 144.0693 199.3411
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 2.273737e-13 -1.421085e-13 -8.526513e-14 1.421085e-13 -1.421085e-14
[6] -8.526513e-14 5.684342e-14 5.684342e-14 -1.705303e-13 1.705303e-13
[11] -2.842171e-14 0.000000e+00 1.421085e-14 -2.842171e-14 0.000000e+00
[16] -1.421085e-14 -2.842171e-14 2.273737e-13 0.000000e+00 2.842171e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
1 12
8 10
7 15
9 4
6 9
4 2
8 2
8 10
7 1
2 19
2 13
8 1
1 3
4 3
10 19
5 15
4 16
9 20
9 8
2 19
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] 2.464678
> Min(tmp)
[1] -2.202964
> mean(tmp)
[1] 0.2049964
> Sum(tmp)
[1] 20.49964
> Var(tmp)
[1] 0.8097203
>
> rowMeans(tmp)
[1] 0.2049964
> rowSums(tmp)
[1] 20.49964
> rowVars(tmp)
[1] 0.8097203
> rowSd(tmp)
[1] 0.8998446
> rowMax(tmp)
[1] 2.464678
> rowMin(tmp)
[1] -2.202964
>
> colMeans(tmp)
[1] -0.016583224 0.346003122 -1.213547720 0.841402313 1.007334591
[6] -0.420564862 0.523926355 -1.152889432 1.459171451 -0.321130119
[11] 0.038810419 0.636886263 1.229868917 0.459473419 1.361313593
[16] 0.015472824 1.101320107 -0.644308875 -1.555546394 0.357114065
[21] 1.930339697 -0.006955985 0.887062697 -1.156370451 0.432080461
[26] -1.123623083 0.409917760 1.441208374 0.273490336 0.153035678
[31] -0.474647796 -1.254330492 -0.143428826 0.403481863 1.349870902
[36] 0.234757533 0.531967899 0.729239808 -1.301593076 -0.642067008
[41] -0.086642975 1.072134105 0.548104075 0.866514218 -0.695113516
[46] -1.282794160 1.262679292 0.465641141 0.329468754 0.371773358
[51] -1.093637611 0.647197799 0.636909242 1.089547667 -0.667240712
[56] 0.093723983 -0.612567421 -0.016463002 -1.048422073 -0.665079871
[61] -2.202963650 -0.044422202 0.659727747 -0.498709603 -0.359148539
[66] 0.453227127 0.902645755 1.898409872 0.145301293 -0.607350468
[71] -0.388216396 1.056322226 0.096715564 -0.377605304 0.289336999
[76] -0.294328104 0.171501425 1.083058800 1.041188552 2.191025519
[81] 0.687619837 -0.459964100 1.140893208 -0.012650009 -1.085343234
[86] 0.021763057 0.960615373 0.052395105 0.012337777 -0.599553512
[91] 0.357263180 2.464677516 0.095136333 1.847668767 1.325510739
[96] 0.806542680 -1.557116737 1.480851156 -0.133922163 -0.063494062
> colSums(tmp)
[1] -0.016583224 0.346003122 -1.213547720 0.841402313 1.007334591
[6] -0.420564862 0.523926355 -1.152889432 1.459171451 -0.321130119
[11] 0.038810419 0.636886263 1.229868917 0.459473419 1.361313593
[16] 0.015472824 1.101320107 -0.644308875 -1.555546394 0.357114065
[21] 1.930339697 -0.006955985 0.887062697 -1.156370451 0.432080461
[26] -1.123623083 0.409917760 1.441208374 0.273490336 0.153035678
[31] -0.474647796 -1.254330492 -0.143428826 0.403481863 1.349870902
[36] 0.234757533 0.531967899 0.729239808 -1.301593076 -0.642067008
[41] -0.086642975 1.072134105 0.548104075 0.866514218 -0.695113516
[46] -1.282794160 1.262679292 0.465641141 0.329468754 0.371773358
[51] -1.093637611 0.647197799 0.636909242 1.089547667 -0.667240712
[56] 0.093723983 -0.612567421 -0.016463002 -1.048422073 -0.665079871
[61] -2.202963650 -0.044422202 0.659727747 -0.498709603 -0.359148539
[66] 0.453227127 0.902645755 1.898409872 0.145301293 -0.607350468
[71] -0.388216396 1.056322226 0.096715564 -0.377605304 0.289336999
[76] -0.294328104 0.171501425 1.083058800 1.041188552 2.191025519
[81] 0.687619837 -0.459964100 1.140893208 -0.012650009 -1.085343234
[86] 0.021763057 0.960615373 0.052395105 0.012337777 -0.599553512
[91] 0.357263180 2.464677516 0.095136333 1.847668767 1.325510739
[96] 0.806542680 -1.557116737 1.480851156 -0.133922163 -0.063494062
> 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] -0.016583224 0.346003122 -1.213547720 0.841402313 1.007334591
[6] -0.420564862 0.523926355 -1.152889432 1.459171451 -0.321130119
[11] 0.038810419 0.636886263 1.229868917 0.459473419 1.361313593
[16] 0.015472824 1.101320107 -0.644308875 -1.555546394 0.357114065
