Ben Bolstad
| Snapshot Date: 2026-01-07 13:40 -0500 (Wed, 07 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 2026-01-08 11:34 -0500 (Thu, 08 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" | 4815 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4593 |
| 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 253/2332 | 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: 2026-01-07 21:35:40 -0500 (Wed, 07 Jan 2026) |
| EndedAt: 2026-01-07 21:36:05 -0500 (Wed, 07 Jan 2026) |
| EllapsedTime: 25.1 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
0.242 0.046 0.277
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 7 21:35:54 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 7 21:35:54 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: 0x6260d1e4a2b0>
>
>
>
> 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 7 21:35:55 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 7 21:35:55 2026"
>
> ColMode(tmp2)
<pointer: 0x6260d1e4a2b0>
>
>
>
> ### 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,] 101.4494508 0.16260478 -1.2374861 -0.5821053
[2,] -0.3305229 1.13486963 1.2845235 1.1147890
[3,] 0.5632354 -0.18779844 -1.4780607 -0.2789088
[4,] -0.2200570 -0.04238396 0.7506683 0.9993550
> 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,] 101.4494508 0.16260478 1.2374861 0.5821053
[2,] 0.3305229 1.13486963 1.2845235 1.1147890
[3,] 0.5632354 0.18779844 1.4780607 0.2789088
[4,] 0.2200570 0.04238396 0.7506683 0.9993550
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0722118 0.4032428 1.1124235 0.7629583
[2,] 0.5749112 1.0653026 1.1333682 1.0558357
[3,] 0.7504901 0.4333572 1.2157552 0.5281182
[4,] 0.4691023 0.2058737 0.8664111 0.9996774
>
> 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,] 227.17157 29.19503 37.36172 33.21169
[2,] 31.07963 36.78790 37.61821 36.67315
[3,] 33.06814 29.52137 38.63561 30.56009
[4,] 29.91108 27.10112 34.41478 35.99613
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6260d2551500>
> exp(tmp5)
<pointer: 0x6260d2551500>
> log(tmp5,2)
<pointer: 0x6260d2551500>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.8279
> Min(tmp5)
[1] 54.02099
> mean(tmp5)
[1] 73.09426
> Sum(tmp5)
[1] 14618.85
> Var(tmp5)
[1] 877.7155
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.35150 71.39374 70.82373 69.99147 70.95662 72.06949 68.98654 73.08788
[9] 73.21537 69.06630
> rowSums(tmp5)
[1] 1827.030 1427.875 1416.475 1399.829 1419.132 1441.390 1379.731 1461.758
[9] 1464.307 1381.326
> rowVars(tmp5)
[1] 8154.84329 79.42566 63.09756 58.04188 75.80514 79.53449
[7] 54.71034 64.21684 74.62964 78.36486
> rowSd(tmp5)
[1] 90.304171 8.912107 7.943397 7.618522 8.706615 8.918211 7.396644
[8] 8.013541 8.638845 8.852393
> rowMax(tmp5)
[1] 472.82786 87.49219 85.58005 85.74061 87.91768 90.44524 84.70295
[8] 88.72883 89.42755 85.51134
> rowMin(tmp5)
[1] 54.59983 54.02099 56.01973 56.40743 54.05200 57.47798 56.24932 58.71377
[9] 60.12711 54.97462
>
> colMeans(tmp5)
[1] 111.35398 64.13216 76.84185 71.91605 71.34649 72.44086 70.88870
[8] 72.58767 74.16384 71.07625 73.47303 65.87138 70.40658 72.71532
[15] 67.69845 73.09793 72.72209 70.42183 65.08596 73.64487
> colSums(tmp5)
[1] 1113.5398 641.3216 768.4185 719.1605 713.4649 724.4086 708.8870
[8] 725.8767 741.6384 710.7625 734.7303 658.7138 704.0658 727.1532
[15] 676.9845 730.9793 727.2209 704.2183 650.8596 736.4487
> colVars(tmp5)
[1] 16188.336226 30.382877 58.150052 35.999156 57.116400
[6] 116.100783 150.811817 64.793180 108.273860 148.065476
[11] 114.854087 5.244302 96.916905 20.583488 61.630606
[16] 63.328764 63.247860 25.070684 33.368658 38.446866
> colSd(tmp5)
[1] 127.233393 5.512066 7.625618 5.999930 7.557539 10.775007
[7] 12.280546 8.049421 10.405473 12.168216 10.717000 2.290044
[13] 9.844638 4.536903 7.850516 7.957937 7.952852 5.007063
[19] 5.776561 6.200554
> colMax(tmp5)
[1] 472.82786 76.56918 85.32128 77.66019 86.58956 89.42755 88.72883
[8] 85.51134 89.86450 84.70295 90.44524 70.13739 85.59402 79.30882
[15] 82.29069 79.68614 85.74061 76.82707 72.96469 82.35125
> colMin(tmp5)
[1] 62.25600 56.40743 58.64220 59.76242 62.16980 56.24932 54.05200 60.37708
[9] 58.66684 54.02099 58.98287 62.39046 57.79991 62.38908 57.47798 58.71377
[17] 58.82720 62.74341 56.01973 63.04183
>
>
> ### 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] 91.35150 NA 70.82373 69.99147 70.95662 72.06949 68.98654 73.08788
[9] 73.21537 69.06630
> rowSums(tmp5)
[1] 1827.030 NA 1416.475 1399.829 1419.132 1441.390 1379.731 1461.758
[9] 1464.307 1381.326
> rowVars(tmp5)
[1] 8154.84329 82.41304 63.09756 58.04188 75.80514 79.53449
[7] 54.71034 64.21684 74.62964 78.36486
> rowSd(tmp5)
[1] 90.304171 9.078163 7.943397 7.618522 8.706615 8.918211 7.396644
[8] 8.013541 8.638845 8.852393
> rowMax(tmp5)
[1] 472.82786 NA 85.58005 85.74061 87.91768 90.44524 84.70295
[8] 88.72883 89.42755 85.51134
> rowMin(tmp5)
[1] 54.59983 NA 56.01973 56.40743 54.05200 57.47798 56.24932 58.71377
[9] 60.12711 54.97462
>
> colMeans(tmp5)
[1] 111.35398 64.13216 76.84185 NA 71.34649 72.44086 70.88870
[8] 72.58767 74.16384 71.07625 73.47303 65.87138 70.40658 72.71532
