Ben Bolstad
| Snapshot Date: 2026-03-16 13:40 -0400 (Mon, 16 Mar 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 Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-03-17 11:33 -0400 (Tue, 17 Mar 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences" | 4845 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-03-01 r89506) -- "Unsuffered Consequences" | 4060 |
| 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 257/2367 | 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 | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | ERROR | ERROR | skipped | skipped | |||||||||
| 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: 2026-03-16 21:37:14 -0400 (Mon, 16 Mar 2026) |
| EndedAt: 2026-03-16 21:37:39 -0400 (Mon, 16 Mar 2026) |
| EllapsedTime: 25.0 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 Under development (unstable) (2026-03-05 r89546)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-03-17 01:37:14 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 Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.244 0.044 0.278
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
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 479482 25.7 1050322 56.1 639251 34.2
Vcells 886403 6.8 8388608 64.0 2083267 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] "Mon Mar 16 21:37:29 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] "Mon Mar 16 21:37:29 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: 0x57223a5b54f0>
>
>
>
> 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] "Mon Mar 16 21:37:29 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] "Mon Mar 16 21:37:29 2026"
>
> ColMode(tmp2)
<pointer: 0x57223a5b54f0>
>
>
>
> ### 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,] 99.612272 1.060349 -0.6926594 -0.8026987
[2,] 1.116152 -1.038988 -0.7191747 0.6142167
[3,] -0.868209 1.306133 2.7217778 -0.8046151
[4,] 1.427781 1.073854 -0.1268543 -0.5585988
> 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,] 99.612272 1.060349 0.6926594 0.8026987
[2,] 1.116152 1.038988 0.7191747 0.6142167
[3,] 0.868209 1.306133 2.7217778 0.8046151
[4,] 1.427781 1.073854 0.1268543 0.5585988
> 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,] 9.9805948 1.029733 0.8322616 0.8959345
[2,] 1.0564811 1.019307 0.8480417 0.7837198
[3,] 0.9317773 1.142862 1.6497811 0.8970034
[4,] 1.1948978 1.036269 0.3561661 0.7473947
>
> 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,] 224.41822 36.35768 34.01528 34.76204
[2,] 36.68096 36.23206 34.19959 33.45141
[3,] 35.18598 37.73475 44.21959 34.77465
[4,] 38.37676 36.43655 28.68852 33.03255
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x57223bc135a0>
> exp(tmp5)
<pointer: 0x57223bc135a0>
> log(tmp5,2)
<pointer: 0x57223bc135a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.0971
> Min(tmp5)
[1] 54.1289
> mean(tmp5)
[1] 71.48091
> Sum(tmp5)
[1] 14296.18
> Var(tmp5)
[1] 846.9321
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.79367 70.32611 71.31450 69.47682 69.34229 69.30847 69.08327 70.57127
[9] 68.39203 67.20069
> rowSums(tmp5)
[1] 1795.873 1406.522 1426.290 1389.536 1386.846 1386.169 1381.665 1411.425
[9] 1367.841 1344.014
> rowVars(tmp5)
[1] 7911.94226 26.60412 100.74944 49.52290 55.03512 60.64037
[7] 63.10631 83.55869 69.13143 45.50776
> rowSd(tmp5)
[1] 88.949099 5.157918 10.037402 7.037251 7.418566 7.787193 7.943948
[8] 9.141044 8.314531 6.745944
> rowMax(tmp5)
[1] 467.09712 76.73646 92.03728 86.31898 88.00527 84.17786 83.81787
[8] 84.79190 90.32052 80.84925
> rowMin(tmp5)
[1] 57.83138 58.58045 54.12890 58.84667 59.65406 56.09211 55.36034 54.84440
[9] 55.99979 55.12741
>
> colMeans(tmp5)
[1] 110.32643 72.01098 72.20736 67.61991 73.26368 68.39009 68.92589
[8] 72.79066 67.36996 70.19075 68.90279 65.76307 71.30721 69.58258
[15] 66.05740 68.19520 65.68487 70.70418 73.17362 67.15160
> colSums(tmp5)
[1] 1103.2643 720.1098 722.0736 676.1991 732.6368 683.9009 689.2589
[8] 727.9066 673.6996 701.9075 689.0279 657.6307 713.0721 695.8258
[15] 660.5740 681.9520 656.8487 707.0418 731.7362 671.5160
> colVars(tmp5)
[1] 15757.08263 41.97921 82.61279 56.77649 29.09456 43.89071
[7] 96.41049 81.55234 53.47772 44.77096 69.90602 42.96578
[13] 28.50947 36.98309 37.37345 68.00105 42.88738 89.22605
[19] 85.48614 45.15575
> colSd(tmp5)
[1] 125.527219 6.479137 9.089158 7.535018 5.393938 6.625006
[7] 9.818884 9.030634 7.312846 6.691110 8.360982 6.554829
[13] 5.339426 6.081373 6.113383 8.246275 6.548846 9.445954
[19] 9.245872 6.719803
> colMax(tmp5)
[1] 467.09712 78.57917 92.03728 80.76426 81.59780 79.71285 82.60804
[8] 88.00527 76.73646 81.33231 83.81787 74.85274 78.78622 77.91558
[15] 73.13315 84.17786 75.12031 86.31898 90.32052 76.33688
> colMin(tmp5)
[1] 58.96183 61.09791 59.71139 56.09211 64.57506 57.27597 55.99979 61.72773
[9] 54.12890 61.92050 55.12741 57.80848 61.51249 60.11605 55.26801 54.84440
[17] 55.36034 57.83138 61.84510 55.45440
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] NA 70.32611 71.31450 69.47682 69.34229 69.30847 69.08327 70.57127
[9] 68.39203 67.20069
> rowSums(tmp5)
[1] NA 1406.522 1426.290 1389.536 1386.846 1386.169 1381.665 1411.425
[9] 1367.841 1344.014
> rowVars(tmp5)
[1] 8326.81639 26.60412 100.74944 49.52290 55.03512 60.64037
[7] 63.10631 83.55869 69.13143 45.50776
> rowSd(tmp5)
[1] 91.251391 5.157918 10.037402 7.037251 7.418566 7.787193 7.943948
