Ben Bolstad
| Snapshot Date: 2026-02-19 13:40 -0500 (Thu, 19 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 2026-02-20 11:32 -0500 (Fri, 20 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" | 4869 |
| 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: 2026-02-19 21:46:50 -0500 (Thu, 19 Feb 2026) |
| EndedAt: 2026-02-19 21:47:15 -0500 (Thu, 19 Feb 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
0.252 0.056 0.292
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] "Thu Feb 19 21:47:05 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] "Thu Feb 19 21:47:05 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: 0x6015c77f4c10>
>
>
>
> 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] "Thu Feb 19 21:47:05 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] "Thu Feb 19 21:47:05 2026"
>
> ColMode(tmp2)
<pointer: 0x6015c77f4c10>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.9512340 -0.9596542 1.0257691 -0.2018870
[2,] -0.3363918 -1.4767491 -0.8025801 0.6660436
[3,] -1.3754348 -1.5801711 1.2419896 1.2801102
[4,] -1.8325089 -1.0463902 1.5007561 1.5530943
> 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,] 100.9512340 0.9596542 1.0257691 0.2018870
[2,] 0.3363918 1.4767491 0.8025801 0.6660436
[3,] 1.3754348 1.5801711 1.2419896 1.2801102
[4,] 1.8325089 1.0463902 1.5007561 1.5530943
> 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,] 10.0474491 0.9796194 1.0128026 0.4493183
[2,] 0.5799929 1.2152156 0.8958684 0.8161150
[3,] 1.1727893 1.2570486 1.1144459 1.1314196
[4,] 1.3537019 1.0229322 1.2250535 1.2462321
>
> 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,] 226.42573 35.75585 36.15380 29.69507
[2,] 31.13632 38.62891 34.76126 33.82719
[3,] 38.10333 39.15066 37.38645 37.59431
[4,] 40.36953 36.27571 38.75129 39.01541
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6015c7982cb0>
> exp(tmp5)
<pointer: 0x6015c7982cb0>
> log(tmp5,2)
<pointer: 0x6015c7982cb0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.2755
> Min(tmp5)
[1] 53.87421
> mean(tmp5)
[1] 72.35856
> Sum(tmp5)
[1] 14471.71
> Var(tmp5)
[1] 870.2135
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.22066 70.37455 74.43929 71.27535 67.76187 69.72782 72.27742 69.04107
[9] 70.40401 68.06360
> rowSums(tmp5)
[1] 1804.413 1407.491 1488.786 1425.507 1355.237 1394.556 1445.548 1380.821
[9] 1408.080 1361.272
> rowVars(tmp5)
[1] 8117.99077 93.58276 58.95671 57.32790 51.44434 59.59517
[7] 46.07940 78.55805 90.82747 49.63870
> rowSd(tmp5)
[1] 90.099893 9.673818 7.678327 7.571519 7.172471 7.719790 6.788181
[8] 8.863298 9.530345 7.045474
> rowMax(tmp5)
[1] 471.27548 89.35701 93.59329 84.02388 82.64486 87.88109 83.10348
[8] 85.34877 83.78821 81.41620
> rowMin(tmp5)
[1] 57.57417 53.87421 59.52797 57.73195 57.19521 57.86848 59.66445 56.17517
[9] 55.18066 57.21286
>
> colMeans(tmp5)
[1] 114.94716 73.80771 75.12792 69.10306 68.18164 70.82140 66.65223
[8] 64.23804 65.20662 75.25954 68.77536 71.26099 68.63721 67.65570
[15] 68.89310 73.72076 72.37156 68.99933 72.97316 70.53877
> colSums(tmp5)
[1] 1149.4716 738.0771 751.2792 691.0306 681.8164 708.2140 666.5223
[8] 642.3804 652.0662 752.5954 687.7536 712.6099 686.3721 676.5570
[15] 688.9310 737.2076 723.7156 689.9933 729.7316 705.3877
> colVars(tmp5)
[1] 15754.53576 56.87487 36.90551 52.03968 45.70866 81.90913
[7] 45.07176 38.81508 48.03727 91.30822 32.23654 108.62067
[13] 47.00169 31.96397 140.26883 46.00793 94.44146 75.91543
[19] 60.16367 30.35587
> colSd(tmp5)
[1] 125.517074 7.541543 6.074991 7.213853 6.760818 9.050366
[7] 6.713550 6.230175 6.930892 9.555534 5.677723 10.422124
[13] 6.855778 5.653668 11.843514 6.782915 9.718100 8.712946
[19] 7.756524 5.509616
> colMax(tmp5)
[1] 471.27548 82.11073 83.05377 81.20547 76.51472 81.41620 77.07882
[8] 73.88869 77.17555 93.59329 74.73717 87.88109 79.50787 75.33029
[15] 92.36129 85.34877 89.35701 83.78821 85.13484 78.76165
> colMin(tmp5)
[1] 57.22281 59.66445 64.82271 57.86848 56.60008 53.87421 57.19521 56.17517
[9] 55.18066 62.73567 58.07804 58.57600 60.45990 57.21286 54.83108 64.49411
[17] 58.23320 55.97546 63.61408 63.52240
>
>
> ### 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] 90.22066 70.37455 74.43929 71.27535 67.76187 69.72782 NA 69.04107
[9] 70.40401 68.06360
> rowSums(tmp5)
[1] 1804.413 1407.491 1488.786 1425.507 1355.237 1394.556 NA 1380.821
[9] 1408.080 1361.272
> rowVars(tmp5)
[1] 8117.99077 93.58276 58.95671 57.32790 51.44434 59.59517
[7] 43.42721 78.55805 90.82747 49.63870
> rowSd(tmp5)
[1] 90.099893 9.673818 7.678327 7.571519 7.172471 7.719790 6.589932
[8] 8.863298 9.530345 7.045474
> rowMax(tmp5)
[1] 471.27548 89.35701 93.59329 84.02388 82.64486 87.88109 NA
[8] 85.34877 83.78821 81.41620
> rowMin(tmp5)
[1] 57.57417 53.87421 59.52797 57.73195 57.19521 57.86848 NA 56.17517
[9] 55.18066 57.21286
>
> colMeans(tmp5)
[1] 114.94716 73.80771 75.12792 69.10306 68.18164 70.82140 66.65223
[8] 64.23804 65.20662 75.25954 NA 71.26099 68.63721 67.65570
[15] 68.89310 73.72076 72.37156 68.99933 72.97316 70.53877
> colSums(tmp5)
[1] 1149.4716 738.0771 751.2792 691.0306 681.8164 708.2140 666.5223
[8] 642.3804 652.0662 752.5954 NA 712.6099 686.3721 676.5570
[15] 688.9310 737.2076 723.7156 689.9933 729.7316 705.3877
