Ben Bolstad
| Snapshot Date: 2026-05-01 13:45 -0400 (Fri, 01 May 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 2d99771 |
| git_last_commit_date: 2026-04-28 08:32:08 -0400 (Tue, 28 Apr 2026) |
| Back to Build/check report for BioC 3.24: simplified long |
|
This page was generated on 2026-05-02 11:32 -0400 (Sat, 02 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4844 |
| 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 252/2366 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.77.0 (landing page) Ben Bolstad
| nebbiolo2 | 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: 1.77.0 |
| Command: /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings BufferedMatrix_1.77.0.tar.gz |
| StartedAt: 2026-05-01 22:01:27 -0400 (Fri, 01 May 2026) |
| EndedAt: 2026-05-01 22:01:52 -0400 (Fri, 01 May 2026) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings BufferedMatrix_1.77.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.24-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: 2026-05-02 02:01:28 UTC
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.77.0’
* 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-3.24-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.77.0’
** 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-3.24-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-3.24-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-3.24-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-3.24-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-3.24-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-3.24-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.24-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
0.244 0.044 0.275
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-3.24-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] "Fri May 1 22:01:43 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] "Fri May 1 22:01:43 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: 0x599523495520>
>
>
>
> 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] "Fri May 1 22:01:43 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] "Fri May 1 22:01:43 2026"
>
> ColMode(tmp2)
<pointer: 0x599523495520>
>
>
>
> ### 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,] 100.97245432 0.09341549 0.6170159 -1.7194649
[2,] 0.03995258 -0.11340287 -0.6755119 -0.1437946
[3,] 1.11659101 -1.64612082 0.8678471 -1.1101844
[4,] 0.54122999 0.35265651 0.7126903 0.2945198
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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,] 100.97245432 0.09341549 0.6170159 1.7194649
[2,] 0.03995258 0.11340287 0.6755119 0.1437946
[3,] 1.11659101 1.64612082 0.8678471 1.1101844
[4,] 0.54122999 0.35265651 0.7126903 0.2945198
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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,] 10.0485051 0.3056395 0.7855036 1.3112837
[2,] 0.1998814 0.3367534 0.8218953 0.3792026
[3,] 1.0566887 1.2830124 0.9315831 1.0536529
[4,] 0.7356834 0.5938489 0.8442099 0.5426967
>
> 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-3.24-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,] 226.45751 28.14981 33.47205 39.83230
[2,] 27.03877 28.48094 33.89447 28.93582
[3,] 36.68348 39.47624 35.18368 36.64671
[4,] 32.89806 31.29115 34.15479 30.72149
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5995242808f0>
> exp(tmp5)
<pointer: 0x5995242808f0>
> log(tmp5,2)
<pointer: 0x5995242808f0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.3416
> Min(tmp5)
[1] 53.61415
> mean(tmp5)
[1] 71.56707
> Sum(tmp5)
[1] 14313.41
> Var(tmp5)
[1] 875.8947
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.77404 69.62186 73.52927 69.90999 68.05871 71.40970 66.30121 69.59319
[9] 67.60714 70.86560
> rowSums(tmp5)
[1] 1775.481 1392.437 1470.585 1398.200 1361.174 1428.194 1326.024 1391.864
[9] 1352.143 1417.312
> rowVars(tmp5)
[1] 8170.61918 56.02853 51.63158 66.50451 72.00022 75.81990
[7] 78.85998 64.89585 60.13089 91.46814
> rowSd(tmp5)
[1] 90.391477 7.485221 7.185512 8.155030 8.485294 8.707462 8.880314
[8] 8.055796 7.754411 9.563898
> rowMax(tmp5)
[1] 471.34163 86.14069 88.02266 87.14993 84.16085 87.66003 83.71198
[8] 82.96761 81.32425 85.07196
> rowMin(tmp5)
[1] 55.86900 56.27765 59.30708 58.12131 57.17881 55.73022 53.61415 55.22107
[9] 55.42157 54.73025
>
> colMeans(tmp5)
[1] 108.07468 66.95487 70.23791 68.39178 70.26792 65.60174 73.08531
[8] 67.93321 74.51661 67.39333 67.90158 73.77710 72.39373 70.13332
[15] 70.76237 71.87582 67.34993 69.95341 66.98797 67.74883
> colSums(tmp5)
[1] 1080.7468 669.5487 702.3791 683.9178 702.6792 656.0174 730.8531
[8] 679.3321 745.1661 673.9333 679.0158 737.7710 723.9373 701.3332
[15] 707.6237 718.7582 673.4993 699.5341 669.8797 677.4883
> colVars(tmp5)
[1] 16369.63525 92.56609 58.30299 63.05446 82.69948 51.14104
[7] 57.62823 74.11092 64.59217 91.24551 38.30826 41.96823
[13] 117.75662 62.36334 45.50261 97.53079 60.06780 45.89993
[19] 120.75596 40.13504
> colSd(tmp5)
[1] 127.943875 9.621127 7.635640 7.940684 9.093926 7.151297
[7] 7.591326 8.608770 8.036926 9.552252 6.189366 6.478289
[13] 10.851572 7.897046 6.745563 9.875768 7.750342 6.774948
[19] 10.988902 6.335222
> colMax(tmp5)
[1] 471.34163 82.16463 83.47214 82.90572 85.07196 76.01185 87.14993
[8] 81.78230 84.16085 88.02266 79.72972 82.22405 87.66003 83.71198
[15] 77.73491 86.52873 81.38961 85.04582 86.14069 77.15722
