Ben Bolstad
| Snapshot Date: 2026-01-08 13:45 -0500 (Thu, 08 Jan 2026) |
| 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 2026-01-12 11:58 -0500 (Mon, 12 Jan 2026).
| 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 |
| 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 | | ||||||||
| 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: 2026-01-08 21:43:30 -0500 (Thu, 08 Jan 2026) |
| EndedAt: 2026-01-08 21:43:54 -0500 (Thu, 08 Jan 2026) |
| 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
###
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* 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
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###
### 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
0.257 0.038 0.284
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 Jan 8 21:43:45 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Jan 8 21:43:45 2026"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x58d9482d1370>
>
>
>
> 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 Jan 8 21:43:45 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Jan 8 21:43:45 2026"
>
> ColMode(tmp2)
<pointer: 0x58d9482d1370>
>
>
>
> ### 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,] 1.001621e+02 -0.09420226 1.6817454 -0.3288349
[2,] 5.642991e-01 -0.56907988 -0.0963382 -1.2977858
[3,] 2.474022e-02 1.10363632 -1.6215891 -0.1510085
[4,] 4.419685e-03 0.45138679 0.9738763 1.5690510
> 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,] 1.001621e+02 0.09420226 1.6817454 0.3288349
[2,] 5.642991e-01 0.56907988 0.0963382 1.2977858
[3,] 2.474022e-02 1.10363632 1.6215891 0.1510085
[4,] 4.419685e-03 0.45138679 0.9738763 1.5690510
> 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,] 10.00810370 0.3069239 1.2968213 0.5734413
[2,] 0.75119847 0.7543738 0.3103840 1.1392040
[3,] 0.15729023 1.0505410 1.2734163 0.3885982
[4,] 0.06648071 0.6718533 0.9868517 1.2526177
>
> 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,] 225.24318 28.16344 39.64996 31.06325
[2,] 33.07628 33.11282 28.20018 37.68983
[3,] 26.59764 36.60905 39.35575 29.03699
[4,] 25.66923 32.16992 35.84239 39.09523
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x58d9492cd9b0>
> exp(tmp5)
<pointer: 0x58d9492cd9b0>
> log(tmp5,2)
<pointer: 0x58d9492cd9b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.8142
> Min(tmp5)
[1] 53.42713
> mean(tmp5)
[1] 72.43606
> Sum(tmp5)
[1] 14487.21
> Var(tmp5)
[1] 872.346
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.29955 69.80067 68.73480 72.03247 68.68861 69.62031 71.77586 70.37606
[9] 69.78949 70.24279
> rowSums(tmp5)
[1] 1865.991 1396.013 1374.696 1440.649 1373.772 1392.406 1435.517 1407.521
[9] 1395.790 1404.856
> rowVars(tmp5)
[1] 7926.80966 77.42734 90.69488 90.89318 59.50527 96.64394
[7] 96.20544 42.73277 43.15545 92.02033
> rowSd(tmp5)
[1] 89.032633 8.799281 9.523386 9.533792 7.713966 9.830765 9.808437
[8] 6.537030 6.569281 9.592723
> rowMax(tmp5)
[1] 468.81416 91.37104 88.87885 92.12363 84.74942 91.82783 84.19960
[8] 83.04791 83.55605 87.19870
> rowMin(tmp5)
[1] 58.49063 58.69498 54.29972 53.42713 57.23905 54.24211 54.29558 60.12355
[9] 57.87252 56.58093
>
> colMeans(tmp5)
[1] 105.09441 69.05751 70.58052 73.64249 66.31220 72.28073 67.00041
[8] 70.04933 72.33743 70.37004 74.10153 70.53597 69.43640 72.02303
[15] 69.07838 68.20174 70.49857 68.75517 77.57422 71.79114
> colSums(tmp5)
[1] 1050.9441 690.5751 705.8052 736.4249 663.1220 722.8073 670.0041
[8] 700.4933 723.3743 703.7004 741.0153 705.3597 694.3640 720.2303
[15] 690.7838 682.0174 704.9857 687.5517 775.7422 717.9114
> colVars(tmp5)
[1] 16403.41566 61.09890 65.18807 50.04036 42.87538 164.60499
[7] 94.27226 76.14957 117.75542 33.62414 110.71728 126.40446
[13] 93.78278 21.36161 40.99454 75.20617 87.47129 109.48955
[19] 68.49206 58.03598
> colSd(tmp5)
[1] 128.075820 7.816578 8.073913 7.073921 6.547930 12.829848
[7] 9.709390 8.726372 10.851517 5.798633 10.522228 11.242974
[13] 9.684151 4.621862 6.402698 8.672149 9.352609 10.463725
[19] 8.275993 7.618135
> colMax(tmp5)
[1] 468.81416 83.81053 82.52619 81.37159 76.61884 92.12363 79.15784
[8] 83.04791 91.37104 79.05654 88.87885 85.34829 87.19870 79.37375
[15] 75.82542 81.58378 88.89645 81.52101 91.50194 84.74942
> colMin(tmp5)
[1] 53.42713 58.61851 58.69498 60.43669 55.38399 57.73241 54.29558 57.87252
[9] 56.66685 61.72556 60.12644 55.49572 60.12355 63.60580 56.62185 57.23905
[17] 57.85463 54.24211 62.76627 61.34207
>
>
> ### 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] 93.29955 69.80067 68.73480 72.03247 68.68861 69.62031 71.77586 NA
[9] 69.78949 70.24279
> rowSums(tmp5)
[1] 1865.991 1396.013 1374.696 1440.649 1373.772 1392.406 1435.517 NA
[9] 1395.790 1404.856
> rowVars(tmp5)
[1] 7926.80966 77.42734 90.69488 90.89318 59.50527 96.64394
[7] 96.20544 44.72165 43.15545 92.02033
> rowSd(tmp5)
[1] 89.032633 8.799281 9.523386 9.533792 7.713966 9.830765 9.808437
[8] 6.687425 6.569281 9.592723
> rowMax(tmp5)
[1] 468.81416 91.37104 88.87885 92.12363 84.74942 91.82783 84.19960
[8] NA 83.55605 87.19870
> rowMin(tmp5)
[1] 58.49063 58.69498 54.29972 53.42713 57.23905 54.24211 54.29558 NA
[9] 57.87252 56.58093
>
> colMeans(tmp5)
[1] 105.09441 69.05751 70.58052 73.64249 66.31220 72.28073 67.00041
[8] 70.04933 72.33743 70.37004 74.10153 70.53597 69.43640 72.02303
