Ben Bolstad
| Snapshot Date: 2025-11-18 13:40 -0500 (Tue, 18 Nov 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 2025-11-19 10:12 -0500 (Wed, 19 Nov 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" | 4827 |
| lconway | macOS 12.7.6 Monterey | x86_64 | R Under development (unstable) (2025-10-21 r88958) -- "Unsuffered Consequences" | 4600 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4564 |
| 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 251/2325 | 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 | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | 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: 2025-11-18 22:29:26 -0500 (Tue, 18 Nov 2025) |
| EndedAt: 2025-11-18 22:29:51 -0500 (Tue, 18 Nov 2025) |
| 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
###
##############################################################################
##############################################################################
* 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
##############################################################################
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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) (2025-10-20 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
0.245 0.057 0.290
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] "Tue Nov 18 22:29:42 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] "Tue Nov 18 22:29:42 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: 0x62a96f0c05e0>
>
>
>
> 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] "Tue Nov 18 22:29:42 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] "Tue Nov 18 22:29:42 2025"
>
> ColMode(tmp2)
<pointer: 0x62a96f0c05e0>
>
>
>
> ### 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,] 101.18146920 0.2108286 -0.53819658 0.7341196
[2,] -0.04716566 -0.2743599 -0.09746091 -0.4923904
[3,] -1.77828034 0.5017061 -0.07431666 -0.1785959
[4,] 0.33179858 2.3241418 0.85779622 -1.6916878
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.18146920 0.2108286 0.53819658 0.7341196
[2,] 0.04716566 0.2743599 0.09746091 0.4923904
[3,] 1.77828034 0.5017061 0.07431666 0.1785959
[4,] 0.33179858 2.3241418 0.85779622 1.6916878
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0589000 0.4591608 0.7336188 0.8568078
[2,] 0.2171766 0.5237937 0.3121873 0.7017053
[3,] 1.3335218 0.7083122 0.2726108 0.4226061
[4,] 0.5760196 1.5245136 0.9261729 1.3006490
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.77047 29.80244 32.87438 34.30220
[2,] 27.21893 30.51230 28.21933 32.50944
[3,] 40.11350 32.58483 27.80042 29.40466
[4,] 31.09199 42.56928 35.11953 39.69818
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x62a96ec4b840>
> exp(tmp5)
<pointer: 0x62a96ec4b840>
> log(tmp5,2)
<pointer: 0x62a96ec4b840>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.993
> Min(tmp5)
[1] 53.12249
> mean(tmp5)
[1] 72.0574
> Sum(tmp5)
[1] 14411.48
> Var(tmp5)
[1] 886.1196
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.19456 68.11242 68.74703 70.06051 70.99299 71.05365 69.30588 69.84941
[9] 70.42196 71.83561
> rowSums(tmp5)
[1] 1803.891 1362.248 1374.941 1401.210 1419.860 1421.073 1386.118 1396.988
[9] 1408.439 1436.712
> rowVars(tmp5)
[1] 8166.77711 67.00157 89.99357 68.20386 88.22812 122.95530
[7] 64.99069 80.01628 96.10295 40.06117
> rowSd(tmp5)
[1] 90.370222 8.185449 9.486494 8.258563 9.392982 11.088521 8.061680
[8] 8.945182 9.803211 6.329390
> rowMax(tmp5)
[1] 471.99302 84.04834 87.63375 88.60238 87.47540 100.43294 86.15765
[8] 85.01487 87.84618 82.03190
> rowMin(tmp5)
[1] 58.92772 55.05379 53.12249 58.24492 56.59905 56.02443 56.66802 55.73166
[9] 55.08141 62.01865
>
> colMeans(tmp5)
[1] 107.20218 75.63099 65.66393 71.10834 67.78912 71.24072 66.35681
[8] 74.66289 70.56120 69.11523 67.08727 71.42252 68.37516 67.28390
[15] 72.10575 68.88114 71.94449 70.88140 74.77953 69.05550
> colSums(tmp5)
[1] 1072.0218 756.3099 656.6393 711.0834 677.8912 712.4072 663.5681
[8] 746.6289 705.6120 691.1523 670.8727 714.2252 683.7516 672.8390
[15] 721.0575 688.8114 719.4449 708.8140 747.7953 690.5550
> colVars(tmp5)
[1] 16480.62064 101.76154 31.97926 167.63816 103.62856 58.87496
[7] 39.31974 56.56274 64.45135 39.22097 88.06797 76.32976
[13] 65.18266 82.75473 115.99291 127.97855 107.90472 106.04453
[19] 42.08781 27.65742
> colSd(tmp5)
[1] 128.376870 10.087693 5.655020 12.947516 10.179811 7.673002
[7] 6.270546 7.520821 8.028160 6.262665 9.384454 8.736690
[13] 8.073578 9.096962 10.770000 11.312761 10.387720 10.297793
[19] 6.487512 5.259033
> colMax(tmp5)
[1] 471.99302 88.60238 73.09669 100.43294 87.63375 82.03190 75.86513
[8] 84.04834 85.80848 77.65834 80.68329 86.40386 79.43548 79.71116
[15] 87.84618 91.80661 87.47540 85.85232 84.35098 77.14512
> colMin(tmp5)
[1] 56.65264 62.02987 57.86294 58.77090 56.65102 58.24492 56.59905 59.62160
[9] 60.28000 60.96369 55.08141 60.84763 53.12249 55.73166 57.23571 55.05379
[17] 56.02443 58.32085 63.58609 59.13575
>
>
> ### 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] NA 68.11242 68.74703 70.06051 70.99299 71.05365 69.30588 69.84941
[9] 70.42196 71.83561
> rowSums(tmp5)
[1] NA 1362.248 1374.941 1401.210 1419.860 1421.073 1386.118 1396.988
[9] 1408.439 1436.712
> rowVars(tmp5)
[1] 8600.39247 67.00157 89.99357 68.20386 88.22812 122.95530
[7] 64.99069 80.01628 96.10295 40.06117
