Ben Bolstad
| Snapshot Date: 2026-04-29 13:45 -0400 (Wed, 29 Apr 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 2d99771 |
| git_last_commit_date: 2026-04-28 08:32:08 -0400 (Tue, 28 Apr 2026) |
| Back to Build/check report for BioC 3.24: simplified long |
|
This page was generated on 2026-04-30 11:32 -0400 (Thu, 30 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4843 |
| 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 252/2366 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.77.0 (landing page) Ben Bolstad
| nebbiolo2 | 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: 1.77.0 |
| Command: /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings BufferedMatrix_1.77.0.tar.gz |
| StartedAt: 2026-04-29 22:02:44 -0400 (Wed, 29 Apr 2026) |
| EndedAt: 2026-04-29 22:03:09 -0400 (Wed, 29 Apr 2026) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings BufferedMatrix_1.77.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.24-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: 2026-04-30 02:02:44 UTC
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.77.0’
* 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-3.24-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.77.0’
** 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-3.24-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-3.24-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-3.24-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-3.24-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-3.24-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-3.24-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.24-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
0.244 0.056 0.288
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-3.24-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] "Wed Apr 29 22:03:00 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 29 22:03:00 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: 0x60f63fee1520>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Apr 29 22:03:00 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 29 22:03:01 2026"
>
> ColMode(tmp2)
<pointer: 0x60f63fee1520>
>
>
>
> ### 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,] 99.0280639 1.3907532 0.99025319 0.26168596
[2,] -0.1991027 -0.3113685 -1.69973847 0.03719059
[3,] 0.8029334 -0.1980844 2.09982683 -0.76089142
[4,] 1.3586192 0.6229895 0.02593718 0.84501393
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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,] 99.0280639 1.3907532 0.99025319 0.26168596
[2,] 0.1991027 0.3113685 1.69973847 0.03719059
[3,] 0.8029334 0.1980844 2.09982683 0.76089142
[4,] 1.3586192 0.6229895 0.02593718 0.84501393
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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,] 9.9512845 1.1793020 0.9951147 0.5115525
[2,] 0.4462093 0.5580040 1.3037402 0.1928486
[3,] 0.8960655 0.4450667 1.4490779 0.8722909
[4,] 1.1655982 0.7892968 0.1610502 0.9192464
>
> 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-3.24-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,] 223.54091 38.18377 35.94140 30.37721
[2,] 29.66120 30.89141 39.73714 26.96568
[3,] 34.76359 29.64875 41.59061 34.48380
[4,] 38.01460 33.51596 26.63644 35.03748
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x60f640ccc8f0>
> exp(tmp5)
<pointer: 0x60f640ccc8f0>
> log(tmp5,2)
<pointer: 0x60f640ccc8f0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.2711
> Min(tmp5)
[1] 53.67659
> mean(tmp5)
[1] 74.17479
> Sum(tmp5)
[1] 14834.96
> Var(tmp5)
[1] 857.4443
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.81586 71.04894 73.37491 71.71110 72.02488 72.62302 69.07390 73.88514
[9] 71.79772 72.39242
> rowSums(tmp5)
[1] 1876.317 1420.979 1467.498 1434.222 1440.498 1452.460 1381.478 1477.703
[9] 1435.954 1447.848
> rowVars(tmp5)
[1] 7710.99381 79.19467 80.24495 140.12142 133.71852 61.14545
[7] 86.10841 59.60488 79.10732 82.76892
> rowSd(tmp5)
[1] 87.812265 8.899139 8.957955 11.837290 11.563672 7.819556 9.279461
[8] 7.720420 8.894229 9.097742
> rowMax(tmp5)
[1] 465.27111 86.21860 86.95613 96.59382 96.96066 89.74192 91.80401
[8] 87.86591 86.67365 87.66920
> rowMin(tmp5)
[1] 59.36272 56.12552 56.92419 53.75311 54.41811 57.50685 53.92179 60.79462
[9] 53.67659 60.41643
>
> colMeans(tmp5)
[1] 114.25774 70.17937 71.69691 69.65907 71.51402 74.68107 70.61926
[8] 74.79753 70.81773 79.54152 67.49136 76.56625 72.97747 71.52809
[15] 70.67535 67.61071 74.02566 73.05113 71.33682 70.46870
> colSums(tmp5)
[1] 1142.5774 701.7937 716.9691 696.5907 715.1402 746.8107 706.1926
[8] 747.9753 708.1773 795.4152 674.9136 765.6625 729.7747 715.2809
[15] 706.7535 676.1071 740.2566 730.5113 713.3682 704.6870
> colVars(tmp5)
[1] 15298.84172 57.58814 111.87029 83.59855 51.85007 163.40906
[7] 73.69461 121.12323 42.47737 112.04221 119.56897 77.16094
[13] 48.28747 90.43264 100.72060 63.41703 63.42638 81.89969
[19] 74.11746 71.51002
> colSd(tmp5)
[1] 123.688487 7.588685 10.576875 9.143224 7.200699 12.783155
[7] 8.584557 11.005600 6.517466 10.584999 10.934760 8.784130
[13] 6.948918 9.509608 10.035965 7.963481 7.964068 9.049845
[19] 8.609150 8.456360
> colMax(tmp5)
[1] 465.27111 79.47452 86.56540 80.97009 87.86591 96.18646 82.57740
[8] 87.37670 84.07547 96.59382 89.74192 91.33184 87.66920 82.44843
[15] 91.80401 81.91079 84.82360 86.21860 85.53589 82.08497
> colMin(tmp5)
[1] 61.73589 61.38537 54.84188 53.92179 59.28337 60.15570 58.37919 57.50685