> colVars(tmp5)
[1] 15754.53576 56.87487 36.90551 52.03968 45.70866 81.90913
[7] 45.07176 38.81508 48.03727 91.30822 NA 108.62067
[13] 47.00169 31.96397 140.26883 46.00793 94.44146 75.91543
[19] 60.16367 30.35587
> colSd(tmp5)
[1] 125.517074 7.541543 6.074991 7.213853 6.760818 9.050366
[7] 6.713550 6.230175 6.930892 9.555534 NA 10.422124
[13] 6.855778 5.653668 11.843514 6.782915 9.718100 8.712946
[19] 7.756524 5.509616
> colMax(tmp5)
[1] 471.27548 82.11073 83.05377 81.20547 76.51472 81.41620 77.07882
[8] 73.88869 77.17555 93.59329 NA 87.88109 79.50787 75.33029
[15] 92.36129 85.34877 89.35701 83.78821 85.13484 78.76165
> colMin(tmp5)
[1] 57.22281 59.66445 64.82271 57.86848 56.60008 53.87421 57.19521 56.17517
[9] 55.18066 62.73567 NA 58.57600 60.45990 57.21286 54.83108 64.49411
[17] 58.23320 55.97546 63.61408 63.52240
>
> Max(tmp5,na.rm=TRUE)
[1] 471.2755
> Min(tmp5,na.rm=TRUE)
[1] 53.87421
> mean(tmp5,na.rm=TRUE)
[1] 72.40641
> Sum(tmp5,na.rm=TRUE)
[1] 14408.88
> Var(tmp5,na.rm=TRUE)
[1] 874.1483
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.22066 70.37455 74.43929 71.27535 67.76187 69.72782 72.77430 69.04107
[9] 70.40401 68.06360
> rowSums(tmp5,na.rm=TRUE)
[1] 1804.413 1407.491 1488.786 1425.507 1355.237 1394.556 1382.712 1380.821
[9] 1408.080 1361.272
> rowVars(tmp5,na.rm=TRUE)
[1] 8117.99077 93.58276 58.95671 57.32790 51.44434 59.59517
[7] 43.42721 78.55805 90.82747 49.63870
> rowSd(tmp5,na.rm=TRUE)
[1] 90.099893 9.673818 7.678327 7.571519 7.172471 7.719790 6.589932
[8] 8.863298 9.530345 7.045474
> rowMax(tmp5,na.rm=TRUE)
[1] 471.27548 89.35701 93.59329 84.02388 82.64486 87.88109 83.10348
[8] 85.34877 83.78821 81.41620
> rowMin(tmp5,na.rm=TRUE)
[1] 57.57417 53.87421 59.52797 57.73195 57.19521 57.86848 59.66445 56.17517
[9] 55.18066 57.21286
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.94716 73.80771 75.12792 69.10306 68.18164 70.82140 66.65223
[8] 64.23804 65.20662 75.25954 69.43521 71.26099 68.63721 67.65570
[15] 68.89310 73.72076 72.37156 68.99933 72.97316 70.53877
> colSums(tmp5,na.rm=TRUE)
[1] 1149.4716 738.0771 751.2792 691.0306 681.8164 708.2140 666.5223
[8] 642.3804 652.0662 752.5954 624.9169 712.6099 686.3721 676.5570
[15] 688.9310 737.2076 723.7156 689.9933 729.7316 705.3877
> colVars(tmp5,na.rm=TRUE)
[1] 15754.53576 56.87487 36.90551 52.03968 45.70866 81.90913
[7] 45.07176 38.81508 48.03727 91.30822 31.36776 108.62067
[13] 47.00169 31.96397 140.26883 46.00793 94.44146 75.91543
[19] 60.16367 30.35587
> colSd(tmp5,na.rm=TRUE)
[1] 125.517074 7.541543 6.074991 7.213853 6.760818 9.050366
[7] 6.713550 6.230175 6.930892 9.555534 5.600693 10.422124
[13] 6.855778 5.653668 11.843514 6.782915 9.718100 8.712946
[19] 7.756524 5.509616
> colMax(tmp5,na.rm=TRUE)
[1] 471.27548 82.11073 83.05377 81.20547 76.51472 81.41620 77.07882
[8] 73.88869 77.17555 93.59329 74.73717 87.88109 79.50787 75.33029
[15] 92.36129 85.34877 89.35701 83.78821 85.13484 78.76165
> colMin(tmp5,na.rm=TRUE)
[1] 57.22281 59.66445 64.82271 57.86848 56.60008 53.87421 57.19521 56.17517
[9] 55.18066 62.73567 58.07804 58.57600 60.45990 57.21286 54.83108 64.49411
[17] 58.23320 55.97546 63.61408 63.52240
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.22066 70.37455 74.43929 71.27535 67.76187 69.72782 NaN 69.04107
[9] 70.40401 68.06360
> rowSums(tmp5,na.rm=TRUE)
[1] 1804.413 1407.491 1488.786 1425.507 1355.237 1394.556 0.000 1380.821
[9] 1408.080 1361.272
> rowVars(tmp5,na.rm=TRUE)
[1] 8117.99077 93.58276 58.95671 57.32790 51.44434 59.59517
[7] NA 78.55805 90.82747 49.63870
> rowSd(tmp5,na.rm=TRUE)
[1] 90.099893 9.673818 7.678327 7.571519 7.172471 7.719790 NA
[8] 8.863298 9.530345 7.045474
> rowMax(tmp5,na.rm=TRUE)
[1] 471.27548 89.35701 93.59329 84.02388 82.64486 87.88109 NA
[8] 85.34877 83.78821 81.41620
> rowMin(tmp5,na.rm=TRUE)
[1] 57.57417 53.87421 59.52797 57.73195 57.19521 57.86848 NA 56.17517
[9] 55.18066 57.21286
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.67629 75.37918 74.85750 68.76652 67.25574 70.25258 65.99318
[8] 63.45155 65.16272 76.65108 NaN 69.94516 67.54791 67.19920
[15] 68.78121 74.74594 71.78708 67.79263 73.66895 70.00197
> colSums(tmp5,na.rm=TRUE)
[1] 1068.0866 678.4126 673.7175 618.8987 605.3017 632.2732 593.9386
[8] 571.0640 586.4645 689.8597 0.0000 629.5064 607.9311 604.7928
[15] 619.0309 672.7135 646.0837 610.1336 663.0206 630.0177
> colVars(tmp5,na.rm=TRUE)
[1] 17567.40585 36.20207 40.69601 57.27045 41.77777 88.50773
[7] 45.81925 36.70818 54.02025 80.93740 NA 102.71985
[13] 39.52780 33.61506 157.66159 39.93515 102.40341 69.02328
[19] 62.23767 30.90859
> colSd(tmp5,na.rm=TRUE)
[1] 132.542091 6.016815 6.379343 7.567724 6.463572 9.407855
[7] 6.768992 6.058728 7.349847 8.996522 NA 10.135080
[13] 6.287114 5.797849 12.556337 6.319427 10.119457 8.308025
[19] 7.889085 5.559550
> colMax(tmp5,na.rm=TRUE)
[1] 471.27548 82.11073 83.05377 81.20547 76.10743 81.41620 77.07882
[8] 73.88869 77.17555 93.59329 -Inf 87.88109 79.50787 75.33029
[15] 92.36129 85.34877 89.35701 83.78821 85.13484 78.76165
> colMin(tmp5,na.rm=TRUE)
[1] 57.22281 62.36740 64.82271 57.86848 56.60008 53.87421 57.19521 56.17517
[9] 55.18066 67.96980 Inf 58.57600 60.45990 57.21286 54.83108 65.69773
