Ben Bolstad
| Snapshot Date: 2025-12-18 13:45 -0500 (Thu, 18 Dec 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-12-22 12:03 -0500 (Mon, 22 Dec 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4883 |
| merida1 | macOS 12.7.6 Monterey | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4673 |
| kjohnson1 | macOS 13.7.5 Ventura | arm64 | 4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble" | 4607 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4671 |
| 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 257/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.74.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.7.5 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | 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: 1.74.0 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2025-12-18 21:41:11 -0500 (Thu, 18 Dec 2025) |
| EndedAt: 2025-12-18 21:41:35 -0500 (Thu, 18 Dec 2025) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.2 (2025-10-31)
* 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 ‘1.74.0’
* 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 ... NOTE
Note: information on .o files is not available
* 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: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** 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-3.22-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-3.22-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-3.22-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-3.22-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-3.22-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-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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
0.266 0.054 0.305
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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-3.22-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 478284 25.6 1046725 56 639600 34.2
Vcells 884773 6.8 8388608 64 2081613 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] "Thu Dec 18 21:41:27 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] "Thu Dec 18 21:41:27 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: 0x5fad78846370>
>
>
>
> 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] "Thu Dec 18 21:41:27 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] "Thu Dec 18 21:41:27 2025"
>
> ColMode(tmp2)
<pointer: 0x5fad78846370>
>
>
>
> ### 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,] 99.8363270 1.7826856 0.06249236 0.01054185
[2,] -0.6918603 1.7781864 -1.25328293 -1.22525878
[3,] -1.3592210 -0.5431543 -0.70922838 -0.17974152
[4,] -0.2487214 2.5276597 -0.35234951 1.44354760
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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,] 99.8363270 1.7826856 0.06249236 0.01054185
[2,] 0.6918603 1.7781864 1.25328293 1.22525878
[3,] 1.3592210 0.5431543 0.70922838 0.17974152
[4,] 0.2487214 2.5276597 0.35234951 1.44354760
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9918130 1.335172 0.2499847 0.1026735
[2,] 0.8317814 1.333487 1.1195012 1.1069141
[3,] 1.1658563 0.736990 0.8421570 0.4239593
[4,] 0.4987197 1.589862 0.5935904 1.2014773
>
> 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-3.22-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,] 224.75446 40.13441 27.56234 26.03728
[2,] 34.00967 40.11305 37.44829 37.29440
[3,] 38.01778 32.91305 34.13080 29.41933
[4,] 30.23592 43.42628 31.28825 38.45832
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5fad798429b0>
> exp(tmp5)
<pointer: 0x5fad798429b0>
> log(tmp5,2)
<pointer: 0x5fad798429b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.797
> Min(tmp5)
[1] 53.16171
> mean(tmp5)
[1] 73.00034
> Sum(tmp5)
[1] 14600.07
> Var(tmp5)
[1] 871.9353
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.30309 71.80242 70.10956 73.48179 72.67401 71.34192 71.40206 69.13724
[9] 70.63539 72.11597
> rowSums(tmp5)
[1] 1746.062 1436.048 1402.191 1469.636 1453.480 1426.838 1428.041 1382.745
[9] 1412.708 1442.319
> rowVars(tmp5)
[1] 8091.49245 121.60206 69.78395 133.15832 104.14639 70.27986
[7] 78.96864 57.90514 63.31700 87.71908
> rowSd(tmp5)
[1] 89.952723 11.027333 8.353679 11.539425 10.205214 8.383308 8.886430
[8] 7.609542 7.957198 9.365847
> rowMax(tmp5)
[1] 467.79696 96.94169 95.44379 96.43501 93.71697 90.31495 87.15592
[8] 81.19905 83.00931 88.70734
> rowMin(tmp5)
[1] 54.19318 54.53875 60.17084 56.43358 56.63625 56.06917 55.30451 53.16171
[9] 57.66131 55.69346
>
> colMeans(tmp5)
[1] 113.16801 78.24360 66.90734 73.27172 75.44586 64.53802 75.00622
[8] 72.83571 70.27771 69.51002 73.61553 74.74307 69.03423 71.30910
[15] 70.89458 61.25025 74.98844 67.92566 70.78138 66.26043
> colSums(tmp5)
[1] 1131.6801 782.4360 669.0734 732.7172 754.4586 645.3802 750.0622
[8] 728.3571 702.7771 695.1002 736.1553 747.4307 690.3423 713.0910
[15] 708.9458 612.5025 749.8844 679.2566 707.8138 662.6043
> colVars(tmp5)
[1] 15579.06494 47.04360 97.77917 125.07948 67.63751 26.43832
[7] 64.90298 141.63167 44.38786 71.06686 77.09323 129.85616
[13] 92.43572 58.73385 29.55439 49.88095 146.57164 56.87400
[19] 63.18306 61.43376
> colSd(tmp5)
[1] 124.816125 6.858834 9.888335 11.183894 8.224203 5.141821
[7] 8.056239 11.900910 6.662421 8.430116 8.780275 11.395445
[13] 9.614350 7.663801 5.436395 7.062644 12.106677 7.541485
[19] 7.948777 7.837969