> rowSd(tmp5)
[1] 92.738301 8.185449 9.486494 8.258563 9.392982 11.088521 8.061680
[8] 8.945182 9.803211 6.329390
> rowMax(tmp5)
[1] NA 84.04834 87.63375 88.60238 87.47540 100.43294 86.15765
[8] 85.01487 87.84618 82.03190
> rowMin(tmp5)
[1] NA 55.05379 53.12249 58.24492 56.59905 56.02443 56.66802 55.73166
[9] 55.08141 62.01865
>
> colMeans(tmp5)
[1] 107.20218 75.63099 65.66393 71.10834 67.78912 71.24072 66.35681
[8] 74.66289 70.56120 NA 67.08727 71.42252 68.37516 67.28390
[15] 72.10575 68.88114 71.94449 70.88140 74.77953 69.05550
> colSums(tmp5)
[1] 1072.0218 756.3099 656.6393 711.0834 677.8912 712.4072 663.5681
[8] 746.6289 705.6120 NA 670.8727 714.2252 683.7516 672.8390
[15] 721.0575 688.8114 719.4449 708.8140 747.7953 690.5550
> colVars(tmp5)
[1] 16480.62064 101.76154 31.97926 167.63816 103.62856 58.87496
[7] 39.31974 56.56274 64.45135 NA 88.06797 76.32976
[13] 65.18266 82.75473 115.99291 127.97855 107.90472 106.04453
[19] 42.08781 27.65742
> colSd(tmp5)
[1] 128.376870 10.087693 5.655020 12.947516 10.179811 7.673002
[7] 6.270546 7.520821 8.028160 NA 9.384454 8.736690
[13] 8.073578 9.096962 10.770000 11.312761 10.387720 10.297793
[19] 6.487512 5.259033
> colMax(tmp5)
[1] 471.99302 88.60238 73.09669 100.43294 87.63375 82.03190 75.86513
[8] 84.04834 85.80848 NA 80.68329 86.40386 79.43548 79.71116
[15] 87.84618 91.80661 87.47540 85.85232 84.35098 77.14512
> colMin(tmp5)
[1] 56.65264 62.02987 57.86294 58.77090 56.65102 58.24492 56.59905 59.62160
[9] 60.28000 NA 55.08141 60.84763 53.12249 55.73166 57.23571 55.05379
[17] 56.02443 58.32085 63.58609 59.13575
>
> Max(tmp5,na.rm=TRUE)
[1] 471.993
> Min(tmp5,na.rm=TRUE)
[1] 53.12249
> mean(tmp5,na.rm=TRUE)
[1] 72.05941
> Sum(tmp5,na.rm=TRUE)
[1] 14339.82
> Var(tmp5,na.rm=TRUE)
[1] 890.5942
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.17019 68.11242 68.74703 70.06051 70.99299 71.05365 69.30588 69.84941
[9] 70.42196 71.83561
> rowSums(tmp5,na.rm=TRUE)
[1] 1732.234 1362.248 1374.941 1401.210 1419.860 1421.073 1386.118 1396.988
[9] 1408.439 1436.712
> rowVars(tmp5,na.rm=TRUE)
[1] 8600.39247 67.00157 89.99357 68.20386 88.22812 122.95530
[7] 64.99069 80.01628 96.10295 40.06117
> rowSd(tmp5,na.rm=TRUE)
[1] 92.738301 8.185449 9.486494 8.258563 9.392982 11.088521 8.061680
[8] 8.945182 9.803211 6.329390
> rowMax(tmp5,na.rm=TRUE)
[1] 471.99302 84.04834 87.63375 88.60238 87.47540 100.43294 86.15765
[8] 85.01487 87.84618 82.03190
> rowMin(tmp5,na.rm=TRUE)
[1] 58.92772 55.05379 53.12249 58.24492 56.59905 56.02443 56.66802 55.73166
[9] 55.08141 62.01865
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.20218 75.63099 65.66393 71.10834 67.78912 71.24072 66.35681
[8] 74.66289 70.56120 68.83273 67.08727 71.42252 68.37516 67.28390
[15] 72.10575 68.88114 71.94449 70.88140 74.77953 69.05550
> colSums(tmp5,na.rm=TRUE)
[1] 1072.0218 756.3099 656.6393 711.0834 677.8912 712.4072 663.5681
[8] 746.6289 705.6120 619.4946 670.8727 714.2252 683.7516 672.8390
[15] 721.0575 688.8114 719.4449 708.8140 747.7953 690.5550
> colVars(tmp5,na.rm=TRUE)
[1] 16480.62064 101.76154 31.97926 167.63816 103.62856 58.87496
[7] 39.31974 56.56274 64.45135 43.22580 88.06797 76.32976
[13] 65.18266 82.75473 115.99291 127.97855 107.90472 106.04453
[19] 42.08781 27.65742
> colSd(tmp5,na.rm=TRUE)
[1] 128.376870 10.087693 5.655020 12.947516 10.179811 7.673002
[7] 6.270546 7.520821 8.028160 6.574633 9.384454 8.736690
[13] 8.073578 9.096962 10.770000 11.312761 10.387720 10.297793
[19] 6.487512 5.259033
> colMax(tmp5,na.rm=TRUE)
[1] 471.99302 88.60238 73.09669 100.43294 87.63375 82.03190 75.86513
[8] 84.04834 85.80848 77.65834 80.68329 86.40386 79.43548 79.71116
[15] 87.84618 91.80661 87.47540 85.85232 84.35098 77.14512
> colMin(tmp5,na.rm=TRUE)
[1] 56.65264 62.02987 57.86294 58.77090 56.65102 58.24492 56.59905 59.62160
[9] 60.28000 60.96369 55.08141 60.84763 53.12249 55.73166 57.23571 55.05379
[17] 56.02443 58.32085 63.58609 59.13575
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 68.11242 68.74703 70.06051 70.99299 71.05365 69.30588 69.84941
[9] 70.42196 71.83561
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1362.248 1374.941 1401.210 1419.860 1421.073 1386.118 1396.988
[9] 1408.439 1436.712
> rowVars(tmp5,na.rm=TRUE)
[1] NA 67.00157 89.99357 68.20386 88.22812 122.95530 64.99069
[8] 80.01628 96.10295 40.06117
> rowSd(tmp5,na.rm=TRUE)
[1] NA 8.185449 9.486494 8.258563 9.392982 11.088521 8.061680
[8] 8.945182 9.803211 6.329390
> rowMax(tmp5,na.rm=TRUE)
[1] NA 84.04834 87.63375 88.60238 87.47540 100.43294 86.15765
[8] 85.01487 87.84618 82.03190
> rowMin(tmp5,na.rm=TRUE)
[1] NA 55.05379 53.12249 58.24492 56.59905 56.02443 56.66802 55.73166
[9] 55.08141 62.01865
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 66.66987 77.14222 65.35729 71.07643 68.60804 70.83086 66.92191 76.33415
[9] 71.17786 NaN 67.99389 70.15476 68.26531 66.47949 70.36477 69.98307
[17] 70.65147 69.25797 74.58349 70.15769
> colSums(tmp5,na.rm=TRUE)
[1] 600.0288 694.2800 588.2156 639.6879 617.4724 637.4777 602.2972 687.0073
[9] 640.6007 0.0000 611.9450 631.3928 614.3878 598.3154 633.2830 629.8476
[17] 635.8632 623.3217 671.2514 631.4192
> colVars(tmp5,na.rm=TRUE)
[1] 58.42646 88.78861 34.91882 188.58147 109.03751 64.34447 40.64216
[8] 32.21078 68.22974 NA 89.82947 67.78992 73.19473 85.81948
[15] 96.39346 130.31577 102.58396 89.65044 46.91645 17.44776