[15] 67.69845 73.09793 72.72209 70.42183 65.08596 73.64487
> colSums(tmp5)
[1] 1113.5398 641.3216 768.4185 NA 713.4649 724.4086 708.8870
[8] 725.8767 741.6384 710.7625 734.7303 658.7138 704.0658 727.1532
[15] 676.9845 730.9793 727.2209 704.2183 650.8596 736.4487
> colVars(tmp5)
[1] 16188.336226 30.382877 58.150052 NA 57.116400
[6] 116.100783 150.811817 64.793180 108.273860 148.065476
[11] 114.854087 5.244302 96.916905 20.583488 61.630606
[16] 63.328764 63.247860 25.070684 33.368658 38.446866
> colSd(tmp5)
[1] 127.233393 5.512066 7.625618 NA 7.557539 10.775007
[7] 12.280546 8.049421 10.405473 12.168216 10.717000 2.290044
[13] 9.844638 4.536903 7.850516 7.957937 7.952852 5.007063
[19] 5.776561 6.200554
> colMax(tmp5)
[1] 472.82786 76.56918 85.32128 NA 86.58956 89.42755 88.72883
[8] 85.51134 89.86450 84.70295 90.44524 70.13739 85.59402 79.30882
[15] 82.29069 79.68614 85.74061 76.82707 72.96469 82.35125
> colMin(tmp5)
[1] 62.25600 56.40743 58.64220 NA 62.16980 56.24932 54.05200 60.37708
[9] 58.66684 54.02099 58.98287 62.39046 57.79991 62.38908 57.47798 58.71377
[17] 58.82720 62.74341 56.01973 63.04183
>
> Max(tmp5,na.rm=TRUE)
[1] 472.8279
> Min(tmp5,na.rm=TRUE)
[1] 54.02099
> mean(tmp5,na.rm=TRUE)
[1] 73.078
> Sum(tmp5,na.rm=TRUE)
[1] 14542.52
> Var(tmp5,na.rm=TRUE)
[1] 882.0953
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.35150 71.13391 70.82373 69.99147 70.95662 72.06949 68.98654 73.08788
[9] 73.21537 69.06630
> rowSums(tmp5,na.rm=TRUE)
[1] 1827.030 1351.544 1416.475 1399.829 1419.132 1441.390 1379.731 1461.758
[9] 1464.307 1381.326
> rowVars(tmp5,na.rm=TRUE)
[1] 8154.84329 82.41304 63.09756 58.04188 75.80514 79.53449
[7] 54.71034 64.21684 74.62964 78.36486
> rowSd(tmp5,na.rm=TRUE)
[1] 90.304171 9.078163 7.943397 7.618522 8.706615 8.918211 7.396644
[8] 8.013541 8.638845 8.852393
> rowMax(tmp5,na.rm=TRUE)
[1] 472.82786 87.49219 85.58005 85.74061 87.91768 90.44524 84.70295
[8] 88.72883 89.42755 85.51134
> rowMin(tmp5,na.rm=TRUE)
[1] 54.59983 54.02099 56.01973 56.40743 54.05200 57.47798 56.24932 58.71377
[9] 60.12711 54.97462
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.35398 64.13216 76.84185 71.42557 71.34649 72.44086 70.88870
[8] 72.58767 74.16384 71.07625 73.47303 65.87138 70.40658 72.71532
[15] 67.69845 73.09793 72.72209 70.42183 65.08596 73.64487
> colSums(tmp5,na.rm=TRUE)
[1] 1113.5398 641.3216 768.4185 642.8301 713.4649 724.4086 708.8870
[8] 725.8767 741.6384 710.7625 734.7303 658.7138 704.0658 727.1532
[15] 676.9845 730.9793 727.2209 704.2183 650.8596 736.4487
> colVars(tmp5,na.rm=TRUE)
[1] 16188.336226 30.382877 58.150052 37.792656 57.116400
[6] 116.100783 150.811817 64.793180 108.273860 148.065476
[11] 114.854087 5.244302 96.916905 20.583488 61.630606
[16] 63.328764 63.247860 25.070684 33.368658 38.446866
> colSd(tmp5,na.rm=TRUE)
[1] 127.233393 5.512066 7.625618 6.147573 7.557539 10.775007
[7] 12.280546 8.049421 10.405473 12.168216 10.717000 2.290044
[13] 9.844638 4.536903 7.850516 7.957937 7.952852 5.007063
[19] 5.776561 6.200554
> colMax(tmp5,na.rm=TRUE)
[1] 472.82786 76.56918 85.32128 77.66019 86.58956 89.42755 88.72883
[8] 85.51134 89.86450 84.70295 90.44524 70.13739 85.59402 79.30882
[15] 82.29069 79.68614 85.74061 76.82707 72.96469 82.35125
> colMin(tmp5,na.rm=TRUE)
[1] 62.25600 56.40743 58.64220 59.76242 62.16980 56.24932 54.05200 60.37708
[9] 58.66684 54.02099 58.98287 62.39046 57.79991 62.38908 57.47798 58.71377
[17] 58.82720 62.74341 56.01973 63.04183
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.35150 NaN 70.82373 69.99147 70.95662 72.06949 68.98654 73.08788
[9] 73.21537 69.06630
> rowSums(tmp5,na.rm=TRUE)
[1] 1827.030 0.000 1416.475 1399.829 1419.132 1441.390 1379.731 1461.758
[9] 1464.307 1381.326
> rowVars(tmp5,na.rm=TRUE)
[1] 8154.84329 NA 63.09756 58.04188 75.80514 79.53449
[7] 54.71034 64.21684 74.62964 78.36486
> rowSd(tmp5,na.rm=TRUE)
[1] 90.304171 NA 7.943397 7.618522 8.706615 8.918211 7.396644
[8] 8.013541 8.638845 8.852393
> rowMax(tmp5,na.rm=TRUE)
[1] 472.82786 NA 85.58005 85.74061 87.91768 90.44524 84.70295
[8] 88.72883 89.42755 85.51134
> rowMin(tmp5,na.rm=TRUE)
[1] 54.59983 NA 56.01973 56.40743 54.05200 57.47798 56.24932 58.71377
[9] 60.12711 54.97462
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.53907 62.75027 76.68013 NaN 69.65282 72.59689 71.25861
[8] 72.76531 72.68291 72.97128 73.53237 66.11852 69.58807 73.86268
[15] 68.63885 72.46422 72.55677 69.71013 65.62256 74.24722
> colSums(tmp5,na.rm=TRUE)
[1] 1048.8516 564.7524 690.1211 0.0000 626.8754 653.3720 641.3275
[8] 654.8878 654.1462 656.7415 661.7913 595.0667 626.2926 664.7642
[15] 617.7497 652.1780 653.0109 627.3912 590.6031 668.2250
> colVars(tmp5,na.rm=TRUE)
[1] 17909.420459 12.697457 65.124568 NA 31.984984
[6] 130.339488 168.123882 72.537317 97.135175 126.173396
[11] 129.171234 5.212733 101.494332 8.346516 59.385478
[16] 66.726995 70.846350 22.506306 34.300355 39.170977
> colSd(tmp5,na.rm=TRUE)
[1] 133.826083 3.563349 8.069979 NA 5.655527 11.416632
[7] 12.966259 8.516884 9.855718 11.232693 11.365352 2.283141
[13] 10.074440 2.889034 7.706197 8.168659 8.417027 4.744081
[19] 5.856650 6.258672
> colMax(tmp5,na.rm=TRUE)