> colMax(tmp5)
[1] 467.79696 90.38610 86.44571 87.15592 92.52280 73.85869 90.31495
[8] 96.94169 81.41148 88.70734 85.73961 93.71697 83.00931 85.29839
[15] 78.21948 79.30815 96.43501 76.95462 80.34855 77.49392
> colMin(tmp5)
[1] 62.15951 68.50421 56.06917 54.19318 61.59425 58.59142 60.87064 58.96559
[9] 59.90040 57.48575 56.22519 61.06365 53.16171 58.71082 63.13164 54.53875
[17] 58.60996 55.30451 57.66131 56.43358
>
>
> ### 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] 87.30309 71.80242 70.10956 73.48179 NA 71.34192 71.40206 69.13724
[9] 70.63539 72.11597
> rowSums(tmp5)
[1] 1746.062 1436.048 1402.191 1469.636 NA 1426.838 1428.041 1382.745
[9] 1412.708 1442.319
> rowVars(tmp5)
[1] 8091.49245 121.60206 69.78395 133.15832 108.62654 70.27986
[7] 78.96864 57.90514 63.31700 87.71908
> rowSd(tmp5)
[1] 89.952723 11.027333 8.353679 11.539425 10.422406 8.383308 8.886430
[8] 7.609542 7.957198 9.365847
> rowMax(tmp5)
[1] 467.79696 96.94169 95.44379 96.43501 NA 90.31495 87.15592
[8] 81.19905 83.00931 88.70734
> rowMin(tmp5)
[1] 54.19318 54.53875 60.17084 56.43358 NA 56.06917 55.30451 53.16171
[9] 57.66131 55.69346
>
> colMeans(tmp5)
[1] 113.16801 78.24360 66.90734 73.27172 75.44586 64.53802 75.00622
[8] 72.83571 70.27771 69.51002 73.61553 74.74307 69.03423 71.30910
[15] 70.89458 61.25025 74.98844 67.92566 70.78138 NA
> colSums(tmp5)
[1] 1131.6801 782.4360 669.0734 732.7172 754.4586 645.3802 750.0622
[8] 728.3571 702.7771 695.1002 736.1553 747.4307 690.3423 713.0910
[15] 708.9458 612.5025 749.8844 679.2566 707.8138 NA
> colVars(tmp5)
[1] 15579.06494 47.04360 97.77917 125.07948 67.63751 26.43832
[7] 64.90298 141.63167 44.38786 71.06686 77.09323 129.85616
[13] 92.43572 58.73385 29.55439 49.88095 146.57164 56.87400
[19] 63.18306 NA
> colSd(tmp5)
[1] 124.816125 6.858834 9.888335 11.183894 8.224203 5.141821
[7] 8.056239 11.900910 6.662421 8.430116 8.780275 11.395445
[13] 9.614350 7.663801 5.436395 7.062644 12.106677 7.541485
[19] 7.948777 NA
> colMax(tmp5)
[1] 467.79696 90.38610 86.44571 87.15592 92.52280 73.85869 90.31495
[8] 96.94169 81.41148 88.70734 85.73961 93.71697 83.00931 85.29839
[15] 78.21948 79.30815 96.43501 76.95462 80.34855 NA
> colMin(tmp5)
[1] 62.15951 68.50421 56.06917 54.19318 61.59425 58.59142 60.87064 58.96559
[9] 59.90040 57.48575 56.22519 61.06365 53.16171 58.71082 63.13164 54.53875
[17] 58.60996 55.30451 57.66131 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 467.797
> Min(tmp5,na.rm=TRUE)
[1] 53.16171
> mean(tmp5,na.rm=TRUE)
[1] 72.97824
> Sum(tmp5,na.rm=TRUE)
[1] 14522.67
> Var(tmp5,na.rm=TRUE)
[1] 876.2408
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.30309 71.80242 70.10956 73.48179 72.42531 71.34192 71.40206 69.13724
[9] 70.63539 72.11597
> rowSums(tmp5,na.rm=TRUE)
[1] 1746.062 1436.048 1402.191 1469.636 1376.081 1426.838 1428.041 1382.745
[9] 1412.708 1442.319
> rowVars(tmp5,na.rm=TRUE)
[1] 8091.49245 121.60206 69.78395 133.15832 108.62654 70.27986
[7] 78.96864 57.90514 63.31700 87.71908
> rowSd(tmp5,na.rm=TRUE)
[1] 89.952723 11.027333 8.353679 11.539425 10.422406 8.383308 8.886430
[8] 7.609542 7.957198 9.365847
> rowMax(tmp5,na.rm=TRUE)
[1] 467.79696 96.94169 95.44379 96.43501 93.71697 90.31495 87.15592
[8] 81.19905 83.00931 88.70734
> rowMin(tmp5,na.rm=TRUE)
[1] 54.19318 54.53875 60.17084 56.43358 56.63625 56.06917 55.30451 53.16171
[9] 57.66131 55.69346
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.16801 78.24360 66.90734 73.27172 75.44586 64.53802 75.00622
[8] 72.83571 70.27771 69.51002 73.61553 74.74307 69.03423 71.30910
[15] 70.89458 61.25025 74.98844 67.92566 70.78138 65.02278
> colSums(tmp5,na.rm=TRUE)
[1] 1131.6801 782.4360 669.0734 732.7172 754.4586 645.3802 750.0622
[8] 728.3571 702.7771 695.1002 736.1553 747.4307 690.3423 713.0910
[15] 708.9458 612.5025 749.8844 679.2566 707.8138 585.2050
> colVars(tmp5,na.rm=TRUE)
[1] 15579.06494 47.04360 97.77917 125.07948 67.63751 26.43832
[7] 64.90298 141.63167 44.38786 71.06686 77.09323 129.85616
[13] 92.43572 58.73385 29.55439 49.88095 146.57164 56.87400
[19] 63.18306 51.88040
> colSd(tmp5,na.rm=TRUE)
[1] 124.816125 6.858834 9.888335 11.183894 8.224203 5.141821
[7] 8.056239 11.900910 6.662421 8.430116 8.780275 11.395445
[13] 9.614350 7.663801 5.436395 7.062644 12.106677 7.541485
[19] 7.948777 7.202805
> colMax(tmp5,na.rm=TRUE)
[1] 467.79696 90.38610 86.44571 87.15592 92.52280 73.85869 90.31495
[8] 96.94169 81.41148 88.70734 85.73961 93.71697 83.00931 85.29839
[15] 78.21948 79.30815 96.43501 76.95462 80.34855 77.49392
> colMin(tmp5,na.rm=TRUE)
[1] 62.15951 68.50421 56.06917 54.19318 61.59425 58.59142 60.87064 58.96559
[9] 59.90040 57.48575 56.22519 61.06365 53.16171 58.71082 63.13164 54.53875
[17] 58.60996 55.30451 57.66131 56.43358
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.30309 71.80242 70.10956 73.48179 NaN 71.34192 71.40206 69.13724
[9] 70.63539 72.11597
> rowSums(tmp5,na.rm=TRUE)
[1] 1746.062 1436.048 1402.191 1469.636 0.000 1426.838 1428.041 1382.745
[9] 1412.708 1442.319
> rowVars(tmp5,na.rm=TRUE)
[1] 8091.49245 121.60206 69.78395 133.15832 NA 70.27986
[7] 78.96864 57.90514 63.31700 87.71908
> rowSd(tmp5,na.rm=TRUE)
[1] 89.952723 11.027333 8.353679 11.539425 NA 8.383308 8.886430
[8] 7.609542 7.957198 9.365847
> rowMax(tmp5,na.rm=TRUE)
[1] 467.79696 96.94169 95.44379 96.43501 NA 90.31495 87.15592
[8] 81.19905 83.00931 88.70734
> rowMin(tmp5,na.rm=TRUE)