[21] 1.930339697 -0.006955985 0.887062697 -1.156370451 0.432080461
[26] -1.123623083 0.409917760 1.441208374 0.273490336 0.153035678
[31] -0.474647796 -1.254330492 -0.143428826 0.403481863 1.349870902
[36] 0.234757533 0.531967899 0.729239808 -1.301593076 -0.642067008
[41] -0.086642975 1.072134105 0.548104075 0.866514218 -0.695113516
[46] -1.282794160 1.262679292 0.465641141 0.329468754 0.371773358
[51] -1.093637611 0.647197799 0.636909242 1.089547667 -0.667240712
[56] 0.093723983 -0.612567421 -0.016463002 -1.048422073 -0.665079871
[61] -2.202963650 -0.044422202 0.659727747 -0.498709603 -0.359148539
[66] 0.453227127 0.902645755 1.898409872 0.145301293 -0.607350468
[71] -0.388216396 1.056322226 0.096715564 -0.377605304 0.289336999
[76] -0.294328104 0.171501425 1.083058800 1.041188552 2.191025519
[81] 0.687619837 -0.459964100 1.140893208 -0.012650009 -1.085343234
[86] 0.021763057 0.960615373 0.052395105 0.012337777 -0.599553512
[91] 0.357263180 2.464677516 0.095136333 1.847668767 1.325510739
[96] 0.806542680 -1.557116737 1.480851156 -0.133922163 -0.063494062
> colMin(tmp)
[1] -0.016583224 0.346003122 -1.213547720 0.841402313 1.007334591
[6] -0.420564862 0.523926355 -1.152889432 1.459171451 -0.321130119
[11] 0.038810419 0.636886263 1.229868917 0.459473419 1.361313593
[16] 0.015472824 1.101320107 -0.644308875 -1.555546394 0.357114065
[21] 1.930339697 -0.006955985 0.887062697 -1.156370451 0.432080461
[26] -1.123623083 0.409917760 1.441208374 0.273490336 0.153035678
[31] -0.474647796 -1.254330492 -0.143428826 0.403481863 1.349870902
[36] 0.234757533 0.531967899 0.729239808 -1.301593076 -0.642067008
[41] -0.086642975 1.072134105 0.548104075 0.866514218 -0.695113516
[46] -1.282794160 1.262679292 0.465641141 0.329468754 0.371773358
[51] -1.093637611 0.647197799 0.636909242 1.089547667 -0.667240712
[56] 0.093723983 -0.612567421 -0.016463002 -1.048422073 -0.665079871
[61] -2.202963650 -0.044422202 0.659727747 -0.498709603 -0.359148539
[66] 0.453227127 0.902645755 1.898409872 0.145301293 -0.607350468
[71] -0.388216396 1.056322226 0.096715564 -0.377605304 0.289336999
[76] -0.294328104 0.171501425 1.083058800 1.041188552 2.191025519
[81] 0.687619837 -0.459964100 1.140893208 -0.012650009 -1.085343234
[86] 0.021763057 0.960615373 0.052395105 0.012337777 -0.599553512
[91] 0.357263180 2.464677516 0.095136333 1.847668767 1.325510739
[96] 0.806542680 -1.557116737 1.480851156 -0.133922163 -0.063494062
> colMedians(tmp)
[1] -0.016583224 0.346003122 -1.213547720 0.841402313 1.007334591
[6] -0.420564862 0.523926355 -1.152889432 1.459171451 -0.321130119
[11] 0.038810419 0.636886263 1.229868917 0.459473419 1.361313593
[16] 0.015472824 1.101320107 -0.644308875 -1.555546394 0.357114065
[21] 1.930339697 -0.006955985 0.887062697 -1.156370451 0.432080461
[26] -1.123623083 0.409917760 1.441208374 0.273490336 0.153035678
[31] -0.474647796 -1.254330492 -0.143428826 0.403481863 1.349870902
[36] 0.234757533 0.531967899 0.729239808 -1.301593076 -0.642067008
[41] -0.086642975 1.072134105 0.548104075 0.866514218 -0.695113516
[46] -1.282794160 1.262679292 0.465641141 0.329468754 0.371773358
[51] -1.093637611 0.647197799 0.636909242 1.089547667 -0.667240712
[56] 0.093723983 -0.612567421 -0.016463002 -1.048422073 -0.665079871
[61] -2.202963650 -0.044422202 0.659727747 -0.498709603 -0.359148539
[66] 0.453227127 0.902645755 1.898409872 0.145301293 -0.607350468
[71] -0.388216396 1.056322226 0.096715564 -0.377605304 0.289336999
[76] -0.294328104 0.171501425 1.083058800 1.041188552 2.191025519
[81] 0.687619837 -0.459964100 1.140893208 -0.012650009 -1.085343234
[86] 0.021763057 0.960615373 0.052395105 0.012337777 -0.599553512
[91] 0.357263180 2.464677516 0.095136333 1.847668767 1.325510739
[96] 0.806542680 -1.557116737 1.480851156 -0.133922163 -0.063494062
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.01658322 0.3460031 -1.213548 0.8414023 1.007335 -0.4205649 0.5239264
