Ben Bolstad
| Snapshot Date: 2025-12-15 13:40 -0500 (Mon, 15 Dec 2025) |
| 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 2025-12-16 11:34 -0500 (Tue, 16 Dec 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4875 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4583 |
| 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: 2025-12-15 21:27:26 -0500 (Mon, 15 Dec 2025) |
| EndedAt: 2025-12-15 21:27:52 -0500 (Mon, 15 Dec 2025) |
| EllapsedTime: 26.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* 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
##############################################################################
##############################################################################
###
### 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) (2025-10-20 r88955) -- "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
0.236 0.053 0.278
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "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 478818 25.6 1048392 56 639317 34.2
Vcells 885623 6.8 8388608 64 2082728 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] "Mon Dec 15 21:27:43 2025"
> 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] "Mon Dec 15 21:27:43 2025"
>
>
> 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: 0x61ff523155e0>
>
>
>
> 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] "Mon Dec 15 21:27:43 2025"
> 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] "Mon Dec 15 21:27:43 2025"
>
> ColMode(tmp2)
<pointer: 0x61ff523155e0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.4270002 -0.4530989 1.7156058 0.2089908
[2,] -0.9794666 -1.1264877 -0.8306319 1.3425342
[3,] 0.2210405 0.7905584 -1.5811570 -0.7675133
[4,] 0.4106070 1.2636560 2.7450519 -1.4533487
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.4270002 0.4530989 1.7156058 0.2089908
[2,] 0.9794666 1.1264877 0.8306319 1.3425342
[3,] 0.2210405 0.7905584 1.5811570 0.7675133
[4,] 0.4106070 1.2636560 2.7450519 1.4533487
> 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,] 10.0213273 0.6731262 1.3098114 0.4571551
[2,] 0.9896800 1.0613612 0.9113901 1.1586778
[3,] 0.4701495 0.8891335 1.2574407 0.8760784
[4,] 0.6407862 1.1241245 1.6568198 1.2055491
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.64027 32.18436 39.81372 29.78054
[2,] 35.87627 36.74010 34.94453 37.92931
[3,] 29.92254 34.68189 39.15556 34.52830
[4,] 31.81847 37.50490 44.31325 38.50884
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x61ff51ea0840>
> exp(tmp5)
<pointer: 0x61ff51ea0840>
> log(tmp5,2)
<pointer: 0x61ff51ea0840>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.6407
> Min(tmp5)
[1] 53.1576
> mean(tmp5)
[1] 74.48488
> Sum(tmp5)
[1] 14896.98
> Var(tmp5)
[1] 865.5438
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.83046 75.29473 68.23066 74.80807 73.70940 73.72974 72.79964 70.50288
[9] 72.17220 70.77098
> rowSums(tmp5)
[1] 1856.609 1505.895 1364.613 1496.161 1474.188 1474.595 1455.993 1410.058
[9] 1443.444 1415.420
> rowVars(tmp5)
[1] 7936.68866 44.85754 72.91547 107.25841 79.27679 114.32234
[7] 48.55621 76.08763 45.45609 102.70247
> rowSd(tmp5)
[1] 89.088095 6.697577 8.539056 10.356564 8.903751 10.692163 6.968229
[8] 8.722822 6.742113 10.134223
> rowMax(tmp5)
[1] 469.64066 85.92678 85.22494 92.23222 90.82078 100.61016 85.85045
[8] 93.20395 88.42684 94.12750
> rowMin(tmp5)
[1] 54.34534 58.98216 56.13359 57.57486 54.83267 59.65774 59.16411 53.15760
[9] 61.35623 58.51750
>
> colMeans(tmp5)
[1] 108.60875 73.39553 82.04902 73.34898 74.80602 67.28094 72.35418
[8] 70.86010 73.74512 75.61354 70.57027 71.73653 70.57297 73.28465
[15] 70.62288 72.98094 74.19786 71.47425 69.62032 72.57467
> colSums(tmp5)
[1] 1086.0875 733.9553 820.4902 733.4898 748.0602 672.8094 723.5418
[8] 708.6010 737.4512 756.1354 705.7027 717.3653 705.7297 732.8465
[15] 706.2288 729.8094 741.9786 714.7425 696.2032 725.7467
> colVars(tmp5)
[1] 16128.66277 35.78451 106.80848 79.50134 31.56429 45.24507
[7] 76.48628 83.51964 80.61818 102.35011 66.47437 75.37046
[13] 76.00931 74.45538 67.12516 108.60905 55.68758 152.49856
[19] 99.58508 48.56996
> colSd(tmp5)
[1] 126.998672 5.982015 10.334819 8.916352 5.618210 6.726446
[7] 8.745644 9.138908 8.978763 10.116823 8.153182 8.681616
[13] 8.718332 8.628753 8.192995 10.421567 7.462411 12.349031
[19] 9.979232 6.969215
> colMax(tmp5)
[1] 469.64066 83.30752 100.61016 86.51430 84.73883 79.38094 88.42684
[8] 84.14727 83.17248 91.14143 81.25264 83.43260 90.82078 87.72914
[15] 85.89829 86.59284 82.52001 94.12750 85.92678 85.85045
> colMin(tmp5)
[1] 60.48399 64.46640 68.39798 58.94166 69.06303 59.71660 60.36048 53.15760
[9] 54.34534 61.80252 57.85806 59.16411 58.98216 62.93214 59.65774 60.27475
[17] 58.83511 54.83267 56.13359 62.84560
>
>
> ### 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] 92.83046 75.29473 68.23066 74.80807 73.70940 73.72974 72.79964 70.50288
[9] NA 70.77098
> rowSums(tmp5)
[1] 1856.609 1505.895 1364.613 1496.161 1474.188 1474.595 1455.993 1410.058
[9] NA 1415.420
> rowVars(tmp5)
[1] 7936.68866 44.85754 72.91547 107.25841 79.27679 114.32234
[7] 48.55621 76.08763 47.64293 102.70247
> rowSd(tmp5)
[1] 89.088095 6.697577 8.539056 10.356564 8.903751 10.692163 6.968229
[8] 8.722822 6.902386 10.134223
> rowMax(tmp5)
