Ben Bolstad
| Snapshot Date: 2026-05-01 13:40 -0400 (Fri, 01 May 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_23 |
| git_last_commit: 9d72964 |
| git_last_commit_date: 2026-04-28 08:32:08 -0400 (Tue, 28 Apr 2026) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-05-02 11:34 -0400 (Sat, 02 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4988 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 Patched (2026-04-24 r89963) -- "Because it was There" | 4718 |
| 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 262/2418 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.76.0 (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: 1.76.0 |
| 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_1.76.0.tar.gz |
| StartedAt: 2026-05-01 22:14:54 -0400 (Fri, 01 May 2026) |
| EndedAt: 2026-05-01 22:15:20 -0400 (Fri, 01 May 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_1.76.0.tar.gz
###
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##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* 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: 2026-05-02 02:14:55 UTC
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.76.0’
* 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 ‘1.76.0’
** 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 RC (2026-04-17 r89917) -- "Because it was There"
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
0.253 0.040 0.282
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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 480233 25.7 1053308 56.3 637571 34.1
Vcells 887253 6.8 8388608 64.0 2083896 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 May 1 22:15:10 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 May 1 22:15:10 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: 0x5d69a3043690>
>
>
>
> 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 May 1 22:15:10 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 May 1 22:15:11 2026"
>
> ColMode(tmp2)
<pointer: 0x5d69a3043690>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.7907236 0.17820405 0.5190097 0.12431698
[2,] -1.4831904 -2.86548889 0.7534370 1.21125890
[3,] -0.5915942 -0.02539844 1.9948173 0.09739178
[4,] 0.3549836 -0.33590215 -0.1102209 1.47607603
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.7907236 0.17820405 0.5190097 0.12431698
[2,] 1.4831904 2.86548889 0.7534370 1.21125890
[3,] 0.5915942 0.02539844 1.9948173 0.09739178
[4,] 0.3549836 0.33590215 0.1102209 1.47607603
> 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,] 10.0394583 0.4221422 0.7204233 0.3525861
[2,] 1.2178631 1.6927755 0.8680075 1.1005721
[3,] 0.7691516 0.1593689 1.4123800 0.3120766
[4,] 0.5958050 0.5795707 0.3319954 1.2149387
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.18531 29.39963 32.72324 28.65018
[2,] 38.66182 44.79324 34.43351 37.21698
[3,] 33.28311 26.61909 41.11862 28.21816
[4,] 31.31303 31.13161 28.43017 38.62546
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5d69a43f70c0>
> exp(tmp5)
<pointer: 0x5d69a43f70c0>
> log(tmp5,2)
<pointer: 0x5d69a43f70c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.7751
> Min(tmp5)
[1] 53.29145
> mean(tmp5)
[1] 73.01763
> Sum(tmp5)
[1] 14603.53
> Var(tmp5)
[1] 880.3501
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.99846 71.55786 67.85971 73.65826 73.28246 69.71466 71.99304 68.60461
[9] 66.59765 74.90964
> rowSums(tmp5)
[1] 1839.969 1431.157 1357.194 1473.165 1465.649 1394.293 1439.861 1372.092
[9] 1331.953 1498.193
> rowVars(tmp5)
[1] 8021.07595 105.91907 89.60614 73.60446 40.23134 108.87917
[7] 82.73328 51.87297 52.08570 104.27169
> rowSd(tmp5)
[1] 89.560460 10.291699 9.466052 8.579304 6.342818 10.434518 9.095784
[8] 7.202289 7.217042 10.211351
> rowMax(tmp5)
[1] 470.77508 93.23127 88.23612 89.06471 86.58928 87.83771 87.36332
[8] 79.73690 78.01813 93.02754
> rowMin(tmp5)
[1] 59.04061 55.77439 53.70719 59.17368 58.81408 55.11986 54.61418 57.80456
[9] 53.29145 55.99435
>
> colMeans(tmp5)
[1] 108.21769 68.67432 72.39173 68.25534 72.61696 68.65007 67.43574
[8] 73.57554 67.66438 70.30818 71.67860 69.06656 74.34746 71.18355
[15] 72.76997 74.61434 72.74653 72.32382 72.18200 71.64990
> colSums(tmp5)
[1] 1082.1769 686.7432 723.9173 682.5534 726.1696 686.5007 674.3574
[8] 735.7554 676.6438 703.0818 716.7860 690.6656 743.4746 711.8355
[15] 727.6997 746.1434 727.4653 723.2382 721.8200 716.4990
> colVars(tmp5)
[1] 16289.38892 158.55020 80.20517 133.50903 59.55674 65.10099
[7] 91.96314 53.82541 61.37482 118.99464 118.51435 126.16376
[13] 113.75970 86.53496 64.55281 46.19926 37.05351 76.83067
[19] 60.81522 71.56474
> colSd(tmp5)
[1] 127.629890 12.591672 8.955734 11.554611 7.717302 8.068518
[7] 9.589741 7.336580 7.834208 10.908467 10.886429 11.232264
[13] 10.665819 9.302417 8.034476 6.797004 6.087159 8.765311
[19] 7.798411 8.459595
> colMax(tmp5)
[1] 470.77508 93.23127 87.36332 87.34938 85.93655 80.28693 78.29409
[8] 88.34551 78.55300 89.24694 88.84534 89.06471 93.02754 87.14775
[15] 87.83771 86.58928 84.95332 83.33524 84.51311 85.98893
> colMin(tmp5)
[1] 54.61418 55.11986 59.17368 56.39731 60.14392 58.19752 53.70719 61.98084
[9] 59.04061 53.29145 54.93590 55.99435 60.17825 59.82035 61.66691 64.43360
[17] 61.61179 60.15433 56.89717 57.80456
>
>