[15] 69.07838 68.20174 70.49857 68.75517 77.57422 NA
> colSums(tmp5)
[1] 1050.9441 690.5751 705.8052 736.4249 663.1220 722.8073 670.0041
[8] 700.4933 723.3743 703.7004 741.0153 705.3597 694.3640 720.2303
[15] 690.7838 682.0174 704.9857 687.5517 775.7422 NA
> colVars(tmp5)
[1] 16403.41566 61.09890 65.18807 50.04036 42.87538 164.60499
[7] 94.27226 76.14957 117.75542 33.62414 110.71728 126.40446
[13] 93.78278 21.36161 40.99454 75.20617 87.47129 109.48955
[19] 68.49206 NA
> colSd(tmp5)
[1] 128.075820 7.816578 8.073913 7.073921 6.547930 12.829848
[7] 9.709390 8.726372 10.851517 5.798633 10.522228 11.242974
[13] 9.684151 4.621862 6.402698 8.672149 9.352609 10.463725
[19] 8.275993 NA
> colMax(tmp5)
[1] 468.81416 83.81053 82.52619 81.37159 76.61884 92.12363 79.15784
[8] 83.04791 91.37104 79.05654 88.87885 85.34829 87.19870 79.37375
[15] 75.82542 81.58378 88.89645 81.52101 91.50194 NA
> colMin(tmp5)
[1] 53.42713 58.61851 58.69498 60.43669 55.38399 57.73241 54.29558 57.87252
[9] 56.66685 61.72556 60.12644 55.49572 60.12355 63.60580 56.62185 57.23905
[17] 57.85463 54.24211 62.76627 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 468.8142
> Min(tmp5,na.rm=TRUE)
[1] 53.42713
> mean(tmp5,na.rm=TRUE)
[1] 72.45931
> Sum(tmp5,na.rm=TRUE)
[1] 14419.4
> Var(tmp5,na.rm=TRUE)
[1] 876.6432
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.29955 69.80067 68.73480 72.03247 68.68861 69.62031 71.77586 70.51113
[9] 69.78949 70.24279
> rowSums(tmp5,na.rm=TRUE)
[1] 1865.991 1396.013 1374.696 1440.649 1373.772 1392.406 1435.517 1339.711
[9] 1395.790 1404.856
> rowVars(tmp5,na.rm=TRUE)
[1] 7926.80966 77.42734 90.69488 90.89318 59.50527 96.64394
[7] 96.20544 44.72165 43.15545 92.02033
> rowSd(tmp5,na.rm=TRUE)
[1] 89.032633 8.799281 9.523386 9.533792 7.713966 9.830765 9.808437
[8] 6.687425 6.569281 9.592723
> rowMax(tmp5,na.rm=TRUE)
[1] 468.81416 91.37104 88.87885 92.12363 84.74942 91.82783 84.19960
[8] 83.04791 83.55605 87.19870
> rowMin(tmp5,na.rm=TRUE)
[1] 58.49063 58.69498 54.29972 53.42713 57.23905 54.24211 54.29558 60.12355
[9] 57.87252 56.58093
>
> colMeans(tmp5,na.rm=TRUE)
[1] 105.09441 69.05751 70.58052 73.64249 66.31220 72.28073 67.00041
[8] 70.04933 72.33743 70.37004 74.10153 70.53597 69.43640 72.02303
[15] 69.07838 68.20174 70.49857 68.75517 77.57422 72.23353
> colSums(tmp5,na.rm=TRUE)
[1] 1050.9441 690.5751 705.8052 736.4249 663.1220 722.8073 670.0041
[8] 700.4933 723.3743 703.7004 741.0153 705.3597 694.3640 720.2303
[15] 690.7838 682.0174 704.9857 687.5517 775.7422 650.1018
> colVars(tmp5,na.rm=TRUE)
[1] 16403.41566 61.09890 65.18807 50.04036 42.87538 164.60499
[7] 94.27226 76.14957 117.75542 33.62414 110.71728 126.40446
[13] 93.78278 21.36161 40.99454 75.20617 87.47129 109.48955
[19] 68.49206 63.08882
> colSd(tmp5,na.rm=TRUE)
[1] 128.075820 7.816578 8.073913 7.073921 6.547930 12.829848
[7] 9.709390 8.726372 10.851517 5.798633 10.522228 11.242974
[13] 9.684151 4.621862 6.402698 8.672149 9.352609 10.463725
[19] 8.275993 7.942847
> colMax(tmp5,na.rm=TRUE)
[1] 468.81416 83.81053 82.52619 81.37159 76.61884 92.12363 79.15784
[8] 83.04791 91.37104 79.05654 88.87885 85.34829 87.19870 79.37375
[15] 75.82542 81.58378 88.89645 81.52101 91.50194 84.74942
> colMin(tmp5,na.rm=TRUE)
[1] 53.42713 58.61851 58.69498 60.43669 55.38399 57.73241 54.29558 57.87252
[9] 56.66685 61.72556 60.12644 55.49572 60.12355 63.60580 56.62185 57.23905
[17] 57.85463 54.24211 62.76627 61.34207
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.29955 69.80067 68.73480 72.03247 68.68861 69.62031 71.77586 NaN
[9] 69.78949 70.24279
> rowSums(tmp5,na.rm=TRUE)
[1] 1865.991 1396.013 1374.696 1440.649 1373.772 1392.406 1435.517 0.000
[9] 1395.790 1404.856
> rowVars(tmp5,na.rm=TRUE)
[1] 7926.80966 77.42734 90.69488 90.89318 59.50527 96.64394
[7] 96.20544 NA 43.15545 92.02033
> rowSd(tmp5,na.rm=TRUE)
[1] 89.032633 8.799281 9.523386 9.533792 7.713966 9.830765 9.808437
[8] NA 6.569281 9.592723
> rowMax(tmp5,na.rm=TRUE)
[1] 468.81416 91.37104 88.87885 92.12363 84.74942 91.82783 84.19960
[8] NA 83.55605 87.19870
> rowMin(tmp5,na.rm=TRUE)
[1] 58.49063 58.69498 54.29972 53.42713 57.23905 54.24211 54.29558 NA
[9] 57.87252 56.58093
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 110.00644 69.56688 70.47204 74.30078 66.57612 71.79543 66.59181
[8] 68.60504 73.19342 70.55914 74.86266 69.61949 70.47116 72.66831
[15] 68.44396 67.24533 70.80328 68.01178 77.27238 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 990.0579 626.1019 634.2484 668.7070 599.1851 646.1589 599.3263 617.4454
[9] 658.7408 635.0323 673.7639 626.5754 634.2404 654.0148 615.9956 605.2080
[17] 637.2296 612.1061 695.4514 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 18182.40220 65.81739 73.20421 51.42019 47.45117 182.53103
[7] 104.17803 62.20115 124.23172 37.42486 118.03963 132.75576
[13] 93.45992 19.34739 41.59077 74.31643 97.36061 116.95868
[19] 76.02866 NA
> colSd(tmp5,na.rm=TRUE)
[1] 134.842138 8.112792 8.555946 7.170788 6.888481 13.510405
[7] 10.206764 7.886770 11.145929 6.117586 10.864604 11.521969
[13] 9.667467 4.398567 6.449090 8.620698 9.867148 10.814744
[19] 8.719441 NA
> colMax(tmp5,na.rm=TRUE)
[1] 468.81416 83.81053 82.52619 81.37159 76.61884 92.12363 79.15784
[8] 80.83681 91.37104 79.05654 88.87885 85.34829 87.19870 79.37375