> colSd(tmp5,na.rm=TRUE)
[1] 7.643720 9.422771 5.909215 13.732497 10.442103 8.021501 6.375120
[8] 5.675454 8.260130 NA 9.477841 8.233464 8.555392 9.263881
[15] 9.818017 11.415593 10.128374 9.468392 6.849558 4.177051
> colMax(tmp5,na.rm=TRUE)
[1] 83.49099 88.60238 73.09669 100.43294 87.63375 82.03190 75.86513
[8] 84.04834 85.80848 -Inf 80.68329 86.40386 79.43548 79.71116
[15] 87.84618 91.80661 87.47540 85.85232 84.35098 77.14512
> colMin(tmp5,na.rm=TRUE)
[1] 56.65264 63.50735 57.86294 58.77090 56.65102 58.24492 56.59905 66.56393
[9] 60.28000 Inf 55.08141 60.84763 53.12249 55.73166 57.23571 55.05379
[17] 56.02443 58.32085 63.58609 65.97023
>
>
>
>
> 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] 183.2970 240.4390 298.1487 231.2425 276.1424 226.5305 322.9149 266.3930
[9] 117.2337 275.2196
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 183.2970 240.4390 298.1487 231.2425 276.1424 226.5305 322.9149 266.3930
[9] 117.2337 275.2196
>
>
>
> 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] -2.842171e-14 1.136868e-13 5.684342e-14 -1.705303e-13 -8.526513e-14
[6] -6.394885e-14 -2.842171e-14 -1.705303e-13 -1.421085e-14 8.526513e-14
[11] 2.273737e-13 5.684342e-14 -5.684342e-14 1.136868e-13 -2.557954e-13
[16] -5.684342e-14 2.842171e-14 -5.684342e-14 0.000000e+00 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
4 6
4 1
6 5
7 4
2 1
10 8
4 4
6 19
2 11
6 12
10 2
3 20
8 15
7 16
10 20
3 13
6 5
5 17
2 11
2 8
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] 2.803325
> Min(tmp)
[1] -1.937776
> mean(tmp)
[1] -0.02098428
> Sum(tmp)
[1] -2.098428
> Var(tmp)
[1] 0.8909885
>
> rowMeans(tmp)
[1] -0.02098428
> rowSums(tmp)
[1] -2.098428
> rowVars(tmp)
[1] 0.8909885
> rowSd(tmp)
[1] 0.9439219
> rowMax(tmp)
[1] 2.803325
> rowMin(tmp)
[1] -1.937776
>
> colMeans(tmp)
[1] -0.674083202 -1.163458073 0.101657517 -1.334924340 -0.420500720
[6] 0.324744327 -1.458918858 0.302172680 0.266336661 -1.846380509
[11] 0.609735062 -0.330315867 -1.091252211 -0.853486442 -0.087925589
[16] 0.918683981 -0.844353694 0.687425683 -0.105403242 0.650530577
[21] 2.803324649 -0.877984402 0.386680861 -0.011295217 0.793299708
[26] -1.222337918 -0.532702846 0.489036920 0.142413674 -0.045275217
[31] 1.054040523 0.449719020 0.446987543 0.269233969 -1.327139921
[36] 1.163060298 -0.820230874 0.367609060 -1.547265479 -1.700227218
[41] 1.958859560 0.357884294 -1.127348461 1.711694051 -0.489907920
[46] 0.506295260 -0.647072988 -0.078884351 0.861226724 -0.883100240
[51] -1.169959929 -0.263009165 -1.900214732 -0.105753643 0.168382111
[56] 1.854345019 -0.729854670 -1.318217301 0.197938022 0.171867623
[61] 0.082047659 0.197570863 -0.014168886 0.067683676 -1.937775706
[66] -1.156629710 -0.870787194 0.709681798 0.351778798 -0.366870894
[71] -1.170606021 0.975731569 -0.040516362 -1.004397392 1.947171227
[76] 0.715469852 1.541417972 1.100072513 -0.633552447 -0.024471649
[81] -0.265151866 -0.008963047 -0.341603983 0.151346262 -0.340635550
[86] 1.801738144 1.345444307 0.407288947 -0.308889967 -0.153461789
[91] 0.568545476 0.416141630 0.223064026 0.351289024 -0.510955240
[96] -0.311092092 0.112537841 0.949992992 1.606377540 -1.266690248
> colSums(tmp)
[1] -0.674083202 -1.163458073 0.101657517 -1.334924340 -0.420500720
[6] 0.324744327 -1.458918858 0.302172680 0.266336661 -1.846380509
[11] 0.609735062 -0.330315867 -1.091252211 -0.853486442 -0.087925589
[16] 0.918683981 -0.844353694 0.687425683 -0.105403242 0.650530577
[21] 2.803324649 -0.877984402 0.386680861 -0.011295217 0.793299708
[26] -1.222337918 -0.532702846 0.489036920 0.142413674 -0.045275217
[31] 1.054040523 0.449719020 0.446987543 0.269233969 -1.327139921
[36] 1.163060298 -0.820230874 0.367609060 -1.547265479 -1.700227218
[41] 1.958859560 0.357884294 -1.127348461 1.711694051 -0.489907920
[46] 0.506295260 -0.647072988 -0.078884351 0.861226724 -0.883100240
[51] -1.169959929 -0.263009165 -1.900214732 -0.105753643 0.168382111
[56] 1.854345019 -0.729854670 -1.318217301 0.197938022 0.171867623
[61] 0.082047659 0.197570863 -0.014168886 0.067683676 -1.937775706
[66] -1.156629710 -0.870787194 0.709681798 0.351778798 -0.366870894
[71] -1.170606021 0.975731569 -0.040516362 -1.004397392 1.947171227
[76] 0.715469852 1.541417972 1.100072513 -0.633552447 -0.024471649
[81] -0.265151866 -0.008963047 -0.341603983 0.151346262 -0.340635550
[86] 1.801738144 1.345444307 0.407288947 -0.308889967 -0.153461789
[91] 0.568545476 0.416141630 0.223064026 0.351289024 -0.510955240
[96] -0.311092092 0.112537841 0.949992992 1.606377540 -1.266690248
> 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] -0.674083202 -1.163458073 0.101657517 -1.334924340 -0.420500720
[6] 0.324744327 -1.458918858 0.302172680 0.266336661 -1.846380509
[11] 0.609735062 -0.330315867 -1.091252211 -0.853486442 -0.087925589
[16] 0.918683981 -0.844353694 0.687425683 -0.105403242 0.650530577
[21] 2.803324649 -0.877984402 0.386680861 -0.011295217 0.793299708
[26] -1.222337918 -0.532702846 0.489036920 0.142413674 -0.045275217
[31] 1.054040523 0.449719020 0.446987543 0.269233969 -1.327139921
[36] 1.163060298 -0.820230874 0.367609060 -1.547265479 -1.700227218
[41] 1.958859560 0.357884294 -1.127348461 1.711694051 -0.489907920
[46] 0.506295260 -0.647072988 -0.078884351 0.861226724 -0.883100240
[51] -1.169959929 -0.263009165 -1.900214732 -0.105753643 0.168382111
