Ben Bolstad
| Snapshot Date: 2026-04-02 13:40 -0400 (Thu, 02 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 2026-04-03 11:38 -0400 (Fri, 03 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.6.0 alpha (2026-03-30 r89742) | 4894 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 258/2381 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 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: 2026-04-02 21:38:19 -0400 (Thu, 02 Apr 2026) |
| EndedAt: 2026-04-02 21:38:43 -0400 (Thu, 02 Apr 2026) |
| EllapsedTime: 24.1 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 alpha (2026-03-30 r89742)
* 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: 2026-04-03 01:38:19 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/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o
installing to /home/biocbuild/bbs-3.23-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.6.0 alpha (2026-03-30 r89742)
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
0.240 0.050 0.278
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 alpha (2026-03-30 r89742)
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 480181 25.7 1053160 56.3 637571 34.1
Vcells 887210 6.8 8388608 64.0 2083864 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] "Thu Apr 2 21:38:34 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] "Thu Apr 2 21:38:34 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: 0x649eaa129380>
>
>
>
> 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] "Thu Apr 2 21:38:34 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] "Thu Apr 2 21:38:34 2026"
>
> ColMode(tmp2)
<pointer: 0x649eaa129380>
>
>
>
> ### 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,] 99.8157424 0.2199824 -0.5491235 0.3231308
[2,] 0.5013313 0.2680338 2.1041606 0.5831865
[3,] 2.1997818 0.7763458 0.5951202 -0.9873637
[4,] 0.8804600 0.9902443 1.0101979 2.1263583
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8157424 0.2199824 0.5491235 0.3231308
[2,] 0.5013313 0.2680338 2.1041606 0.5831865
[3,] 2.1997818 0.7763458 0.5951202 0.9873637
[4,] 0.8804600 0.9902443 1.0101979 2.1263583
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9907829 0.4690228 0.7410287 0.5684460
[2,] 0.7080475 0.5177198 1.4505725 0.7636665
[3,] 1.4831661 0.8811049 0.7714403 0.9936618
[4,] 0.9383283 0.9951102 1.0050860 1.4582038
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.72357 29.91021 32.95941 31.00759
[2,] 32.58181 30.44523 41.60989 33.21985
[3,] 42.03144 34.58739 33.30952 35.92398
[4,] 35.26374 35.94135 36.06106 41.70840
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x649eab845580>
> exp(tmp5)
<pointer: 0x649eab845580>
> log(tmp5,2)
<pointer: 0x649eab845580>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.7327
> Min(tmp5)
[1] 53.05262
> mean(tmp5)
[1] 71.61296
> Sum(tmp5)
[1] 14322.59
> Var(tmp5)
[1] 876.8441
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.76701 69.96109 73.94814 73.27572 67.70683 72.21805 66.51318 67.09516
[9] 69.17197 68.47247
> rowSums(tmp5)
[1] 1755.340 1399.222 1478.963 1465.514 1354.137 1444.361 1330.264 1341.903
[9] 1383.439 1369.449
> rowVars(tmp5)
[1] 8045.80872 46.44918 86.49189 105.50841 82.81011 85.07230
[7] 70.94745 107.21467 97.55357 87.75969
> rowSd(tmp5)
[1] 89.698432 6.815364 9.300102 10.271729 9.100006 9.223465 8.423031
[8] 10.354451 9.876921 9.368014
> rowMax(tmp5)
[1] 467.73267 86.60553 87.48294 92.00597 87.09856 86.61570 81.55413
[8] 86.99668 86.34335 87.58188
> rowMin(tmp5)
[1] 54.19261 60.47482 53.56909 56.77094 54.20967 54.91327 54.29185 53.05262
[9] 53.38682 55.63741
>
> colMeans(tmp5)
[1] 115.49690 65.72098 70.11775 72.76706 67.20322 67.16312 65.81595
[8] 67.93473 66.60578 74.54554 68.45824 73.16393 67.36626 74.34740
[15] 71.02337 71.01828 65.50550 71.24094 67.68659 69.07770
> colSums(tmp5)
[1] 1154.9690 657.2098 701.1775 727.6706 672.0322 671.6312 658.1595
[8] 679.3473 666.0578 745.4554 684.5824 731.6393 673.6626 743.4740
[15] 710.2337 710.1828 655.0550 712.4094 676.8659 690.7770
> colVars(tmp5)
[1] 15418.84658 92.64098 91.88597 47.80449 85.74214 92.08908
[7] 61.19563 61.31824 75.53433 17.87242 131.33144 81.18831
[13] 79.05378 81.55519 67.80221 88.83169 52.10066 90.72080
[19] 136.54858 109.49970
> colSd(tmp5)
[1] 124.172648 9.625019 9.585717 6.914079 9.259705 9.596306
[7] 7.822763 7.830596 8.691049 4.227579 11.459993 9.010456
[13] 8.891219 9.030791 8.234210 9.425057 7.218079 9.524747
[19] 11.685400 10.464210
> colMax(tmp5)
[1] 467.73267 83.29329 86.60553 86.81056 83.76675 87.09856 76.06384
[8] 79.61121 78.09236 82.35755 87.47668 87.37545 84.56641 86.54754
[15] 85.71907 87.58188 79.08013 92.00597 84.11795 82.85343
> colMin(tmp5)
[1] 59.02686 54.29185 55.05329 64.53824 56.42224 57.12343 54.20967 57.91636
[9] 53.05262 67.41915 53.56909 56.93669 56.77094 54.68439 59.43129 60.14751
[17] 56.48076 57.36027 53.38682 53.14839
>
>
> ### 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] 87.76701 69.96109 73.94814 73.27572 NA 72.21805 66.51318 67.09516
[9] 69.17197 68.47247
> rowSums(tmp5)
[1] 1755.340 1399.222 1478.963 1465.514 NA 1444.361 1330.264 1341.903
[9] 1383.439 1369.449
> rowVars(tmp5)
[1] 8045.80872 46.44918 86.49189 105.50841 81.15037 85.07230
[7] 70.94745 107.21467 97.55357 87.75969
> rowSd(tmp5)
[1] 89.698432 6.815364 9.300102 10.271729 9.008350 9.223465 8.423031
