Ben Bolstad
| Snapshot Date: 2026-05-19 13:40 -0400 (Tue, 19 May 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_23 |
| git_last_commit: 9d72964 |
| git_last_commit_date: 2026-04-28 08:32:08 -0400 (Tue, 28 Apr 2026) |
| Back to Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-05-20 11:32 -0400 (Wed, 20 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4995 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 262/2418 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.76.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.76.0 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.76.0.tar.gz |
| StartedAt: 2026-05-19 22:05:04 -0400 (Tue, 19 May 2026) |
| EndedAt: 2026-05-19 22:05:29 -0400 (Tue, 19 May 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_1.76.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-20 02:05:05 UTC
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.76.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ...* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.76.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.23-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.23-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.23-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.257 0.051 0.297
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 480233 25.7 1053308 56.3 637571 34.1
Vcells 887253 6.8 8388608 64.0 2083896 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue May 19 22:05:20 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue May 19 22:05:20 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: 0x64ba83343690>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue May 19 22:05:21 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue May 19 22:05:21 2026"
>
> ColMode(tmp2)
<pointer: 0x64ba83343690>
>
>
>
> ### 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,] 99.3194841 -0.9027296 -0.71930556 0.62965494
[2,] 0.8285939 -0.3040798 0.05802662 -0.33345151
[3,] 0.8710487 -0.4382926 -1.74925730 -0.07605686
[4,] -0.2770833 -0.7523063 1.25404284 -0.24839761
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.3194841 0.9027296 0.71930556 0.62965494
[2,] 0.8285939 0.3040798 0.05802662 0.33345151
[3,] 0.8710487 0.4382926 1.74925730 0.07605686
[4,] 0.2770833 0.7523063 1.25404284 0.24839761
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9659161 0.9501209 0.8481188 0.7935080
[2,] 0.9102714 0.5514343 0.2408872 0.5774526
[3,] 0.9332999 0.6620367 1.3225949 0.2757841
[4,] 0.5263870 0.8673559 1.1198405 0.4983950
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 223.97865 35.40394 34.20049 33.56473
[2,] 34.93131 30.81842 27.46690 31.10798
[3,] 35.20405 32.05866 39.97521 27.83390
[4,] 30.54095 34.42587 37.45245 30.23235
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x64ba82532ff0>
> exp(tmp5)
<pointer: 0x64ba82532ff0>
> log(tmp5,2)
<pointer: 0x64ba82532ff0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.1822
> Min(tmp5)
[1] 52.88073
> mean(tmp5)
[1] 72.14198
> Sum(tmp5)
[1] 14428.4
> Var(tmp5)
[1] 856.2696
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.89501 70.78784 68.82730 70.27051 68.54613 70.34649 70.80869 70.60483
[9] 71.08494 70.24805
> rowSums(tmp5)
[1] 1797.900 1415.757 1376.546 1405.410 1370.923 1406.930 1416.174 1412.097
[9] 1421.699 1404.961
> rowVars(tmp5)
[1] 7893.40256 108.96131 59.52105 77.64113 34.31001 51.95592
[7] 87.11768 58.26619 91.25818 130.60845
> rowSd(tmp5)
[1] 88.844823 10.438454 7.714989 8.811420 5.857474 7.208045 9.333685
[8] 7.633229 9.552915 11.428405
> rowMax(tmp5)
[1] 466.18220 93.60462 83.20315 94.18467 78.99222 85.01414 81.34755
[8] 83.25173 87.15812 90.10233
> rowMin(tmp5)
[1] 56.77238 57.16875 54.81359 55.24448 58.99342 58.76246 54.56547 58.86792
[9] 52.88073 54.43503
>
> colMeans(tmp5)
[1] 109.24718 72.84570 69.80047 66.07111 67.76654 70.17003 65.88931
[8] 65.51108 66.40297 72.19598 73.06315 71.29475 71.53921 69.69382
[15] 71.97108 71.39870 75.15242 68.42203 70.71306 73.69096
> colSums(tmp5)
[1] 1092.4718 728.4570 698.0047 660.7111 677.6654 701.7003 658.8931
[8] 655.1108 664.0297 721.9598 730.6315 712.9475 715.3921 696.9382
[15] 719.7108 713.9870 751.5242 684.2203 707.1306 736.9096
> colVars(tmp5)
[1] 15782.02695 34.45762 85.28902 80.86613 58.41144 93.67471
[7] 79.80040 50.79842 61.15043 42.76423 58.84670 77.94139
[13] 115.56093 51.05700 140.47495 88.77694 92.70537 53.72893
[19] 42.46271 70.59686
> colSd(tmp5)
[1] 125.626538 5.870061 9.235206 8.992560 7.642738 9.678569
[7] 8.933107 7.127301 7.819874 6.539436 7.671160 8.828442
[13] 10.749927 7.145418 11.852213 9.422151 9.628363 7.330002
[19] 6.516342 8.402194
> colMax(tmp5)
[1] 466.18220 81.89473 83.20315 85.01414 83.25173 90.10233 76.45275
[8] 75.58339 79.88865 84.02603 89.26232 83.65518 93.60462 78.99222
[15] 91.96453 82.54755 94.18467 80.56122 80.57912 87.15812
> colMin(tmp5)
[1] 54.56547 64.14451 57.16875 57.80586 58.27659 58.81203 53.38405 54.69590
[9] 52.88073 62.82875 60.16340 58.60142 57.96505 56.96733 54.43503 54.66379
[17] 66.30206 56.21353 61.53753 61.60079
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.89501 70.78784 68.82730 NA 68.54613 70.34649 70.80869 70.60483
[9] 71.08494 70.24805
> rowSums(tmp5)
[1] 1797.900 1415.757 1376.546 NA 1370.923 1406.930 1416.174 1412.097