[1] 54.19318 54.53875 60.17084 56.43358 NA 56.06917 55.30451 53.16171
[9] 57.66131 55.69346
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.83562 77.71044 66.39087 74.59156 75.29337 65.08820 75.05193
[8] 71.25584 70.17468 70.84605 72.26841 72.63485 69.09347 71.13670
[15] 70.73328 61.76291 75.85055 67.27219 69.71836 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1069.5205 699.3940 597.5178 671.3240 677.6403 585.7938 675.4674
[8] 641.3025 631.5721 637.6145 650.4157 653.7137 621.8412 640.2303
[15] 636.5995 555.8662 682.6550 605.4497 627.4653 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17165.07775 49.72619 107.00070 121.11722 75.83060 26.33786
[7] 72.99236 131.25580 49.81691 59.86924 66.31415 96.08692
[13] 103.95071 65.74122 32.95601 53.15926 156.53170 59.17932
[19] 58.36835 NA
> colSd(tmp5,na.rm=TRUE)
[1] 131.015563 7.051680 10.344114 11.005327 8.708076 5.132043
[7] 8.543556 11.456692 7.058110 7.737522 8.143350 9.802394
[13] 10.195622 8.108096 5.740733 7.291040 12.511263 7.692809
[19] 7.639918 NA
> colMax(tmp5,na.rm=TRUE)
[1] 467.79696 90.38610 86.44571 87.15592 92.52280 73.85869 90.31495
[8] 96.94169 81.41148 88.70734 81.00292 87.46622 83.00931 85.29839
[15] 78.21948 79.30815 96.43501 76.95462 78.48373 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 62.93210 68.50421 56.06917 54.19318 61.59425 58.59142 60.87064 58.96559
[9] 59.90040 60.86350 56.22519 61.06365 53.16171 58.71082 63.13164 54.53875
[17] 58.60996 55.30451 57.66131 Inf
>
>
>
>
> 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] 202.5495 172.6320 120.8239 342.8157 260.6911 141.3241 220.3597 229.2783
[9] 175.9271 237.8820
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 202.5495 172.6320 120.8239 342.8157 260.6911 141.3241 220.3597 229.2783
[9] 175.9271 237.8820
>
>
>
> 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 0.000000e+00 -8.526513e-14 -8.526513e-14 -5.684342e-14
[6] -1.136868e-13 -1.136868e-13 -2.842171e-14 -5.684342e-14 -3.410605e-13
[11] 5.684342e-14 0.000000e+00 -5.684342e-14 0.000000e+00 -1.136868e-13
[16] -2.842171e-13 5.684342e-14 0.000000e+00 -2.131628e-14 1.421085e-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)
+ }
7 19
1 19
8 2
1 2
10 19
9 7
9 10
7 7
7 3
6 15
1 16
8 19
10 7
8 14
7 10
2 13
4 8
10 1
6 5
3 2
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] 2.568278
> Min(tmp)
[1] -2.703916
> mean(tmp)
[1] -0.08147798
> Sum(tmp)
[1] -8.147798
> Var(tmp)
[1] 1.017303
>
> rowMeans(tmp)
[1] -0.08147798
> rowSums(tmp)
[1] -8.147798
> rowVars(tmp)
[1] 1.017303
> rowSd(tmp)
[1] 1.008615
> rowMax(tmp)
[1] 2.568278
> rowMin(tmp)
[1] -2.703916
>
> colMeans(tmp)
[1] 0.03323449 0.14463382 1.23034078 -0.32691146 0.51770957 -1.22680479
[7] 0.41916124 -0.36587853 -1.14813087 1.02641964 -0.58966770 -0.71564053
[13] -0.44232675 0.05576963 -0.41639459 0.57659546 -0.63933989 -0.94695850
[19] 0.34475269 -0.44089898 1.48258928 0.78050863 0.33429996 -0.97914344
[25] 1.38999400 -1.21828573 0.27980125 0.74308001 -1.59089064 -1.15147675
[31] 0.37194112 0.95489662 -0.28881869 0.03959818 0.13718343 2.26964581
[37] 0.84422524 -0.27682115 0.54048771 -0.32929379 0.49764303 -0.44005484
[43] -0.33725606 -0.62406909 -0.28184994 -1.02221434 -0.62400865 0.93606754
[49] 0.59226466 -0.98876244 -0.31382444 0.40153143 0.11869658 -1.60747327
[55] -0.69740519 1.49505195 -0.78180740 -0.39501682 -0.69121149 -1.69386782
[61] 1.40462589 -2.05380755 -2.04284520 -0.18713806 1.21954582 0.10926703
[67] -0.35927798 -2.70391591 0.96299589 0.94738322 -0.21653567 -1.36510281
[73] 0.30269123 -1.49777604 -0.51421292 0.64517040 -2.36509202 -0.23513468
[79] 2.56827828 0.19868970 1.25916873 -0.42589116 0.56848401 0.84232821
[85] -0.35942499 0.35672055 -0.65217648 0.60695517 2.04433513 -0.81166024
[91] 1.13951593 -0.52701538 0.30089956 -1.37475201 -1.14361966 -0.69080574
[97] 0.75599792 1.95545255 -1.09756886 -0.67816886
> colSums(tmp)
[1] 0.03323449 0.14463382 1.23034078 -0.32691146 0.51770957 -1.22680479
[7] 0.41916124 -0.36587853 -1.14813087 1.02641964 -0.58966770 -0.71564053
[13] -0.44232675 0.05576963 -0.41639459 0.57659546 -0.63933989 -0.94695850
[19] 0.34475269 -0.44089898 1.48258928 0.78050863 0.33429996 -0.97914344
[25] 1.38999400 -1.21828573 0.27980125 0.74308001 -1.59089064 -1.15147675
[31] 0.37194112 0.95489662 -0.28881869 0.03959818 0.13718343 2.26964581
[37] 0.84422524 -0.27682115 0.54048771 -0.32929379 0.49764303 -0.44005484
[43] -0.33725606 -0.62406909 -0.28184994 -1.02221434 -0.62400865 0.93606754
[49] 0.59226466 -0.98876244 -0.31382444 0.40153143 0.11869658 -1.60747327
[55] -0.69740519 1.49505195 -0.78180740 -0.39501682 -0.69121149 -1.69386782
[61] 1.40462589 -2.05380755 -2.04284520 -0.18713806 1.21954582 0.10926703
[67] -0.35927798 -2.70391591 0.96299589 0.94738322 -0.21653567 -1.36510281
[73] 0.30269123 -1.49777604 -0.51421292 0.64517040 -2.36509202 -0.23513468
[79] 2.56827828 0.19868970 1.25916873 -0.42589116 0.56848401 0.84232821
[85] -0.35942499 0.35672055 -0.65217648 0.60695517 2.04433513 -0.81166024
[91] 1.13951593 -0.52701538 0.30089956 -1.37475201 -1.14361966 -0.69080574
[97] 0.75599792 1.95545255 -1.09756886 -0.67816886
> 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] 0.03323449 0.14463382 1.23034078 -0.32691146 0.51770957 -1.22680479
[7] 0.41916124 -0.36587853 -1.14813087 1.02641964 -0.58966770 -0.71564053
[13] -0.44232675 0.05576963 -0.41639459 0.57659546 -0.63933989 -0.94695850