[8] 10.354451 9.876921 9.368014
> rowMax(tmp5)
[1] 467.73267 86.60553 87.48294 92.00597 NA 86.61570 81.55413
[8] 86.99668 86.34335 87.58188
> rowMin(tmp5)
[1] 54.19261 60.47482 53.56909 56.77094 NA 54.91327 54.29185 53.05262
[9] 53.38682 55.63741
>
> colMeans(tmp5)
[1] 115.49690 65.72098 70.11775 72.76706 67.20322 67.16312 65.81595
[8] 67.93473 66.60578 74.54554 68.45824 73.16393 67.36626 74.34740
[15] 71.02337 71.01828 65.50550 NA 67.68659 69.07770
> colSums(tmp5)
[1] 1154.9690 657.2098 701.1775 727.6706 672.0322 671.6312 658.1595
[8] 679.3473 666.0578 745.4554 684.5824 731.6393 673.6626 743.4740
[15] 710.2337 710.1828 655.0550 NA 676.8659 690.7770
> colVars(tmp5)
[1] 15418.84658 92.64098 91.88597 47.80449 85.74214 92.08908
[7] 61.19563 61.31824 75.53433 17.87242 131.33144 81.18831
[13] 79.05378 81.55519 67.80221 88.83169 52.10066 NA
[19] 136.54858 109.49970
> colSd(tmp5)
[1] 124.172648 9.625019 9.585717 6.914079 9.259705 9.596306
[7] 7.822763 7.830596 8.691049 4.227579 11.459993 9.010456
[13] 8.891219 9.030791 8.234210 9.425057 7.218079 NA
[19] 11.685400 10.464210
> colMax(tmp5)
[1] 467.73267 83.29329 86.60553 86.81056 83.76675 87.09856 76.06384
[8] 79.61121 78.09236 82.35755 87.47668 87.37545 84.56641 86.54754
[15] 85.71907 87.58188 79.08013 NA 84.11795 82.85343
> colMin(tmp5)
[1] 59.02686 54.29185 55.05329 64.53824 56.42224 57.12343 54.20967 57.91636
[9] 53.05262 67.41915 53.56909 56.93669 56.77094 54.68439 59.43129 60.14751
[17] 56.48076 NA 53.38682 53.14839
>
> Max(tmp5,na.rm=TRUE)
[1] 467.7327
> Min(tmp5,na.rm=TRUE)
[1] 53.05262
> mean(tmp5,na.rm=TRUE)
[1] 71.68458
> Sum(tmp5,na.rm=TRUE)
[1] 14265.23
> Var(tmp5,na.rm=TRUE)
[1] 880.2415
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.76701 69.96109 73.94814 73.27572 68.25138 72.21805 66.51318 67.09516
[9] 69.17197 68.47247
> rowSums(tmp5,na.rm=TRUE)
[1] 1755.340 1399.222 1478.963 1465.514 1296.776 1444.361 1330.264 1341.903
[9] 1383.439 1369.449
> rowVars(tmp5,na.rm=TRUE)
[1] 8045.80872 46.44918 86.49189 105.50841 81.15037 85.07230
[7] 70.94745 107.21467 97.55357 87.75969
> rowSd(tmp5,na.rm=TRUE)
[1] 89.698432 6.815364 9.300102 10.271729 9.008350 9.223465 8.423031
[8] 10.354451 9.876921 9.368014
> rowMax(tmp5,na.rm=TRUE)
[1] 467.73267 86.60553 87.48294 92.00597 87.09856 86.61570 81.55413
[8] 86.99668 86.34335 87.58188
> rowMin(tmp5,na.rm=TRUE)
[1] 54.19261 60.47482 53.56909 56.77094 54.20967 54.91327 54.29185 53.05262
[9] 53.38682 55.63741
>
> colMeans(tmp5,na.rm=TRUE)
[1] 115.49690 65.72098 70.11775 72.76706 67.20322 67.16312 65.81595
[8] 67.93473 66.60578 74.54554 68.45824 73.16393 67.36626 74.34740
[15] 71.02337 71.01828 65.50550 72.78324 67.68659 69.07770
> colSums(tmp5,na.rm=TRUE)
[1] 1154.9690 657.2098 701.1775 727.6706 672.0322 671.6312 658.1595
[8] 679.3473 666.0578 745.4554 684.5824 731.6393 673.6626 743.4740
[15] 710.2337 710.1828 655.0550 655.0491 676.8659 690.7770
> colVars(tmp5,na.rm=TRUE)
[1] 15418.84658 92.64098 91.88597 47.80449 85.74214 92.08908
[7] 61.19563 61.31824 75.53433 17.87242 131.33144 81.18831
[13] 79.05378 81.55519 67.80221 88.83169 52.10066 75.30077
[19] 136.54858 109.49970
> colSd(tmp5,na.rm=TRUE)
[1] 124.172648 9.625019 9.585717 6.914079 9.259705 9.596306
[7] 7.822763 7.830596 8.691049 4.227579 11.459993 9.010456
[13] 8.891219 9.030791 8.234210 9.425057 7.218079 8.677601
[19] 11.685400 10.464210
> colMax(tmp5,na.rm=TRUE)
[1] 467.73267 83.29329 86.60553 86.81056 83.76675 87.09856 76.06384
[8] 79.61121 78.09236 82.35755 87.47668 87.37545 84.56641 86.54754
[15] 85.71907 87.58188 79.08013 92.00597 84.11795 82.85343
> colMin(tmp5,na.rm=TRUE)
[1] 59.02686 54.29185 55.05329 64.53824 56.42224 57.12343 54.20967 57.91636
[9] 53.05262 67.41915 53.56909 56.93669 56.77094 54.68439 59.43129 60.14751
[17] 56.48076 63.92238 53.38682 53.14839
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.76701 69.96109 73.94814 73.27572 NaN 72.21805 66.51318 67.09516
[9] 69.17197 68.47247
> rowSums(tmp5,na.rm=TRUE)
[1] 1755.340 1399.222 1478.963 1465.514 0.000 1444.361 1330.264 1341.903
[9] 1383.439 1369.449
> rowVars(tmp5,na.rm=TRUE)
[1] 8045.80872 46.44918 86.49189 105.50841 NA 85.07230
[7] 70.94745 107.21467 97.55357 87.75969
> rowSd(tmp5,na.rm=TRUE)
[1] 89.698432 6.815364 9.300102 10.271729 NA 9.223465 8.423031
[8] 10.354451 9.876921 9.368014
> rowMax(tmp5,na.rm=TRUE)
[1] 467.73267 86.60553 87.48294 92.00597 NA 86.61570 81.55413
[8] 86.99668 86.34335 87.58188
> rowMin(tmp5,na.rm=TRUE)
[1] 54.19261 60.47482 53.56909 56.77094 NA 54.91327 54.29185 53.05262
[9] 53.38682 55.63741
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 121.77135 66.59795 71.39487 72.72639 66.03592 64.94807 67.10553
[8] 67.80919 65.93417 74.27935 67.93727 73.36429 67.50751 73.73397
[15] 70.98245 72.08743 65.05781 NaN 68.83604 70.04671
> colSums(tmp5,na.rm=TRUE)
[1] 1095.9422 599.3816 642.5538 654.5375 594.3233 584.5326 603.9498
[8] 610.2827 593.4075 668.5141 611.4355 660.2786 607.5676 663.6058
[15] 638.8421 648.7869 585.5203 0.0000 619.5243 630.4204
> colVars(tmp5,na.rm=TRUE)
[1] 16903.30430 95.56887 85.02252 53.76144 81.13074 48.40273
[7] 50.13596 68.80571 79.90176 19.30930 144.69462 90.88525
[13] 88.71104 87.51634 76.25866 87.07582 56.35847 NA
[19] 138.75346 112.62362
> colSd(tmp5,na.rm=TRUE)
[1] 130.012708 9.775933 9.220766 7.332220 9.007260 6.957207
