Ben Bolstad
| Snapshot Date: 2026-01-01 13:45 -0500 (Thu, 01 Jan 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-01-05 11:58 -0500 (Mon, 05 Jan 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4883 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4671 |
| 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. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.74.0 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2026-01-02 09:27:48 -0000 (Fri, 02 Jan 2026) |
| EndedAt: 2026-01-02 09:28:49 -0000 (Fri, 02 Jan 2026) |
| EllapsedTime: 60.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* 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: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/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){
| ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -shared -L/home/biocbuild/R/R-4.5.0/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.5.0/lib -lR
installing to /home/biocbuild/R/R-4.5.0/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 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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
0.345 0.033 0.365
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 478398 25.6 1047041 56 639620 34.2
Vcells 885166 6.8 8388608 64 2080985 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 Jan 2 09:28:42 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Jan 2 09:28:42 2026"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x164fbff0>
>
>
>
> 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 Jan 2 09:28:43 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] "Fri Jan 2 09:28:43 2026"
>
> ColMode(tmp2)
<pointer: 0x164fbff0>
>
>
>
> ### 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,] 100.7996404 -2.003271 1.1585412 -0.4162937
[2,] 0.7583899 -0.159488 -1.7717943 -1.2292202
[3,] 0.4848232 0.931601 0.1523631 1.0896973
[4,] -0.8665627 1.660383 2.0541583 0.6638711
> 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,] 100.7996404 2.003271 1.1585412 0.4162937
[2,] 0.7583899 0.159488 1.7717943 1.2292202
[3,] 0.4848232 0.931601 0.1523631 1.0896973
[4,] 0.8665627 1.660383 2.0541583 0.6638711
> 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,] 10.0399024 1.4153696 1.0763555 0.6452082
[2,] 0.8708559 0.3993595 1.3310876 1.1087020
[3,] 0.6962925 0.9651948 0.3903371 1.0438857
[4,] 0.9308935 1.2885585 1.4332335 0.8147829
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.19866 41.15697 36.92210 31.86838
[2,] 34.46695 29.15308 40.08267 37.31624
[3,] 32.44775 35.58355 29.05573 36.52855
[4,] 35.17550 39.54597 41.38649 33.81170
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x151de6c0>
> exp(tmp5)
<pointer: 0x151de6c0>
> log(tmp5,2)
<pointer: 0x151de6c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.8029
> Min(tmp5)
[1] 54.44836
> mean(tmp5)
[1] 73.73161
> Sum(tmp5)
[1] 14746.32
> Var(tmp5)
[1] 865.3606
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.50524 72.33118 71.90458 73.22752 70.06813 71.23188 74.36960 71.92451
[9] 70.32131 70.43218
> rowSums(tmp5)
[1] 1830.105 1446.624 1438.092 1464.550 1401.363 1424.638 1487.392 1438.490
[9] 1406.426 1408.644
> rowVars(tmp5)
[1] 8013.80571 51.71513 89.82853 62.12356 67.90027 70.52510
[7] 67.67233 89.95038 105.72122 57.62522
> rowSd(tmp5)
[1] 89.519862 7.191323 9.477792 7.881850 8.240162 8.397923 8.226319
[8] 9.484218 10.282082 7.591128
> rowMax(tmp5)
[1] 470.80288 83.90150 90.37187 86.14056 88.18244 86.80065 92.26113
[8] 87.17713 87.56782 80.49067
> rowMin(tmp5)
[1] 59.34874 54.82474 55.92743 62.51422 59.64107 54.44836 58.79641 54.90485
[9] 57.24252 57.17090
>
> colMeans(tmp5)
[1] 109.59812 74.60202 70.24780 74.00105 70.42696 73.06198 71.72616
[8] 67.04054 72.02563 73.93146 73.79780 70.95510 75.09803 73.59527
[15] 73.97577 75.09397 66.57626 74.82433 66.79269 67.26125
> colSums(tmp5)
[1] 1095.9812 746.0202 702.4780 740.0105 704.2696 730.6198 717.2616
[8] 670.4054 720.2563 739.3146 737.9780 709.5510 750.9803 735.9527
[15] 739.7577 750.9397 665.7626 748.2433 667.9269 672.6125
> colVars(tmp5)
[1] 16123.92454 102.53148 109.42499 72.27492 119.97406 29.31511
[7] 29.09139 51.54269 138.77694 15.27632 85.61784 53.11317
[13] 86.52665 79.00507 60.82676 34.46431 56.69967 68.91307
[19] 55.77412 76.11429
> colSd(tmp5)
[1] 126.980016 10.125783 10.460640 8.501466 10.953267 5.414343
[7] 5.393644 7.179324 11.780363 3.908493 9.252991 7.287878
[13] 9.301970 8.888479 7.799151 5.870631 7.529918 8.301389
