Ben Bolstad
| Snapshot Date: 2026-02-04 13:40 -0500 (Wed, 04 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 2026-02-05 11:32 -0500 (Thu, 05 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" | 4852 |
| 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 | | ||||||||
| 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: 2026-02-04 21:43:08 -0500 (Wed, 04 Feb 2026) |
| EndedAt: 2026-02-04 21:43:33 -0500 (Wed, 04 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
0.237 0.058 0.282
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] "Wed Feb 4 21:43:23 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Feb 4 21:43:23 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: 0x5b3ef9b01c10>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Feb 4 21:43:24 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Feb 4 21:43:24 2026"
>
> ColMode(tmp2)
<pointer: 0x5b3ef9b01c10>
>
>
>
> ### 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,] 100.1016318 0.1155236 0.9510660 1.3852732
[2,] -0.2560048 0.7132336 -0.3180515 0.3391389
[3,] -0.4645860 1.7493484 -0.2027227 -0.7736820
[4,] 1.9477943 -0.4440624 -0.9911463 0.2808703
> 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,] 100.1016318 0.1155236 0.9510660 1.3852732
[2,] 0.2560048 0.7132336 0.3180515 0.3391389
[3,] 0.4645860 1.7493484 0.2027227 0.7736820
[4,] 1.9477943 0.4440624 0.9911463 0.2808703
> 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,] 10.0050803 0.3398876 0.9752261 1.1769763
[2,] 0.5059692 0.8445316 0.5639606 0.5823563
[3,] 0.6816055 1.3226294 0.4502473 0.8795919
[4,] 1.3956340 0.6663801 0.9955633 0.5299720
>
> 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,] 225.15243 28.51440 35.70333 38.15504
[2,] 30.31570 34.15855 30.95766 31.16270
[3,] 32.28064 39.97564 29.70520 34.56960
[4,] 40.90413 32.10786 35.94678 30.58059
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5b3efa958ff0>
> exp(tmp5)
<pointer: 0x5b3efa958ff0>
> log(tmp5,2)
<pointer: 0x5b3efa958ff0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.6253
> Min(tmp5)
[1] 53.85927
> mean(tmp5)
[1] 72.7656
> Sum(tmp5)
[1] 14553.12
> Var(tmp5)
[1] 859.1928
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.56313 71.45422 70.12345 71.75490 71.22059 70.26074 72.01527 70.97183
[9] 69.88014 69.41175
> rowSums(tmp5)
[1] 1811.263 1429.084 1402.469 1435.098 1424.412 1405.215 1440.305 1419.437
[9] 1397.603 1388.235
> rowVars(tmp5)
[1] 8007.67528 78.02522 64.74047 63.74678 59.48149 47.23254
[7] 73.57062 52.86803 109.04495 65.17002
> rowSd(tmp5)
[1] 89.485615 8.833188 8.046146 7.984158 7.712424 6.872594 8.577332
[8] 7.271041 10.442459 8.072795
> rowMax(tmp5)
[1] 468.62529 86.20468 83.20406 85.13660 88.26814 81.65907 86.28033
[8] 89.64214 87.77676 85.04639
> rowMin(tmp5)
[1] 54.17818 55.71191 54.71047 54.38663 56.97795 59.63208 54.20157 59.49617
[9] 53.85927 53.88176
>
> colMeans(tmp5)
[1] 114.18390 69.08618 71.21574 68.99682 72.74874 70.99999 68.12894
[8] 74.20246 69.92830 74.17144 69.06818 68.58956 71.31207 68.16577
[15] 72.01111 69.06654 73.94786 68.50389 67.23180 73.75276
> colSums(tmp5)
[1] 1141.8390 690.8618 712.1574 689.9682 727.4874 709.9999 681.2894
[8] 742.0246 699.2830 741.7144 690.6818 685.8956 713.1207 681.6577
[15] 720.1111 690.6654 739.4786 685.0389 672.3180 737.5276
> colVars(tmp5)
[1] 15582.04532 56.37864 81.78820 34.70462 44.71497 69.38044
[7] 57.61444 78.91369 93.53615 65.07886 98.45321 66.19739
[13] 110.63770 81.60085 66.45040 43.75394 33.83904 64.82882
[19] 50.28091 104.04479
> colSd(tmp5)
[1] 124.828063 7.508571 9.043683 5.891063 6.686926 8.329492
[7] 7.590418 8.883338 9.671409 8.067147 9.922359 8.136178
[13] 10.518446 9.033319 8.151711 6.614676 5.817133 8.051635
[19] 7.090903 10.200235
> colMax(tmp5)
[1] 468.62529 83.20406 86.28033 79.41471 86.54628 85.84323 77.28337
[8] 89.58170 82.97380 84.66895 88.26814 82.55479 86.20468 79.48115
[15] 84.82125 80.58566 81.33057 77.21775 76.67179 89.64214
> colMin(tmp5)
[1] 63.09815 59.34899 59.49617 63.50780 63.33844 60.01807 57.17553 62.68974
[9] 53.88176 64.02140 54.17818 56.42992 53.85927 54.38663 60.64464 59.63076
[17] 61.05397 54.20157 54.71047 58.89031
>
>
> ### 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] 90.56313 71.45422 70.12345 NA 71.22059 70.26074 72.01527 70.97183
[9] 69.88014 69.41175
> rowSums(tmp5)
[1] 1811.263 1429.084 1402.469 NA 1424.412 1405.215 1440.305 1419.437
[9] 1397.603 1388.235
> rowVars(tmp5)
[1] 8007.67528 78.02522 64.74047 60.67032 59.48149 47.23254
[7] 73.57062 52.86803 109.04495 65.17002
> rowSd(tmp5)
[1] 89.485615 8.833188 8.046146 7.789115 7.712424 6.872594 8.577332
[8] 7.271041 10.442459 8.072795
> rowMax(tmp5)
[1] 468.62529 86.20468 83.20406 NA 88.26814 81.65907 86.28033
[8] 89.64214 87.77676 85.04639
> rowMin(tmp5)
[1] 54.17818 55.71191 54.71047 NA 56.97795 59.63208 54.20157 59.49617
[9] 53.85927 53.88176
>
> colMeans(tmp5)
[1] 114.18390 69.08618 71.21574 68.99682 72.74874 70.99999 68.12894
[8] 74.20246 69.92830 74.17144 69.06818 68.58956 NA 68.16577
[15] 72.01111 69.06654 73.94786 68.50389 67.23180 73.75276
> colSums(tmp5)
[1] 1141.8390 690.8618 712.1574 689.9682 727.4874 709.9999 681.2894
