Ben Bolstad
| Snapshot Date: 2026-05-12 13:40 -0400 (Tue, 12 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 Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-05-13 11:32 -0400 (Wed, 13 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" | 4994 |
| 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 | | ||||||||
| 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: 2026-05-12 22:04:31 -0400 (Tue, 12 May 2026) |
| EndedAt: 2026-05-12 22:04:56 -0400 (Tue, 12 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: 2026-05-13 02:04:31 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
0.241 0.052 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] "Tue May 12 22:04:46 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] "Tue May 12 22:04:46 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: 0x57b30e580690>
>
>
>
> 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] "Tue May 12 22:04:47 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] "Tue May 12 22:04:47 2026"
>
> ColMode(tmp2)
<pointer: 0x57b30e580690>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.77638828 0.6641116 1.1374751 0.6925922
[2,] 0.52591047 0.1870474 0.5907189 0.1114169
[3,] 0.04847238 1.4836361 -2.0895093 -0.7059735
[4,] 0.17186160 0.1150552 0.5069138 -2.2543930
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.77638828 0.6641116 1.1374751 0.6925922
[2,] 0.52591047 0.1870474 0.5907189 0.1114169
[3,] 0.04847238 1.4836361 2.0895093 0.7059735
[4,] 0.17186160 0.1150552 0.5069138 2.2543930
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9888132 0.8149304 1.0665248 0.8322212
[2,] 0.7251968 0.4324898 0.7685824 0.3337916
[3,] 0.2201644 1.2180460 1.4455135 0.8402223
[4,] 0.4145619 0.3391978 0.7119788 1.5014636
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.66452 33.81342 36.80272 34.01480
[2,] 32.77788 29.51195 33.27654 28.44933
[3,] 27.25012 38.66410 41.54464 34.10820
[4,] 29.31748 28.50703 32.62670 42.26903
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x57b30f9340c0>
> exp(tmp5)
<pointer: 0x57b30f9340c0>
> log(tmp5,2)
<pointer: 0x57b30f9340c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.6098
> Min(tmp5)
[1] 53.12555
> mean(tmp5)
[1] 73.51067
> Sum(tmp5)
[1] 14702.13
> Var(tmp5)
[1] 866.3184
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.98190 69.79249 69.70500 71.61623 74.34034 71.11343 69.83618 72.65316
[9] 73.68137 72.38656
> rowSums(tmp5)
[1] 1799.638 1395.850 1394.100 1432.325 1486.807 1422.269 1396.724 1453.063
[9] 1473.627 1447.731
> rowVars(tmp5)
[1] 7968.78090 41.26053 106.97299 127.12967 91.07636 65.68333
[7] 77.75549 85.64024 72.89248 94.07641
> rowSd(tmp5)
[1] 89.268028 6.423436 10.342775 11.275180 9.543394 8.104526 8.817908
[8] 9.254201 8.537709 9.699300
> rowMax(tmp5)
[1] 467.60976 84.42833 87.88422 97.00938 89.36451 87.19914 84.39947
[8] 93.38040 83.96139 94.27701
> rowMin(tmp5)
[1] 54.37861 57.38739 55.91693 56.08767 57.70604 54.73138 57.37185 56.16812
[9] 58.65251 53.12555
>
> colMeans(tmp5)
[1] 107.63985 70.00420 73.55996 70.59687 70.01553 71.14881 76.36240
[8] 66.62638 66.50840 73.63460 73.17134 68.64229 76.87418 71.11784
[15] 76.49153 71.43546 70.52861 74.79665 69.04908 72.00933
> colSums(tmp5)
[1] 1076.3985 700.0420 735.5996 705.9687 700.1553 711.4881 763.6240
[8] 666.2638 665.0840 736.3460 731.7134 686.4229 768.7418 711.1784
[15] 764.9153 714.3546 705.2861 747.9665 690.4908 720.0933
> colVars(tmp5)
[1] 16051.58966 95.76922 95.47920 76.29769 74.97211 70.83207
[7] 34.11696 88.73914 56.21877 100.15174 107.16373 79.72939
[13] 60.45308 101.20637 125.24318 54.92817 117.03064 117.10166
[19] 84.05973 14.50290
> colSd(tmp5)
[1] 126.694868 9.786175 9.771346 8.734855 8.658643 8.416179
[7] 5.840973 9.420145 7.497918 10.007584 10.351992 8.929132
[13] 7.775158 10.060138 11.191210 7.411354 10.818070 10.821352
[19] 9.168410 3.808267
> colMax(tmp5)
[1] 467.60976 80.47425 86.46973 87.97745 81.96676 84.42833 83.80737
[8] 87.88422 78.43843 87.21334 93.38040 81.32350 84.02612 87.19914
[15] 94.27701 83.96139 89.36451 97.00938 83.11936 77.87729
> colMin(tmp5)
[1] 56.71755 57.37185 59.78713 59.21356 54.37861 59.77385 66.69597 57.70604
[9] 56.16812 61.61551 56.08767 57.24881 59.65870 53.12555 61.97931 58.91644
[17] 54.73138 64.27887 55.91693 63.07139
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.98190 69.79249 69.70500 71.61623 74.34034 71.11343 69.83618 72.65316
[9] 73.68137 NA
> rowSums(tmp5)
[1] 1799.638 1395.850 1394.100 1432.325 1486.807 1422.269 1396.724 1453.063
[9] 1473.627 NA
> rowVars(tmp5)
[1] 7968.78090 41.26053 106.97299 127.12967 91.07636 65.68333
[7] 77.75549 85.64024 72.89248 98.89449
> rowSd(tmp5)
[1] 89.268028 6.423436 10.342775 11.275180 9.543394 8.104526 8.817908
[8] 9.254201 8.537709 9.944571
> rowMax(tmp5)
[1] 467.60976 84.42833 87.88422 97.00938 89.36451 87.19914 84.39947
[8] 93.38040 83.96139 NA
> rowMin(tmp5)
[1] 54.37861 57.38739 55.91693 56.08767 57.70604 54.73138 57.37185 56.16812
[9] 58.65251 NA
>
> colMeans(tmp5)
[1] 107.63985 NA 73.55996 70.59687 70.01553 71.14881 76.36240
[8] 66.62638 66.50840 73.63460 73.17134 68.64229 76.87418 71.11784
[15] 76.49153 71.43546 70.52861 74.79665 69.04908 72.00933
