Ben Bolstad
| Snapshot Date: 2025-11-14 13:45 -0500 (Fri, 14 Nov 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-11-15 11:58 -0500 (Sat, 15 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4903 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4668 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 257/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.74.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.74.0 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2025-11-14 21:48:59 -0500 (Fri, 14 Nov 2025) |
| EndedAt: 2025-11-14 21:49:24 -0500 (Fri, 14 Nov 2025) |
| EllapsedTime: 25.2 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 4.5.1 Patched (2025-08-23 r88802)
* 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 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
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
0.242 0.048 0.277
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
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 478419 25.6 1047111 56 639600 34.2
Vcells 885237 6.8 8388608 64 2081604 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] "Fri Nov 14 21:49:15 2025"
> 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] "Fri Nov 14 21:49:15 2025"
>
>
> 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: 0x557b9e3bfb10>
>
>
>
> 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] "Fri Nov 14 21:49:15 2025"
> 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] "Fri Nov 14 21:49:15 2025"
>
> ColMode(tmp2)
<pointer: 0x557b9e3bfb10>
>
>
>
> ### 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,] 100.3472256 -0.5570025 0.02617937 -1.58561621
[2,] 1.4826985 -0.5965289 -0.33455834 -1.07109181
[3,] 1.8383962 0.8671411 1.24523859 0.07097501
[4,] 0.3263431 -1.0672656 -0.59882374 2.17553706
> 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,] 100.3472256 0.5570025 0.02617937 1.58561621
[2,] 1.4826985 0.5965289 0.33455834 1.07109181
[3,] 1.8383962 0.8671411 1.24523859 0.07097501
[4,] 0.3263431 1.0672656 0.59882374 2.17553706
> 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,] 10.0173462 0.7463260 0.1618004 1.2592125
[2,] 1.2176611 0.7723528 0.5784102 1.0349357
[3,] 1.3558747 0.9312041 1.1159026 0.2664114
[4,] 0.5712644 1.0330855 0.7738370 1.4749702
>
> 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,] 225.52069 33.02026 26.64418 39.17774
[2,] 38.65931 33.32006 31.11866 36.42045
[3,] 40.39714 35.17918 37.40426 27.73509
[4,] 31.03899 36.39812 33.33719 41.92524
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x557b9ddbd5c0>
> exp(tmp5)
<pointer: 0x557b9ddbd5c0>
> log(tmp5,2)
<pointer: 0x557b9ddbd5c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.3918
> Min(tmp5)
[1] 54.89281
> mean(tmp5)
[1] 73.48929
> Sum(tmp5)
[1] 14697.86
> Var(tmp5)
[1] 868.9734
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.00138 71.50743 70.95777 73.46570 70.69376 70.82884 72.11960 69.60013
[9] 71.15502 74.56326
> rowSums(tmp5)
[1] 1800.028 1430.149 1419.155 1469.314 1413.875 1416.577 1442.392 1392.003
[9] 1423.100 1491.265
> rowVars(tmp5)
[1] 8086.40286 52.49092 68.47658 49.62345 77.77108 102.77486
[7] 61.27862 78.80834 64.61020 120.71356
> rowSd(tmp5)
[1] 89.924429 7.245062 8.275058 7.044391 8.818791 10.137794 7.828066
[8] 8.877406 8.038047 10.986972
> rowMax(tmp5)
[1] 469.39176 89.10327 84.08136 89.01655 84.69433 88.72429 86.14996
[8] 87.96499 89.84252 94.85088
> rowMin(tmp5)
[1] 55.45638 60.73691 57.72695 62.88486 55.07627 55.17756 54.89281 55.16247
[9] 58.40588 56.87835
>
> colMeans(tmp5)
[1] 109.68783 70.06727 69.60461 72.51026 71.71321 73.47464 70.52841
[8] 71.62270 71.77606 72.24413 68.52333 73.01996 73.64664 76.18514
[15] 66.93855 69.05602 72.27156 71.16272 70.77273 74.98001
> colSums(tmp5)
[1] 1096.8783 700.6727 696.0461 725.1026 717.1321 734.7464 705.2841
[8] 716.2270 717.7606 722.4413 685.2333 730.1996 736.4664 761.8514
[15] 669.3855 690.5602 722.7156 711.6272 707.7273 749.8001
> colVars(tmp5)
[1] 16028.83698 123.17210 64.80431 101.33897 73.32322 71.65679
[7] 94.64625 70.10602 122.35358 76.44236 47.26216 112.13489
[13] 23.86560 124.81304 41.14298 83.58100 39.90364 65.98110
[19] 109.15142 106.98258
> colSd(tmp5)
[1] 126.605043 11.098293 8.050112 10.066726 8.562898 8.465033
[7] 9.728631 8.372934 11.061355 8.743132 6.874748 10.589376
[13] 4.885243 11.171976 6.414280 9.142264 6.316933 8.122875
[19] 10.447556 10.343238
> colMax(tmp5)
[1] 469.39176 94.07226 82.59692 87.26189 83.49434 89.10327 89.01655
[8] 87.96499 87.14911 88.72429 78.35889 89.84252 81.54439 94.85088
[15] 78.45371 80.68921 88.75387 81.04299 86.14996 96.28916
> colMin(tmp5)
[1] 61.71275 55.89420 55.45638 57.72695 55.17756 61.93712 56.52314 59.77909
[9] 54.89281 59.87074 59.73315 56.41632 66.89933 58.09584 59.18310 55.16247
[17] 67.25849 60.40517 58.20793 56.87835
>
>
> ### 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] 90.00138 71.50743 70.95777 73.46570 70.69376 70.82884 NA 69.60013
[9] 71.15502 74.56326
> rowSums(tmp5)
[1] 1800.028 1430.149 1419.155 1469.314 1413.875 1416.577 NA 1392.003
[9] 1423.100 1491.265
> rowVars(tmp5)
[1] 8086.40286 52.49092 68.47658 49.62345 77.77108 102.77486
[7] 64.68067 78.80834 64.61020 120.71356
> rowSd(tmp5)
