Ben Bolstad
| Snapshot Date: 2026-04-10 13:40 -0400 (Fri, 10 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 2026-04-11 11:36 -0400 (Sat, 11 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) | 4919 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 alpha (2026-04-08 r89818) | 4631 |
| 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 259/2390 | 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 | | ||||||||
| 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: 2026-04-10 21:53:12 -0400 (Fri, 10 Apr 2026) |
| EndedAt: 2026-04-10 21:53:37 -0400 (Fri, 10 Apr 2026) |
| EllapsedTime: 25.1 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 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: 2026-04-11 01:53:12 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
0.240 0.051 0.283
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 10 21:53:27 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 10 21:53:27 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: 0x55c4f515fa60>
>
>
>
> 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 10 21:53:28 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 10 21:53:28 2026"
>
> ColMode(tmp2)
<pointer: 0x55c4f515fa60>
>
>
>
> ### 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,] 99.82730655 -0.8660476 1.062396 0.7966277
[2,] 0.08368788 -0.4982609 1.057959 0.2781171
[3,] -2.68476420 -0.3195006 -2.418700 1.3385687
[4,] 0.08444834 -0.5661042 1.051958 -0.8403893
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.82730655 0.8660476 1.062396 0.7966277
[2,] 0.08368788 0.4982609 1.057959 0.2781171
[3,] 2.68476420 0.3195006 2.418700 1.3385687
[4,] 0.08444834 0.5661042 1.051958 0.8403893
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9913616 0.9306168 1.030726 0.8925400
[2,] 0.2892886 0.7058760 1.028571 0.5273681
[3,] 1.6385250 0.5652439 1.555217 1.1569653
[4,] 0.2906000 0.7523989 1.025650 0.9167275
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.74092 35.17222 36.36965 34.72203
[2,] 27.97657 32.55702 36.34367 30.55180
[3,] 44.07001 30.97194 42.97087 37.90822
[4,] 27.99045 33.09009 36.30846 35.00766
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55c4f5e2d5c0>
> exp(tmp5)
<pointer: 0x55c4f5e2d5c0>
> log(tmp5,2)
<pointer: 0x55c4f5e2d5c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.7688
> Min(tmp5)
[1] 53.44182
> mean(tmp5)
[1] 72.63085
> Sum(tmp5)
[1] 14526.17
> Var(tmp5)
[1] 859.3725
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 97.11045 66.84254 70.60446 70.79947 69.98300 69.99970 70.25680 70.53460
[9] 70.48105 69.69639
> rowSums(tmp5)
[1] 1942.209 1336.851 1412.089 1415.989 1399.660 1399.994 1405.136 1410.692
[9] 1409.621 1393.928
> rowVars(tmp5)
[1] 7664.39816 29.39638 100.45744 106.73892 58.83303 38.22167
[7] 59.39114 110.68202 64.16824 55.44371
> rowSd(tmp5)
[1] 87.546549 5.421842 10.022846 10.331453 7.670269 6.182368 7.706565
[8] 10.520552 8.010508 7.446053
> rowMax(tmp5)
[1] 467.76878 75.79481 91.72596 86.85541 86.22563 80.71668 84.05536
[8] 91.18377 87.73670 86.15086
> rowMin(tmp5)
[1] 66.72450 57.69780 57.99574 53.89561 57.59949 56.63247 57.42134 53.44182
[9] 57.44709 56.97660
>
> colMeans(tmp5)
[1] 108.56581 67.18030 74.34840 71.91534 69.76994 70.64438 72.92766
[8] 70.48847 71.79768 68.22332 71.58049 73.19764 68.29981 74.53754
[15] 73.18505 71.12793 68.42097 71.33887 66.71697 68.35038
> colSums(tmp5)
[1] 1085.6581 671.8030 743.4840 719.1534 697.6994 706.4438 729.2766
[8] 704.8847 717.9768 682.2332 715.8049 731.9764 682.9981 745.3754
[15] 731.8505 711.2793 684.2097 713.3887 667.1697 683.5038
> colVars(tmp5)
[1] 16041.63550 62.15939 68.60305 40.94014 92.86762 52.08022
[7] 45.24961 87.97118 40.82362 36.92184 63.93650 98.06545
[13] 93.08980 156.11905 54.89736 62.43617 86.58166 102.88089
[19] 51.29103 40.36035
> colSd(tmp5)
[1] 126.655578 7.884123 8.282696 6.398448 9.636785 7.216663
[7] 6.726783 9.379295 6.389336 6.076334 7.996030 9.902800
[13] 9.648306 12.494761 7.409275 7.901656 9.304927 10.143022
[19] 7.161776 6.352979
> colMax(tmp5)
[1] 467.76878 84.05536 89.43823 80.14502 81.49887 81.89776 82.39078
[8] 87.73670 86.21347 76.60310 82.40974 91.18377 86.75846 91.54883
[15] 83.51204 86.22563 87.42291 95.08358 81.49374 80.10382
> colMin(tmp5)
[1] 57.34120 56.63247 61.48798 60.88694 53.89561 57.42134 63.64177 58.43211
[9] 63.73525 55.32171 60.36946 57.44709 56.97660 53.44182 59.22595 59.61472
[17] 57.59949 60.08353 57.24487 61.27705
>
>
> ### 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] 97.11045 66.84254 70.60446 70.79947 NA 69.99970 70.25680 70.53460
[9] 70.48105 69.69639
> rowSums(tmp5)
[1] 1942.209 1336.851 1412.089 1415.989 NA 1399.994 1405.136 1410.692
[9] 1409.621 1393.928
> rowVars(tmp5)
[1] 7664.39816 29.39638 100.45744 106.73892 60.64217 38.22167
[7] 59.39114 110.68202 64.16824 55.44371
> rowSd(tmp5)
[1] 87.546549 5.421842 10.022846 10.331453 7.787308 6.182368 7.706565
[8] 10.520552 8.010508 7.446053
> rowMax(tmp5)
[1] 467.76878 75.79481 91.72596 86.85541 NA 80.71668 84.05536
[8] 91.18377 87.73670 86.15086
> rowMin(tmp5)
[1] 66.72450 57.69780 57.99574 53.89561 NA 56.63247 57.42134 53.44182
[9] 57.44709 56.97660
>
> colMeans(tmp5)
[1] 108.56581 67.18030 74.34840 71.91534 69.76994 70.64438 72.92766
