Ben Bolstad
| Snapshot Date: 2026-01-27 13:40 -0500 (Tue, 27 Jan 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 2026-01-28 11:32 -0500 (Wed, 28 Jan 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" | 4815 |
| 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 254/2347 | 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 | | ||||||||
|
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: 2026-01-27 21:48:00 -0500 (Tue, 27 Jan 2026) |
| EndedAt: 2026-01-27 21:48:25 -0500 (Tue, 27 Jan 2026) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### 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
###
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##############################################################################
* 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
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###
### 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
0.261 0.039 0.287
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 Jan 27 21:48:15 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 Jan 27 21:48:15 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: 0x5ffe71269c10>
>
>
>
> 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 Jan 27 21:48:16 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 Jan 27 21:48:16 2026"
>
> ColMode(tmp2)
<pointer: 0x5ffe71269c10>
>
>
>
> ### 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,] 99.88997827 -1.1150962 1.0801924 0.01045508
[2,] -0.23695626 1.2297499 0.2143220 -1.88834825
[3,] 0.08177976 -0.5683163 0.6748686 1.31101650
[4,] 0.09657983 1.0638900 1.0148505 -0.18479611
> 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,] 99.88997827 1.1150962 1.0801924 0.01045508
[2,] 0.23695626 1.2297499 0.2143220 1.88834825
[3,] 0.08177976 0.5683163 0.6748686 1.31101650
[4,] 0.09657983 1.0638900 1.0148505 0.18479611
> 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,] 9.9944974 1.0559811 1.0393230 0.1022501
[2,] 0.4867815 1.1089409 0.4629492 1.3741718
[3,] 0.2859716 0.7538676 0.8215039 1.1449963
[4,] 0.3107729 1.0314504 1.0073979 0.4298792
>
> 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,] 224.83495 36.67491 36.47342 26.03296
[2,] 30.10477 37.31916 29.84381 40.63007
[3,] 27.94150 33.10699 33.88991 37.76098
[4,] 28.20431 36.37839 36.08883 29.48359
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5ffe720c0ff0>
> exp(tmp5)
<pointer: 0x5ffe720c0ff0>
> log(tmp5,2)
<pointer: 0x5ffe720c0ff0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.9645
> Min(tmp5)
[1] 53.1833
> mean(tmp5)
[1] 73.12401
> Sum(tmp5)
[1] 14624.8
> Var(tmp5)
[1] 860.9931
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.24208 69.94533 68.86502 69.85391 71.99173 71.47418 72.46489 71.55633
[9] 70.26216 72.58448
> rowSums(tmp5)
[1] 1844.842 1398.907 1377.300 1397.078 1439.835 1429.484 1449.298 1431.127
[9] 1405.243 1451.690
> rowVars(tmp5)
[1] 7868.55466 97.14851 64.17843 49.59975 74.09756 75.99927
[7] 103.40253 55.89773 98.47165 88.51025
> rowSd(tmp5)
[1] 88.704874 9.856394 8.011144 7.042709 8.607994 8.717756 10.168703
[8] 7.476478 9.923288 9.407989
> rowMax(tmp5)
[1] 467.96450 89.41302 85.31202 79.94187 87.42351 93.78745 89.01429
[8] 86.44054 84.80100 85.79625
> rowMin(tmp5)
[1] 54.18419 53.87902 54.25759 56.26162 57.96494 56.48944 57.96477 56.65062
[9] 53.44713 53.18330
>
> colMeans(tmp5)
[1] 108.10250 71.00138 73.55230 71.02157 68.07337 68.50245 68.61766
[8] 70.54257 69.26760 71.11178 73.67152 72.15087 70.72213 72.91306
[15] 71.26545 69.81357 73.19233 73.68129 74.07177 71.20504
> colSums(tmp5)
[1] 1081.0250 710.0138 735.5230 710.2157 680.7337 685.0245 686.1766
[8] 705.4257 692.6760 711.1178 736.7152 721.5087 707.2213 729.1306
[15] 712.6545 698.1357 731.9233 736.8129 740.7177 712.0504
> colVars(tmp5)
[1] 16053.90343 93.85560 30.32306 157.81684 77.39351 100.77248
[7] 64.44782 90.46218 57.87254 67.88015 81.70984 33.22178
[13] 92.86641 91.33816 64.96704 64.29649 69.78445 122.20867
[19] 43.97971 76.48893
> colSd(tmp5)
[1] 126.703999 9.687910 5.506638 12.562517 8.797358 10.038550
[7] 8.027940 9.511161 7.607400 8.238941 9.039349 5.763834
[13] 9.636722 9.557100 8.060213 8.018509 8.353709 11.054803
[19] 6.631720 8.745795
> colMax(tmp5)
[1] 467.96450 88.60715 79.90251 93.78745 79.27022 83.90996 78.69257
[8] 86.98813 77.59364 81.32376 89.01429 85.04918 82.33886 84.90227
[15] 81.99814 82.63257 86.44054 89.41302 85.31202 85.79625
> colMin(tmp5)
[1] 58.15656 56.48944 62.11599 54.18419 56.66529 53.18330 53.88393 53.44713
[9] 54.73491 54.25759 56.26162 63.73499 54.45602 53.87902 55.22129 59.79374
[17] 59.95449 58.79408 68.63157 57.96494
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] NA 69.94533 68.86502 69.85391 71.99173 71.47418 72.46489 71.55633
[9] 70.26216 72.58448
> rowSums(tmp5)
[1] NA 1398.907 1377.300 1397.078 1439.835 1429.484 1449.298 1431.127
[9] 1405.243 1451.690
> rowVars(tmp5)
[1] 8285.14024 97.14851 64.17843 49.59975 74.09756 75.99927
[7] 103.40253 55.89773 98.47165 88.51025
> rowSd(tmp5)
[1] 91.022746 9.856394 8.011144 7.042709 8.607994 8.717756 10.168703
[8] 7.476478 9.923288 9.407989
> rowMax(tmp5)
[1] NA 89.41302 85.31202 79.94187 87.42351 93.78745 89.01429 86.44054
[9] 84.80100 85.79625
> rowMin(tmp5)
