Ben Bolstad
| Snapshot Date: 2026-04-26 13:40 -0400 (Sun, 26 Apr 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0400 (Wed, 29 Oct 2025) |
| Back to Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-04-27 11:32 -0400 (Mon, 27 Apr 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" | 4980 |
| 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 262/2417 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.75.0 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz |
| StartedAt: 2026-04-26 22:01:25 -0400 (Sun, 26 Apr 2026) |
| EndedAt: 2026-04-26 22:01:50 -0400 (Sun, 26 Apr 2026) |
| EllapsedTime: 25.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 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: 2026-04-27 02:01:26 UTC
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.75.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ...* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.23-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.23-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.23-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.6.0 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
0.247 0.050 0.285
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] "Sun Apr 26 22:01:41 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] "Sun Apr 26 22:01:41 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: 0x6219233148e0>
>
>
>
> 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] "Sun Apr 26 22:01:41 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] "Sun Apr 26 22:01:42 2026"
>
> ColMode(tmp2)
<pointer: 0x6219233148e0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2934438 -0.5017787 0.4771174 0.51995194
[2,] 0.1936197 0.5633830 -1.1150116 -0.94293251
[3,] -1.1280058 -0.4910196 2.2130671 0.05514873
[4,] -0.3830620 0.9119914 1.4147493 -1.56610156
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2934438 0.5017787 0.4771174 0.51995194
[2,] 0.1936197 0.5633830 1.1150116 0.94293251
[3,] 1.1280058 0.4910196 2.2130671 0.05514873
[4,] 0.3830620 0.9119914 1.4147493 1.56610156
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0146614 0.7083634 0.6907369 0.7210769
[2,] 0.4400224 0.7505884 1.0559411 0.9710471
[3,] 1.0620762 0.7007279 1.4876381 0.2348377
[4,] 0.6189200 0.9549824 1.1894323 1.2514398
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.44006 32.58541 32.38449 32.73072
[2,] 29.59384 33.06927 36.67442 35.65340
[3,] 36.74877 32.49830 42.08945 27.40353
[4,] 31.57226 35.46182 38.30907 39.08050
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6219233d6900>
> exp(tmp5)
<pointer: 0x6219233d6900>
> log(tmp5,2)
<pointer: 0x6219233d6900>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.2239
> Min(tmp5)
[1] 53.14131
> mean(tmp5)
[1] 71.5108
> Sum(tmp5)
[1] 14302.16
> Var(tmp5)
[1] 867.7157
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.53374 69.52546 65.13652 72.36665 69.14524 69.16396 69.72330 68.18106
[9] 71.93742 68.39470
> rowSums(tmp5)
[1] 1830.675 1390.509 1302.730 1447.333 1382.905 1383.279 1394.466 1363.621
[9] 1438.748 1367.894
> rowVars(tmp5)
[1] 7968.61312 70.34777 78.21312 91.10500 67.19452 83.61509
[7] 62.84329 40.15558 55.12852 64.12051
> rowSd(tmp5)
[1] 89.267089 8.387358 8.843818 9.544894 8.197226 9.144129 7.927376
[8] 6.336843 7.424858 8.007528
> rowMax(tmp5)
[1] 469.22394 85.72472 87.60367 88.80335 88.39617 87.80963 84.02742
[8] 80.04228 90.85246 82.36643
> rowMin(tmp5)
[1] 57.48472 54.03363 53.14131 54.07897 53.88989 56.21728 53.87525 60.45064
[9] 61.03554 57.14913
>
> colMeans(tmp5)
[1] 107.76945 70.80519 71.88624 67.35963 68.23748 68.28532 69.27658
[8] 70.96049 66.75389 68.20879 64.52415 69.82544 68.69712 68.12456
[15] 72.47441 71.32946 75.50473 72.37261 67.39535 70.42519
> colSums(tmp5)
[1] 1077.6945 708.0519 718.8624 673.5963 682.3748 682.8532 692.7658
[8] 709.6049 667.5389 682.0879 645.2415 698.2544 686.9712 681.2456
[15] 724.7441 713.2946 755.0473 723.7261 673.9535 704.2519
> colVars(tmp5)
[1] 16220.44867 13.68709 82.64295 65.40396 46.78686 102.70431
[7] 64.73812 75.70074 39.01442 39.08049 52.26692 145.70947
[13] 40.09959 116.88242 117.32394 54.20631 43.54147 81.87281
[19] 58.61164 59.53304
> colSd(tmp5)
[1] 127.359525 3.699607 9.090817 8.087272 6.840092 10.134314
[7] 8.046000 8.700617 6.246152 6.251439 7.229586 12.071018
[13] 6.332424 10.811217 10.831618 7.362493 6.598596 9.048360
[19] 7.655824 7.715766
> colMax(tmp5)
[1] 469.22394 77.56007 87.60367 81.34094 77.87103 85.72472 80.54039
[8] 83.44188 80.53677 76.52835 77.63173 88.80335 80.66816 81.60766
[15] 90.85246 86.02150 84.02742 84.47775 78.71538 81.15474
> colMin(tmp5)
[1] 56.21728 66.02802 57.14913 56.51413 58.62425 54.41103 53.88989 57.48472
[9] 58.12809 58.42123 54.07897 57.00063 60.65020 54.03363 53.14131 59.27451
[17] 66.12315 54.63498 53.87525 61.03554
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 91.53374 69.52546 65.13652 72.36665 69.14524 NA 69.72330 68.18106
[9] 71.93742 68.39470
> rowSums(tmp5)
[1] 1830.675 1390.509 1302.730 1447.333 1382.905 NA 1394.466 1363.621
[9] 1438.748 1367.894
> rowVars(tmp5)
[1] 7968.61312 70.34777 78.21312 91.10500 67.19452 87.97348
[7] 62.84329 40.15558 55.12852 64.12051
> rowSd(tmp5)
[1] 89.267089 8.387358 8.843818 9.544894 8.197226 9.379418 7.927376