[8] 70.48847 71.79768 68.22332 71.58049 73.19764 68.29981 74.53754
[15] 73.18505 71.12793 68.42097 71.33887 NA 68.35038
> colSums(tmp5)
[1] 1085.6581 671.8030 743.4840 719.1534 697.6994 706.4438 729.2766
[8] 704.8847 717.9768 682.2332 715.8049 731.9764 682.9981 745.3754
[15] 731.8505 711.2793 684.2097 713.3887 NA 683.5038
> colVars(tmp5)
[1] 16041.63550 62.15939 68.60305 40.94014 92.86762 52.08022
[7] 45.24961 87.97118 40.82362 36.92184 63.93650 98.06545
[13] 93.08980 156.11905 54.89736 62.43617 86.58166 102.88089
[19] NA 40.36035
> colSd(tmp5)
[1] 126.655578 7.884123 8.282696 6.398448 9.636785 7.216663
[7] 6.726783 9.379295 6.389336 6.076334 7.996030 9.902800
[13] 9.648306 12.494761 7.409275 7.901656 9.304927 10.143022
[19] NA 6.352979
> colMax(tmp5)
[1] 467.76878 84.05536 89.43823 80.14502 81.49887 81.89776 82.39078
[8] 87.73670 86.21347 76.60310 82.40974 91.18377 86.75846 91.54883
[15] 83.51204 86.22563 87.42291 95.08358 NA 80.10382
> colMin(tmp5)
[1] 57.34120 56.63247 61.48798 60.88694 53.89561 57.42134 63.64177 58.43211
[9] 63.73525 55.32171 60.36946 57.44709 56.97660 53.44182 59.22595 59.61472
[17] 57.59949 60.08353 NA 61.27705
>
> Max(tmp5,na.rm=TRUE)
[1] 467.7688
> Min(tmp5,na.rm=TRUE)
[1] 53.44182
> mean(tmp5,na.rm=TRUE)
[1] 72.66926
> Sum(tmp5,na.rm=TRUE)
[1] 14461.18
> Var(tmp5,na.rm=TRUE)
[1] 863.4163
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 97.11045 66.84254 70.60446 70.79947 70.24592 69.99970 70.25680 70.53460
[9] 70.48105 69.69639
> rowSums(tmp5,na.rm=TRUE)
[1] 1942.209 1336.851 1412.089 1415.989 1334.673 1399.994 1405.136 1410.692
[9] 1409.621 1393.928
> rowVars(tmp5,na.rm=TRUE)
[1] 7664.39816 29.39638 100.45744 106.73892 60.64217 38.22167
[7] 59.39114 110.68202 64.16824 55.44371
> rowSd(tmp5,na.rm=TRUE)
[1] 87.546549 5.421842 10.022846 10.331453 7.787308 6.182368 7.706565
[8] 10.520552 8.010508 7.446053
> rowMax(tmp5,na.rm=TRUE)
[1] 467.76878 75.79481 91.72596 86.85541 86.22563 80.71668 84.05536
[8] 91.18377 87.73670 86.15086
> rowMin(tmp5,na.rm=TRUE)
[1] 66.72450 57.69780 57.99574 53.89561 57.59949 56.63247 57.42134 53.44182
[9] 57.44709 56.97660
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.56581 67.18030 74.34840 71.91534 69.76994 70.64438 72.92766
[8] 70.48847 71.79768 68.22332 71.58049 73.19764 68.29981 74.53754
[15] 73.18505 71.12793 68.42097 71.33887 66.90913 68.35038
> colSums(tmp5,na.rm=TRUE)
[1] 1085.6581 671.8030 743.4840 719.1534 697.6994 706.4438 729.2766
[8] 704.8847 717.9768 682.2332 715.8049 731.9764 682.9981 745.3754
[15] 731.8505 711.2793 684.2097 713.3887 602.1822 683.5038
> colVars(tmp5,na.rm=TRUE)
[1] 16041.63550 62.15939 68.60305 40.94014 92.86762 52.08022
[7] 45.24961 87.97118 40.82362 36.92184 63.93650 98.06545
[13] 93.08980 156.11905 54.89736 62.43617 86.58166 102.88089
[19] 57.28698 40.36035
> colSd(tmp5,na.rm=TRUE)
[1] 126.655578 7.884123 8.282696 6.398448 9.636785 7.216663
[7] 6.726783 9.379295 6.389336 6.076334 7.996030 9.902800
[13] 9.648306 12.494761 7.409275 7.901656 9.304927 10.143022
[19] 7.568816 6.352979
> colMax(tmp5,na.rm=TRUE)
[1] 467.76878 84.05536 89.43823 80.14502 81.49887 81.89776 82.39078
[8] 87.73670 86.21347 76.60310 82.40974 91.18377 86.75846 91.54883
[15] 83.51204 86.22563 87.42291 95.08358 81.49374 80.10382
> colMin(tmp5,na.rm=TRUE)
[1] 57.34120 56.63247 61.48798 60.88694 53.89561 57.42134 63.64177 58.43211
[9] 63.73525 55.32171 60.36946 57.44709 56.97660 53.44182 59.22595 59.61472
[17] 57.59949 60.08353 57.24487 61.27705
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 97.11045 66.84254 70.60446 70.79947 NaN 69.99970 70.25680 70.53460
[9] 70.48105 69.69639
> rowSums(tmp5,na.rm=TRUE)
[1] 1942.209 1336.851 1412.089 1415.989 0.000 1399.994 1405.136 1410.692
[9] 1409.621 1393.928
> rowVars(tmp5,na.rm=TRUE)
[1] 7664.39816 29.39638 100.45744 106.73892 NA 38.22167
[7] 59.39114 110.68202 64.16824 55.44371
> rowSd(tmp5,na.rm=TRUE)
[1] 87.546549 5.421842 10.022846 10.331453 NA 6.182368 7.706565
[8] 10.520552 8.010508 7.446053
> rowMax(tmp5,na.rm=TRUE)
[1] 467.76878 75.79481 91.72596 86.85541 NA 80.71668 84.05536
[8] 91.18377 87.73670 86.15086
> rowMin(tmp5,na.rm=TRUE)
[1] 66.72450 57.69780 57.99574 53.89561 NA 56.63247 57.42134 53.44182
[9] 57.44709 56.97660
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.92566 67.46904 75.05239 71.20847 70.41502 70.79190 71.87620
[8] 71.06035 71.89081 67.29223 72.29645 73.31876 68.79844 74.17900
[15] 73.57420 69.45040 69.62336 72.23292 NaN 69.13631
> colSums(tmp5,na.rm=TRUE)
[1] 1007.3310 607.2214 675.4716 640.8762 633.7352 637.1271 646.8858
[8] 639.5432 647.0173 605.6301 650.6680 659.8688 619.1860 667.6110
[15] 662.1678 625.0536 626.6102 650.0963 0.0000 622.2268
> colVars(tmp5,na.rm=TRUE)
[1] 17919.84346 68.99137 71.60285 40.43641 99.79454 58.34541
[7] 38.46823 95.28829 45.82900 31.78418 66.16192 110.15860
[13] 101.92890 174.18775 60.05588 38.58229 81.13985 106.74860
[19] NA 38.45650
> colSd(tmp5,na.rm=TRUE)
[1] 133.865020 8.306104 8.461847 6.358963 9.989722 7.638417
[7] 6.202277 9.761572 6.769712 5.637746 8.133998 10.495647
[13] 10.095984 13.198021 7.749573 6.211464 9.007766 10.331922
[19] NA 6.201331
> colMax(tmp5,na.rm=TRUE)
[1] 467.76878 84.05536 89.43823 80.14502 81.49887 81.89776 81.30740