[9] 1421.699 1404.961
> rowVars(tmp5)
[1] 7893.40256 108.96131 59.52105 81.49361 34.31001 51.95592
[7] 87.11768 58.26619 91.25818 130.60845
> rowSd(tmp5)
[1] 88.844823 10.438454 7.714989 9.027381 5.857474 7.208045 9.333685
[8] 7.633229 9.552915 11.428405
> rowMax(tmp5)
[1] 466.18220 93.60462 83.20315 NA 78.99222 85.01414 81.34755
[8] 83.25173 87.15812 90.10233
> rowMin(tmp5)
[1] 56.77238 57.16875 54.81359 NA 58.99342 58.76246 54.56547 58.86792
[9] 52.88073 54.43503
>
> colMeans(tmp5)
[1] 109.24718 72.84570 69.80047 66.07111 67.76654 70.17003 65.88931
[8] 65.51108 66.40297 72.19598 73.06315 71.29475 NA 69.69382
[15] 71.97108 71.39870 75.15242 68.42203 70.71306 73.69096
> colSums(tmp5)
[1] 1092.4718 728.4570 698.0047 660.7111 677.6654 701.7003 658.8931
[8] 655.1108 664.0297 721.9598 730.6315 712.9475 NA 696.9382
[15] 719.7108 713.9870 751.5242 684.2203 707.1306 736.9096
> colVars(tmp5)
[1] 15782.02695 34.45762 85.28902 80.86613 58.41144 93.67471
[7] 79.80040 50.79842 61.15043 42.76423 58.84670 77.94139
[13] NA 51.05700 140.47495 88.77694 92.70537 53.72893
[19] 42.46271 70.59686
> colSd(tmp5)
[1] 125.626538 5.870061 9.235206 8.992560 7.642738 9.678569
[7] 8.933107 7.127301 7.819874 6.539436 7.671160 8.828442
[13] NA 7.145418 11.852213 9.422151 9.628363 7.330002
[19] 6.516342 8.402194
> colMax(tmp5)
[1] 466.18220 81.89473 83.20315 85.01414 83.25173 90.10233 76.45275
[8] 75.58339 79.88865 84.02603 89.26232 83.65518 NA 78.99222
[15] 91.96453 82.54755 94.18467 80.56122 80.57912 87.15812
> colMin(tmp5)
[1] 54.56547 64.14451 57.16875 57.80586 58.27659 58.81203 53.38405 54.69590
[9] 52.88073 62.82875 60.16340 58.60142 NA 56.96733 54.43503 54.66379
[17] 66.30206 56.21353 61.53753 61.60079
>
> Max(tmp5,na.rm=TRUE)
[1] 466.1822
> Min(tmp5,na.rm=TRUE)
[1] 52.88073
> mean(tmp5,na.rm=TRUE)
[1] 72.16549
> Sum(tmp5,na.rm=TRUE)
[1] 14360.93
> Var(tmp5,na.rm=TRUE)
[1] 860.4831
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.89501 70.78784 68.82730 70.41827 68.54613 70.34649 70.80869 70.60483
[9] 71.08494 70.24805
> rowSums(tmp5,na.rm=TRUE)
[1] 1797.900 1415.757 1376.546 1337.947 1370.923 1406.930 1416.174 1412.097
[9] 1421.699 1404.961
> rowVars(tmp5,na.rm=TRUE)
[1] 7893.40256 108.96131 59.52105 81.49361 34.31001 51.95592
[7] 87.11768 58.26619 91.25818 130.60845
> rowSd(tmp5,na.rm=TRUE)
[1] 88.844823 10.438454 7.714989 9.027381 5.857474 7.208045 9.333685
[8] 7.633229 9.552915 11.428405
> rowMax(tmp5,na.rm=TRUE)
[1] 466.18220 93.60462 83.20315 94.18467 78.99222 85.01414 81.34755
[8] 83.25173 87.15812 90.10233
> rowMin(tmp5,na.rm=TRUE)
[1] 56.77238 57.16875 54.81359 55.24448 58.99342 58.76246 54.56547 58.86792
[9] 52.88073 54.43503
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.24718 72.84570 69.80047 66.07111 67.76654 70.17003 65.88931
[8] 65.51108 66.40297 72.19598 73.06315 71.29475 71.99211 69.69382
[15] 71.97108 71.39870 75.15242 68.42203 70.71306 73.69096
> colSums(tmp5,na.rm=TRUE)
[1] 1092.4718 728.4570 698.0047 660.7111 677.6654 701.7003 658.8931
[8] 655.1108 664.0297 721.9598 730.6315 712.9475 647.9290 696.9382
[15] 719.7108 713.9870 751.5242 684.2203 707.1306 736.9096
> colVars(tmp5,na.rm=TRUE)
[1] 15782.02695 34.45762 85.28902 80.86613 58.41144 93.67471
[7] 79.80040 50.79842 61.15043 42.76423 58.84670 77.94139
[13] 127.69845 51.05700 140.47495 88.77694 92.70537 53.72893
[19] 42.46271 70.59686
> colSd(tmp5,na.rm=TRUE)
[1] 125.626538 5.870061 9.235206 8.992560 7.642738 9.678569
[7] 8.933107 7.127301 7.819874 6.539436 7.671160 8.828442
[13] 11.300374 7.145418 11.852213 9.422151 9.628363 7.330002
[19] 6.516342 8.402194
> colMax(tmp5,na.rm=TRUE)
[1] 466.18220 81.89473 83.20315 85.01414 83.25173 90.10233 76.45275
[8] 75.58339 79.88865 84.02603 89.26232 83.65518 93.60462 78.99222
[15] 91.96453 82.54755 94.18467 80.56122 80.57912 87.15812
> colMin(tmp5,na.rm=TRUE)
[1] 54.56547 64.14451 57.16875 57.80586 58.27659 58.81203 53.38405 54.69590
[9] 52.88073 62.82875 60.16340 58.60142 57.96505 56.96733 54.43503 54.66379
[17] 66.30206 56.21353 61.53753 61.60079
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.89501 70.78784 68.82730 NaN 68.54613 70.34649 70.80869 70.60483
[9] 71.08494 70.24805
> rowSums(tmp5,na.rm=TRUE)
[1] 1797.900 1415.757 1376.546 0.000 1370.923 1406.930 1416.174 1412.097
[9] 1421.699 1404.961
> rowVars(tmp5,na.rm=TRUE)
[1] 7893.40256 108.96131 59.52105 NA 34.31001 51.95592
[7] 87.11768 58.26619 91.25818 130.60845
> rowSd(tmp5,na.rm=TRUE)
[1] 88.844823 10.438454 7.714989 NA 5.857474 7.208045 9.333685
[8] 7.633229 9.552915 11.428405
> rowMax(tmp5,na.rm=TRUE)
[1] 466.18220 93.60462 83.20315 NA 78.99222 85.01414 81.34755
[8] 83.25173 87.15812 90.10233
> rowMin(tmp5,na.rm=TRUE)
[1] 56.77238 57.16875 54.81359 NA 58.99342 58.76246 54.56547 58.86792
[9] 52.88073 54.43503
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.32275 72.97823 68.89470 66.42071 67.85812 69.01805 67.07207
[8] 65.01206 66.75756 70.88153 73.35629 71.52867 NaN 69.15096
[15] 72.44084 71.24676 73.03773 68.52022 71.53754 74.97144
> colSums(tmp5,na.rm=TRUE)
[1] 1028.9048 656.8041 620.0523 597.7864 610.7231 621.1624 603.6486
[8] 585.1086 600.8181 637.9338 660.2066 643.7581 0.0000 622.3586
[15] 651.9676 641.2209 657.3396 616.6820 643.8378 674.7430
> colVars(tmp5,na.rm=TRUE)
