Ben Bolstad
| Snapshot Date: 2026-01-12 13:45 -0500 (Mon, 12 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 2026-01-15 11:58 -0500 (Thu, 15 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" | 4886 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4672 |
| 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: 2026-01-12 22:09:27 -0500 (Mon, 12 Jan 2026) |
| EndedAt: 2026-01-12 22:09:51 -0500 (Mon, 12 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
0.239 0.046 0.275
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] "Mon Jan 12 22:09:42 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] "Mon Jan 12 22:09:42 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: 0x5c231cd35370>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Jan 12 22:09:42 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] "Mon Jan 12 22:09:42 2026"
>
> ColMode(tmp2)
<pointer: 0x5c231cd35370>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.1592357 -0.2107201 -1.2121543 -1.1708630
[2,] 0.4261646 -0.7968181 0.1022643 -0.1571572
[3,] 1.2837059 -0.6101959 0.3497481 0.4011717
[4,] -0.7969544 0.3041202 1.5235770 0.3961141
> 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,] 101.1592357 0.2107201 1.2121543 1.1708630
[2,] 0.4261646 0.7968181 0.1022643 0.1571572
[3,] 1.2837059 0.6101959 0.3497481 0.4011717
[4,] 0.7969544 0.3041202 1.5235770 0.3961141
> 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,] 10.0577948 0.4590426 1.1009788 1.0820642
[2,] 0.6528128 0.8926467 0.3197878 0.3964305
[3,] 1.1330075 0.7811503 0.5913950 0.6333811
[4,] 0.8927230 0.5514710 1.2343326 0.6293759
>
> 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,] 226.73718 29.80115 37.22194 36.99151
[2,] 31.95429 34.72328 28.30014 29.12146
[3,] 37.61378 33.42170 31.26370 31.73498
[4,] 34.72418 30.81883 38.86690 31.68987
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5c231dd319b0>
> exp(tmp5)
<pointer: 0x5c231dd319b0>
> log(tmp5,2)
<pointer: 0x5c231dd319b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.9237
> Min(tmp5)
[1] 54.97727
> mean(tmp5)
[1] 72.20192
> Sum(tmp5)
[1] 14440.38
> Var(tmp5)
[1] 875.945
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.13026 69.48912 72.68915 69.18619 69.90846 71.37895 72.57539 69.59352
[9] 66.88420 70.18401
> rowSums(tmp5)
[1] 1802.605 1389.782 1453.783 1383.724 1398.169 1427.579 1451.508 1391.870
[9] 1337.684 1403.680
> rowVars(tmp5)
[1] 8130.89389 51.83541 84.59635 84.64562 80.01510 45.47990
[7] 102.66270 83.74738 31.34114 75.63086
> rowSd(tmp5)
[1] 90.171469 7.199681 9.197628 9.200305 8.945116 6.743878 10.132261
[8] 9.151359 5.598316 8.696600
> rowMax(tmp5)
[1] 471.92374 85.32716 92.47575 85.24742 89.85529 84.59144 91.64619
[8] 80.96669 77.43318 87.60632
> rowMin(tmp5)
[1] 58.05298 58.90304 55.92138 55.25080 57.35308 56.14822 57.10836 55.91722
[9] 56.36520 54.97727
>
> colMeans(tmp5)
[1] 112.48359 66.38139 70.37686 72.45308 74.36310 68.84105 73.64868
[8] 71.27824 68.89906 67.77612 69.98791 71.54463 70.26039 69.04089
[15] 69.61830 67.91320 70.58441 70.31534 72.55516 65.71710
> colSums(tmp5)
[1] 1124.8359 663.8139 703.7686 724.5308 743.6310 688.4105 736.4868
[8] 712.7824 688.9906 677.7612 699.8791 715.4463 702.6039 690.4089
[15] 696.1830 679.1320 705.8441 703.1534 725.5516 657.1710
> colVars(tmp5)
[1] 15989.95911 32.00289 116.35764 84.33452 129.08657 33.79577
[7] 127.97317 61.63029 41.92298 51.54575 57.68552 113.91727
[13] 69.36693 72.17290 66.26438 56.55693 92.06719 60.34182
[19] 82.39546 26.72809
> colSd(tmp5)
[1] 126.451410 5.657109 10.786920 9.183383 11.361627 5.813413
[7] 11.312523 7.850496 6.474796 7.179537 7.595098 10.673203
[13] 8.328681 8.495463 8.140293 7.520434 9.595165 7.768000
[19] 9.077194 5.169921
> colMax(tmp5)
[1] 471.92374 72.70015 89.85529 87.60632 92.47575 80.92706 90.06250
[8] 88.10233 80.31528 81.29432 83.34083 86.83029 82.38525 77.43318
[15] 82.06187 78.88830 85.24742 84.59144 88.62831 71.10441
> colMin(tmp5)
[1] 64.17686 58.16795 57.82169 60.61251 61.00822 62.98808 54.97727 63.00212
[9] 60.39364 58.89032 59.71841 55.25080 59.52932 55.91722 58.05298 56.83973
[17] 55.92138 57.23939 57.35308 57.11868
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] NA 69.48912 72.68915 69.18619 69.90846 71.37895 72.57539 69.59352
[9] 66.88420 70.18401
> rowSums(tmp5)
[1] NA 1389.782 1453.783 1383.724 1398.169 1427.579 1451.508 1391.870
[9] 1337.684 1403.680
> rowVars(tmp5)
[1] 8536.42408 51.83541 84.59635 84.64562 80.01510 45.47990
[7] 102.66270 83.74738 31.34114 75.63086
> rowSd(tmp5)
[1] 92.392771 7.199681 9.197628 9.200305 8.945116 6.743878 10.132261
[8] 9.151359 5.598316 8.696600
> rowMax(tmp5)
[1] NA 85.32716 92.47575 85.24742 89.85529 84.59144 91.64619 80.96669
[9] 77.43318 87.60632
> rowMin(tmp5)
[1] NA 58.90304 55.92138 55.25080 57.35308 56.14822 57.10836 55.91722
[9] 56.36520 54.97727
>
> colMeans(tmp5)
[1] 112.48359 NA 70.37686 72.45308 74.36310 68.84105 73.64868
[8] 71.27824 68.89906 67.77612 69.98791 71.54463 70.26039 69.04089
[15] 69.61830 67.91320 70.58441 70.31534 72.55516 65.71710
> colSums(tmp5)
[1] 1124.8359 NA 703.7686 724.5308 743.6310 688.4105 736.4868
[8] 712.7824 688.9906 677.7612 699.8791 715.4463 702.6039 690.4089
[15] 696.1830 679.1320 705.8441 703.1534 725.5516 657.1710