[15] 75.82542 81.58378 88.89645 81.52101 91.50194 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 53.42713 58.61851 58.69498 60.43669 55.38399 57.73241 54.29558 57.87252
[9] 56.66685 61.72556 60.12644 55.49572 61.61695 63.60580 56.62185 57.23905
[17] 57.85463 54.24211 62.76627 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] 294.0239 189.5555 204.1502 266.0315 139.6339 113.4458 265.5283 117.7989
[9] 330.3970 100.2434
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 294.0239 189.5555 204.1502 266.0315 139.6339 113.4458 265.5283 117.7989
[9] 330.3970 100.2434
>
>
>
> 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] 0.000000e+00 1.136868e-13 -2.842171e-14 -1.421085e-13 -1.136868e-13
[6] 0.000000e+00 5.684342e-14 -2.842171e-14 1.705303e-13 5.684342e-14
[11] 1.136868e-13 -2.842171e-14 5.684342e-14 0.000000e+00 -1.705303e-13
[16] -1.989520e-13 -5.684342e-14 -2.842171e-14 -5.684342e-14 -3.410605e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
1 1
6 8
6 1
6 1
3 12
1 1
7 4
7 3
5 16
9 11
7 5
10 9
10 15
10 16
3 10
2 17
2 3
4 1
3 20
6 7
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] 2.570763
> Min(tmp)
[1] -2.468256
> mean(tmp)
[1] -0.02924306
> Sum(tmp)
[1] -2.924306
> Var(tmp)
[1] 0.9079789
>
> rowMeans(tmp)
[1] -0.02924306
> rowSums(tmp)
[1] -2.924306
> rowVars(tmp)
[1] 0.9079789
> rowSd(tmp)
[1] 0.9528793
> rowMax(tmp)
[1] 2.570763
> rowMin(tmp)
[1] -2.468256
>
> colMeans(tmp)
[1] 0.239880360 -0.484947733 -0.059219206 0.345908465 0.280773344
[6] -0.408794551 -0.447595125 -0.131918781 -0.361338017 -0.233482918
[11] 0.886877866 0.055112729 0.264126299 -0.461679152 0.141485269
[16] -1.895258913 -0.866707003 -0.922496349 1.433066336 -0.342819193
[21] 0.564962124 -0.318680004 -0.134986967 -0.920360382 0.247424082
[26] -1.622037324 0.146969158 -1.731222565 0.232984610 -0.995436371
[31] 0.337051408 -0.974865447 -0.319500363 -1.370400231 -0.731463886
[36] 0.873793638 0.461726868 0.724307760 -0.291877384 -0.574549677
[41] 1.510803411 0.239684451 -0.141818680 -0.208278418 0.485890595
[46] 0.316479700 1.288911262 0.287160159 -0.133995406 -0.959911038
[51] 1.161777461 1.005006634 0.883407648 0.097784773 -0.934143631
[56] -0.358742929 0.478578229 -0.205415936 2.570763320 1.525614338
[61] -1.373245195 1.265448380 -2.058219343 1.027257886 1.034045945
[66] -1.211961930 0.989235422 -2.468256245 -0.204689786 0.544405014
[71] 1.260162203 -0.326401731 -0.163716134 -0.665545058 0.561877964
[76] -0.556701952 -0.798670441 -1.244072509 -0.588252588 1.129327619
[81] 1.645861139 -0.196804416 -0.951820358 -0.408872395 -1.053239371
[86] 0.801444232 1.721467431 -0.009121567 -0.755141361 -0.814854605
[91] 0.170129059 -0.647582160 1.860085989 -0.346876415 -1.273977941
[96] 0.479766468 0.827250032 1.246994431 1.042374100 -1.957784594
> colSums(tmp)
[1] 0.239880360 -0.484947733 -0.059219206 0.345908465 0.280773344
[6] -0.408794551 -0.447595125 -0.131918781 -0.361338017 -0.233482918
[11] 0.886877866 0.055112729 0.264126299 -0.461679152 0.141485269
[16] -1.895258913 -0.866707003 -0.922496349 1.433066336 -0.342819193
[21] 0.564962124 -0.318680004 -0.134986967 -0.920360382 0.247424082
[26] -1.622037324 0.146969158 -1.731222565 0.232984610 -0.995436371
[31] 0.337051408 -0.974865447 -0.319500363 -1.370400231 -0.731463886
[36] 0.873793638 0.461726868 0.724307760 -0.291877384 -0.574549677
[41] 1.510803411 0.239684451 -0.141818680 -0.208278418 0.485890595
[46] 0.316479700 1.288911262 0.287160159 -0.133995406 -0.959911038
[51] 1.161777461 1.005006634 0.883407648 0.097784773 -0.934143631
[56] -0.358742929 0.478578229 -0.205415936 2.570763320 1.525614338
[61] -1.373245195 1.265448380 -2.058219343 1.027257886 1.034045945
[66] -1.211961930 0.989235422 -2.468256245 -0.204689786 0.544405014
[71] 1.260162203 -0.326401731 -0.163716134 -0.665545058 0.561877964
[76] -0.556701952 -0.798670441 -1.244072509 -0.588252588 1.129327619
[81] 1.645861139 -0.196804416 -0.951820358 -0.408872395 -1.053239371
[86] 0.801444232 1.721467431 -0.009121567 -0.755141361 -0.814854605
[91] 0.170129059 -0.647582160 1.860085989 -0.346876415 -1.273977941
[96] 0.479766468 0.827250032 1.246994431 1.042374100 -1.957784594
> 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] 0.239880360 -0.484947733 -0.059219206 0.345908465 0.280773344
[6] -0.408794551 -0.447595125 -0.131918781 -0.361338017 -0.233482918
[11] 0.886877866 0.055112729 0.264126299 -0.461679152 0.141485269
[16] -1.895258913 -0.866707003 -0.922496349 1.433066336 -0.342819193
[21] 0.564962124 -0.318680004 -0.134986967 -0.920360382 0.247424082
[26] -1.622037324 0.146969158 -1.731222565 0.232984610 -0.995436371
[31] 0.337051408 -0.974865447 -0.319500363 -1.370400231 -0.731463886
[36] 0.873793638 0.461726868 0.724307760 -0.291877384 -0.574549677
[41] 1.510803411 0.239684451 -0.141818680 -0.208278418 0.485890595
[46] 0.316479700 1.288911262 0.287160159 -0.133995406 -0.959911038
[51] 1.161777461 1.005006634 0.883407648 0.097784773 -0.934143631
[56] -0.358742929 0.478578229 -0.205415936 2.570763320 1.525614338
[61] -1.373245195 1.265448380 -2.058219343 1.027257886 1.034045945
[66] -1.211961930 0.989235422 -2.468256245 -0.204689786 0.544405014
[71] 1.260162203 -0.326401731 -0.163716134 -0.665545058 0.561877964
[76] -0.556701952 -0.798670441 -1.244072509 -0.588252588 1.129327619