[7] 7.080675 8.294921 8.938779 4.394235 12.028908 9.533375
[13] 9.418654 9.355017 8.732620 9.331443 7.507228 NA
[19] 11.779366 10.612427
> colMax(tmp5,na.rm=TRUE)
[1] 467.73267 83.29329 86.60553 86.81056 83.76675 78.14756 76.06384
[8] 79.61121 78.09236 82.35755 87.47668 87.37545 84.56641 86.54754
[15] 85.71907 87.58188 79.08013 -Inf 84.11795 82.85343
> colMin(tmp5,na.rm=TRUE)
[1] 67.81476 54.29185 55.05329 64.53824 56.42224 57.12343 54.91327 57.91636
[9] 53.05262 67.41915 53.56909 56.93669 56.77094 54.68439 59.43129 60.14751
[17] 56.48076 Inf 53.38682 53.14839
>
>
>
>
> 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] 108.5336 199.2447 249.0357 233.4380 234.3277 227.5240 198.5066 278.4041
[9] 268.9369 156.8502
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 108.5336 199.2447 249.0357 233.4380 234.3277 227.5240 198.5066 278.4041
[9] 268.9369 156.8502
>
>
>
> 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] -1.136868e-13 -2.842171e-14 0.000000e+00 5.684342e-14 -1.136868e-13
[6] 1.421085e-13 -2.273737e-13 0.000000e+00 8.526513e-14 5.684342e-14
[11] 8.526513e-14 -5.684342e-14 0.000000e+00 2.842171e-14 0.000000e+00
[16] -1.278977e-13 0.000000e+00 1.705303e-13 5.684342e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 13
3 8
4 11
6 5
4 11
2 16
8 19
6 19
9 9
3 19
3 2
2 18
8 14
6 16
6 4
9 10
10 16
2 12
8 11
8 1
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] 1.851864
> Min(tmp)
[1] -2.675066
> mean(tmp)
[1] 0.009165986
> Sum(tmp)
[1] 0.9165986
> Var(tmp)
[1] 0.9621822
>
> rowMeans(tmp)
[1] 0.009165986
> rowSums(tmp)
[1] 0.9165986
> rowVars(tmp)
[1] 0.9621822
> rowSd(tmp)
[1] 0.9809089
> rowMax(tmp)
[1] 1.851864
> rowMin(tmp)
[1] -2.675066
>
> colMeans(tmp)
[1] -0.206844599 0.357996141 -1.268734311 -1.094465523 1.813283140
[6] 1.851864091 -1.017346748 -0.591369258 -0.809193214 -0.300704364
[11] -0.589216814 1.613617341 -0.802472371 0.420719656 0.507170972
[16] 0.443054325 1.549070455 1.028747168 -1.639261503 1.168613284
[21] 0.256832790 1.452408896 -0.199714337 -1.654974908 0.529860081
[26] 0.517995364 1.150167283 -0.333563829 0.068934380 0.297050335
[31] 0.308533755 0.967353370 1.189324824 0.500749625 -0.311078751
[36] -2.432268355 -0.218293868 -1.259312244 1.235918026 0.295276187
[41] -0.043208710 -1.000908448 -1.182331847 -0.835199625 0.077191412
[46] 0.741331743 -0.311510551 -0.892991329 0.776534609 0.316153493
[51] 1.254370753 0.052133522 -0.991703139 0.543025828 -1.032200698
[56] -2.675065860 0.550700804 -1.063334705 -0.938452708 0.521755798
[61] 0.643147776 -1.078868502 1.543397062 0.939799761 -0.423225906
[66] 1.360702451 -0.736422814 -0.237488059 0.297711541 1.067793101
[71] 0.534726093 -2.270337258 0.748771847 0.466563094 -0.637651920
[76] -0.168992309 0.598422135 0.279282141 -1.902869913 0.707031372
[81] 1.013670654 0.455199991 -0.155118242 -0.778994952 -0.056700443
[86] -1.245187281 -0.192319322 0.429555028 0.000228144 0.687547019
[91] -0.637221308 -1.325243389 0.266535360 0.395019150 1.440992067
[96] -1.870614990 0.657574080 1.096781789 0.411361553 -0.069974888
> colSums(tmp)
[1] -0.206844599 0.357996141 -1.268734311 -1.094465523 1.813283140
[6] 1.851864091 -1.017346748 -0.591369258 -0.809193214 -0.300704364
[11] -0.589216814 1.613617341 -0.802472371 0.420719656 0.507170972
[16] 0.443054325 1.549070455 1.028747168 -1.639261503 1.168613284
[21] 0.256832790 1.452408896 -0.199714337 -1.654974908 0.529860081
[26] 0.517995364 1.150167283 -0.333563829 0.068934380 0.297050335
[31] 0.308533755 0.967353370 1.189324824 0.500749625 -0.311078751
[36] -2.432268355 -0.218293868 -1.259312244 1.235918026 0.295276187
[41] -0.043208710 -1.000908448 -1.182331847 -0.835199625 0.077191412
[46] 0.741331743 -0.311510551 -0.892991329 0.776534609 0.316153493
[51] 1.254370753 0.052133522 -0.991703139 0.543025828 -1.032200698
[56] -2.675065860 0.550700804 -1.063334705 -0.938452708 0.521755798
[61] 0.643147776 -1.078868502 1.543397062 0.939799761 -0.423225906
[66] 1.360702451 -0.736422814 -0.237488059 0.297711541 1.067793101
[71] 0.534726093 -2.270337258 0.748771847 0.466563094 -0.637651920
[76] -0.168992309 0.598422135 0.279282141 -1.902869913 0.707031372
[81] 1.013670654 0.455199991 -0.155118242 -0.778994952 -0.056700443
[86] -1.245187281 -0.192319322 0.429555028 0.000228144 0.687547019
[91] -0.637221308 -1.325243389 0.266535360 0.395019150 1.440992067
[96] -1.870614990 0.657574080 1.096781789 0.411361553 -0.069974888
> 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] -0.206844599 0.357996141 -1.268734311 -1.094465523 1.813283140
[6] 1.851864091 -1.017346748 -0.591369258 -0.809193214 -0.300704364
[11] -0.589216814 1.613617341 -0.802472371 0.420719656 0.507170972
[16] 0.443054325 1.549070455 1.028747168 -1.639261503 1.168613284
[21] 0.256832790 1.452408896 -0.199714337 -1.654974908 0.529860081
[26] 0.517995364 1.150167283 -0.333563829 0.068934380 0.297050335
[31] 0.308533755 0.967353370 1.189324824 0.500749625 -0.311078751
[36] -2.432268355 -0.218293868 -1.259312244 1.235918026 0.295276187
[41] -0.043208710 -1.000908448 -1.182331847 -0.835199625 0.077191412
[46] 0.741331743 -0.311510551 -0.892991329 0.776534609 0.316153493
[51] 1.254370753 0.052133522 -0.991703139 0.543025828 -1.032200698
[56] -2.675065860 0.550700804 -1.063334705 -0.938452708 0.521755798
[61] 0.643147776 -1.078868502 1.543397062 0.939799761 -0.423225906