[8] 6.336843 7.424858 8.007528
> rowMax(tmp5)
[1] 469.22394 85.72472 87.60367 88.80335 88.39617 NA 84.02742
[8] 80.04228 90.85246 82.36643
> rowMin(tmp5)
[1] 57.48472 54.03363 53.14131 54.07897 53.88989 NA 53.87525 60.45064
[9] 61.03554 57.14913
>
> colMeans(tmp5)
[1] 107.76945 70.80519 71.88624 67.35963 68.23748 68.28532 69.27658
[8] 70.96049 66.75389 68.20879 64.52415 69.82544 68.69712 68.12456
[15] 72.47441 71.32946 NA 72.37261 67.39535 70.42519
> colSums(tmp5)
[1] 1077.6945 708.0519 718.8624 673.5963 682.3748 682.8532 692.7658
[8] 709.6049 667.5389 682.0879 645.2415 698.2544 686.9712 681.2456
[15] 724.7441 713.2946 NA 723.7261 673.9535 704.2519
> colVars(tmp5)
[1] 16220.44867 13.68709 82.64295 65.40396 46.78686 102.70431
[7] 64.73812 75.70074 39.01442 39.08049 52.26692 145.70947
[13] 40.09959 116.88242 117.32394 54.20631 NA 81.87281
[19] 58.61164 59.53304
> colSd(tmp5)
[1] 127.359525 3.699607 9.090817 8.087272 6.840092 10.134314
[7] 8.046000 8.700617 6.246152 6.251439 7.229586 12.071018
[13] 6.332424 10.811217 10.831618 7.362493 NA 9.048360
[19] 7.655824 7.715766
> colMax(tmp5)
[1] 469.22394 77.56007 87.60367 81.34094 77.87103 85.72472 80.54039
[8] 83.44188 80.53677 76.52835 77.63173 88.80335 80.66816 81.60766
[15] 90.85246 86.02150 NA 84.47775 78.71538 81.15474
> colMin(tmp5)
[1] 56.21728 66.02802 57.14913 56.51413 58.62425 54.41103 53.88989 57.48472
[9] 58.12809 58.42123 54.07897 57.00063 60.65020 54.03363 53.14131 59.27451
[17] NA 54.63498 53.87525 61.03554
>
> Max(tmp5,na.rm=TRUE)
[1] 469.2239
> Min(tmp5,na.rm=TRUE)
[1] 53.14131
> mean(tmp5,na.rm=TRUE)
[1] 71.51147
> Sum(tmp5,na.rm=TRUE)
[1] 14230.78
> Var(tmp5,na.rm=TRUE)
[1] 872.098
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.53374 69.52546 65.13652 72.36665 69.14524 69.04739 69.72330 68.18106
[9] 71.93742 68.39470
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.675 1390.509 1302.730 1447.333 1382.905 1311.900 1394.466 1363.621
[9] 1438.748 1367.894
> rowVars(tmp5,na.rm=TRUE)
[1] 7968.61312 70.34777 78.21312 91.10500 67.19452 87.97348
[7] 62.84329 40.15558 55.12852 64.12051
> rowSd(tmp5,na.rm=TRUE)
[1] 89.267089 8.387358 8.843818 9.544894 8.197226 9.379418 7.927376
[8] 6.336843 7.424858 8.007528
> rowMax(tmp5,na.rm=TRUE)
[1] 469.22394 85.72472 87.60367 88.80335 88.39617 87.80963 84.02742
[8] 80.04228 90.85246 82.36643
> rowMin(tmp5,na.rm=TRUE)
[1] 57.48472 54.03363 53.14131 54.07897 53.88989 56.21728 53.87525 60.45064
[9] 61.03554 57.14913
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.76945 70.80519 71.88624 67.35963 68.23748 68.28532 69.27658
[8] 70.96049 66.75389 68.20879 64.52415 69.82544 68.69712 68.12456
[15] 72.47441 71.32946 75.96316 72.37261 67.39535 70.42519
> colSums(tmp5,na.rm=TRUE)
[1] 1077.6945 708.0519 718.8624 673.5963 682.3748 682.8532 692.7658
[8] 709.6049 667.5389 682.0879 645.2415 698.2544 686.9712 681.2456
[15] 724.7441 713.2946 683.6684 723.7261 673.9535 704.2519
> colVars(tmp5,na.rm=TRUE)
[1] 16220.44867 13.68709 82.64295 65.40396 46.78686 102.70431
[7] 64.73812 75.70074 39.01442 39.08049 52.26692 145.70947
[13] 40.09959 116.88242 117.32394 54.20631 46.61989 81.87281
[19] 58.61164 59.53304
> colSd(tmp5,na.rm=TRUE)
[1] 127.359525 3.699607 9.090817 8.087272 6.840092 10.134314
[7] 8.046000 8.700617 6.246152 6.251439 7.229586 12.071018
[13] 6.332424 10.811217 10.831618 7.362493 6.827876 9.048360
[19] 7.655824 7.715766
> colMax(tmp5,na.rm=TRUE)
[1] 469.22394 77.56007 87.60367 81.34094 77.87103 85.72472 80.54039
[8] 83.44188 80.53677 76.52835 77.63173 88.80335 80.66816 81.60766
[15] 90.85246 86.02150 84.02742 84.47775 78.71538 81.15474
> colMin(tmp5,na.rm=TRUE)
[1] 56.21728 66.02802 57.14913 56.51413 58.62425 54.41103 53.88989 57.48472
[9] 58.12809 58.42123 54.07897 57.00063 60.65020 54.03363 53.14131 59.27451
[17] 66.12315 54.63498 53.87525 61.03554
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.53374 69.52546 65.13652 72.36665 69.14524 NaN 69.72330 68.18106
[9] 71.93742 68.39470
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.675 1390.509 1302.730 1447.333 1382.905 0.000 1394.466 1363.621
[9] 1438.748 1367.894
> rowVars(tmp5,na.rm=TRUE)
[1] 7968.61312 70.34777 78.21312 91.10500 67.19452 NA
[7] 62.84329 40.15558 55.12852 64.12051
> rowSd(tmp5,na.rm=TRUE)
[1] 89.267089 8.387358 8.843818 9.544894 8.197226 NA 7.927376
[8] 6.336843 7.424858 8.007528
> rowMax(tmp5,na.rm=TRUE)
[1] 469.22394 85.72472 87.60367 88.80335 88.39617 NA 84.02742
[8] 80.04228 90.85246 82.36643
> rowMin(tmp5,na.rm=TRUE)
[1] 57.48472 54.03363 53.14131 54.07897 53.88989 NA 53.87525 60.45064
[9] 61.03554 57.14913
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.49747 70.65184 72.83822 68.56469 69.30561 67.21132 68.93130
[8] 69.86926 65.22246 67.79763 64.24694 67.82720 69.13524 69.41683
[15] 73.65487 71.61225 NaN 72.89295 67.55903 69.23302
> colSums(tmp5,na.rm=TRUE)
[1] 1021.4772 635.8666 655.5440 617.0822 623.7505 604.9019 620.3817
[8] 628.8233 587.0022 610.1787 578.2224 610.4448 622.2172 624.7515
[15] 662.8938 644.5102 0.0000 656.0365 608.0313 623.0972
> colVars(tmp5,na.rm=TRUE)
[1] 17878.88997 15.13342 82.77784 57.24267 39.79993 102.56588
[7] 71.48918 71.76696 17.50683 42.06376 57.93574 119.00219
[13] 42.95256 112.70555 116.31283 60.08242 NA 89.06098
[19] 65.63670 50.98533
