Ben Bolstad
| Snapshot Date: 2026-03-17 13:45 -0400 (Tue, 17 Mar 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 -0400 (Wed, 29 Oct 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-03-18 11:57 -0400 (Wed, 18 Mar 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" | 4892 |
| 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: 2026-03-17 21:36:40 -0400 (Tue, 17 Mar 2026) |
| EndedAt: 2026-03-17 21:37:04 -0400 (Tue, 17 Mar 2026) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
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### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.74.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.22-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.243 0.041 0.273
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] "Tue Mar 17 21:36:55 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] "Tue Mar 17 21:36:55 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: 0x5b96fa67a1c0>
>
>
>
> 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] "Tue Mar 17 21:36:55 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] "Tue Mar 17 21:36:55 2026"
>
> ColMode(tmp2)
<pointer: 0x5b96fa67a1c0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.9258338 -1.044465 1.7217850 -0.5735839
[2,] -0.8251591 -0.203069 0.4125262 0.4278338
[3,] 0.5881727 1.467345 0.2795536 0.3490375
[4,] -0.5649499 0.889680 -0.6444169 1.2554536
> 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,] 99.9258338 1.044465 1.7217850 0.5735839
[2,] 0.8251591 0.203069 0.4125262 0.4278338
[3,] 0.5881727 1.467345 0.2795536 0.3490375
[4,] 0.5649499 0.889680 0.6444169 1.2554536
> 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,] 9.9962910 1.0219907 1.3121681 0.7573532
[2,] 0.9083827 0.4506318 0.6422820 0.6540900
[3,] 0.7669242 1.2113402 0.5287283 0.5907940
[4,] 0.7516315 0.9432285 0.8027558 1.1204703
>
> 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,] 224.88874 36.26437 39.84347 33.14712
[2,] 34.90899 29.70939 31.83535 31.96873
[3,] 33.25741 38.58075 30.56684 31.25698
[4,] 33.08127 35.32197 33.67197 37.46016
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5b96fb2808b0>
> exp(tmp5)
<pointer: 0x5b96fb2808b0>
> log(tmp5,2)
<pointer: 0x5b96fb2808b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.0765
> Min(tmp5)
[1] 52.85481
> mean(tmp5)
[1] 72.85561
> Sum(tmp5)
[1] 14571.12
> Var(tmp5)
[1] 852.9234
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.81207 68.13673 72.48620 68.89819 70.30573 69.86615 70.07555 71.67918
[9] 73.30811 72.98822
> rowSums(tmp5)
[1] 1816.241 1362.735 1449.724 1377.964 1406.115 1397.323 1401.511 1433.584
[9] 1466.162 1459.764
> rowVars(tmp5)
[1] 7933.64459 66.63739 51.86999 36.70508 69.81754 76.56219
[7] 59.81572 68.50684 78.00697 86.13266
> rowSd(tmp5)
[1] 89.071009 8.163173 7.202082 6.058472 8.355689 8.749983 7.734062
[8] 8.276886 8.832155 9.280768
> rowMax(tmp5)
[1] 468.07646 84.56952 84.95164 80.19909 83.30385 86.39625 87.19775
[8] 84.20807 84.00099 88.97678
> rowMin(tmp5)
[1] 59.04846 55.98801 57.47619 52.85481 58.13523 53.56408 57.75234 54.95612
[9] 53.81502 53.88614
>
> colMeans(tmp5)
[1] 112.33895 72.22289 69.77881 70.37123 71.43304 68.28187 67.28555
[8] 69.53934 74.60648 72.09987 70.93312 68.81418 77.39431 68.61867
[15] 70.14186 67.39814 68.26291 72.81735 73.32515 71.44857
> colSums(tmp5)
[1] 1123.3895 722.2289 697.7881 703.7123 714.3304 682.8187 672.8555
[8] 695.3934 746.0648 720.9987 709.3312 688.1418 773.9431 686.1867
[15] 701.4186 673.9814 682.6291 728.1735 733.2515 714.4857
> colVars(tmp5)
[1] 15662.26712 98.58026 27.12928 66.86917 22.14723 124.13338
[7] 38.92332 90.65842 71.73184 44.07149 92.96714 62.22316
[13] 26.94544 106.22053 45.46872 41.29442 27.76156 91.02866
[19] 133.09794 27.12054
> colSd(tmp5)
[1] 125.148980 9.928759 5.208578 8.177357 4.706084 11.141516
[7] 6.238856 9.521472 8.469465 6.638636 9.641947 7.888166
[13] 5.190899 10.306334 6.743050 6.426074 5.268924 9.540894
[19] 11.536808 5.207738
> colMax(tmp5)
[1] 468.07646 84.00099 82.92895 80.62534 81.13764 82.06522 81.81989
[8] 86.39625 84.95164 82.06606 84.97189 82.65430 87.19775 83.94856
[15] 82.18885 74.76817 76.77633 86.40791 88.97678 79.94265
> colMin(tmp5)
[1] 60.73410 57.75234 63.62086 53.81502 65.39475 53.88614 61.49350 54.95612
[9] 55.98801 59.67385 53.56408 58.83743 68.65184 52.85481 59.43299 56.79209
[17] 60.15713 59.99617 58.64282 64.31663
>
>
> ### 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] 90.81207 68.13673 72.48620 68.89819 70.30573 69.86615 70.07555 NA
[9] 73.30811 72.98822
> rowSums(tmp5)
[1] 1816.241 1362.735 1449.724 1377.964 1406.115 1397.323 1401.511 NA
[9] 1466.162 1459.764
> rowVars(tmp5)
[1] 7933.64459 66.63739 51.86999 36.70508 69.81754 76.56219
[7] 59.81572 71.34128 78.00697 86.13266
> rowSd(tmp5)
[1] 89.071009 8.163173 7.202082 6.058472 8.355689 8.749983 7.734062
[8] 8.446377 8.832155 9.280768
> rowMax(tmp5)
[1] 468.07646 84.56952 84.95164 80.19909 83.30385 86.39625 87.19775
[8] NA 84.00099 88.97678
> rowMin(tmp5)
[1] 59.04846 55.98801 57.47619 52.85481 58.13523 53.56408 57.75234 NA
[9] 53.81502 53.88614
>
> colMeans(tmp5)
[1] 112.33895 72.22289 69.77881 70.37123 71.43304 68.28187 67.28555
[8] 69.53934 74.60648 72.09987 70.93312 NA 77.39431 68.61867