[66] 1.360702451 -0.736422814 -0.237488059 0.297711541 1.067793101
[71] 0.534726093 -2.270337258 0.748771847 0.466563094 -0.637651920
[76] -0.168992309 0.598422135 0.279282141 -1.902869913 0.707031372
[81] 1.013670654 0.455199991 -0.155118242 -0.778994952 -0.056700443
[86] -1.245187281 -0.192319322 0.429555028 0.000228144 0.687547019
[91] -0.637221308 -1.325243389 0.266535360 0.395019150 1.440992067
[96] -1.870614990 0.657574080 1.096781789 0.411361553 -0.069974888
> colMin(tmp)
[1] -0.206844599 0.357996141 -1.268734311 -1.094465523 1.813283140
[6] 1.851864091 -1.017346748 -0.591369258 -0.809193214 -0.300704364
[11] -0.589216814 1.613617341 -0.802472371 0.420719656 0.507170972
[16] 0.443054325 1.549070455 1.028747168 -1.639261503 1.168613284
[21] 0.256832790 1.452408896 -0.199714337 -1.654974908 0.529860081
[26] 0.517995364 1.150167283 -0.333563829 0.068934380 0.297050335
[31] 0.308533755 0.967353370 1.189324824 0.500749625 -0.311078751
[36] -2.432268355 -0.218293868 -1.259312244 1.235918026 0.295276187
[41] -0.043208710 -1.000908448 -1.182331847 -0.835199625 0.077191412
[46] 0.741331743 -0.311510551 -0.892991329 0.776534609 0.316153493
[51] 1.254370753 0.052133522 -0.991703139 0.543025828 -1.032200698
[56] -2.675065860 0.550700804 -1.063334705 -0.938452708 0.521755798
[61] 0.643147776 -1.078868502 1.543397062 0.939799761 -0.423225906
[66] 1.360702451 -0.736422814 -0.237488059 0.297711541 1.067793101
[71] 0.534726093 -2.270337258 0.748771847 0.466563094 -0.637651920
[76] -0.168992309 0.598422135 0.279282141 -1.902869913 0.707031372
[81] 1.013670654 0.455199991 -0.155118242 -0.778994952 -0.056700443
[86] -1.245187281 -0.192319322 0.429555028 0.000228144 0.687547019
[91] -0.637221308 -1.325243389 0.266535360 0.395019150 1.440992067
[96] -1.870614990 0.657574080 1.096781789 0.411361553 -0.069974888
> colMedians(tmp)
[1] -0.206844599 0.357996141 -1.268734311 -1.094465523 1.813283140
[6] 1.851864091 -1.017346748 -0.591369258 -0.809193214 -0.300704364
[11] -0.589216814 1.613617341 -0.802472371 0.420719656 0.507170972
[16] 0.443054325 1.549070455 1.028747168 -1.639261503 1.168613284
[21] 0.256832790 1.452408896 -0.199714337 -1.654974908 0.529860081
[26] 0.517995364 1.150167283 -0.333563829 0.068934380 0.297050335
[31] 0.308533755 0.967353370 1.189324824 0.500749625 -0.311078751
[36] -2.432268355 -0.218293868 -1.259312244 1.235918026 0.295276187
[41] -0.043208710 -1.000908448 -1.182331847 -0.835199625 0.077191412
[46] 0.741331743 -0.311510551 -0.892991329 0.776534609 0.316153493
[51] 1.254370753 0.052133522 -0.991703139 0.543025828 -1.032200698
[56] -2.675065860 0.550700804 -1.063334705 -0.938452708 0.521755798
[61] 0.643147776 -1.078868502 1.543397062 0.939799761 -0.423225906
[66] 1.360702451 -0.736422814 -0.237488059 0.297711541 1.067793101
[71] 0.534726093 -2.270337258 0.748771847 0.466563094 -0.637651920
[76] -0.168992309 0.598422135 0.279282141 -1.902869913 0.707031372
[81] 1.013670654 0.455199991 -0.155118242 -0.778994952 -0.056700443
[86] -1.245187281 -0.192319322 0.429555028 0.000228144 0.687547019
[91] -0.637221308 -1.325243389 0.266535360 0.395019150 1.440992067
[96] -1.870614990 0.657574080 1.096781789 0.411361553 -0.069974888
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.2068446 0.3579961 -1.268734 -1.094466 1.813283 1.851864 -1.017347
[2,] -0.2068446 0.3579961 -1.268734 -1.094466 1.813283 1.851864 -1.017347
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.5913693 -0.8091932 -0.3007044 -0.5892168 1.613617 -0.8024724 0.4207197
[2,] -0.5913693 -0.8091932 -0.3007044 -0.5892168 1.613617 -0.8024724 0.4207197
[,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] 0.507171 0.4430543 1.54907 1.028747 -1.639262 1.168613 0.2568328 1.452409
[2,] 0.507171 0.4430543 1.54907 1.028747 -1.639262 1.168613 0.2568328 1.452409
[,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] -0.1997143 -1.654975 0.5298601 0.5179954 1.150167 -0.3335638 0.06893438
[2,] -0.1997143 -1.654975 0.5298601 0.5179954 1.150167 -0.3335638 0.06893438
[,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] 0.2970503 0.3085338 0.9673534 1.189325 0.5007496 -0.3110788 -2.432268
[2,] 0.2970503 0.3085338 0.9673534 1.189325 0.5007496 -0.3110788 -2.432268
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] -0.2182939 -1.259312 1.235918 0.2952762 -0.04320871 -1.000908 -1.182332
[2,] -0.2182939 -1.259312 1.235918 0.2952762 -0.04320871 -1.000908 -1.182332
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] -0.8351996 0.07719141 0.7413317 -0.3115106 -0.8929913 0.7765346 0.3161535
[2,] -0.8351996 0.07719141 0.7413317 -0.3115106 -0.8929913 0.7765346 0.3161535
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] 1.254371 0.05213352 -0.9917031 0.5430258 -1.032201 -2.675066 0.5507008
[2,] 1.254371 0.05213352 -0.9917031 0.5430258 -1.032201 -2.675066 0.5507008
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] -1.063335 -0.9384527 0.5217558 0.6431478 -1.078869 1.543397 0.9397998
[2,] -1.063335 -0.9384527 0.5217558 0.6431478 -1.078869 1.543397 0.9397998
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] -0.4232259 1.360702 -0.7364228 -0.2374881 0.2977115 1.067793 0.5347261
[2,] -0.4232259 1.360702 -0.7364228 -0.2374881 0.2977115 1.067793 0.5347261
[,72] [,73] [,74] [,75] [,76] [,77] [,78]
[1,] -2.270337 0.7487718 0.4665631 -0.6376519 -0.1689923 0.5984221 0.2792821