[9] 61.91474 64.12733 53.67659 60.79462 66.41320 54.41811 59.10143 54.27470
[17] 60.63560 59.29489 61.01436 58.00280
>
>
> ### 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] NA 71.04894 73.37491 71.71110 72.02488 72.62302 69.07390 73.88514
[9] 71.79772 72.39242
> rowSums(tmp5)
[1] NA 1420.979 1467.498 1434.222 1440.498 1452.460 1381.478 1477.703
[9] 1435.954 1447.848
> rowVars(tmp5)
[1] 8130.35577 79.19467 80.24495 140.12142 133.71852 61.14545
[7] 86.10841 59.60488 79.10732 82.76892
> rowSd(tmp5)
[1] 90.168485 8.899139 8.957955 11.837290 11.563672 7.819556 9.279461
[8] 7.720420 8.894229 9.097742
> rowMax(tmp5)
[1] NA 86.21860 86.95613 96.59382 96.96066 89.74192 91.80401 87.86591
[9] 86.67365 87.66920
> rowMin(tmp5)
[1] NA 56.12552 56.92419 53.75311 54.41811 57.50685 53.92179 60.79462
[9] 53.67659 60.41643
>
> colMeans(tmp5)
[1] 114.25774 70.17937 71.69691 69.65907 71.51402 74.68107 NA
[8] 74.79753 70.81773 79.54152 67.49136 76.56625 72.97747 71.52809
[15] 70.67535 67.61071 74.02566 73.05113 71.33682 70.46870
> colSums(tmp5)
[1] 1142.5774 701.7937 716.9691 696.5907 715.1402 746.8107 NA
[8] 747.9753 708.1773 795.4152 674.9136 765.6625 729.7747 715.2809
[15] 706.7535 676.1071 740.2566 730.5113 713.3682 704.6870
> colVars(tmp5)
[1] 15298.84172 57.58814 111.87029 83.59855 51.85007 163.40906
[7] NA 121.12323 42.47737 112.04221 119.56897 77.16094
[13] 48.28747 90.43264 100.72060 63.41703 63.42638 81.89969
[19] 74.11746 71.51002
> colSd(tmp5)
[1] 123.688487 7.588685 10.576875 9.143224 7.200699 12.783155
[7] NA 11.005600 6.517466 10.584999 10.934760 8.784130
[13] 6.948918 9.509608 10.035965 7.963481 7.964068 9.049845
[19] 8.609150 8.456360
> colMax(tmp5)
[1] 465.27111 79.47452 86.56540 80.97009 87.86591 96.18646 NA
[8] 87.37670 84.07547 96.59382 89.74192 91.33184 87.66920 82.44843
[15] 91.80401 81.91079 84.82360 86.21860 85.53589 82.08497
> colMin(tmp5)
[1] 61.73589 61.38537 54.84188 53.92179 59.28337 60.15570 NA 57.50685
[9] 61.91474 64.12733 53.67659 60.79462 66.41320 54.41811 59.10143 54.27470
[17] 60.63560 59.29489 61.01436 58.00280
>
> Max(tmp5,na.rm=TRUE)
[1] 465.2711
> Min(tmp5,na.rm=TRUE)
[1] 53.67659
> mean(tmp5,na.rm=TRUE)
[1] 74.13852
> Sum(tmp5,na.rm=TRUE)
[1] 14753.57
> Var(tmp5,na.rm=TRUE)
[1] 861.5104
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 94.46975 71.04894 73.37491 71.71110 72.02488 72.62302 69.07390 73.88514
[9] 71.79772 72.39242
> rowSums(tmp5,na.rm=TRUE)
[1] 1794.925 1420.979 1467.498 1434.222 1440.498 1452.460 1381.478 1477.703
[9] 1435.954 1447.848
> rowVars(tmp5,na.rm=TRUE)
[1] 8130.35577 79.19467 80.24495 140.12142 133.71852 61.14545
[7] 86.10841 59.60488 79.10732 82.76892
> rowSd(tmp5,na.rm=TRUE)
[1] 90.168485 8.899139 8.957955 11.837290 11.563672 7.819556 9.279461
[8] 7.720420 8.894229 9.097742
> rowMax(tmp5,na.rm=TRUE)
[1] 465.27111 86.21860 86.95613 96.59382 96.96066 89.74192 91.80401
[8] 87.86591 86.67365 87.66920
> rowMin(tmp5,na.rm=TRUE)
[1] 59.36272 56.12552 56.92419 53.75311 54.41811 57.50685 53.92179 60.79462
[9] 53.67659 60.41643
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.25774 70.17937 71.69691 69.65907 71.51402 74.68107 69.42230
[8] 74.79753 70.81773 79.54152 67.49136 76.56625 72.97747 71.52809
[15] 70.67535 67.61071 74.02566 73.05113 71.33682 70.46870
> colSums(tmp5,na.rm=TRUE)
[1] 1142.5774 701.7937 716.9691 696.5907 715.1402 746.8107 624.8007
[8] 747.9753 708.1773 795.4152 674.9136 765.6625 729.7747 715.2809
[15] 706.7535 676.1071 740.2566 730.5113 713.3682 704.6870
> colVars(tmp5,na.rm=TRUE)
[1] 15298.84172 57.58814 111.87029 83.59855 51.85007 163.40906
[7] 66.78838 121.12323 42.47737 112.04221 119.56897 77.16094
[13] 48.28747 90.43264 100.72060 63.41703 63.42638 81.89969
[19] 74.11746 71.51002
> colSd(tmp5,na.rm=TRUE)
[1] 123.688487 7.588685 10.576875 9.143224 7.200699 12.783155
[7] 8.172416 11.005600 6.517466 10.584999 10.934760 8.784130
[13] 6.948918 9.509608 10.035965 7.963481 7.964068 9.049845
[19] 8.609150 8.456360
> colMax(tmp5,na.rm=TRUE)
[1] 465.27111 79.47452 86.56540 80.97009 87.86591 96.18646 82.57740
[8] 87.37670 84.07547 96.59382 89.74192 91.33184 87.66920 82.44843
[15] 91.80401 81.91079 84.82360 86.21860 85.53589 82.08497
> colMin(tmp5,na.rm=TRUE)
[1] 61.73589 61.38537 54.84188 53.92179 59.28337 60.15570 58.37919 57.50685
[9] 61.91474 64.12733 53.67659 60.79462 66.41320 54.41811 59.10143 54.27470
[17] 60.63560 59.29489 61.01436 58.00280
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.04894 73.37491 71.71110 72.02488 72.62302 69.07390 73.88514
[9] 71.79772 72.39242
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1420.979 1467.498 1434.222 1440.498 1452.460 1381.478 1477.703
[9] 1435.954 1447.848
> rowVars(tmp5,na.rm=TRUE)
[1] NA 79.19467 80.24495 140.12142 133.71852 61.14545 86.10841
[8] 59.60488 79.10732 82.76892
> rowSd(tmp5,na.rm=TRUE)
[1] NA 8.899139 8.957955 11.837290 11.563672 7.819556 9.279461
[8] 7.720420 8.894229 9.097742
> rowMax(tmp5,na.rm=TRUE)
[1] NA 86.21860 86.95613 96.59382 96.96066 89.74192 91.80401 87.86591
[9] 86.67365 87.66920
> rowMin(tmp5,na.rm=TRUE)
[1] NA 56.12552 56.92419 53.75311 54.41811 57.50685 53.92179 60.79462
[9] 53.67659 60.41643
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 75.25625 69.14657 71.35131 70.37384 71.12682 73.57962 NaN 73.56552
[9] 71.03144 80.28693 68.39454 75.64278 73.17989 70.31472 71.61750 67.79694
[17] 72.82589 73.54206 71.53431 69.85971
> colSums(tmp5,na.rm=TRUE)