[2,] -0.01658322 0.3460031 -1.213548 0.8414023 1.007335 -0.4205649 0.5239264
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.152889 1.459171 -0.3211301 0.03881042 0.6368863 1.229869 0.4594734
[2,] -1.152889 1.459171 -0.3211301 0.03881042 0.6368863 1.229869 0.4594734
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.361314 0.01547282 1.10132 -0.6443089 -1.555546 0.3571141 1.93034
[2,] 1.361314 0.01547282 1.10132 -0.6443089 -1.555546 0.3571141 1.93034
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.006955985 0.8870627 -1.15637 0.4320805 -1.123623 0.4099178 1.441208
[2,] -0.006955985 0.8870627 -1.15637 0.4320805 -1.123623 0.4099178 1.441208
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2734903 0.1530357 -0.4746478 -1.25433 -0.1434288 0.4034819 1.349871
[2,] 0.2734903 0.1530357 -0.4746478 -1.25433 -0.1434288 0.4034819 1.349871
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.2347575 0.5319679 0.7292398 -1.301593 -0.642067 -0.08664297 1.072134
[2,] 0.2347575 0.5319679 0.7292398 -1.301593 -0.642067 -0.08664297 1.072134
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5481041 0.8665142 -0.6951135 -1.282794 1.262679 0.4656411 0.3294688
[2,] 0.5481041 0.8665142 -0.6951135 -1.282794 1.262679 0.4656411 0.3294688
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3717734 -1.093638 0.6471978 0.6369092 1.089548 -0.6672407 0.09372398
[2,] 0.3717734 -1.093638 0.6471978 0.6369092 1.089548 -0.6672407 0.09372398
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.6125674 -0.016463 -1.048422 -0.6650799 -2.202964 -0.0444222 0.6597277
[2,] -0.6125674 -0.016463 -1.048422 -0.6650799 -2.202964 -0.0444222 0.6597277
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.4987096 -0.3591485 0.4532271 0.9026458 1.89841 0.1453013 -0.6073505
[2,] -0.4987096 -0.3591485 0.4532271 0.9026458 1.89841 0.1453013 -0.6073505
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.3882164 1.056322 0.09671556 -0.3776053 0.289337 -0.2943281 0.1715014
[2,] -0.3882164 1.056322 0.09671556 -0.3776053 0.289337 -0.2943281 0.1715014
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.083059 1.041189 2.191026 0.6876198 -0.4599641 1.140893 -0.01265001
[2,] 1.083059 1.041189 2.191026 0.6876198 -0.4599641 1.140893 -0.01265001
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.085343 0.02176306 0.9606154 0.0523951 0.01233778 -0.5995535 0.3572632
[2,] -1.085343 0.02176306 0.9606154 0.0523951 0.01233778 -0.5995535 0.3572632
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 2.464678 0.09513633 1.847669 1.325511 0.8065427 -1.557117 1.480851
[2,] 2.464678 0.09513633 1.847669 1.325511 0.8065427 -1.557117 1.480851
[,99] [,100]
[1,] -0.1339222 -0.06349406
[2,] -0.1339222 -0.06349406
>
>
> Max(tmp2)
[1] 2.321815
> Min(tmp2)
[1] -2.233777
> mean(tmp2)
[1] -0.001930628
> Sum(tmp2)
[1] -0.1930628
> Var(tmp2)
[1] 1.109269
>
> rowMeans(tmp2)
[1] -1.285832348 1.068766457 -1.278468943 -0.581897511 -0.015227547
[6] -2.233776529 0.734830706 -0.058664146 0.208316863 -0.734700734
[11] -0.592604985 1.659379291 -0.398432823 -1.299902333 1.850021756
[16] 0.861217648 -0.210999691 0.691454030 0.203219420 0.487180398
[21] 0.860529090 -0.260092135 1.322819401 0.270576461 -1.510089414
[26] -0.168446763 0.945333096 0.383804512 -0.239702039 0.831310539
[31] 0.106741556 0.813303050 0.001225186 1.166783712 -0.624830945
[36] 1.505191333 0.554456323 -0.722069409 1.654148550 -1.098496625
[41] 0.634955578 -1.018543502 1.209114384 -0.124992942 0.417587454
[46] 0.295388502 -1.784848500 -0.475363135 -1.079117795 2.039612671
[51] 0.271584009 0.567385385 -1.722173894 0.281059519 0.064965793
[56] 1.511993811 1.275480210 1.208851082 -1.213768520 -1.188467436
[61] -1.966109905 0.169120484 -0.012143327 -0.160316498 0.258894096
[66] -0.026745287 -0.985039121 -0.253887555 -1.290294248 -0.996871460