[1] NA 53.87902 54.25759 56.26162 57.96494 56.48944 57.96477 56.65062
[9] 53.44713 53.18330
>
> colMeans(tmp5)
[1] 108.10250 71.00138 73.55230 71.02157 68.07337 68.50245 68.61766
[8] 70.54257 69.26760 NA 73.67152 72.15087 70.72213 72.91306
[15] 71.26545 69.81357 73.19233 73.68129 74.07177 71.20504
> colSums(tmp5)
[1] 1081.0250 710.0138 735.5230 710.2157 680.7337 685.0245 686.1766
[8] 705.4257 692.6760 NA 736.7152 721.5087 707.2213 729.1306
[15] 712.6545 698.1357 731.9233 736.8129 740.7177 712.0504
> colVars(tmp5)
[1] 16053.90343 93.85560 30.32306 157.81684 77.39351 100.77248
[7] 64.44782 90.46218 57.87254 NA 81.70984 33.22178
[13] 92.86641 91.33816 64.96704 64.29649 69.78445 122.20867
[19] 43.97971 76.48893
> colSd(tmp5)
[1] 126.703999 9.687910 5.506638 12.562517 8.797358 10.038550
[7] 8.027940 9.511161 7.607400 NA 9.039349 5.763834
[13] 9.636722 9.557100 8.060213 8.018509 8.353709 11.054803
[19] 6.631720 8.745795
> colMax(tmp5)
[1] 467.96450 88.60715 79.90251 93.78745 79.27022 83.90996 78.69257
[8] 86.98813 77.59364 NA 89.01429 85.04918 82.33886 84.90227
[15] 81.99814 82.63257 86.44054 89.41302 85.31202 85.79625
> colMin(tmp5)
[1] 58.15656 56.48944 62.11599 54.18419 56.66529 53.18330 53.88393 53.44713
[9] 54.73491 NA 56.26162 63.73499 54.45602 53.87902 55.22129 59.79374
[17] 59.95449 58.79408 68.63157 57.96494
>
> Max(tmp5,na.rm=TRUE)
[1] 467.9645
> Min(tmp5,na.rm=TRUE)
[1] 53.1833
> mean(tmp5,na.rm=TRUE)
[1] 73.12215
> Sum(tmp5,na.rm=TRUE)
[1] 14551.31
> Var(tmp5,na.rm=TRUE)
[1] 865.3409
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.22885 69.94533 68.86502 69.85391 71.99173 71.47418 72.46489 71.55633
[9] 70.26216 72.58448
> rowSums(tmp5,na.rm=TRUE)
[1] 1771.348 1398.907 1377.300 1397.078 1439.835 1429.484 1449.298 1431.127
[9] 1405.243 1451.690
> rowVars(tmp5,na.rm=TRUE)
[1] 8285.14024 97.14851 64.17843 49.59975 74.09756 75.99927
[7] 103.40253 55.89773 98.47165 88.51025
> rowSd(tmp5,na.rm=TRUE)
[1] 91.022746 9.856394 8.011144 7.042709 8.607994 8.717756 10.168703
[8] 7.476478 9.923288 9.407989
> rowMax(tmp5,na.rm=TRUE)
[1] 467.96450 89.41302 85.31202 79.94187 87.42351 93.78745 89.01429
[8] 86.44054 84.80100 85.79625
> rowMin(tmp5,na.rm=TRUE)
[1] 54.18419 53.87902 54.25759 56.26162 57.96494 56.48944 57.96477 56.65062
[9] 53.44713 53.18330
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.10250 71.00138 73.55230 71.02157 68.07337 68.50245 68.61766
[8] 70.54257 69.26760 70.84716 73.67152 72.15087 70.72213 72.91306
[15] 71.26545 69.81357 73.19233 73.68129 74.07177 71.20504
> colSums(tmp5,na.rm=TRUE)
[1] 1081.0250 710.0138 735.5230 710.2157 680.7337 685.0245 686.1766
[8] 705.4257 692.6760 637.6244 736.7152 721.5087 707.2213 729.1306
[15] 712.6545 698.1357 731.9233 736.8129 740.7177 712.0504
> colVars(tmp5,na.rm=TRUE)
[1] 16053.90343 93.85560 30.32306 157.81684 77.39351 100.77248
[7] 64.44782 90.46218 57.87254 75.57738 81.70984 33.22178
[13] 92.86641 91.33816 64.96704 64.29649 69.78445 122.20867
[19] 43.97971 76.48893
> colSd(tmp5,na.rm=TRUE)
[1] 126.703999 9.687910 5.506638 12.562517 8.797358 10.038550
[7] 8.027940 9.511161 7.607400 8.693525 9.039349 5.763834
[13] 9.636722 9.557100 8.060213 8.018509 8.353709 11.054803
[19] 6.631720 8.745795
> colMax(tmp5,na.rm=TRUE)
[1] 467.96450 88.60715 79.90251 93.78745 79.27022 83.90996 78.69257
[8] 86.98813 77.59364 81.32376 89.01429 85.04918 82.33886 84.90227
[15] 81.99814 82.63257 86.44054 89.41302 85.31202 85.79625
> colMin(tmp5,na.rm=TRUE)
[1] 58.15656 56.48944 62.11599 54.18419 56.66529 53.18330 53.88393 53.44713
[9] 54.73491 54.25759 56.26162 63.73499 54.45602 53.87902 55.22129 59.79374
[17] 59.95449 58.79408 68.63157 57.96494
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 69.94533 68.86502 69.85391 71.99173 71.47418 72.46489 71.55633
[9] 70.26216 72.58448
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1398.907 1377.300 1397.078 1439.835 1429.484 1449.298 1431.127
[9] 1405.243 1451.690
> rowVars(tmp5,na.rm=TRUE)
[1] NA 97.14851 64.17843 49.59975 74.09756 75.99927 103.40253
[8] 55.89773 98.47165 88.51025
> rowSd(tmp5,na.rm=TRUE)
[1] NA 9.856394 8.011144 7.042709 8.607994 8.717756 10.168703
[8] 7.476478 9.923288 9.407989
> rowMax(tmp5,na.rm=TRUE)
[1] NA 89.41302 85.31202 79.94187 87.42351 93.78745 89.01429 86.44054
[9] 84.80100 85.79625
> rowMin(tmp5,na.rm=TRUE)
[1] NA 53.87902 54.25759 56.26162 57.96494 56.48944 57.96477 56.65062
[9] 53.44713 53.18330
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 68.11783 70.40887 73.28981 72.89239 68.53147 67.53504 67.87546 68.71529
[9] 69.48212 NaN 74.03161 73.08596 70.05493 72.35645 70.86237 68.83167
[17] 73.52884 73.54738 74.63802 71.36292
> colSums(tmp5,na.rm=TRUE)
[1] 613.0605 633.6798 659.6083 656.0315 616.7833 607.8154 610.8791 618.4376
[9] 625.3391 0.0000 666.2845 657.7737 630.4944 651.2080 637.7614 619.4850
[17] 661.7596 661.9264 671.7422 642.2662
> colVars(tmp5,na.rm=TRUE)
[1] 74.43918 101.63797 33.33835 138.16932 84.70676 102.84037 66.30658
[8] 64.20655 64.58889 NA 90.46477 27.53742 99.46676 99.27001
[15] 71.26011 61.48708 77.23352 137.28302 45.87001 85.76964
> colSd(tmp5,na.rm=TRUE)
[1] 8.627814 10.081566 5.773937 11.754545 9.203627 10.141024 8.142885
[8] 8.012899 8.036721 NA 9.511297 5.247611 9.973302 9.963434