[15] 70.14186 67.39814 68.26291 72.81735 73.32515 71.44857
> colSums(tmp5)
[1] 1123.3895 722.2289 697.7881 703.7123 714.3304 682.8187 672.8555
[8] 695.3934 746.0648 720.9987 709.3312 NA 773.9431 686.1867
[15] 701.4186 673.9814 682.6291 728.1735 733.2515 714.4857
> colVars(tmp5)
[1] 15662.26712 98.58026 27.12928 66.86917 22.14723 124.13338
[7] 38.92332 90.65842 71.73184 44.07149 92.96714 NA
[13] 26.94544 106.22053 45.46872 41.29442 27.76156 91.02866
[19] 133.09794 27.12054
> colSd(tmp5)
[1] 125.148980 9.928759 5.208578 8.177357 4.706084 11.141516
[7] 6.238856 9.521472 8.469465 6.638636 9.641947 NA
[13] 5.190899 10.306334 6.743050 6.426074 5.268924 9.540894
[19] 11.536808 5.207738
> colMax(tmp5)
[1] 468.07646 84.00099 82.92895 80.62534 81.13764 82.06522 81.81989
[8] 86.39625 84.95164 82.06606 84.97189 NA 87.19775 83.94856
[15] 82.18885 74.76817 76.77633 86.40791 88.97678 79.94265
> colMin(tmp5)
[1] 60.73410 57.75234 63.62086 53.81502 65.39475 53.88614 61.49350 54.95612
[9] 55.98801 59.67385 53.56408 NA 68.65184 52.85481 59.43299 56.79209
[17] 60.15713 59.99617 58.64282 64.31663
>
> Max(tmp5,na.rm=TRUE)
[1] 468.0765
> Min(tmp5,na.rm=TRUE)
[1] 52.85481
> mean(tmp5,na.rm=TRUE)
[1] 72.84104
> Sum(tmp5,na.rm=TRUE)
[1] 14495.37
> Var(tmp5,na.rm=TRUE)
[1] 857.1884
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.81207 68.13673 72.48620 68.89819 70.30573 69.86615 70.07555 71.46466
[9] 73.30811 72.98822
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.241 1362.735 1449.724 1377.964 1406.115 1397.323 1401.511 1357.829
[9] 1466.162 1459.764
> rowVars(tmp5,na.rm=TRUE)
[1] 7933.64459 66.63739 51.86999 36.70508 69.81754 76.56219
[7] 59.81572 71.34128 78.00697 86.13266
> rowSd(tmp5,na.rm=TRUE)
[1] 89.071009 8.163173 7.202082 6.058472 8.355689 8.749983 7.734062
[8] 8.446377 8.832155 9.280768
> rowMax(tmp5,na.rm=TRUE)
[1] 468.07646 84.56952 84.95164 80.19909 83.30385 86.39625 87.19775
[8] 84.20807 84.00099 88.97678
> rowMin(tmp5,na.rm=TRUE)
[1] 59.04846 55.98801 57.47619 52.85481 58.13523 53.56408 57.75234 54.95612
[9] 53.81502 53.88614
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.33895 72.22289 69.77881 70.37123 71.43304 68.28187 67.28555
[8] 69.53934 74.60648 72.09987 70.93312 68.04297 77.39431 68.61867
[15] 70.14186 67.39814 68.26291 72.81735 73.32515 71.44857
> colSums(tmp5,na.rm=TRUE)
[1] 1123.3895 722.2289 697.7881 703.7123 714.3304 682.8187 672.8555
[8] 695.3934 746.0648 720.9987 709.3312 612.3868 773.9431 686.1867
[15] 701.4186 673.9814 682.6291 728.1735 733.2515 714.4857
> colVars(tmp5,na.rm=TRUE)
[1] 15662.26712 98.58026 27.12928 66.86917 22.14723 124.13338
[7] 38.92332 90.65842 71.73184 44.07149 92.96714 63.31002
[13] 26.94544 106.22053 45.46872 41.29442 27.76156 91.02866
[19] 133.09794 27.12054
> colSd(tmp5,na.rm=TRUE)
[1] 125.148980 9.928759 5.208578 8.177357 4.706084 11.141516
[7] 6.238856 9.521472 8.469465 6.638636 9.641947 7.956759
[13] 5.190899 10.306334 6.743050 6.426074 5.268924 9.540894
[19] 11.536808 5.207738
> colMax(tmp5,na.rm=TRUE)
[1] 468.07646 84.00099 82.92895 80.62534 81.13764 82.06522 81.81989
[8] 86.39625 84.95164 82.06606 84.97189 82.65430 87.19775 83.94856
[15] 82.18885 74.76817 76.77633 86.40791 88.97678 79.94265
> colMin(tmp5,na.rm=TRUE)
[1] 60.73410 57.75234 63.62086 53.81502 65.39475 53.88614 61.49350 54.95612
[9] 55.98801 59.67385 53.56408 58.83743 68.65184 52.85481 59.43299 56.79209
[17] 60.15713 59.99617 58.64282 64.31663
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.81207 68.13673 72.48620 68.89819 70.30573 69.86615 70.07555 NaN
[9] 73.30811 72.98822
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.241 1362.735 1449.724 1377.964 1406.115 1397.323 1401.511 0.000
[9] 1466.162 1459.764
> rowVars(tmp5,na.rm=TRUE)
[1] 7933.64459 66.63739 51.86999 36.70508 69.81754 76.56219
[7] 59.81572 NA 78.00697 86.13266
> rowSd(tmp5,na.rm=TRUE)
[1] 89.071009 8.163173 7.202082 6.058472 8.355689 8.749983 7.734062
[8] NA 8.832155 9.280768
> rowMax(tmp5,na.rm=TRUE)
[1] 468.07646 84.56952 84.95164 80.19909 83.30385 86.39625 87.19775
[8] NA 84.00099 88.97678
> rowMin(tmp5,na.rm=TRUE)
[1] 59.04846 55.98801 57.47619 52.85481 58.13523 53.56408 57.75234 NA
[9] 53.81502 53.88614
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.61789 71.49625 70.18726 70.84996 71.56333 69.51024 67.50196
[8] 71.15969 74.11929 70.99251 70.52324 NaN 77.91626 69.33335
[15] 68.80331 66.64789 68.82541 71.55171 73.17004 70.91401
> colSums(tmp5,na.rm=TRUE)
[1] 1049.5610 643.4662 631.6853 637.6497 644.0700 625.5921 607.5176
[8] 640.4372 667.0736 638.9326 634.7091 0.0000 701.2463 624.0002
[15] 619.2297 599.8311 619.4287 643.9654 658.5303 638.2261
> colVars(tmp5,na.rm=TRUE)
[1] 17414.07055 104.96269 28.64363 72.64947 24.72465 122.67501
[7] 43.26189 72.45320 78.02803 35.78528 102.69803 NA
[13] 27.24883 113.75191 30.99535 40.12404 27.67218 84.38661
[19] 149.46452 27.29590
> colSd(tmp5,na.rm=TRUE)
[1] 131.962383 10.245130 5.351974 8.523466 4.972389 11.075875
[7] 6.577377 8.511945 8.833348 5.982080 10.134004 NA
[13] 5.220041 10.665454 5.567347 6.334354 5.260435 9.186218
[19] 12.225568 5.224548
> colMax(tmp5,na.rm=TRUE)
[1] 468.07646 84.00099 82.92895 80.62534 81.13764 82.06522 81.81989
[8] 86.39625 84.95164 81.64082 84.97189 -Inf 87.19775 83.94856