> ### 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] 91.99846 71.55786 67.85971 73.65826 73.28246 69.71466 71.99304 68.60461
[9] NA 74.90964
> rowSums(tmp5)
[1] 1839.969 1431.157 1357.194 1473.165 1465.649 1394.293 1439.861 1372.092
[9] NA 1498.193
> rowVars(tmp5)
[1] 8021.07595 105.91907 89.60614 73.60446 40.23134 108.87917
[7] 82.73328 51.87297 47.02635 104.27169
> rowSd(tmp5)
[1] 89.560460 10.291699 9.466052 8.579304 6.342818 10.434518 9.095784
[8] 7.202289 6.857576 10.211351
> rowMax(tmp5)
[1] 470.77508 93.23127 88.23612 89.06471 86.58928 87.83771 87.36332
[8] 79.73690 NA 93.02754
> rowMin(tmp5)
[1] 59.04061 55.77439 53.70719 59.17368 58.81408 55.11986 54.61418 57.80456
[9] NA 55.99435
>
> colMeans(tmp5)
[1] 108.21769 68.67432 72.39173 68.25534 72.61696 68.65007 67.43574
[8] 73.57554 67.66438 70.30818 NA 69.06656 74.34746 71.18355
[15] 72.76997 74.61434 72.74653 72.32382 72.18200 71.64990
> colSums(tmp5)
[1] 1082.1769 686.7432 723.9173 682.5534 726.1696 686.5007 674.3574
[8] 735.7554 676.6438 703.0818 NA 690.6656 743.4746 711.8355
[15] 727.6997 746.1434 727.4653 723.2382 721.8200 716.4990
> colVars(tmp5)
[1] 16289.38892 158.55020 80.20517 133.50903 59.55674 65.10099
[7] 91.96314 53.82541 61.37482 118.99464 NA 126.16376
[13] 113.75970 86.53496 64.55281 46.19926 37.05351 76.83067
[19] 60.81522 71.56474
> colSd(tmp5)
[1] 127.629890 12.591672 8.955734 11.554611 7.717302 8.068518
[7] 9.589741 7.336580 7.834208 10.908467 NA 11.232264
[13] 10.665819 9.302417 8.034476 6.797004 6.087159 8.765311
[19] 7.798411 8.459595
> colMax(tmp5)
[1] 470.77508 93.23127 87.36332 87.34938 85.93655 80.28693 78.29409
[8] 88.34551 78.55300 89.24694 NA 89.06471 93.02754 87.14775
[15] 87.83771 86.58928 84.95332 83.33524 84.51311 85.98893
> colMin(tmp5)
[1] 54.61418 55.11986 59.17368 56.39731 60.14392 58.19752 53.70719 61.98084
[9] 59.04061 53.29145 NA 55.99435 60.17825 59.82035 61.66691 64.43360
[17] 61.61179 60.15433 56.89717 57.80456
>
> Max(tmp5,na.rm=TRUE)
[1] 470.7751
> Min(tmp5,na.rm=TRUE)
[1] 53.29145
> mean(tmp5,na.rm=TRUE)
[1] 73.1085
> Sum(tmp5,na.rm=TRUE)
[1] 14548.59
> Var(tmp5,na.rm=TRUE)
[1] 883.1367
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.99846 71.55786 67.85971 73.65826 73.28246 69.71466 71.99304 68.60461
[9] 67.21142 74.90964
> rowSums(tmp5,na.rm=TRUE)
[1] 1839.969 1431.157 1357.194 1473.165 1465.649 1394.293 1439.861 1372.092
[9] 1277.017 1498.193
> rowVars(tmp5,na.rm=TRUE)
[1] 8021.07595 105.91907 89.60614 73.60446 40.23134 108.87917
[7] 82.73328 51.87297 47.02635 104.27169
> rowSd(tmp5,na.rm=TRUE)
[1] 89.560460 10.291699 9.466052 8.579304 6.342818 10.434518 9.095784
[8] 7.202289 6.857576 10.211351
> rowMax(tmp5,na.rm=TRUE)
[1] 470.77508 93.23127 88.23612 89.06471 86.58928 87.83771 87.36332
[8] 79.73690 78.01813 93.02754
> rowMin(tmp5,na.rm=TRUE)
[1] 59.04061 55.77439 53.70719 59.17368 58.81408 55.11986 54.61418 57.80456
[9] 53.29145 55.99435
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.21769 68.67432 72.39173 68.25534 72.61696 68.65007 67.43574
[8] 73.57554 67.66438 70.30818 73.53890 69.06656 74.34746 71.18355
[15] 72.76997 74.61434 72.74653 72.32382 72.18200 71.64990
> colSums(tmp5,na.rm=TRUE)
[1] 1082.1769 686.7432 723.9173 682.5534 726.1696 686.5007 674.3574
[8] 735.7554 676.6438 703.0818 661.8501 690.6656 743.4746 711.8355
[15] 727.6997 746.1434 727.4653 723.2382 721.8200 716.4990
> colVars(tmp5,na.rm=TRUE)
[1] 16289.38892 158.55020 80.20517 133.50903 59.55674 65.10099
[7] 91.96314 53.82541 61.37482 118.99464 94.39557 126.16376
[13] 113.75970 86.53496 64.55281 46.19926 37.05351 76.83067
[19] 60.81522 71.56474
> colSd(tmp5,na.rm=TRUE)
[1] 127.629890 12.591672 8.955734 11.554611 7.717302 8.068518
[7] 9.589741 7.336580 7.834208 10.908467 9.715738 11.232264
[13] 10.665819 9.302417 8.034476 6.797004 6.087159 8.765311
[19] 7.798411 8.459595
> colMax(tmp5,na.rm=TRUE)
[1] 470.77508 93.23127 87.36332 87.34938 85.93655 80.28693 78.29409
[8] 88.34551 78.55300 89.24694 88.84534 89.06471 93.02754 87.14775
[15] 87.83771 86.58928 84.95332 83.33524 84.51311 85.98893
> colMin(tmp5,na.rm=TRUE)
[1] 54.61418 55.11986 59.17368 56.39731 60.14392 58.19752 53.70719 61.98084
[9] 59.04061 53.29145 59.60749 55.99435 60.17825 59.82035 61.66691 64.43360
[17] 61.61179 60.15433 56.89717 57.80456
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.99846 71.55786 67.85971 73.65826 73.28246 69.71466 71.99304 68.60461
[9] NaN 74.90964
> rowSums(tmp5,na.rm=TRUE)
[1] 1839.969 1431.157 1357.194 1473.165 1465.649 1394.293 1439.861 1372.092
[9] 0.000 1498.193
> rowVars(tmp5,na.rm=TRUE)
[1] 8021.07595 105.91907 89.60614 73.60446 40.23134 108.87917
[7] 82.73328 51.87297 NA 104.27169
> rowSd(tmp5,na.rm=TRUE)
[1] 89.560460 10.291699 9.466052 8.579304 6.342818 10.434518 9.095784
[8] 7.202289 NA 10.211351
> rowMax(tmp5,na.rm=TRUE)
[1] 470.77508 93.23127 88.23612 89.06471 86.58928 87.83771 87.36332
[8] 79.73690 NA 93.02754
> rowMin(tmp5,na.rm=TRUE)
[1] 59.04061 55.77439 53.70719 59.17368 58.81408 55.11986 54.61418 57.80456
[9] NA 55.99435
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.57320 68.88334 72.37340 69.24672 72.88220 67.79741 67.57615
[8] 74.31163 68.44663 72.19893 NaN 68.65180 75.88720 71.93037
[15] 72.64439 74.65640 73.05564 73.23403 73.88031 71.85068
> colSums(tmp5,na.rm=TRUE)
