Ben Bolstad
| Snapshot Date: 2026-01-22 13:45 -0500 (Thu, 22 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 Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-01-26 11:57 -0500 (Mon, 26 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 |
| 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 | | ||||||||
|
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: 2026-01-22 21:47:48 -0500 (Thu, 22 Jan 2026) |
| EndedAt: 2026-01-22 21:48:13 -0500 (Thu, 22 Jan 2026) |
| EllapsedTime: 25.0 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
0.231 0.046 0.267
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 478284 25.6 1046725 56 639600 34.2
Vcells 884773 6.8 8388608 64 2081613 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Jan 22 21:48:05 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Jan 22 21:48:05 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: 0x595c3a8fd370>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Jan 22 21:48:05 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Jan 22 21:48:05 2026"
>
> ColMode(tmp2)
<pointer: 0x595c3a8fd370>
>
>
>
> ### 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,] 100.6053095 -0.5016036 1.3157878 -0.5922831
[2,] -0.9322619 1.7267933 -1.6114319 1.1732453
[3,] 1.5412854 1.4847574 -0.8505209 -1.2738011
[4,] -0.6398159 0.2510101 -0.3182699 -0.9538158
> 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,] 100.6053095 0.5016036 1.3157878 0.5922831
[2,] 0.9322619 1.7267933 1.6114319 1.1732453
[3,] 1.5412854 1.4847574 0.8505209 1.2738011
[4,] 0.6398159 0.2510101 0.3182699 0.9538158
> 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,] 10.0302198 0.7082398 1.1470780 0.7695993
[2,] 0.9655371 1.3140751 1.2694219 1.0831645
[3,] 1.2414852 1.2185062 0.9222369 1.1286280
[4,] 0.7998849 0.5010090 0.5641541 0.9766350
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.90751 32.58400 37.78657 33.28828
[2,] 35.58763 39.86754 39.30565 37.00489
[3,] 38.95614 38.66982 35.07289 37.56008
[4,] 33.63867 30.26110 30.95981 35.72017
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x595c3b8f99b0>
> exp(tmp5)
<pointer: 0x595c3b8f99b0>
> log(tmp5,2)
<pointer: 0x595c3b8f99b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.1969
> Min(tmp5)
[1] 54.49973
> mean(tmp5)
[1] 73.38359
> Sum(tmp5)
[1] 14676.72
> Var(tmp5)
[1] 861.2279
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.25923 72.50711 73.50669 70.84954 69.85025 70.71678 73.02613 69.60858
[9] 68.89745 73.61417
> rowSums(tmp5)
[1] 1825.185 1450.142 1470.134 1416.991 1397.005 1414.336 1460.523 1392.172
[9] 1377.949 1472.283
> rowVars(tmp5)
[1] 8008.51635 53.04662 40.76026 73.98463 59.63646 81.20508
[7] 76.08588 97.13782 54.95056 73.96138
> rowSd(tmp5)
[1] 89.490314 7.283311 6.384376 8.601432 7.722465 9.011386 8.722722
[8] 9.855852 7.412864 8.600080
> rowMax(tmp5)
[1] 470.19688 87.51024 81.08210 90.28929 89.72751 88.44154 88.76441
[8] 83.99595 84.47068 90.69477
> rowMin(tmp5)
[1] 59.03056 60.86365 62.68597 54.94305 58.95883 56.37914 58.48532 54.49973
[9] 57.48213 59.52534
>
> colMeans(tmp5)
[1] 111.43922 76.38150 75.08062 73.02805 69.65559 69.77417 67.21744
[8] 74.21348 72.54813 72.05369 73.45099 69.68477 67.17918 72.72721
[15] 72.92045 71.44076 69.93348 72.48639 69.91765 66.53910
> colSums(tmp5)
[1] 1114.3922 763.8150 750.8062 730.2805 696.5559 697.7417 672.1744
[8] 742.1348 725.4813 720.5369 734.5099 696.8477 671.7918 727.2721
[15] 729.2045 714.4076 699.3348 724.8639 699.1765 665.3910
> colVars(tmp5)
[1] 15935.37049 75.41342 68.44644 92.11837 32.87502 69.36198
[7] 79.71195 86.50458 95.10249 53.31333 46.81425 19.52542
[13] 33.47298 55.39701 80.48944 68.23282 99.50176 72.15928
[19] 97.66283 40.68112
> colSd(tmp5)
[1] 126.235377 8.684090 8.273236 9.597831 5.733674 8.328384
[7] 8.928155 9.300784 9.752050 7.301598 6.842094 4.418758
[13] 5.785583 7.442917 8.971591 8.260316 9.975057 8.494662
[19] 9.882451 6.378175
> colMax(tmp5)
[1] 470.19688 85.76611 89.72751 88.76441 78.82754 78.50000 80.53240
[8] 88.44154 87.71642 86.66175 86.36025 76.68299 80.32751 83.28138
[15] 90.28929 87.51024 90.69477 86.29382 83.99595 74.89456
> colMin(tmp5)
[1] 59.42640 62.98452 63.91780 57.48213 59.52534 56.34820 55.14597 54.94305
[9] 57.71380 61.33120 63.95562 64.93690 61.86239 58.94204 59.03056 61.92148
[17] 58.48532 62.01693 57.94622 54.49973
>
>
> ### 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] 91.25923 72.50711 73.50669 70.84954 69.85025 70.71678 73.02613 69.60858
[9] 68.89745 NA
> rowSums(tmp5)
[1] 1825.185 1450.142 1470.134 1416.991 1397.005 1414.336 1460.523 1392.172
[9] 1377.949 NA
> rowVars(tmp5)
[1] 8008.51635 53.04662 40.76026 73.98463 59.63646 81.20508
[7] 76.08588 97.13782 54.95056 61.00912
> rowSd(tmp5)
[1] 89.490314 7.283311 6.384376 8.601432 7.722465 9.011386 8.722722
[8] 9.855852 7.412864 7.810834
> rowMax(tmp5)
[1] 470.19688 87.51024 81.08210 90.28929 89.72751 88.44154 88.76441
[8] 83.99595 84.47068 NA
> rowMin(tmp5)
[1] 59.03056 60.86365 62.68597 54.94305 58.95883 56.37914 58.48532 54.49973
[9] 57.48213 NA
>
> colMeans(tmp5)
[1] 111.43922 76.38150 75.08062 73.02805 69.65559 69.77417 67.21744