> colMin(tmp5)
[1] 54.73025 58.30238 57.22766 56.10671 54.08829 55.73022 61.74469 55.22107
[9] 63.40417 56.60578 61.62715 63.49702 57.22630 55.42157 57.17881 53.61415
[17] 58.02784 58.12131 56.51846 56.70293
>
>
> ### 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] 88.77404 69.62186 73.52927 69.90999 68.05871 71.40970 66.30121 NA
[9] 67.60714 70.86560
> rowSums(tmp5)
[1] 1775.481 1392.437 1470.585 1398.200 1361.174 1428.194 1326.024 NA
[9] 1352.143 1417.312
> rowVars(tmp5)
[1] 8170.61918 56.02853 51.63158 66.50451 72.00022 75.81990
[7] 78.85998 68.49787 60.13089 91.46814
> rowSd(tmp5)
[1] 90.391477 7.485221 7.185512 8.155030 8.485294 8.707462 8.880314
[8] 8.276344 7.754411 9.563898
> rowMax(tmp5)
[1] 471.34163 86.14069 88.02266 87.14993 84.16085 87.66003 83.71198
[8] NA 81.32425 85.07196
> rowMin(tmp5)
[1] 55.86900 56.27765 59.30708 58.12131 57.17881 55.73022 53.61415 NA
[9] 55.42157 54.73025
>
> colMeans(tmp5)
[1] 108.07468 66.95487 70.23791 68.39178 70.26792 65.60174 73.08531
[8] 67.93321 74.51661 67.39333 67.90158 73.77710 NA 70.13332
[15] 70.76237 71.87582 67.34993 69.95341 66.98797 67.74883
> colSums(tmp5)
[1] 1080.7468 669.5487 702.3791 683.9178 702.6792 656.0174 730.8531
[8] 679.3321 745.1661 673.9333 679.0158 737.7710 NA 701.3332
[15] 707.6237 718.7582 673.4993 699.5341 669.8797 677.4883
> colVars(tmp5)
[1] 16369.63525 92.56609 58.30299 63.05446 82.69948 51.14104
[7] 57.62823 74.11092 64.59217 91.24551 38.30826 41.96823
[13] NA 62.36334 45.50261 97.53079 60.06780 45.89993
[19] 120.75596 40.13504
> colSd(tmp5)
[1] 127.943875 9.621127 7.635640 7.940684 9.093926 7.151297
[7] 7.591326 8.608770 8.036926 9.552252 6.189366 6.478289
[13] NA 7.897046 6.745563 9.875768 7.750342 6.774948
[19] 10.988902 6.335222
> colMax(tmp5)
[1] 471.34163 82.16463 83.47214 82.90572 85.07196 76.01185 87.14993
[8] 81.78230 84.16085 88.02266 79.72972 82.22405 NA 83.71198
[15] 77.73491 86.52873 81.38961 85.04582 86.14069 77.15722
> colMin(tmp5)
[1] 54.73025 58.30238 57.22766 56.10671 54.08829 55.73022 61.74469 55.22107
[9] 63.40417 56.60578 61.62715 63.49702 NA 55.42157 57.17881 53.61415
[17] 58.02784 58.12131 56.51846 56.70293
>
> Max(tmp5,na.rm=TRUE)
[1] 471.3416
> Min(tmp5,na.rm=TRUE)
[1] 53.61415
> mean(tmp5,na.rm=TRUE)
[1] 71.57818
> Sum(tmp5,na.rm=TRUE)
[1] 14244.06
> Var(tmp5,na.rm=TRUE)
[1] 880.2936
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.77404 69.62186 73.52927 69.90999 68.05871 71.40970 66.30121 69.60569
[9] 67.60714 70.86560
> rowSums(tmp5,na.rm=TRUE)
[1] 1775.481 1392.437 1470.585 1398.200 1361.174 1428.194 1326.024 1322.508
[9] 1352.143 1417.312
> rowVars(tmp5,na.rm=TRUE)
[1] 8170.61918 56.02853 51.63158 66.50451 72.00022 75.81990
[7] 78.85998 68.49787 60.13089 91.46814
> rowSd(tmp5,na.rm=TRUE)
[1] 90.391477 7.485221 7.185512 8.155030 8.485294 8.707462 8.880314
[8] 8.276344 7.754411 9.563898
> rowMax(tmp5,na.rm=TRUE)
[1] 471.34163 86.14069 88.02266 87.14993 84.16085 87.66003 83.71198
[8] 82.96761 81.32425 85.07196
> rowMin(tmp5,na.rm=TRUE)
[1] 55.86900 56.27765 59.30708 58.12131 57.17881 55.73022 53.61415 55.22107
[9] 55.42157 54.73025
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.07468 66.95487 70.23791 68.39178 70.26792 65.60174 73.08531
[8] 67.93321 74.51661 67.39333 67.90158 73.77710 72.73129 70.13332
[15] 70.76237 71.87582 67.34993 69.95341 66.98797 67.74883
> colSums(tmp5,na.rm=TRUE)
[1] 1080.7468 669.5487 702.3791 683.9178 702.6792 656.0174 730.8531
[8] 679.3321 745.1661 673.9333 679.0158 737.7710 654.5816 701.3332
[15] 707.6237 718.7582 673.4993 699.5341 669.8797 677.4883
> colVars(tmp5,na.rm=TRUE)
[1] 16369.63525 92.56609 58.30299 63.05446 82.69948 51.14104
[7] 57.62823 74.11092 64.59217 91.24551 38.30826 41.96823
[13] 131.19429 62.36334 45.50261 97.53079 60.06780 45.89993
[19] 120.75596 40.13504
> colSd(tmp5,na.rm=TRUE)
[1] 127.943875 9.621127 7.635640 7.940684 9.093926 7.151297
[7] 7.591326 8.608770 8.036926 9.552252 6.189366 6.478289
[13] 11.454008 7.897046 6.745563 9.875768 7.750342 6.774948
[19] 10.988902 6.335222
> colMax(tmp5,na.rm=TRUE)
[1] 471.34163 82.16463 83.47214 82.90572 85.07196 76.01185 87.14993
[8] 81.78230 84.16085 88.02266 79.72972 82.22405 87.66003 83.71198
[15] 77.73491 86.52873 81.38961 85.04582 86.14069 77.15722
> colMin(tmp5,na.rm=TRUE)
[1] 54.73025 58.30238 57.22766 56.10671 54.08829 55.73022 61.74469 55.22107
[9] 63.40417 56.60578 61.62715 63.49702 57.22630 55.42157 57.17881 53.61415
[17] 58.02784 58.12131 56.51846 56.70293
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.77404 69.62186 73.52927 69.90999 68.05871 71.40970 66.30121 NaN
[9] 67.60714 70.86560
> rowSums(tmp5,na.rm=TRUE)
[1] 1775.481 1392.437 1470.585 1398.200 1361.174 1428.194 1326.024 0.000
[9] 1352.143 1417.312
> rowVars(tmp5,na.rm=TRUE)
[1] 8170.61918 56.02853 51.63158 66.50451 72.00022 75.81990
[7] 78.85998 NA 60.13089 91.46814
> rowSd(tmp5,na.rm=TRUE)
[1] 90.391477 7.485221 7.185512 8.155030 8.485294 8.707462 8.880314
[8] NA 7.754411 9.563898
> rowMax(tmp5,na.rm=TRUE)
[1] 471.34163 86.14069 88.02266 87.14993 84.16085 87.66003 83.71198
[8] NA 81.32425 85.07196
> rowMin(tmp5,na.rm=TRUE)
[1] 55.86900 56.27765 59.30708 58.12131 57.17881 55.73022 53.61415 NA
[9] 55.42157 54.73025
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.41414 65.56767 70.74805 68.71350 69.85134 65.80252 72.96745
[8] 69.34567 75.24308 68.02312 68.02549 72.83855 NaN 69.97940
