Ben Bolstad
| Snapshot Date: 2026-02-23 13:45 -0500 (Mon, 23 Feb 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 Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-02-24 11:57 -0500 (Tue, 24 Feb 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" | 4891 |
| 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 | | ||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
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: 2026-02-23 21:38:15 -0500 (Mon, 23 Feb 2026) |
| EndedAt: 2026-02-23 21:38:39 -0500 (Mon, 23 Feb 2026) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.74.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.22-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.238 0.045 0.272
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 Feb 23 21:38:30 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 Feb 23 21:38:30 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: 0x5f7b3fd821c0>
>
>
>
> 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 Feb 23 21:38:30 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 Feb 23 21:38:30 2026"
>
> ColMode(tmp2)
<pointer: 0x5f7b3fd821c0>
>
>
>
> ### 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,] 97.5411231 1.4665956 0.07471315 -1.68423008
[2,] 0.1072961 2.2104728 -0.08852371 -0.06653838
[3,] -1.4435855 -0.4386609 1.33267332 1.23345197
[4,] -1.3768034 0.2221139 -0.55478999 0.05439887
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 97.5411231 1.4665956 0.07471315 1.68423008
[2,] 0.1072961 2.2104728 0.08852371 0.06653838
[3,] 1.4435855 0.4386609 1.33267332 1.23345197
[4,] 1.3768034 0.2221139 0.55478999 0.05439887
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.8762910 1.2110308 0.2733371 1.2977789
[2,] 0.3275608 1.4867659 0.2975294 0.2579503
[3,] 1.2014931 0.6623148 1.1544147 1.1106088
[4,] 1.1733726 0.4712896 0.7448423 0.2332357
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 221.30403 38.57690 27.80808 39.66202
[2,] 28.38290 42.07813 28.06382 27.64604
[3,] 38.45852 32.06181 37.87682 37.33954
[4,] 38.11053 29.93501 33.00321 27.38676
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5f7b40a513b0>
> exp(tmp5)
<pointer: 0x5f7b40a513b0>
> log(tmp5,2)
<pointer: 0x5f7b40a513b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 460.6153
> Min(tmp5)
[1] 53.3087
> mean(tmp5)
[1] 72.41067
> Sum(tmp5)
[1] 14482.13
> Var(tmp5)
[1] 831.4593
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.52806 68.42840 69.16865 70.60463 72.43233 68.21924 70.17636 74.66292
[9] 67.67129 71.21479
> rowSums(tmp5)
[1] 1830.561 1368.568 1383.373 1412.093 1448.647 1364.385 1403.527 1493.258
[9] 1353.426 1424.296
> rowVars(tmp5)
[1] 7606.46791 80.71045 63.59388 56.25432 102.45953 73.46428
[7] 58.20570 48.89303 80.13333 68.12267
> rowSd(tmp5)
[1] 87.215067 8.983899 7.974577 7.500288 10.122230 8.571131 7.629266
[8] 6.992355 8.951722 8.253646
> rowMax(tmp5)
[1] 460.61535 88.34399 80.66754 82.58818 91.39283 87.77262 84.44604
[8] 87.71506 86.44419 86.84491
> rowMin(tmp5)
[1] 57.87888 55.91326 58.35848 56.49891 57.59895 53.30870 55.58826 64.37520
[9] 55.35055 58.48166
>
> colMeans(tmp5)
[1] 111.11491 75.06557 67.45028 67.79983 65.95112 70.14225 68.75186
[8] 72.07914 71.67166 70.78174 70.09930 68.79195 71.76468 75.12935
[15] 70.79012 68.68259 73.01615 70.49409 68.18867 70.44808
> colSums(tmp5)
[1] 1111.1491 750.6557 674.5028 677.9983 659.5112 701.4225 687.5186
[8] 720.7914 716.7166 707.8174 700.9930 687.9195 717.6468 751.2935
[15] 707.9012 686.8259 730.1615 704.9409 681.8867 704.4808
> colVars(tmp5)
[1] 15121.11110 78.63320 95.86577 129.05713 27.27705 39.19060
[7] 58.54538 106.78008 50.95290 37.33924 112.23566 98.98215
[13] 26.18524 49.65393 94.00564 57.82344 67.53110 71.46875
[19] 83.15709 108.70803
> colSd(tmp5)
[1] 122.967927 8.867536 9.791107 11.360331 5.222743 6.260240
[7] 7.651495 10.333445 7.138130 6.110584 10.594133 9.948978
[13] 5.117151 7.046555 9.695650 7.604172 8.217731 8.453919
[19] 9.119051 10.426314
> colMax(tmp5)
[1] 460.61535 87.58012 84.42992 82.55130 71.49222 79.38071 84.05783
[8] 88.34399 82.58818 79.42464 87.71506 91.39283 80.36989 87.77262
[15] 89.80154 79.83346 84.44604 81.16442 86.17683 86.84491
> colMin(tmp5)
[1] 59.07530 62.30580 56.37216 53.30870 56.21105 62.72268 57.59895 58.94061
[9] 62.52403 60.77255 55.91326 58.35848 65.16691 64.19483 56.50655 58.41453
[17] 58.97448 58.75954 56.49891 55.58826
>
>
> ### 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] 91.52806 68.42840 NA 70.60463 72.43233 68.21924 70.17636 74.66292
[9] 67.67129 71.21479
> rowSums(tmp5)
[1] 1830.561 1368.568 NA 1412.093 1448.647 1364.385 1403.527 1493.258
[9] 1353.426 1424.296
> rowVars(tmp5)
[1] 7606.46791 80.71045 67.11808 56.25432 102.45953 73.46428
[7] 58.20570 48.89303 80.13333 68.12267
> rowSd(tmp5)
[1] 87.215067 8.983899 8.192563 7.500288 10.122230 8.571131 7.629266
[8] 6.992355 8.951722 8.253646
> rowMax(tmp5)
[1] 460.61535 88.34399 NA 82.58818 91.39283 87.77262 84.44604
[8] 87.71506 86.44419 86.84491
> rowMin(tmp5)
[1] 57.87888 55.91326 NA 56.49891 57.59895 53.30870 55.58826 64.37520
[9] 55.35055 58.48166
>
> colMeans(tmp5)
[1] 111.11491 75.06557 67.45028 67.79983 65.95112 NA 68.75186
[8] 72.07914 71.67166 70.78174 70.09930 68.79195 71.76468 75.12935
