Ben Bolstad
| Snapshot Date: 2026-01-14 13:40 -0500 (Wed, 14 Jan 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-01-15 11:34 -0500 (Thu, 15 Jan 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences" | 4848 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4628 |
| 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 253/2343 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.75.0 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz |
| StartedAt: 2026-01-14 21:47:15 -0500 (Wed, 14 Jan 2026) |
| EndedAt: 2026-01-14 21:47:40 -0500 (Wed, 14 Jan 2026) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-12-22 r89219)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.75.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ...* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.23-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.23-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.23-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences"
Copyright (C) 2025 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
0.251 0.060 0.297
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences"
Copyright (C) 2025 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 478851 25.6 1048487 56 639317 34.2
Vcells 885659 6.8 8388608 64 2082734 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 Jan 14 21:47:30 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 Jan 14 21:47:30 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: 0x5929b961e2b0>
>
>
>
> 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 Jan 14 21:47:31 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 Jan 14 21:47:31 2026"
>
> ColMode(tmp2)
<pointer: 0x5929b961e2b0>
>
>
>
> ### 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,] 98.93956229 -1.8156961 -1.6876149 -1.92240083
[2,] 0.08081434 -1.9596927 1.1286478 0.08462404
[3,] 1.30984657 0.5106037 -0.8306336 -1.55096871
[4,] -0.22202923 -1.4253131 -0.8148425 1.46702722
> 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,] 98.93956229 1.8156961 1.6876149 1.92240083
[2,] 0.08081434 1.9596927 1.1286478 0.08462404
[3,] 1.30984657 0.5106037 0.8306336 1.55096871
[4,] 0.22202923 1.4253131 0.8148425 1.46702722
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9468368 1.3474777 1.2990823 1.3865067
[2,] 0.2842786 1.3998903 1.0623784 0.2909021
[3,] 1.1444853 0.7145654 0.9113911 1.2453789
[4,] 0.4711998 1.1938648 0.9026862 1.2112090
>
> 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,] 223.40793 40.29047 39.67844 40.78747
[2,] 27.92360 40.95860 36.75243 27.99365
[3,] 37.75470 32.65626 34.94454 39.00476
[4,] 29.93403 38.36396 34.84170 38.57912
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5929b9d25500>
> exp(tmp5)
<pointer: 0x5929b9d25500>
> log(tmp5,2)
<pointer: 0x5929b9d25500>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 464.9943
> Min(tmp5)
[1] 55.11969
> mean(tmp5)
[1] 72.69042
> Sum(tmp5)
[1] 14538.08
> Var(tmp5)
[1] 853.3565
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.70728 67.52219 71.07122 73.06521 71.55043 70.29395 67.29098 70.61734
[9] 73.87499 70.91064
> rowSums(tmp5)
[1] 1814.146 1350.444 1421.424 1461.304 1431.009 1405.879 1345.820 1412.347
[9] 1477.500 1418.213
> rowVars(tmp5)
[1] 7834.78335 67.19502 60.05346 83.05223 101.07277 85.71088
[7] 57.76211 73.60053 76.47071 77.93239
> rowSd(tmp5)
[1] 88.514312 8.197257 7.749417 9.113300 10.053496 9.258017 7.600139
[8] 8.579075 8.744753 8.827933
> rowMax(tmp5)
[1] 464.99434 85.24995 85.40378 88.45619 91.03060 88.53700 80.66997
[8] 83.99956 90.77826 91.84293
> rowMin(tmp5)
[1] 58.58596 58.11932 58.78911 57.41838 55.11969 55.36396 56.22818 55.32191
[9] 61.90309 55.46082
>
> colMeans(tmp5)
[1] 111.34822 74.17721 74.16690 67.93275 69.37164 69.02384 70.57035
[8] 73.36743 71.37498 67.80706 70.83816 72.24650 68.87019 67.63518
[15] 70.12943 74.30502 65.88497 70.90768 75.15545 68.69550
> colSums(tmp5)
[1] 1113.4822 741.7721 741.6690 679.3275 693.7164 690.2384 705.7035
[8] 733.6743 713.7498 678.0706 708.3816 722.4650 688.7019 676.3518
[15] 701.2943 743.0502 658.8497 709.0768 751.5545 686.9550
> colVars(tmp5)
[1] 15538.32730 84.59032 77.21395 129.40466 83.60870 62.54662
[7] 58.19105 63.20916 60.84326 27.96594 74.93523 84.55385
[13] 67.24251 124.28847 103.58429 100.07890 50.44023 40.49915
[19] 104.35443 42.88051
> colSd(tmp5)
[1] 124.652827 9.197299 8.787147 11.375617 9.143779 7.908642
[7] 7.628306 7.950419 7.800209 5.288283 8.656514 9.195317
[13] 8.200153 11.148474 10.177637 10.003944 7.102129 6.363894
[19] 10.215402 6.548321
> colMax(tmp5)
[1] 464.99434 85.24995 91.84293 84.89377 85.40378 80.51704 83.99956
[8] 84.71253 81.72422 76.69740 81.56283 88.53700 83.84552 85.01580
[15] 90.77826 88.84172 77.23835 82.55815 88.45619 77.34397
> colMin(tmp5)
[1] 58.11932 58.67210 60.58426 55.32191 56.93134 57.06569 61.87810 61.40918
[9] 60.11767 57.97779 57.42573 56.48074 58.42753 55.11969 58.58596 55.46082
[17] 57.41838 59.93557 60.66134 56.22818
>
>
> ### 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] 90.70728 67.52219 71.07122 73.06521 NA 70.29395 67.29098 70.61734
[9] 73.87499 70.91064
> rowSums(tmp5)
[1] 1814.146 1350.444 1421.424 1461.304 NA 1405.879 1345.820 1412.347
[9] 1477.500 1418.213
> rowVars(tmp5)