[56] 1.854345019 -0.729854670 -1.318217301 0.197938022 0.171867623
[61] 0.082047659 0.197570863 -0.014168886 0.067683676 -1.937775706
[66] -1.156629710 -0.870787194 0.709681798 0.351778798 -0.366870894
[71] -1.170606021 0.975731569 -0.040516362 -1.004397392 1.947171227
[76] 0.715469852 1.541417972 1.100072513 -0.633552447 -0.024471649
[81] -0.265151866 -0.008963047 -0.341603983 0.151346262 -0.340635550
[86] 1.801738144 1.345444307 0.407288947 -0.308889967 -0.153461789
[91] 0.568545476 0.416141630 0.223064026 0.351289024 -0.510955240
[96] -0.311092092 0.112537841 0.949992992 1.606377540 -1.266690248
> colMin(tmp)
[1] -0.674083202 -1.163458073 0.101657517 -1.334924340 -0.420500720
[6] 0.324744327 -1.458918858 0.302172680 0.266336661 -1.846380509
[11] 0.609735062 -0.330315867 -1.091252211 -0.853486442 -0.087925589
[16] 0.918683981 -0.844353694 0.687425683 -0.105403242 0.650530577
[21] 2.803324649 -0.877984402 0.386680861 -0.011295217 0.793299708
[26] -1.222337918 -0.532702846 0.489036920 0.142413674 -0.045275217
[31] 1.054040523 0.449719020 0.446987543 0.269233969 -1.327139921
[36] 1.163060298 -0.820230874 0.367609060 -1.547265479 -1.700227218
[41] 1.958859560 0.357884294 -1.127348461 1.711694051 -0.489907920
[46] 0.506295260 -0.647072988 -0.078884351 0.861226724 -0.883100240
[51] -1.169959929 -0.263009165 -1.900214732 -0.105753643 0.168382111
[56] 1.854345019 -0.729854670 -1.318217301 0.197938022 0.171867623
[61] 0.082047659 0.197570863 -0.014168886 0.067683676 -1.937775706
[66] -1.156629710 -0.870787194 0.709681798 0.351778798 -0.366870894
[71] -1.170606021 0.975731569 -0.040516362 -1.004397392 1.947171227
[76] 0.715469852 1.541417972 1.100072513 -0.633552447 -0.024471649
[81] -0.265151866 -0.008963047 -0.341603983 0.151346262 -0.340635550
[86] 1.801738144 1.345444307 0.407288947 -0.308889967 -0.153461789
[91] 0.568545476 0.416141630 0.223064026 0.351289024 -0.510955240
[96] -0.311092092 0.112537841 0.949992992 1.606377540 -1.266690248
> colMedians(tmp)
[1] -0.674083202 -1.163458073 0.101657517 -1.334924340 -0.420500720
[6] 0.324744327 -1.458918858 0.302172680 0.266336661 -1.846380509
[11] 0.609735062 -0.330315867 -1.091252211 -0.853486442 -0.087925589
[16] 0.918683981 -0.844353694 0.687425683 -0.105403242 0.650530577
[21] 2.803324649 -0.877984402 0.386680861 -0.011295217 0.793299708
[26] -1.222337918 -0.532702846 0.489036920 0.142413674 -0.045275217
[31] 1.054040523 0.449719020 0.446987543 0.269233969 -1.327139921
[36] 1.163060298 -0.820230874 0.367609060 -1.547265479 -1.700227218
[41] 1.958859560 0.357884294 -1.127348461 1.711694051 -0.489907920
[46] 0.506295260 -0.647072988 -0.078884351 0.861226724 -0.883100240
[51] -1.169959929 -0.263009165 -1.900214732 -0.105753643 0.168382111
[56] 1.854345019 -0.729854670 -1.318217301 0.197938022 0.171867623
[61] 0.082047659 0.197570863 -0.014168886 0.067683676 -1.937775706
[66] -1.156629710 -0.870787194 0.709681798 0.351778798 -0.366870894
[71] -1.170606021 0.975731569 -0.040516362 -1.004397392 1.947171227
[76] 0.715469852 1.541417972 1.100072513 -0.633552447 -0.024471649
[81] -0.265151866 -0.008963047 -0.341603983 0.151346262 -0.340635550
[86] 1.801738144 1.345444307 0.407288947 -0.308889967 -0.153461789
[91] 0.568545476 0.416141630 0.223064026 0.351289024 -0.510955240
[96] -0.311092092 0.112537841 0.949992992 1.606377540 -1.266690248
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.6740832 -1.163458 0.1016575 -1.334924 -0.4205007 0.3247443 -1.458919
[2,] -0.6740832 -1.163458 0.1016575 -1.334924 -0.4205007 0.3247443 -1.458919
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.3021727 0.2663367 -1.846381 0.6097351 -0.3303159 -1.091252 -0.8534864
[2,] 0.3021727 0.2663367 -1.846381 0.6097351 -0.3303159 -1.091252 -0.8534864
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.08792559 0.918684 -0.8443537 0.6874257 -0.1054032 0.6505306 2.803325
[2,] -0.08792559 0.918684 -0.8443537 0.6874257 -0.1054032 0.6505306 2.803325
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.8779844 0.3866809 -0.01129522 0.7932997 -1.222338 -0.5327028 0.4890369
[2,] -0.8779844 0.3866809 -0.01129522 0.7932997 -1.222338 -0.5327028 0.4890369
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.1424137 -0.04527522 1.054041 0.449719 0.4469875 0.269234 -1.32714
[2,] 0.1424137 -0.04527522 1.054041 0.449719 0.4469875 0.269234 -1.32714
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.16306 -0.8202309 0.3676091 -1.547265 -1.700227 1.95886 0.3578843
[2,] 1.16306 -0.8202309 0.3676091 -1.547265 -1.700227 1.95886 0.3578843
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.127348 1.711694 -0.4899079 0.5062953 -0.647073 -0.07888435 0.8612267
[2,] -1.127348 1.711694 -0.4899079 0.5062953 -0.647073 -0.07888435 0.8612267
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.8831002 -1.16996 -0.2630092 -1.900215 -0.1057536 0.1683821 1.854345
[2,] -0.8831002 -1.16996 -0.2630092 -1.900215 -0.1057536 0.1683821 1.854345
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.7298547 -1.318217 0.197938 0.1718676 0.08204766 0.1975709 -0.01416889
[2,] -0.7298547 -1.318217 0.197938 0.1718676 0.08204766 0.1975709 -0.01416889
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.06768368 -1.937776 -1.15663 -0.8707872 0.7096818 0.3517788 -0.3668709
[2,] 0.06768368 -1.937776 -1.15663 -0.8707872 0.7096818 0.3517788 -0.3668709