[81] 1.645861139 -0.196804416 -0.951820358 -0.408872395 -1.053239371
[86] 0.801444232 1.721467431 -0.009121567 -0.755141361 -0.814854605
[91] 0.170129059 -0.647582160 1.860085989 -0.346876415 -1.273977941
[96] 0.479766468 0.827250032 1.246994431 1.042374100 -1.957784594
> colMin(tmp)
[1] 0.239880360 -0.484947733 -0.059219206 0.345908465 0.280773344
[6] -0.408794551 -0.447595125 -0.131918781 -0.361338017 -0.233482918
[11] 0.886877866 0.055112729 0.264126299 -0.461679152 0.141485269
[16] -1.895258913 -0.866707003 -0.922496349 1.433066336 -0.342819193
[21] 0.564962124 -0.318680004 -0.134986967 -0.920360382 0.247424082
[26] -1.622037324 0.146969158 -1.731222565 0.232984610 -0.995436371
[31] 0.337051408 -0.974865447 -0.319500363 -1.370400231 -0.731463886
[36] 0.873793638 0.461726868 0.724307760 -0.291877384 -0.574549677
[41] 1.510803411 0.239684451 -0.141818680 -0.208278418 0.485890595
[46] 0.316479700 1.288911262 0.287160159 -0.133995406 -0.959911038
[51] 1.161777461 1.005006634 0.883407648 0.097784773 -0.934143631
[56] -0.358742929 0.478578229 -0.205415936 2.570763320 1.525614338
[61] -1.373245195 1.265448380 -2.058219343 1.027257886 1.034045945
[66] -1.211961930 0.989235422 -2.468256245 -0.204689786 0.544405014
[71] 1.260162203 -0.326401731 -0.163716134 -0.665545058 0.561877964
[76] -0.556701952 -0.798670441 -1.244072509 -0.588252588 1.129327619
[81] 1.645861139 -0.196804416 -0.951820358 -0.408872395 -1.053239371
[86] 0.801444232 1.721467431 -0.009121567 -0.755141361 -0.814854605
[91] 0.170129059 -0.647582160 1.860085989 -0.346876415 -1.273977941
[96] 0.479766468 0.827250032 1.246994431 1.042374100 -1.957784594
> colMedians(tmp)
[1] 0.239880360 -0.484947733 -0.059219206 0.345908465 0.280773344
[6] -0.408794551 -0.447595125 -0.131918781 -0.361338017 -0.233482918
[11] 0.886877866 0.055112729 0.264126299 -0.461679152 0.141485269
[16] -1.895258913 -0.866707003 -0.922496349 1.433066336 -0.342819193
[21] 0.564962124 -0.318680004 -0.134986967 -0.920360382 0.247424082
[26] -1.622037324 0.146969158 -1.731222565 0.232984610 -0.995436371
[31] 0.337051408 -0.974865447 -0.319500363 -1.370400231 -0.731463886
[36] 0.873793638 0.461726868 0.724307760 -0.291877384 -0.574549677
[41] 1.510803411 0.239684451 -0.141818680 -0.208278418 0.485890595
[46] 0.316479700 1.288911262 0.287160159 -0.133995406 -0.959911038
[51] 1.161777461 1.005006634 0.883407648 0.097784773 -0.934143631
[56] -0.358742929 0.478578229 -0.205415936 2.570763320 1.525614338
[61] -1.373245195 1.265448380 -2.058219343 1.027257886 1.034045945
[66] -1.211961930 0.989235422 -2.468256245 -0.204689786 0.544405014
[71] 1.260162203 -0.326401731 -0.163716134 -0.665545058 0.561877964
[76] -0.556701952 -0.798670441 -1.244072509 -0.588252588 1.129327619
[81] 1.645861139 -0.196804416 -0.951820358 -0.408872395 -1.053239371
[86] 0.801444232 1.721467431 -0.009121567 -0.755141361 -0.814854605
[91] 0.170129059 -0.647582160 1.860085989 -0.346876415 -1.273977941
[96] 0.479766468 0.827250032 1.246994431 1.042374100 -1.957784594
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.2398804 -0.4849477 -0.05921921 0.3459085 0.2807733 -0.4087946 -0.4475951
[2,] 0.2398804 -0.4849477 -0.05921921 0.3459085 0.2807733 -0.4087946 -0.4475951
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.1319188 -0.361338 -0.2334829 0.8868779 0.05511273 0.2641263 -0.4616792
[2,] -0.1319188 -0.361338 -0.2334829 0.8868779 0.05511273 0.2641263 -0.4616792
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.1414853 -1.895259 -0.866707 -0.9224963 1.433066 -0.3428192 0.5649621
[2,] 0.1414853 -1.895259 -0.866707 -0.9224963 1.433066 -0.3428192 0.5649621
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.31868 -0.134987 -0.9203604 0.2474241 -1.622037 0.1469692 -1.731223
[2,] -0.31868 -0.134987 -0.9203604 0.2474241 -1.622037 0.1469692 -1.731223
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2329846 -0.9954364 0.3370514 -0.9748654 -0.3195004 -1.3704 -0.7314639
[2,] 0.2329846 -0.9954364 0.3370514 -0.9748654 -0.3195004 -1.3704 -0.7314639
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8737936 0.4617269 0.7243078 -0.2918774 -0.5745497 1.510803 0.2396845
[2,] 0.8737936 0.4617269 0.7243078 -0.2918774 -0.5745497 1.510803 0.2396845
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1418187 -0.2082784 0.4858906 0.3164797 1.288911 0.2871602 -0.1339954
[2,] -0.1418187 -0.2082784 0.4858906 0.3164797 1.288911 0.2871602 -0.1339954
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.959911 1.161777 1.005007 0.8834076 0.09778477 -0.9341436 -0.3587429
[2,] -0.959911 1.161777 1.005007 0.8834076 0.09778477 -0.9341436 -0.3587429
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4785782 -0.2054159 2.570763 1.525614 -1.373245 1.265448 -2.058219
[2,] 0.4785782 -0.2054159 2.570763 1.525614 -1.373245 1.265448 -2.058219
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.027258 1.034046 -1.211962 0.9892354 -2.468256 -0.2046898 0.544405
[2,] 1.027258 1.034046 -1.211962 0.9892354 -2.468256 -0.2046898 0.544405
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.260162 -0.3264017 -0.1637161 -0.6655451 0.561878 -0.556702 -0.7986704
[2,] 1.260162 -0.3264017 -0.1637161 -0.6655451 0.561878 -0.556702 -0.7986704
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.244073 -0.5882526 1.129328 1.645861 -0.1968044 -0.9518204 -0.4088724