[15] 70.79012 68.68259 73.01615 70.49409 68.18867 70.44808
> colSums(tmp5)
[1] 1111.1491 750.6557 674.5028 677.9983 659.5112 NA 687.5186
[8] 720.7914 716.7166 707.8174 700.9930 687.9195 717.6468 751.2935
[15] 707.9012 686.8259 730.1615 704.9409 681.8867 704.4808
> colVars(tmp5)
[1] 15121.11110 78.63320 95.86577 129.05713 27.27705 NA
[7] 58.54538 106.78008 50.95290 37.33924 112.23566 98.98215
[13] 26.18524 49.65393 94.00564 57.82344 67.53110 71.46875
[19] 83.15709 108.70803
> colSd(tmp5)
[1] 122.967927 8.867536 9.791107 11.360331 5.222743 NA
[7] 7.651495 10.333445 7.138130 6.110584 10.594133 9.948978
[13] 5.117151 7.046555 9.695650 7.604172 8.217731 8.453919
[19] 9.119051 10.426314
> colMax(tmp5)
[1] 460.61535 87.58012 84.42992 82.55130 71.49222 NA 84.05783
[8] 88.34399 82.58818 79.42464 87.71506 91.39283 80.36989 87.77262
[15] 89.80154 79.83346 84.44604 81.16442 86.17683 86.84491
> colMin(tmp5)
[1] 59.07530 62.30580 56.37216 53.30870 56.21105 NA 57.59895 58.94061
[9] 62.52403 60.77255 55.91326 58.35848 65.16691 64.19483 56.50655 58.41453
[17] 58.97448 58.75954 56.49891 55.58826
>
> Max(tmp5,na.rm=TRUE)
[1] 460.6153
> Min(tmp5,na.rm=TRUE)
[1] 53.3087
> mean(tmp5,na.rm=TRUE)
[1] 72.42501
> Sum(tmp5,na.rm=TRUE)
[1] 14412.58
> Var(tmp5,na.rm=TRUE)
[1] 835.6173
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.52806 68.42840 69.14825 70.60463 72.43233 68.21924 70.17636 74.66292
[9] 67.67129 71.21479
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.561 1368.568 1313.817 1412.093 1448.647 1364.385 1403.527 1493.258
[9] 1353.426 1424.296
> rowVars(tmp5,na.rm=TRUE)
[1] 7606.46791 80.71045 67.11808 56.25432 102.45953 73.46428
[7] 58.20570 48.89303 80.13333 68.12267
> rowSd(tmp5,na.rm=TRUE)
[1] 87.215067 8.983899 8.192563 7.500288 10.122230 8.571131 7.629266
[8] 6.992355 8.951722 8.253646
> rowMax(tmp5,na.rm=TRUE)
[1] 460.61535 88.34399 80.66754 82.58818 91.39283 87.77262 84.44604
[8] 87.71506 86.44419 86.84491
> rowMin(tmp5,na.rm=TRUE)
[1] 57.87888 55.91326 58.35848 56.49891 57.59895 53.30870 55.58826 64.37520
[9] 55.35055 58.48166
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.11491 75.06557 67.45028 67.79983 65.95112 70.20735 68.75186
[8] 72.07914 71.67166 70.78174 70.09930 68.79195 71.76468 75.12935
[15] 70.79012 68.68259 73.01615 70.49409 68.18867 70.44808
> colSums(tmp5,na.rm=TRUE)
[1] 1111.1491 750.6557 674.5028 677.9983 659.5112 631.8662 687.5186
[8] 720.7914 716.7166 707.8174 700.9930 687.9195 717.6468 751.2935
[15] 707.9012 686.8259 730.1615 704.9409 681.8867 704.4808
> colVars(tmp5,na.rm=TRUE)
[1] 15121.11110 78.63320 95.86577 129.05713 27.27705 44.04174
[7] 58.54538 106.78008 50.95290 37.33924 112.23566 98.98215
[13] 26.18524 49.65393 94.00564 57.82344 67.53110 71.46875
[19] 83.15709 108.70803
> colSd(tmp5,na.rm=TRUE)
[1] 122.967927 8.867536 9.791107 11.360331 5.222743 6.636395
[7] 7.651495 10.333445 7.138130 6.110584 10.594133 9.948978
[13] 5.117151 7.046555 9.695650 7.604172 8.217731 8.453919
[19] 9.119051 10.426314
> colMax(tmp5,na.rm=TRUE)
[1] 460.61535 87.58012 84.42992 82.55130 71.49222 79.38071 84.05783
[8] 88.34399 82.58818 79.42464 87.71506 91.39283 80.36989 87.77262
[15] 89.80154 79.83346 84.44604 81.16442 86.17683 86.84491
> colMin(tmp5,na.rm=TRUE)
[1] 59.07530 62.30580 56.37216 53.30870 56.21105 62.72268 57.59895 58.94061
[9] 62.52403 60.77255 55.91326 58.35848 65.16691 64.19483 56.50655 58.41453
[17] 58.97448 58.75954 56.49891 55.58826
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.52806 68.42840 NaN 70.60463 72.43233 68.21924 70.17636 74.66292
[9] 67.67129 71.21479
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.561 1368.568 0.000 1412.093 1448.647 1364.385 1403.527 1493.258
[9] 1353.426 1424.296
> rowVars(tmp5,na.rm=TRUE)
[1] 7606.46791 80.71045 NA 56.25432 102.45953 73.46428
[7] 58.20570 48.89303 80.13333 68.12267
> rowSd(tmp5,na.rm=TRUE)
[1] 87.215067 8.983899 NA 7.500288 10.122230 8.571131 7.629266
[8] 6.992355 8.951722 8.253646
> rowMax(tmp5,na.rm=TRUE)
[1] 460.61535 88.34399 NA 82.58818 91.39283 87.77262 84.44604
[8] 87.71506 86.44419 86.84491
> rowMin(tmp5,na.rm=TRUE)
[1] 57.87888 55.91326 NA 56.49891 57.59895 53.30870 55.58826 64.37520
[9] 55.35055 58.48166
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.56697 75.99147 66.18524 66.69788 66.41296 NaN 69.41668
[8] 73.53898 71.70878 71.89387 70.24533 69.95123 70.80855 74.51399
[15] 70.85829 68.64381 72.39936 71.79793 69.00771 70.57142
> colSums(tmp5,na.rm=TRUE)
[1] 1031.1027 683.9232 595.6672 600.2809 597.7167 0.0000 624.7502
[8] 661.8508 645.3790 647.0448 632.2080 629.5611 637.2770 670.6259
[15] 637.7246 617.7943 651.5942 646.1814 621.0694 635.1428
> colVars(tmp5,na.rm=TRUE)
[1] 16877.18683 78.81779 89.84533 131.52851 28.28709 NA
[7] 60.89109 96.15245 57.30651 28.09221 126.02522 96.23583
[13] 19.17373 51.60073 105.70407 65.03446 71.69268 61.27737
[19] 86.00495 122.12538
> colSd(tmp5,na.rm=TRUE)
[1] 129.912227 8.877938 9.478678 11.468588 5.318561 NA
[7] 7.803274 9.805735 7.570106 5.300208 11.226096 9.809986
[13] 4.378782 7.183365 10.281248 8.064394 8.467153 7.827987
[19] 9.273886 11.051035
> colMax(tmp5,na.rm=TRUE)
[1] 460.61535 87.58012 84.42992 82.55130 71.49222 -Inf 84.05783
[8] 88.34399 82.58818 79.42464 87.71506 91.39283 78.12228 87.77262