[15] 73.31805 74.76817 76.77633 86.40791 88.97678 79.94265
> colMin(tmp5,na.rm=TRUE)
[1] 60.73410 57.75234 63.62086 53.81502 65.39475 53.88614 61.49350 59.21255
[9] 55.98801 59.67385 53.56408 Inf 68.65184 52.85481 59.43299 56.79209
[17] 60.15713 59.99617 58.64282 64.31663
>
>
>
>
> 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] 235.76764 219.02663 385.73181 87.69418 359.05484 214.88748 147.67194
[8] 240.80325 351.94936 313.47682
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 235.76764 219.02663 385.73181 87.69418 359.05484 214.88748 147.67194
[8] 240.80325 351.94936 313.47682
>
>
>
> 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] 1.421085e-13 -1.136868e-13 -2.842171e-13 -5.684342e-14 -2.842171e-14
[6] 5.684342e-14 1.705303e-13 -1.421085e-13 0.000000e+00 -2.842171e-14
[11] 5.684342e-14 -6.394885e-14 -1.136868e-13 -2.842171e-14 -1.421085e-13
[16] -2.842171e-14 -1.421085e-13 2.842171e-14 -5.684342e-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)
+ }
4 19
10 20
2 9
2 3
2 8
5 20
2 13
4 9
2 3
4 5
10 1
4 7
2 1
7 14
2 5
2 13
3 4
8 4
10 4
5 1
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] 1.996647
> Min(tmp)
[1] -2.448433
> mean(tmp)
[1] -0.0312911
> Sum(tmp)
[1] -3.12911
> Var(tmp)
[1] 0.994264
>
> rowMeans(tmp)
[1] -0.0312911
> rowSums(tmp)
[1] -3.12911
> rowVars(tmp)
[1] 0.994264
> rowSd(tmp)
[1] 0.9971279
> rowMax(tmp)
[1] 1.996647
> rowMin(tmp)
[1] -2.448433
>
> colMeans(tmp)
[1] -0.550907192 -1.619054213 -0.019224435 0.045237736 0.340400733
[6] -0.361239968 -0.994122012 1.035560785 0.806726854 -0.891873815
[11] 0.925867775 0.641752126 -0.816091801 -0.293813470 -1.669409430
[16] 1.661747586 -0.153886866 1.225066493 -0.512707146 -0.754056844
[21] -0.234496988 1.017201291 0.907118940 -2.448432641 -0.402726811
[26] 0.524314663 0.075299855 -2.184062757 -1.072036709 0.640031426
[31] -0.581110266 1.847208307 1.307400422 0.391438420 1.243815083
[36] -0.380463691 0.224782080 0.880512860 0.817569134 1.271660069
[41] -2.133755992 -0.766600363 0.185641786 -1.493734481 -1.141858783
[46] 0.452491653 0.754224994 1.456677705 -0.262754075 -0.467602752
[51] -1.691810619 -1.152657695 -0.036750188 -0.750646687 0.008238349
[56] 0.595108431 -1.200133709 0.163927754 0.568268868 -0.347036837
[61] -1.067545586 0.100795488 1.065583491 -0.288286442 1.854175144
[66] 0.256019684 -1.184765329 0.228656429 -0.354616571 -1.044005242
[71] 1.996646874 -0.863141632 1.655639200 0.984944040 -1.093021366
[76] -0.248466594 -0.272669886 -0.508394253 0.236054134 0.074693861
[81] 1.807213516 0.047351688 1.239542811 -0.530228315 1.067855020
[86] -1.909471539 -0.125268042 -0.553767195 1.862364663 -0.398502655
[91] 0.379522020 -0.159264498 0.420055510 -0.865591342 -1.910190318
[96] -0.274110063 0.674157110 -0.230885871 -0.153919191 0.325498054
> colSums(tmp)
[1] -0.550907192 -1.619054213 -0.019224435 0.045237736 0.340400733
[6] -0.361239968 -0.994122012 1.035560785 0.806726854 -0.891873815
[11] 0.925867775 0.641752126 -0.816091801 -0.293813470 -1.669409430
[16] 1.661747586 -0.153886866 1.225066493 -0.512707146 -0.754056844
[21] -0.234496988 1.017201291 0.907118940 -2.448432641 -0.402726811
[26] 0.524314663 0.075299855 -2.184062757 -1.072036709 0.640031426
[31] -0.581110266 1.847208307 1.307400422 0.391438420 1.243815083
[36] -0.380463691 0.224782080 0.880512860 0.817569134 1.271660069
[41] -2.133755992 -0.766600363 0.185641786 -1.493734481 -1.141858783
[46] 0.452491653 0.754224994 1.456677705 -0.262754075 -0.467602752
[51] -1.691810619 -1.152657695 -0.036750188 -0.750646687 0.008238349
[56] 0.595108431 -1.200133709 0.163927754 0.568268868 -0.347036837
[61] -1.067545586 0.100795488 1.065583491 -0.288286442 1.854175144
[66] 0.256019684 -1.184765329 0.228656429 -0.354616571 -1.044005242
[71] 1.996646874 -0.863141632 1.655639200 0.984944040 -1.093021366
[76] -0.248466594 -0.272669886 -0.508394253 0.236054134 0.074693861
[81] 1.807213516 0.047351688 1.239542811 -0.530228315 1.067855020
[86] -1.909471539 -0.125268042 -0.553767195 1.862364663 -0.398502655
[91] 0.379522020 -0.159264498 0.420055510 -0.865591342 -1.910190318
[96] -0.274110063 0.674157110 -0.230885871 -0.153919191 0.325498054
> 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] -0.550907192 -1.619054213 -0.019224435 0.045237736 0.340400733
[6] -0.361239968 -0.994122012 1.035560785 0.806726854 -0.891873815
[11] 0.925867775 0.641752126 -0.816091801 -0.293813470 -1.669409430
[16] 1.661747586 -0.153886866 1.225066493 -0.512707146 -0.754056844
[21] -0.234496988 1.017201291 0.907118940 -2.448432641 -0.402726811
[26] 0.524314663 0.075299855 -2.184062757 -1.072036709 0.640031426
[31] -0.581110266 1.847208307 1.307400422 0.391438420 1.243815083
[36] -0.380463691 0.224782080 0.880512860 0.817569134 1.271660069
[41] -2.133755992 -0.766600363 0.185641786 -1.493734481 -1.141858783
[46] 0.452491653 0.754224994 1.456677705 -0.262754075 -0.467602752
[51] -1.691810619 -1.152657695 -0.036750188 -0.750646687 0.008238349
[56] 0.595108431 -1.200133709 0.163927754 0.568268868 -0.347036837
[61] -1.067545586 0.100795488 1.065583491 -0.288286442 1.854175144
[66] 0.256019684 -1.184765329 0.228656429 -0.354616571 -1.044005242
[71] 1.996646874 -0.863141632 1.655639200 0.984944040 -1.093021366
