Ben Bolstad
| Snapshot Date: 2026-04-08 13:40 -0400 (Wed, 08 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 2026-04-09 11:35 -0400 (Thu, 09 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) | 4912 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-03-26 r89717) -- "Unsuffered Consequences" | 4623 |
| 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 258/2388 | 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: 2026-04-08 21:55:06 -0400 (Wed, 08 Apr 2026) |
| EndedAt: 2026-04-08 21:55:31 -0400 (Wed, 08 Apr 2026) |
| EllapsedTime: 25.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### 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: 2026-04-09 01:55:07 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
##############################################################################
##############################################################################
###
### 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 0.051 0.282
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] "Wed Apr 8 21:55:21 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 8 21:55:22 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: 0x5b94b4f04a60>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Apr 8 21:55:22 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 8 21:55:22 2026"
>
> ColMode(tmp2)
<pointer: 0x5b94b4f04a60>
>
>
>
> ### 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,] 102.22801838 -0.5479141 -0.61772721 -2.5743474
[2,] -0.54643275 -0.2566035 0.06297128 0.6299464
[3,] -0.02299227 -1.3669563 -1.61425764 -0.9066420
[4,] -1.45108536 0.8286448 0.53059993 0.5478683
> 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,] 102.22801838 0.5479141 0.61772721 2.5743474
[2,] 0.54643275 0.2566035 0.06297128 0.6299464
[3,] 0.02299227 1.3669563 1.61425764 0.9066420
[4,] 1.45108536 0.8286448 0.53059993 0.5478683
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.1107872 0.7402122 0.7859562 1.6044773
[2,] 0.7392109 0.5065605 0.2509408 0.7936916
[3,] 0.1516320 1.1691691 1.2705344 0.9521775
[4,] 1.2046100 0.9102993 0.7284229 0.7401813
>
> 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,] 228.33589 32.95004 33.47729 43.61912
[2,] 32.93854 30.32221 27.57238 33.56686
[3,] 26.53931 38.05865 39.31960 35.42842
[4,] 38.49719 34.93164 32.81483 32.94968
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5b94b4e85e20>
> exp(tmp5)
<pointer: 0x5b94b4e85e20>
> log(tmp5,2)
<pointer: 0x5b94b4e85e20>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 475.2512
> Min(tmp5)
[1] 54.01339
> mean(tmp5)
[1] 72.04052
> Sum(tmp5)
[1] 14408.1
> Var(tmp5)
[1] 888.1171
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.45803 70.73736 69.07863 70.17387 72.49686 68.01182 68.70412 71.59587
[9] 69.56013 69.58851
> rowSums(tmp5)
[1] 1809.161 1414.747 1381.573 1403.477 1449.937 1360.236 1374.082 1431.917
[9] 1391.203 1391.770
> rowVars(tmp5)
[1] 8267.00788 121.96546 51.77245 89.96485 60.98182 54.85048
[7] 49.59104 56.96217 60.69039 74.28965
> rowSd(tmp5)
[1] 90.923088 11.043797 7.195307 9.484980 7.809086 7.406111 7.042091
[8] 7.547328 7.790404 8.619144
> rowMax(tmp5)
[1] 475.25124 89.24057 81.83860 96.58106 88.49831 87.42483 82.55667
[8] 85.25241 82.93233 87.00318
> rowMin(tmp5)
[1] 56.93579 54.01339 55.23810 54.06954 55.75890 54.91435 58.18775 55.31388
[9] 56.52527 54.18193
>
> colMeans(tmp5)
[1] 111.70092 74.43260 70.36877 71.35342 67.76939 69.44271 71.18553
[8] 71.29739 71.22357 70.61787 70.30276 70.23722 69.43983 71.94598
[15] 70.88966 67.40847 66.54942 69.00578 67.51926 68.11981
> colSums(tmp5)
[1] 1117.0092 744.3260 703.6877 713.5342 677.6939 694.4271 711.8553
[8] 712.9739 712.2357 706.1787 703.0276 702.3722 694.3983 719.4598
[15] 708.8966 674.0847 665.4942 690.0578 675.1926 681.1981
> colVars(tmp5)
[1] 16383.25689 56.26949 64.38692 88.26196 101.19589 57.96476
[7] 74.16032 72.63004 60.07278 82.75329 112.19789 27.55397
[13] 80.99340 130.07032 73.45949 64.55504 35.00475 56.42000
[19] 37.08830 65.73570
> colSd(tmp5)
[1] 127.997097 7.501299 8.024146 9.394784 10.059617 7.613459
[7] 8.611639 8.522326 7.750663 9.096884 10.592350 5.249188
[13] 8.999633 11.404837 8.570851 8.034615 5.916481 7.511325
[19] 6.090017 8.107755
> colMax(tmp5)
[1] 475.25124 87.00318 82.93233 90.78748 89.24057 76.76937 85.25241
[8] 82.73922 81.23509 88.49831 87.42483 78.15124 85.16435 96.58106
[15] 83.50288 84.12089 75.91609 89.13397 79.59435 82.55667
> colMin(tmp5)
[1] 55.23810 63.11170 57.38829 58.18775 54.18193 56.93579 59.08298 54.01339
[9] 61.07696 58.64194 54.06954 62.87303 56.52527 55.31388 54.99511 55.75890
[17] 60.16011 63.47384 58.75493 54.91435
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.45803 70.73736 69.07863 70.17387 NA 68.01182 68.70412 71.59587
[9] 69.56013 69.58851
> rowSums(tmp5)
[1] 1809.161 1414.747 1381.573 1403.477 NA 1360.236 1374.082 1431.917
[9] 1391.203 1391.770
> rowVars(tmp5)
[1] 8267.00788 121.96546 51.77245 89.96485 58.05453 54.85048
[7] 49.59104 56.96217 60.69039 74.28965
> rowSd(tmp5)
[1] 90.923088 11.043797 7.195307 9.484980 7.619352 7.406111 7.042091
[8] 7.547328 7.790404 8.619144
> rowMax(tmp5)
[1] 475.25124 89.24057 81.83860 96.58106 NA 87.42483 82.55667