> colVars(tmp5)
[1] 15989.95911 NA 116.35764 84.33452 129.08657 33.79577
[7] 127.97317 61.63029 41.92298 51.54575 57.68552 113.91727
[13] 69.36693 72.17290 66.26438 56.55693 92.06719 60.34182
[19] 82.39546 26.72809
> colSd(tmp5)
[1] 126.451410 NA 10.786920 9.183383 11.361627 5.813413
[7] 11.312523 7.850496 6.474796 7.179537 7.595098 10.673203
[13] 8.328681 8.495463 8.140293 7.520434 9.595165 7.768000
[19] 9.077194 5.169921
> colMax(tmp5)
[1] 471.92374 NA 89.85529 87.60632 92.47575 80.92706 90.06250
[8] 88.10233 80.31528 81.29432 83.34083 86.83029 82.38525 77.43318
[15] 82.06187 78.88830 85.24742 84.59144 88.62831 71.10441
> colMin(tmp5)
[1] 64.17686 NA 57.82169 60.61251 61.00822 62.98808 54.97727 63.00212
[9] 60.39364 58.89032 59.71841 55.25080 59.52932 55.91722 58.05298 56.83973
[17] 55.92138 57.23939 57.35308 57.11868
>
> Max(tmp5,na.rm=TRUE)
[1] 471.9237
> Min(tmp5,na.rm=TRUE)
[1] 54.97727
> mean(tmp5,na.rm=TRUE)
[1] 72.25305
> Sum(tmp5,na.rm=TRUE)
[1] 14378.36
> Var(tmp5,na.rm=TRUE)
[1] 879.8435
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.60937 69.48912 72.68915 69.18619 69.90846 71.37895 72.57539 69.59352
[9] 66.88420 70.18401
> rowSums(tmp5,na.rm=TRUE)
[1] 1740.578 1389.782 1453.783 1383.724 1398.169 1427.579 1451.508 1391.870
[9] 1337.684 1403.680
> rowVars(tmp5,na.rm=TRUE)
[1] 8536.42408 51.83541 84.59635 84.64562 80.01510 45.47990
[7] 102.66270 83.74738 31.34114 75.63086
> rowSd(tmp5,na.rm=TRUE)
[1] 92.392771 7.199681 9.197628 9.200305 8.945116 6.743878 10.132261
[8] 9.151359 5.598316 8.696600
> rowMax(tmp5,na.rm=TRUE)
[1] 471.92374 85.32716 92.47575 85.24742 89.85529 84.59144 91.64619
[8] 80.96669 77.43318 87.60632
> rowMin(tmp5,na.rm=TRUE)
[1] 58.05298 58.90304 55.92138 55.25080 57.35308 56.14822 57.10836 55.91722
[9] 56.36520 54.97727
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.48359 66.86519 70.37686 72.45308 74.36310 68.84105 73.64868
[8] 71.27824 68.89906 67.77612 69.98791 71.54463 70.26039 69.04089
[15] 69.61830 67.91320 70.58441 70.31534 72.55516 65.71710
> colSums(tmp5,na.rm=TRUE)
[1] 1124.8359 601.7867 703.7686 724.5308 743.6310 688.4105 736.4868
[8] 712.7824 688.9906 677.7612 699.8791 715.4463 702.6039 690.4089
[15] 696.1830 679.1320 705.8441 703.1534 725.5516 657.1710
> colVars(tmp5,na.rm=TRUE)
[1] 15989.95911 33.37003 116.35764 84.33452 129.08657 33.79577
[7] 127.97317 61.63029 41.92298 51.54575 57.68552 113.91727
[13] 69.36693 72.17290 66.26438 56.55693 92.06719 60.34182
[19] 82.39546 26.72809
> colSd(tmp5,na.rm=TRUE)
[1] 126.451410 5.776680 10.786920 9.183383 11.361627 5.813413
[7] 11.312523 7.850496 6.474796 7.179537 7.595098 10.673203
[13] 8.328681 8.495463 8.140293 7.520434 9.595165 7.768000
[19] 9.077194 5.169921
> colMax(tmp5,na.rm=TRUE)
[1] 471.92374 72.70015 89.85529 87.60632 92.47575 80.92706 90.06250
[8] 88.10233 80.31528 81.29432 83.34083 86.83029 82.38525 77.43318
[15] 82.06187 78.88830 85.24742 84.59144 88.62831 71.10441
> colMin(tmp5,na.rm=TRUE)
[1] 64.17686 58.16795 57.82169 60.61251 61.00822 62.98808 54.97727 63.00212
[9] 60.39364 58.89032 59.71841 55.25080 59.52932 55.91722 58.05298 56.83973
[17] 55.92138 57.23939 57.35308 57.11868
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 69.48912 72.68915 69.18619 69.90846 71.37895 72.57539 69.59352
[9] 66.88420 70.18401
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1389.782 1453.783 1383.724 1398.169 1427.579 1451.508 1391.870
[9] 1337.684 1403.680
> rowVars(tmp5,na.rm=TRUE)
[1] NA 51.83541 84.59635 84.64562 80.01510 45.47990 102.66270
[8] 83.74738 31.34114 75.63086
> rowSd(tmp5,na.rm=TRUE)
[1] NA 7.199681 9.197628 9.200305 8.945116 6.743878 10.132261
[8] 9.151359 5.598316 8.696600
> rowMax(tmp5,na.rm=TRUE)
[1] NA 85.32716 92.47575 85.24742 89.85529 84.59144 91.64619 80.96669
[9] 77.43318 87.60632
> rowMin(tmp5,na.rm=TRUE)
[1] NA 58.90304 55.92138 55.25080 57.35308 56.14822 57.10836 55.91722
[9] 56.36520 54.97727
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 72.54580 NaN 69.58844 71.94865 75.84697 69.37194 72.32781 70.64950
[9] 68.71249 66.27410 70.92928 71.10609 70.23331 69.94274 70.90334 67.76554
[17] 70.51796 70.74453 72.60403 65.32005
> colSums(tmp5,na.rm=TRUE)
[1] 652.9122 0.0000 626.2960 647.5378 682.6228 624.3474 650.9503 635.8455
[9] 618.4124 596.4669 638.3635 639.9548 632.0998 629.4847 638.1301 609.8898
[17] 634.6617 636.7007 653.4363 587.8805
> colVars(tmp5,na.rm=TRUE)
[1] 44.64560 NA 123.90937 92.01375 120.45116 34.84954 124.34213
[8] 64.88677 46.77173 32.60818 54.92669 125.99329 78.02955 72.04441
[15] 55.97010 63.38125 103.52591 65.81230 92.66802 28.29561
> colSd(tmp5,na.rm=TRUE)
[1] 6.681736 NA 11.131458 9.592380 10.975025 5.903349 11.150880
[8] 8.055232 6.838986 5.710357 7.411255 11.224673 8.833434 8.487898
[15] 7.481316 7.961234 10.174769 8.112478 9.626423 5.319362
> colMax(tmp5,na.rm=TRUE)
[1] 80.64396 -Inf 89.85529 87.60632 92.47575 80.92706 90.06250 88.10233
[9] 80.31528 74.02756 83.34083 86.83029 82.38525 77.43318 82.06187 78.88830
[17] 85.24742 84.59144 88.62831 71.10441
> colMin(tmp5,na.rm=TRUE)
[1] 64.17686 Inf 57.82169 60.61251 62.61951 62.98808 54.97727 63.00212
[9] 60.39364 58.89032 59.71841 55.25080 59.52932 55.91722 59.60145 56.83973