[15] 89.80154 79.83346 84.44604 81.16442 86.17683 86.84491
> colMin(tmp5,na.rm=TRUE)
[1] 59.07530 62.30580 56.37216 53.30870 56.21105 Inf 57.59895 60.77983
[9] 62.52403 64.51472 55.91326 58.48166 65.16691 64.19483 56.50655 58.41453
[17] 58.97448 60.64209 56.49891 55.58826
>
>
>
>
> 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] 290.1216 469.1328 168.7182 120.8520 147.9120 199.7711 191.5182 296.9365
[9] 299.7530 119.2578
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 290.1216 469.1328 168.7182 120.8520 147.9120 199.7711 191.5182 296.9365
[9] 299.7530 119.2578
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.989520e-13 -1.136868e-13 8.526513e-14 -2.842171e-14 5.684342e-14
[6] -3.410605e-13 5.684342e-14 -5.684342e-14 -9.947598e-14 8.526513e-14
[11] 5.684342e-14 1.136868e-13 -2.842171e-14 0.000000e+00 8.526513e-14
[16] 2.842171e-14 -5.684342e-14 5.684342e-14 -2.842171e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 10
7 17
1 7
5 20
6 18
6 7
1 6
9 7
8 14
10 11
6 3
4 8
4 11
1 6
2 17
4 20
10 13
7 6
8 5
8 13
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] 2.232418
> Min(tmp)
[1] -1.997944
> mean(tmp)
[1] 0.03612068
> Sum(tmp)
[1] 3.612068
> Var(tmp)
[1] 0.7630001
>
> rowMeans(tmp)
[1] 0.03612068
> rowSums(tmp)
[1] 3.612068
> rowVars(tmp)
[1] 0.7630001
> rowSd(tmp)
[1] 0.8734988
> rowMax(tmp)
[1] 2.232418
> rowMin(tmp)
[1] -1.997944
>
> colMeans(tmp)
[1] -0.139277248 0.869640906 -0.865209442 1.395075427 -0.277634225
[6] -0.971107151 0.539849176 0.849652722 -0.437076261 0.707376496
[11] 1.953045046 1.388433906 -0.358672305 0.541116622 0.287048187
[16] -0.089375490 0.081452759 1.396827213 -0.646730233 0.373977019
[21] -0.535892325 -0.769208492 -0.426448041 -0.610095653 2.232417579
[26] 1.559160805 -0.109953686 -0.912296635 -1.080346898 0.559344737
[31] 0.007203013 -1.646542975 -0.475777931 1.543842295 0.371359539
[36] 0.645057299 2.115233578 1.223703590 -0.657405265 -0.470136165
[41] -0.866384764 0.120087776 -0.271440127 -0.923466529 -0.371312305
[46] 0.841904838 0.799822526 -1.130340010 -0.292589762 0.071900531
[51] -1.086916849 0.477378278 0.200220583 0.333817034 1.375624964
[56] 0.502320975 0.691130967 -0.505445613 0.244307390 -0.943421588
[61] -1.254106015 -1.514296659 -0.652373014 -0.181836824 1.868315489
[66] -0.900133932 0.543029854 0.895924440 -0.137805014 0.167567844
[71] -0.437180223 0.228439404 -0.117654776 -0.152857732 0.312035041
[76] -0.150211111 -0.094036446 -0.139572810 1.350271083 -0.146553199
[81] 0.456662335 -1.020620450 0.712174462 -0.169578801 1.120845908
[86] -0.330102902 -0.953181175 0.076637923 -0.050819524 -1.914128740
[91] -0.368902943 -0.847952516 -0.278774807 -0.563343818 0.212119249
[96] 0.675134647 0.036037987 -1.997943876 -0.313528159 1.215537990
> colSums(tmp)
[1] -0.139277248 0.869640906 -0.865209442 1.395075427 -0.277634225
[6] -0.971107151 0.539849176 0.849652722 -0.437076261 0.707376496
[11] 1.953045046 1.388433906 -0.358672305 0.541116622 0.287048187
[16] -0.089375490 0.081452759 1.396827213 -0.646730233 0.373977019
[21] -0.535892325 -0.769208492 -0.426448041 -0.610095653 2.232417579
[26] 1.559160805 -0.109953686 -0.912296635 -1.080346898 0.559344737
[31] 0.007203013 -1.646542975 -0.475777931 1.543842295 0.371359539
[36] 0.645057299 2.115233578 1.223703590 -0.657405265 -0.470136165
[41] -0.866384764 0.120087776 -0.271440127 -0.923466529 -0.371312305
[46] 0.841904838 0.799822526 -1.130340010 -0.292589762 0.071900531
[51] -1.086916849 0.477378278 0.200220583 0.333817034 1.375624964
[56] 0.502320975 0.691130967 -0.505445613 0.244307390 -0.943421588
[61] -1.254106015 -1.514296659 -0.652373014 -0.181836824 1.868315489
[66] -0.900133932 0.543029854 0.895924440 -0.137805014 0.167567844
[71] -0.437180223 0.228439404 -0.117654776 -0.152857732 0.312035041
[76] -0.150211111 -0.094036446 -0.139572810 1.350271083 -0.146553199
[81] 0.456662335 -1.020620450 0.712174462 -0.169578801 1.120845908
[86] -0.330102902 -0.953181175 0.076637923 -0.050819524 -1.914128740
[91] -0.368902943 -0.847952516 -0.278774807 -0.563343818 0.212119249
[96] 0.675134647 0.036037987 -1.997943876 -0.313528159 1.215537990
> 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] -0.139277248 0.869640906 -0.865209442 1.395075427 -0.277634225
[6] -0.971107151 0.539849176 0.849652722 -0.437076261 0.707376496
[11] 1.953045046 1.388433906 -0.358672305 0.541116622 0.287048187
[16] -0.089375490 0.081452759 1.396827213 -0.646730233 0.373977019
[21] -0.535892325 -0.769208492 -0.426448041 -0.610095653 2.232417579
[26] 1.559160805 -0.109953686 -0.912296635 -1.080346898 0.559344737
[31] 0.007203013 -1.646542975 -0.475777931 1.543842295 0.371359539
[36] 0.645057299 2.115233578 1.223703590 -0.657405265 -0.470136165
[41] -0.866384764 0.120087776 -0.271440127 -0.923466529 -0.371312305
[46] 0.841904838 0.799822526 -1.130340010 -0.292589762 0.071900531
[51] -1.086916849 0.477378278 0.200220583 0.333817034 1.375624964
[56] 0.502320975 0.691130967 -0.505445613 0.244307390 -0.943421588
[61] -1.254106015 -1.514296659 -0.652373014 -0.181836824 1.868315489
[66] -0.900133932 0.543029854 0.895924440 -0.137805014 0.167567844
[71] -0.437180223 0.228439404 -0.117654776 -0.152857732 0.312035041
[76] -0.150211111 -0.094036446 -0.139572810 1.350271083 -0.146553199