[8] 85.25241 82.93233 87.00318
> rowMin(tmp5)
[1] 56.93579 54.01339 55.23810 54.06954 NA 54.91435 58.18775 55.31388
[9] 56.52527 54.18193
>
> colMeans(tmp5)
[1] 111.70092 74.43260 70.36877 71.35342 67.76939 69.44271 71.18553
[8] 71.29739 71.22357 70.61787 70.30276 70.23722 69.43983 71.94598
[15] NA 67.40847 66.54942 69.00578 67.51926 68.11981
> colSums(tmp5)
[1] 1117.0092 744.3260 703.6877 713.5342 677.6939 694.4271 711.8553
[8] 712.9739 712.2357 706.1787 703.0276 702.3722 694.3983 719.4598
[15] NA 674.0847 665.4942 690.0578 675.1926 681.1981
> colVars(tmp5)
[1] 16383.25689 56.26949 64.38692 88.26196 101.19589 57.96476
[7] 74.16032 72.63004 60.07278 82.75329 112.19789 27.55397
[13] 80.99340 130.07032 NA 64.55504 35.00475 56.42000
[19] 37.08830 65.73570
> colSd(tmp5)
[1] 127.997097 7.501299 8.024146 9.394784 10.059617 7.613459
[7] 8.611639 8.522326 7.750663 9.096884 10.592350 5.249188
[13] 8.999633 11.404837 NA 8.034615 5.916481 7.511325
[19] 6.090017 8.107755
> colMax(tmp5)
[1] 475.25124 87.00318 82.93233 90.78748 89.24057 76.76937 85.25241
[8] 82.73922 81.23509 88.49831 87.42483 78.15124 85.16435 96.58106
[15] NA 84.12089 75.91609 89.13397 79.59435 82.55667
> colMin(tmp5)
[1] 55.23810 63.11170 57.38829 58.18775 54.18193 56.93579 59.08298 54.01339
[9] 61.07696 58.64194 54.06954 62.87303 56.52527 55.31388 NA 55.75890
[17] 60.16011 63.47384 58.75493 54.91435
>
> Max(tmp5,na.rm=TRUE)
[1] 475.2512
> Min(tmp5,na.rm=TRUE)
[1] 54.01339
> mean(tmp5,na.rm=TRUE)
[1] 71.986
> Sum(tmp5,na.rm=TRUE)
[1] 14325.21
> Var(tmp5,na.rm=TRUE)
[1] 892.0052
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.45803 70.73736 69.07863 70.17387 71.94992 68.01182 68.70412 71.59587
[9] 69.56013 69.58851
> rowSums(tmp5,na.rm=TRUE)
[1] 1809.161 1414.747 1381.573 1403.477 1367.048 1360.236 1374.082 1431.917
[9] 1391.203 1391.770
> rowVars(tmp5,na.rm=TRUE)
[1] 8267.00788 121.96546 51.77245 89.96485 58.05453 54.85048
[7] 49.59104 56.96217 60.69039 74.28965
> rowSd(tmp5,na.rm=TRUE)
[1] 90.923088 11.043797 7.195307 9.484980 7.619352 7.406111 7.042091
[8] 7.547328 7.790404 8.619144
> rowMax(tmp5,na.rm=TRUE)
[1] 475.25124 89.24057 81.83860 96.58106 88.49831 87.42483 82.55667
[8] 85.25241 82.93233 87.00318
> rowMin(tmp5,na.rm=TRUE)
[1] 56.93579 54.01339 55.23810 54.06954 55.75890 54.91435 58.18775 55.31388
[9] 56.52527 54.18193
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.70092 74.43260 70.36877 71.35342 67.76939 69.44271 71.18553
[8] 71.29739 71.22357 70.61787 70.30276 70.23722 69.43983 71.94598
[15] 69.55644 67.40847 66.54942 69.00578 67.51926 68.11981
> colSums(tmp5,na.rm=TRUE)
[1] 1117.0092 744.3260 703.6877 713.5342 677.6939 694.4271 711.8553
[8] 712.9739 712.2357 706.1787 703.0276 702.3722 694.3983 719.4598
[15] 626.0080 674.0847 665.4942 690.0578 675.1926 681.1981
> colVars(tmp5,na.rm=TRUE)
[1] 16383.25689 56.26949 64.38692 88.26196 101.19589 57.96476
[7] 74.16032 72.63004 60.07278 82.75329 112.19789 27.55397
[13] 80.99340 130.07032 62.64531 64.55504 35.00475 56.42000
[19] 37.08830 65.73570
> colSd(tmp5,na.rm=TRUE)
[1] 127.997097 7.501299 8.024146 9.394784 10.059617 7.613459
[7] 8.611639 8.522326 7.750663 9.096884 10.592350 5.249188
[13] 8.999633 11.404837 7.914879 8.034615 5.916481 7.511325
[19] 6.090017 8.107755
> colMax(tmp5,na.rm=TRUE)
[1] 475.25124 87.00318 82.93233 90.78748 89.24057 76.76937 85.25241
[8] 82.73922 81.23509 88.49831 87.42483 78.15124 85.16435 96.58106
[15] 83.50288 84.12089 75.91609 89.13397 79.59435 82.55667
> colMin(tmp5,na.rm=TRUE)
[1] 55.23810 63.11170 57.38829 58.18775 54.18193 56.93579 59.08298 54.01339
[9] 61.07696 58.64194 54.06954 62.87303 56.52527 55.31388 54.99511 55.75890
[17] 60.16011 63.47384 58.75493 54.91435
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.45803 70.73736 69.07863 70.17387 NaN 68.01182 68.70412 71.59587
[9] 69.56013 69.58851
> rowSums(tmp5,na.rm=TRUE)
[1] 1809.161 1414.747 1381.573 1403.477 0.000 1360.236 1374.082 1431.917
[9] 1391.203 1391.770
> rowVars(tmp5,na.rm=TRUE)
[1] 8267.00788 121.96546 51.77245 89.96485 NA 54.85048
[7] 49.59104 56.96217 60.69039 74.28965
> rowSd(tmp5,na.rm=TRUE)
[1] 90.923088 11.043797 7.195307 9.484980 NA 7.406111 7.042091
[8] 7.547328 7.790404 8.619144
> rowMax(tmp5,na.rm=TRUE)
[1] 475.25124 89.24057 81.83860 96.58106 NA 87.42483 82.55667
[8] 85.25241 82.93233 87.00318
> rowMin(tmp5,na.rm=TRUE)
[1] 56.93579 54.01339 55.23810 54.06954 NA 54.91435 58.18775 55.31388
[9] 56.52527 54.18193
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.01022 73.41777 70.35173 72.19690 67.26629 68.62863 70.77274
[8] 70.42679 71.51002 68.63115 69.24478 70.37399 69.55141 72.19646
[15] NaN 68.70286 65.61843 69.62044 67.56795 68.15126
> colSums(tmp5,na.rm=TRUE)
[1] 1044.0920 660.7599 633.1656 649.7721 605.3966 617.6577 636.9547
[8] 633.8411 643.5902 617.6803 623.2030 633.3659 625.9627 649.7682
[15] 0.0000 618.3258 590.5659 626.5840 608.1116 613.3613
> colVars(tmp5,na.rm=TRUE)
[1] 18222.25083 51.71680 72.43202 91.29081 110.99790 57.75480
[7] 81.51344 73.18191 66.65875 48.69325 113.63020 30.78778
[13] 90.97751 145.62325 NA 53.77548 29.62958 59.22217
[19] 41.69766 73.94154
> colSd(tmp5,na.rm=TRUE)