[17] 55.92138 57.23939 57.35308 57.11868
>
>
>
>
> 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] 216.8128 227.8556 161.5503 208.3119 343.3640 199.9058 249.4231 231.0268
[9] 270.3664 163.9951
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 216.8128 227.8556 161.5503 208.3119 343.3640 199.9058 249.4231 231.0268
[9] 270.3664 163.9951
>
>
>
> 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 5.684342e-14 -5.684342e-14 -2.273737e-13 -5.684342e-14
[6] 4.263256e-14 0.000000e+00 5.684342e-14 -2.842171e-14 0.000000e+00
[11] 8.526513e-14 -1.705303e-13 -5.684342e-14 -5.684342e-14 1.136868e-13
[16] -2.842171e-14 -2.557954e-13 1.136868e-13 -5.684342e-14 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
7 4
6 1
3 8
1 8
4 17
10 1
2 12
6 19
5 14
6 19
2 11
1 4
4 20
5 6
7 16
8 13
1 13
9 8
7 4
9 5
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] 2.494194
> Min(tmp)
[1] -3.343938
> mean(tmp)
[1] 0.04502868
> Sum(tmp)
[1] 4.502868
> Var(tmp)
[1] 0.9063928
>
> rowMeans(tmp)
[1] 0.04502868
> rowSums(tmp)
[1] 4.502868
> rowVars(tmp)
[1] 0.9063928
> rowSd(tmp)
[1] 0.9520466
> rowMax(tmp)
[1] 2.494194
> rowMin(tmp)
[1] -3.343938
>
> colMeans(tmp)
[1] 0.622045595 0.126352802 -0.424901892 -3.343938335 1.438783044
[6] 1.321942909 0.027236390 -0.374325204 2.494193610 0.329408121
[11] 0.088460800 0.199819523 0.156222417 -0.031428149 -1.477149698
[16] 0.133358730 -1.846676149 1.783824967 0.515620316 0.272251779
[21] -1.551350390 1.487589943 -0.301383233 -0.809156030 0.374163719
[26] -0.090828668 -0.232373808 -1.103681036 -0.736170553 -0.664626057
[31] -0.051598737 1.056422870 -0.486903404 -1.330049264 -0.087525822
[36] -0.199209545 1.911982671 -0.181317835 0.526154989 0.159794874
[41] -0.713955400 0.354660127 -0.123129588 1.276944474 1.860815332
[46] 0.506791111 0.960544522 0.089599334 0.956715704 -0.893532512
[51] -1.168907121 -0.258760665 -1.329685258 -0.777991319 0.291203057
[56] -0.449069922 1.777628787 -0.122023684 -0.690250740 0.139261478
[61] 0.211220131 -0.391380996 1.634648817 -0.594812736 -0.299394575
[66] -0.950848669 -0.738468987 0.694010215 -0.874295080 0.264181398
[71] 0.283286366 0.250670591 0.009964733 0.489775426 -0.450737677
[76] 1.583265294 0.899540321 0.249056081 0.518486885 0.553103362
[81] 0.682177026 -1.073939710 -0.042970401 0.332040822 0.780772192
[86] -0.909663776 0.582574685 1.826395439 -1.831088118 0.350960114
[91] -0.661024020 0.707640331 -0.626892673 -0.224350830 1.497772503
[96] -0.703041696 -0.739411070 -0.778699791 0.989600698 -0.385148668
> colSums(tmp)
[1] 0.622045595 0.126352802 -0.424901892 -3.343938335 1.438783044
[6] 1.321942909 0.027236390 -0.374325204 2.494193610 0.329408121
[11] 0.088460800 0.199819523 0.156222417 -0.031428149 -1.477149698
[16] 0.133358730 -1.846676149 1.783824967 0.515620316 0.272251779
[21] -1.551350390 1.487589943 -0.301383233 -0.809156030 0.374163719
[26] -0.090828668 -0.232373808 -1.103681036 -0.736170553 -0.664626057
[31] -0.051598737 1.056422870 -0.486903404 -1.330049264 -0.087525822
[36] -0.199209545 1.911982671 -0.181317835 0.526154989 0.159794874
[41] -0.713955400 0.354660127 -0.123129588 1.276944474 1.860815332
[46] 0.506791111 0.960544522 0.089599334 0.956715704 -0.893532512
[51] -1.168907121 -0.258760665 -1.329685258 -0.777991319 0.291203057
[56] -0.449069922 1.777628787 -0.122023684 -0.690250740 0.139261478
[61] 0.211220131 -0.391380996 1.634648817 -0.594812736 -0.299394575
[66] -0.950848669 -0.738468987 0.694010215 -0.874295080 0.264181398
[71] 0.283286366 0.250670591 0.009964733 0.489775426 -0.450737677
[76] 1.583265294 0.899540321 0.249056081 0.518486885 0.553103362
[81] 0.682177026 -1.073939710 -0.042970401 0.332040822 0.780772192
[86] -0.909663776 0.582574685 1.826395439 -1.831088118 0.350960114
[91] -0.661024020 0.707640331 -0.626892673 -0.224350830 1.497772503
[96] -0.703041696 -0.739411070 -0.778699791 0.989600698 -0.385148668
> 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] 0.622045595 0.126352802 -0.424901892 -3.343938335 1.438783044
[6] 1.321942909 0.027236390 -0.374325204 2.494193610 0.329408121
[11] 0.088460800 0.199819523 0.156222417 -0.031428149 -1.477149698
[16] 0.133358730 -1.846676149 1.783824967 0.515620316 0.272251779
[21] -1.551350390 1.487589943 -0.301383233 -0.809156030 0.374163719
[26] -0.090828668 -0.232373808 -1.103681036 -0.736170553 -0.664626057
[31] -0.051598737 1.056422870 -0.486903404 -1.330049264 -0.087525822
[36] -0.199209545 1.911982671 -0.181317835 0.526154989 0.159794874
[41] -0.713955400 0.354660127 -0.123129588 1.276944474 1.860815332
[46] 0.506791111 0.960544522 0.089599334 0.956715704 -0.893532512
[51] -1.168907121 -0.258760665 -1.329685258 -0.777991319 0.291203057
[56] -0.449069922 1.777628787 -0.122023684 -0.690250740 0.139261478
[61] 0.211220131 -0.391380996 1.634648817 -0.594812736 -0.299394575
[66] -0.950848669 -0.738468987 0.694010215 -0.874295080 0.264181398
[71] 0.283286366 0.250670591 0.009964733 0.489775426 -0.450737677
[76] 1.583265294 0.899540321 0.249056081 0.518486885 0.553103362
[81] 0.682177026 -1.073939710 -0.042970401 0.332040822 0.780772192
[86] -0.909663776 0.582574685 1.826395439 -1.831088118 0.350960114
[91] -0.661024020 0.707640331 -0.626892673 -0.224350830 1.497772503