[8] 742.0246 699.2830 741.7144 690.6818 685.8956 NA 681.6577
[15] 720.1111 690.6654 739.4786 685.0389 672.3180 737.5276
> colVars(tmp5)
[1] 15582.04532 56.37864 81.78820 34.70462 44.71497 69.38044
[7] 57.61444 78.91369 93.53615 65.07886 98.45321 66.19739
[13] NA 81.60085 66.45040 43.75394 33.83904 64.82882
[19] 50.28091 104.04479
> colSd(tmp5)
[1] 124.828063 7.508571 9.043683 5.891063 6.686926 8.329492
[7] 7.590418 8.883338 9.671409 8.067147 9.922359 8.136178
[13] NA 9.033319 8.151711 6.614676 5.817133 8.051635
[19] 7.090903 10.200235
> colMax(tmp5)
[1] 468.62529 83.20406 86.28033 79.41471 86.54628 85.84323 77.28337
[8] 89.58170 82.97380 84.66895 88.26814 82.55479 NA 79.48115
[15] 84.82125 80.58566 81.33057 77.21775 76.67179 89.64214
> colMin(tmp5)
[1] 63.09815 59.34899 59.49617 63.50780 63.33844 60.01807 57.17553 62.68974
[9] 53.88176 64.02140 54.17818 56.42992 NA 54.38663 60.64464 59.63076
[17] 61.05397 54.20157 54.71047 58.89031
>
> Max(tmp5,na.rm=TRUE)
[1] 468.6253
> Min(tmp5,na.rm=TRUE)
[1] 53.85927
> mean(tmp5,na.rm=TRUE)
[1] 72.71722
> Sum(tmp5,na.rm=TRUE)
[1] 14470.73
> Var(tmp5,na.rm=TRUE)
[1] 863.0617
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.56313 71.45422 70.12345 71.19501 71.22059 70.26074 72.01527 70.97183
[9] 69.88014 69.41175
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.263 1429.084 1402.469 1352.705 1424.412 1405.215 1440.305 1419.437
[9] 1397.603 1388.235
> rowVars(tmp5,na.rm=TRUE)
[1] 8007.67528 78.02522 64.74047 60.67032 59.48149 47.23254
[7] 73.57062 52.86803 109.04495 65.17002
> rowSd(tmp5,na.rm=TRUE)
[1] 89.485615 8.833188 8.046146 7.789115 7.712424 6.872594 8.577332
[8] 7.271041 10.442459 8.072795
> rowMax(tmp5,na.rm=TRUE)
[1] 468.62529 86.20468 83.20406 85.13660 88.26814 81.65907 86.28033
[8] 89.64214 87.77676 85.04639
> rowMin(tmp5,na.rm=TRUE)
[1] 54.17818 55.71191 54.71047 54.38663 56.97795 59.63208 54.20157 59.49617
[9] 53.85927 53.88176
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.18390 69.08618 71.21574 68.99682 72.74874 70.99999 68.12894
[8] 74.20246 69.92830 74.17144 69.06818 68.58956 70.08086 68.16577
[15] 72.01111 69.06654 73.94786 68.50389 67.23180 73.75276
> colSums(tmp5,na.rm=TRUE)
[1] 1141.8390 690.8618 712.1574 689.9682 727.4874 709.9999 681.2894
[8] 742.0246 699.2830 741.7144 690.6818 685.8956 630.7278 681.6577
[15] 720.1111 690.6654 739.4786 685.0389 672.3180 737.5276
> colVars(tmp5,na.rm=TRUE)
[1] 15582.04532 56.37864 81.78820 34.70462 44.71497 69.38044
[7] 57.61444 78.91369 93.53615 65.07886 98.45321 66.19739
[13] 107.41396 81.60085 66.45040 43.75394 33.83904 64.82882
[19] 50.28091 104.04479
> colSd(tmp5,na.rm=TRUE)
[1] 124.828063 7.508571 9.043683 5.891063 6.686926 8.329492
[7] 7.590418 8.883338 9.671409 8.067147 9.922359 8.136178
[13] 10.364071 9.033319 8.151711 6.614676 5.817133 8.051635
[19] 7.090903 10.200235
> colMax(tmp5,na.rm=TRUE)
[1] 468.62529 83.20406 86.28033 79.41471 86.54628 85.84323 77.28337
[8] 89.58170 82.97380 84.66895 88.26814 82.55479 86.20468 79.48115
[15] 84.82125 80.58566 81.33057 77.21775 76.67179 89.64214
> colMin(tmp5,na.rm=TRUE)
[1] 63.09815 59.34899 59.49617 63.50780 63.33844 60.01807 57.17553 62.68974
[9] 53.88176 64.02140 54.17818 56.42992 53.85927 54.38663 60.64464 59.63076
[17] 61.05397 54.20157 54.71047 58.89031
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.56313 71.45422 70.12345 NaN 71.22059 70.26074 72.01527 70.97183
[9] 69.88014 69.41175
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.263 1429.084 1402.469 0.000 1424.412 1405.215 1440.305 1419.437
[9] 1397.603 1388.235
> rowVars(tmp5,na.rm=TRUE)
[1] 8007.67528 78.02522 64.74047 NA 59.48149 47.23254
[7] 73.57062 52.86803 109.04495 65.17002
> rowSd(tmp5,na.rm=TRUE)
[1] 89.485615 8.833188 8.046146 NA 7.712424 6.872594 8.577332
[8] 7.271041 10.442459 8.072795
> rowMax(tmp5,na.rm=TRUE)
[1] 468.62529 86.20468 83.20406 NA 88.26814 81.65907 86.28033
[8] 89.64214 87.77676 85.04639
> rowMin(tmp5,na.rm=TRUE)
[1] 54.17818 55.71191 54.71047 NA 56.97795 59.63208 54.20157 59.49617
[9] 53.85927 53.88176
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.41138 69.33705 70.81544 69.59097 73.02504 72.09774 67.30195
[8] 73.75409 69.37742 73.02631 69.84688 68.92163 NaN 69.69678
[15] 71.93673 68.95519 74.28674 68.30123 66.39930 73.39533
> colSums(tmp5,na.rm=TRUE)
[1] 1056.7024 624.0335 637.3389 626.3187 657.2253 648.8797 605.7176
[8] 663.7868 624.3968 657.2368 628.6219 620.2947 0.0000 627.2710
[15] 647.4306 620.5967 668.5807 614.7111 597.5937 660.5579
> colVars(tmp5,na.rm=TRUE)
[1] 17412.61402 62.71792 90.20895 35.07132 49.44553 64.49615
[7] 57.12222 86.51626 101.81424 58.46127 103.93820 73.23154
[13] NA 65.43088 74.69445 49.08368 36.77691 72.47036
[19] 48.76897 115.61309
> colSd(tmp5,na.rm=TRUE)
[1] 131.956864 7.919464 9.497839 5.922105 7.031751 8.030950
[7] 7.557925 9.301412 10.090304 7.645997 10.195009 8.557543
[13] NA 8.088935 8.642595 7.005975 6.064397 8.512953
[19] 6.983479 10.752353
> colMax(tmp5,na.rm=TRUE)
[1] 468.62529 83.20406 86.28033 79.41471 86.54628 85.84323 77.28337
[8] 89.58170 82.97380 84.66895 88.26814 82.55479 -Inf 79.48115
[15] 84.82125 80.58566 81.33057 77.21775 76.67179 89.64214