[2,] -2.270337 0.7487718 0.4665631 -0.6376519 -0.1689923 0.5984221 0.2792821
[,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] -1.90287 0.7070314 1.013671 0.4552 -0.1551182 -0.778995 -0.05670044
[2,] -1.90287 0.7070314 1.013671 0.4552 -0.1551182 -0.778995 -0.05670044
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] -1.245187 -0.1923193 0.429555 0.000228144 0.687547 -0.6372213 -1.325243
[2,] -1.245187 -0.1923193 0.429555 0.000228144 0.687547 -0.6372213 -1.325243
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] 0.2665354 0.3950192 1.440992 -1.870615 0.6575741 1.096782 0.4113616
[2,] 0.2665354 0.3950192 1.440992 -1.870615 0.6575741 1.096782 0.4113616
[,100]
[1,] -0.06997489
[2,] -0.06997489
>
>
> Max(tmp2)
[1] 2.661917
> Min(tmp2)
[1] -1.8844
> mean(tmp2)
[1] 0.02490287
> Sum(tmp2)
[1] 2.490287
> Var(tmp2)
[1] 0.7788674
>
> rowMeans(tmp2)
[1] 0.260631542 0.600637586 -0.604014635 1.637818652 -0.971236174
[6] 0.382182301 0.263693304 0.007963902 1.091866127 -0.212987574
[11] 1.404087526 0.328011445 -0.697718169 -0.949409224 0.403651346
[16] 0.119581524 -0.048108157 0.822510593 -1.884400367 -1.283247770
[21] 0.856583563 0.914461888 1.273003677 0.952645100 -0.328110861
[26] 0.019275123 -0.555504829 -0.939908303 -0.486162402 -1.252399182
[31] 0.133986811 -0.071000732 -0.317820743 0.100437513 -0.334069268
[36] -0.167090089 1.026212280 -0.280476873 1.860259135 -1.277336306
[41] 0.347295397 -1.532649152 0.391047311 0.567499019 2.661916537
[46] -1.126245011 -0.698045339 -0.322807135 -0.167143914 -1.360275378
[51] 0.830214286 -0.244366919 0.141259509 -1.388004256 -0.441862716
[56] -0.414430202 0.425837657 -0.689987852 -0.332509684 0.228462749
[61] 1.116905878 0.566301619 -0.499867799 -0.891997630 0.392515621
[66] 0.240300172 -0.615889746 -0.102703301 -0.981877147 -1.503826941
[71] 1.047574735 1.434335100 1.377037652 1.338473246 -0.131367984
[76] -1.778615238 1.181684538 0.831936371 0.130269007 -0.041857931
[81] 0.168486874 0.238234128 0.405763413 0.701196386 0.556471721
[86] 0.153954929 1.272683279 0.184243989 0.434823042 1.022196585
[91] -0.875028362 -0.243406036 0.022469836 -1.766943823 -0.744011059
[96] -0.277702131 -0.410181807 1.362546062 -1.036550622 -0.461993450
> rowSums(tmp2)
[1] 0.260631542 0.600637586 -0.604014635 1.637818652 -0.971236174
[6] 0.382182301 0.263693304 0.007963902 1.091866127 -0.212987574
[11] 1.404087526 0.328011445 -0.697718169 -0.949409224 0.403651346
[16] 0.119581524 -0.048108157 0.822510593 -1.884400367 -1.283247770
[21] 0.856583563 0.914461888 1.273003677 0.952645100 -0.328110861
[26] 0.019275123 -0.555504829 -0.939908303 -0.486162402 -1.252399182
[31] 0.133986811 -0.071000732 -0.317820743 0.100437513 -0.334069268
[36] -0.167090089 1.026212280 -0.280476873 1.860259135 -1.277336306
[41] 0.347295397 -1.532649152 0.391047311 0.567499019 2.661916537
[46] -1.126245011 -0.698045339 -0.322807135 -0.167143914 -1.360275378
[51] 0.830214286 -0.244366919 0.141259509 -1.388004256 -0.441862716
[56] -0.414430202 0.425837657 -0.689987852 -0.332509684 0.228462749
[61] 1.116905878 0.566301619 -0.499867799 -0.891997630 0.392515621
[66] 0.240300172 -0.615889746 -0.102703301 -0.981877147 -1.503826941
[71] 1.047574735 1.434335100 1.377037652 1.338473246 -0.131367984
[76] -1.778615238 1.181684538 0.831936371 0.130269007 -0.041857931
[81] 0.168486874 0.238234128 0.405763413 0.701196386 0.556471721
[86] 0.153954929 1.272683279 0.184243989 0.434823042 1.022196585
[91] -0.875028362 -0.243406036 0.022469836 -1.766943823 -0.744011059
[96] -0.277702131 -0.410181807 1.362546062 -1.036550622 -0.461993450
> 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] 0.260631542 0.600637586 -0.604014635 1.637818652 -0.971236174
[6] 0.382182301 0.263693304 0.007963902 1.091866127 -0.212987574
[11] 1.404087526 0.328011445 -0.697718169 -0.949409224 0.403651346
[16] 0.119581524 -0.048108157 0.822510593 -1.884400367 -1.283247770
[21] 0.856583563 0.914461888 1.273003677 0.952645100 -0.328110861
[26] 0.019275123 -0.555504829 -0.939908303 -0.486162402 -1.252399182
[31] 0.133986811 -0.071000732 -0.317820743 0.100437513 -0.334069268
[36] -0.167090089 1.026212280 -0.280476873 1.860259135 -1.277336306
[41] 0.347295397 -1.532649152 0.391047311 0.567499019 2.661916537
[46] -1.126245011 -0.698045339 -0.322807135 -0.167143914 -1.360275378
[51] 0.830214286 -0.244366919 0.141259509 -1.388004256 -0.441862716
[56] -0.414430202 0.425837657 -0.689987852 -0.332509684 0.228462749
[61] 1.116905878 0.566301619 -0.499867799 -0.891997630 0.392515621
[66] 0.240300172 -0.615889746 -0.102703301 -0.981877147 -1.503826941
[71] 1.047574735 1.434335100 1.377037652 1.338473246 -0.131367984
[76] -1.778615238 1.181684538 0.831936371 0.130269007 -0.041857931
[81] 0.168486874 0.238234128 0.405763413 0.701196386 0.556471721
[86] 0.153954929 1.272683279 0.184243989 0.434823042 1.022196585
[91] -0.875028362 -0.243406036 0.022469836 -1.766943823 -0.744011059
[96] -0.277702131 -0.410181807 1.362546062 -1.036550622 -0.461993450
> rowMin(tmp2)
[1] 0.260631542 0.600637586 -0.604014635 1.637818652 -0.971236174
[6] 0.382182301 0.263693304 0.007963902 1.091866127 -0.212987574
[11] 1.404087526 0.328011445 -0.697718169 -0.949409224 0.403651346
[16] 0.119581524 -0.048108157 0.822510593 -1.884400367 -1.283247770