[19] 0.34475269 -0.44089898 1.48258928 0.78050863 0.33429996 -0.97914344
[25] 1.38999400 -1.21828573 0.27980125 0.74308001 -1.59089064 -1.15147675
[31] 0.37194112 0.95489662 -0.28881869 0.03959818 0.13718343 2.26964581
[37] 0.84422524 -0.27682115 0.54048771 -0.32929379 0.49764303 -0.44005484
[43] -0.33725606 -0.62406909 -0.28184994 -1.02221434 -0.62400865 0.93606754
[49] 0.59226466 -0.98876244 -0.31382444 0.40153143 0.11869658 -1.60747327
[55] -0.69740519 1.49505195 -0.78180740 -0.39501682 -0.69121149 -1.69386782
[61] 1.40462589 -2.05380755 -2.04284520 -0.18713806 1.21954582 0.10926703
[67] -0.35927798 -2.70391591 0.96299589 0.94738322 -0.21653567 -1.36510281
[73] 0.30269123 -1.49777604 -0.51421292 0.64517040 -2.36509202 -0.23513468
[79] 2.56827828 0.19868970 1.25916873 -0.42589116 0.56848401 0.84232821
[85] -0.35942499 0.35672055 -0.65217648 0.60695517 2.04433513 -0.81166024
[91] 1.13951593 -0.52701538 0.30089956 -1.37475201 -1.14361966 -0.69080574
[97] 0.75599792 1.95545255 -1.09756886 -0.67816886
> colMin(tmp)
[1] 0.03323449 0.14463382 1.23034078 -0.32691146 0.51770957 -1.22680479
[7] 0.41916124 -0.36587853 -1.14813087 1.02641964 -0.58966770 -0.71564053
[13] -0.44232675 0.05576963 -0.41639459 0.57659546 -0.63933989 -0.94695850
[19] 0.34475269 -0.44089898 1.48258928 0.78050863 0.33429996 -0.97914344
[25] 1.38999400 -1.21828573 0.27980125 0.74308001 -1.59089064 -1.15147675
[31] 0.37194112 0.95489662 -0.28881869 0.03959818 0.13718343 2.26964581
[37] 0.84422524 -0.27682115 0.54048771 -0.32929379 0.49764303 -0.44005484
[43] -0.33725606 -0.62406909 -0.28184994 -1.02221434 -0.62400865 0.93606754
[49] 0.59226466 -0.98876244 -0.31382444 0.40153143 0.11869658 -1.60747327
[55] -0.69740519 1.49505195 -0.78180740 -0.39501682 -0.69121149 -1.69386782
[61] 1.40462589 -2.05380755 -2.04284520 -0.18713806 1.21954582 0.10926703
[67] -0.35927798 -2.70391591 0.96299589 0.94738322 -0.21653567 -1.36510281
[73] 0.30269123 -1.49777604 -0.51421292 0.64517040 -2.36509202 -0.23513468
[79] 2.56827828 0.19868970 1.25916873 -0.42589116 0.56848401 0.84232821
[85] -0.35942499 0.35672055 -0.65217648 0.60695517 2.04433513 -0.81166024
[91] 1.13951593 -0.52701538 0.30089956 -1.37475201 -1.14361966 -0.69080574
[97] 0.75599792 1.95545255 -1.09756886 -0.67816886
> colMedians(tmp)
[1] 0.03323449 0.14463382 1.23034078 -0.32691146 0.51770957 -1.22680479
[7] 0.41916124 -0.36587853 -1.14813087 1.02641964 -0.58966770 -0.71564053
[13] -0.44232675 0.05576963 -0.41639459 0.57659546 -0.63933989 -0.94695850
[19] 0.34475269 -0.44089898 1.48258928 0.78050863 0.33429996 -0.97914344
[25] 1.38999400 -1.21828573 0.27980125 0.74308001 -1.59089064 -1.15147675
[31] 0.37194112 0.95489662 -0.28881869 0.03959818 0.13718343 2.26964581
[37] 0.84422524 -0.27682115 0.54048771 -0.32929379 0.49764303 -0.44005484
[43] -0.33725606 -0.62406909 -0.28184994 -1.02221434 -0.62400865 0.93606754
[49] 0.59226466 -0.98876244 -0.31382444 0.40153143 0.11869658 -1.60747327
[55] -0.69740519 1.49505195 -0.78180740 -0.39501682 -0.69121149 -1.69386782
[61] 1.40462589 -2.05380755 -2.04284520 -0.18713806 1.21954582 0.10926703
[67] -0.35927798 -2.70391591 0.96299589 0.94738322 -0.21653567 -1.36510281
[73] 0.30269123 -1.49777604 -0.51421292 0.64517040 -2.36509202 -0.23513468
[79] 2.56827828 0.19868970 1.25916873 -0.42589116 0.56848401 0.84232821
[85] -0.35942499 0.35672055 -0.65217648 0.60695517 2.04433513 -0.81166024
[91] 1.13951593 -0.52701538 0.30089956 -1.37475201 -1.14361966 -0.69080574
[97] 0.75599792 1.95545255 -1.09756886 -0.67816886
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.03323449 0.1446338 1.230341 -0.3269115 0.5177096 -1.226805 0.4191612
[2,] 0.03323449 0.1446338 1.230341 -0.3269115 0.5177096 -1.226805 0.4191612
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3658785 -1.148131 1.02642 -0.5896677 -0.7156405 -0.4423267 0.05576963
[2,] -0.3658785 -1.148131 1.02642 -0.5896677 -0.7156405 -0.4423267 0.05576963
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.4163946 0.5765955 -0.6393399 -0.9469585 0.3447527 -0.440899 1.482589
[2,] -0.4163946 0.5765955 -0.6393399 -0.9469585 0.3447527 -0.440899 1.482589
[,22] [,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] 0.7805086 0.3343 -0.9791434 1.389994 -1.218286 0.2798013 0.74308 -1.590891
[2,] 0.7805086 0.3343 -0.9791434 1.389994 -1.218286 0.2798013 0.74308 -1.590891
[,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] -1.151477 0.3719411 0.9548966 -0.2888187 0.03959818 0.1371834 2.269646
[2,] -1.151477 0.3719411 0.9548966 -0.2888187 0.03959818 0.1371834 2.269646
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 0.8442252 -0.2768211 0.5404877 -0.3292938 0.497643 -0.4400548 -0.3372561
[2,] 0.8442252 -0.2768211 0.5404877 -0.3292938 0.497643 -0.4400548 -0.3372561
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] -0.6240691 -0.2818499 -1.022214 -0.6240087 0.9360675 0.5922647 -0.9887624
[2,] -0.6240691 -0.2818499 -1.022214 -0.6240087 0.9360675 0.5922647 -0.9887624
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] -0.3138244 0.4015314 0.1186966 -1.607473 -0.6974052 1.495052 -0.7818074
[2,] -0.3138244 0.4015314 0.1186966 -1.607473 -0.6974052 1.495052 -0.7818074
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] -0.3950168 -0.6912115 -1.693868 1.404626 -2.053808 -2.042845 -0.1871381
[2,] -0.3950168 -0.6912115 -1.693868 1.404626 -2.053808 -2.042845 -0.1871381