[96] -0.703041696 -0.739411070 -0.778699791 0.989600698 -0.385148668
> colMin(tmp)
[1] 0.622045595 0.126352802 -0.424901892 -3.343938335 1.438783044
[6] 1.321942909 0.027236390 -0.374325204 2.494193610 0.329408121
[11] 0.088460800 0.199819523 0.156222417 -0.031428149 -1.477149698
[16] 0.133358730 -1.846676149 1.783824967 0.515620316 0.272251779
[21] -1.551350390 1.487589943 -0.301383233 -0.809156030 0.374163719
[26] -0.090828668 -0.232373808 -1.103681036 -0.736170553 -0.664626057
[31] -0.051598737 1.056422870 -0.486903404 -1.330049264 -0.087525822
[36] -0.199209545 1.911982671 -0.181317835 0.526154989 0.159794874
[41] -0.713955400 0.354660127 -0.123129588 1.276944474 1.860815332
[46] 0.506791111 0.960544522 0.089599334 0.956715704 -0.893532512
[51] -1.168907121 -0.258760665 -1.329685258 -0.777991319 0.291203057
[56] -0.449069922 1.777628787 -0.122023684 -0.690250740 0.139261478
[61] 0.211220131 -0.391380996 1.634648817 -0.594812736 -0.299394575
[66] -0.950848669 -0.738468987 0.694010215 -0.874295080 0.264181398
[71] 0.283286366 0.250670591 0.009964733 0.489775426 -0.450737677
[76] 1.583265294 0.899540321 0.249056081 0.518486885 0.553103362
[81] 0.682177026 -1.073939710 -0.042970401 0.332040822 0.780772192
[86] -0.909663776 0.582574685 1.826395439 -1.831088118 0.350960114
[91] -0.661024020 0.707640331 -0.626892673 -0.224350830 1.497772503
[96] -0.703041696 -0.739411070 -0.778699791 0.989600698 -0.385148668
> colMedians(tmp)
[1] 0.622045595 0.126352802 -0.424901892 -3.343938335 1.438783044
[6] 1.321942909 0.027236390 -0.374325204 2.494193610 0.329408121
[11] 0.088460800 0.199819523 0.156222417 -0.031428149 -1.477149698
[16] 0.133358730 -1.846676149 1.783824967 0.515620316 0.272251779
[21] -1.551350390 1.487589943 -0.301383233 -0.809156030 0.374163719
[26] -0.090828668 -0.232373808 -1.103681036 -0.736170553 -0.664626057
[31] -0.051598737 1.056422870 -0.486903404 -1.330049264 -0.087525822
[36] -0.199209545 1.911982671 -0.181317835 0.526154989 0.159794874
[41] -0.713955400 0.354660127 -0.123129588 1.276944474 1.860815332
[46] 0.506791111 0.960544522 0.089599334 0.956715704 -0.893532512
[51] -1.168907121 -0.258760665 -1.329685258 -0.777991319 0.291203057
[56] -0.449069922 1.777628787 -0.122023684 -0.690250740 0.139261478
[61] 0.211220131 -0.391380996 1.634648817 -0.594812736 -0.299394575
[66] -0.950848669 -0.738468987 0.694010215 -0.874295080 0.264181398
[71] 0.283286366 0.250670591 0.009964733 0.489775426 -0.450737677
[76] 1.583265294 0.899540321 0.249056081 0.518486885 0.553103362
[81] 0.682177026 -1.073939710 -0.042970401 0.332040822 0.780772192
[86] -0.909663776 0.582574685 1.826395439 -1.831088118 0.350960114
[91] -0.661024020 0.707640331 -0.626892673 -0.224350830 1.497772503
[96] -0.703041696 -0.739411070 -0.778699791 0.989600698 -0.385148668
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.6220456 0.1263528 -0.4249019 -3.343938 1.438783 1.321943 0.02723639
[2,] 0.6220456 0.1263528 -0.4249019 -3.343938 1.438783 1.321943 0.02723639
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3743252 2.494194 0.3294081 0.0884608 0.1998195 0.1562224 -0.03142815
[2,] -0.3743252 2.494194 0.3294081 0.0884608 0.1998195 0.1562224 -0.03142815
[,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] -1.47715 0.1333587 -1.846676 1.783825 0.5156203 0.2722518 -1.55135 1.48759
[2,] -1.47715 0.1333587 -1.846676 1.783825 0.5156203 0.2722518 -1.55135 1.48759
[,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] -0.3013832 -0.809156 0.3741637 -0.09082867 -0.2323738 -1.103681 -0.7361706
[2,] -0.3013832 -0.809156 0.3741637 -0.09082867 -0.2323738 -1.103681 -0.7361706
[,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.6646261 -0.05159874 1.056423 -0.4869034 -1.330049 -0.08752582
[2,] -0.6646261 -0.05159874 1.056423 -0.4869034 -1.330049 -0.08752582
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.1992095 1.911983 -0.1813178 0.526155 0.1597949 -0.7139554 0.3546601
[2,] -0.1992095 1.911983 -0.1813178 0.526155 0.1597949 -0.7139554 0.3546601
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1231296 1.276944 1.860815 0.5067911 0.9605445 0.08959933 0.9567157
[2,] -0.1231296 1.276944 1.860815 0.5067911 0.9605445 0.08959933 0.9567157
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.8935325 -1.168907 -0.2587607 -1.329685 -0.7779913 0.2912031 -0.4490699
[2,] -0.8935325 -1.168907 -0.2587607 -1.329685 -0.7779913 0.2912031 -0.4490699
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.777629 -0.1220237 -0.6902507 0.1392615 0.2112201 -0.391381 1.634649
[2,] 1.777629 -0.1220237 -0.6902507 0.1392615 0.2112201 -0.391381 1.634649
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.5948127 -0.2993946 -0.9508487 -0.738469 0.6940102 -0.8742951 0.2641814
[2,] -0.5948127 -0.2993946 -0.9508487 -0.738469 0.6940102 -0.8742951 0.2641814
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.2832864 0.2506706 0.009964733 0.4897754 -0.4507377 1.583265 0.8995403
[2,] 0.2832864 0.2506706 0.009964733 0.4897754 -0.4507377 1.583265 0.8995403
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.2490561 0.5184869 0.5531034 0.682177 -1.07394 -0.0429704 0.3320408
[2,] 0.2490561 0.5184869 0.5531034 0.682177 -1.07394 -0.0429704 0.3320408