[1] 469.64066 85.92678 85.22494 92.23222 90.82078 100.61016 85.85045
[8] 93.20395 NA 94.12750
> rowMin(tmp5)
[1] 54.34534 58.98216 56.13359 57.57486 54.83267 59.65774 59.16411 53.15760
[9] NA 58.51750
>
> colMeans(tmp5)
[1] 108.60875 73.39553 82.04902 73.34898 74.80602 NA 72.35418
[8] 70.86010 73.74512 75.61354 70.57027 71.73653 70.57297 73.28465
[15] 70.62288 72.98094 74.19786 71.47425 69.62032 72.57467
> colSums(tmp5)
[1] 1086.0875 733.9553 820.4902 733.4898 748.0602 NA 723.5418
[8] 708.6010 737.4512 756.1354 705.7027 717.3653 705.7297 732.8465
[15] 706.2288 729.8094 741.9786 714.7425 696.2032 725.7467
> colVars(tmp5)
[1] 16128.66277 35.78451 106.80848 79.50134 31.56429 NA
[7] 76.48628 83.51964 80.61818 102.35011 66.47437 75.37046
[13] 76.00931 74.45538 67.12516 108.60905 55.68758 152.49856
[19] 99.58508 48.56996
> colSd(tmp5)
[1] 126.998672 5.982015 10.334819 8.916352 5.618210 NA
[7] 8.745644 9.138908 8.978763 10.116823 8.153182 8.681616
[13] 8.718332 8.628753 8.192995 10.421567 7.462411 12.349031
[19] 9.979232 6.969215
> colMax(tmp5)
[1] 469.64066 83.30752 100.61016 86.51430 84.73883 NA 88.42684
[8] 84.14727 83.17248 91.14143 81.25264 83.43260 90.82078 87.72914
[15] 85.89829 86.59284 82.52001 94.12750 85.92678 85.85045
> colMin(tmp5)
[1] 60.48399 64.46640 68.39798 58.94166 69.06303 NA 60.36048 53.15760
[9] 54.34534 61.80252 57.85806 59.16411 58.98216 62.93214 59.65774 60.27475
[17] 58.83511 54.83267 56.13359 62.84560
>
> Max(tmp5,na.rm=TRUE)
[1] 469.6407
> Min(tmp5,na.rm=TRUE)
[1] 53.1576
> mean(tmp5,na.rm=TRUE)
[1] 74.48441
> Sum(tmp5,na.rm=TRUE)
[1] 14822.4
> Var(tmp5,na.rm=TRUE)
[1] 869.9152
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.83046 75.29473 68.23066 74.80807 73.70940 73.72974 72.79964 70.50288
[9] 72.04557 70.77098
> rowSums(tmp5,na.rm=TRUE)
[1] 1856.609 1505.895 1364.613 1496.161 1474.188 1474.595 1455.993 1410.058
[9] 1368.866 1415.420
> rowVars(tmp5,na.rm=TRUE)
[1] 7936.68866 44.85754 72.91547 107.25841 79.27679 114.32234
[7] 48.55621 76.08763 47.64293 102.70247
> rowSd(tmp5,na.rm=TRUE)
[1] 89.088095 6.697577 8.539056 10.356564 8.903751 10.692163 6.968229
[8] 8.722822 6.902386 10.134223
> rowMax(tmp5,na.rm=TRUE)
[1] 469.64066 85.92678 85.22494 92.23222 90.82078 100.61016 85.85045
[8] 93.20395 88.42684 94.12750
> rowMin(tmp5,na.rm=TRUE)
[1] 54.34534 58.98216 56.13359 57.57486 54.83267 59.65774 59.16411 53.15760
[9] 61.35623 58.51750
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.60875 73.39553 82.04902 73.34898 74.80602 66.47014 72.35418
[8] 70.86010 73.74512 75.61354 70.57027 71.73653 70.57297 73.28465
[15] 70.62288 72.98094 74.19786 71.47425 69.62032 72.57467
> colSums(tmp5,na.rm=TRUE)
[1] 1086.0875 733.9553 820.4902 733.4898 748.0602 598.2313 723.5418
[8] 708.6010 737.4512 756.1354 705.7027 717.3653 705.7297 732.8465
[15] 706.2288 729.8094 741.9786 714.7425 696.2032 725.7467
> colVars(tmp5,na.rm=TRUE)
[1] 16128.66277 35.78451 106.80848 79.50134 31.56429 43.50506
[7] 76.48628 83.51964 80.61818 102.35011 66.47437 75.37046
[13] 76.00931 74.45538 67.12516 108.60905 55.68758 152.49856
[19] 99.58508 48.56996
> colSd(tmp5,na.rm=TRUE)
[1] 126.998672 5.982015 10.334819 8.916352 5.618210 6.595836
[7] 8.745644 9.138908 8.978763 10.116823 8.153182 8.681616
[13] 8.718332 8.628753 8.192995 10.421567 7.462411 12.349031
[19] 9.979232 6.969215
> colMax(tmp5,na.rm=TRUE)
[1] 469.64066 83.30752 100.61016 86.51430 84.73883 79.38094 88.42684
[8] 84.14727 83.17248 91.14143 81.25264 83.43260 90.82078 87.72914
[15] 85.89829 86.59284 82.52001 94.12750 85.92678 85.85045
> colMin(tmp5,na.rm=TRUE)
[1] 60.48399 64.46640 68.39798 58.94166 69.06303 59.71660 60.36048 53.15760
[9] 54.34534 61.80252 57.85806 59.16411 58.98216 62.93214 59.65774 60.27475
[17] 58.83511 54.83267 56.13359 62.84560
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.83046 75.29473 68.23066 74.80807 73.70940 73.72974 72.79964 70.50288
[9] NaN 70.77098
> rowSums(tmp5,na.rm=TRUE)
[1] 1856.609 1505.895 1364.613 1496.161 1474.188 1474.595 1455.993 1410.058
[9] 0.000 1415.420
> rowVars(tmp5,na.rm=TRUE)
[1] 7936.68866 44.85754 72.91547 107.25841 79.27679 114.32234
[7] 48.55621 76.08763 NA 102.70247
> rowSd(tmp5,na.rm=TRUE)
[1] 89.088095 6.697577 8.539056 10.356564 8.903751 10.692163 6.968229
[8] 8.722822 NA 10.134223
> rowMax(tmp5,na.rm=TRUE)
[1] 469.64066 85.92678 85.22494 92.23222 90.82078 100.61016 85.85045
[8] 93.20395 NA 94.12750
> rowMin(tmp5,na.rm=TRUE)
[1] 54.34534 58.98216 56.13359 57.57486 54.83267 59.65774 59.16411 53.15760
[9] NA 58.51750
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.60581 73.51364 83.04786 73.63229 75.44413 NaN 70.56833
[8] 71.17966 74.22662 75.77301 69.99526 70.43697 70.12587 74.09970
[15] 69.88795 74.22859 73.72775 72.59848 70.20321 73.07153
> colSums(tmp5,na.rm=TRUE)
[1] 1013.4523 661.6227 747.4308 662.6906 678.9972 0.0000 635.1150
[8] 640.6170 668.0396 681.9571 629.9574 633.9327 631.1328 666.8973
[15] 628.9915 668.0573 663.5498 653.3863 631.8289 657.6438
> colVars(tmp5,na.rm=TRUE)
[1] 17965.01000 40.10065 108.93557 88.53602 30.92899 NA
[7] 50.16783 92.81073 88.08724 114.85778 71.06400 65.79204
[13] 83.26165 76.28885 69.43940 104.67305 60.16233 157.34222
[19] 108.21093 51.86394
> colSd(tmp5,na.rm=TRUE)
[1] 134.033615 6.332507 10.437220 9.409358 5.561384 NA