[1] 7834.78335 67.19502 60.05346 83.05223 99.43213 85.71088
[7] 57.76211 73.60053 76.47071 77.93239
> rowSd(tmp5)
[1] 88.514312 8.197257 7.749417 9.113300 9.971566 9.258017 7.600139
[8] 8.579075 8.744753 8.827933
> rowMax(tmp5)
[1] 464.99434 85.24995 85.40378 88.45619 NA 88.53700 80.66997
[8] 83.99956 90.77826 91.84293
> rowMin(tmp5)
[1] 58.58596 58.11932 58.78911 57.41838 NA 55.36396 56.22818 55.32191
[9] 61.90309 55.46082
>
> colMeans(tmp5)
[1] 111.34822 74.17721 74.16690 67.93275 69.37164 69.02384 70.57035
[8] 73.36743 71.37498 67.80706 70.83816 72.24650 68.87019 67.63518
[15] NA 74.30502 65.88497 70.90768 75.15545 68.69550
> colSums(tmp5)
[1] 1113.4822 741.7721 741.6690 679.3275 693.7164 690.2384 705.7035
[8] 733.6743 713.7498 678.0706 708.3816 722.4650 688.7019 676.3518
[15] NA 743.0502 658.8497 709.0768 751.5545 686.9550
> colVars(tmp5)
[1] 15538.32730 84.59032 77.21395 129.40466 83.60870 62.54662
[7] 58.19105 63.20916 60.84326 27.96594 74.93523 84.55385
[13] 67.24251 124.28847 NA 100.07890 50.44023 40.49915
[19] 104.35443 42.88051
> colSd(tmp5)
[1] 124.652827 9.197299 8.787147 11.375617 9.143779 7.908642
[7] 7.628306 7.950419 7.800209 5.288283 8.656514 9.195317
[13] 8.200153 11.148474 NA 10.003944 7.102129 6.363894
[19] 10.215402 6.548321
> colMax(tmp5)
[1] 464.99434 85.24995 91.84293 84.89377 85.40378 80.51704 83.99956
[8] 84.71253 81.72422 76.69740 81.56283 88.53700 83.84552 85.01580
[15] NA 88.84172 77.23835 82.55815 88.45619 77.34397
> colMin(tmp5)
[1] 58.11932 58.67210 60.58426 55.32191 56.93134 57.06569 61.87810 61.40918
[9] 60.11767 57.97779 57.42573 56.48074 58.42753 55.11969 NA 55.46082
[17] 57.41838 59.93557 60.66134 56.22818
>
> Max(tmp5,na.rm=TRUE)
[1] 464.9943
> Min(tmp5,na.rm=TRUE)
[1] 55.11969
> mean(tmp5,na.rm=TRUE)
[1] 72.75213
> Sum(tmp5,na.rm=TRUE)
[1] 14477.67
> Var(tmp5,na.rm=TRUE)
[1] 856.9011
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.70728 67.52219 71.07122 73.06521 72.13669 70.29395 67.29098 70.61734
[9] 73.87499 70.91064
> rowSums(tmp5,na.rm=TRUE)
[1] 1814.146 1350.444 1421.424 1461.304 1370.597 1405.879 1345.820 1412.347
[9] 1477.500 1418.213
> rowVars(tmp5,na.rm=TRUE)
[1] 7834.78335 67.19502 60.05346 83.05223 99.43213 85.71088
[7] 57.76211 73.60053 76.47071 77.93239
> rowSd(tmp5,na.rm=TRUE)
[1] 88.514312 8.197257 7.749417 9.113300 9.971566 9.258017 7.600139
[8] 8.579075 8.744753 8.827933
> rowMax(tmp5,na.rm=TRUE)
[1] 464.99434 85.24995 85.40378 88.45619 91.03060 88.53700 80.66997
[8] 83.99956 90.77826 91.84293
> rowMin(tmp5,na.rm=TRUE)
[1] 58.58596 58.11932 58.78911 57.41838 55.11969 55.36396 56.22818 55.32191
[9] 61.90309 55.46082
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.34822 74.17721 74.16690 67.93275 69.37164 69.02384 70.57035
[8] 73.36743 71.37498 67.80706 70.83816 72.24650 68.87019 67.63518
[15] 71.20919 74.30502 65.88497 70.90768 75.15545 68.69550
> colSums(tmp5,na.rm=TRUE)
[1] 1113.4822 741.7721 741.6690 679.3275 693.7164 690.2384 705.7035
[8] 733.6743 713.7498 678.0706 708.3816 722.4650 688.7019 676.3518
[15] 640.8827 743.0502 658.8497 709.0768 751.5545 686.9550
> colVars(tmp5,na.rm=TRUE)
[1] 15538.32730 84.59032 77.21395 129.40466 83.60870 62.54662
[7] 58.19105 63.20916 60.84326 27.96594 74.93523 84.55385
[13] 67.24251 124.28847 103.41612 100.07890 50.44023 40.49915
[19] 104.35443 42.88051
> colSd(tmp5,na.rm=TRUE)
[1] 124.652827 9.197299 8.787147 11.375617 9.143779 7.908642
[7] 7.628306 7.950419 7.800209 5.288283 8.656514 9.195317
[13] 8.200153 11.148474 10.169372 10.003944 7.102129 6.363894
[19] 10.215402 6.548321
> colMax(tmp5,na.rm=TRUE)
[1] 464.99434 85.24995 91.84293 84.89377 85.40378 80.51704 83.99956
[8] 84.71253 81.72422 76.69740 81.56283 88.53700 83.84552 85.01580
[15] 90.77826 88.84172 77.23835 82.55815 88.45619 77.34397
> colMin(tmp5,na.rm=TRUE)
[1] 58.11932 58.67210 60.58426 55.32191 56.93134 57.06569 61.87810 61.40918
[9] 60.11767 57.97779 57.42573 56.48074 58.42753 55.11969 58.58596 55.46082
[17] 57.41838 59.93557 60.66134 56.22818
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.70728 67.52219 71.07122 73.06521 NaN 70.29395 67.29098 70.61734
[9] 73.87499 70.91064
> rowSums(tmp5,na.rm=TRUE)
[1] 1814.146 1350.444 1421.424 1461.304 0.000 1405.879 1345.820 1412.347
[9] 1477.500 1418.213
> rowVars(tmp5,na.rm=TRUE)
[1] 7834.78335 67.19502 60.05346 83.05223 NA 85.71088
[7] 57.76211 73.60053 76.47071 77.93239
> rowSd(tmp5,na.rm=TRUE)
[1] 88.514312 8.197257 7.749417 9.113300 NA 9.258017 7.600139
[8] 8.579075 8.744753 8.827933
> rowMax(tmp5,na.rm=TRUE)
[1] 464.99434 85.24995 85.40378 88.45619 NA 88.53700 80.66997
[8] 83.99956 90.77826 91.84293
> rowMin(tmp5,na.rm=TRUE)
[1] 58.58596 58.11932 58.78911 57.41838 NA 55.36396 56.22818 55.32191
[9] 61.90309 55.46082
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.60574 74.22730 74.40008 69.07048 69.46703 69.87741 71.17600
[8] 73.57022 70.41926 68.57102 69.84511 71.23416 68.60257 69.02579
[15] NaN 72.68984 65.81693 70.99051 74.34799 68.19517
> colSums(tmp5,na.rm=TRUE)
[1] 1022.4516 668.0457 669.6007 621.6343 625.2033 628.8967 640.5840
[8] 662.1320 633.7733 617.1391 628.6060 641.1074 617.4231 621.2321
[15] 0.0000 654.2085 592.3524 638.9146 669.1319 613.7565
> colVars(tmp5,na.rm=TRUE)
[1] 17423.28406 95.13588 86.25403 131.01792 93.95741 62.16846