[1] 89.924429 7.245062 8.275058 7.044391 8.818791 10.137794 8.042429
[8] 8.877406 8.038047 10.986972
> rowMax(tmp5)
[1] 469.39176 89.10327 84.08136 89.01655 84.69433 88.72429 NA
[8] 87.96499 89.84252 94.85088
> rowMin(tmp5)
[1] 55.45638 60.73691 57.72695 62.88486 55.07627 55.17756 NA 55.16247
[9] 58.40588 56.87835
>
> colMeans(tmp5)
[1] 109.68783 70.06727 69.60461 72.51026 71.71321 NA 70.52841
[8] 71.62270 71.77606 72.24413 68.52333 73.01996 73.64664 76.18514
[15] 66.93855 69.05602 72.27156 71.16272 70.77273 74.98001
> colSums(tmp5)
[1] 1096.8783 700.6727 696.0461 725.1026 717.1321 NA 705.2841
[8] 716.2270 717.7606 722.4413 685.2333 730.1996 736.4664 761.8514
[15] 669.3855 690.5602 722.7156 711.6272 707.7273 749.8001
> colVars(tmp5)
[1] 16028.83698 123.17210 64.80431 101.33897 73.32322 NA
[7] 94.64625 70.10602 122.35358 76.44236 47.26216 112.13489
[13] 23.86560 124.81304 41.14298 83.58100 39.90364 65.98110
[19] 109.15142 106.98258
> colSd(tmp5)
[1] 126.605043 11.098293 8.050112 10.066726 8.562898 NA
[7] 9.728631 8.372934 11.061355 8.743132 6.874748 10.589376
[13] 4.885243 11.171976 6.414280 9.142264 6.316933 8.122875
[19] 10.447556 10.343238
> colMax(tmp5)
[1] 469.39176 94.07226 82.59692 87.26189 83.49434 NA 89.01655
[8] 87.96499 87.14911 88.72429 78.35889 89.84252 81.54439 94.85088
[15] 78.45371 80.68921 88.75387 81.04299 86.14996 96.28916
> colMin(tmp5)
[1] 61.71275 55.89420 55.45638 57.72695 55.17756 NA 56.52314 59.77909
[9] 54.89281 59.87074 59.73315 56.41632 66.89933 58.09584 59.18310 55.16247
[17] 67.25849 60.40517 58.20793 56.87835
>
> Max(tmp5,na.rm=TRUE)
[1] 469.3918
> Min(tmp5,na.rm=TRUE)
[1] 54.89281
> mean(tmp5,na.rm=TRUE)
[1] 73.49517
> Sum(tmp5,na.rm=TRUE)
[1] 14625.54
> Var(tmp5,na.rm=TRUE)
[1] 873.3552
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.00138 71.50743 70.95777 73.46570 70.69376 70.82884 72.10912 69.60013
[9] 71.15502 74.56326
> rowSums(tmp5,na.rm=TRUE)
[1] 1800.028 1430.149 1419.155 1469.314 1413.875 1416.577 1370.073 1392.003
[9] 1423.100 1491.265
> rowVars(tmp5,na.rm=TRUE)
[1] 8086.40286 52.49092 68.47658 49.62345 77.77108 102.77486
[7] 64.68067 78.80834 64.61020 120.71356
> rowSd(tmp5,na.rm=TRUE)
[1] 89.924429 7.245062 8.275058 7.044391 8.818791 10.137794 8.042429
[8] 8.877406 8.038047 10.986972
> rowMax(tmp5,na.rm=TRUE)
[1] 469.39176 89.10327 84.08136 89.01655 84.69433 88.72429 86.14996
[8] 87.96499 89.84252 94.85088
> rowMin(tmp5,na.rm=TRUE)
[1] 55.45638 60.73691 57.72695 62.88486 55.07627 55.17756 54.89281 55.16247
[9] 58.40588 56.87835
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.68783 70.06727 69.60461 72.51026 71.71321 73.60307 70.52841
[8] 71.62270 71.77606 72.24413 68.52333 73.01996 73.64664 76.18514
[15] 66.93855 69.05602 72.27156 71.16272 70.77273 74.98001
> colSums(tmp5,na.rm=TRUE)
[1] 1096.8783 700.6727 696.0461 725.1026 717.1321 662.4277 705.2841
[8] 716.2270 717.7606 722.4413 685.2333 730.1996 736.4664 761.8514
[15] 669.3855 690.5602 722.7156 711.6272 707.7273 749.8001
> colVars(tmp5,na.rm=TRUE)
[1] 16028.83698 123.17210 64.80431 101.33897 73.32322 80.42831
[7] 94.64625 70.10602 122.35358 76.44236 47.26216 112.13489
[13] 23.86560 124.81304 41.14298 83.58100 39.90364 65.98110
[19] 109.15142 106.98258
> colSd(tmp5,na.rm=TRUE)
[1] 126.605043 11.098293 8.050112 10.066726 8.562898 8.968183
[7] 9.728631 8.372934 11.061355 8.743132 6.874748 10.589376
[13] 4.885243 11.171976 6.414280 9.142264 6.316933 8.122875
[19] 10.447556 10.343238
> colMax(tmp5,na.rm=TRUE)
[1] 469.39176 94.07226 82.59692 87.26189 83.49434 89.10327 89.01655
[8] 87.96499 87.14911 88.72429 78.35889 89.84252 81.54439 94.85088
[15] 78.45371 80.68921 88.75387 81.04299 86.14996 96.28916
> colMin(tmp5,na.rm=TRUE)
[1] 61.71275 55.89420 55.45638 57.72695 55.17756 61.93712 56.52314 59.77909
[9] 54.89281 59.87074 59.73315 56.41632 66.89933 58.09584 59.18310 55.16247
[17] 67.25849 60.40517 58.20793 56.87835
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.00138 71.50743 70.95777 73.46570 70.69376 70.82884 NaN 69.60013
[9] 71.15502 74.56326
> rowSums(tmp5,na.rm=TRUE)
[1] 1800.028 1430.149 1419.155 1469.314 1413.875 1416.577 0.000 1392.003
[9] 1423.100 1491.265
> rowVars(tmp5,na.rm=TRUE)
[1] 8086.40286 52.49092 68.47658 49.62345 77.77108 102.77486
[7] NA 78.80834 64.61020 120.71356
> rowSd(tmp5,na.rm=TRUE)
[1] 89.924429 7.245062 8.275058 7.044391 8.818791 10.137794 NA
[8] 8.877406 8.038047 10.986972
> rowMax(tmp5,na.rm=TRUE)
[1] 469.39176 89.10327 84.08136 89.01655 84.69433 88.72429 NA
[8] 87.96499 89.84252 94.85088
> rowMin(tmp5,na.rm=TRUE)
[1] 55.45638 60.73691 57.72695 62.88486 55.07627 55.17756 NA 55.16247
[9] 58.40588 56.87835
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.86785 69.28255 68.93293 73.07007 72.21046 NaN 72.08455
[8] 71.82798 73.65198 71.47510 67.71969 73.29113 73.47204 75.86531
[15] 66.70649 68.55235 72.46022 70.44507 69.06415 74.24654
> colSums(tmp5,na.rm=TRUE)
[1] 1033.8106 623.5430 620.3964 657.6307 649.8941 0.0000 648.7610
[8] 646.4518 662.8678 643.2759 609.4772 659.6202 661.2483 682.7878
[15] 600.3584 616.9712 652.1419 634.0057 621.5773 668.2189
> colVars(tmp5,na.rm=TRUE)
[1] 17730.57509 131.64099 67.82930 110.48072 79.70704 NA
[7] 79.23430 78.39521 98.05832 79.34449 45.90426 125.32450