[1] 1004.1588 619.9500 651.3606 623.2205 655.9398 610.1767 608.1854
[8] 668.8046 616.0197 649.7903 0.0000 617.8662 682.9848 647.3734
[15] 653.7995 671.9076 657.5008 659.1063 664.9228 646.6561
> colVars(tmp5,na.rm=TRUE)
[1] 18198.89399 177.87748 90.22704 139.14083 66.20988 65.05949
[7] 103.23674 54.45813 62.16265 93.65104 NA 139.99890
[13] 101.30818 91.07727 72.44448 51.95426 40.61023 77.11413
[19] 35.96909 80.05682
> colSd(tmp5,na.rm=TRUE)
[1] 134.903276 13.337071 9.498791 11.795797 8.136945 8.065946
[7] 10.160548 7.379575 7.884329 9.677347 NA 11.832113
[13] 10.065197 9.543441 8.511432 7.207930 6.372615 8.781465
[19] 5.997423 8.947447
> colMax(tmp5,na.rm=TRUE)
[1] 470.77508 93.23127 87.36332 87.34938 85.93655 80.28693 78.29409
[8] 88.34551 78.55300 89.24694 -Inf 89.06471 93.02754 87.14775
[15] 87.83771 86.58928 84.95332 83.33524 84.51311 85.98893
> colMin(tmp5,na.rm=TRUE)
[1] 54.61418 55.11986 59.17368 56.39731 60.14392 58.19752 53.70719 61.98084
[9] 59.04061 55.77439 Inf 55.99435 60.17825 59.82035 61.66691 64.43360
[17] 61.61179 60.15433 66.68423 57.80456
>
>
>
>
> 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] 216.01336 214.45521 97.29971 249.25817 147.49823 122.19664 130.60267
[8] 205.44034 183.91136 133.54030
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 216.01336 214.45521 97.29971 249.25817 147.49823 122.19664 130.60267
[8] 205.44034 183.91136 133.54030
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 1.136868e-13 0.000000e+00 1.136868e-13 -1.705303e-13
[6] 1.421085e-13 -1.705303e-13 1.989520e-13 0.000000e+00 0.000000e+00
[11] 1.136868e-13 1.136868e-13 5.684342e-14 7.105427e-14 3.410605e-13
[16] 1.705303e-13 0.000000e+00 -1.421085e-13 -5.684342e-14 1.421085e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
8 15
8 11
8 6
10 8
4 14
9 16
10 4
7 4
3 7
2 4
7 1
4 14
2 7
3 14
10 2
9 1
7 18
1 5
3 2
3 7
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] 2.756983
> Min(tmp)
[1] -2.041116
> mean(tmp)
[1] 0.1760855
> Sum(tmp)
[1] 17.60855
> Var(tmp)
[1] 0.9141502
>
> rowMeans(tmp)
[1] 0.1760855
> rowSums(tmp)
[1] 17.60855
> rowVars(tmp)
[1] 0.9141502
> rowSd(tmp)
[1] 0.956112
> rowMax(tmp)
[1] 2.756983
> rowMin(tmp)
[1] -2.041116
>
> colMeans(tmp)
[1] -0.11837767 -0.19172614 -0.22598059 -2.04111628 0.53678285 -0.29258192
[7] 0.62610853 0.33014335 1.38792437 0.13024985 0.41637784 0.12825567
[13] -1.40101929 -0.63067924 1.46125728 0.02415404 0.89227566 -0.39860235
[19] -0.41684848 -1.08822483 -0.09952648 -1.17057262 1.11107025 0.86336212
[25] 0.71846538 -0.11556604 -1.02038646 0.47150746 -0.25810882 1.91600085
[31] -0.74904874 -0.78695378 2.75698337 1.36182001 0.24736200 1.84610475
[37] 1.65747704 0.52560241 0.25245418 -0.23125188 0.70212801 2.63001967
[43] 1.28961659 -0.42798357 0.07071461 -0.88580075 0.70575833 0.28669500
[49] 2.20224233 -0.56491680 0.85784190 -1.32459820 1.47049980 1.20728569
[55] 1.88161667 -0.01184464 0.48902322 1.16768147 -0.65666754 0.59495776
[61] 0.56185176 1.79767555 -0.24915188 1.13518533 0.27000341 -1.30109683
[67] 0.82982415 -0.23558285 0.80496294 0.29317558 -0.63522394 -1.16005464
[73] 0.44209479 0.14802564 -1.34614178 -1.26458672 -1.06469198 -1.55971894
[79] 0.31180471 -0.17987575 -1.57836115 -0.24168343 0.01335301 0.10861332
[85] -0.54465992 0.25917771 0.67348637 0.68345815 -0.59787919 -0.25484005
[91] -0.15978624 -0.26200385 -0.96816892 0.05574547 0.65914232 1.08864471
[97] 0.90969220 -0.34687597 0.63644323 -0.23285899
> colSums(tmp)
[1] -0.11837767 -0.19172614 -0.22598059 -2.04111628 0.53678285 -0.29258192
[7] 0.62610853 0.33014335 1.38792437 0.13024985 0.41637784 0.12825567
[13] -1.40101929 -0.63067924 1.46125728 0.02415404 0.89227566 -0.39860235
[19] -0.41684848 -1.08822483 -0.09952648 -1.17057262 1.11107025 0.86336212
[25] 0.71846538 -0.11556604 -1.02038646 0.47150746 -0.25810882 1.91600085
[31] -0.74904874 -0.78695378 2.75698337 1.36182001 0.24736200 1.84610475
[37] 1.65747704 0.52560241 0.25245418 -0.23125188 0.70212801 2.63001967
[43] 1.28961659 -0.42798357 0.07071461 -0.88580075 0.70575833 0.28669500
[49] 2.20224233 -0.56491680 0.85784190 -1.32459820 1.47049980 1.20728569
[55] 1.88161667 -0.01184464 0.48902322 1.16768147 -0.65666754 0.59495776
[61] 0.56185176 1.79767555 -0.24915188 1.13518533 0.27000341 -1.30109683
[67] 0.82982415 -0.23558285 0.80496294 0.29317558 -0.63522394 -1.16005464
[73] 0.44209479 0.14802564 -1.34614178 -1.26458672 -1.06469198 -1.55971894
[79] 0.31180471 -0.17987575 -1.57836115 -0.24168343 0.01335301 0.10861332
[85] -0.54465992 0.25917771 0.67348637 0.68345815 -0.59787919 -0.25484005
[91] -0.15978624 -0.26200385 -0.96816892 0.05574547 0.65914232 1.08864471
[97] 0.90969220 -0.34687597 0.63644323 -0.23285899
> 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] -0.11837767 -0.19172614 -0.22598059 -2.04111628 0.53678285 -0.29258192
[7] 0.62610853 0.33014335 1.38792437 0.13024985 0.41637784 0.12825567
[13] -1.40101929 -0.63067924 1.46125728 0.02415404 0.89227566 -0.39860235
[19] -0.41684848 -1.08822483 -0.09952648 -1.17057262 1.11107025 0.86336212
[25] 0.71846538 -0.11556604 -1.02038646 0.47150746 -0.25810882 1.91600085
[31] -0.74904874 -0.78695378 2.75698337 1.36182001 0.24736200 1.84610475
[37] 1.65747704 0.52560241 0.25245418 -0.23125188 0.70212801 2.63001967