[7] 61.33840 70.64766 58.17293 24.89584 73.20787 83.59377
[13] 74.84210 118.06931 NA 83.23940 56.69317 45.48436
[19] 110.06380 45.42440
> colSd(tmp5,na.rm=TRUE)
[1] 131.997288 9.753762 9.287305 11.446306 9.693163 7.884698
[7] 7.831884 8.405217 7.627118 4.989573 8.556160 9.142963
[13] 8.651133 10.865970 NA 9.123563 7.529487 6.744209
[19] 10.491130 6.739763
> colMax(tmp5,na.rm=TRUE)
[1] 464.99434 85.24995 91.84293 84.89377 85.40378 80.51704 83.99956
[8] 84.71253 81.72422 76.69740 81.56283 88.53700 83.84552 85.01580
[15] -Inf 84.26652 77.23835 82.55815 88.45619 77.34397
> colMin(tmp5,na.rm=TRUE)
[1] 58.11932 58.67210 60.58426 55.32191 56.93134 57.06569 61.87810 61.40918
[9] 60.11767 57.97779 57.42573 56.48074 58.42753 55.36396 Inf 55.46082
[17] 57.41838 59.93557 60.66134 56.22818
>
>
>
>
> 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] 204.0558 204.0838 261.8932 147.9870 161.1941 194.1661 152.6500 219.8944
[9] 200.4612 229.9148
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 204.0558 204.0838 261.8932 147.9870 161.1941 194.1661 152.6500 219.8944
[9] 200.4612 229.9148
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 5.684342e-14 0.000000e+00 -8.526513e-14 -5.684342e-14 -5.684342e-14
[6] -1.136868e-13 0.000000e+00 1.136868e-13 -5.684342e-14 -5.684342e-14
[11] 5.684342e-14 0.000000e+00 5.684342e-14 1.989520e-13 -1.136868e-13
[16] 0.000000e+00 -5.684342e-14 5.684342e-14 2.842171e-14 -8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
1 20
9 5
8 16
5 6
9 15
3 9
2 11
9 10
1 10
8 16
4 15
1 10
10 3
10 1
1 1
2 11
6 3
1 9
4 10
7 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] 2.441612
> Min(tmp)
[1] -1.6096
> mean(tmp)
[1] 0.1791568
> Sum(tmp)
[1] 17.91568
> Var(tmp)
[1] 0.7810934
>
> rowMeans(tmp)
[1] 0.1791568
> rowSums(tmp)
[1] 17.91568
> rowVars(tmp)
[1] 0.7810934
> rowSd(tmp)
[1] 0.8837949
> rowMax(tmp)
[1] 2.441612
> rowMin(tmp)
[1] -1.6096
>
> colMeans(tmp)
[1] -0.42464459 0.99016255 1.08525230 -0.10625682 -0.32271859 -0.64147094
[7] 0.73294935 -0.55666225 1.45364617 -0.66749480 -1.20162268 1.13613645
[13] 0.29086137 0.34714121 0.14182663 0.39035021 2.03654939 -1.25794870
[19] 0.60338537 -1.45128130 0.27796395 -0.62642875 0.15300882 -0.92967646
[25] -0.38124110 0.69365233 0.71062409 -0.04264782 0.67434780 -1.60960049
[31] 0.70830640 0.45755614 -0.65853666 1.35623939 0.09177315 -0.99034480
[37] -0.66931200 0.69816523 0.19460619 0.62604942 1.61950557 0.92885834
[43] 2.01548482 -0.52615822 0.25025615 0.47859776 1.13614424 -1.04002674
[49] 1.33186824 0.21525641 -1.06100694 0.17012015 -0.80601323 1.88225053
[55] -1.53906088 0.04534964 -0.56125396 -0.48685211 -0.43246677 0.49412882
[61] -0.42129255 -1.07269568 0.52843487 2.01160540 -0.70292865 0.05916848
[67] -0.28789387 1.38779182 0.44787583 0.21467208 2.44161178 0.99771084
[73] 0.37673521 -0.48232660 0.38158423 0.96343145 0.66069493 0.56527591
[79] 0.38729609 0.05220781 -0.80011532 1.30743011 -0.55059583 1.16496686
[85] -0.58548807 -0.91154030 0.75890995 1.12063409 0.51995315 0.24466484
[91] 0.21628320 -0.42056343 -1.36728400 0.64356075 -0.83918854 1.00439004
[97] 0.18572528 0.54008957 0.71746109 -0.97022477
> colSums(tmp)
[1] -0.42464459 0.99016255 1.08525230 -0.10625682 -0.32271859 -0.64147094
[7] 0.73294935 -0.55666225 1.45364617 -0.66749480 -1.20162268 1.13613645
[13] 0.29086137 0.34714121 0.14182663 0.39035021 2.03654939 -1.25794870
[19] 0.60338537 -1.45128130 0.27796395 -0.62642875 0.15300882 -0.92967646
[25] -0.38124110 0.69365233 0.71062409 -0.04264782 0.67434780 -1.60960049
[31] 0.70830640 0.45755614 -0.65853666 1.35623939 0.09177315 -0.99034480
[37] -0.66931200 0.69816523 0.19460619 0.62604942 1.61950557 0.92885834
[43] 2.01548482 -0.52615822 0.25025615 0.47859776 1.13614424 -1.04002674
[49] 1.33186824 0.21525641 -1.06100694 0.17012015 -0.80601323 1.88225053
[55] -1.53906088 0.04534964 -0.56125396 -0.48685211 -0.43246677 0.49412882
[61] -0.42129255 -1.07269568 0.52843487 2.01160540 -0.70292865 0.05916848
[67] -0.28789387 1.38779182 0.44787583 0.21467208 2.44161178 0.99771084
[73] 0.37673521 -0.48232660 0.38158423 0.96343145 0.66069493 0.56527591
[79] 0.38729609 0.05220781 -0.80011532 1.30743011 -0.55059583 1.16496686
[85] -0.58548807 -0.91154030 0.75890995 1.12063409 0.51995315 0.24466484
[91] 0.21628320 -0.42056343 -1.36728400 0.64356075 -0.83918854 1.00439004
[97] 0.18572528 0.54008957 0.71746109 -0.97022477
> 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] -0.42464459 0.99016255 1.08525230 -0.10625682 -0.32271859 -0.64147094
[7] 0.73294935 -0.55666225 1.45364617 -0.66749480 -1.20162268 1.13613645
[13] 0.29086137 0.34714121 0.14182663 0.39035021 2.03654939 -1.25794870
[19] 0.60338537 -1.45128130 0.27796395 -0.62642875 0.15300882 -0.92967646
[25] -0.38124110 0.69365233 0.71062409 -0.04264782 0.67434780 -1.60960049
[31] 0.70830640 0.45755614 -0.65853666 1.35623939 0.09177315 -0.99034480
[37] -0.66931200 0.69816523 0.19460619 0.62604942 1.61950557 0.92885834
[43] 2.01548482 -0.52615822 0.25025615 0.47859776 1.13614424 -1.04002674
[49] 1.33186824 0.21525641 -1.06100694 0.17012015 -0.80601323 1.88225053
[55] -1.53906088 0.04534964 -0.56125396 -0.48685211 -0.43246677 0.49412882
[61] -0.42129255 -1.07269568 0.52843487 2.01160540 -0.70292865 0.05916848