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.7807722 -0.9096638 0.5825747 1.826395 -1.831088 0.3509601 -0.661024
[2,] 0.7807722 -0.9096638 0.5825747 1.826395 -1.831088 0.3509601 -0.661024
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.7076403 -0.6268927 -0.2243508 1.497773 -0.7030417 -0.7394111 -0.7786998
[2,] 0.7076403 -0.6268927 -0.2243508 1.497773 -0.7030417 -0.7394111 -0.7786998
[,99] [,100]
[1,] 0.9896007 -0.3851487
[2,] 0.9896007 -0.3851487
>
>
> Max(tmp2)
[1] 2.843563
> Min(tmp2)
[1] -2.739669
> mean(tmp2)
[1] 0.06630719
> Sum(tmp2)
[1] 6.630719
> Var(tmp2)
[1] 0.8699063
>
> rowMeans(tmp2)
[1] 0.361177250 -0.605823511 1.152284133 -0.786191789 1.106665073
[6] -0.209612751 -0.400832202 -0.857127858 1.899947775 1.402502084
[11] -0.431056247 0.208842081 1.848799400 1.828357540 -1.230260084
[16] 2.188738782 0.458605616 -1.586521824 -0.416694073 -0.076386127
[21] -0.838003547 -0.502149760 0.709553632 0.076368989 -1.292862181
[26] 0.513694213 -1.122080369 -0.244445196 0.118575909 0.804670813
[31] -0.892304213 -0.700889553 -0.434594630 0.239009969 -2.739668760
[36] 1.025332619 0.692583420 -0.050749836 1.362730250 0.730552095
[41] 0.944149234 -0.833801652 -0.231502574 0.599015621 -0.338530220
[46] -0.003473357 -0.010223207 -0.653539511 -1.158633107 0.308282297
[51] -0.091692871 -0.426829884 0.505024373 1.401291275 0.091822716
[56] -0.310779826 0.078409983 -0.307922276 2.037459410 -0.362105074
[61] 0.285103434 -0.778082655 -0.874556703 -1.316007353 0.284147491
[66] -0.654170400 0.379726004 0.340769083 -0.461917949 -0.366570080
[71] 0.246427851 0.701680524 0.138818019 0.051769860 1.372564136
[76] 0.096299337 0.823344606 1.184966116 0.879277331 -0.895455716
[81] 2.843562968 -0.182547379 0.866087124 0.526174532 0.036474299
[86] -0.512772016 0.251110160 -0.842315377 0.157906413 -0.746284081
[91] -0.582765648 -0.801838035 1.953603457 -0.666969044 1.465266795
[96] -0.677475556 -0.596442162 -0.365587839 -1.147039710 -0.332721371
> rowSums(tmp2)
[1] 0.361177250 -0.605823511 1.152284133 -0.786191789 1.106665073
[6] -0.209612751 -0.400832202 -0.857127858 1.899947775 1.402502084
[11] -0.431056247 0.208842081 1.848799400 1.828357540 -1.230260084
[16] 2.188738782 0.458605616 -1.586521824 -0.416694073 -0.076386127
[21] -0.838003547 -0.502149760 0.709553632 0.076368989 -1.292862181
[26] 0.513694213 -1.122080369 -0.244445196 0.118575909 0.804670813
[31] -0.892304213 -0.700889553 -0.434594630 0.239009969 -2.739668760
[36] 1.025332619 0.692583420 -0.050749836 1.362730250 0.730552095
[41] 0.944149234 -0.833801652 -0.231502574 0.599015621 -0.338530220
[46] -0.003473357 -0.010223207 -0.653539511 -1.158633107 0.308282297
[51] -0.091692871 -0.426829884 0.505024373 1.401291275 0.091822716
[56] -0.310779826 0.078409983 -0.307922276 2.037459410 -0.362105074
[61] 0.285103434 -0.778082655 -0.874556703 -1.316007353 0.284147491
[66] -0.654170400 0.379726004 0.340769083 -0.461917949 -0.366570080
[71] 0.246427851 0.701680524 0.138818019 0.051769860 1.372564136
[76] 0.096299337 0.823344606 1.184966116 0.879277331 -0.895455716
[81] 2.843562968 -0.182547379 0.866087124 0.526174532 0.036474299
[86] -0.512772016 0.251110160 -0.842315377 0.157906413 -0.746284081
[91] -0.582765648 -0.801838035 1.953603457 -0.666969044 1.465266795
[96] -0.677475556 -0.596442162 -0.365587839 -1.147039710 -0.332721371
> 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] 0.361177250 -0.605823511 1.152284133 -0.786191789 1.106665073
[6] -0.209612751 -0.400832202 -0.857127858 1.899947775 1.402502084
[11] -0.431056247 0.208842081 1.848799400 1.828357540 -1.230260084
[16] 2.188738782 0.458605616 -1.586521824 -0.416694073 -0.076386127
[21] -0.838003547 -0.502149760 0.709553632 0.076368989 -1.292862181
[26] 0.513694213 -1.122080369 -0.244445196 0.118575909 0.804670813
[31] -0.892304213 -0.700889553 -0.434594630 0.239009969 -2.739668760
[36] 1.025332619 0.692583420 -0.050749836 1.362730250 0.730552095
[41] 0.944149234 -0.833801652 -0.231502574 0.599015621 -0.338530220
[46] -0.003473357 -0.010223207 -0.653539511 -1.158633107 0.308282297
[51] -0.091692871 -0.426829884 0.505024373 1.401291275 0.091822716
[56] -0.310779826 0.078409983 -0.307922276 2.037459410 -0.362105074
[61] 0.285103434 -0.778082655 -0.874556703 -1.316007353 0.284147491
[66] -0.654170400 0.379726004 0.340769083 -0.461917949 -0.366570080
[71] 0.246427851 0.701680524 0.138818019 0.051769860 1.372564136
[76] 0.096299337 0.823344606 1.184966116 0.879277331 -0.895455716
[81] 2.843562968 -0.182547379 0.866087124 0.526174532 0.036474299
[86] -0.512772016 0.251110160 -0.842315377 0.157906413 -0.746284081
[91] -0.582765648 -0.801838035 1.953603457 -0.666969044 1.465266795
[96] -0.677475556 -0.596442162 -0.365587839 -1.147039710 -0.332721371
> rowMin(tmp2)
[1] 0.361177250 -0.605823511 1.152284133 -0.786191789 1.106665073
[6] -0.209612751 -0.400832202 -0.857127858 1.899947775 1.402502084
[11] -0.431056247 0.208842081 1.848799400 1.828357540 -1.230260084
[16] 2.188738782 0.458605616 -1.586521824 -0.416694073 -0.076386127
[21] -0.838003547 -0.502149760 0.709553632 0.076368989 -1.292862181
[26] 0.513694213 -1.122080369 -0.244445196 0.118575909 0.804670813
[31] -0.892304213 -0.700889553 -0.434594630 0.239009969 -2.739668760