[1] 17464.96378 38.56722 86.72051 89.59939 65.61852 90.45470
[7] 74.03762 54.34680 67.37971 28.67225 65.23582 87.06845
[13] NA 54.12378 155.55173 99.61434 53.98431 60.33657
[19] 40.12318 60.97570
> colSd(tmp5,na.rm=TRUE)
[1] 132.155075 6.210251 9.312385 9.465695 8.100526 9.510767
[7] 8.604512 7.372028 8.208514 5.354648 8.076869 9.331048
[13] NA 7.356887 12.472038 9.980698 7.347402 7.767662
[19] 6.334286 7.808694
> colMax(tmp5,na.rm=TRUE)
[1] 466.18220 81.89473 83.20315 85.01414 83.25173 90.10233 76.45275
[8] 75.58339 79.88865 80.23931 89.26232 83.65518 -Inf 78.99222
[15] 91.96453 82.54755 89.62538 80.56122 80.57912 87.15812
> colMin(tmp5,na.rm=TRUE)
[1] 54.56547 64.14451 57.16875 57.80586 58.27659 58.81203 53.38405 54.69590
[9] 52.88073 62.82875 60.16340 58.60142 Inf 56.96733 54.43503 54.66379
[17] 66.30206 56.21353 61.53753 61.60079
>
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col <- 1
> cat(which.row," ",which.col,"\n")
3 1
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> rowVars(tmp5,na.rm=TRUE)
[1] 180.5926 268.6114 425.0242 363.9084 313.0108 202.6692 218.6687 313.4548
[9] 171.4150 288.6275
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 180.5926 268.6114 425.0242 363.9084 313.0108 202.6692 218.6687 313.4548
[9] 171.4150 288.6275
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 5.684342e-14 -2.557954e-13 7.105427e-14 1.421085e-14 1.136868e-13
[6] 5.684342e-14 0.000000e+00 0.000000e+00 2.842171e-14 2.842171e-13
[11] 8.526513e-14 2.842171e-14 -5.684342e-14 2.842171e-14 -2.842171e-14
[16] -8.526513e-14 -5.684342e-14 -5.684342e-14 0.000000e+00 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)
+ }
1 16
5 14
2 16
8 5
10 6
4 17
8 15
10 1
6 4
10 12
4 18
9 10
4 10
7 5
10 19
1 6
7 19
1 16
3 9
2 17
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] 2.267322
> Min(tmp)
[1] -2.400734
> mean(tmp)
[1] -0.04921274
> Sum(tmp)
[1] -4.921274
> Var(tmp)
[1] 0.9915006
>
> rowMeans(tmp)
[1] -0.04921274
> rowSums(tmp)
[1] -4.921274
> rowVars(tmp)
[1] 0.9915006
> rowSd(tmp)
[1] 0.9957412
> rowMax(tmp)
[1] 2.267322
> rowMin(tmp)
[1] -2.400734
>
> colMeans(tmp)
[1] -0.83179686 -0.54055386 -0.59707056 1.07983652 0.09621516 1.15021207
[7] -0.19699199 0.53954191 0.10346068 0.55968525 0.92754390 0.09007383
[13] -0.16536371 1.24664015 -2.02302389 0.98310043 -0.93041310 0.85581672
[19] -0.44629299 -2.07208944 0.02996951 0.92300508 0.48210361 0.19899701
[25] -0.61637773 0.21563184 1.85926704 -2.12894541 1.02656437 0.33948439
[31] -0.31017569 -0.28038798 -0.47426164 -0.52625369 0.43350929 -0.98416864
[37] -0.07313596 1.14103942 1.41507928 0.09302471 -0.06950660 -0.76532256
[43] -0.08463067 -0.41421564 0.99946222 -0.23031589 0.17482209 1.23910002
[49] -0.50697145 0.32414079 0.45433279 -0.78153191 1.21314602 -2.08971354
[55] -0.03558540 2.26732216 0.41681804 -0.58488631 -1.71638398 -1.32899227
[61] -0.20021034 -1.28817998 1.27411275 -0.81693321 -0.74851390 1.15397164
[67] 0.78328223 0.04405355 0.88427948 0.97678886 -0.50537961 -0.78528250
[73] -2.40073373 0.09906508 0.18873473 1.00680945 -2.01092941 0.16770588
[79] -0.66270798 0.87044045 -0.47708282 -1.88283254 -1.27638673 0.55741600
[85] -0.05271661 -1.64784185 -0.74001952 0.39610624 0.88836350 -0.20173937
[91] -0.49745030 0.52501160 -0.01834041 -0.22830268 1.88978491 0.73867806
[97] 1.41179282 -0.07991884 -2.03483996 -1.29491582
> colSums(tmp)
[1] -0.83179686 -0.54055386 -0.59707056 1.07983652 0.09621516 1.15021207
[7] -0.19699199 0.53954191 0.10346068 0.55968525 0.92754390 0.09007383
[13] -0.16536371 1.24664015 -2.02302389 0.98310043 -0.93041310 0.85581672
[19] -0.44629299 -2.07208944 0.02996951 0.92300508 0.48210361 0.19899701
[25] -0.61637773 0.21563184 1.85926704 -2.12894541 1.02656437 0.33948439
[31] -0.31017569 -0.28038798 -0.47426164 -0.52625369 0.43350929 -0.98416864
[37] -0.07313596 1.14103942 1.41507928 0.09302471 -0.06950660 -0.76532256
[43] -0.08463067 -0.41421564 0.99946222 -0.23031589 0.17482209 1.23910002
[49] -0.50697145 0.32414079 0.45433279 -0.78153191 1.21314602 -2.08971354
[55] -0.03558540 2.26732216 0.41681804 -0.58488631 -1.71638398 -1.32899227
[61] -0.20021034 -1.28817998 1.27411275 -0.81693321 -0.74851390 1.15397164
[67] 0.78328223 0.04405355 0.88427948 0.97678886 -0.50537961 -0.78528250
[73] -2.40073373 0.09906508 0.18873473 1.00680945 -2.01092941 0.16770588
[79] -0.66270798 0.87044045 -0.47708282 -1.88283254 -1.27638673 0.55741600
[85] -0.05271661 -1.64784185 -0.74001952 0.39610624 0.88836350 -0.20173937
[91] -0.49745030 0.52501160 -0.01834041 -0.22830268 1.88978491 0.73867806
[97] 1.41179282 -0.07991884 -2.03483996 -1.29491582
> 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] -0.83179686 -0.54055386 -0.59707056 1.07983652 0.09621516 1.15021207
[7] -0.19699199 0.53954191 0.10346068 0.55968525 0.92754390 0.09007383
[13] -0.16536371 1.24664015 -2.02302389 0.98310043 -0.93041310 0.85581672
[19] -0.44629299 -2.07208944 0.02996951 0.92300508 0.48210361 0.19899701
[25] -0.61637773 0.21563184 1.85926704 -2.12894541 1.02656437 0.33948439
[31] -0.31017569 -0.28038798 -0.47426164 -0.52625369 0.43350929 -0.98416864
[37] -0.07313596 1.14103942 1.41507928 0.09302471 -0.06950660 -0.76532256
[43] -0.08463067 -0.41421564 0.99946222 -0.23031589 0.17482209 1.23910002
[49] -0.50697145 0.32414079 0.45433279 -0.78153191 1.21314602 -2.08971354