> colSd(tmp5,na.rm=TRUE)
[1] 133.711966 3.890170 9.098233 7.565888 6.308718 10.127481
[7] 8.455127 8.471538 4.184117 6.485658 7.611553 10.908812
[13] 6.553820 10.616287 10.784842 7.751285 NA 9.437212
[19] 8.101648 7.140401
> colMax(tmp5,na.rm=TRUE)
[1] 469.22394 77.56007 87.60367 81.34094 77.87103 85.72472 80.54039
[8] 83.44188 69.98401 76.52835 77.63173 88.80335 80.66816 81.60766
[15] 90.85246 86.02150 -Inf 84.47775 78.71538 78.93929
> colMin(tmp5,na.rm=TRUE)
[1] 57.25275 66.02802 57.14913 57.03685 60.45064 54.41103 53.88989 57.48472
[9] 58.12809 58.42123 54.07897 57.00063 60.65020 54.03363 53.14131 59.27451
[17] Inf 54.63498 53.87525 61.03554
>
>
>
>
> 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] 180.05054 128.99572 162.54576 162.15450 174.66886 235.49700 117.07258
[8] 237.23796 88.41603 282.10844
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 180.05054 128.99572 162.54576 162.15450 174.66886 235.49700 117.07258
[8] 237.23796 88.41603 282.10844
>
>
>
> 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] 0.000000e+00 -2.842171e-14 -1.421085e-14 5.684342e-14 -8.526513e-14
[6] 8.526513e-14 5.684342e-14 0.000000e+00 2.131628e-14 -5.684342e-14
[11] 5.684342e-14 5.684342e-14 -5.684342e-14 1.136868e-13 4.263256e-14
[16] 2.273737e-13 2.842171e-14 0.000000e+00 1.705303e-13 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 14
6 19
6 19
6 3
1 6
2 15
9 8
7 13
2 7
8 1
7 17
3 19
7 18
5 9
7 20
8 1
8 14
3 5
6 16
7 2
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] 2.633651
> Min(tmp)
[1] -2.503098
> mean(tmp)
[1] 0.09305181
> Sum(tmp)
[1] 9.305181
> Var(tmp)
[1] 1.001384
>
> rowMeans(tmp)
[1] 0.09305181
> rowSums(tmp)
[1] 9.305181
> rowVars(tmp)
[1] 1.001384
> rowSd(tmp)
[1] 1.000692
> rowMax(tmp)
[1] 2.633651
> rowMin(tmp)
[1] -2.503098
>
> colMeans(tmp)
[1] 0.071633408 1.119865045 -0.123533003 -1.510213201 -0.866800812
[6] 0.422602944 -1.468979075 -2.503098074 0.849017014 0.215459022
[11] 0.839763686 0.430523972 1.411033207 -0.121618038 -0.085437995
[16] 0.281621924 0.316050633 2.633650674 -0.665778350 1.423436400
[21] -0.288244888 0.888212574 -0.556940346 -0.526688072 1.116797139
[26] 0.570426631 -1.454285246 0.929096258 -0.503689717 0.726747375
[31] 0.384199906 0.856581305 0.776624254 -0.099939348 -0.022647672
[36] -1.442888720 0.393745155 -0.500226030 0.603985011 -0.700539304
[41] -0.470310132 -1.154660275 -0.915489880 1.686421744 -1.028382365
[46] 0.048017883 -2.332944136 -0.823817281 0.668157321 -0.933094093
[51] -0.239537811 1.654634131 -1.747093705 -1.869521152 1.017864475
[56] 0.413650895 0.729694340 0.273210675 -0.256785156 -1.137965477
[61] 0.490526105 -0.610131101 -0.444322331 -1.037809679 0.538822656
[66] -0.671592427 -0.184117625 0.033751991 0.919894282 0.100434441
[71] -0.291434812 1.196859587 -1.009437138 0.297735107 -0.088683118
[76] 1.438345932 1.679206509 -2.054242313 0.369958178 -0.095042995
[81] 1.347601261 -0.336466557 0.648407707 1.533622716 0.028851827
[86] 1.113569213 0.474039020 -1.627750193 1.668862929 -0.515230821
[91] 0.966061374 1.097170534 -0.094351311 0.834362346 1.860657269
[96] 1.191904787 0.001809134 0.301975148 -0.095517649 0.925305367
> colSums(tmp)
[1] 0.071633408 1.119865045 -0.123533003 -1.510213201 -0.866800812
[6] 0.422602944 -1.468979075 -2.503098074 0.849017014 0.215459022
[11] 0.839763686 0.430523972 1.411033207 -0.121618038 -0.085437995
[16] 0.281621924 0.316050633 2.633650674 -0.665778350 1.423436400
[21] -0.288244888 0.888212574 -0.556940346 -0.526688072 1.116797139
[26] 0.570426631 -1.454285246 0.929096258 -0.503689717 0.726747375
[31] 0.384199906 0.856581305 0.776624254 -0.099939348 -0.022647672
[36] -1.442888720 0.393745155 -0.500226030 0.603985011 -0.700539304
[41] -0.470310132 -1.154660275 -0.915489880 1.686421744 -1.028382365
[46] 0.048017883 -2.332944136 -0.823817281 0.668157321 -0.933094093
[51] -0.239537811 1.654634131 -1.747093705 -1.869521152 1.017864475
[56] 0.413650895 0.729694340 0.273210675 -0.256785156 -1.137965477
[61] 0.490526105 -0.610131101 -0.444322331 -1.037809679 0.538822656
[66] -0.671592427 -0.184117625 0.033751991 0.919894282 0.100434441
[71] -0.291434812 1.196859587 -1.009437138 0.297735107 -0.088683118
[76] 1.438345932 1.679206509 -2.054242313 0.369958178 -0.095042995
[81] 1.347601261 -0.336466557 0.648407707 1.533622716 0.028851827
[86] 1.113569213 0.474039020 -1.627750193 1.668862929 -0.515230821
[91] 0.966061374 1.097170534 -0.094351311 0.834362346 1.860657269
[96] 1.191904787 0.001809134 0.301975148 -0.095517649 0.925305367
> 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] 0.071633408 1.119865045 -0.123533003 -1.510213201 -0.866800812
[6] 0.422602944 -1.468979075 -2.503098074 0.849017014 0.215459022
[11] 0.839763686 0.430523972 1.411033207 -0.121618038 -0.085437995
[16] 0.281621924 0.316050633 2.633650674 -0.665778350 1.423436400
[21] -0.288244888 0.888212574 -0.556940346 -0.526688072 1.116797139
[26] 0.570426631 -1.454285246 0.929096258 -0.503689717 0.726747375
[31] 0.384199906 0.856581305 0.776624254 -0.099939348 -0.022647672
[36] -1.442888720 0.393745155 -0.500226030 0.603985011 -0.700539304
[41] -0.470310132 -1.154660275 -0.915489880 1.686421744 -1.028382365
[46] 0.048017883 -2.332944136 -0.823817281 0.668157321 -0.933094093
