Ben Bolstad
| Snapshot Date: 2026-04-17 13:40 -0400 (Fri, 17 Apr 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 -0400 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-04-18 11:35 -0400 (Sat, 18 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 alpha (2026-04-05 r89794) | 4957 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 alpha (2026-04-08 r89818) | 4686 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4627 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 259/2404 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | 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: 2026-04-17 21:57:02 -0400 (Fri, 17 Apr 2026) |
| EndedAt: 2026-04-17 21:57:27 -0400 (Fri, 17 Apr 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
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 alpha (2026-04-05 r89794)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-04-18 01:57:02 UTC
* 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 13.3.0-6ubuntu2~24.04.1) 13.3.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ...* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
‘/home/biocbuild/bbs-3.23-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 13.3.0-6ubuntu2~24.04.1) 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 version 4.6.0 alpha (2026-04-05 r89794)
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
0.242 0.050 0.280
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 alpha (2026-04-05 r89794)
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 480193 25.7 1053195 56.3 637568 34.1
Vcells 887233 6.8 8388608 64.0 2083868 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] "Fri Apr 17 21:57:17 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] "Fri Apr 17 21:57:17 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: 0x60f5e1cd6a60>
>
>
>
> 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] "Fri Apr 17 21:57:18 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] "Fri Apr 17 21:57:18 2026"
>
> ColMode(tmp2)
<pointer: 0x60f5e1cd6a60>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8379969 -2.2134548 -0.1094299 0.03433539
[2,] -0.9737503 -1.2978737 -0.3282383 -0.61436740
[3,] -0.9836275 0.7919599 0.9754012 -0.19344754
[4,] 1.1576133 -0.7544671 -0.3678162 -0.11465851
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8379969 2.2134548 0.1094299 0.03433539
[2,] 0.9737503 1.2978737 0.3282383 0.61436740
[3,] 0.9836275 0.7919599 0.9754012 0.19344754
[4,] 1.1576133 0.7544671 0.3678162 0.11465851
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9918966 1.4877684 0.3308018 0.1852981
[2,] 0.9867879 1.1392426 0.5729208 0.7838159
[3,] 0.9917800 0.8899213 0.9876240 0.4398267
[4,] 1.0759244 0.8686007 0.6064785 0.3386126
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.75696 42.09114 28.41745 26.88732
[2,] 35.84163 37.69030 31.05745 33.45253
[3,] 35.90143 34.69117 35.85164 29.59171
[4,] 36.91686 34.44047 31.43260 28.50078
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x60f5e1c57e20>
> exp(tmp5)
<pointer: 0x60f5e1c57e20>
> log(tmp5,2)
<pointer: 0x60f5e1c57e20>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.8022
> Min(tmp5)
[1] 53.6703
> mean(tmp5)
[1] 71.73398
> Sum(tmp5)
[1] 14346.8
> Var(tmp5)
[1] 861.3013
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.74795 71.23997 70.75792 70.95494 67.72147 69.23311 68.53851 69.09457
[9] 70.39370 69.65765
> rowSums(tmp5)
[1] 1794.959 1424.799 1415.158 1419.099 1354.429 1384.662 1370.770 1381.891
[9] 1407.874 1393.153
> rowVars(tmp5)
[1] 8047.63460 49.69249 59.65801 106.12429 57.97361 72.97071
[7] 53.39377 56.03650 65.49156 60.49924
> rowSd(tmp5)
[1] 89.708609 7.049290 7.723860 10.301664 7.614040 8.542290 7.307104
[8] 7.485753 8.092685 7.778126
> rowMax(tmp5)
[1] 467.80217 84.00289 84.52449 90.76244 83.63876 91.51016 82.44748
[8] 83.90342 88.05393 84.43287
> rowMin(tmp5)
[1] 55.54218 59.35353 54.92405 55.34629 55.47485 56.47597 53.67030 58.86597
[9] 55.57585 55.23330
>
> colMeans(tmp5)
[1] 110.09560 73.35454 70.62370 64.09787 64.83034 70.74326 72.21609
[8] 74.10604 65.92119 64.22572 76.90963 69.01309 68.40334 66.12501
[15] 73.72944 70.59348 67.75274 67.57233 72.41226 71.95396
> colSums(tmp5)
[1] 1100.9560 733.5454 706.2370 640.9787 648.3034 707.4326 722.1609
[8] 741.0604 659.2119 642.2572 769.0963 690.1309 684.0334 661.2501
[15] 737.2944 705.9348 677.5274 675.7233 724.1226 719.5396
> colVars(tmp5)
[1] 15821.99214 53.32899 59.77384 29.88271 53.25960 71.09651
[7] 133.77694 46.10162 44.41753 26.38383 110.57547 55.75869
[13] 55.72203 40.89085 126.75737 72.06741 54.09636 67.14509
[19] 84.39432 43.40448
> colSd(tmp5)
[1] 125.785501 7.302670 7.731354 5.466508 7.297917 8.431875
[7] 11.566198 6.789817 6.664648 5.136519 10.515487 7.467174
[13] 7.464719 6.394596 11.258657 8.489253 7.355023 8.194211
[19] 9.186638 6.588208
> colMax(tmp5)
[1] 467.80217 87.60719 82.34709 72.47992 77.69166 84.43287 89.87694
[8] 83.83234 77.98304 70.60687 90.76244 82.44748 82.01022 77.15541
[15] 91.51016 82.16328 83.90342 84.00289 84.52449 83.78759
> colMin(tmp5)
[1] 62.22545 59.24904 59.14720 55.96243 53.67030 58.86597 55.57585 62.78058
[9] 55.23330 56.16958 63.07867 55.54218 56.38229 54.92405 58.48557 55.47485
[17] 57.05086 55.34629 56.04003 60.36523
>
>
