Ben Bolstad
| Snapshot Date: 2026-05-20 13:40 -0400 (Wed, 20 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 2026-05-21 11:32 -0400 (Thu, 21 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: 2026-05-20 22:06:47 -0400 (Wed, 20 May 2026) |
| EndedAt: 2026-05-20 22:07:13 -0400 (Wed, 20 May 2026) |
| EllapsedTime: 26.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### 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
###
##############################################################################
##############################################################################
* 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: 2026-05-21 02:06:48 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
##############################################################################
##############################################################################
###
### 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
0.296 0.053 0.335
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] "Wed May 20 22:07:03 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed May 20 22:07:03 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: 0x5b603a439690>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed May 20 22:07:04 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed May 20 22:07:04 2026"
>
> ColMode(tmp2)
<pointer: 0x5b603a439690>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.6597545 -0.2745058 -0.03848362 0.6971902
[2,] 0.9123669 0.1684673 -0.64445950 0.4196384
[3,] 1.5002333 -1.2401105 0.08867077 -0.5706021
[4,] 0.1889853 0.1557878 1.28537629 -1.0789219
> 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,] 100.6597545 0.2745058 0.03848362 0.6971902
[2,] 0.9123669 0.1684673 0.64445950 0.4196384
[3,] 1.5002333 1.2401105 0.08867077 0.5706021
[4,] 0.1889853 0.1557878 1.28537629 1.0789219
> 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,] 10.0329335 0.5239330 0.1961724 0.8349792
[2,] 0.9551790 0.4104477 0.8027823 0.6477950
[3,] 1.2248401 1.1136025 0.2977764 0.7553821
[4,] 0.4347244 0.3946996 1.1337444 1.0387116
>
> 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,] 225.98909 30.51384 27.00021 34.04698
[2,] 35.46416 29.27294 33.67228 31.89759
[3,] 38.74863 37.37614 28.06643 33.12442
[4,] 29.53623 29.10278 37.62282 36.46604
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5b603b7ed0c0>
> exp(tmp5)
<pointer: 0x5b603b7ed0c0>
> log(tmp5,2)
<pointer: 0x5b603b7ed0c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.3667
> Min(tmp5)
[1] 54.21562
> mean(tmp5)
[1] 72.17125
> Sum(tmp5)
[1] 14434.25
> Var(tmp5)
[1] 861.7202
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.15384 71.55389 71.51061 69.42124 70.68538 71.45308 70.13260 67.97410
[9] 66.70053 72.12726
> rowSums(tmp5)
[1] 1803.077 1431.078 1430.212 1388.425 1413.708 1429.062 1402.652 1359.482
[9] 1334.011 1442.545
> rowVars(tmp5)
[1] 8076.55620 40.98974 72.39957 65.72531 66.75871 57.84984
[7] 60.66964 75.33293 45.86445 56.73307
> rowSd(tmp5)
[1] 89.869662 6.402323 8.508794 8.107115 8.170600 7.605908 7.789072
[8] 8.679455 6.772330 7.532136
> rowMax(tmp5)
[1] 470.36668 83.69552 86.52171 83.65817 85.07207 95.49863 82.12495
[8] 83.32559 76.79447 84.33318
> rowMin(tmp5)
[1] 54.81641 60.88496 58.41661 54.21562 58.30454 60.37499 56.24358 54.59964
[9] 55.56774 55.32456
>
> colMeans(tmp5)
[1] 111.86079 67.56774 71.60082 74.22688 66.26300 67.99935 66.54212
[8] 74.42726 68.51643 70.10984 69.95161 71.45445 69.65579 67.35939
[15] 67.02819 71.71112 71.34214 68.38357 72.94394 74.48062
> colSums(tmp5)
[1] 1118.6079 675.6774 716.0082 742.2688 662.6300 679.9935 665.4212
[8] 744.2726 685.1643 701.0984 699.5161 714.5445 696.5579 673.5939
[15] 670.2819 717.1112 713.4214 683.8357 729.4394 744.8062
> colVars(tmp5)
[1] 15894.43704 79.75762 72.95239 18.75397 72.25340 45.61511
[7] 61.32545 26.79488 17.59097 60.53080 135.10905 92.15433
[13] 77.92599 58.32987 44.11727 34.73929 70.32076 73.60905
[19] 64.63935 63.46907
> colSd(tmp5)
[1] 126.073142 8.930712 8.541217 4.330585 8.500200 6.753896
[7] 7.831057 5.176377 4.194159 7.780154 11.623642 9.599705
[13] 8.827570 7.637399 6.642083 5.894004 8.385747 8.579571
[19] 8.039860 7.966748
> colMax(tmp5)
[1] 470.36668 80.51946 81.61618 79.31076 83.69552 76.95497 80.53846
[8] 82.12495 75.36133 82.05081 95.49863 84.33318 83.65817 76.79447
[15] 76.35699 82.45290 85.07207 83.32559 87.38426 86.52171
> colMin(tmp5)
[1] 61.47579 55.56774 56.19740 66.39065 58.49423 58.26077 57.17713 67.27434
[9] 60.88496 56.33764 54.59964 54.21562 56.24358 54.81641 56.38622 63.49482
[17] 55.32456 56.70751 63.00858 61.06139
>
>
> ### 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] 90.15384 71.55389 71.51061 69.42124 70.68538 NA 70.13260 67.97410
[9] 66.70053 72.12726
> rowSums(tmp5)
[1] 1803.077 1431.078 1430.212 1388.425 1413.708 NA 1402.652 1359.482
[9] 1334.011 1442.545
> rowVars(tmp5)
[1] 8076.55620 40.98974 72.39957 65.72531 66.75871 57.43785
[7] 60.66964 75.33293 45.86445 56.73307
> rowSd(tmp5)
[1] 89.869662 6.402323 8.508794 8.107115 8.170600 7.578776 7.789072
[8] 8.679455 6.772330 7.532136
> rowMax(tmp5)
[1] 470.36668 83.69552 86.52171 83.65817 85.07207 NA 82.12495