[51] -0.239537811 1.654634131 -1.747093705 -1.869521152 1.017864475
[56] 0.413650895 0.729694340 0.273210675 -0.256785156 -1.137965477
[61] 0.490526105 -0.610131101 -0.444322331 -1.037809679 0.538822656
[66] -0.671592427 -0.184117625 0.033751991 0.919894282 0.100434441
[71] -0.291434812 1.196859587 -1.009437138 0.297735107 -0.088683118
[76] 1.438345932 1.679206509 -2.054242313 0.369958178 -0.095042995
[81] 1.347601261 -0.336466557 0.648407707 1.533622716 0.028851827
[86] 1.113569213 0.474039020 -1.627750193 1.668862929 -0.515230821
[91] 0.966061374 1.097170534 -0.094351311 0.834362346 1.860657269
[96] 1.191904787 0.001809134 0.301975148 -0.095517649 0.925305367
> colMin(tmp)
[1] 0.071633408 1.119865045 -0.123533003 -1.510213201 -0.866800812
[6] 0.422602944 -1.468979075 -2.503098074 0.849017014 0.215459022
[11] 0.839763686 0.430523972 1.411033207 -0.121618038 -0.085437995
[16] 0.281621924 0.316050633 2.633650674 -0.665778350 1.423436400
[21] -0.288244888 0.888212574 -0.556940346 -0.526688072 1.116797139
[26] 0.570426631 -1.454285246 0.929096258 -0.503689717 0.726747375
[31] 0.384199906 0.856581305 0.776624254 -0.099939348 -0.022647672
[36] -1.442888720 0.393745155 -0.500226030 0.603985011 -0.700539304
[41] -0.470310132 -1.154660275 -0.915489880 1.686421744 -1.028382365
[46] 0.048017883 -2.332944136 -0.823817281 0.668157321 -0.933094093
[51] -0.239537811 1.654634131 -1.747093705 -1.869521152 1.017864475
[56] 0.413650895 0.729694340 0.273210675 -0.256785156 -1.137965477
[61] 0.490526105 -0.610131101 -0.444322331 -1.037809679 0.538822656
[66] -0.671592427 -0.184117625 0.033751991 0.919894282 0.100434441
[71] -0.291434812 1.196859587 -1.009437138 0.297735107 -0.088683118
[76] 1.438345932 1.679206509 -2.054242313 0.369958178 -0.095042995
[81] 1.347601261 -0.336466557 0.648407707 1.533622716 0.028851827
[86] 1.113569213 0.474039020 -1.627750193 1.668862929 -0.515230821
[91] 0.966061374 1.097170534 -0.094351311 0.834362346 1.860657269
[96] 1.191904787 0.001809134 0.301975148 -0.095517649 0.925305367
> colMedians(tmp)
[1] 0.071633408 1.119865045 -0.123533003 -1.510213201 -0.866800812
[6] 0.422602944 -1.468979075 -2.503098074 0.849017014 0.215459022
[11] 0.839763686 0.430523972 1.411033207 -0.121618038 -0.085437995
[16] 0.281621924 0.316050633 2.633650674 -0.665778350 1.423436400
[21] -0.288244888 0.888212574 -0.556940346 -0.526688072 1.116797139
[26] 0.570426631 -1.454285246 0.929096258 -0.503689717 0.726747375
[31] 0.384199906 0.856581305 0.776624254 -0.099939348 -0.022647672
[36] -1.442888720 0.393745155 -0.500226030 0.603985011 -0.700539304
[41] -0.470310132 -1.154660275 -0.915489880 1.686421744 -1.028382365
[46] 0.048017883 -2.332944136 -0.823817281 0.668157321 -0.933094093
[51] -0.239537811 1.654634131 -1.747093705 -1.869521152 1.017864475
[56] 0.413650895 0.729694340 0.273210675 -0.256785156 -1.137965477
[61] 0.490526105 -0.610131101 -0.444322331 -1.037809679 0.538822656
[66] -0.671592427 -0.184117625 0.033751991 0.919894282 0.100434441
[71] -0.291434812 1.196859587 -1.009437138 0.297735107 -0.088683118
[76] 1.438345932 1.679206509 -2.054242313 0.369958178 -0.095042995
[81] 1.347601261 -0.336466557 0.648407707 1.533622716 0.028851827
[86] 1.113569213 0.474039020 -1.627750193 1.668862929 -0.515230821
[91] 0.966061374 1.097170534 -0.094351311 0.834362346 1.860657269
[96] 1.191904787 0.001809134 0.301975148 -0.095517649 0.925305367
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.07163341 1.119865 -0.123533 -1.510213 -0.8668008 0.4226029 -1.468979
[2,] 0.07163341 1.119865 -0.123533 -1.510213 -0.8668008 0.4226029 -1.468979
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -2.503098 0.849017 0.215459 0.8397637 0.430524 1.411033 -0.121618
[2,] -2.503098 0.849017 0.215459 0.8397637 0.430524 1.411033 -0.121618
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.08543799 0.2816219 0.3160506 2.633651 -0.6657784 1.423436 -0.2882449
[2,] -0.08543799 0.2816219 0.3160506 2.633651 -0.6657784 1.423436 -0.2882449
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.8882126 -0.5569403 -0.5266881 1.116797 0.5704266 -1.454285 0.9290963
[2,] 0.8882126 -0.5569403 -0.5266881 1.116797 0.5704266 -1.454285 0.9290963
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5036897 0.7267474 0.3841999 0.8565813 0.7766243 -0.09993935 -0.02264767
[2,] -0.5036897 0.7267474 0.3841999 0.8565813 0.7766243 -0.09993935 -0.02264767
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.442889 0.3937452 -0.500226 0.603985 -0.7005393 -0.4703101 -1.15466
[2,] -1.442889 0.3937452 -0.500226 0.603985 -0.7005393 -0.4703101 -1.15466
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.9154899 1.686422 -1.028382 0.04801788 -2.332944 -0.8238173 0.6681573
[2,] -0.9154899 1.686422 -1.028382 0.04801788 -2.332944 -0.8238173 0.6681573
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.9330941 -0.2395378 1.654634 -1.747094 -1.869521 1.017864 0.4136509
[2,] -0.9330941 -0.2395378 1.654634 -1.747094 -1.869521 1.017864 0.4136509
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.7296943 0.2732107 -0.2567852 -1.137965 0.4905261 -0.6101311 -0.4443223
[2,] 0.7296943 0.2732107 -0.2567852 -1.137965 0.4905261 -0.6101311 -0.4443223
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.03781 0.5388227 -0.6715924 -0.1841176 0.03375199 0.9198943 0.1004344