[13] 26.50581 139.26392 45.68002 91.17475 44.49121 68.43479
[19] 89.95380 114.30324
> colSd(tmp5,na.rm=TRUE)
[1] 133.156206 11.473491 8.235854 10.510981 8.927880 NA
[7] 8.901365 8.854107 9.902440 8.907552 6.775268 11.194842
[13] 5.148379 11.801013 6.758699 9.548547 6.670173 8.272532
[19] 9.484398 10.691270
> colMax(tmp5,na.rm=TRUE)
[1] 469.39176 94.07226 82.59692 87.26189 83.49434 -Inf 89.01655
[8] 87.96499 87.14911 88.72429 78.35889 89.84252 81.54439 94.85088
[15] 78.45371 80.68921 88.75387 81.04299 85.68495 96.28916
> colMin(tmp5,na.rm=TRUE)
[1] 61.71275 55.89420 55.45638 57.72695 55.17756 Inf 61.19179 59.77909
[9] 55.07627 59.87074 59.73315 56.41632 66.89933 58.09584 59.18310 55.16247
[17] 67.25849 60.40517 58.20793 56.87835
>
>
>
>
> 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] 187.4854 408.4117 82.6319 352.1825 202.6243 176.3290 209.0141 147.1944
[9] 380.3011 183.1125
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 187.4854 408.4117 82.6319 352.1825 202.6243 176.3290 209.0141 147.1944
[9] 380.3011 183.1125
>
>
>
> 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] 2.842171e-14 5.684342e-14 5.684342e-14 0.000000e+00 5.684342e-14
[6] 1.421085e-14 9.947598e-14 5.684342e-14 0.000000e+00 -2.842171e-14
[11] -1.705303e-13 -1.705303e-13 5.684342e-14 5.684342e-14 2.273737e-13
[16] 0.000000e+00 -1.136868e-13 1.136868e-13 1.421085e-13 -1.421085e-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 4
10 1
3 8
6 2
4 12
1 12
8 11
2 3
7 13
2 4
10 10
1 15
3 13
2 9
3 12
5 2
8 2
1 17
7 13
5 7
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.804275
> Min(tmp)
[1] -2.280138
> mean(tmp)
[1] 0.03672538
> Sum(tmp)
[1] 3.672538
> Var(tmp)
[1] 0.9502558
>
> rowMeans(tmp)
[1] 0.03672538
> rowSums(tmp)
[1] 3.672538
> rowVars(tmp)
[1] 0.9502558
> rowSd(tmp)
[1] 0.9748107
> rowMax(tmp)
[1] 2.804275
> rowMin(tmp)
[1] -2.280138
>
> colMeans(tmp)
[1] -2.28013758 1.44259583 0.78576485 -0.67422462 -0.96815466 -0.50081674
[7] -0.33963525 -0.38726696 -0.22713554 -0.96363268 2.14864138 0.79762365
[13] -0.48536888 0.44534588 -0.48905903 -1.19504032 -1.87748662 0.90923109
[19] -0.50335045 1.18356903 -0.54916344 -0.28214651 -0.03116380 -0.41710156
[25] 0.54594802 -0.75559340 0.40587919 0.95026630 -0.17151385 -2.03468140
[31] 0.01758868 0.30409064 -0.11267933 0.72658832 -0.40385690 -0.41366180
[37] 1.21500093 0.18311189 -0.83281061 1.14547584 0.23297722 1.72933198
[43] -0.83319508 -0.96262294 -0.38696336 0.74103037 0.71665959 0.44942759
[49] -1.72466818 -0.66046839 -1.28907277 0.46859279 0.72521008 1.24120332
[55] 0.23533908 0.49726555 0.11249254 -0.14535191 -0.74189347 2.80427453
[61] 1.89343950 0.45595832 -0.40522037 2.17659494 -0.94133058 -0.36045791
[67] 0.54502457 1.51032069 0.16487824 0.20684629 -0.58683602 -1.19738660
[73] 0.77228496 0.62517688 -0.38567052 -0.15965305 -0.69650092 -0.01385687
[79] 0.80808665 0.25860638 -1.50899965 -1.15419092 0.57585299 -0.13226154
[85] 0.17565680 0.04229494 -0.36855308 -1.81170954 1.88003958 -0.27671603
[91] 0.96661409 -0.29293479 0.88423842 -1.38062495 0.55585306 1.06613729
[97] -1.16947765 -0.41593803 1.55833845 0.28800584
> colSums(tmp)
[1] -2.28013758 1.44259583 0.78576485 -0.67422462 -0.96815466 -0.50081674
[7] -0.33963525 -0.38726696 -0.22713554 -0.96363268 2.14864138 0.79762365
[13] -0.48536888 0.44534588 -0.48905903 -1.19504032 -1.87748662 0.90923109
[19] -0.50335045 1.18356903 -0.54916344 -0.28214651 -0.03116380 -0.41710156
[25] 0.54594802 -0.75559340 0.40587919 0.95026630 -0.17151385 -2.03468140
[31] 0.01758868 0.30409064 -0.11267933 0.72658832 -0.40385690 -0.41366180
[37] 1.21500093 0.18311189 -0.83281061 1.14547584 0.23297722 1.72933198
[43] -0.83319508 -0.96262294 -0.38696336 0.74103037 0.71665959 0.44942759
[49] -1.72466818 -0.66046839 -1.28907277 0.46859279 0.72521008 1.24120332
[55] 0.23533908 0.49726555 0.11249254 -0.14535191 -0.74189347 2.80427453
[61] 1.89343950 0.45595832 -0.40522037 2.17659494 -0.94133058 -0.36045791
[67] 0.54502457 1.51032069 0.16487824 0.20684629 -0.58683602 -1.19738660
[73] 0.77228496 0.62517688 -0.38567052 -0.15965305 -0.69650092 -0.01385687
[79] 0.80808665 0.25860638 -1.50899965 -1.15419092 0.57585299 -0.13226154
[85] 0.17565680 0.04229494 -0.36855308 -1.81170954 1.88003958 -0.27671603
[91] 0.96661409 -0.29293479 0.88423842 -1.38062495 0.55585306 1.06613729
[97] -1.16947765 -0.41593803 1.55833845 0.28800584
> 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] -2.28013758 1.44259583 0.78576485 -0.67422462 -0.96815466 -0.50081674
[7] -0.33963525 -0.38726696 -0.22713554 -0.96363268 2.14864138 0.79762365
[13] -0.48536888 0.44534588 -0.48905903 -1.19504032 -1.87748662 0.90923109
[19] -0.50335045 1.18356903 -0.54916344 -0.28214651 -0.03116380 -0.41710156
[25] 0.54594802 -0.75559340 0.40587919 0.95026630 -0.17151385 -2.03468140
[31] 0.01758868 0.30409064 -0.11267933 0.72658832 -0.40385690 -0.41366180
[37] 1.21500093 0.18311189 -0.83281061 1.14547584 0.23297722 1.72933198
[43] -0.83319508 -0.96262294 -0.38696336 0.74103037 0.71665959 0.44942759
[49] -1.72466818 -0.66046839 -1.28907277 0.46859279 0.72521008 1.24120332
[55] 0.23533908 0.49726555 0.11249254 -0.14535191 -0.74189347 2.80427453
[61] 1.89343950 0.45595832 -0.40522037 2.17659494 -0.94133058 -0.36045791