[7] 7.082925 9.633832 9.385480 10.717172 8.429946 8.111229
[13] 9.124782 8.734349 8.333030 10.230985 7.756438 12.543613
[19] 10.402448 7.201662
> colMax(tmp5,na.rm=TRUE)
[1] 469.64066 83.30752 100.61016 86.51430 84.73883 -Inf 82.97030
[8] 84.14727 83.17248 91.14143 81.25264 82.84640 90.82078 87.72914
[15] 85.89829 86.59284 82.52001 94.12750 85.92678 85.85045
> colMin(tmp5,na.rm=TRUE)
[1] 60.48399 64.46640 68.39798 58.94166 69.19239 Inf 60.36048 53.15760
[9] 54.34534 61.80252 57.85806 59.16411 58.98216 62.93214 59.65774 60.27475
[17] 58.83511 54.83267 56.13359 62.84560
>
>
>
>
> 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] 177.91465 167.85999 216.55576 181.57305 138.00916 93.50059 191.04101
[8] 206.58837 290.49927 314.49639
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 177.91465 167.85999 216.55576 181.57305 138.00916 93.50059 191.04101
[8] 206.58837 290.49927 314.49639
>
>
>
> 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] -1.421085e-14 2.273737e-13 -1.421085e-14 1.136868e-13 -1.136868e-13
[6] -2.842171e-14 1.421085e-14 1.136868e-13 -1.421085e-14 -5.684342e-14
[11] -1.989520e-13 -1.136868e-13 -1.136868e-13 -2.842171e-14 1.136868e-13
[16] 2.557954e-13 1.278977e-13 0.000000e+00 2.842171e-14 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 2
9 18
8 20
7 18
10 12
10 3
9 8
1 10
5 8
9 11
5 6
9 20
2 10
7 13
7 1
5 5
8 6
1 12
8 9
1 11
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] 2.647031
> Min(tmp)
[1] -2.865792
> mean(tmp)
[1] 0.02254846
> Sum(tmp)
[1] 2.254846
> Var(tmp)
[1] 1.138059
>
> rowMeans(tmp)
[1] 0.02254846
> rowSums(tmp)
[1] 2.254846
> rowVars(tmp)
[1] 1.138059
> rowSd(tmp)
[1] 1.066799
> rowMax(tmp)
[1] 2.647031
> rowMin(tmp)
[1] -2.865792
>
> colMeans(tmp)
[1] 0.243144897 1.285859659 0.585036829 -1.526340139 0.352375367
[6] 2.324752246 -0.961788072 1.445011766 0.594266151 1.023552995
[11] -0.582182128 0.872460824 -2.865791967 -0.166481115 -0.081890316
[16] 0.033289027 0.456719313 -0.911701802 -1.950855227 -0.628597142
[21] -0.016159119 -0.281225142 1.228162663 -1.040735003 0.750460333
[26] 1.950094835 -0.236337213 0.142553051 0.738791981 0.211522651
[31] 0.674455636 0.897295983 -1.179089632 2.647031315 0.001830488
[36] -0.053763701 -0.111174953 -0.677285316 -0.320632848 1.425476354
[41] -2.342332506 0.329139625 0.581127255 -0.467923339 -1.288762461
[46] 0.416256519 -1.048695495 -0.321345706 -0.026729933 1.302018639
[51] 0.676449132 0.454527246 -0.048873809 0.518519379 0.027875120
[56] -0.047064167 1.067509991 -0.654613919 0.448688430 -1.138982867
[61] 0.368304351 -0.989000180 0.837202762 1.307359647 0.518256391
[66] -0.855260008 1.003693451 0.249653761 0.045400068 -0.088633512
[71] -0.240190233 1.233747406 0.907680799 0.584082504 -0.471154343
[76] -1.537910625 -2.127389966 -1.841100364 0.946750807 1.607649459
[81] 1.368338122 0.847218432 0.200051087 -1.563602872 0.713168451
[86] -0.901329021 -0.263030235 0.645037682 1.569574371 -2.720742822
[91] 0.099981400 -1.428123651 -0.317936222 -1.076319223 2.016934738
[96] -1.077861467 -0.303222597 -0.413214998 -0.363667245 -0.964450724
> colSums(tmp)
[1] 0.243144897 1.285859659 0.585036829 -1.526340139 0.352375367
[6] 2.324752246 -0.961788072 1.445011766 0.594266151 1.023552995
[11] -0.582182128 0.872460824 -2.865791967 -0.166481115 -0.081890316
[16] 0.033289027 0.456719313 -0.911701802 -1.950855227 -0.628597142
[21] -0.016159119 -0.281225142 1.228162663 -1.040735003 0.750460333
[26] 1.950094835 -0.236337213 0.142553051 0.738791981 0.211522651
[31] 0.674455636 0.897295983 -1.179089632 2.647031315 0.001830488
[36] -0.053763701 -0.111174953 -0.677285316 -0.320632848 1.425476354
[41] -2.342332506 0.329139625 0.581127255 -0.467923339 -1.288762461
[46] 0.416256519 -1.048695495 -0.321345706 -0.026729933 1.302018639
[51] 0.676449132 0.454527246 -0.048873809 0.518519379 0.027875120
[56] -0.047064167 1.067509991 -0.654613919 0.448688430 -1.138982867
[61] 0.368304351 -0.989000180 0.837202762 1.307359647 0.518256391
[66] -0.855260008 1.003693451 0.249653761 0.045400068 -0.088633512
[71] -0.240190233 1.233747406 0.907680799 0.584082504 -0.471154343
[76] -1.537910625 -2.127389966 -1.841100364 0.946750807 1.607649459
[81] 1.368338122 0.847218432 0.200051087 -1.563602872 0.713168451
[86] -0.901329021 -0.263030235 0.645037682 1.569574371 -2.720742822
[91] 0.099981400 -1.428123651 -0.317936222 -1.076319223 2.016934738
[96] -1.077861467 -0.303222597 -0.413214998 -0.363667245 -0.964450724
> 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] 0.243144897 1.285859659 0.585036829 -1.526340139 0.352375367
[6] 2.324752246 -0.961788072 1.445011766 0.594266151 1.023552995
[11] -0.582182128 0.872460824 -2.865791967 -0.166481115 -0.081890316
[16] 0.033289027 0.456719313 -0.911701802 -1.950855227 -0.628597142
[21] -0.016159119 -0.281225142 1.228162663 -1.040735003 0.750460333
[26] 1.950094835 -0.236337213 0.142553051 0.738791981 0.211522651
[31] 0.674455636 0.897295983 -1.179089632 2.647031315 0.001830488
[36] -0.053763701 -0.111174953 -0.677285316 -0.320632848 1.425476354
[41] -2.342332506 0.329139625 0.581127255 -0.467923339 -1.288762461
[46] 0.416256519 -1.048695495 -0.321345706 -0.026729933 1.302018639
[51] 0.676449132 0.454527246 -0.048873809 0.518519379 0.027875120