> ### 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] 89.74795 71.23997 70.75792 70.95494 67.72147 69.23311 68.53851 69.09457
[9] 70.39370 NA
> rowSums(tmp5)
[1] 1794.959 1424.799 1415.158 1419.099 1354.429 1384.662 1370.770 1381.891
[9] 1407.874 NA
> rowVars(tmp5)
[1] 8047.63460 49.69249 59.65801 106.12429 57.97361 72.97071
[7] 53.39377 56.03650 65.49156 63.84756
> rowSd(tmp5)
[1] 89.708609 7.049290 7.723860 10.301664 7.614040 8.542290 7.307104
[8] 7.485753 8.092685 7.990467
> rowMax(tmp5)
[1] 467.80217 84.00289 84.52449 90.76244 83.63876 91.51016 82.44748
[8] 83.90342 88.05393 NA
> rowMin(tmp5)
[1] 55.54218 59.35353 54.92405 55.34629 55.47485 56.47597 53.67030 58.86597
[9] 55.57585 NA
>
> colMeans(tmp5)
[1] 110.09560 73.35454 NA 64.09787 64.83034 70.74326 72.21609
[8] 74.10604 65.92119 64.22572 76.90963 69.01309 68.40334 66.12501
[15] 73.72944 70.59348 67.75274 67.57233 72.41226 71.95396
> colSums(tmp5)
[1] 1100.9560 733.5454 NA 640.9787 648.3034 707.4326 722.1609
[8] 741.0604 659.2119 642.2572 769.0963 690.1309 684.0334 661.2501
[15] 737.2944 705.9348 677.5274 675.7233 724.1226 719.5396
> colVars(tmp5)
[1] 15821.99214 53.32899 NA 29.88271 53.25960 71.09651
[7] 133.77694 46.10162 44.41753 26.38383 110.57547 55.75869
[13] 55.72203 40.89085 126.75737 72.06741 54.09636 67.14509
[19] 84.39432 43.40448
> colSd(tmp5)
[1] 125.785501 7.302670 NA 5.466508 7.297917 8.431875
[7] 11.566198 6.789817 6.664648 5.136519 10.515487 7.467174
[13] 7.464719 6.394596 11.258657 8.489253 7.355023 8.194211
[19] 9.186638 6.588208
> colMax(tmp5)
[1] 467.80217 87.60719 NA 72.47992 77.69166 84.43287 89.87694
[8] 83.83234 77.98304 70.60687 90.76244 82.44748 82.01022 77.15541
[15] 91.51016 82.16328 83.90342 84.00289 84.52449 83.78759
> colMin(tmp5)
[1] 62.22545 59.24904 NA 55.96243 53.67030 58.86597 55.57585 62.78058
[9] 55.23330 56.16958 63.07867 55.54218 56.38229 54.92405 58.48557 55.47485
[17] 57.05086 55.34629 56.04003 60.36523
>
> Max(tmp5,na.rm=TRUE)
[1] 467.8022
> Min(tmp5,na.rm=TRUE)
[1] 53.6703
> mean(tmp5,na.rm=TRUE)
[1] 71.74207
> Sum(tmp5,na.rm=TRUE)
[1] 14276.67
> Var(tmp5,na.rm=TRUE)
[1] 865.6381
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.74795 71.23997 70.75792 70.95494 67.72147 69.23311 68.53851 69.09457
[9] 70.39370 69.63307
> rowSums(tmp5,na.rm=TRUE)
[1] 1794.959 1424.799 1415.158 1419.099 1354.429 1384.662 1370.770 1381.891
[9] 1407.874 1323.028
> rowVars(tmp5,na.rm=TRUE)
[1] 8047.63460 49.69249 59.65801 106.12429 57.97361 72.97071
[7] 53.39377 56.03650 65.49156 63.84756
> rowSd(tmp5,na.rm=TRUE)
[1] 89.708609 7.049290 7.723860 10.301664 7.614040 8.542290 7.307104
[8] 7.485753 8.092685 7.990467
> rowMax(tmp5,na.rm=TRUE)
[1] 467.80217 84.00289 84.52449 90.76244 83.63876 91.51016 82.44748
[8] 83.90342 88.05393 84.43287
> rowMin(tmp5,na.rm=TRUE)
[1] 55.54218 59.35353 54.92405 55.34629 55.47485 56.47597 53.67030 58.86597
[9] 55.57585 55.23330
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.09560 73.35454 70.67915 64.09787 64.83034 70.74326 72.21609
[8] 74.10604 65.92119 64.22572 76.90963 69.01309 68.40334 66.12501
[15] 73.72944 70.59348 67.75274 67.57233 72.41226 71.95396
> colSums(tmp5,na.rm=TRUE)
[1] 1100.9560 733.5454 636.1123 640.9787 648.3034 707.4326 722.1609
[8] 741.0604 659.2119 642.2572 769.0963 690.1309 684.0334 661.2501
[15] 737.2944 705.9348 677.5274 675.7233 724.1226 719.5396
> colVars(tmp5,na.rm=TRUE)
[1] 15821.99214 53.32899 67.21098 29.88271 53.25960 71.09651
[7] 133.77694 46.10162 44.41753 26.38383 110.57547 55.75869
[13] 55.72203 40.89085 126.75737 72.06741 54.09636 67.14509
[19] 84.39432 43.40448
> colSd(tmp5,na.rm=TRUE)
[1] 125.785501 7.302670 8.198230 5.466508 7.297917 8.431875
[7] 11.566198 6.789817 6.664648 5.136519 10.515487 7.467174
[13] 7.464719 6.394596 11.258657 8.489253 7.355023 8.194211
[19] 9.186638 6.588208
> colMax(tmp5,na.rm=TRUE)
[1] 467.80217 87.60719 82.34709 72.47992 77.69166 84.43287 89.87694
[8] 83.83234 77.98304 70.60687 90.76244 82.44748 82.01022 77.15541
[15] 91.51016 82.16328 83.90342 84.00289 84.52449 83.78759
> colMin(tmp5,na.rm=TRUE)
[1] 62.22545 59.24904 59.14720 55.96243 53.67030 58.86597 55.57585 62.78058
[9] 55.23330 56.16958 63.07867 55.54218 56.38229 54.92405 58.48557 55.47485
[17] 57.05086 55.34629 56.04003 60.36523
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.74795 71.23997 70.75792 70.95494 67.72147 69.23311 68.53851 69.09457
[9] 70.39370 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1794.959 1424.799 1415.158 1419.099 1354.429 1384.662 1370.770 1381.891
[9] 1407.874 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8047.63460 49.69249 59.65801 106.12429 57.97361 72.97071
[7] 53.39377 56.03650 65.49156 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.708609 7.049290 7.723860 10.301664 7.614040 8.542290 7.307104
[8] 7.485753 8.092685 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 467.80217 84.00289 84.52449 90.76244 83.63876 91.51016 82.44748
[8] 83.90342 88.05393 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.54218 59.35353 54.92405 55.34629 55.47485 56.47597 53.67030 58.86597
[9] 55.57585 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.24432 72.99450 NaN 63.54815 64.73252 69.22220 71.28101
[8] 74.93045 67.10873 64.36940 78.44640 68.88375 68.06321 65.93987