[1] 472.82786 67.62660 85.32128 -Inf 80.07190 89.42755 88.72883
[8] 85.51134 89.86450 84.70295 90.44524 70.13739 85.59402 79.30882
[15] 82.29069 79.68614 85.74061 75.07434 72.96469 82.35125
> colMin(tmp5,na.rm=TRUE)
[1] 62.25600 56.40743 58.64220 Inf 62.16980 56.24932 54.05200 60.37708
[9] 58.66684 54.59983 58.98287 62.39046 57.79991 69.88759 57.47798 58.71377
[17] 58.82720 62.74341 56.01973 63.04183
>
>
>
>
> 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] 197.6116 139.6796 138.4140 128.2120 244.8690 198.8143 116.4013 331.7404
[9] 163.5535 179.8218
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 197.6116 139.6796 138.4140 128.2120 244.8690 198.8143 116.4013 331.7404
[9] 163.5535 179.8218
>
>
>
> 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 7.105427e-14 8.526513e-14 2.842171e-14 5.684342e-14
[6] 0.000000e+00 -1.705303e-13 -2.842171e-14 2.273737e-13 -2.273737e-13
[11] 0.000000e+00 -2.557954e-13 0.000000e+00 1.136868e-13 5.684342e-14
[16] -5.684342e-14 5.684342e-14 0.000000e+00 5.684342e-14 -1.705303e-13
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
8 4
6 8
3 6
10 8
8 2
9 14
9 16
8 3
3 9
6 9
10 4
8 6
4 1
5 8
2 2
6 19
1 15
7 15
1 9
9 3
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] 3.080607
> Min(tmp)
[1] -2.642174
> mean(tmp)
[1] 0.1740977
> Sum(tmp)
[1] 17.40977
> Var(tmp)
[1] 0.8965595
>
> rowMeans(tmp)
[1] 0.1740977
> rowSums(tmp)
[1] 17.40977
> rowVars(tmp)
[1] 0.8965595
> rowSd(tmp)
[1] 0.9468683
> rowMax(tmp)
[1] 3.080607
> rowMin(tmp)
[1] -2.642174
>
> colMeans(tmp)
[1] 0.78244534 0.29306028 -0.29359393 -0.52914409 -1.02713350 0.77503589
[7] 0.39179900 0.95453580 -1.22899738 -1.06799617 -0.02175118 1.11642053
[13] -1.72456322 0.62226054 1.32291465 0.02161349 0.71373555 0.40822953
[19] -1.90718713 1.12743157 0.73588470 -0.69375697 -1.22827040 0.23767634
[25] 0.08029393 -0.67299796 -0.08831075 -2.24531148 0.99804705 -0.55167546
[31] -0.12323458 3.08060741 -1.34079093 0.76651180 0.58077202 -0.31881990
[37] 1.08346732 1.69117947 -0.45468070 -0.72139005 -0.27867141 0.43709866
[43] -1.12814813 -0.39958238 -0.49668422 1.94594432 -0.15391150 1.60684074
[49] 0.78266628 0.62710137 0.49294733 0.64199036 1.10092449 0.21276973
[55] 0.57433242 -0.17828203 0.99798827 2.30510652 -0.93213894 0.86758256
[61] 1.20740712 0.26314045 -2.64217437 0.54248492 -1.80892846 0.64502338
[67] 0.71508949 0.16817936 -0.32461785 0.74837977 0.37738550 1.13362240
[73] -0.37109305 0.74627642 -0.76557448 -0.44209285 0.23936404 -0.10981994
[79] 1.58639050 0.52022647 1.20517584 0.05985932 -0.38116201 0.02060864
[85] 1.15221902 0.36670803 -0.62053282 0.97171745 -0.31715571 0.85237639
[91] 0.21776906 0.51819751 -1.07101862 0.44523180 0.37514068 0.21823744
[97] -0.60682647 0.45196771 0.02969208 0.52270478
> colSums(tmp)
[1] 0.78244534 0.29306028 -0.29359393 -0.52914409 -1.02713350 0.77503589
[7] 0.39179900 0.95453580 -1.22899738 -1.06799617 -0.02175118 1.11642053
[13] -1.72456322 0.62226054 1.32291465 0.02161349 0.71373555 0.40822953
[19] -1.90718713 1.12743157 0.73588470 -0.69375697 -1.22827040 0.23767634
[25] 0.08029393 -0.67299796 -0.08831075 -2.24531148 0.99804705 -0.55167546
[31] -0.12323458 3.08060741 -1.34079093 0.76651180 0.58077202 -0.31881990
[37] 1.08346732 1.69117947 -0.45468070 -0.72139005 -0.27867141 0.43709866
[43] -1.12814813 -0.39958238 -0.49668422 1.94594432 -0.15391150 1.60684074
[49] 0.78266628 0.62710137 0.49294733 0.64199036 1.10092449 0.21276973
[55] 0.57433242 -0.17828203 0.99798827 2.30510652 -0.93213894 0.86758256
[61] 1.20740712 0.26314045 -2.64217437 0.54248492 -1.80892846 0.64502338
[67] 0.71508949 0.16817936 -0.32461785 0.74837977 0.37738550 1.13362240
[73] -0.37109305 0.74627642 -0.76557448 -0.44209285 0.23936404 -0.10981994
[79] 1.58639050 0.52022647 1.20517584 0.05985932 -0.38116201 0.02060864
[85] 1.15221902 0.36670803 -0.62053282 0.97171745 -0.31715571 0.85237639
[91] 0.21776906 0.51819751 -1.07101862 0.44523180 0.37514068 0.21823744
[97] -0.60682647 0.45196771 0.02969208 0.52270478
> 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] 0.78244534 0.29306028 -0.29359393 -0.52914409 -1.02713350 0.77503589
[7] 0.39179900 0.95453580 -1.22899738 -1.06799617 -0.02175118 1.11642053
[13] -1.72456322 0.62226054 1.32291465 0.02161349 0.71373555 0.40822953
[19] -1.90718713 1.12743157 0.73588470 -0.69375697 -1.22827040 0.23767634
[25] 0.08029393 -0.67299796 -0.08831075 -2.24531148 0.99804705 -0.55167546
[31] -0.12323458 3.08060741 -1.34079093 0.76651180 0.58077202 -0.31881990
[37] 1.08346732 1.69117947 -0.45468070 -0.72139005 -0.27867141 0.43709866
[43] -1.12814813 -0.39958238 -0.49668422 1.94594432 -0.15391150 1.60684074
[49] 0.78266628 0.62710137 0.49294733 0.64199036 1.10092449 0.21276973
[55] 0.57433242 -0.17828203 0.99798827 2.30510652 -0.93213894 0.86758256
[61] 1.20740712 0.26314045 -2.64217437 0.54248492 -1.80892846 0.64502338
[67] 0.71508949 0.16817936 -0.32461785 0.74837977 0.37738550 1.13362240
[73] -0.37109305 0.74627642 -0.76557448 -0.44209285 0.23936404 -0.10981994
[79] 1.58639050 0.52022647 1.20517584 0.05985932 -0.38116201 0.02060864
[85] 1.15221902 0.36670803 -0.62053282 0.97171745 -0.31715571 0.85237639