[55] -0.03558540 2.26732216 0.41681804 -0.58488631 -1.71638398 -1.32899227
[61] -0.20021034 -1.28817998 1.27411275 -0.81693321 -0.74851390 1.15397164
[67] 0.78328223 0.04405355 0.88427948 0.97678886 -0.50537961 -0.78528250
[73] -2.40073373 0.09906508 0.18873473 1.00680945 -2.01092941 0.16770588
[79] -0.66270798 0.87044045 -0.47708282 -1.88283254 -1.27638673 0.55741600
[85] -0.05271661 -1.64784185 -0.74001952 0.39610624 0.88836350 -0.20173937
[91] -0.49745030 0.52501160 -0.01834041 -0.22830268 1.88978491 0.73867806
[97] 1.41179282 -0.07991884 -2.03483996 -1.29491582
> colMin(tmp)
[1] -0.83179686 -0.54055386 -0.59707056 1.07983652 0.09621516 1.15021207
[7] -0.19699199 0.53954191 0.10346068 0.55968525 0.92754390 0.09007383
[13] -0.16536371 1.24664015 -2.02302389 0.98310043 -0.93041310 0.85581672
[19] -0.44629299 -2.07208944 0.02996951 0.92300508 0.48210361 0.19899701
[25] -0.61637773 0.21563184 1.85926704 -2.12894541 1.02656437 0.33948439
[31] -0.31017569 -0.28038798 -0.47426164 -0.52625369 0.43350929 -0.98416864
[37] -0.07313596 1.14103942 1.41507928 0.09302471 -0.06950660 -0.76532256
[43] -0.08463067 -0.41421564 0.99946222 -0.23031589 0.17482209 1.23910002
[49] -0.50697145 0.32414079 0.45433279 -0.78153191 1.21314602 -2.08971354
[55] -0.03558540 2.26732216 0.41681804 -0.58488631 -1.71638398 -1.32899227
[61] -0.20021034 -1.28817998 1.27411275 -0.81693321 -0.74851390 1.15397164
[67] 0.78328223 0.04405355 0.88427948 0.97678886 -0.50537961 -0.78528250
[73] -2.40073373 0.09906508 0.18873473 1.00680945 -2.01092941 0.16770588
[79] -0.66270798 0.87044045 -0.47708282 -1.88283254 -1.27638673 0.55741600
[85] -0.05271661 -1.64784185 -0.74001952 0.39610624 0.88836350 -0.20173937
[91] -0.49745030 0.52501160 -0.01834041 -0.22830268 1.88978491 0.73867806
[97] 1.41179282 -0.07991884 -2.03483996 -1.29491582
> colMedians(tmp)
[1] -0.83179686 -0.54055386 -0.59707056 1.07983652 0.09621516 1.15021207
[7] -0.19699199 0.53954191 0.10346068 0.55968525 0.92754390 0.09007383
[13] -0.16536371 1.24664015 -2.02302389 0.98310043 -0.93041310 0.85581672
[19] -0.44629299 -2.07208944 0.02996951 0.92300508 0.48210361 0.19899701
[25] -0.61637773 0.21563184 1.85926704 -2.12894541 1.02656437 0.33948439
[31] -0.31017569 -0.28038798 -0.47426164 -0.52625369 0.43350929 -0.98416864
[37] -0.07313596 1.14103942 1.41507928 0.09302471 -0.06950660 -0.76532256
[43] -0.08463067 -0.41421564 0.99946222 -0.23031589 0.17482209 1.23910002
[49] -0.50697145 0.32414079 0.45433279 -0.78153191 1.21314602 -2.08971354
[55] -0.03558540 2.26732216 0.41681804 -0.58488631 -1.71638398 -1.32899227
[61] -0.20021034 -1.28817998 1.27411275 -0.81693321 -0.74851390 1.15397164
[67] 0.78328223 0.04405355 0.88427948 0.97678886 -0.50537961 -0.78528250
[73] -2.40073373 0.09906508 0.18873473 1.00680945 -2.01092941 0.16770588
[79] -0.66270798 0.87044045 -0.47708282 -1.88283254 -1.27638673 0.55741600
[85] -0.05271661 -1.64784185 -0.74001952 0.39610624 0.88836350 -0.20173937
[91] -0.49745030 0.52501160 -0.01834041 -0.22830268 1.88978491 0.73867806
[97] 1.41179282 -0.07991884 -2.03483996 -1.29491582
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.8317969 -0.5405539 -0.5970706 1.079837 0.09621516 1.150212 -0.196992
[2,] -0.8317969 -0.5405539 -0.5970706 1.079837 0.09621516 1.150212 -0.196992
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.5395419 0.1034607 0.5596853 0.9275439 0.09007383 -0.1653637 1.24664
[2,] 0.5395419 0.1034607 0.5596853 0.9275439 0.09007383 -0.1653637 1.24664
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -2.023024 0.9831004 -0.9304131 0.8558167 -0.446293 -2.072089 0.02996951
[2,] -2.023024 0.9831004 -0.9304131 0.8558167 -0.446293 -2.072089 0.02996951
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.9230051 0.4821036 0.198997 -0.6163777 0.2156318 1.859267 -2.128945
[2,] 0.9230051 0.4821036 0.198997 -0.6163777 0.2156318 1.859267 -2.128945
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.026564 0.3394844 -0.3101757 -0.280388 -0.4742616 -0.5262537 0.4335093
[2,] 1.026564 0.3394844 -0.3101757 -0.280388 -0.4742616 -0.5262537 0.4335093
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.9841686 -0.07313596 1.141039 1.415079 0.09302471 -0.0695066 -0.7653226
[2,] -0.9841686 -0.07313596 1.141039 1.415079 0.09302471 -0.0695066 -0.7653226
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.08463067 -0.4142156 0.9994622 -0.2303159 0.1748221 1.2391 -0.5069715
[2,] -0.08463067 -0.4142156 0.9994622 -0.2303159 0.1748221 1.2391 -0.5069715
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3241408 0.4543328 -0.7815319 1.213146 -2.089714 -0.0355854 2.267322
[2,] 0.3241408 0.4543328 -0.7815319 1.213146 -2.089714 -0.0355854 2.267322
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.416818 -0.5848863 -1.716384 -1.328992 -0.2002103 -1.28818 1.274113
[2,] 0.416818 -0.5848863 -1.716384 -1.328992 -0.2002103 -1.28818 1.274113
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.8169332 -0.7485139 1.153972 0.7832822 0.04405355 0.8842795 0.9767889
[2,] -0.8169332 -0.7485139 1.153972 0.7832822 0.04405355 0.8842795 0.9767889
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5053796 -0.7852825 -2.400734 0.09906508 0.1887347 1.006809 -2.010929
[2,] -0.5053796 -0.7852825 -2.400734 0.09906508 0.1887347 1.006809 -2.010929