[8] 74.21348 72.54813 72.05369 73.45099 69.68477 67.17918 72.72721
[15] 72.92045 71.44076 NA 72.48639 69.91765 66.53910
> colSums(tmp5)
[1] 1114.3922 763.8150 750.8062 730.2805 696.5559 697.7417 672.1744
[8] 742.1348 725.4813 720.5369 734.5099 696.8477 671.7918 727.2721
[15] 729.2045 714.4076 NA 724.8639 699.1765 665.3910
> colVars(tmp5)
[1] 15935.37049 75.41342 68.44644 92.11837 32.87502 69.36198
[7] 79.71195 86.50458 95.10249 53.31333 46.81425 19.52542
[13] 33.47298 55.39701 80.48944 68.23282 NA 72.15928
[19] 97.66283 40.68112
> colSd(tmp5)
[1] 126.235377 8.684090 8.273236 9.597831 5.733674 8.328384
[7] 8.928155 9.300784 9.752050 7.301598 6.842094 4.418758
[13] 5.785583 7.442917 8.971591 8.260316 NA 8.494662
[19] 9.882451 6.378175
> colMax(tmp5)
[1] 470.19688 85.76611 89.72751 88.76441 78.82754 78.50000 80.53240
[8] 88.44154 87.71642 86.66175 86.36025 76.68299 80.32751 83.28138
[15] 90.28929 87.51024 NA 86.29382 83.99595 74.89456
> colMin(tmp5)
[1] 59.42640 62.98452 63.91780 57.48213 59.52534 56.34820 55.14597 54.94305
[9] 57.71380 61.33120 63.95562 64.93690 61.86239 58.94204 59.03056 61.92148
[17] NA 62.01693 57.94622 54.49973
>
> Max(tmp5,na.rm=TRUE)
[1] 470.1969
> Min(tmp5,na.rm=TRUE)
[1] 54.49973
> mean(tmp5,na.rm=TRUE)
[1] 73.2966
> Sum(tmp5,na.rm=TRUE)
[1] 14586.02
> Var(tmp5,na.rm=TRUE)
[1] 864.0564
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.25923 72.50711 73.50669 70.84954 69.85025 70.71678 73.02613 69.60858
[9] 68.89745 72.71519
> rowSums(tmp5,na.rm=TRUE)
[1] 1825.185 1450.142 1470.134 1416.991 1397.005 1414.336 1460.523 1392.172
[9] 1377.949 1381.589
> rowVars(tmp5,na.rm=TRUE)
[1] 8008.51635 53.04662 40.76026 73.98463 59.63646 81.20508
[7] 76.08588 97.13782 54.95056 61.00912
> rowSd(tmp5,na.rm=TRUE)
[1] 89.490314 7.283311 6.384376 8.601432 7.722465 9.011386 8.722722
[8] 9.855852 7.412864 7.810834
> rowMax(tmp5,na.rm=TRUE)
[1] 470.19688 87.51024 81.08210 90.28929 89.72751 88.44154 88.76441
[8] 83.99595 84.47068 86.36025
> rowMin(tmp5,na.rm=TRUE)
[1] 59.03056 60.86365 62.68597 54.94305 58.95883 56.37914 58.48532 54.49973
[9] 57.48213 59.52534
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.43922 76.38150 75.08062 73.02805 69.65559 69.77417 67.21744
[8] 74.21348 72.54813 72.05369 73.45099 69.68477 67.17918 72.72721
[15] 72.92045 71.44076 67.62667 72.48639 69.91765 66.53910
> colSums(tmp5,na.rm=TRUE)
[1] 1114.3922 763.8150 750.8062 730.2805 696.5559 697.7417 672.1744
[8] 742.1348 725.4813 720.5369 734.5099 696.8477 671.7918 727.2721
[15] 729.2045 714.4076 608.6400 724.8639 699.1765 665.3910
> colVars(tmp5,na.rm=TRUE)
[1] 15935.37049 75.41342 68.44644 92.11837 32.87502 69.36198
[7] 79.71195 86.50458 95.10249 53.31333 46.81425 19.52542
[13] 33.47298 55.39701 80.48944 68.23282 52.07404 72.15928
[19] 97.66283 40.68112
> colSd(tmp5,na.rm=TRUE)
[1] 126.235377 8.684090 8.273236 9.597831 5.733674 8.328384
[7] 8.928155 9.300784 9.752050 7.301598 6.842094 4.418758
[13] 5.785583 7.442917 8.971591 8.260316 7.216234 8.494662
[19] 9.882451 6.378175
> colMax(tmp5,na.rm=TRUE)
[1] 470.19688 85.76611 89.72751 88.76441 78.82754 78.50000 80.53240
[8] 88.44154 87.71642 86.66175 86.36025 76.68299 80.32751 83.28138
[15] 90.28929 87.51024 79.92055 86.29382 83.99595 74.89456
> colMin(tmp5,na.rm=TRUE)
[1] 59.42640 62.98452 63.91780 57.48213 59.52534 56.34820 55.14597 54.94305
[9] 57.71380 61.33120 63.95562 64.93690 61.86239 58.94204 59.03056 61.92148
[17] 58.48532 62.01693 57.94622 54.49973
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.25923 72.50711 73.50669 70.84954 69.85025 70.71678 73.02613 69.60858
[9] 68.89745 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1825.185 1450.142 1470.134 1416.991 1397.005 1414.336 1460.523 1392.172
[9] 1377.949 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8008.51635 53.04662 40.76026 73.98463 59.63646 81.20508
[7] 76.08588 97.13782 54.95056 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.490314 7.283311 6.384376 8.601432 7.722465 9.011386 8.722722
[8] 9.855852 7.412864 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 470.19688 87.51024 81.08210 90.28929 89.72751 88.44154 88.76441
[8] 83.99595 84.47068 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 59.03056 60.86365 62.68597 54.94305 58.95883 56.37914 58.48532 54.49973
[9] 57.48213 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.32877 76.35774 74.28514 72.52087 70.78117 68.86726 65.73800
[8] 73.45750 72.33178 72.70849 72.01663 69.66567 67.76993 73.27489
[15] 73.01201 71.93707 NaN 73.64966 68.66780 66.16242
> colSums(tmp5,na.rm=TRUE)
[1] 1046.9589 687.2196 668.5662 652.6878 637.0305 619.8054 591.6420
[8] 661.1175 650.9860 654.3764 648.1496 626.9911 609.9294 659.4740
[15] 657.1080 647.4337 0.0000 662.8470 618.0102 595.4617
> colVars(tmp5,na.rm=TRUE)
[1] 17658.33019 84.83374 69.88333 100.73932 22.73136 68.77925
[7] 65.05260 90.88834 106.46373 55.15396 29.52033 21.96200
[13] 33.73096 58.94714 90.45631 73.99070 NA 65.95564
[19] 92.29679 44.16995
> colSd(tmp5,na.rm=TRUE)
[1] 132.884650 9.210524 8.359625 10.036898 4.767741 8.293325
[7] 8.065519 9.533537 10.318126 7.426571 5.433262 4.686363
[13] 5.807836 7.677704 9.510852 8.601785 NA 8.121308