[1] 134.989818 7.191440 8.510700 9.554622 10.535554 7.599658
[7] 9.028479 8.554643 8.164481 6.978055 10.659747 5.548674
[13] 9.538213 12.067446 NA 7.333177 5.443306 7.695594
[19] 6.457373 8.598927
> colMax(tmp5,na.rm=TRUE)
[1] 475.25124 87.00318 82.93233 90.78748 89.24057 75.59251 85.25241
[8] 82.73922 81.23509 78.85613 87.42483 78.15124 85.16435 96.58106
[15] -Inf 84.12089 75.91609 89.13397 79.59435 82.55667
> colMin(tmp5,na.rm=TRUE)
[1] 55.23810 63.11170 57.38829 58.18775 54.18193 56.93579 59.08298 54.01339
[9] 61.07696 58.64194 54.06954 62.87303 56.52527 55.31388 Inf 58.79171
[17] 60.16011 63.77478 58.75493 54.91435
>
>
>
>
> 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] 366.1963 242.6500 444.4350 195.8097 247.3322 246.1175 226.3068 211.8888
[9] 298.0817 328.0318
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 366.1963 242.6500 444.4350 195.8097 247.3322 246.1175 226.3068 211.8888
[9] 298.0817 328.0318
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 -1.705303e-13 -5.684342e-14 9.947598e-14 2.842171e-14
[6] -1.136868e-13 -2.273737e-13 -1.136868e-13 0.000000e+00 2.842171e-14
[11] 0.000000e+00 2.273737e-13 0.000000e+00 -5.684342e-14 0.000000e+00
[16] -2.273737e-13 2.557954e-13 2.842171e-14 -4.263256e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
6 7
1 7
2 11
5 11
7 4
9 9
6 13
3 14
6 8
1 15
6 5
5 12
3 12
8 19
4 9
9 6
1 7
8 20
3 20
4 9
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.782981
> Min(tmp)
[1] -2.509344
> mean(tmp)
[1] -0.08778331
> Sum(tmp)
[1] -8.778331
> Var(tmp)
[1] 1.121268
>
> rowMeans(tmp)
[1] -0.08778331
> rowSums(tmp)
[1] -8.778331
> rowVars(tmp)
[1] 1.121268
> rowSd(tmp)
[1] 1.0589
> rowMax(tmp)
[1] 2.782981
> rowMin(tmp)
[1] -2.509344
>
> colMeans(tmp)
[1] 0.36880253 -0.84454959 0.20302167 -2.03297516 0.93490796 -0.43662587
[7] 0.21291317 0.86716060 1.02057524 -2.02145621 0.27276238 -0.83584633
[13] -1.42325485 0.89051304 1.21310796 0.42281503 -0.33181932 -1.02892184
[19] 0.67836204 2.67003630 0.95950980 0.60542578 -0.50316071 2.27983308
[25] -0.13519742 0.94028715 -0.07048807 0.25019414 -0.25169819 0.81727018
[31] -0.23526069 0.76297568 -0.11234630 -1.87520584 0.09960494 0.02101273
[37] 0.43841910 0.03122152 -1.62497460 -1.05043497 0.36044532 -1.28636539
[43] 0.02315224 0.56992320 -0.06124355 0.07443295 0.32131764 0.77164364
[49] 1.16523788 -0.34906358 -2.50934386 2.78298146 -0.79871476 -0.23065050
[55] -0.02198299 -1.25715050 -2.01791712 0.87070206 -0.85645113 -2.13130261
[61] 0.52382479 -0.14637221 -0.17426425 0.65185364 -1.26921419 0.76872889
[67] -0.98284413 -1.89587339 0.02850025 -0.60984591 -0.34274433 -0.12765081
[73] -0.78016100 -0.75800758 -1.91024606 -1.61658297 -1.05573963 1.37934126
[79] 1.38503833 -0.45935412 0.77858844 0.10536365 -1.19146326 0.03241893
[85] -0.36485082 -0.02198120 0.78536220 0.94872121 0.53270582 0.33534622
[91] 0.21039840 0.66523134 1.42725415 -0.62054910 -0.36327613 -1.52618774
[97] -2.09344722 1.89582935 0.16158195 -0.64993055
> colSums(tmp)
[1] 0.36880253 -0.84454959 0.20302167 -2.03297516 0.93490796 -0.43662587
[7] 0.21291317 0.86716060 1.02057524 -2.02145621 0.27276238 -0.83584633
[13] -1.42325485 0.89051304 1.21310796 0.42281503 -0.33181932 -1.02892184
[19] 0.67836204 2.67003630 0.95950980 0.60542578 -0.50316071 2.27983308
[25] -0.13519742 0.94028715 -0.07048807 0.25019414 -0.25169819 0.81727018
[31] -0.23526069 0.76297568 -0.11234630 -1.87520584 0.09960494 0.02101273
[37] 0.43841910 0.03122152 -1.62497460 -1.05043497 0.36044532 -1.28636539
[43] 0.02315224 0.56992320 -0.06124355 0.07443295 0.32131764 0.77164364
[49] 1.16523788 -0.34906358 -2.50934386 2.78298146 -0.79871476 -0.23065050
[55] -0.02198299 -1.25715050 -2.01791712 0.87070206 -0.85645113 -2.13130261
[61] 0.52382479 -0.14637221 -0.17426425 0.65185364 -1.26921419 0.76872889
[67] -0.98284413 -1.89587339 0.02850025 -0.60984591 -0.34274433 -0.12765081
[73] -0.78016100 -0.75800758 -1.91024606 -1.61658297 -1.05573963 1.37934126
[79] 1.38503833 -0.45935412 0.77858844 0.10536365 -1.19146326 0.03241893
[85] -0.36485082 -0.02198120 0.78536220 0.94872121 0.53270582 0.33534622
[91] 0.21039840 0.66523134 1.42725415 -0.62054910 -0.36327613 -1.52618774
[97] -2.09344722 1.89582935 0.16158195 -0.64993055
> 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] 0.36880253 -0.84454959 0.20302167 -2.03297516 0.93490796 -0.43662587
[7] 0.21291317 0.86716060 1.02057524 -2.02145621 0.27276238 -0.83584633
[13] -1.42325485 0.89051304 1.21310796 0.42281503 -0.33181932 -1.02892184
[19] 0.67836204 2.67003630 0.95950980 0.60542578 -0.50316071 2.27983308
[25] -0.13519742 0.94028715 -0.07048807 0.25019414 -0.25169819 0.81727018
[31] -0.23526069 0.76297568 -0.11234630 -1.87520584 0.09960494 0.02101273
[37] 0.43841910 0.03122152 -1.62497460 -1.05043497 0.36044532 -1.28636539
[43] 0.02315224 0.56992320 -0.06124355 0.07443295 0.32131764 0.77164364
[49] 1.16523788 -0.34906358 -2.50934386 2.78298146 -0.79871476 -0.23065050
[55] -0.02198299 -1.25715050 -2.01791712 0.87070206 -0.85645113 -2.13130261
[61] 0.52382479 -0.14637221 -0.17426425 0.65185364 -1.26921419 0.76872889
[67] -0.98284413 -1.89587339 0.02850025 -0.60984591 -0.34274433 -0.12765081