[91] 0.21776906 0.51819751 -1.07101862 0.44523180 0.37514068 0.21823744
[97] -0.60682647 0.45196771 0.02969208 0.52270478
> colMin(tmp)
[1] 0.78244534 0.29306028 -0.29359393 -0.52914409 -1.02713350 0.77503589
[7] 0.39179900 0.95453580 -1.22899738 -1.06799617 -0.02175118 1.11642053
[13] -1.72456322 0.62226054 1.32291465 0.02161349 0.71373555 0.40822953
[19] -1.90718713 1.12743157 0.73588470 -0.69375697 -1.22827040 0.23767634
[25] 0.08029393 -0.67299796 -0.08831075 -2.24531148 0.99804705 -0.55167546
[31] -0.12323458 3.08060741 -1.34079093 0.76651180 0.58077202 -0.31881990
[37] 1.08346732 1.69117947 -0.45468070 -0.72139005 -0.27867141 0.43709866
[43] -1.12814813 -0.39958238 -0.49668422 1.94594432 -0.15391150 1.60684074
[49] 0.78266628 0.62710137 0.49294733 0.64199036 1.10092449 0.21276973
[55] 0.57433242 -0.17828203 0.99798827 2.30510652 -0.93213894 0.86758256
[61] 1.20740712 0.26314045 -2.64217437 0.54248492 -1.80892846 0.64502338
[67] 0.71508949 0.16817936 -0.32461785 0.74837977 0.37738550 1.13362240
[73] -0.37109305 0.74627642 -0.76557448 -0.44209285 0.23936404 -0.10981994
[79] 1.58639050 0.52022647 1.20517584 0.05985932 -0.38116201 0.02060864
[85] 1.15221902 0.36670803 -0.62053282 0.97171745 -0.31715571 0.85237639
[91] 0.21776906 0.51819751 -1.07101862 0.44523180 0.37514068 0.21823744
[97] -0.60682647 0.45196771 0.02969208 0.52270478
> colMedians(tmp)
[1] 0.78244534 0.29306028 -0.29359393 -0.52914409 -1.02713350 0.77503589
[7] 0.39179900 0.95453580 -1.22899738 -1.06799617 -0.02175118 1.11642053
[13] -1.72456322 0.62226054 1.32291465 0.02161349 0.71373555 0.40822953
[19] -1.90718713 1.12743157 0.73588470 -0.69375697 -1.22827040 0.23767634
[25] 0.08029393 -0.67299796 -0.08831075 -2.24531148 0.99804705 -0.55167546
[31] -0.12323458 3.08060741 -1.34079093 0.76651180 0.58077202 -0.31881990
[37] 1.08346732 1.69117947 -0.45468070 -0.72139005 -0.27867141 0.43709866
[43] -1.12814813 -0.39958238 -0.49668422 1.94594432 -0.15391150 1.60684074
[49] 0.78266628 0.62710137 0.49294733 0.64199036 1.10092449 0.21276973
[55] 0.57433242 -0.17828203 0.99798827 2.30510652 -0.93213894 0.86758256
[61] 1.20740712 0.26314045 -2.64217437 0.54248492 -1.80892846 0.64502338
[67] 0.71508949 0.16817936 -0.32461785 0.74837977 0.37738550 1.13362240
[73] -0.37109305 0.74627642 -0.76557448 -0.44209285 0.23936404 -0.10981994
[79] 1.58639050 0.52022647 1.20517584 0.05985932 -0.38116201 0.02060864
[85] 1.15221902 0.36670803 -0.62053282 0.97171745 -0.31715571 0.85237639
[91] 0.21776906 0.51819751 -1.07101862 0.44523180 0.37514068 0.21823744
[97] -0.60682647 0.45196771 0.02969208 0.52270478
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.7824453 0.2930603 -0.2935939 -0.5291441 -1.027133 0.7750359 0.391799
[2,] 0.7824453 0.2930603 -0.2935939 -0.5291441 -1.027133 0.7750359 0.391799
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.9545358 -1.228997 -1.067996 -0.02175118 1.116421 -1.724563 0.6222605
[2,] 0.9545358 -1.228997 -1.067996 -0.02175118 1.116421 -1.724563 0.6222605
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.322915 0.02161349 0.7137356 0.4082295 -1.907187 1.127432 0.7358847
[2,] 1.322915 0.02161349 0.7137356 0.4082295 -1.907187 1.127432 0.7358847
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.693757 -1.22827 0.2376763 0.08029393 -0.672998 -0.08831075 -2.245311
[2,] -0.693757 -1.22827 0.2376763 0.08029393 -0.672998 -0.08831075 -2.245311
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.998047 -0.5516755 -0.1232346 3.080607 -1.340791 0.7665118 0.580772
[2,] 0.998047 -0.5516755 -0.1232346 3.080607 -1.340791 0.7665118 0.580772
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.3188199 1.083467 1.691179 -0.4546807 -0.72139 -0.2786714 0.4370987
[2,] -0.3188199 1.083467 1.691179 -0.4546807 -0.72139 -0.2786714 0.4370987
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.128148 -0.3995824 -0.4966842 1.945944 -0.1539115 1.606841 0.7826663
[2,] -1.128148 -0.3995824 -0.4966842 1.945944 -0.1539115 1.606841 0.7826663
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.6271014 0.4929473 0.6419904 1.100924 0.2127697 0.5743324 -0.178282
[2,] 0.6271014 0.4929473 0.6419904 1.100924 0.2127697 0.5743324 -0.178282
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.9979883 2.305107 -0.9321389 0.8675826 1.207407 0.2631405 -2.642174
[2,] 0.9979883 2.305107 -0.9321389 0.8675826 1.207407 0.2631405 -2.642174
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.5424849 -1.808928 0.6450234 0.7150895 0.1681794 -0.3246179 0.7483798
[2,] 0.5424849 -1.808928 0.6450234 0.7150895 0.1681794 -0.3246179 0.7483798
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.3773855 1.133622 -0.3710931 0.7462764 -0.7655745 -0.4420929 0.239364
[2,] 0.3773855 1.133622 -0.3710931 0.7462764 -0.7655745 -0.4420929 0.239364
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.1098199 1.58639 0.5202265 1.205176 0.05985932 -0.381162 0.02060864
[2,] -0.1098199 1.58639 0.5202265 1.205176 0.05985932 -0.381162 0.02060864
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.152219 0.366708 -0.6205328 0.9717175 -0.3171557 0.8523764 0.2177691