[1] 677.3063 622.3192 642.1618 633.3645 640.1414 662.2166 0.0000 662.0896
[9] 639.2829 722.5824 615.5509 680.7850 658.6190 632.8324 644.5575 610.1724
[17] 655.4330 661.8786 643.8088 628.7374
> colVars(tmp5,na.rm=TRUE)
[1] 98.64287 52.78668 124.51038 88.30087 56.64474 170.18693 NA
[8] 119.18765 47.27327 119.79659 125.33803 77.21208 53.86246 85.17369
[15] 103.32469 70.95401 55.16085 89.42579 82.94333 76.27650
> colSd(tmp5,na.rm=TRUE)
[1] 9.931912 7.265444 11.158422 9.396854 7.526270 13.045571 NA
[8] 10.917310 6.875556 10.945163 11.195447 8.787040 7.339105 9.228959
[15] 10.164875 8.423420 7.427035 9.456521 9.107323 8.733642
> colMax(tmp5,na.rm=TRUE)
[1] 96.96066 79.09794 86.56540 80.97009 87.86591 96.18646 -Inf 87.37670
[9] 84.07547 96.59382 89.74192 91.33184 87.66920 82.08967 91.80401 81.91079
[17] 83.26058 86.21860 85.53589 82.08497
> colMin(tmp5,na.rm=TRUE)
[1] 61.73589 61.38537 54.84188 53.92179 59.28337 60.15570 Inf 57.50685
[9] 61.91474 64.12733 53.67659 60.79462 66.41320 54.41811 59.10143 54.27470
[17] 60.63560 59.29489 61.01436 58.00280
>
>
>
>
> 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] 260.1437 418.3501 185.6862 310.5968 283.4090 288.9659 125.1241 138.5885
[9] 211.8930 167.0920
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 260.1437 418.3501 185.6862 310.5968 283.4090 288.9659 125.1241 138.5885
[9] 211.8930 167.0920
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 -5.684342e-14 2.842171e-13 -4.263256e-14 0.000000e+00
[6] -2.842171e-14 2.842171e-14 0.000000e+00 1.705303e-13 1.136868e-13
[11] -1.989520e-13 1.136868e-13 -5.684342e-14 5.684342e-14 7.105427e-14
[16] -2.842171e-14 1.705303e-13 0.000000e+00 -2.842171e-13 -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 8
3 2
1 2
10 1
9 1
9 6
5 4
4 14
9 1
10 16
10 20
7 1
3 20
5 15
2 3
2 2
10 4
8 9
1 16
8 11
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] 2.002768
> Min(tmp)
[1] -2.658037
> mean(tmp)
[1] -0.03541706
> Sum(tmp)
[1] -3.541706
> Var(tmp)
[1] 0.9466922
>
> rowMeans(tmp)
[1] -0.03541706
> rowSums(tmp)
[1] -3.541706
> rowVars(tmp)
[1] 0.9466922
> rowSd(tmp)
[1] 0.9729811
> rowMax(tmp)
[1] 2.002768
> rowMin(tmp)
[1] -2.658037
>
> colMeans(tmp)
[1] -0.019459868 1.023747947 -1.474469653 -0.592806235 0.661148119
[6] -2.658037162 1.368305058 0.028617791 -0.353381581 0.401449764
[11] -1.316779092 0.081637313 0.130253902 0.664799438 0.904112807
[16] 0.957420535 -0.993174403 -0.451686419 -0.270070255 -0.036948878
[21] 0.826499679 1.112939557 0.372650371 -1.104355901 1.015736337
[26] 1.700978622 0.463760074 -0.751543816 -1.240495520 0.785982390
[31] -0.764937273 -1.436500065 0.012237821 0.095551262 0.225314403
[36] -0.501217479 -0.982943078 0.898282432 -0.538458952 0.537946146
[41] -0.566502396 -0.889658065 0.810248328 2.002767715 1.245934815
[46] 1.666838965 -2.247218132 -1.082250444 -0.457718514 0.166641731
[51] -1.319190488 -0.588030771 0.752192862 -1.399325953 -1.999813384
[56] 0.167937433 -0.272410600 -0.456087788 -0.511162961 -1.237998122
[61] -0.536697068 -0.354195352 -1.652763387 0.254277619 -0.078560119
[66] -0.483645180 0.624555480 1.520440036 0.973779398 0.650780528
[71] 0.972950214 -1.498885209 0.196523444 1.123031785 1.052139308
[76] -1.438849994 -0.343207995 1.391023626 0.491289638 -0.002319196
[81] 0.131201456 0.636298269 -0.834224278 -1.982550039 0.348465766
[86] -0.251342618 -1.395120099 0.697276901 -0.239017895 0.975299492
[91] -0.636824436 0.749201488 1.468877105 0.787074329 0.126663517
[96] 0.158805815 0.946721350 -0.458066899 -0.995343901 0.795931077
> colSums(tmp)
[1] -0.019459868 1.023747947 -1.474469653 -0.592806235 0.661148119
[6] -2.658037162 1.368305058 0.028617791 -0.353381581 0.401449764
[11] -1.316779092 0.081637313 0.130253902 0.664799438 0.904112807
[16] 0.957420535 -0.993174403 -0.451686419 -0.270070255 -0.036948878
[21] 0.826499679 1.112939557 0.372650371 -1.104355901 1.015736337
[26] 1.700978622 0.463760074 -0.751543816 -1.240495520 0.785982390
[31] -0.764937273 -1.436500065 0.012237821 0.095551262 0.225314403
[36] -0.501217479 -0.982943078 0.898282432 -0.538458952 0.537946146
[41] -0.566502396 -0.889658065 0.810248328 2.002767715 1.245934815
[46] 1.666838965 -2.247218132 -1.082250444 -0.457718514 0.166641731
[51] -1.319190488 -0.588030771 0.752192862 -1.399325953 -1.999813384
[56] 0.167937433 -0.272410600 -0.456087788 -0.511162961 -1.237998122
[61] -0.536697068 -0.354195352 -1.652763387 0.254277619 -0.078560119
[66] -0.483645180 0.624555480 1.520440036 0.973779398 0.650780528
[71] 0.972950214 -1.498885209 0.196523444 1.123031785 1.052139308
[76] -1.438849994 -0.343207995 1.391023626 0.491289638 -0.002319196
[81] 0.131201456 0.636298269 -0.834224278 -1.982550039 0.348465766
[86] -0.251342618 -1.395120099 0.697276901 -0.239017895 0.975299492
[91] -0.636824436 0.749201488 1.468877105 0.787074329 0.126663517
[96] 0.158805815 0.946721350 -0.458066899 -0.995343901 0.795931077
> 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] -0.019459868 1.023747947 -1.474469653 -0.592806235 0.661148119
[6] -2.658037162 1.368305058 0.028617791 -0.353381581 0.401449764
[11] -1.316779092 0.081637313 0.130253902 0.664799438 0.904112807
[16] 0.957420535 -0.993174403 -0.451686419 -0.270070255 -0.036948878
[21] 0.826499679 1.112939557 0.372650371 -1.104355901 1.015736337
[26] 1.700978622 0.463760074 -0.751543816 -1.240495520 0.785982390
[31] -0.764937273 -1.436500065 0.012237821 0.095551262 0.225314403