[8] 9.141044 8.314531 6.745944
> rowMax(tmp5)
[1] NA 76.73646 92.03728 86.31898 88.00527 84.17786 83.81787 84.79190
[9] 90.32052 80.84925
> rowMin(tmp5)
[1] NA 58.58045 54.12890 58.84667 59.65406 56.09211 55.36034 54.84440
[9] 55.99979 55.12741
>
> colMeans(tmp5)
[1] 110.32643 72.01098 72.20736 67.61991 73.26368 68.39009 68.92589
[8] 72.79066 67.36996 70.19075 68.90279 65.76307 71.30721 NA
[15] 66.05740 68.19520 65.68487 70.70418 73.17362 67.15160
> colSums(tmp5)
[1] 1103.2643 720.1098 722.0736 676.1991 732.6368 683.9009 689.2589
[8] 727.9066 673.6996 701.9075 689.0279 657.6307 713.0721 NA
[15] 660.5740 681.9520 656.8487 707.0418 731.7362 671.5160
> colVars(tmp5)
[1] 15757.08263 41.97921 82.61279 56.77649 29.09456 43.89071
[7] 96.41049 81.55234 53.47772 44.77096 69.90602 42.96578
[13] 28.50947 NA 37.37345 68.00105 42.88738 89.22605
[19] 85.48614 45.15575
> colSd(tmp5)
[1] 125.527219 6.479137 9.089158 7.535018 5.393938 6.625006
[7] 9.818884 9.030634 7.312846 6.691110 8.360982 6.554829
[13] 5.339426 NA 6.113383 8.246275 6.548846 9.445954
[19] 9.245872 6.719803
> colMax(tmp5)
[1] 467.09712 78.57917 92.03728 80.76426 81.59780 79.71285 82.60804
[8] 88.00527 76.73646 81.33231 83.81787 74.85274 78.78622 NA
[15] 73.13315 84.17786 75.12031 86.31898 90.32052 76.33688
> colMin(tmp5)
[1] 58.96183 61.09791 59.71139 56.09211 64.57506 57.27597 55.99979 61.72773
[9] 54.12890 61.92050 55.12741 57.80848 61.51249 NA 55.26801 54.84440
[17] 55.36034 57.83138 61.84510 55.45440
>
> Max(tmp5,na.rm=TRUE)
[1] 467.0971
> Min(tmp5,na.rm=TRUE)
[1] 54.1289
> mean(tmp5,na.rm=TRUE)
[1] 71.49212
> Sum(tmp5,na.rm=TRUE)
[1] 14226.93
> Var(tmp5,na.rm=TRUE)
[1] 851.1842
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.87486 70.32611 71.31450 69.47682 69.34229 69.30847 69.08327 70.57127
[9] 68.39203 67.20069
> rowSums(tmp5,na.rm=TRUE)
[1] 1726.622 1406.522 1426.290 1389.536 1386.846 1386.169 1381.665 1411.425
[9] 1367.841 1344.014
> rowVars(tmp5,na.rm=TRUE)
[1] 8326.81639 26.60412 100.74944 49.52290 55.03512 60.64037
[7] 63.10631 83.55869 69.13143 45.50776
> rowSd(tmp5,na.rm=TRUE)
[1] 91.251391 5.157918 10.037402 7.037251 7.418566 7.787193 7.943948
[8] 9.141044 8.314531 6.745944
> rowMax(tmp5,na.rm=TRUE)
[1] 467.09712 76.73646 92.03728 86.31898 88.00527 84.17786 83.81787
[8] 84.79190 90.32052 80.84925
> rowMin(tmp5,na.rm=TRUE)
[1] 57.83138 58.58045 54.12890 58.84667 59.65406 56.09211 55.36034 54.84440
[9] 55.99979 55.12741
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.32643 72.01098 72.20736 67.61991 73.26368 68.39009 68.92589
[8] 72.79066 67.36996 70.19075 68.90279 65.76307 71.30721 69.61942
[15] 66.05740 68.19520 65.68487 70.70418 73.17362 67.15160
> colSums(tmp5,na.rm=TRUE)
[1] 1103.2643 720.1098 722.0736 676.1991 732.6368 683.9009 689.2589
[8] 727.9066 673.6996 701.9075 689.0279 657.6307 713.0721 626.5747
[15] 660.5740 681.9520 656.8487 707.0418 731.7362 671.5160
> colVars(tmp5,na.rm=TRUE)
[1] 15757.08263 41.97921 82.61279 56.77649 29.09456 43.89071
[7] 96.41049 81.55234 53.47772 44.77096 69.90602 42.96578
[13] 28.50947 41.59072 37.37345 68.00105 42.88738 89.22605
[19] 85.48614 45.15575
> colSd(tmp5,na.rm=TRUE)
[1] 125.527219 6.479137 9.089158 7.535018 5.393938 6.625006
[7] 9.818884 9.030634 7.312846 6.691110 8.360982 6.554829
[13] 5.339426 6.449087 6.113383 8.246275 6.548846 9.445954
[19] 9.245872 6.719803
> colMax(tmp5,na.rm=TRUE)
[1] 467.09712 78.57917 92.03728 80.76426 81.59780 79.71285 82.60804
[8] 88.00527 76.73646 81.33231 83.81787 74.85274 78.78622 77.91558
[15] 73.13315 84.17786 75.12031 86.31898 90.32052 76.33688
> colMin(tmp5,na.rm=TRUE)
[1] 58.96183 61.09791 59.71139 56.09211 64.57506 57.27597 55.99979 61.72773
[9] 54.12890 61.92050 55.12741 57.80848 61.51249 60.11605 55.26801 54.84440
[17] 55.36034 57.83138 61.84510 55.45440
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 70.32611 71.31450 69.47682 69.34229 69.30847 69.08327 70.57127
[9] 68.39203 67.20069
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1406.522 1426.290 1389.536 1386.846 1386.169 1381.665 1411.425
[9] 1367.841 1344.014
> rowVars(tmp5,na.rm=TRUE)
[1] NA 26.60412 100.74944 49.52290 55.03512 60.64037 63.10631
[8] 83.55869 69.13143 45.50776
> rowSd(tmp5,na.rm=TRUE)
[1] NA 5.157918 10.037402 7.037251 7.418566 7.787193 7.943948
[8] 9.141044 8.314531 6.745944
> rowMax(tmp5,na.rm=TRUE)
[1] NA 76.73646 92.03728 86.31898 88.00527 84.17786 83.81787 84.79190
[9] 90.32052 80.84925
> rowMin(tmp5,na.rm=TRUE)
[1] NA 58.58045 54.12890 58.84667 59.65406 56.09211 55.36034 54.84440
[9] 55.99979 55.12741
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 70.68524 71.60401 72.36392 67.09405 73.01183 68.66496 68.15982 73.28314
[9] 67.30388 70.93873 68.27727 64.80897 71.50976 NaN 65.27121 67.99365
[17] 66.25749 72.13449 73.03900 66.90240
> colSums(tmp5,na.rm=TRUE)
[1] 636.1672 644.4361 651.2753 603.8465 657.1064 617.9847 613.4384 659.5483
[9] 605.7349 638.4486 614.4954 583.2808 643.5878 0.0000 587.4409 611.9429
[17] 596.3174 649.2104 657.3510 602.1216
> colVars(tmp5,na.rm=TRUE)
[1] 48.20051 45.36331 92.66365 60.76262 32.01778 48.52707 101.85960
[8] 89.01780 60.11331 44.07334 74.24232 38.09565 31.61158 NA
[15] 35.09148 76.04418 44.55950 77.36418 95.96802 50.10161
> colSd(tmp5,na.rm=TRUE)
[1] 6.942659 6.735229 9.626196 7.795038 5.658425 6.966137 10.092552