> colSums(tmp5)
[1] 1076.3985 NA 735.5996 705.9687 700.1553 711.4881 763.6240
[8] 666.2638 665.0840 736.3460 731.7134 686.4229 768.7418 711.1784
[15] 764.9153 714.3546 705.2861 747.9665 690.4908 720.0933
> colVars(tmp5)
[1] 16051.58966 NA 95.47920 76.29769 74.97211 70.83207
[7] 34.11696 88.73914 56.21877 100.15174 107.16373 79.72939
[13] 60.45308 101.20637 125.24318 54.92817 117.03064 117.10166
[19] 84.05973 14.50290
> colSd(tmp5)
[1] 126.694868 NA 9.771346 8.734855 8.658643 8.416179
[7] 5.840973 9.420145 7.497918 10.007584 10.351992 8.929132
[13] 7.775158 10.060138 11.191210 7.411354 10.818070 10.821352
[19] 9.168410 3.808267
> colMax(tmp5)
[1] 467.60976 NA 86.46973 87.97745 81.96676 84.42833 83.80737
[8] 87.88422 78.43843 87.21334 93.38040 81.32350 84.02612 87.19914
[15] 94.27701 83.96139 89.36451 97.00938 83.11936 77.87729
> colMin(tmp5)
[1] 56.71755 NA 59.78713 59.21356 54.37861 59.77385 66.69597 57.70604
[9] 56.16812 61.61551 56.08767 57.24881 59.65870 53.12555 61.97931 58.91644
[17] 54.73138 64.27887 55.91693 63.07139
>
> Max(tmp5,na.rm=TRUE)
[1] 467.6098
> Min(tmp5,na.rm=TRUE)
[1] 53.12555
> mean(tmp5,na.rm=TRUE)
[1] 73.50303
> Sum(tmp5,na.rm=TRUE)
[1] 14627.1
> Var(tmp5,na.rm=TRUE)
[1] 870.6821
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.98190 69.79249 69.70500 71.61623 74.34034 71.11343 69.83618 72.65316
[9] 73.68137 72.24747
> rowSums(tmp5,na.rm=TRUE)
[1] 1799.638 1395.850 1394.100 1432.325 1486.807 1422.269 1396.724 1453.063
[9] 1473.627 1372.702
> rowVars(tmp5,na.rm=TRUE)
[1] 7968.78090 41.26053 106.97299 127.12967 91.07636 65.68333
[7] 77.75549 85.64024 72.89248 98.89449
> rowSd(tmp5,na.rm=TRUE)
[1] 89.268028 6.423436 10.342775 11.275180 9.543394 8.104526 8.817908
[8] 9.254201 8.537709 9.944571
> rowMax(tmp5,na.rm=TRUE)
[1] 467.60976 84.42833 87.88422 97.00938 89.36451 87.19914 84.39947
[8] 93.38040 83.96139 94.27701
> rowMin(tmp5,na.rm=TRUE)
[1] 54.37861 57.38739 55.91693 56.08767 57.70604 54.73138 57.37185 56.16812
[9] 58.65251 53.12555
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.63985 69.44587 73.55996 70.59687 70.01553 71.14881 76.36240
[8] 66.62638 66.50840 73.63460 73.17134 68.64229 76.87418 71.11784
[15] 76.49153 71.43546 70.52861 74.79665 69.04908 72.00933
> colSums(tmp5,na.rm=TRUE)
[1] 1076.3985 625.0128 735.5996 705.9687 700.1553 711.4881 763.6240
[8] 666.2638 665.0840 736.3460 731.7134 686.4229 768.7418 711.1784
[15] 764.9153 714.3546 705.2861 747.9665 690.4908 720.0933
> colVars(tmp5,na.rm=TRUE)
[1] 16051.58966 104.23335 95.47920 76.29769 74.97211 70.83207
[7] 34.11696 88.73914 56.21877 100.15174 107.16373 79.72939
[13] 60.45308 101.20637 125.24318 54.92817 117.03064 117.10166
[19] 84.05973 14.50290
> colSd(tmp5,na.rm=TRUE)
[1] 126.694868 10.209474 9.771346 8.734855 8.658643 8.416179
[7] 5.840973 9.420145 7.497918 10.007584 10.351992 8.929132
[13] 7.775158 10.060138 11.191210 7.411354 10.818070 10.821352
[19] 9.168410 3.808267
> colMax(tmp5,na.rm=TRUE)
[1] 467.60976 80.47425 86.46973 87.97745 81.96676 84.42833 83.80737
[8] 87.88422 78.43843 87.21334 93.38040 81.32350 84.02612 87.19914
[15] 94.27701 83.96139 89.36451 97.00938 83.11936 77.87729
> colMin(tmp5,na.rm=TRUE)
[1] 56.71755 57.37185 59.78713 59.21356 54.37861 59.77385 66.69597 57.70604
[9] 56.16812 61.61551 56.08767 57.24881 59.65870 53.12555 61.97931 58.91644
[17] 54.73138 64.27887 55.91693 63.07139
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.98190 69.79249 69.70500 71.61623 74.34034 71.11343 69.83618 72.65316
[9] 73.68137 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1799.638 1395.850 1394.100 1432.325 1486.807 1422.269 1396.724 1453.063
[9] 1473.627 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7968.78090 41.26053 106.97299 127.12967 91.07636 65.68333
[7] 77.75549 85.64024 72.89248 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.268028 6.423436 10.342775 11.275180 9.543394 8.104526 8.817908
[8] 9.254201 8.537709 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 467.60976 84.42833 87.88422 97.00938 89.36451 87.19914 84.39947
[8] 93.38040 83.96139 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 54.37861 57.38739 55.91693 56.08767 57.70604 54.73138 57.37185 56.16812
[9] 58.65251 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.28367 NaN 74.73858 71.03639 69.26629 70.13843 76.67799
[8] 67.11243 66.59562 72.82875 73.93634 67.76653 76.31097 73.11699
[15] 74.51537 70.71141 69.18930 75.96529 69.71778 71.35733
> colSums(tmp5,na.rm=TRUE)
[1] 1010.5531 0.0000 672.6472 639.3275 623.3966 631.2458 690.1019
[8] 604.0118 599.3606 655.4587 665.4271 609.8988 686.7987 658.0529
[15] 670.6383 636.4027 622.7037 683.6876 627.4600 642.2160
> colVars(tmp5,na.rm=TRUE)
[1] 17815.43103 NA 91.78601 83.66168 78.02831 68.20121
[7] 37.26111 97.17385 63.16053 105.36493 113.97530 81.06747
[13] 64.44118 68.89568 96.96481 55.89639 111.47958 116.37497
[19] 89.53657 11.53340
> colSd(tmp5,na.rm=TRUE)
[1] 133.474458 NA 9.580502 9.146676 8.833364 8.258403
[7] 6.104188 9.857680 7.947360 10.264742 10.675922 9.003747
[13] 8.027526 8.300342 9.847071 7.476389 10.558389 10.787723
[19] 9.462377 3.396086
> colMax(tmp5,na.rm=TRUE)
[1] 467.60976 -Inf 86.46973 87.97745 81.96676 84.42833 83.80737