[17] 58.23320 55.97546 63.61408 63.52240
>
>
>
>
> 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] 135.0463 179.9530 130.5256 224.0260 178.5760 144.1456 239.8280 296.6731
[9] 257.0679 177.7563
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 135.0463 179.9530 130.5256 224.0260 178.5760 144.1456 239.8280 296.6731
[9] 257.0679 177.7563
>
>
>
> 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 -1.136868e-13 1.421085e-14 1.136868e-13 1.136868e-13
[6] -1.421085e-14 8.526513e-14 4.547474e-13 0.000000e+00 -5.684342e-14
[11] -8.526513e-14 -2.842171e-14 4.263256e-14 8.526513e-14 0.000000e+00
[16] -2.842171e-14 5.684342e-14 5.684342e-14 1.136868e-13 -1.136868e-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)
+ }
4 16
7 15
6 11
2 2
1 13
6 15
2 8
10 5
7 19
5 5
9 12
2 12
1 12
4 11
6 6
3 18
3 20
10 7
8 20
7 16
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] 2.862618
> Min(tmp)
[1] -3.94139
> mean(tmp)
[1] -0.04033901
> Sum(tmp)
[1] -4.033901
> Var(tmp)
[1] 1.130726
>
> rowMeans(tmp)
[1] -0.04033901
> rowSums(tmp)
[1] -4.033901
> rowVars(tmp)
[1] 1.130726
> rowSd(tmp)
[1] 1.063356
> rowMax(tmp)
[1] 2.862618
> rowMin(tmp)
[1] -3.94139
>
> colMeans(tmp)
[1] -0.787766280 -0.868233724 -0.213078491 0.779887999 0.273095763
[6] 1.211596458 1.143400621 -1.674721939 -1.542347853 -0.799440420
[11] 0.102058471 -1.892860666 0.444369535 -1.708280133 -0.105808154
[16] 1.341447150 0.495785448 0.936481917 0.640411884 -0.713431896
[21] 0.685099155 0.398061041 1.994649520 -1.134798602 -2.099151419
[26] 0.994593277 -2.087193358 0.467305340 0.481657578 -1.027124681
[31] 0.454969730 0.270255479 0.781589594 -0.394503311 1.097567038
[36] -1.011008782 0.149771191 0.046038892 0.324069310 -0.002166589
[41] 1.159212187 0.236827292 -0.120963134 1.547643394 0.154614504
[46] -0.798148191 1.022505660 -0.825144038 -0.558194182 -1.165990996
[51] -0.349390223 -1.196369919 0.178424473 0.756999893 -0.389002067
[56] 0.057314959 -3.941389788 -1.220418453 -0.025529917 0.190474565
[61] 0.162502246 2.091140550 0.165709621 -0.172415282 1.043941128
[66] 0.018006505 1.046285907 1.049894741 0.788443098 -1.229705298
[71] 0.853931366 -0.264158563 0.165116149 0.820918354 -0.036144083
[76] 0.679759513 -0.483927080 0.378372806 -0.190720380 0.745438937
[81] -0.074528938 -0.821681189 0.193962260 0.747557760 0.441213021
[86] -0.056072683 -0.697087112 -2.242189705 0.530045642 0.883500347
[91] -2.177845221 -1.075001245 2.049224597 2.862617531 -1.217757564
[96] -0.905246698 -0.440453163 -0.725033575 -0.912898273 -0.194338753
> colSums(tmp)
[1] -0.787766280 -0.868233724 -0.213078491 0.779887999 0.273095763
[6] 1.211596458 1.143400621 -1.674721939 -1.542347853 -0.799440420
[11] 0.102058471 -1.892860666 0.444369535 -1.708280133 -0.105808154
[16] 1.341447150 0.495785448 0.936481917 0.640411884 -0.713431896
[21] 0.685099155 0.398061041 1.994649520 -1.134798602 -2.099151419
[26] 0.994593277 -2.087193358 0.467305340 0.481657578 -1.027124681
[31] 0.454969730 0.270255479 0.781589594 -0.394503311 1.097567038
[36] -1.011008782 0.149771191 0.046038892 0.324069310 -0.002166589
[41] 1.159212187 0.236827292 -0.120963134 1.547643394 0.154614504
[46] -0.798148191 1.022505660 -0.825144038 -0.558194182 -1.165990996
[51] -0.349390223 -1.196369919 0.178424473 0.756999893 -0.389002067
[56] 0.057314959 -3.941389788 -1.220418453 -0.025529917 0.190474565
[61] 0.162502246 2.091140550 0.165709621 -0.172415282 1.043941128
[66] 0.018006505 1.046285907 1.049894741 0.788443098 -1.229705298
[71] 0.853931366 -0.264158563 0.165116149 0.820918354 -0.036144083
[76] 0.679759513 -0.483927080 0.378372806 -0.190720380 0.745438937
[81] -0.074528938 -0.821681189 0.193962260 0.747557760 0.441213021
[86] -0.056072683 -0.697087112 -2.242189705 0.530045642 0.883500347
[91] -2.177845221 -1.075001245 2.049224597 2.862617531 -1.217757564
[96] -0.905246698 -0.440453163 -0.725033575 -0.912898273 -0.194338753
> 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] -0.787766280 -0.868233724 -0.213078491 0.779887999 0.273095763
[6] 1.211596458 1.143400621 -1.674721939 -1.542347853 -0.799440420
[11] 0.102058471 -1.892860666 0.444369535 -1.708280133 -0.105808154
[16] 1.341447150 0.495785448 0.936481917 0.640411884 -0.713431896
[21] 0.685099155 0.398061041 1.994649520 -1.134798602 -2.099151419
[26] 0.994593277 -2.087193358 0.467305340 0.481657578 -1.027124681
[31] 0.454969730 0.270255479 0.781589594 -0.394503311 1.097567038
[36] -1.011008782 0.149771191 0.046038892 0.324069310 -0.002166589
[41] 1.159212187 0.236827292 -0.120963134 1.547643394 0.154614504
[46] -0.798148191 1.022505660 -0.825144038 -0.558194182 -1.165990996
[51] -0.349390223 -1.196369919 0.178424473 0.756999893 -0.389002067
[56] 0.057314959 -3.941389788 -1.220418453 -0.025529917 0.190474565
[61] 0.162502246 2.091140550 0.165709621 -0.172415282 1.043941128
[66] 0.018006505 1.046285907 1.049894741 0.788443098 -1.229705298
[71] 0.853931366 -0.264158563 0.165116149 0.820918354 -0.036144083
[76] 0.679759513 -0.483927080 0.378372806 -0.190720380 0.745438937
[81] -0.074528938 -0.821681189 0.193962260 0.747557760 0.441213021
[86] -0.056072683 -0.697087112 -2.242189705 0.530045642 0.883500347