[67] 0.54502457 1.51032069 0.16487824 0.20684629 -0.58683602 -1.19738660
[73] 0.77228496 0.62517688 -0.38567052 -0.15965305 -0.69650092 -0.01385687
[79] 0.80808665 0.25860638 -1.50899965 -1.15419092 0.57585299 -0.13226154
[85] 0.17565680 0.04229494 -0.36855308 -1.81170954 1.88003958 -0.27671603
[91] 0.96661409 -0.29293479 0.88423842 -1.38062495 0.55585306 1.06613729
[97] -1.16947765 -0.41593803 1.55833845 0.28800584
> colMin(tmp)
[1] -2.28013758 1.44259583 0.78576485 -0.67422462 -0.96815466 -0.50081674
[7] -0.33963525 -0.38726696 -0.22713554 -0.96363268 2.14864138 0.79762365
[13] -0.48536888 0.44534588 -0.48905903 -1.19504032 -1.87748662 0.90923109
[19] -0.50335045 1.18356903 -0.54916344 -0.28214651 -0.03116380 -0.41710156
[25] 0.54594802 -0.75559340 0.40587919 0.95026630 -0.17151385 -2.03468140
[31] 0.01758868 0.30409064 -0.11267933 0.72658832 -0.40385690 -0.41366180
[37] 1.21500093 0.18311189 -0.83281061 1.14547584 0.23297722 1.72933198
[43] -0.83319508 -0.96262294 -0.38696336 0.74103037 0.71665959 0.44942759
[49] -1.72466818 -0.66046839 -1.28907277 0.46859279 0.72521008 1.24120332
[55] 0.23533908 0.49726555 0.11249254 -0.14535191 -0.74189347 2.80427453
[61] 1.89343950 0.45595832 -0.40522037 2.17659494 -0.94133058 -0.36045791
[67] 0.54502457 1.51032069 0.16487824 0.20684629 -0.58683602 -1.19738660
[73] 0.77228496 0.62517688 -0.38567052 -0.15965305 -0.69650092 -0.01385687
[79] 0.80808665 0.25860638 -1.50899965 -1.15419092 0.57585299 -0.13226154
[85] 0.17565680 0.04229494 -0.36855308 -1.81170954 1.88003958 -0.27671603
[91] 0.96661409 -0.29293479 0.88423842 -1.38062495 0.55585306 1.06613729
[97] -1.16947765 -0.41593803 1.55833845 0.28800584
> colMedians(tmp)
[1] -2.28013758 1.44259583 0.78576485 -0.67422462 -0.96815466 -0.50081674
[7] -0.33963525 -0.38726696 -0.22713554 -0.96363268 2.14864138 0.79762365
[13] -0.48536888 0.44534588 -0.48905903 -1.19504032 -1.87748662 0.90923109
[19] -0.50335045 1.18356903 -0.54916344 -0.28214651 -0.03116380 -0.41710156
[25] 0.54594802 -0.75559340 0.40587919 0.95026630 -0.17151385 -2.03468140
[31] 0.01758868 0.30409064 -0.11267933 0.72658832 -0.40385690 -0.41366180
[37] 1.21500093 0.18311189 -0.83281061 1.14547584 0.23297722 1.72933198
[43] -0.83319508 -0.96262294 -0.38696336 0.74103037 0.71665959 0.44942759
[49] -1.72466818 -0.66046839 -1.28907277 0.46859279 0.72521008 1.24120332
[55] 0.23533908 0.49726555 0.11249254 -0.14535191 -0.74189347 2.80427453
[61] 1.89343950 0.45595832 -0.40522037 2.17659494 -0.94133058 -0.36045791
[67] 0.54502457 1.51032069 0.16487824 0.20684629 -0.58683602 -1.19738660
[73] 0.77228496 0.62517688 -0.38567052 -0.15965305 -0.69650092 -0.01385687
[79] 0.80808665 0.25860638 -1.50899965 -1.15419092 0.57585299 -0.13226154
[85] 0.17565680 0.04229494 -0.36855308 -1.81170954 1.88003958 -0.27671603
[91] 0.96661409 -0.29293479 0.88423842 -1.38062495 0.55585306 1.06613729
[97] -1.16947765 -0.41593803 1.55833845 0.28800584
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -2.280138 1.442596 0.7857649 -0.6742246 -0.9681547 -0.5008167 -0.3396353
[2,] -2.280138 1.442596 0.7857649 -0.6742246 -0.9681547 -0.5008167 -0.3396353
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.387267 -0.2271355 -0.9636327 2.148641 0.7976237 -0.4853689 0.4453459
[2,] -0.387267 -0.2271355 -0.9636327 2.148641 0.7976237 -0.4853689 0.4453459
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.489059 -1.19504 -1.877487 0.9092311 -0.5033504 1.183569 -0.5491634
[2,] -0.489059 -1.19504 -1.877487 0.9092311 -0.5033504 1.183569 -0.5491634
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.2821465 -0.0311638 -0.4171016 0.545948 -0.7555934 0.4058792 0.9502663
[2,] -0.2821465 -0.0311638 -0.4171016 0.545948 -0.7555934 0.4058792 0.9502663
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.1715139 -2.034681 0.01758868 0.3040906 -0.1126793 0.7265883 -0.4038569
[2,] -0.1715139 -2.034681 0.01758868 0.3040906 -0.1126793 0.7265883 -0.4038569
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.4136618 1.215001 0.1831119 -0.8328106 1.145476 0.2329772 1.729332
[2,] -0.4136618 1.215001 0.1831119 -0.8328106 1.145476 0.2329772 1.729332
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.8331951 -0.9626229 -0.3869634 0.7410304 0.7166596 0.4494276 -1.724668
[2,] -0.8331951 -0.9626229 -0.3869634 0.7410304 0.7166596 0.4494276 -1.724668
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.6604684 -1.289073 0.4685928 0.7252101 1.241203 0.2353391 0.4972656
[2,] -0.6604684 -1.289073 0.4685928 0.7252101 1.241203 0.2353391 0.4972656
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.1124925 -0.1453519 -0.7418935 2.804275 1.89344 0.4559583 -0.4052204
[2,] 0.1124925 -0.1453519 -0.7418935 2.804275 1.89344 0.4559583 -0.4052204
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 2.176595 -0.9413306 -0.3604579 0.5450246 1.510321 0.1648782 0.2068463
[2,] 2.176595 -0.9413306 -0.3604579 0.5450246 1.510321 0.1648782 0.2068463
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.586836 -1.197387 0.772285 0.6251769 -0.3856705 -0.159653 -0.6965009
[2,] -0.586836 -1.197387 0.772285 0.6251769 -0.3856705 -0.159653 -0.6965009
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.01385687 0.8080867 0.2586064 -1.509 -1.154191 0.575853 -0.1322615