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.170606 0.9757316 -0.04051636 -1.004397 1.947171 0.7154699 1.541418
[2,] -1.170606 0.9757316 -0.04051636 -1.004397 1.947171 0.7154699 1.541418
[,78] [,79] [,80] [,81] [,82] [,83]
[1,] 1.100073 -0.6335524 -0.02447165 -0.2651519 -0.008963047 -0.341604
[2,] 1.100073 -0.6335524 -0.02447165 -0.2651519 -0.008963047 -0.341604
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.1513463 -0.3406356 1.801738 1.345444 0.4072889 -0.30889 -0.1534618
[2,] 0.1513463 -0.3406356 1.801738 1.345444 0.4072889 -0.30889 -0.1534618
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.5685455 0.4161416 0.223064 0.351289 -0.5109552 -0.3110921 0.1125378
[2,] 0.5685455 0.4161416 0.223064 0.351289 -0.5109552 -0.3110921 0.1125378
[,98] [,99] [,100]
[1,] 0.949993 1.606378 -1.26669
[2,] 0.949993 1.606378 -1.26669
>
>
> Max(tmp2)
[1] 2.292474
> Min(tmp2)
[1] -2.764591
> mean(tmp2)
[1] -0.002562363
> Sum(tmp2)
[1] -0.2562363
> Var(tmp2)
[1] 0.8552075
>
> rowMeans(tmp2)
[1] 0.113523943 -0.442800140 1.601637167 -0.462007761 -0.070956112
[6] 0.044695861 0.386905067 0.833569535 0.610489312 0.768505282
[11] -0.735733411 -0.354427916 0.601497199 -0.787233322 1.313737028
[16] 1.681770994 0.064780097 -1.428599891 -0.020088858 -1.468208917
[21] 1.411396485 0.440674950 -0.025631100 0.737495335 -0.893183508
[26] -0.883348665 -1.087733060 -0.343299468 -0.089197460 -0.766042194
[31] 0.392868072 -0.122568944 -0.435491905 -1.409677421 0.467105948
[36] -0.413682997 0.979631975 -1.269003070 -1.380350219 1.415296076
[41] 0.316931313 0.673223027 0.146715197 -1.079467916 -0.991241521
[46] 0.047662310 1.807619602 -0.932556166 0.923597745 -1.298424721
[51] -1.381491100 1.990706210 0.429728411 0.433671234 -0.244374461
[56] 0.224479147 -0.538354405 1.461664035 -1.456192889 -0.052147893
[61] -1.170676510 -0.392023776 -0.235707364 0.615870657 1.303760364
[66] 0.804734670 -1.350979280 -1.267080698 0.876685664 -0.828972082
[71] 0.473745088 0.446843148 0.103078723 -1.240803895 1.666761212
[76] 0.762748902 -1.500112131 -0.487702101 0.949804262 -0.203665403
[81] 0.106253728 0.694334477 0.033637679 -2.764590900 -0.178208535
[86] 0.467554964 0.299629500 0.105754770 0.407391555 0.251475251
[91] -0.005711032 -0.114186487 -0.076033332 0.126720362 2.292474312
[96] -0.278320857 0.134298285 0.571320122 -1.159678528 0.045277776
> rowSums(tmp2)
[1] 0.113523943 -0.442800140 1.601637167 -0.462007761 -0.070956112
[6] 0.044695861 0.386905067 0.833569535 0.610489312 0.768505282
[11] -0.735733411 -0.354427916 0.601497199 -0.787233322 1.313737028
[16] 1.681770994 0.064780097 -1.428599891 -0.020088858 -1.468208917
[21] 1.411396485 0.440674950 -0.025631100 0.737495335 -0.893183508
[26] -0.883348665 -1.087733060 -0.343299468 -0.089197460 -0.766042194
[31] 0.392868072 -0.122568944 -0.435491905 -1.409677421 0.467105948
[36] -0.413682997 0.979631975 -1.269003070 -1.380350219 1.415296076
[41] 0.316931313 0.673223027 0.146715197 -1.079467916 -0.991241521
[46] 0.047662310 1.807619602 -0.932556166 0.923597745 -1.298424721
[51] -1.381491100 1.990706210 0.429728411 0.433671234 -0.244374461
[56] 0.224479147 -0.538354405 1.461664035 -1.456192889 -0.052147893
[61] -1.170676510 -0.392023776 -0.235707364 0.615870657 1.303760364
[66] 0.804734670 -1.350979280 -1.267080698 0.876685664 -0.828972082
[71] 0.473745088 0.446843148 0.103078723 -1.240803895 1.666761212
[76] 0.762748902 -1.500112131 -0.487702101 0.949804262 -0.203665403
[81] 0.106253728 0.694334477 0.033637679 -2.764590900 -0.178208535
[86] 0.467554964 0.299629500 0.105754770 0.407391555 0.251475251
[91] -0.005711032 -0.114186487 -0.076033332 0.126720362 2.292474312
[96] -0.278320857 0.134298285 0.571320122 -1.159678528 0.045277776
> 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] 0.113523943 -0.442800140 1.601637167 -0.462007761 -0.070956112
[6] 0.044695861 0.386905067 0.833569535 0.610489312 0.768505282
[11] -0.735733411 -0.354427916 0.601497199 -0.787233322 1.313737028
[16] 1.681770994 0.064780097 -1.428599891 -0.020088858 -1.468208917
[21] 1.411396485 0.440674950 -0.025631100 0.737495335 -0.893183508
[26] -0.883348665 -1.087733060 -0.343299468 -0.089197460 -0.766042194
[31] 0.392868072 -0.122568944 -0.435491905 -1.409677421 0.467105948
[36] -0.413682997 0.979631975 -1.269003070 -1.380350219 1.415296076
[41] 0.316931313 0.673223027 0.146715197 -1.079467916 -0.991241521
[46] 0.047662310 1.807619602 -0.932556166 0.923597745 -1.298424721
[51] -1.381491100 1.990706210 0.429728411 0.433671234 -0.244374461
[56] 0.224479147 -0.538354405 1.461664035 -1.456192889 -0.052147893
[61] -1.170676510 -0.392023776 -0.235707364 0.615870657 1.303760364
[66] 0.804734670 -1.350979280 -1.267080698 0.876685664 -0.828972082
[71] 0.473745088 0.446843148 0.103078723 -1.240803895 1.666761212
[76] 0.762748902 -1.500112131 -0.487702101 0.949804262 -0.203665403
[81] 0.106253728 0.694334477 0.033637679 -2.764590900 -0.178208535
[86] 0.467554964 0.299629500 0.105754770 0.407391555 0.251475251
[91] -0.005711032 -0.114186487 -0.076033332 0.126720362 2.292474312
[96] -0.278320857 0.134298285 0.571320122 -1.159678528 0.045277776
> rowMin(tmp2)
[1] 0.113523943 -0.442800140 1.601637167 -0.462007761 -0.070956112
[6] 0.044695861 0.386905067 0.833569535 0.610489312 0.768505282
[11] -0.735733411 -0.354427916 0.601497199 -0.787233322 1.313737028