[19] 9.607122 6.646048
> colMax(tmp5,na.rm=TRUE)
[1] 470.19688 85.76611 89.72751 88.76441 78.82754 78.50000 76.61992
[8] 88.44154 87.71642 86.66175 80.96155 76.68299 80.32751 83.28138
[15] 90.28929 87.51024 -Inf 86.29382 83.99595 74.89456
> colMin(tmp5,na.rm=TRUE)
[1] 59.42640 62.98452 63.91780 57.48213 65.60859 56.34820 55.14597 54.94305
[9] 57.71380 61.33120 63.95562 64.93690 61.86788 58.94204 59.03056 61.92148
[17] Inf 62.26422 57.94622 54.49973
>
>
>
>
> 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] 164.36728 221.40767 172.64043 211.52878 291.99381 363.92530 175.65517
[8] 78.96037 218.68494 218.98672
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 164.36728 221.40767 172.64043 211.52878 291.99381 363.92530 175.65517
[8] 78.96037 218.68494 218.98672
>
>
>
> 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] -4.263256e-14 -8.526513e-14 5.684342e-14 5.684342e-14 5.684342e-14
[6] -1.705303e-13 4.547474e-13 2.842171e-14 -1.421085e-13 -2.842171e-14
[11] -1.705303e-13 0.000000e+00 0.000000e+00 0.000000e+00 -2.842171e-14
[16] -2.842171e-14 5.684342e-14 -2.842171e-14 -5.684342e-14 -2.557954e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 8
9 6
9 16
4 2
2 4
6 9
10 8
2 6
8 20
4 2
1 19
8 20
4 14
2 10
3 3
2 7
6 4
5 18
6 2
2 18
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] 1.96479
> Min(tmp)
[1] -3.196978
> mean(tmp)
[1] -0.1130786
> Sum(tmp)
[1] -11.30786
> Var(tmp)
[1] 1.02187
>
> rowMeans(tmp)
[1] -0.1130786
> rowSums(tmp)
[1] -11.30786
> rowVars(tmp)
[1] 1.02187
> rowSd(tmp)
[1] 1.010876
> rowMax(tmp)
[1] 1.96479
> rowMin(tmp)
[1] -3.196978
>
> colMeans(tmp)
[1] 1.45005460 -0.91927751 0.54409643 1.23226428 -1.12385032 1.21595268
[7] -0.70576578 -1.85528794 -0.72905179 -0.17185110 -1.30943800 -2.38499245
[13] 0.28863968 -1.50761516 -1.02910371 -0.08635262 0.78459331 1.21966315
[19] -1.02730259 -0.30181641 -0.96652670 -0.97397855 0.39045405 1.71878830
[25] -1.51086025 1.55346785 -0.76660749 -0.74832000 -3.19697813 0.79765563
[31] -1.10735773 0.91528481 0.75202867 -0.46900844 -0.64461330 0.77046953
[37] 0.18615966 1.43757805 -1.01348469 0.43705775 1.50249332 0.17034911
[43] -0.82956397 -2.00343901 -0.70892553 1.29313705 -0.91177621 0.68856476
[49] 0.05215415 -0.25766829 1.18889051 -0.25975703 -0.70346191 0.65894004
[55] -0.96899034 0.45032779 0.15756694 0.50621706 -0.88599004 0.62932882
[61] 0.29956093 0.11210977 -2.09750286 0.97419564 -0.41463297 -1.06360884
[67] 0.53122157 -0.19410805 1.12352835 0.07740225 1.96479016 -0.09832492
[73] -1.35053380 -0.52366236 -1.52855053 -0.44091322 -1.05849102 1.48027230
[79] -0.52192627 -0.33218792 -0.16263392 -0.07129991 -0.60386828 0.83553849
[85] 0.87073361 -0.39635275 -0.66493136 0.12297971 0.69437948 -1.73649131
[91] -0.90125873 0.93237025 0.93278207 -0.11240088 -0.69917107 0.29555357
[97] 0.60052593 1.35014194 -0.12289405 -0.32336140
> colSums(tmp)
[1] 1.45005460 -0.91927751 0.54409643 1.23226428 -1.12385032 1.21595268
[7] -0.70576578 -1.85528794 -0.72905179 -0.17185110 -1.30943800 -2.38499245
[13] 0.28863968 -1.50761516 -1.02910371 -0.08635262 0.78459331 1.21966315
[19] -1.02730259 -0.30181641 -0.96652670 -0.97397855 0.39045405 1.71878830
[25] -1.51086025 1.55346785 -0.76660749 -0.74832000 -3.19697813 0.79765563
[31] -1.10735773 0.91528481 0.75202867 -0.46900844 -0.64461330 0.77046953
[37] 0.18615966 1.43757805 -1.01348469 0.43705775 1.50249332 0.17034911
[43] -0.82956397 -2.00343901 -0.70892553 1.29313705 -0.91177621 0.68856476
[49] 0.05215415 -0.25766829 1.18889051 -0.25975703 -0.70346191 0.65894004
[55] -0.96899034 0.45032779 0.15756694 0.50621706 -0.88599004 0.62932882
[61] 0.29956093 0.11210977 -2.09750286 0.97419564 -0.41463297 -1.06360884
[67] 0.53122157 -0.19410805 1.12352835 0.07740225 1.96479016 -0.09832492
[73] -1.35053380 -0.52366236 -1.52855053 -0.44091322 -1.05849102 1.48027230
[79] -0.52192627 -0.33218792 -0.16263392 -0.07129991 -0.60386828 0.83553849
[85] 0.87073361 -0.39635275 -0.66493136 0.12297971 0.69437948 -1.73649131
[91] -0.90125873 0.93237025 0.93278207 -0.11240088 -0.69917107 0.29555357
[97] 0.60052593 1.35014194 -0.12289405 -0.32336140
> 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] 1.45005460 -0.91927751 0.54409643 1.23226428 -1.12385032 1.21595268
[7] -0.70576578 -1.85528794 -0.72905179 -0.17185110 -1.30943800 -2.38499245
[13] 0.28863968 -1.50761516 -1.02910371 -0.08635262 0.78459331 1.21966315
[19] -1.02730259 -0.30181641 -0.96652670 -0.97397855 0.39045405 1.71878830
[25] -1.51086025 1.55346785 -0.76660749 -0.74832000 -3.19697813 0.79765563
[31] -1.10735773 0.91528481 0.75202867 -0.46900844 -0.64461330 0.77046953
[37] 0.18615966 1.43757805 -1.01348469 0.43705775 1.50249332 0.17034911
[43] -0.82956397 -2.00343901 -0.70892553 1.29313705 -0.91177621 0.68856476
[49] 0.05215415 -0.25766829 1.18889051 -0.25975703 -0.70346191 0.65894004
[55] -0.96899034 0.45032779 0.15756694 0.50621706 -0.88599004 0.62932882
[61] 0.29956093 0.11210977 -2.09750286 0.97419564 -0.41463297 -1.06360884
[67] 0.53122157 -0.19410805 1.12352835 0.07740225 1.96479016 -0.09832492
[73] -1.35053380 -0.52366236 -1.52855053 -0.44091322 -1.05849102 1.48027230