[8] 87.73670 86.21347 74.31511 82.40974 91.18377 86.75846 91.54883
[15] 83.51204 76.52524 87.42291 95.08358 -Inf 80.10382
> colMin(tmp5,na.rm=TRUE)
[1] 57.34120 56.63247 61.48798 60.88694 53.89561 57.42134 63.64177 58.43211
[9] 63.73525 55.32171 60.36946 57.44709 56.97660 53.44182 59.22595 59.61472
[17] 60.77637 60.08353 Inf 61.75204
>
>
>
>
> 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] 224.6500 256.9155 125.5406 151.5096 310.4845 271.9704 296.0046 314.3688
[9] 262.9673 297.1223
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 224.6500 256.9155 125.5406 151.5096 310.4845 271.9704 296.0046 314.3688
[9] 262.9673 297.1223
>
>
>
> 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 5.684342e-14 -5.684342e-14 -5.684342e-14
[6] 0.000000e+00 0.000000e+00 2.273737e-13 4.973799e-14 -1.705303e-13
[11] 8.526513e-14 0.000000e+00 2.842171e-14 5.684342e-14 -5.684342e-14
[16] 1.136868e-13 -8.526513e-14 1.705303e-13 8.526513e-14 -2.842171e-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)
+ }
2 16
7 8
4 8
1 3
10 4
3 20
8 10
6 12
2 8
1 17
5 13
10 6
7 14
6 12
10 15
9 9
10 6
2 10
1 1
1 14
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] 2.558567
> Min(tmp)
[1] -2.999348
> mean(tmp)
[1] -0.001303227
> Sum(tmp)
[1] -0.1303227
> Var(tmp)
[1] 1.094587
>
> rowMeans(tmp)
[1] -0.001303227
> rowSums(tmp)
[1] -0.1303227
> rowVars(tmp)
[1] 1.094587
> rowSd(tmp)
[1] 1.046225
> rowMax(tmp)
[1] 2.558567
> rowMin(tmp)
[1] -2.999348
>
> colMeans(tmp)
[1] 0.039910445 1.641970949 -1.077199779 0.356511674 -2.999347844
[6] 0.223726355 0.228069779 1.055845402 0.761424393 -0.176996640
[11] -0.258787354 -2.726770776 -0.057583732 -0.033786140 -1.062106361
[16] -0.303216831 -0.947335573 0.993898872 0.014613443 -0.029750400
[21] -0.567621518 -0.364301477 0.544281366 -2.109942814 -0.406158352
[26] -0.838048663 1.099820749 0.016139545 -1.047160494 -0.310717718
[31] -1.614428595 0.515358648 1.361728788 0.411082099 -0.009720984
[36] -0.669704579 0.221247338 -1.450947969 -0.494312390 -1.637647424
[41] 0.094680407 -0.362758372 -1.303619036 0.507357049 1.022017442
[46] 1.430404464 0.419598968 -0.833318646 0.714108772 2.230847905
[51] 0.825348199 -0.995178046 0.180172845 1.102969795 -1.756736374
[56] 0.911813210 -0.048908154 0.774428630 0.777389679 1.047457659
[61] -0.073469163 -0.039776364 0.019632731 0.064365256 -0.129167197
[66] 0.906539278 -0.394531062 -1.089377707 1.819507857 0.267806194
[71] -0.524300456 0.331774498 -0.989440643 2.558566580 1.950986569
[76] 1.727011364 -0.830817186 -0.706694945 -1.437759778 -0.462005944
[81] 0.914765289 0.780759439 -1.523456688 -0.146582503 0.192544508
[86] 1.324196713 -0.767310814 0.748717187 -0.337363173 -0.976368788
[91] 0.608781588 -1.136398965 -0.722309721 0.527271329 1.553171228
[96] 0.938930871 -0.085404352 1.886262577 -0.374396717 -1.535093463
> colSums(tmp)
[1] 0.039910445 1.641970949 -1.077199779 0.356511674 -2.999347844
[6] 0.223726355 0.228069779 1.055845402 0.761424393 -0.176996640
[11] -0.258787354 -2.726770776 -0.057583732 -0.033786140 -1.062106361
[16] -0.303216831 -0.947335573 0.993898872 0.014613443 -0.029750400
[21] -0.567621518 -0.364301477 0.544281366 -2.109942814 -0.406158352
[26] -0.838048663 1.099820749 0.016139545 -1.047160494 -0.310717718
[31] -1.614428595 0.515358648 1.361728788 0.411082099 -0.009720984
[36] -0.669704579 0.221247338 -1.450947969 -0.494312390 -1.637647424
[41] 0.094680407 -0.362758372 -1.303619036 0.507357049 1.022017442
[46] 1.430404464 0.419598968 -0.833318646 0.714108772 2.230847905
[51] 0.825348199 -0.995178046 0.180172845 1.102969795 -1.756736374
[56] 0.911813210 -0.048908154 0.774428630 0.777389679 1.047457659
[61] -0.073469163 -0.039776364 0.019632731 0.064365256 -0.129167197
[66] 0.906539278 -0.394531062 -1.089377707 1.819507857 0.267806194
[71] -0.524300456 0.331774498 -0.989440643 2.558566580 1.950986569
[76] 1.727011364 -0.830817186 -0.706694945 -1.437759778 -0.462005944
[81] 0.914765289 0.780759439 -1.523456688 -0.146582503 0.192544508
[86] 1.324196713 -0.767310814 0.748717187 -0.337363173 -0.976368788
[91] 0.608781588 -1.136398965 -0.722309721 0.527271329 1.553171228
[96] 0.938930871 -0.085404352 1.886262577 -0.374396717 -1.535093463
> 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] 0.039910445 1.641970949 -1.077199779 0.356511674 -2.999347844
[6] 0.223726355 0.228069779 1.055845402 0.761424393 -0.176996640
[11] -0.258787354 -2.726770776 -0.057583732 -0.033786140 -1.062106361
[16] -0.303216831 -0.947335573 0.993898872 0.014613443 -0.029750400
[21] -0.567621518 -0.364301477 0.544281366 -2.109942814 -0.406158352
[26] -0.838048663 1.099820749 0.016139545 -1.047160494 -0.310717718
[31] -1.614428595 0.515358648 1.361728788 0.411082099 -0.009720984
[36] -0.669704579 0.221247338 -1.450947969 -0.494312390 -1.637647424
[41] 0.094680407 -0.362758372 -1.303619036 0.507357049 1.022017442
[46] 1.430404464 0.419598968 -0.833318646 0.714108772 2.230847905
[51] 0.825348199 -0.995178046 0.180172845 1.102969795 -1.756736374
[56] 0.911813210 -0.048908154 0.774428630 0.777389679 1.047457659
[61] -0.073469163 -0.039776364 0.019632731 0.064365256 -0.129167197
[66] 0.906539278 -0.394531062 -1.089377707 1.819507857 0.267806194