[76] -0.248466594 -0.272669886 -0.508394253 0.236054134 0.074693861
[81] 1.807213516 0.047351688 1.239542811 -0.530228315 1.067855020
[86] -1.909471539 -0.125268042 -0.553767195 1.862364663 -0.398502655
[91] 0.379522020 -0.159264498 0.420055510 -0.865591342 -1.910190318
[96] -0.274110063 0.674157110 -0.230885871 -0.153919191 0.325498054
> colMin(tmp)
[1] -0.550907192 -1.619054213 -0.019224435 0.045237736 0.340400733
[6] -0.361239968 -0.994122012 1.035560785 0.806726854 -0.891873815
[11] 0.925867775 0.641752126 -0.816091801 -0.293813470 -1.669409430
[16] 1.661747586 -0.153886866 1.225066493 -0.512707146 -0.754056844
[21] -0.234496988 1.017201291 0.907118940 -2.448432641 -0.402726811
[26] 0.524314663 0.075299855 -2.184062757 -1.072036709 0.640031426
[31] -0.581110266 1.847208307 1.307400422 0.391438420 1.243815083
[36] -0.380463691 0.224782080 0.880512860 0.817569134 1.271660069
[41] -2.133755992 -0.766600363 0.185641786 -1.493734481 -1.141858783
[46] 0.452491653 0.754224994 1.456677705 -0.262754075 -0.467602752
[51] -1.691810619 -1.152657695 -0.036750188 -0.750646687 0.008238349
[56] 0.595108431 -1.200133709 0.163927754 0.568268868 -0.347036837
[61] -1.067545586 0.100795488 1.065583491 -0.288286442 1.854175144
[66] 0.256019684 -1.184765329 0.228656429 -0.354616571 -1.044005242
[71] 1.996646874 -0.863141632 1.655639200 0.984944040 -1.093021366
[76] -0.248466594 -0.272669886 -0.508394253 0.236054134 0.074693861
[81] 1.807213516 0.047351688 1.239542811 -0.530228315 1.067855020
[86] -1.909471539 -0.125268042 -0.553767195 1.862364663 -0.398502655
[91] 0.379522020 -0.159264498 0.420055510 -0.865591342 -1.910190318
[96] -0.274110063 0.674157110 -0.230885871 -0.153919191 0.325498054
> colMedians(tmp)
[1] -0.550907192 -1.619054213 -0.019224435 0.045237736 0.340400733
[6] -0.361239968 -0.994122012 1.035560785 0.806726854 -0.891873815
[11] 0.925867775 0.641752126 -0.816091801 -0.293813470 -1.669409430
[16] 1.661747586 -0.153886866 1.225066493 -0.512707146 -0.754056844
[21] -0.234496988 1.017201291 0.907118940 -2.448432641 -0.402726811
[26] 0.524314663 0.075299855 -2.184062757 -1.072036709 0.640031426
[31] -0.581110266 1.847208307 1.307400422 0.391438420 1.243815083
[36] -0.380463691 0.224782080 0.880512860 0.817569134 1.271660069
[41] -2.133755992 -0.766600363 0.185641786 -1.493734481 -1.141858783
[46] 0.452491653 0.754224994 1.456677705 -0.262754075 -0.467602752
[51] -1.691810619 -1.152657695 -0.036750188 -0.750646687 0.008238349
[56] 0.595108431 -1.200133709 0.163927754 0.568268868 -0.347036837
[61] -1.067545586 0.100795488 1.065583491 -0.288286442 1.854175144
[66] 0.256019684 -1.184765329 0.228656429 -0.354616571 -1.044005242
[71] 1.996646874 -0.863141632 1.655639200 0.984944040 -1.093021366
[76] -0.248466594 -0.272669886 -0.508394253 0.236054134 0.074693861
[81] 1.807213516 0.047351688 1.239542811 -0.530228315 1.067855020
[86] -1.909471539 -0.125268042 -0.553767195 1.862364663 -0.398502655
[91] 0.379522020 -0.159264498 0.420055510 -0.865591342 -1.910190318
[96] -0.274110063 0.674157110 -0.230885871 -0.153919191 0.325498054
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5509072 -1.619054 -0.01922444 0.04523774 0.3404007 -0.36124 -0.994122
[2,] -0.5509072 -1.619054 -0.01922444 0.04523774 0.3404007 -0.36124 -0.994122
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.035561 0.8067269 -0.8918738 0.9258678 0.6417521 -0.8160918 -0.2938135
[2,] 1.035561 0.8067269 -0.8918738 0.9258678 0.6417521 -0.8160918 -0.2938135
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.669409 1.661748 -0.1538869 1.225066 -0.5127071 -0.7540568 -0.234497
[2,] -1.669409 1.661748 -0.1538869 1.225066 -0.5127071 -0.7540568 -0.234497
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.017201 0.9071189 -2.448433 -0.4027268 0.5243147 0.07529986 -2.184063
[2,] 1.017201 0.9071189 -2.448433 -0.4027268 0.5243147 0.07529986 -2.184063
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.072037 0.6400314 -0.5811103 1.847208 1.3074 0.3914384 1.243815
[2,] -1.072037 0.6400314 -0.5811103 1.847208 1.3074 0.3914384 1.243815
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.3804637 0.2247821 0.8805129 0.8175691 1.27166 -2.133756 -0.7666004
[2,] -0.3804637 0.2247821 0.8805129 0.8175691 1.27166 -2.133756 -0.7666004
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.1856418 -1.493734 -1.141859 0.4524917 0.754225 1.456678 -0.2627541
[2,] 0.1856418 -1.493734 -1.141859 0.4524917 0.754225 1.456678 -0.2627541
[,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.4676028 -1.691811 -1.152658 -0.03675019 -0.7506467 0.008238349
[2,] -0.4676028 -1.691811 -1.152658 -0.03675019 -0.7506467 0.008238349
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.5951084 -1.200134 0.1639278 0.5682689 -0.3470368 -1.067546 0.1007955
[2,] 0.5951084 -1.200134 0.1639278 0.5682689 -0.3470368 -1.067546 0.1007955
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 1.065583 -0.2882864 1.854175 0.2560197 -1.184765 0.2286564 -0.3546166
[2,] 1.065583 -0.2882864 1.854175 0.2560197 -1.184765 0.2286564 -0.3546166
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -1.044005 1.996647 -0.8631416 1.655639 0.984944 -1.093021 -0.2484666
[2,] -1.044005 1.996647 -0.8631416 1.655639 0.984944 -1.093021 -0.2484666