[71] -0.788201859 -0.846342581 -1.724304684 0.878778949 1.791677834
[76] -0.426339159 1.940346497 1.849719299 -0.451124238 0.713851282
[81] 0.033699682 0.531557187 -0.192785578 -1.846572364 -0.993606583
[86] 0.706070225 2.321815135 2.167688774 0.089872535 0.338087376
[91] -0.509867074 -0.933476345 -0.184269143 -1.126341210 -1.973577678
[96] -1.304665984 0.357616524 -1.134157599 0.220890325 -0.472786648
> rowSums(tmp2)
[1] -1.285832348 1.068766457 -1.278468943 -0.581897511 -0.015227547
[6] -2.233776529 0.734830706 -0.058664146 0.208316863 -0.734700734
[11] -0.592604985 1.659379291 -0.398432823 -1.299902333 1.850021756
[16] 0.861217648 -0.210999691 0.691454030 0.203219420 0.487180398
[21] 0.860529090 -0.260092135 1.322819401 0.270576461 -1.510089414
[26] -0.168446763 0.945333096 0.383804512 -0.239702039 0.831310539
[31] 0.106741556 0.813303050 0.001225186 1.166783712 -0.624830945
[36] 1.505191333 0.554456323 -0.722069409 1.654148550 -1.098496625
[41] 0.634955578 -1.018543502 1.209114384 -0.124992942 0.417587454
[46] 0.295388502 -1.784848500 -0.475363135 -1.079117795 2.039612671
[51] 0.271584009 0.567385385 -1.722173894 0.281059519 0.064965793
[56] 1.511993811 1.275480210 1.208851082 -1.213768520 -1.188467436
[61] -1.966109905 0.169120484 -0.012143327 -0.160316498 0.258894096
[66] -0.026745287 -0.985039121 -0.253887555 -1.290294248 -0.996871460
[71] -0.788201859 -0.846342581 -1.724304684 0.878778949 1.791677834
[76] -0.426339159 1.940346497 1.849719299 -0.451124238 0.713851282
[81] 0.033699682 0.531557187 -0.192785578 -1.846572364 -0.993606583
[86] 0.706070225 2.321815135 2.167688774 0.089872535 0.338087376
[91] -0.509867074 -0.933476345 -0.184269143 -1.126341210 -1.973577678
[96] -1.304665984 0.357616524 -1.134157599 0.220890325 -0.472786648
> 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] -1.285832348 1.068766457 -1.278468943 -0.581897511 -0.015227547
[6] -2.233776529 0.734830706 -0.058664146 0.208316863 -0.734700734
[11] -0.592604985 1.659379291 -0.398432823 -1.299902333 1.850021756
[16] 0.861217648 -0.210999691 0.691454030 0.203219420 0.487180398
[21] 0.860529090 -0.260092135 1.322819401 0.270576461 -1.510089414
[26] -0.168446763 0.945333096 0.383804512 -0.239702039 0.831310539
[31] 0.106741556 0.813303050 0.001225186 1.166783712 -0.624830945
[36] 1.505191333 0.554456323 -0.722069409 1.654148550 -1.098496625
[41] 0.634955578 -1.018543502 1.209114384 -0.124992942 0.417587454
[46] 0.295388502 -1.784848500 -0.475363135 -1.079117795 2.039612671
[51] 0.271584009 0.567385385 -1.722173894 0.281059519 0.064965793
[56] 1.511993811 1.275480210 1.208851082 -1.213768520 -1.188467436
[61] -1.966109905 0.169120484 -0.012143327 -0.160316498 0.258894096
[66] -0.026745287 -0.985039121 -0.253887555 -1.290294248 -0.996871460
[71] -0.788201859 -0.846342581 -1.724304684 0.878778949 1.791677834
[76] -0.426339159 1.940346497 1.849719299 -0.451124238 0.713851282
[81] 0.033699682 0.531557187 -0.192785578 -1.846572364 -0.993606583
[86] 0.706070225 2.321815135 2.167688774 0.089872535 0.338087376
[91] -0.509867074 -0.933476345 -0.184269143 -1.126341210 -1.973577678
[96] -1.304665984 0.357616524 -1.134157599 0.220890325 -0.472786648
> rowMin(tmp2)
[1] -1.285832348 1.068766457 -1.278468943 -0.581897511 -0.015227547
[6] -2.233776529 0.734830706 -0.058664146 0.208316863 -0.734700734
[11] -0.592604985 1.659379291 -0.398432823 -1.299902333 1.850021756
[16] 0.861217648 -0.210999691 0.691454030 0.203219420 0.487180398
[21] 0.860529090 -0.260092135 1.322819401 0.270576461 -1.510089414
[26] -0.168446763 0.945333096 0.383804512 -0.239702039 0.831310539
[31] 0.106741556 0.813303050 0.001225186 1.166783712 -0.624830945
[36] 1.505191333 0.554456323 -0.722069409 1.654148550 -1.098496625
[41] 0.634955578 -1.018543502 1.209114384 -0.124992942 0.417587454
[46] 0.295388502 -1.784848500 -0.475363135 -1.079117795 2.039612671