[79] -0.52192627 -0.33218792 -0.16263392 -0.07129991 -0.60386828 0.83553849
[85] 0.87073361 -0.39635275 -0.66493136 0.12297971 0.69437948 -1.73649131
[91] -0.90125873 0.93237025 0.93278207 -0.11240088 -0.69917107 0.29555357
[97] 0.60052593 1.35014194 -0.12289405 -0.32336140
> colMin(tmp)
[1] 1.45005460 -0.91927751 0.54409643 1.23226428 -1.12385032 1.21595268
[7] -0.70576578 -1.85528794 -0.72905179 -0.17185110 -1.30943800 -2.38499245
[13] 0.28863968 -1.50761516 -1.02910371 -0.08635262 0.78459331 1.21966315
[19] -1.02730259 -0.30181641 -0.96652670 -0.97397855 0.39045405 1.71878830
[25] -1.51086025 1.55346785 -0.76660749 -0.74832000 -3.19697813 0.79765563
[31] -1.10735773 0.91528481 0.75202867 -0.46900844 -0.64461330 0.77046953
[37] 0.18615966 1.43757805 -1.01348469 0.43705775 1.50249332 0.17034911
[43] -0.82956397 -2.00343901 -0.70892553 1.29313705 -0.91177621 0.68856476
[49] 0.05215415 -0.25766829 1.18889051 -0.25975703 -0.70346191 0.65894004
[55] -0.96899034 0.45032779 0.15756694 0.50621706 -0.88599004 0.62932882
[61] 0.29956093 0.11210977 -2.09750286 0.97419564 -0.41463297 -1.06360884
[67] 0.53122157 -0.19410805 1.12352835 0.07740225 1.96479016 -0.09832492
[73] -1.35053380 -0.52366236 -1.52855053 -0.44091322 -1.05849102 1.48027230
[79] -0.52192627 -0.33218792 -0.16263392 -0.07129991 -0.60386828 0.83553849
[85] 0.87073361 -0.39635275 -0.66493136 0.12297971 0.69437948 -1.73649131
[91] -0.90125873 0.93237025 0.93278207 -0.11240088 -0.69917107 0.29555357
[97] 0.60052593 1.35014194 -0.12289405 -0.32336140
> colMedians(tmp)
[1] 1.45005460 -0.91927751 0.54409643 1.23226428 -1.12385032 1.21595268
[7] -0.70576578 -1.85528794 -0.72905179 -0.17185110 -1.30943800 -2.38499245
[13] 0.28863968 -1.50761516 -1.02910371 -0.08635262 0.78459331 1.21966315
[19] -1.02730259 -0.30181641 -0.96652670 -0.97397855 0.39045405 1.71878830
[25] -1.51086025 1.55346785 -0.76660749 -0.74832000 -3.19697813 0.79765563
[31] -1.10735773 0.91528481 0.75202867 -0.46900844 -0.64461330 0.77046953
[37] 0.18615966 1.43757805 -1.01348469 0.43705775 1.50249332 0.17034911
[43] -0.82956397 -2.00343901 -0.70892553 1.29313705 -0.91177621 0.68856476
[49] 0.05215415 -0.25766829 1.18889051 -0.25975703 -0.70346191 0.65894004
[55] -0.96899034 0.45032779 0.15756694 0.50621706 -0.88599004 0.62932882
[61] 0.29956093 0.11210977 -2.09750286 0.97419564 -0.41463297 -1.06360884
[67] 0.53122157 -0.19410805 1.12352835 0.07740225 1.96479016 -0.09832492
[73] -1.35053380 -0.52366236 -1.52855053 -0.44091322 -1.05849102 1.48027230
[79] -0.52192627 -0.33218792 -0.16263392 -0.07129991 -0.60386828 0.83553849
[85] 0.87073361 -0.39635275 -0.66493136 0.12297971 0.69437948 -1.73649131
[91] -0.90125873 0.93237025 0.93278207 -0.11240088 -0.69917107 0.29555357
[97] 0.60052593 1.35014194 -0.12289405 -0.32336140
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.450055 -0.9192775 0.5440964 1.232264 -1.12385 1.215953 -0.7057658
[2,] 1.450055 -0.9192775 0.5440964 1.232264 -1.12385 1.215953 -0.7057658
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.855288 -0.7290518 -0.1718511 -1.309438 -2.384992 0.2886397 -1.507615
[2,] -1.855288 -0.7290518 -0.1718511 -1.309438 -2.384992 0.2886397 -1.507615
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.029104 -0.08635262 0.7845933 1.219663 -1.027303 -0.3018164 -0.9665267
[2,] -1.029104 -0.08635262 0.7845933 1.219663 -1.027303 -0.3018164 -0.9665267
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.9739786 0.390454 1.718788 -1.51086 1.553468 -0.7666075 -0.74832
[2,] -0.9739786 0.390454 1.718788 -1.51086 1.553468 -0.7666075 -0.74832
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -3.196978 0.7976556 -1.107358 0.9152848 0.7520287 -0.4690084 -0.6446133
[2,] -3.196978 0.7976556 -1.107358 0.9152848 0.7520287 -0.4690084 -0.6446133
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.7704695 0.1861597 1.437578 -1.013485 0.4370577 1.502493 0.1703491
[2,] 0.7704695 0.1861597 1.437578 -1.013485 0.4370577 1.502493 0.1703491
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.829564 -2.003439 -0.7089255 1.293137 -0.9117762 0.6885648 0.05215415
[2,] -0.829564 -2.003439 -0.7089255 1.293137 -0.9117762 0.6885648 0.05215415
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.2576683 1.188891 -0.259757 -0.7034619 0.65894 -0.9689903 0.4503278
[2,] -0.2576683 1.188891 -0.259757 -0.7034619 0.65894 -0.9689903 0.4503278
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.1575669 0.5062171 -0.88599 0.6293288 0.2995609 0.1121098 -2.097503
[2,] 0.1575669 0.5062171 -0.88599 0.6293288 0.2995609 0.1121098 -2.097503
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.9741956 -0.414633 -1.063609 0.5312216 -0.1941081 1.123528 0.07740225
[2,] 0.9741956 -0.414633 -1.063609 0.5312216 -0.1941081 1.123528 0.07740225
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.96479 -0.09832492 -1.350534 -0.5236624 -1.528551 -0.4409132 -1.058491
[2,] 1.96479 -0.09832492 -1.350534 -0.5236624 -1.528551 -0.4409132 -1.058491
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.480272 -0.5219263 -0.3321879 -0.1626339 -0.07129991 -0.6038683 0.8355385
[2,] 1.480272 -0.5219263 -0.3321879 -0.1626339 -0.07129991 -0.6038683 0.8355385