[15] 70.34786 70.88917 67.19459 69.85632 65.21246 68.97615
> colSums(tmp5,na.rm=TRUE)
[1] 1020.7272 590.1090 636.7324 618.4215 628.6621 592.2227 656.7071
[8] 624.1111 677.1878 612.2081 612.2294 655.5470 0.0000 629.8146
[15] 633.1307 638.0025 604.7514 628.7068 586.9121 620.7854
> colVars(tmp5,na.rm=TRUE)
[1] 18095.10413 82.48815 62.66315 69.77184 91.08462 57.08012
[7] 64.67550 60.93054 66.72891 98.18908 42.92406 37.30442
[13] NA 69.89224 49.25743 98.77051 67.30481 51.53135
[19] 100.38533 28.20582
> colSd(tmp5,na.rm=TRUE)
[1] 134.518044 9.082299 7.916006 8.352954 9.543826 7.555139
[7] 8.042108 7.805802 8.168777 9.909040 6.551646 6.107734
[13] NA 8.360158 7.018364 9.938336 8.203951 7.178534
[19] 10.019248 5.310915
> colMax(tmp5,na.rm=TRUE)
[1] 471.34163 82.16463 83.47214 82.90572 85.07196 76.01185 87.14993
[8] 81.78230 84.16085 88.02266 79.72972 80.17478 -Inf 83.71198
[15] 77.73491 86.52873 81.38961 85.04582 86.14069 77.15722
> colMin(tmp5,na.rm=TRUE)
[1] 54.73025 58.30238 57.22766 56.10671 54.08829 55.73022 61.74469 59.30539
[9] 63.40417 56.60578 61.62715 63.49702 Inf 55.42157 57.17881 53.61415
[17] 58.02784 58.12131 56.51846 62.32884
>
>
>
>
> 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] 225.25346 110.70224 207.19824 152.88954 182.54610 96.01261 295.45012
[8] 167.69703 296.88844 218.89362
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 225.25346 110.70224 207.19824 152.88954 182.54610 96.01261 295.45012
[8] 167.69703 296.88844 218.89362
>
>
>
> 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] 3.410605e-13 1.705303e-13 -1.421085e-13 -8.526513e-14 5.684342e-14
[6] -1.136868e-13 -1.136868e-13 5.684342e-14 0.000000e+00 -5.684342e-14
[11] -5.684342e-14 -2.273737e-13 0.000000e+00 0.000000e+00 1.136868e-13
[16] 0.000000e+00 5.684342e-14 2.273737e-13 -9.947598e-14 -8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 13
1 2
7 4
1 8
1 14
5 9
4 19
2 3
3 15
2 2
1 16
5 11
4 9
10 14
5 5
5 9
2 10
3 9
7 10
10 5
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] 2.421371
> Min(tmp)
[1] -2.483261
> mean(tmp)
[1] -0.09300642
> Sum(tmp)
[1] -9.300642
> Var(tmp)
[1] 1.040747
>
> rowMeans(tmp)
[1] -0.09300642
> rowSums(tmp)
[1] -9.300642
> rowVars(tmp)
[1] 1.040747
> rowSd(tmp)
[1] 1.02017
> rowMax(tmp)
[1] 2.421371
> rowMin(tmp)
[1] -2.483261
>
> colMeans(tmp)
[1] -0.505518596 -1.314011934 -0.382260260 -1.125631563 0.016879197
[6] -1.164300082 0.277935862 0.250066647 -0.652737894 0.014183032
[11] -0.372785903 0.940476217 -0.938520624 1.621385645 0.177501658
[16] -0.465029585 -0.256164853 -0.610580936 -0.157948250 0.154842019
[21] 0.093907645 0.062232694 -0.484774624 0.986317096 0.026320048
[26] 0.137152498 0.017157449 -0.165481969 -1.509162913 0.008974782
[31] 0.175102761 -0.452607739 0.029645502 1.208618637 0.724363673
[36] -1.453961316 -1.377252629 2.128055968 0.859139332 -1.578845442
[41] -2.483260853 -1.014669930 -0.126362482 -0.108237865 0.043187509
[46] 0.524543776 -1.266862555 -0.819308644 0.648575578 -2.273494900
[51] 0.058598924 -1.454693353 -0.968709614 -2.348159741 1.364971094
[56] 0.826622667 0.446929553 -0.953789789 -0.320628503 -0.452053351
[61] 1.549955233 0.069308145 -0.077599320 0.800411624 0.022679704
[66] 0.727778218 -0.648462412 2.421371079 1.379823205 0.053690910
[71] 0.656842764 -1.777797808 -0.064591373 1.138749000 0.997824878
[76] -1.663670796 1.306463513 -1.042642941 -1.089585347 -0.546534607
[81] 1.278129145 -0.055133992 1.420592803 -0.226058455 0.930802223
[86] 0.541481875 -2.270675407 0.916372189 -0.439678768 0.274685944
[91] 0.946444826 -0.265681677 0.609043607 -2.346171288 0.763502743
[96] -0.449504382 1.447681606 0.578791476 -0.029621049 -1.405537854
> colSums(tmp)
[1] -0.505518596 -1.314011934 -0.382260260 -1.125631563 0.016879197
[6] -1.164300082 0.277935862 0.250066647 -0.652737894 0.014183032
[11] -0.372785903 0.940476217 -0.938520624 1.621385645 0.177501658
[16] -0.465029585 -0.256164853 -0.610580936 -0.157948250 0.154842019
[21] 0.093907645 0.062232694 -0.484774624 0.986317096 0.026320048
[26] 0.137152498 0.017157449 -0.165481969 -1.509162913 0.008974782
[31] 0.175102761 -0.452607739 0.029645502 1.208618637 0.724363673
[36] -1.453961316 -1.377252629 2.128055968 0.859139332 -1.578845442
[41] -2.483260853 -1.014669930 -0.126362482 -0.108237865 0.043187509
[46] 0.524543776 -1.266862555 -0.819308644 0.648575578 -2.273494900
[51] 0.058598924 -1.454693353 -0.968709614 -2.348159741 1.364971094
[56] 0.826622667 0.446929553 -0.953789789 -0.320628503 -0.452053351
[61] 1.549955233 0.069308145 -0.077599320 0.800411624 0.022679704
[66] 0.727778218 -0.648462412 2.421371079 1.379823205 0.053690910
[71] 0.656842764 -1.777797808 -0.064591373 1.138749000 0.997824878
[76] -1.663670796 1.306463513 -1.042642941 -1.089585347 -0.546534607
[81] 1.278129145 -0.055133992 1.420592803 -0.226058455 0.930802223
[86] 0.541481875 -2.270675407 0.916372189 -0.439678768 0.274685944
[91] 0.946444826 -0.265681677 0.609043607 -2.346171288 0.763502743
[96] -0.449504382 1.447681606 0.578791476 -0.029621049 -1.405537854
> 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] -0.505518596 -1.314011934 -0.382260260 -1.125631563 0.016879197
[6] -1.164300082 0.277935862 0.250066647 -0.652737894 0.014183032
[11] -0.372785903 0.940476217 -0.938520624 1.621385645 0.177501658
[16] -0.465029585 -0.256164853 -0.610580936 -0.157948250 0.154842019
[21] 0.093907645 0.062232694 -0.484774624 0.986317096 0.026320048