[67] -0.28789387 1.38779182 0.44787583 0.21467208 2.44161178 0.99771084
[73] 0.37673521 -0.48232660 0.38158423 0.96343145 0.66069493 0.56527591
[79] 0.38729609 0.05220781 -0.80011532 1.30743011 -0.55059583 1.16496686
[85] -0.58548807 -0.91154030 0.75890995 1.12063409 0.51995315 0.24466484
[91] 0.21628320 -0.42056343 -1.36728400 0.64356075 -0.83918854 1.00439004
[97] 0.18572528 0.54008957 0.71746109 -0.97022477
> colMin(tmp)
[1] -0.42464459 0.99016255 1.08525230 -0.10625682 -0.32271859 -0.64147094
[7] 0.73294935 -0.55666225 1.45364617 -0.66749480 -1.20162268 1.13613645
[13] 0.29086137 0.34714121 0.14182663 0.39035021 2.03654939 -1.25794870
[19] 0.60338537 -1.45128130 0.27796395 -0.62642875 0.15300882 -0.92967646
[25] -0.38124110 0.69365233 0.71062409 -0.04264782 0.67434780 -1.60960049
[31] 0.70830640 0.45755614 -0.65853666 1.35623939 0.09177315 -0.99034480
[37] -0.66931200 0.69816523 0.19460619 0.62604942 1.61950557 0.92885834
[43] 2.01548482 -0.52615822 0.25025615 0.47859776 1.13614424 -1.04002674
[49] 1.33186824 0.21525641 -1.06100694 0.17012015 -0.80601323 1.88225053
[55] -1.53906088 0.04534964 -0.56125396 -0.48685211 -0.43246677 0.49412882
[61] -0.42129255 -1.07269568 0.52843487 2.01160540 -0.70292865 0.05916848
[67] -0.28789387 1.38779182 0.44787583 0.21467208 2.44161178 0.99771084
[73] 0.37673521 -0.48232660 0.38158423 0.96343145 0.66069493 0.56527591
[79] 0.38729609 0.05220781 -0.80011532 1.30743011 -0.55059583 1.16496686
[85] -0.58548807 -0.91154030 0.75890995 1.12063409 0.51995315 0.24466484
[91] 0.21628320 -0.42056343 -1.36728400 0.64356075 -0.83918854 1.00439004
[97] 0.18572528 0.54008957 0.71746109 -0.97022477
> colMedians(tmp)
[1] -0.42464459 0.99016255 1.08525230 -0.10625682 -0.32271859 -0.64147094
[7] 0.73294935 -0.55666225 1.45364617 -0.66749480 -1.20162268 1.13613645
[13] 0.29086137 0.34714121 0.14182663 0.39035021 2.03654939 -1.25794870
[19] 0.60338537 -1.45128130 0.27796395 -0.62642875 0.15300882 -0.92967646
[25] -0.38124110 0.69365233 0.71062409 -0.04264782 0.67434780 -1.60960049
[31] 0.70830640 0.45755614 -0.65853666 1.35623939 0.09177315 -0.99034480
[37] -0.66931200 0.69816523 0.19460619 0.62604942 1.61950557 0.92885834
[43] 2.01548482 -0.52615822 0.25025615 0.47859776 1.13614424 -1.04002674
[49] 1.33186824 0.21525641 -1.06100694 0.17012015 -0.80601323 1.88225053
[55] -1.53906088 0.04534964 -0.56125396 -0.48685211 -0.43246677 0.49412882
[61] -0.42129255 -1.07269568 0.52843487 2.01160540 -0.70292865 0.05916848
[67] -0.28789387 1.38779182 0.44787583 0.21467208 2.44161178 0.99771084
[73] 0.37673521 -0.48232660 0.38158423 0.96343145 0.66069493 0.56527591
[79] 0.38729609 0.05220781 -0.80011532 1.30743011 -0.55059583 1.16496686
[85] -0.58548807 -0.91154030 0.75890995 1.12063409 0.51995315 0.24466484
[91] 0.21628320 -0.42056343 -1.36728400 0.64356075 -0.83918854 1.00439004
[97] 0.18572528 0.54008957 0.71746109 -0.97022477
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.4246446 0.9901626 1.085252 -0.1062568 -0.3227186 -0.6414709 0.7329494
[2,] -0.4246446 0.9901626 1.085252 -0.1062568 -0.3227186 -0.6414709 0.7329494
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.5566622 1.453646 -0.6674948 -1.201623 1.136136 0.2908614 0.3471412
[2,] -0.5566622 1.453646 -0.6674948 -1.201623 1.136136 0.2908614 0.3471412
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.1418266 0.3903502 2.036549 -1.257949 0.6033854 -1.451281 0.277964
[2,] 0.1418266 0.3903502 2.036549 -1.257949 0.6033854 -1.451281 0.277964
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.6264288 0.1530088 -0.9296765 -0.3812411 0.6936523 0.7106241 -0.04264782
[2,] -0.6264288 0.1530088 -0.9296765 -0.3812411 0.6936523 0.7106241 -0.04264782
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.6743478 -1.6096 0.7083064 0.4575561 -0.6585367 1.356239 0.09177315
[2,] 0.6743478 -1.6096 0.7083064 0.4575561 -0.6585367 1.356239 0.09177315
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.9903448 -0.669312 0.6981652 0.1946062 0.6260494 1.619506 0.9288583
[2,] -0.9903448 -0.669312 0.6981652 0.1946062 0.6260494 1.619506 0.9288583
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 2.015485 -0.5261582 0.2502561 0.4785978 1.136144 -1.040027 1.331868
[2,] 2.015485 -0.5261582 0.2502561 0.4785978 1.136144 -1.040027 1.331868
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.2152564 -1.061007 0.1701202 -0.8060132 1.882251 -1.539061 0.04534964
[2,] 0.2152564 -1.061007 0.1701202 -0.8060132 1.882251 -1.539061 0.04534964
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.561254 -0.4868521 -0.4324668 0.4941288 -0.4212926 -1.072696 0.5284349
[2,] -0.561254 -0.4868521 -0.4324668 0.4941288 -0.4212926 -1.072696 0.5284349
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 2.011605 -0.7029286 0.05916848 -0.2878939 1.387792 0.4478758 0.2146721
[2,] 2.011605 -0.7029286 0.05916848 -0.2878939 1.387792 0.4478758 0.2146721
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 2.441612 0.9977108 0.3767352 -0.4823266 0.3815842 0.9634315 0.6606949
[2,] 2.441612 0.9977108 0.3767352 -0.4823266 0.3815842 0.9634315 0.6606949
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.5652759 0.3872961 0.05220781 -0.8001153 1.30743 -0.5505958 1.164967
[2,] 0.5652759 0.3872961 0.05220781 -0.8001153 1.30743 -0.5505958 1.164967