[8] 83.32559 76.79447 84.33318
> rowMin(tmp5)
[1] 54.81641 60.88496 58.41661 54.21562 58.30454 NA 56.24358 54.59964
[9] 55.56774 55.32456
>
> colMeans(tmp5)
[1] 111.86079 67.56774 71.60082 74.22688 66.26300 67.99935 66.54212
[8] 74.42726 68.51643 70.10984 69.95161 NA 69.65579 67.35939
[15] 67.02819 71.71112 71.34214 68.38357 72.94394 74.48062
> colSums(tmp5)
[1] 1118.6079 675.6774 716.0082 742.2688 662.6300 679.9935 665.4212
[8] 744.2726 685.1643 701.0984 699.5161 NA 696.5579 673.5939
[15] 670.2819 717.1112 713.4214 683.8357 729.4394 744.8062
> colVars(tmp5)
[1] 15894.43704 79.75762 72.95239 18.75397 72.25340 45.61511
[7] 61.32545 26.79488 17.59097 60.53080 135.10905 NA
[13] 77.92599 58.32987 44.11727 34.73929 70.32076 73.60905
[19] 64.63935 63.46907
> colSd(tmp5)
[1] 126.073142 8.930712 8.541217 4.330585 8.500200 6.753896
[7] 7.831057 5.176377 4.194159 7.780154 11.623642 NA
[13] 8.827570 7.637399 6.642083 5.894004 8.385747 8.579571
[19] 8.039860 7.966748
> colMax(tmp5)
[1] 470.36668 80.51946 81.61618 79.31076 83.69552 76.95497 80.53846
[8] 82.12495 75.36133 82.05081 95.49863 NA 83.65817 76.79447
[15] 76.35699 82.45290 85.07207 83.32559 87.38426 86.52171
> colMin(tmp5)
[1] 61.47579 55.56774 56.19740 66.39065 58.49423 58.26077 57.17713 67.27434
[9] 60.88496 56.33764 54.59964 NA 56.24358 54.81641 56.38622 63.49482
[17] 55.32456 56.70751 63.00858 61.06139
>
> Max(tmp5,na.rm=TRUE)
[1] 470.3667
> Min(tmp5,na.rm=TRUE)
[1] 54.21562
> mean(tmp5,na.rm=TRUE)
[1] 72.21443
> Sum(tmp5,na.rm=TRUE)
[1] 14370.67
> Var(tmp5,na.rm=TRUE)
[1] 865.6976
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.15384 71.55389 71.51061 69.42124 70.68538 71.86751 70.13260 67.97410
[9] 66.70053 72.12726
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.077 1431.078 1430.212 1388.425 1413.708 1365.483 1402.652 1359.482
[9] 1334.011 1442.545
> rowVars(tmp5,na.rm=TRUE)
[1] 8076.55620 40.98974 72.39957 65.72531 66.75871 57.43785
[7] 60.66964 75.33293 45.86445 56.73307
> rowSd(tmp5,na.rm=TRUE)
[1] 89.869662 6.402323 8.508794 8.107115 8.170600 7.578776 7.789072
[8] 8.679455 6.772330 7.532136
> rowMax(tmp5,na.rm=TRUE)
[1] 470.36668 83.69552 86.52171 83.65817 85.07207 95.49863 82.12495
[8] 83.32559 76.79447 84.33318
> rowMin(tmp5,na.rm=TRUE)
[1] 54.81641 60.88496 58.41661 54.21562 58.30454 60.37499 56.24358 54.59964
[9] 55.56774 55.32456
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.86079 67.56774 71.60082 74.22688 66.26300 67.99935 66.54212
[8] 74.42726 68.51643 70.10984 69.95161 72.32951 69.65579 67.35939
[15] 67.02819 71.71112 71.34214 68.38357 72.94394 74.48062
> colSums(tmp5,na.rm=TRUE)
[1] 1118.6079 675.6774 716.0082 742.2688 662.6300 679.9935 665.4212
[8] 744.2726 685.1643 701.0984 699.5161 650.9656 696.5579 673.5939
[15] 670.2819 717.1112 713.4214 683.8357 729.4394 744.8062
> colVars(tmp5,na.rm=TRUE)
[1] 15894.43704 79.75762 72.95239 18.75397 72.25340 45.61511
[7] 61.32545 26.79488 17.59097 60.53080 135.10905 95.05917
[13] 77.92599 58.32987 44.11727 34.73929 70.32076 73.60905
[19] 64.63935 63.46907
> colSd(tmp5,na.rm=TRUE)
[1] 126.073142 8.930712 8.541217 4.330585 8.500200 6.753896
[7] 7.831057 5.176377 4.194159 7.780154 11.623642 9.749829
[13] 8.827570 7.637399 6.642083 5.894004 8.385747 8.579571
[19] 8.039860 7.966748
> colMax(tmp5,na.rm=TRUE)
[1] 470.36668 80.51946 81.61618 79.31076 83.69552 76.95497 80.53846
[8] 82.12495 75.36133 82.05081 95.49863 84.33318 83.65817 76.79447
[15] 76.35699 82.45290 85.07207 83.32559 87.38426 86.52171
> colMin(tmp5,na.rm=TRUE)
[1] 61.47579 55.56774 56.19740 66.39065 58.49423 58.26077 57.17713 67.27434
[9] 60.88496 56.33764 54.59964 54.21562 56.24358 54.81641 56.38622 63.49482
[17] 55.32456 56.70751 63.00858 61.06139
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.15384 71.55389 71.51061 69.42124 70.68538 NaN 70.13260 67.97410
[9] 66.70053 72.12726
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.077 1431.078 1430.212 1388.425 1413.708 0.000 1402.652 1359.482
[9] 1334.011 1442.545
> rowVars(tmp5,na.rm=TRUE)
[1] 8076.55620 40.98974 72.39957 65.72531 66.75871 NA
[7] 60.66964 75.33293 45.86445 56.73307
> rowSd(tmp5,na.rm=TRUE)
[1] 89.869662 6.402323 8.508794 8.107115 8.170600 NA 7.789072
[8] 8.679455 6.772330 7.532136
> rowMax(tmp5,na.rm=TRUE)
[1] 470.36668 83.69552 86.52171 83.65817 85.07207 NA 82.12495
[8] 83.32559 76.79447 84.33318
> rowMin(tmp5,na.rm=TRUE)
[1] 54.81641 60.88496 58.41661 54.21562 58.30454 NA 56.24358 54.59964
[9] 55.56774 55.32456
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.71963 67.54834 71.27774 73.66200 65.98747 68.12873 67.22735
[8] 74.82780 68.27184 69.65760 67.11305 NaN 69.40298 66.57327
[15] 66.75039 70.51759 71.81914 68.71500 73.44931 75.04223
> colSums(tmp5,na.rm=TRUE)
[1] 1050.4767 607.9351 641.4997 662.9580 593.8872 613.1586 605.0462
[8] 673.4502 614.4466 626.9184 604.0175 0.0000 624.6268 599.1595
[15] 600.7535 634.6583 646.3723 618.4350 661.0438 675.3801
> colVars(tmp5,na.rm=TRUE)
[1] 17615.64809 89.72309 80.89716 17.50851 80.43098 51.12868
[7] 63.70870 28.33937 19.11685 65.79624 61.35179 NA
[13] 86.94770 58.66885 48.76372 23.05588 76.55110 81.57443
[19] 69.84596 67.85442
> colSd(tmp5,na.rm=TRUE)