[43] 1.28961659 -0.42798357 0.07071461 -0.88580075 0.70575833 0.28669500
[49] 2.20224233 -0.56491680 0.85784190 -1.32459820 1.47049980 1.20728569
[55] 1.88161667 -0.01184464 0.48902322 1.16768147 -0.65666754 0.59495776
[61] 0.56185176 1.79767555 -0.24915188 1.13518533 0.27000341 -1.30109683
[67] 0.82982415 -0.23558285 0.80496294 0.29317558 -0.63522394 -1.16005464
[73] 0.44209479 0.14802564 -1.34614178 -1.26458672 -1.06469198 -1.55971894
[79] 0.31180471 -0.17987575 -1.57836115 -0.24168343 0.01335301 0.10861332
[85] -0.54465992 0.25917771 0.67348637 0.68345815 -0.59787919 -0.25484005
[91] -0.15978624 -0.26200385 -0.96816892 0.05574547 0.65914232 1.08864471
[97] 0.90969220 -0.34687597 0.63644323 -0.23285899
> colMin(tmp)
[1] -0.11837767 -0.19172614 -0.22598059 -2.04111628 0.53678285 -0.29258192
[7] 0.62610853 0.33014335 1.38792437 0.13024985 0.41637784 0.12825567
[13] -1.40101929 -0.63067924 1.46125728 0.02415404 0.89227566 -0.39860235
[19] -0.41684848 -1.08822483 -0.09952648 -1.17057262 1.11107025 0.86336212
[25] 0.71846538 -0.11556604 -1.02038646 0.47150746 -0.25810882 1.91600085
[31] -0.74904874 -0.78695378 2.75698337 1.36182001 0.24736200 1.84610475
[37] 1.65747704 0.52560241 0.25245418 -0.23125188 0.70212801 2.63001967
[43] 1.28961659 -0.42798357 0.07071461 -0.88580075 0.70575833 0.28669500
[49] 2.20224233 -0.56491680 0.85784190 -1.32459820 1.47049980 1.20728569
[55] 1.88161667 -0.01184464 0.48902322 1.16768147 -0.65666754 0.59495776
[61] 0.56185176 1.79767555 -0.24915188 1.13518533 0.27000341 -1.30109683
[67] 0.82982415 -0.23558285 0.80496294 0.29317558 -0.63522394 -1.16005464
[73] 0.44209479 0.14802564 -1.34614178 -1.26458672 -1.06469198 -1.55971894
[79] 0.31180471 -0.17987575 -1.57836115 -0.24168343 0.01335301 0.10861332
[85] -0.54465992 0.25917771 0.67348637 0.68345815 -0.59787919 -0.25484005
[91] -0.15978624 -0.26200385 -0.96816892 0.05574547 0.65914232 1.08864471
[97] 0.90969220 -0.34687597 0.63644323 -0.23285899
> colMedians(tmp)
[1] -0.11837767 -0.19172614 -0.22598059 -2.04111628 0.53678285 -0.29258192
[7] 0.62610853 0.33014335 1.38792437 0.13024985 0.41637784 0.12825567
[13] -1.40101929 -0.63067924 1.46125728 0.02415404 0.89227566 -0.39860235
[19] -0.41684848 -1.08822483 -0.09952648 -1.17057262 1.11107025 0.86336212
[25] 0.71846538 -0.11556604 -1.02038646 0.47150746 -0.25810882 1.91600085
[31] -0.74904874 -0.78695378 2.75698337 1.36182001 0.24736200 1.84610475
[37] 1.65747704 0.52560241 0.25245418 -0.23125188 0.70212801 2.63001967
[43] 1.28961659 -0.42798357 0.07071461 -0.88580075 0.70575833 0.28669500
[49] 2.20224233 -0.56491680 0.85784190 -1.32459820 1.47049980 1.20728569
[55] 1.88161667 -0.01184464 0.48902322 1.16768147 -0.65666754 0.59495776
[61] 0.56185176 1.79767555 -0.24915188 1.13518533 0.27000341 -1.30109683
[67] 0.82982415 -0.23558285 0.80496294 0.29317558 -0.63522394 -1.16005464
[73] 0.44209479 0.14802564 -1.34614178 -1.26458672 -1.06469198 -1.55971894
[79] 0.31180471 -0.17987575 -1.57836115 -0.24168343 0.01335301 0.10861332
[85] -0.54465992 0.25917771 0.67348637 0.68345815 -0.59787919 -0.25484005
[91] -0.15978624 -0.26200385 -0.96816892 0.05574547 0.65914232 1.08864471
[97] 0.90969220 -0.34687597 0.63644323 -0.23285899
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1183777 -0.1917261 -0.2259806 -2.041116 0.5367828 -0.2925819 0.6261085
[2,] -0.1183777 -0.1917261 -0.2259806 -2.041116 0.5367828 -0.2925819 0.6261085
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.3301434 1.387924 0.1302499 0.4163778 0.1282557 -1.401019 -0.6306792
[2,] 0.3301434 1.387924 0.1302499 0.4163778 0.1282557 -1.401019 -0.6306792
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.461257 0.02415404 0.8922757 -0.3986024 -0.4168485 -1.088225 -0.09952648
[2,] 1.461257 0.02415404 0.8922757 -0.3986024 -0.4168485 -1.088225 -0.09952648
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.170573 1.11107 0.8633621 0.7184654 -0.115566 -1.020386 0.4715075
[2,] -1.170573 1.11107 0.8633621 0.7184654 -0.115566 -1.020386 0.4715075
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.2581088 1.916001 -0.7490487 -0.7869538 2.756983 1.36182 0.247362
[2,] -0.2581088 1.916001 -0.7490487 -0.7869538 2.756983 1.36182 0.247362
[,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 1.846105 1.657477 0.5256024 0.2524542 -0.2312519 0.702128 2.63002 1.289617
[2,] 1.846105 1.657477 0.5256024 0.2524542 -0.2312519 0.702128 2.63002 1.289617
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] -0.4279836 0.07071461 -0.8858007 0.7057583 0.286695 2.202242 -0.5649168
[2,] -0.4279836 0.07071461 -0.8858007 0.7057583 0.286695 2.202242 -0.5649168
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] 0.8578419 -1.324598 1.4705 1.207286 1.881617 -0.01184464 0.4890232
[2,] 0.8578419 -1.324598 1.4705 1.207286 1.881617 -0.01184464 0.4890232
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] 1.167681 -0.6566675 0.5949578 0.5618518 1.797676 -0.2491519 1.135185
[2,] 1.167681 -0.6566675 0.5949578 0.5618518 1.797676 -0.2491519 1.135185
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] 0.2700034 -1.301097 0.8298242 -0.2355829 0.8049629 0.2931756 -0.6352239
[2,] 0.2700034 -1.301097 0.8298242 -0.2355829 0.8049629 0.2931756 -0.6352239
[,72] [,73] [,74] [,75] [,76] [,77] [,78]