[2,] -1.03781 0.5388227 -0.6715924 -0.1841176 0.03375199 0.9198943 0.1004344
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.2914348 1.19686 -1.009437 0.2977351 -0.08868312 1.438346 1.679207
[2,] -0.2914348 1.19686 -1.009437 0.2977351 -0.08868312 1.438346 1.679207
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -2.054242 0.3699582 -0.09504299 1.347601 -0.3364666 0.6484077 1.533623
[2,] -2.054242 0.3699582 -0.09504299 1.347601 -0.3364666 0.6484077 1.533623
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.02885183 1.113569 0.474039 -1.62775 1.668863 -0.5152308 0.9660614
[2,] 0.02885183 1.113569 0.474039 -1.62775 1.668863 -0.5152308 0.9660614
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.097171 -0.09435131 0.8343623 1.860657 1.191905 0.001809134 0.3019751
[2,] 1.097171 -0.09435131 0.8343623 1.860657 1.191905 0.001809134 0.3019751
[,99] [,100]
[1,] -0.09551765 0.9253054
[2,] -0.09551765 0.9253054
>
>
> Max(tmp2)
[1] 2.5629
> Min(tmp2)
[1] -2.075273
> mean(tmp2)
[1] 0.0261286
> Sum(tmp2)
[1] 2.61286
> Var(tmp2)
[1] 0.80672
>
> rowMeans(tmp2)
[1] 0.76919515 0.28435173 -0.23505650 0.65434321 -0.88690535 0.49858747
[7] -0.31805512 -1.00170838 0.04146569 -0.29449601 2.08220613 0.61612200
[13] 0.03374992 0.88820194 -0.07011952 -1.14279996 0.18448776 -0.33676136
[19] 0.54316405 0.81852996 0.87314284 -0.02977821 -0.31274740 -0.64687241
[25] -0.96043691 -0.01956337 0.13426016 0.60223629 -0.08260404 0.95887665
[31] 1.41197519 -0.93606184 0.20330453 -0.59854205 -1.06021165 0.89831605
[37] 0.05463010 0.12725013 0.83847081 1.56569542 0.27726825 0.01272732
[43] 2.56290036 -0.47472684 -1.08070993 -0.53883136 -0.55845349 0.50044550
[49] 0.25944927 0.54480358 0.85605385 -0.54336767 2.01672349 -0.76439522
[55] 0.13142137 0.47914032 0.06974256 -0.53688277 1.81735796 -0.95339493
[61] -0.37956435 0.50245382 -0.41866832 -1.46067471 1.87192344 -0.08738063
[67] -1.11524682 -1.22476035 0.92429310 -1.17470106 -0.98065889 0.77777449
[73] -0.13811240 -1.70049747 0.19910169 -0.11587581 -0.88951820 -0.14530128
[79] -2.07527335 0.65046079 0.31958977 -0.81018395 0.53670734 -0.52689118
[85] -1.91046451 0.47108365 0.54095977 0.21263896 -0.15037217 0.40270411
[91] -0.81297812 -0.14375618 0.96461440 -1.12346312 -0.30647413 0.79971513
[97] 2.38439204 -0.65404785 -0.43125664 -0.39654523
> rowSums(tmp2)
[1] 0.76919515 0.28435173 -0.23505650 0.65434321 -0.88690535 0.49858747
[7] -0.31805512 -1.00170838 0.04146569 -0.29449601 2.08220613 0.61612200
[13] 0.03374992 0.88820194 -0.07011952 -1.14279996 0.18448776 -0.33676136
[19] 0.54316405 0.81852996 0.87314284 -0.02977821 -0.31274740 -0.64687241
[25] -0.96043691 -0.01956337 0.13426016 0.60223629 -0.08260404 0.95887665
[31] 1.41197519 -0.93606184 0.20330453 -0.59854205 -1.06021165 0.89831605
[37] 0.05463010 0.12725013 0.83847081 1.56569542 0.27726825 0.01272732
[43] 2.56290036 -0.47472684 -1.08070993 -0.53883136 -0.55845349 0.50044550
[49] 0.25944927 0.54480358 0.85605385 -0.54336767 2.01672349 -0.76439522
[55] 0.13142137 0.47914032 0.06974256 -0.53688277 1.81735796 -0.95339493
[61] -0.37956435 0.50245382 -0.41866832 -1.46067471 1.87192344 -0.08738063
[67] -1.11524682 -1.22476035 0.92429310 -1.17470106 -0.98065889 0.77777449
[73] -0.13811240 -1.70049747 0.19910169 -0.11587581 -0.88951820 -0.14530128
[79] -2.07527335 0.65046079 0.31958977 -0.81018395 0.53670734 -0.52689118
[85] -1.91046451 0.47108365 0.54095977 0.21263896 -0.15037217 0.40270411
[91] -0.81297812 -0.14375618 0.96461440 -1.12346312 -0.30647413 0.79971513
[97] 2.38439204 -0.65404785 -0.43125664 -0.39654523
> 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] 0.76919515 0.28435173 -0.23505650 0.65434321 -0.88690535 0.49858747
[7] -0.31805512 -1.00170838 0.04146569 -0.29449601 2.08220613 0.61612200
[13] 0.03374992 0.88820194 -0.07011952 -1.14279996 0.18448776 -0.33676136
[19] 0.54316405 0.81852996 0.87314284 -0.02977821 -0.31274740 -0.64687241
[25] -0.96043691 -0.01956337 0.13426016 0.60223629 -0.08260404 0.95887665
[31] 1.41197519 -0.93606184 0.20330453 -0.59854205 -1.06021165 0.89831605
[37] 0.05463010 0.12725013 0.83847081 1.56569542 0.27726825 0.01272732
[43] 2.56290036 -0.47472684 -1.08070993 -0.53883136 -0.55845349 0.50044550
[49] 0.25944927 0.54480358 0.85605385 -0.54336767 2.01672349 -0.76439522
[55] 0.13142137 0.47914032 0.06974256 -0.53688277 1.81735796 -0.95339493
[61] -0.37956435 0.50245382 -0.41866832 -1.46067471 1.87192344 -0.08738063
[67] -1.11524682 -1.22476035 0.92429310 -1.17470106 -0.98065889 0.77777449
[73] -0.13811240 -1.70049747 0.19910169 -0.11587581 -0.88951820 -0.14530128
[79] -2.07527335 0.65046079 0.31958977 -0.81018395 0.53670734 -0.52689118
[85] -1.91046451 0.47108365 0.54095977 0.21263896 -0.15037217 0.40270411
[91] -0.81297812 -0.14375618 0.96461440 -1.12346312 -0.30647413 0.79971513
[97] 2.38439204 -0.65404785 -0.43125664 -0.39654523
> rowMin(tmp2)
[1] 0.76919515 0.28435173 -0.23505650 0.65434321 -0.88690535 0.49858747
[7] -0.31805512 -1.00170838 0.04146569 -0.29449601 2.08220613 0.61612200
[13] 0.03374992 0.88820194 -0.07011952 -1.14279996 0.18448776 -0.33676136
[19] 0.54316405 0.81852996 0.87314284 -0.02977821 -0.31274740 -0.64687241
[25] -0.96043691 -0.01956337 0.13426016 0.60223629 -0.08260404 0.95887665