[8] 87.88422 78.43843 87.21334 93.38040 81.32350 84.02612 87.19914
[15] 85.73609 83.96139 89.36451 97.00938 83.11936 73.97238
> colMin(tmp5,na.rm=TRUE)
[1] 56.71755 Inf 59.78713 59.21356 54.37861 59.77385 66.69597 57.70604
[9] 56.16812 61.61551 56.08767 57.24881 59.65870 65.00812 61.97931 58.91644
[17] 54.73138 64.50558 55.91693 63.07139
>
>
>
>
> 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] 306.5352 142.2238 332.9347 252.6063 201.2325 399.5183 197.3238 116.7422
[9] 135.7054 166.3581
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 306.5352 142.2238 332.9347 252.6063 201.2325 399.5183 197.3238 116.7422
[9] 135.7054 166.3581
>
>
>
> 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 -2.842171e-14 1.421085e-13 -2.842171e-13 -1.136868e-13
[6] -1.136868e-13 -2.842171e-14 -1.705303e-13 -1.136868e-13 -1.136868e-13
[11] -7.105427e-14 5.684342e-14 -2.273737e-13 1.136868e-13 4.263256e-14
[16] -5.684342e-14 1.705303e-13 0.000000e+00 2.842171e-14 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 4
7 5
2 15
4 20
5 14
3 13
6 14
8 7
8 19
2 5
10 12
4 17
8 7
9 19
6 8
9 20
6 17
3 19
1 5
8 3
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] 2.24912
> Min(tmp)
[1] -2.023466
> mean(tmp)
[1] -0.005862997
> Sum(tmp)
[1] -0.5862997
> Var(tmp)
[1] 0.8249618
>
> rowMeans(tmp)
[1] -0.005862997
> rowSums(tmp)
[1] -0.5862997
> rowVars(tmp)
[1] 0.8249618
> rowSd(tmp)
[1] 0.9082741
> rowMax(tmp)
[1] 2.24912
> rowMin(tmp)
[1] -2.023466
>
> colMeans(tmp)
[1] 1.021801241 -0.163086385 -1.317217803 0.463046426 -0.073053554
[6] -0.843677269 0.878608539 -1.201826092 0.363772658 0.904964191
[11] -0.451324166 -1.092547708 -1.635975911 -1.114303211 -0.289512516
[16] -1.143306252 0.420793123 0.350810119 -1.376059344 1.562757785
[21] -0.089763439 0.945570793 1.373893555 0.793174514 0.334278541
[26] -1.259694265 -0.969595092 0.310891323 1.084185431 0.004457687
[31] 1.015063054 -0.098262151 0.323067402 0.053521555 0.812007339
[36] -0.190144014 0.552244416 -1.642558090 -0.375289252 0.792014786
[41] -0.922830642 0.634551248 0.351040294 -1.219537265 1.226769768
[46] 1.020874163 1.146757086 -0.822859534 0.340410237 -0.196374907
[51] -0.421661282 -0.699517534 0.215366129 -1.021680866 0.986254195
[56] -1.679054039 -0.485152677 -0.452163386 -0.650718991 0.177676698
[61] 2.249119787 -0.172244286 1.165596095 -1.282788463 0.060717128
[66] 1.212679340 -1.428605264 -1.288989927 1.752652167 -0.728342189
[71] 0.067981970 0.497003838 -0.106247032 -0.015984760 0.269232326
[76] -1.280284004 0.990207516 -0.422354154 -0.098685445 -0.146325939
[81] -0.496432464 1.464682547 1.008597198 -1.264923958 1.332470427
[86] -0.138207093 0.775906089 -0.879222893 0.595943300 0.362184051
[91] 0.226318704 0.708214918 -2.023466101 -0.229775256 -0.528319671
[96] -0.083848510 0.701147005 -0.684199801 1.244563556 -0.534147115
> colSums(tmp)
[1] 1.021801241 -0.163086385 -1.317217803 0.463046426 -0.073053554
[6] -0.843677269 0.878608539 -1.201826092 0.363772658 0.904964191
[11] -0.451324166 -1.092547708 -1.635975911 -1.114303211 -0.289512516
[16] -1.143306252 0.420793123 0.350810119 -1.376059344 1.562757785
[21] -0.089763439 0.945570793 1.373893555 0.793174514 0.334278541
[26] -1.259694265 -0.969595092 0.310891323 1.084185431 0.004457687
[31] 1.015063054 -0.098262151 0.323067402 0.053521555 0.812007339
[36] -0.190144014 0.552244416 -1.642558090 -0.375289252 0.792014786
[41] -0.922830642 0.634551248 0.351040294 -1.219537265 1.226769768
[46] 1.020874163 1.146757086 -0.822859534 0.340410237 -0.196374907
[51] -0.421661282 -0.699517534 0.215366129 -1.021680866 0.986254195
[56] -1.679054039 -0.485152677 -0.452163386 -0.650718991 0.177676698
[61] 2.249119787 -0.172244286 1.165596095 -1.282788463 0.060717128
[66] 1.212679340 -1.428605264 -1.288989927 1.752652167 -0.728342189
[71] 0.067981970 0.497003838 -0.106247032 -0.015984760 0.269232326
[76] -1.280284004 0.990207516 -0.422354154 -0.098685445 -0.146325939
[81] -0.496432464 1.464682547 1.008597198 -1.264923958 1.332470427
[86] -0.138207093 0.775906089 -0.879222893 0.595943300 0.362184051
[91] 0.226318704 0.708214918 -2.023466101 -0.229775256 -0.528319671
[96] -0.083848510 0.701147005 -0.684199801 1.244563556 -0.534147115
> 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] 1.021801241 -0.163086385 -1.317217803 0.463046426 -0.073053554
[6] -0.843677269 0.878608539 -1.201826092 0.363772658 0.904964191
[11] -0.451324166 -1.092547708 -1.635975911 -1.114303211 -0.289512516
[16] -1.143306252 0.420793123 0.350810119 -1.376059344 1.562757785
[21] -0.089763439 0.945570793 1.373893555 0.793174514 0.334278541
[26] -1.259694265 -0.969595092 0.310891323 1.084185431 0.004457687
[31] 1.015063054 -0.098262151 0.323067402 0.053521555 0.812007339
[36] -0.190144014 0.552244416 -1.642558090 -0.375289252 0.792014786
[41] -0.922830642 0.634551248 0.351040294 -1.219537265 1.226769768
[46] 1.020874163 1.146757086 -0.822859534 0.340410237 -0.196374907
[51] -0.421661282 -0.699517534 0.215366129 -1.021680866 0.986254195
[56] -1.679054039 -0.485152677 -0.452163386 -0.650718991 0.177676698
[61] 2.249119787 -0.172244286 1.165596095 -1.282788463 0.060717128
[66] 1.212679340 -1.428605264 -1.288989927 1.752652167 -0.728342189