[15] 8.441570 7.841370 8.788261 11.716784 6.772740 9.261190
> colMax(tmp5,na.rm=TRUE)
[1] 81.69470 88.60715 79.90251 93.78745 79.27022 83.90996 78.69257 83.60871
[9] 77.59364 -Inf 89.01429 85.04918 82.33886 84.90227 81.99814 82.63257
[17] 86.44054 89.41302 85.31202 85.79625
> colMin(tmp5,na.rm=TRUE)
[1] 58.15656 56.48944 62.11599 56.65062 56.66529 53.18330 53.88393 53.44713
[9] 54.73491 Inf 56.26162 66.49392 54.45602 53.87902 55.22129 59.79374
[17] 59.95449 58.79408 68.63157 57.96494
>
>
>
>
> 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] 216.0196 259.0744 167.1063 130.7008 269.8529 264.7025 358.9300 166.5066
[9] 385.8233 372.6938
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 216.0196 259.0744 167.1063 130.7008 269.8529 264.7025 358.9300 166.5066
[9] 385.8233 372.6938
>
>
>
> 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] 5.684342e-14 2.842171e-14 0.000000e+00 0.000000e+00 2.842171e-14
[6] 0.000000e+00 -1.421085e-13 -1.705303e-13 -1.421085e-13 0.000000e+00
[11] 1.705303e-13 -1.705303e-13 8.526513e-14 1.136868e-13 0.000000e+00
[16] 8.526513e-14 2.842171e-14 5.684342e-14 5.684342e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 9
4 5
2 16
3 3
2 3
4 17
6 9
1 3
8 11
5 17
6 10
6 16
9 12
10 19
7 2
6 2
9 1
7 8
8 4
2 11
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] 2.505827
> Min(tmp)
[1] -1.983627
> mean(tmp)
[1] 0.0499816
> Sum(tmp)
[1] 4.99816
> Var(tmp)
[1] 0.9847581
>
> rowMeans(tmp)
[1] 0.0499816
> rowSums(tmp)
[1] 4.99816
> rowVars(tmp)
[1] 0.9847581
> rowSd(tmp)
[1] 0.9923498
> rowMax(tmp)
[1] 2.505827
> rowMin(tmp)
[1] -1.983627
>
> colMeans(tmp)
[1] 0.723805972 0.291947697 -0.819475739 0.292071290 1.491333262
[6] -1.983626721 -0.391909545 -0.774433702 -0.261765633 -1.084435843
[11] 0.900370022 -0.056549623 -0.093370693 1.558743367 0.433390462
[16] -1.718085286 0.383613498 -1.711884660 0.024050272 0.623605305
[21] 1.523899850 1.292394322 1.068362433 1.007700561 0.071374911
[26] 0.700389851 2.123225756 -0.629342232 -0.514995640 0.527279492
[31] -1.905529501 0.428323487 0.454771771 -0.101628104 0.729834897
[36] 1.219827214 -1.576332941 -0.757370614 0.798335333 -1.466116055
[41] -0.373359306 -0.869157690 -1.530583062 0.415554890 -0.155407942
[46] -0.821925244 1.151699146 1.739708665 -0.206807420 -0.544482171
[51] 0.951639339 -0.238525493 -0.231365672 -0.537394445 1.853608100
[56] -0.460618975 0.644542463 0.708849244 0.404881614 -0.804791557
[61] 1.837401080 0.968466692 0.212136648 0.945702061 0.147713539
[66] -1.313807274 1.052713832 -0.717269592 0.803397757 1.778345908
[71] 1.437401633 -0.607914498 1.368580139 0.961072553 -1.255819476
[76] 2.505826523 0.168527366 -0.646552694 0.671710464 0.104623659
[81] 0.413959376 0.320608284 -0.983244818 -0.128090698 0.230817337
[86] 0.231752813 0.302218734 -1.240138450 -0.899398846 -0.430278022
[91] -1.384945046 -0.469376483 -0.002642674 -1.221218376 -0.989862615
[96] -0.466345638 0.364449116 -0.409583548 -1.218400256 -1.362239755
> colSums(tmp)
[1] 0.723805972 0.291947697 -0.819475739 0.292071290 1.491333262
[6] -1.983626721 -0.391909545 -0.774433702 -0.261765633 -1.084435843
[11] 0.900370022 -0.056549623 -0.093370693 1.558743367 0.433390462
[16] -1.718085286 0.383613498 -1.711884660 0.024050272 0.623605305
[21] 1.523899850 1.292394322 1.068362433 1.007700561 0.071374911
[26] 0.700389851 2.123225756 -0.629342232 -0.514995640 0.527279492
[31] -1.905529501 0.428323487 0.454771771 -0.101628104 0.729834897
[36] 1.219827214 -1.576332941 -0.757370614 0.798335333 -1.466116055
[41] -0.373359306 -0.869157690 -1.530583062 0.415554890 -0.155407942
[46] -0.821925244 1.151699146 1.739708665 -0.206807420 -0.544482171
[51] 0.951639339 -0.238525493 -0.231365672 -0.537394445 1.853608100
[56] -0.460618975 0.644542463 0.708849244 0.404881614 -0.804791557
[61] 1.837401080 0.968466692 0.212136648 0.945702061 0.147713539
[66] -1.313807274 1.052713832 -0.717269592 0.803397757 1.778345908
[71] 1.437401633 -0.607914498 1.368580139 0.961072553 -1.255819476
[76] 2.505826523 0.168527366 -0.646552694 0.671710464 0.104623659
[81] 0.413959376 0.320608284 -0.983244818 -0.128090698 0.230817337
[86] 0.231752813 0.302218734 -1.240138450 -0.899398846 -0.430278022
[91] -1.384945046 -0.469376483 -0.002642674 -1.221218376 -0.989862615
[96] -0.466345638 0.364449116 -0.409583548 -1.218400256 -1.362239755
> 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] 0.723805972 0.291947697 -0.819475739 0.292071290 1.491333262
[6] -1.983626721 -0.391909545 -0.774433702 -0.261765633 -1.084435843
[11] 0.900370022 -0.056549623 -0.093370693 1.558743367 0.433390462
[16] -1.718085286 0.383613498 -1.711884660 0.024050272 0.623605305
[21] 1.523899850 1.292394322 1.068362433 1.007700561 0.071374911
[26] 0.700389851 2.123225756 -0.629342232 -0.514995640 0.527279492
[31] -1.905529501 0.428323487 0.454771771 -0.101628104 0.729834897
[36] 1.219827214 -1.576332941 -0.757370614 0.798335333 -1.466116055
[41] -0.373359306 -0.869157690 -1.530583062 0.415554890 -0.155407942
[46] -0.821925244 1.151699146 1.739708665 -0.206807420 -0.544482171
[51] 0.951639339 -0.238525493 -0.231365672 -0.537394445 1.853608100
[56] -0.460618975 0.644542463 0.708849244 0.404881614 -0.804791557