> colMin(tmp5,na.rm=TRUE)
[1] 63.09815 59.34899 59.49617 63.50780 63.33844 60.01807 57.17553 62.68974
[9] 53.88176 64.02140 54.17818 56.42992 Inf 56.55333 60.64464 59.63076
[17] 61.05397 54.20157 54.71047 58.89031
>
>
>
>
> 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] 228.5137 309.2314 198.5199 202.9034 211.8947 340.1559 222.8902 202.2895
[9] 169.9399 239.2206
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 228.5137 309.2314 198.5199 202.9034 211.8947 340.1559 222.8902 202.2895
[9] 169.9399 239.2206
>
>
>
> 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] 9.947598e-14 1.705303e-13 1.421085e-13 -1.705303e-13 -1.705303e-13
[6] -4.263256e-14 0.000000e+00 -5.684342e-14 1.421085e-13 1.136868e-13
[11] 0.000000e+00 -1.136868e-13 -5.684342e-14 2.842171e-14 5.684342e-14
[16] 2.842171e-14 0.000000e+00 -5.684342e-14 -1.421085e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 11
10 14
3 9
1 19
7 2
5 15
3 11
7 5
4 17
7 2
1 2
7 11
9 19
10 19
4 9
8 16
4 15
4 11
3 16
3 9
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] 2.493915
> Min(tmp)
[1] -3.191368
> mean(tmp)
[1] -0.05036603
> Sum(tmp)
[1] -5.036603
> Var(tmp)
[1] 1.027819
>
> rowMeans(tmp)
[1] -0.05036603
> rowSums(tmp)
[1] -5.036603
> rowVars(tmp)
[1] 1.027819
> rowSd(tmp)
[1] 1.013814
> rowMax(tmp)
[1] 2.493915
> rowMin(tmp)
[1] -3.191368
>
> colMeans(tmp)
[1] -0.756056610 0.844422311 1.016156240 0.209236272 0.157256644
[6] 0.299489639 -0.444873368 -0.535227751 -1.395177465 -0.022738729
[11] -1.852985032 1.295923528 0.362966980 1.977572916 0.295451332
[16] -1.071104097 -0.105160723 0.446102354 0.272654973 -1.522068865
[21] -0.993947183 1.115129178 0.797554661 0.130736791 0.433499829
[26] -0.622131872 0.406064720 -0.801384363 -1.568596817 0.335478651
[31] 0.491771316 0.986633232 0.977479848 0.951691833 -0.457679077
[36] -2.523386358 0.636937748 -0.717166791 0.983799946 0.316973145
[41] -0.928318375 -0.564263337 -0.514722428 0.473948078 0.359292082
[46] 0.830066409 0.562611383 1.217011625 -1.519744472 0.278852666
[51] 0.684214859 0.184480688 0.060614709 -0.860934912 -0.508830200
[56] -0.476292446 0.487226781 0.451609364 -0.008419574 -1.782033876
[61] 0.533036965 -3.191367887 -0.579005502 -0.315749065 -0.680517375
[66] -0.554369827 0.383589498 -0.760238517 1.126738090 -0.924812893
[71] -0.958326176 -1.031830233 -0.498673689 0.079818986 1.995425814
[76] 1.538421452 1.649912371 -0.846241760 0.957818305 1.290588792
[81] 1.183432158 1.398766437 -1.555529955 -0.810806658 -0.224193089
[86] -1.527697817 -0.955795250 0.456737739 -0.789018577 1.022139522
[91] -0.052649991 -1.371014127 2.493915368 -0.857149089 -0.376557299
[96] -1.621259184 0.865992916 0.262542697 0.086947756 -0.657292200
> colSums(tmp)
[1] -0.756056610 0.844422311 1.016156240 0.209236272 0.157256644
[6] 0.299489639 -0.444873368 -0.535227751 -1.395177465 -0.022738729
[11] -1.852985032 1.295923528 0.362966980 1.977572916 0.295451332
[16] -1.071104097 -0.105160723 0.446102354 0.272654973 -1.522068865
[21] -0.993947183 1.115129178 0.797554661 0.130736791 0.433499829
[26] -0.622131872 0.406064720 -0.801384363 -1.568596817 0.335478651
[31] 0.491771316 0.986633232 0.977479848 0.951691833 -0.457679077
[36] -2.523386358 0.636937748 -0.717166791 0.983799946 0.316973145
[41] -0.928318375 -0.564263337 -0.514722428 0.473948078 0.359292082
[46] 0.830066409 0.562611383 1.217011625 -1.519744472 0.278852666
[51] 0.684214859 0.184480688 0.060614709 -0.860934912 -0.508830200
[56] -0.476292446 0.487226781 0.451609364 -0.008419574 -1.782033876
[61] 0.533036965 -3.191367887 -0.579005502 -0.315749065 -0.680517375
[66] -0.554369827 0.383589498 -0.760238517 1.126738090 -0.924812893
[71] -0.958326176 -1.031830233 -0.498673689 0.079818986 1.995425814
[76] 1.538421452 1.649912371 -0.846241760 0.957818305 1.290588792
[81] 1.183432158 1.398766437 -1.555529955 -0.810806658 -0.224193089
[86] -1.527697817 -0.955795250 0.456737739 -0.789018577 1.022139522
[91] -0.052649991 -1.371014127 2.493915368 -0.857149089 -0.376557299
[96] -1.621259184 0.865992916 0.262542697 0.086947756 -0.657292200
> 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] -0.756056610 0.844422311 1.016156240 0.209236272 0.157256644
[6] 0.299489639 -0.444873368 -0.535227751 -1.395177465 -0.022738729
[11] -1.852985032 1.295923528 0.362966980 1.977572916 0.295451332
[16] -1.071104097 -0.105160723 0.446102354 0.272654973 -1.522068865
[21] -0.993947183 1.115129178 0.797554661 0.130736791 0.433499829
[26] -0.622131872 0.406064720 -0.801384363 -1.568596817 0.335478651
[31] 0.491771316 0.986633232 0.977479848 0.951691833 -0.457679077
[36] -2.523386358 0.636937748 -0.717166791 0.983799946 0.316973145
[41] -0.928318375 -0.564263337 -0.514722428 0.473948078 0.359292082
[46] 0.830066409 0.562611383 1.217011625 -1.519744472 0.278852666
[51] 0.684214859 0.184480688 0.060614709 -0.860934912 -0.508830200
[56] -0.476292446 0.487226781 0.451609364 -0.008419574 -1.782033876
[61] 0.533036965 -3.191367887 -0.579005502 -0.315749065 -0.680517375
[66] -0.554369827 0.383589498 -0.760238517 1.126738090 -0.924812893
[71] -0.958326176 -1.031830233 -0.498673689 0.079818986 1.995425814