[71] 0.067981970 0.497003838 -0.106247032 -0.015984760 0.269232326
[76] -1.280284004 0.990207516 -0.422354154 -0.098685445 -0.146325939
[81] -0.496432464 1.464682547 1.008597198 -1.264923958 1.332470427
[86] -0.138207093 0.775906089 -0.879222893 0.595943300 0.362184051
[91] 0.226318704 0.708214918 -2.023466101 -0.229775256 -0.528319671
[96] -0.083848510 0.701147005 -0.684199801 1.244563556 -0.534147115
> colMin(tmp)
[1] 1.021801241 -0.163086385 -1.317217803 0.463046426 -0.073053554
[6] -0.843677269 0.878608539 -1.201826092 0.363772658 0.904964191
[11] -0.451324166 -1.092547708 -1.635975911 -1.114303211 -0.289512516
[16] -1.143306252 0.420793123 0.350810119 -1.376059344 1.562757785
[21] -0.089763439 0.945570793 1.373893555 0.793174514 0.334278541
[26] -1.259694265 -0.969595092 0.310891323 1.084185431 0.004457687
[31] 1.015063054 -0.098262151 0.323067402 0.053521555 0.812007339
[36] -0.190144014 0.552244416 -1.642558090 -0.375289252 0.792014786
[41] -0.922830642 0.634551248 0.351040294 -1.219537265 1.226769768
[46] 1.020874163 1.146757086 -0.822859534 0.340410237 -0.196374907
[51] -0.421661282 -0.699517534 0.215366129 -1.021680866 0.986254195
[56] -1.679054039 -0.485152677 -0.452163386 -0.650718991 0.177676698
[61] 2.249119787 -0.172244286 1.165596095 -1.282788463 0.060717128
[66] 1.212679340 -1.428605264 -1.288989927 1.752652167 -0.728342189
[71] 0.067981970 0.497003838 -0.106247032 -0.015984760 0.269232326
[76] -1.280284004 0.990207516 -0.422354154 -0.098685445 -0.146325939
[81] -0.496432464 1.464682547 1.008597198 -1.264923958 1.332470427
[86] -0.138207093 0.775906089 -0.879222893 0.595943300 0.362184051
[91] 0.226318704 0.708214918 -2.023466101 -0.229775256 -0.528319671
[96] -0.083848510 0.701147005 -0.684199801 1.244563556 -0.534147115
> colMedians(tmp)
[1] 1.021801241 -0.163086385 -1.317217803 0.463046426 -0.073053554
[6] -0.843677269 0.878608539 -1.201826092 0.363772658 0.904964191
[11] -0.451324166 -1.092547708 -1.635975911 -1.114303211 -0.289512516
[16] -1.143306252 0.420793123 0.350810119 -1.376059344 1.562757785
[21] -0.089763439 0.945570793 1.373893555 0.793174514 0.334278541
[26] -1.259694265 -0.969595092 0.310891323 1.084185431 0.004457687
[31] 1.015063054 -0.098262151 0.323067402 0.053521555 0.812007339
[36] -0.190144014 0.552244416 -1.642558090 -0.375289252 0.792014786
[41] -0.922830642 0.634551248 0.351040294 -1.219537265 1.226769768
[46] 1.020874163 1.146757086 -0.822859534 0.340410237 -0.196374907
[51] -0.421661282 -0.699517534 0.215366129 -1.021680866 0.986254195
[56] -1.679054039 -0.485152677 -0.452163386 -0.650718991 0.177676698
[61] 2.249119787 -0.172244286 1.165596095 -1.282788463 0.060717128
[66] 1.212679340 -1.428605264 -1.288989927 1.752652167 -0.728342189
[71] 0.067981970 0.497003838 -0.106247032 -0.015984760 0.269232326
[76] -1.280284004 0.990207516 -0.422354154 -0.098685445 -0.146325939
[81] -0.496432464 1.464682547 1.008597198 -1.264923958 1.332470427
[86] -0.138207093 0.775906089 -0.879222893 0.595943300 0.362184051
[91] 0.226318704 0.708214918 -2.023466101 -0.229775256 -0.528319671
[96] -0.083848510 0.701147005 -0.684199801 1.244563556 -0.534147115
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.021801 -0.1630864 -1.317218 0.4630464 -0.07305355 -0.8436773 0.8786085
[2,] 1.021801 -0.1630864 -1.317218 0.4630464 -0.07305355 -0.8436773 0.8786085
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.201826 0.3637727 0.9049642 -0.4513242 -1.092548 -1.635976 -1.114303
[2,] -1.201826 0.3637727 0.9049642 -0.4513242 -1.092548 -1.635976 -1.114303
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.2895125 -1.143306 0.4207931 0.3508101 -1.376059 1.562758 -0.08976344
[2,] -0.2895125 -1.143306 0.4207931 0.3508101 -1.376059 1.562758 -0.08976344
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.9455708 1.373894 0.7931745 0.3342785 -1.259694 -0.9695951 0.3108913
[2,] 0.9455708 1.373894 0.7931745 0.3342785 -1.259694 -0.9695951 0.3108913
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.084185 0.004457687 1.015063 -0.09826215 0.3230674 0.05352155 0.8120073
[2,] 1.084185 0.004457687 1.015063 -0.09826215 0.3230674 0.05352155 0.8120073
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.190144 0.5522444 -1.642558 -0.3752893 0.7920148 -0.9228306 0.6345512
[2,] -0.190144 0.5522444 -1.642558 -0.3752893 0.7920148 -0.9228306 0.6345512
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.3510403 -1.219537 1.22677 1.020874 1.146757 -0.8228595 0.3404102
[2,] 0.3510403 -1.219537 1.22677 1.020874 1.146757 -0.8228595 0.3404102
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.1963749 -0.4216613 -0.6995175 0.2153661 -1.021681 0.9862542 -1.679054
[2,] -0.1963749 -0.4216613 -0.6995175 0.2153661 -1.021681 0.9862542 -1.679054
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.4851527 -0.4521634 -0.650719 0.1776767 2.24912 -0.1722443 1.165596
[2,] -0.4851527 -0.4521634 -0.650719 0.1776767 2.24912 -0.1722443 1.165596
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.282788 0.06071713 1.212679 -1.428605 -1.28899 1.752652 -0.7283422
[2,] -1.282788 0.06071713 1.212679 -1.428605 -1.28899 1.752652 -0.7283422