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.8707336 -0.3963527 -0.6649314 0.1229797 0.6943795 -1.736491 -0.9012587
[2,] 0.8707336 -0.3963527 -0.6649314 0.1229797 0.6943795 -1.736491 -0.9012587
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.9323702 0.9327821 -0.1124009 -0.6991711 0.2955536 0.6005259 1.350142
[2,] 0.9323702 0.9327821 -0.1124009 -0.6991711 0.2955536 0.6005259 1.350142
[,99] [,100]
[1,] -0.122894 -0.3233614
[2,] -0.122894 -0.3233614
>
>
> Max(tmp2)
[1] 2.072251
> Min(tmp2)
[1] -2.741714
> mean(tmp2)
[1] 0.07718342
> Sum(tmp2)
[1] 7.718342
> Var(tmp2)
[1] 0.9507778
>
> rowMeans(tmp2)
[1] 0.667799399 0.597774054 -0.251628226 0.491699212 -0.587029391
[6] 0.807812394 -0.138451929 -0.707675938 -0.108120553 0.852350410
[11] -0.518699823 1.477521742 0.220738511 -0.597895495 -1.839716491
[16] 1.699678646 0.486370793 0.035479957 -0.813619507 0.265315476
[21] 1.047633029 1.206310438 -0.107498626 -0.774137592 2.072251370
[26] 0.579448155 1.290205019 -1.948213480 0.040024435 -0.664447740
[31] -0.960382283 0.852182964 1.149271999 -0.204198030 -0.187628223
[36] -0.093135929 0.367215182 -0.198838893 0.172559006 0.051286806
[41] 0.910184523 0.295488065 -1.078205196 -0.472045400 -1.217157467
[46] -1.786074492 0.303793030 0.061012124 1.091985059 0.925294559
[51] 0.236950751 0.522454508 0.116031030 0.192263595 0.057650466
[56] -2.741713702 -0.114886186 -1.265400998 0.517340705 0.302708716
[61] 1.877833950 -0.460474222 1.170316106 -0.101904829 -0.174890380
[66] -0.987697148 -1.070168781 0.833637577 1.139527333 0.195510330
[71] -1.815976826 -2.367375098 -0.715430750 0.806814967 -0.898954599
[76] -0.808097479 1.038474461 0.790320008 1.427323192 -0.087854082
[81] -0.003650934 -0.879575305 -0.337233076 1.031971928 0.752172542
[86] 0.511139483 0.638919786 -0.065584530 1.281029017 1.476892259
[91] 0.847222117 0.200656020 1.937939101 -0.404414830 -0.085021072
[96] -0.861084570 -1.457498228 0.404272920 -1.547727279 1.899698279
> rowSums(tmp2)
[1] 0.667799399 0.597774054 -0.251628226 0.491699212 -0.587029391
[6] 0.807812394 -0.138451929 -0.707675938 -0.108120553 0.852350410
[11] -0.518699823 1.477521742 0.220738511 -0.597895495 -1.839716491
[16] 1.699678646 0.486370793 0.035479957 -0.813619507 0.265315476
[21] 1.047633029 1.206310438 -0.107498626 -0.774137592 2.072251370
[26] 0.579448155 1.290205019 -1.948213480 0.040024435 -0.664447740
[31] -0.960382283 0.852182964 1.149271999 -0.204198030 -0.187628223
[36] -0.093135929 0.367215182 -0.198838893 0.172559006 0.051286806
[41] 0.910184523 0.295488065 -1.078205196 -0.472045400 -1.217157467
[46] -1.786074492 0.303793030 0.061012124 1.091985059 0.925294559
[51] 0.236950751 0.522454508 0.116031030 0.192263595 0.057650466
[56] -2.741713702 -0.114886186 -1.265400998 0.517340705 0.302708716
[61] 1.877833950 -0.460474222 1.170316106 -0.101904829 -0.174890380
[66] -0.987697148 -1.070168781 0.833637577 1.139527333 0.195510330
[71] -1.815976826 -2.367375098 -0.715430750 0.806814967 -0.898954599
[76] -0.808097479 1.038474461 0.790320008 1.427323192 -0.087854082
[81] -0.003650934 -0.879575305 -0.337233076 1.031971928 0.752172542
[86] 0.511139483 0.638919786 -0.065584530 1.281029017 1.476892259
[91] 0.847222117 0.200656020 1.937939101 -0.404414830 -0.085021072
[96] -0.861084570 -1.457498228 0.404272920 -1.547727279 1.899698279
> 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] 0.667799399 0.597774054 -0.251628226 0.491699212 -0.587029391
[6] 0.807812394 -0.138451929 -0.707675938 -0.108120553 0.852350410
[11] -0.518699823 1.477521742 0.220738511 -0.597895495 -1.839716491
[16] 1.699678646 0.486370793 0.035479957 -0.813619507 0.265315476
[21] 1.047633029 1.206310438 -0.107498626 -0.774137592 2.072251370
[26] 0.579448155 1.290205019 -1.948213480 0.040024435 -0.664447740
[31] -0.960382283 0.852182964 1.149271999 -0.204198030 -0.187628223
[36] -0.093135929 0.367215182 -0.198838893 0.172559006 0.051286806
[41] 0.910184523 0.295488065 -1.078205196 -0.472045400 -1.217157467
[46] -1.786074492 0.303793030 0.061012124 1.091985059 0.925294559
[51] 0.236950751 0.522454508 0.116031030 0.192263595 0.057650466
[56] -2.741713702 -0.114886186 -1.265400998 0.517340705 0.302708716
[61] 1.877833950 -0.460474222 1.170316106 -0.101904829 -0.174890380
[66] -0.987697148 -1.070168781 0.833637577 1.139527333 0.195510330
[71] -1.815976826 -2.367375098 -0.715430750 0.806814967 -0.898954599
[76] -0.808097479 1.038474461 0.790320008 1.427323192 -0.087854082
[81] -0.003650934 -0.879575305 -0.337233076 1.031971928 0.752172542
[86] 0.511139483 0.638919786 -0.065584530 1.281029017 1.476892259
[91] 0.847222117 0.200656020 1.937939101 -0.404414830 -0.085021072
[96] -0.861084570 -1.457498228 0.404272920 -1.547727279 1.899698279
> rowMin(tmp2)
[1] 0.667799399 0.597774054 -0.251628226 0.491699212 -0.587029391
[6] 0.807812394 -0.138451929 -0.707675938 -0.108120553 0.852350410
[11] -0.518699823 1.477521742 0.220738511 -0.597895495 -1.839716491
[16] 1.699678646 0.486370793 0.035479957 -0.813619507 0.265315476
[21] 1.047633029 1.206310438 -0.107498626 -0.774137592 2.072251370
[26] 0.579448155 1.290205019 -1.948213480 0.040024435 -0.664447740