[73] -0.78016100 -0.75800758 -1.91024606 -1.61658297 -1.05573963 1.37934126
[79] 1.38503833 -0.45935412 0.77858844 0.10536365 -1.19146326 0.03241893
[85] -0.36485082 -0.02198120 0.78536220 0.94872121 0.53270582 0.33534622
[91] 0.21039840 0.66523134 1.42725415 -0.62054910 -0.36327613 -1.52618774
[97] -2.09344722 1.89582935 0.16158195 -0.64993055
> colMin(tmp)
[1] 0.36880253 -0.84454959 0.20302167 -2.03297516 0.93490796 -0.43662587
[7] 0.21291317 0.86716060 1.02057524 -2.02145621 0.27276238 -0.83584633
[13] -1.42325485 0.89051304 1.21310796 0.42281503 -0.33181932 -1.02892184
[19] 0.67836204 2.67003630 0.95950980 0.60542578 -0.50316071 2.27983308
[25] -0.13519742 0.94028715 -0.07048807 0.25019414 -0.25169819 0.81727018
[31] -0.23526069 0.76297568 -0.11234630 -1.87520584 0.09960494 0.02101273
[37] 0.43841910 0.03122152 -1.62497460 -1.05043497 0.36044532 -1.28636539
[43] 0.02315224 0.56992320 -0.06124355 0.07443295 0.32131764 0.77164364
[49] 1.16523788 -0.34906358 -2.50934386 2.78298146 -0.79871476 -0.23065050
[55] -0.02198299 -1.25715050 -2.01791712 0.87070206 -0.85645113 -2.13130261
[61] 0.52382479 -0.14637221 -0.17426425 0.65185364 -1.26921419 0.76872889
[67] -0.98284413 -1.89587339 0.02850025 -0.60984591 -0.34274433 -0.12765081
[73] -0.78016100 -0.75800758 -1.91024606 -1.61658297 -1.05573963 1.37934126
[79] 1.38503833 -0.45935412 0.77858844 0.10536365 -1.19146326 0.03241893
[85] -0.36485082 -0.02198120 0.78536220 0.94872121 0.53270582 0.33534622
[91] 0.21039840 0.66523134 1.42725415 -0.62054910 -0.36327613 -1.52618774
[97] -2.09344722 1.89582935 0.16158195 -0.64993055
> colMedians(tmp)
[1] 0.36880253 -0.84454959 0.20302167 -2.03297516 0.93490796 -0.43662587
[7] 0.21291317 0.86716060 1.02057524 -2.02145621 0.27276238 -0.83584633
[13] -1.42325485 0.89051304 1.21310796 0.42281503 -0.33181932 -1.02892184
[19] 0.67836204 2.67003630 0.95950980 0.60542578 -0.50316071 2.27983308
[25] -0.13519742 0.94028715 -0.07048807 0.25019414 -0.25169819 0.81727018
[31] -0.23526069 0.76297568 -0.11234630 -1.87520584 0.09960494 0.02101273
[37] 0.43841910 0.03122152 -1.62497460 -1.05043497 0.36044532 -1.28636539
[43] 0.02315224 0.56992320 -0.06124355 0.07443295 0.32131764 0.77164364
[49] 1.16523788 -0.34906358 -2.50934386 2.78298146 -0.79871476 -0.23065050
[55] -0.02198299 -1.25715050 -2.01791712 0.87070206 -0.85645113 -2.13130261
[61] 0.52382479 -0.14637221 -0.17426425 0.65185364 -1.26921419 0.76872889
[67] -0.98284413 -1.89587339 0.02850025 -0.60984591 -0.34274433 -0.12765081
[73] -0.78016100 -0.75800758 -1.91024606 -1.61658297 -1.05573963 1.37934126
[79] 1.38503833 -0.45935412 0.77858844 0.10536365 -1.19146326 0.03241893
[85] -0.36485082 -0.02198120 0.78536220 0.94872121 0.53270582 0.33534622
[91] 0.21039840 0.66523134 1.42725415 -0.62054910 -0.36327613 -1.52618774
[97] -2.09344722 1.89582935 0.16158195 -0.64993055
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3688025 -0.8445496 0.2030217 -2.032975 0.934908 -0.4366259 0.2129132
[2,] 0.3688025 -0.8445496 0.2030217 -2.032975 0.934908 -0.4366259 0.2129132
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.8671606 1.020575 -2.021456 0.2727624 -0.8358463 -1.423255 0.890513
[2,] 0.8671606 1.020575 -2.021456 0.2727624 -0.8358463 -1.423255 0.890513
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.213108 0.422815 -0.3318193 -1.028922 0.678362 2.670036 0.9595098
[2,] 1.213108 0.422815 -0.3318193 -1.028922 0.678362 2.670036 0.9595098
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.6054258 -0.5031607 2.279833 -0.1351974 0.9402872 -0.07048807 0.2501941
[2,] 0.6054258 -0.5031607 2.279833 -0.1351974 0.9402872 -0.07048807 0.2501941
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.2516982 0.8172702 -0.2352607 0.7629757 -0.1123463 -1.875206 0.09960494
[2,] -0.2516982 0.8172702 -0.2352607 0.7629757 -0.1123463 -1.875206 0.09960494
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.02101273 0.4384191 0.03122152 -1.624975 -1.050435 0.3604453 -1.286365
[2,] 0.02101273 0.4384191 0.03122152 -1.624975 -1.050435 0.3604453 -1.286365
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.02315224 0.5699232 -0.06124355 0.07443295 0.3213176 0.7716436 1.165238
[2,] 0.02315224 0.5699232 -0.06124355 0.07443295 0.3213176 0.7716436 1.165238
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.3490636 -2.509344 2.782981 -0.7987148 -0.2306505 -0.02198299 -1.25715
[2,] -0.3490636 -2.509344 2.782981 -0.7987148 -0.2306505 -0.02198299 -1.25715
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -2.017917 0.8707021 -0.8564511 -2.131303 0.5238248 -0.1463722 -0.1742643
[2,] -2.017917 0.8707021 -0.8564511 -2.131303 0.5238248 -0.1463722 -0.1742643
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.6518536 -1.269214 0.7687289 -0.9828441 -1.895873 0.02850025 -0.6098459
[2,] 0.6518536 -1.269214 0.7687289 -0.9828441 -1.895873 0.02850025 -0.6098459
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.3427443 -0.1276508 -0.780161 -0.7580076 -1.910246 -1.616583 -1.05574
[2,] -0.3427443 -0.1276508 -0.780161 -0.7580076 -1.910246 -1.616583 -1.05574
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.379341 1.385038 -0.4593541 0.7785884 0.1053636 -1.191463 0.03241893