[91] -2.177845221 -1.075001245 2.049224597 2.862617531 -1.217757564
[96] -0.905246698 -0.440453163 -0.725033575 -0.912898273 -0.194338753
> colMin(tmp)
[1] -0.787766280 -0.868233724 -0.213078491 0.779887999 0.273095763
[6] 1.211596458 1.143400621 -1.674721939 -1.542347853 -0.799440420
[11] 0.102058471 -1.892860666 0.444369535 -1.708280133 -0.105808154
[16] 1.341447150 0.495785448 0.936481917 0.640411884 -0.713431896
[21] 0.685099155 0.398061041 1.994649520 -1.134798602 -2.099151419
[26] 0.994593277 -2.087193358 0.467305340 0.481657578 -1.027124681
[31] 0.454969730 0.270255479 0.781589594 -0.394503311 1.097567038
[36] -1.011008782 0.149771191 0.046038892 0.324069310 -0.002166589
[41] 1.159212187 0.236827292 -0.120963134 1.547643394 0.154614504
[46] -0.798148191 1.022505660 -0.825144038 -0.558194182 -1.165990996
[51] -0.349390223 -1.196369919 0.178424473 0.756999893 -0.389002067
[56] 0.057314959 -3.941389788 -1.220418453 -0.025529917 0.190474565
[61] 0.162502246 2.091140550 0.165709621 -0.172415282 1.043941128
[66] 0.018006505 1.046285907 1.049894741 0.788443098 -1.229705298
[71] 0.853931366 -0.264158563 0.165116149 0.820918354 -0.036144083
[76] 0.679759513 -0.483927080 0.378372806 -0.190720380 0.745438937
[81] -0.074528938 -0.821681189 0.193962260 0.747557760 0.441213021
[86] -0.056072683 -0.697087112 -2.242189705 0.530045642 0.883500347
[91] -2.177845221 -1.075001245 2.049224597 2.862617531 -1.217757564
[96] -0.905246698 -0.440453163 -0.725033575 -0.912898273 -0.194338753
> colMedians(tmp)
[1] -0.787766280 -0.868233724 -0.213078491 0.779887999 0.273095763
[6] 1.211596458 1.143400621 -1.674721939 -1.542347853 -0.799440420
[11] 0.102058471 -1.892860666 0.444369535 -1.708280133 -0.105808154
[16] 1.341447150 0.495785448 0.936481917 0.640411884 -0.713431896
[21] 0.685099155 0.398061041 1.994649520 -1.134798602 -2.099151419
[26] 0.994593277 -2.087193358 0.467305340 0.481657578 -1.027124681
[31] 0.454969730 0.270255479 0.781589594 -0.394503311 1.097567038
[36] -1.011008782 0.149771191 0.046038892 0.324069310 -0.002166589
[41] 1.159212187 0.236827292 -0.120963134 1.547643394 0.154614504
[46] -0.798148191 1.022505660 -0.825144038 -0.558194182 -1.165990996
[51] -0.349390223 -1.196369919 0.178424473 0.756999893 -0.389002067
[56] 0.057314959 -3.941389788 -1.220418453 -0.025529917 0.190474565
[61] 0.162502246 2.091140550 0.165709621 -0.172415282 1.043941128
[66] 0.018006505 1.046285907 1.049894741 0.788443098 -1.229705298
[71] 0.853931366 -0.264158563 0.165116149 0.820918354 -0.036144083
[76] 0.679759513 -0.483927080 0.378372806 -0.190720380 0.745438937
[81] -0.074528938 -0.821681189 0.193962260 0.747557760 0.441213021
[86] -0.056072683 -0.697087112 -2.242189705 0.530045642 0.883500347
[91] -2.177845221 -1.075001245 2.049224597 2.862617531 -1.217757564
[96] -0.905246698 -0.440453163 -0.725033575 -0.912898273 -0.194338753
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.7877663 -0.8682337 -0.2130785 0.779888 0.2730958 1.211596 1.143401
[2,] -0.7877663 -0.8682337 -0.2130785 0.779888 0.2730958 1.211596 1.143401
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.674722 -1.542348 -0.7994404 0.1020585 -1.892861 0.4443695 -1.70828
[2,] -1.674722 -1.542348 -0.7994404 0.1020585 -1.892861 0.4443695 -1.70828
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.1058082 1.341447 0.4957854 0.9364819 0.6404119 -0.7134319 0.6850992
[2,] -0.1058082 1.341447 0.4957854 0.9364819 0.6404119 -0.7134319 0.6850992
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.398061 1.99465 -1.134799 -2.099151 0.9945933 -2.087193 0.4673053
[2,] 0.398061 1.99465 -1.134799 -2.099151 0.9945933 -2.087193 0.4673053
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.4816576 -1.027125 0.4549697 0.2702555 0.7815896 -0.3945033 1.097567
[2,] 0.4816576 -1.027125 0.4549697 0.2702555 0.7815896 -0.3945033 1.097567
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.011009 0.1497712 0.04603889 0.3240693 -0.002166589 1.159212 0.2368273
[2,] -1.011009 0.1497712 0.04603889 0.3240693 -0.002166589 1.159212 0.2368273
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1209631 1.547643 0.1546145 -0.7981482 1.022506 -0.825144 -0.5581942
[2,] -0.1209631 1.547643 0.1546145 -0.7981482 1.022506 -0.825144 -0.5581942
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.165991 -0.3493902 -1.19637 0.1784245 0.7569999 -0.3890021 0.05731496
[2,] -1.165991 -0.3493902 -1.19637 0.1784245 0.7569999 -0.3890021 0.05731496
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -3.94139 -1.220418 -0.02552992 0.1904746 0.1625022 2.091141 0.1657096
[2,] -3.94139 -1.220418 -0.02552992 0.1904746 0.1625022 2.091141 0.1657096
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.1724153 1.043941 0.0180065 1.046286 1.049895 0.7884431 -1.229705
[2,] -0.1724153 1.043941 0.0180065 1.046286 1.049895 0.7884431 -1.229705
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.8539314 -0.2641586 0.1651161 0.8209184 -0.03614408 0.6797595 -0.4839271
[2,] 0.8539314 -0.2641586 0.1651161 0.8209184 -0.03614408 0.6797595 -0.4839271
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.3783728 -0.1907204 0.7454389 -0.07452894 -0.8216812 0.1939623 0.7475578
[2,] 0.3783728 -0.1907204 0.7454389 -0.07452894 -0.8216812 0.1939623 0.7475578