[31] 1.41197519 -0.93606184 0.20330453 -0.59854205 -1.06021165 0.89831605
[37] 0.05463010 0.12725013 0.83847081 1.56569542 0.27726825 0.01272732
[43] 2.56290036 -0.47472684 -1.08070993 -0.53883136 -0.55845349 0.50044550
[49] 0.25944927 0.54480358 0.85605385 -0.54336767 2.01672349 -0.76439522
[55] 0.13142137 0.47914032 0.06974256 -0.53688277 1.81735796 -0.95339493
[61] -0.37956435 0.50245382 -0.41866832 -1.46067471 1.87192344 -0.08738063
[67] -1.11524682 -1.22476035 0.92429310 -1.17470106 -0.98065889 0.77777449
[73] -0.13811240 -1.70049747 0.19910169 -0.11587581 -0.88951820 -0.14530128
[79] -2.07527335 0.65046079 0.31958977 -0.81018395 0.53670734 -0.52689118
[85] -1.91046451 0.47108365 0.54095977 0.21263896 -0.15037217 0.40270411
[91] -0.81297812 -0.14375618 0.96461440 -1.12346312 -0.30647413 0.79971513
[97] 2.38439204 -0.65404785 -0.43125664 -0.39654523
>
> colMeans(tmp2)
[1] 0.0261286
> colSums(tmp2)
[1] 2.61286
> colVars(tmp2)
[1] 0.80672
> colSd(tmp2)
[1] 0.8981759
> colMax(tmp2)
[1] 2.5629
> colMin(tmp2)
[1] -2.075273
> colMedians(tmp2)
[1] -0.003418025
> colRanges(tmp2)
[,1]
[1,] -2.075273
[2,] 2.562900
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.4797245 -0.7757528 2.0992228 0.6530962 6.2578478 -1.9183544
[7] -7.2387072 -2.6373784 1.0629071 1.5822609
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.49725438
[2,] -0.30821625
[3,] -0.08396127
[4,] 0.27796652
[5,] 1.02665034
>
> rowApply(tmp,sum)
[1] -0.29699515 -7.67810794 2.78411456 2.91798122 -1.05700879 1.67576211
[7] -3.92885730 -0.34656610 -0.01150978 4.54660467
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 3 5 8 2 6 6 7 4 3
[2,] 3 4 1 7 9 5 10 2 3 9
[3,] 1 9 7 10 4 3 3 10 8 2
[4,] 9 7 8 5 8 2 8 8 1 5
[5,] 8 10 10 6 10 4 1 5 10 8
[6,] 2 6 2 1 3 7 7 9 6 6
[7,] 4 1 3 9 6 1 9 4 2 1
[8,] 10 8 4 3 1 8 2 1 7 4
[9,] 6 5 6 2 7 10 5 3 9 7
[10,] 5 2 9 4 5 9 4 6 5 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.3191770 0.6451610 1.6451343 1.2959267 1.5225950 0.6855633
[7] 1.1092557 2.8909258 0.1484465 1.7820820 -1.6506818 0.7558434
[13] -2.6862734 -1.5766482 -0.5338907 1.0103206 1.4526506 2.2110240
[19] 4.2231981 1.9882757
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6982799
[2,] -0.6670667
[3,] 0.2033623
[4,] 0.6828168
[5,] 1.7983445
>
> rowApply(tmp,sum)
[1] -5.804743 5.724583 17.131716 2.133656 -0.947127
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 14 17 12 6
[2,] 2 19 8 9 9
[3,] 14 3 19 15 7
[4,] 17 4 18 14 4
[5,] 3 7 4 20 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.6982799 -1.30073669 0.01736835 0.1755552 -1.2844818 -0.03056481
[2,] 0.6828168 1.49591455 -0.94505415 -0.4418674 -0.2625931 -0.03094849
[3,] 1.7983445 0.58578576 1.96657879 1.8349511 0.1008723 1.61766897
[4,] 0.2033623 -0.01633983 1.01957422 0.7561960 1.7098894 -0.95503844
[5,] -0.6670667 -0.11946278 -0.41333290 -1.0289082 1.2589082 0.08444603
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1392852 0.006843212 0.1065671 0.8277354 -0.8127851 -0.9662366
[2,] 0.8752777 1.274540611 -0.3035459 -1.1553847 0.3093341 2.0864743
[3,] 1.7247688 0.257977289 1.7614579 -0.4517066 -0.8696806 0.7711228
[4,] -0.5626170 0.162327468 -2.2847551 1.6126560 1.1804196 -0.7516232
[5,] -0.7888885 1.189237256 0.8687225 0.9487819 -1.4579699 -0.3838940
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.7423867 -0.3257518 0.80502323 0.17380704 -1.5006658 -0.491343026
[2,] -0.3004580 0.5462951 -0.21634248 -1.43647266 1.1579289 1.342470442
[3,] 0.4431145 0.9670303 -1.77717989 1.51138841 0.3152543 1.474115565
[4,] -0.5741618 -1.6246359 0.62860850 0.03570986 1.1450142 -0.111281748
[5,] -1.5123813 -1.1395859 0.02599997 0.72588798 0.3351190 -0.002937263
[,19] [,20]
[1,] 0.8503258 -0.4754506
[2,] 0.6579588 0.3882387
[3,] 2.3989305 0.7009213
[4,] -0.5701563 1.1305079
[5,] 0.8861393 0.2440583
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 647 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 561 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.223899 1.234947 0.9699891 -1.989324 0.06079405 -0.6190912 -0.2057098
col8 col9 col10 col11 col12 col13 col14
row1 1.084046 0.8570108 -0.322732 0.8233766 0.001208873 0.4887142 -0.546988
col15 col16 col17 col18 col19 col20
row1 -1.004788 -0.2955623 -0.3225074 -2.314758 1.21089 0.8108775
> tmp[,"col10"]
col10
row1 -0.32273195
row2 0.70345953
row3 0.07199561
row4 -1.30201189
row5 0.51553430
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.2238994 1.234947 0.9699891 -1.989324 0.06079405 -0.6190912 -0.2057098
row5 0.4471519 2.046461 -1.0492090 -1.426630 0.81387898 -1.0429114 1.1391628
col8 col9 col10 col11 col12 col13 col14
row1 1.0840457 0.8570108 -0.3227320 0.8233766 0.001208873 0.4887142 -0.546988
row5 -0.9533678 1.2116824 0.5155343 -0.7111404 0.944126645 1.5429307 -3.023613
col15 col16 col17 col18 col19 col20
row1 -1.0047882 -0.2955623 -0.3225074 -2.3147577 1.210890 0.8108775
row5 -0.5380532 1.1457548 -0.4243051 -0.1440524 1.177873 -0.6824539
> tmp[,c("col6","col20")]
col6 col20
row1 -0.6190912 0.8108775
row2 -1.7255990 0.4387945
row3 -0.4844936 0.4819316
row4 0.4557170 0.5744018
row5 -1.0429114 -0.6824539
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.6190912 0.8108775
row5 -1.0429114 -0.6824539