[56] -0.047064167 1.067509991 -0.654613919 0.448688430 -1.138982867
[61] 0.368304351 -0.989000180 0.837202762 1.307359647 0.518256391
[66] -0.855260008 1.003693451 0.249653761 0.045400068 -0.088633512
[71] -0.240190233 1.233747406 0.907680799 0.584082504 -0.471154343
[76] -1.537910625 -2.127389966 -1.841100364 0.946750807 1.607649459
[81] 1.368338122 0.847218432 0.200051087 -1.563602872 0.713168451
[86] -0.901329021 -0.263030235 0.645037682 1.569574371 -2.720742822
[91] 0.099981400 -1.428123651 -0.317936222 -1.076319223 2.016934738
[96] -1.077861467 -0.303222597 -0.413214998 -0.363667245 -0.964450724
> colMin(tmp)
[1] 0.243144897 1.285859659 0.585036829 -1.526340139 0.352375367
[6] 2.324752246 -0.961788072 1.445011766 0.594266151 1.023552995
[11] -0.582182128 0.872460824 -2.865791967 -0.166481115 -0.081890316
[16] 0.033289027 0.456719313 -0.911701802 -1.950855227 -0.628597142
[21] -0.016159119 -0.281225142 1.228162663 -1.040735003 0.750460333
[26] 1.950094835 -0.236337213 0.142553051 0.738791981 0.211522651
[31] 0.674455636 0.897295983 -1.179089632 2.647031315 0.001830488
[36] -0.053763701 -0.111174953 -0.677285316 -0.320632848 1.425476354
[41] -2.342332506 0.329139625 0.581127255 -0.467923339 -1.288762461
[46] 0.416256519 -1.048695495 -0.321345706 -0.026729933 1.302018639
[51] 0.676449132 0.454527246 -0.048873809 0.518519379 0.027875120
[56] -0.047064167 1.067509991 -0.654613919 0.448688430 -1.138982867
[61] 0.368304351 -0.989000180 0.837202762 1.307359647 0.518256391
[66] -0.855260008 1.003693451 0.249653761 0.045400068 -0.088633512
[71] -0.240190233 1.233747406 0.907680799 0.584082504 -0.471154343
[76] -1.537910625 -2.127389966 -1.841100364 0.946750807 1.607649459
[81] 1.368338122 0.847218432 0.200051087 -1.563602872 0.713168451
[86] -0.901329021 -0.263030235 0.645037682 1.569574371 -2.720742822
[91] 0.099981400 -1.428123651 -0.317936222 -1.076319223 2.016934738
[96] -1.077861467 -0.303222597 -0.413214998 -0.363667245 -0.964450724
> colMedians(tmp)
[1] 0.243144897 1.285859659 0.585036829 -1.526340139 0.352375367
[6] 2.324752246 -0.961788072 1.445011766 0.594266151 1.023552995
[11] -0.582182128 0.872460824 -2.865791967 -0.166481115 -0.081890316
[16] 0.033289027 0.456719313 -0.911701802 -1.950855227 -0.628597142
[21] -0.016159119 -0.281225142 1.228162663 -1.040735003 0.750460333
[26] 1.950094835 -0.236337213 0.142553051 0.738791981 0.211522651
[31] 0.674455636 0.897295983 -1.179089632 2.647031315 0.001830488
[36] -0.053763701 -0.111174953 -0.677285316 -0.320632848 1.425476354
[41] -2.342332506 0.329139625 0.581127255 -0.467923339 -1.288762461
[46] 0.416256519 -1.048695495 -0.321345706 -0.026729933 1.302018639
[51] 0.676449132 0.454527246 -0.048873809 0.518519379 0.027875120
[56] -0.047064167 1.067509991 -0.654613919 0.448688430 -1.138982867
[61] 0.368304351 -0.989000180 0.837202762 1.307359647 0.518256391
[66] -0.855260008 1.003693451 0.249653761 0.045400068 -0.088633512
[71] -0.240190233 1.233747406 0.907680799 0.584082504 -0.471154343
[76] -1.537910625 -2.127389966 -1.841100364 0.946750807 1.607649459
[81] 1.368338122 0.847218432 0.200051087 -1.563602872 0.713168451
[86] -0.901329021 -0.263030235 0.645037682 1.569574371 -2.720742822
[91] 0.099981400 -1.428123651 -0.317936222 -1.076319223 2.016934738
[96] -1.077861467 -0.303222597 -0.413214998 -0.363667245 -0.964450724
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.2431449 1.28586 0.5850368 -1.52634 0.3523754 2.324752 -0.9617881
[2,] 0.2431449 1.28586 0.5850368 -1.52634 0.3523754 2.324752 -0.9617881
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.445012 0.5942662 1.023553 -0.5821821 0.8724608 -2.865792 -0.1664811
[2,] 1.445012 0.5942662 1.023553 -0.5821821 0.8724608 -2.865792 -0.1664811
[,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.08189032 0.03328903 0.4567193 -0.9117018 -1.950855 -0.6285971
[2,] -0.08189032 0.03328903 0.4567193 -0.9117018 -1.950855 -0.6285971
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] -0.01615912 -0.2812251 1.228163 -1.040735 0.7504603 1.950095 -0.2363372
[2,] -0.01615912 -0.2812251 1.228163 -1.040735 0.7504603 1.950095 -0.2363372
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.1425531 0.738792 0.2115227 0.6744556 0.897296 -1.17909 2.647031
[2,] 0.1425531 0.738792 0.2115227 0.6744556 0.897296 -1.17909 2.647031
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.001830488 -0.0537637 -0.111175 -0.6772853 -0.3206328 1.425476 -2.342333
[2,] 0.001830488 -0.0537637 -0.111175 -0.6772853 -0.3206328 1.425476 -2.342333
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.3291396 0.5811273 -0.4679233 -1.288762 0.4162565 -1.048695 -0.3213457
[2,] 0.3291396 0.5811273 -0.4679233 -1.288762 0.4162565 -1.048695 -0.3213457
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.02672993 1.302019 0.6764491 0.4545272 -0.04887381 0.5185194 0.02787512
[2,] -0.02672993 1.302019 0.6764491 0.4545272 -0.04887381 0.5185194 0.02787512
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.04706417 1.06751 -0.6546139 0.4486884 -1.138983 0.3683044 -0.9890002
[2,] -0.04706417 1.06751 -0.6546139 0.4486884 -1.138983 0.3683044 -0.9890002
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.8372028 1.30736 0.5182564 -0.85526 1.003693 0.2496538 0.04540007
[2,] 0.8372028 1.30736 0.5182564 -0.85526 1.003693 0.2496538 0.04540007