[1,] -1.160055 0.4420948 0.1480256 -1.346142 -1.264587 -1.064692 -1.559719
[2,] -1.160055 0.4420948 0.1480256 -1.346142 -1.264587 -1.064692 -1.559719
[,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] 0.3118047 -0.1798758 -1.578361 -0.2416834 0.01335301 0.1086133 -0.5446599
[2,] 0.3118047 -0.1798758 -1.578361 -0.2416834 0.01335301 0.1086133 -0.5446599
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] 0.2591777 0.6734864 0.6834582 -0.5978792 -0.2548401 -0.1597862 -0.2620039
[2,] 0.2591777 0.6734864 0.6834582 -0.5978792 -0.2548401 -0.1597862 -0.2620039
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] -0.9681689 0.05574547 0.6591423 1.088645 0.9096922 -0.346876 0.6364432
[2,] -0.9681689 0.05574547 0.6591423 1.088645 0.9096922 -0.346876 0.6364432
[,100]
[1,] -0.232859
[2,] -0.232859
>
>
> Max(tmp2)
[1] 2.556131
> Min(tmp2)
[1] -3.146281
> mean(tmp2)
[1] -0.1086454
> Sum(tmp2)
[1] -10.86454
> Var(tmp2)
[1] 1.064975
>
> rowMeans(tmp2)
[1] -1.305723227 0.967515236 0.026285936 -0.575849655 0.492548203
[6] 0.095297115 0.140908640 1.413136884 -0.906009122 0.979026865
[11] 1.164393119 -2.834647694 0.843238329 1.024945693 -0.247392015
[16] 0.824754080 -0.360883978 1.147811486 0.578289372 0.201330360
[21] 0.228162176 2.556131441 -1.856157807 -0.229409743 -0.718158293
[26] -0.618729273 0.374399704 -0.621423053 1.738085099 -0.907460392
[31] -0.683177422 1.161395836 -0.312497069 0.280056480 -0.537780904
[36] -0.434384781 -1.139875180 0.831833650 1.502855373 -0.864580541
[41] -0.448214589 -0.463246259 -0.349032539 -1.018754410 -0.086173655
[46] 0.621704331 0.531158971 0.526622001 -1.483237627 -0.169971563
[51] 0.094778226 -1.690215757 0.005271669 -1.488329491 0.164247272
[56] -0.603370337 0.369641692 -2.325988303 -0.295113144 -0.385915672
[61] -0.765296517 -1.228488747 -0.021166091 0.209469669 0.935265803
[66] -0.242522049 0.128697424 0.416761912 1.188457060 1.205837138
[71] 1.007215016 0.996769862 -0.180611652 -0.943245760 1.752988697
[76] -0.431706196 -1.603868231 -0.059356850 -0.332878467 0.378985914
[81] 0.661503806 -0.246220770 -1.133498229 -0.631096957 -2.064482850
[86] 0.274386931 -1.306963256 0.918222564 0.150118923 0.999875577
[91] -0.866954227 -0.430419938 -1.003353282 1.809172049 -3.146280769
[96] -0.191038041 -2.218643915 -0.684495167 -0.194312731 1.104510904
> rowSums(tmp2)
[1] -1.305723227 0.967515236 0.026285936 -0.575849655 0.492548203
[6] 0.095297115 0.140908640 1.413136884 -0.906009122 0.979026865
[11] 1.164393119 -2.834647694 0.843238329 1.024945693 -0.247392015
[16] 0.824754080 -0.360883978 1.147811486 0.578289372 0.201330360
[21] 0.228162176 2.556131441 -1.856157807 -0.229409743 -0.718158293
[26] -0.618729273 0.374399704 -0.621423053 1.738085099 -0.907460392
[31] -0.683177422 1.161395836 -0.312497069 0.280056480 -0.537780904
[36] -0.434384781 -1.139875180 0.831833650 1.502855373 -0.864580541
[41] -0.448214589 -0.463246259 -0.349032539 -1.018754410 -0.086173655
[46] 0.621704331 0.531158971 0.526622001 -1.483237627 -0.169971563
[51] 0.094778226 -1.690215757 0.005271669 -1.488329491 0.164247272
[56] -0.603370337 0.369641692 -2.325988303 -0.295113144 -0.385915672
[61] -0.765296517 -1.228488747 -0.021166091 0.209469669 0.935265803
[66] -0.242522049 0.128697424 0.416761912 1.188457060 1.205837138
[71] 1.007215016 0.996769862 -0.180611652 -0.943245760 1.752988697
[76] -0.431706196 -1.603868231 -0.059356850 -0.332878467 0.378985914
[81] 0.661503806 -0.246220770 -1.133498229 -0.631096957 -2.064482850
[86] 0.274386931 -1.306963256 0.918222564 0.150118923 0.999875577
[91] -0.866954227 -0.430419938 -1.003353282 1.809172049 -3.146280769
[96] -0.191038041 -2.218643915 -0.684495167 -0.194312731 1.104510904
> 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] -1.305723227 0.967515236 0.026285936 -0.575849655 0.492548203
[6] 0.095297115 0.140908640 1.413136884 -0.906009122 0.979026865
[11] 1.164393119 -2.834647694 0.843238329 1.024945693 -0.247392015
[16] 0.824754080 -0.360883978 1.147811486 0.578289372 0.201330360
[21] 0.228162176 2.556131441 -1.856157807 -0.229409743 -0.718158293
[26] -0.618729273 0.374399704 -0.621423053 1.738085099 -0.907460392
[31] -0.683177422 1.161395836 -0.312497069 0.280056480 -0.537780904
[36] -0.434384781 -1.139875180 0.831833650 1.502855373 -0.864580541
[41] -0.448214589 -0.463246259 -0.349032539 -1.018754410 -0.086173655
[46] 0.621704331 0.531158971 0.526622001 -1.483237627 -0.169971563
[51] 0.094778226 -1.690215757 0.005271669 -1.488329491 0.164247272
[56] -0.603370337 0.369641692 -2.325988303 -0.295113144 -0.385915672
[61] -0.765296517 -1.228488747 -0.021166091 0.209469669 0.935265803
[66] -0.242522049 0.128697424 0.416761912 1.188457060 1.205837138
[71] 1.007215016 0.996769862 -0.180611652 -0.943245760 1.752988697
[76] -0.431706196 -1.603868231 -0.059356850 -0.332878467 0.378985914
[81] 0.661503806 -0.246220770 -1.133498229 -0.631096957 -2.064482850
[86] 0.274386931 -1.306963256 0.918222564 0.150118923 0.999875577
[91] -0.866954227 -0.430419938 -1.003353282 1.809172049 -3.146280769
[96] -0.191038041 -2.218643915 -0.684495167 -0.194312731 1.104510904
> rowMin(tmp2)
[1] -1.305723227 0.967515236 0.026285936 -0.575849655 0.492548203
[6] 0.095297115 0.140908640 1.413136884 -0.906009122 0.979026865
[11] 1.164393119 -2.834647694 0.843238329 1.024945693 -0.247392015