[26] 0.137152498 0.017157449 -0.165481969 -1.509162913 0.008974782
[31] 0.175102761 -0.452607739 0.029645502 1.208618637 0.724363673
[36] -1.453961316 -1.377252629 2.128055968 0.859139332 -1.578845442
[41] -2.483260853 -1.014669930 -0.126362482 -0.108237865 0.043187509
[46] 0.524543776 -1.266862555 -0.819308644 0.648575578 -2.273494900
[51] 0.058598924 -1.454693353 -0.968709614 -2.348159741 1.364971094
[56] 0.826622667 0.446929553 -0.953789789 -0.320628503 -0.452053351
[61] 1.549955233 0.069308145 -0.077599320 0.800411624 0.022679704
[66] 0.727778218 -0.648462412 2.421371079 1.379823205 0.053690910
[71] 0.656842764 -1.777797808 -0.064591373 1.138749000 0.997824878
[76] -1.663670796 1.306463513 -1.042642941 -1.089585347 -0.546534607
[81] 1.278129145 -0.055133992 1.420592803 -0.226058455 0.930802223
[86] 0.541481875 -2.270675407 0.916372189 -0.439678768 0.274685944
[91] 0.946444826 -0.265681677 0.609043607 -2.346171288 0.763502743
[96] -0.449504382 1.447681606 0.578791476 -0.029621049 -1.405537854
> colMin(tmp)
[1] -0.505518596 -1.314011934 -0.382260260 -1.125631563 0.016879197
[6] -1.164300082 0.277935862 0.250066647 -0.652737894 0.014183032
[11] -0.372785903 0.940476217 -0.938520624 1.621385645 0.177501658
[16] -0.465029585 -0.256164853 -0.610580936 -0.157948250 0.154842019
[21] 0.093907645 0.062232694 -0.484774624 0.986317096 0.026320048
[26] 0.137152498 0.017157449 -0.165481969 -1.509162913 0.008974782
[31] 0.175102761 -0.452607739 0.029645502 1.208618637 0.724363673
[36] -1.453961316 -1.377252629 2.128055968 0.859139332 -1.578845442
[41] -2.483260853 -1.014669930 -0.126362482 -0.108237865 0.043187509
[46] 0.524543776 -1.266862555 -0.819308644 0.648575578 -2.273494900
[51] 0.058598924 -1.454693353 -0.968709614 -2.348159741 1.364971094
[56] 0.826622667 0.446929553 -0.953789789 -0.320628503 -0.452053351
[61] 1.549955233 0.069308145 -0.077599320 0.800411624 0.022679704
[66] 0.727778218 -0.648462412 2.421371079 1.379823205 0.053690910
[71] 0.656842764 -1.777797808 -0.064591373 1.138749000 0.997824878
[76] -1.663670796 1.306463513 -1.042642941 -1.089585347 -0.546534607
[81] 1.278129145 -0.055133992 1.420592803 -0.226058455 0.930802223
[86] 0.541481875 -2.270675407 0.916372189 -0.439678768 0.274685944
[91] 0.946444826 -0.265681677 0.609043607 -2.346171288 0.763502743
[96] -0.449504382 1.447681606 0.578791476 -0.029621049 -1.405537854
> colMedians(tmp)
[1] -0.505518596 -1.314011934 -0.382260260 -1.125631563 0.016879197
[6] -1.164300082 0.277935862 0.250066647 -0.652737894 0.014183032
[11] -0.372785903 0.940476217 -0.938520624 1.621385645 0.177501658
[16] -0.465029585 -0.256164853 -0.610580936 -0.157948250 0.154842019
[21] 0.093907645 0.062232694 -0.484774624 0.986317096 0.026320048
[26] 0.137152498 0.017157449 -0.165481969 -1.509162913 0.008974782
[31] 0.175102761 -0.452607739 0.029645502 1.208618637 0.724363673
[36] -1.453961316 -1.377252629 2.128055968 0.859139332 -1.578845442
[41] -2.483260853 -1.014669930 -0.126362482 -0.108237865 0.043187509
[46] 0.524543776 -1.266862555 -0.819308644 0.648575578 -2.273494900
[51] 0.058598924 -1.454693353 -0.968709614 -2.348159741 1.364971094
[56] 0.826622667 0.446929553 -0.953789789 -0.320628503 -0.452053351
[61] 1.549955233 0.069308145 -0.077599320 0.800411624 0.022679704
[66] 0.727778218 -0.648462412 2.421371079 1.379823205 0.053690910
[71] 0.656842764 -1.777797808 -0.064591373 1.138749000 0.997824878
[76] -1.663670796 1.306463513 -1.042642941 -1.089585347 -0.546534607
[81] 1.278129145 -0.055133992 1.420592803 -0.226058455 0.930802223
[86] 0.541481875 -2.270675407 0.916372189 -0.439678768 0.274685944
[91] 0.946444826 -0.265681677 0.609043607 -2.346171288 0.763502743
[96] -0.449504382 1.447681606 0.578791476 -0.029621049 -1.405537854
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5055186 -1.314012 -0.3822603 -1.125632 0.0168792 -1.1643 0.2779359
[2,] -0.5055186 -1.314012 -0.3822603 -1.125632 0.0168792 -1.1643 0.2779359
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2500666 -0.6527379 0.01418303 -0.3727859 0.9404762 -0.9385206 1.621386
[2,] 0.2500666 -0.6527379 0.01418303 -0.3727859 0.9404762 -0.9385206 1.621386
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.1775017 -0.4650296 -0.2561649 -0.6105809 -0.1579483 0.154842 0.09390764
[2,] 0.1775017 -0.4650296 -0.2561649 -0.6105809 -0.1579483 0.154842 0.09390764
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.06223269 -0.4847746 0.9863171 0.02632005 0.1371525 0.01715745 -0.165482
[2,] 0.06223269 -0.4847746 0.9863171 0.02632005 0.1371525 0.01715745 -0.165482
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.509163 0.008974782 0.1751028 -0.4526077 0.0296455 1.208619 0.7243637
[2,] -1.509163 0.008974782 0.1751028 -0.4526077 0.0296455 1.208619 0.7243637
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.453961 -1.377253 2.128056 0.8591393 -1.578845 -2.483261 -1.01467
[2,] -1.453961 -1.377253 2.128056 0.8591393 -1.578845 -2.483261 -1.01467
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1263625 -0.1082379 0.04318751 0.5245438 -1.266863 -0.8193086 0.6485756
[2,] -0.1263625 -0.1082379 0.04318751 0.5245438 -1.266863 -0.8193086 0.6485756
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -2.273495 0.05859892 -1.454693 -0.9687096 -2.34816 1.364971 0.8266227
[2,] -2.273495 0.05859892 -1.454693 -0.9687096 -2.34816 1.364971 0.8266227