[8] 9.434925 7.753277 6.638775 8.616398 6.172167 5.622418 NA
[15] 5.923807 8.720332 6.675290 8.795691 9.796327 7.078249
> colMax(tmp5,na.rm=TRUE)
[1] 79.87619 78.57917 92.03728 80.76426 81.59780 79.71285 82.60804 88.00527
[9] 76.73646 81.33231 83.81787 74.85274 78.78622 -Inf 71.87860 84.17786
[17] 75.12031 86.31898 90.32052 76.33688
> colMin(tmp5,na.rm=TRUE)
[1] 58.96183 61.09791 59.71139 56.09211 64.57506 57.27597 55.99979 61.72773
[9] 54.12890 61.92050 55.12741 57.80848 61.51249 Inf 55.26801 54.84440
[17] 55.36034 58.58045 61.84510 55.45440
>
>
>
>
> 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] 105.22367 218.01615 597.84662 153.52951 283.93446 92.85886 268.46810
[8] 255.49129 193.99720 333.83895
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 105.22367 218.01615 597.84662 153.52951 283.93446 92.85886 268.46810
[8] 255.49129 193.99720 333.83895
>
>
>
> 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] -2.842171e-14 2.557954e-13 7.105427e-15 1.563194e-13 -1.136868e-13
[6] 2.842171e-13 4.263256e-14 -5.684342e-14 -2.273737e-13 -5.684342e-14
[11] -2.842171e-14 -2.842171e-14 1.136868e-13 1.705303e-13 -5.684342e-14
[16] 5.684342e-14 1.136868e-13 4.263256e-14 -2.842171e-14 8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 20
4 7
6 2
6 7
5 3
10 18
5 19
1 2
8 8
9 6
10 6
6 14
1 4
7 3
9 10
3 11
7 18
10 12
10 13
4 18
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] 2.157998
> Min(tmp)
[1] -2.728913
> mean(tmp)
[1] -0.007155049
> Sum(tmp)
[1] -0.7155049
> Var(tmp)
[1] 1.046414
>
> rowMeans(tmp)
[1] -0.007155049
> rowSums(tmp)
[1] -0.7155049
> rowVars(tmp)
[1] 1.046414
> rowSd(tmp)
[1] 1.022944
> rowMax(tmp)
[1] 2.157998
> rowMin(tmp)
[1] -2.728913
>
> colMeans(tmp)
[1] -0.1909105349 -0.3906222697 1.9602539474 -0.0895968237 -0.8659091021
[6] 0.9785766463 1.1715768133 -0.2332380394 2.1579980111 -0.0031910864
[11] -0.5410447631 -0.5057904227 -0.1571246359 0.7067519448 0.3616037309
[16] 1.4297523173 -0.1726930374 0.1770672081 -0.5493768476 0.3654904594
[21] 1.0225705399 -1.0210937105 1.9557408108 -1.6117858152 -0.1192868533
[26] -1.5414737578 0.9858582833 1.3748054854 -0.2416252577 -0.3949792187
[31] -0.5321366201 -0.8274060875 -1.9998963144 -0.8762679179 0.6058563030
[36] -1.8484849295 -0.0381753528 1.3603423808 0.0396970229 -0.5243458699
[41] 1.0251246315 -0.0336581284 -0.0431496042 -1.3658148736 1.1584626906
[46] 0.8015706872 -1.0188038584 1.2492749833 0.2120814340 0.3901844940
[51] 1.1610405109 0.8348257637 -0.5586242438 1.7536606852 -0.2358374186
[56] -1.0117573460 1.0328431943 -0.4795918684 -0.3761967666 0.6912157564
[61] 0.3653570782 -2.7289129487 0.4763726406 -0.5927722990 -1.5661793581
[66] -1.2937539323 -0.2119644670 0.7570010593 -0.4178602598 1.4855542459
[71] -0.0498102765 -1.5990246395 0.8147241788 -0.4813650450 0.9263445060
[76] -1.7605705452 -1.0557652809 0.4680038001 0.5527040194 -0.5830877605
[81] 0.5802985896 -0.0900019379 0.7338554231 -0.6449547436 -1.1546679254
[86] 1.5694419538 -0.8871620764 -0.0001456922 1.0692299534 -1.8134387361
[91] 0.7530256611 1.5797887075 1.1057024957 0.0958011464 -1.2481060509
[96] 0.0263954363 -0.6072109038 -1.1943785729 -1.6360052913 0.9776956060
> colSums(tmp)
[1] -0.1909105349 -0.3906222697 1.9602539474 -0.0895968237 -0.8659091021
[6] 0.9785766463 1.1715768133 -0.2332380394 2.1579980111 -0.0031910864
[11] -0.5410447631 -0.5057904227 -0.1571246359 0.7067519448 0.3616037309
[16] 1.4297523173 -0.1726930374 0.1770672081 -0.5493768476 0.3654904594
[21] 1.0225705399 -1.0210937105 1.9557408108 -1.6117858152 -0.1192868533
[26] -1.5414737578 0.9858582833 1.3748054854 -0.2416252577 -0.3949792187
[31] -0.5321366201 -0.8274060875 -1.9998963144 -0.8762679179 0.6058563030
[36] -1.8484849295 -0.0381753528 1.3603423808 0.0396970229 -0.5243458699
[41] 1.0251246315 -0.0336581284 -0.0431496042 -1.3658148736 1.1584626906
[46] 0.8015706872 -1.0188038584 1.2492749833 0.2120814340 0.3901844940
[51] 1.1610405109 0.8348257637 -0.5586242438 1.7536606852 -0.2358374186
[56] -1.0117573460 1.0328431943 -0.4795918684 -0.3761967666 0.6912157564
[61] 0.3653570782 -2.7289129487 0.4763726406 -0.5927722990 -1.5661793581
[66] -1.2937539323 -0.2119644670 0.7570010593 -0.4178602598 1.4855542459
[71] -0.0498102765 -1.5990246395 0.8147241788 -0.4813650450 0.9263445060
[76] -1.7605705452 -1.0557652809 0.4680038001 0.5527040194 -0.5830877605
[81] 0.5802985896 -0.0900019379 0.7338554231 -0.6449547436 -1.1546679254
[86] 1.5694419538 -0.8871620764 -0.0001456922 1.0692299534 -1.8134387361
[91] 0.7530256611 1.5797887075 1.1057024957 0.0958011464 -1.2481060509
[96] 0.0263954363 -0.6072109038 -1.1943785729 -1.6360052913 0.9776956060
> 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] -0.1909105349 -0.3906222697 1.9602539474 -0.0895968237 -0.8659091021
[6] 0.9785766463 1.1715768133 -0.2332380394 2.1579980111 -0.0031910864
[11] -0.5410447631 -0.5057904227 -0.1571246359 0.7067519448 0.3616037309
[16] 1.4297523173 -0.1726930374 0.1770672081 -0.5493768476 0.3654904594
[21] 1.0225705399 -1.0210937105 1.9557408108 -1.6117858152 -0.1192868533
[26] -1.5414737578 0.9858582833 1.3748054854 -0.2416252577 -0.3949792187
[31] -0.5321366201 -0.8274060875 -1.9998963144 -0.8762679179 0.6058563030
[36] -1.8484849295 -0.0381753528 1.3603423808 0.0396970229 -0.5243458699
[41] 1.0251246315 -0.0336581284 -0.0431496042 -1.3658148736 1.1584626906