[15] 75.28582 70.59787 67.91375 68.33079 71.13619 71.58564
> colSums(tmp5,na.rm=TRUE)
[1] 1028.1989 656.9505 0.0000 571.9334 582.5926 622.9998 641.5291
[8] 674.3741 603.9786 579.3246 706.0176 619.9537 612.5689 593.4589
[15] 677.5724 635.3808 611.2237 614.9771 640.2257 644.2708
> colVars(tmp5,na.rm=TRUE)
[1] 17606.10756 58.53679 NA 30.21847 59.80939 53.95506
[7] 140.66233 44.21818 34.10430 29.44959 97.82858 62.54034
[13] 61.38577 45.61659 115.35111 81.07562 60.56677 69.06645
[19] 76.62447 47.30389
> colSd(tmp5,na.rm=TRUE)
[1] 132.688008 7.650934 NA 5.497133 7.733653 7.345411
[7] 11.860115 6.649675 5.839889 5.426748 9.890833 7.908245
[13] 7.834907 6.754005 10.740164 9.004200 7.782466 8.310623
[19] 8.753540 6.877782
> colMax(tmp5,na.rm=TRUE)
[1] 467.80217 87.60719 -Inf 72.47992 77.69166 77.67294 89.87694
[8] 83.83234 77.98304 70.60687 90.76244 82.44748 82.01022 77.15541
[15] 91.51016 82.16328 83.90342 84.00289 84.52449 83.78759
> colMin(tmp5,na.rm=TRUE)
[1] 62.22545 59.24904 Inf 55.96243 53.67030 58.86597 55.57585 62.78058
[9] 60.54678 56.16958 64.85111 55.54218 56.38229 54.92405 58.48557 55.47485
[17] 57.05086 55.34629 56.04003 60.36523
>
>
>
>
> 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] 103.8507 168.9089 183.2525 134.1088 234.2605 247.5919 148.3938 200.4494
[9] 352.7362 222.5001
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 103.8507 168.9089 183.2525 134.1088 234.2605 247.5919 148.3938 200.4494
[9] 352.7362 222.5001
>
>
>
> 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 -5.684342e-14 1.705303e-13 8.526513e-14 -2.842171e-14
[6] 1.136868e-13 0.000000e+00 1.421085e-13 1.136868e-13 4.263256e-14
[11] 5.684342e-14 -5.684342e-14 -5.684342e-14 -8.526513e-14 1.136868e-13
[16] -1.136868e-13 -1.136868e-13 1.705303e-13 -5.684342e-14 -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)
+ }
6 7
4 9
6 4
4 18
4 17
10 8
3 17
7 18
5 17
7 12
2 17
3 1
5 3
6 3
4 5
2 1
10 4
5 9
9 17
4 6
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] 2.606799
> Min(tmp)
[1] -3.142198
> mean(tmp)
[1] -0.08863257
> Sum(tmp)
[1] -8.863257
> Var(tmp)
[1] 1.031024
>
> rowMeans(tmp)
[1] -0.08863257
> rowSums(tmp)
[1] -8.863257
> rowVars(tmp)
[1] 1.031024
> rowSd(tmp)
[1] 1.015393
> rowMax(tmp)
[1] 2.606799
> rowMin(tmp)
[1] -3.142198
>
> colMeans(tmp)
[1] -0.71470446 0.70001490 -0.44626354 -1.11281309 -1.14460516 -1.35727430
[7] 1.49470576 -0.49219706 -0.82774134 -0.72189051 -1.10330295 -1.59950617
[13] 0.59967661 0.23168036 1.27634294 0.21807110 -0.87772261 1.62338004
[19] -1.34829015 0.61634221 -0.77168362 0.78285652 1.23304746 0.95583103
[25] -0.10188292 0.61876213 1.09231463 -0.56959710 2.60679932 -1.18765690
[31] 0.22632097 -0.12116766 -0.52821244 0.37338552 0.69193561 0.16012456
[37] 1.67119787 -0.05011250 1.54957475 -0.10250732 -0.22079978 0.59957639
[43] -0.92718684 -1.78947784 -0.51985377 -0.51562036 0.15332336 0.35464693
[49] -1.32938513 0.83250260 -0.69777123 2.42800497 1.21362516 -1.37883034
[55] 2.22334479 1.04612756 -0.53327682 -0.92567558 -0.67010863 0.41815463
[61] -1.31750362 -0.87356087 -0.36431782 -0.84089773 1.31806115 1.68464962
[67] -0.91644710 -0.13346570 -1.41111854 0.10396208 0.52884384 -0.84412478
[73] -3.14219827 -0.52660621 -0.59716545 -0.30772474 -0.32523454 -0.31474113
[79] 0.53910240 -0.60799165 -0.09813716 0.10477499 1.37131547 -1.70925136
[85] -0.46315006 -0.19600860 -1.04938418 -0.44740410 -0.94608214 0.03595400
[91] -0.53009640 -0.57711077 0.13060191 0.16053422 -1.16517332 -0.56049016
[97] -0.47785020 1.47914959 -0.18497656 1.30345466
> colSums(tmp)
[1] -0.71470446 0.70001490 -0.44626354 -1.11281309 -1.14460516 -1.35727430
[7] 1.49470576 -0.49219706 -0.82774134 -0.72189051 -1.10330295 -1.59950617
[13] 0.59967661 0.23168036 1.27634294 0.21807110 -0.87772261 1.62338004
[19] -1.34829015 0.61634221 -0.77168362 0.78285652 1.23304746 0.95583103
[25] -0.10188292 0.61876213 1.09231463 -0.56959710 2.60679932 -1.18765690
[31] 0.22632097 -0.12116766 -0.52821244 0.37338552 0.69193561 0.16012456
[37] 1.67119787 -0.05011250 1.54957475 -0.10250732 -0.22079978 0.59957639
[43] -0.92718684 -1.78947784 -0.51985377 -0.51562036 0.15332336 0.35464693
[49] -1.32938513 0.83250260 -0.69777123 2.42800497 1.21362516 -1.37883034
[55] 2.22334479 1.04612756 -0.53327682 -0.92567558 -0.67010863 0.41815463
[61] -1.31750362 -0.87356087 -0.36431782 -0.84089773 1.31806115 1.68464962
[67] -0.91644710 -0.13346570 -1.41111854 0.10396208 0.52884384 -0.84412478
[73] -3.14219827 -0.52660621 -0.59716545 -0.30772474 -0.32523454 -0.31474113
[79] 0.53910240 -0.60799165 -0.09813716 0.10477499 1.37131547 -1.70925136
[85] -0.46315006 -0.19600860 -1.04938418 -0.44740410 -0.94608214 0.03595400
[91] -0.53009640 -0.57711077 0.13060191 0.16053422 -1.16517332 -0.56049016
[97] -0.47785020 1.47914959 -0.18497656 1.30345466
> 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] -0.71470446 0.70001490 -0.44626354 -1.11281309 -1.14460516 -1.35727430
[7] 1.49470576 -0.49219706 -0.82774134 -0.72189051 -1.10330295 -1.59950617
[13] 0.59967661 0.23168036 1.27634294 0.21807110 -0.87772261 1.62338004
[19] -1.34829015 0.61634221 -0.77168362 0.78285652 1.23304746 0.95583103
[25] -0.10188292 0.61876213 1.09231463 -0.56959710 2.60679932 -1.18765690
[31] 0.22632097 -0.12116766 -0.52821244 0.37338552 0.69193561 0.16012456