[36] -0.501217479 -0.982943078 0.898282432 -0.538458952 0.537946146
[41] -0.566502396 -0.889658065 0.810248328 2.002767715 1.245934815
[46] 1.666838965 -2.247218132 -1.082250444 -0.457718514 0.166641731
[51] -1.319190488 -0.588030771 0.752192862 -1.399325953 -1.999813384
[56] 0.167937433 -0.272410600 -0.456087788 -0.511162961 -1.237998122
[61] -0.536697068 -0.354195352 -1.652763387 0.254277619 -0.078560119
[66] -0.483645180 0.624555480 1.520440036 0.973779398 0.650780528
[71] 0.972950214 -1.498885209 0.196523444 1.123031785 1.052139308
[76] -1.438849994 -0.343207995 1.391023626 0.491289638 -0.002319196
[81] 0.131201456 0.636298269 -0.834224278 -1.982550039 0.348465766
[86] -0.251342618 -1.395120099 0.697276901 -0.239017895 0.975299492
[91] -0.636824436 0.749201488 1.468877105 0.787074329 0.126663517
[96] 0.158805815 0.946721350 -0.458066899 -0.995343901 0.795931077
> colMin(tmp)
[1] -0.019459868 1.023747947 -1.474469653 -0.592806235 0.661148119
[6] -2.658037162 1.368305058 0.028617791 -0.353381581 0.401449764
[11] -1.316779092 0.081637313 0.130253902 0.664799438 0.904112807
[16] 0.957420535 -0.993174403 -0.451686419 -0.270070255 -0.036948878
[21] 0.826499679 1.112939557 0.372650371 -1.104355901 1.015736337
[26] 1.700978622 0.463760074 -0.751543816 -1.240495520 0.785982390
[31] -0.764937273 -1.436500065 0.012237821 0.095551262 0.225314403
[36] -0.501217479 -0.982943078 0.898282432 -0.538458952 0.537946146
[41] -0.566502396 -0.889658065 0.810248328 2.002767715 1.245934815
[46] 1.666838965 -2.247218132 -1.082250444 -0.457718514 0.166641731
[51] -1.319190488 -0.588030771 0.752192862 -1.399325953 -1.999813384
[56] 0.167937433 -0.272410600 -0.456087788 -0.511162961 -1.237998122
[61] -0.536697068 -0.354195352 -1.652763387 0.254277619 -0.078560119
[66] -0.483645180 0.624555480 1.520440036 0.973779398 0.650780528
[71] 0.972950214 -1.498885209 0.196523444 1.123031785 1.052139308
[76] -1.438849994 -0.343207995 1.391023626 0.491289638 -0.002319196
[81] 0.131201456 0.636298269 -0.834224278 -1.982550039 0.348465766
[86] -0.251342618 -1.395120099 0.697276901 -0.239017895 0.975299492
[91] -0.636824436 0.749201488 1.468877105 0.787074329 0.126663517
[96] 0.158805815 0.946721350 -0.458066899 -0.995343901 0.795931077
> colMedians(tmp)
[1] -0.019459868 1.023747947 -1.474469653 -0.592806235 0.661148119
[6] -2.658037162 1.368305058 0.028617791 -0.353381581 0.401449764
[11] -1.316779092 0.081637313 0.130253902 0.664799438 0.904112807
[16] 0.957420535 -0.993174403 -0.451686419 -0.270070255 -0.036948878
[21] 0.826499679 1.112939557 0.372650371 -1.104355901 1.015736337
[26] 1.700978622 0.463760074 -0.751543816 -1.240495520 0.785982390
[31] -0.764937273 -1.436500065 0.012237821 0.095551262 0.225314403
[36] -0.501217479 -0.982943078 0.898282432 -0.538458952 0.537946146
[41] -0.566502396 -0.889658065 0.810248328 2.002767715 1.245934815
[46] 1.666838965 -2.247218132 -1.082250444 -0.457718514 0.166641731
[51] -1.319190488 -0.588030771 0.752192862 -1.399325953 -1.999813384
[56] 0.167937433 -0.272410600 -0.456087788 -0.511162961 -1.237998122
[61] -0.536697068 -0.354195352 -1.652763387 0.254277619 -0.078560119
[66] -0.483645180 0.624555480 1.520440036 0.973779398 0.650780528
[71] 0.972950214 -1.498885209 0.196523444 1.123031785 1.052139308
[76] -1.438849994 -0.343207995 1.391023626 0.491289638 -0.002319196
[81] 0.131201456 0.636298269 -0.834224278 -1.982550039 0.348465766
[86] -0.251342618 -1.395120099 0.697276901 -0.239017895 0.975299492
[91] -0.636824436 0.749201488 1.468877105 0.787074329 0.126663517
[96] 0.158805815 0.946721350 -0.458066899 -0.995343901 0.795931077
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.01945987 1.023748 -1.47447 -0.5928062 0.6611481 -2.658037 1.368305
[2,] -0.01945987 1.023748 -1.47447 -0.5928062 0.6611481 -2.658037 1.368305
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.02861779 -0.3533816 0.4014498 -1.316779 0.08163731 0.1302539 0.6647994
[2,] 0.02861779 -0.3533816 0.4014498 -1.316779 0.08163731 0.1302539 0.6647994
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.9041128 0.9574205 -0.9931744 -0.4516864 -0.2700703 -0.03694888 0.8264997
[2,] 0.9041128 0.9574205 -0.9931744 -0.4516864 -0.2700703 -0.03694888 0.8264997
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.11294 0.3726504 -1.104356 1.015736 1.700979 0.4637601 -0.7515438
[2,] 1.11294 0.3726504 -1.104356 1.015736 1.700979 0.4637601 -0.7515438
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.240496 0.7859824 -0.7649373 -1.4365 0.01223782 0.09555126 0.2253144
[2,] -1.240496 0.7859824 -0.7649373 -1.4365 0.01223782 0.09555126 0.2253144
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.5012175 -0.9829431 0.8982824 -0.538459 0.5379461 -0.5665024 -0.8896581
[2,] -0.5012175 -0.9829431 0.8982824 -0.538459 0.5379461 -0.5665024 -0.8896581
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.8102483 2.002768 1.245935 1.666839 -2.247218 -1.08225 -0.4577185
[2,] 0.8102483 2.002768 1.245935 1.666839 -2.247218 -1.08225 -0.4577185
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.1666417 -1.31919 -0.5880308 0.7521929 -1.399326 -1.999813 0.1679374
[2,] 0.1666417 -1.31919 -0.5880308 0.7521929 -1.399326 -1.999813 0.1679374
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.2724106 -0.4560878 -0.511163 -1.237998 -0.5366971 -0.3541954 -1.652763
[2,] -0.2724106 -0.4560878 -0.511163 -1.237998 -0.5366971 -0.3541954 -1.652763