[31] -0.960382283 0.852182964 1.149271999 -0.204198030 -0.187628223
[36] -0.093135929 0.367215182 -0.198838893 0.172559006 0.051286806
[41] 0.910184523 0.295488065 -1.078205196 -0.472045400 -1.217157467
[46] -1.786074492 0.303793030 0.061012124 1.091985059 0.925294559
[51] 0.236950751 0.522454508 0.116031030 0.192263595 0.057650466
[56] -2.741713702 -0.114886186 -1.265400998 0.517340705 0.302708716
[61] 1.877833950 -0.460474222 1.170316106 -0.101904829 -0.174890380
[66] -0.987697148 -1.070168781 0.833637577 1.139527333 0.195510330
[71] -1.815976826 -2.367375098 -0.715430750 0.806814967 -0.898954599
[76] -0.808097479 1.038474461 0.790320008 1.427323192 -0.087854082
[81] -0.003650934 -0.879575305 -0.337233076 1.031971928 0.752172542
[86] 0.511139483 0.638919786 -0.065584530 1.281029017 1.476892259
[91] 0.847222117 0.200656020 1.937939101 -0.404414830 -0.085021072
[96] -0.861084570 -1.457498228 0.404272920 -1.547727279 1.899698279
>
> colMeans(tmp2)
[1] 0.07718342
> colSums(tmp2)
[1] 7.718342
> colVars(tmp2)
[1] 0.9507778
> colSd(tmp2)
[1] 0.9750784
> colMax(tmp2)
[1] 2.072251
> colMin(tmp2)
[1] -2.741714
> colMedians(tmp2)
[1] 0.08852158
> colRanges(tmp2)
[,1]
[1,] -2.741714
[2,] 2.072251
>
> 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] 1.6838456 0.9396486 -0.9998865 2.5970892 1.3334478 2.6587151
[7] -0.9905247 -2.1593628 -0.9137275 5.6327665
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7431164
[2,] -0.3309692
[3,] 0.3874478
[4,] 0.7686816
[5,] 1.2383334
>
> rowApply(tmp,sum)
[1] -1.4693029 4.1056822 0.3230407 -1.4494808 -7.2403612 1.5669033
[7] -2.5149693 3.9629864 6.9455815 5.5519314
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 1 7 4 9 8 1 7 5 8
[2,] 2 6 8 6 6 3 8 4 6 9
[3,] 8 3 4 7 8 7 2 1 7 1
[4,] 5 5 3 8 4 2 9 10 8 2
[5,] 4 8 5 10 10 6 3 3 3 3
[6,] 3 10 1 2 5 1 7 9 9 10
[7,] 10 4 6 1 2 9 5 8 1 4
[8,] 1 2 2 3 3 5 10 2 10 5
[9,] 9 7 9 5 1 4 6 5 4 7
[10,] 6 9 10 9 7 10 4 6 2 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.25002924 1.46104294 -2.95506626 -0.53091211 -2.12456756 -0.79532114
[7] 4.01534984 1.74634288 -0.13171956 -0.11891948 -2.17130836 -1.24629552
[13] -1.62600006 -0.11387821 -0.90800604 -1.58332649 -2.62676369 2.37509661
[19] 2.48743883 -0.04614601
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5104103
[2,] -1.0154007
[3,] -0.4058972
[4,] -0.1874993
[5,] -0.1308218
>
> rowApply(tmp,sum)
[1] 6.1589075 -3.2620356 -6.8203285 -4.9496142 0.7300821
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 9 13 3 8
[2,] 12 14 11 19 6
[3,] 4 4 20 1 7
[4,] 13 10 8 18 2
[5,] 5 20 4 2 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.0154007 0.3717304 -0.7563788 0.3788616 -0.3747230 0.9765721
[2,] -0.4058972 0.4644569 -0.9859378 -0.1815462 1.1861301 0.5795915
[3,] -0.1874993 -0.3256701 1.1915471 -0.3958690 -1.3069767 -0.6489438
[4,] -1.5104103 1.2895461 -2.1941317 0.8119567 -1.7875638 -0.4244238
[5,] -0.1308218 -0.3390204 -0.2101650 -1.1443152 0.1585659 -1.2781171
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3264474 -0.10070330 0.002006268 0.51821858 -0.3395243 -0.79603438
[2,] 0.3523220 0.91365850 0.448696182 -0.52207442 -2.0405077 0.06317714
[3,] 0.9629796 0.38335729 -0.062854974 0.35553400 -0.3632724 -0.38659291
[4,] 1.4002035 0.62860108 -1.241726184 -0.45087314 0.0378412 0.80069351
[5,] 0.9733974 -0.07857069 0.722159145 -0.01972449 0.5341549 -0.92753889
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.3686302 1.0665692 0.2835235 -0.96849660 -0.023844100 2.2391076
[2,] -1.1114967 0.6787206 0.7776565 0.53713091 -1.935994583 -0.7506252
[3,] -0.4134038 -0.1967202 -1.8205129 -1.43813633 0.009354603 -0.8093216
[4,] -0.5925094 -0.7546975 -0.6486502 -0.01334375 -0.692459932 0.1994134
[5,] -0.8772203 -0.9077502 0.4999771 0.29951928 0.016180326 1.4965224
[,19] [,20]
[1,] 1.2553898 1.7469560
[2,] -0.5973867 -0.7321093
[3,] 0.3490227 -1.7163498
[4,] -0.2107171 0.4036373
[5,] 1.6911301 0.2517198
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 564 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 -0.6681619 -1.962752 -1.17346 0.8289952 0.4767978 0.6474136 0.05885912
col8 col9 col10 col11 col12 col13 col14
row1 -0.7805542 2.242419 -0.2104928 1.530749 0.6295136 -0.9402991 0.607
col15 col16 col17 col18 col19 col20
row1 0.604006 -0.8294512 1.51483 -0.3754343 -0.8406598 -0.7791491
> tmp[,"col10"]
col10
row1 -0.2104928
row2 -1.7803492
row3 1.0352142
row4 -1.6697921
row5 -0.2616765
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.6681619 -1.9627515 -1.1734604 0.8289952 0.4767978 0.6474136
row5 -0.6936230 -0.7170836 -0.4889842 -0.8185879 -1.2879063 -1.4927310
col7 col8 col9 col10 col11 col12 col13
row1 0.05885912 -0.7805542 2.2424187 -0.2104928 1.5307492 0.6295136 -0.9402991
row5 -0.30186541 -0.9654073 0.4534674 -0.2616765 0.7753874 0.4807692 0.5536791
col14 col15 col16 col17 col18 col19 col20
row1 0.6070000 0.604006 -0.8294512 1.5148298 -0.3754343 -0.8406598 -0.7791491
row5 0.1101018 0.584041 0.4101213 0.5958405 -0.5348197 -1.1059380 1.0533864
> tmp[,c("col6","col20")]
col6 col20
row1 0.6474136 -0.77914907
row2 -0.1677066 -1.30272678
row3 0.8165026 1.78734784
row4 1.2492880 -0.04468671