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4469296 -0.9537898 -0.3206285 -0.4520534 1.549955 0.06930815 -0.07759932
[2,] 0.4469296 -0.9537898 -0.3206285 -0.4520534 1.549955 0.06930815 -0.07759932
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.8004116 0.0226797 0.7277782 -0.6484624 2.421371 1.379823 0.05369091
[2,] 0.8004116 0.0226797 0.7277782 -0.6484624 2.421371 1.379823 0.05369091
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.6568428 -1.777798 -0.06459137 1.138749 0.9978249 -1.663671 1.306464
[2,] 0.6568428 -1.777798 -0.06459137 1.138749 0.9978249 -1.663671 1.306464
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.042643 -1.089585 -0.5465346 1.278129 -0.05513399 1.420593 -0.2260585
[2,] -1.042643 -1.089585 -0.5465346 1.278129 -0.05513399 1.420593 -0.2260585
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.9308022 0.5414819 -2.270675 0.9163722 -0.4396788 0.2746859 0.9464448
[2,] 0.9308022 0.5414819 -2.270675 0.9163722 -0.4396788 0.2746859 0.9464448
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.2656817 0.6090436 -2.346171 0.7635027 -0.4495044 1.447682 0.5787915
[2,] -0.2656817 0.6090436 -2.346171 0.7635027 -0.4495044 1.447682 0.5787915
[,99] [,100]
[1,] -0.02962105 -1.405538
[2,] -0.02962105 -1.405538
>
>
> Max(tmp2)
[1] 2.484248
> Min(tmp2)
[1] -2.302785
> mean(tmp2)
[1] 0.1527969
> Sum(tmp2)
[1] 15.27969
> Var(tmp2)
[1] 0.8899365
>
> rowMeans(tmp2)
[1] 0.437365664 -1.914874970 0.305764392 -0.383563976 1.111715311
[6] 1.157229877 -0.368802940 -0.161178185 1.750465366 0.496744018
[11] -0.870506853 -0.879120683 -0.265692792 -0.048517083 0.050626912
[16] 0.365936364 1.000584577 0.089399267 -1.577766509 0.787213317
[21] -0.086306521 -1.211666685 -0.494065873 -1.355857776 0.247922872
[26] -0.219793774 1.126035187 1.928582002 0.935654284 -0.570983450
[31] 1.123549636 -0.045551119 0.418913944 -0.824925229 0.911874092
[36] -0.477987200 0.826710253 0.859724912 0.024606388 0.029287341
[41] 1.666440386 0.002892212 0.532124651 -1.286175497 0.804259907
[46] -0.234445307 0.755158650 -1.902783708 -1.351963374 -0.034851589
[51] -0.189106172 2.484247703 0.128060900 -0.017395751 0.965239570
[56] -1.086929893 1.396052238 1.573955275 0.963091508 -0.054889138
[61] 0.943495500 -0.798825136 0.028225698 0.686809091 -1.223726629
[66] -0.452004028 -0.481761609 1.285099627 0.761266118 0.709299333
[71] 0.049922369 1.503012473 0.103160177 -1.171027170 -0.802679302
[76] -0.032973247 -1.270224119 -0.597780588 1.781564280 -2.302785221
[81] 0.150022129 0.248377400 0.448670691 -1.054520117 0.731475568
[86] -0.205053363 0.233415322 0.858696687 -0.351618950 0.646992564
[91] 2.015960985 -0.106905964 0.905894563 1.429370576 -0.689985295
[96] -0.084295486 -0.561248316 0.817186946 0.643090304 1.144364530
> rowSums(tmp2)
[1] 0.437365664 -1.914874970 0.305764392 -0.383563976 1.111715311
[6] 1.157229877 -0.368802940 -0.161178185 1.750465366 0.496744018
[11] -0.870506853 -0.879120683 -0.265692792 -0.048517083 0.050626912
[16] 0.365936364 1.000584577 0.089399267 -1.577766509 0.787213317
[21] -0.086306521 -1.211666685 -0.494065873 -1.355857776 0.247922872
[26] -0.219793774 1.126035187 1.928582002 0.935654284 -0.570983450
[31] 1.123549636 -0.045551119 0.418913944 -0.824925229 0.911874092
[36] -0.477987200 0.826710253 0.859724912 0.024606388 0.029287341
[41] 1.666440386 0.002892212 0.532124651 -1.286175497 0.804259907
[46] -0.234445307 0.755158650 -1.902783708 -1.351963374 -0.034851589
[51] -0.189106172 2.484247703 0.128060900 -0.017395751 0.965239570
[56] -1.086929893 1.396052238 1.573955275 0.963091508 -0.054889138
[61] 0.943495500 -0.798825136 0.028225698 0.686809091 -1.223726629
[66] -0.452004028 -0.481761609 1.285099627 0.761266118 0.709299333
[71] 0.049922369 1.503012473 0.103160177 -1.171027170 -0.802679302
[76] -0.032973247 -1.270224119 -0.597780588 1.781564280 -2.302785221
[81] 0.150022129 0.248377400 0.448670691 -1.054520117 0.731475568
[86] -0.205053363 0.233415322 0.858696687 -0.351618950 0.646992564
[91] 2.015960985 -0.106905964 0.905894563 1.429370576 -0.689985295
[96] -0.084295486 -0.561248316 0.817186946 0.643090304 1.144364530
> 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] 0.437365664 -1.914874970 0.305764392 -0.383563976 1.111715311
[6] 1.157229877 -0.368802940 -0.161178185 1.750465366 0.496744018
[11] -0.870506853 -0.879120683 -0.265692792 -0.048517083 0.050626912
[16] 0.365936364 1.000584577 0.089399267 -1.577766509 0.787213317
[21] -0.086306521 -1.211666685 -0.494065873 -1.355857776 0.247922872
[26] -0.219793774 1.126035187 1.928582002 0.935654284 -0.570983450
[31] 1.123549636 -0.045551119 0.418913944 -0.824925229 0.911874092
[36] -0.477987200 0.826710253 0.859724912 0.024606388 0.029287341
[41] 1.666440386 0.002892212 0.532124651 -1.286175497 0.804259907
[46] -0.234445307 0.755158650 -1.902783708 -1.351963374 -0.034851589
[51] -0.189106172 2.484247703 0.128060900 -0.017395751 0.965239570
[56] -1.086929893 1.396052238 1.573955275 0.963091508 -0.054889138
[61] 0.943495500 -0.798825136 0.028225698 0.686809091 -1.223726629
[66] -0.452004028 -0.481761609 1.285099627 0.761266118 0.709299333
[71] 0.049922369 1.503012473 0.103160177 -1.171027170 -0.802679302
[76] -0.032973247 -1.270224119 -0.597780588 1.781564280 -2.302785221
[81] 0.150022129 0.248377400 0.448670691 -1.054520117 0.731475568
[86] -0.205053363 0.233415322 0.858696687 -0.351618950 0.646992564
[91] 2.015960985 -0.106905964 0.905894563 1.429370576 -0.689985295