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.5854881 -0.9115403 0.75891 1.120634 0.5199531 0.2446648 0.2162832
[2,] -0.5854881 -0.9115403 0.75891 1.120634 0.5199531 0.2446648 0.2162832
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.4205634 -1.367284 0.6435608 -0.8391885 1.00439 0.1857253 0.5400896
[2,] -0.4205634 -1.367284 0.6435608 -0.8391885 1.00439 0.1857253 0.5400896
[,99] [,100]
[1,] 0.7174611 -0.9702248
[2,] 0.7174611 -0.9702248
>
>
> Max(tmp2)
[1] 2.15918
> Min(tmp2)
[1] -2.548254
> mean(tmp2)
[1] 0.005402214
> Sum(tmp2)
[1] 0.5402214
> Var(tmp2)
[1] 1.045598
>
> rowMeans(tmp2)
[1] -0.573621155 0.206356817 2.055282973 0.797845219 -0.820460849
[6] -0.564273705 1.587732968 0.346864716 -0.024132813 -1.546744545
[11] 0.922989238 -1.980902836 -0.190292738 1.426447545 -0.008140772
[16] 0.040399939 1.519059630 -1.475328834 -0.581614670 -1.122675016
[21] 0.067155919 -0.172183128 -0.922643172 -0.776063376 0.183435630
[26] 1.821607289 1.811787613 0.184133927 -0.055988365 -0.851462815
[31] -1.743596468 -1.800942101 0.784649061 -0.150548553 -0.243114959
[36] 0.813584784 0.508044172 -0.816747234 0.961470086 0.929038669
[41] 1.831923473 -0.350473924 -0.773118200 0.514173120 -0.900143186
[46] -1.191896266 1.580899910 -0.787080301 -1.003623881 0.997958443
[51] 0.258241957 -0.424976629 0.245803174 0.932051246 0.614963409
[56] -0.251736546 0.782020574 0.047456531 1.259994363 -1.494509071
[61] 1.105873488 0.446233567 0.081884944 -0.334785818 -0.591548836
[66] -0.287680550 -0.299375815 -0.194834218 0.479486045 1.029841088
[71] 0.123065941 -0.450869793 0.762181067 -0.205776056 -1.121704610
[76] 0.231355122 -2.548254447 2.159180093 -0.415946428 0.408271439
[81] -0.282377024 -0.835236260 1.872784042 -1.171898260 -2.022368589
[86] -0.426563561 -0.174408867 -0.113063451 -1.249589242 -2.234545697
[91] -0.195352787 0.734221493 1.631300328 1.051520144 0.321571722
[96] -1.083932597 1.102418183 0.616155786 0.971193292 -0.782539762
> rowSums(tmp2)
[1] -0.573621155 0.206356817 2.055282973 0.797845219 -0.820460849
[6] -0.564273705 1.587732968 0.346864716 -0.024132813 -1.546744545
[11] 0.922989238 -1.980902836 -0.190292738 1.426447545 -0.008140772
[16] 0.040399939 1.519059630 -1.475328834 -0.581614670 -1.122675016
[21] 0.067155919 -0.172183128 -0.922643172 -0.776063376 0.183435630
[26] 1.821607289 1.811787613 0.184133927 -0.055988365 -0.851462815
[31] -1.743596468 -1.800942101 0.784649061 -0.150548553 -0.243114959
[36] 0.813584784 0.508044172 -0.816747234 0.961470086 0.929038669
[41] 1.831923473 -0.350473924 -0.773118200 0.514173120 -0.900143186
[46] -1.191896266 1.580899910 -0.787080301 -1.003623881 0.997958443
[51] 0.258241957 -0.424976629 0.245803174 0.932051246 0.614963409
[56] -0.251736546 0.782020574 0.047456531 1.259994363 -1.494509071
[61] 1.105873488 0.446233567 0.081884944 -0.334785818 -0.591548836
[66] -0.287680550 -0.299375815 -0.194834218 0.479486045 1.029841088
[71] 0.123065941 -0.450869793 0.762181067 -0.205776056 -1.121704610
[76] 0.231355122 -2.548254447 2.159180093 -0.415946428 0.408271439
[81] -0.282377024 -0.835236260 1.872784042 -1.171898260 -2.022368589
[86] -0.426563561 -0.174408867 -0.113063451 -1.249589242 -2.234545697
[91] -0.195352787 0.734221493 1.631300328 1.051520144 0.321571722
[96] -1.083932597 1.102418183 0.616155786 0.971193292 -0.782539762
> 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] -0.573621155 0.206356817 2.055282973 0.797845219 -0.820460849
[6] -0.564273705 1.587732968 0.346864716 -0.024132813 -1.546744545
[11] 0.922989238 -1.980902836 -0.190292738 1.426447545 -0.008140772
[16] 0.040399939 1.519059630 -1.475328834 -0.581614670 -1.122675016
[21] 0.067155919 -0.172183128 -0.922643172 -0.776063376 0.183435630
[26] 1.821607289 1.811787613 0.184133927 -0.055988365 -0.851462815
[31] -1.743596468 -1.800942101 0.784649061 -0.150548553 -0.243114959
[36] 0.813584784 0.508044172 -0.816747234 0.961470086 0.929038669
[41] 1.831923473 -0.350473924 -0.773118200 0.514173120 -0.900143186
[46] -1.191896266 1.580899910 -0.787080301 -1.003623881 0.997958443
[51] 0.258241957 -0.424976629 0.245803174 0.932051246 0.614963409
[56] -0.251736546 0.782020574 0.047456531 1.259994363 -1.494509071
[61] 1.105873488 0.446233567 0.081884944 -0.334785818 -0.591548836
[66] -0.287680550 -0.299375815 -0.194834218 0.479486045 1.029841088
[71] 0.123065941 -0.450869793 0.762181067 -0.205776056 -1.121704610
[76] 0.231355122 -2.548254447 2.159180093 -0.415946428 0.408271439
[81] -0.282377024 -0.835236260 1.872784042 -1.171898260 -2.022368589
[86] -0.426563561 -0.174408867 -0.113063451 -1.249589242 -2.234545697
[91] -0.195352787 0.734221493 1.631300328 1.051520144 0.321571722
[96] -1.083932597 1.102418183 0.616155786 0.971193292 -0.782539762
> rowMin(tmp2)
[1] -0.573621155 0.206356817 2.055282973 0.797845219 -0.820460849
[6] -0.564273705 1.587732968 0.346864716 -0.024132813 -1.546744545
[11] 0.922989238 -1.980902836 -0.190292738 1.426447545 -0.008140772
[16] 0.040399939 1.519059630 -1.475328834 -0.581614670 -1.122675016
[21] 0.067155919 -0.172183128 -0.922643172 -0.776063376 0.183435630
[26] 1.821607289 1.811787613 0.184133927 -0.055988365 -0.851462815
[31] -1.743596468 -1.800942101 0.784649061 -0.150548553 -0.243114959