[76] 1.538421452 1.649912371 -0.846241760 0.957818305 1.290588792
[81] 1.183432158 1.398766437 -1.555529955 -0.810806658 -0.224193089
[86] -1.527697817 -0.955795250 0.456737739 -0.789018577 1.022139522
[91] -0.052649991 -1.371014127 2.493915368 -0.857149089 -0.376557299
[96] -1.621259184 0.865992916 0.262542697 0.086947756 -0.657292200
> colMin(tmp)
[1] -0.756056610 0.844422311 1.016156240 0.209236272 0.157256644
[6] 0.299489639 -0.444873368 -0.535227751 -1.395177465 -0.022738729
[11] -1.852985032 1.295923528 0.362966980 1.977572916 0.295451332
[16] -1.071104097 -0.105160723 0.446102354 0.272654973 -1.522068865
[21] -0.993947183 1.115129178 0.797554661 0.130736791 0.433499829
[26] -0.622131872 0.406064720 -0.801384363 -1.568596817 0.335478651
[31] 0.491771316 0.986633232 0.977479848 0.951691833 -0.457679077
[36] -2.523386358 0.636937748 -0.717166791 0.983799946 0.316973145
[41] -0.928318375 -0.564263337 -0.514722428 0.473948078 0.359292082
[46] 0.830066409 0.562611383 1.217011625 -1.519744472 0.278852666
[51] 0.684214859 0.184480688 0.060614709 -0.860934912 -0.508830200
[56] -0.476292446 0.487226781 0.451609364 -0.008419574 -1.782033876
[61] 0.533036965 -3.191367887 -0.579005502 -0.315749065 -0.680517375
[66] -0.554369827 0.383589498 -0.760238517 1.126738090 -0.924812893
[71] -0.958326176 -1.031830233 -0.498673689 0.079818986 1.995425814
[76] 1.538421452 1.649912371 -0.846241760 0.957818305 1.290588792
[81] 1.183432158 1.398766437 -1.555529955 -0.810806658 -0.224193089
[86] -1.527697817 -0.955795250 0.456737739 -0.789018577 1.022139522
[91] -0.052649991 -1.371014127 2.493915368 -0.857149089 -0.376557299
[96] -1.621259184 0.865992916 0.262542697 0.086947756 -0.657292200
> colMedians(tmp)
[1] -0.756056610 0.844422311 1.016156240 0.209236272 0.157256644
[6] 0.299489639 -0.444873368 -0.535227751 -1.395177465 -0.022738729
[11] -1.852985032 1.295923528 0.362966980 1.977572916 0.295451332
[16] -1.071104097 -0.105160723 0.446102354 0.272654973 -1.522068865
[21] -0.993947183 1.115129178 0.797554661 0.130736791 0.433499829
[26] -0.622131872 0.406064720 -0.801384363 -1.568596817 0.335478651
[31] 0.491771316 0.986633232 0.977479848 0.951691833 -0.457679077
[36] -2.523386358 0.636937748 -0.717166791 0.983799946 0.316973145
[41] -0.928318375 -0.564263337 -0.514722428 0.473948078 0.359292082
[46] 0.830066409 0.562611383 1.217011625 -1.519744472 0.278852666
[51] 0.684214859 0.184480688 0.060614709 -0.860934912 -0.508830200
[56] -0.476292446 0.487226781 0.451609364 -0.008419574 -1.782033876
[61] 0.533036965 -3.191367887 -0.579005502 -0.315749065 -0.680517375
[66] -0.554369827 0.383589498 -0.760238517 1.126738090 -0.924812893
[71] -0.958326176 -1.031830233 -0.498673689 0.079818986 1.995425814
[76] 1.538421452 1.649912371 -0.846241760 0.957818305 1.290588792
[81] 1.183432158 1.398766437 -1.555529955 -0.810806658 -0.224193089
[86] -1.527697817 -0.955795250 0.456737739 -0.789018577 1.022139522
[91] -0.052649991 -1.371014127 2.493915368 -0.857149089 -0.376557299
[96] -1.621259184 0.865992916 0.262542697 0.086947756 -0.657292200
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.7560566 0.8444223 1.016156 0.2092363 0.1572566 0.2994896 -0.4448734
[2,] -0.7560566 0.8444223 1.016156 0.2092363 0.1572566 0.2994896 -0.4448734
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.5352278 -1.395177 -0.02273873 -1.852985 1.295924 0.362967 1.977573
[2,] -0.5352278 -1.395177 -0.02273873 -1.852985 1.295924 0.362967 1.977573
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.2954513 -1.071104 -0.1051607 0.4461024 0.272655 -1.522069 -0.9939472
[2,] 0.2954513 -1.071104 -0.1051607 0.4461024 0.272655 -1.522069 -0.9939472
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.115129 0.7975547 0.1307368 0.4334998 -0.6221319 0.4060647 -0.8013844
[2,] 1.115129 0.7975547 0.1307368 0.4334998 -0.6221319 0.4060647 -0.8013844
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.568597 0.3354787 0.4917713 0.9866332 0.9774798 0.9516918 -0.4576791
[2,] -1.568597 0.3354787 0.4917713 0.9866332 0.9774798 0.9516918 -0.4576791
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -2.523386 0.6369377 -0.7171668 0.9837999 0.3169731 -0.9283184 -0.5642633
[2,] -2.523386 0.6369377 -0.7171668 0.9837999 0.3169731 -0.9283184 -0.5642633
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.5147224 0.4739481 0.3592921 0.8300664 0.5626114 1.217012 -1.519744
[2,] -0.5147224 0.4739481 0.3592921 0.8300664 0.5626114 1.217012 -1.519744
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.2788527 0.6842149 0.1844807 0.06061471 -0.8609349 -0.5088302 -0.4762924
[2,] 0.2788527 0.6842149 0.1844807 0.06061471 -0.8609349 -0.5088302 -0.4762924
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4872268 0.4516094 -0.008419574 -1.782034 0.533037 -3.191368 -0.5790055
[2,] 0.4872268 0.4516094 -0.008419574 -1.782034 0.533037 -3.191368 -0.5790055
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.3157491 -0.6805174 -0.5543698 0.3835895 -0.7602385 1.126738 -0.9248129
[2,] -0.3157491 -0.6805174 -0.5543698 0.3835895 -0.7602385 1.126738 -0.9248129
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.9583262 -1.03183 -0.4986737 0.07981899 1.995426 1.538421 1.649912