[46] 0.8015706872 -1.0188038584 1.2492749833 0.2120814340 0.3901844940
[51] 1.1610405109 0.8348257637 -0.5586242438 1.7536606852 -0.2358374186
[56] -1.0117573460 1.0328431943 -0.4795918684 -0.3761967666 0.6912157564
[61] 0.3653570782 -2.7289129487 0.4763726406 -0.5927722990 -1.5661793581
[66] -1.2937539323 -0.2119644670 0.7570010593 -0.4178602598 1.4855542459
[71] -0.0498102765 -1.5990246395 0.8147241788 -0.4813650450 0.9263445060
[76] -1.7605705452 -1.0557652809 0.4680038001 0.5527040194 -0.5830877605
[81] 0.5802985896 -0.0900019379 0.7338554231 -0.6449547436 -1.1546679254
[86] 1.5694419538 -0.8871620764 -0.0001456922 1.0692299534 -1.8134387361
[91] 0.7530256611 1.5797887075 1.1057024957 0.0958011464 -1.2481060509
[96] 0.0263954363 -0.6072109038 -1.1943785729 -1.6360052913 0.9776956060
> colMin(tmp)
[1] -0.1909105349 -0.3906222697 1.9602539474 -0.0895968237 -0.8659091021
[6] 0.9785766463 1.1715768133 -0.2332380394 2.1579980111 -0.0031910864
[11] -0.5410447631 -0.5057904227 -0.1571246359 0.7067519448 0.3616037309
[16] 1.4297523173 -0.1726930374 0.1770672081 -0.5493768476 0.3654904594
[21] 1.0225705399 -1.0210937105 1.9557408108 -1.6117858152 -0.1192868533
[26] -1.5414737578 0.9858582833 1.3748054854 -0.2416252577 -0.3949792187
[31] -0.5321366201 -0.8274060875 -1.9998963144 -0.8762679179 0.6058563030
[36] -1.8484849295 -0.0381753528 1.3603423808 0.0396970229 -0.5243458699
[41] 1.0251246315 -0.0336581284 -0.0431496042 -1.3658148736 1.1584626906
[46] 0.8015706872 -1.0188038584 1.2492749833 0.2120814340 0.3901844940
[51] 1.1610405109 0.8348257637 -0.5586242438 1.7536606852 -0.2358374186
[56] -1.0117573460 1.0328431943 -0.4795918684 -0.3761967666 0.6912157564
[61] 0.3653570782 -2.7289129487 0.4763726406 -0.5927722990 -1.5661793581
[66] -1.2937539323 -0.2119644670 0.7570010593 -0.4178602598 1.4855542459
[71] -0.0498102765 -1.5990246395 0.8147241788 -0.4813650450 0.9263445060
[76] -1.7605705452 -1.0557652809 0.4680038001 0.5527040194 -0.5830877605
[81] 0.5802985896 -0.0900019379 0.7338554231 -0.6449547436 -1.1546679254
[86] 1.5694419538 -0.8871620764 -0.0001456922 1.0692299534 -1.8134387361
[91] 0.7530256611 1.5797887075 1.1057024957 0.0958011464 -1.2481060509
[96] 0.0263954363 -0.6072109038 -1.1943785729 -1.6360052913 0.9776956060
> colMedians(tmp)
[1] -0.1909105349 -0.3906222697 1.9602539474 -0.0895968237 -0.8659091021
[6] 0.9785766463 1.1715768133 -0.2332380394 2.1579980111 -0.0031910864
[11] -0.5410447631 -0.5057904227 -0.1571246359 0.7067519448 0.3616037309
[16] 1.4297523173 -0.1726930374 0.1770672081 -0.5493768476 0.3654904594
[21] 1.0225705399 -1.0210937105 1.9557408108 -1.6117858152 -0.1192868533
[26] -1.5414737578 0.9858582833 1.3748054854 -0.2416252577 -0.3949792187
[31] -0.5321366201 -0.8274060875 -1.9998963144 -0.8762679179 0.6058563030
[36] -1.8484849295 -0.0381753528 1.3603423808 0.0396970229 -0.5243458699
[41] 1.0251246315 -0.0336581284 -0.0431496042 -1.3658148736 1.1584626906
[46] 0.8015706872 -1.0188038584 1.2492749833 0.2120814340 0.3901844940
[51] 1.1610405109 0.8348257637 -0.5586242438 1.7536606852 -0.2358374186
[56] -1.0117573460 1.0328431943 -0.4795918684 -0.3761967666 0.6912157564
[61] 0.3653570782 -2.7289129487 0.4763726406 -0.5927722990 -1.5661793581
[66] -1.2937539323 -0.2119644670 0.7570010593 -0.4178602598 1.4855542459
[71] -0.0498102765 -1.5990246395 0.8147241788 -0.4813650450 0.9263445060
[76] -1.7605705452 -1.0557652809 0.4680038001 0.5527040194 -0.5830877605
[81] 0.5802985896 -0.0900019379 0.7338554231 -0.6449547436 -1.1546679254
[86] 1.5694419538 -0.8871620764 -0.0001456922 1.0692299534 -1.8134387361
[91] 0.7530256611 1.5797887075 1.1057024957 0.0958011464 -1.2481060509
[96] 0.0263954363 -0.6072109038 -1.1943785729 -1.6360052913 0.9776956060
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1909105 -0.3906223 1.960254 -0.08959682 -0.8659091 0.9785766 1.171577
[2,] -0.1909105 -0.3906223 1.960254 -0.08959682 -0.8659091 0.9785766 1.171577
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.233238 2.157998 -0.003191086 -0.5410448 -0.5057904 -0.1571246 0.7067519
[2,] -0.233238 2.157998 -0.003191086 -0.5410448 -0.5057904 -0.1571246 0.7067519
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.3616037 1.429752 -0.172693 0.1770672 -0.5493768 0.3654905 1.022571
[2,] 0.3616037 1.429752 -0.172693 0.1770672 -0.5493768 0.3654905 1.022571
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.021094 1.955741 -1.611786 -0.1192869 -1.541474 0.9858583 1.374805
[2,] -1.021094 1.955741 -1.611786 -0.1192869 -1.541474 0.9858583 1.374805
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.2416253 -0.3949792 -0.5321366 -0.8274061 -1.999896 -0.8762679 0.6058563
[2,] -0.2416253 -0.3949792 -0.5321366 -0.8274061 -1.999896 -0.8762679 0.6058563
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.848485 -0.03817535 1.360342 0.03969702 -0.5243459 1.025125 -0.03365813
[2,] -1.848485 -0.03817535 1.360342 0.03969702 -0.5243459 1.025125 -0.03365813
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.0431496 -1.365815 1.158463 0.8015707 -1.018804 1.249275 0.2120814
[2,] -0.0431496 -1.365815 1.158463 0.8015707 -1.018804 1.249275 0.2120814
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3901845 1.161041 0.8348258 -0.5586242 1.753661 -0.2358374 -1.011757