[16] 0.824754080 -0.360883978 1.147811486 0.578289372 0.201330360
[21] 0.228162176 2.556131441 -1.856157807 -0.229409743 -0.718158293
[26] -0.618729273 0.374399704 -0.621423053 1.738085099 -0.907460392
[31] -0.683177422 1.161395836 -0.312497069 0.280056480 -0.537780904
[36] -0.434384781 -1.139875180 0.831833650 1.502855373 -0.864580541
[41] -0.448214589 -0.463246259 -0.349032539 -1.018754410 -0.086173655
[46] 0.621704331 0.531158971 0.526622001 -1.483237627 -0.169971563
[51] 0.094778226 -1.690215757 0.005271669 -1.488329491 0.164247272
[56] -0.603370337 0.369641692 -2.325988303 -0.295113144 -0.385915672
[61] -0.765296517 -1.228488747 -0.021166091 0.209469669 0.935265803
[66] -0.242522049 0.128697424 0.416761912 1.188457060 1.205837138
[71] 1.007215016 0.996769862 -0.180611652 -0.943245760 1.752988697
[76] -0.431706196 -1.603868231 -0.059356850 -0.332878467 0.378985914
[81] 0.661503806 -0.246220770 -1.133498229 -0.631096957 -2.064482850
[86] 0.274386931 -1.306963256 0.918222564 0.150118923 0.999875577
[91] -0.866954227 -0.430419938 -1.003353282 1.809172049 -3.146280769
[96] -0.191038041 -2.218643915 -0.684495167 -0.194312731 1.104510904
>
> colMeans(tmp2)
[1] -0.1086454
> colSums(tmp2)
[1] -10.86454
> colVars(tmp2)
[1] 1.064975
> colSd(tmp2)
[1] 1.031976
> colMax(tmp2)
[1] 2.556131
> colMin(tmp2)
[1] -3.146281
> colMedians(tmp2)
[1] -0.1752916
> colRanges(tmp2)
[,1]
[1,] -3.146281
[2,] 2.556131
>
> 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] -2.4200226 2.4489532 7.0492706 -4.7851361 5.7978042 -0.0540844
[7] 0.8021530 -2.0723221 1.6946429 -1.8210594
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6029888
[2,] -0.8116309
[3,] -0.2596295
[4,] 0.1412665
[5,] 1.8594450
>
> rowApply(tmp,sum)
[1] -2.7919011 0.5903618 0.8741322 2.8217019 -2.5243976 2.9430120
[7] 2.2461711 -2.4537435 3.4396985 1.4951640
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 6 5 5 2 5 5 4 10 1
[2,] 10 1 3 9 6 3 7 2 7 9
[3,] 6 9 7 10 8 8 8 5 3 10
[4,] 1 3 2 2 1 9 2 3 6 5
[5,] 2 10 1 4 10 7 10 10 9 6
[6,] 4 8 6 3 7 6 1 8 8 8
[7,] 7 7 9 1 9 10 6 9 2 2
[8,] 8 2 8 6 3 2 3 6 4 3
[9,] 9 5 10 7 5 4 9 1 1 7
[10,] 5 4 4 8 4 1 4 7 5 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.94058248 -1.20884661 1.76086308 -1.19216009 3.96325981 -3.24559327
[7] -4.24340107 0.20458675 5.03305214 0.82642698 5.31167376 0.05171861
[13] -0.42620684 -2.55481940 1.88027747 -1.49403904 -2.65843048 -4.12329591
[19] -2.65838854 -3.99888624
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.07712106
[2,] 0.25165561
[3,] 0.31211175
[4,] 0.41859083
[5,] 0.88110323
>
> rowApply(tmp,sum)
[1] -3.015982 -5.688567 -2.566223 1.548837 2.890308
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 15 12 17 10
[2,] 5 12 16 9 5
[3,] 13 5 14 18 15
[4,] 4 7 6 16 16
[5,] 20 17 15 19 6
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.07712106 -1.33098333 0.2202052 -1.3542634 2.1152244 -0.2787504
[2,] 0.41859083 -0.02104005 -0.8975801 -0.7426516 0.6316361 -2.3204362
[3,] 0.25165561 0.96901486 0.2972315 -0.9697426 0.3371991 0.2893740
[4,] 0.88110323 0.17618363 1.1076408 0.8148127 1.4442160 0.2544171
[5,] 0.31211175 -1.00202172 1.0333656 1.0596848 -0.5650159 -1.1901978
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.3142115 -1.8531708 0.9592921 0.7194641 1.8316041 -0.4004971
[2,] -0.5283528 0.5541777 0.6885777 0.2468361 0.6462692 -0.9576330
[3,] -1.6658185 -0.8518432 2.1299894 1.2960918 0.9852173 0.1741673
[4,] 0.5600904 2.0531661 -0.4892470 -1.6189293 0.4518818 0.7237566
[5,] -2.2951088 0.3022569 1.7444401 0.1829642 1.3967014 0.5119248
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.0859602 0.20252535 0.4982612 0.70238636 1.8641972 -3.3502097
[2,] 1.1116800 0.01281738 -0.1363310 -1.50767854 -0.8264189 -0.1259636
[3,] -0.3713662 -1.19452625 1.2336947 -0.05707332 -1.5681433 -1.7290524
[4,] -0.6364861 -0.08930951 -1.0608066 0.54123829 -2.6692088 0.4204196
[5,] 0.5559256 -1.48632637 1.3454592 -1.17291182 0.5411433 0.6615102
[,19] [,20]
[1,] -0.19368910 -2.0445275
[2,] -1.48250131 -0.4525648
[3,] -0.06025662 -2.0620365
[4,] -0.45984064 -0.8562609
[5,] -0.46210086 1.4165035
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.5500864 -0.1930665 -0.4967342 0.4144091 1.143031 1.923756 -0.3157482
col8 col9 col10 col11 col12 col13 col14
row1 -1.465757 -1.458607 -1.714323 -0.7267976 0.5499303 0.8797812 0.2768584
col15 col16 col17 col18 col19 col20
row1 1.223874 0.1752388 1.519179 0.4475276 -1.174762 0.5538453
> tmp[,"col10"]
col10
row1 -1.7143228
row2 0.4220037
row3 -0.2530549
row4 1.6639287
row5 -0.4594253
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.5500864 -0.1930665 -0.4967342 0.4144091 1.143031 1.9237557 -0.3157482
row5 -0.2309596 0.2322773 1.0155286 -0.2339955 1.779828 -0.5426777 -0.7115973
col8 col9 col10 col11 col12 col13
row1 -1.4657574 -1.4586065 -1.7143228 -0.7267976 0.5499303 0.8797812
row5 0.9510468 -0.7947709 -0.4594253 -0.9245502 -1.3206286 -0.3271831
col14 col15 col16 col17 col18 col19 col20
row1 0.2768584 1.2238737 0.1752388 1.519179 0.4475276 -1.174762 0.5538453
row5 -0.2135732 -0.2800396 0.5316035 -1.077768 0.4829820 2.145112 1.3252572
> tmp[,c("col6","col20")]
col6 col20
row1 1.9237557 0.5538453
row2 0.2645631 0.7881648
row3 -1.1606174 0.4158708