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.2726699 -0.5083943 0.2360541 0.07469386 1.807214 0.04735169 1.239543
[2,] -0.2726699 -0.5083943 0.2360541 0.07469386 1.807214 0.04735169 1.239543
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.5302283 1.067855 -1.909472 -0.125268 -0.5537672 1.862365 -0.3985027
[2,] -0.5302283 1.067855 -1.909472 -0.125268 -0.5537672 1.862365 -0.3985027
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.379522 -0.1592645 0.4200555 -0.8655913 -1.91019 -0.2741101 0.6741571
[2,] 0.379522 -0.1592645 0.4200555 -0.8655913 -1.91019 -0.2741101 0.6741571
[,98] [,99] [,100]
[1,] -0.2308859 -0.1539192 0.3254981
[2,] -0.2308859 -0.1539192 0.3254981
>
>
> Max(tmp2)
[1] 2.231763
> Min(tmp2)
[1] -3.243668
> mean(tmp2)
[1] -0.03497705
> Sum(tmp2)
[1] -3.497705
> Var(tmp2)
[1] 1.099689
>
> rowMeans(tmp2)
[1] 2.231762827 1.003133767 1.201693690 -0.320098505 -0.574813382
[6] 1.281230523 -0.952413794 0.145689237 -0.547617342 0.883522870
[11] 0.984776837 -0.235196696 -0.572804049 -0.569007542 0.464181059
[16] -0.247197155 -0.082026208 1.208774113 0.497599146 -0.807138978
[21] -0.416237324 -1.773789356 -1.064996363 -0.071278149 -1.702551222
[26] 0.738882233 0.243144898 -0.671272294 1.253813343 1.025695003
[31] -0.795712912 1.174299232 -0.445256795 0.291700607 1.779530708
[36] -0.875045967 -1.793340355 0.964511108 -0.391779399 -0.075013595
[41] 0.265503846 -0.225179117 0.038907191 0.367171591 -0.699282743
[46] -1.360577922 0.166318520 -1.120297452 1.923444031 0.179652509
[51] -0.893794323 2.082333724 -1.644599959 -2.380249692 -0.476250717
[56] 1.045173733 -0.442291519 -0.659467442 -0.954996358 -0.126064901
[61] 0.172779076 0.846350787 -0.004803824 -0.202983040 -1.848068142
[66] 0.577070435 0.456767648 -0.389377460 0.052034398 -1.079438205
[71] 1.682165787 -0.411785658 1.522964981 -0.643101624 -1.332435159
[76] 0.021040019 1.101788580 -0.716743877 0.561056059 0.080545010
[81] 2.147120792 0.457421419 -1.126991060 0.672429382 -1.932324012
[86] -0.643900941 -0.233719744 1.357128519 -1.156881205 -0.254293133
[91] -1.659311535 -0.184738971 1.094010475 -0.186732679 0.257363150
[96] 1.131239845 0.242860355 -3.243667734 0.514016926 1.330632862
> rowSums(tmp2)
[1] 2.231762827 1.003133767 1.201693690 -0.320098505 -0.574813382
[6] 1.281230523 -0.952413794 0.145689237 -0.547617342 0.883522870
[11] 0.984776837 -0.235196696 -0.572804049 -0.569007542 0.464181059
[16] -0.247197155 -0.082026208 1.208774113 0.497599146 -0.807138978
[21] -0.416237324 -1.773789356 -1.064996363 -0.071278149 -1.702551222
[26] 0.738882233 0.243144898 -0.671272294 1.253813343 1.025695003
[31] -0.795712912 1.174299232 -0.445256795 0.291700607 1.779530708
[36] -0.875045967 -1.793340355 0.964511108 -0.391779399 -0.075013595
[41] 0.265503846 -0.225179117 0.038907191 0.367171591 -0.699282743
[46] -1.360577922 0.166318520 -1.120297452 1.923444031 0.179652509
[51] -0.893794323 2.082333724 -1.644599959 -2.380249692 -0.476250717
[56] 1.045173733 -0.442291519 -0.659467442 -0.954996358 -0.126064901
[61] 0.172779076 0.846350787 -0.004803824 -0.202983040 -1.848068142
[66] 0.577070435 0.456767648 -0.389377460 0.052034398 -1.079438205
[71] 1.682165787 -0.411785658 1.522964981 -0.643101624 -1.332435159
[76] 0.021040019 1.101788580 -0.716743877 0.561056059 0.080545010
[81] 2.147120792 0.457421419 -1.126991060 0.672429382 -1.932324012
[86] -0.643900941 -0.233719744 1.357128519 -1.156881205 -0.254293133
[91] -1.659311535 -0.184738971 1.094010475 -0.186732679 0.257363150
[96] 1.131239845 0.242860355 -3.243667734 0.514016926 1.330632862
> 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] 2.231762827 1.003133767 1.201693690 -0.320098505 -0.574813382
[6] 1.281230523 -0.952413794 0.145689237 -0.547617342 0.883522870
[11] 0.984776837 -0.235196696 -0.572804049 -0.569007542 0.464181059
[16] -0.247197155 -0.082026208 1.208774113 0.497599146 -0.807138978
[21] -0.416237324 -1.773789356 -1.064996363 -0.071278149 -1.702551222
[26] 0.738882233 0.243144898 -0.671272294 1.253813343 1.025695003
[31] -0.795712912 1.174299232 -0.445256795 0.291700607 1.779530708
[36] -0.875045967 -1.793340355 0.964511108 -0.391779399 -0.075013595
[41] 0.265503846 -0.225179117 0.038907191 0.367171591 -0.699282743
[46] -1.360577922 0.166318520 -1.120297452 1.923444031 0.179652509
[51] -0.893794323 2.082333724 -1.644599959 -2.380249692 -0.476250717
[56] 1.045173733 -0.442291519 -0.659467442 -0.954996358 -0.126064901
[61] 0.172779076 0.846350787 -0.004803824 -0.202983040 -1.848068142
[66] 0.577070435 0.456767648 -0.389377460 0.052034398 -1.079438205
[71] 1.682165787 -0.411785658 1.522964981 -0.643101624 -1.332435159
[76] 0.021040019 1.101788580 -0.716743877 0.561056059 0.080545010
[81] 2.147120792 0.457421419 -1.126991060 0.672429382 -1.932324012
[86] -0.643900941 -0.233719744 1.357128519 -1.156881205 -0.254293133
[91] -1.659311535 -0.184738971 1.094010475 -0.186732679 0.257363150
[96] 1.131239845 0.242860355 -3.243667734 0.514016926 1.330632862
> rowMin(tmp2)
[1] 2.231762827 1.003133767 1.201693690 -0.320098505 -0.574813382
[6] 1.281230523 -0.952413794 0.145689237 -0.547617342 0.883522870
[11] 0.984776837 -0.235196696 -0.572804049 -0.569007542 0.464181059
[16] -0.247197155 -0.082026208 1.208774113 0.497599146 -0.807138978