[2,] 0.3901845 1.161041 0.8348258 -0.5586242 1.753661 -0.2358374 -1.011757
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.032843 -0.4795919 -0.3761968 0.6912158 0.3653571 -2.728913 0.4763726
[2,] 1.032843 -0.4795919 -0.3761968 0.6912158 0.3653571 -2.728913 0.4763726
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.5927723 -1.566179 -1.293754 -0.2119645 0.7570011 -0.4178603 1.485554
[2,] -0.5927723 -1.566179 -1.293754 -0.2119645 0.7570011 -0.4178603 1.485554
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.04981028 -1.599025 0.8147242 -0.481365 0.9263445 -1.760571 -1.055765
[2,] -0.04981028 -1.599025 0.8147242 -0.481365 0.9263445 -1.760571 -1.055765
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.4680038 0.552704 -0.5830878 0.5802986 -0.09000194 0.7338554 -0.6449547
[2,] 0.4680038 0.552704 -0.5830878 0.5802986 -0.09000194 0.7338554 -0.6449547
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.154668 1.569442 -0.8871621 -0.0001456922 1.06923 -1.813439 0.7530257
[2,] -1.154668 1.569442 -0.8871621 -0.0001456922 1.06923 -1.813439 0.7530257
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.579789 1.105702 0.09580115 -1.248106 0.02639544 -0.6072109 -1.194379
[2,] 1.579789 1.105702 0.09580115 -1.248106 0.02639544 -0.6072109 -1.194379
[,99] [,100]
[1,] -1.636005 0.9776956
[2,] -1.636005 0.9776956
>
>
> Max(tmp2)
[1] 3.106567
> Min(tmp2)
[1] -2.354537
> mean(tmp2)
[1] -0.02055058
> Sum(tmp2)
[1] -2.055058
> Var(tmp2)
[1] 0.9229784
>
> rowMeans(tmp2)
[1] 3.10656656 -0.76443307 -1.69672578 1.65467516 -0.07515522 -0.40574341
[7] 0.33947316 0.10330353 -0.29444214 -1.38510558 0.28926936 0.71256786
[13] 1.79299965 -0.17523009 -0.77098838 0.72111222 0.32403294 1.38292533
[19] -0.85303950 0.45603760 0.28463088 0.14973185 -1.09635373 -0.97702534
[25] 0.75726747 -1.47514872 0.73838537 -0.84214331 1.06105618 1.08283562
[31] -1.44395431 -0.17443853 0.25962260 0.35887720 -0.56492907 -0.55975956
[37] -1.59941391 0.03192228 0.40016224 -0.44884972 -0.97513069 -0.82077194
[43] -0.36641849 -0.33265391 -0.86480677 0.68621145 0.94845542 0.71356066
[49] 0.11222283 1.46088481 0.28229011 -0.15789272 0.05625576 -1.53365358
[55] 0.22852874 -0.32628496 0.07379632 0.74556357 0.73908009 0.54265356
[61] -1.53506637 1.57311460 -0.56487072 -0.92757738 0.86703830 0.56370537
[67] -0.50909658 0.73342706 -2.35453685 0.25770716 0.50149391 -0.17652072
[73] 1.88524473 0.75064258 0.29060742 -1.39073984 -0.58998291 -0.66467108
[79] 0.01496553 0.80041075 1.32643324 -0.93864830 0.85146879 -1.23446837
[85] 0.15308734 0.44639216 0.18888502 -1.30287379 -1.81044318 0.58965762
[91] -0.27601160 -0.31624768 -0.01122121 1.07561100 -0.75623801 0.59161804
[97] 0.54877341 -0.85499592 -2.16482901 0.69723201
> rowSums(tmp2)
[1] 3.10656656 -0.76443307 -1.69672578 1.65467516 -0.07515522 -0.40574341
[7] 0.33947316 0.10330353 -0.29444214 -1.38510558 0.28926936 0.71256786
[13] 1.79299965 -0.17523009 -0.77098838 0.72111222 0.32403294 1.38292533
[19] -0.85303950 0.45603760 0.28463088 0.14973185 -1.09635373 -0.97702534
[25] 0.75726747 -1.47514872 0.73838537 -0.84214331 1.06105618 1.08283562
[31] -1.44395431 -0.17443853 0.25962260 0.35887720 -0.56492907 -0.55975956
[37] -1.59941391 0.03192228 0.40016224 -0.44884972 -0.97513069 -0.82077194
[43] -0.36641849 -0.33265391 -0.86480677 0.68621145 0.94845542 0.71356066
[49] 0.11222283 1.46088481 0.28229011 -0.15789272 0.05625576 -1.53365358
[55] 0.22852874 -0.32628496 0.07379632 0.74556357 0.73908009 0.54265356
[61] -1.53506637 1.57311460 -0.56487072 -0.92757738 0.86703830 0.56370537
[67] -0.50909658 0.73342706 -2.35453685 0.25770716 0.50149391 -0.17652072
[73] 1.88524473 0.75064258 0.29060742 -1.39073984 -0.58998291 -0.66467108
[79] 0.01496553 0.80041075 1.32643324 -0.93864830 0.85146879 -1.23446837
[85] 0.15308734 0.44639216 0.18888502 -1.30287379 -1.81044318 0.58965762
[91] -0.27601160 -0.31624768 -0.01122121 1.07561100 -0.75623801 0.59161804
[97] 0.54877341 -0.85499592 -2.16482901 0.69723201
> 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] 3.10656656 -0.76443307 -1.69672578 1.65467516 -0.07515522 -0.40574341
[7] 0.33947316 0.10330353 -0.29444214 -1.38510558 0.28926936 0.71256786
[13] 1.79299965 -0.17523009 -0.77098838 0.72111222 0.32403294 1.38292533
[19] -0.85303950 0.45603760 0.28463088 0.14973185 -1.09635373 -0.97702534
[25] 0.75726747 -1.47514872 0.73838537 -0.84214331 1.06105618 1.08283562
[31] -1.44395431 -0.17443853 0.25962260 0.35887720 -0.56492907 -0.55975956
[37] -1.59941391 0.03192228 0.40016224 -0.44884972 -0.97513069 -0.82077194
[43] -0.36641849 -0.33265391 -0.86480677 0.68621145 0.94845542 0.71356066
[49] 0.11222283 1.46088481 0.28229011 -0.15789272 0.05625576 -1.53365358
[55] 0.22852874 -0.32628496 0.07379632 0.74556357 0.73908009 0.54265356
[61] -1.53506637 1.57311460 -0.56487072 -0.92757738 0.86703830 0.56370537
[67] -0.50909658 0.73342706 -2.35453685 0.25770716 0.50149391 -0.17652072
[73] 1.88524473 0.75064258 0.29060742 -1.39073984 -0.58998291 -0.66467108
[79] 0.01496553 0.80041075 1.32643324 -0.93864830 0.85146879 -1.23446837
[85] 0.15308734 0.44639216 0.18888502 -1.30287379 -1.81044318 0.58965762
[91] -0.27601160 -0.31624768 -0.01122121 1.07561100 -0.75623801 0.59161804
[97] 0.54877341 -0.85499592 -2.16482901 0.69723201
> rowMin(tmp2)
[1] 3.10656656 -0.76443307 -1.69672578 1.65467516 -0.07515522 -0.40574341