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.08863351 -0.2401902 1.233747 0.9076808 0.5840825 -0.4711543 -1.537911
[2,] -0.08863351 -0.2401902 1.233747 0.9076808 0.5840825 -0.4711543 -1.537911
[,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -2.12739 -1.8411 0.9467508 1.607649 1.368338 0.8472184 0.2000511 -1.563603
[2,] -2.12739 -1.8411 0.9467508 1.607649 1.368338 0.8472184 0.2000511 -1.563603
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.7131685 -0.901329 -0.2630302 0.6450377 1.569574 -2.720743 0.0999814
[2,] 0.7131685 -0.901329 -0.2630302 0.6450377 1.569574 -2.720743 0.0999814
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.428124 -0.3179362 -1.076319 2.016935 -1.077861 -0.3032226 -0.413215
[2,] -1.428124 -0.3179362 -1.076319 2.016935 -1.077861 -0.3032226 -0.413215
[,99] [,100]
[1,] -0.3636672 -0.9644507
[2,] -0.3636672 -0.9644507
>
>
> Max(tmp2)
[1] 2.320035
> Min(tmp2)
[1] -1.961044
> mean(tmp2)
[1] 0.08856677
> Sum(tmp2)
[1] 8.856677
> Var(tmp2)
[1] 0.8382006
>
> rowMeans(tmp2)
[1] -1.104017002 -0.017664335 -0.178780514 -0.727246273 -0.901763774
[6] 1.955030429 0.104918105 0.297119525 -0.729292646 1.187730108
[11] -0.728239162 -0.864632613 -0.242802745 0.253999702 0.820172151
[16] -0.172249433 -1.961043513 -0.572097877 -0.524732599 -1.874304148
[21] -1.586719214 -1.299753259 1.509885349 1.619307825 1.403274886
[26] -0.500578197 -0.130472954 0.042712999 0.671742029 0.441926522
[31] 0.577277471 -0.046068559 1.761373365 0.899425866 0.851538189
[36] 1.037036815 1.311210932 0.425510316 -0.991810498 -0.312885144
[41] -0.590238535 -0.525009426 -0.834843498 -0.287720776 -0.076031665
[46] -0.111020461 0.817142224 0.044520339 -0.007891746 -0.543088979
[51] 1.400734251 1.009751522 0.925687747 0.469088408 0.603698706
[56] 1.024200937 1.736022521 -0.820652985 -0.891955329 0.129517627
[61] -0.401097430 0.254103366 -0.284667709 1.482873164 -0.074545411
[66] 0.126750460 1.310048925 0.641123341 -0.074219863 -0.855584304
[71] 1.047069101 -0.100977264 -0.708068258 -1.147631133 0.657084889
[76] -1.051462296 -0.477722142 1.356238248 0.946952884 1.410369529
[81] 0.049878913 2.320035478 0.859894787 -0.483146740 -0.528608382
[86] 1.244784830 -0.671260136 0.526959791 0.468247932 -0.306310164
[91] -1.466612428 -0.585888238 0.011823424 -1.111106120 1.179586386
[96] -0.445191050 -0.135432312 0.547833094 -1.413455506 -0.437943441
> rowSums(tmp2)
[1] -1.104017002 -0.017664335 -0.178780514 -0.727246273 -0.901763774
[6] 1.955030429 0.104918105 0.297119525 -0.729292646 1.187730108
[11] -0.728239162 -0.864632613 -0.242802745 0.253999702 0.820172151
[16] -0.172249433 -1.961043513 -0.572097877 -0.524732599 -1.874304148
[21] -1.586719214 -1.299753259 1.509885349 1.619307825 1.403274886
[26] -0.500578197 -0.130472954 0.042712999 0.671742029 0.441926522
[31] 0.577277471 -0.046068559 1.761373365 0.899425866 0.851538189
[36] 1.037036815 1.311210932 0.425510316 -0.991810498 -0.312885144
[41] -0.590238535 -0.525009426 -0.834843498 -0.287720776 -0.076031665
[46] -0.111020461 0.817142224 0.044520339 -0.007891746 -0.543088979
[51] 1.400734251 1.009751522 0.925687747 0.469088408 0.603698706
[56] 1.024200937 1.736022521 -0.820652985 -0.891955329 0.129517627
[61] -0.401097430 0.254103366 -0.284667709 1.482873164 -0.074545411
[66] 0.126750460 1.310048925 0.641123341 -0.074219863 -0.855584304
[71] 1.047069101 -0.100977264 -0.708068258 -1.147631133 0.657084889
[76] -1.051462296 -0.477722142 1.356238248 0.946952884 1.410369529
[81] 0.049878913 2.320035478 0.859894787 -0.483146740 -0.528608382
[86] 1.244784830 -0.671260136 0.526959791 0.468247932 -0.306310164
[91] -1.466612428 -0.585888238 0.011823424 -1.111106120 1.179586386
[96] -0.445191050 -0.135432312 0.547833094 -1.413455506 -0.437943441
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -1.104017002 -0.017664335 -0.178780514 -0.727246273 -0.901763774
[6] 1.955030429 0.104918105 0.297119525 -0.729292646 1.187730108
[11] -0.728239162 -0.864632613 -0.242802745 0.253999702 0.820172151
[16] -0.172249433 -1.961043513 -0.572097877 -0.524732599 -1.874304148
[21] -1.586719214 -1.299753259 1.509885349 1.619307825 1.403274886
[26] -0.500578197 -0.130472954 0.042712999 0.671742029 0.441926522
[31] 0.577277471 -0.046068559 1.761373365 0.899425866 0.851538189
[36] 1.037036815 1.311210932 0.425510316 -0.991810498 -0.312885144
[41] -0.590238535 -0.525009426 -0.834843498 -0.287720776 -0.076031665
[46] -0.111020461 0.817142224 0.044520339 -0.007891746 -0.543088979
[51] 1.400734251 1.009751522 0.925687747 0.469088408 0.603698706
[56] 1.024200937 1.736022521 -0.820652985 -0.891955329 0.129517627
[61] -0.401097430 0.254103366 -0.284667709 1.482873164 -0.074545411
[66] 0.126750460 1.310048925 0.641123341 -0.074219863 -0.855584304
[71] 1.047069101 -0.100977264 -0.708068258 -1.147631133 0.657084889
[76] -1.051462296 -0.477722142 1.356238248 0.946952884 1.410369529
[81] 0.049878913 2.320035478 0.859894787 -0.483146740 -0.528608382
[86] 1.244784830 -0.671260136 0.526959791 0.468247932 -0.306310164
[91] -1.466612428 -0.585888238 0.011823424 -1.111106120 1.179586386
[96] -0.445191050 -0.135432312 0.547833094 -1.413455506 -0.437943441
> rowMin(tmp2)
[1] -1.104017002 -0.017664335 -0.178780514 -0.727246273 -0.901763774