[36] 0.813584784 0.508044172 -0.816747234 0.961470086 0.929038669
[41] 1.831923473 -0.350473924 -0.773118200 0.514173120 -0.900143186
[46] -1.191896266 1.580899910 -0.787080301 -1.003623881 0.997958443
[51] 0.258241957 -0.424976629 0.245803174 0.932051246 0.614963409
[56] -0.251736546 0.782020574 0.047456531 1.259994363 -1.494509071
[61] 1.105873488 0.446233567 0.081884944 -0.334785818 -0.591548836
[66] -0.287680550 -0.299375815 -0.194834218 0.479486045 1.029841088
[71] 0.123065941 -0.450869793 0.762181067 -0.205776056 -1.121704610
[76] 0.231355122 -2.548254447 2.159180093 -0.415946428 0.408271439
[81] -0.282377024 -0.835236260 1.872784042 -1.171898260 -2.022368589
[86] -0.426563561 -0.174408867 -0.113063451 -1.249589242 -2.234545697
[91] -0.195352787 0.734221493 1.631300328 1.051520144 0.321571722
[96] -1.083932597 1.102418183 0.616155786 0.971193292 -0.782539762
>
> colMeans(tmp2)
[1] 0.005402214
> colSums(tmp2)
[1] 0.5402214
> colVars(tmp2)
[1] 1.045598
> colSd(tmp2)
[1] 1.022545
> colMax(tmp2)
[1] 2.15918
> colMin(tmp2)
[1] -2.548254
> colMedians(tmp2)
[1] -0.04006059
> colRanges(tmp2)
[,1]
[1,] -2.548254
[2,] 2.159180
>
> 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] -3.8054290 -0.9128910 0.7994604 -2.7560953 -3.1506105 2.2143124
[7] 1.4470249 -5.2277862 -0.2586874 0.9519380
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9317544
[2,] -1.0430461
[3,] -0.6104373
[4,] 0.6205877
[5,] 0.9933923
>
> rowApply(tmp,sum)
[1] 4.5521841 -3.4144699 -1.7427064 2.4991311 -0.6950528 0.4420584
[7] -5.4467342 0.9082813 -2.1394404 -5.6620150
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 4 10 9 2 4 4 6 1 2
[2,] 9 6 8 7 6 2 9 5 7 1
[3,] 10 10 2 3 9 1 6 10 9 6
[4,] 2 1 1 8 1 7 10 7 3 4
[5,] 8 5 9 5 5 5 5 2 2 3
[6,] 1 3 6 10 10 6 8 8 4 8
[7,] 5 8 5 2 7 9 7 4 10 7
[8,] 3 2 7 6 8 3 1 3 5 5
[9,] 4 9 4 4 4 10 2 1 6 10
[10,] 6 7 3 1 3 8 3 9 8 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.9876938 0.5018204 -1.5460037 -2.7696826 0.1807457 2.0068474
[7] -1.0068284 -3.0872573 1.1216364 -1.6609837 -1.4036598 3.2862530
[13] 0.4724979 -3.3001613 3.6132515 -3.2872148 -2.1902934 -2.1615595
[19] -3.4320122 0.4764875
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.23576116
[2,] -1.93086746
[3,] -0.12201672
[4,] 0.01578508
[5,] 1.28516652
>
> rowApply(tmp,sum)
[1] 3.584063 1.192918 -10.661881 -5.534352 -5.754559
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 1 13 19 2
[2,] 6 18 9 20 7
[3,] 12 13 15 12 1
[4,] 5 8 2 11 9
[5,] 17 2 20 7 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.01578508 -0.3669628 0.34709594 -0.44197096 1.30764068 0.4827398
[2,] -2.23576116 0.7932049 0.32550512 -0.02816994 -1.20365646 -0.5546206
[3,] -0.12201672 -0.5982093 -0.01474863 -1.46039922 0.62526709 -0.1091478
[4,] 1.28516652 1.2882630 -0.08394506 -0.27702268 -0.57017034 0.4370530
[5,] -1.93086746 -0.6144754 -2.11991107 -0.56211977 0.02166478 1.7508231
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.2999962 0.5428039 0.1969974 0.3501085 0.74256129 2.0637392
[2,] 1.6243156 -0.2688051 0.4617648 0.2871674 0.45236644 0.2856852
[3,] 0.2358996 -1.3299606 0.2850775 -0.5724086 0.01515964 -0.6556767
[4,] -1.8510524 -1.8249240 0.2886515 -0.5277762 -1.23387414 0.1131119
[5,] -0.7159950 -0.2063715 -0.1108547 -1.1980747 -1.37987300 1.4793934
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.3645783 -0.64030130 1.7403764 -0.8160839 -0.3440465 -1.4519935
[2,] 0.5396474 -0.05828539 1.0188745 -0.7904165 -0.4961532 0.3092677
[3,] -1.6020724 -1.06012880 -0.4907650 -1.0093607 -0.5356017 0.3197927
[4,] 0.7664268 -1.36068254 0.3310693 -0.5357772 -0.4257564 -0.9509299
[5,] -0.5960822 -0.18076323 1.0136963 -0.1355765 -0.3887355 -0.3876966
[,19] [,20]
[1,] -0.8892565 -0.3197523
[2,] 0.4309330 0.3000545
[3,] -1.2896169 -1.2929640
[4,] -0.9915154 0.5893323
[5,] -0.6925565 1.1998169
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.4114934 0.1953823 1.538321 1.088028 0.006413766 -1.308895 -1.530725
col8 col9 col10 col11 col12 col13 col14
row1 1.655984 1.849071 0.3939849 1.106586 -0.9146741 3.05522 0.1449153
col15 col16 col17 col18 col19 col20
row1 -2.079052 -1.249165 -0.4171696 -0.2727197 -1.529551 0.2314724
> tmp[,"col10"]
col10
row1 0.39398492
row2 -0.15232705
row3 1.33687133
row4 1.41276484
row5 -0.08422925
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.4114934 0.1953823 1.538321 1.088028 0.006413766 -1.308895 -1.530725
row5 3.6848126 0.7362953 1.341923 2.273176 -1.173037148 1.205488 -1.070863
col8 col9 col10 col11 col12 col13
row1 1.6559845 1.8490708 0.39398492 1.1065865 -0.9146741 3.055220
row5 -0.5729811 -0.5778124 -0.08422925 0.1384729 0.2463048 -0.437222
col14 col15 col16 col17 col18 col19
row1 0.1449153 -2.079052 -1.2491653 -0.4171696 -0.27271973 -1.52955104
row5 -0.4409244 -1.366208 0.9291727 0.1792004 -0.06377782 -0.05355313
col20
row1 0.2314724
row5 1.1358474
> tmp[,c("col6","col20")]
col6 col20
row1 -1.308895144 0.23147244
row2 -1.390327158 -0.02756868
row3 0.024489742 -2.57910831
row4 -0.009139677 0.70385981
row5 1.205487808 1.13584743
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.308895 0.2314724
row5 1.205488 1.1358474
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.58652 50.0365 50.11833 50.75492 49.88697 105.0985 49.23592 48.67574