[1] 132.723954 9.472227 8.994285 4.184318 8.968332 7.150432
[7] 7.981773 5.323474 4.372282 8.111488 7.832738 NA
[13] 9.324575 7.659559 6.983102 4.801654 8.749348 9.031856
[19] 8.357390 8.237379
> colMax(tmp5,na.rm=TRUE)
[1] 470.36668 80.51946 81.61618 79.20308 83.69552 76.95497 80.53846
[8] 82.12495 75.36133 82.05081 77.67924 -Inf 83.65817 76.79447
[15] 76.35699 76.63508 85.07207 83.32559 87.38426 86.52171
> colMin(tmp5,na.rm=TRUE)
[1] 61.47579 55.56774 56.19740 66.39065 58.49423 58.26077 57.17713 67.27434
[9] 60.88496 56.33764 54.59964 Inf 56.24358 54.81641 56.38622 63.49482
[17] 55.32456 56.70751 63.00858 61.06139
>
>
>
>
> 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] 280.2211 128.7378 213.3125 267.7804 147.2916 260.9253 255.6685 216.5589
[9] 303.3734 179.3316
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 280.2211 128.7378 213.3125 267.7804 147.2916 260.9253 255.6685 216.5589
[9] 303.3734 179.3316
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 0.000000e+00 -1.705303e-13 -1.421085e-14 -2.842171e-14 -1.136868e-13
[6] 9.947598e-14 5.684342e-14 2.557954e-13 0.000000e+00 4.263256e-14
[11] -5.684342e-14 -1.136868e-13 0.000000e+00 -1.136868e-13 -1.989520e-13
[16] -2.842171e-14 -8.526513e-14 -5.684342e-14 -2.842171e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 17
1 1
8 5
4 18
10 11
2 8
9 18
4 1
7 19
8 17
6 15
6 10
7 11
2 18
7 10
5 12
2 1
1 15
6 6
3 15
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 1.989371
> Min(tmp)
[1] -1.92577
> mean(tmp)
[1] 0.1343605
> Sum(tmp)
[1] 13.43605
> Var(tmp)
[1] 0.8455968
>
> rowMeans(tmp)
[1] 0.1343605
> rowSums(tmp)
[1] 13.43605
> rowVars(tmp)
[1] 0.8455968
> rowSd(tmp)
[1] 0.9195634
> rowMax(tmp)
[1] 1.989371
> rowMin(tmp)
[1] -1.92577
>
> colMeans(tmp)
[1] 1.298376166 -1.564391392 -0.957197895 -1.065359779 1.324199139
[6] -0.788892219 -0.439689909 -0.251971233 -0.240859098 -0.514311897
[11] 0.568503943 1.095914669 -0.149864381 1.628267173 1.010006039
[16] 0.633130091 -1.925770080 0.106198241 0.954788355 0.714930510
[21] 0.202974002 0.658304133 0.514899767 0.209524772 -1.710989338
[26] -0.852730467 0.868854796 0.039604732 -0.547188800 1.378323525
[31] 0.979082881 -0.199761080 0.772290884 -0.338795891 0.208964097
[36] 0.318474378 0.030203973 0.899421830 0.588332727 0.706800058
[41] -0.633840900 0.917631516 -0.537017564 0.883924184 -0.076528438
[46] -0.788783088 -0.609772229 0.284858826 1.409437603 -0.356610682
[51] 1.116901343 -0.373104481 -1.500112646 -0.675400598 0.474261110
[56] -0.175180219 0.802475822 0.684605360 0.942161052 1.886951529
[61] -0.239589684 0.102811784 0.832062777 -0.691441599 0.471440486
[66] 1.410639840 0.567212920 0.100974164 -0.459248728 1.666282292
[71] 1.917777990 0.840429055 -0.372731047 0.695817350 0.841976557
[76] -0.328528688 0.009052554 -1.210485762 0.428679880 0.885489009
[81] -1.079098867 0.620739527 0.222886868 -0.041241732 -1.848833272
[86] -1.069854500 1.207028855 -1.442327281 -0.946691351 1.989371393
[91] -0.081496312 -1.631676073 -0.340357289 1.034913227 -0.894624330
[96] 1.226521631 1.363749037 -0.738455677 -0.972370062 -0.450210082
> colSums(tmp)
[1] 1.298376166 -1.564391392 -0.957197895 -1.065359779 1.324199139
[6] -0.788892219 -0.439689909 -0.251971233 -0.240859098 -0.514311897
[11] 0.568503943 1.095914669 -0.149864381 1.628267173 1.010006039
[16] 0.633130091 -1.925770080 0.106198241 0.954788355 0.714930510
[21] 0.202974002 0.658304133 0.514899767 0.209524772 -1.710989338
[26] -0.852730467 0.868854796 0.039604732 -0.547188800 1.378323525
[31] 0.979082881 -0.199761080 0.772290884 -0.338795891 0.208964097
[36] 0.318474378 0.030203973 0.899421830 0.588332727 0.706800058
[41] -0.633840900 0.917631516 -0.537017564 0.883924184 -0.076528438
[46] -0.788783088 -0.609772229 0.284858826 1.409437603 -0.356610682
[51] 1.116901343 -0.373104481 -1.500112646 -0.675400598 0.474261110
[56] -0.175180219 0.802475822 0.684605360 0.942161052 1.886951529
[61] -0.239589684 0.102811784 0.832062777 -0.691441599 0.471440486
[66] 1.410639840 0.567212920 0.100974164 -0.459248728 1.666282292
[71] 1.917777990 0.840429055 -0.372731047 0.695817350 0.841976557
[76] -0.328528688 0.009052554 -1.210485762 0.428679880 0.885489009
[81] -1.079098867 0.620739527 0.222886868 -0.041241732 -1.848833272
[86] -1.069854500 1.207028855 -1.442327281 -0.946691351 1.989371393
[91] -0.081496312 -1.631676073 -0.340357289 1.034913227 -0.894624330
[96] 1.226521631 1.363749037 -0.738455677 -0.972370062 -0.450210082
> 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] 1.298376166 -1.564391392 -0.957197895 -1.065359779 1.324199139
[6] -0.788892219 -0.439689909 -0.251971233 -0.240859098 -0.514311897
[11] 0.568503943 1.095914669 -0.149864381 1.628267173 1.010006039
[16] 0.633130091 -1.925770080 0.106198241 0.954788355 0.714930510
[21] 0.202974002 0.658304133 0.514899767 0.209524772 -1.710989338
[26] -0.852730467 0.868854796 0.039604732 -0.547188800 1.378323525
[31] 0.979082881 -0.199761080 0.772290884 -0.338795891 0.208964097
[36] 0.318474378 0.030203973 0.899421830 0.588332727 0.706800058
[41] -0.633840900 0.917631516 -0.537017564 0.883924184 -0.076528438
[46] -0.788783088 -0.609772229 0.284858826 1.409437603 -0.356610682