[61] 1.837401080 0.968466692 0.212136648 0.945702061 0.147713539
[66] -1.313807274 1.052713832 -0.717269592 0.803397757 1.778345908
[71] 1.437401633 -0.607914498 1.368580139 0.961072553 -1.255819476
[76] 2.505826523 0.168527366 -0.646552694 0.671710464 0.104623659
[81] 0.413959376 0.320608284 -0.983244818 -0.128090698 0.230817337
[86] 0.231752813 0.302218734 -1.240138450 -0.899398846 -0.430278022
[91] -1.384945046 -0.469376483 -0.002642674 -1.221218376 -0.989862615
[96] -0.466345638 0.364449116 -0.409583548 -1.218400256 -1.362239755
> colMin(tmp)
[1] 0.723805972 0.291947697 -0.819475739 0.292071290 1.491333262
[6] -1.983626721 -0.391909545 -0.774433702 -0.261765633 -1.084435843
[11] 0.900370022 -0.056549623 -0.093370693 1.558743367 0.433390462
[16] -1.718085286 0.383613498 -1.711884660 0.024050272 0.623605305
[21] 1.523899850 1.292394322 1.068362433 1.007700561 0.071374911
[26] 0.700389851 2.123225756 -0.629342232 -0.514995640 0.527279492
[31] -1.905529501 0.428323487 0.454771771 -0.101628104 0.729834897
[36] 1.219827214 -1.576332941 -0.757370614 0.798335333 -1.466116055
[41] -0.373359306 -0.869157690 -1.530583062 0.415554890 -0.155407942
[46] -0.821925244 1.151699146 1.739708665 -0.206807420 -0.544482171
[51] 0.951639339 -0.238525493 -0.231365672 -0.537394445 1.853608100
[56] -0.460618975 0.644542463 0.708849244 0.404881614 -0.804791557
[61] 1.837401080 0.968466692 0.212136648 0.945702061 0.147713539
[66] -1.313807274 1.052713832 -0.717269592 0.803397757 1.778345908
[71] 1.437401633 -0.607914498 1.368580139 0.961072553 -1.255819476
[76] 2.505826523 0.168527366 -0.646552694 0.671710464 0.104623659
[81] 0.413959376 0.320608284 -0.983244818 -0.128090698 0.230817337
[86] 0.231752813 0.302218734 -1.240138450 -0.899398846 -0.430278022
[91] -1.384945046 -0.469376483 -0.002642674 -1.221218376 -0.989862615
[96] -0.466345638 0.364449116 -0.409583548 -1.218400256 -1.362239755
> colMedians(tmp)
[1] 0.723805972 0.291947697 -0.819475739 0.292071290 1.491333262
[6] -1.983626721 -0.391909545 -0.774433702 -0.261765633 -1.084435843
[11] 0.900370022 -0.056549623 -0.093370693 1.558743367 0.433390462
[16] -1.718085286 0.383613498 -1.711884660 0.024050272 0.623605305
[21] 1.523899850 1.292394322 1.068362433 1.007700561 0.071374911
[26] 0.700389851 2.123225756 -0.629342232 -0.514995640 0.527279492
[31] -1.905529501 0.428323487 0.454771771 -0.101628104 0.729834897
[36] 1.219827214 -1.576332941 -0.757370614 0.798335333 -1.466116055
[41] -0.373359306 -0.869157690 -1.530583062 0.415554890 -0.155407942
[46] -0.821925244 1.151699146 1.739708665 -0.206807420 -0.544482171
[51] 0.951639339 -0.238525493 -0.231365672 -0.537394445 1.853608100
[56] -0.460618975 0.644542463 0.708849244 0.404881614 -0.804791557
[61] 1.837401080 0.968466692 0.212136648 0.945702061 0.147713539
[66] -1.313807274 1.052713832 -0.717269592 0.803397757 1.778345908
[71] 1.437401633 -0.607914498 1.368580139 0.961072553 -1.255819476
[76] 2.505826523 0.168527366 -0.646552694 0.671710464 0.104623659
[81] 0.413959376 0.320608284 -0.983244818 -0.128090698 0.230817337
[86] 0.231752813 0.302218734 -1.240138450 -0.899398846 -0.430278022
[91] -1.384945046 -0.469376483 -0.002642674 -1.221218376 -0.989862615
[96] -0.466345638 0.364449116 -0.409583548 -1.218400256 -1.362239755
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.723806 0.2919477 -0.8194757 0.2920713 1.491333 -1.983627 -0.3919095
[2,] 0.723806 0.2919477 -0.8194757 0.2920713 1.491333 -1.983627 -0.3919095
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.7744337 -0.2617656 -1.084436 0.90037 -0.05654962 -0.09337069 1.558743
[2,] -0.7744337 -0.2617656 -1.084436 0.90037 -0.05654962 -0.09337069 1.558743
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.4333905 -1.718085 0.3836135 -1.711885 0.02405027 0.6236053 1.5239
[2,] 0.4333905 -1.718085 0.3836135 -1.711885 0.02405027 0.6236053 1.5239
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.292394 1.068362 1.007701 0.07137491 0.7003899 2.123226 -0.6293422
[2,] 1.292394 1.068362 1.007701 0.07137491 0.7003899 2.123226 -0.6293422
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5149956 0.5272795 -1.90553 0.4283235 0.4547718 -0.1016281 0.7298349
[2,] -0.5149956 0.5272795 -1.90553 0.4283235 0.4547718 -0.1016281 0.7298349
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.219827 -1.576333 -0.7573706 0.7983353 -1.466116 -0.3733593 -0.8691577
[2,] 1.219827 -1.576333 -0.7573706 0.7983353 -1.466116 -0.3733593 -0.8691577
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.530583 0.4155549 -0.1554079 -0.8219252 1.151699 1.739709 -0.2068074
[2,] -1.530583 0.4155549 -0.1554079 -0.8219252 1.151699 1.739709 -0.2068074
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.5444822 0.9516393 -0.2385255 -0.2313657 -0.5373944 1.853608 -0.460619
[2,] -0.5444822 0.9516393 -0.2385255 -0.2313657 -0.5373944 1.853608 -0.460619
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.6445425 0.7088492 0.4048816 -0.8047916 1.837401 0.9684667 0.2121366
[2,] 0.6445425 0.7088492 0.4048816 -0.8047916 1.837401 0.9684667 0.2121366
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.9457021 0.1477135 -1.313807 1.052714 -0.7172696 0.8033978 1.778346
[2,] 0.9457021 0.1477135 -1.313807 1.052714 -0.7172696 0.8033978 1.778346