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.441213 -0.05607268 -0.6970871 -2.24219 0.5300456 0.8835003 -2.177845
[2,] 0.441213 -0.05607268 -0.6970871 -2.24219 0.5300456 0.8835003 -2.177845
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.075001 2.049225 2.862618 -1.217758 -0.9052467 -0.4404532 -0.7250336
[2,] -1.075001 2.049225 2.862618 -1.217758 -0.9052467 -0.4404532 -0.7250336
[,99] [,100]
[1,] -0.9128983 -0.1943388
[2,] -0.9128983 -0.1943388
>
>
> Max(tmp2)
[1] 2.457199
> Min(tmp2)
[1] -2.185569
> mean(tmp2)
[1] -0.00465884
> Sum(tmp2)
[1] -0.465884
> Var(tmp2)
[1] 0.8424019
>
> rowMeans(tmp2)
[1] 0.098785800 -1.242884152 -0.815781075 0.851737132 -0.993357329
[6] 0.554611360 -1.168331570 -0.400010879 -0.067547093 0.573923282
[11] 0.074820913 1.297350411 0.733110220 0.122388269 -0.574031233
[16] -0.134416659 0.029158221 1.034860778 -0.618958581 -1.790900254
[21] 0.754708561 1.136437610 0.498095611 0.232113424 -0.375811630
[26] 0.184095826 0.871565084 -1.488253122 -0.654226987 -0.593119936
[31] -1.843936250 0.379395721 -0.401435071 0.856349444 0.041266471
[36] 2.457198617 -0.539942673 -1.302037321 -0.376476383 0.763578592
[41] 0.345915741 0.418220093 -0.473606154 0.519847522 -1.762652012
[46] -0.008378577 -0.119758539 -0.152320784 0.184041351 0.368802786
[51] -1.425085422 0.297281638 -2.185568580 -0.773330744 0.851177602
[56] 2.214803786 -0.273373432 0.625927166 -1.123410929 0.032885748
[61] -0.152604299 0.497548272 0.530070652 1.056855881 -0.998736294
[66] -0.336329024 -0.069884898 1.134850032 -0.569639991 -0.004296353
[71] -0.371976458 0.877279821 -1.246018081 -1.285156702 0.408245134
[76] 1.765122904 0.640530392 0.042733068 1.396295941 -0.989263459
[81] -0.664241743 0.816859125 -1.618377976 -0.381561687 1.253420029
[86] -0.373673337 0.426069297 -0.544169239 0.913962591 -1.918202687
[91] 1.633137164 -0.158471156 0.230646708 0.701326837 0.448141248
[96] -0.694538951 0.079191430 0.154811654 -0.264405385 1.443054146
> rowSums(tmp2)
[1] 0.098785800 -1.242884152 -0.815781075 0.851737132 -0.993357329
[6] 0.554611360 -1.168331570 -0.400010879 -0.067547093 0.573923282
[11] 0.074820913 1.297350411 0.733110220 0.122388269 -0.574031233
[16] -0.134416659 0.029158221 1.034860778 -0.618958581 -1.790900254
[21] 0.754708561 1.136437610 0.498095611 0.232113424 -0.375811630
[26] 0.184095826 0.871565084 -1.488253122 -0.654226987 -0.593119936
[31] -1.843936250 0.379395721 -0.401435071 0.856349444 0.041266471
[36] 2.457198617 -0.539942673 -1.302037321 -0.376476383 0.763578592
[41] 0.345915741 0.418220093 -0.473606154 0.519847522 -1.762652012
[46] -0.008378577 -0.119758539 -0.152320784 0.184041351 0.368802786
[51] -1.425085422 0.297281638 -2.185568580 -0.773330744 0.851177602
[56] 2.214803786 -0.273373432 0.625927166 -1.123410929 0.032885748
[61] -0.152604299 0.497548272 0.530070652 1.056855881 -0.998736294
[66] -0.336329024 -0.069884898 1.134850032 -0.569639991 -0.004296353
[71] -0.371976458 0.877279821 -1.246018081 -1.285156702 0.408245134
[76] 1.765122904 0.640530392 0.042733068 1.396295941 -0.989263459
[81] -0.664241743 0.816859125 -1.618377976 -0.381561687 1.253420029
[86] -0.373673337 0.426069297 -0.544169239 0.913962591 -1.918202687
[91] 1.633137164 -0.158471156 0.230646708 0.701326837 0.448141248
[96] -0.694538951 0.079191430 0.154811654 -0.264405385 1.443054146
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.098785800 -1.242884152 -0.815781075 0.851737132 -0.993357329
[6] 0.554611360 -1.168331570 -0.400010879 -0.067547093 0.573923282
[11] 0.074820913 1.297350411 0.733110220 0.122388269 -0.574031233
[16] -0.134416659 0.029158221 1.034860778 -0.618958581 -1.790900254
[21] 0.754708561 1.136437610 0.498095611 0.232113424 -0.375811630
[26] 0.184095826 0.871565084 -1.488253122 -0.654226987 -0.593119936
[31] -1.843936250 0.379395721 -0.401435071 0.856349444 0.041266471
[36] 2.457198617 -0.539942673 -1.302037321 -0.376476383 0.763578592
[41] 0.345915741 0.418220093 -0.473606154 0.519847522 -1.762652012
[46] -0.008378577 -0.119758539 -0.152320784 0.184041351 0.368802786
[51] -1.425085422 0.297281638 -2.185568580 -0.773330744 0.851177602
[56] 2.214803786 -0.273373432 0.625927166 -1.123410929 0.032885748
[61] -0.152604299 0.497548272 0.530070652 1.056855881 -0.998736294
[66] -0.336329024 -0.069884898 1.134850032 -0.569639991 -0.004296353
[71] -0.371976458 0.877279821 -1.246018081 -1.285156702 0.408245134
[76] 1.765122904 0.640530392 0.042733068 1.396295941 -0.989263459
[81] -0.664241743 0.816859125 -1.618377976 -0.381561687 1.253420029
[86] -0.373673337 0.426069297 -0.544169239 0.913962591 -1.918202687
[91] 1.633137164 -0.158471156 0.230646708 0.701326837 0.448141248
[96] -0.694538951 0.079191430 0.154811654 -0.264405385 1.443054146
> rowMin(tmp2)
[1] 0.098785800 -1.242884152 -0.815781075 0.851737132 -0.993357329
[6] 0.554611360 -1.168331570 -0.400010879 -0.067547093 0.573923282
[11] 0.074820913 1.297350411 0.733110220 0.122388269 -0.574031233
[16] -0.134416659 0.029158221 1.034860778 -0.618958581 -1.790900254
[21] 0.754708561 1.136437610 0.498095611 0.232113424 -0.375811630
[26] 0.184095826 0.871565084 -1.488253122 -0.654226987 -0.593119936