[2,] -1.244073 -0.5882526 1.129328 1.645861 -0.1968044 -0.9518204 -0.4088724
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.053239 0.8014442 1.721467 -0.009121567 -0.7551414 -0.8148546 0.1701291
[2,] -1.053239 0.8014442 1.721467 -0.009121567 -0.7551414 -0.8148546 0.1701291
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.6475822 1.860086 -0.3468764 -1.273978 0.4797665 0.82725 1.246994
[2,] -0.6475822 1.860086 -0.3468764 -1.273978 0.4797665 0.82725 1.246994
[,99] [,100]
[1,] 1.042374 -1.957785
[2,] 1.042374 -1.957785
>
>
> Max(tmp2)
[1] 2.347392
> Min(tmp2)
[1] -2.178762
> mean(tmp2)
[1] 0.0901218
> Sum(tmp2)
[1] 9.01218
> Var(tmp2)
[1] 0.9933756
>
> rowMeans(tmp2)
[1] 0.444341898 -0.258956615 1.293413802 0.106646455 0.438041262
[6] 1.783577955 0.543365395 0.460237829 -0.140476794 0.085204570
[11] 0.809609280 -0.474783387 -0.842771767 -1.654439600 0.520228779
[16] -0.916406911 0.534878159 -0.031151028 -0.113849894 0.105897369
[21] -0.947317405 -0.669729156 1.841112838 1.129628758 -0.350152315
[26] 1.686243357 0.798836350 -1.713793946 0.535058080 -1.854787802
[31] 1.182450209 -0.155444294 -0.096843805 0.768561754 0.802507557
[36] 0.651111279 0.156839669 -0.443516208 2.148139131 -0.877890194
[41] -0.614814476 0.361412865 -1.017500773 -1.690004064 0.203559624
[46] 1.548593981 0.674755568 0.268601320 -0.240000453 0.482022610
[51] -0.976805224 1.012617396 -1.645762265 -0.157004598 -0.992248729
[56] 1.365181175 -1.400224885 0.471696483 -0.754722764 -0.973335114
[61] 0.398262428 0.102333522 -1.819331551 1.842528775 -1.588673749
[66] 0.102613184 0.894633702 0.520793753 -0.203581121 1.382176807
[71] -0.631463118 -2.178762320 0.996638525 -2.005372464 0.735152219
[76] -0.177023690 0.914209528 0.951469942 -0.840185114 1.189602520
[81] -0.079179477 -1.399216549 0.203799916 -1.627465911 0.916506527
[86] 0.393527759 -0.379367118 -0.393484134 1.506561664 -0.093176683
[91] 1.100717549 0.695201544 0.633645757 -0.007186574 2.347391583
[96] 0.348425693 -0.081403877 0.460686930 -0.005078900 0.675614068
> rowSums(tmp2)
[1] 0.444341898 -0.258956615 1.293413802 0.106646455 0.438041262
[6] 1.783577955 0.543365395 0.460237829 -0.140476794 0.085204570
[11] 0.809609280 -0.474783387 -0.842771767 -1.654439600 0.520228779
[16] -0.916406911 0.534878159 -0.031151028 -0.113849894 0.105897369
[21] -0.947317405 -0.669729156 1.841112838 1.129628758 -0.350152315
[26] 1.686243357 0.798836350 -1.713793946 0.535058080 -1.854787802
[31] 1.182450209 -0.155444294 -0.096843805 0.768561754 0.802507557
[36] 0.651111279 0.156839669 -0.443516208 2.148139131 -0.877890194
[41] -0.614814476 0.361412865 -1.017500773 -1.690004064 0.203559624
[46] 1.548593981 0.674755568 0.268601320 -0.240000453 0.482022610
[51] -0.976805224 1.012617396 -1.645762265 -0.157004598 -0.992248729
[56] 1.365181175 -1.400224885 0.471696483 -0.754722764 -0.973335114
[61] 0.398262428 0.102333522 -1.819331551 1.842528775 -1.588673749
[66] 0.102613184 0.894633702 0.520793753 -0.203581121 1.382176807
[71] -0.631463118 -2.178762320 0.996638525 -2.005372464 0.735152219
[76] -0.177023690 0.914209528 0.951469942 -0.840185114 1.189602520
[81] -0.079179477 -1.399216549 0.203799916 -1.627465911 0.916506527
[86] 0.393527759 -0.379367118 -0.393484134 1.506561664 -0.093176683
[91] 1.100717549 0.695201544 0.633645757 -0.007186574 2.347391583
[96] 0.348425693 -0.081403877 0.460686930 -0.005078900 0.675614068
> 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] 0.444341898 -0.258956615 1.293413802 0.106646455 0.438041262
[6] 1.783577955 0.543365395 0.460237829 -0.140476794 0.085204570
[11] 0.809609280 -0.474783387 -0.842771767 -1.654439600 0.520228779
[16] -0.916406911 0.534878159 -0.031151028 -0.113849894 0.105897369
[21] -0.947317405 -0.669729156 1.841112838 1.129628758 -0.350152315
[26] 1.686243357 0.798836350 -1.713793946 0.535058080 -1.854787802
[31] 1.182450209 -0.155444294 -0.096843805 0.768561754 0.802507557
[36] 0.651111279 0.156839669 -0.443516208 2.148139131 -0.877890194
[41] -0.614814476 0.361412865 -1.017500773 -1.690004064 0.203559624
[46] 1.548593981 0.674755568 0.268601320 -0.240000453 0.482022610
[51] -0.976805224 1.012617396 -1.645762265 -0.157004598 -0.992248729
[56] 1.365181175 -1.400224885 0.471696483 -0.754722764 -0.973335114
[61] 0.398262428 0.102333522 -1.819331551 1.842528775 -1.588673749
[66] 0.102613184 0.894633702 0.520793753 -0.203581121 1.382176807
[71] -0.631463118 -2.178762320 0.996638525 -2.005372464 0.735152219
[76] -0.177023690 0.914209528 0.951469942 -0.840185114 1.189602520
[81] -0.079179477 -1.399216549 0.203799916 -1.627465911 0.916506527
[86] 0.393527759 -0.379367118 -0.393484134 1.506561664 -0.093176683
[91] 1.100717549 0.695201544 0.633645757 -0.007186574 2.347391583
[96] 0.348425693 -0.081403877 0.460686930 -0.005078900 0.675614068
> rowMin(tmp2)
[1] 0.444341898 -0.258956615 1.293413802 0.106646455 0.438041262
[6] 1.783577955 0.543365395 0.460237829 -0.140476794 0.085204570
[11] 0.809609280 -0.474783387 -0.842771767 -1.654439600 0.520228779
[16] -0.916406911 0.534878159 -0.031151028 -0.113849894 0.105897369
[21] -0.947317405 -0.669729156 1.841112838 1.129628758 -0.350152315
[26] 1.686243357 0.798836350 -1.713793946 0.535058080 -1.854787802
[31] 1.182450209 -0.155444294 -0.096843805 0.768561754 0.802507557