[2,] 1.152219 0.366708 -0.6205328 0.9717175 -0.3171557 0.8523764 0.2177691
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.5181975 -1.071019 0.4452318 0.3751407 0.2182374 -0.6068265 0.4519677
[2,] 0.5181975 -1.071019 0.4452318 0.3751407 0.2182374 -0.6068265 0.4519677
[,99] [,100]
[1,] 0.02969208 0.5227048
[2,] 0.02969208 0.5227048
>
>
> Max(tmp2)
[1] 1.733115
> Min(tmp2)
[1] -2.456515
> mean(tmp2)
[1] 0.01729533
> Sum(tmp2)
[1] 1.729533
> Var(tmp2)
[1] 0.8655978
>
> rowMeans(tmp2)
[1] -0.964032550 -1.579286307 0.006164245 0.371499864 0.229499975
[6] -0.791169760 1.499099464 0.633939869 0.384098028 -0.074535182
[11] 0.028096333 -1.219741710 0.184783983 0.358219067 -0.795803014
[16] -2.268076744 1.259041243 -0.971050463 -0.500696166 0.776287938
[21] -1.405706209 -0.235133409 -0.018178473 -1.764334804 0.146212437
[26] 0.413115246 0.879087927 1.355622236 -0.971733084 -0.151242134
[31] -1.013227774 0.388616973 0.794172564 -1.168937315 0.569070542
[36] 1.150309188 1.101234894 -0.008427868 -1.005397151 0.391377836
[41] -0.174736936 -0.395452678 1.572242250 0.062872582 0.130827576
[46] 0.715936188 1.157376856 -0.172344935 -0.308858189 1.444305134
[51] 1.205008459 -1.007502665 -1.160161877 0.235737128 0.793822531
[56] 0.512400244 -1.702207958 0.514766081 -1.203013638 -1.512631993
[61] 0.242934269 -0.046315403 0.372734800 -0.570127753 -0.129403353
[66] -1.644256588 0.661279183 -2.456515085 0.105112003 -0.691162528
[71] 1.317207066 0.541063866 -0.036639840 -1.267265786 0.842006375
[76] 0.492923166 0.271277907 0.052026971 -0.523705935 -0.569828666
[81] 1.142665266 -0.313370962 -0.750040688 1.088639099 0.035115801
[86] -0.425285935 0.960335025 1.630938441 0.911689648 -1.092742979
[91] -0.281271625 -1.075989233 1.733114592 1.189275430 0.710461969
[96] -0.349034349 0.309416704 1.124358944 0.443630180 1.053059143
> rowSums(tmp2)
[1] -0.964032550 -1.579286307 0.006164245 0.371499864 0.229499975
[6] -0.791169760 1.499099464 0.633939869 0.384098028 -0.074535182
[11] 0.028096333 -1.219741710 0.184783983 0.358219067 -0.795803014
[16] -2.268076744 1.259041243 -0.971050463 -0.500696166 0.776287938
[21] -1.405706209 -0.235133409 -0.018178473 -1.764334804 0.146212437
[26] 0.413115246 0.879087927 1.355622236 -0.971733084 -0.151242134
[31] -1.013227774 0.388616973 0.794172564 -1.168937315 0.569070542
[36] 1.150309188 1.101234894 -0.008427868 -1.005397151 0.391377836
[41] -0.174736936 -0.395452678 1.572242250 0.062872582 0.130827576
[46] 0.715936188 1.157376856 -0.172344935 -0.308858189 1.444305134
[51] 1.205008459 -1.007502665 -1.160161877 0.235737128 0.793822531
[56] 0.512400244 -1.702207958 0.514766081 -1.203013638 -1.512631993
[61] 0.242934269 -0.046315403 0.372734800 -0.570127753 -0.129403353
[66] -1.644256588 0.661279183 -2.456515085 0.105112003 -0.691162528
[71] 1.317207066 0.541063866 -0.036639840 -1.267265786 0.842006375
[76] 0.492923166 0.271277907 0.052026971 -0.523705935 -0.569828666
[81] 1.142665266 -0.313370962 -0.750040688 1.088639099 0.035115801
[86] -0.425285935 0.960335025 1.630938441 0.911689648 -1.092742979
[91] -0.281271625 -1.075989233 1.733114592 1.189275430 0.710461969
[96] -0.349034349 0.309416704 1.124358944 0.443630180 1.053059143
> 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] -0.964032550 -1.579286307 0.006164245 0.371499864 0.229499975
[6] -0.791169760 1.499099464 0.633939869 0.384098028 -0.074535182
[11] 0.028096333 -1.219741710 0.184783983 0.358219067 -0.795803014
[16] -2.268076744 1.259041243 -0.971050463 -0.500696166 0.776287938
[21] -1.405706209 -0.235133409 -0.018178473 -1.764334804 0.146212437
[26] 0.413115246 0.879087927 1.355622236 -0.971733084 -0.151242134
[31] -1.013227774 0.388616973 0.794172564 -1.168937315 0.569070542
[36] 1.150309188 1.101234894 -0.008427868 -1.005397151 0.391377836
[41] -0.174736936 -0.395452678 1.572242250 0.062872582 0.130827576
[46] 0.715936188 1.157376856 -0.172344935 -0.308858189 1.444305134
[51] 1.205008459 -1.007502665 -1.160161877 0.235737128 0.793822531
[56] 0.512400244 -1.702207958 0.514766081 -1.203013638 -1.512631993
[61] 0.242934269 -0.046315403 0.372734800 -0.570127753 -0.129403353
[66] -1.644256588 0.661279183 -2.456515085 0.105112003 -0.691162528
[71] 1.317207066 0.541063866 -0.036639840 -1.267265786 0.842006375
[76] 0.492923166 0.271277907 0.052026971 -0.523705935 -0.569828666
[81] 1.142665266 -0.313370962 -0.750040688 1.088639099 0.035115801
[86] -0.425285935 0.960335025 1.630938441 0.911689648 -1.092742979
[91] -0.281271625 -1.075989233 1.733114592 1.189275430 0.710461969
[96] -0.349034349 0.309416704 1.124358944 0.443630180 1.053059143
> rowMin(tmp2)
[1] -0.964032550 -1.579286307 0.006164245 0.371499864 0.229499975
[6] -0.791169760 1.499099464 0.633939869 0.384098028 -0.074535182
[11] 0.028096333 -1.219741710 0.184783983 0.358219067 -0.795803014
[16] -2.268076744 1.259041243 -0.971050463 -0.500696166 0.776287938
[21] -1.405706209 -0.235133409 -0.018178473 -1.764334804 0.146212437
[26] 0.413115246 0.879087927 1.355622236 -0.971733084 -0.151242134
[31] -1.013227774 0.388616973 0.794172564 -1.168937315 0.569070542