[31] -1.843936250 0.379395721 -0.401435071 0.856349444 0.041266471
[36] 2.457198617 -0.539942673 -1.302037321 -0.376476383 0.763578592
[41] 0.345915741 0.418220093 -0.473606154 0.519847522 -1.762652012
[46] -0.008378577 -0.119758539 -0.152320784 0.184041351 0.368802786
[51] -1.425085422 0.297281638 -2.185568580 -0.773330744 0.851177602
[56] 2.214803786 -0.273373432 0.625927166 -1.123410929 0.032885748
[61] -0.152604299 0.497548272 0.530070652 1.056855881 -0.998736294
[66] -0.336329024 -0.069884898 1.134850032 -0.569639991 -0.004296353
[71] -0.371976458 0.877279821 -1.246018081 -1.285156702 0.408245134
[76] 1.765122904 0.640530392 0.042733068 1.396295941 -0.989263459
[81] -0.664241743 0.816859125 -1.618377976 -0.381561687 1.253420029
[86] -0.373673337 0.426069297 -0.544169239 0.913962591 -1.918202687
[91] 1.633137164 -0.158471156 0.230646708 0.701326837 0.448141248
[96] -0.694538951 0.079191430 0.154811654 -0.264405385 1.443054146
>
> colMeans(tmp2)
[1] -0.00465884
> colSums(tmp2)
[1] -0.465884
> colVars(tmp2)
[1] 0.8424019
> colSd(tmp2)
[1] 0.9178245
> colMax(tmp2)
[1] 2.457199
> colMin(tmp2)
[1] -2.185569
> colMedians(tmp2)
[1] 0.03707611
> colRanges(tmp2)
[,1]
[1,] -2.185569
[2,] 2.457199
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.597585059 1.196140464 1.007433324 0.007622189 -1.705565112
[6] 0.719259565 -0.713667514 -0.247616667 2.127810718 4.728901882
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1898083
[2,] -0.5314657
[3,] 0.2053773
[4,] 0.6249561
[5,] 1.1241454
>
> rowApply(tmp,sum)
[1] 1.0680533 1.7883115 -1.8880943 1.7332578 1.5080004 -0.3869562
[7] -0.8191627 1.4778056 5.6300753 -2.3933868
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 1 2 10 6 4 2 9 3 9
[2,] 5 5 1 2 10 8 9 3 8 1
[3,] 10 8 8 9 4 3 1 5 1 6
[4,] 6 3 6 5 7 1 6 10 9 2
[5,] 9 9 5 1 1 2 4 7 6 5
[6,] 3 6 4 7 3 9 8 2 7 10
[7,] 1 4 10 6 2 5 5 8 5 7
[8,] 2 2 3 8 9 10 3 4 4 3
[9,] 4 7 9 4 5 7 10 1 2 8
[10,] 7 10 7 3 8 6 7 6 10 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.7977742 1.4650257 -1.9667982 -1.0263337 -0.6540334 0.2713377
[7] 0.8773971 -1.4586104 -2.2130795 -1.5238627 -2.1195120 1.1155479
[13] 0.2191795 -5.0497790 -2.7061812 2.0169058 0.8678767 3.7416581
[19] 2.6005983 3.0035020
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0448163
[2,] 0.2791478
[3,] 1.4739935
[4,] 1.5320668
[5,] 2.5573824
>
> rowApply(tmp,sum)
[1] -6.0056618 2.9353623 1.5556330 0.2253373 3.5479421
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 3 18 20 10
[2,] 18 19 11 4 8
[3,] 5 17 5 6 1
[4,] 9 8 7 11 13
[5,] 8 7 14 9 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.4739935 0.8358701 -1.0150249 -0.52254194 -0.54631284 0.66483011
[2,] -1.0448163 1.7186511 1.4001898 -0.36487155 -0.48070498 1.04643281
[3,] 2.5573824 -0.1129294 -0.7928673 -0.64860684 0.35751703 -1.91200509
[4,] 1.5320668 -1.0904166 -0.4208037 0.09172901 -0.07597197 0.07739746
[5,] 0.2791478 0.1138505 -1.1382921 0.41795760 0.09143933 0.39468246
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.7459835 -1.6343991 0.39530963 -1.2582087 -0.8295643 0.02956479
[2,] -0.9424781 -0.2587379 0.05788793 -2.0106057 -0.8477263 -1.14061793
[3,] 2.7673993 1.5513913 -0.49410972 2.7801282 -0.3870963 0.21956961
[4,] 0.7329290 -0.1853453 -1.51325361 -1.5554718 -0.2269822 1.35825524
[5,] -0.9344696 -0.9315194 -0.65891378 0.5202953 0.1718572 0.64877615
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.9521318 -2.1320582 -1.90591215 0.4746948 -0.3954225 0.14457123
[2,] 0.1390747 -0.5430004 0.72944468 1.4898914 0.8172331 0.03614657
[3,] -1.1142153 -0.7002641 -2.46213573 -1.0456979 0.5397248 0.98171469
[4,] -1.0753527 -1.9550970 1.01494807 0.1485708 0.2511766 1.45576625
[5,] 1.3175410 0.2806407 -0.08252606 0.9494467 -0.3448354 1.12345932
[,19] [,20]
[1,] 0.3805461 -0.37174574
[2,] 1.2720419 1.86192732
[3,] -0.5696643 0.04039756
[4,] 0.8617332 0.79945979
[5,] 0.6559414 0.67346309
>
>
> 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 : 566 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 0.9719025 0.0632308 1.324591 -0.1578766 -1.949729 0.6438043 -0.3439778
col8 col9 col10 col11 col12 col13 col14
row1 -0.09640689 -1.083152 1.863609 0.09938996 -1.804573 -1.370138 -0.5490326
col15 col16 col17 col18 col19 col20
row1 1.565328 -0.6979065 0.2913738 -0.611923 -1.209247 -0.7847246
> tmp[,"col10"]
col10
row1 1.8636093
row2 0.5240958
row3 0.7525710
row4 -0.8249878
row5 0.1911781
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.9719025 0.0632308 1.3245910 -0.1578766 -1.949729 0.6438043 -0.3439778
row5 1.0318480 -0.2066841 0.6702444 -0.1027227 -2.054403 -0.4632342 0.5117844
col8 col9 col10 col11 col12 col13
row1 -0.09640689 -1.0831521 1.8636093 0.09938996 -1.8045728 -1.3701384
row5 1.26909589 0.9262231 0.1911781 0.44248640 -0.7164177 -0.5430071
col14 col15 col16 col17 col18 col19 col20
row1 -0.5490326 1.565328 -0.6979065 0.2913738 -0.6119230 -1.2092470 -0.7847246
row5 -1.2066206 1.704847 0.4613120 0.2763964 0.3492323 -0.5732973 -0.2288127
> tmp[,c("col6","col20")]
col6 col20
row1 0.6438043 -0.7847246
row2 -0.1381716 0.5360492
row3 -0.2649739 -0.7911241
row4 0.1692289 0.3213366
row5 -0.4632342 -0.2288127
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.6438043 -0.7847246