[2,] -0.9583262 -1.03183 -0.4986737 0.07981899 1.995426 1.538421 1.649912
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.8462418 0.9578183 1.290589 1.183432 1.398766 -1.55553 -0.8108067
[2,] -0.8462418 0.9578183 1.290589 1.183432 1.398766 -1.55553 -0.8108067
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.2241931 -1.527698 -0.9557952 0.4567377 -0.7890186 1.02214 -0.05264999
[2,] -0.2241931 -1.527698 -0.9557952 0.4567377 -0.7890186 1.02214 -0.05264999
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.371014 2.493915 -0.8571491 -0.3765573 -1.621259 0.8659929 0.2625427
[2,] -1.371014 2.493915 -0.8571491 -0.3765573 -1.621259 0.8659929 0.2625427
[,99] [,100]
[1,] 0.08694776 -0.6572922
[2,] 0.08694776 -0.6572922
>
>
> Max(tmp2)
[1] 2.002593
> Min(tmp2)
[1] -2.251989
> mean(tmp2)
[1] 0.08463915
> Sum(tmp2)
[1] 8.463915
> Var(tmp2)
[1] 0.7653005
>
> rowMeans(tmp2)
[1] -1.03558904 -1.69163128 0.75019240 1.55785319 1.14139810 0.57321555
[7] 1.53210962 -0.31988422 -0.60704217 0.22212544 0.74038069 0.06248429
[13] 0.77134422 0.76176372 1.27421799 -1.12812913 -0.94818492 1.34935585
[19] -0.40895216 -1.04144366 -0.04930238 -0.41331761 0.72661489 -0.45413918
[25] -0.57489637 -1.11886604 0.26841248 -0.29020089 -0.60665668 -2.25198895
[31] 0.53412333 0.62597233 -0.76450873 -0.45336829 1.17896404 2.00259268
[37] 0.17952172 0.40548621 -1.16277510 -1.07897375 -0.14626370 0.72142763
[43] 0.40356831 -0.29532276 0.97701166 0.34877333 -0.22937881 1.00700597
[49] 1.04409747 -0.15853022 0.34660961 0.20364112 -0.15650587 -0.14641224
[55] 0.59996318 0.92137479 0.99324784 1.02535295 1.53867808 -0.94047120
[61] -0.62722318 0.51356354 0.65202607 -1.07102843 0.30658677 -0.43617235
[67] 0.34364012 -1.17157048 0.73670119 0.52850291 0.44852300 -0.36169227
[73] 0.19786130 1.74008976 -0.46116193 -1.05570389 0.77165741 -1.12292814
[79] 0.21303270 -0.04270506 -0.35950307 -0.42949622 -1.12269146 -0.15343319
[85] -0.36411260 0.43886097 1.28486100 1.23666374 -0.74039077 -0.72170111
[91] 0.58321589 -1.55991529 0.27902051 0.90927785 -0.21779048 1.00165413
[97] 1.96249853 -1.23342543 -0.24880210 -0.49901994
> rowSums(tmp2)
[1] -1.03558904 -1.69163128 0.75019240 1.55785319 1.14139810 0.57321555
[7] 1.53210962 -0.31988422 -0.60704217 0.22212544 0.74038069 0.06248429
[13] 0.77134422 0.76176372 1.27421799 -1.12812913 -0.94818492 1.34935585
[19] -0.40895216 -1.04144366 -0.04930238 -0.41331761 0.72661489 -0.45413918
[25] -0.57489637 -1.11886604 0.26841248 -0.29020089 -0.60665668 -2.25198895
[31] 0.53412333 0.62597233 -0.76450873 -0.45336829 1.17896404 2.00259268
[37] 0.17952172 0.40548621 -1.16277510 -1.07897375 -0.14626370 0.72142763
[43] 0.40356831 -0.29532276 0.97701166 0.34877333 -0.22937881 1.00700597
[49] 1.04409747 -0.15853022 0.34660961 0.20364112 -0.15650587 -0.14641224
[55] 0.59996318 0.92137479 0.99324784 1.02535295 1.53867808 -0.94047120
[61] -0.62722318 0.51356354 0.65202607 -1.07102843 0.30658677 -0.43617235
[67] 0.34364012 -1.17157048 0.73670119 0.52850291 0.44852300 -0.36169227
[73] 0.19786130 1.74008976 -0.46116193 -1.05570389 0.77165741 -1.12292814
[79] 0.21303270 -0.04270506 -0.35950307 -0.42949622 -1.12269146 -0.15343319
[85] -0.36411260 0.43886097 1.28486100 1.23666374 -0.74039077 -0.72170111
[91] 0.58321589 -1.55991529 0.27902051 0.90927785 -0.21779048 1.00165413
[97] 1.96249853 -1.23342543 -0.24880210 -0.49901994
> 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] -1.03558904 -1.69163128 0.75019240 1.55785319 1.14139810 0.57321555
[7] 1.53210962 -0.31988422 -0.60704217 0.22212544 0.74038069 0.06248429
[13] 0.77134422 0.76176372 1.27421799 -1.12812913 -0.94818492 1.34935585
[19] -0.40895216 -1.04144366 -0.04930238 -0.41331761 0.72661489 -0.45413918
[25] -0.57489637 -1.11886604 0.26841248 -0.29020089 -0.60665668 -2.25198895
[31] 0.53412333 0.62597233 -0.76450873 -0.45336829 1.17896404 2.00259268
[37] 0.17952172 0.40548621 -1.16277510 -1.07897375 -0.14626370 0.72142763
[43] 0.40356831 -0.29532276 0.97701166 0.34877333 -0.22937881 1.00700597
[49] 1.04409747 -0.15853022 0.34660961 0.20364112 -0.15650587 -0.14641224
[55] 0.59996318 0.92137479 0.99324784 1.02535295 1.53867808 -0.94047120
[61] -0.62722318 0.51356354 0.65202607 -1.07102843 0.30658677 -0.43617235
[67] 0.34364012 -1.17157048 0.73670119 0.52850291 0.44852300 -0.36169227
[73] 0.19786130 1.74008976 -0.46116193 -1.05570389 0.77165741 -1.12292814
[79] 0.21303270 -0.04270506 -0.35950307 -0.42949622 -1.12269146 -0.15343319
[85] -0.36411260 0.43886097 1.28486100 1.23666374 -0.74039077 -0.72170111
[91] 0.58321589 -1.55991529 0.27902051 0.90927785 -0.21779048 1.00165413
[97] 1.96249853 -1.23342543 -0.24880210 -0.49901994
> rowMin(tmp2)
[1] -1.03558904 -1.69163128 0.75019240 1.55785319 1.14139810 0.57321555
[7] 1.53210962 -0.31988422 -0.60704217 0.22212544 0.74038069 0.06248429
[13] 0.77134422 0.76176372 1.27421799 -1.12812913 -0.94818492 1.34935585
[19] -0.40895216 -1.04144366 -0.04930238 -0.41331761 0.72661489 -0.45413918
[25] -0.57489637 -1.11886604 0.26841248 -0.29020089 -0.60665668 -2.25198895
[31] 0.53412333 0.62597233 -0.76450873 -0.45336829 1.17896404 2.00259268