[36] 1.150309188 1.101234894 -0.008427868 -1.005397151 0.391377836
[41] -0.174736936 -0.395452678 1.572242250 0.062872582 0.130827576
[46] 0.715936188 1.157376856 -0.172344935 -0.308858189 1.444305134
[51] 1.205008459 -1.007502665 -1.160161877 0.235737128 0.793822531
[56] 0.512400244 -1.702207958 0.514766081 -1.203013638 -1.512631993
[61] 0.242934269 -0.046315403 0.372734800 -0.570127753 -0.129403353
[66] -1.644256588 0.661279183 -2.456515085 0.105112003 -0.691162528
[71] 1.317207066 0.541063866 -0.036639840 -1.267265786 0.842006375
[76] 0.492923166 0.271277907 0.052026971 -0.523705935 -0.569828666
[81] 1.142665266 -0.313370962 -0.750040688 1.088639099 0.035115801
[86] -0.425285935 0.960335025 1.630938441 0.911689648 -1.092742979
[91] -0.281271625 -1.075989233 1.733114592 1.189275430 0.710461969
[96] -0.349034349 0.309416704 1.124358944 0.443630180 1.053059143
>
> colMeans(tmp2)
[1] 0.01729533
> colSums(tmp2)
[1] 1.729533
> colVars(tmp2)
[1] 0.8655978
> colSd(tmp2)
[1] 0.9303751
> colMax(tmp2)
[1] 1.733115
> colMin(tmp2)
[1] -2.456515
> colMedians(tmp2)
[1] 0.08399229
> colRanges(tmp2)
[,1]
[1,] -2.456515
[2,] 1.733115
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -6.8477937 1.6843912 -2.5701615 -0.7056415 -7.3846594 7.2345798
[7] 4.3491250 2.2698615 -0.9039145 6.8101579
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.01290738
[2,] -1.24921216
[3,] -0.83969547
[4,] -0.04230923
[5,] 1.25321430
>
> rowApply(tmp,sum)
[1] -0.5820917 2.6252463 -0.4741144 -0.4046006 5.3270134 3.8477684
[7] 1.2105058 -1.4642029 -3.2415497 -2.9080297
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 5 2 1 7 1 6 4 2 2
[2,] 2 2 9 8 10 2 2 7 6 8
[3,] 1 3 8 5 2 3 7 10 4 1
[4,] 5 8 3 4 4 9 4 2 3 9
[5,] 3 1 5 7 1 6 1 5 1 4
[6,] 8 9 10 3 9 10 8 3 7 7
[7,] 10 6 4 6 3 8 9 9 9 6
[8,] 7 4 6 10 8 7 3 1 8 3
[9,] 6 7 1 9 5 5 10 6 5 5
[10,] 9 10 7 2 6 4 5 8 10 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.7940311 0.4100394 -5.8858179 0.1098240 -2.2782115 -2.6022313
[7] -0.6733569 -0.3594647 0.9895794 -0.3282674 1.7935148 -0.1951469
[13] 0.2039698 -5.2151881 3.2288262 -2.1816847 2.8148430 -1.1602854
[19] 0.1540089 -3.4027652
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.97239572
[2,] -0.74988798
[3,] -0.07354199
[4,] -0.06942016
[5,] 0.07121471
>
> rowApply(tmp,sum)
[1] -3.894297 -4.500824 -5.663305 3.794152 -6.107573
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 12 5 9 7
[2,] 19 10 8 6 13
[3,] 1 6 3 14 1
[4,] 6 8 13 20 8
[5,] 15 16 6 1 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.07121471 1.12767955 -1.9633217 -0.7590757 0.2451639 -1.315685641
[2,] -0.06942016 -0.09160973 -0.6902383 -0.6093949 0.1713283 -0.006899803
[3,] -0.97239572 -0.65614746 -1.2268374 0.2938463 -0.9034179 -1.101635780
[4,] -0.07354199 -0.17625276 0.6804922 1.8740469 -2.0932562 1.054203311
[5,] -0.74988798 0.20636976 -2.6859127 -0.6895986 0.3019704 -1.232213435
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.2764943 0.6743896 -1.1986128 -0.7271724 0.497082796 -0.454924622
[2,] -1.1063143 -0.6566443 0.3166616 -0.4944280 -0.007574418 -1.465481237
[3,] 0.0795828 0.6372884 0.9874995 0.6304546 -0.092558920 0.004246757
[4,] 0.2805569 -0.1452566 1.4608736 0.9335534 -0.273104799 1.277471626
[5,] 0.3493120 -0.8692418 -0.5768425 -0.6706750 1.669670161 0.443540626
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.0798202 -1.7128711 2.8837221 -0.8587491 0.1532117 -0.4473300
[2,] 0.5871211 -0.0857555 -1.5709919 -0.7694215 2.4478252 0.5176234
[3,] -1.7127137 -2.4615984 0.2965053 0.4288049 -0.3165000 -0.8477872
[4,] 1.4733142 -0.1371479 0.3659872 -0.5146747 0.2530237 -0.9046414
[5,] -1.2235720 -0.8178152 1.2536034 -0.4676442 0.2772823 0.5218498
[,19] [,20]
[1,] -0.7173474 -0.1949966
[2,] 0.0691949 -0.9864041
[3,] 0.7835400 0.4865192
[4,] 0.3454334 -1.8869281
[5,] -0.3268120 -0.8209556
>
>
> 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 : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.7728531 0.895378 -0.7012966 -0.3232149 1.773927 -0.09316934 0.02167106
col8 col9 col10 col11 col12 col13 col14
row1 3.041208 0.6906887 0.5515582 1.414572 -0.3463405 -0.3159079 0.300897
col15 col16 col17 col18 col19 col20
row1 -0.6728857 -0.8124006 0.4062096 1.001576 -0.3880432 1.203736
> tmp[,"col10"]
col10
row1 0.5515582
row2 0.6539020
row3 -0.3356969
row4 2.3922509
row5 2.1666930
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.7728531 0.89537800 -0.7012966 -0.3232149 1.7739274 -0.09316934
row5 0.7789567 -0.04664213 0.1232265 -0.4247152 0.8208485 1.14006230
col7 col8 col9 col10 col11 col12 col13
row1 0.02167106 3.041208 0.6906887 0.5515582 1.414572 -0.3463405 -0.3159079
row5 -0.52585876 -2.166875 -0.9310567 2.1666930 -1.191514 -2.0081465 -0.8824715
col14 col15 col16 col17 col18 col19 col20
row1 0.3008970 -0.6728857 -0.8124006 0.4062096 1.001576 -0.3880432 1.2037359
row5 -0.5715791 0.8509813 0.8767132 1.0489732 -2.135226 0.2759689 0.4530907
> tmp[,c("col6","col20")]
col6 col20
row1 -0.09316934 1.2037359
row2 0.05517612 -0.1110939
row3 -0.02317430 0.1134395
row4 1.38073869 -2.5147340
row5 1.14006230 0.4530907
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.09316934 1.2037359