row4 -0.9826736 -0.1895990
row5 -0.5426777 1.3252572
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.9237557 0.5538453
row5 -0.5426777 1.3252572
>
>
>
>
> 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 50.24002 50.50266 51.53668 49.60473 49.80486 104.9393 48.62259 49.06963
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.8747 50.07161 50.58713 47.9224 49.58141 50.75654 49.23088 49.37735
col17 col18 col19 col20
row1 50.46591 49.00661 50.19784 105.7341
> tmp[,"col10"]
col10
row1 50.07161
row2 30.27279
row3 32.14992
row4 30.95313
row5 48.73848
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.24002 50.50266 51.53668 49.60473 49.80486 104.9393 48.62259 49.06963
row5 49.57084 51.44496 50.87121 49.02961 51.56830 107.8111 47.91614 48.73796
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.87470 50.07161 50.58713 47.92240 49.58141 50.75654 49.23088 49.37735
row5 51.25726 48.73848 49.99041 48.49016 50.51173 48.68191 49.00917 47.37621
col17 col18 col19 col20
row1 50.46591 49.00661 50.19784 105.7341
row5 49.06885 50.40985 48.76783 105.6581
> tmp[,c("col6","col20")]
col6 col20
row1 104.93934 105.73413
row2 74.23997 77.11643
row3 74.10718 76.34406
row4 75.43948 73.99687
row5 107.81114 105.65808
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9393 105.7341
row5 107.8111 105.6581
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9393 105.7341
row5 107.8111 105.6581
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.1834391
[2,] -1.2593163
[3,] 0.7536344
[4,] -1.3712694
[5,] -0.3188324
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.4565334 0.12651809
[2,] -0.5706404 1.47450703
[3,] -0.2056369 1.45048225
[4,] -1.1246397 0.03362381
[5,] -1.4717456 0.40386674
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.6727332 0.4477057
[2,] -1.3390737 0.3119131
[3,] 1.2271258 -1.1934003
[4,] 0.2214509 0.6834657
[5,] 0.2269805 -0.4222216
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.6727332
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.6727332
[2,] -1.3390737
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.9742988 0.6840310 -1.2696063 0.7826641 1.265547 -0.9121573 -1.544795
row1 -0.5093915 0.6144267 0.2494923 -0.8647914 -1.055280 -0.5046613 -1.085806
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.91666972 1.2545328 -1.1409261 -1.4742148 -2.2596270 -1.5692942
row1 0.06922017 -0.1508492 -0.1523743 0.7844815 0.3494478 -0.9172973
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.1154464 0.07628607 -0.4349292 1.0203261 1.35171939 -0.3885036
row1 0.4971636 0.76624794 0.6716894 -0.5585122 -0.04818671 0.7142126
[,20]
row3 0.89909581
row1 0.02687699
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.137191 -1.134077 -0.1033408 -0.8545187 -0.2053735 0.2600403 -0.4318999
[,8] [,9] [,10]
row2 -0.3264265 1.049186 0.3047114
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.122591 -0.2844012 -1.905261 0.0422294 -0.8043969 -1.438712 1.532202
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.3830088 0.3179606 -1.150317 0.02139624 -0.2576819 1.082989 -0.07471329
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.516744 0.3100019 -1.182406 0.250835 -1.760695 1.108825
>
>
> 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: 0x5d69a4348040>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc8603bcdcaf6"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc8602c13b549"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc86023f2fee0"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc86031064680"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc86029982c13"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc8605dad4ca9"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc8607d28064e"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc8603740018a"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc86060d359e9"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc860614513b9"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc8601d16577d"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc860513ffba2"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc8604915d7ea"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc86014203ef6"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fc860799e4329"
>
>
> ### 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: 0x5d69a48f0660>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5d69a48f0660>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5d69a48f0660>
> rowMedians(tmp)
[1] -0.043582254 -0.149305210 0.199930001 -0.100901579 -0.414958305
[6] 0.376662991 0.075932043 0.279680916 0.032977027 -0.150505579
[11] -0.223172440 -0.072646725 -0.240656743 -0.119646922 -0.257322433
[16] 0.018104674 -0.425781174 0.486288618 -0.483804932 -0.395627713
[21] 0.016941443 0.136722364 0.017135558 0.041646322 -0.758958296
[26] -0.180134054 0.896363146 -0.310401398 0.190364668 0.475863872
[31] -0.286316354 -0.372465758 -0.231305953 -0.371963447 -0.080901792
[36] 0.001902417 -0.411711788 0.032091859 0.603524108 -0.630889330
[41] 0.307180056 0.027447221 -0.469482101 0.287462515 -0.306994617
[46] 0.213896282 -0.159409907 -0.536470861 -0.075247836 -0.162670065
[51] 0.500398287 0.030213409 0.120340061 -0.157028418 -0.268668140
[56] -0.135270760 -0.346635096 0.674238885 0.536152588 -0.291007558