[51] 1.116901343 -0.373104481 -1.500112646 -0.675400598 0.474261110
[56] -0.175180219 0.802475822 0.684605360 0.942161052 1.886951529
[61] -0.239589684 0.102811784 0.832062777 -0.691441599 0.471440486
[66] 1.410639840 0.567212920 0.100974164 -0.459248728 1.666282292
[71] 1.917777990 0.840429055 -0.372731047 0.695817350 0.841976557
[76] -0.328528688 0.009052554 -1.210485762 0.428679880 0.885489009
[81] -1.079098867 0.620739527 0.222886868 -0.041241732 -1.848833272
[86] -1.069854500 1.207028855 -1.442327281 -0.946691351 1.989371393
[91] -0.081496312 -1.631676073 -0.340357289 1.034913227 -0.894624330
[96] 1.226521631 1.363749037 -0.738455677 -0.972370062 -0.450210082
> colMin(tmp)
[1] 1.298376166 -1.564391392 -0.957197895 -1.065359779 1.324199139
[6] -0.788892219 -0.439689909 -0.251971233 -0.240859098 -0.514311897
[11] 0.568503943 1.095914669 -0.149864381 1.628267173 1.010006039
[16] 0.633130091 -1.925770080 0.106198241 0.954788355 0.714930510
[21] 0.202974002 0.658304133 0.514899767 0.209524772 -1.710989338
[26] -0.852730467 0.868854796 0.039604732 -0.547188800 1.378323525
[31] 0.979082881 -0.199761080 0.772290884 -0.338795891 0.208964097
[36] 0.318474378 0.030203973 0.899421830 0.588332727 0.706800058
[41] -0.633840900 0.917631516 -0.537017564 0.883924184 -0.076528438
[46] -0.788783088 -0.609772229 0.284858826 1.409437603 -0.356610682
[51] 1.116901343 -0.373104481 -1.500112646 -0.675400598 0.474261110
[56] -0.175180219 0.802475822 0.684605360 0.942161052 1.886951529
[61] -0.239589684 0.102811784 0.832062777 -0.691441599 0.471440486
[66] 1.410639840 0.567212920 0.100974164 -0.459248728 1.666282292
[71] 1.917777990 0.840429055 -0.372731047 0.695817350 0.841976557
[76] -0.328528688 0.009052554 -1.210485762 0.428679880 0.885489009
[81] -1.079098867 0.620739527 0.222886868 -0.041241732 -1.848833272
[86] -1.069854500 1.207028855 -1.442327281 -0.946691351 1.989371393
[91] -0.081496312 -1.631676073 -0.340357289 1.034913227 -0.894624330
[96] 1.226521631 1.363749037 -0.738455677 -0.972370062 -0.450210082
> colMedians(tmp)
[1] 1.298376166 -1.564391392 -0.957197895 -1.065359779 1.324199139
[6] -0.788892219 -0.439689909 -0.251971233 -0.240859098 -0.514311897
[11] 0.568503943 1.095914669 -0.149864381 1.628267173 1.010006039
[16] 0.633130091 -1.925770080 0.106198241 0.954788355 0.714930510
[21] 0.202974002 0.658304133 0.514899767 0.209524772 -1.710989338
[26] -0.852730467 0.868854796 0.039604732 -0.547188800 1.378323525
[31] 0.979082881 -0.199761080 0.772290884 -0.338795891 0.208964097
[36] 0.318474378 0.030203973 0.899421830 0.588332727 0.706800058
[41] -0.633840900 0.917631516 -0.537017564 0.883924184 -0.076528438
[46] -0.788783088 -0.609772229 0.284858826 1.409437603 -0.356610682
[51] 1.116901343 -0.373104481 -1.500112646 -0.675400598 0.474261110
[56] -0.175180219 0.802475822 0.684605360 0.942161052 1.886951529
[61] -0.239589684 0.102811784 0.832062777 -0.691441599 0.471440486
[66] 1.410639840 0.567212920 0.100974164 -0.459248728 1.666282292
[71] 1.917777990 0.840429055 -0.372731047 0.695817350 0.841976557
[76] -0.328528688 0.009052554 -1.210485762 0.428679880 0.885489009
[81] -1.079098867 0.620739527 0.222886868 -0.041241732 -1.848833272
[86] -1.069854500 1.207028855 -1.442327281 -0.946691351 1.989371393
[91] -0.081496312 -1.631676073 -0.340357289 1.034913227 -0.894624330
[96] 1.226521631 1.363749037 -0.738455677 -0.972370062 -0.450210082
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.298376 -1.564391 -0.9571979 -1.06536 1.324199 -0.7888922 -0.4396899
[2,] 1.298376 -1.564391 -0.9571979 -1.06536 1.324199 -0.7888922 -0.4396899
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.2519712 -0.2408591 -0.5143119 0.5685039 1.095915 -0.1498644 1.628267
[2,] -0.2519712 -0.2408591 -0.5143119 0.5685039 1.095915 -0.1498644 1.628267
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.010006 0.6331301 -1.92577 0.1061982 0.9547884 0.7149305 0.202974
[2,] 1.010006 0.6331301 -1.92577 0.1061982 0.9547884 0.7149305 0.202974
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.6583041 0.5148998 0.2095248 -1.710989 -0.8527305 0.8688548 0.03960473
[2,] 0.6583041 0.5148998 0.2095248 -1.710989 -0.8527305 0.8688548 0.03960473
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5471888 1.378324 0.9790829 -0.1997611 0.7722909 -0.3387959 0.2089641
[2,] -0.5471888 1.378324 0.9790829 -0.1997611 0.7722909 -0.3387959 0.2089641
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.3184744 0.03020397 0.8994218 0.5883327 0.7068001 -0.6338409 0.9176315
[2,] 0.3184744 0.03020397 0.8994218 0.5883327 0.7068001 -0.6338409 0.9176315
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.5370176 0.8839242 -0.07652844 -0.7887831 -0.6097722 0.2848588 1.409438
[2,] -0.5370176 0.8839242 -0.07652844 -0.7887831 -0.6097722 0.2848588 1.409438
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.3566107 1.116901 -0.3731045 -1.500113 -0.6754006 0.4742611 -0.1751802
[2,] -0.3566107 1.116901 -0.3731045 -1.500113 -0.6754006 0.4742611 -0.1751802
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.8024758 0.6846054 0.9421611 1.886952 -0.2395897 0.1028118 0.8320628
[2,] 0.8024758 0.6846054 0.9421611 1.886952 -0.2395897 0.1028118 0.8320628