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.2542776 -0.07856012 -0.4836452 0.6245555 1.52044 0.9737794 0.6507805
[2,] 0.2542776 -0.07856012 -0.4836452 0.6245555 1.52044 0.9737794 0.6507805
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.9729502 -1.498885 0.1965234 1.123032 1.052139 -1.43885 -0.343208
[2,] 0.9729502 -1.498885 0.1965234 1.123032 1.052139 -1.43885 -0.343208
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.391024 0.4912896 -0.002319196 0.1312015 0.6362983 -0.8342243 -1.98255
[2,] 1.391024 0.4912896 -0.002319196 0.1312015 0.6362983 -0.8342243 -1.98255
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.3484658 -0.2513426 -1.39512 0.6972769 -0.2390179 0.9752995 -0.6368244
[2,] 0.3484658 -0.2513426 -1.39512 0.6972769 -0.2390179 0.9752995 -0.6368244
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.7492015 1.468877 0.7870743 0.1266635 0.1588058 0.9467214 -0.4580669
[2,] 0.7492015 1.468877 0.7870743 0.1266635 0.1588058 0.9467214 -0.4580669
[,99] [,100]
[1,] -0.9953439 0.7959311
[2,] -0.9953439 0.7959311
>
>
> Max(tmp2)
[1] 2.8756
> Min(tmp2)
[1] -1.85314
> mean(tmp2)
[1] 0.05733556
> Sum(tmp2)
[1] 5.733556
> Var(tmp2)
[1] 1.022356
>
> rowMeans(tmp2)
[1] 1.0233989703 -0.7211767544 -0.5893030863 -0.8452676480 1.0890747391
[6] -0.7965843955 2.0554534035 0.0002967327 1.2985470745 0.1521850149
[11] 0.1405296560 -1.4287105654 1.3184311880 -0.9215512072 -1.3150008423
[16] 1.2177114608 0.3828978227 -1.1060724765 -1.0171348331 0.7749540930
[21] -1.7267763031 -1.0372769373 -0.5500523973 1.2360556566 0.7050232919
[26] 1.1009311141 0.5191036653 -0.3370776531 0.2185710766 -0.1652730547
[31] 0.8615673708 0.0085184456 -1.7496051052 0.9013110769 0.2380655601
[36] 0.8921130444 -0.5164987566 -1.4797185017 2.4919654321 2.1104102851
[41] -0.3547821820 -0.6411779903 -0.1579691250 1.4585860337 -1.6324208021
[46] 1.2891898590 1.1325511750 1.1575119871 -0.1852217523 -0.9553734799
[51] -0.6917875531 -0.9985780395 -0.4752967264 1.4550688794 0.9833070565
[56] -0.8065497090 0.5065836729 0.6717559238 -1.8531401658 -0.0261160677
[61] -0.0456421272 2.8755998982 1.2926700059 0.2281781415 -1.0749597968
[66] 0.7446730660 1.0752352240 -0.2222544983 -0.5043494822 0.6431137220
[71] -0.5633237933 -0.5348459660 0.4535070356 0.4018781835 -0.7414919109
[76] -1.3936813981 0.9227889004 0.5305066865 1.0004863740 -0.7692152003
[81] -0.5620559897 -1.2335144472 -0.7995374145 -1.7532311769 0.0122821365
[86] 0.3266659391 -0.1109496007 -0.4450525991 -0.3619597901 1.1975108845
[91] -0.2074292658 -0.8560492799 -1.1641802694 -0.4072568182 0.7084548076
[96] -0.1790822084 1.5510291381 0.0903224469 0.9629021170 0.3356373798
> rowSums(tmp2)
[1] 1.0233989703 -0.7211767544 -0.5893030863 -0.8452676480 1.0890747391
[6] -0.7965843955 2.0554534035 0.0002967327 1.2985470745 0.1521850149
[11] 0.1405296560 -1.4287105654 1.3184311880 -0.9215512072 -1.3150008423
[16] 1.2177114608 0.3828978227 -1.1060724765 -1.0171348331 0.7749540930
[21] -1.7267763031 -1.0372769373 -0.5500523973 1.2360556566 0.7050232919
[26] 1.1009311141 0.5191036653 -0.3370776531 0.2185710766 -0.1652730547
[31] 0.8615673708 0.0085184456 -1.7496051052 0.9013110769 0.2380655601
[36] 0.8921130444 -0.5164987566 -1.4797185017 2.4919654321 2.1104102851
[41] -0.3547821820 -0.6411779903 -0.1579691250 1.4585860337 -1.6324208021
[46] 1.2891898590 1.1325511750 1.1575119871 -0.1852217523 -0.9553734799
[51] -0.6917875531 -0.9985780395 -0.4752967264 1.4550688794 0.9833070565
[56] -0.8065497090 0.5065836729 0.6717559238 -1.8531401658 -0.0261160677
[61] -0.0456421272 2.8755998982 1.2926700059 0.2281781415 -1.0749597968
[66] 0.7446730660 1.0752352240 -0.2222544983 -0.5043494822 0.6431137220
[71] -0.5633237933 -0.5348459660 0.4535070356 0.4018781835 -0.7414919109
[76] -1.3936813981 0.9227889004 0.5305066865 1.0004863740 -0.7692152003
[81] -0.5620559897 -1.2335144472 -0.7995374145 -1.7532311769 0.0122821365
[86] 0.3266659391 -0.1109496007 -0.4450525991 -0.3619597901 1.1975108845
[91] -0.2074292658 -0.8560492799 -1.1641802694 -0.4072568182 0.7084548076
[96] -0.1790822084 1.5510291381 0.0903224469 0.9629021170 0.3356373798
> 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] 1.0233989703 -0.7211767544 -0.5893030863 -0.8452676480 1.0890747391
[6] -0.7965843955 2.0554534035 0.0002967327 1.2985470745 0.1521850149
[11] 0.1405296560 -1.4287105654 1.3184311880 -0.9215512072 -1.3150008423
[16] 1.2177114608 0.3828978227 -1.1060724765 -1.0171348331 0.7749540930
[21] -1.7267763031 -1.0372769373 -0.5500523973 1.2360556566 0.7050232919
[26] 1.1009311141 0.5191036653 -0.3370776531 0.2185710766 -0.1652730547
[31] 0.8615673708 0.0085184456 -1.7496051052 0.9013110769 0.2380655601
[36] 0.8921130444 -0.5164987566 -1.4797185017 2.4919654321 2.1104102851
[41] -0.3547821820 -0.6411779903 -0.1579691250 1.4585860337 -1.6324208021
[46] 1.2891898590 1.1325511750 1.1575119871 -0.1852217523 -0.9553734799
[51] -0.6917875531 -0.9985780395 -0.4752967264 1.4550688794 0.9833070565
[56] -0.8065497090 0.5065836729 0.6717559238 -1.8531401658 -0.0261160677
[61] -0.0456421272 2.8755998982 1.2926700059 0.2281781415 -1.0749597968
[66] 0.7446730660 1.0752352240 -0.2222544983 -0.5043494822 0.6431137220
[71] -0.5633237933 -0.5348459660 0.4535070356 0.4018781835 -0.7414919109
[76] -1.3936813981 0.9227889004 0.5305066865 1.0004863740 -0.7692152003
[81] -0.5620559897 -1.2335144472 -0.7995374145 -1.7532311769 0.0122821365
[86] 0.3266659391 -0.1109496007 -0.4450525991 -0.3619597901 1.1975108845