[36] 0.651111279 0.156839669 -0.443516208 2.148139131 -0.877890194
[41] -0.614814476 0.361412865 -1.017500773 -1.690004064 0.203559624
[46] 1.548593981 0.674755568 0.268601320 -0.240000453 0.482022610
[51] -0.976805224 1.012617396 -1.645762265 -0.157004598 -0.992248729
[56] 1.365181175 -1.400224885 0.471696483 -0.754722764 -0.973335114
[61] 0.398262428 0.102333522 -1.819331551 1.842528775 -1.588673749
[66] 0.102613184 0.894633702 0.520793753 -0.203581121 1.382176807
[71] -0.631463118 -2.178762320 0.996638525 -2.005372464 0.735152219
[76] -0.177023690 0.914209528 0.951469942 -0.840185114 1.189602520
[81] -0.079179477 -1.399216549 0.203799916 -1.627465911 0.916506527
[86] 0.393527759 -0.379367118 -0.393484134 1.506561664 -0.093176683
[91] 1.100717549 0.695201544 0.633645757 -0.007186574 2.347391583
[96] 0.348425693 -0.081403877 0.460686930 -0.005078900 0.675614068
>
> colMeans(tmp2)
[1] 0.0901218
> colSums(tmp2)
[1] 9.01218
> colVars(tmp2)
[1] 0.9933756
> colSd(tmp2)
[1] 0.9966823
> colMax(tmp2)
[1] 2.347392
> colMin(tmp2)
[1] -2.178762
> colMedians(tmp2)
[1] 0.1317431
> colRanges(tmp2)
[,1]
[1,] -2.178762
[2,] 2.347392
>
> 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] -2.2008337 3.0178903 -4.1753106 1.8176432 2.7581065 0.9570429
[7] 3.2524324 0.2166910 -0.5775642 -2.8181183
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.21140125
[2,] -0.58846099
[3,] -0.06701438
[4,] 0.32615526
[5,] 1.24091093
>
> rowApply(tmp,sum)
[1] -0.6337262 -1.4138860 -1.7532542 3.2914368 1.1373083 6.1742911
[7] 0.7129341 -4.4546539 -3.3397029 2.5272326
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 1 9 9 1 2 7 4 7 6
[2,] 9 9 2 6 4 1 10 9 3 8
[3,] 4 8 8 1 5 5 4 7 1 2
[4,] 8 6 4 8 9 3 6 2 5 5
[5,] 10 4 3 2 8 4 9 6 10 9
[6,] 1 10 1 5 10 6 3 8 8 10
[7,] 7 2 10 10 6 8 8 5 4 7
[8,] 3 3 6 3 7 10 5 1 9 4
[9,] 2 7 7 4 2 9 2 10 6 1
[10,] 5 5 5 7 3 7 1 3 2 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.674648651 -2.101648314 -1.280487868 0.933399096 1.778609872
[6] 2.873449970 -0.006330129 1.650254190 -0.570471853 0.688066924
[11] 0.298457716 -0.460287812 -3.693131745 1.152049871 3.784508974
[16] 2.449871547 0.490995264 -2.416029000 -1.645708105 -0.730657532
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.79995510
[2,] 0.01451131
[3,] 0.42729815
[4,] 0.85262177
[5,] 2.18017252
>
> rowApply(tmp,sum)
[1] -0.1853807 4.2361423 -3.0159711 3.1688680 1.6659012
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 10 18 9 3
[2,] 7 2 5 13 10
[3,] 15 7 12 4 2
[4,] 12 5 7 19 19
[5,] 9 20 3 14 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 2.18017252 -0.28444879 0.44136057 0.1524319 0.01097435 1.1722559
[2,] 0.42729815 -1.58100299 0.07131047 -0.9461745 1.99738024 0.7246240
[3,] 0.85262177 -0.76461519 -0.11375191 -0.6549356 -0.80576991 0.5181030
[4,] 0.01451131 0.53390150 -0.59561145 1.3719975 0.72280987 0.7936941
[5,] -0.79995510 -0.00548285 -1.08379555 1.0100798 -0.14678469 -0.3352271
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.8631270 0.06152912 -0.5164024 0.46932774 -0.2359008 -0.8347999
[2,] 1.2117002 -0.36949326 1.6205521 0.61417961 1.0408890 0.3175135
[3,] -0.5201922 -0.08594994 -0.2920937 -0.96007507 -0.7939441 2.2479032
[4,] -0.7355552 0.42898690 -0.2498514 -0.04162108 -0.5604814 -1.6294934
[5,] 0.9008440 1.61518137 -1.1326764 0.60625572 0.8478950 -0.5614112
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.6669328 0.8091866 0.74891431 0.36030943 -1.7225473 0.4147652
[2,] -1.5070214 0.3260316 1.90997264 0.45979141 1.2585464 -1.3972767
[3,] -0.3694903 -0.6871375 0.48898090 -0.07853293 -0.1673501 -2.1460351
[4,] 0.5232658 0.7836637 0.08770795 1.14267546 0.9759738 1.4532979
[5,] -0.6729530 -0.0796945 0.54893317 0.56562817 0.1463724 -0.7407804
[,19] [,20]
[1,] -0.8962590005 0.01380961
[2,] 0.4547051204 -2.39738341
[3,] 0.2566558789 1.05963780
[4,] -1.4602081272 -0.39079586
[5,] -0.0006019766 0.98407433
>
>
> 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 : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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 -1.043375 -0.03356671 -1.226759 1.433739 -0.3920492 -0.5942928 0.4003496
col8 col9 col10 col11 col12 col13 col14
row1 -0.08543143 -0.7046285 -1.762351 -0.9452243 -0.2116673 0.6352496 0.237139
col15 col16 col17 col18 col19 col20
row1 -1.533051 -1.22969 0.3754532 -0.1233067 2.276309 0.3975597
> tmp[,"col10"]
col10
row1 -1.76235119
row2 0.05956872
row3 -0.48126565
row4 0.68665925
row5 -1.08228254
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.0433752 -0.03356671 -1.226759 1.4337392 -0.3920492 -0.5942928 0.4003496
row5 0.1598302 -0.91232728 0.817915 0.5195167 0.3348075 1.0178861 0.5242685
col8 col9 col10 col11 col12 col13
row1 -0.08543143 -0.7046285 -1.762351 -0.9452243 -0.2116673 0.6352496
row5 1.74183846 -1.8012303 -1.082283 1.2105205 1.3396209 -0.7250351
col14 col15 col16 col17 col18 col19 col20
row1 0.237139 -1.5330510 -1.2296897 0.3754532 -0.1233067 2.2763093 0.3975597
row5 -1.599621 -0.1599543 -0.4250619 1.7940943 0.1542213 -0.1392339 -0.2059409
> tmp[,c("col6","col20")]
col6 col20
row1 -0.5942928 0.3975597
row2 2.4712079 0.2003496
row3 -0.7974423 -0.3872303
row4 0.9290562 -0.9968774
row5 1.0178861 -0.2059409
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.5942928 0.3975597