[7] 0.33947316 0.10330353 -0.29444214 -1.38510558 0.28926936 0.71256786
[13] 1.79299965 -0.17523009 -0.77098838 0.72111222 0.32403294 1.38292533
[19] -0.85303950 0.45603760 0.28463088 0.14973185 -1.09635373 -0.97702534
[25] 0.75726747 -1.47514872 0.73838537 -0.84214331 1.06105618 1.08283562
[31] -1.44395431 -0.17443853 0.25962260 0.35887720 -0.56492907 -0.55975956
[37] -1.59941391 0.03192228 0.40016224 -0.44884972 -0.97513069 -0.82077194
[43] -0.36641849 -0.33265391 -0.86480677 0.68621145 0.94845542 0.71356066
[49] 0.11222283 1.46088481 0.28229011 -0.15789272 0.05625576 -1.53365358
[55] 0.22852874 -0.32628496 0.07379632 0.74556357 0.73908009 0.54265356
[61] -1.53506637 1.57311460 -0.56487072 -0.92757738 0.86703830 0.56370537
[67] -0.50909658 0.73342706 -2.35453685 0.25770716 0.50149391 -0.17652072
[73] 1.88524473 0.75064258 0.29060742 -1.39073984 -0.58998291 -0.66467108
[79] 0.01496553 0.80041075 1.32643324 -0.93864830 0.85146879 -1.23446837
[85] 0.15308734 0.44639216 0.18888502 -1.30287379 -1.81044318 0.58965762
[91] -0.27601160 -0.31624768 -0.01122121 1.07561100 -0.75623801 0.59161804
[97] 0.54877341 -0.85499592 -2.16482901 0.69723201
>
> colMeans(tmp2)
[1] -0.02055058
> colSums(tmp2)
[1] -2.055058
> colVars(tmp2)
[1] 0.9229784
> colSd(tmp2)
[1] 0.9607176
> colMax(tmp2)
[1] 3.106567
> colMin(tmp2)
[1] -2.354537
> colMedians(tmp2)
[1] 0.08854992
> colRanges(tmp2)
[,1]
[1,] -2.354537
[2,] 3.106567
>
> 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] 0.56041840 5.15109359 1.86581747 -1.78707963 0.85575744 0.61160218
[7] 2.66791869 2.84313710 -0.44625511 -0.03119708
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.93418457
[2,] -0.46510117
[3,] -0.07563765
[4,] 0.24994434
[5,] 1.50179044
>
> rowApply(tmp,sum)
[1] 4.9751256 3.6537723 7.1121301 -3.3304538 5.2596821 -0.7870209
[7] -1.1818781 -2.7424608 -2.0734935 1.4058101
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 10 3 5 5 6 4 10 5 3
[2,] 6 9 6 10 9 2 8 7 3 9
[3,] 8 5 2 8 3 5 10 8 4 7
[4,] 1 1 5 1 10 1 1 9 9 10
[5,] 5 6 1 9 4 9 9 1 10 8
[6,] 9 7 9 6 2 7 5 2 7 1
[7,] 7 8 4 2 1 10 6 6 1 6
[8,] 10 2 10 7 7 3 2 5 8 5
[9,] 4 4 8 4 6 4 7 4 6 2
[10,] 2 3 7 3 8 8 3 3 2 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.05477733 -0.02515395 1.81035840 1.48063368 0.31653097 1.32236564
[7] 0.20944139 -0.05030579 0.47579389 0.35554264 1.51649766 2.78577568
[13] 3.57576553 -0.03359548 -1.33564673 2.69263697 -3.68570681 0.66261118
[19] 1.71250393 -1.07234137
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1191792
[2,] -1.0283689
[3,] -0.2262809
[4,] 0.6419624
[5,] 0.6770893
>
> rowApply(tmp,sum)
[1] 6.236592 -3.915286 4.392175 -5.149440 9.094890
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 2 7 3 11
[2,] 7 18 4 2 18
[3,] 9 16 11 20 8
[4,] 15 12 14 15 5
[5,] 1 9 17 10 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.6770893 0.1422951 0.19410480 0.9684797 -1.67649010 -0.5826634
[2,] -2.1191792 0.4656865 0.35808820 0.0519574 0.02199096 -0.3634586
[3,] -0.2262809 -0.7965035 0.07818125 0.7325153 1.33882471 -0.6056566
[4,] -1.0283689 -1.2957997 1.11224113 0.2082163 -0.33528774 0.8575661
[5,] 0.6419624 1.4591676 0.06774303 -0.4805351 0.96749315 2.0165782
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.9503605422 -0.7607806 0.98233882 0.9994018 0.6890154 0.3397727
[2,] -0.0093847225 0.0231031 0.08417592 1.1334655 -0.5429491 0.4145340
[3,] 0.0008875357 0.7111193 0.06740189 -1.1485575 1.0262150 2.0673781
[4,] -0.1472026009 -0.3340233 0.34887967 -1.4368601 -0.4240395 -0.7344149
[5,] 1.3155017230 0.3102757 -1.00700242 0.8080929 0.7682558 0.6985058
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.8889269 1.5963456 -0.15169802 0.9447929 -1.1870955 0.91349625
[2,] 0.3411588 -0.3483729 0.02255697 0.5441443 -0.2435976 0.07277718
[3,] -1.3548851 0.2430784 -0.24351374 1.3392089 -1.2048847 -0.03166195
[4,] 0.1847556 -0.7896482 0.01021793 -0.4977806 -0.8997588 0.22444158
[5,] 2.5158093 -0.7349983 -0.97320987 0.3622714 -0.1503703 -0.51644189
[,19] [,20]
[1,] 1.0589687 0.15065190
[2,] -1.2599474 -2.56203561
[3,] 1.4605700 0.93873821
[4,] -0.6175904 0.44501615
[5,] 1.0705030 -0.04471203
>
>
> 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 : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.198305 0.4613611 -0.5035156 1.106723 -1.451935 0.4485557 0.1585972
col8 col9 col10 col11 col12 col13 col14
row1 -0.9630753 2.008232 -2.768573 1.714599 -0.6452383 -0.5954844 -0.04386238
col15 col16 col17 col18 col19 col20
row1 1.037284 0.4872484 -0.4166716 0.2004024 1.02974 0.1469227
> tmp[,"col10"]
col10
row1 -2.7685733
row2 -1.2196451
row3 0.5691640
row4 -0.6974035
row5 2.1807870
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.1983050 0.46136111 -0.5035156 1.106723 -1.4519349 0.4485557 0.1585972
row5 -0.2148111 0.02610665 -0.6921599 -1.938588 -0.4563817 -0.6405534 1.0158015
col8 col9 col10 col11 col12 col13
row1 -0.9630753 2.0082325 -2.768573 1.7145992 -0.6452383 -0.5954844
row5 -0.3269829 0.9427249 2.180787 -0.7654615 0.2164012 -1.0742414
col14 col15 col16 col17 col18 col19 col20
row1 -0.04386238 1.037284 0.4872484 -0.4166716 0.2004024 1.0297403 0.1469227
row5 -0.28395406 1.312594 0.2942154 1.0124408 -0.5394140 -0.5706147 -1.4215821
> tmp[,c("col6","col20")]
col6 col20
row1 0.4485557 0.14692271
row2 0.3535324 0.86056019
row3 -0.2121888 -0.04661494
row4 -1.8133056 0.39441210