[16] 1.681770994 0.064780097 -1.428599891 -0.020088858 -1.468208917
[21] 1.411396485 0.440674950 -0.025631100 0.737495335 -0.893183508
[26] -0.883348665 -1.087733060 -0.343299468 -0.089197460 -0.766042194
[31] 0.392868072 -0.122568944 -0.435491905 -1.409677421 0.467105948
[36] -0.413682997 0.979631975 -1.269003070 -1.380350219 1.415296076
[41] 0.316931313 0.673223027 0.146715197 -1.079467916 -0.991241521
[46] 0.047662310 1.807619602 -0.932556166 0.923597745 -1.298424721
[51] -1.381491100 1.990706210 0.429728411 0.433671234 -0.244374461
[56] 0.224479147 -0.538354405 1.461664035 -1.456192889 -0.052147893
[61] -1.170676510 -0.392023776 -0.235707364 0.615870657 1.303760364
[66] 0.804734670 -1.350979280 -1.267080698 0.876685664 -0.828972082
[71] 0.473745088 0.446843148 0.103078723 -1.240803895 1.666761212
[76] 0.762748902 -1.500112131 -0.487702101 0.949804262 -0.203665403
[81] 0.106253728 0.694334477 0.033637679 -2.764590900 -0.178208535
[86] 0.467554964 0.299629500 0.105754770 0.407391555 0.251475251
[91] -0.005711032 -0.114186487 -0.076033332 0.126720362 2.292474312
[96] -0.278320857 0.134298285 0.571320122 -1.159678528 0.045277776
>
> colMeans(tmp2)
[1] -0.002562363
> colSums(tmp2)
[1] -0.2562363
> colVars(tmp2)
[1] 0.8552075
> colSd(tmp2)
[1] 0.9247743
> colMax(tmp2)
[1] 2.292474
> colMin(tmp2)
[1] -2.764591
> colMedians(tmp2)
[1] 0.04498682
> colRanges(tmp2)
[,1]
[1,] -2.764591
[2,] 2.292474
>
> 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] 2.5840235 4.7699513 -3.5178856 1.4706782 0.5883347 3.7850018
[7] -3.2280149 1.6554110 2.8327291 -0.4912158
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8398103
[2,] -0.3584062
[3,] 0.1762713
[4,] 1.0404039
[5,] 1.4260172
>
> rowApply(tmp,sum)
[1] 2.5861856 2.3562784 0.3640536 0.9107406 -1.2695259 1.9544039
[7] 2.5774767 0.6433527 -2.2980472 2.6240949
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 8 6 9 4 4 2 10 5 7
[2,] 5 6 8 4 6 10 6 7 10 2
[3,] 3 3 1 7 9 7 9 4 3 1
[4,] 6 10 4 3 10 8 8 1 1 6
[5,] 1 7 10 5 5 6 3 3 2 10
[6,] 2 4 9 10 3 9 4 5 4 8
[7,] 9 5 3 1 2 1 1 9 8 4
[8,] 7 9 2 8 7 2 7 8 6 5
[9,] 10 2 7 2 1 5 10 6 7 9
[10,] 8 1 5 6 8 3 5 2 9 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.58672421 -0.36800090 0.41522158 0.01547263 3.10223791 1.89096363
[7] 2.13336245 0.56018882 -1.58839146 3.08158780 -1.04748234 -2.14951419
[13] 1.94620024 0.65559785 -1.02406641 -2.14095836 -1.96048158 4.50998881
[19] -1.99789331 -0.64154931
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6463035
[2,] 0.4639808
[3,] 0.9613529
[4,] 1.1362052
[5,] 2.6714889
>
> rowApply(tmp,sum)
[1] -6.552525 4.387456 4.123645 4.937266 3.083366
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 12 17 16 20
[2,] 1 5 18 3 19
[3,] 12 20 3 11 4
[4,] 4 19 13 2 9
[5,] 16 15 10 20 11
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.6463035 -2.3286483 -0.4907431 -1.3391354 0.5268103 0.3333539 0.2483369
[2,] 0.4639808 -0.3976976 2.1364270 2.1275921 0.6471887 -0.1123743 0.0807513
[3,] 1.1362052 1.5625371 -0.9896281 0.5898882 0.3131988 1.6279397 0.2808229
[4,] 0.9613529 -0.9847104 0.6277152 -1.0136082 1.4017907 0.8796748 0.5714856
[5,] 2.6714889 1.7805185 -0.8685494 -0.3492640 0.2132493 -0.8376305 0.9519657
[,8] [,9] [,10] [,11] [,12] [,13]
[1,] 1.1686585 -0.8015685 0.1631769 -0.5922576 -1.5660800 0.92249728
[2,] -0.1202340 -0.2367065 0.7030120 0.5583647 1.1533308 0.61342291
[3,] -2.1437241 0.9753363 0.5613996 0.6804176 -0.9747855 -0.06061344
[4,] 0.3235848 -0.8008602 1.1699349 -1.1496371 -0.4847733 -0.45061910
[5,] 1.3319036 -0.7245925 0.4840643 -0.5443700 -0.2772062 0.92151260
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 1.9600978 -0.8632503 -0.7902397 -1.0943217 1.2280736 -1.0590509
[2,] -1.4209836 -1.3110329 -1.2378972 0.2161497 1.5601309 -1.2707710
[3,] 0.5617084 0.7502395 -0.2016599 -1.2817248 -0.4468158 -0.6383060
[4,] 0.7831413 0.7884498 1.0513108 -0.9550919 1.1959346 0.3630300
[5,] -1.2283661 -0.3884725 -0.9624723 1.1545072 0.9726654 0.6072045
[,20]
[1,] -1.5319310
[2,] 0.2348022
[3,] 1.8212095
[4,] 0.6591605
[5,] -1.8247905
>
>
> 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 : 648 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 : 562 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 1.166242 -0.2562253 -0.2261805 -0.1021515 0.1343466 -2.065162 0.1656781
col8 col9 col10 col11 col12 col13 col14
row1 0.9767721 0.5193555 1.022474 1.397054 -1.794945 -0.5491016 -0.2678859
col15 col16 col17 col18 col19 col20
row1 -1.921655 0.8501233 1.309385 0.7860661 0.9231617 1.003872
> tmp[,"col10"]
col10
row1 1.02247367
row2 1.59085698
row3 0.89449535
row4 -1.96116404
row5 -0.04834925
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.1662424 -0.2562253 -0.2261805 -0.1021515 0.1343466 -2.065162 0.1656781
row5 0.4204711 0.7585339 0.1591387 0.7880580 -1.8082340 1.768324 0.1179885
col8 col9 col10 col11 col12 col13
row1 0.9767721 0.5193555 1.02247367 1.3970536 -1.7949453 -0.54910161
row5 1.1788805 -0.0421391 -0.04834925 -0.1934508 0.1475642 0.09074508
col14 col15 col16 col17 col18 col19 col20
row1 -0.2678859 -1.9216547 0.8501233 1.3093849 0.7860661 0.9231617 1.0038722
row5 0.3212492 -0.5588578 0.6969431 -0.7504378 2.6574273 2.3713504 -0.7858115
> tmp[,c("col6","col20")]
col6 col20
row1 -2.0651618 1.0038722
row2 0.8279424 1.1368390
row3 1.1942842 1.8219267
row4 0.6340930 0.7751104