[36] 1.025332619 0.692583420 -0.050749836 1.362730250 0.730552095
[41] 0.944149234 -0.833801652 -0.231502574 0.599015621 -0.338530220
[46] -0.003473357 -0.010223207 -0.653539511 -1.158633107 0.308282297
[51] -0.091692871 -0.426829884 0.505024373 1.401291275 0.091822716
[56] -0.310779826 0.078409983 -0.307922276 2.037459410 -0.362105074
[61] 0.285103434 -0.778082655 -0.874556703 -1.316007353 0.284147491
[66] -0.654170400 0.379726004 0.340769083 -0.461917949 -0.366570080
[71] 0.246427851 0.701680524 0.138818019 0.051769860 1.372564136
[76] 0.096299337 0.823344606 1.184966116 0.879277331 -0.895455716
[81] 2.843562968 -0.182547379 0.866087124 0.526174532 0.036474299
[86] -0.512772016 0.251110160 -0.842315377 0.157906413 -0.746284081
[91] -0.582765648 -0.801838035 1.953603457 -0.666969044 1.465266795
[96] -0.677475556 -0.596442162 -0.365587839 -1.147039710 -0.332721371
>
> colMeans(tmp2)
[1] 0.06630719
> colSums(tmp2)
[1] 6.630719
> colVars(tmp2)
[1] 0.8699063
> colSd(tmp2)
[1] 0.9326877
> colMax(tmp2)
[1] 2.843563
> colMin(tmp2)
[1] -2.739669
> colMedians(tmp2)
[1] -0.006848282
> colRanges(tmp2)
[,1]
[1,] -2.739669
[2,] 2.843563
>
> 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] -1.1681415 0.3543329 -0.2525929 0.5674405 4.3975116 -1.2636255
[7] 4.4310629 -2.5635992 4.0860707 6.7634701
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.18285407
[2,] -0.68579780
[3,] -0.02080333
[4,] 0.52328489
[5,] 1.64347422
>
> rowApply(tmp,sum)
[1] 2.0452506 1.0545731 3.2185974 0.3957538 5.0050510 -0.2330379
[7] 5.3728421 1.2186548 0.9941630 -3.7199182
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 9 2 3 9 6 4 1 2 3
[2,] 6 1 3 8 8 3 1 4 8 10
[3,] 1 5 6 6 4 2 9 8 4 6
[4,] 7 2 7 5 5 10 3 5 3 2
[5,] 3 7 4 10 7 7 6 10 7 9
[6,] 4 3 9 7 2 1 5 2 10 4
[7,] 2 10 5 4 6 4 10 9 1 8
[8,] 10 4 1 1 3 5 2 3 6 5
[9,] 5 8 10 2 1 8 8 7 9 1
[10,] 9 6 8 9 10 9 7 6 5 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.50190282 0.86567600 -2.72795643 -0.22841638 0.11373693 0.41330427
[7] -1.55214093 2.94579857 2.58002082 3.53866662 0.08837278 2.92120283
[13] 0.95889779 1.84840148 -1.48649696 0.44575275 -4.64835756 3.57367617
[19] -1.90660195 -1.05484274
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8174086
[2,] -0.9064591
[3,] -0.8879682
[4,] 0.3666246
[5,] 0.7433085
>
> rowApply(tmp,sum)
[1] -0.873991536 0.622966176 0.111277037 0.004305588 4.322233940
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 1 16 3 3
[2,] 8 8 14 11 16
[3,] 19 2 6 6 2
[4,] 4 10 9 15 9
[5,] 7 18 5 10 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.3666246 -0.36639226 0.8527075 -0.7618595 -0.39285030 0.07710151
[2,] -1.8174086 -0.39795185 -1.3569841 -0.1163527 1.44898875 0.18116250
[3,] 0.7433085 0.63326336 -0.4950202 0.2057765 -0.98257454 0.30057314
[4,] -0.8879682 -0.08304114 -0.3911860 0.2331801 -0.09916354 -0.35691996
[5,] -0.9064591 1.07979789 -1.3374736 0.2108392 0.13933655 0.21138709
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.0918141 -0.09608247 -0.34496100 0.7275560 2.1332726 0.09124584
[2,] -0.4549193 0.45025524 0.91930607 1.4636722 -0.1523063 1.14316289
[3,] -1.9238656 1.88958251 -0.07932555 0.5519022 -0.1678910 0.69403407
[4,] 1.7657383 -0.57856135 1.42722722 0.1878261 0.1512554 0.73065276
[5,] -0.8472802 1.28060464 0.65777408 0.6077101 -1.8759579 0.26210726
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.3938909 -1.468332 -0.8157679 -0.3468354 -0.64460358 -0.9655042
[2,] -1.2756863 1.657913 0.7357133 -1.1614471 -1.08915370 0.9925217
[3,] 0.8764706 1.236880 -1.3796391 0.3178537 -2.15962448 1.4014465
[4,] -0.3132062 -0.760420 -0.3184700 1.7608988 0.05287633 0.3876929
[5,] 2.0652106 1.182359 0.2916668 -0.1247173 -0.80785214 1.7575192
[,19] [,20]
[1,] 0.8225907 0.74380306
[2,] -0.5952250 0.04770524
[3,] -1.8366100 0.28473594
[4,] -1.1712177 -1.73288832
[5,] 0.8738601 -0.39819867
>
>
> 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 : 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 -0.06866676 -1.087034 -1.03858 1.528374 -0.5223012 0.3530989 -0.7725881
col8 col9 col10 col11 col12 col13 col14
row1 1.041226 0.4460632 -0.4927826 1.876148 -0.02395372 -0.8914898 1.78085
col15 col16 col17 col18 col19 col20
row1 -1.402067 -2.077017 -0.2621083 -0.1698218 1.280314 0.6818309
> tmp[,"col10"]
col10
row1 -0.4927826
row2 0.9081065
row3 0.5506221
row4 -0.6448453
row5 -0.3960525
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.06866676 -1.087034 -1.038580 1.5283742 -0.5223012 0.3530989 -0.7725881
row5 -0.78693247 0.364251 0.753738 0.1865841 -0.5250215 1.0795053 0.8227968
col8 col9 col10 col11 col12 col13
row1 1.041226 0.4460632 -0.4927826 1.8761477 -0.02395372 -0.8914898
row5 -1.766714 -2.3273222 -0.3960525 0.4616141 -0.46001567 -1.4839412
col14 col15 col16 col17 col18 col19
row1 1.7808500 -1.4020667 -2.07701662 -0.2621083 -0.1698218 1.2803136
row5 -0.6351194 0.1277307 -0.08412469 -0.6973153 0.2680801 -0.6432226
col20
row1 0.6818309
row5 1.0104065
> tmp[,c("col6","col20")]
col6 col20
row1 0.3530989 0.6818309
row2 0.6780606 -0.6810540
row3 -0.2014580 -0.3911186
row4 1.0927322 -1.2742446
row5 1.0795053 1.0104065
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.3530989 0.6818309
row5 1.0795053 1.0104065