[61] -0.045074627 -0.254494182 0.217320656 0.059878205 -0.064746462
[66] -0.483274350 -0.536644469 0.833612778 0.240742207 0.022671695
[71] 0.621261272 -0.416619188 -0.017022171 -0.271836157 0.451164581
[76] -0.692343471 -0.535178294 0.431400595 0.243791754 -0.326581799
[81] -0.170806175 0.554749259 -0.078070622 -0.082285433 0.511488523
[86] 0.261594592 -0.087926510 -0.116360864 -0.360970176 -0.424033160
[91] 0.337715182 -0.054454161 -0.301460813 0.374360227 0.126119552
[96] 0.398919811 -0.253333725 0.103191182 0.652094219 0.104212088
[101] -0.655998016 0.071292980 -0.129243825 0.389471249 -0.230494413
[106] 0.010318611 -0.133323003 0.319746292 0.046354403 -0.199086901
[111] -0.162864128 -0.442586325 0.393556049 -0.306855865 0.329553848
[116] -0.702344445 -0.144593445 0.431115820 -0.626830019 -0.550204011
[121] -0.699376634 -0.287610549 -0.639750211 -0.359357725 -0.162169810
[126] -0.121109197 0.106373557 -0.018870687 0.117821924 0.277765078
[131] 0.065822281 -0.250421148 -0.158730457 0.066098449 -0.094718477
[136] -0.592417782 0.513653185 0.093374322 0.060827058 0.094768094
[141] -0.153807461 0.636346475 0.165914854 -0.270266162 -0.231480247
[146] -0.097288704 0.044935851 -0.697737262 0.381199056 0.014415132
[151] -0.293245968 -0.444472517 0.551072436 0.558285949 -0.220706972
[156] -0.067846166 0.311610603 -0.358759646 0.018436310 0.435599354
[161] 0.339692230 0.260692914 -0.047222699 -0.499078835 -0.441618994
[166] -0.516099462 0.233496681 -0.123797845 0.127165514 0.158447482
[171] -0.089558048 -0.302134487 0.028648889 0.413642484 -0.201520660
[176] -0.070033133 0.314390807 -0.845521642 0.278320774 -0.316285777
[181] 0.269571580 -0.577588383 0.123411532 0.254449329 -0.076887054
[186] 0.490654913 -0.167421122 -0.147390787 -0.237502817 0.169318715
[191] 0.040895328 -0.273550724 0.250688469 -0.366363658 0.082567991
[196] 0.437999779 0.108379926 -0.172413906 -0.009183286 -0.899493048
[201] -0.193967400 -0.177589497 0.225428315 -0.489196171 -0.498421617
[206] 0.300024537 0.286948075 -0.123280263 -0.023211452 0.269222168
[211] -0.057022749 -0.245080560 0.190697299 0.020832589 -0.067313025
[216] 0.658180724 0.812645789 -0.158950807 -0.109499229 -0.113055370
[221] 0.330007538 -0.244994078 0.147489499 -0.062937839 -0.124793925
[226] 0.005283141 0.124281499 0.154010275 0.207448458 0.062639808
>
> proc.time()
user system elapsed
1.276 1.599 2.864
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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: 0x62bffc51b0f0>
> .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: 0x62bffc51b0f0>
> .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: 0x62bffc51b0f0>
> .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: 0x62bffc51b0f0>
> 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: 0x62bffd369690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffd369690>
> .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: 0x62bffd369690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffd369690>
> .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: 0x62bffd369690>
> 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: 0x62bffeda3010>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffeda3010>
> .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: 0x62bffeda3010>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x62bffeda3010>
> .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: 0x62bffeda3010>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x62bffeda3010>
> .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: 0x62bffeda3010>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x62bffeda3010>
> .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: 0x62bffeda3010>
> 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: 0x62bffedf3070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x62bffedf3070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffedf3070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffedf3070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2fd8b7718ef9a3" "BufferedMatrixFile2fd8b77c371cb9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2fd8b7718ef9a3" "BufferedMatrixFile2fd8b77c371cb9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffcaad7e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffcaad7e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x62bffcaad7e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x62bffcaad7e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x62bffcaad7e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x62bffcaad7e0>
> .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: 0x62bffea493b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62bffea493b0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x62bffea493b0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x62bffea493b0>
> 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: 0x62bffcc0f520>
> .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: 0x62bffcc0f520>
> rm(P)
>
> proc.time()
user system elapsed
0.249 0.053 0.291
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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Platform: x86_64-pc-linux-gnu
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.242 0.045 0.292