row5 1.14006230 0.4530907
>
>
>
>
> 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 51.38112 49.68751 49.49377 50.94771 49.95081 105.1222 47.95322 51.02903
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.24447 51.07523 52.04311 49.62865 50.31606 52.1979 50.95623 49.73375
col17 col18 col19 col20
row1 50.78354 48.78388 49.81804 104.4266
> tmp[,"col10"]
col10
row1 51.07523
row2 29.80238
row3 30.25956
row4 29.06203
row5 51.38590
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.38112 49.68751 49.49377 50.94771 49.95081 105.1222 47.95322 51.02903
row5 50.71288 48.92514 49.68741 51.24488 48.71322 105.1566 51.89512 49.88552
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.24447 51.07523 52.04311 49.62865 50.31606 52.19790 50.95623 49.73375
row5 51.07892 51.38590 49.38764 50.24665 49.59277 51.84425 50.29807 49.02041
col17 col18 col19 col20
row1 50.78354 48.78388 49.81804 104.4266
row5 51.25401 50.36199 50.91543 105.9989
> tmp[,c("col6","col20")]
col6 col20
row1 105.12222 104.42661
row2 76.49100 74.43085
row3 75.03369 74.19053
row4 76.02252 74.05512
row5 105.15660 105.99894
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1222 104.4266
row5 105.1566 105.9989
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1222 104.4266
row5 105.1566 105.9989
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.38443021
[2,] -0.30379693
[3,] -0.49282085
[4,] -0.03662926
[5,] 1.67694635
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.18961507 0.33191249
[2,] 1.10984134 1.71718803
[3,] -1.01275392 1.34515894
[4,] 0.01076635 0.06651774
[5,] 0.22839726 0.05535784
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.3716058 0.5774824
[2,] 0.1604755 0.4379846
[3,] -1.2743198 -1.4056920
[4,] -0.7422964 1.4801797
[5,] -0.9573869 0.1781953
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3716058
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.3716058
[2,] 0.1604755
>
>
>
> 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 -0.3959535 -1.364787 -1.0223046 0.1084517 -2.00904001 0.5984027
row1 0.1323206 -0.980723 -0.0204195 0.2881870 0.04666047 0.4697823
[,7] [,8] [,9] [,10] [,11] [,12]
row3 1.10197244 -0.3694553 0.5608745 -0.03006331 0.8437989 0.9930711
row1 -0.02777556 -0.8317165 1.5460166 0.25037428 -0.5352001 -0.4328855
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 1.413058 0.1281447 0.1395667 -0.5643978 0.3232339 0.6131884 0.4463361
row1 -1.171867 -0.8046686 0.4364592 -0.4933020 0.3673270 -1.4360943 -0.4685787
[,20]
row3 -0.7074321
row1 0.5662487
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.007457 -0.04359881 -2.229229 1.513703 -0.8309578 1.161585 0.3038792
[,8] [,9] [,10]
row2 0.06181085 -0.9772004 -1.000023
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.871729 0.0390032 0.6671985 0.01304672 0.8137233 0.4433741 -1.247737
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.1487661 -1.57036 -0.4448558 0.8120515 2.381494 -0.4067434 0.5641561
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -2.863215 -0.4680052 -0.3489402 1.290459 -0.290861 -0.3157481
>
>
> 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: 0x6260d16cbaf0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c32369282b"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c375c6956f"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c32ae3c542"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c31160f280"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c330319d9e"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c34c3ad237"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c361666564"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c3120c9566"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c31374ff44"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c3539c2536"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c319b13bbf"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c36125f8a3"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c375fe6e42"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c351dd91ce"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM24a9c31b83307c"
>
>
> ### 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: 0x6260d307bad0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6260d307bad0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6260d307bad0>
> rowMedians(tmp)
[1] 0.204538163 -0.066645943 -0.092078805 0.303135095 0.153024900
[6] 0.089838300 -0.715582047 -1.018832229 0.512779573 0.055188919
[11] 0.217007976 0.471385975 -0.059398518 -0.245295961 0.123279831
[16] 0.344986113 0.439671814 -0.040941543 -0.608828047 0.584157244
[21] 0.267713206 0.021068166 -0.599619959 0.088125256 -0.097942723
[26] 0.676871039 -0.311473007 -0.221976078 0.290508956 0.269489896
[31] 0.322158356 0.070773361 0.151238067 -0.023938719 -0.521510803
[36] -0.105971578 -0.382203891 -0.047680799 -0.087221620 0.106261088
[41] 0.041238603 0.086013350 0.107839985 0.166948968 -0.008945402
[46] -0.009813836 -0.465061478 0.131598135 -0.737432069 -0.075743344
[51] 0.503753174 -0.258668038 0.216010572 -0.121209618 -0.519752172
[56] 0.832524819 -0.357964472 -0.117949439 0.298866975 0.079516384