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.06798197 0.4970038 -0.106247 -0.01598476 0.2692323 -1.280284 0.9902075
[2,] 0.06798197 0.4970038 -0.106247 -0.01598476 0.2692323 -1.280284 0.9902075
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.4223542 -0.09868545 -0.1463259 -0.4964325 1.464683 1.008597 -1.264924
[2,] -0.4223542 -0.09868545 -0.1463259 -0.4964325 1.464683 1.008597 -1.264924
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.33247 -0.1382071 0.7759061 -0.8792229 0.5959433 0.3621841 0.2263187
[2,] 1.33247 -0.1382071 0.7759061 -0.8792229 0.5959433 0.3621841 0.2263187
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.7082149 -2.023466 -0.2297753 -0.5283197 -0.08384851 0.701147 -0.6841998
[2,] 0.7082149 -2.023466 -0.2297753 -0.5283197 -0.08384851 0.701147 -0.6841998
[,99] [,100]
[1,] 1.244564 -0.5341471
[2,] 1.244564 -0.5341471
>
>
> Max(tmp2)
[1] 2.539969
> Min(tmp2)
[1] -2.76195
> mean(tmp2)
[1] 0.05902703
> Sum(tmp2)
[1] 5.902703
> Var(tmp2)
[1] 1.073894
>
> rowMeans(tmp2)
[1] 0.75296893 -2.03398108 0.46207968 -0.09397526 -0.85666399 0.73170765
[7] 1.55881340 -0.41375790 0.19917493 1.38700868 -1.28430311 -1.44434738
[13] 0.29986599 -1.46642641 0.57472230 0.42389057 0.29659416 0.68199706
[19] 0.37523097 -1.56556579 0.95140185 -2.62201189 0.13124155 -0.17515170
[25] -0.46109893 0.10440525 -0.95697768 -0.18762681 1.14246429 -0.34103893
[31] -0.26856596 1.14671646 -0.41168494 0.49254953 -1.10355595 -0.17391861
[37] 0.22124297 -0.60570410 1.00148685 -0.52208506 -2.76194989 -0.61600254
[43] -0.27411594 -0.27835133 0.68887554 1.70971486 -1.30964580 0.16713338
[49] 0.19448847 0.74828421 -2.13630488 1.11996629 -0.56480067 -0.01028238
[55] 1.82070303 -0.23391846 -0.46677445 0.80633119 0.69705675 -1.85400729
[61] 0.91522391 0.59158826 2.53996933 0.69901434 -1.11991638 0.46697360
[67] -0.73810206 1.09114499 -0.41367299 -0.25102701 -0.85061995 1.41621331
[73] 0.66520705 0.79860210 -1.25734344 -0.77543001 1.72974454 0.57477175
[79] 1.11949886 0.44814742 -1.84436509 -1.16294387 -0.73402425 0.34401715
[85] 0.02984127 0.32732384 1.10707977 0.06960112 -0.08831886 0.49042890
[91] 2.04016481 -0.48220596 1.20943250 0.22454647 1.67514216 1.82759085
[97] -0.87899890 0.85814105 -0.04220543 -0.11105432
> rowSums(tmp2)
[1] 0.75296893 -2.03398108 0.46207968 -0.09397526 -0.85666399 0.73170765
[7] 1.55881340 -0.41375790 0.19917493 1.38700868 -1.28430311 -1.44434738
[13] 0.29986599 -1.46642641 0.57472230 0.42389057 0.29659416 0.68199706
[19] 0.37523097 -1.56556579 0.95140185 -2.62201189 0.13124155 -0.17515170
[25] -0.46109893 0.10440525 -0.95697768 -0.18762681 1.14246429 -0.34103893
[31] -0.26856596 1.14671646 -0.41168494 0.49254953 -1.10355595 -0.17391861
[37] 0.22124297 -0.60570410 1.00148685 -0.52208506 -2.76194989 -0.61600254
[43] -0.27411594 -0.27835133 0.68887554 1.70971486 -1.30964580 0.16713338
[49] 0.19448847 0.74828421 -2.13630488 1.11996629 -0.56480067 -0.01028238
[55] 1.82070303 -0.23391846 -0.46677445 0.80633119 0.69705675 -1.85400729
[61] 0.91522391 0.59158826 2.53996933 0.69901434 -1.11991638 0.46697360
[67] -0.73810206 1.09114499 -0.41367299 -0.25102701 -0.85061995 1.41621331
[73] 0.66520705 0.79860210 -1.25734344 -0.77543001 1.72974454 0.57477175
[79] 1.11949886 0.44814742 -1.84436509 -1.16294387 -0.73402425 0.34401715
[85] 0.02984127 0.32732384 1.10707977 0.06960112 -0.08831886 0.49042890
[91] 2.04016481 -0.48220596 1.20943250 0.22454647 1.67514216 1.82759085
[97] -0.87899890 0.85814105 -0.04220543 -0.11105432
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.75296893 -2.03398108 0.46207968 -0.09397526 -0.85666399 0.73170765
[7] 1.55881340 -0.41375790 0.19917493 1.38700868 -1.28430311 -1.44434738
[13] 0.29986599 -1.46642641 0.57472230 0.42389057 0.29659416 0.68199706
[19] 0.37523097 -1.56556579 0.95140185 -2.62201189 0.13124155 -0.17515170
[25] -0.46109893 0.10440525 -0.95697768 -0.18762681 1.14246429 -0.34103893
[31] -0.26856596 1.14671646 -0.41168494 0.49254953 -1.10355595 -0.17391861
[37] 0.22124297 -0.60570410 1.00148685 -0.52208506 -2.76194989 -0.61600254
[43] -0.27411594 -0.27835133 0.68887554 1.70971486 -1.30964580 0.16713338
[49] 0.19448847 0.74828421 -2.13630488 1.11996629 -0.56480067 -0.01028238
[55] 1.82070303 -0.23391846 -0.46677445 0.80633119 0.69705675 -1.85400729
[61] 0.91522391 0.59158826 2.53996933 0.69901434 -1.11991638 0.46697360
[67] -0.73810206 1.09114499 -0.41367299 -0.25102701 -0.85061995 1.41621331
[73] 0.66520705 0.79860210 -1.25734344 -0.77543001 1.72974454 0.57477175
[79] 1.11949886 0.44814742 -1.84436509 -1.16294387 -0.73402425 0.34401715
[85] 0.02984127 0.32732384 1.10707977 0.06960112 -0.08831886 0.49042890
[91] 2.04016481 -0.48220596 1.20943250 0.22454647 1.67514216 1.82759085
[97] -0.87899890 0.85814105 -0.04220543 -0.11105432
> rowMin(tmp2)
[1] 0.75296893 -2.03398108 0.46207968 -0.09397526 -0.85666399 0.73170765
[7] 1.55881340 -0.41375790 0.19917493 1.38700868 -1.28430311 -1.44434738
[13] 0.29986599 -1.46642641 0.57472230 0.42389057 0.29659416 0.68199706
[19] 0.37523097 -1.56556579 0.95140185 -2.62201189 0.13124155 -0.17515170
[25] -0.46109893 0.10440525 -0.95697768 -0.18762681 1.14246429 -0.34103893