[71] -0.524300456 0.331774498 -0.989440643 2.558566580 1.950986569
[76] 1.727011364 -0.830817186 -0.706694945 -1.437759778 -0.462005944
[81] 0.914765289 0.780759439 -1.523456688 -0.146582503 0.192544508
[86] 1.324196713 -0.767310814 0.748717187 -0.337363173 -0.976368788
[91] 0.608781588 -1.136398965 -0.722309721 0.527271329 1.553171228
[96] 0.938930871 -0.085404352 1.886262577 -0.374396717 -1.535093463
> colMin(tmp)
[1] 0.039910445 1.641970949 -1.077199779 0.356511674 -2.999347844
[6] 0.223726355 0.228069779 1.055845402 0.761424393 -0.176996640
[11] -0.258787354 -2.726770776 -0.057583732 -0.033786140 -1.062106361
[16] -0.303216831 -0.947335573 0.993898872 0.014613443 -0.029750400
[21] -0.567621518 -0.364301477 0.544281366 -2.109942814 -0.406158352
[26] -0.838048663 1.099820749 0.016139545 -1.047160494 -0.310717718
[31] -1.614428595 0.515358648 1.361728788 0.411082099 -0.009720984
[36] -0.669704579 0.221247338 -1.450947969 -0.494312390 -1.637647424
[41] 0.094680407 -0.362758372 -1.303619036 0.507357049 1.022017442
[46] 1.430404464 0.419598968 -0.833318646 0.714108772 2.230847905
[51] 0.825348199 -0.995178046 0.180172845 1.102969795 -1.756736374
[56] 0.911813210 -0.048908154 0.774428630 0.777389679 1.047457659
[61] -0.073469163 -0.039776364 0.019632731 0.064365256 -0.129167197
[66] 0.906539278 -0.394531062 -1.089377707 1.819507857 0.267806194
[71] -0.524300456 0.331774498 -0.989440643 2.558566580 1.950986569
[76] 1.727011364 -0.830817186 -0.706694945 -1.437759778 -0.462005944
[81] 0.914765289 0.780759439 -1.523456688 -0.146582503 0.192544508
[86] 1.324196713 -0.767310814 0.748717187 -0.337363173 -0.976368788
[91] 0.608781588 -1.136398965 -0.722309721 0.527271329 1.553171228
[96] 0.938930871 -0.085404352 1.886262577 -0.374396717 -1.535093463
> colMedians(tmp)
[1] 0.039910445 1.641970949 -1.077199779 0.356511674 -2.999347844
[6] 0.223726355 0.228069779 1.055845402 0.761424393 -0.176996640
[11] -0.258787354 -2.726770776 -0.057583732 -0.033786140 -1.062106361
[16] -0.303216831 -0.947335573 0.993898872 0.014613443 -0.029750400
[21] -0.567621518 -0.364301477 0.544281366 -2.109942814 -0.406158352
[26] -0.838048663 1.099820749 0.016139545 -1.047160494 -0.310717718
[31] -1.614428595 0.515358648 1.361728788 0.411082099 -0.009720984
[36] -0.669704579 0.221247338 -1.450947969 -0.494312390 -1.637647424
[41] 0.094680407 -0.362758372 -1.303619036 0.507357049 1.022017442
[46] 1.430404464 0.419598968 -0.833318646 0.714108772 2.230847905
[51] 0.825348199 -0.995178046 0.180172845 1.102969795 -1.756736374
[56] 0.911813210 -0.048908154 0.774428630 0.777389679 1.047457659
[61] -0.073469163 -0.039776364 0.019632731 0.064365256 -0.129167197
[66] 0.906539278 -0.394531062 -1.089377707 1.819507857 0.267806194
[71] -0.524300456 0.331774498 -0.989440643 2.558566580 1.950986569
[76] 1.727011364 -0.830817186 -0.706694945 -1.437759778 -0.462005944
[81] 0.914765289 0.780759439 -1.523456688 -0.146582503 0.192544508
[86] 1.324196713 -0.767310814 0.748717187 -0.337363173 -0.976368788
[91] 0.608781588 -1.136398965 -0.722309721 0.527271329 1.553171228
[96] 0.938930871 -0.085404352 1.886262577 -0.374396717 -1.535093463
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.03991044 1.641971 -1.0772 0.3565117 -2.999348 0.2237264 0.2280698
[2,] 0.03991044 1.641971 -1.0772 0.3565117 -2.999348 0.2237264 0.2280698
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.055845 0.7614244 -0.1769966 -0.2587874 -2.726771 -0.05758373 -0.03378614
[2,] 1.055845 0.7614244 -0.1769966 -0.2587874 -2.726771 -0.05758373 -0.03378614
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.062106 -0.3032168 -0.9473356 0.9938989 0.01461344 -0.0297504 -0.5676215
[2,] -1.062106 -0.3032168 -0.9473356 0.9938989 0.01461344 -0.0297504 -0.5676215
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.3643015 0.5442814 -2.109943 -0.4061584 -0.8380487 1.099821 0.01613954
[2,] -0.3643015 0.5442814 -2.109943 -0.4061584 -0.8380487 1.099821 0.01613954
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.04716 -0.3107177 -1.614429 0.5153586 1.361729 0.4110821 -0.009720984
[2,] -1.04716 -0.3107177 -1.614429 0.5153586 1.361729 0.4110821 -0.009720984
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.6697046 0.2212473 -1.450948 -0.4943124 -1.637647 0.09468041 -0.3627584
[2,] -0.6697046 0.2212473 -1.450948 -0.4943124 -1.637647 0.09468041 -0.3627584
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.303619 0.507357 1.022017 1.430404 0.419599 -0.8333186 0.7141088
[2,] -1.303619 0.507357 1.022017 1.430404 0.419599 -0.8333186 0.7141088
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 2.230848 0.8253482 -0.995178 0.1801728 1.10297 -1.756736 0.9118132
[2,] 2.230848 0.8253482 -0.995178 0.1801728 1.10297 -1.756736 0.9118132
[,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.04890815 0.7744286 0.7773897 1.047458 -0.07346916 -0.03977636
[2,] -0.04890815 0.7744286 0.7773897 1.047458 -0.07346916 -0.03977636
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.01963273 0.06436526 -0.1291672 0.9065393 -0.3945311 -1.089378 1.819508
[2,] 0.01963273 0.06436526 -0.1291672 0.9065393 -0.3945311 -1.089378 1.819508
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.2678062 -0.5243005 0.3317745 -0.9894406 2.558567 1.950987 1.727011