row5 1.7683242 -0.7858115
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -2.065162 1.0038722
row5 1.768324 -0.7858115
>
>
>
>
> 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 47.51902 50.24965 49.8603 49.46261 49.79729 104.5786 49.59837 48.42672
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.06544 49.48188 52.32479 49.7576 49.49928 50.10995 49.9669 50.04859
col17 col18 col19 col20
row1 50.04393 49.81277 50.54764 104.3838
> tmp[,"col10"]
col10
row1 49.48188
row2 30.30738
row3 29.63327
row4 29.47580
row5 48.37463
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 47.51902 50.24965 49.86030 49.46261 49.79729 104.5786 49.59837 48.42672
row5 49.76279 49.21133 48.58205 50.34704 50.72968 105.1025 48.20620 48.87270
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.06544 49.48188 52.32479 49.75760 49.49928 50.10995 49.96690 50.04859
row5 50.20370 48.37463 50.77355 48.35648 50.10891 51.63575 49.93155 49.46939
col17 col18 col19 col20
row1 50.04393 49.81277 50.54764 104.3838
row5 50.15718 50.11562 52.11981 106.1728
> tmp[,c("col6","col20")]
col6 col20
row1 104.57860 104.38380
row2 76.76266 74.09486
row3 75.49614 75.13831
row4 74.98600 74.58995
row5 105.10246 106.17281
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5786 104.3838
row5 105.1025 106.1728
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5786 104.3838
row5 105.1025 106.1728
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3809914
[2,] 0.8417280
[3,] -0.3235010
[4,] -0.1664300
[5,] 1.3995828
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.6542904963 -0.4170203
[2,] -1.0138973619 -0.6999876
[3,] 1.2632268738 -0.7212136
[4,] -0.9002852670 -0.2083169
[5,] -0.0005089105 -1.1958251
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.30568609 -0.29863997
[2,] 0.01341719 0.77776615
[3,] 0.05104190 0.66575391
[4,] -0.51153482 -0.02479394
[5,] 1.38657631 0.16927690
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3056861
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.30568609
[2,] 0.01341719
>
>
>
> 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 -1.942806 0.02266793 -0.8757441 0.2130755 0.5969522 -0.6991313 0.4496306
row1 -1.344988 1.25131439 0.6743754 0.9136138 -0.5921746 -0.7698674 0.8587025
[,8] [,9] [,10] [,11] [,12] [,13]
row3 1.4704154 0.07328321 1.5717517 -0.09209155 1.221559 -1.132817
row1 -0.2530407 -0.75626926 -0.7967615 1.26123306 -0.942357 -1.404405
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.04082142 -0.7296809 -0.128536 -0.4167561 0.02470627 -0.6710211
row1 0.69956968 -0.7259236 2.253295 -1.1611403 0.67438632 0.7111506
[,20]
row3 0.6682874
row1 0.1531166
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.828377 -0.1903021 -2.31089 -0.31829 -2.287124 0.4278986 0.3561379
[,8] [,9] [,10]
row2 -0.5687022 -0.2126173 -0.1264356
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.239851 1.04252 -0.9826771 -1.789926 0.1637707 -1.244414 1.08606
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7416302 0.6849539 0.7468324 -0.3594374 0.6513463 2.195412 0.9743922
[,15] [,16] [,17] [,18] [,19] [,20]
row5 2.327368 -1.720721 -0.6799975 1.031129 -0.4444699 -0.09749272
>
>
> 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: 0x62a96ea08c20>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c866535cc01"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c865b99648e"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c8653dc91f"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c86361640f5"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c865662c59a"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c86751ec20f"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c862c3f06fb"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c8611ad4ddc"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c8633decf59"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c8637a3d52d"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c865dbf56d5"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c8650432961"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c86715cdb62"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c862d4b30"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa3c861a2a77"
>
>
> ### 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: 0x62a96d932800>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x62a96d932800>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x62a96d932800>
> rowMedians(tmp)
[1] 0.2995461858 0.1218746338 0.2180184273 -0.1124832054 0.3961179885
[6] 0.2922409035 -0.3589847499 -0.1523659959 0.4344458205 -0.4254616300
[11] 0.0002487389 0.1672754003 -0.0328305369 -0.5118383795 0.3919086350
[16] 0.2121011414 -0.0846064054 0.0485241344 0.5362129735 0.0009214384
[21] -0.1616585657 -0.4819568959 -0.0175929928 0.1706976237 -0.4200742247
[26] -0.7515475199 0.2480210862 -0.0716832807 0.7604194663 -0.0309773834
[31] 0.3318532488 -0.4399222137 -0.1712284529 -0.3953887590 -0.1558935532
[36] -0.7165835685 -0.2354180826 0.1984186075 -0.3008727380 -0.3904638305
[41] 0.3081191639 0.1760989984 -0.0797623762 -0.0735506013 -0.5475412741
[46] -0.0803740675 0.1241499082 -0.1546086481 0.2912523548 0.0632750489
[51] 0.3263765838 0.3865382048 0.1970382612 -0.0279038120 -0.0642634061
[56] -0.5230284102 -0.2974806238 -0.1627816107 -0.0488130887 0.1300644356