[2,] 1.379341 1.385038 -0.4593541 0.7785884 0.1053636 -1.191463 0.03241893
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.3648508 -0.0219812 0.7853622 0.9487212 0.5327058 0.3353462 0.2103984
[2,] -0.3648508 -0.0219812 0.7853622 0.9487212 0.5327058 0.3353462 0.2103984
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.6652313 1.427254 -0.6205491 -0.3632761 -1.526188 -2.093447 1.895829
[2,] 0.6652313 1.427254 -0.6205491 -0.3632761 -1.526188 -2.093447 1.895829
[,99] [,100]
[1,] 0.161582 -0.6499306
[2,] 0.161582 -0.6499306
>
>
> Max(tmp2)
[1] 2.706019
> Min(tmp2)
[1] -2.955963
> mean(tmp2)
[1] 0.1714606
> Sum(tmp2)
[1] 17.14606
> Var(tmp2)
[1] 1.02036
>
> rowMeans(tmp2)
[1] 1.917118720 -0.503194125 1.006877055 1.392405657 -0.485504704
[6] -0.298845934 -0.024522657 0.056175229 -0.728137415 -0.081088265
[11] 2.275052160 1.381370782 0.613665913 1.428024064 -1.299708146
[16] 1.115390723 0.247033093 0.944478934 -1.035126892 -0.734368075
[21] 0.470344853 1.147595331 -0.007633371 -0.946192126 -0.514470799
[26] 0.894124619 -0.878402769 0.909441338 0.333211643 1.163567926
[31] 1.273465490 1.161403568 -2.955963316 1.335452193 -0.055921662
[36] -1.887490011 -0.293060813 1.331695859 -0.269121809 0.437069051
[41] -0.883996817 -0.345486994 2.495555591 -0.534945800 0.983965186
[46] -0.037402509 -0.657156723 0.531820134 -0.920346672 1.196675279
[51] -1.345663859 0.283862931 -0.084290698 -1.909085789 0.869565173
[56] -0.899258861 1.558357009 -0.481720950 0.638825993 0.890604994
[61] 0.114297766 1.555428380 0.657116987 -0.129074879 0.263204973
[66] 1.201104467 0.922924762 0.131612041 1.767423997 0.294022359
[71] -0.118612262 0.957806291 0.084033408 -0.883598745 -2.051389301
[76] 0.397608684 -0.590787359 -0.129077634 0.298699797 1.254644362
[81] -0.089464166 -0.644728125 0.497449564 -0.179251034 -0.993491315
[86] -0.657291837 -0.179039496 -0.401695796 0.151732596 -1.168636796
[91] 2.706019445 0.830957038 0.160636103 -0.742316499 -1.242683282
[96] -0.112041389 -0.561079716 0.744117785 1.163522589 0.679866016
> rowSums(tmp2)
[1] 1.917118720 -0.503194125 1.006877055 1.392405657 -0.485504704
[6] -0.298845934 -0.024522657 0.056175229 -0.728137415 -0.081088265
[11] 2.275052160 1.381370782 0.613665913 1.428024064 -1.299708146
[16] 1.115390723 0.247033093 0.944478934 -1.035126892 -0.734368075
[21] 0.470344853 1.147595331 -0.007633371 -0.946192126 -0.514470799
[26] 0.894124619 -0.878402769 0.909441338 0.333211643 1.163567926
[31] 1.273465490 1.161403568 -2.955963316 1.335452193 -0.055921662
[36] -1.887490011 -0.293060813 1.331695859 -0.269121809 0.437069051
[41] -0.883996817 -0.345486994 2.495555591 -0.534945800 0.983965186
[46] -0.037402509 -0.657156723 0.531820134 -0.920346672 1.196675279
[51] -1.345663859 0.283862931 -0.084290698 -1.909085789 0.869565173
[56] -0.899258861 1.558357009 -0.481720950 0.638825993 0.890604994
[61] 0.114297766 1.555428380 0.657116987 -0.129074879 0.263204973
[66] 1.201104467 0.922924762 0.131612041 1.767423997 0.294022359
[71] -0.118612262 0.957806291 0.084033408 -0.883598745 -2.051389301
[76] 0.397608684 -0.590787359 -0.129077634 0.298699797 1.254644362
[81] -0.089464166 -0.644728125 0.497449564 -0.179251034 -0.993491315
[86] -0.657291837 -0.179039496 -0.401695796 0.151732596 -1.168636796
[91] 2.706019445 0.830957038 0.160636103 -0.742316499 -1.242683282
[96] -0.112041389 -0.561079716 0.744117785 1.163522589 0.679866016
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.917118720 -0.503194125 1.006877055 1.392405657 -0.485504704
[6] -0.298845934 -0.024522657 0.056175229 -0.728137415 -0.081088265
[11] 2.275052160 1.381370782 0.613665913 1.428024064 -1.299708146
[16] 1.115390723 0.247033093 0.944478934 -1.035126892 -0.734368075
[21] 0.470344853 1.147595331 -0.007633371 -0.946192126 -0.514470799
[26] 0.894124619 -0.878402769 0.909441338 0.333211643 1.163567926
[31] 1.273465490 1.161403568 -2.955963316 1.335452193 -0.055921662
[36] -1.887490011 -0.293060813 1.331695859 -0.269121809 0.437069051
[41] -0.883996817 -0.345486994 2.495555591 -0.534945800 0.983965186
[46] -0.037402509 -0.657156723 0.531820134 -0.920346672 1.196675279
[51] -1.345663859 0.283862931 -0.084290698 -1.909085789 0.869565173
[56] -0.899258861 1.558357009 -0.481720950 0.638825993 0.890604994
[61] 0.114297766 1.555428380 0.657116987 -0.129074879 0.263204973
[66] 1.201104467 0.922924762 0.131612041 1.767423997 0.294022359
[71] -0.118612262 0.957806291 0.084033408 -0.883598745 -2.051389301
[76] 0.397608684 -0.590787359 -0.129077634 0.298699797 1.254644362
[81] -0.089464166 -0.644728125 0.497449564 -0.179251034 -0.993491315
[86] -0.657291837 -0.179039496 -0.401695796 0.151732596 -1.168636796
[91] 2.706019445 0.830957038 0.160636103 -0.742316499 -1.242683282
[96] -0.112041389 -0.561079716 0.744117785 1.163522589 0.679866016
> rowMin(tmp2)
[1] 1.917118720 -0.503194125 1.006877055 1.392405657 -0.485504704
[6] -0.298845934 -0.024522657 0.056175229 -0.728137415 -0.081088265
[11] 2.275052160 1.381370782 0.613665913 1.428024064 -1.299708146
[16] 1.115390723 0.247033093 0.944478934 -1.035126892 -0.734368075
[21] 0.470344853 1.147595331 -0.007633371 -0.946192126 -0.514470799