row5 -0.6405534 -1.42158215
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.4485557 0.1469227
row5 -0.6405534 -1.4215821
>
>
>
>
> 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 51.33828 50.52152 49.97301 48.44009 50.6658 105.853 50.70285 50.36045
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.33855 50.47421 49.81749 51.06982 51.56489 48.43355 49.96442 50.36286
col17 col18 col19 col20
row1 49.03396 49.32736 50.46206 104.0493
> tmp[,"col10"]
col10
row1 50.47421
row2 29.43173
row3 30.02287
row4 29.17295
row5 51.07528
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.33828 50.52152 49.97301 48.44009 50.66580 105.8530 50.70285 50.36045
row5 50.78569 51.99759 50.60105 50.33589 50.83848 107.2542 51.37313 49.79323
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.33855 50.47421 49.81749 51.06982 51.56489 48.43355 49.96442 50.36286
row5 51.15074 51.07528 49.25407 49.67910 51.30323 50.52905 51.59167 50.31791
col17 col18 col19 col20
row1 49.03396 49.32736 50.46206 104.0493
row5 50.78615 50.79490 49.38006 106.3101
> tmp[,c("col6","col20")]
col6 col20
row1 105.85298 104.04933
row2 76.42521 72.85849
row3 74.31382 72.31615
row4 74.25465 74.79012
row5 107.25422 106.31009
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.8530 104.0493
row5 107.2542 106.3101
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.8530 104.0493
row5 107.2542 106.3101
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.3599626
[2,] -1.1285716
[3,] -1.1376448
[4,] 1.3623430
[5,] 0.5607565
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.3379430 -1.0310149
[2,] -0.7417941 -1.5826927
[3,] 0.6258701 -0.6870828
[4,] -1.4610954 -0.2732554
[5,] 0.7475773 0.2954486
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.2593430 0.03474071
[2,] 0.5423435 0.14176725
[3,] -0.4425313 -1.02187531
[4,] 0.1198373 0.05685817
[5,] -0.3176438 1.47885101
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.259343
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.2593430
[2,] 0.5423435
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.1150104 0.1813601 0.7893191 0.3268784 0.02079055 -0.3042538 0.3834073
row1 -1.0551265 0.1343789 0.8978959 -0.1037593 1.20086531 0.7134713 0.3052312
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.1569463 -0.8894382 0.005041973 1.8546886 -0.6101713 0.9755448
row1 -0.1400564 1.0740870 -2.268415978 -0.5976732 -0.6875976 -0.3625966
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.9669279 1.005789 1.056476 -0.3403630 1.068352 0.8182408 -1.3111911
row1 1.1663554 1.306091 -1.547823 -0.2949072 -1.016150 -0.8776843 0.5621787
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.636172 0.477347 -0.4430044 -1.170802 -0.9990925 -0.219992 -0.3464966
[,8] [,9] [,10]
row2 0.5788855 0.360235 -0.02821316
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.6545218 0.1180536 1.07656 -0.9766582 -1.038037 1.790617 -0.1599597
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.9730885 -0.8419863 0.5619509 1.343338 0.9507097 -0.360928 0.3092713
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.9436051 0.7910306 -0.3331748 1.12891 -0.2989368 0.9146196
>
>
> 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: 0x57223a3c4930>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3242533cc269ea"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM324253eb38be5"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM324253e3a07bc"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32425324b66af9"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3242534917aa7e"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM324253223fbafb"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM324253bb31085"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM324253b06c49a"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3242533b5a5192"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3242531186223f"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM324253abd3879"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM324253495e4113"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32425359d544e8"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3242537dfb537f"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM3242536142e25c"
>
>
> ### 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: 0x57223deecdb0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x57223deecdb0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x57223deecdb0>
> rowMedians(tmp)
[1] 0.591461615 -0.174370580 0.144279375 0.138679427 0.137972024
[6] 0.407599053 0.061168246 0.117005560 0.114456703 -0.034281645
[11] -0.204976105 -0.147426815 -0.208724853 0.038362832 0.166474180
[16] 0.636360388 -0.050597201 -0.374645384 0.274795681 -0.089724133
[21] -0.503121399 0.034261005 0.208864355 0.516204211 0.047600665
[26] -0.258736439 0.386407954 -0.200068592 -0.202698552 0.227907635
[31] -0.354008160 -0.090894378 -0.097904390 0.164784000 0.562385147
[36] 0.402910642 -0.210492665 0.140640272 -0.121947267 -0.078706189
[41] -0.077637023 -0.588812356 0.042155862 -0.072830935 -0.366214644
[46] 0.034013984 0.089079200 0.033497269 -0.478475441 -0.613852458
[51] 0.166093459 0.487147414 0.016874503 -0.586132815 0.221599535
[56] 0.041537064 -0.359094288 0.357122260 0.220642832 0.186124033
[61] -0.478193248 -0.239821084 -0.366950800 -0.028079792 0.322023723