[21] 0.856583563 0.914461888 1.273003677 0.952645100 -0.328110861
[26] 0.019275123 -0.555504829 -0.939908303 -0.486162402 -1.252399182
[31] 0.133986811 -0.071000732 -0.317820743 0.100437513 -0.334069268
[36] -0.167090089 1.026212280 -0.280476873 1.860259135 -1.277336306
[41] 0.347295397 -1.532649152 0.391047311 0.567499019 2.661916537
[46] -1.126245011 -0.698045339 -0.322807135 -0.167143914 -1.360275378
[51] 0.830214286 -0.244366919 0.141259509 -1.388004256 -0.441862716
[56] -0.414430202 0.425837657 -0.689987852 -0.332509684 0.228462749
[61] 1.116905878 0.566301619 -0.499867799 -0.891997630 0.392515621
[66] 0.240300172 -0.615889746 -0.102703301 -0.981877147 -1.503826941
[71] 1.047574735 1.434335100 1.377037652 1.338473246 -0.131367984
[76] -1.778615238 1.181684538 0.831936371 0.130269007 -0.041857931
[81] 0.168486874 0.238234128 0.405763413 0.701196386 0.556471721
[86] 0.153954929 1.272683279 0.184243989 0.434823042 1.022196585
[91] -0.875028362 -0.243406036 0.022469836 -1.766943823 -0.744011059
[96] -0.277702131 -0.410181807 1.362546062 -1.036550622 -0.461993450
>
> colMeans(tmp2)
[1] 0.02490287
> colSums(tmp2)
[1] 2.490287
> colVars(tmp2)
[1] 0.7788674
> colSd(tmp2)
[1] 0.8825346
> colMax(tmp2)
[1] 2.661917
> colMin(tmp2)
[1] -1.8844
> colMedians(tmp2)
[1] 0.02087248
> colRanges(tmp2)
[,1]
[1,] -1.884400
[2,] 2.661917
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.0663849 0.6983078 0.3311918 1.8586241 2.1834165 -1.2157855
[7] 0.6267460 -2.5375230 -2.0286569 -6.0588771
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0602821
[2,] -0.2511214
[3,] 0.3065634
[4,] 0.8254341
[5,] 1.7950049
>
> rowApply(tmp,sum)
[1] 2.3390114 -1.9202286 -8.3433434 -3.4511082 -0.2543244 1.5509048
[7] -4.4322109 7.1878661 7.1854805 -3.9382187
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 4 8 7 7 8 9 4 10 1
[2,] 9 7 1 4 6 3 2 2 9 10
[3,] 1 9 9 5 2 6 8 1 7 9
[4,] 3 8 7 6 5 10 4 6 4 6
[5,] 6 5 6 8 9 5 10 3 5 4
[6,] 10 1 10 3 10 1 5 8 2 5
[7,] 4 3 4 10 4 7 6 10 6 2
[8,] 5 2 2 9 3 2 3 5 8 8
[9,] 7 6 5 1 8 4 7 7 3 3
[10,] 2 10 3 2 1 9 1 9 1 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -5.41289432 -4.51480185 0.71034992 -0.72917197 1.53525650 -0.78795018
[7] 1.13206137 1.94311713 0.59037169 -1.84197338 3.91238682 2.54317103
[13] 1.36552484 -4.13085576 2.28211555 0.17791922 2.06618736 0.27104908
[19] 0.08130973 -1.22235482
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.73803183
[2,] -1.60969803
[3,] -1.17116071
[4,] -0.99102601
[5,] 0.09702226
>
> rowApply(tmp,sum)
[1] 2.84412477 -0.01456071 -1.66200210 2.95308123 -4.14982522
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 1 1 13 6
[2,] 1 2 14 2 8
[3,] 8 14 9 14 17
[4,] 15 17 17 1 1
[5,] 16 11 3 17 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.17116071 -1.8640647 -0.1614449 0.5695326 1.08190029 -0.53159691
[2,] -1.73803183 -1.4460016 0.2171031 0.7759830 0.07263366 0.50255043
[3,] -1.60969803 0.5002152 -0.3322962 1.0859880 -1.40810377 0.57055385
[4,] 0.09702226 -0.8641819 0.1406571 -0.9796565 1.02659044 -0.00758448
[5,] -0.99102601 -0.8407689 0.8463309 -2.1810190 0.76223589 -1.32187307
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.370707268 1.75518322 0.32927197 -1.0442200 0.1870329 -0.67494573
[2,] -0.003359192 0.09805094 -0.01089903 -1.2350283 2.6795053 0.08064627
[3,] 1.088228736 -0.86101269 -0.62992691 0.3066418 -0.7977386 1.00950596
[4,] 0.761666458 0.04007138 -0.07330274 -0.4084945 1.3973499 1.41486967
[5,] -1.085181897 0.91082429 0.97522840 0.5391276 0.4462373 0.71309486
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.006092541 -0.0185942 -1.5035293 1.2692595 1.8277640 0.4184446
[2,] -0.890644271 -0.8931209 1.2446345 1.3340569 -0.3598176 0.7546807
[3,] 1.188449369 -1.6084506 1.3155367 -0.7063284 0.1946220 -0.2596986
[4,] -0.261757166 -0.2400383 1.5147521 -0.3573390 -0.2674963 -0.4644754
[5,] 1.323384367 -1.3706518 -0.2892785 -1.3617297 0.6711154 -0.1779022
[,19] [,20]
[1,] 2.6311322 -0.63263980
[2,] -1.1863556 -0.01114707
[3,] -0.4514587 -0.25703123
[4,] -0.1035620 0.58799022
[5,] -0.8084462 -0.90952694
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.6451517 -1.486159 -0.7618649 -1.416112 -0.1484615 0.1167016 0.06070573
col8 col9 col10 col11 col12 col13 col14
row1 -2.653301 2.377327 0.3426134 -1.135321 -0.8599021 1.473343 -0.9572744
col15 col16 col17 col18 col19 col20
row1 -0.6037974 0.8776536 -0.185149 0.8423104 0.8851658 -0.7944401
> tmp[,"col10"]
col10
row1 0.3426134
row2 0.2840670
row3 -0.6822629
row4 -0.1602167
row5 0.7784068
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.6451517 -1.486159 -0.7618649 -1.416112 -0.1484615 0.1167016
row5 -0.4228324 1.615521 0.2132561 1.651551 -0.7479301 -1.0178178
col7 col8 col9 col10 col11 col12 col13
row1 0.06070573 -2.6533010 2.377327 0.3426134 -1.1353210 -0.8599021 1.473343
row5 -1.72899524 -0.6773912 -1.840645 0.7784068 -0.3193972 0.7443999 -1.975423
col14 col15 col16 col17 col18 col19
row1 -0.9572744 -0.60379742 0.8776536 -0.1851490 0.8423104 0.8851658
row5 0.2272426 -0.05396027 -0.7586418 0.2602309 1.1422097 0.7901926
col20
row1 -0.7944401
row5 -0.0126969
> tmp[,c("col6","col20")]
col6 col20
row1 0.1167016 -0.7944401
row2 1.6272720 -0.6602766
row3 -1.0053722 0.1477410
row4 1.8642321 1.5262700
row5 -1.0178178 -0.0126969
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.1167016 -0.7944401