>
>
>
>
> 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 50.70564 50.45939 50.35674 49.49196 50.26218 105.7677 49.15694 48.22996
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.03004 49.45909 48.91192 49.3829 46.92707 51.14776 49.97088 50.80323
col17 col18 col19 col20
row1 49.56419 49.73807 50.86084 105.5821
> tmp[,"col10"]
col10
row1 49.45909
row2 30.32571
row3 29.89851
row4 30.49098
row5 50.93216
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.70564 50.45939 50.35674 49.49196 50.26218 105.7677 49.15694 48.22996
row5 49.73808 50.04193 49.75476 48.28552 50.98126 103.4508 50.47489 50.69457
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.03004 49.45909 48.91192 49.38290 46.92707 51.14776 49.97088 50.80323
row5 49.92833 50.93216 49.07706 49.51241 50.79262 50.54702 49.30887 52.28745
col17 col18 col19 col20
row1 49.56419 49.73807 50.86084 105.5821
row5 52.49994 50.28871 49.17951 104.8141
> tmp[,c("col6","col20")]
col6 col20
row1 105.76766 105.58214
row2 74.83931 75.87560
row3 74.53087 75.66713
row4 75.29130 75.62774
row5 103.45081 104.81415
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7677 105.5821
row5 103.4508 104.8141
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7677 105.5821
row5 103.4508 104.8141
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.7526368
[2,] -1.8568709
[3,] -0.6897805
[4,] -0.5961660
[5,] 0.6010085
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5272603 -0.21269894
[2,] 0.4605608 0.36107008
[3,] 0.9875991 -0.07211715
[4,] -1.2666184 0.37975677
[5,] -1.4479813 -0.30702352
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.5681039 -1.6138569
[2,] 1.0686840 0.4637844
[3,] -0.3202134 1.6789271
[4,] 2.7503572 -0.8791836
[5,] 0.8446649 0.3979375
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.5681039
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.5681039
[2,] 1.0686840
>
>
>
> 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 0.5862857 0.1319525 -0.8243812 0.9438292 2.5487169 1.6961142 1.8290968
row1 0.6866613 -0.3302455 0.4850446 -0.2858952 -0.5358334 0.9681791 -0.6442747
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.6791524 0.1965890 -2.27886881 -0.3764709 -0.48702553 -2.1782170
row1 -0.3740073 -0.2444768 -0.08382065 -0.8058981 0.09092256 -0.1151769
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.1332193 1.081406 -0.110244 0.2468780 -0.2983254 0.3268068 -1.8342542
row1 -0.4367102 0.552764 1.694532 -0.4323043 0.8197818 -0.1873402 0.1902193
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 2.226981 -0.5499932 -0.3476727 -0.7404941 0.6539505 -0.5667577 -0.7011841
[,8] [,9] [,10]
row2 -1.272659 2.106453 -1.528673
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.671659 0.4844969 0.2595819 -0.2104469 0.07910978 -0.04338866 1.355734
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6923835 -1.026941 0.5215266 -0.04657201 -1.898057 -0.784287 0.9086701
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.37311 0.6072618 -0.6122071 1.757229 0.05832715 -1.056807
>
>
> 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: 0x5c231da32ed0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b2a465f96"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b4c3152bd"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b65b177d7"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b1a9c7d9c"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b6a362746"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b200174b3"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b2cf35484"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b57a1e248"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5bcb8292b"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b1c60deeb"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b2d6658c5"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5bb539494"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b4af335f1"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b4c088c71"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM127a5b5a32a9d9"
>
>
> ### 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: 0x5c231e284150>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5c231e284150>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5c231e284150>
> rowMedians(tmp)
[1] 5.148907e-01 1.093272e-01 6.579084e-01 1.994509e-01 -1.833722e-01
[6] -2.395649e-01 -7.468918e-01 -2.338463e-02 -1.656382e-01 2.706874e-01
[11] 5.551737e-02 -3.140367e-02 1.020290e-01 1.726721e-01 4.945456e-01
[16] 2.492470e-01 -4.260638e-02 7.205701e-01 4.431561e-01 -2.802710e-01
[21] 8.085634e-02 2.550723e-01 5.711951e-01 9.731504e-02 8.770716e-02
[26] 2.697972e-01 -2.307850e-02 4.809820e-02 -5.557768e-01 -5.981748e-01
[31] -9.652300e-03 -2.612436e-01 -4.388651e-02 2.889223e-01 -1.658294e-01
[36] 2.250784e-01 -2.008878e-01 7.993171e-01 -2.643924e-01 5.341796e-01
[41] 6.983828e-01 -1.976929e-01 9.170456e-03 3.126869e-01 3.339458e-02
[46] 1.778862e-01 4.792450e-01 1.824128e-01 -3.304747e-02 2.447618e-01
[51] -4.505250e-01 -1.226475e-01 2.171812e-01 5.042008e-04 -6.098470e-02
[56] -7.459783e-04 7.985118e-01 -6.984734e-01 -3.965428e-01 1.467634e-01
[61] 1.275593e-01 -1.615016e-02 -4.770516e-01 3.987669e-01 4.382962e-01