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] 1.219546 0.109267 -0.359278 -2.703916 0.9629959 0.9473832 -0.2165357
[2,] 1.219546 0.109267 -0.359278 -2.703916 0.9629959 0.9473832 -0.2165357
[,72] [,73] [,74] [,75] [,76] [,77] [,78]
[1,] -1.365103 0.3026912 -1.497776 -0.5142129 0.6451704 -2.365092 -0.2351347
[2,] -1.365103 0.3026912 -1.497776 -0.5142129 0.6451704 -2.365092 -0.2351347
[,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] 2.568278 0.1986897 1.259169 -0.4258912 0.568484 0.8423282 -0.359425
[2,] 2.568278 0.1986897 1.259169 -0.4258912 0.568484 0.8423282 -0.359425
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] 0.3567205 -0.6521765 0.6069552 2.044335 -0.8116602 1.139516 -0.5270154
[2,] 0.3567205 -0.6521765 0.6069552 2.044335 -0.8116602 1.139516 -0.5270154
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] 0.3008996 -1.374752 -1.14362 -0.6908057 0.7559979 1.955453 -1.097569
[2,] 0.3008996 -1.374752 -1.14362 -0.6908057 0.7559979 1.955453 -1.097569
[,100]
[1,] -0.6781689
[2,] -0.6781689
>
>
> Max(tmp2)
[1] 2.505039
> Min(tmp2)
[1] -2.551236
> mean(tmp2)
[1] 0.05662628
> Sum(tmp2)
[1] 5.662628
> Var(tmp2)
[1] 0.9836463
>
> rowMeans(tmp2)
[1] 1.200568809 -0.551678356 0.870599514 -1.892060008 1.663016806
[6] 0.371096666 0.786264938 0.610086518 -1.150238253 0.754964229
[11] 0.903964336 -0.040051584 1.419290965 0.119725410 -0.294286649
[16] 0.395277582 -1.440369345 0.452767951 1.097008139 -0.408377572
[21] 0.450149856 -0.951230385 1.422382412 1.273621586 0.806188982
[26] -0.939478758 -1.289486108 0.258579285 0.393355969 -1.096841719
[31] 0.540231555 0.007371603 -1.017249971 0.797606646 -0.461850318
[36] -1.004977080 2.505038930 -0.266544458 1.810533452 1.147226685
[41] 0.329106827 0.386373890 0.576095876 0.954803954 0.023839883
[46] -0.912670378 0.547793564 -0.573678373 0.345394174 1.069233073
[51] 0.158446692 -0.934127471 -1.117936352 -0.839977599 0.159063858
[56] 0.081390517 -1.964115026 0.657716115 -0.580331000 -1.826859797
[61] -0.577294692 -1.484803092 -0.117148793 -0.387579858 -1.816624874
[66] 0.778805260 -0.400343672 0.155027746 0.637338341 0.304307786
[71] -2.551235933 0.491077301 -0.632118068 1.268049867 1.229621898
[76] -1.101152136 -1.197080474 1.238885505 1.788772838 -1.423498570
[81] -0.516375766 0.694923983 0.529102332 1.897339231 0.639236843
[86] -0.630266876 -0.024895945 -1.313103483 0.291374365 1.074882039
[91] -0.394960331 -0.595189060 0.172102244 -0.894824233 1.486376763
[96] 0.090431105 -0.006333834 1.175774982 -0.325869910 0.318136925
> rowSums(tmp2)
[1] 1.200568809 -0.551678356 0.870599514 -1.892060008 1.663016806
[6] 0.371096666 0.786264938 0.610086518 -1.150238253 0.754964229
[11] 0.903964336 -0.040051584 1.419290965 0.119725410 -0.294286649
[16] 0.395277582 -1.440369345 0.452767951 1.097008139 -0.408377572
[21] 0.450149856 -0.951230385 1.422382412 1.273621586 0.806188982
[26] -0.939478758 -1.289486108 0.258579285 0.393355969 -1.096841719
[31] 0.540231555 0.007371603 -1.017249971 0.797606646 -0.461850318
[36] -1.004977080 2.505038930 -0.266544458 1.810533452 1.147226685
[41] 0.329106827 0.386373890 0.576095876 0.954803954 0.023839883
[46] -0.912670378 0.547793564 -0.573678373 0.345394174 1.069233073
[51] 0.158446692 -0.934127471 -1.117936352 -0.839977599 0.159063858
[56] 0.081390517 -1.964115026 0.657716115 -0.580331000 -1.826859797
[61] -0.577294692 -1.484803092 -0.117148793 -0.387579858 -1.816624874
[66] 0.778805260 -0.400343672 0.155027746 0.637338341 0.304307786
[71] -2.551235933 0.491077301 -0.632118068 1.268049867 1.229621898
[76] -1.101152136 -1.197080474 1.238885505 1.788772838 -1.423498570
[81] -0.516375766 0.694923983 0.529102332 1.897339231 0.639236843
[86] -0.630266876 -0.024895945 -1.313103483 0.291374365 1.074882039
[91] -0.394960331 -0.595189060 0.172102244 -0.894824233 1.486376763
[96] 0.090431105 -0.006333834 1.175774982 -0.325869910 0.318136925
> 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] 1.200568809 -0.551678356 0.870599514 -1.892060008 1.663016806
[6] 0.371096666 0.786264938 0.610086518 -1.150238253 0.754964229
[11] 0.903964336 -0.040051584 1.419290965 0.119725410 -0.294286649
[16] 0.395277582 -1.440369345 0.452767951 1.097008139 -0.408377572
[21] 0.450149856 -0.951230385 1.422382412 1.273621586 0.806188982
[26] -0.939478758 -1.289486108 0.258579285 0.393355969 -1.096841719
[31] 0.540231555 0.007371603 -1.017249971 0.797606646 -0.461850318
[36] -1.004977080 2.505038930 -0.266544458 1.810533452 1.147226685
[41] 0.329106827 0.386373890 0.576095876 0.954803954 0.023839883
[46] -0.912670378 0.547793564 -0.573678373 0.345394174 1.069233073
[51] 0.158446692 -0.934127471 -1.117936352 -0.839977599 0.159063858
[56] 0.081390517 -1.964115026 0.657716115 -0.580331000 -1.826859797
[61] -0.577294692 -1.484803092 -0.117148793 -0.387579858 -1.816624874
[66] 0.778805260 -0.400343672 0.155027746 0.637338341 0.304307786
[71] -2.551235933 0.491077301 -0.632118068 1.268049867 1.229621898
[76] -1.101152136 -1.197080474 1.238885505 1.788772838 -1.423498570
[81] -0.516375766 0.694923983 0.529102332 1.897339231 0.639236843
[86] -0.630266876 -0.024895945 -1.313103483 0.291374365 1.074882039
[91] -0.394960331 -0.595189060 0.172102244 -0.894824233 1.486376763
[96] 0.090431105 -0.006333834 1.175774982 -0.325869910 0.318136925
> rowMin(tmp2)
[1] 1.200568809 -0.551678356 0.870599514 -1.892060008 1.663016806