row5 -1.0178178 -0.0126969
>
>
>
>
> 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 48.42473 50.63117 49.97993 51.7499 49.49906 104.6066 49.82073 49.81165
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.4875 50.7876 48.4033 48.41284 49.6796 50.55821 49.78688 51.3844
col17 col18 col19 col20
row1 49.53066 50.79233 50.57176 105.0697
> tmp[,"col10"]
col10
row1 50.78760
row2 30.12299
row3 29.53215
row4 30.37370
row5 49.35779
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.42473 50.63117 49.97993 51.74990 49.49906 104.6066 49.82073 49.81165
row5 49.68373 50.81581 49.40308 50.19314 50.77920 105.1109 49.35467 49.72136
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.4875 50.78760 48.40330 48.41284 49.67960 50.55821 49.78688 51.38440
row5 50.5262 49.35779 49.87479 50.92479 50.59123 49.95755 50.88914 49.36187
col17 col18 col19 col20
row1 49.53066 50.79233 50.57176 105.0697
row5 50.67090 49.32572 50.69042 103.7640
> tmp[,c("col6","col20")]
col6 col20
row1 104.60655 105.06974
row2 76.43728 75.30107
row3 73.52619 76.29459
row4 75.50159 76.22351
row5 105.11087 103.76401
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.6066 105.0697
row5 105.1109 103.7640
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.6066 105.0697
row5 105.1109 103.7640
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4381706
[2,] 1.8055770
[3,] -1.5999049
[4,] -0.2618324
[5,] 2.5904421
> tmp[,c("col17","col7")]
col17 col7
[1,] 2.9967352 0.03314749
[2,] 0.3778520 0.55412965
[3,] -0.1401467 -0.13539898
[4,] -0.6110875 -0.47907794
[5,] -0.7334981 0.29421360
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.12414667 -0.15766848
[2,] 0.98433333 0.05827269
[3,] -0.01042384 -0.48288572
[4,] 0.50180923 -0.28822753
[5,] 1.84159528 -0.98193392
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.1241467
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.1241467
[2,] 0.9843333
>
>
>
> 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 -1.3195975 -0.4555727 -1.25458875 0.45244478 -0.9038601 -0.560403
row1 -0.1723999 -0.6361126 0.04379847 -0.06432116 0.3892467 1.282467
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.07585361 0.5470588 -0.5679814 -1.63145452 -0.6607309 0.1919786
row1 2.19655352 -0.9990874 0.9860396 -0.05648017 0.1018216 0.1844163
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -0.1726689 0.5754407 -0.07641894 -0.2789401 -0.1242184 1.4481732
row1 -1.3966743 -1.1423298 -2.54384184 -0.8964295 -2.4975908 0.5673285
[,19] [,20]
row3 1.4778276 0.2631340
row1 -0.5213122 -0.4048172
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.169027 -1.809598 -2.363961 1.173892 -0.527284 -0.2171419 -0.08823006
[,8] [,9] [,10]
row2 2.053637 0.6929554 -0.5188772
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.405992 -1.342516 1.238452 0.5865209 -0.08463704 0.4840292 1.01321
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.7581733 1.356364 -0.4201792 0.8409137 3.998768 0.003423997 -1.443048
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.3024099 0.1554983 -1.970683 -0.4877048 0.651658 -0.007520982
>
>
> 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: 0x649eaddbf900>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd506a274f9b"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd506d2dcf12"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd5011dd99f9"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd50f8bcf5a"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd501b14c080"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd5012bd7d8b"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd505f86b5ae"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd50592b4894"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd50187b8be1"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd504d4d4f87"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd5040e2acdb"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd5058eb1dbf"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd505f417c68"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd505d59b115"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1acd503b844b52"
>
>
> ### 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: 0x649eaa85b9c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x649eaa85b9c0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x649eaa85b9c0>
> rowMedians(tmp)
[1] -0.0362763928 -0.0363104687 -0.3297638106 0.1675452399 -0.0722233379
[6] 0.4148777177 -0.2552136183 0.0295407950 0.2933311467 -0.0079196452
[11] -0.1660929640 -0.1955368181 0.3667527551 -0.2287418434 -0.1668297644
[16] 0.1962191098 0.4342436960 0.5039810656 -0.5243121327 -0.0028178320
[21] 0.1144155615 0.5142030489 -0.8389470246 -0.2543837913 -0.0181360514
[26] -0.5680349302 0.4356525027 0.0969012021 -0.0734066824 0.3113064111
[31] -0.4297256794 0.1756897805 -0.2645896267 -0.2463300675 0.1867721969
[36] 0.4024307223 0.1596589689 -0.0252135542 0.5524303599 -0.3812714263
[41] -0.7761913288 0.4410279141 0.0138336282 -0.3259282330 -0.6534290109
[46] -0.2884461105 0.3341557380 0.2385326255 -0.0150980512 -0.1666792424
[51] -0.0356351072 0.6246820944 -0.1119196005 -0.5069032367 0.1744371203
[56] -0.0270123234 -0.1665177904 0.2798095099 -0.1423871923 -0.1144685656
[61] -0.5971494663 0.3140772830 0.1149150523 -0.0808188003 -0.4409033781