[26] 0.894124619 -0.878402769 0.909441338 0.333211643 1.163567926
[31] 1.273465490 1.161403568 -2.955963316 1.335452193 -0.055921662
[36] -1.887490011 -0.293060813 1.331695859 -0.269121809 0.437069051
[41] -0.883996817 -0.345486994 2.495555591 -0.534945800 0.983965186
[46] -0.037402509 -0.657156723 0.531820134 -0.920346672 1.196675279
[51] -1.345663859 0.283862931 -0.084290698 -1.909085789 0.869565173
[56] -0.899258861 1.558357009 -0.481720950 0.638825993 0.890604994
[61] 0.114297766 1.555428380 0.657116987 -0.129074879 0.263204973
[66] 1.201104467 0.922924762 0.131612041 1.767423997 0.294022359
[71] -0.118612262 0.957806291 0.084033408 -0.883598745 -2.051389301
[76] 0.397608684 -0.590787359 -0.129077634 0.298699797 1.254644362
[81] -0.089464166 -0.644728125 0.497449564 -0.179251034 -0.993491315
[86] -0.657291837 -0.179039496 -0.401695796 0.151732596 -1.168636796
[91] 2.706019445 0.830957038 0.160636103 -0.742316499 -1.242683282
[96] -0.112041389 -0.561079716 0.744117785 1.163522589 0.679866016
>
> colMeans(tmp2)
[1] 0.1714606
> colSums(tmp2)
[1] 17.14606
> colVars(tmp2)
[1] 1.02036
> colSd(tmp2)
[1] 1.010129
> colMax(tmp2)
[1] 2.706019
> colMin(tmp2)
[1] -2.955963
> colMedians(tmp2)
[1] 0.1229549
> colRanges(tmp2)
[,1]
[1,] -2.955963
[2,] 2.706019
>
> 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] -0.8147827 5.2567118 -1.0293798 5.2790103 4.0986456 -1.6982132
[7] -1.1463265 -2.5840939 0.5845686 -2.0469014
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9641792
[2,] -0.4799325
[3,] 0.1451809
[4,] 0.3869438
[5,] 0.9738108
>
> rowApply(tmp,sum)
[1] 3.2054336 -1.7146859 -0.5656949 -4.1611437 -0.5981691 1.9449752
[7] 1.3867010 3.6690822 -2.4346912 5.1674317
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 8 10 7 6 2 8 1 1 6
[2,] 9 6 6 6 4 7 10 4 4 9
[3,] 5 5 2 1 8 3 4 5 9 5
[4,] 10 9 5 8 9 5 2 7 5 10
[5,] 7 10 8 5 10 9 3 8 8 7
[6,] 1 1 4 4 3 8 7 6 3 8
[7,] 2 4 1 9 7 10 5 9 2 2
[8,] 8 3 7 3 2 1 1 10 7 4
[9,] 6 7 3 10 5 4 6 3 6 1
[10,] 4 2 9 2 1 6 9 2 10 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.4017690 0.9979457 1.4737543 -1.8128347 -0.5384336 -1.9675548
[7] 2.5359512 -0.3587035 1.2728531 -1.0327546 0.8751928 -1.2582169
[13] -1.8177104 -3.7926739 -1.0530569 -0.5675936 -1.5969876 1.2283519
[19] 0.4749614 2.3069366
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.62327451
[2,] -1.37845328
[3,] -1.11575804
[4,] -0.01290426
[5,] 1.72862110
>
> rowApply(tmp,sum)
[1] -2.693662 -9.137136 3.733346 5.046210 -3.981100
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 5 2 9 19 2
[2,] 20 3 13 7 15
[3,] 1 19 14 20 13
[4,] 15 7 8 5 3
[5,] 16 8 15 4 4
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.11575804 1.47776425 -2.02312938 0.5245540 0.8379393 1.2605776
[2,] -1.62327451 -1.27710898 0.52108438 -0.8337112 -0.8271067 -2.3660312
[3,] -0.01290426 0.46838018 0.76156014 -0.1662707 0.8270589 -1.2101142
[4,] 1.72862110 -0.08792384 2.14570441 -0.1563104 -0.2495079 -0.4422665
[5,] -1.37845328 0.41683412 0.06853473 -1.1810964 -1.1268172 0.7902795
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.168204495 -0.97951386 0.47599843 0.41635204 0.3772266 1.2165156
[2,] 1.622871489 0.46225801 0.02665598 -1.18718464 0.1312040 -1.1745033
[3,] -0.190755707 -1.04286318 -0.35523996 0.01721484 1.4032349 -0.9407247
[4,] 0.928486005 0.03789706 -0.08657773 -1.29672432 0.7036332 0.3840348
[5,] 0.007144961 1.16351847 1.21201639 1.01758751 -1.7401058 -0.7435392
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.2049185 -1.7379365 -0.7020574 -0.8051995 -1.3667017 0.91056456
[2,] -0.7639618 -0.9793765 0.2993893 -0.1061364 0.2499878 -0.47862473
[3,] -0.4717630 -0.6994104 0.1020426 0.8409632 0.1190697 0.83125134
[4,] -0.8344470 0.5381619 0.2531447 0.3230633 0.4648440 0.01537935
[5,] 1.4573799 -0.9141124 -1.0055762 -0.8202842 -1.0641874 -0.05021864
[,19] [,20]
[1,] -0.23361211 -0.1905322
[2,] -0.13737362 -0.6961937
[3,] 1.39785501 2.0547617
[4,] -0.09953365 0.7765317
[5,] -0.45237421 0.3623691
>
>
> 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 : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.6645908 0.5097546 -0.09155558 0.2311369 1.147539 -0.3957186 1.810224
col8 col9 col10 col11 col12 col13 col14
row1 -0.3137747 -0.146375 -1.341639 0.6835324 0.4689312 1.714353 0.5093112
col15 col16 col17 col18 col19 col20
row1 -2.2109 0.8727238 0.1606551 -0.6239422 -2.280239 0.3047685
> tmp[,"col10"]
col10
row1 -1.3416386
row2 -0.1860278
row3 0.3084381
row4 0.4933497
row5 -2.4469128
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.6645908 0.5097546 -0.09155558 0.2311369 1.1475385 -0.3957186 1.8102244
row5 -0.9003227 0.5246171 -1.64314842 0.5353422 0.1602815 -0.8957641 -0.5612133
col8 col9 col10 col11 col12 col13
row1 -0.3137747 -0.146375 -1.341639 0.68353239 0.4689312 1.7143530
row5 -0.2943202 -1.258511 -2.446913 -0.05258836 -0.2746720 -0.8286225
col14 col15 col16 col17 col18 col19 col20
row1 0.5093112 -2.210900 0.8727238 0.1606551 -0.6239422 -2.2802386 0.3047685
row5 -0.4812731 -1.347987 0.2462554 1.5342014 0.8357834 -0.7339656 1.1558195
> tmp[,c("col6","col20")]
col6 col20
row1 -0.3957186 0.30476847
row2 0.4180257 -0.04913056
row3 1.6370867 -0.24196203