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.437402 -0.6079145 1.36858 0.9610726 -1.255819 2.505827 0.1685274
[2,] 1.437402 -0.6079145 1.36858 0.9610726 -1.255819 2.505827 0.1685274
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.6465527 0.6717105 0.1046237 0.4139594 0.3206083 -0.9832448 -0.1280907
[2,] -0.6465527 0.6717105 0.1046237 0.4139594 0.3206083 -0.9832448 -0.1280907
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.2308173 0.2317528 0.3022187 -1.240138 -0.8993988 -0.430278 -1.384945
[2,] 0.2308173 0.2317528 0.3022187 -1.240138 -0.8993988 -0.430278 -1.384945
[,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.4693765 -0.002642674 -1.221218 -0.9898626 -0.4663456 0.3644491
[2,] -0.4693765 -0.002642674 -1.221218 -0.9898626 -0.4663456 0.3644491
[,98] [,99] [,100]
[1,] -0.4095835 -1.2184 -1.36224
[2,] -0.4095835 -1.2184 -1.36224
>
>
> Max(tmp2)
[1] 2.245361
> Min(tmp2)
[1] -3.057939
> mean(tmp2)
[1] -0.1130832
> Sum(tmp2)
[1] -11.30832
> Var(tmp2)
[1] 1.004042
>
> rowMeans(tmp2)
[1] -1.41462274 -0.64632896 0.50439798 -0.03015459 -0.49755019 -0.79415265
[7] 0.96643342 -0.37221358 -0.51475109 -0.84695659 1.07471574 -0.22700183
[13] 0.88153331 -0.95097498 -0.29320668 -1.13776061 -1.09023546 -0.45413503
[19] -0.01563626 -2.36415723 0.11955482 -1.25489114 -0.35884507 0.91802246
[25] -0.33549856 -0.33041624 -0.89293758 0.15243521 0.02933330 1.13122093
[31] -1.73686863 -1.42415617 -0.21709712 -0.10067855 -0.57432676 -0.38855718
[37] -1.33241167 0.61045651 0.69805658 0.23764005 0.37265131 -2.36966522
[43] -3.05793950 0.80240207 0.81658671 -1.20085880 0.70256414 -0.88740735
[49] -0.87735723 0.31308345 -0.79171133 -0.92440512 0.46940949 0.44450965
[55] 0.76838038 -0.13979711 0.82856235 0.76503250 -0.85998284 0.73537146
[61] 0.04227580 1.86926095 0.18006554 0.42754886 0.21915675 -0.60008869
[67] -0.41207871 0.10559773 2.24536141 0.80875940 -0.09266219 0.21958499
[73] -1.49416749 0.37846309 -0.54547789 0.91112934 0.85096014 1.35723025
[79] -0.57065247 -2.03649577 -1.98537901 0.96891871 0.42794185 1.22869242
[85] -0.50056922 -0.54808769 -0.39626348 -1.18202765 1.03206275 1.76525146
[91] 0.54044140 -0.57856255 0.82513322 -0.62756385 -0.88909936 0.89644711
[97] 2.22108311 0.10110470 -1.83559039 0.72726600
> rowSums(tmp2)
[1] -1.41462274 -0.64632896 0.50439798 -0.03015459 -0.49755019 -0.79415265
[7] 0.96643342 -0.37221358 -0.51475109 -0.84695659 1.07471574 -0.22700183
[13] 0.88153331 -0.95097498 -0.29320668 -1.13776061 -1.09023546 -0.45413503
[19] -0.01563626 -2.36415723 0.11955482 -1.25489114 -0.35884507 0.91802246
[25] -0.33549856 -0.33041624 -0.89293758 0.15243521 0.02933330 1.13122093
[31] -1.73686863 -1.42415617 -0.21709712 -0.10067855 -0.57432676 -0.38855718
[37] -1.33241167 0.61045651 0.69805658 0.23764005 0.37265131 -2.36966522
[43] -3.05793950 0.80240207 0.81658671 -1.20085880 0.70256414 -0.88740735
[49] -0.87735723 0.31308345 -0.79171133 -0.92440512 0.46940949 0.44450965
[55] 0.76838038 -0.13979711 0.82856235 0.76503250 -0.85998284 0.73537146
[61] 0.04227580 1.86926095 0.18006554 0.42754886 0.21915675 -0.60008869
[67] -0.41207871 0.10559773 2.24536141 0.80875940 -0.09266219 0.21958499
[73] -1.49416749 0.37846309 -0.54547789 0.91112934 0.85096014 1.35723025
[79] -0.57065247 -2.03649577 -1.98537901 0.96891871 0.42794185 1.22869242
[85] -0.50056922 -0.54808769 -0.39626348 -1.18202765 1.03206275 1.76525146
[91] 0.54044140 -0.57856255 0.82513322 -0.62756385 -0.88909936 0.89644711
[97] 2.22108311 0.10110470 -1.83559039 0.72726600
> 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] -1.41462274 -0.64632896 0.50439798 -0.03015459 -0.49755019 -0.79415265
[7] 0.96643342 -0.37221358 -0.51475109 -0.84695659 1.07471574 -0.22700183
[13] 0.88153331 -0.95097498 -0.29320668 -1.13776061 -1.09023546 -0.45413503
[19] -0.01563626 -2.36415723 0.11955482 -1.25489114 -0.35884507 0.91802246
[25] -0.33549856 -0.33041624 -0.89293758 0.15243521 0.02933330 1.13122093
[31] -1.73686863 -1.42415617 -0.21709712 -0.10067855 -0.57432676 -0.38855718
[37] -1.33241167 0.61045651 0.69805658 0.23764005 0.37265131 -2.36966522
[43] -3.05793950 0.80240207 0.81658671 -1.20085880 0.70256414 -0.88740735
[49] -0.87735723 0.31308345 -0.79171133 -0.92440512 0.46940949 0.44450965
[55] 0.76838038 -0.13979711 0.82856235 0.76503250 -0.85998284 0.73537146
[61] 0.04227580 1.86926095 0.18006554 0.42754886 0.21915675 -0.60008869
[67] -0.41207871 0.10559773 2.24536141 0.80875940 -0.09266219 0.21958499
[73] -1.49416749 0.37846309 -0.54547789 0.91112934 0.85096014 1.35723025
[79] -0.57065247 -2.03649577 -1.98537901 0.96891871 0.42794185 1.22869242
[85] -0.50056922 -0.54808769 -0.39626348 -1.18202765 1.03206275 1.76525146
[91] 0.54044140 -0.57856255 0.82513322 -0.62756385 -0.88909936 0.89644711
[97] 2.22108311 0.10110470 -1.83559039 0.72726600
> rowMin(tmp2)
[1] -1.41462274 -0.64632896 0.50439798 -0.03015459 -0.49755019 -0.79415265
[7] 0.96643342 -0.37221358 -0.51475109 -0.84695659 1.07471574 -0.22700183
[13] 0.88153331 -0.95097498 -0.29320668 -1.13776061 -1.09023546 -0.45413503
[19] -0.01563626 -2.36415723 0.11955482 -1.25489114 -0.35884507 0.91802246
[25] -0.33549856 -0.33041624 -0.89293758 0.15243521 0.02933330 1.13122093