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.81434 51.45664 50.43793 50.3876 47.91636 49.45828 49.33172 50.14578
col17 col18 col19 col20
row1 50.23519 50.97639 50.76956 105.7807
> tmp[,"col10"]
col10
row1 51.45664
row2 31.38321
row3 30.07554
row4 30.01044
row5 48.43020
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.58652 50.03650 50.11833 50.75492 49.88697 105.0985 49.23592 48.67574
row5 51.01502 52.05356 49.47004 52.01470 49.90302 106.4264 49.14135 50.79392
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.81434 51.45664 50.43793 50.38760 47.91636 49.45828 49.33172 50.14578
row5 51.30887 48.43020 49.66474 50.30448 49.23130 50.55983 49.81163 49.35169
col17 col18 col19 col20
row1 50.23519 50.97639 50.76956 105.7807
row5 50.02893 51.07376 51.16285 105.7880
> tmp[,c("col6","col20")]
col6 col20
row1 105.09852 105.78071
row2 75.14604 73.03522
row3 74.34406 76.21901
row4 75.28688 74.74524
row5 106.42636 105.78796
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.0985 105.7807
row5 106.4264 105.7880
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.0985 105.7807
row5 106.4264 105.7880
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.3349800
[2,] 0.7861578
[3,] 0.3895248
[4,] 0.4845344
[5,] 0.9724462
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9719844 -0.6690689
[2,] -0.1296653 1.1952084
[3,] -0.7807609 -0.6173395
[4,] -0.2033645 0.8881720
[5,] 0.1722937 0.1612875
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.4470602 1.0306895
[2,] 0.7677492 1.2764587
[3,] -0.2933079 1.2167854
[4,] 0.5503691 -0.8313043
[5,] 1.0409527 1.8201302
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.4470602
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.4470602
[2,] 0.7677492
>
>
>
> 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 1.233693 2.9689242 -0.7026380 0.5562776 -0.74375041 0.3277397
row1 -1.338413 -0.2805255 0.9438223 -1.5835875 -0.07814653 0.5769451
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.041650481 -0.5090762 -0.7226675 -0.4903325 -0.8803935 0.9777371
row1 -0.009724706 1.3903601 -0.6056021 0.3891552 0.4274170 -0.8684529
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 0.8946655 0.5319006 1.3716007 0.07393216 0.3452461 -0.8149852 0.3134758
row1 1.2821875 0.5086573 -0.5100772 -0.19275954 0.6052824 0.9892075 -0.3317572
[,20]
row3 1.129101868
row1 -0.001944388
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.972879 -0.7471957 0.5117975 0.4518906 -1.353466 -0.5460005 0.7598199
[,8] [,9] [,10]
row2 0.3323371 2.900095 -0.4828721
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.3934736 0.1312192 0.2031722 -0.02913828 0.7786129 0.8640486 -0.5392456
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.114041 0.5301354 -1.46245 -1.416303 0.5800628 -1.340069 -0.6154528
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8854964 1.218311 -1.058175 -0.4277059 1.077756 -0.0764166
>
>
> 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: 0x5929b8d23680>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df2a391f3f"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df43d8bac"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df52362c4b"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df9b2c2b1"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df268c02ca"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df3b772b7f"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df746a1b69"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df5d68c730"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df3ef720db"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df520aee5c"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df6a7f82b1"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df460b4f79"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df2dc39341"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40df75ce1c7e"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM2c40dfd019d65"
>
>
> ### 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: 0x5929bb084170>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5929bb084170>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5929bb084170>
> rowMedians(tmp)
[1] 4.316697e-01 -1.224219e-01 -8.662930e-02 -7.368525e-02 -9.313524e-03
[6] -1.064672e+00 3.510477e-01 -9.102438e-02 -1.679870e-01 6.810925e-02
[11] 3.065300e-01 2.356547e-01 7.938029e-01 2.831900e-01 3.526037e-01
[16] -8.240149e-02 -6.399855e-02 1.130506e-01 -1.966855e-01 9.511862e-02
[21] -2.916617e-02 1.507592e-01 1.593322e-01 3.686343e-01 3.805222e-01
[26] -1.493972e-01 -2.166231e-01 5.474200e-02 -2.095394e-03 1.342994e-01
[31] 3.670786e-01 -2.484932e-02 2.871797e-02 2.874867e-01 2.890143e-01
[36] -1.020325e-01 2.913757e-01 -2.700447e-01 -2.706642e-01 5.668696e-01
[41] 3.425095e-01 -5.610737e-02 -8.112330e-02 -2.854634e-01 1.952272e-01
[46] 3.137641e-01 5.735836e-02 1.291684e-01 2.675189e-01 2.204893e-01
[51] 2.016209e-01 5.963656e-01 3.584538e-01 3.468259e-02 3.567076e-01
[56] 2.366478e-01 2.586985e-01 2.749528e-01 -5.124607e-02 -4.659773e-01
[61] -6.093869e-01 -2.709828e-01 -4.128817e-02 -1.476127e-01 3.254470e-01
[66] -7.552411e-01 -1.962518e-01 -7.384029e-02 -5.068075e-06 -3.114618e-02
[71] -2.253036e-01 -3.020753e-01 7.410838e-02 1.520186e-01 -2.190678e-02