row5 -0.4632342 -0.2288127
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.17252 51.64708 50.66311 47.95744 50.11753 104.1748 49.96099 51.48895
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.32117 50.41119 50.25178 50.70563 50.16551 49.17542 48.16497 48.51623
col17 col18 col19 col20
row1 49.72488 47.99107 50.29362 104.842
> tmp[,"col10"]
col10
row1 50.41119
row2 30.04202
row3 30.53966
row4 30.26954
row5 50.41512
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.17252 51.64708 50.66311 47.95744 50.11753 104.1748 49.96099 51.48895
row5 51.52223 50.81291 48.97237 50.18632 49.82654 105.4428 51.85806 49.68609
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.32117 50.41119 50.25178 50.70563 50.16551 49.17542 48.16497 48.51623
row5 51.99982 50.41512 49.66249 50.00092 48.70094 47.82308 51.10365 49.52626
col17 col18 col19 col20
row1 49.72488 47.99107 50.29362 104.8420
row5 50.71765 49.07341 48.74668 105.1487
> tmp[,c("col6","col20")]
col6 col20
row1 104.17478 104.84196
row2 75.65713 74.42522
row3 76.29459 74.32677
row4 75.13107 75.72833
row5 105.44280 105.14873
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.1748 104.8420
row5 105.4428 105.1487
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.1748 104.8420
row5 105.4428 105.1487
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4306855
[2,] -0.1440514
[3,] 0.1699743
[4,] 0.7599805
[5,] 0.8065542
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.2563185 1.3849295
[2,] -0.1856889 0.2654225
[3,] 0.2723753 -0.8790412
[4,] -0.6072931 0.1226013
[5,] 0.4104294 0.6649531
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.2337163 1.9101160
[2,] 1.5053672 -0.6635884
[3,] -0.1702017 -0.2724343
[4,] 1.0608913 -0.2603600
[5,] -0.8418139 -0.9476502
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2337163
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2337163
[2,] 1.5053672
>
>
>
> 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 0.4069645 -0.4275089 -1.9064556 0.07991955 -0.2582093 1.0989948
row1 -1.4905757 -0.1819682 -0.8235508 -0.84047688 0.4737451 0.6119143
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.7180908 -2.411903 0.3201465 -1.5354220 -0.1593146 0.2653098 -0.5455379
row1 0.6180720 1.787947 0.6677188 -0.1271525 0.3283343 -1.6395730 0.2637451
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.7875344 1.441425 -0.1888805 0.1175856 -0.6951494 -0.5965217 -1.0119073
row1 1.4301090 1.206891 2.1843880 0.8478790 1.4372401 0.2472052 0.3764409
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.1184646 0.7813291 0.9682624 0.0273609 0.1724191 0.8825997 -0.9445164
[,8] [,9] [,10]
row2 0.2263951 0.4716522 1.095639
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1804522 0.3920143 -0.8059868 -1.085305 0.5164818 1.740842 0.3027046
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5712941 -0.7194377 0.09022404 -0.2975401 -0.655214 0.8006945 0.1909864
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.263202 0.0558472 -0.1688797 -0.1103592 -0.3339955 1.456251
>
>
> 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: 0x6015c8cbd710>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f716a9ca5d"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f76fd4b047"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f767329397"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f77c1c818"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f7803f6ae"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f758fcc47a"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f74b859508"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f759609eb3"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f76865482a"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f717ca50ce"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f7d71789"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f71c7882d3"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f761389e62"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f74aa9a8b3"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a77f77e37a5ed"
>
>
> ### 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: 0x6015cbdbe780>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6015cbdbe780>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6015cbdbe780>
> rowMedians(tmp)
[1] -0.071622614 -0.043065572 -0.148301606 -0.066777574 0.259876189
[6] 0.044252514 -0.335819000 0.341300580 -0.289271120 -0.202703950
[11] -0.423952566 -0.140524320 0.354636771 0.176974172 0.332191089
[16] -0.100321900 -0.052403286 0.227727788 -0.038469528 -0.191723153
[21] 0.357264142 0.172431746 -0.538488588 0.134408941 0.179539204
[26] -0.174516312 0.141818780 0.357189444 -0.041987265 0.138017649
[31] 0.033494791 0.202743204 0.653423902 -0.175029587 -0.263444914
[36] -0.079144829 -0.043880977 0.058938707 0.165503479 0.262487058
[41] 0.286282450 0.293227239 0.083203212 0.008337438 0.098715476
[46] -0.365602057 -0.076858282 0.520197512 0.181634390 -0.141452126
[51] -0.002631016 0.236907255 -0.253447011 -0.120866562 -0.191274272
[56] 0.231168228 -0.236505255 0.303535393 -0.042245197 0.780039242
[61] 0.640448180 -0.125764194 -0.277430873 -0.078119906 -0.374032986