[96] -0.084295486 -0.561248316 0.817186946 0.643090304 1.144364530
> rowMin(tmp2)
[1] 0.437365664 -1.914874970 0.305764392 -0.383563976 1.111715311
[6] 1.157229877 -0.368802940 -0.161178185 1.750465366 0.496744018
[11] -0.870506853 -0.879120683 -0.265692792 -0.048517083 0.050626912
[16] 0.365936364 1.000584577 0.089399267 -1.577766509 0.787213317
[21] -0.086306521 -1.211666685 -0.494065873 -1.355857776 0.247922872
[26] -0.219793774 1.126035187 1.928582002 0.935654284 -0.570983450
[31] 1.123549636 -0.045551119 0.418913944 -0.824925229 0.911874092
[36] -0.477987200 0.826710253 0.859724912 0.024606388 0.029287341
[41] 1.666440386 0.002892212 0.532124651 -1.286175497 0.804259907
[46] -0.234445307 0.755158650 -1.902783708 -1.351963374 -0.034851589
[51] -0.189106172 2.484247703 0.128060900 -0.017395751 0.965239570
[56] -1.086929893 1.396052238 1.573955275 0.963091508 -0.054889138
[61] 0.943495500 -0.798825136 0.028225698 0.686809091 -1.223726629
[66] -0.452004028 -0.481761609 1.285099627 0.761266118 0.709299333
[71] 0.049922369 1.503012473 0.103160177 -1.171027170 -0.802679302
[76] -0.032973247 -1.270224119 -0.597780588 1.781564280 -2.302785221
[81] 0.150022129 0.248377400 0.448670691 -1.054520117 0.731475568
[86] -0.205053363 0.233415322 0.858696687 -0.351618950 0.646992564
[91] 2.015960985 -0.106905964 0.905894563 1.429370576 -0.689985295
[96] -0.084295486 -0.561248316 0.817186946 0.643090304 1.144364530
>
> colMeans(tmp2)
[1] 0.1527969
> colSums(tmp2)
[1] 15.27969
> colVars(tmp2)
[1] 0.8899365
> colSd(tmp2)
[1] 0.9433645
> colMax(tmp2)
[1] 2.484248
> colMin(tmp2)
[1] -2.302785
> colMedians(tmp2)
[1] 0.07001309
> colRanges(tmp2)
[,1]
[1,] -2.302785
[2,] 2.484248
>
> 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] 1.4328692 0.6334373 -3.4094247 -4.0605767 3.7249201 4.2526908
[7] 1.1899616 4.0407327 -1.0760320 -1.5894973
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1148433
[2,] -0.3871703
[3,] 0.2541322
[4,] 0.5046327
[5,] 1.7491930
>
> rowApply(tmp,sum)
[1] 2.699235 6.328737 3.478247 -1.721935 -3.580609 -4.472681 0.958152
[8] 1.560493 -1.314485 1.203927
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 10 3 3 3 6 6 7 5 8
[2,] 5 2 7 7 8 8 5 6 1 6
[3,] 9 5 1 5 5 1 1 2 6 10
[4,] 2 7 2 1 6 7 8 4 2 5
[5,] 3 6 6 8 2 10 10 3 8 4
[6,] 7 4 8 9 9 5 4 5 10 3
[7,] 10 1 5 10 1 3 9 9 7 7
[8,] 8 9 9 6 10 2 7 1 4 9
[9,] 4 8 4 2 7 4 2 10 9 2
[10,] 1 3 10 4 4 9 3 8 3 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.2020163 -0.8201159 2.0326822 4.0550585 0.5802763 -4.1096007
[7] -2.9023177 -0.4791937 3.7108076 0.2305955 -1.8853891 -1.0267995
[13] 0.8248661 0.9276986 0.0914522 -0.4444395 0.1295081 -0.5999987
[19] -2.8179617 1.4097911
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0333027
[2,] -0.5501919
[3,] -0.4477500
[4,] -0.3600563
[5,] 0.1892846
>
> rowApply(tmp,sum)
[1] -2.484568 3.709136 -1.839143 -4.894252 2.213730
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 6 9 8 3
[2,] 20 9 1 20 1
[3,] 15 11 20 2 19
[4,] 11 18 17 19 16
[5,] 10 4 11 14 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1892846 1.2656358 0.3320026 0.06038275 0.05835697 -1.7817966
[2,] -0.5501919 -0.3432069 -0.1447554 1.93767230 -0.80816128 -0.7155538
[3,] -0.4477500 -1.3138169 2.3966244 0.71602057 -0.19731221 -0.8007979
[4,] -0.3600563 0.9464547 -1.7663287 0.75553001 0.35001033 -0.9881146
[5,] -1.0333027 -1.3751827 1.2151392 0.58545284 1.17738250 0.1766621
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.70913363 0.54951574 0.504651561 -1.4286379 -0.07845027 -1.0668022
[2,] -0.43338730 0.02188112 1.364688392 -2.1393816 0.84047675 1.7804023
[3,] -1.06829688 -0.95508588 -0.004661387 1.0244564 -0.29098454 -1.0290720
[4,] -0.07603151 -0.66702547 0.649353712 0.3919713 -2.60355313 -0.4734350
[5,] -0.61546833 0.57152082 1.196775308 2.3821873 0.24712204 -0.2378926
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.1613529 -0.45661777 0.2308309 -0.6221794 0.5267709 -0.3348571
[2,] 1.9707383 1.97469855 -0.8881939 0.6861623 -0.3838731 -0.1490113
[3,] -0.7963626 0.59610470 0.5928171 -0.1617379 -0.5272675 -1.0090141
[4,] -0.2472160 -1.22439089 0.6394702 -0.1022145 0.7078794 0.3146110
[5,] -0.2636464 0.03790405 -0.4834721 -0.2444700 -0.1940015 0.5782727
[,19] [,20]
[1,] -0.7955482 0.9106708
[2,] -0.9344049 0.6225375
[3,] 0.1437893 1.2932044
[4,] -0.1465462 -0.9946208
[5,] -1.0852518 -0.4220006
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.24-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-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.237101 -0.09875794 -1.930764 -0.3861882 -1.228043 -1.348179 -0.475081
col8 col9 col10 col11 col12 col13 col14
row1 2.1259 -1.38937 -0.4907883 0.4841475 -0.02539275 -1.350419 0.6637154
col15 col16 col17 col18 col19 col20
row1 0.198439 -1.210852 -1.244435 -0.3921905 -0.6533327 0.5990724
> tmp[,"col10"]
col10
row1 -0.49078830
row2 1.85950042
row3 -0.75890910
row4 1.01011081
row5 -0.09242809
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.2371013 -0.09875794 -1.930764 -0.3861882 -1.228043 -1.3481792 -0.4750810
row5 0.8863605 -0.28797290 -1.716883 1.3461219 2.264558 0.2796782 0.1119766
col8 col9 col10 col11 col12 col13
row1 2.1258998 -1.389370 -0.49078830 0.4841475 -0.02539275 -1.3504187
row5 0.8314201 1.228801 -0.09242809 0.3417825 -1.12525544 -0.3214206
col14 col15 col16 col17 col18 col19 col20
row1 0.6637154 0.198439 -1.2108516 -1.2444346 -0.3921905 -0.6533327 0.5990724