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.61858 51.19326 49.87303 51.32185 50.63014 104.7274 50.01521 50.9758
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.82384 50.55268 50.6013 52.17961 48.22354 51.0095 50.20738 50.06732
col17 col18 col19 col20
row1 51.42237 49.74464 50.39399 105.4612
> tmp[,"col10"]
col10
row1 50.55268
row2 28.56388
row3 29.93348
row4 28.93392
row5 50.20199
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.61858 51.19326 49.87303 51.32185 50.63014 104.7274 50.01521 50.97580
row5 49.88419 50.28066 47.90785 51.22430 49.43225 103.0556 49.48417 50.26694
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.82384 50.55268 50.60130 52.17961 48.22354 51.00950 50.20738 50.06732
row5 48.91756 50.20199 51.42497 50.81362 51.03445 52.15276 47.31386 50.34386
col17 col18 col19 col20
row1 51.42237 49.74464 50.39399 105.4612
row5 48.90156 50.58748 49.08142 105.1212
> tmp[,c("col6","col20")]
col6 col20
row1 104.72743 105.46120
row2 74.63664 74.85513
row3 74.06093 74.63929
row4 76.45990 76.22880
row5 103.05560 105.12121
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7274 105.4612
row5 103.0556 105.1212
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7274 105.4612
row5 103.0556 105.1212
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.5911602
[2,] 1.7605503
[3,] 1.7926922
[4,] -1.2681527
[5,] 0.2837900
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7501018 -0.6109692
[2,] -0.2516972 -0.6806790
[3,] -1.1917884 1.7737901
[4,] 1.2803822 0.2472310
[5,] -1.0494921 -0.4295332
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.8639920 -0.6365007
[2,] 1.2497729 1.0489793
[3,] -0.3628029 0.7299889
[4,] 0.8382213 -0.2913589
[5,] 0.8444762 0.1156631
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.863992
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.863992
[2,] 1.249773
>
>
>
> 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 0.001656607 1.1287755 -0.7169772 -0.7069009 -0.1036060 0.4034627
row1 -0.142542781 -0.7453146 -0.9434917 -0.5319992 0.9021058 0.5609782
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.28154526 -0.35332682 1.5198092 2.0554996 -4.575961e-05 0.02302036
row1 0.08635349 -0.04142623 -0.9051156 -0.6042949 3.733385e-01 -0.16619321
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.1998848 0.888408 -1.4089986 -0.1683414 -1.3721525 0.5646340 -0.1514714
row1 0.1628596 1.231993 0.1790188 0.9884762 0.3665107 -0.2259499 -1.0191074
[,20]
row3 -0.5734677
row1 -0.8713764
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.090166 -0.0570018 1.819652 0.9515978 -1.463163 0.9523876 1.202884
[,8] [,9] [,10]
row2 -1.454447 0.5567696 -0.3240561
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.393984 1.213779 -0.7990189 -1.418698 0.58654 0.07410797 0.914809
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.2737379 -2.52133 0.3966871 0.7265654 1.355574 -0.6878722 0.2547247
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.002589894 1.043498 -0.9818277 1.22106 -1.181034 1.399907
>
>
> 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: 0x6219217928c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a54e09d3f"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a4d60469a"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a65091519"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a45ab6f9d"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a415f63d2"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a6655e6dd"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a28fac1e7"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a7975cea9"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a1e7300ab"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a53474f44"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a7dde4b42"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a6b9f6dcb"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a1fee7a90"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a37d723cd"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM5886a39379648"
>
>
> ### 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: 0x6219229c4a50>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6219229c4a50>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6219229c4a50>
> rowMedians(tmp)
[1] 0.5059744995 -0.3839682284 -0.0037338064 0.0385948668 0.1696587296
[6] -0.3855176690 0.0431874199 0.1450783999 0.0097615173 0.4976310049
[11] -0.2454597262 -0.2103576300 0.1619023903 -0.1359925802 0.0561008096
[16] -0.3594746006 -0.3742095733 -0.1825558786 0.3062676524 0.1464255066
[21] 0.6972840824 0.2177694065 -0.1436486580 -0.6554250513 0.1791151542
[26] 0.1960681490 -0.1431261413 -0.2592293933 -0.1950648762 -0.0680994939
[31] 0.0143208101 0.8044669297 -0.5267398688 -0.3404806678 -0.2863260124
[36] -0.0757063612 0.3914973603 -0.0382817779 0.0237851241 0.0943127465
[41] -0.2159629108 0.2757056316 0.0154372959 0.2977329777 -0.2489081527
[46] 0.2878765400 0.3120540333 -0.0189405532 0.0065488781 0.1152287751
[51] -0.3962289459 -0.1908622891 -0.1448310208 -0.1684261733 -0.0953049848
[56] -0.7241798269 0.3326370386 0.1714772927 -0.3282609535 -0.3908047800
[61] 0.0969074471 -0.1077183412 0.0651999005 0.1909411866 -0.6963240306
[66] -0.3804033081 0.2538485539 -0.3566753495 0.1477230217 -0.0123929324