[51] 0.271584009 0.567385385 -1.722173894 0.281059519 0.064965793
[56] 1.511993811 1.275480210 1.208851082 -1.213768520 -1.188467436
[61] -1.966109905 0.169120484 -0.012143327 -0.160316498 0.258894096
[66] -0.026745287 -0.985039121 -0.253887555 -1.290294248 -0.996871460
[71] -0.788201859 -0.846342581 -1.724304684 0.878778949 1.791677834
[76] -0.426339159 1.940346497 1.849719299 -0.451124238 0.713851282
[81] 0.033699682 0.531557187 -0.192785578 -1.846572364 -0.993606583
[86] 0.706070225 2.321815135 2.167688774 0.089872535 0.338087376
[91] -0.509867074 -0.933476345 -0.184269143 -1.126341210 -1.973577678
[96] -1.304665984 0.357616524 -1.134157599 0.220890325 -0.472786648
>
> colMeans(tmp2)
[1] -0.001930628
> colSums(tmp2)
[1] -0.1930628
> colVars(tmp2)
[1] 1.109269
> colSd(tmp2)
[1] 1.053218
> colMax(tmp2)
[1] 2.321815
> colMin(tmp2)
[1] -2.233777
> colMedians(tmp2)
[1] -0.005459071
> colRanges(tmp2)
[,1]
[1,] -2.233777
[2,] 2.321815
>
> 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] -2.738617322 0.006701725 -0.709274610 3.354304703 -3.615965488
[6] 5.690389901 -1.674452244 2.099525978 -0.053259724 -4.835963252
> colApply(tmp,quantile)[,1]
[,1]
[1,] -3.04841873
[2,] -1.21900357
[3,] 0.01399602
[4,] 0.65740500
[5,] 2.07421119
>
> rowApply(tmp,sum)
[1] -2.6331021 -1.3023188 1.9768499 5.7751960 5.3047225 -0.4767552
[7] -7.3888762 -3.0964764 -3.2566961 2.6208460
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 8 7 3 9 1 1 10 6 3
[2,] 9 1 5 1 4 4 9 9 3 7
[3,] 4 9 9 7 1 5 4 7 7 1
[4,] 2 7 10 6 3 3 8 6 8 10
[5,] 6 10 2 4 2 6 3 1 2 6
[6,] 10 6 3 5 6 8 7 5 10 8
[7,] 5 3 4 2 5 2 5 8 1 9
[8,] 8 4 8 9 10 7 10 4 4 5
[9,] 7 5 6 10 8 10 2 2 9 2
[10,] 3 2 1 8 7 9 6 3 5 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.04844463 4.48489530 -1.38260254 0.28112568 2.99475937 0.65062938
[7] 1.90797737 0.11241309 1.90054318 0.67449267 0.65200202 3.03360550
[13] 3.25856713 -0.08249033 -0.39039031 4.48694615 -4.56312916 0.57901164
[19] 0.49858357 -0.42225369
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8100657
[2,] -0.4886951
[3,] 0.1988041
[4,] 0.4241835
[5,] 0.6273285
>
> rowApply(tmp,sum)
[1] 7.254270 1.283072 3.085282 3.621229 3.382389
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 7 13 16 5
[2,] 17 20 2 18 18
[3,] 2 2 8 10 16
[4,] 12 8 9 12 7
[5,] 15 16 16 8 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1988041 0.7733518 -0.7077439 0.6390747 0.73490409 0.6883931
[2,] -0.4886951 2.0044147 -1.5468335 -0.1925014 0.97114523 1.6906846
[3,] 0.4241835 -0.9777991 -0.2244484 -0.1017392 0.60483862 -1.5893597
[4,] 0.6273285 1.1957735 0.1875859 0.2425989 -0.03653167 -0.5673989
[5,] -0.8100657 1.4891544 0.9088373 -0.3063072 0.72040311 0.4283103
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.12695720 -0.6687217 1.17506479 0.2537037 -0.2336769 2.0694356
[2,] -0.06211598 -0.9058730 0.05803031 0.8262999 -0.7287025 1.0702871
[3,] 1.57924377 0.4026487 0.44624876 -0.3257022 -0.4753183 -0.3620395
[4,] 0.85539635 0.3846674 1.31450337 -1.2340144 0.1813291 -0.3165117
[5,] -0.33758958 0.8996917 -1.09330405 1.1542055 1.9083707 0.5724340
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.4691198 0.6511174 0.01198694 1.95118752 -0.6078208 0.02720922
[2,] 0.3050997 1.0461294 -1.24946045 0.72459042 -2.0280857 0.83877252
[3,] 0.7667839 0.1633142 -0.26748745 1.58488567 0.4294694 -0.04321127
[4,] 2.0008549 -0.2212439 -0.44605679 0.31750427 -1.3398003 -0.22732624
[5,] -0.2832912 -1.7218074 1.56062744 -0.09122173 -1.0168918 -0.01643259
[,19] [,20]
[1,] 0.7441730 -0.7883355
[2,] -1.1700728 0.1199587
[3,] -0.2750392 1.3258092
[4,] 0.4812392 0.2213315
[5,] 0.7182834 -1.3010177
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-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 0.03496159 0.5289047 2.777348 1.329298 1.904468 -0.7722051 -0.8281112
col8 col9 col10 col11 col12 col13 col14