[81] 0.456662335 -1.020620450 0.712174462 -0.169578801 1.120845908
[86] -0.330102902 -0.953181175 0.076637923 -0.050819524 -1.914128740
[91] -0.368902943 -0.847952516 -0.278774807 -0.563343818 0.212119249
[96] 0.675134647 0.036037987 -1.997943876 -0.313528159 1.215537990
> colMin(tmp)
[1] -0.139277248 0.869640906 -0.865209442 1.395075427 -0.277634225
[6] -0.971107151 0.539849176 0.849652722 -0.437076261 0.707376496
[11] 1.953045046 1.388433906 -0.358672305 0.541116622 0.287048187
[16] -0.089375490 0.081452759 1.396827213 -0.646730233 0.373977019
[21] -0.535892325 -0.769208492 -0.426448041 -0.610095653 2.232417579
[26] 1.559160805 -0.109953686 -0.912296635 -1.080346898 0.559344737
[31] 0.007203013 -1.646542975 -0.475777931 1.543842295 0.371359539
[36] 0.645057299 2.115233578 1.223703590 -0.657405265 -0.470136165
[41] -0.866384764 0.120087776 -0.271440127 -0.923466529 -0.371312305
[46] 0.841904838 0.799822526 -1.130340010 -0.292589762 0.071900531
[51] -1.086916849 0.477378278 0.200220583 0.333817034 1.375624964
[56] 0.502320975 0.691130967 -0.505445613 0.244307390 -0.943421588
[61] -1.254106015 -1.514296659 -0.652373014 -0.181836824 1.868315489
[66] -0.900133932 0.543029854 0.895924440 -0.137805014 0.167567844
[71] -0.437180223 0.228439404 -0.117654776 -0.152857732 0.312035041
[76] -0.150211111 -0.094036446 -0.139572810 1.350271083 -0.146553199
[81] 0.456662335 -1.020620450 0.712174462 -0.169578801 1.120845908
[86] -0.330102902 -0.953181175 0.076637923 -0.050819524 -1.914128740
[91] -0.368902943 -0.847952516 -0.278774807 -0.563343818 0.212119249
[96] 0.675134647 0.036037987 -1.997943876 -0.313528159 1.215537990
> colMedians(tmp)
[1] -0.139277248 0.869640906 -0.865209442 1.395075427 -0.277634225
[6] -0.971107151 0.539849176 0.849652722 -0.437076261 0.707376496
[11] 1.953045046 1.388433906 -0.358672305 0.541116622 0.287048187
[16] -0.089375490 0.081452759 1.396827213 -0.646730233 0.373977019
[21] -0.535892325 -0.769208492 -0.426448041 -0.610095653 2.232417579
[26] 1.559160805 -0.109953686 -0.912296635 -1.080346898 0.559344737
[31] 0.007203013 -1.646542975 -0.475777931 1.543842295 0.371359539
[36] 0.645057299 2.115233578 1.223703590 -0.657405265 -0.470136165
[41] -0.866384764 0.120087776 -0.271440127 -0.923466529 -0.371312305
[46] 0.841904838 0.799822526 -1.130340010 -0.292589762 0.071900531
[51] -1.086916849 0.477378278 0.200220583 0.333817034 1.375624964
[56] 0.502320975 0.691130967 -0.505445613 0.244307390 -0.943421588
[61] -1.254106015 -1.514296659 -0.652373014 -0.181836824 1.868315489
[66] -0.900133932 0.543029854 0.895924440 -0.137805014 0.167567844
[71] -0.437180223 0.228439404 -0.117654776 -0.152857732 0.312035041
[76] -0.150211111 -0.094036446 -0.139572810 1.350271083 -0.146553199
[81] 0.456662335 -1.020620450 0.712174462 -0.169578801 1.120845908
[86] -0.330102902 -0.953181175 0.076637923 -0.050819524 -1.914128740
[91] -0.368902943 -0.847952516 -0.278774807 -0.563343818 0.212119249
[96] 0.675134647 0.036037987 -1.997943876 -0.313528159 1.215537990
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1392772 0.8696409 -0.8652094 1.395075 -0.2776342 -0.9711072 0.5398492
[2,] -0.1392772 0.8696409 -0.8652094 1.395075 -0.2776342 -0.9711072 0.5398492
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.8496527 -0.4370763 0.7073765 1.953045 1.388434 -0.3586723 0.5411166
[2,] 0.8496527 -0.4370763 0.7073765 1.953045 1.388434 -0.3586723 0.5411166
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.2870482 -0.08937549 0.08145276 1.396827 -0.6467302 0.373977 -0.5358923
[2,] 0.2870482 -0.08937549 0.08145276 1.396827 -0.6467302 0.373977 -0.5358923
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.7692085 -0.426448 -0.6100957 2.232418 1.559161 -0.1099537 -0.9122966
[2,] -0.7692085 -0.426448 -0.6100957 2.232418 1.559161 -0.1099537 -0.9122966
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.080347 0.5593447 0.007203013 -1.646543 -0.4757779 1.543842 0.3713595
[2,] -1.080347 0.5593447 0.007203013 -1.646543 -0.4757779 1.543842 0.3713595
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.6450573 2.115234 1.223704 -0.6574053 -0.4701362 -0.8663848 0.1200878
[2,] 0.6450573 2.115234 1.223704 -0.6574053 -0.4701362 -0.8663848 0.1200878
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2714401 -0.9234665 -0.3713123 0.8419048 0.7998225 -1.13034 -0.2925898
[2,] -0.2714401 -0.9234665 -0.3713123 0.8419048 0.7998225 -1.13034 -0.2925898
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.07190053 -1.086917 0.4773783 0.2002206 0.333817 1.375625 0.502321
[2,] 0.07190053 -1.086917 0.4773783 0.2002206 0.333817 1.375625 0.502321
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.691131 -0.5054456 0.2443074 -0.9434216 -1.254106 -1.514297 -0.652373
[2,] 0.691131 -0.5054456 0.2443074 -0.9434216 -1.254106 -1.514297 -0.652373
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.1818368 1.868315 -0.9001339 0.5430299 0.8959244 -0.137805 0.1675678
[2,] -0.1818368 1.868315 -0.9001339 0.5430299 0.8959244 -0.137805 0.1675678
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.4371802 0.2284394 -0.1176548 -0.1528577 0.312035 -0.1502111 -0.09403645
[2,] -0.4371802 0.2284394 -0.1176548 -0.1528577 0.312035 -0.1502111 -0.09403645