[2,] -0.01385687 0.8080867 0.2586064 -1.509 -1.154191 0.575853 -0.1322615
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1756568 0.04229494 -0.3685531 -1.81171 1.88004 -0.276716 0.9666141
[2,] 0.1756568 0.04229494 -0.3685531 -1.81171 1.88004 -0.276716 0.9666141
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.2929348 0.8842384 -1.380625 0.5558531 1.066137 -1.169478 -0.415938
[2,] -0.2929348 0.8842384 -1.380625 0.5558531 1.066137 -1.169478 -0.415938
[,99] [,100]
[1,] 1.558338 0.2880058
[2,] 1.558338 0.2880058
>
>
> Max(tmp2)
[1] 2.513811
> Min(tmp2)
[1] -4.042841
> mean(tmp2)
[1] -0.09009476
> Sum(tmp2)
[1] -9.009476
> Var(tmp2)
[1] 1.015195
>
> rowMeans(tmp2)
[1] 0.482102568 0.749327827 0.866695976 -1.841801283 -1.153002383
[6] 0.606296565 -1.468945376 -0.091731072 0.167139242 0.269060955
[11] -1.392388081 -2.351399702 -0.749349870 -0.121968055 -1.250275897
[16] -0.538285104 -0.507799891 -0.313450289 0.994979964 -0.195286006
[21] 1.210530314 0.428770479 0.922292712 0.883410421 0.307854380
[26] -0.473388941 0.182659578 -1.035328863 -0.333893533 0.315964544
[31] 1.303784742 -0.016619749 1.327330280 -0.041253151 0.222889072
[36] -1.371200605 -0.278764866 -0.356153606 1.580289419 -0.451934411
[41] -1.534769303 -0.030228334 -0.987152140 -1.293722327 0.723237886
[46] 0.968211283 -0.293910337 1.249809795 -0.474682663 1.102011581
[51] -0.668125853 -0.340262919 0.213289264 -0.253559309 -1.177672370
[56] -1.312812591 -1.053834734 0.564110488 0.533828961 -1.595721378
[61] -0.235844403 -0.229483596 0.925181789 0.462230385 0.010044733
[66] -0.422734913 -0.443923993 0.968361689 0.574859707 -0.802980691
[71] 1.980837378 0.322974772 0.853104349 -0.899715186 -0.746989828
[76] -1.144504314 -1.354196043 -0.005963722 -0.379254524 0.557075213
[81] -0.653715170 -0.217403186 1.364424189 0.132032107 -0.445252913
[86] -1.989278273 1.126630998 1.179151416 -0.678249348 -0.442646169
[91] 0.703882514 1.033810997 -0.293733694 0.535901934 -4.042841043
[96] 2.513810993 0.496590128 1.066146057 -1.149394829 -0.063624572
> rowSums(tmp2)
[1] 0.482102568 0.749327827 0.866695976 -1.841801283 -1.153002383
[6] 0.606296565 -1.468945376 -0.091731072 0.167139242 0.269060955
[11] -1.392388081 -2.351399702 -0.749349870 -0.121968055 -1.250275897
[16] -0.538285104 -0.507799891 -0.313450289 0.994979964 -0.195286006
[21] 1.210530314 0.428770479 0.922292712 0.883410421 0.307854380
[26] -0.473388941 0.182659578 -1.035328863 -0.333893533 0.315964544
[31] 1.303784742 -0.016619749 1.327330280 -0.041253151 0.222889072
[36] -1.371200605 -0.278764866 -0.356153606 1.580289419 -0.451934411
[41] -1.534769303 -0.030228334 -0.987152140 -1.293722327 0.723237886
[46] 0.968211283 -0.293910337 1.249809795 -0.474682663 1.102011581
[51] -0.668125853 -0.340262919 0.213289264 -0.253559309 -1.177672370
[56] -1.312812591 -1.053834734 0.564110488 0.533828961 -1.595721378
[61] -0.235844403 -0.229483596 0.925181789 0.462230385 0.010044733
[66] -0.422734913 -0.443923993 0.968361689 0.574859707 -0.802980691
[71] 1.980837378 0.322974772 0.853104349 -0.899715186 -0.746989828
[76] -1.144504314 -1.354196043 -0.005963722 -0.379254524 0.557075213
[81] -0.653715170 -0.217403186 1.364424189 0.132032107 -0.445252913
[86] -1.989278273 1.126630998 1.179151416 -0.678249348 -0.442646169
[91] 0.703882514 1.033810997 -0.293733694 0.535901934 -4.042841043
[96] 2.513810993 0.496590128 1.066146057 -1.149394829 -0.063624572
> 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] 0.482102568 0.749327827 0.866695976 -1.841801283 -1.153002383
[6] 0.606296565 -1.468945376 -0.091731072 0.167139242 0.269060955
[11] -1.392388081 -2.351399702 -0.749349870 -0.121968055 -1.250275897
[16] -0.538285104 -0.507799891 -0.313450289 0.994979964 -0.195286006
[21] 1.210530314 0.428770479 0.922292712 0.883410421 0.307854380
[26] -0.473388941 0.182659578 -1.035328863 -0.333893533 0.315964544
[31] 1.303784742 -0.016619749 1.327330280 -0.041253151 0.222889072
[36] -1.371200605 -0.278764866 -0.356153606 1.580289419 -0.451934411
[41] -1.534769303 -0.030228334 -0.987152140 -1.293722327 0.723237886
[46] 0.968211283 -0.293910337 1.249809795 -0.474682663 1.102011581
[51] -0.668125853 -0.340262919 0.213289264 -0.253559309 -1.177672370
[56] -1.312812591 -1.053834734 0.564110488 0.533828961 -1.595721378
[61] -0.235844403 -0.229483596 0.925181789 0.462230385 0.010044733
[66] -0.422734913 -0.443923993 0.968361689 0.574859707 -0.802980691
[71] 1.980837378 0.322974772 0.853104349 -0.899715186 -0.746989828
[76] -1.144504314 -1.354196043 -0.005963722 -0.379254524 0.557075213
[81] -0.653715170 -0.217403186 1.364424189 0.132032107 -0.445252913
[86] -1.989278273 1.126630998 1.179151416 -0.678249348 -0.442646169
[91] 0.703882514 1.033810997 -0.293733694 0.535901934 -4.042841043
[96] 2.513810993 0.496590128 1.066146057 -1.149394829 -0.063624572
> rowMin(tmp2)
[1] 0.482102568 0.749327827 0.866695976 -1.841801283 -1.153002383
[6] 0.606296565 -1.468945376 -0.091731072 0.167139242 0.269060955
[11] -1.392388081 -2.351399702 -0.749349870 -0.121968055 -1.250275897
[16] -0.538285104 -0.507799891 -0.313450289 0.994979964 -0.195286006
[21] 1.210530314 0.428770479 0.922292712 0.883410421 0.307854380