row5 1.0178861 -0.2059409
>
>
>
>
> 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 50.93119 50.28602 50.6116 50.61162 48.81291 104.7329 49.97835 48.75048
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.0311 49.3161 48.39091 50.83178 50.05611 49.33814 51.25263 49.29769
col17 col18 col19 col20
row1 50.78756 49.42208 51.19767 103.8893
> tmp[,"col10"]
col10
row1 49.31610
row2 29.38028
row3 31.48194
row4 28.80520
row5 50.07479
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.93119 50.28602 50.61160 50.61162 48.81291 104.7329 49.97835 48.75048
row5 50.22547 51.65005 48.97586 49.92281 48.83324 105.4273 50.59806 49.83971
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.03110 49.31610 48.39091 50.83178 50.05611 49.33814 51.25263 49.29769
row5 51.49191 50.07479 50.11589 50.11051 49.61298 49.77639 48.92079 50.26646
col17 col18 col19 col20
row1 50.78756 49.42208 51.19767 103.8893
row5 49.57891 50.84387 49.83180 104.6675
> tmp[,c("col6","col20")]
col6 col20
row1 104.73294 103.88935
row2 74.44236 76.34514
row3 73.86619 72.42320
row4 75.21578 76.39673
row5 105.42726 104.66749
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7329 103.8893
row5 105.4273 104.6675
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7329 103.8893
row5 105.4273 104.6675
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.5202114
[2,] -0.1967095
[3,] -0.1191520
[4,] 1.2094247
[5,] 1.3406936
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.93690772 1.8178256
[2,] 0.02533892 1.0529047
[3,] 0.51282240 -0.8377611
[4,] -0.57387920 -0.9791347
[5,] -0.42160094 -0.2193758
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.5368988 0.41955625
[2,] 0.6192398 -0.57163196
[3,] 1.2765472 0.09462249
[4,] 0.2493080 1.16119282
[5,] 2.0648272 1.70174844
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.5368988
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.5368988
[2,] 0.6192398
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.6044029 0.346598 -0.1430116 0.08638625 -0.3373328 -0.5384524 0.09232349
row1 0.4584284 1.684495 -1.9095703 1.23277377 -0.5166499 0.2941916 0.19346080
[,8] [,9] [,10] [,11] [,12] [,13]
row3 1.34330047 -0.4306718 -0.2284716 0.3416041 -0.4896657 -0.3955005
row1 0.02675206 -0.1830576 -1.0194936 -1.2839443 -0.3793811 0.4212236
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.092471 -0.4814558 -2.0873893 0.7840227 -0.3200846 0.2945699
row1 -1.287705 0.3114116 0.6306543 -1.3378755 2.2622191 -0.3072560
[,20]
row3 -0.9702097
row1 0.1300924
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2510605 0.9425912 -0.445132 -0.3914641 0.7519521 1.543381 -0.3899984
[,8] [,9] [,10]
row2 0.6598509 0.3429053 -0.002628955
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 2.023982 1.436954 0.7896848 -1.725817 0.9003518 0.6620379 -0.1828038
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6601545 1.036708 -0.8461104 0.2892136 -1.644067 -1.353885 0.4240602
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.6170116 1.182971 -1.487005 -2.801783 -1.662845 0.005536422
>
>
> 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: 0x58d948fec0e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485329f94243"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM304853709e9c8"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3048536cb232e"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM304853641fdee5"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3048535da6c716"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3048534bc6b39d"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485338dfab1f"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485319278458"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM304853755060d5"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485332f26759"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485344901a1a"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485371bc450e"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485346dcb895"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3048532c65971a"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM30485325bdc7c1"
>
>
> ### 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: 0x58d949783130>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x58d949783130>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x58d949783130>
> rowMedians(tmp)
[1] 4.657280e-01 3.160065e-01 9.112460e-02 2.010906e-01 -4.906504e-02
[6] -1.197287e-01 5.373958e-01 3.523586e-01 4.271321e-01 -1.692040e-01
[11] 4.018411e-01 4.268238e-03 -5.890520e-02 1.036397e-01 -3.799429e-01
[16] -2.875615e-01 3.381206e-01 3.744179e-01 -9.298971e-02 -2.136806e-01
[21] 8.536950e-02 1.227014e-02 2.312302e-03 2.456195e-01 7.756600e-01
[26] 1.688496e-01 -5.050424e-02 6.285903e-01 -4.922851e-01 7.483401e-01
[31] -4.606042e-02 -1.814882e-01 -1.089535e-01 4.268755e-01 2.826987e-01
[36] -1.216230e-01 -1.878284e-01 -3.221282e-01 1.100789e-01 2.073748e-01
[41] -6.885103e-02 -3.763615e-01 -3.863960e-01 8.912520e-02 -1.857333e-01
[46] -1.529354e-01 -1.264838e-01 -4.801225e-03 -2.855437e-01 -1.024517e-01
[51] 3.123828e-02 7.083960e-01 1.815880e-01 4.848594e-02 5.930718e-01
[56] 8.388709e-02 -3.748156e-01 2.252827e-01 4.213746e-01 -1.125415e-01
[61] 1.935392e-02 -2.804121e-01 9.647651e-02 4.901797e-01 3.527915e-02