row1 -0.183513 -1.951884 -1.161365 -0.05746576 -1.362813 0.6964863 -1.089734
col15 col16 col17 col18 col19 col20
row1 -0.2226396 -0.5109971 0.01719182 0.3744059 -0.7647721 0.9640789
> tmp[,"col10"]
col10
row1 -1.1613650
row2 -0.3561795
row3 -0.6674430
row4 -0.4077458
row5 0.9241209
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.03496159 0.5289047 2.777348 1.3292978 1.90446783 -0.7722051
row5 0.01539380 -0.3327791 1.620289 -0.8931916 -0.08431747 1.2456644
col7 col8 col9 col10 col11 col12 col13
row1 -0.8281112 -0.1835130 -1.951884 -1.1613650 -0.05746576 -1.362813 0.6964863
row5 -0.8507711 -0.8990512 1.409644 0.9241209 0.52586866 -1.097044 0.8965914
col14 col15 col16 col17 col18 col19
row1 -1.0897341 -0.2226396 -0.5109971 0.01719182 0.3744059 -0.7647721
row5 0.5902024 -0.6807754 1.5094170 -0.18523603 1.5770959 -1.9888246
col20
row1 0.9640789
row5 -0.6560793
> tmp[,c("col6","col20")]
col6 col20
row1 -0.77220513 0.9640789
row2 -0.73427552 0.7136051
row3 0.23847518 -0.6897946
row4 -0.03110975 -1.1413533
row5 1.24566442 -0.6560793
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.7722051 0.9640789
row5 1.2456644 -0.6560793
>
>
>
>
> 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 48.83443 50.84668 48.8535 51.73259 50.35226 105.2592 51.14183 49.58497
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.41955 50.24021 51.09124 51.05989 49.27671 51.60752 49.18432 50.18895
col17 col18 col19 col20
row1 49.08347 48.86498 50.06024 105.0475
> tmp[,"col10"]
col10
row1 50.24021
row2 29.15360
row3 30.90976
row4 29.01408
row5 49.98991
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.83443 50.84668 48.85350 51.73259 50.35226 105.2592 51.14183 49.58497
row5 50.74489 49.34760 48.39869 51.63408 49.33060 105.2531 50.40460 53.18475
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.41955 50.24021 51.09124 51.05989 49.27671 51.60752 49.18432 50.18895
row5 48.77157 49.98991 49.44517 49.43136 48.72204 51.47875 50.07202 51.07654
col17 col18 col19 col20
row1 49.08347 48.86498 50.06024 105.0475
row5 49.70117 50.46070 49.43199 104.9196
> tmp[,c("col6","col20")]
col6 col20
row1 105.25917 105.04752
row2 75.36002 74.17587
row3 74.47147 75.15099
row4 75.63176 74.88124
row5 105.25306 104.91965
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.2592 105.0475
row5 105.2531 104.9196
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.2592 105.0475
row5 105.2531 104.9196
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.57710047
[2,] -0.62807933
[3,] -0.42052723
[4,] -0.07586091
[5,] 0.97783283
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.3440905 0.1507872
[2,] 0.6097798 1.7254306
[3,] 0.8566952 -0.8374531
[4,] 0.9987188 0.7873156
[5,] 2.6865128 1.6703340
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.37356207 1.2787732
[2,] -0.97540254 1.0530783
[3,] 0.05620648 1.1081145
[4,] -1.02710404 -2.1321324
[5,] -0.59697836 -0.4684145
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3735621
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.3735621
[2,] -0.9754025
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.1461547 -0.2662398 -0.1971678 0.6631017 -0.5930124 -1.095463 0.163630
row1 -0.8596146 -0.1972343 0.1187174 -0.4513800 -1.9485393 1.164407 1.397359
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.7947848 -0.6559411 0.2084335 1.345568 -2.7287854 0.5092514 0.1162121
row1 0.3256624 1.5323472 0.6846484 1.250097 -0.1038882 0.5141828 -0.9395643
[,15] [,16] [,17] [,18] [,19] [,20]
row3 1.772394 -0.6033953 1.8278323 0.6281181 0.50768454 1.0239886
row1 -1.129109 0.4780548 -0.7641641 0.6077814 0.04061933 0.2827904
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.294325 -0.2722386 -1.16741 -1.034545 1.491337 0.542484 -0.07362183
[,8] [,9] [,10]
row2 -0.9212043 -1.176354 -0.9953127
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.5472971 -0.3524707 1.2436 -1.40298 0.001631353 -0.544859 0.1765196