[37] 0.17952172 0.40548621 -1.16277510 -1.07897375 -0.14626370 0.72142763
[43] 0.40356831 -0.29532276 0.97701166 0.34877333 -0.22937881 1.00700597
[49] 1.04409747 -0.15853022 0.34660961 0.20364112 -0.15650587 -0.14641224
[55] 0.59996318 0.92137479 0.99324784 1.02535295 1.53867808 -0.94047120
[61] -0.62722318 0.51356354 0.65202607 -1.07102843 0.30658677 -0.43617235
[67] 0.34364012 -1.17157048 0.73670119 0.52850291 0.44852300 -0.36169227
[73] 0.19786130 1.74008976 -0.46116193 -1.05570389 0.77165741 -1.12292814
[79] 0.21303270 -0.04270506 -0.35950307 -0.42949622 -1.12269146 -0.15343319
[85] -0.36411260 0.43886097 1.28486100 1.23666374 -0.74039077 -0.72170111
[91] 0.58321589 -1.55991529 0.27902051 0.90927785 -0.21779048 1.00165413
[97] 1.96249853 -1.23342543 -0.24880210 -0.49901994
>
> colMeans(tmp2)
[1] 0.08463915
> colSums(tmp2)
[1] 8.463915
> colVars(tmp2)
[1] 0.7653005
> colSd(tmp2)
[1] 0.8748146
> colMax(tmp2)
[1] 2.002593
> colMin(tmp2)
[1] -2.251989
> colMedians(tmp2)
[1] 0.1886915
> colRanges(tmp2)
[,1]
[1,] -2.251989
[2,] 2.002593
>
> 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] 0.5275703042 -1.7136692816 -2.0121791112 -4.7287023520 -0.2457501843
[6] -0.3253202352 -5.7412407354 0.0002711605 -0.6500315914 2.8718817036
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6384970
[2,] -0.8296441
[3,] 0.0667349
[4,] 0.7073462
[5,] 1.8937163
>
> rowApply(tmp,sum)
[1] -3.49315899 -0.83380778 -2.29731381 -4.94123573 -0.62678876 -1.46773192
[7] -0.02946108 1.70816991 -0.79703146 0.76118930
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 3 2 7 2 2 10 9 5 7
[2,] 4 10 1 5 8 5 5 3 7 5
[3,] 10 2 5 10 5 3 2 1 9 2
[4,] 1 8 10 1 3 6 8 2 2 4
[5,] 3 7 9 6 9 1 1 5 10 6
[6,] 2 9 8 4 6 7 7 7 3 8
[7,] 8 6 4 2 1 4 6 8 4 1
[8,] 7 1 7 9 4 10 9 4 1 9
[9,] 5 5 6 3 10 9 3 6 6 3
[10,] 6 4 3 8 7 8 4 10 8 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.4063927 -3.7072519 -1.7315123 -0.6708531 0.9913210 0.2956658
[7] 0.7363168 3.5993952 0.9984391 1.9017465 1.2423098 -0.5078662
[13] 0.7414802 3.5207812 -1.5838360 1.0146485 2.4476737 -1.0749670
[19] 1.2485230 0.2294775
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2114325
[2,] -0.3737213
[3,] 0.5018016
[4,] 0.6863674
[5,] 0.8033775
>
> rowApply(tmp,sum)
[1] 6.6290393 5.5916251 0.2635441 -2.0940471 -0.2922770
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 14 17 5 4 14
[2,] 1 1 14 10 4
[3,] 11 5 2 17 1
[4,] 2 15 13 16 2
[5,] 7 2 11 19 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.6863674 -1.60085340 0.4153269 -0.7904662 0.15740741 0.46700392
[2,] 0.8033775 -1.37410320 -0.2891609 0.7090934 -0.78295525 0.07334573
[3,] -0.3737213 0.25788826 -1.0805534 0.2188246 0.05908163 0.05671588
[4,] -1.2114325 -0.00886321 0.5971629 0.5360498 1.16551157 0.40930591
[5,] 0.5018016 -0.98132032 -1.3742878 -1.3443548 0.39227563 -0.71070567
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.4403351 1.67455828 0.28940327 -0.1473636 0.2708700 1.5470434
[2,] -0.4519183 0.03824276 0.10611536 -0.5213960 0.0245497 0.1471619
[3,] 1.2050771 1.25887904 0.01927257 0.3266319 0.6662593 -1.0124430
[4,] -1.3142480 0.42068666 0.05829132 0.6999032 -1.2813245 -1.2044453
[5,] 0.8570710 0.20702846 0.52535661 1.5439710 1.5619553 0.0148168
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.36872060 0.9403860 0.2433387 -0.5661570 0.02145164 0.7208152
[2,] 0.11219334 3.1957741 0.6180329 0.5811001 1.14696649 -0.2419163
[3,] -0.02727388 -0.4301871 -1.8498118 -0.3601354 1.14040929 -0.3465004
[4,] -0.26662271 0.4449153 0.2285134 1.5451768 -1.02182751 -0.1740317
[5,] -0.44553716 -0.6301071 -0.8239092 -0.1853361 1.16067376 -1.0333338
[,19] [,20]
[1,] 0.7873627 -0.29651108
[2,] 0.7543868 0.94273485
[3,] 0.4600651 0.07506597
[4,] -1.5894027 -0.12736598
[5,] 0.8361111 -0.36444625
>
>
> 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 -1.348857 -0.6497651 1.112249 0.1925831 0.6263365 -1.814196 0.09131447
col8 col9 col10 col11 col12 col13 col14
row1 0.2795586 1.022697 -0.8431465 0.4729752 -0.7445506 0.8281507 0.4634484
col15 col16 col17 col18 col19 col20
row1 1.487781 1.342713 0.1171997 -0.80172 0.1057259 1.212708
> tmp[,"col10"]
col10
row1 -0.8431465
row2 1.0485011
row3 -1.8683211
row4 0.1525355
row5 0.2108168
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.3488571 -0.6497651 1.112249 0.1925831 0.6263365 -1.8141962 0.09131447
row5 -0.2142898 -0.2486107 1.170524 0.8623381 1.2470272 0.6189173 0.66313870
col8 col9 col10 col11 col12 col13 col14
row1 0.2795586 1.022697 -0.8431465 0.4729752 -0.7445506 0.8281507 0.4634484
row5 -1.2202677 1.575862 0.2108168 -1.1383288 1.2673920 -0.8724801 0.6988435
col15 col16 col17 col18 col19 col20
row1 1.487781 1.342713 0.1171997 -0.80172 0.1057259 1.212708
row5 1.047133 1.154196 -0.1772889 -0.16546 0.9145042 0.138762
> tmp[,c("col6","col20")]
col6 col20
row1 -1.8141962 1.2127084
row2 -0.1874134 0.8096419
row3 1.2493620 -0.8461305
row4 -0.9704658 -0.7550543
row5 0.6189173 0.1387620
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.8141962 1.212708
row5 0.6189173 0.138762
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.72907 50.0952 51.64454 49.62489 49.92341 105.217 51.90404 50.6023