[26] -0.473388941 0.182659578 -1.035328863 -0.333893533 0.315964544
[31] 1.303784742 -0.016619749 1.327330280 -0.041253151 0.222889072
[36] -1.371200605 -0.278764866 -0.356153606 1.580289419 -0.451934411
[41] -1.534769303 -0.030228334 -0.987152140 -1.293722327 0.723237886
[46] 0.968211283 -0.293910337 1.249809795 -0.474682663 1.102011581
[51] -0.668125853 -0.340262919 0.213289264 -0.253559309 -1.177672370
[56] -1.312812591 -1.053834734 0.564110488 0.533828961 -1.595721378
[61] -0.235844403 -0.229483596 0.925181789 0.462230385 0.010044733
[66] -0.422734913 -0.443923993 0.968361689 0.574859707 -0.802980691
[71] 1.980837378 0.322974772 0.853104349 -0.899715186 -0.746989828
[76] -1.144504314 -1.354196043 -0.005963722 -0.379254524 0.557075213
[81] -0.653715170 -0.217403186 1.364424189 0.132032107 -0.445252913
[86] -1.989278273 1.126630998 1.179151416 -0.678249348 -0.442646169
[91] 0.703882514 1.033810997 -0.293733694 0.535901934 -4.042841043
[96] 2.513810993 0.496590128 1.066146057 -1.149394829 -0.063624572
>
> colMeans(tmp2)
[1] -0.09009476
> colSums(tmp2)
[1] -9.009476
> colVars(tmp2)
[1] 1.015195
> colSd(tmp2)
[1] 1.007569
> colMax(tmp2)
[1] 2.513811
> colMin(tmp2)
[1] -4.042841
> colMedians(tmp2)
[1] -0.1068496
> colRanges(tmp2)
[,1]
[1,] -4.042841
[2,] 2.513811
>
> 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] 4.6629548 2.7138631 0.7149977 -0.3075777 -2.2027163 6.1766679
[7] -5.3075931 -0.9913235 5.8683875 -5.1117017
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8728467
[2,] -0.1981744
[3,] 0.1988468
[4,] 1.4385694
[5,] 2.5829194
>
> rowApply(tmp,sum)
[1] 0.08172191 -1.44920821 -0.74572458 2.88519945 2.45563826 -2.86974738
[7] 2.40797175 2.09917575 -1.36384971 2.71478142
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 10 4 10 4 10 9 4 2 4
[2,] 9 7 3 6 7 8 1 6 7 10
[3,] 2 9 10 7 5 2 6 7 9 1
[4,] 6 5 1 5 3 5 7 8 6 8
[5,] 8 6 5 1 9 7 3 2 3 3
[6,] 10 1 9 8 8 6 10 1 5 9
[7,] 3 3 2 2 1 1 8 3 10 2
[8,] 1 4 7 3 2 9 4 9 8 5
[9,] 4 8 8 9 10 4 5 10 4 7
[10,] 5 2 6 4 6 3 2 5 1 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.00508344 7.62081988 -1.52017926 4.37129956 5.64987604 2.93515150
[7] -6.83578546 -1.59580441 -2.73949027 1.96211664 -3.90843847 -0.46205862
[13] -2.98969800 -2.74384211 -0.09623975 -1.16142374 5.19484627 -2.49692124
[19] -5.83747906 -0.74657822
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.216038935
[2,] -0.145836668
[3,] 0.003736741
[4,] 0.410380917
[5,] 1.952841389
>
> rowApply(tmp,sum)
[1] 7.337229 -3.502710 -3.914205 4.249009 -7.564068
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 10 11 11 13
[2,] 19 13 19 20 20
[3,] 17 8 2 10 4
[4,] 10 20 15 14 18
[5,] 20 18 17 18 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.952841389 1.9540801 1.9253222 0.2198529 2.0498232 1.1831230 -1.560302
[2,] -0.216038935 0.1882223 -0.2446210 2.1896738 1.2374455 0.3081985 -1.370933
[3,] -0.145836668 1.7683224 -1.9102302 0.5075494 1.0150453 1.1017687 -1.063481
[4,] 0.410380917 1.8988264 0.2331405 0.6046731 1.5317024 0.1861345 -1.465469
[5,] 0.003736741 1.8113687 -1.5237908 0.8495504 -0.1841403 0.1559268 -1.375601
[,8] [,9] [,10] [,11] [,12] [,13]
[1,] -1.25061123 -1.5542178 0.1959337 -1.3683326 -0.6586510 1.2287775
[2,] -0.16468398 0.6252824 1.4505025 -0.2173373 -1.3725957 -0.9385704
[3,] 0.45017457 -0.1549494 1.9786279 -1.8334878 -0.9623699 -1.4647882
[4,] 0.04725855 -0.6517660 -1.0504363 1.3175552 1.3390932 0.4109845
[5,] -0.67794233 -1.0038394 -0.6125111 -1.8068360 1.1924648 -2.2261013
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 1.0255490 0.5807333 0.1242611 1.5495240 0.4047707 -0.3774271
[2,] -1.7145035 0.8392016 -0.8773532 0.6729703 -3.4073599 -0.4081446
[3,] -2.6832598 0.3606067 -0.4962680 0.7996540 -0.4617014 -0.7940526
[4,] 0.4268137 -1.2681628 -0.4495655 1.6026648 1.3000562 -2.3962174
[5,] 0.2015584 -0.6086185 0.5375018 0.5700331 -0.3326869 -1.8616374
[,20]
[1,] -0.28782196
[2,] -0.08206572
[3,] 0.07447144
[4,] 0.22134245
[5,] -0.67250442
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.3043873 -1.334932 0.6660398 1.68123 -0.7732232 -1.316848 -0.3745571
col8 col9 col10 col11 col12 col13 col14
row1 -0.02091469 0.5853776 0.211821 -2.607546 -0.2710588 0.05887356 -0.8469448
col15 col16 col17 col18 col19 col20
row1 0.8995367 -0.6395755 0.08596008 -1.402897 0.6093068 1.393753
> tmp[,"col10"]
col10
row1 0.2118210
row2 -1.9948732
row3 0.0168371
row4 0.7046839
row5 -1.6128022
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.3043873 -1.334932 0.6660398 1.6812302 -0.7732232 -1.316848 -0.37455714
row5 -1.2821451 -1.250864 0.1859656 -0.9450326 -0.5924678 1.857557 -0.04351933
col8 col9 col10 col11 col12 col13
row1 -0.02091469 0.5853776 0.211821 -2.6075457 -0.2710588 0.05887356
row5 0.13473700 0.7843737 -1.612802 0.6507923 1.2655718 -0.64020517
col14 col15 col16 col17 col18 col19
row1 -0.8469448 0.8995367 -0.6395755 0.08596008 -1.40289673 0.6093068
row5 1.3218028 -1.1055187 -1.6706651 1.42486949 0.04796551 -0.6227180
col20
row1 1.3937530
row5 -0.3747855
> tmp[,c("col6","col20")]
col6 col20
row1 -1.31684844 1.3937530
row2 0.06586562 0.4312663
row3 0.24151478 -1.0531399
row4 0.05719229 -0.4527370
row5 1.85755746 -0.3747855
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.316848 1.3937530