[66] -0.0415407357 0.0002155551 0.2255236619 -0.2384427882 -0.4736897865
[71] -0.1345302081 0.0934602690 -0.7331241189 0.1613579770 -0.3286234391
[76] -0.2471858681 0.0151106279 -0.2235283160 -0.5786010864 -0.0379930898
[81] 0.0488941101 0.6454914463 -0.0114850460 -0.3344108342 0.6098867152
[86] -0.3141581026 0.1998939275 0.3573948036 0.2566694358 0.1984400206
[91] 0.0493255504 0.0415288270 -0.4454231444 -0.2052774833 -0.2180836789
[96] 0.0346829400 0.1214577817 0.0782887342 -0.0339065137 -0.3136402672
[101] 0.7217514997 -0.5634059571 0.0993012164 -0.3663785358 0.2520674303
[106] -0.5511614055 -0.3179032642 -0.1148218619 0.2334173760 -0.6196811803
[111] 0.1970898684 0.5338279925 0.0560799682 -0.1021038344 0.4317594461
[116] 0.2461451928 -0.1034195037 -0.2486935242 -0.0078979514 -0.0652013198
[121] -0.2075367973 -0.1188750982 -0.3020048866 -0.2986611035 0.1948032611
[126] 0.2411762740 -0.0691318158 -0.1342350976 -0.1429730286 -0.2738022646
[131] -0.3795590283 -0.1915153296 -0.1415523387 0.0729159608 -0.2123212415
[136] -0.2070391275 0.0536733431 0.2031900671 -0.3989278438 0.2599713358
[141] -0.6001759245 0.0375457285 -0.1778953321 0.0047675661 0.2446989539
[146] 0.2189771468 0.1158375645 0.2814146436 -0.0187955512 0.4100513619
[151] -0.1309114562 -0.4672769771 0.4106124060 0.0817186426 0.1497971499
[156] -0.0128270662 0.1747581559 -0.0154836034 0.2553451312 0.4100612787
[161] 0.0424891232 0.0657803180 -0.1452621985 -0.0210029356 0.3735385238
[166] -0.0297352467 0.4994988036 -0.3920430260 -0.1307359970 0.3661507513
[171] -0.3739409130 -0.7839697032 -0.1169285188 -0.2655805329 -0.1276047636
[176] 0.0750305794 0.1378541905 0.4726519804 0.3873989739 -0.1970821495
[181] -0.0597477346 0.2072069059 -0.2569424403 -0.0173578065 -0.0579393077
[186] -0.0739714390 -0.8705730152 0.3603312379 0.1304840842 -0.1699281496
[191] 0.0477469258 0.4197759916 0.2231063368 -0.7100335477 -0.3003132836
[196] 0.1028331184 0.0613608424 -0.2148078430 0.1929771733 0.1346214617
[201] 0.0336014218 0.1799182843 0.5101004573 -0.4833483790 -0.1477443119
[206] -0.1081460547 -0.4820367017 0.0609852367 0.1626552288 0.0184583505
[211] 0.2544335683 -0.0746331114 0.1932455773 0.1786415700 -0.0379287569
[216] -0.0674909399 -0.0344465065 0.4107463608 0.1045395720 0.1523062443
[221] -0.2159858653 -0.4367599774 0.0918616689 -0.3908524641 0.0793942804
[226] 0.2046804135 -0.1659467783 -0.3875283149 0.5240884902 0.0456452965
>
> proc.time()
user system elapsed
1.226 1.488 2.702
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 alpha (2026-03-30 r89742)
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: 0x5ea167391720>
> .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: 0x5ea167391720>
> .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: 0x5ea167391720>
> .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: 0x5ea167391720>
> 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: 0x5ea168078290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea168078290>
> .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: 0x5ea168078290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea168078290>
> .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: 0x5ea168078290>
> 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: 0x5ea166d35610>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea166d35610>
> .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: 0x5ea166d35610>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5ea166d35610>
> .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: 0x5ea166d35610>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5ea166d35610>
> .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: 0x5ea166d35610>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5ea166d35610>
> .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: 0x5ea166d35610>
> 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: 0x5ea167248ac0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5ea167248ac0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea167248ac0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea167248ac0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1acf261663ec00" "BufferedMatrixFile1acf2623b89c2f"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1acf261663ec00" "BufferedMatrixFile1acf2623b89c2f"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea167ec5530>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea167ec5530>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5ea167ec5530>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5ea167ec5530>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5ea167ec5530>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5ea167ec5530>
> .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: 0x5ea16695d380>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5ea16695d380>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5ea16695d380>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5ea16695d380>
> 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: 0x5ea166e2a3c0>
> .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: 0x5ea166e2a3c0>
> rm(P)
>
> proc.time()
user system elapsed
0.235 0.059 0.281
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 alpha (2026-03-30 r89742)
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
0.236 0.042 0.266