[31] -1.73686863 -1.42415617 -0.21709712 -0.10067855 -0.57432676 -0.38855718
[37] -1.33241167 0.61045651 0.69805658 0.23764005 0.37265131 -2.36966522
[43] -3.05793950 0.80240207 0.81658671 -1.20085880 0.70256414 -0.88740735
[49] -0.87735723 0.31308345 -0.79171133 -0.92440512 0.46940949 0.44450965
[55] 0.76838038 -0.13979711 0.82856235 0.76503250 -0.85998284 0.73537146
[61] 0.04227580 1.86926095 0.18006554 0.42754886 0.21915675 -0.60008869
[67] -0.41207871 0.10559773 2.24536141 0.80875940 -0.09266219 0.21958499
[73] -1.49416749 0.37846309 -0.54547789 0.91112934 0.85096014 1.35723025
[79] -0.57065247 -2.03649577 -1.98537901 0.96891871 0.42794185 1.22869242
[85] -0.50056922 -0.54808769 -0.39626348 -1.18202765 1.03206275 1.76525146
[91] 0.54044140 -0.57856255 0.82513322 -0.62756385 -0.88909936 0.89644711
[97] 2.22108311 0.10110470 -1.83559039 0.72726600
>
> colMeans(tmp2)
[1] -0.1130832
> colSums(tmp2)
[1] -11.30832
> colVars(tmp2)
[1] 1.004042
> colSd(tmp2)
[1] 1.002019
> colMax(tmp2)
[1] 2.245361
> colMin(tmp2)
[1] -3.057939
> colMedians(tmp2)
[1] -0.09667037
> colRanges(tmp2)
[,1]
[1,] -3.057939
[2,] 2.245361
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.1903956 -0.7592161 -0.1819458 1.2665594 -0.1462820 -5.9351134
[7] -6.9067753 -2.1884163 -3.2199412 2.1639806
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4123913
[2,] -0.4772889
[3,] 0.1350138
[4,] 1.4397082
[5,] 1.6944101
>
> rowApply(tmp,sum)
[1] -1.5034233 -6.7391046 -2.2890550 1.7931669 -1.7511906 1.7869488
[7] 3.2361632 -4.4521001 -3.5430955 0.7449357
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 2 10 7 9 2 10 8 5 4
[2,] 3 9 8 5 8 7 6 5 9 1
[3,] 6 7 4 6 7 9 1 7 8 7
[4,] 5 8 9 1 1 8 5 10 6 9
[5,] 8 10 2 9 10 6 2 1 1 8
[6,] 7 1 6 2 5 5 3 4 2 3
[7,] 2 3 3 3 4 4 7 2 4 2
[8,] 1 5 7 8 2 10 4 9 3 5
[9,] 4 6 1 10 3 3 8 6 7 6
[10,] 10 4 5 4 6 1 9 3 10 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.86041440 -0.75513054 3.39034056 3.57918660 1.59005283 1.68429624
[7] -0.69491122 -0.54823294 0.36354970 -0.77782090 -1.12870247 0.15475916
[13] 2.28390628 -3.13309561 -0.01450309 -1.43007300 -3.16856635 0.86966436
[19] 2.21549485 -1.77763813
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1511072
[2,] -0.9505198
[3,] -0.6007176
[4,] -0.3436694
[5,] 0.1855995
>
> rowApply(tmp,sum)
[1] 5.2249123 -0.3491867 -6.3833941 -2.9741688 4.3239993
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 3 10 14 8
[2,] 6 11 6 16 14
[3,] 11 17 17 19 7
[4,] 16 12 3 20 20
[5,] 14 15 14 1 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.1511072 -1.0217752 0.4914796 1.19154628 0.8021616 -0.29382262
[2,] -0.9505198 -0.2022367 1.1490889 0.01887467 1.0387321 1.24039771
[3,] -0.6007176 -0.9398212 1.0277230 -1.49209638 0.1599410 1.30246661
[4,] 0.1855995 0.7657302 1.1056728 1.69027373 -1.7025256 0.06756928
[5,] -0.3436694 0.6429725 -0.3836238 2.17058830 1.2917437 -0.63231474
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.2423937 2.1029985 -1.28260860 0.9454514 -1.0962531 1.4618708
[2,] -0.4478895 0.5932098 1.07302406 0.1373448 -0.6633397 -0.9074517
[3,] -0.9893244 -1.8844375 0.04201336 -0.2190611 0.4480399 -1.0737265
[4,] -1.2964635 -0.3256937 -0.60112536 -0.8843679 0.6573242 0.8047687
[5,] 1.7963724 -1.0343100 1.13224624 -0.7571881 -0.4744738 -0.1307022
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.79377396 -1.7050451 -0.2655670 0.2350226 -1.6717581 2.1417086
[2,] -0.64668373 1.2869271 1.6514683 -0.9460874 -1.7977550 -0.7477704
[3,] 1.11871017 -2.6956141 -0.6592997 1.3605383 0.3950157 -0.8146013
[4,] 0.92544723 0.1276910 -1.0328432 -0.4293371 -1.3434484 -1.2134670
[5,] 0.09265865 -0.1470546 0.2917385 -1.6502095 1.2493794 1.5037945
[,19] [,20]
[1,] 2.54701807 0.7574241
[2,] -0.25052240 -0.9779979
[3,] 0.01007077 -0.8792133
[4,] -0.21918718 -0.2557866
[5,] 0.12811558 -0.4220645
>
>
> 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 : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-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 0.4943249 0.07638262 0.9314145 1.743332 -1.410033 0.6205411 0.4558522
col8 col9 col10 col11 col12 col13 col14 col15
row1 0.736832 -2.087105 0.713727 -1.989014 0.5275917 -0.2482586 -1.446 1.747269
col16 col17 col18 col19 col20
row1 -0.5578145 0.1558309 0.2508421 -1.202764 0.07637955
> tmp[,"col10"]
col10
row1 0.71372704
row2 -1.21372504
row3 0.20032727
row4 -2.68450096
row5 0.02597674
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.4943249 0.07638262 0.9314145 1.7433316 -1.410033 0.6205411 0.4558522
row5 1.9167107 -1.98750988 1.0924702 -0.8895512 -1.179247 1.4875386 -0.7944726
col8 col9 col10 col11 col12 col13 col14
row1 0.7368320 -2.087105 0.71372704 -1.9890141 0.5275917 -0.2482586 -1.4460003
row5 0.7331177 -0.644671 0.02597674 0.9915097 -1.1155743 -1.2400805 0.4866139
col15 col16 col17 col18 col19 col20
row1 1.7472693 -0.5578145 0.1558309 0.2508421 -1.202764 0.07637955
row5 0.6725515 -0.8820223 0.5382020 -0.9080520 1.277804 -0.25076026
> tmp[,c("col6","col20")]
col6 col20
row1 0.6205411 0.07637955
row2 0.3362069 -1.85247720
row3 1.3620321 1.16655267
row4 -0.1877167 -1.27990999
row5 1.4875386 -0.25076026
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.6205411 0.07637955
row5 1.4875386 -0.25076026