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.1677059 -0.662708 0.8704405 -0.4770828 -1.882833 -1.276387 0.557416
[2,] 0.1677059 -0.662708 0.8704405 -0.4770828 -1.882833 -1.276387 0.557416
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.05271661 -1.647842 -0.7400195 0.3961062 0.8883635 -0.2017394 -0.4974503
[2,] -0.05271661 -1.647842 -0.7400195 0.3961062 0.8883635 -0.2017394 -0.4974503
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.5250116 -0.01834041 -0.2283027 1.889785 0.7386781 1.411793 -0.07991884
[2,] 0.5250116 -0.01834041 -0.2283027 1.889785 0.7386781 1.411793 -0.07991884
[,99] [,100]
[1,] -2.03484 -1.294916
[2,] -2.03484 -1.294916
>
>
> Max(tmp2)
[1] 3.04527
> Min(tmp2)
[1] -3.807674
> mean(tmp2)
[1] 0.008180308
> Sum(tmp2)
[1] 0.8180308
> Var(tmp2)
[1] 1.092559
>
> rowMeans(tmp2)
[1] 1.012579764 -0.347497701 -0.393723938 -0.897277349 -0.139994198
[6] -0.698247902 1.333535698 2.050503723 -0.633955059 0.160058774
[11] 1.590558001 -0.370503548 -0.696535639 -0.072553936 -0.843052379
[16] -1.470491911 -1.059720453 -0.447091212 -0.400947866 -0.787052886
[21] 1.181344334 0.469318870 1.917068006 0.477336508 -1.362253340
[26] -0.958429505 1.129214315 3.045269905 0.573687285 -0.519859879
[31] 1.078093629 0.831923091 -0.266535597 -1.379910563 0.782174411
[36] -0.130663796 -0.160689312 -0.960599801 -0.390446870 1.242946053
[41] -0.244244572 -3.807673737 1.039780011 -1.319837349 -1.201639545
[46] -0.271884507 -0.356330013 0.204606122 0.255187298 -0.266529492
[51] 1.000285022 -0.610594612 1.106218748 0.297758747 -0.424333836
[56] 1.181807832 0.485934554 1.701367958 -0.170890425 -0.184381720
[61] 1.310466733 0.253267835 -0.504501469 -0.839337614 -1.328144570
[66] -0.941774093 -0.784152881 -0.663408639 1.825711293 -0.911698544
[71] 1.621809579 -1.291670225 -1.259154338 -1.058915479 0.490760808
[76] -0.250745610 0.018221423 1.354650857 0.420597108 -0.437327080
[81] -0.635858320 -0.685790359 -0.432248607 0.684575939 1.745075603
[86] 0.810439209 0.991188164 0.233640477 -0.992031987 0.527198542
[91] 0.008554408 0.247069193 -2.396739522 0.554534250 -0.844398427
[96] 0.429432762 1.700589034 -0.367941744 -0.022487361 0.336390291
> rowSums(tmp2)
[1] 1.012579764 -0.347497701 -0.393723938 -0.897277349 -0.139994198
[6] -0.698247902 1.333535698 2.050503723 -0.633955059 0.160058774
[11] 1.590558001 -0.370503548 -0.696535639 -0.072553936 -0.843052379
[16] -1.470491911 -1.059720453 -0.447091212 -0.400947866 -0.787052886
[21] 1.181344334 0.469318870 1.917068006 0.477336508 -1.362253340
[26] -0.958429505 1.129214315 3.045269905 0.573687285 -0.519859879
[31] 1.078093629 0.831923091 -0.266535597 -1.379910563 0.782174411
[36] -0.130663796 -0.160689312 -0.960599801 -0.390446870 1.242946053
[41] -0.244244572 -3.807673737 1.039780011 -1.319837349 -1.201639545
[46] -0.271884507 -0.356330013 0.204606122 0.255187298 -0.266529492
[51] 1.000285022 -0.610594612 1.106218748 0.297758747 -0.424333836
[56] 1.181807832 0.485934554 1.701367958 -0.170890425 -0.184381720
[61] 1.310466733 0.253267835 -0.504501469 -0.839337614 -1.328144570
[66] -0.941774093 -0.784152881 -0.663408639 1.825711293 -0.911698544
[71] 1.621809579 -1.291670225 -1.259154338 -1.058915479 0.490760808
[76] -0.250745610 0.018221423 1.354650857 0.420597108 -0.437327080
[81] -0.635858320 -0.685790359 -0.432248607 0.684575939 1.745075603
[86] 0.810439209 0.991188164 0.233640477 -0.992031987 0.527198542
[91] 0.008554408 0.247069193 -2.396739522 0.554534250 -0.844398427
[96] 0.429432762 1.700589034 -0.367941744 -0.022487361 0.336390291
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.012579764 -0.347497701 -0.393723938 -0.897277349 -0.139994198
[6] -0.698247902 1.333535698 2.050503723 -0.633955059 0.160058774
[11] 1.590558001 -0.370503548 -0.696535639 -0.072553936 -0.843052379
[16] -1.470491911 -1.059720453 -0.447091212 -0.400947866 -0.787052886
[21] 1.181344334 0.469318870 1.917068006 0.477336508 -1.362253340
[26] -0.958429505 1.129214315 3.045269905 0.573687285 -0.519859879
[31] 1.078093629 0.831923091 -0.266535597 -1.379910563 0.782174411
[36] -0.130663796 -0.160689312 -0.960599801 -0.390446870 1.242946053
[41] -0.244244572 -3.807673737 1.039780011 -1.319837349 -1.201639545
[46] -0.271884507 -0.356330013 0.204606122 0.255187298 -0.266529492
[51] 1.000285022 -0.610594612 1.106218748 0.297758747 -0.424333836
[56] 1.181807832 0.485934554 1.701367958 -0.170890425 -0.184381720
[61] 1.310466733 0.253267835 -0.504501469 -0.839337614 -1.328144570
[66] -0.941774093 -0.784152881 -0.663408639 1.825711293 -0.911698544
[71] 1.621809579 -1.291670225 -1.259154338 -1.058915479 0.490760808
[76] -0.250745610 0.018221423 1.354650857 0.420597108 -0.437327080
[81] -0.635858320 -0.685790359 -0.432248607 0.684575939 1.745075603
[86] 0.810439209 0.991188164 0.233640477 -0.992031987 0.527198542
[91] 0.008554408 0.247069193 -2.396739522 0.554534250 -0.844398427
[96] 0.429432762 1.700589034 -0.367941744 -0.022487361 0.336390291
> rowMin(tmp2)
[1] 1.012579764 -0.347497701 -0.393723938 -0.897277349 -0.139994198
[6] -0.698247902 1.333535698 2.050503723 -0.633955059 0.160058774
[11] 1.590558001 -0.370503548 -0.696535639 -0.072553936 -0.843052379
[16] -1.470491911 -1.059720453 -0.447091212 -0.400947866 -0.787052886
[21] 1.181344334 0.469318870 1.917068006 0.477336508 -1.362253340