[91] -0.2074292658 -0.8560492799 -1.1641802694 -0.4072568182 0.7084548076
[96] -0.1790822084 1.5510291381 0.0903224469 0.9629021170 0.3356373798
> rowMin(tmp2)
[1] 1.0233989703 -0.7211767544 -0.5893030863 -0.8452676480 1.0890747391
[6] -0.7965843955 2.0554534035 0.0002967327 1.2985470745 0.1521850149
[11] 0.1405296560 -1.4287105654 1.3184311880 -0.9215512072 -1.3150008423
[16] 1.2177114608 0.3828978227 -1.1060724765 -1.0171348331 0.7749540930
[21] -1.7267763031 -1.0372769373 -0.5500523973 1.2360556566 0.7050232919
[26] 1.1009311141 0.5191036653 -0.3370776531 0.2185710766 -0.1652730547
[31] 0.8615673708 0.0085184456 -1.7496051052 0.9013110769 0.2380655601
[36] 0.8921130444 -0.5164987566 -1.4797185017 2.4919654321 2.1104102851
[41] -0.3547821820 -0.6411779903 -0.1579691250 1.4585860337 -1.6324208021
[46] 1.2891898590 1.1325511750 1.1575119871 -0.1852217523 -0.9553734799
[51] -0.6917875531 -0.9985780395 -0.4752967264 1.4550688794 0.9833070565
[56] -0.8065497090 0.5065836729 0.6717559238 -1.8531401658 -0.0261160677
[61] -0.0456421272 2.8755998982 1.2926700059 0.2281781415 -1.0749597968
[66] 0.7446730660 1.0752352240 -0.2222544983 -0.5043494822 0.6431137220
[71] -0.5633237933 -0.5348459660 0.4535070356 0.4018781835 -0.7414919109
[76] -1.3936813981 0.9227889004 0.5305066865 1.0004863740 -0.7692152003
[81] -0.5620559897 -1.2335144472 -0.7995374145 -1.7532311769 0.0122821365
[86] 0.3266659391 -0.1109496007 -0.4450525991 -0.3619597901 1.1975108845
[91] -0.2074292658 -0.8560492799 -1.1641802694 -0.4072568182 0.7084548076
[96] -0.1790822084 1.5510291381 0.0903224469 0.9629021170 0.3356373798
>
> colMeans(tmp2)
[1] 0.05733556
> colSums(tmp2)
[1] 5.733556
> colVars(tmp2)
[1] 1.022356
> colSd(tmp2)
[1] 1.011116
> colMax(tmp2)
[1] 2.8756
> colMin(tmp2)
[1] -1.85314
> colMedians(tmp2)
[1] -0.01290967
> colRanges(tmp2)
[,1]
[1,] -1.85314
[2,] 2.87560
>
> 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] -1.45373330 -2.82716227 1.10424155 -1.79671169 -5.62647471 -1.30271959
[7] -1.91954925 -3.24839307 0.07668564 -2.77129619
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.24692800
[2,] -0.70937544
[3,] -0.04675953
[4,] 0.42992032
[5,] 0.99826477
>
> rowApply(tmp,sum)
[1] -4.0040458 -0.8170989 -7.8838142 -3.9433660 1.6029936 5.3332095
[7] -0.4892299 -3.1735414 -3.8320418 -2.5581781
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 5 9 8 4 4 2 7 10 2
[2,] 5 3 1 3 7 10 10 4 4 4
[3,] 10 10 3 9 3 5 4 3 3 1
[4,] 3 4 8 4 6 3 7 5 9 9
[5,] 1 7 2 1 2 9 3 9 2 7
[6,] 4 8 4 2 5 7 5 6 7 10
[7,] 2 9 7 6 1 6 9 8 6 6
[8,] 8 2 6 7 9 8 1 2 1 8
[9,] 7 6 5 10 8 1 6 10 5 5
[10,] 6 1 10 5 10 2 8 1 8 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.4803779 1.6123104 0.5878905 0.5010636 1.8275012 2.1566984
[7] 2.0965101 -3.5873329 -1.6624071 0.8084322 -0.5009773 1.1641506
[13] 4.0169822 1.4554592 -1.6970905 -3.8788739 -1.9151179 1.5399134
[19] 2.5651810 -1.5010022
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3335060
[2,] -1.0669501
[3,] -0.9677177
[4,] -0.4259324
[5,] 2.3137283
>
> rowApply(tmp,sum)
[1] 2.730699 1.654363 4.880160 7.088913 -12.245223
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 4 20 2 11
[2,] 7 13 10 20 10
[3,] 16 9 6 11 8
[4,] 15 19 2 10 3
[5,] 17 8 13 13 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.3335060 -0.3902310 0.935897830 0.9189882 1.0076044 1.2961340
[2,] -0.9677177 0.3118551 -0.009907901 1.7469159 -0.1896339 -0.8526853
[3,] 2.3137283 0.2744479 0.029074666 -1.1652127 0.4785961 2.0871126
[4,] -1.0669501 1.8544764 0.614251573 0.6116403 0.6841975 0.8808402
[5,] -0.4259324 -0.4382379 -0.981425646 -1.6112682 -0.1532629 -1.2547030
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.2528700 -0.2746407 -0.4732536 -0.1867432 -0.7089180 0.4600127
[2,] 0.2448971 -0.7880812 0.1889333 1.3147750 1.0135582 2.3018698
[3,] 0.5178315 -2.8252059 -0.9873419 0.6506491 0.8530472 0.1771270
[4,] 1.1267327 0.6995673 -0.6793794 0.6341789 0.2437383 0.3672017
[5,] 0.4599189 -0.3989725 0.2886345 -1.6044276 -1.9024030 -2.1420606
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.04307771 1.7569071 0.3223304 -0.3161859 -0.7443750 -0.5501252
[2,] 0.31500577 -1.2110016 -1.9053177 -1.4196146 0.2674517 1.4034526
[3,] -0.09409007 -0.9112552 0.1109987 0.4556299 0.2353796 1.1698480
[4,] 1.59630557 1.1536997 -0.3374121 -2.3455623 -0.1665993 0.2030236
[5,] 1.15668322 0.6671092 0.1123102 -0.2531410 -1.5069750 -0.6862857
[,19] [,20]
[1,] 0.8424485 -0.6218528
[2,] 0.3697847 -0.4801761
[3,] 1.2163565 0.2934389
[4,] 1.3163272 -0.3013649
[5,] -1.1797359 -0.3910474
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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-3.24-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-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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 -0.4271471 0.666601 -0.09174821 -1.412937 -0.6394119 0.8743176 -1.770069
col8 col9 col10 col11 col12 col13 col14
row1 -1.087154 0.3320988 -0.5682606 0.818659 -0.6955655 -0.723738 -1.286685
col15 col16 col17 col18 col19 col20
row1 0.7570868 0.9331613 -0.6526417 0.4797415 0.6279209 -0.2628688
> tmp[,"col10"]
col10
row1 -0.5682606
row2 1.4521836
row3 1.1424689
row4 0.0669676
row5 1.5060472
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.4271471 0.666601 -0.09174821 -1.412937391 -0.6394119 0.8743176
row5 0.6539301 0.360425 -2.34813766 -0.003850589 -0.1908156 -0.6329590
col7 col8 col9 col10 col11 col12 col13