[31] -0.26856596 1.14671646 -0.41168494 0.49254953 -1.10355595 -0.17391861
[37] 0.22124297 -0.60570410 1.00148685 -0.52208506 -2.76194989 -0.61600254
[43] -0.27411594 -0.27835133 0.68887554 1.70971486 -1.30964580 0.16713338
[49] 0.19448847 0.74828421 -2.13630488 1.11996629 -0.56480067 -0.01028238
[55] 1.82070303 -0.23391846 -0.46677445 0.80633119 0.69705675 -1.85400729
[61] 0.91522391 0.59158826 2.53996933 0.69901434 -1.11991638 0.46697360
[67] -0.73810206 1.09114499 -0.41367299 -0.25102701 -0.85061995 1.41621331
[73] 0.66520705 0.79860210 -1.25734344 -0.77543001 1.72974454 0.57477175
[79] 1.11949886 0.44814742 -1.84436509 -1.16294387 -0.73402425 0.34401715
[85] 0.02984127 0.32732384 1.10707977 0.06960112 -0.08831886 0.49042890
[91] 2.04016481 -0.48220596 1.20943250 0.22454647 1.67514216 1.82759085
[97] -0.87899890 0.85814105 -0.04220543 -0.11105432
>
> colMeans(tmp2)
[1] 0.05902703
> colSums(tmp2)
[1] 5.902703
> colVars(tmp2)
[1] 1.073894
> colSd(tmp2)
[1] 1.036288
> colMax(tmp2)
[1] 2.539969
> colMin(tmp2)
[1] -2.76195
> colMedians(tmp2)
[1] 0.1491875
> colRanges(tmp2)
[,1]
[1,] -2.761950
[2,] 2.539969
>
> 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] 4.35660858 -2.92316209 1.70027696 2.03663647 -2.71617783 1.23317060
[7] -3.95166960 -6.42431827 1.29049632 -0.07236246
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.52885595
[2,] 0.02408839
[3,] 0.22961437
[4,] 1.02759894
[5,] 1.40331747
>
> rowApply(tmp,sum)
[1] 2.8385144 -0.7766782 -1.7383133 2.4944997 -3.2508607 -3.3020051
[7] 2.4734311 -2.9429539 0.4676848 -1.7338201
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 8 5 5 4 10 8 10 9 7
[2,] 4 2 7 4 9 1 7 7 1 8
[3,] 9 1 4 9 5 3 10 9 5 4
[4,] 7 7 9 7 7 8 4 2 8 9
[5,] 6 6 1 8 1 9 9 6 6 2
[6,] 8 4 6 6 3 5 5 8 2 10
[7,] 1 5 8 3 6 6 6 1 4 3
[8,] 2 3 3 10 10 2 1 3 7 1
[9,] 3 9 2 2 8 7 2 4 10 6
[10,] 10 10 10 1 2 4 3 5 3 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.0142703943 -5.3112110256 -4.5886593624 -4.3727115028 0.1982276115
[6] 1.1773948344 4.8358194791 2.3948018706 1.4501143908 1.8098382796
[11] -0.8280201301 0.0008574999 4.6421519633 3.8334593511 1.3985629134
[16] -1.7340682559 -0.0920756345 -2.4610614434 1.0144973307 -1.5905356781
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.76608967
[2,] -0.36310433
[3,] 0.04806591
[4,] 0.35420695
[5,] 0.71265074
>
> rowApply(tmp,sum)
[1] -2.599458 4.258239 4.348680 2.786903 -7.031254
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 9 13 12 10
[2,] 1 4 9 8 1
[3,] 3 1 3 15 4
[4,] 2 2 12 2 6
[5,] 17 11 10 7 5
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.76608967 -2.1486436 -1.0742565 -1.3150863 0.5826346 0.49591439
[2,] 0.04806591 -0.5548954 -2.1761464 -1.6687574 0.2130858 0.05336026
[3,] 0.71265074 0.1995501 -1.0231739 0.5688047 0.4292533 0.82992088
[4,] 0.35420695 -0.2308153 0.4883970 -1.3736415 -0.2558516 0.75584565
[5,] -0.36310433 -2.5764068 -0.8034795 -0.5840310 -0.7708944 -0.95764634
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.9199656 0.31216698 -0.62280076 -0.6244458 -0.78037770 -0.24862766
[2,] -0.6846512 0.37530472 1.51884114 0.9854674 -0.01528119 1.58963475
[3,] 1.1934397 1.26033772 0.47582265 -0.2055044 0.88940240 -0.25517848
[4,] 2.1553733 0.46511479 0.09596788 1.0330514 -1.48350013 -0.07488571
[5,] 0.2516920 -0.01812234 -0.01771652 0.6212697 0.56173648 -1.01008540
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 2.42135603 1.2970895 -0.1860500 -0.88101214 -0.21536403 -0.1202248
[2,] 0.51549258 1.3984575 -0.4214976 0.83004948 -0.18598840 -0.1226735
[3,] 0.07055924 1.0635918 2.2951146 -1.11375949 -0.69707730 -2.2966781
[4,] 1.77506400 0.4449711 -0.6643470 -0.54337171 0.96694249 0.3048048
[5,] -0.14031988 -0.3706506 0.3753428 -0.02597439 0.03941161 -0.2262898
[,19] [,20]
[1,] 0.06918676 -0.7147924
[2,] 1.14171379 1.4186572
[3,] 0.82523219 -0.8736279
[4,] -0.45001908 -0.9764040
[5,] -0.57161634 -0.4443686
>
>
> 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 -0.08164674 -1.417194 -0.6013201 1.638889 0.02992594 0.7822593 -0.520068
col8 col9 col10 col11 col12 col13 col14
row1 0.8114794 -0.7439814 -0.6308779 -0.419355 0.009484528 -1.268943 0.8425789
col15 col16 col17 col18 col19 col20
row1 1.346417 -0.2340535 -0.7661275 0.68311 0.08764006 -1.448372
> tmp[,"col10"]
col10
row1 -0.6308779
row2 0.2763218
row3 -0.4199067
row4 -1.7427435
row5 -0.1710194
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.08164674 -1.41719411 -0.6013201 1.6388888 0.02992594 0.78225930
row5 -1.65888666 0.06336773 -2.2160365 0.4829097 1.40246881 -0.08367231
col7 col8 col9 col10 col11 col12
row1 -0.5200680 0.8114794 -0.7439814 -0.6308779 -0.41935496 0.009484528
row5 0.0653734 -0.6083957 -0.2369542 -0.1710194 0.07631862 0.711090736
col13 col14 col15 col16 col17 col18 col19
row1 -1.2689430 0.8425789 1.346417 -0.2340535 -0.7661275 0.6831100 0.08764006
row5 0.4663435 0.2868693 -1.371779 0.4656263 -0.8926064 -0.6233106 0.15042359
col20
row1 -1.4483721
row5 -0.5799216
> tmp[,c("col6","col20")]
col6 col20
row1 0.78225930 -1.4483721
row2 -1.03292383 1.3732839
row3 0.70771793 0.9796866
row4 -0.67351007 -0.5640490
row5 -0.08367231 -0.5799216
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.78225930 -1.4483721