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.6914416 0.4714405 1.41064 0.5672129 0.1009742 -0.4592487 1.666282
[2,] -0.6914416 0.4714405 1.41064 0.5672129 0.1009742 -0.4592487 1.666282
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.917778 0.8404291 -0.372731 0.6958173 0.8419766 -0.3285287 0.009052554
[2,] 1.917778 0.8404291 -0.372731 0.6958173 0.8419766 -0.3285287 0.009052554
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.210486 0.4286799 0.885489 -1.079099 0.6207395 0.2228869 -0.04124173
[2,] -1.210486 0.4286799 0.885489 -1.079099 0.6207395 0.2228869 -0.04124173
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.848833 -1.069854 1.207029 -1.442327 -0.9466914 1.989371 -0.08149631
[2,] -1.848833 -1.069854 1.207029 -1.442327 -0.9466914 1.989371 -0.08149631
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.631676 -0.3403573 1.034913 -0.8946243 1.226522 1.363749 -0.7384557
[2,] -1.631676 -0.3403573 1.034913 -0.8946243 1.226522 1.363749 -0.7384557
[,99] [,100]
[1,] -0.9723701 -0.4502101
[2,] -0.9723701 -0.4502101
>
>
> Max(tmp2)
[1] 2.625234
> Min(tmp2)
[1] -2.864787
> mean(tmp2)
[1] -0.06038239
> Sum(tmp2)
[1] -6.038239
> Var(tmp2)
[1] 0.998427
>
> rowMeans(tmp2)
[1] 0.55120221 1.03432524 -0.28807373 -0.10944405 0.98033356 -0.54026532
[7] 1.12542182 -0.44141636 2.09446340 -0.50027520 1.15315014 1.06939752
[13] 0.37655893 -0.65402693 0.59507445 -0.41358499 -1.30013319 -1.16027877
[19] -0.61991540 -0.68645101 0.39115161 1.41358368 0.31981843 -1.23152502
[25] -0.67414552 1.05897859 -0.43243502 1.02169646 0.45023248 -1.84245233
[31] -1.13929821 0.14849494 0.42620506 0.27547672 -0.29873515 -0.28605360
[37] 0.21069820 -0.18341128 -0.33774305 0.03487211 -0.52675107 -0.91215246
[43] -2.86478731 -0.47891290 1.17776422 -1.41079174 1.36312542 -0.87656659
[49] -0.53490576 -0.78815512 0.76872112 0.09219640 -0.60412636 0.81482353
[55] 0.84439542 0.01699766 -0.40249103 -0.06721257 -1.01786235 -1.88434084
[61] -1.08622457 0.26640074 -1.01001814 1.36062963 -0.94876679 -0.98628673
[67] 0.38000674 0.47236411 0.09988682 0.92784296 -0.66751228 -1.27464059
[73] -1.28674196 -0.43705847 1.24408391 0.93950110 2.62523440 0.72765844
[79] 0.05336456 0.17930306 -0.68917297 -0.55810578 -0.18399749 0.78373824
[85] -1.51404990 2.13283617 0.45866197 1.91707981 -1.64387016 -1.09133665
[91] -0.06208341 -0.28978517 1.39550383 -0.84028698 -0.75471858 0.60027188
[97] 0.98762812 -1.48361198 0.62812234 -1.71052810
> rowSums(tmp2)
[1] 0.55120221 1.03432524 -0.28807373 -0.10944405 0.98033356 -0.54026532
[7] 1.12542182 -0.44141636 2.09446340 -0.50027520 1.15315014 1.06939752
[13] 0.37655893 -0.65402693 0.59507445 -0.41358499 -1.30013319 -1.16027877
[19] -0.61991540 -0.68645101 0.39115161 1.41358368 0.31981843 -1.23152502
[25] -0.67414552 1.05897859 -0.43243502 1.02169646 0.45023248 -1.84245233
[31] -1.13929821 0.14849494 0.42620506 0.27547672 -0.29873515 -0.28605360
[37] 0.21069820 -0.18341128 -0.33774305 0.03487211 -0.52675107 -0.91215246
[43] -2.86478731 -0.47891290 1.17776422 -1.41079174 1.36312542 -0.87656659
[49] -0.53490576 -0.78815512 0.76872112 0.09219640 -0.60412636 0.81482353
[55] 0.84439542 0.01699766 -0.40249103 -0.06721257 -1.01786235 -1.88434084
[61] -1.08622457 0.26640074 -1.01001814 1.36062963 -0.94876679 -0.98628673
[67] 0.38000674 0.47236411 0.09988682 0.92784296 -0.66751228 -1.27464059
[73] -1.28674196 -0.43705847 1.24408391 0.93950110 2.62523440 0.72765844
[79] 0.05336456 0.17930306 -0.68917297 -0.55810578 -0.18399749 0.78373824
[85] -1.51404990 2.13283617 0.45866197 1.91707981 -1.64387016 -1.09133665
[91] -0.06208341 -0.28978517 1.39550383 -0.84028698 -0.75471858 0.60027188
[97] 0.98762812 -1.48361198 0.62812234 -1.71052810
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.55120221 1.03432524 -0.28807373 -0.10944405 0.98033356 -0.54026532
[7] 1.12542182 -0.44141636 2.09446340 -0.50027520 1.15315014 1.06939752
[13] 0.37655893 -0.65402693 0.59507445 -0.41358499 -1.30013319 -1.16027877
[19] -0.61991540 -0.68645101 0.39115161 1.41358368 0.31981843 -1.23152502
[25] -0.67414552 1.05897859 -0.43243502 1.02169646 0.45023248 -1.84245233
[31] -1.13929821 0.14849494 0.42620506 0.27547672 -0.29873515 -0.28605360
[37] 0.21069820 -0.18341128 -0.33774305 0.03487211 -0.52675107 -0.91215246
[43] -2.86478731 -0.47891290 1.17776422 -1.41079174 1.36312542 -0.87656659
[49] -0.53490576 -0.78815512 0.76872112 0.09219640 -0.60412636 0.81482353
[55] 0.84439542 0.01699766 -0.40249103 -0.06721257 -1.01786235 -1.88434084
[61] -1.08622457 0.26640074 -1.01001814 1.36062963 -0.94876679 -0.98628673
[67] 0.38000674 0.47236411 0.09988682 0.92784296 -0.66751228 -1.27464059
[73] -1.28674196 -0.43705847 1.24408391 0.93950110 2.62523440 0.72765844
[79] 0.05336456 0.17930306 -0.68917297 -0.55810578 -0.18399749 0.78373824
[85] -1.51404990 2.13283617 0.45866197 1.91707981 -1.64387016 -1.09133665
[91] -0.06208341 -0.28978517 1.39550383 -0.84028698 -0.75471858 0.60027188
[97] 0.98762812 -1.48361198 0.62812234 -1.71052810
> rowMin(tmp2)
[1] 0.55120221 1.03432524 -0.28807373 -0.10944405 0.98033356 -0.54026532
[7] 1.12542182 -0.44141636 2.09446340 -0.50027520 1.15315014 1.06939752