>
>
>
>
> 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 49.42723 48.69369 48.41469 49.51861 50.47252 104.0195 49.01349 49.70244
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.67238 49.81592 49.83225 51.92543 49.9596 49.19384 51.55038 50.45829
col17 col18 col19 col20
row1 50.53678 50.50411 49.09924 104.7026
> tmp[,"col10"]
col10
row1 49.81592
row2 29.42326
row3 29.40684
row4 31.09034
row5 51.06441
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.42723 48.69369 48.41469 49.51861 50.47252 104.0195 49.01349 49.70244
row5 51.08526 48.56942 50.23191 50.17212 49.61549 105.7816 50.07866 50.67335
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.67238 49.81592 49.83225 51.92543 49.95960 49.19384 51.55038 50.45829
row5 50.05842 51.06441 50.08117 49.98649 49.60925 50.82244 50.09096 49.76014
col17 col18 col19 col20
row1 50.53678 50.50411 49.09924 104.7026
row5 49.79853 51.14974 50.30534 105.7992
> tmp[,c("col6","col20")]
col6 col20
row1 104.01946 104.70257
row2 74.87768 73.79094
row3 74.68780 76.09110
row4 75.41039 75.46776
row5 105.78159 105.79925
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.0195 104.7026
row5 105.7816 105.7992
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.0195 104.7026
row5 105.7816 105.7992
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.72009776
[2,] 1.29423476
[3,] -0.09996269
[4,] 1.13110880
[5,] 1.13626563
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.74419928 0.01195814
[2,] -0.07660301 -0.23770405
[3,] 0.44228878 0.15628688
[4,] -0.16211717 1.97906548
[5,] 2.34810436 -1.21361245
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.5996409 1.14005231
[2,] -0.5133254 -0.61900449
[3,] 2.1590346 -0.21234863
[4,] 0.1375211 -0.63194950
[5,] -0.7661768 0.05471429
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.599641
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.5996409
[2,] -0.5133254
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.3474315 -1.267067 -1.0223887 -0.8034280 0.03272916 -0.6440535
row1 0.6172441 -0.612830 -0.1582661 0.5449177 -1.21356465 0.5097338
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.9145976 0.1147438 -0.6477460 -0.7564228 2.2850275 1.977192
row1 -0.1982261 -0.6607542 -0.6638373 -0.4769960 0.3555583 -1.543091
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -0.008348287 0.2468693 -1.246889 0.3924723 -0.7526866 0.2249749
row1 -0.973629888 -0.3165094 2.167906 -1.4114527 1.6594457 0.9808370
[,19] [,20]
row3 0.05466109 0.66676375
row1 -1.60028175 -0.07200412
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.3852743 1.62568 0.1239268 0.426127 2.280593 -0.07716562 0.9559531
[,8] [,9] [,10]
row2 -1.800285 0.1842636 1.047232
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.753382 -1.055353 0.981596 -0.905308 0.7346132 0.2180913 -0.1194079
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4709192 0.6044072 0.3363253 1.446315 -0.9263046 -0.9805157 -0.1579007
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.985778 0.8060426 -0.7296633 0.7457118 -1.129067 0.8225325
>
>
> 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: 0x5ffe73404840>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e410ab02e"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e56dc0001"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e7e3c1fe8"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e5bce6cc5"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e25a555d4"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e61f3b4db"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e722c7869"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e59164350"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e6bebdba8"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e7a0ea248"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e73c3fafd"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e46982123"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e30f85662"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e22516a5b"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a727e1f681d75"
>
>
> ### 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: 0x5ffe735c2fc0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5ffe735c2fc0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5ffe735c2fc0>
> rowMedians(tmp)
[1] 0.268072898 -0.034513698 -0.236384959 -0.219824664 0.229761175
[6] 0.501122291 0.177460086 0.451729517 0.180638754 -0.276037384
[11] -0.118056546 0.019946857 -0.531860474 0.115325262 -0.075188926
[16] 0.152988187 -0.369488628 0.210723715 0.239274383 0.385607071
[21] -0.132371803 0.088998156 -0.054939630 -0.176125724 0.485864617
[26] 0.313493287 0.083437690 -0.046429748 -0.095969426 0.508271334
[31] 0.624153144 -0.246409953 0.355442710 -0.330978847 -0.462347439
[36] 0.154934617 0.434545638 0.388396784 -0.092092606 -0.201108297
[41] -0.249143093 0.007893058 0.730536113 0.135483770 -0.346038081
[46] 0.017755368 0.083354411 -0.753187242 -0.083127145 -0.014026388
[51] 0.076966563 -0.112320642 -0.356238544 0.338917711 0.345649297
[56] 0.775989753 -0.334132444 -0.037948349 0.366512782 0.245689214
[61] -0.021189740 0.309427534 0.096741479 0.010947926 0.496494385
[66] -0.076612728 0.134952472 0.093893890 0.077608454 -0.446594947