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.1395728 1.350271 -0.1465532 0.4566623 -1.02062 0.7121745 -0.1695788
[2,] -0.1395728 1.350271 -0.1465532 0.4566623 -1.02062 0.7121745 -0.1695788
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.120846 -0.3301029 -0.9531812 0.07663792 -0.05081952 -1.914129 -0.3689029
[2,] 1.120846 -0.3301029 -0.9531812 0.07663792 -0.05081952 -1.914129 -0.3689029
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.8479525 -0.2787748 -0.5633438 0.2121192 0.6751346 0.03603799 -1.997944
[2,] -0.8479525 -0.2787748 -0.5633438 0.2121192 0.6751346 0.03603799 -1.997944
[,99] [,100]
[1,] -0.3135282 1.215538
[2,] -0.3135282 1.215538
>
>
> Max(tmp2)
[1] 2.922859
> Min(tmp2)
[1] -2.321202
> mean(tmp2)
[1] 0.05644518
> Sum(tmp2)
[1] 5.644518
> Var(tmp2)
[1] 1.098938
>
> rowMeans(tmp2)
[1] -0.050305167 -0.664702281 -1.969084513 0.248215786 0.100158389
[6] 0.133033860 0.841048370 -0.317504392 0.462449426 -0.989491145
[11] 1.060580243 0.417767060 -0.282699340 -1.290716149 -0.348645712
[16] -1.456925095 0.551019228 0.948501780 0.723999622 -0.273540812
[21] 0.449826255 0.353412032 -2.074514640 1.704965535 0.253863107
[26] 0.926126072 0.661938137 -0.016818525 0.799153305 -1.104048855
[31] -2.144433008 2.922859441 1.931704286 1.044009967 -0.064011297
[36] -1.152687539 1.213188104 -0.402089308 0.357093927 0.033042343
[41] 1.649769928 -0.861343861 -0.701021657 -1.246057295 1.303928930
[46] -0.539500570 0.374720816 -0.137154702 0.269626200 -0.244501543
[51] 1.454928332 0.577308412 -1.100517167 0.601983025 -2.321202497
[56] 1.771145145 -1.081379639 -0.456979505 1.497025017 0.318646204
[61] -0.175746728 2.251982892 -0.076440407 -0.141992505 -0.064604097
[66] -0.036496744 0.006079139 -1.024490546 -0.286376178 0.318931878
[71] -0.930761957 1.173767663 -0.036593210 -0.853662949 -2.007833309
[76] -0.756092794 1.161473193 2.773205774 0.745032907 -0.582048047
[81] 0.811816889 -1.630797849 -0.609797137 0.061096871 0.573999257
[86] -1.344763015 -0.385224467 1.229409829 1.826390257 -1.554399311
[91] -0.102857759 0.037507472 -0.715847818 0.510854301 0.249100002
[96] 1.081683271 0.301794034 -0.646825539 -0.275821273 0.104703567
> rowSums(tmp2)
[1] -0.050305167 -0.664702281 -1.969084513 0.248215786 0.100158389
[6] 0.133033860 0.841048370 -0.317504392 0.462449426 -0.989491145
[11] 1.060580243 0.417767060 -0.282699340 -1.290716149 -0.348645712
[16] -1.456925095 0.551019228 0.948501780 0.723999622 -0.273540812
[21] 0.449826255 0.353412032 -2.074514640 1.704965535 0.253863107
[26] 0.926126072 0.661938137 -0.016818525 0.799153305 -1.104048855
[31] -2.144433008 2.922859441 1.931704286 1.044009967 -0.064011297
[36] -1.152687539 1.213188104 -0.402089308 0.357093927 0.033042343
[41] 1.649769928 -0.861343861 -0.701021657 -1.246057295 1.303928930
[46] -0.539500570 0.374720816 -0.137154702 0.269626200 -0.244501543
[51] 1.454928332 0.577308412 -1.100517167 0.601983025 -2.321202497
[56] 1.771145145 -1.081379639 -0.456979505 1.497025017 0.318646204
[61] -0.175746728 2.251982892 -0.076440407 -0.141992505 -0.064604097
[66] -0.036496744 0.006079139 -1.024490546 -0.286376178 0.318931878
[71] -0.930761957 1.173767663 -0.036593210 -0.853662949 -2.007833309
[76] -0.756092794 1.161473193 2.773205774 0.745032907 -0.582048047
[81] 0.811816889 -1.630797849 -0.609797137 0.061096871 0.573999257
[86] -1.344763015 -0.385224467 1.229409829 1.826390257 -1.554399311
[91] -0.102857759 0.037507472 -0.715847818 0.510854301 0.249100002
[96] 1.081683271 0.301794034 -0.646825539 -0.275821273 0.104703567
> 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] -0.050305167 -0.664702281 -1.969084513 0.248215786 0.100158389
[6] 0.133033860 0.841048370 -0.317504392 0.462449426 -0.989491145
[11] 1.060580243 0.417767060 -0.282699340 -1.290716149 -0.348645712
[16] -1.456925095 0.551019228 0.948501780 0.723999622 -0.273540812
[21] 0.449826255 0.353412032 -2.074514640 1.704965535 0.253863107
[26] 0.926126072 0.661938137 -0.016818525 0.799153305 -1.104048855
[31] -2.144433008 2.922859441 1.931704286 1.044009967 -0.064011297
[36] -1.152687539 1.213188104 -0.402089308 0.357093927 0.033042343
[41] 1.649769928 -0.861343861 -0.701021657 -1.246057295 1.303928930
[46] -0.539500570 0.374720816 -0.137154702 0.269626200 -0.244501543
[51] 1.454928332 0.577308412 -1.100517167 0.601983025 -2.321202497
[56] 1.771145145 -1.081379639 -0.456979505 1.497025017 0.318646204
[61] -0.175746728 2.251982892 -0.076440407 -0.141992505 -0.064604097
[66] -0.036496744 0.006079139 -1.024490546 -0.286376178 0.318931878
[71] -0.930761957 1.173767663 -0.036593210 -0.853662949 -2.007833309
[76] -0.756092794 1.161473193 2.773205774 0.745032907 -0.582048047
[81] 0.811816889 -1.630797849 -0.609797137 0.061096871 0.573999257
[86] -1.344763015 -0.385224467 1.229409829 1.826390257 -1.554399311
[91] -0.102857759 0.037507472 -0.715847818 0.510854301 0.249100002
[96] 1.081683271 0.301794034 -0.646825539 -0.275821273 0.104703567
> rowMin(tmp2)
[1] -0.050305167 -0.664702281 -1.969084513 0.248215786 0.100158389
[6] 0.133033860 0.841048370 -0.317504392 0.462449426 -0.989491145
[11] 1.060580243 0.417767060 -0.282699340 -1.290716149 -0.348645712
[16] -1.456925095 0.551019228 0.948501780 0.723999622 -0.273540812
[21] 0.449826255 0.353412032 -2.074514640 1.704965535 0.253863107