[37] 1.67119787 -0.05011250 1.54957475 -0.10250732 -0.22079978 0.59957639
[43] -0.92718684 -1.78947784 -0.51985377 -0.51562036 0.15332336 0.35464693
[49] -1.32938513 0.83250260 -0.69777123 2.42800497 1.21362516 -1.37883034
[55] 2.22334479 1.04612756 -0.53327682 -0.92567558 -0.67010863 0.41815463
[61] -1.31750362 -0.87356087 -0.36431782 -0.84089773 1.31806115 1.68464962
[67] -0.91644710 -0.13346570 -1.41111854 0.10396208 0.52884384 -0.84412478
[73] -3.14219827 -0.52660621 -0.59716545 -0.30772474 -0.32523454 -0.31474113
[79] 0.53910240 -0.60799165 -0.09813716 0.10477499 1.37131547 -1.70925136
[85] -0.46315006 -0.19600860 -1.04938418 -0.44740410 -0.94608214 0.03595400
[91] -0.53009640 -0.57711077 0.13060191 0.16053422 -1.16517332 -0.56049016
[97] -0.47785020 1.47914959 -0.18497656 1.30345466
> colMin(tmp)
[1] -0.71470446 0.70001490 -0.44626354 -1.11281309 -1.14460516 -1.35727430
[7] 1.49470576 -0.49219706 -0.82774134 -0.72189051 -1.10330295 -1.59950617
[13] 0.59967661 0.23168036 1.27634294 0.21807110 -0.87772261 1.62338004
[19] -1.34829015 0.61634221 -0.77168362 0.78285652 1.23304746 0.95583103
[25] -0.10188292 0.61876213 1.09231463 -0.56959710 2.60679932 -1.18765690
[31] 0.22632097 -0.12116766 -0.52821244 0.37338552 0.69193561 0.16012456
[37] 1.67119787 -0.05011250 1.54957475 -0.10250732 -0.22079978 0.59957639
[43] -0.92718684 -1.78947784 -0.51985377 -0.51562036 0.15332336 0.35464693
[49] -1.32938513 0.83250260 -0.69777123 2.42800497 1.21362516 -1.37883034
[55] 2.22334479 1.04612756 -0.53327682 -0.92567558 -0.67010863 0.41815463
[61] -1.31750362 -0.87356087 -0.36431782 -0.84089773 1.31806115 1.68464962
[67] -0.91644710 -0.13346570 -1.41111854 0.10396208 0.52884384 -0.84412478
[73] -3.14219827 -0.52660621 -0.59716545 -0.30772474 -0.32523454 -0.31474113
[79] 0.53910240 -0.60799165 -0.09813716 0.10477499 1.37131547 -1.70925136
[85] -0.46315006 -0.19600860 -1.04938418 -0.44740410 -0.94608214 0.03595400
[91] -0.53009640 -0.57711077 0.13060191 0.16053422 -1.16517332 -0.56049016
[97] -0.47785020 1.47914959 -0.18497656 1.30345466
> colMedians(tmp)
[1] -0.71470446 0.70001490 -0.44626354 -1.11281309 -1.14460516 -1.35727430
[7] 1.49470576 -0.49219706 -0.82774134 -0.72189051 -1.10330295 -1.59950617
[13] 0.59967661 0.23168036 1.27634294 0.21807110 -0.87772261 1.62338004
[19] -1.34829015 0.61634221 -0.77168362 0.78285652 1.23304746 0.95583103
[25] -0.10188292 0.61876213 1.09231463 -0.56959710 2.60679932 -1.18765690
[31] 0.22632097 -0.12116766 -0.52821244 0.37338552 0.69193561 0.16012456
[37] 1.67119787 -0.05011250 1.54957475 -0.10250732 -0.22079978 0.59957639
[43] -0.92718684 -1.78947784 -0.51985377 -0.51562036 0.15332336 0.35464693
[49] -1.32938513 0.83250260 -0.69777123 2.42800497 1.21362516 -1.37883034
[55] 2.22334479 1.04612756 -0.53327682 -0.92567558 -0.67010863 0.41815463
[61] -1.31750362 -0.87356087 -0.36431782 -0.84089773 1.31806115 1.68464962
[67] -0.91644710 -0.13346570 -1.41111854 0.10396208 0.52884384 -0.84412478
[73] -3.14219827 -0.52660621 -0.59716545 -0.30772474 -0.32523454 -0.31474113
[79] 0.53910240 -0.60799165 -0.09813716 0.10477499 1.37131547 -1.70925136
[85] -0.46315006 -0.19600860 -1.04938418 -0.44740410 -0.94608214 0.03595400
[91] -0.53009640 -0.57711077 0.13060191 0.16053422 -1.16517332 -0.56049016
[97] -0.47785020 1.47914959 -0.18497656 1.30345466
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.7147045 0.7000149 -0.4462635 -1.112813 -1.144605 -1.357274 1.494706
[2,] -0.7147045 0.7000149 -0.4462635 -1.112813 -1.144605 -1.357274 1.494706
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.4921971 -0.8277413 -0.7218905 -1.103303 -1.599506 0.5996766 0.2316804
[2,] -0.4921971 -0.8277413 -0.7218905 -1.103303 -1.599506 0.5996766 0.2316804
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.276343 0.2180711 -0.8777226 1.62338 -1.34829 0.6163422 -0.7716836
[2,] 1.276343 0.2180711 -0.8777226 1.62338 -1.34829 0.6163422 -0.7716836
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.7828565 1.233047 0.955831 -0.1018829 0.6187621 1.092315 -0.5695971
[2,] 0.7828565 1.233047 0.955831 -0.1018829 0.6187621 1.092315 -0.5695971
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 2.606799 -1.187657 0.226321 -0.1211677 -0.5282124 0.3733855 0.6919356
[2,] 2.606799 -1.187657 0.226321 -0.1211677 -0.5282124 0.3733855 0.6919356
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.1601246 1.671198 -0.0501125 1.549575 -0.1025073 -0.2207998 0.5995764
[2,] 0.1601246 1.671198 -0.0501125 1.549575 -0.1025073 -0.2207998 0.5995764
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.9271868 -1.789478 -0.5198538 -0.5156204 0.1533234 0.3546469 -1.329385
[2,] -0.9271868 -1.789478 -0.5198538 -0.5156204 0.1533234 0.3546469 -1.329385
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.8325026 -0.6977712 2.428005 1.213625 -1.37883 2.223345 1.046128
[2,] 0.8325026 -0.6977712 2.428005 1.213625 -1.37883 2.223345 1.046128
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5332768 -0.9256756 -0.6701086 0.4181546 -1.317504 -0.8735609 -0.3643178
[2,] -0.5332768 -0.9256756 -0.6701086 0.4181546 -1.317504 -0.8735609 -0.3643178
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.8408977 1.318061 1.68465 -0.9164471 -0.1334657 -1.411119 0.1039621