row5 -0.08367231 -0.5799216
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.91792 52.01964 50.68241 51.87052 50.19543 106.2072 48.7281 52.17584
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.63558 49.4647 50.9358 49.78613 49.85458 49.93439 51.30892 50.0685
col17 col18 col19 col20
row1 49.00998 48.89644 48.61758 105.2518
> tmp[,"col10"]
col10
row1 49.46470
row2 30.32556
row3 29.68587
row4 30.08476
row5 49.31202
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.91792 52.01964 50.68241 51.87052 50.19543 106.2072 48.72810 52.17584
row5 49.67975 48.95243 50.94544 50.39669 51.14505 103.2809 50.09883 47.80505
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.63558 49.46470 50.93580 49.78613 49.85458 49.93439 51.30892 50.06850
row5 50.20575 49.31202 50.49046 49.51380 51.97148 48.75846 49.69293 51.62918
col17 col18 col19 col20
row1 49.00998 48.89644 48.61758 105.2518
row5 51.73869 49.73483 49.38007 105.2411
> tmp[,c("col6","col20")]
col6 col20
row1 106.20721 105.25176
row2 76.65774 76.87178
row3 76.28919 72.88362
row4 75.59311 74.95859
row5 103.28091 105.24109
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.2072 105.2518
row5 103.2809 105.2411
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.2072 105.2518
row5 103.2809 105.2411
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.4323381
[2,] 1.3615770
[3,] 1.1696617
[4,] -0.7948713
[5,] -1.1582024
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.44973045 1.5650838
[2,] -1.61772127 -0.6069068
[3,] -0.04580122 -0.2979606
[4,] -1.07742353 -0.3280684
[5,] 1.42768687 -0.1588986
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.41468396 -0.12882103
[2,] -1.32457492 0.08884426
[3,] 0.37649615 -1.06724361
[4,] 0.76388017 0.79444474
[5,] 0.01888498 -0.70971691
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.414684
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.414684
[2,] -1.324575
>
>
>
> 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 -0.1663148 0.388619 -0.6957765 -0.4884566 0.9066775 0.5066132
row1 -0.5462497 -1.863052 0.6399334 -0.4197213 -1.3626032 -1.4655099
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.43318276 -0.07634688 1.708349 0.5730272 2.2160928 0.08767247
row1 0.03033954 -0.56102866 0.742592 -1.0071631 -0.2537613 -0.85308526
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.2529465 2.9144067 1.4904435 0.05857074 -0.856092318 -0.1667542
row1 0.7315474 0.8470926 0.5958841 1.52217405 0.006792673 0.9045166
[,19] [,20]
row3 0.8498144 0.5519042
row1 -1.0677188 1.6249524
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.803481 1.330851 -0.9821014 -1.587503 -0.3934669 0.4814204 0.2039982
[,8] [,9] [,10]
row2 -0.02128232 0.3718304 0.1310363
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9497005 -0.05435146 -0.3521871 -1.507718 0.1147303 0.2986123 0.4801523
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5661751 -0.109713 0.09771985 -2.795822 -0.6554266 -0.5929438 -0.08663974
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.9736642 0.05155287 -1.831533 -1.115067 -0.6186452 0.9487163
>
>
> 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: 0x57b30f949810>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc515f7b8a"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc1b7bbedb"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc36353150"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc6cdb239d"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc43552fb3"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc57302139"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc715f3de"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc44204880"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc77ff396b"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc11911864"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc5c829f28"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc27cbd9e3"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc7192810e"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc7571ffe"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e91fc439c61b5"
>
>
> ### 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: 0x57b30e4c70b0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x57b30e4c70b0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x57b30e4c70b0>
> rowMedians(tmp)
[1] 0.533428212 -0.272778441 -0.153411041 -0.477057112 0.199167264
[6] 0.285753070 -0.078075695 -0.095579553 -0.544227771 -0.429116818
[11] -0.054538102 -0.169610569 -0.218996545 -0.126999011 0.118746173
[16] 0.425283152 -0.070080923 0.426571455 0.080240002 -0.108846511
[21] -0.060543485 -0.418827904 -0.242339282 0.283505859 0.457993648
[26] 0.156886294 0.267314240 0.118713256 0.262364623 -0.292746188
[31] -0.036691249 0.300235276 -0.089934065 -0.088248590 -0.080961320
[36] 0.358034547 -0.193083828 0.160267375 -0.686798522 -0.434855418
[41] -0.361570582 0.647164464 -0.621191967 0.107534521 -0.019153330
[46] -0.207707272 0.055474256 0.532600377 0.299904510 0.006872559
[51] 0.277747001 -0.390271381 -0.177084327 -0.777991609 0.151913511
[56] 0.153060883 0.251952190 0.031142196 0.027087632 -0.338996517