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.22262 50.59466 49.71946 50.61702 49.4972 49.47336 48.05774 49.20863
col17 col18 col19 col20
row1 48.93562 51.30218 49.18697 104.765
> tmp[,"col10"]
col10
row1 50.59466
row2 30.98236
row3 29.76052
row4 30.15134
row5 50.43135
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.72907 50.09520 51.64454 49.62489 49.92341 105.2170 51.90404 50.60230
row5 51.99169 47.66998 50.50189 48.72509 50.19701 105.6033 49.54463 49.97127
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.22262 50.59466 49.71946 50.61702 49.49720 49.47336 48.05774 49.20863
row5 50.01191 50.43135 48.56926 49.43388 49.83926 48.85035 48.56986 48.69509
col17 col18 col19 col20
row1 48.93562 51.30218 49.18697 104.765
row5 48.34529 49.40207 51.90015 105.408
> tmp[,c("col6","col20")]
col6 col20
row1 105.21699 104.76500
row2 73.75251 76.06754
row3 72.40465 75.62271
row4 74.54439 73.72867
row5 105.60327 105.40802
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.2170 104.765
row5 105.6033 105.408
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.2170 104.765
row5 105.6033 105.408
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8351296
[2,] 0.1877681
[3,] 0.9763471
[4,] -0.4762933
[5,] -2.8927772
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7271373 -0.8394205
[2,] -0.4892603 -0.5495558
[3,] 0.7634799 1.0279212
[4,] 0.6548378 -0.3496966
[5,] 0.1128815 0.4355514
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.03745205 1.3495161
[2,] -1.30477783 1.0960251
[3,] -0.29022006 0.4568657
[4,] 0.01446059 -0.4547513
[5,] -0.74885765 0.5254487
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.037452
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.037452
[2,] -1.304778
>
>
>
> 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 0.03028084 -2.0182624 1.2922936 -0.6232322 -0.7525573 0.04307731
row1 -0.45711238 0.4025787 0.5174191 0.5969295 -0.5633884 0.21111082
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.5414028 1.123729 0.7597738 -0.04190868 0.96738642 -0.7245293 1.13287
row1 1.0520956 -1.512985 0.3243556 1.67641147 0.03161294 -0.8807726 -1.32483
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 2.814550 -1.0320785 -0.4922528 1.007857 -1.24506036 -0.7027986 0.6814865
row1 -2.222017 -0.9986006 0.3780223 1.609034 0.07036529 0.4907062 -0.2109846
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.301323 0.06468205 -2.501389 -1.475546 -0.4812255 -2.061037 -0.1678738
[,8] [,9] [,10]
row2 -0.4321814 -0.4039564 0.5386717
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.5966684 0.05748723 1.198114 -0.1964173 0.4725859 1.099303 0.749184
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.909343 -0.349138 1.702192 0.9880846 1.519228 -0.4054065 0.05619322
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.051446 0.3860881 -0.476734 -0.3313208 0.5927111 0.6744156
>
>
> 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: 0x5b3efab0b7d0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd787f165e3a"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd7861b7c2e8"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd789a0d449"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd786b25ac12"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd7822b7f2b6"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd785cbfbdd1"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd7877d78c06"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd78130d9212"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd783c86e4b6"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd78376531de"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd785a6dac60"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd783e8598be"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd78959b33e"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd786cd0dc8"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd782289f267"
>
>
> ### 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: 0x5b3efc5cd630>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5b3efc5cd630>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5b3efc5cd630>
> rowMedians(tmp)
[1] -0.5149098009 -0.1210942107 -0.4524396227 -0.2715774053 0.5965553619
[6] -0.3838636148 0.1753035756 0.1536179987 0.4318729997 -0.1323253563
[11] 0.0733937423 -0.4056429867 -0.1355808468 0.0058253095 0.2542183055
[16] -0.4810101405 0.5534339923 -0.3580899457 -0.2350316188 -0.0977889961
[21] 0.1098913929 -0.0524691136 -0.2249611427 -0.1390538483 -0.2616715806
[26] -0.3327616353 0.3289693240 0.3155141172 0.1441215465 -0.0207082432
[31] 0.4160409541 -0.3209358590 -0.1458776472 0.0226531777 0.3352757091
[36] -0.5762279490 0.0854983742 -0.5093029711 0.1290281415 -0.1680588615
[41] -0.1675485859 0.0395019716 0.1127187865 0.0833943139 0.1371168748
[46] -0.1457243639 0.6144777838 -0.0925674760 -0.7935473485 -0.2303646504
[51] 0.1103388492 -0.0502807552 0.0773878223 -0.2420411985 -0.2579838602
[56] -0.0478183048 -0.2213192223 0.6143114690 0.4909886147 -0.0537752042
[61] 0.1135987703 -0.2027322002 0.2145652019 0.3096707886 0.3517724909