[61] -0.461731580 -0.552269874 0.275460249 0.094525554 0.437063462
[66] -0.089189927 0.405940393 -0.559615472 -0.001480678 0.020252668
[71] -0.603274201 0.014748989 0.004061008 -0.416051823 0.289186160
[76] 0.371034463 -0.245964339 -0.581238837 0.696349457 -0.726798888
[81] -0.393559415 0.158787141 -0.092238752 -0.054168972 0.307372493
[86] -0.598129306 -0.039632080 0.128273021 -0.334727289 -0.460985153
[91] -0.145557662 0.093868096 0.368794477 -0.373190108 -0.587992967
[96] 0.108582349 -0.205864398 -0.121233061 0.152568615 0.130512435
[101] -0.187473433 -0.223247940 -0.264978890 0.318909677 0.316395393
[106] -0.476106775 0.425282984 -0.205132628 0.083924890 -0.112130612
[111] 0.430247783 0.367643516 0.361606303 -0.136381759 -0.046999079
[116] -0.359606374 -0.005182035 0.520157282 -0.284377696 -0.064630420
[121] -0.536148444 0.018386051 0.032206105 -0.101735488 0.151056246
[126] 0.096714481 -0.208915254 0.456267849 -0.041465219 -0.125844369
[131] -0.387469262 -0.099938594 0.561557036 -0.216915439 0.099376227
[136] 0.186268043 -0.045372403 0.395504723 -0.084750914 -0.145863956
[141] -0.063408595 0.426500928 0.289954802 -0.033386271 0.306837316
[146] -0.098868992 -0.487660831 -0.004649711 0.618440547 0.112858599
[151] 0.079743415 -0.535423398 -0.075459865 -0.083429866 0.154089348
[156] -0.627402503 0.231709433 0.170297331 0.013570768 0.087819012
[161] -0.092828599 0.453347489 -0.126458812 0.440531805 -0.156647147
[166] 0.155332661 -0.442826052 -0.022641628 -0.038462641 0.265944488
[171] 0.428690046 -0.047865886 -0.089189533 -0.085354932 0.353684477
[176] 0.697030089 -0.178092764 -0.462410735 0.358699607 0.300167007
[181] 0.106387903 0.346146978 0.144614875 0.446773768 0.241212309
[186] -0.303436913 -0.250789460 0.192649687 -0.247117913 -0.072049213
[191] -0.608183355 0.642604552 0.125812890 0.026559901 -0.541583292
[196] -0.013797833 0.388830208 0.261772799 -0.491251246 0.189690162
[201] -0.033307461 -0.065924394 0.195516033 -0.199700976 -0.022983561
[206] 0.156816852 0.052989138 0.470143061 -0.266165889 -0.622118183
[211] -0.025320769 0.069549671 -0.224747711 0.148441685 0.716317346
[216] 0.408698947 -0.415725576 0.370831901 -0.120202509 0.208656093
[221] 0.014544558 0.424693514 0.217774349 0.333444183 0.025017991
[226] -0.323150292 0.078045196 -0.173731427 -0.296633939 -0.034308127
>
> proc.time()
user system elapsed
1.341 1.478 2.809
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: 0x6530f1a565f0>
> .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: 0x6530f1a565f0>
> .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: 0x6530f1a565f0>
> .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: 0x6530f1a565f0>
> 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: 0x6530f22d42b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f22d42b0>
> .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: 0x6530f22d42b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f22d42b0>
> .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: 0x6530f22d42b0>
> 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: 0x6530f19b7a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f19b7a20>
> .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: 0x6530f19b7a20>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6530f19b7a20>
> .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: 0x6530f19b7a20>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6530f19b7a20>
> .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: 0x6530f19b7a20>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6530f19b7a20>
> .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: 0x6530f19b7a20>
> 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: 0x6530f2194e00>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6530f2194e00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f2194e00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f2194e00>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile24aafd2407aa84" "BufferedMatrixFile24aafd7d7a9db7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile24aafd2407aa84" "BufferedMatrixFile24aafd7d7a9db7"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f209c4c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f209c4c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6530f209c4c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6530f209c4c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6530f209c4c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6530f209c4c0>
> .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: 0x6530f24457e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6530f24457e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6530f24457e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6530f24457e0>
> 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: 0x6530f351e520>
> .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: 0x6530f351e520>
> rm(P)
>
> proc.time()
user system elapsed
0.249 0.047 0.285
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
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.245 0.044 0.277