row1 -1.770069 -1.0871541 0.3320988 -0.5682606 0.8186590 -0.6955655 -0.723738
row5 -2.013146 0.2557361 -1.3933314 1.5060472 0.7141065 0.4964332 2.787237
col14 col15 col16 col17 col18 col19 col20
row1 -1.286685 0.7570868 0.9331613 -0.6526417 0.4797415 0.6279209 -0.2628688
row5 -2.108321 -0.6690901 0.9717487 0.1539149 0.2608978 -1.5665288 0.8181879
> tmp[,c("col6","col20")]
col6 col20
row1 0.87431763 -0.2628688
row2 0.06603795 -0.3029128
row3 -1.63283067 -1.0607492
row4 -1.53185965 -0.5155318
row5 -0.63295900 0.8181879
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.8743176 -0.2628688
row5 -0.6329590 0.8181879
>
>
>
>
> 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 48.48618 51.01902 49.6918 49.67178 49.58227 104.6178 48.73267 48.10418
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.66039 48.48487 49.99673 50.81295 50.61871 50.91623 50.65848 49.38894
col17 col18 col19 col20
row1 50.76438 48.74468 49.53424 104.7515
> tmp[,"col10"]
col10
row1 48.48487
row2 29.27841
row3 30.86760
row4 26.84230
row5 50.25364
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.48618 51.01902 49.69180 49.67178 49.58227 104.6178 48.73267 48.10418
row5 49.67886 49.95326 51.69497 49.14961 49.43242 104.7144 50.94439 47.44661
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.66039 48.48487 49.99673 50.81295 50.61871 50.91623 50.65848 49.38894
row5 48.75525 50.25364 50.24454 50.22191 49.97388 48.33121 49.65653 50.25879
col17 col18 col19 col20
row1 50.76438 48.74468 49.53424 104.7515
row5 49.11839 50.46491 51.33470 106.1994
> tmp[,c("col6","col20")]
col6 col20
row1 104.61783 104.75151
row2 74.13583 76.35667
row3 75.69482 75.13523
row4 75.15449 76.82903
row5 104.71438 106.19942
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.6178 104.7515
row5 104.7144 106.1994
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.6178 104.7515
row5 104.7144 106.1994
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.5967260
[2,] 0.8361518
[3,] 0.2971169
[4,] 0.7567107
[5,] -0.2233946
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.3451985 -0.05599057
[2,] 0.2880730 1.00998228
[3,] 0.7011673 -2.10098533
[4,] -0.8669595 1.34219421
[5,] -0.6148039 1.39257601
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.33578155 -1.0967897
[2,] -0.03189193 0.2426719
[3,] 0.49280021 1.5709489
[4,] 0.79599729 -0.7565318
[5,] 0.34720547 0.1549710
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.3357816
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.33578155
[2,] -0.03189193
>
>
>
> 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 -0.2484054 -0.3000128 0.1939035 -0.3955608 0.2163384 -0.5206729 1.077098
row1 1.3977851 1.2081597 0.5448658 1.6926905 -0.7332755 -0.5700460 2.129062
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.8970161 -2.3902067 0.8175378 0.3996053 -2.1706612 1.134730 -0.06170533
row1 -0.7581346 0.1319919 0.3840546 1.5108248 0.7675993 -1.362119 0.99554561
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.8093147 0.2455308 1.4000951 -1.186429 0.4599942 0.7139036
row1 -0.2409579 -1.8221318 -0.5475246 1.147654 -0.4006876 -0.9913244
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.6449622 -1.076116 -1.144342 -1.466952 -0.6159018 0.2832767 -1.318974
[,8] [,9] [,10]
row2 -0.6710258 0.3625889 0.6184548
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.010146 -2.044415 0.2295256 -0.1207025 0.6842258 -0.08194824 -0.2247674
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.3122457 0.4380444 0.3187857 -0.9110816 -0.02833821 0.3451321 0.2813706
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.834422 2.205164 -1.054948 0.9134743 -0.61443 0.1765458
>
>
> 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: 0x60f641d9d130>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb315ec68033"
[2] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb314fc201fd"
[3] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb3130a5a233"
[4] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb317d3b8365"
[5] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb3152ea3bdd"
[6] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb317eca00"
[7] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb3128486a17"
[8] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb31467ef8cd"
[9] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb312708d6d5"
[10] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb31368bf51f"
[11] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb311bc83b53"
[12] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb3151b56334"
[13] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb3141914070"
[14] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb3152bd54a5"
[15] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cbb317a9ea1b6"
>
>
> ### 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: 0x60f63f99c8e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60f63f99c8e0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60f63f99c8e0>
> rowMedians(tmp)
[1] 0.183488574 0.469926590 -0.234087933 0.086330088 0.242675739
[6] -0.506046238 0.198898701 0.066881757 -0.056871640 0.169611949
[11] 0.717432346 -0.196424494 -0.140318530 -0.486587292 -0.212633924
[16] 0.037976509 0.046734075 0.183570981 0.175563916 -0.066856793
[21] -0.256879308 -0.061086349 0.157629417 -0.244852938 0.012475932
[26] -0.159379458 0.643269183 0.220353016 0.188545956 -0.204989533
[31] 0.224493876 -0.171351114 0.010057629 -0.291935663 -0.025940403