[71] 0.5019776575 0.1305100008 -0.7121723681 -0.2962650486 0.3961674697
[76] 0.1583837626 -0.5987990310 -0.3704126391 -0.0576359230 -0.0104604078
[81] -0.0819254288 0.0227993208 -0.2271998603 -0.0221638792 -0.1233332708
[86] 0.2263937846 -0.6695329662 -0.3527418963 -0.1282655188 -0.2372132214
[91] -0.2644978248 0.6731833823 -0.0895272849 0.2942396085 -0.0657841809
[96] 0.1558566445 -0.4418051934 0.0360731573 -0.2352694198 0.1413067290
[101] -0.1130591939 -0.3029848074 0.6075043125 -0.1894849488 0.1152784285
[106] -0.4128086904 -0.4395509478 -0.2898610785 0.2401331697 0.3028866333
[111] -0.2858063738 0.0706738944 -0.0192947883 0.0306364917 0.0835230660
[116] 0.4354016542 0.0551358803 -0.1220145668 -0.4401673232 0.3495642088
[121] 0.0918834461 -0.0092434405 -0.3823773297 0.0645488276 0.4392817586
[126] 0.1408380922 -0.0539609571 0.0681293658 -0.0132728187 0.0005733914
[131] -0.2654086184 -0.4009544606 -0.1169596910 0.3466256070 -0.1854570281
[136] -0.3485946465 0.3843486301 -0.2431074171 0.5725785302 -0.0816386079
[141] -0.3690152733 -0.0172131935 -0.0987276512 0.1180619628 0.0872565768
[146] -0.1935444514 -0.1145945907 0.1105996560 0.2410882137 0.0561015063
[151] -0.8568195310 0.0772934822 -0.4849314187 -0.1917733622 0.6569125229
[156] 0.0299414691 -0.3031701786 -0.0055753136 -0.0166224329 -0.3185852990
[161] -0.1743206673 0.2103420140 0.1351637335 0.1199184358 0.0681293601
[166] -0.1941942164 0.3933936914 -0.0906675389 0.2922470882 0.0964017809
[171] 0.0609971577 -0.1473323123 0.4331468113 -0.3134709032 -0.3656990694
[176] 0.1846174143 0.0082670349 -0.3893921707 -0.1768726779 -0.0970625526
[181] -0.0011248267 -0.0752436653 0.1692542139 -0.0391140012 0.1442202450
[186] -0.0689706899 -0.3560273574 -0.2904883719 -0.3171871665 -0.4330461722
[191] 0.3396592524 0.2926525282 0.0978906286 -0.1113940724 -0.1321599003
[196] -0.2652904053 0.1372286863 0.2086543620 0.2564779398 -0.0474151174
[201] -0.3320464625 0.3248960192 -0.2778870492 0.0207890402 0.3080000734
[206] 0.5230775359 -0.0620920405 0.1304842775 0.0202283046 -0.2747594241
[211] -0.3668755128 0.1998944867 0.0215179369 -0.5592692946 0.1755948421
[216] -0.8381034495 0.2319809763 -0.3404591422 -0.0982109434 0.1399082731
[221] 0.1630452690 -0.1346135575 0.0277246007 -0.4518134051 0.0580238530
[226] 0.1700010451 0.1083513448 -0.2952817105 -0.3290591617 -0.0912499554
>
> proc.time()
user system elapsed
1.350 1.564 2.903
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: 0x59266a415fe0>
> .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: 0x59266a415fe0>
> .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: 0x59266a415fe0>
> .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: 0x59266a415fe0>
> 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: 0x59266bb5c480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59266bb5c480>
> .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: 0x59266bb5c480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59266bb5c480>
> .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: 0x59266bb5c480>
> 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: 0x59266c4e0050>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59266c4e0050>
> .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: 0x59266c4e0050>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x59266c4e0050>
> .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: 0x59266c4e0050>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x59266c4e0050>
> .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: 0x59266c4e0050>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x59266c4e0050>
> .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: 0x59266c4e0050>
> 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: 0x59266c5300b0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x59266c5300b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59266c5300b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59266c5300b0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile589951161bb0e" "BufferedMatrixFile5899536e88af7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile589951161bb0e" "BufferedMatrixFile5899536e88af7"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x592669c363f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x592669c363f0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x592669c363f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x592669c363f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x592669c363f0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x592669c363f0>
> .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: 0x59266c6be700>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59266c6be700>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x59266c6be700>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x59266c6be700>
> 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: 0x59266b12c4a0>
> .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: 0x59266b12c4a0>
> rm(P)
>
> proc.time()
user system elapsed
0.268 0.048 0.305
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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Platform: x86_64-pc-linux-gnu
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.260 0.036 0.284