[26] -0.958429505 1.129214315 3.045269905 0.573687285 -0.519859879
[31] 1.078093629 0.831923091 -0.266535597 -1.379910563 0.782174411
[36] -0.130663796 -0.160689312 -0.960599801 -0.390446870 1.242946053
[41] -0.244244572 -3.807673737 1.039780011 -1.319837349 -1.201639545
[46] -0.271884507 -0.356330013 0.204606122 0.255187298 -0.266529492
[51] 1.000285022 -0.610594612 1.106218748 0.297758747 -0.424333836
[56] 1.181807832 0.485934554 1.701367958 -0.170890425 -0.184381720
[61] 1.310466733 0.253267835 -0.504501469 -0.839337614 -1.328144570
[66] -0.941774093 -0.784152881 -0.663408639 1.825711293 -0.911698544
[71] 1.621809579 -1.291670225 -1.259154338 -1.058915479 0.490760808
[76] -0.250745610 0.018221423 1.354650857 0.420597108 -0.437327080
[81] -0.635858320 -0.685790359 -0.432248607 0.684575939 1.745075603
[86] 0.810439209 0.991188164 0.233640477 -0.992031987 0.527198542
[91] 0.008554408 0.247069193 -2.396739522 0.554534250 -0.844398427
[96] 0.429432762 1.700589034 -0.367941744 -0.022487361 0.336390291
>
> colMeans(tmp2)
[1] 0.008180308
> colSums(tmp2)
[1] 0.8180308
> colVars(tmp2)
[1] 1.092559
> colSd(tmp2)
[1] 1.045255
> colMax(tmp2)
[1] 3.04527
> colMin(tmp2)
[1] -3.807674
> colMedians(tmp2)
[1] -0.1657899
> colRanges(tmp2)
[,1]
[1,] -3.807674
[2,] 3.045270
>
> 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] -6.9927124 4.5914974 -1.7853413 -0.4241975 0.8786385 2.7455326
[7] -2.3854958 -0.1631157 0.5803956 -3.7467827
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.4137494
[2,] -1.7291368
[3,] -0.2827333
[4,] -0.1826404
[5,] 1.3085627
>
> rowApply(tmp,sum)
[1] -2.3230129 -0.5914228 3.5935436 -0.1381303 3.8708705 -1.7059213
[7] -0.4361810 -1.4972632 -1.4771608 -5.9969030
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 1 5 10 3 1 5 5 6 2
[2,] 9 2 10 7 7 9 10 4 10 3
[3,] 4 5 4 8 6 2 2 1 8 7
[4,] 6 8 3 3 8 5 1 6 7 6
[5,] 3 10 9 2 9 7 7 2 4 5
[6,] 8 9 6 5 4 8 9 3 5 9
[7,] 7 7 7 1 10 4 4 9 3 1
[8,] 2 6 8 6 2 3 8 7 9 8
[9,] 10 3 2 9 1 10 6 8 1 10
[10,] 5 4 1 4 5 6 3 10 2 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.1690324 5.0980255 -2.7675324 -2.7341115 0.5573663 -1.1109029
[7] 3.8783913 1.2935907 2.5944363 0.3973470 -0.3976511 2.1235936
[13] -1.6139368 2.1330581 0.8455165 -0.8629884 -2.3349121 2.3475669
[19] 0.5796720 -1.7568684
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2816262
[2,] -0.5348937
[3,] -0.3438739
[4,] 0.5079427
[5,] 1.4834186
>
> rowApply(tmp,sum)
[1] -0.3074857 2.5025239 3.2587658 -0.2377360 2.8845602
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 5 3 7 18
[2,] 19 19 18 9 13
[3,] 12 14 1 11 1
[4,] 4 2 13 12 2
[5,] 2 7 20 19 10
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5079427 1.8317051 0.33128769 -1.35934208 -1.7809124 -2.4979199
[2,] -0.5348937 1.5657262 0.34783528 -1.06461356 -0.1117250 0.3701052
[3,] -1.2816262 1.2606454 -1.43908559 0.73657549 1.5285452 0.2128802
[4,] -0.3438739 -0.1257766 0.04573139 0.06925102 1.0397566 -0.3525374
[5,] 1.4834186 0.5657255 -2.05330121 -1.11598240 -0.1182981 1.1565691
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.7286785 0.6180920 2.0362839 0.1300904 0.8019039 0.9584826
[2,] 1.9489409 -0.4385869 0.3414381 0.7904648 0.7298179 0.1717762
[3,] -0.4027378 1.1462668 1.1738250 -0.1863341 -1.0532111 0.3629280
[4,] 1.0001168 0.6244722 -0.2619016 0.5804223 -0.6791455 -0.7787667
[5,] 0.6033929 -0.6566533 -0.6952090 -0.9172963 -0.1970163 1.4091735
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.2543459 -0.1397507 -0.1922024 -1.5936783 -0.48758637 1.22430526
[2,] -0.7864477 1.0583593 -1.3969238 -0.6680486 -0.03325618 -0.02360905
[3,] -1.4036061 1.4006938 -0.7837039 1.0041925 0.24939911 0.11024379
[4,] -0.6577954 -1.8937250 1.2879544 0.5681435 -1.43774969 1.02385285
[5,] 0.9795665 1.7074808 1.9303923 -0.1735975 -0.62571900 0.01277408
[,19] [,20]
[1,] -0.72447684 -0.95473443
[2,] 0.01813103 0.21803350
[3,] 1.04138004 -0.41850476
[4,] 0.07796099 -0.02412606
[5,] 0.16667678 -0.57753661
>
>
> 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 : 649 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 : 562 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 -0.03479457 0.8554472 1.313845 0.1339177 -1.071624 -1.294197 1.184474
col8 col9 col10 col11 col12 col13 col14
row1 -0.7392893 0.8431495 0.9211931 -0.2104672 -0.7657916 -2.019799 0.791896
col15 col16 col17 col18 col19 col20
row1 1.090739 -0.4878955 -0.7049795 0.8867937 0.5433906 -1.687085
> tmp[,"col10"]
col10
row1 0.92119305
row2 1.46808791
row3 1.51120409
row4 -0.09457575
row5 0.03560139
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.03479457 0.855447245 1.313845 0.1339177 -1.0716236 -1.2941971
row5 1.23612289 -0.002495617 1.257000 -0.4900096 0.1855672 -0.9469018
col7 col8 col9 col10 col11 col12
row1 1.1844742 -0.7392893 0.8431495 0.92119305 -0.2104672 -0.7657916
row5 0.4755102 -0.2431737 -1.3078836 0.03560139 -0.3969805 1.3155574
col13 col14 col15 col16 col17 col18
row1 -2.0197986 0.791896 1.0907389 -0.4878955 -0.70497953 0.8867937
row5 -0.1229237 -1.004685 0.8373966 -0.3374712 0.05057261 -0.2311474
col19 col20
row1 0.5433906 -1.6870854
row5 -1.2723703 -0.8347727
> tmp[,c("col6","col20")]
col6 col20
row1 -1.2941971 -1.68708539
row2 -0.3139215 -1.33344928
row3 -1.0140118 0.03200006