[66] 0.214047687 0.068710483 0.318121989 0.500717004 -0.227473823
[71] -0.519038431 0.135226904 0.300752081 0.152657865 0.457379838
[76] -0.245007932 0.466966377 -0.365127694 0.164133134 0.097768184
[81] 0.173486033 0.233182134 -0.227975854 -0.246185050 -0.210617322
[86] -0.336747049 0.267214654 -0.394163882 -0.179735281 0.356161483
[91] 0.499908142 -0.444441523 0.025971237 -0.086948012 -0.126565929
[96] 0.553276696 -0.011745777 0.336547823 -0.037325732 0.206585621
[101] 0.483227704 1.093210516 -0.102897944 0.175470941 -0.124186582
[106] 0.147589213 -0.006780796 0.339552259 -0.288784271 0.163461643
[111] 0.039310804 -0.037292956 0.069937582 0.320429308 0.637592582
[116] -0.304785581 -0.024924628 0.627852070 0.029230482 0.652856976
[121] -0.583332425 -0.110325569 0.106717869 -0.264578995 -0.072972536
[126] -0.152146234 -0.083474167 0.441318844 -0.048523370 0.217321647
[131] 0.456269897 -0.074793377 -0.131516843 0.072612617 0.421458958
[136] 0.075212406 -0.166859864 0.240091729 0.293068645 0.017804941
[141] -0.281060642 -0.252968556 0.374659447 -0.538865574 -0.204189603
[146] 0.306448586 -0.374293108 0.012580239 -0.625953163 0.140954144
[151] 0.110413457 0.184024116 -0.645073826 -0.270568528 0.512415423
[156] 0.109220513 0.236528022 0.268324282 0.214197591 0.012741257
[161] 0.108796589 0.268802105 0.132957627 0.065744543 -0.569762081
[166] 0.078456172 0.230038786 -0.086189235 -0.299704123 0.308291875
[171] 0.571094440 -0.177713349 -0.182517200 -0.400335151 -0.544667826
[176] 0.368808331 -0.126786143 0.409266409 0.119346151 -0.042652265
[181] -0.081701772 0.047795885 0.179484669 0.155986040 0.504705324
[186] 0.022838724 -0.171409187 -0.667894558 0.240406397 0.328421535
[191] 0.331509400 -0.391778269 -0.109405387 0.043053268 0.358367368
[196] -0.348173329 -0.310359506 -0.166339807 -0.249646379 0.307504668
[201] 0.303310967 0.194925807 -0.129694439 0.128074359 0.816698189
[206] 0.286229654 -0.156215289 0.099665122 -0.311250034 0.201553516
[211] -0.396439964 0.718003550 -0.709037523 -0.229564258 0.383246960
[216] -0.184944755 0.111012061 0.058413509 -0.141558198 0.019567220
[221] -0.266395159 -0.108990978 0.524307956 -0.655722926 0.371871856
[226] 0.226305190 0.312457623 0.248748350 0.474435075 0.199680339
>
> proc.time()
user system elapsed
1.296 1.497 2.779
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
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: 0x5fed87110ff0>
> .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: 0x5fed87110ff0>
> .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: 0x5fed87110ff0>
> .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: 0x5fed87110ff0>
> 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: 0x5fed86dbc710>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed86dbc710>
> .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: 0x5fed86dbc710>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed86dbc710>
> .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: 0x5fed86dbc710>
> 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: 0x5fed871203f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed871203f0>
> .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: 0x5fed871203f0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5fed871203f0>
> .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: 0x5fed871203f0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5fed871203f0>
> .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: 0x5fed871203f0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5fed871203f0>
> .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: 0x5fed871203f0>
> 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: 0x5fed868578c0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5fed868578c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed868578c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed868578c0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3242cc1fcce405" "BufferedMatrixFile3242cc67ff3aa5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3242cc1fcce405" "BufferedMatrixFile3242cc67ff3aa5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed86583e30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed86583e30>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5fed86583e30>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5fed86583e30>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5fed86583e30>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5fed86583e30>
> .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: 0x5fed876df790>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fed876df790>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5fed876df790>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5fed876df790>
> 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: 0x5fed86aca860>
> .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: 0x5fed86aca860>
> rm(P)
>
> proc.time()
user system elapsed
0.247 0.047 0.282
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
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Platform: x86_64-pc-linux-gnu
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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
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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
0.245 0.042 0.274