[2,] -0.8408977 1.318061 1.68465 -0.9164471 -0.1334657 -1.411119 0.1039621
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.5288438 -0.8441248 -3.142198 -0.5266062 -0.5971655 -0.3077247 -0.3252345
[2,] 0.5288438 -0.8441248 -3.142198 -0.5266062 -0.5971655 -0.3077247 -0.3252345
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.3147411 0.5391024 -0.6079916 -0.09813716 0.104775 1.371315 -1.709251
[2,] -0.3147411 0.5391024 -0.6079916 -0.09813716 0.104775 1.371315 -1.709251
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.4631501 -0.1960086 -1.049384 -0.4474041 -0.9460821 0.035954 -0.5300964
[2,] -0.4631501 -0.1960086 -1.049384 -0.4474041 -0.9460821 0.035954 -0.5300964
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.5771108 0.1306019 0.1605342 -1.165173 -0.5604902 -0.4778502 1.47915
[2,] -0.5771108 0.1306019 0.1605342 -1.165173 -0.5604902 -0.4778502 1.47915
[,99] [,100]
[1,] -0.1849766 1.303455
[2,] -0.1849766 1.303455
>
>
> Max(tmp2)
[1] 1.780184
> Min(tmp2)
[1] -2.86367
> mean(tmp2)
[1] -0.1427147
> Sum(tmp2)
[1] -14.27147
> Var(tmp2)
[1] 0.8411097
>
> rowMeans(tmp2)
[1] 0.58951044 -0.37323464 -1.62930542 -0.16993301 0.67620798 0.37695676
[7] -1.36222458 -1.19453067 -0.18255474 -0.84973479 -0.70977238 -0.63793578
[13] 0.85482436 -0.07003026 0.38301013 -0.06019994 -0.72276486 -0.72365173
[19] -1.22844205 -0.16024434 1.09524037 -0.44726214 0.67749026 -1.17520324
[25] -2.67360525 1.28309223 0.51431366 0.82223499 -1.84496634 -0.11593921
[31] 0.25148235 -1.08104429 -0.62413067 -1.56421634 0.93730169 0.76226028
[37] -1.42815881 -1.26878978 1.32925522 -0.15693794 0.88929088 -0.60098490
[43] 0.10954557 -1.47892470 -0.34682858 0.72064457 -1.34938048 -1.54111400
[49] -1.20680742 0.30690923 -1.25336702 -0.49269231 0.28701985 0.72683679
[55] -0.29286881 -0.51096425 -0.71563276 0.87951048 0.47172459 -0.91679206
[61] 0.97482404 0.39538877 0.93261228 -2.86367025 0.01663558 -1.32067608
[67] -0.18094276 0.33117547 0.02497147 1.02780728 -0.34558304 -0.13823644
[73] -0.60098285 1.10259388 0.20519138 0.80317529 0.18879345 0.25261706
[79] 0.52369556 1.62051315 -1.89421455 -0.63382390 0.25493142 0.32590690
[85] -0.61351634 -0.26123546 0.99575346 -0.30622809 0.87902699 -0.94150398
[91] 0.97872361 -0.08333497 0.05863446 0.23120019 0.20652888 -0.48327446
[97] -0.12076221 1.78018415 -0.11019585 0.73233115
> rowSums(tmp2)
[1] 0.58951044 -0.37323464 -1.62930542 -0.16993301 0.67620798 0.37695676
[7] -1.36222458 -1.19453067 -0.18255474 -0.84973479 -0.70977238 -0.63793578
[13] 0.85482436 -0.07003026 0.38301013 -0.06019994 -0.72276486 -0.72365173
[19] -1.22844205 -0.16024434 1.09524037 -0.44726214 0.67749026 -1.17520324
[25] -2.67360525 1.28309223 0.51431366 0.82223499 -1.84496634 -0.11593921
[31] 0.25148235 -1.08104429 -0.62413067 -1.56421634 0.93730169 0.76226028
[37] -1.42815881 -1.26878978 1.32925522 -0.15693794 0.88929088 -0.60098490
[43] 0.10954557 -1.47892470 -0.34682858 0.72064457 -1.34938048 -1.54111400
[49] -1.20680742 0.30690923 -1.25336702 -0.49269231 0.28701985 0.72683679
[55] -0.29286881 -0.51096425 -0.71563276 0.87951048 0.47172459 -0.91679206
[61] 0.97482404 0.39538877 0.93261228 -2.86367025 0.01663558 -1.32067608
[67] -0.18094276 0.33117547 0.02497147 1.02780728 -0.34558304 -0.13823644
[73] -0.60098285 1.10259388 0.20519138 0.80317529 0.18879345 0.25261706
[79] 0.52369556 1.62051315 -1.89421455 -0.63382390 0.25493142 0.32590690
[85] -0.61351634 -0.26123546 0.99575346 -0.30622809 0.87902699 -0.94150398
[91] 0.97872361 -0.08333497 0.05863446 0.23120019 0.20652888 -0.48327446
[97] -0.12076221 1.78018415 -0.11019585 0.73233115
> 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] 0.58951044 -0.37323464 -1.62930542 -0.16993301 0.67620798 0.37695676
[7] -1.36222458 -1.19453067 -0.18255474 -0.84973479 -0.70977238 -0.63793578
[13] 0.85482436 -0.07003026 0.38301013 -0.06019994 -0.72276486 -0.72365173
[19] -1.22844205 -0.16024434 1.09524037 -0.44726214 0.67749026 -1.17520324
[25] -2.67360525 1.28309223 0.51431366 0.82223499 -1.84496634 -0.11593921
[31] 0.25148235 -1.08104429 -0.62413067 -1.56421634 0.93730169 0.76226028
[37] -1.42815881 -1.26878978 1.32925522 -0.15693794 0.88929088 -0.60098490
[43] 0.10954557 -1.47892470 -0.34682858 0.72064457 -1.34938048 -1.54111400
[49] -1.20680742 0.30690923 -1.25336702 -0.49269231 0.28701985 0.72683679
[55] -0.29286881 -0.51096425 -0.71563276 0.87951048 0.47172459 -0.91679206
[61] 0.97482404 0.39538877 0.93261228 -2.86367025 0.01663558 -1.32067608
[67] -0.18094276 0.33117547 0.02497147 1.02780728 -0.34558304 -0.13823644
[73] -0.60098285 1.10259388 0.20519138 0.80317529 0.18879345 0.25261706
[79] 0.52369556 1.62051315 -1.89421455 -0.63382390 0.25493142 0.32590690
[85] -0.61351634 -0.26123546 0.99575346 -0.30622809 0.87902699 -0.94150398
[91] 0.97872361 -0.08333497 0.05863446 0.23120019 0.20652888 -0.48327446
[97] -0.12076221 1.78018415 -0.11019585 0.73233115
> rowMin(tmp2)
[1] 0.58951044 -0.37323464 -1.62930542 -0.16993301 0.67620798 0.37695676
[7] -1.36222458 -1.19453067 -0.18255474 -0.84973479 -0.70977238 -0.63793578
[13] 0.85482436 -0.07003026 0.38301013 -0.06019994 -0.72276486 -0.72365173
[19] -1.22844205 -0.16024434 1.09524037 -0.44726214 0.67749026 -1.17520324
[25] -2.67360525 1.28309223 0.51431366 0.82223499 -1.84496634 -0.11593921