row5 -0.1523047 1.275359 -0.8362597 0.5415842 -0.3463746 0.8958906 -1.7212945
> tmp[,c("col6","col20")]
col6 col20
row1 -1.34817918 0.5990724
row2 -0.04794052 0.5541044
row3 1.02845539 -0.3711954
row4 0.96249288 -0.8828026
row5 0.27967823 -1.7212945
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.3481792 0.5990724
row5 0.2796782 -1.7212945
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.05964 50.03259 50.66768 50.2359 50.54649 106.026 50.55834 49.41406
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.62305 49.59621 48.93092 50.21307 49.65356 48.6873 49.95363 50.22045
col17 col18 col19 col20
row1 50.39283 51.77292 50.46818 104.3625
> tmp[,"col10"]
col10
row1 49.59621
row2 30.24494
row3 31.32233
row4 28.87622
row5 48.44571
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.05964 50.03259 50.66768 50.23590 50.54649 106.0260 50.55834 49.41406
row5 49.20580 51.00572 50.37705 51.98086 49.88029 106.0113 50.43299 50.48501
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.62305 49.59621 48.93092 50.21307 49.65356 48.68730 49.95363 50.22045
row5 50.36761 48.44571 50.31659 50.02384 51.26789 50.68061 48.56309 50.36681
col17 col18 col19 col20
row1 50.39283 51.77292 50.46818 104.3625
row5 50.82133 50.35955 50.08835 104.2718
> tmp[,c("col6","col20")]
col6 col20
row1 106.02605 104.36254
row2 75.79512 75.09595
row3 75.56180 74.26027
row4 75.09878 77.76861
row5 106.01133 104.27184
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.0260 104.3625
row5 106.0113 104.2718
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.0260 104.3625
row5 106.0113 104.2718
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.6347178
[2,] 0.9506235
[3,] -0.4944339
[4,] -1.8006078
[5,] 0.5698086
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.09850408 0.3542522158
[2,] 0.06876731 -0.1291286639
[3,] -1.06249245 -0.0002257324
[4,] 1.22545115 1.5335326270
[5,] -0.07017088 -0.7742334697
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.9220179 -1.4581242
[2,] -1.0350319 1.5346835
[3,] 0.0194618 -0.3570020
[4,] 2.3931328 1.3799433
[5,] -0.3887139 -0.3214503
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9220179
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9220179
[2,] -1.0350319
>
>
>
> 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 0.2005650 0.7320891 -1.239445 2.0810876 -1.225054 -0.2022624 1.8914455
row1 -0.6699626 -1.3213936 1.089610 -0.3150624 1.075691 0.2052969 0.8160139
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.4310556 1.1189601 -0.8018432 0.1364444 0.3697321 -1.900184 -0.6001941
row1 -0.5840590 0.2891091 0.3960856 -2.6262968 -0.2846070 1.001281 2.3343678
[,15] [,16] [,17] [,18] [,19] [,20]
row3 3.313591 -0.3482994 -0.2635911 -1.838072 -0.4149728 0.3283678
row1 0.487892 -0.9688211 0.7597606 1.847613 -1.1269803 0.7410412
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5128621 0.7566864 -0.565056 0.3056905 0.0005971756 0.01530624 0.5399635
[,8] [,9] [,10]
row2 -2.091834 -1.309719 -0.6082702
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.7504852 0.7634022 1.185054 -1.319052 -0.6148559 0.2897168 0.5282409
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.63207 -0.5578261 -0.8181023 -0.1251341 -0.9250965 -0.7348039 -0.4000377
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.9378088 0.2586928 0.7100421 -0.2593295 -0.762124 -0.5689137
>
>
> 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: 0x599523a3aed0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62246cb2c592"
[2] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62246e835952"
[3] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a6224287e056c"
[4] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62245273097f"
[5] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62248c757db"
[6] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62243f724153"
[7] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a6224644e4ab3"
[8] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62246b4bfdcb"
[9] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62245a4b5caf"
[10] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62242c6b160a"
[11] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a622449336077"
[12] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62246e10d5f0"
[13] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a622434d04121"
[14] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a622454affa52"
[15] "/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM2a62242c3871b5"
>
>
> ### 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: 0x5995255a7b60>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5995255a7b60>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5995255a7b60>
> rowMedians(tmp)
[1] -0.5119456455 0.3109239020 0.2087235072 0.1192420451 0.1436383370
[6] 0.0172861831 0.1377507236 0.0478851211 0.1453303600 -0.4737756335
[11] 0.0784236628 0.3888955953 -0.4047670639 0.3259309480 0.2050381573
[16] -0.4121361044 0.3322894957 -0.1133533803 0.5147716959 0.5870545098
[21] 0.3400560429 -0.1061556259 -0.0602587044 -0.0293479078 0.0279500336
[26] 0.3225871582 0.1538502822 -0.3898278102 -0.0938392238 -0.3223490473
[31] 0.0438600190 0.1997469655 0.3925750482 -0.2513978870 -0.4486092610
[36] 0.3358610781 0.3461464844 0.3675439880 0.2045115319 -0.3986971284
[41] -0.4079782519 0.0575429551 0.0067771377 -0.7786923300 0.1327688736