row4 -0.1989540 1.71056076
row5 -0.9469018 -0.83477268
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.2941971 -1.6870854
row5 -0.9469018 -0.8347727
>
>
>
>
> 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 49.08896 50.04377 48.76354 50.35291 50.16737 105.6219 49.83196 48.91361
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.64137 50.61194 49.79392 51.49995 48.55272 49.9008 49.19953 48.76074
col17 col18 col19 col20
row1 49.98655 49.88118 49.77495 106.5092
> tmp[,"col10"]
col10
row1 50.61194
row2 29.18433
row3 31.85603
row4 31.35904
row5 49.74561
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.08896 50.04377 48.76354 50.35291 50.16737 105.6219 49.83196 48.91361
row5 48.79695 52.90964 49.90730 50.18631 51.68516 105.9664 49.22541 48.78829
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.64137 50.61194 49.79392 51.49995 48.55272 49.90080 49.19953 48.76074
row5 50.37965 49.74561 50.83523 51.22166 49.72156 50.51679 50.50213 50.01008
col17 col18 col19 col20
row1 49.98655 49.88118 49.77495 106.5092
row5 50.84217 48.78241 48.87819 105.5079
> tmp[,c("col6","col20")]
col6 col20
row1 105.62189 106.50923
row2 74.11137 75.03860
row3 75.25384 75.16085
row4 73.69738 74.13076
row5 105.96640 105.50788
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6219 106.5092
row5 105.9664 105.5079
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6219 106.5092
row5 105.9664 105.5079
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1441533
[2,] 0.4159491
[3,] 2.5414078
[4,] -0.1929271
[5,] 1.0445451
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.9997300 0.2692890
[2,] 0.6963054 0.2428379
[3,] -1.0882805 -0.3698033
[4,] -1.7082662 -1.1667181
[5,] -1.9328881 -0.7237432
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.5187291 -0.8298552
[2,] 1.1839544 -0.8759027
[3,] -0.8199325 0.8183768
[4,] 0.8972008 -2.5069590
[5,] -0.4789288 0.9430348
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.5187291
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.5187291
[2,] 1.1839544
>
>
>
> 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 -0.1357323 0.306378 -1.3428040 -0.9998823 0.3592102 -0.9003453 -1.429614
row1 1.1631524 1.541613 0.4212276 -0.6005902 -1.9229632 -1.5178485 1.359923
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.120913 -0.2191956 -1.4769625 -0.9539495 1.2975961 -0.5642047 -0.4788739
row1 1.019610 1.0966363 0.2049638 -1.5409676 0.7980119 1.9593812 0.4075054
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.007733895 0.2845605 1.1886947 0.3968695 1.5563103 -1.890645626
row1 1.243055864 -0.9616050 0.1643325 0.9855837 -0.8500774 -0.009743821
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2625056 0.3053896 2.682762 0.9089181 -1.577925 0.2550522 -2.782959
[,8] [,9] [,10]
row2 1.278226 0.4170765 -0.3113708
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2846115 -2.362009 0.6977344 -0.3477348 -1.211417 -0.3514051 -1.064333
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.560171 -0.4925649 1.418756 1.297735 -1.405077 -1.555676 -0.7540807
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.159461 -0.1827839 -1.45533 -0.7091497 1.443432 0.6785771
>
>
> 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: 0x64ba84666ed0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c56046d70a27"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c560349a6b48"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c560383c398c"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c56064452f55"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c56013bdf305"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c56049be3a7"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5603afa8050"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5602044361a"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5605f3b43c"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5606744f5c8"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5601d6e22d5"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5601e7e6471"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5605d5dc944"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c560786274fa"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7c5607071b343"
>
>
> ### 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: 0x64ba84a59990>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x64ba84a59990>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x64ba84a59990>
> rowMedians(tmp)
[1] -7.279931e-02 -3.735908e-01 -1.339105e-01 3.215767e-01 -3.015060e-01
[6] -1.239732e-01 3.078352e-01 -2.900589e-01 5.199948e-01 3.328969e-02
[11] -1.768217e-01 2.286961e-02 -6.040362e-01 -6.123051e-01 8.642932e-02
[16] -5.605139e-01 7.116550e-02 3.332379e-01 -3.387989e-01 -4.572604e-01
[21] -2.850483e-01 3.747569e-01 1.493441e-01 1.136391e-01 -2.456458e-01
[26] -4.002064e-01 2.605858e-01 1.764354e-01 6.564802e-02 1.873461e-01
[31] -1.659070e-01 4.385686e-01 -4.199744e-01 -6.210168e-01 -8.032610e-02
[36] -2.086856e-01 -1.070294e-01 5.478865e-01 4.017319e-02 -4.293492e-02
[41] -4.188055e-01 2.235115e-03 -4.766176e-02 -3.381344e-01 -3.773964e-01
[46] -1.036944e-01 -1.375869e-01 -8.344581e-01 -7.051391e-02 -1.654222e-01
[51] 8.626346e-02 4.012052e-01 -4.057714e-01 2.540163e-01 -7.396020e-03