row5 -1.4927310 1.05338636
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.6474136 -0.7791491
row5 -1.4927310 1.0533864
>
>
>
>
> 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 49.85747 50.70465 51.61174 50.87914 51.08433 104.3329 52.63473 47.65275
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.76558 49.64028 49.00558 47.89334 50.25851 48.51913 50.0881 49.87979
col17 col18 col19 col20
row1 50.19818 50.01513 50.15119 103.3426
> tmp[,"col10"]
col10
row1 49.64028
row2 29.63101
row3 30.01465
row4 31.78798
row5 49.79867
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.85747 50.70465 51.61174 50.87914 51.08433 104.3329 52.63473 47.65275
row5 49.71843 49.65924 50.03085 49.72049 50.12140 106.9212 49.34527 50.72163
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.76558 49.64028 49.00558 47.89334 50.25851 48.51913 50.08810 49.87979
row5 50.29784 49.79867 49.93714 49.65544 50.41664 51.03260 50.54465 49.82203
col17 col18 col19 col20
row1 50.19818 50.01513 50.15119 103.3426
row5 51.39376 50.78076 48.18495 104.2850
> tmp[,c("col6","col20")]
col6 col20
row1 104.33291 103.34263
row2 73.72834 74.70507
row3 74.81002 73.60445
row4 72.80975 76.71807
row5 106.92115 104.28504
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.3329 103.3426
row5 106.9212 104.2850
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.3329 103.3426
row5 106.9212 104.2850
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.9868945
[2,] -0.3754572
[3,] 2.4004331
[4,] -0.9396909
[5,] -0.1313829
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.2277400 -0.4556394
[2,] -0.7122239 0.2261368
[3,] -0.1208145 1.2878175
[4,] -0.8934299 -0.0356839
[5,] 2.4257056 -0.1439599
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.1927022 -1.1555903
[2,] -0.3108186 -0.8011672
[3,] -1.2031718 0.8128378
[4,] -0.3812943 -0.2334931
[5,] 0.5671989 2.5708012
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.1927022
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.1927022
[2,] -0.3108186
>
>
>
> 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 -0.2440097 1.167013 0.1924225 1.1166585 -0.2170628 0.6922100 0.5390077
row1 0.2634636 -1.572593 -0.9397214 -0.6093975 -0.2024835 -0.7279255 0.9294834
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.602692 -0.7421107 1.4260204 0.1121635 0.3228817 -0.4093543 -0.9273632
row1 -1.254318 1.7429808 0.6490989 0.1350815 -0.5998656 1.5917849 -0.8032765
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.6163656 -2.056493 -0.5769534 2.201686 0.5088278 -0.03962215
row1 1.8970772 -1.114608 -0.4446216 1.820650 0.1987445 -0.09055161
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2039735 0.6886759 -1.163015 0.5158104 1.214661 -0.1116665 -1.019759
[,8] [,9] [,10]
row2 -1.255661 -0.5886739 0.2792637
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.180738 1.880532 -0.2667233 -0.1772898 -1.213988 -0.08742777 -0.7364433
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.8283139 -0.5666673 -0.3685804 -0.942211 0.8829703 -0.5052418 -0.657079
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4011609 0.6879667 -1.486822 0.1402454 -0.2071722 0.330189
>
>
> 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: 0x595c3b4fb220>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede1c8e6d18"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede74b46f"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede5e298ba7"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede6de7b123"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede54b12a15"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede2ef5738d"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede29a4141d"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede53c2276a"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede6c01722e"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede33ddf3f2"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede3b569189"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede35ecfadf"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede3ece0767"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede61e91658"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3c7ede1ccbb4d"
>
>
> ### 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: 0x595c3b880000>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x595c3b880000>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x595c3b880000>
> rowMedians(tmp)
[1] -0.076320709 -0.608349134 0.059165910 -0.384616476 0.122651020
[6] 0.394166692 -0.035447748 0.159786793 -0.220976761 -0.065842933
[11] -0.440833684 0.389666873 0.298849414 -0.053924594 0.007864853
[16] -0.220488329 0.081816299 -0.778001658 -0.384193821 0.071744976
[21] -0.177966562 0.512587183 -0.085476434 0.299682384 -0.062015767
[26] 0.127843268 0.420686966 0.430716544 -0.609690298 0.330188490
[31] 0.315275798 -0.388313150 0.236311618 -0.074944566 -0.359036943
[36] -0.499413962 -0.260720184 -0.085643336 -0.195277052 -0.170747264
[41] -0.193632194 -0.062668854 -0.269652830 0.137189449 -0.345797385
[46] 0.739499690 -0.070138485 -0.005936025 0.344628191 0.330527623
[51] -0.044532663 -0.494413927 0.746175558 0.245442940 0.091046933