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.7907055 0.5547693 -1.151907 -0.1984964 0.4763079 -1.616897 -0.8564082
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.489848 1.103378 0.06491709 -0.9133695 -0.8707255 0.7692521
>
>
> 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: 0x631a4245d9d0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e3245466f"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e6dbe02fc"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e499e83c7"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e4327dba8"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e23396c95"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e31eb7db9"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e608c90"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e4263b397"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e2f2f756a"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e1be9f296"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e6817b4b5"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e1b31c37"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978e660a69b5"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978ee97dd8e"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3b978eab521ab"
>
>
> ### 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: 0x631a416e8250>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x631a416e8250>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x631a416e8250>
> rowMedians(tmp)
[1] 0.0880925800 0.1408683999 -0.1729224327 0.2426453874 -0.0498574172
[6] 0.0744299553 -0.5260364990 0.0708762956 0.3197488654 0.2255011806
[11] 0.2058267431 -0.2572438528 -0.2300432166 0.1362295099 -0.6227403277
[16] 0.3681441594 -0.0850958670 0.1702350478 0.4177895045 0.2855397436
[21] -0.4377456164 0.2601655911 -0.1120434152 0.0956543079 -0.1553636243
[26] 0.0098596114 -0.1447372238 0.1555402594 0.6526872289 0.3463221100
[31] 0.3135127232 -0.0472248550 0.2835716125 0.6334162010 -0.3130918063
[36] -0.6176600395 -0.2889775250 0.2715156845 0.0363660153 0.0203656114
[41] -0.3270569771 0.1887637495 -0.2893272814 0.0711239409 0.2406838143
[46] -0.2912544913 -0.2406011169 -0.0237732581 0.2957430562 0.1256065380
[51] -0.3308873116 0.1701675067 0.0585313051 -0.4101606396 -0.4321038897
[56] -0.4550534796 0.2149434079 -0.5887615989 -0.5524037350 0.3168939124
[61] 0.3710727521 0.2224316613 0.1116980983 -0.3926672294 -0.3955307792
[66] -0.1446845500 0.5776480827 0.0074707435 -0.5317019579 0.4763128253
[71] -0.3175157895 -0.1213565640 0.3255103037 0.0724611555 -0.7491238117
[76] 0.1426320140 -0.0722352396 0.2236130649 -0.2315065164 0.1676083021
[81] -0.2426731334 -0.0177869545 0.2658624423 0.0829871862 -0.0396862379
[86] -0.2801162910 0.0607714390 0.3325646737 -0.3685951054 0.3209825044
[91] -0.1514529182 -0.1532360708 -0.0124817575 0.4547204290 -0.0988040480
[96] 0.3009777102 -0.0134020136 -0.0016249881 -0.4120285841 -0.2783162494
[101] -0.5662500018 -0.5709876368 0.3306817571 -0.4381502649 0.4522338802
[106] 0.4854053503 0.6863066800 -0.1637981887 0.1210132806 -0.3680941772
[111] -0.4835065205 -0.2536922297 -0.0307862514 -0.2888750308 0.4342944519
[116] -0.1250691044 0.0535858505 -0.1771688854 0.2033267383 -0.2783756162
[121] -0.0856597254 0.2188942531 0.1677740573 -0.5641427713 0.0683594772
[126] 0.0009066806 0.0225354841 -0.0901766050 -0.0103036377 -0.1164930404
[131] 0.2017457323 0.1611180665 0.3634830675 -0.0590593913 0.3760554885
[136] 0.3694638229 0.5418579083 -0.1522775074 -0.0214999093 0.1094297763
[141] 0.4098320362 -0.5103777652 -0.2698643419 0.2345451277 -0.2580775335
[146] 0.2992113072 0.5634785269 -0.1775922391 0.1094162026 -0.0500214652
[151] -0.0498752103 -0.5282463563 0.2178302621 -0.4488469643 0.1697738011
[156] -0.0396557216 0.2727209242 0.1999554805 0.0900733317 -0.3989286110