[31] 0.25148235 -1.08104429 -0.62413067 -1.56421634 0.93730169 0.76226028
[37] -1.42815881 -1.26878978 1.32925522 -0.15693794 0.88929088 -0.60098490
[43] 0.10954557 -1.47892470 -0.34682858 0.72064457 -1.34938048 -1.54111400
[49] -1.20680742 0.30690923 -1.25336702 -0.49269231 0.28701985 0.72683679
[55] -0.29286881 -0.51096425 -0.71563276 0.87951048 0.47172459 -0.91679206
[61] 0.97482404 0.39538877 0.93261228 -2.86367025 0.01663558 -1.32067608
[67] -0.18094276 0.33117547 0.02497147 1.02780728 -0.34558304 -0.13823644
[73] -0.60098285 1.10259388 0.20519138 0.80317529 0.18879345 0.25261706
[79] 0.52369556 1.62051315 -1.89421455 -0.63382390 0.25493142 0.32590690
[85] -0.61351634 -0.26123546 0.99575346 -0.30622809 0.87902699 -0.94150398
[91] 0.97872361 -0.08333497 0.05863446 0.23120019 0.20652888 -0.48327446
[97] -0.12076221 1.78018415 -0.11019585 0.73233115
>
> colMeans(tmp2)
[1] -0.1427147
> colSums(tmp2)
[1] -14.27147
> colVars(tmp2)
[1] 0.8411097
> colSd(tmp2)
[1] 0.9171203
> colMax(tmp2)
[1] 1.780184
> colMin(tmp2)
[1] -2.86367
> colMedians(tmp2)
[1] -0.1130675
> colRanges(tmp2)
[,1]
[1,] -2.863670
[2,] 1.780184
>
> 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] -0.7216773 1.1363688 3.0669378 2.9016383 -5.3267083 -0.6376581
[7] -7.1355847 -0.5065442 -3.9794739 -5.9222380
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.85022713
[2,] -0.81061435
[3,] 0.04122488
[4,] 0.71055583
[5,] 1.16590647
>
> rowApply(tmp,sum)
[1] -4.4068401 -3.1484043 -1.6286052 4.5392537 9.6438502 -8.0103696
[7] 0.5428209 -3.9507539 -8.6234832 -2.0824082
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 2 8 7 6 10 2 9 7 5
[2,] 6 8 6 2 10 9 8 5 6 10
[3,] 9 7 4 6 9 7 4 7 10 6
[4,] 8 9 9 8 2 2 6 6 2 9
[5,] 2 5 3 3 1 8 9 10 9 1
[6,] 5 6 10 5 5 1 5 3 3 7
[7,] 3 10 2 1 4 6 1 2 4 3
[8,] 10 3 7 4 8 3 10 4 1 8
[9,] 4 1 1 9 7 5 3 8 8 4
[10,] 1 4 5 10 3 4 7 1 5 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.17630698 2.12199351 -1.34098826 -0.29433459 2.54313271 0.97719692
[7] -0.76963923 -5.15658514 2.34716859 -1.94130261 -2.68808455 0.26544764
[13] 1.24109415 -0.44135957 0.21363225 0.06386764 1.62074317 3.18972877
[19] -1.28116938 0.04193244
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7422527
[2,] -0.8879333
[3,] -0.8437428
[4,] 0.1167914
[5,] 0.1808304
>
> rowApply(tmp,sum)
[1] 3.3458696 -5.7963489 2.7415224 -3.1408936 0.3860179
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 5 1 3 11
[2,] 9 20 3 15 18
[3,] 11 3 17 1 16
[4,] 2 14 11 7 17
[5,] 16 12 18 17 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1808304 0.1176537 0.1974527 -1.0099311 0.94053961 1.08308398
[2,] -0.8879333 1.7461302 -1.1565572 0.3058129 -0.08588657 -0.54015601
[3,] -1.7422527 -1.0304702 0.7972577 0.2884122 0.96145469 0.71183870
[4,] -0.8437428 0.3183097 -1.7899183 -0.5692992 0.48594836 0.02131185
[5,] 0.1167914 0.9703702 0.6107768 0.6906707 0.24107661 -0.29888159
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8156293 -0.6992269 1.1178172 -0.6452709 -0.2456775 -0.03499508
[2,] 0.3315650 -2.4052216 -0.1251231 -0.5111999 -2.4288938 -0.85513902
[3,] 0.4027725 -0.4414628 1.4799670 -0.3677378 0.2118718 0.73631357
[4,] -0.4798106 -0.1798497 0.2457016 0.2431840 -0.7570118 -0.08723274
[5,] -1.8397955 -1.4308242 -0.3711941 -0.6602779 0.5316267 0.50650091
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.2519967 -1.96101416 0.34760187 1.65757611 1.36232949 0.7888580
[2,] 0.4674071 -0.78602227 -0.06322189 -0.09417242 0.39837207 1.4160456
[3,] -0.5308223 0.08984498 -0.09878953 0.49084097 0.09361960 0.6027923
[4,] 1.4109230 0.66546992 0.46246932 -0.63967395 -0.28965256 1.0091529
[5,] 0.1455831 1.55036196 -0.43442752 -1.35070306 0.05607457 -0.6271200
[,19] [,20]
[1,] -0.91477316 0.4993828
[2,] -0.93273791 0.4105831
[3,] 1.17721127 -1.0911395
[4,] -0.70509477 -1.6620777
[5,] 0.09422519 1.8851838
>
>
> 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 1.48207 -1.212258 0.6664302 0.5850595 1.082707 1.297491 -1.059092
col8 col9 col10 col11 col12 col13 col14
row1 -0.1331005 -0.8496735 -1.806747 -0.8959516 0.09297655 -0.6723235 -1.193669
col15 col16 col17 col18 col19 col20
row1 -0.3906416 0.4688942 -0.07478797 -0.4078538 -2.22779 0.3423722
> tmp[,"col10"]
col10
row1 -1.80674660
row2 -2.08515897
row3 0.06970212
row4 1.01194562
row5 -0.67739003
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.4820700 -1.2122580 0.6664302 0.5850595 1.0827072 1.297491 -1.0590915
row5 0.3807811 0.4732917 -0.8216711 -0.1171487 0.5477887 1.298563 0.8381681
col8 col9 col10 col11 col12 col13
row1 -0.1331005 -0.84967351 -1.806747 -0.89595165 0.09297655 -0.6723235
row5 -2.1160146 0.05844622 -0.677390 0.06255367 -0.98253454 1.1256519
col14 col15 col16 col17 col18 col19
row1 -1.1936687 -0.3906416 0.4688942 -0.07478797 -0.4078538 -2.2277897
row5 0.5101198 0.3228397 1.0560973 -1.38162723 -0.3998564 0.5711117
col20
row1 0.3423722
row5 -0.4352250
> tmp[,c("col6","col20")]
col6 col20
row1 1.29749133 0.3423722
row2 0.01793526 1.0637263
row3 0.54752638 1.8692462
row4 0.91409592 0.5372683
row5 1.29856294 -0.4352250
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.297491 0.3423722
row5 1.298563 -0.4352250
>
>
>
>
> 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 50.62285 51.14878 50.60107 50.16133 49.48363 105.6354 49.2682 49.88029