[56] 2.137520e-01 8.021830e-02 -1.248641e-01 1.503349e-01 1.454913e-01
[61] -2.454266e-01 -8.870175e-01 4.074731e-02 3.551941e-01 1.858927e-01
[66] 2.762708e-01 2.688580e-03 1.821526e-01 2.116705e-01 -3.408011e-01
[71] -2.041505e-01 -4.976028e-01 5.038055e-01 -2.833895e-01 2.482129e-02
[76] 6.930363e-02 -5.919932e-01 -5.800664e-01 -2.157430e-01 -2.515149e-01
[81] 2.344901e-01 -2.606980e-01 -6.003364e-02 1.182783e-01 2.270408e-05
[86] 1.276248e-01 3.134454e-01 -2.526171e-01 3.538455e-01 1.631705e-01
[91] -5.798015e-01 4.297123e-01 -3.386082e-02 -8.209578e-01 -2.799432e-03
[96] 3.323951e-01 6.031628e-02 5.409004e-01 -5.443784e-02 -7.149756e-02
[101] 3.487074e-01 4.257349e-01 9.133224e-02 -2.271018e-01 -3.256403e-01
[106] 7.283463e-01 -2.143447e-01 7.366416e-02 -4.427377e-01 -3.071173e-01
[111] -6.904243e-01 -4.477034e-01 -5.719171e-01 6.161236e-01 5.268106e-03
[116] -1.197119e-01 -2.860074e-01 -4.043134e-01 -6.409947e-02 -2.659434e-01
[121] 2.168712e-01 -4.582253e-01 -4.039698e-01 2.557263e-01 -2.239270e-01
[126] 3.304576e-02 2.624932e-01 3.137943e-01 5.141110e-01 -4.148728e-01
[131] 3.293340e-01 1.929670e-01 -1.587362e-02 -7.252967e-02 -4.092713e-02
[136] 3.177800e-01 1.134921e-01 -3.006065e-01 -3.347329e-01 2.194608e-01
[141] -4.585713e-02 -1.428879e-01 1.185712e-01 1.096803e-01 2.531491e-01
[146] 3.078677e-01 -2.495041e-01 3.520382e-01 -3.613506e-01 8.177937e-02
[151] 1.514705e-01 -2.236725e-01 2.040901e-02 -2.401401e-01 -1.293344e-01
[156] -1.707955e-01 1.189236e-01 -2.578626e-01 1.414972e-01 -9.787934e-03
[161] -2.381893e-01 -9.114353e-01 1.286940e-01 -7.556011e-01 4.376934e-02
[166] 8.796434e-02 4.147045e-01 1.446256e-01 -7.319483e-02 2.122565e-01
[171] 6.948569e-01 -3.464085e-01 2.261562e-01 -3.755397e-01 -1.120012e-01
[176] -4.635309e-01 2.499951e-01 1.738869e-01 8.589945e-02 5.106282e-01
[181] 2.184040e-01 -4.564699e-01 -1.337645e-01 -9.145157e-02 -2.770565e-01
[186] -7.391745e-01 -2.313845e-01 -4.120240e-01 2.118423e-02 3.757041e-01
[191] -1.192428e-01 8.414150e-01 -1.185017e-01 2.508346e-01 -2.784204e-01
[196] 1.193928e-01 2.330396e-02 2.729988e-01 -2.314638e-01 -3.888465e-01
[201] -7.411797e-02 -8.172373e-02 -1.890250e-01 7.337006e-01 2.241179e-01
[206] -1.930155e-01 -1.104182e-01 1.829515e-01 -4.393826e-01 1.239486e-01
[211] 6.790506e-03 3.827488e-01 7.378640e-02 -3.258315e-01 -3.129090e-02
[216] 2.649069e-01 -2.681794e-01 3.862290e-01 1.389255e-01 2.617116e-03
[221] -4.738781e-01 -5.793129e-01 4.559663e-01 -2.890825e-01 -1.148834e-01
[226] 4.107031e-01 -3.057267e-01 -2.630927e-01 -2.926377e-01 4.879910e-01
>
> proc.time()
user system elapsed
1.338 1.583 2.909
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x650f9f3d00f0>
> .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: 0x650f9f3d00f0>
> .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: 0x650f9f3d00f0>
> .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: 0x650f9f3d00f0>
> 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: 0x650fa021e690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x650fa021e690>
> .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: 0x650fa021e690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x650fa021e690>
> .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: 0x650fa021e690>
> 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: 0x650fa1c58010>
> .Call("R_bm_AddColumn",P)
<pointer: 0x650fa1c58010>
> .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: 0x650fa1c58010>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x650fa1c58010>
> .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: 0x650fa1c58010>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x650fa1c58010>
> .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: 0x650fa1c58010>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x650fa1c58010>
> .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: 0x650fa1c58010>
> 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: 0x650fa1ca8070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x650fa1ca8070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x650fa1ca8070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x650fa1ca8070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7c66e4fd12810" "BufferedMatrixFile7c66e6b1b1c76"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7c66e4fd12810" "BufferedMatrixFile7c66e6b1b1c76"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x650f9fada7d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x650f9fada7d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x650f9fada7d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x650f9fada7d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x650f9fada7d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x650f9fada7d0>
> .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: 0x650fa15de2d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x650fa15de2d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x650fa15de2d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x650fa15de2d0>
> 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: 0x650fa08a44a0>
> .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: 0x650fa08a44a0>
> rm(P)
>
> proc.time()
user system elapsed
0.260 0.062 0.310
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.247 0.054 0.288