[6] 0.371096666 0.786264938 0.610086518 -1.150238253 0.754964229
[11] 0.903964336 -0.040051584 1.419290965 0.119725410 -0.294286649
[16] 0.395277582 -1.440369345 0.452767951 1.097008139 -0.408377572
[21] 0.450149856 -0.951230385 1.422382412 1.273621586 0.806188982
[26] -0.939478758 -1.289486108 0.258579285 0.393355969 -1.096841719
[31] 0.540231555 0.007371603 -1.017249971 0.797606646 -0.461850318
[36] -1.004977080 2.505038930 -0.266544458 1.810533452 1.147226685
[41] 0.329106827 0.386373890 0.576095876 0.954803954 0.023839883
[46] -0.912670378 0.547793564 -0.573678373 0.345394174 1.069233073
[51] 0.158446692 -0.934127471 -1.117936352 -0.839977599 0.159063858
[56] 0.081390517 -1.964115026 0.657716115 -0.580331000 -1.826859797
[61] -0.577294692 -1.484803092 -0.117148793 -0.387579858 -1.816624874
[66] 0.778805260 -0.400343672 0.155027746 0.637338341 0.304307786
[71] -2.551235933 0.491077301 -0.632118068 1.268049867 1.229621898
[76] -1.101152136 -1.197080474 1.238885505 1.788772838 -1.423498570
[81] -0.516375766 0.694923983 0.529102332 1.897339231 0.639236843
[86] -0.630266876 -0.024895945 -1.313103483 0.291374365 1.074882039
[91] -0.394960331 -0.595189060 0.172102244 -0.894824233 1.486376763
[96] 0.090431105 -0.006333834 1.175774982 -0.325869910 0.318136925
>
> colMeans(tmp2)
[1] 0.05662628
> colSums(tmp2)
[1] 5.662628
> colVars(tmp2)
[1] 0.9836463
> colSd(tmp2)
[1] 0.9917894
> colMax(tmp2)
[1] 2.505039
> colMin(tmp2)
[1] -2.551236
> colMedians(tmp2)
[1] 0.1587553
> colRanges(tmp2)
[,1]
[1,] -2.551236
[2,] 2.505039
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.2667437 2.1630281 2.7619782 0.9180075 4.4737191 0.2485388
[7] -3.1413688 -0.4118114 -4.4940541 0.8770260
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7167488
[2,] -0.4922720
[3,] 0.1605754
[4,] 0.8699568
[5,] 2.0142164
>
> rowApply(tmp,sum)
[1] 2.9796863 -1.3027685 0.3462088 -0.5437273 -0.4072689 2.9685571
[7] 0.8287750 -2.4469197 5.2263754 -2.9871110
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 3 8 5 4 6 10 1 9 10
[2,] 10 8 7 6 10 2 6 10 5 1
[3,] 7 9 10 3 9 1 5 7 10 3
[4,] 9 4 5 4 1 9 9 6 4 4
[5,] 3 10 6 7 7 7 7 8 8 5
[6,] 4 6 3 10 8 10 8 9 1 2
[7,] 5 2 9 1 3 4 3 2 3 6
[8,] 6 7 2 9 2 3 4 3 7 8
[9,] 8 1 1 2 6 5 1 4 2 9
[10,] 2 5 4 8 5 8 2 5 6 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.1236511 -0.8824673 1.7312796 1.1049001 2.9980738 0.3849813
[7] 0.5145946 -1.5271609 -3.2954353 3.0360268 -1.1731496 -1.1861567
[13] -1.3796336 2.3608836 -2.4646965 -0.5244911 -3.1438824 -1.1171619
[19] -0.4424304 -1.2828715
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.46366093
[2,] -0.42434376
[3,] 0.08566395
[4,] 0.81367020
[5,] 1.11232165
>
> rowApply(tmp,sum)
[1] -1.588097 -1.343003 2.723310 -4.190575 -1.766782
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 10 17 18 10
[2,] 16 13 4 4 12
[3,] 9 16 11 13 16
[4,] 5 15 5 20 14
[5,] 10 19 18 9 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.46366093 0.87549900 0.02699483 -0.7259385 0.1534252 1.08375398
[2,] -0.42434376 -0.07912156 0.72973873 0.7206667 1.1350984 0.84413283
[3,] 1.11232165 -0.82339587 0.18405543 -0.7570154 1.4548834 -0.03156602
[4,] 0.81367020 -1.15100381 0.22518258 1.5179601 -0.4580186 -0.27203594
[5,] 0.08566395 0.29555495 0.56530799 0.3492273 0.7126853 -1.23930358
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.4478227 0.6449802 0.5250325 1.4617429 0.372315826 -1.6811802
[2,] 0.9892658 -0.4313654 -0.4262559 -1.8077504 -0.441597707 -1.3173086
[3,] 2.5109517 -0.4009895 -1.1807309 0.9935841 -1.890470984 2.3211149
[4,] -0.6740711 -1.6817054 -1.6349360 1.0081232 0.784811781 -0.8031775
[5,] -1.8637292 0.3419191 -0.5785450 1.3803270 0.001791449 0.2943947
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.1545331 1.1484107 -0.4831509 0.297944603 -2.1861494 0.9963525
[2,] -0.2207777 -0.3459035 -0.8313460 -1.184560899 -0.4487544 -0.6952714
[3,] 0.4812334 0.3823998 -0.5403463 0.910820581 -1.8152528 -0.5141692
[4,] -1.1540626 0.4113040 -1.0626770 -0.006219706 0.3623559 0.7185875
[5,] -0.6405598 0.7646725 0.4528236 -0.542475719 0.9439183 -1.6226614
[,19] [,20]
[1,] -1.6535110 -0.6876685
[2,] 2.3914226 0.5010295
[3,] 0.7946693 -0.4687871
[4,] -0.6882139 -0.4464491
[5,] -1.2867974 -0.1809962
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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 0.1455789 -0.5800605 0.3101277 -1.780399 1.059234 1.376793 1.467429
col8 col9 col10 col11 col12 col13 col14
row1 0.1939619 2.463398 0.7042621 0.5321449 -0.08630906 0.5681436 1.901193
col15 col16 col17 col18 col19 col20
row1 0.1697285 -0.2395976 -0.3733492 -1.329782 0.145084 0.7653684
> tmp[,"col10"]
col10
row1 0.7042621
row2 -0.9971576
row3 -0.3368011
row4 -1.7153439
row5 1.0944258
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.1455789 -0.5800605 0.3101277 -1.780399 1.059234 1.376793 1.4674288
row5 -0.1248405 1.3690270 -0.1711670 -1.904556 -0.922453 -1.036582 0.1749473
col8 col9 col10 col11 col12 col13
row1 0.19396192 2.46339843 0.7042621 0.5321449 -0.08630906 0.5681436
row5 0.02168566 -0.03306341 1.0944258 -0.3140946 1.10629759 -0.8284332
col14 col15 col16 col17 col18 col19 col20
row1 1.901193 0.1697285 -0.2395976 -0.3733492 -1.3297823 0.1450840 0.7653684
row5 0.346496 -1.2812121 0.9264688 1.7747859 -0.5342512 0.6142905 -1.3998392
> tmp[,c("col6","col20")]
col6 col20
row1 1.37679276 0.7653684