[21] -0.416237324 -1.773789356 -1.064996363 -0.071278149 -1.702551222
[26] 0.738882233 0.243144898 -0.671272294 1.253813343 1.025695003
[31] -0.795712912 1.174299232 -0.445256795 0.291700607 1.779530708
[36] -0.875045967 -1.793340355 0.964511108 -0.391779399 -0.075013595
[41] 0.265503846 -0.225179117 0.038907191 0.367171591 -0.699282743
[46] -1.360577922 0.166318520 -1.120297452 1.923444031 0.179652509
[51] -0.893794323 2.082333724 -1.644599959 -2.380249692 -0.476250717
[56] 1.045173733 -0.442291519 -0.659467442 -0.954996358 -0.126064901
[61] 0.172779076 0.846350787 -0.004803824 -0.202983040 -1.848068142
[66] 0.577070435 0.456767648 -0.389377460 0.052034398 -1.079438205
[71] 1.682165787 -0.411785658 1.522964981 -0.643101624 -1.332435159
[76] 0.021040019 1.101788580 -0.716743877 0.561056059 0.080545010
[81] 2.147120792 0.457421419 -1.126991060 0.672429382 -1.932324012
[86] -0.643900941 -0.233719744 1.357128519 -1.156881205 -0.254293133
[91] -1.659311535 -0.184738971 1.094010475 -0.186732679 0.257363150
[96] 1.131239845 0.242860355 -3.243667734 0.514016926 1.330632862
>
> colMeans(tmp2)
[1] -0.03497705
> colSums(tmp2)
[1] -3.497705
> colVars(tmp2)
[1] 1.099689
> colSd(tmp2)
[1] 1.048661
> colMax(tmp2)
[1] 2.231763
> colMin(tmp2)
[1] -3.243668
> colMedians(tmp2)
[1] -0.0785199
> colRanges(tmp2)
[,1]
[1,] -3.243668
[2,] 2.231763
>
> 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] 4.9356248 2.9892137 -1.7202174 -5.2189863 -0.2293346 -3.6045395
[7] 0.8399207 -8.6465667 -0.8478802 3.5558893
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1954162
[2,] -0.1208623
[3,] 0.2893185
[4,] 1.3620812
[5,] 2.2120805
>
> rowApply(tmp,sum)
[1] -0.78318431 4.28258040 -2.71849471 1.92207574 0.57968392 0.04788399
[7] -3.69469959 -5.08209238 -0.19360874 -2.30702039
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 5 7 4 10 10 2 3 10 7
[2,] 5 7 9 3 9 2 9 9 8 5
[3,] 1 2 4 8 1 5 7 8 9 8
[4,] 6 1 5 2 4 6 5 6 3 2
[5,] 2 10 1 5 3 9 8 5 5 10
[6,] 3 8 6 7 5 1 3 2 4 6
[7,] 9 4 10 6 8 7 1 10 2 3
[8,] 7 3 3 1 2 4 4 1 1 9
[9,] 4 9 2 9 6 3 10 4 6 4
[10,] 8 6 8 10 7 8 6 7 7 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.92897400 1.06221119 -2.16935736 2.39205599 1.58536719 -6.88346601
[7] 3.40759847 3.46237124 2.69240744 -1.62790416 -4.56277884 1.00235551
[13] -2.66037255 1.18782271 0.83879929 -0.61323152 -0.01888312 -0.20618595
[19] 4.31426008 -1.76257094
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4232648
[2,] -1.1265185
[3,] -0.5572550
[4,] -0.2893481
[5,] 0.4674124
>
> rowApply(tmp,sum)
[1] -6.6307727 0.4016551 0.1517491 -2.0741794 6.6630725
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 1 8 6 1
[2,] 11 13 5 8 19
[3,] 3 8 12 5 10
[4,] 9 19 17 12 16
[5,] 20 17 10 3 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.4674124 -0.2831187 -1.36205690 -0.5546073 1.3225573 -2.7843308
[2,] -1.4232648 0.2749276 -0.39307352 1.2384522 1.1973486 -0.1848819
[3,] -0.2893481 -0.7204954 -0.02122193 0.9675679 -0.1821143 -0.9358781
[4,] -0.5572550 -0.5396354 -0.61516106 0.1292050 -1.1464759 -2.5840069
[5,] -1.1265185 2.3305330 0.22215604 0.6114381 0.3940515 -0.3943684
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.7414516 1.1850293 1.05824117 -1.43113846 -1.2862185 -0.68249045
[2,] 1.2021863 -0.8628002 -0.88642040 -0.38630248 -0.9044430 1.06388414
[3,] 0.7794906 1.5878137 -0.07126088 0.53267005 -0.9294718 -0.01338129
[4,] 0.3376974 1.8065726 0.26070022 -0.27665545 -1.2390363 0.83628843
[5,] 0.3467726 -0.2542441 2.33114734 -0.06647781 -0.2036092 -0.20194532
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.7487659 -0.91201428 -1.1568306 -0.1520731 0.1365337 -0.02595421
[2,] -1.0649575 0.70385787 0.5028930 -0.7455655 -0.1923846 -0.09533280
[3,] -1.9492833 -0.21628374 -0.3592034 1.2609284 0.5287977 -0.36135985
[4,] 0.2630763 1.56370080 0.8175067 -0.5410768 -0.6863470 0.05317300
[5,] 0.8395577 0.04856206 1.0344335 -0.4354445 0.1945171 0.22328792
[,19] [,20]
[1,] 0.2885022 -0.4509011
[2,] 1.9177368 -0.5602048
[3,] 1.7091596 -1.1653768
[4,] 0.1690981 -0.1255481
[5,] 0.2297634 0.5394599
>
>
> 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 : 647 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 : 562 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 -0.1034337 1.5748 0.2186775 -1.004112 1.780369 -2.470913 0.5632072
col8 col9 col10 col11 col12 col13 col14
row1 0.7137374 -0.715711 -0.6410398 -0.2008271 -0.7906039 -0.8638455 -2.406804
col15 col16 col17 col18 col19 col20
row1 1.043447 -0.5517647 1.622024 1.696658 -0.4325849 -2.333719
> tmp[,"col10"]
col10
row1 -0.6410398
row2 0.1285636
row3 0.3526391
row4 -0.7155450
row5 0.6572399
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.1034337 1.5748000 0.2186775 -1.0041115 1.7803695 -2.47091271
row5 -0.7709844 -0.1950049 -0.3306283 0.1261547 -0.2505559 -0.02153105
col7 col8 col9 col10 col11 col12
row1 0.5632072 0.7137374 -0.71571100 -0.6410398 -0.2008271 -0.7906039
row5 -0.1091649 -0.6008770 0.09097675 0.6572399 -0.2580842 -1.1397614
col13 col14 col15 col16 col17 col18
row1 -0.86384549 -2.4068037 1.043447 -0.5517647 1.6220241 1.6966576
row5 0.06661835 0.8940329 -1.546707 -0.1551988 -0.4472066 0.1567804
col19 col20
row1 -0.4325849 -2.3337192