row4 -0.1355968 1.17304937
row5 -0.8957641 1.15581953
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.3957186 0.3047685
row5 -0.8957641 1.1558195
>
>
>
>
> 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 50.12661 50.20113 49.74055 49.37185 51.38342 104.5715 51.11221 50.85746
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.07609 50.81766 49.44612 51.917 50.055 50.07292 49.7127 49.66444
col17 col18 col19 col20
row1 50.17477 50.09752 49.35815 105.38
> tmp[,"col10"]
col10
row1 50.81766
row2 30.84077
row3 30.63419
row4 29.08307
row5 50.53880
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.12661 50.20113 49.74055 49.37185 51.38342 104.5715 51.11221 50.85746
row5 50.67685 49.92436 48.72946 52.13248 50.35450 105.0089 50.91489 47.96256
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.07609 50.81766 49.44612 51.91700 50.05500 50.07292 49.7127 49.66444
row5 50.00741 50.53880 50.82948 50.45322 48.32656 50.95837 50.5587 50.05952
col17 col18 col19 col20
row1 50.17477 50.09752 49.35815 105.3800
row5 51.40641 50.51269 50.44692 104.3503
> tmp[,c("col6","col20")]
col6 col20
row1 104.57145 105.37995
row2 75.52462 76.30155
row3 75.38459 76.79482
row4 75.63773 75.11587
row5 105.00895 104.35029
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5715 105.3800
row5 105.0089 104.3503
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5715 105.3800
row5 105.0089 104.3503
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.22521726
[2,] -0.15672861
[3,] 1.07083081
[4,] -0.49403645
[5,] 0.09223625
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.3547273 -0.13558094
[2,] -1.0641554 1.03899533
[3,] 0.8036014 2.74832541
[4,] 0.3528370 0.09994907
[5,] 1.7034034 0.69725561
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.50387292 -0.207617441
[2,] 0.24663486 -1.305376652
[3,] -0.62037377 -0.432374904
[4,] 1.04982906 -0.001242211
[5,] 0.04177502 -0.477166792
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.5038729
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.5038729
[2,] 0.2466349
>
>
>
> 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 0.3393388 0.4168920 2.9542162 -0.9409385 -1.2873669 -0.7128765
row1 -0.1900407 -0.5592478 -0.1490919 -0.6405931 -0.4428428 0.2214640
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.8660891 -0.3049156 -1.208325 -0.4102736 0.5710229 0.3167068 -0.9366906
row1 0.2775958 0.9774628 -2.495443 -0.6919051 0.8448281 -0.4506171 -0.5813742
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3261990 0.02636431 0.2155853 -0.1357770 1.4052384 0.6389059
row1 0.4630998 -0.54066998 0.2266441 0.3579034 -0.4854521 0.1784158
[,20]
row3 -1.1960819
row1 -0.3570071
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.3611352 0.6327711 0.2582294 -0.3699529 -1.505276 -0.2293102 0.3788863
[,8] [,9] [,10]
row2 -0.5217973 -1.097996 -0.3931275
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5427608 0.9141565 -0.2162515 0.645846 -0.002738678 -0.07897531 0.1833707
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5659947 1.639742 0.311876 -0.2928047 0.292855 -1.57558 0.6635971
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.1530336 0.179177 -0.6438025 -0.8080454 2.168255 0.1471226
>
>
> 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: 0x5b94b7058c00>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c6544110b"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c6edbd82c"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c4d0672a6"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c6aac38c2"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c3c1f5a74"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c135ca84"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c3d8ed584"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c3f08853b"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c360da2c6"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c5229adb8"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c4af50b52"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c44a21d41"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c5a95ce92"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c53912970"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3acf6c5b078ff9"
>
>
> ### 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: 0x5b94b4ef2400>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5b94b4ef2400>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5b94b4ef2400>
> rowMedians(tmp)
[1] -0.476303825 0.144757700 -0.010787967 -0.051606699 0.003485189
[6] -0.374053767 0.059768924 -0.324986661 -0.502084233 0.106554897
[11] 0.576384389 -0.348561287 -0.184362138 0.474642772 0.112274229
[16] -0.315806719 0.054509612 -0.351552841 0.334589726 0.307758672
[21] 0.201372232 0.289440184 0.226948931 0.433133039 -0.465335503
[26] 0.169874865 -0.413802836 0.232725826 -0.373116437 -0.115929888
[31] -0.330809894 0.003405076 0.279556363 -0.111552661 0.313742789
[36] -0.493883989 -0.083137819 -0.132968024 -0.127491884 -0.542072549
[41] 0.505537452 -0.354029918 0.003899922 -0.204575388 0.064447960
[46] 0.297423063 0.058392554 0.231772916 0.142514029 -0.163224291