[61] 0.1909470679 0.6134775985 -0.0904009266 0.1168502833 -0.5081381763
[66] 0.2684845327 -0.2833328583 0.4363123120 -0.0225132243 0.4576117839
[71] -0.0796082273 0.3917462536 0.0958026467 0.3954572014 0.1188879262
[76] 0.4520739701 0.1684030555 0.4254207658 -0.0442862692 -0.1714750931
[81] -0.3188478193 -0.2264799446 -0.1646403439 -0.0546248058 0.5406480258
[86] 0.0227819965 0.1827645686 -0.2529445619 -0.3265242664 0.0942300267
[91] 0.0400003384 -0.0701956359 0.2495067968 0.4654491642 0.6459517258
[96] -0.3784295406 -0.1622416132 0.0837518568 -0.2099404268 0.4245517319
[101] -0.0447328591 0.0892957495 -0.3456385694 -0.3642777022 -0.6016847298
[106] -0.2981750255 -0.1412585374 0.0326868150 -0.6193252176 -0.4445565256
[111] 0.2044924230 -0.0962419939 0.3126519829 0.3478604390 -0.1594536102
[116] -0.7762445842 -0.2368063308 -0.4518067501 0.3381671142 0.5019309030
[121] 0.0286431271 -0.3457495745 -0.4793390160 -0.2788266846 0.1231820208
[126] -0.2811076915 -0.0996305416 0.3502622426 0.1996908783 0.2151332172
[131] -0.2442956806 -0.1231891644 0.5494777927 -0.4235179345 -0.1848601549
[136] -0.0235070879 -0.4696029891 0.7992386426 0.0492618880 -0.7871647604
[141] 0.1838576426 -0.0895231095 0.2062662810 -0.3318878183 0.1990082838
[146] -0.6035117393 0.3823444173 0.3105332156 0.0171695889 0.4635228811
[151] -0.3331940458 -0.1054630169 0.1472647090 0.1498669142 0.5969834083
[156] -0.1254341308 0.2054256115 0.1550760436 0.1219820362 0.1622842873
[161] -0.0497705665 0.6936384419 -0.0049757857 -0.0690530857 -0.4985774974
[166] 0.1938744637 -0.1184549645 -0.9234346984 0.0627018341 -0.0864330893
[171] 0.2735489686 0.0178686547 -0.9122597214 0.0890387905 -0.1570666768
[176] -0.1626187908 -0.1244446779 -0.4302232681 0.1264552167 0.2147656688
[181] -0.0812218340 0.0821367983 -0.2219159331 0.0800572326 -0.2738701242
[186] -0.1725556736 -0.1276900706 -0.0994388341 0.2067694060 0.2817381133
[191] 0.3047851812 -0.4648374372 -0.2297321375 -0.1967102026 -0.1505421667
[196] 0.0370935141 0.0428359124 -0.1208116859 -0.1831918894 -0.1868124908
[201] -0.6684339916 -0.7494111454 0.0533152090 -0.0995559115 0.0280648553
[206] -0.5240048747 0.2332764572 0.4996952475 -0.1355627822 0.4365900764
[211] 0.2250651150 -0.1921272464 -0.3797963984 -0.3131636796 -0.3396091226
[216] -0.1203181418 -0.5117392565 -0.2827028055 -0.4298146657 -0.5700701711
[221] -0.0627000906 0.3394532634 -0.3614764487 -0.0530986249 0.2900851270
[226] 0.0322142373 0.4459848714 -0.1177120309 -0.0944446345 0.0324404742
>
> proc.time()
user system elapsed
1.344 1.420 2.753
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: 0x63a0db08cb20>
> .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: 0x63a0db08cb20>
> .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: 0x63a0db08cb20>
> .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: 0x63a0db08cb20>
> 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: 0x63a0db06d410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0db06d410>
> .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: 0x63a0db06d410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0db06d410>
> .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: 0x63a0db06d410>
> 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: 0x63a0d991a7a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0d991a7a0>
> .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: 0x63a0d991a7a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x63a0d991a7a0>
> .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: 0x63a0d991a7a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x63a0d991a7a0>
> .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: 0x63a0d991a7a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x63a0d991a7a0>
> .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: 0x63a0d991a7a0>
> 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: 0x63a0d9e5e070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x63a0d9e5e070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0d9e5e070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0d9e5e070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilea3eea1c9e9b19" "BufferedMatrixFilea3eea2bb96bee"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilea3eea1c9e9b19" "BufferedMatrixFilea3eea2bb96bee"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0da9f10c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0da9f10c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x63a0da9f10c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x63a0da9f10c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x63a0da9f10c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x63a0da9f10c0>
> .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: 0x63a0dba07a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63a0dba07a10>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x63a0dba07a10>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x63a0dba07a10>
> 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: 0x63a0dae8ac60>
> .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: 0x63a0dae8ac60>
> rm(P)
>
> proc.time()
user system elapsed
0.233 0.058 0.282
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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Platform: x86_64-pc-linux-gnu
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.231 0.054 0.275