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.03836 50.7919 49.19842 48.49073 52.33099 49.71079 49.33771 50.44021
col17 col18 col19 col20
row1 50.60796 50.42268 49.04801 105.114
> tmp[,"col10"]
col10
row1 50.79190
row2 29.51146
row3 29.80683
row4 28.96829
row5 49.49721
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.62285 51.14878 50.60107 50.16133 49.48363 105.6354 49.26820 49.88029
row5 49.86891 51.46985 50.20768 49.91732 49.72609 105.9332 50.15548 49.72172
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.03836 50.79190 49.19842 48.49073 52.33099 49.71079 49.33771 50.44021
row5 49.04695 49.49721 49.01429 49.33989 49.82849 48.72586 48.43323 49.47624
col17 col18 col19 col20
row1 50.60796 50.42268 49.04801 105.114
row5 50.75341 50.42345 50.52711 107.612
> tmp[,c("col6","col20")]
col6 col20
row1 105.63540 105.11402
row2 75.16742 73.81009
row3 76.49731 77.31160
row4 75.42321 75.51176
row5 105.93317 107.61203
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6354 105.114
row5 105.9332 107.612
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6354 105.114
row5 105.9332 107.612
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.07495827
[2,] -1.37418830
[3,] -1.04025889
[4,] 0.54349752
[5,] 0.35223818
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.6512731 -0.1996069
[2,] 0.3536319 -0.1801748
[3,] 1.6529969 0.5860229
[4,] 1.9428700 -1.0034291
[5,] 1.5981580 0.9959518
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.3942578 -0.3695561
[2,] -0.1951262 0.2996669
[3,] -1.1872283 1.0477059
[4,] 0.1492372 -0.5778347
[5,] -2.2139131 1.9513158
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.3942578
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.3942578
[2,] -0.1951262
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.6198479 -0.1791093 -0.11693702 -1.4625620 -1.321955 1.213826 2.024562
row1 1.9001089 1.7380773 0.04522493 0.9262466 2.243568 -1.046906 -2.420646
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.05291239 0.73207001 0.4023319 -1.7156238 -0.2383853 1.3395922
row1 -0.22164103 -0.02321567 0.1600006 -0.5894054 -1.1076339 -0.5649042
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.5877333 -0.5980269 -0.3110978 -0.4137742 -1.3235438 -0.2749783
row1 0.2835414 1.1895977 0.7599833 -1.2391290 0.4242296 -1.2905022
[,20]
row3 0.9508931
row1 -1.3655808
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.3279614 -0.1662032 1.094762 1.965185 0.01478922 -1.787844 0.3712717
[,8] [,9] [,10]
row2 -1.584647 -0.2229894 0.00112505
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.4694176 0.5792198 -0.2765778 -1.459538 0.1032366 -0.9759258 -0.1185845
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.309587 -1.115515 -1.334141 -0.1955085 -1.16852 -0.5992967 0.6851573
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.3172675 1.677514 -0.3638809 -0.9303406 -1.118583 0.3953411
>
>
> 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: 0x60f5e27db200>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a12a3150c"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a558e6974"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a62d8921"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a7078bf74"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a252555da"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a735d172"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a704997c7"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a467a72a"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a19ff0b43"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a24089562"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a19e18d8f"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a36bc098"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a2c02fbb4"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a45b76fc5"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM23e98a41744ba4"
>
>
> ### 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: 0x60f5e4643690>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60f5e4643690>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60f5e4643690>
> rowMedians(tmp)
[1] -0.7783284125 0.1749435702 -0.0859146165 0.4210599132 0.6885288808
[6] -0.1495180364 -0.5780948815 -0.0119550606 -0.3930534927 -0.1936925028
[11] 0.5637028953 0.3610789157 -0.0027433860 0.7100470764 -0.3335855177
[16] 0.1014198828 -0.0196058442 -0.3220963773 -0.0111011395 0.0352097736
[21] -0.1721962051 -0.1182442921 0.4813433077 -0.0325353310 -0.6222921596
[26] 0.2447641827 0.0132910981 -0.4261957421 -0.2159138796 -0.0850082019
[31] 0.3957093502 0.2425544162 0.2769742243 -0.2861034143 -0.1585998600
[36] -0.5127619794 -0.3195325378 -0.2907810713 0.2097034677 0.0789587877
[41] -0.1631687252 0.3107998551 -0.0003501191 0.7271407222 0.2175336232
[46] -0.1284190506 -0.0437307618 -0.2744506251 -0.3416625647 0.2059746315
[51] -0.1258327615 0.3101272923 0.0684534408 0.0980716817 0.2152282765
[56] 0.2296459930 -0.0430148237 0.1636026296 0.5288214757 -0.1259161373
[61] -0.8173424609 0.7121911292 -0.3118206279 0.0372447856 0.2949015977
[66] -0.2933588962 0.0578292877 0.0072847127 -0.1764897239 0.3618820151
[71] 0.2076174363 -0.0060768755 0.4971175223 -0.1031681808 -0.1244175911