[56] -0.362169035 -0.400648617 -0.152300311 0.025177182 0.157835036
[61] 0.047340309 0.352871700 -0.149244412 0.183052885 -0.351333487
[66] -0.510291984 -0.097989867 0.614756634 -0.270086542 0.230367440
[71] -0.257387055 -0.078383483 -0.215273338 -0.031974830 -0.437073683
[76] 0.222734138 -0.040162424 -0.020620618 0.185129264 -0.487978491
[81] 0.382960291 -0.007659244 0.307276922 0.259078747 0.116591610
[86] 0.112670411 -0.261863655 0.218809339 0.140395477 0.087995208
[91] 0.566927732 0.352880458 0.177975985 0.050460626 -0.033707660
[96] 0.069439531 -0.282430295 0.277665054 0.607701013 0.366777413
[101] 0.201403658 -0.404001657 -0.531202878 0.551951684 -0.326783177
[106] -0.247992363 0.138913609 0.002230599 0.119486184 -0.378016145
[111] -0.096385287 0.122916228 0.137959013 -0.224750350 0.067716960
[116] 0.343713603 0.650118049 -0.027903294 -0.171035806 -0.156643155
[121] -0.023515057 -0.434693728 0.763520717 -0.848732120 0.469818948
[126] 0.187811285 -0.117483715 0.021173961 0.083557881 -0.154776518
[131] -0.004576451 0.424924715 0.115564302 0.225994264 -0.023625498
[136] 0.044975369 0.154871258 0.018926510 -0.622075988 0.062999213
[141] 0.248157527 0.146022724 0.545772999 0.038906366 -0.399730080
[146] -0.014496741 -0.105390861 -0.299722521 -0.137881022 -0.089169338
[151] 0.158756472 0.204609037 0.068092384 -0.089829964 0.104928864
[156] 0.099034426 -0.082438045 0.067056021 0.122025595 0.255353698
[161] 0.196674270 -0.080765445 0.225186989 -0.022747847 -0.124016859
[166] -0.183556082 -0.577396084 0.208261004 -0.245797316 0.532411281
[171] 0.433006678 0.191862142 0.242276196 -0.027783295 0.122669872
[176] 0.231489967 -0.295142051 0.289619440 0.102032633 0.089222754
[181] 0.030644631 -0.214497862 0.235321543 0.453615024 0.224421875
[186] -0.262876993 -0.396529439 -0.010718149 0.193012531 0.089797879
[191] -0.306547660 0.359076753 0.287891643 0.217887954 -0.066852801
[196] 0.455139948 -0.063416671 -0.237036212 -0.012030877 0.043063364
[201] 0.522955698 -0.167372468 -0.067335645 -0.354780751 -0.355243271
[206] -0.166034658 -0.306242996 -0.370270644 0.169370963 0.186384408
[211] -0.482928472 -0.446525706 -0.212810411 0.559246465 -0.085684236
[216] -0.032021566 0.388732748 -0.119431891 0.213912212 -0.054536970
[221] 0.193183200 -0.529373165 0.252472446 -0.232662595 -0.057184545
[226] -0.482565955 0.879816491 -0.127827113 -0.011993475 0.161614087
>
> proc.time()
user system elapsed
1.211 0.668 1.865
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: 0x57846ca97370>
> .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: 0x57846ca97370>
> .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: 0x57846ca97370>
> .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: 0x57846ca97370>
> 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: 0x57846ca7f1c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846ca7f1c0>
> .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: 0x57846ca7f1c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846ca7f1c0>
> .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: 0x57846ca7f1c0>
> 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: 0x57846cd62120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846cd62120>
> .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: 0x57846cd62120>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x57846cd62120>
> .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: 0x57846cd62120>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x57846cd62120>
> .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: 0x57846cd62120>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x57846cd62120>
> .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: 0x57846cd62120>
> 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: 0x57846bab2390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x57846bab2390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846bab2390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846bab2390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3c7f32283eaac3" "BufferedMatrixFile3c7f327ece5285"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3c7f32283eaac3" "BufferedMatrixFile3c7f327ece5285"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846b9a93d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846b9a93d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x57846b9a93d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x57846b9a93d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x57846b9a93d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x57846b9a93d0>
> .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: 0x57846d4defa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x57846d4defa0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x57846d4defa0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x57846d4defa0>
> 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: 0x57846bcb6ff0>
> .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: 0x57846bcb6ff0>
> rm(P)
>
> proc.time()
user system elapsed
0.243 0.041 0.275
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
0.231 0.049 0.268