[26] 0.926126072 0.661938137 -0.016818525 0.799153305 -1.104048855
[31] -2.144433008 2.922859441 1.931704286 1.044009967 -0.064011297
[36] -1.152687539 1.213188104 -0.402089308 0.357093927 0.033042343
[41] 1.649769928 -0.861343861 -0.701021657 -1.246057295 1.303928930
[46] -0.539500570 0.374720816 -0.137154702 0.269626200 -0.244501543
[51] 1.454928332 0.577308412 -1.100517167 0.601983025 -2.321202497
[56] 1.771145145 -1.081379639 -0.456979505 1.497025017 0.318646204
[61] -0.175746728 2.251982892 -0.076440407 -0.141992505 -0.064604097
[66] -0.036496744 0.006079139 -1.024490546 -0.286376178 0.318931878
[71] -0.930761957 1.173767663 -0.036593210 -0.853662949 -2.007833309
[76] -0.756092794 1.161473193 2.773205774 0.745032907 -0.582048047
[81] 0.811816889 -1.630797849 -0.609797137 0.061096871 0.573999257
[86] -1.344763015 -0.385224467 1.229409829 1.826390257 -1.554399311
[91] -0.102857759 0.037507472 -0.715847818 0.510854301 0.249100002
[96] 1.081683271 0.301794034 -0.646825539 -0.275821273 0.104703567
>
> colMeans(tmp2)
[1] 0.05644518
> colSums(tmp2)
[1] 5.644518
> colVars(tmp2)
[1] 1.098938
> colSd(tmp2)
[1] 1.048303
> colMax(tmp2)
[1] 2.922859
> colMin(tmp2)
[1] -2.321202
> colMedians(tmp2)
[1] 0.01956074
> colRanges(tmp2)
[,1]
[1,] -2.321202
[2,] 2.922859
>
> 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] -2.5072728 2.0636908 -0.6744742 3.9384684 -6.0452349 -0.3538444
[7] -2.3563262 -3.8121388 -1.1965234 4.8846375
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1249677
[2,] -0.5410093
[3,] -0.2209863
[4,] 0.5300877
[5,] 0.8356469
>
> rowApply(tmp,sum)
[1] -4.7844492 -3.5315679 1.7005382 0.4323156 -0.4289932 -3.2036406
[7] 1.5698919 2.2469397 2.2063768 -2.2664294
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 1 3 6 4 2 8 3 8 7
[2,] 1 8 5 8 7 8 5 9 9 8
[3,] 2 6 7 4 2 9 7 7 2 9
[4,] 3 4 6 2 6 10 10 8 10 6
[5,] 6 5 9 1 3 1 3 1 3 5
[6,] 4 7 10 10 8 4 1 2 7 4
[7,] 5 3 8 7 9 6 4 4 6 1
[8,] 8 2 2 5 1 3 9 6 4 2
[9,] 7 10 1 3 5 7 2 10 5 3
[10,] 10 9 4 9 10 5 6 5 1 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -6.52953199 0.39396369 1.85801982 1.59929040 2.50111247 -1.06211898
[7] 1.88672017 3.86507917 2.25851661 -1.48879620 -1.64806017 1.74241838
[13] 0.01854339 -0.87083875 2.18966345 1.13231290 0.05992512 0.66939239
[19] -0.06030913 -2.12387309
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.5158907
[2,] -1.2887231
[3,] -1.1917955
[4,] -0.8015973
[5,] -0.7315252
>
> rowApply(tmp,sum)
[1] 0.07796574 2.92884100 6.16271090 -1.79340791 -0.98468011
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 3 4 1 3
[2,] 9 4 15 8 15
[3,] 10 19 20 2 6
[4,] 4 20 16 18 4
[5,] 2 13 18 9 18
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.1917955 -0.1757986 -0.120490 -1.1776311 -1.29775480 -0.46203567
[2,] -0.7315252 -0.6449121 1.631835 1.7349198 0.44669109 0.29169936
[3,] -0.8015973 0.8324218 2.385594 1.2457598 1.86226473 -0.83764631
[4,] -2.5158907 -0.1318610 -1.224368 0.9715822 -0.03875004 -0.02115379
[5,] -1.2887231 0.5141136 -0.814551 -1.1753403 1.52866149 -0.03298258
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8370719 1.4017998 1.5754299 -1.37395898 -0.76991212 0.9596687
[2,] -0.5013720 -0.3556752 -0.2305048 0.28956184 0.03768352 0.5647445
[3,] -0.5966793 1.2693624 -0.3474125 -1.78901644 0.73171996 0.7329936
[4,] 0.5140472 -0.7110106 0.4639491 1.29751599 -1.05480307 -0.8752631
[5,] 1.6336524 2.2606028 0.7970549 0.08710139 -0.59274847 0.3602747
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.5360281 1.01486728 0.6681033 1.3027540 0.04334185 0.4827726
[2,] 0.7432455 -1.44857838 1.2084716 -0.2475232 0.88484483 -0.2441779
[3,] -0.4470365 0.02991992 -0.4136245 0.3975085 0.45172428 2.2041868
[4,] 1.0995848 -0.98092775 0.6091585 -0.9304228 0.45136860 0.8939743
[5,] -0.8412223 0.51388017 0.1175544 0.6099963 -1.77135444 -2.6673636
[,19] [,20]
[1,] 0.05431184 -1.15675051
[2,] 0.54498053 -1.04556748
[3,] -0.86103718 0.11330506
[4,] 0.29760310 0.09225896
[5,] -0.09616742 -0.12711912
>
>
> 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 : 643 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 : 557 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 -1.124355 -0.7223499 -0.3942049 -0.1993776 -0.563167 -0.557186 -0.776869
col8 col9 col10 col11 col12 col13 col14
row1 -0.9356526 1.316739 -0.1413407 -0.5320777 1.191132 -0.5412265 0.3858552
col15 col16 col17 col18 col19 col20
row1 -2.14944 0.2257069 -0.3506877 -0.9173196 -0.6444641 -0.3378207
> tmp[,"col10"]
col10
row1 -0.1413407
row2 1.0104433
row3 -1.2140697
row4 0.4592992
row5 -0.3326569
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.124355 -0.72234993 -0.3942049 -0.1993776 -0.5631670 -0.5571860
row5 -1.300676 0.07963618 -0.9425595 -0.2987314 0.1988613 0.7492138
col7 col8 col9 col10 col11 col12
row1 -0.776869 -0.9356526 1.3167390 -0.1413407 -0.5320777 1.1911319
row5 -1.315518 1.7476445 -0.3731028 -0.3326569 0.4001910 -0.6339528
col13 col14 col15 col16 col17 col18 col19
row1 -0.5412265 0.3858552 -2.149440 0.2257069 -0.3506877 -0.9173196 -0.6444641
row5 1.5222625 0.7045815 -1.017501 -0.5367360 0.4688402 1.2625938 2.5070545
col20
row1 -0.3378207
row5 -0.2563306
> tmp[,c("col6","col20")]
col6 col20
row1 -0.5571860 -0.3378207
row2 -1.7048383 -0.3227153
row3 -0.9955256 0.5276701