[71] -0.171970311 0.355559645 -0.279268363 0.357187601 -0.198209831
[76] 0.335794645 0.249024534 -0.024929648 0.005597728 0.298448741
[81] 0.241603964 -0.295968444 -0.209494916 -0.034889252 0.070986324
[86] 0.545990358 -0.015123929 0.322979444 -0.114141152 -0.568529853
[91] 0.094785813 0.388945219 -0.017029510 0.078191094 0.047843565
[96] -0.166279769 0.237497037 0.244972461 -0.854024937 -0.422801482
[101] -0.432476255 0.736184700 0.349901285 -0.005362766 0.484111226
[106] -0.008358358 -0.648023862 -0.829563858 0.142693959 0.562226016
[111] -0.685132617 0.017282805 -0.293686739 0.458036120 -0.119777990
[116] 0.322827192 0.039672496 0.298073977 -0.042996510 0.315314758
[121] -0.338541003 0.538868368 -0.096957350 -0.117846998 0.174156197
[126] 0.187913254 0.260472593 0.049672232 -0.177829472 -0.308852458
[131] -0.140513821 -0.370760792 0.568440521 -0.267145990 -0.105411539
[136] -0.009817113 -0.534607973 0.211116291 -0.106992109 -0.288002875
[141] 0.208355477 0.080592778 0.268246418 0.141546188 0.189324638
[146] -0.025137925 0.251581336 0.026794163 0.225158025 -0.258785608
[151] -0.278755842 0.073871931 -0.121344138 0.086545568 0.715590216
[156] -0.362928885 -0.483350865 0.169202159 0.498529846 -0.084111502
[161] -0.177347926 -0.166484346 -0.043946211 0.176151560 -0.086705830
[166] 0.391170850 -0.273180424 0.062774769 0.137433915 0.321161812
[171] 0.180713605 0.103111051 0.317699483 -0.430031197 0.049699057
[176] -0.410035843 0.488377213 -0.159003271 -0.145879596 0.156432030
[181] 0.068412297 -0.079132742 0.327394903 0.174434731 0.204078419
[186] -0.089679259 0.049799551 -0.169974353 1.007740997 -0.390726993
[191] -0.190034319 -0.371600078 0.235488483 0.409497780 -0.116171099
[196] -0.061718872 -0.230725868 -0.357502022 -0.349231091 0.032342578
[201] -0.243851642 0.126425615 -0.282359602 -0.285009896 0.294322650
[206] 0.218180842 0.202958332 -0.486095906 0.083389278 0.035559901
[211] -0.312249322 -0.239049301 -0.002666844 0.102224220 0.219616230
[216] 0.444662289 -0.236798204 -0.178172761 0.517586145 0.079609929
[221] -0.096695913 0.389991509 -0.197539685 -0.055829957 -0.052656352
[226] -0.165444514 -0.249948543 0.677733481 0.584746278 0.186462282
>
> proc.time()
user system elapsed
1.354 1.478 2.820
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: 0x5890fa6f2c10>
> .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: 0x5890fa6f2c10>
> .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: 0x5890fa6f2c10>
> .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: 0x5890fa6f2c10>
> 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: 0x5890fb3b52d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fb3b52d0>
> .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: 0x5890fb3b52d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fb3b52d0>
> .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: 0x5890fb3b52d0>
> 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: 0x5890fba8ad70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fba8ad70>
> .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: 0x5890fba8ad70>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5890fba8ad70>
> .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: 0x5890fba8ad70>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5890fba8ad70>
> .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: 0x5890fba8ad70>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5890fba8ad70>
> .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: 0x5890fba8ad70>
> 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: 0x5890fb5fe370>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5890fb5fe370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fb5fe370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fb5fe370>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a72ecb07a845" "BufferedMatrixFile3a72ecdeff320"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a72ecb07a845" "BufferedMatrixFile3a72ecdeff320"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fb549ff0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fb549ff0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5890fb549ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5890fb549ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5890fb549ff0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5890fb549ff0>
> .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: 0x5890fb72c3d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5890fb72c3d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5890fb72c3d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5890fb72c3d0>
> 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: 0x5890fceddfb0>
> .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: 0x5890fceddfb0>
> rm(P)
>
> proc.time()
user system elapsed
0.252 0.049 0.289
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
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Platform: x86_64-pc-linux-gnu
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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
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> 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
0.239 0.047 0.274