[76] -1.060253e-01 2.993994e-02 -4.659003e-02 -6.324923e-02 -1.209951e-01
[81] -3.798974e-01 -8.762645e-02 -4.949445e-01 6.283276e-01 6.100364e-02
[86] -1.431841e-01 4.969070e-01 1.661924e-01 6.295860e-02 -5.178830e-02
[91] 1.787551e-01 5.329148e-02 -5.039956e-01 -2.808473e-01 3.914931e-01
[96] 3.016267e-01 9.648836e-02 -6.998561e-02 -1.701091e-01 -8.355054e-01
[101] -9.796637e-02 1.367846e-01 -2.433303e-01 1.425492e-01 -2.330942e-01
[106] 1.449533e-01 3.698785e-01 -4.306614e-01 1.994885e-02 -9.673280e-02
[111] 3.374890e-01 -1.176620e-01 -2.577801e-02 -2.140335e-01 1.609282e-01
[116] 3.069954e-02 9.316505e-02 -2.631131e-01 -6.477563e-01 4.467522e-01
[121] 5.703826e-01 -7.225165e-01 1.665712e-01 7.649653e-02 2.030941e-01
[126] -2.503308e-01 1.227347e-01 2.651011e-01 4.283884e-01 1.412389e-01
[131] 1.993960e-01 -2.251722e-01 -2.322055e-01 6.757448e-02 3.059977e-01
[136] -1.909242e-01 1.070466e-01 -5.836420e-01 2.006022e-01 1.198836e-01
[141] -4.538794e-01 6.756539e-01 -4.589707e-01 -6.016586e-02 -1.394911e-01
[146] 1.965764e-01 -3.077010e-01 -4.856638e-01 -4.507951e-01 5.904900e-01
[151] 4.532308e-01 3.342568e-01 2.552000e-01 -4.475304e-01 -2.165299e-01
[156] -4.833769e-02 2.843980e-01 -2.384237e-01 -3.579451e-01 5.236660e-01
[161] 2.062571e-01 -5.145530e-02 -1.325340e-01 -1.803789e-01 -5.421904e-01
[166] 1.030288e-01 -4.025201e-01 -1.682132e-01 4.388082e-01 -2.430683e-01
[171] 4.199331e-03 5.824106e-01 3.432704e-01 -3.491639e-01 -4.273940e-02
[176] 2.657581e-01 3.011207e-01 1.432565e-01 9.551315e-02 2.939365e-01
[181] -3.257248e-01 6.236870e-02 -6.838371e-01 1.785303e-01 1.350145e-02
[186] -6.125039e-01 1.301566e-01 -6.025707e-01 7.690784e-01 1.784073e-01
[191] -1.590526e-01 8.305511e-02 -1.394982e-01 -4.207574e-01 -1.913384e-01
[196] -1.075271e-01 3.626651e-01 2.190046e-01 1.806009e-01 3.064480e-01
[201] -2.777129e-02 8.366592e-02 5.983204e-02 -8.770133e-01 -2.474372e-01
[206] -2.440503e-01 3.839825e-01 -8.054888e-02 -2.011026e-01 7.866139e-01
[211] 1.219517e-01 1.133185e-01 -1.638485e-01 7.333329e-02 -9.473610e-01
[216] -9.515204e-02 4.333669e-01 5.988980e-01 -5.411382e-01 -1.822253e-01
[221] -1.423796e-01 7.524452e-01 -5.697945e-01 -6.634627e-02 -2.872370e-04
[226] 2.403143e-01 2.072799e-01 1.578166e-01 -9.892049e-02 7.253090e-02
>
> proc.time()
user system elapsed
1.320 1.451 2.757
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences"
Copyright (C) 2025 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: 0x604c422c85f0>
> .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: 0x604c422c85f0>
> .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: 0x604c422c85f0>
> .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: 0x604c422c85f0>
> 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: 0x604c42b462b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c42b462b0>
> .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: 0x604c42b462b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c42b462b0>
> .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: 0x604c42b462b0>
> 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: 0x604c42229a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c42229a20>
> .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: 0x604c42229a20>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x604c42229a20>
> .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: 0x604c42229a20>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x604c42229a20>
> .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: 0x604c42229a20>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x604c42229a20>
> .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: 0x604c42229a20>
> 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: 0x604c42a06e00>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x604c42a06e00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c42a06e00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c42a06e00>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2c4217331d2ef9" "BufferedMatrixFile2c42173d7f4da2"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2c4217331d2ef9" "BufferedMatrixFile2c42173d7f4da2"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c4290e4c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c4290e4c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x604c4290e4c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x604c4290e4c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x604c4290e4c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x604c4290e4c0>
> .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: 0x604c42cb77e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x604c42cb77e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x604c42cb77e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x604c42cb77e0>
> 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: 0x604c43d90520>
> .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: 0x604c43d90520>
> rm(P)
>
> proc.time()
user system elapsed
0.258 0.043 0.289
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences"
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Platform: x86_64-pc-linux-gnu
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.253 0.044 0.284