row4 0.5550394 0.5109566
row5 0.7492138 -0.2563306
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.5571860 -0.3378207
row5 0.7492138 -0.2563306
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.8031 48.56854 48.30056 49.7537 48.01079 106.6758 50.20248 50.54553
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.46929 49.68685 51.6331 52.08455 51.28651 50.33656 49.73559 49.10947
col17 col18 col19 col20
row1 49.8683 48.72759 50.22862 104.522
> tmp[,"col10"]
col10
row1 49.68685
row2 31.82095
row3 29.24727
row4 29.27631
row5 50.91855
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.8031 48.56854 48.30056 49.7537 48.01079 106.6758 50.20248 50.54553
row5 49.3804 50.58443 49.32294 50.3952 51.92887 105.4694 49.60226 51.10673
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.46929 49.68685 51.6331 52.08455 51.28651 50.33656 49.73559 49.10947
row5 52.02909 50.91855 49.2275 50.66902 49.61823 49.87552 49.88618 49.57597
col17 col18 col19 col20
row1 49.86830 48.72759 50.22862 104.5220
row5 49.79019 49.49050 48.10487 107.2063
> tmp[,c("col6","col20")]
col6 col20
row1 106.67581 104.52201
row2 75.05867 76.30394
row3 75.99646 75.95166
row4 75.64042 75.11842
row5 105.46936 107.20633
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.6758 104.5220
row5 105.4694 107.2063
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.6758 104.5220
row5 105.4694 107.2063
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8326112
[2,] 1.8358493
[3,] 0.0706478
[4,] 0.6453362
[5,] -1.3994777
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.6044657 -1.1955506
[2,] 0.7167764 -1.7821292
[3,] 0.6020586 0.7695785
[4,] 0.2248651 0.9965432
[5,] -0.2632400 0.3240544
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.754111942 0.8561997
[2,] 0.005677469 0.1878893
[3,] -1.296657818 0.9453322
[4,] 1.119006905 0.7244570
[5,] -0.441107424 0.5649825
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.754112
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.754111942
[2,] 0.005677469
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.1876061 -0.1350094 0.6689570 0.4466958971 0.8591724 0.2782339
row1 -1.5376888 0.5492211 0.2876622 0.0006889514 -0.1123719 -1.4761070
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.597863 -0.6140711 -0.3966209 1.4558562 -0.2883541 0.08733446
row1 0.242240 -1.2045034 0.1490943 -0.2389452 0.9342745 -1.05428345
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3687752 0.7510891 0.3661645 0.4495368 0.1606886 -1.7105193 -2.233922
row1 -0.1046683 0.8233771 1.3266378 -0.2786535 1.0594862 -0.7800989 -2.341111
[,20]
row3 1.1696903
row1 -0.5243932
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.49378 -1.536147 -0.2587476 -1.310144 -1.328914 -0.1609608 -0.2524601
[,8] [,9] [,10]
row2 0.5363934 2.797868 0.5841025
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1071045 -1.04031 1.323807 -1.062826 -1.478963 1.09797 0.640395
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.689891 0.8575996 -0.06636397 1.718144 0.9818964 0.7062615 0.373183
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.310032 0.2779403 0.6628524 0.7983881 1.624599 -0.1113537
>
>
> 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: 0x5f7b4099dd30>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf77db7a30"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf4de2f041"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddafb3fd593"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf6df4c5e3"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf62cf6eb2"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf2f30742d"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf52ca7006"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf58620ea"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf598c3fcb"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf1ccba03a"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf5bd38b2e"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf69acf109"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf41bae2da"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf1c15c568"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMddaf3cbdad97"
>
>
> ### 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: 0x5f7b40845f10>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5f7b40845f10>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5f7b40845f10>
> rowMedians(tmp)
[1] -0.4273820856 -0.4673007310 0.1966685489 0.3199084659 -0.1238696670
[6] 0.3562152076 -0.1585621964 -0.2277955181 0.1668537152 -0.0738243391
[11] -0.0655309579 -0.3716699286 -0.1388116789 -0.0382084333 -0.2406854426
[16] -0.2435353019 0.5009185578 -0.0149681548 -0.2275841829 -0.5146352668
[21] 0.0911871749 0.2137181899 0.2378030684 -0.4337071419 -0.1727492044
[26] 0.0100629349 -0.3579937630 -0.4499698282 0.0632063104 0.2730285624
[31] -0.0489083696 0.1329280621 -0.1288006008 0.6094186233 0.2750585032
[36] -0.2651721487 -0.3242274703 -0.7150310796 0.3614606510 0.2405698763
[41] 0.7535355685 -0.0929434352 -0.1462516253 -0.2446638716 -0.5027920620
[46] 0.2434142627 -0.2742288414 0.1076504575 0.7439846545 0.2814304256
[51] -0.3746757764 0.8656719930 -0.0391460907 -0.3601564239 -0.0833028036