[13] 0.37655893 -0.65402693 0.59507445 -0.41358499 -1.30013319 -1.16027877
[19] -0.61991540 -0.68645101 0.39115161 1.41358368 0.31981843 -1.23152502
[25] -0.67414552 1.05897859 -0.43243502 1.02169646 0.45023248 -1.84245233
[31] -1.13929821 0.14849494 0.42620506 0.27547672 -0.29873515 -0.28605360
[37] 0.21069820 -0.18341128 -0.33774305 0.03487211 -0.52675107 -0.91215246
[43] -2.86478731 -0.47891290 1.17776422 -1.41079174 1.36312542 -0.87656659
[49] -0.53490576 -0.78815512 0.76872112 0.09219640 -0.60412636 0.81482353
[55] 0.84439542 0.01699766 -0.40249103 -0.06721257 -1.01786235 -1.88434084
[61] -1.08622457 0.26640074 -1.01001814 1.36062963 -0.94876679 -0.98628673
[67] 0.38000674 0.47236411 0.09988682 0.92784296 -0.66751228 -1.27464059
[73] -1.28674196 -0.43705847 1.24408391 0.93950110 2.62523440 0.72765844
[79] 0.05336456 0.17930306 -0.68917297 -0.55810578 -0.18399749 0.78373824
[85] -1.51404990 2.13283617 0.45866197 1.91707981 -1.64387016 -1.09133665
[91] -0.06208341 -0.28978517 1.39550383 -0.84028698 -0.75471858 0.60027188
[97] 0.98762812 -1.48361198 0.62812234 -1.71052810
>
> colMeans(tmp2)
[1] -0.06038239
> colSums(tmp2)
[1] -6.038239
> colVars(tmp2)
[1] 0.998427
> colSd(tmp2)
[1] 0.9992132
> colMax(tmp2)
[1] 2.625234
> colMin(tmp2)
[1] -2.864787
> colMedians(tmp2)
[1] -0.1464277
> colRanges(tmp2)
[,1]
[1,] -2.864787
[2,] 2.625234
>
> 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] 0.55582119 0.07198868 5.06062938 -1.51735745 5.37988718 -1.33214717
[7] 5.10075625 0.32774332 0.09643764 0.46100606
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.34314721
[2,] -0.17514480
[3,] 0.08180809
[4,] 0.56877590
[5,] 0.83331120
>
> rowApply(tmp,sum)
[1] 0.2828485 7.4679191 5.0946066 -3.3735879 -5.0057809 2.3086127
[7] 1.4765699 3.6917206 3.6838367 -1.4219803
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 6 2 9 10 6 5 6 1 3
[2,] 8 1 7 5 2 2 9 7 5 6
[3,] 9 8 3 8 8 4 7 8 6 4
[4,] 2 9 10 1 1 1 8 2 7 5
[5,] 3 7 9 10 6 10 1 5 3 8
[6,] 4 2 6 7 5 7 2 1 9 1
[7,] 10 4 8 4 3 8 10 3 8 2
[8,] 7 5 4 3 4 3 4 4 10 7
[9,] 5 10 1 6 9 5 3 9 4 9
[10,] 1 3 5 2 7 9 6 10 2 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.9946248 -0.5147813 -0.2065087 4.9777594 2.6516368 0.9030393
[7] 1.2114668 0.4049099 3.1655928 0.2062170 -2.1476323 -3.4012426
[13] -2.0180175 3.1878668 0.4863563 1.7709380 1.7810072 -1.5330440
[19] 0.3185766 -0.9113611
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5612703
[2,] 0.2029191
[3,] 0.4480471
[4,] 1.4319087
[5,] 1.4730201
>
> rowApply(tmp,sum)
[1] 0.8603928 -0.6170721 -0.1475070 5.8599312 6.3716595
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 2 12 19 18
[2,] 19 11 3 1 14
[3,] 1 18 5 20 10
[4,] 11 15 19 18 16
[5,] 18 6 18 11 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.4480471 0.8860941 -3.0469707 0.4996726 0.8834336 -1.3181477
[2,] -1.5612703 -0.2258700 1.2368106 0.6959970 -0.4616207 1.4893536
[3,] 0.2029191 -0.7934806 -0.6206920 1.4525188 0.9977654 0.6755545
[4,] 1.4730201 -1.1146978 1.8731749 1.2693305 0.4740611 0.2452149
[5,] 1.4319087 0.7331730 0.3511685 1.0602406 0.7579975 -0.1889360
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.5932593 0.62269513 1.59231802 -0.1758204 0.5118713 -0.8471100
[2,] -0.5498898 -0.33931401 0.04747796 0.2987548 -0.4212662 -1.3239873
[3,] 1.7636599 -0.06163379 -0.44057089 0.3532201 -0.3257317 -0.9872795
[4,] 0.2256029 1.05443586 0.45889675 -0.9623587 -0.2451359 0.1798913
[5,] 0.3653530 -0.87127324 1.50747093 0.6924212 -1.6673699 -0.4227571
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.5491468 0.6201439 0.7369135 -0.3453931 -0.256785145 0.8235809
[2,] -1.3365475 -0.3099883 -0.3077406 0.6514637 1.031997979 -1.5668331
[3,] -0.6868433 0.5296141 -0.4067402 0.7824839 0.155985562 -0.4683304
[4,] 0.7113095 0.8312945 -0.7945119 0.5847096 0.841919259 0.7886602
[5,] -0.1567894 1.5168026 1.2584356 0.0976739 0.007889545 -1.1101215
[,19] [,20]
[1,] -0.3272568 0.6955126
[2,] 0.7891917 1.5462084
[3,] 0.2201449 -2.4900709
[4,] -1.0492950 -0.9855910
[5,] 0.6857918 0.3225798
>
>
> 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 0.4855953 0.6007159 0.1598437 -1.783932 1.282495 0.07894916 -1.038453
col8 col9 col10 col11 col12 col13 col14
row1 -1.482976 -0.4500745 -0.0152546 -0.3668087 -2.309434 0.0762444 -0.5952556
col15 col16 col17 col18 col19 col20
row1 -0.1387581 1.322331 0.1077433 0.8454661 -1.331277 0.1380536
> tmp[,"col10"]
col10
row1 -0.0152546
row2 -1.4355127
row3 1.1248084
row4 1.1798296
row5 2.3744888
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.4855953 0.6007159 0.1598437 -1.783932 1.2824952 0.07894916 -1.038453
row5 -0.6395211 0.5897494 -0.1834950 1.202295 -0.8992427 -0.70665666 -0.828424
col8 col9 col10 col11 col12 col13 col14
row1 -1.482976 -0.4500745 -0.0152546 -0.3668087 -2.309434 0.0762444 -0.5952556
row5 0.240018 0.7747894 2.3744888 0.8669550 -1.046508 0.9617928 1.2270977
col15 col16 col17 col18 col19 col20
row1 -0.1387581 1.3223315 0.1077433 0.8454661 -1.331277 0.1380536
row5 -0.1537034 -0.6536463 -0.5905628 0.4835034 0.319302 -0.1906974
> tmp[,c("col6","col20")]
col6 col20
row1 0.07894916 0.1380536
row2 -0.03554899 -0.7236617
row3 -1.21586565 1.0518212
row4 -0.40641193 0.7011159