[66] -0.460679283 0.694239217 0.061512740 0.175758097 -0.291480141
[71] 0.047856841 0.215095919 -0.058976500 -0.226360063 -0.455735783
[76] 0.145767659 -0.508841771 -0.164632020 0.347355839 0.159731095
[81] 0.105753692 0.143127186 -0.021492647 -0.337299166 -0.051286348
[86] 0.082986281 -0.208543108 0.391953383 0.070504752 0.117073255
[91] 0.097872433 0.453205291 -0.089207405 -0.279050017 0.136190231
[96] 0.207030430 0.384070029 -0.568988501 0.451751047 -0.117920850
[101] 0.091826991 0.257786512 0.408636420 -0.558525061 0.014941017
[106] -0.313812951 -0.227358836 -0.232840220 -0.609274275 0.084274500
[111] 0.517078267 -0.145116875 -0.313214519 0.320167180 -0.263034138
[116] -0.240296071 -0.071441913 -0.193717779 -0.529568907 -0.306741395
[121] 0.163377736 -0.733925282 0.344360403 0.344943477 0.221132679
[126] 0.149589069 0.467402392 -0.249082073 0.039200768 -0.286503250
[131] -0.184178698 0.142844409 0.620015897 -0.028822650 0.536021645
[136] -0.100404877 0.124519395 -0.810820991 -0.457985189 0.550219978
[141] 0.255002335 -0.432869763 0.153717723 0.375105725 -0.519449460
[146] -0.358353350 0.021817102 0.666605026 0.696258450 -0.278056926
[151] 0.281231229 0.545199801 -0.384364030 -0.144193184 0.087556039
[156] -0.482742735 0.167112249 -0.525419168 -0.029584640 0.437320608
[161] 0.180908778 0.051665308 -0.093580974 0.034399477 0.257378674
[166] -0.333541304 0.104058134 -0.062631976 -0.360054351 -0.090100716
[171] 0.312623733 -0.144108038 0.203067526 0.221691020 0.359871080
[176] 0.890723306 -0.571416416 -0.147906032 0.273084304 0.146285865
[181] -0.188894379 0.157981721 0.306226946 -0.272698793 0.365064514
[186] 0.100873487 -0.348870438 0.057852555 0.042946114 0.295075434
[191] -0.146651266 -0.432713447 0.227316877 -0.234551374 -0.067504921
[196] -0.182872518 0.074546079 -0.942356062 -0.203947269 0.216700716
[201] 0.286172545 0.228007857 -0.488497804 -0.286781692 -0.333490317
[206] -0.341103845 0.456989611 -0.024454199 0.506935001 0.039718308
[211] -0.183254824 -0.233175773 0.059786735 0.012853133 -0.048515158
[216] -0.012930641 0.235214097 0.233441458 0.107747216 0.125765554
[221] 0.120922174 0.031509106 0.111594246 -0.334539589 0.390776905
[226] 0.568531035 -0.044822118 -0.206691038 -0.199047502 0.198298379
>
> proc.time()
user system elapsed
1.419 1.456 2.860
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: 0x591e1b13cc10>
> .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: 0x591e1b13cc10>
> .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: 0x591e1b13cc10>
> .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: 0x591e1b13cc10>
> 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: 0x591e1bdff2d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1bdff2d0>
> .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: 0x591e1bdff2d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1bdff2d0>
> .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: 0x591e1bdff2d0>
> 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: 0x591e1c4d4d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1c4d4d70>
> .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: 0x591e1c4d4d70>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x591e1c4d4d70>
> .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: 0x591e1c4d4d70>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x591e1c4d4d70>
> .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: 0x591e1c4d4d70>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x591e1c4d4d70>
> .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: 0x591e1c4d4d70>
> 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: 0x591e1c048370>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x591e1c048370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1c048370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1c048370>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a78c01e9c68f5" "BufferedMatrixFile3a78c0d7d0378"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a78c01e9c68f5" "BufferedMatrixFile3a78c0d7d0378"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1bf93ff0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1bf93ff0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x591e1bf93ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x591e1bf93ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x591e1bf93ff0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x591e1bf93ff0>
> .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: 0x591e1c16c5b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x591e1c16c5b0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x591e1c16c5b0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x591e1c16c5b0>
> 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: 0x591e1d149500>
> .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: 0x591e1d149500>
> rm(P)
>
> proc.time()
user system elapsed
0.266 0.053 0.307
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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Type 'license()' or 'licence()' for distribution details.
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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
0.241 0.051 0.278