row5 0.8895482 -0.4474479
> tmp[,c("col6","col20")]
col6 col20
row1 -2.47091271 -2.3337192
row2 -0.55810418 0.6908446
row3 0.11388382 -0.7108528
row4 1.78582008 0.9586271
row5 -0.02153105 -0.4474479
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -2.47091271 -2.3337192
row5 -0.02153105 -0.4474479
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.47781 49.88018 49.91734 50.85087 49.49359 104.6281 50.07275 49.9773
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.38062 48.63648 48.21442 49.05268 47.58992 52.26273 49.96156 49.63158
col17 col18 col19 col20
row1 50.27467 48.91076 49.18372 105.8848
> tmp[,"col10"]
col10
row1 48.63648
row2 31.95061
row3 29.03921
row4 30.48597
row5 49.99632
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.47781 49.88018 49.91734 50.85087 49.49359 104.6281 50.07275 49.97730
row5 48.75976 49.26965 49.79221 50.91040 50.10793 103.1674 50.00434 49.78856
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.38062 48.63648 48.21442 49.05268 47.58992 52.26273 49.96156 49.63158
row5 49.40797 49.99632 50.22004 49.72577 48.77699 50.04783 48.80495 50.45143
col17 col18 col19 col20
row1 50.27467 48.91076 49.18372 105.8848
row5 50.69805 49.05189 49.13095 105.3173
> tmp[,c("col6","col20")]
col6 col20
row1 104.62808 105.88476
row2 73.04182 75.61299
row3 73.82371 74.01798
row4 74.28004 72.33460
row5 103.16740 105.31730
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.6281 105.8848
row5 103.1674 105.3173
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.6281 105.8848
row5 103.1674 105.3173
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.6901933
[2,] 0.9585465
[3,] -1.0552979
[4,] -1.1228336
[5,] 0.6406290
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7212221 -0.9328980
[2,] 1.5747618 -0.3754084
[3,] -0.1455079 0.5019342
[4,] 0.1584275 -0.8599506
[5,] -1.5823947 -0.2131413
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.07511095 0.9494981
[2,] -0.48111532 0.6700799
[3,] 0.35134583 -0.2280433
[4,] -0.43310084 0.5583861
[5,] 0.02239791 -0.9165896
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.075111
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.0751110
[2,] -0.4811153
>
>
>
> 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 -1.0606294 -0.8785593 -1.3049267 -0.9333454 -0.2189006 -0.4927543
row1 0.8009794 -0.3754097 -0.2126314 -0.3888705 0.4508147 -0.3029448
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.5260705 1.596326 -0.6938442 -0.5934525 0.2405986 -0.1398073 -0.905329
row1 -1.1326597 -0.332074 1.2208142 1.4441799 -1.2666579 0.2205071 1.313309
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.2375136 0.9849863 -1.5865167 0.6383316 -2.465689 -0.5187972 -0.9552051
row1 -1.4499322 1.2601535 -0.7320609 -0.9065362 -1.493650 -1.1829367 -0.3727786
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.9743698 -0.5299217 -2.32844 0.1013885 0.6787801 -1.089066 1.034988
[,8] [,9] [,10]
row2 0.219983 -0.2075124 1.848751
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2277747 1.212155 -0.4706006 1.31031 -1.488426 1.010246 0.2071529
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.08225703 0.4916089 0.08131047 0.4498576 0.8475532 0.02391908 0.7910807
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4475641 0.1466148 -0.2984925 -1.079899 1.148556 0.03723481
>
>
> 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: 0x5b96fa0a4ac0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe252776a29296"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe25271b17f99b"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe252756f6861b"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe25273dfed733"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe252769427470"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe2527492b95c7"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe25271f21070d"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe25272cb93cf9"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe2527829da9c"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe25273d52aca3"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe252727748a2a"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe252751931b83"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe25275b89da2b"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe252747e954f6"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMe25275bf47729"
>
>
> ### 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: 0x5b96fb0ec3e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5b96fb0ec3e0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5b96fb0ec3e0>
> rowMedians(tmp)
[1] 0.314488408 0.329886968 0.216268915 0.031086630 0.286284051
[6] -0.349403732 0.104660601 0.425882073 0.191211454 0.143294847
[11] -0.092585749 -0.080867905 -0.106269439 -0.092845979 -0.143885643
[16] 0.248415898 -0.129588871 0.057010594 0.078205599 0.326227624
[21] 0.533305086 0.506430810 -0.013873677 -0.531765409 0.316567234
[26] 0.172074631 -0.199454853 -0.218445787 -0.112390576 -0.120123701
[31] 0.281826612 0.418258727 0.226401029 -0.687774429 0.244984148
[36] -0.323588494 -0.409382697 -0.137051468 -0.109293971 1.012808070
[41] 0.339401056 -0.040707419 0.212354412 -0.184718245 0.199671149