row5 -0.70665666 -0.1906974
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.07894916 0.1380536
row5 -0.70665666 -0.1906974
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.93398 48.94298 48.59003 49.6392 50.46412 105.5834 51.24772 49.09525
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.78255 50.40473 49.93126 49.63773 49.11957 49.75461 48.65258 50.41995
col17 col18 col19 col20
row1 50.41001 50.60066 51.5561 107.1764
> tmp[,"col10"]
col10
row1 50.40473
row2 29.07056
row3 30.18286
row4 30.17404
row5 50.20619
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.93398 48.94298 48.59003 49.63920 50.46412 105.5834 51.24772 49.09525
row5 50.08577 49.22885 48.94510 48.30273 51.28880 106.5262 49.56973 48.60876
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.78255 50.40473 49.93126 49.63773 49.11957 49.75461 48.65258 50.41995
row5 48.61314 50.20619 51.76530 49.95912 50.40045 49.98421 50.75910 49.96664
col17 col18 col19 col20
row1 50.41001 50.60066 51.55610 107.1764
row5 50.40244 49.58003 50.65223 105.5217
> tmp[,c("col6","col20")]
col6 col20
row1 105.58339 107.17637
row2 74.88942 77.41872
row3 74.41666 73.85542
row4 74.35837 75.54240
row5 106.52621 105.52175
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.5834 107.1764
row5 106.5262 105.5217
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.5834 107.1764
row5 106.5262 105.5217
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1618972
[2,] -1.4620753
[3,] 1.1454275
[4,] 1.5199784
[5,] 0.2765887
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.1120351 0.1210203
[2,] 0.7761329 0.1442748
[3,] 0.9989783 -0.6296344
[4,] 2.0125998 -1.0661478
[5,] 1.2197471 1.4175658
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.6223694 0.7847841
[2,] 0.1010638 0.3878688
[3,] 1.7825411 0.6470227
[4,] -0.3836748 0.7745203
[5,] -1.7919250 0.8503652
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.6223694
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.6223694
[2,] 0.1010638
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 1.0664454 1.7221390 0.06579695 0.4156266 -0.09918505 1.7743449
row1 0.1589745 0.5810021 0.26549067 -0.9792945 1.67784678 -0.8145038
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.2604761 -0.4225023 -0.5263903 1.734266 -2.5952387 0.470695 0.9566412
row1 -1.2646952 0.8354566 0.8309139 -1.210900 0.9854556 -1.732228 -0.3852433
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.1709007 -0.80420820 0.4181905 -0.6954184 0.1206605 -0.5436048
row1 -1.8064534 0.01903283 -0.1546202 -0.5179834 1.1103011 0.2078738
[,20]
row3 2.2088783
row1 0.1583932
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2340178 0.821748 0.05964853 0.1948299 1.214611 -0.1846677 0.9457795
[,8] [,9] [,10]
row2 -0.7149842 0.547149 -0.76293
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.4437486 -0.1625871 -1.076088 0.05470158 0.6695337 -0.7372124 -1.363413
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6990343 -0.322433 -0.5706609 1.265642 -1.998109 0.02255828 0.6504889
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.9693855 1.138432 0.06061104 0.6827151 -0.7852247 -1.415134
>
>
> 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: 0x5b60399a1060>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM21010228acdd5c"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2101024008bf14"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2101027a1632cf"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM210102361834f2"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM21010228482d6d"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2101027bc04a91"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM21010214f68abc"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM210102721fd9c4"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2101024283cd89"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2101023454bed5"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM21010264b39175"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2101025df78c69"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM210102898eb68"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM21010265918696"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2101025ec40d49"
>
>
> ### 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: 0x5b603bae0c20>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5b603bae0c20>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5b603bae0c20>
> rowMedians(tmp)
[1] 0.820793345 0.300998661 -0.376236689 0.221028011 -0.459027025
[6] -0.167744942 -0.756573720 0.089640592 -0.127166201 0.434663110
[11] 0.317726248 0.851835407 -0.184406740 0.082868346 -0.162372147
[16] -0.345951584 -0.041138248 -0.437979459 0.120735834 -0.351274838
[21] -0.186771066 -0.070414537 -0.248528722 -0.082002384 0.504334376
[26] -0.239989575 0.639027063 0.501466144 -0.210900813 -0.205825229
[31] -0.335142212 -0.244755764 0.124245029 0.455767273 -0.349894371
[36] 0.040357359 -0.733838366 -0.284827679 0.245843402 -0.431912962
[41] 0.009366357 -0.182945603 0.340558673 0.067470528 0.139170734
[46] -0.120734168 -0.030616407 -0.258370552 0.386912934 -0.269445141