[46] 0.5943240871 0.2800177510 -0.0165359300 -0.1040528796 0.0339786364
[51] -0.0669621753 -0.0586973758 0.0910170857 0.3460800296 -0.4075084712
[56] 0.3627578567 -0.7779946004 0.2095518523 -0.2305244338 -0.3331413426
[61] -0.2752778581 0.6459613253 -0.2218814264 0.1345846752 0.2258582901
[66] -0.3677047097 -0.1732374444 0.1891978890 0.1910012220 -0.5947001005
[71] 0.3623166969 0.4860196895 0.2547787274 -0.2738021824 -1.0140128743
[76] -0.0969997390 0.3893053731 -0.3821754785 -0.2352030817 -0.0757945746
[81] -0.5479336449 0.2136629493 -0.1752669071 -0.1283690706 0.0117159951
[86] -0.0739667503 0.3053105365 -0.0462569662 0.0861186925 0.2610408904
[91] 0.2272951093 -0.6311262213 -0.3267884328 0.4088203958 0.0353497664
[96] 0.1771690045 -0.2979258912 -0.2063040093 0.5570045888 -0.2379047273
[101] -0.5292924799 0.0390679374 0.2443150831 0.0780196071 0.0391822374
[106] -0.2965390227 -0.3430411060 0.2877229374 0.6557711066 -0.1835442516
[111] 0.1142726874 0.1342664515 -0.1029789978 0.2927620349 -0.2974224349
[116] 0.3083303359 0.2646756018 -0.2343695342 -0.1059585933 0.1251703702
[121] -0.2756189084 -0.0879983390 0.0069936153 0.2735404500 0.6148868821
[126] 0.3754369143 0.3770986305 0.2468058519 0.3101908977 0.6860478331
[131] -0.0199148010 -0.3965158090 -0.4725870826 0.8477634977 0.3408755641
[136] -0.2473143063 -0.4410060225 -0.6326751119 -0.2945086823 0.0003177534
[141] -0.1106664339 0.0036455689 0.2623801254 0.0266198861 -0.3308784853
[146] 0.1399565487 0.8621151658 -0.0697751623 0.2036111274 -0.0942234334
[151] 0.1557394614 0.1246540484 -0.1452548670 -0.1962307610 -0.7949370073
[156] 0.1861325188 0.3199776022 0.4691320567 0.9724631917 -0.2188274436
[161] 0.3785894693 -0.2200398614 0.2131107449 -0.1738313248 0.2117416052
[166] 0.1227551003 0.0837309095 0.1278219747 0.4222465336 0.2588487562
[171] -0.2185697209 0.0900563149 -0.1843422156 -0.2125946642 0.3797033033
[176] 0.0005416873 -0.7106134282 0.5020516663 -0.2334880306 -0.3388169253
[181] -0.3442371381 -0.2928016665 -0.5648038877 0.0519087032 0.0821471083
[186] 0.0056199492 -0.0398308104 0.0139158707 0.4604448300 0.3758521952
[191] 0.1197085508 0.0535346775 -0.4510938631 -0.0302338481 -0.0652379315
[196] 0.0325945370 -0.3718757101 0.1583093820 -0.3645523625 -0.1706987506
[201] -0.1216430046 -0.1615024616 0.5433348232 -0.0148468030 0.5060424580
[206] 0.2072411336 0.2556750978 -0.1421335964 -0.4502519688 0.0618731470
[211] 0.2655721066 -0.0406477879 -0.8225464349 0.2379837178 0.2089642648
[216] 0.1547107332 0.1380398048 -0.2708066726 -0.1719349304 0.0544019952
[221] -0.0168937108 -0.4448990860 0.1682385397 -0.1373588889 0.0428756866
[226] -0.0731942007 0.3230685005 0.6865645831 -0.4079654719 0.4248963061
>
> proc.time()
user system elapsed
1.225 0.716 1.930
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: 0x5645cf764520>
> .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: 0x5645cf764520>
> .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: 0x5645cf764520>
> .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: 0x5645cf764520>
> 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: 0x5645cf30df60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cf30df60>
> .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: 0x5645cf30df60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cf30df60>
> .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: 0x5645cf30df60>
> 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: 0x5645cfeb7b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cfeb7b40>
> .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: 0x5645cfeb7b40>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5645cfeb7b40>
> .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: 0x5645cfeb7b40>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5645cfeb7b40>
> .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: 0x5645cfeb7b40>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5645cfeb7b40>
> .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: 0x5645cfeb7b40>
> 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: 0x5645cfef4bc0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5645cfef4bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cfef4bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cfef4bc0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2a63c8144b9b26" "BufferedMatrixFile2a63c835ecddee"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2a63c8144b9b26" "BufferedMatrixFile2a63c835ecddee"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cfe8e000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cfe8e000>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5645cfe8e000>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5645cfe8e000>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5645cfe8e000>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5645cfe8e000>
> .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: 0x5645cefc1e30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5645cefc1e30>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5645cefc1e30>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5645cefc1e30>
> 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: 0x5645cf5eba50>
> .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: 0x5645cf5eba50>
> rm(P)
>
> proc.time()
user system elapsed
0.263 0.045 0.296
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
0.241 0.045 0.272