[61] 0.383118019 0.125123137 -0.115456672 0.224811297 -0.352179046
[66] 0.411123885 -0.363481358 -0.073319568 0.059190995 -0.078016070
[71] 0.609158702 0.128655052 -0.254879467 0.212279211 0.423880026
[76] 0.015705079 0.561260649 -0.175157376 0.068529217 -0.307526963
[81] 0.132574016 -0.562989948 -0.121057054 0.071847218 -0.379861950
[86] -0.478814369 0.055650471 0.115245019 0.050967596 -0.096028814
[91] -0.421425645 0.103050283 0.013454399 -0.161071078 0.133348628
[96] 0.880074299 -0.149911885 -0.126996339 0.099766754 0.586261083
[101] 0.380669906 0.139437345 0.250690592 -0.223526560 0.260467403
[106] 0.816407100 -0.299577567 -0.273673253 -0.176197822 -0.150408053
[111] -0.128019444 0.297872533 0.146850277 0.113496214 0.279495519
[116] -0.538912837 0.325026139 -0.354564467 0.109950450 0.103900353
[121] 0.100192110 -0.300645466 0.050675987 -0.073401999 0.007147719
[126] 0.280578977 -0.091733596 -0.502162004 0.188775155 -0.542116735
[131] -0.260693254 -0.445595276 0.087042416 -0.179210004 -0.137466774
[136] -0.236531162 0.300460271 0.005624457 -0.112921590 -0.225775452
[141] 0.009570958 -0.030131072 -0.217610527 -0.180020749 0.761456852
[146] 0.738806205 0.062404221 -0.093436383 -0.163302985 -0.163433152
[151] -0.140310788 0.149994885 0.428545318 -0.075503139 0.098707299
[156] -0.759277746 -0.314486699 -0.075637614 -0.021134228 -0.332397493
[161] 0.111358049 0.127539084 -0.449818073 0.111426785 0.244515629
[166] 0.294771266 -0.247462843 0.719307622 -0.240274830 -0.151448025
[171] -0.095191363 0.771040866 -0.019762572 0.002926229 -0.094305324
[176] 0.079062028 -0.284254396 -0.127599627 -0.324537535 0.333270571
[181] 0.148744394 0.398178598 0.297091336 -0.387275975 -0.199020877
[186] -0.272384864 -0.097921180 -0.066402371 -0.400760218 -0.333273513
[191] -0.073527738 0.238832333 -0.233839694 0.044500056 -0.404564984
[196] 0.076825943 0.254464898 -0.267963105 0.649407004 -0.133273557
[201] 0.014895389 0.361656549 0.068335270 0.422220482 -0.080206521
[206] -0.123333573 -0.436961925 -0.460710326 -0.672293838 -0.292629744
[211] -0.070711235 0.214123865 -0.122096665 0.566955174 -0.404118215
[216] -0.089940736 0.481366710 0.401939411 -0.066569355 0.097724195
[221] 0.578692035 0.330695643 0.078641577 0.348742530 -0.101176480
[226] 0.330838608 0.164182940 0.241370694 -0.471887172 -0.350382494
>
> proc.time()
user system elapsed
1.298 1.574 2.862
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: 0x6038e89e80f0>
> .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: 0x6038e89e80f0>
> .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: 0x6038e89e80f0>
> .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: 0x6038e89e80f0>
> 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: 0x6038e9836690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038e9836690>
> .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: 0x6038e9836690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038e9836690>
> .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: 0x6038e9836690>
> 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: 0x6038eb270010>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038eb270010>
> .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: 0x6038eb270010>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6038eb270010>
> .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: 0x6038eb270010>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6038eb270010>
> .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: 0x6038eb270010>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6038eb270010>
> .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: 0x6038eb270010>
> 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: 0x6038eb2c0070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6038eb2c0070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038eb2c0070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038eb2c0070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e935920882ff9" "BufferedMatrixFile1e935975440d9e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e935920882ff9" "BufferedMatrixFile1e935975440d9e"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038e8f7a7e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038e8f7a7e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6038e8f7a7e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6038e8f7a7e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6038e8f7a7e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6038e8f7a7e0>
> .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: 0x6038eaf163b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6038eaf163b0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6038eaf163b0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6038eaf163b0>
> 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: 0x6038e90dc520>
> .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: 0x6038e90dc520>
> rm(P)
>
> proc.time()
user system elapsed
0.240 0.061 0.287
BufferedMatrix.Rcheck/tests/Rcodetesting.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.
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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
0.250 0.037 0.276