[51] 0.089099589 0.160331295 -0.186375046 -0.103929978 -0.290742572
[56] -0.141213540 0.082467787 0.053610337 -0.325518649 -0.143247951
[61] -0.193101917 0.274149693 0.071793781 0.164333648 -0.186649578
[66] 0.203025370 0.007306444 -0.174258018 -0.103490892 0.125032015
[71] -0.099279462 -0.006377054 -0.070477448 -0.467143750 -0.269516761
[76] -0.092064919 0.003188362 0.474738861 0.264527836 -0.410013212
[81] -0.061729401 0.005865278 -0.293502957 -0.081251621 0.244864206
[86] -0.506155861 -0.030263901 -0.159187584 -0.267851868 -0.481388580
[91] -0.140609156 0.161725854 0.250397749 -0.130712752 -0.152698211
[96] 0.163895428 0.008672932 0.035159162 0.041597673 0.165974551
[101] 0.507503144 -0.607191452 0.047556836 -0.155664523 -0.409546798
[106] -0.097674076 -0.536788293 0.472054532 0.225169022 -0.266116484
[111] -0.396746121 0.195433262 -0.566029993 -0.095757946 -0.229420587
[116] -0.004252719 -0.640456082 0.299991073 0.148025799 -0.532914699
[121] -0.509188927 0.009643604 -0.342565365 0.067111100 -0.104308131
[126] 0.116929972 0.783193710 0.112784935 0.080629903 -0.631121221
[131] -0.088748070 0.005163604 0.412033356 0.337198487 -0.661426294
[136] 0.017886477 -0.502851526 -0.177547664 0.365348373 -0.329266564
[141] -0.306926575 0.126319308 -0.133481958 0.330628621 -0.834205041
[146] -0.201604615 0.137542203 -0.543830075 0.509692944 -0.153229327
[151] -0.019843981 -0.218029090 0.095359168 -0.534638216 0.271216996
[156] 0.210441878 0.139414920 -0.580253484 0.266268111 -0.074491371
[161] -0.143762995 -0.046494872 -0.437976738 0.022105268 -0.201565537
[166] 0.323129941 0.087058165 -0.268338602 -0.176808816 0.042258313
[171] -0.250602376 0.227819640 -0.316583779 0.643188051 0.478644029
[176] 0.521513426 -0.070484412 -0.165483630 0.716994387 0.513748954
[181] -0.166805625 -0.196581273 -0.558614433 0.728941896 0.463831469
[186] 0.269044104 0.205170815 0.113854661 -0.206919398 0.362639090
[191] 0.930786611 0.233839720 0.718546950 0.540758638 0.152441025
[196] -0.222282850 -0.086847691 -0.234186315 -0.550688002 -0.217100516
[201] 0.545794976 0.670749830 0.045281752 -0.176058788 -0.416252340
[206] -0.088406504 -0.568757323 0.148547272 -0.975897799 -0.080910707
[211] 0.038254116 -0.114894422 -0.214028538 0.027506908 0.187319646
[216] -0.433400298 -0.328650855 -0.101892700 -0.357984348 0.318597154
[221] 0.114605594 0.073023129 -0.157769109 -0.376315737 0.156013141
[226] 0.052084376 -0.141474443 0.116457832 0.077786933 0.548214482
>
> proc.time()
user system elapsed
1.297 1.457 2.742
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: 0x5615e603cff0>
> .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: 0x5615e603cff0>
> .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: 0x5615e603cff0>
> .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: 0x5615e603cff0>
> 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: 0x5615e5c5ba60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e5c5ba60>
> .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: 0x5615e5c5ba60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e5c5ba60>
> .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: 0x5615e5c5ba60>
> 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: 0x5615e59c1240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e59c1240>
> .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: 0x5615e59c1240>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5615e59c1240>
> .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: 0x5615e59c1240>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5615e59c1240>
> .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: 0x5615e59c1240>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5615e59c1240>
> .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: 0x5615e59c1240>
> 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: 0x5615e6a02160>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5615e6a02160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e6a02160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e6a02160>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3ad1032ed2b5a1" "BufferedMatrixFile3ad1039867396"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3ad1032ed2b5a1" "BufferedMatrixFile3ad1039867396"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e6c73d20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e6c73d20>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5615e6c73d20>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5615e6c73d20>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5615e6c73d20>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5615e6c73d20>
> .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: 0x5615e6ea5390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5615e6ea5390>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5615e6ea5390>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5615e6ea5390>
> 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: 0x5615e817f7c0>
> .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: 0x5615e817f7c0>
> rm(P)
>
> proc.time()
user system elapsed
0.238 0.051 0.278
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
0.250 0.041 0.279