[66] 1.815275e-01 -1.246267e-01 5.149110e-01 2.091165e-01 1.036095e-01
[71] -1.861168e-01 1.658877e-01 6.813361e-01 -4.254483e-01 7.334353e-02
[76] -5.105374e-02 -3.512927e-01 -3.850148e-01 -6.346424e-01 2.951464e-03
[81] -4.283181e-02 3.141465e-02 4.594024e-01 4.400202e-01 -3.878875e-01
[86] -2.389518e-01 -1.794016e-01 4.403330e-02 2.862408e-01 4.752604e-01
[91] -3.184362e-01 2.226733e-01 -2.423973e-01 -5.135922e-01 1.226929e-01
[96] -3.916566e-02 -1.014288e-01 6.183857e-02 -4.676605e-01 -2.698140e-01
[101] 5.964908e-01 2.294603e-01 -2.681841e-01 -2.266446e-01 -1.139958e-01
[106] -3.874984e-01 2.496174e-01 1.776306e-02 -1.448832e-01 9.533744e-02
[111] 6.140126e-01 3.051422e-02 3.330283e-01 1.569388e-03 3.274870e-01
[116] 4.714146e-01 4.366600e-01 -2.491362e-01 2.281468e-01 3.190905e-01
[121] 1.802245e-01 -1.236057e-01 8.005573e-02 -4.066484e-01 9.116235e-02
[126] 1.118097e-01 -7.202605e-05 -2.318151e-01 -7.388658e-02 6.750919e-02
[131] 1.584364e-01 4.935527e-01 6.152974e-02 2.718014e-02 1.317855e-02
[136] -3.055649e-01 -2.275995e-01 6.596450e-02 -4.787565e-01 -2.676548e-01
[141] 9.541052e-02 7.989166e-02 -1.551224e-01 -1.693429e-01 -3.877660e-01
[146] -8.581233e-02 -7.016369e-01 3.821900e-01 -1.272537e-01 -7.910551e-02
[151] 9.682448e-02 1.000536e-01 -3.564134e-02 3.084982e-01 -3.683006e-02
[156] 5.351350e-01 -1.532126e-01 -2.979541e-01 -2.669663e-01 -3.439062e-01
[161] -6.007243e-02 -3.913508e-02 3.943893e-02 -2.570801e-01 1.131801e-02
[166] 1.176401e-01 2.787600e-01 1.780364e-01 2.768778e-01 -3.445140e-01
[171] -1.433078e-01 -1.132945e-01 -1.022456e-02 -6.454409e-01 -4.285777e-01
[176] 2.964481e-02 2.537235e-01 -9.032307e-02 -2.055432e-01 -5.675727e-01
[181] -1.050987e-01 -3.797585e-01 2.935166e-01 -4.156023e-01 -9.884503e-01
[186] 5.740133e-01 -7.035021e-02 1.028268e-02 -2.107541e-01 2.527885e-02
[191] -7.269430e-02 5.344622e-02 -3.345434e-02 1.747242e-01 9.349045e-02
[196] -6.090727e-01 -8.284629e-01 1.813153e-01 -4.371045e-01 -2.219227e-01
[201] -3.126739e-02 8.664862e-01 -2.741663e-02 4.479923e-01 3.952441e-01
[206] -6.048229e-01 -1.260848e-01 1.234443e-02 6.348439e-01 1.978149e-02
[211] 2.201733e-01 3.767693e-01 1.712775e-01 -3.786599e-02 -5.414051e-02
[216] -1.957925e-01 3.636472e-01 -7.560902e-02 -6.042605e-01 3.319477e-01
[221] -1.084284e-01 2.750691e-01 -3.914279e-01 -7.611908e-02 -4.979272e-01
[226] -5.384824e-01 -1.529809e-01 -1.163480e-01 -1.512457e-01 -9.508603e-01
>
> proc.time()
user system elapsed
1.235 0.667 1.893
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: 0x621bb0577370>
> .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: 0x621bb0577370>
> .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: 0x621bb0577370>
> .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: 0x621bb0577370>
> 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: 0x621bb055f1c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x621bb055f1c0>
> .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: 0x621bb055f1c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x621bb055f1c0>
> .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: 0x621bb055f1c0>
> 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: 0x621bb0842120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x621bb0842120>
> .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: 0x621bb0842120>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x621bb0842120>
> .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: 0x621bb0842120>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x621bb0842120>
> .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: 0x621bb0842120>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x621bb0842120>
> .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: 0x621bb0842120>
> 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: 0x621baf592390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x621baf592390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x621baf592390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x621baf592390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile304948114ef650" "BufferedMatrixFile30494871d19cdc"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile304948114ef650" "BufferedMatrixFile30494871d19cdc"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x621baf4893d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x621baf4893d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x621baf4893d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x621baf4893d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x621baf4893d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x621baf4893d0>
> .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: 0x621bb0fbefa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x621bb0fbefa0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x621bb0fbefa0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x621bb0fbefa0>
> 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: 0x621baf796ff0>
> .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: 0x621baf796ff0>
> rm(P)
>
> proc.time()
user system elapsed
0.243 0.041 0.274
BufferedMatrix.Rcheck/tests/Rcodetesting.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.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.253 0.048 0.286