[46] 0.405782178 -0.267820527 -0.180138711 0.056925553 -0.131829975
[51] 0.042934051 0.126676762 -0.096893946 -0.878266559 0.355317461
[56] 0.252264898 0.366794142 -0.225356492 -0.203920743 -0.174458367
[61] -0.013478086 -0.580154517 -0.127516284 0.027041091 -0.455774687
[66] 0.389331664 0.150512549 -0.357331363 0.369127443 -0.498166590
[71] -0.040881875 0.275877250 -0.153059990 -0.084552718 -0.417377088
[76] 0.331539909 0.262529184 -0.369847546 0.274493354 -0.263406509
[81] 0.046808649 -0.112791552 -0.445199490 -0.166511386 -0.335317579
[86] 0.215517933 -0.213996930 -0.324492893 -0.279174397 0.177188725
[91] 0.648225624 0.019781499 -0.014968993 -0.632554921 0.608648481
[96] 0.613705765 0.013781470 0.313687295 -0.538650109 0.462121763
[101] 0.171005979 0.159476873 0.001954091 0.202359119 -0.508541839
[106] 0.088923937 0.031465721 -0.315573604 -0.449455396 -0.794009603
[111] 0.344669244 -0.435322415 0.407087483 -0.132955571 0.316762732
[116] 0.008966305 0.116657662 0.504711612 -0.431716994 0.280235178
[121] 0.234781252 -0.317217673 0.359324814 0.167206489 -0.015919340
[126] -0.426912832 -0.207912148 0.158217042 0.210377440 0.038595261
[131] -0.189881949 -0.330436064 -0.062451469 0.037924854 0.039923515
[136] -0.001726610 -0.058769029 -0.189747756 -0.595003672 0.056235896
[141] -0.511145441 0.067662003 0.756280547 -0.118394199 0.714905833
[146] -0.211183005 -0.370576122 -0.205228239 -0.160254917 0.116425038
[151] 0.123804100 -0.197890646 -0.163601369 0.247371669 0.396331888
[156] 0.254967458 -0.306283760 -0.056523918 -0.706801513 0.422492358
[161] -0.364807583 1.045316355 -0.311890477 -0.079148443 0.536625662
[166] -0.392455179 -0.598380882 -0.174091139 -0.007041367 0.023348656
[171] 0.119316319 -0.296494494 0.417056012 -0.145534823 0.356963360
[176] -0.499698672 -0.081616056 0.590585766 0.593082365 0.241571274
[181] 0.371070129 0.003851465 0.223510732 0.163803413 0.190298557
[186] 0.111200886 -0.077220176 0.163857730 0.189971347 -0.113118964
[191] 0.949365737 -0.350248232 -0.027600138 -0.763175853 0.288900900
[196] -0.252988802 0.247330104 0.093753415 0.335493226 0.162814313
[201] 0.140006574 0.570767916 0.268850106 -0.302891588 0.352922172
[206] 0.092965625 0.079482307 0.495626872 -0.125987466 0.085870513
[211] -0.266425580 0.150514279 0.024550349 -0.279417543 -0.707723770
[216] 0.013746968 -0.488175778 -0.377447412 -0.226209880 -0.049636510
[221] 0.045963269 -0.183720976 -0.026558975 0.069910494 0.269172995
[226] 0.020990280 0.210785523 -0.272695342 -0.287197456 0.370213886
>
> proc.time()
user system elapsed
1.207 0.695 1.891
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: 0x5b94809e01c0>
> .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: 0x5b94809e01c0>
> .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: 0x5b94809e01c0>
> .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: 0x5b94809e01c0>
> 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: 0x5b9480cc3120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b9480cc3120>
> .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: 0x5b9480cc3120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b9480cc3120>
> .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: 0x5b9480cc3120>
> 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: 0x5b947f9774a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b947f9774a0>
> .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: 0x5b947f9774a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5b947f9774a0>
> .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: 0x5b947f9774a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5b947f9774a0>
> .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: 0x5b947f9774a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5b947f9774a0>
> .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: 0x5b947f9774a0>
> 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: 0x5b947fa13390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5b947fa13390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b947fa13390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b947fa13390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee26e420b19cb1" "BufferedMatrixFilee26e42d7cde11"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee26e420b19cb1" "BufferedMatrixFilee26e42d7cde11"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b9480292650>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b9480292650>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5b9480292650>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5b9480292650>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5b9480292650>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5b9480292650>
> .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: 0x5b9481419430>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b9481419430>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5b9481419430>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5b9481419430>
> 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: 0x5b948170e250>
> .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: 0x5b948170e250>
> rm(P)
>
> proc.time()
user system elapsed
0.237 0.055 0.281
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.241 0.047 0.278