[66] -0.1744389908 0.7341807547 -0.4599405728 0.0309189310 -0.3667988861
[71] 0.4319199754 0.3769959629 0.2330952614 0.5266347446 0.3757483473
[76] 0.1209688154 0.1340987652 0.1010006359 -0.5030034724 0.1956480591
[81] 0.0590557735 0.5263637543 0.3931712462 0.6679710951 -0.4238314082
[86] 0.4101101722 -0.4394001310 0.1960087368 -0.2528637942 0.2214660384
[91] 0.1777379057 -0.8206555576 -0.1049723899 -0.3243958883 -0.5734196891
[96] 0.0456709116 0.4974909291 0.2499217466 -0.3153297589 -0.2090343797
[101] 0.1058571622 -0.0329978697 -0.2690555434 -0.6018031289 -0.1659471365
[106] -0.6616684252 0.1521974196 -0.1535903668 0.0472205665 0.1586048313
[111] 0.2381508274 0.3043328975 -0.1577661907 -0.0867106414 -0.4428324945
[116] 0.3091549309 0.1626597856 0.3910859933 -0.1272750169 0.3945710487
[121] -0.2323645084 -0.2049764914 0.1077091692 0.1708807237 0.9390379491
[126] 0.1126165707 0.3035987949 -0.1670868089 0.0632454927 -0.0069311696
[131] 0.3196104207 0.0896462757 0.2833284484 -0.1738659013 -0.2198732625
[136] -0.0886844557 -0.1963805345 0.4505043503 -0.1600263142 -0.1154352440
[141] 0.2065549459 0.2235109259 -0.2483722559 0.2747289032 -0.0959509595
[146] -0.1122111886 -0.1476981704 0.0425744051 0.2132502299 -0.2652802762
[151] -0.3534388545 0.1503360161 -0.4740478800 -0.1155757294 -0.0208040638
[156] -0.3847031384 -0.6705185189 0.1762733835 -0.1556607913 0.0091356372
[161] -0.4304901487 0.2428897260 0.1325467945 0.0312745739 0.3282982450
[166] 0.0001455389 -0.3647079359 0.6204717720 -0.2348400918 0.0148272432
[171] 0.0532203504 0.1840667194 -0.4116480430 -0.6836044335 -0.4637003672
[176] 0.6142186917 0.2301993116 -0.0587422003 -0.3696945552 -0.1835188441
[181] -0.0288082994 0.0899482831 0.3659262149 0.3110669810 0.3933777152
[186] -0.2410656432 0.1243802936 -0.2303825398 0.3565962276 -0.1549708104
[191] -0.6294448279 -0.3218910652 -0.4032829194 -0.5640608920 -0.1410308602
[196] 0.4002453745 0.5619994880 0.5071589429 -0.2050112747 -0.5298527735
[201] -0.3356997496 -0.2018902260 0.0076642538 0.3834787568 -0.0052880690
[206] 0.2006888190 -0.6202886241 -0.0482062567 0.4079116115 -0.6256544110
[211] -0.2337890694 -0.2440620883 -0.1688889217 -0.3412830861 0.7669984735
[216] -0.1521294166 -0.0600574868 -0.2329227636 0.1929007874 -0.1591638277
[221] 0.0972907080 0.6791711872 0.2807760473 -0.2939272680 1.1339539244
[226] 0.1275471827 -0.2015529228 -0.8191750081 -0.3089952685 0.2244634231
>
> proc.time()
user system elapsed
1.339 1.478 2.805
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: 0x5bc521f80c10>
> .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: 0x5bc521f80c10>
> .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: 0x5bc521f80c10>
> .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: 0x5bc521f80c10>
> 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: 0x5bc522c432d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc522c432d0>
> .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: 0x5bc522c432d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc522c432d0>
> .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: 0x5bc522c432d0>
> 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: 0x5bc523318d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc523318d70>
> .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: 0x5bc523318d70>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5bc523318d70>
> .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: 0x5bc523318d70>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5bc523318d70>
> .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: 0x5bc523318d70>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5bc523318d70>
> .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: 0x5bc523318d70>
> 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: 0x5bc522e8c370>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5bc522e8c370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc522e8c370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc522e8c370>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12fe3b48a788d1" "BufferedMatrixFile12fe3bb8bbc25"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12fe3b48a788d1" "BufferedMatrixFile12fe3bb8bbc25"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc522dd7ff0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc522dd7ff0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5bc522dd7ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5bc522dd7ff0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5bc522dd7ff0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5bc522dd7ff0>
> .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: 0x5bc522fba3d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5bc522fba3d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5bc522fba3d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5bc522fba3d0>
> 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: 0x5bc52476bfb0>
> .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: 0x5bc52476bfb0>
> rm(P)
>
> proc.time()
user system elapsed
0.243 0.049 0.281
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
0.244 0.053 0.283