[6] 1.955030429 0.104918105 0.297119525 -0.729292646 1.187730108
[11] -0.728239162 -0.864632613 -0.242802745 0.253999702 0.820172151
[16] -0.172249433 -1.961043513 -0.572097877 -0.524732599 -1.874304148
[21] -1.586719214 -1.299753259 1.509885349 1.619307825 1.403274886
[26] -0.500578197 -0.130472954 0.042712999 0.671742029 0.441926522
[31] 0.577277471 -0.046068559 1.761373365 0.899425866 0.851538189
[36] 1.037036815 1.311210932 0.425510316 -0.991810498 -0.312885144
[41] -0.590238535 -0.525009426 -0.834843498 -0.287720776 -0.076031665
[46] -0.111020461 0.817142224 0.044520339 -0.007891746 -0.543088979
[51] 1.400734251 1.009751522 0.925687747 0.469088408 0.603698706
[56] 1.024200937 1.736022521 -0.820652985 -0.891955329 0.129517627
[61] -0.401097430 0.254103366 -0.284667709 1.482873164 -0.074545411
[66] 0.126750460 1.310048925 0.641123341 -0.074219863 -0.855584304
[71] 1.047069101 -0.100977264 -0.708068258 -1.147631133 0.657084889
[76] -1.051462296 -0.477722142 1.356238248 0.946952884 1.410369529
[81] 0.049878913 2.320035478 0.859894787 -0.483146740 -0.528608382
[86] 1.244784830 -0.671260136 0.526959791 0.468247932 -0.306310164
[91] -1.466612428 -0.585888238 0.011823424 -1.111106120 1.179586386
[96] -0.445191050 -0.135432312 0.547833094 -1.413455506 -0.437943441
>
> colMeans(tmp2)
[1] 0.08856677
> colSums(tmp2)
[1] 8.856677
> colVars(tmp2)
[1] 0.8382006
> colSd(tmp2)
[1] 0.9155329
> colMax(tmp2)
[1] 2.320035
> colMin(tmp2)
[1] -1.961044
> colMedians(tmp2)
[1] -0.03186645
> colRanges(tmp2)
[,1]
[1,] -1.961044
[2,] 2.320035
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.8485783 1.1901315 1.5528981 0.6418093 5.5311329 -1.4435328
[7] -2.9249092 0.8421520 1.4854504 1.5545575
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.24016854
[2,] -0.56679317
[3,] -0.07829484
[4,] 0.73430244
[5,] 1.64453773
>
> rowApply(tmp,sum)
[1] -1.4899624 2.5299814 3.5096417 3.7239882 -0.5329733 0.6943045
[7] 1.8370022 0.8164722 -0.8314437 -0.9787427
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 6 7 4 3 10 2 5 6 3
[2,] 4 3 10 7 8 5 8 6 4 2
[3,] 10 10 3 8 2 2 1 7 5 4
[4,] 5 8 1 5 6 6 5 10 2 6
[5,] 7 9 4 2 10 8 4 8 7 10
[6,] 1 4 6 6 1 9 6 2 9 8
[7,] 2 1 5 9 7 1 10 4 1 7
[8,] 8 2 8 1 9 7 3 3 10 5
[9,] 6 5 9 10 5 3 9 1 3 1
[10,] 3 7 2 3 4 4 7 9 8 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.7923501 1.1944933 -2.8652045 0.9077630 -1.7380067 0.3249314
[7] 0.9352180 2.8553766 1.8294058 3.1188288 2.2192703 1.4587726
[13] -1.6517426 -2.0248773 -2.0979513 -0.8111302 -0.9284961 -1.7004005
[19] -1.8675937 1.6557991
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.28661481
[2,] -1.12555058
[3,] -0.05775008
[4,] 0.24758913
[5,] 0.42997626
>
> rowApply(tmp,sum)
[1] 1.4175309 -4.1060497 3.3640624 -0.9133941 -0.7400435
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 12 2 8 15 2
[2,] 5 20 18 11 9
[3,] 3 10 6 2 12
[4,] 13 16 14 13 5
[5,] 1 14 16 4 6
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.24758913 -0.54053344 -0.93801616 0.3928053 -1.5073349 0.59788583
[2,] -1.28661481 1.06087442 -0.30430022 0.4795318 0.3568340 -0.07124379
[3,] -0.05775008 0.98172882 -0.34945814 0.5601037 0.9032294 0.55094396
[4,] 0.42997626 -0.01675152 -1.20755803 0.1294014 -0.9473578 -1.01262460
[5,] -1.12555058 -0.29082494 -0.06587193 -0.6540794 -0.5433774 0.25997002
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.55752933 1.9996814 0.1986749 0.3946373 1.3645650 -0.1951611
[2,] -0.03331992 0.3808884 0.8076929 -0.7939652 -0.6849064 -1.1282911
[3,] -0.43823764 0.3810998 1.5114888 0.2001081 0.8481916 -0.3193567
[4,] -0.07414280 1.0961792 -0.5823803 0.7619209 0.1378138 2.2506145
[5,] 0.92338907 -1.0024722 -0.1060706 2.5561277 0.5536063 0.8509669
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.9110161 0.48070751 -0.07287014 -1.1273712 0.4837681 -0.03677658
[2,] -0.5344009 -1.16747319 0.98316938 -1.3448105 -1.0286668 -0.13004686
[3,] -0.3691012 -1.01545134 -1.81282461 0.5373163 0.9525790 0.06200975
[4,] -0.8708308 -0.23804184 -0.40850013 1.4814677 0.8390687 -1.87967122
[5,] 1.0336064 -0.08461843 -0.78692576 -0.3577326 -2.1752450 0.28408438
[,19] [,20]
[1,] 0.09501982 -0.06625313
[2,] 0.64094410 -0.30794511
[3,] -1.37465407 1.61209698
[4,] -0.92842135 0.12644365
[5,] -0.30048220 0.29145672
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.2276757 -0.8193833 -1.783518 -0.1787637 0.1543568 -1.763538 -0.7372914
col8 col9 col10 col11 col12 col13 col14
row1 -1.727735 0.6912298 -1.300577 -0.03782672 -1.897777 -1.926523 -0.4263533
col15 col16 col17 col18 col19 col20
row1 1.79988 0.08401175 -0.2917408 0.8861536 -1.956086 -0.9311743
> tmp[,"col10"]
col10
row1 -1.3005772
row2 0.2378077
row3 1.6091638
row4 -0.3018916
row5 -1.4554893
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.22767575 -0.8193833 -1.783518 -0.1787637 0.1543568 -1.7635380
row5 -0.04583301 0.2897789 1.128586 0.6073813 1.6321527 -0.8992768
col7 col8 col9 col10 col11 col12
row1 -0.7372914 -1.727735 0.6912298 -1.300577 -0.03782672 -1.8977772
row5 -0.1429186 -1.234755 -1.4894860 -1.455489 -0.43474097 0.6963783
col13 col14 col15 col16 col17 col18
row1 -1.9265230 -0.42635326 1.7998800 0.08401175 -0.2917408 0.88615358
row5 0.6416629 -0.05979417 -0.3293824 -0.21244613 0.6844406 -0.05644689
col19 col20