[76] -0.0417342029 -0.0987443672 -0.0856780994 0.3423512258 0.3299713879
[81] 0.0449413914 -0.3621103083 0.2508152411 -0.0322211998 0.0220477995
[86] 0.3078357353 -0.0086038742 0.0986931287 0.3541705690 0.0070554022
[91] 0.2644291527 -0.2139400952 0.0170345966 0.1710294190 0.2426086371
[96] 0.1782816590 -0.2404518428 0.3100214556 -0.1094920466 -0.3651165923
[101] 0.3423710948 -0.1810665159 -0.0348592457 0.0878804283 0.3502483585
[106] -0.3456305798 -0.0333257201 -0.1364919342 -0.0516246737 0.3247013527
[111] -0.4642450719 0.1570487729 -0.3505225953 -0.2488341324 -0.1235990699
[116] 0.2716162730 0.2599752769 -0.1879136814 0.4602654800 -0.1679540338
[121] -0.2077898195 -0.5395983609 0.6288980588 -0.5371191536 0.1103097794
[126] -0.4507518355 -0.3159178559 -0.1642837637 0.1773228065 0.3550958157
[131] 0.1173909039 0.1101596232 -0.0861344066 0.2403932428 0.4982320127
[136] 0.3486939760 0.7120079947 0.1282985104 0.2245215950 0.3296510743
[141] -0.1257027655 0.1197674362 -0.0217510766 0.3337058640 0.1229190635
[146] 0.2387270008 -0.2851065816 -0.0508363066 0.2257735898 -0.1346138549
[151] 0.1156384688 -0.0071036742 -0.2012214915 -0.1859547712 -0.3996910552
[156] -0.1562256245 -0.1887275748 0.0375325394 -0.0709719704 0.3725033127
[161] 0.0781018671 0.0596768777 -0.5839517904 0.0247667051 0.1374183360
[166] 0.3477795669 -0.5226627938 -0.0923780558 0.1362339913 0.2378659286
[171] 0.1845236436 0.0327165508 -0.4733550569 -0.3471846537 -0.0400398873
[176] 0.0944639935 0.1408531249 0.0085477859 -0.2913703066 0.0053805145
[181] -0.0862474332 0.3847606707 0.6151849804 -0.3213414384 -0.5033726655
[186] -0.1219170930 -0.2226481609 -0.1016703866 -0.0832900771 -0.0712511725
[191] -0.1207603265 0.2989064165 0.7427597476 -0.4611233618 0.0442026694
[196] -0.0284389904 0.5972454265 0.1080520264 0.1591905325 -0.0968036020
[201] -0.2572278031 0.2728735897 -0.6419672525 -0.0404087110 -0.2297805641
[206] -0.1822311405 0.6285411941 0.3274126140 0.8357008267 -0.0272698000
[211] 0.0398104212 -0.3113952160 -0.7056909836 0.2630961772 -0.1311279584
[216] 0.4429081469 0.1932908578 0.1571014058 -0.0371609655 0.0624304919
[221] 0.2724943382 0.3716708148 0.0979797607 0.0955172230 0.3166977467
[226] 0.2345633622 -0.7039121184 0.5584458010 -0.0497314022 0.3077675476
>
> proc.time()
user system elapsed
1.287 1.491 2.766
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 alpha (2026-04-05 r89794)
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: 0x5f92d0a64ff0>
> .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: 0x5f92d0a64ff0>
> .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: 0x5f92d0a64ff0>
> .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: 0x5f92d0a64ff0>
> 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: 0x5f92d0683a60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d0683a60>
> .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: 0x5f92d0683a60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d0683a60>
> .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: 0x5f92d0683a60>
> 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: 0x5f92d03e9240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d03e9240>
> .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: 0x5f92d03e9240>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5f92d03e9240>
> .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: 0x5f92d03e9240>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5f92d03e9240>
> .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: 0x5f92d03e9240>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5f92d03e9240>
> .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: 0x5f92d03e9240>
> 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: 0x5f92d142a160>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5f92d142a160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d142a160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d142a160>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile23ebb45127f421" "BufferedMatrixFile23ebb458a7c9b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile23ebb45127f421" "BufferedMatrixFile23ebb458a7c9b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d169bd20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d169bd20>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5f92d169bd20>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5f92d169bd20>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5f92d169bd20>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5f92d169bd20>
> .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: 0x5f92d18cd390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f92d18cd390>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5f92d18cd390>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5f92d18cd390>
> 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: 0x5f92d2ba77c0>
> .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: 0x5f92d2ba77c0>
> rm(P)
>
> proc.time()
user system elapsed
0.264 0.050 0.300
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 alpha (2026-04-05 r89794)
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.
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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
0.232 0.055 0.277