[2,] 0.2678062 -0.5243005 0.3317745 -0.9894406 2.558567 1.950987 1.727011
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.8308172 -0.7066949 -1.43776 -0.4620059 0.9147653 0.7807594 -1.523457
[2,] -0.8308172 -0.7066949 -1.43776 -0.4620059 0.9147653 0.7807594 -1.523457
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.1465825 0.1925445 1.324197 -0.7673108 0.7487172 -0.3373632 -0.9763688
[2,] -0.1465825 0.1925445 1.324197 -0.7673108 0.7487172 -0.3373632 -0.9763688
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.6087816 -1.136399 -0.7223097 0.5272713 1.553171 0.9389309 -0.08540435
[2,] 0.6087816 -1.136399 -0.7223097 0.5272713 1.553171 0.9389309 -0.08540435
[,98] [,99] [,100]
[1,] 1.886263 -0.3743967 -1.535093
[2,] 1.886263 -0.3743967 -1.535093
>
>
> Max(tmp2)
[1] 2.521394
> Min(tmp2)
[1] -2.352232
> mean(tmp2)
[1] 0.09795351
> Sum(tmp2)
[1] 9.795351
> Var(tmp2)
[1] 1.244041
>
> rowMeans(tmp2)
[1] -0.20444672 0.43459707 -2.03718082 0.64194944 1.14939807 0.03853779
[7] 0.05387479 0.78545105 0.29413506 0.45344681 0.28279876 -0.18553269
[13] -1.40677666 1.52442750 -0.89584186 -0.70740566 -0.20093426 1.14858550
[19] -0.21302393 -0.80154443 0.68821641 0.46623239 1.67775389 -0.83187158
[25] -0.64105930 0.91939201 1.72787373 2.23717342 0.97190766 0.77256664
[31] 1.56557907 0.75106869 1.39831465 -0.09983795 0.19571756 0.32794871
[37] 0.97369666 1.14163839 0.27898220 0.05927078 -0.91416267 1.90399272
[43] -1.17951904 -2.35223240 1.99499811 -0.52295645 0.92658326 -0.39177141
[49] -0.90064088 1.42316049 -0.76654105 -1.84928185 -1.13596210 -1.44548258
[55] -1.72275944 -1.79318718 -1.08893532 0.27603650 0.82671314 -0.29182213
[61] 0.94160626 -0.27481426 0.19953607 0.46066031 -1.70528687 2.29661042
[67] 0.38507414 0.87436108 1.74136354 -0.74088947 -1.23566761 -0.29681475
[73] -0.12628971 -0.00255645 2.52139369 -0.15176592 0.75607306 -0.96766106
[79] -0.33564840 -0.45622622 1.35758019 2.01591147 -0.45081947 -1.03218568
[85] 1.82812245 -1.37469976 -0.24039882 0.32837099 -0.20306487 -1.23957841
[91] -1.93720596 -0.01444010 -0.12146178 0.07770797 -0.32483925 0.56520514
[97] -1.35763473 1.31588713 2.17459910 -1.18607130
> rowSums(tmp2)
[1] -0.20444672 0.43459707 -2.03718082 0.64194944 1.14939807 0.03853779
[7] 0.05387479 0.78545105 0.29413506 0.45344681 0.28279876 -0.18553269
[13] -1.40677666 1.52442750 -0.89584186 -0.70740566 -0.20093426 1.14858550
[19] -0.21302393 -0.80154443 0.68821641 0.46623239 1.67775389 -0.83187158
[25] -0.64105930 0.91939201 1.72787373 2.23717342 0.97190766 0.77256664
[31] 1.56557907 0.75106869 1.39831465 -0.09983795 0.19571756 0.32794871
[37] 0.97369666 1.14163839 0.27898220 0.05927078 -0.91416267 1.90399272
[43] -1.17951904 -2.35223240 1.99499811 -0.52295645 0.92658326 -0.39177141
[49] -0.90064088 1.42316049 -0.76654105 -1.84928185 -1.13596210 -1.44548258
[55] -1.72275944 -1.79318718 -1.08893532 0.27603650 0.82671314 -0.29182213
[61] 0.94160626 -0.27481426 0.19953607 0.46066031 -1.70528687 2.29661042
[67] 0.38507414 0.87436108 1.74136354 -0.74088947 -1.23566761 -0.29681475
[73] -0.12628971 -0.00255645 2.52139369 -0.15176592 0.75607306 -0.96766106
[79] -0.33564840 -0.45622622 1.35758019 2.01591147 -0.45081947 -1.03218568
[85] 1.82812245 -1.37469976 -0.24039882 0.32837099 -0.20306487 -1.23957841
[91] -1.93720596 -0.01444010 -0.12146178 0.07770797 -0.32483925 0.56520514
[97] -1.35763473 1.31588713 2.17459910 -1.18607130
> 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] -0.20444672 0.43459707 -2.03718082 0.64194944 1.14939807 0.03853779
[7] 0.05387479 0.78545105 0.29413506 0.45344681 0.28279876 -0.18553269
[13] -1.40677666 1.52442750 -0.89584186 -0.70740566 -0.20093426 1.14858550
[19] -0.21302393 -0.80154443 0.68821641 0.46623239 1.67775389 -0.83187158
[25] -0.64105930 0.91939201 1.72787373 2.23717342 0.97190766 0.77256664
[31] 1.56557907 0.75106869 1.39831465 -0.09983795 0.19571756 0.32794871
[37] 0.97369666 1.14163839 0.27898220 0.05927078 -0.91416267 1.90399272
[43] -1.17951904 -2.35223240 1.99499811 -0.52295645 0.92658326 -0.39177141
[49] -0.90064088 1.42316049 -0.76654105 -1.84928185 -1.13596210 -1.44548258
[55] -1.72275944 -1.79318718 -1.08893532 0.27603650 0.82671314 -0.29182213
[61] 0.94160626 -0.27481426 0.19953607 0.46066031 -1.70528687 2.29661042
[67] 0.38507414 0.87436108 1.74136354 -0.74088947 -1.23566761 -0.29681475
[73] -0.12628971 -0.00255645 2.52139369 -0.15176592 0.75607306 -0.96766106
[79] -0.33564840 -0.45622622 1.35758019 2.01591147 -0.45081947 -1.03218568
[85] 1.82812245 -1.37469976 -0.24039882 0.32837099 -0.20306487 -1.23957841
[91] -1.93720596 -0.01444010 -0.12146178 0.07770797 -0.32483925 0.56520514
[97] -1.35763473 1.31588713 2.17459910 -1.18607130
> rowMin(tmp2)
[1] -0.20444672 0.43459707 -2.03718082 0.64194944 1.14939807 0.03853779
[7] 0.05387479 0.78545105 0.29413506 0.45344681 0.28279876 -0.18553269
[13] -1.40677666 1.52442750 -0.89584186 -0.70740566 -0.20093426 1.14858550
[19] -0.21302393 -0.80154443 0.68821641 0.46623239 1.67775389 -0.83187158
[25] -0.64105930 0.91939201 1.72787373 2.23717342 0.97190766 0.77256664
[31] 1.56557907 0.75106869 1.39831465 -0.09983795 0.19571756 0.32794871
[37] 0.97369666 1.14163839 0.27898220 0.05927078 -0.91416267 1.90399272