row1 -1.956086 -0.9311743
row5 -1.029211 -0.7650093
> tmp[,c("col6","col20")]
col6 col20
row1 -1.7635380 -0.9311743
row2 0.3668528 1.1429210
row3 -0.5420612 0.9421160
row4 -0.2987381 1.9236624
row5 -0.8992768 -0.7650093
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.7635380 -0.9311743
row5 -0.8992768 -0.7650093
>
>
>
>
> 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 52.60267 48.96062 51.47311 48.40722 47.56381 107.3601 48.52015 50.84419
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.14208 49.14263 48.50113 49.38533 49.66938 48.8326 51.01908 51.79112
col17 col18 col19 col20
row1 49.74966 51.28384 50.05099 105.2022
> tmp[,"col10"]
col10
row1 49.14263
row2 28.59444
row3 29.77341
row4 31.22277
row5 49.73854
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.60267 48.96062 51.47311 48.40722 47.56381 107.3601 48.52015 50.84419
row5 50.44651 51.95515 48.10771 49.66881 49.41380 103.8128 49.40291 50.35382
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.14208 49.14263 48.50113 49.38533 49.66938 48.83260 51.01908 51.79112
row5 49.13349 49.73854 50.41552 48.98578 49.60981 49.17325 47.20820 48.43017
col17 col18 col19 col20
row1 49.74966 51.28384 50.05099 105.2022
row5 51.13420 50.08949 47.56349 103.9172
> tmp[,c("col6","col20")]
col6 col20
row1 107.36008 105.20222
row2 76.50513 74.32682
row3 74.23356 74.87052
row4 74.40406 73.37542
row5 103.81283 103.91717
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 107.3601 105.2022
row5 103.8128 103.9172
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 107.3601 105.2022
row5 103.8128 103.9172
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.8888219
[2,] -0.3035370
[3,] 1.3012205
[4,] -0.1800881
[5,] 1.2776035
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9278814 1.2622463
[2,] -0.6848948 -1.2214166
[3,] -0.3311894 -1.5492767
[4,] -0.1800304 -0.2976911
[5,] -2.1924486 -0.2045351
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.1220570 1.0660000
[2,] -1.5891374 0.1094108
[3,] 0.3578106 0.1708695
[4,] -1.1687548 0.2488152
[5,] -0.2514072 -0.2192465
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.122057
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.122057
[2,] -1.589137
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.902290 -0.2192666 0.3625043 0.770037 -0.67221348 1.1169913 1.1179702
row1 1.666026 -0.7170617 -1.9929972 1.533274 0.03722287 -0.1978978 0.3415202
[,8] [,9] [,10] [,11] [,12] [,13]
row3 1.3456468 0.003361037 1.1618437 -0.04745075 -0.6121526 0.08835299
row1 0.9348196 -1.542716707 0.4638198 -1.54126505 -1.3244050 -0.54351554
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.18021444 0.6673839 1.1578706 -0.9520332 -1.146223 -0.4611129
row1 -0.05051172 -2.4297701 -0.5447831 0.0687536 1.233630 0.9607197
[,20]
row3 2.7065824
row1 -0.3084945
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.214969 -0.2123972 0.05713681 1.200336 0.3642883 0.6935614 1.099308
[,8] [,9] [,10]
row2 -0.3422075 -0.007727529 0.5002928
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.994474 0.8841465 2.729092 0.1069457 -1.241079 1.265521 -0.761235
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.296666 -0.5402214 -1.50332 1.27851 0.3106352 -0.5584043 0.4618078
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.301706 0.4035195 1.227767 0.9992419 0.6279042 -0.1123033
>
>
> 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: 0x61ff518a6830>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3017c939574"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3013d74d9f4"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3013cdb1708"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd301391d66c1"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3011fe61560"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3013afb9522"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3011d29b8e1"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd30137640973"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd301156d41f"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd301422f84d7"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd301540b60d2"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd301aeb82e5"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3017df82659"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3013f433252"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dd3014bd7c1df"
>
>
> ### 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: 0x61ff52e162f0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x61ff52e162f0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x61ff52e162f0>
> rowMedians(tmp)
[1] 0.125095635 -0.113096861 -0.573621818 -0.291988920 -0.520803247
[6] -0.139814286 -0.307115073 0.474522413 0.218613322 0.647667840
[11] 0.307066657 -0.260841250 0.304832160 -0.060266252 0.624278309
[16] 0.415712476 -0.251648156 -0.333638248 0.021122222 -0.541662735
[21] -0.073726115 -0.156329078 -0.064629062 -0.070490622 -0.036670445
[26] 0.075359572 0.437306494 -0.070409624 -0.043022274 -0.217326681
[31] 0.097216272 0.465987280 0.415557651 -0.247021469 -0.489049137
[36] 0.507805151 -0.256091310 -0.314995731 0.237280911 -0.391149766
[41] -0.045251928 0.103403316 0.101246128 -0.018866972 -0.082552502
[46] -0.070663756 0.324517910 0.156041756 -0.019632563 0.574934565