[56] -0.2017045841 0.3807754156 0.0202428985 0.0713121221 0.4201745081
[61] -0.0578521980 0.7041063390 -0.3076831763 -0.3284987878 0.0433289180
[66] -0.3148110865 -0.2908094834 -0.1649592936 0.0647215522 -0.0513304766
[71] 0.4031962956 0.1192142691 -0.4376337189 0.3917553392 0.8573013919
[76] -0.0955679020 0.0702318981 0.3701544516 -0.4713220140 0.0257408302
[81] -0.0668948597 -0.0255725651 0.4286647326 0.0151989851 -0.1816908795
[86] 0.1131551018 0.3690022810 -0.1248643958 0.1583472680 0.1460113713
[91] 0.4481274283 0.1775731471 -0.1847927439 -0.1642061842 0.0398651951
[96] 0.0994617517 0.4594239138 0.5007193512 -0.0840999872 -0.0558803130
[101] 0.2263230229 0.0735070707 -0.0170863329 -0.5091972627 0.0224037668
[106] 0.2635534422 -0.0875491583 0.2642314163 -0.2237667700 -0.2589338618
[111] 0.1232304201 0.4472550198 -0.1569795372 0.5339679126 0.6349053510
[116] -0.1419133553 -0.5135857716 -0.0986260967 -0.4388955223 0.2567900187
[121] -0.5466313370 -0.3361647606 0.0448633552 0.4218627637 -0.3768227743
[126] 0.1518453273 0.2030999503 0.2319020698 -0.2427545665 0.0238351974
[131] -0.1139027898 0.2888027695 0.1457161605 -0.0227549222 0.2392515131
[136] 0.3572999267 -0.0060329638 0.3881889808 -0.8132721514 -0.1092938253
[141] -0.8468950078 -0.2487008323 0.0544630529 0.5123607000 -0.0279637707
[146] 0.0206220981 0.4914041078 -0.0715014213 0.5180446474 0.3660300156
[151] -0.4111744794 0.3133452955 0.0822293391 0.2246715416 -0.2656018804
[156] -0.0475060987 0.4385255411 0.1192404039 -0.4142689791 0.0938920113
[161] -0.1680978824 0.0682824004 0.1108603010 -0.4648276661 -0.2339130838
[166] 0.2763607248 0.2940852694 -0.0050405877 -0.1890100178 0.0354917058
[171] -0.0279588057 0.7475653798 -0.1214374665 -0.1261214454 0.3922759495
[176] 0.2668200026 -0.3745180313 -0.2651671758 -0.3009332491 0.1322212962
[181] -0.2137844090 -0.1340322846 -0.0181348430 0.1754697882 -0.2994416080
[186] 0.1424220365 -0.1943530686 -0.0178003759 -0.6094794489 -0.2854748877
[191] 0.1158695488 -0.1025873999 -0.4167757147 0.2999018627 -0.3088484116
[196] -0.7522137411 0.0276457554 0.3895965008 0.0505241447 -0.3277962904
[201] 0.0362968558 -0.3033333547 -0.1167606424 -0.0199994540 -0.4533403905
[206] 0.1441354563 0.3015043666 0.1482074119 0.5709546519 -0.2333354879
[211] -0.1632346070 0.4493438564 -0.5453243171 -0.3984101517 0.2543989919
[216] 0.4002405545 0.0813201501 0.3576687498 -0.0007244837 -0.4226346483
[221] -0.2412723078 0.5388156509 0.5443679438 0.6223389660 -0.7864013499
[226] -0.0926734280 0.0215266475 -0.6180881467 0.3512023874 0.6982043627
>
> proc.time()
user system elapsed
1.225 0.654 1.868
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: 0x585ede9a71c0>
> .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: 0x585ede9a71c0>
> .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: 0x585ede9a71c0>
> .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: 0x585ede9a71c0>
> 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: 0x585edec8a120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edec8a120>
> .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: 0x585edec8a120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edec8a120>
> .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: 0x585edec8a120>
> 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: 0x585edd93e4a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edd93e4a0>
> .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: 0x585edd93e4a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x585edd93e4a0>
> .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: 0x585edd93e4a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x585edd93e4a0>
> .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: 0x585edd93e4a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x585edd93e4a0>
> .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: 0x585edd93e4a0>
> 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: 0x585edd9da390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x585edd9da390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edd9da390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edd9da390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilede4c2befe26e" "BufferedMatrixFilede4c5cf8bfb5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilede4c2befe26e" "BufferedMatrixFilede4c5cf8bfb5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edd8d13d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edd8d13d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x585edd8d13d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x585edd8d13d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x585edd8d13d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x585edd8d13d0>
> .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: 0x585edf406fa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x585edf406fa0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x585edf406fa0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x585edf406fa0>
> 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: 0x585edf9805d0>
> .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: 0x585edf9805d0>
> rm(P)
>
> proc.time()
user system elapsed
0.242 0.044 0.277
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
0.248 0.044 0.281