row5 1.857557 -0.3747855
>
>
>
>
> 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 50.20052 49.99118 48.79073 48.90104 49.45998 106.2845 49.01356 48.18807
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.16989 50.59853 49.68687 50.29499 49.98029 48.67467 48.67926 49.64301
col17 col18 col19 col20
row1 50.98742 50.24535 47.42413 106.3829
> tmp[,"col10"]
col10
row1 50.59853
row2 29.46745
row3 30.79452
row4 29.77642
row5 49.66507
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.20052 49.99118 48.79073 48.90104 49.45998 106.2845 49.01356 48.18807
row5 49.51770 51.07991 50.35022 49.78513 50.46955 105.7837 49.69203 50.98364
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.16989 50.59853 49.68687 50.29499 49.98029 48.67467 48.67926 49.64301
row5 51.24073 49.66507 51.14442 49.01151 51.73423 49.54047 49.55726 49.89353
col17 col18 col19 col20
row1 50.98742 50.24535 47.42413 106.3829
row5 51.65646 48.27079 50.92060 105.3643
> tmp[,c("col6","col20")]
col6 col20
row1 106.28450 106.38290
row2 73.06389 74.44819
row3 75.29637 75.01557
row4 76.25533 75.63789
row5 105.78369 105.36426
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.2845 106.3829
row5 105.7837 105.3643
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.2845 106.3829
row5 105.7837 105.3643
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.7479779
[2,] 0.4829316
[3,] 0.2084980
[4,] -0.4875892
[5,] 2.1052821
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7039851 -0.1569735
[2,] 0.9012747 1.3974318
[3,] 0.3408802 -1.1181340
[4,] 1.3906318 -1.5893140
[5,] 0.4808993 0.1503184
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.46399626 -1.1106173
[2,] 1.52941036 -0.2657023
[3,] -1.00517549 1.3899299
[4,] 0.08435591 1.5980192
[5,] -1.23191642 -0.1403423
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.4639963
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.4639963
[2,] 1.5294104
>
>
>
> 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 0.5337032 -0.1880530 0.7596667 1.2227998 -1.0622789 0.03117577 1.6877258
row1 0.3371550 -0.7438858 2.6489604 0.2981472 -0.3742896 -1.61983291 -0.7584783
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.8423986 0.03423466 0.3733180 -0.7229829 0.9996712 -1.0742354
row1 1.1454992 -0.30978635 -0.5183179 -0.2351878 -0.4818615 0.8071444
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.4394434 0.6952953 -0.1219739 -0.3289399 -0.8893987 -0.2115453
row1 0.8641308 -0.1370216 0.4018527 0.1426364 -0.4991990 -2.2263744
[,20]
row3 0.7566758
row1 -0.8934756
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.4359666 -0.2867847 -0.3047107 2.126442 -0.8083161 0.584292 0.8468217
[,8] [,9] [,10]
row2 3.51219 -0.8063109 1.186892
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.8957848 1.515053 -1.471067 -0.8242493 -0.5646122 -0.169654 1.270152
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7234722 -0.7401678 1.255313 -0.8102007 0.239956 0.4777824 0.7457342
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.301325 0.3656465 -0.0458851 0.02139407 0.3299842 1.01913
>
>
> 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: 0x557b9f2e08a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1297023a02594e"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12970257897d70"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12970233b002a2"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM129702d16deb3"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1297027f311c0d"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12970214880a02"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM129702768d0d9a"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12970244b1bf84"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1297025cac120f"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM129702791a37f9"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12970272b3d182"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM129702600094"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12970271642e7c"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1297023db205a9"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1297027aa3c65e"
>
>
> ### 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: 0x557b9dc77510>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x557b9dc77510>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x557b9dc77510>
> rowMedians(tmp)
[1] -0.225383864 0.819703560 0.387842382 -0.346102571 -0.061956981
[6] 0.055671654 -0.003133766 0.226235479 0.243474806 0.349009862
[11] 0.195569658 0.233460285 -0.575597349 -0.170269813 0.079647099
[16] -0.633278378 -0.124122128 0.477795380 0.166059458 0.197541738
[21] 0.006065931 -0.515411495 0.401354570 -0.062849526 -0.299359616
[26] -0.305354344 -0.557672951 0.028642755 0.291408866 0.017747746
[31] 0.177468371 -0.201317175 0.446739779 -0.197708345 -0.376569857
[36] -0.696998326 0.318914979 0.210975486 0.272398708 -0.325662996
[41] -0.243002566 0.247461181 -0.276204388 -0.089312987 -0.211356092
[46] -0.440518007 -0.706727469 0.255103009 0.327287580 -0.230703696
[51] 0.241460254 -0.144227380 -0.451130204 0.086854318 0.205046030
[56] -0.351257616 -0.107266305 0.147900423 -0.314078747 0.052605340