[43] -1.17951904 -2.35223240 1.99499811 -0.52295645 0.92658326 -0.39177141
[49] -0.90064088 1.42316049 -0.76654105 -1.84928185 -1.13596210 -1.44548258
[55] -1.72275944 -1.79318718 -1.08893532 0.27603650 0.82671314 -0.29182213
[61] 0.94160626 -0.27481426 0.19953607 0.46066031 -1.70528687 2.29661042
[67] 0.38507414 0.87436108 1.74136354 -0.74088947 -1.23566761 -0.29681475
[73] -0.12628971 -0.00255645 2.52139369 -0.15176592 0.75607306 -0.96766106
[79] -0.33564840 -0.45622622 1.35758019 2.01591147 -0.45081947 -1.03218568
[85] 1.82812245 -1.37469976 -0.24039882 0.32837099 -0.20306487 -1.23957841
[91] -1.93720596 -0.01444010 -0.12146178 0.07770797 -0.32483925 0.56520514
[97] -1.35763473 1.31588713 2.17459910 -1.18607130
>
> colMeans(tmp2)
[1] 0.09795351
> colSums(tmp2)
[1] 9.795351
> colVars(tmp2)
[1] 1.244041
> colSd(tmp2)
[1] 1.115366
> colMax(tmp2)
[1] 2.521394
> colMin(tmp2)
[1] -2.352232
> colMedians(tmp2)
[1] 0.04620629
> colRanges(tmp2)
[,1]
[1,] -2.352232
[2,] 2.521394
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.3063896 2.4056414 -5.6154466 -1.3880640 2.5712517 -1.0993812
[7] -0.8104981 4.0394602 2.5680362 2.0803277
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.300697363
[2,] -1.030009078
[3,] -0.457433193
[4,] 0.008302311
[5,] 1.321703417
>
> rowApply(tmp,sum)
[1] -3.2804096 -0.1444451 3.4965147 -1.9144870 -4.0755825 1.3876825
[7] 0.9964198 -2.5875578 3.6532227 3.9135799
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 2 2 4 5 6 1 10 1 1
[2,] 5 7 5 2 10 8 4 4 3 9
[3,] 2 1 3 9 2 4 2 2 7 6
[4,] 7 4 10 10 4 2 3 1 5 3
[5,] 6 9 9 7 1 10 6 7 8 2
[6,] 3 10 7 5 3 5 8 3 2 4
[7,] 1 5 8 6 8 3 10 5 6 8
[8,] 10 6 1 3 6 9 7 9 10 5
[9,] 4 8 4 8 7 1 9 8 4 10
[10,] 9 3 6 1 9 7 5 6 9 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.82564596 -1.11947211 -0.89963347 1.95732389 -0.76481587 -3.36308318
[7] 1.62557750 -0.69852028 -0.85652243 -0.27830130 1.22346832 -0.58050234
[13] -0.73588157 -1.18047071 -1.12588635 -3.80532830 0.46973150 1.57820163
[19] 0.78023980 -0.02292189
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0420274
[2,] -0.4979955
[3,] -0.2534847
[4,] 0.1859207
[5,] 0.7819410
>
> rowApply(tmp,sum)
[1] -0.2135229 -7.7127453 1.8965438 1.5139367 -4.1066556
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 5 17 11 14
[2,] 3 9 14 6 17
[3,] 15 16 6 7 3
[4,] 13 19 4 16 19
[5,] 8 6 15 10 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.4979955 -0.7922435 0.2260242 0.003689371 -0.3359822 0.1266899
[2,] -1.0420274 -0.5918210 0.6030522 1.035819832 -0.9634109 -1.1547782
[3,] 0.7819410 0.3796649 -0.1698497 -0.851791721 0.4645692 -1.0631973
[4,] -0.2534847 -0.5843234 -0.4466533 0.844047675 -0.2755636 -0.6033691
[5,] 0.1859207 0.4692509 -1.1122069 0.925558731 0.3455715 -0.6684286
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8699827 -1.9047864 0.8007652 -0.07707281 -0.62969060 1.8827766
[2,] -0.4236565 -0.5100718 -2.2552924 0.60586517 -0.02226246 -1.5891698
[3,] 0.1782773 0.3637915 1.0924006 -0.34789646 1.55115634 0.3212295
[4,] 1.4033161 1.8508443 0.2169158 -0.28482396 0.70926467 -1.2364052
[5,] -0.4023421 -0.4982980 -0.7113116 -0.17437324 -0.38499962 0.0410666
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.2510466 1.3317527 -0.08341961 -0.58416686 1.604080 -0.7918901
[2,] -0.8500018 -0.9366253 0.65105483 -1.28191300 1.047364 -0.5672940
[3,] -0.9424179 0.0432692 0.91716708 -0.07131041 -1.470112 0.1231690
[4,] 1.6263067 -1.1693189 -0.99543775 -0.37803335 -0.966865 1.6436799
[5,] -0.3187220 -0.4495485 -1.61525090 -1.48990469 0.255265 1.1705368
[,19] [,20]
[1,] -0.3101724 -0.800817271
[2,] 0.4639316 0.068491968
[3,] 0.5082213 0.088262672
[4,] 0.4086266 0.005213279
[5,] -0.2903673 0.615927466
>
>
> 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 : 647 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 : 561 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.6036594 -1.376268 -2.193193 0.5881531 0.03944998 -0.6236264 1.451595
col8 col9 col10 col11 col12 col13 col14
row1 -0.137259 0.267864 -0.250041 1.455299 -0.5210189 -0.1616293 0.3630463
col15 col16 col17 col18 col19 col20
row1 -1.216652 0.1439596 -0.3000133 1.381491 -1.653883 -0.1520449
> tmp[,"col10"]
col10
row1 -0.2500410
row2 1.3209262
row3 1.1274825
row4 -2.1439111
row5 -0.6074333
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.6036594 -1.376268 -2.193193 0.5881531 0.03944998 -0.6236264 1.4515948
row5 -0.3183696 -1.002643 1.144772 -0.3445024 -1.70183241 -0.4641786 0.7340548
col8 col9 col10 col11 col12 col13 col14
row1 -0.137259 0.267864 -0.2500410 1.4552991 -0.5210189 -0.1616293 0.36304628
row5 1.422120 -1.464666 -0.6074333 0.5165253 0.3194407 -0.1650361 -0.05083534
col15 col16 col17 col18 col19 col20
row1 -1.21665200 0.1439596 -0.3000133 1.3814909 -1.653883 -0.1520449
row5 0.04160984 0.7258851 -0.9788571 -0.5292029 -0.800253 0.1940746
> tmp[,c("col6","col20")]
col6 col20
row1 -0.62362643 -0.1520449
row2 -0.12705518 -0.2661587
row3 -1.12687951 0.4546905
row4 -0.09776231 0.8974844
row5 -0.46417860 0.1940746
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.6236264 -0.1520449
row5 -0.4641786 0.1940746
>
>
>
>
> 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 48.05153 51.15313 49.3433 48.68047 50.89336 107.6636 49.87991 50.64804