[161] -0.1397354417 -0.6147946287 0.3277063461 0.0915274790 -0.2256229965
[166] -0.4772401662 0.3210819585 -0.3183635828 -0.2212616444 0.0241654486
[171] -0.2136987367 -0.0423773813 0.3680717430 0.2105975377 0.3276376867
[176] 0.1174300884 -0.1468609303 -0.0805348649 -0.1798331727 0.4863262481
[181] 0.5264742216 -0.1577553187 -0.7426481502 0.1862512679 -0.3036240723
[186] 0.2812496167 0.4549338243 0.1148962691 0.7440739539 0.1762962282
[191] 0.3351088809 -0.2700182730 -0.7102044183 -0.1140968476 0.1234874268
[196] 0.4978873070 0.3397133751 0.0940923111 0.2879882241 -0.3558427272
[201] -0.1556443816 -0.0364468341 -0.0407251752 -0.0503589650 0.0608240657
[206] 0.1260108551 0.0505974550 -0.3037289339 -0.0744816139 -0.1304307314
[211] 0.0187239226 0.2153133377 0.3199456535 0.2604860242 0.1314438603
[216] -0.0072229953 -0.0104378993 0.2808160038 0.1174084692 0.0708957464
[221] 0.3904217877 -0.0290367745 -0.5486801228 -0.5803139319 0.5376558005
[226] 0.5473331222 0.2750685782 -0.0173711532 -0.4791922065 0.1136084486
>
> proc.time()
user system elapsed
1.301 1.513 2.803
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
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: 0x616d278b0c10>
> .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: 0x616d278b0c10>
> .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: 0x616d278b0c10>
> .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: 0x616d278b0c10>
> 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: 0x616d285732d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d285732d0>
> .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: 0x616d285732d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d285732d0>
> .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: 0x616d285732d0>
> 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: 0x616d28c48d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d28c48d70>
> .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: 0x616d28c48d70>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x616d28c48d70>
> .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: 0x616d28c48d70>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x616d28c48d70>
> .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: 0x616d28c48d70>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x616d28c48d70>
> .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: 0x616d28c48d70>
> 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: 0x616d287bc370>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x616d287bc370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d287bc370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d287bc370>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3b992f343561be" "BufferedMatrixFile3b992f6c50f0ec"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3b992f343561be" "BufferedMatrixFile3b992f6c50f0ec"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d28707ff0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d28707ff0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x616d28707ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x616d28707ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x616d28707ff0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x616d28707ff0>
> .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: 0x616d288ea3d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x616d288ea3d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x616d288ea3d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x616d288ea3d0>
> 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: 0x616d2a09bfb0>
> .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: 0x616d2a09bfb0>
> rm(P)
>
> proc.time()
user system elapsed
0.245 0.055 0.286
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
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
0.255 0.045 0.288