row2 0.10066516 -0.4621124
row3 -0.66501945 -0.2590081
row4 -0.02111383 0.2294264
row5 -1.03658243 -1.3998392
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.376793 0.7653684
row5 -1.036582 -1.3998392
>
>
>
>
> 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 49.7843 48.61557 48.43711 49.86045 50.11527 105.43 49.98439 50.14392
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.27931 49.51108 49.12514 50.1857 50.30955 47.68427 48.87473 48.81595
col17 col18 col19 col20
row1 47.84374 49.93119 49.28298 105.4699
> tmp[,"col10"]
col10
row1 49.51108
row2 31.82891
row3 30.99464
row4 29.10397
row5 50.43730
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.78430 48.61557 48.43711 49.86045 50.11527 105.4300 49.98439 50.14392
row5 50.59514 51.63356 51.39106 51.05550 51.02286 106.1404 48.77288 51.91647
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.27931 49.51108 49.12514 50.18570 50.30955 47.68427 48.87473 48.81595
row5 50.62299 50.43730 48.46900 49.21713 50.49400 50.00986 50.75846 50.15732
col17 col18 col19 col20
row1 47.84374 49.93119 49.28298 105.4699
row5 51.39880 48.99719 49.56583 106.9813
> tmp[,c("col6","col20")]
col6 col20
row1 105.43000 105.46994
row2 75.42812 74.59760
row3 75.43675 75.09124
row4 76.04681 75.41533
row5 106.14037 106.98135
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4300 105.4699
row5 106.1404 106.9813
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4300 105.4699
row5 106.1404 106.9813
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.2356255
[2,] -1.0113597
[3,] -1.3545247
[4,] 0.1312242
[5,] -0.6673746
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.6006721 0.09787989
[2,] -0.2599604 -1.37586078
[3,] -1.2213511 0.67197856
[4,] -0.5200030 0.43203451
[5,] -0.7428715 0.64240922
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.8053474 0.9407064
[2,] 1.0464735 -0.4874619
[3,] -0.2160524 0.6604944
[4,] 0.6028660 0.2766408
[5,] 1.1198610 -0.9472904
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.8053474
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.8053474
[2,] 1.0464735
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.3229624 -1.8418744 -0.3191844 0.4564585 0.08839033 -0.6064936
row1 0.4362268 0.5581543 0.6976593 -0.7479290 1.32888810 0.2794560
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.979514 0.6609832 1.5591540 -1.4063098 0.1632139 -0.93780818 0.5727266
row1 1.288317 -0.8810342 -0.5324319 -0.8118171 2.2234172 0.07765901 0.1457800
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.009968763 -0.8092478 2.3903957 -1.155683 -1.990228 -0.2262833
row1 1.090036594 -0.6584661 -0.4800554 -1.104331 1.121634 -0.3233923
[,20]
row3 -0.02287181
row1 -1.27626772
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.07533508 0.01643537 -1.368188 0.1816378 0.3099384 -1.10482 1.656145
[,8] [,9] [,10]
row2 -0.1510324 0.7453359 -0.2253805
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2408349 -0.7278865 -1.79315 -0.3314085 -2.295102 1.136149 2.19462
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.670131 0.2177701 2.130865 -0.1546007 -1.417523 -0.04360703 0.5293652
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.01488401 -1.373301 -1.762504 0.3304948 0.3844186 -0.2259935
>
>
> 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: 0x5fad77e9c4e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d82bef6155"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d820c99d2d"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d822642b48"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d8691e5261"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d8748e7af6"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d83790aa89"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d8324f4f58"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d841c018ff"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d831204144"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d83c62dc84"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d86b6020ec"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d8311a9050"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d874b68c46"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d8d75d8b3"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1fb3d87d79d3d7"
>
>
> ### 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: 0x5fad7757da40>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5fad7757da40>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5fad7757da40>
> rowMedians(tmp)
[1] 0.4298792793 0.4841097805 -0.0084987892 -0.3053688777 0.3174583860
[6] -0.3828305113 0.1219802867 0.6062573276 0.0407894646 -0.4456377035
[11] 0.4114905759 0.0325147995 -0.4782145697 0.3870749492 0.2480076332
[16] -0.3224191083 0.2907469191 -0.2272366567 0.3625491080 0.4475011211
[21] 0.3109829161 0.1732825428 -0.1051360577 -0.3461294029 -0.1443282480
[26] 0.3143610685 -0.1748360667 0.2263194579 -0.1547649115 0.0216744165
[31] 0.3808636972 0.5923143372 -0.0870951409 -0.3416851421 0.5385865585
[36] -0.0210927144 0.4495841914 -0.0430269406 0.1030511977 -0.6161596841
[41] 0.2882481347 0.1277051582 0.3051621403 0.2032233146 0.1678084546
[46] 0.3903269120 0.3496773090 -0.2212242901 0.1528982581 -0.2957829925
[51] 0.0873989070 0.2158733608 -0.0080327255 -0.4488986806 0.3566569559
[56] 0.3902771749 -0.1496674564 0.0370007730 -0.2344958920 -0.0190470253