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.83111 49.06183 49.56205 49.86213 49.26066 49.01038 48.87791 47.9858
col17 col18 col19 col20
row1 49.72023 49.17938 51.1791 105.5462
> tmp[,"col10"]
col10
row1 49.06183
row2 29.19321
row3 30.06804
row4 30.10775
row5 48.31513
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.05153 51.15313 49.34330 48.68047 50.89336 107.6636 49.87991 50.64804
row5 48.80719 49.54249 50.46627 49.60960 50.97823 105.9444 51.76388 50.05736
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.83111 49.06183 49.56205 49.86213 49.26066 49.01038 48.87791 47.9858
row5 48.84847 48.31513 49.64784 50.72273 49.86827 53.09906 50.31634 48.8340
col17 col18 col19 col20
row1 49.72023 49.17938 51.1791 105.5462
row5 49.45714 50.10217 50.2991 105.3147
> tmp[,c("col6","col20")]
col6 col20
row1 107.66359 105.54617
row2 76.86717 75.26267
row3 75.34438 73.75968
row4 75.41544 72.45619
row5 105.94441 105.31468
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 107.6636 105.5462
row5 105.9444 105.3147
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 107.6636 105.5462
row5 105.9444 105.3147
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.2481226
[2,] 1.4442241
[3,] -0.8945745
[4,] -0.4323777
[5,] -1.3816686
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.3182090 1.8158705
[2,] 0.6949879 -0.1192570
[3,] 0.3758198 1.4344926
[4,] 0.5562525 -0.9550672
[5,] -0.6906027 0.2924535
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.2244440 1.5837388
[2,] 0.8887755 -1.3985307
[3,] -1.7332395 -1.3241482
[4,] -1.4975955 1.0408866
[5,] 0.6097940 0.5103932
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.224444
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.2244440
[2,] 0.8887755
>
>
>
> 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 0.2665782 0.7256644 -0.3713573 -1.170691 -0.8789944 -0.1810273
row1 -0.9985771 -1.5097807 -0.4589095 -0.195061 -1.1645860 1.1210758
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.7623367 2.1465818 0.7711573 -0.8879862 0.5344651 -1.1061358
row1 -0.2894521 -0.2875489 1.3441459 -0.5095852 -0.1986639 0.4069773
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -0.4523323 -0.006746692 0.3755927 1.1947895 -0.9132694 -0.4410023
row1 -0.1932041 0.827214599 -0.1444486 0.9631268 -0.1381405 0.5215314
[,19] [,20]
row3 0.6183302 -0.5661709
row1 -0.4296681 -1.1293863
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.114873 -1.084747 0.08013785 3.239997 -1.044082 -1.635339 1.375799
[,8] [,9] [,10]
row2 -0.510504 -0.1143795 -0.1842001
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9106096 3.211827 -1.028488 -1.049791 0.1955543 -0.826587 -0.147245
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.111277 -0.7131123 0.2648222 1.117293 -0.02197756 -0.5246328 2.095932
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2802812 -0.2079343 -0.6350064 1.164239 -0.3917756 1.062389
>
>
> 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: 0x55c4f663a110>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff822ff49a5d"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff82232439fa"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff8245c8b921"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff8254b94b"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff825212891d"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff82d7d53f6"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff827935bf75"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff821bc398c7"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff8275d38c8f"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff82351c3c7d"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff8264e27a77"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff824558d1be"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff823eeaca2d"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff826967823e"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5ff8226fa903b"
>
>
> ### 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: 0x55c4f6069050>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55c4f6069050>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55c4f6069050>
> rowMedians(tmp)
[1] 0.4600094454 -0.0026094142 0.2584444277 0.0135197859 0.1171828607
[6] 0.4354213576 -0.4983956051 0.1495076568 -0.3017726892 -0.5291708993
[11] -0.2437748674 0.4787232183 0.1315988023 0.4809581153 -0.3779926646
[16] -0.4078340765 -0.0718170795 -0.1904814639 0.4280459891 0.3157167853
[21] 0.0412104684 -0.0602471323 -0.9297847258 -0.1047599735 0.1488761932
[26] 0.0194294387 -0.2373425969 0.5020217329 -0.2670545275 0.6837695303
[31] 0.0845244471 0.0377624232 0.1594159207 -0.0535534419 -0.4441874242
[36] -0.0631106099 -0.1137155472 -0.0706187207 -0.6962235463 -0.0441816027
[41] 0.1164395333 0.0491523440 0.4537795080 -0.1972381326 -0.0372131264
[46] -0.1842793052 -0.2687895686 -0.3992201548 -0.1405110647 -0.0813937173
[51] 0.4035869162 0.1978363603 -0.0363679862 -0.7976030388 -0.1661702347
[56] -0.0844299378 0.1921632931 -0.2878180180 0.3972258877 -0.1342568713
[61] -0.2894475251 0.4809974317 1.0091871030 -0.4410964758 -0.2522105318