[66] 2.965494e-01 -4.901646e-01 1.177752e-01 8.709594e-02 2.096518e-01
[71] 2.552247e-01 -5.496169e-02 -1.865338e-01 -5.772437e-01 -1.761522e-01
[76] -5.675492e-01 -1.350759e-01 -3.626061e-01 2.491079e-01 -8.330087e-01
[81] -2.634370e-01 1.700496e-01 8.491479e-01 -2.911144e-01 -2.659907e-02
[86] -4.596553e-01 -3.824325e-01 -4.677534e-01 1.448394e-01 -3.680118e-01
[91] 1.409462e-01 -1.974636e-01 4.572833e-02 -6.444868e-02 -2.764635e-01
[96] 2.092286e-01 4.481785e-01 -1.284744e-01 -1.172098e-01 1.218080e-01
[101] -1.885642e-01 -1.870361e-01 5.402889e-02 -4.372041e-01 2.024223e-01
[106] 3.891989e-01 1.019181e-01 -2.144056e-01 3.730742e-01 -3.949817e-01
[111] -4.685868e-01 4.132904e-01 -2.467286e-01 -3.279270e-02 3.968638e-01
[116] -5.261334e-01 -2.667752e-01 1.504402e-01 -9.613439e-02 -4.170976e-01
[121] 2.150314e-01 -9.241152e-01 4.857040e-01 -1.756321e-01 -1.706668e-01
[126] 4.023378e-01 5.049287e-02 -1.202566e-02 -1.900167e-01 -1.218556e-01
[131] 1.813900e-01 1.096069e-01 3.985819e-01 -1.980072e-01 1.304873e-01
[136] -1.599130e-01 -1.006276e-01 -9.264997e-02 1.490467e-06 -1.838386e-01
[141] -1.218111e-01 -2.147542e-01 4.283299e-01 -5.092072e-02 -2.449114e-01
[146] 1.149159e-01 2.713055e-01 1.570797e-03 -1.579035e-01 6.260732e-01
[151] -2.615539e-01 -6.056703e-01 5.195448e-01 -4.859963e-01 2.129297e-01
[156] 7.983765e-02 -6.824227e-02 -1.317460e-01 1.953250e-01 -2.333107e-01
[161] -2.603984e-02 -9.483514e-02 -4.533581e-01 -1.343933e-01 -4.060646e-01
[166] -4.962243e-01 -1.462581e-01 4.389254e-01 -2.865517e-03 -2.922634e-01
[171] 3.524261e-02 -4.962111e-01 1.199498e-01 3.109752e-01 3.829933e-01
[176] 2.489228e-01 1.943514e-02 6.244820e-02 -2.797107e-01 -1.145069e-01
[181] -1.548981e-01 2.502290e-01 -5.334578e-02 -3.990423e-01 -5.043392e-03
[186] -5.530187e-01 4.783810e-01 -1.251745e-01 9.030131e-03 4.322174e-02
[191] -5.202132e-01 4.001876e-01 -3.997240e-01 -3.016908e-01 -1.457166e-01
[196] -2.682108e-01 1.309732e-01 -1.015528e-01 2.951869e-01 1.775046e-01
[201] 3.174421e-01 1.940771e-01 2.275108e-01 2.084954e-01 -1.327553e-01
[206] 3.908553e-01 8.633784e-02 3.244237e-01 -1.153234e-02 -5.380068e-01
[211] -2.241083e-01 2.387639e-01 -1.153433e-01 2.009192e-01 2.185101e-01
[216] 3.756693e-01 3.637332e-02 2.929297e-03 3.510259e-01 -8.584758e-02
[221] 6.799893e-02 -2.575071e-01 3.109575e-01 -3.215064e-01 -1.047705e-01
[226] 1.485612e-01 -2.757136e-01 1.901015e-01 3.823584e-01 -3.354624e-01
>
> proc.time()
user system elapsed
1.290 0.657 1.937
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: 0x60d7898d1370>
> .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: 0x60d7898d1370>
> .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: 0x60d7898d1370>
> .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: 0x60d7898d1370>
> 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: 0x60d7898b91c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d7898b91c0>
> .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: 0x60d7898b91c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d7898b91c0>
> .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: 0x60d7898b91c0>
> 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: 0x60d789b9c120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d789b9c120>
> .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: 0x60d789b9c120>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60d789b9c120>
> .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: 0x60d789b9c120>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60d789b9c120>
> .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: 0x60d789b9c120>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60d789b9c120>
> .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: 0x60d789b9c120>
> 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: 0x60d7888ec390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x60d7888ec390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d7888ec390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d7888ec390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile127b9d19f45a88" "BufferedMatrixFile127b9d4ab334a9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile127b9d19f45a88" "BufferedMatrixFile127b9d4ab334a9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d7887e33d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d7887e33d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60d7887e33d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60d7887e33d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60d7887e33d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60d7887e33d0>
> .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: 0x60d78a318fa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d78a318fa0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60d78a318fa0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x60d78a318fa0>
> 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: 0x60d788af0ff0>
> .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: 0x60d788af0ff0>
> rm(P)
>
> proc.time()
user system elapsed
0.252 0.043 0.285
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.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.228 0.052 0.270