[61] -0.2854942093 0.0930302293 -0.3073111639 0.0319166965 0.0923078496
[66] 0.3217357278 -0.1990257429 0.3816107168 0.3442257995 0.4466994330
[71] 0.3683947277 -0.1440543492 0.0153302405 -0.1271745962 0.0003915543
[76] 0.1512360413 0.0594413604 -0.6286619244 -0.2240575317 0.0373025275
[81] 0.4327775098 -0.1390016935 0.3517887676 -0.1477606210 0.1744875917
[86] 0.1219191608 0.2478068542 -0.2959137123 -0.6586810055 0.0068083821
[91] -0.2402251563 0.1999473079 0.3505452089 -0.2702949845 -0.2999841299
[96] -0.1833597659 0.0947559462 0.2002626065 -0.1777192177 -0.0130230908
[101] 0.0148361847 -0.2930041583 0.2126828531 0.1308400668 0.0989340559
[106] 0.1824366310 0.4711500992 -0.0332857503 -0.2212661092 0.4672083626
[111] -0.3354307734 -0.1576723934 -0.1370355420 0.1328133976 0.1410946037
[116] -0.1655569098 -0.0955871080 -0.0386837101 0.2803675698 0.1805214754
[121] -0.2504304322 -0.4143397180 0.0879972977 -0.3187478588 0.3662441309
[126] -0.1187477506 -0.2392604823 -0.7664683088 -0.2304126443 -0.3695421714
[131] -0.1205500518 -0.2552668448 -0.2339337662 -0.2735720792 0.2221236882
[136] -0.1703471062 0.5867382945 -0.0361881091 0.2522358252 0.0305094169
[141] -0.0248337430 0.2164768083 -0.3616267632 -0.1440940939 0.3455815798
[146] 0.1002349387 -0.3754834971 0.0200394510 0.1940700332 -0.1454285498
[151] -0.3070256397 0.0015460163 -0.0412934225 0.0187615269 0.4431829097
[156] -0.3851552386 0.3515530578 0.4900041311 -0.0554879234 -0.0568382015
[161] -0.0445767627 -0.0552580876 -0.1269199837 0.1439932850 -0.2535939161
[166] 0.6277895531 0.5220915236 -0.1367713823 -0.1941933449 -0.4915122985
[171] 0.0330521636 0.0553559112 0.1165644098 0.1467661790 -0.1245037559
[176] -0.4725922063 0.5510546050 0.1349131338 0.0101043484 0.3270258670
[181] 0.4812453484 0.0207842400 -0.2722041644 -0.0007474017 -0.3247485125
[186] -0.3962629553 -0.3677305237 0.3958688611 0.4051181569 -0.1875518301
[191] -0.5587700358 0.0796455072 0.9805461277 0.4920919890 0.1581051404
[196] -0.8151708623 -0.2592681976 0.2868966432 0.0141479678 0.0122698253
[201] 0.2023626457 0.3967623537 -0.0812694423 -0.2199266741 0.0256772291
[206] -0.0815223838 -0.3114483884 0.5131889238 -0.2397256107 0.0396133467
[211] -0.2564784118 -0.5658307426 0.0623395449 -0.3712385155 0.3699285980
[216] -0.5532722080 0.3522446890 -0.3809115004 0.2076531039 -0.2895463394
[221] 0.2083188043 -0.2953264095 0.1223109213 -0.1233906934 -0.0778942189
[226] 0.4100655788 -0.3306323548 -0.0500189373 0.1427180881 0.1498522920
>
> proc.time()
user system elapsed
1.246 0.657 1.892
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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: 0x5fa2ddaab370>
> .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: 0x5fa2ddaab370>
> .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: 0x5fa2ddaab370>
> .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: 0x5fa2ddaab370>
> 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: 0x5fa2dda931c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2dda931c0>
> .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: 0x5fa2dda931c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2dda931c0>
> .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: 0x5fa2dda931c0>
> 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: 0x5fa2ddd76120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2ddd76120>
> .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: 0x5fa2ddd76120>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5fa2ddd76120>
> .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: 0x5fa2ddd76120>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5fa2ddd76120>
> .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: 0x5fa2ddd76120>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5fa2ddd76120>
> .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: 0x5fa2ddd76120>
> 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: 0x5fa2dcac6390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5fa2dcac6390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2dcac6390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2dcac6390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1fb6593a5d5867" "BufferedMatrixFile1fb65941f270b1"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1fb6593a5d5867" "BufferedMatrixFile1fb65941f270b1"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2dc9bd3d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2dc9bd3d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5fa2dc9bd3d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5fa2dc9bd3d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5fa2dc9bd3d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5fa2dc9bd3d0>
> .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: 0x5fa2de4f2fa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5fa2de4f2fa0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5fa2de4f2fa0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5fa2de4f2fa0>
> 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: 0x5fa2dcccaff0>
> .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: 0x5fa2dcccaff0>
> rm(P)
>
> proc.time()
user system elapsed
0.250 0.055 0.294
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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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
0.252 0.036 0.278