[66] 0.1563907346 -0.0455045772 0.1800660910 0.2556304273 -0.2157719319
[71] 0.1436473818 0.2075258828 -0.3403414481 0.1305962760 -0.0346604529
[76] 0.2365445024 -0.1197082748 0.4445071429 0.2879605132 -0.1449041061
[81] 0.2734430618 0.0933472839 -0.5662661783 -0.0144635333 0.0784485302
[86] -0.0953444966 0.0293552469 0.1440735678 -0.0031075944 -0.0009980077
[91] -0.5367279570 -0.2319557539 0.1797054456 -0.0264372127 0.0047221141
[96] -0.1341129846 0.1530881208 -0.4775236657 -0.0923687379 0.2000853939
[101] -0.7383814451 -0.3569371266 0.0602359835 0.0686053026 0.0395746520
[106] -0.4291712584 -0.2246847201 -0.1844369115 -0.4926057450 -0.2203806377
[111] -0.7655837333 0.2724552509 -0.2145108603 -0.1005053414 0.2181951979
[116] -0.5770505398 -0.2063776998 0.0848025862 -0.2031545758 -0.3896822745
[121] -0.2422052497 0.3443260428 0.1920372056 -0.0776690085 0.2215442263
[126] -0.1832468888 -0.0589318910 -0.3378606779 -0.0664940014 -0.3098569155
[131] -0.1058810819 -0.0560766508 0.2119381237 0.1729828006 -0.3980871562
[136] 0.5740084843 0.1750167052 0.0929227144 -0.1311886875 -0.2607104618
[141] 0.7855168423 -0.0246299868 0.0385195489 -0.1425433803 -0.5825975206
[146] -0.4321114506 -0.1443429787 -0.3294913713 -0.7488359754 0.4759643820
[151] 0.3146417479 0.0901283877 -0.1668267851 -0.3650061134 0.1340917287
[156] 0.1961888176 0.1259909831 -0.0797073360 -0.5333150433 -0.2735128898
[161] -0.4834513507 0.3257069883 -0.6595568638 0.0758668046 -0.0075778480
[166] 0.0192543868 0.2069724539 0.3851763214 0.0713241276 0.2576170197
[171] 0.4340860337 0.2737752308 -0.0365023813 -0.0598300631 0.6760935520
[176] 0.1003783200 -0.2724205212 -0.2322429318 -0.1786776076 0.0821978194
[181] -0.2664517631 -0.3536505459 -0.3234316975 -0.4080445403 -0.0636354640
[186] -0.5763905246 0.2489419002 0.4485185907 0.0256329021 0.2800612245
[191] 0.2876484845 0.0188047536 0.0845651086 -0.2116155443 -0.3804037586
[196] 0.2167920948 -0.4172237506 -0.0100350695 -0.1321788067 -0.1360033159
[201] -0.3097191361 0.1422669591 -0.1210531401 0.2435810167 -0.1535712578
[206] -0.0739402462 -0.4741352031 -0.2322286091 0.2053692762 0.5214754294
[211] -0.0691700497 -0.2336875633 -0.4583603581 -0.1345033099 -0.1705652841
[216] -0.4263221415 0.1185498870 0.0787319792 0.2494043015 0.3033263001
[221] -0.4905464360 0.0363780377 0.2824233921 -0.2839798206 0.3940984672
[226] 0.1456802267 -0.1029998284 -0.2715438382 0.0952779551 -0.5394412659
>
> proc.time()
user system elapsed
1.314 1.476 2.777
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: 0x6177caad9ff0>
> .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: 0x6177caad9ff0>
> .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: 0x6177caad9ff0>
> .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: 0x6177caad9ff0>
> 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: 0x6177ca6f8a60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177ca6f8a60>
> .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: 0x6177ca6f8a60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177ca6f8a60>
> .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: 0x6177ca6f8a60>
> 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: 0x6177ca45e240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177ca45e240>
> .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: 0x6177ca45e240>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6177ca45e240>
> .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: 0x6177ca45e240>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6177ca45e240>
> .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: 0x6177ca45e240>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6177ca45e240>
> .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: 0x6177ca45e240>
> 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: 0x6177cb49f160>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6177cb49f160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177cb49f160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177cb49f160>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile601f81a50026e" "BufferedMatrixFile601f83d5b549f"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile601f81a50026e" "BufferedMatrixFile601f83d5b549f"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177cb710d20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177cb710d20>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6177cb710d20>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6177cb710d20>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6177cb710d20>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6177cb710d20>
> .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: 0x6177cacdff50>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6177cacdff50>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6177cacdff50>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6177cacdff50>
> 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: 0x6177cc84fbe0>
> .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: 0x6177cc84fbe0>
> rm(P)
>
> proc.time()
user system elapsed
0.256 0.051 0.294
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.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.233 0.050 0.272