[51] 0.338149289 -0.133602877 -0.151667258 -0.045609953 0.255187403
[56] -0.074151995 -0.636113987 0.044486177 0.359086503 0.065386462
[61] -0.501807758 -0.576134055 0.189616949 -0.530017792 -0.031146660
[66] -0.639158053 -0.051527181 0.200987816 -0.502869772 0.319296772
[71] 0.623082394 0.702041634 -0.291352864 -0.370906370 -0.005485414
[76] -0.289705836 0.225322291 -0.401180023 0.688557130 0.649132265
[81] 0.341633745 -0.582305181 -0.342149478 -0.544165776 -0.200993850
[86] -0.108767855 0.238857554 -0.078207680 0.105546088 -0.182038134
[91] -0.212907221 0.093840782 -0.745020024 0.321749595 -0.085867470
[96] 0.583410448 0.116509458 0.278938517 -0.147543106 -0.011314079
[101] -0.571142109 -0.368124505 -0.831983648 -0.333861071 -0.375221988
[106] -0.375791523 0.250570363 -0.262971683 -0.228930176 0.219035012
[111] -0.355831805 -0.397814785 0.548916324 0.120799933 -0.290331244
[116] 0.175028973 -0.283452390 -0.384563073 0.021498066 -0.039099652
[121] 0.174250499 0.513576671 -0.309443477 0.280453329 -0.304236396
[126] 0.025309163 0.112176988 0.135556937 0.391595884 -0.195991012
[131] 0.002710302 0.293244632 -0.049470442 -1.137106765 0.421684369
[136] -0.136300630 -0.200230860 -0.546967321 -0.005184376 -0.225839324
[141] 0.536009017 -0.347357093 -0.600200072 -0.028857175 -0.166419298
[146] -0.232668342 -0.353981785 0.356783077 0.432936822 -0.395034111
[151] 0.658054108 0.112719441 0.146231417 -0.594856287 0.226092147
[156] 0.122311320 -0.215572825 0.070921264 -0.017550152 0.199872351
[161] 0.335870456 -0.257324562 0.351695629 -0.186730124 0.509226119
[166] 0.467396771 -0.042466494 -0.062377098 0.072958435 0.338455653
[171] -0.014197566 -0.158517771 0.088234591 0.585417280 0.028681968
[176] -0.147696810 0.217803559 0.219740331 -0.140043656 -0.250814271
[181] 0.072063255 0.474251869 0.059377977 -0.547198423 -0.043078044
[186] -0.094772097 -0.135921216 -0.621614270 0.055336302 -0.584734722
[191] -0.206807494 -0.215821169 -0.204203273 0.280215522 0.097743238
[196] -0.271041770 -0.121210558 -0.127784353 -0.089278316 0.526126433
[201] 0.215096406 0.521234546 -0.437559952 -0.258076520 0.305672397
[206] 0.570025607 -0.097649878 0.094364980 -0.230900569 0.264694995
[211] -0.014701311 -0.005663938 0.043711153 -0.265211135 -0.112554091
[216] 0.190703928 0.151958215 0.232604928 -0.221829872 0.476067532
[221] -0.260524017 -0.180376956 -0.030159044 -0.158215543 0.055475817
[226] -0.189373822 -0.102506505 0.671584606 0.274164413 0.303467350
>
> proc.time()
user system elapsed
1.373 1.549 2.911
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: 0x63769d26d0f0>
> .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: 0x63769d26d0f0>
> .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: 0x63769d26d0f0>
> .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: 0x63769d26d0f0>
> 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: 0x63769e0bb690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769e0bb690>
> .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: 0x63769e0bb690>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769e0bb690>
> .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: 0x63769e0bb690>
> 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: 0x63769faf5010>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769faf5010>
> .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: 0x63769faf5010>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x63769faf5010>
> .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: 0x63769faf5010>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x63769faf5010>
> .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: 0x63769faf5010>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x63769faf5010>
> .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: 0x63769faf5010>
> 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: 0x63769fb45070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x63769fb45070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769fb45070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769fb45070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2102881ab9602" "BufferedMatrixFile2102883063d2a8"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2102881ab9602" "BufferedMatrixFile2102883063d2a8"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769d7ff7e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769d7ff7e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x63769d7ff7e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x63769d7ff7e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x63769d7ff7e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x63769d7ff7e0>
> .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: 0x63769f79b3b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63769f79b3b0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x63769f79b3b0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x63769f79b3b0>
> 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: 0x63769d961520>
> .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: 0x63769d961520>
> rm(P)
>
> proc.time()
user system elapsed
0.230 0.064 0.283
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
0.252 0.049 0.287