[51] 0.591018283 0.133458337 -0.214739716 0.032305884 0.267431483
[56] 0.176320218 0.290173979 -0.088501379 -0.278127332 -0.114005880
[61] 0.186944369 -0.203851220 -0.172334982 0.299525097 -0.251278425
[66] -0.442779065 -0.366997467 0.196405245 0.023926585 0.063344289
[71] 0.460439851 -0.539824700 0.107220598 0.170509967 0.057967388
[76] -0.020640727 -0.267727731 0.201584912 0.249183398 0.143867648
[81] 0.344700703 0.170328156 0.583905757 -0.819673971 -0.092719815
[86] 0.043655147 -0.322869496 0.174014235 0.052625727 0.423397916
[91] -0.219042510 -0.108956997 -0.082757729 -0.035925631 -0.071580924
[96] 0.080397710 -0.185499496 -0.033915408 0.306404208 0.065715835
[101] -0.444289573 0.412266232 0.258444568 0.160001620 -0.130407125
[106] -0.024480075 -0.195590840 -0.507821652 0.435128459 -0.959239586
[111] -0.170985651 0.054497925 -0.512841550 0.046016485 -0.014148484
[116] 0.510743565 0.125237891 0.037479092 -0.264229937 -0.331625154
[121] -0.027610562 0.119395397 -0.145219195 0.324049942 0.276456843
[126] 0.283319879 0.114424938 0.544218552 0.078000920 0.269850379
[131] 0.018954904 -0.353234762 0.787980018 -0.197957038 0.055545425
[136] -0.265989750 0.081405668 0.253527196 0.841016562 -0.469178589
[141] -0.544023201 0.141246585 0.326419863 -0.153906727 -0.136468376
[146] -0.396023435 -0.053650096 0.218893634 0.239083435 0.151026108
[151] -0.498592116 -0.177797585 -0.274397141 0.191959496 0.490521880
[156] 0.077954861 -0.269528037 -0.001910436 0.459036392 0.331704195
[161] 0.610173673 0.245940671 -0.568768095 0.780613619 -0.043511858
[166] 0.196088333 0.172471953 0.378200262 0.083613482 0.173596236
[171] 0.333418347 -0.210125559 -0.319239250 -0.199335272 -0.082397828
[176] -0.077844687 0.072350294 0.050963028 -0.285533672 -0.394638190
[181] -0.241946573 0.143198340 -0.472354005 -0.107724689 -0.278773023
[186] -0.276915632 -0.428029810 0.095192497 0.654377819 -0.263079176
[191] 0.590796502 -0.436982604 -0.042370394 0.074014474 0.413414377
[196] 0.107348273 -0.155233764 -0.227310215 -0.579708133 -0.203879929
[201] -0.262015732 0.074366554 -0.211066185 -0.116123486 -0.077953656
[206] -0.402907339 0.225268432 0.286718709 -0.135266924 0.128770981
[211] 0.122967118 -0.211867447 -0.163393738 -0.408580624 -0.132834420
[216] -0.585864721 -0.382187728 -0.016184938 -0.499083770 0.560825848
[221] -0.249448177 -0.148021434 -0.178111471 -0.333956304 -0.125388431
[226] -0.261737376 0.265351873 -0.096100666 0.511238267 0.164276019
>
> proc.time()
user system elapsed
1.283 1.452 2.724
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "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: 0x6259f7785b20>
> .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: 0x6259f7785b20>
> .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: 0x6259f7785b20>
> .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: 0x6259f7785b20>
> 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: 0x6259f7766410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f7766410>
> .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: 0x6259f7766410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f7766410>
> .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: 0x6259f7766410>
> 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: 0x6259f60137a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f60137a0>
> .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: 0x6259f60137a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6259f60137a0>
> .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: 0x6259f60137a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6259f60137a0>
> .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: 0x6259f60137a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6259f60137a0>
> .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: 0x6259f60137a0>
> 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: 0x6259f6fe5680>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6259f6fe5680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f6fe5680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f6fe5680>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1dd41c71e50622" "BufferedMatrixFile1dd41c7d91a4d5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1dd41c71e50622" "BufferedMatrixFile1dd41c7d91a4d5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f6d79490>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f6d79490>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6259f6d79490>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6259f6d79490>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6259f6d79490>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6259f6d79490>
> .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: 0x6259f83d5110>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6259f83d5110>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6259f83d5110>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6259f83d5110>
> 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: 0x6259f84785e0>
> .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: 0x6259f84785e0>
> rm(P)
>
> proc.time()
user system elapsed
0.250 0.047 0.286
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.252 0.053 0.292