[61] -0.643983038 0.551141789 0.614152984 -0.237506906 -0.776708750
[66] -0.072594027 -0.455104773 -0.584328828 0.357613895 0.189868009
[71] -0.249410876 -0.344010045 0.201821853 -0.038444872 0.201213214
[76] 0.207255980 0.155301898 -0.037878239 0.517740296 -0.467142632
[81] 0.393844132 -0.494663709 -0.003258079 0.418426829 0.272536357
[86] 0.404763564 -0.100740878 0.443053449 -0.528556313 -0.094406497
[91] -0.532570024 -0.436495747 0.484808132 0.058992324 0.265208050
[96] 0.452882236 0.189941773 0.238839668 -0.264809587 0.098246501
[101] 0.444810112 -0.045907997 0.121764513 0.282923770 0.231604108
[106] -0.363078570 -0.490501147 0.547428553 0.720794353 -0.331240371
[111] 0.448680200 -0.134195936 0.028848792 -0.157039912 0.575422731
[116] -0.176378155 0.383002717 -0.437022123 0.337838682 0.600872539
[121] 0.449434776 -0.056347406 -0.319884392 0.174644136 -0.460563216
[126] 0.152412747 -0.194306932 -0.051801556 -0.021056696 -0.185142170
[131] 0.385248131 0.171403324 -0.301128484 0.430799404 -0.021734036
[136] 0.138825361 -0.477246981 0.462088408 0.516374106 -0.497739179
[141] -0.296683830 -0.082185944 0.209511729 -0.167780690 -0.423385849
[146] 0.364642445 -0.377850019 0.357780374 -0.532784671 -0.333533511
[151] -0.035428123 0.382551874 -0.234349693 -0.205853557 0.154345647
[156] 0.458008885 -0.398102908 0.148352064 0.229292295 0.142705680
[161] -0.748015347 -0.015690916 0.316248441 -0.479269133 -0.103503236
[166] 0.198223556 0.438744079 -0.761034162 0.784010587 0.085331257
[171] 0.232547480 -0.162124038 0.029397391 -0.592360644 -0.114274823
[176] -0.109163057 -0.211201185 0.052004400 -0.255570113 -0.546520104
[181] 0.137892172 0.251760813 -0.119030657 -0.075204590 -0.069383667
[186] -0.288514987 0.334927223 0.144193658 -0.123249565 0.011249880
[191] -0.181894703 0.424574322 0.144554887 -0.250515096 0.237998661
[196] 0.842176208 -0.450084592 -0.582984934 -0.166622099 -0.341034804
[201] 0.408783014 -0.554616675 -0.296663024 0.319328300 -0.306510871
[206] 0.426037758 -0.137853598 0.711497019 -0.250642291 -0.299799180
[211] -0.318532959 0.097001783 -0.314888996 0.407366407 0.021385760
[216] 0.574940309 -0.340693146 0.161005963 -0.370899204 -0.269696754
[221] -0.075422598 -0.121891873 0.011915028 0.005855864 -0.724787662
[226] -0.414588775 0.395368458 -0.121610450 0.399674388 0.165393117
>
> proc.time()
user system elapsed
1.275 0.672 1.936
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
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: 0x5c2cc9d66b10>
> .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: 0x5c2cc9d66b10>
> .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: 0x5c2cc9d66b10>
> .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: 0x5c2cc9d66b10>
> 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: 0x5c2cc8a18660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2cc8a18660>
> .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: 0x5c2cc8a18660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2cc8a18660>
> .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: 0x5c2cc8a18660>
> 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: 0x5c2cc85f9c40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2cc85f9c40>
> .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: 0x5c2cc85f9c40>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5c2cc85f9c40>
> .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: 0x5c2cc85f9c40>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5c2cc85f9c40>
> .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: 0x5c2cc85f9c40>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5c2cc85f9c40>
> .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: 0x5c2cc85f9c40>
> 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: 0x5c2ccb0e54f0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5c2ccb0e54f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2ccb0e54f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2ccb0e54f0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1297ba1925cd05" "BufferedMatrixFile1297ba3fc78df2"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1297ba1925cd05" "BufferedMatrixFile1297ba3fc78df2"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2ccaa23a80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2ccaa23a80>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5c2ccaa23a80>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5c2ccaa23a80>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5c2ccaa23a80>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5c2ccaa23a80>
> .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: 0x5c2cca900750>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5c2cca900750>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5c2cca900750>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5c2cca900750>
> 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: 0x5c2cc8970fc0>
> .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: 0x5c2cc8970fc0>
> rm(P)
>
> proc.time()
user system elapsed
0.267 0.055 0.307
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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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
0.242 0.049 0.279