[36] -0.150729508 -0.457219148 0.255345869 -0.339409023 0.172490193
[41] -0.127074079 0.217126051 0.281867973 0.613006974 0.336770002
[46] 0.111097909 0.316958214 -0.008049912 -0.298898438 -0.676343642
[51] 0.652281867 -0.298874191 0.012251716 0.612528639 -0.205531096
[56] 0.243814535 0.103274144 -0.108594273 0.495695840 -0.111640819
[61] -0.588198526 0.297380991 0.156735436 0.029752045 -0.341925853
[66] -0.067930236 -0.248078256 -0.237769589 -0.001773492 0.043633352
[71] -0.121533676 -0.140954735 -0.190492513 -0.334818575 -0.350225605
[76] -0.200017720 0.003937011 0.458620242 -0.074225657 -0.166120684
[81] -0.269301732 -0.198986836 0.128669934 -0.591285970 0.224537780
[86] -0.184663298 0.007239989 0.406103656 0.297109088 -0.150409546
[91] 0.211274634 -0.171089213 -0.022792383 0.253575447 -0.341654165
[96] -0.181009747 -0.176206413 0.506170119 0.084838101 -0.475678809
[101] -0.292694017 0.073820209 -0.444408919 0.227029725 -0.154701504
[106] 0.022912407 0.144876565 0.315445407 0.805103584 0.079553505
[111] -0.249327438 0.400977128 0.567388189 0.015605203 -0.260719659
[116] -0.632262876 -0.116553814 -0.753755359 0.237228848 0.469645807
[121] -0.398734522 0.305007604 0.157922489 -0.235493735 0.038027302
[126] 0.053520330 0.383987520 -0.322061709 0.385001397 0.027682402
[131] 0.156117663 -0.504219707 -0.202811656 -0.056494909 0.384669911
[136] 0.199253140 -0.053941343 -0.680386351 0.444941078 -0.124923140
[141] 0.167428187 -0.544127015 0.001047077 0.412074875 -0.173417992
[146] -0.875220122 0.275995203 -0.672270382 -0.189707499 0.297941763
[151] 0.005187924 -0.106830405 -0.127567870 -0.595919088 -0.551377260
[156] 0.238407587 -0.144580969 -0.217966878 -0.371553468 0.036598742
[161] -0.043492247 0.443189539 -0.160590544 -0.044412983 0.030898529
[166] 0.204306202 -0.538810483 -0.278816953 -0.317833441 -0.123551111
[171] -0.476687890 -0.339525313 -0.345663851 -0.489278550 -0.405793215
[176] 0.081005466 0.202332412 -0.329078684 -0.011335316 -0.334024024
[181] -0.211598386 0.142388942 0.217185009 0.174913487 0.363664931
[186] -0.267034964 -0.507447245 0.089972071 -0.052490660 -0.466399180
[191] 0.364396395 0.043058002 0.059084406 0.438020548 -0.078360903
[196] 0.095958952 -0.015227108 0.215321146 0.022474841 0.081875756
[201] -0.597351389 -0.513713398 -0.530330194 -0.195603653 -0.280411851
[206] 0.581975002 0.537791580 -0.558706327 -0.117668660 0.023755174
[211] 0.115547416 0.314545501 0.152401760 0.177218297 0.184275782
[216] 0.154187193 0.223923117 0.236577951 0.863971232 -0.141157964
[221] 0.144842735 0.134145800 0.059206978 0.111748721 -0.773386695
[226] 0.325201904 0.551416608 -0.278394720 -0.189046136 -0.315893056
>
> proc.time()
user system elapsed
1.249 0.700 1.939
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: 0x642d41784520>
> .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: 0x642d41784520>
> .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: 0x642d41784520>
> .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: 0x642d41784520>
> 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: 0x642d4132df60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d4132df60>
> .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: 0x642d4132df60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d4132df60>
> .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: 0x642d4132df60>
> 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: 0x642d41ed7b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d41ed7b40>
> .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: 0x642d41ed7b40>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x642d41ed7b40>
> .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: 0x642d41ed7b40>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x642d41ed7b40>
> .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: 0x642d41ed7b40>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x642d41ed7b40>
> .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: 0x642d41ed7b40>
> 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: 0x642d41f14bc0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x642d41f14bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d41f14bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d41f14bc0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1cbc773e87d4d3" "BufferedMatrixFile1cbc77540014bc"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1cbc773e87d4d3" "BufferedMatrixFile1cbc77540014bc"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d41eae000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d41eae000>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x642d41eae000>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x642d41eae000>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x642d41eae000>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x642d41eae000>
> .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: 0x642d40fe1e30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x642d40fe1e30>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x642d40fe1e30>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x642d40fe1e30>
> 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: 0x642d4160ba50>
> .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: 0x642d4160ba50>
> rm(P)
>
> proc.time()
user system elapsed
0.282 0.046 0.315
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.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.250 0.049 0.285