[19] 7.468207 8.724350
> colMax(tmp5)
[1] 470.80288 88.18244 86.14056 83.90444 87.32402 81.64410 79.24926
[8] 78.19785 92.26113 80.40037 87.17713 80.49067 90.37187 84.47295
[15] 83.75041 85.61931 81.95512 87.56782 77.73837 85.51143
> colMin(tmp5)
[1] 60.78545 57.24252 58.71257 58.39268 54.44836 62.13997 61.68769 54.90485
[9] 56.39541 67.29469 63.39156 60.19637 63.59994 60.40595 58.56829 67.32467
[17] 54.82474 61.55395 55.92743 58.79641
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 91.50524 NA 71.90458 73.22752 70.06813 71.23188 74.36960 71.92451
[9] 70.32131 70.43218
> rowSums(tmp5)
[1] 1830.105 NA 1438.092 1464.550 1401.363 1424.638 1487.392 1438.490
[9] 1406.426 1408.644
> rowVars(tmp5)
[1] 8013.80571 51.98335 89.82853 62.12356 67.90027 70.52510
[7] 67.67233 89.95038 105.72122 57.62522
> rowSd(tmp5)
[1] 89.519862 7.209948 9.477792 7.881850 8.240162 8.397923 8.226319
[8] 9.484218 10.282082 7.591128
> rowMax(tmp5)
[1] 470.80288 NA 90.37187 86.14056 88.18244 86.80065 92.26113
[8] 87.17713 87.56782 80.49067
> rowMin(tmp5)
[1] 59.34874 NA 55.92743 62.51422 59.64107 54.44836 58.79641 54.90485
[9] 57.24252 57.17090
>
> colMeans(tmp5)
[1] 109.59812 74.60202 70.24780 74.00105 70.42696 73.06198 71.72616
[8] 67.04054 72.02563 73.93146 73.79780 70.95510 NA 73.59527
[15] 73.97577 75.09397 66.57626 74.82433 66.79269 67.26125
> colSums(tmp5)
[1] 1095.9812 746.0202 702.4780 740.0105 704.2696 730.6198 717.2616
[8] 670.4054 720.2563 739.3146 737.9780 709.5510 NA 735.9527
[15] 739.7577 750.9397 665.7626 748.2433 667.9269 672.6125
> colVars(tmp5)
[1] 16123.92454 102.53148 109.42499 72.27492 119.97406 29.31511
[7] 29.09139 51.54269 138.77694 15.27632 85.61784 53.11317
[13] NA 79.00507 60.82676 34.46431 56.69967 68.91307
[19] 55.77412 76.11429
> colSd(tmp5)
[1] 126.980016 10.125783 10.460640 8.501466 10.953267 5.414343
[7] 5.393644 7.179324 11.780363 3.908493 9.252991 7.287878
[13] NA 8.888479 7.799151 5.870631 7.529918 8.301389
[19] 7.468207 8.724350
> colMax(tmp5)
[1] 470.80288 88.18244 86.14056 83.90444 87.32402 81.64410 79.24926
[8] 78.19785 92.26113 80.40037 87.17713 80.49067 NA 84.47295
[15] 83.75041 85.61931 81.95512 87.56782 77.73837 85.51143
> colMin(tmp5)
[1] 60.78545 57.24252 58.71257 58.39268 54.44836 62.13997 61.68769 54.90485
[9] 56.39541 67.29469 63.39156 60.19637 NA 60.40595 58.56829 67.32467
[17] 54.82474 61.55395 55.92743 58.79641
>
> Max(tmp5,na.rm=TRUE)
[1] 470.8029
> Min(tmp5,na.rm=TRUE)
[1] 54.44836
> mean(tmp5,na.rm=TRUE)
[1] 73.70511
> Sum(tmp5,na.rm=TRUE)
[1] 14667.32
> Var(tmp5,na.rm=TRUE)
[1] 869.5899
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.50524 71.97991 71.90458 73.22752 70.06813 71.23188 74.36960 71.92451
[9] 70.32131 70.43218
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.105 1367.618 1438.092 1464.550 1401.363 1424.638 1487.392 1438.490
[9] 1406.426 1408.644
> rowVars(tmp5,na.rm=TRUE)
[1] 8013.80571 51.98335 89.82853 62.12356 67.90027 70.52510
[7] 67.67233 89.95038 105.72122 57.62522
> rowSd(tmp5,na.rm=TRUE)
[1] 89.519862 7.209948 9.477792 7.881850 8.240162 8.397923 8.226319
[8] 9.484218 10.282082 7.591128
> rowMax(tmp5,na.rm=TRUE)
[1] 470.80288 83.90150 90.37187 86.14056 88.18244 86.80065 92.26113
[8] 87.17713 87.56782 80.49067
> rowMin(tmp5,na.rm=TRUE)
[1] 59.34874 54.82474 55.92743 62.51422 59.64107 54.44836 58.79641 54.90485
[9] 57.24252 57.17090
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.59812 74.60202 70.24780 74.00105 70.42696 73.06198 71.72616
[8] 67.04054 72.02563 73.93146 73.79780 70.95510 74.66390 73.59527
[15] 73.97577 75.09397 66.57626 74.82433 66.79269 67.26125
> colSums(tmp5,na.rm=TRUE)
[1] 1095.9812 746.0202 702.4780 740.0105 704.2696 730.6198 717.2616
[8] 670.4054 720.2563 739.3146 737.9780 709.5510 671.9751 735.9527
[15] 739.7577 750.9397 665.7626 748.2433 667.9269 672.6125
> colVars(tmp5,na.rm=TRUE)
[1] 16123.92454 102.53148 109.42499 72.27492 119.97406 29.31511
[7] 29.09139 51.54269 138.77694 15.27632 85.61784 53.11317
[13] 95.22218 79.00507 60.82676 34.46431 56.69967 68.91307
[19] 55.77412 76.11429
> colSd(tmp5,na.rm=TRUE)
[1] 126.980016 10.125783 10.460640 8.501466 10.953267 5.414343
[7] 5.393644 7.179324 11.780363 3.908493 9.252991 7.287878
[13] 9.758185 8.888479 7.799151 5.870631 7.529918 8.301389
[19] 7.468207 8.724350
> colMax(tmp5,na.rm=TRUE)
[1] 470.80288 88.18244 86.14056 83.90444 87.32402 81.64410 79.24926
[8] 78.19785 92.26113 80.40037 87.17713 80.49067 90.37187 84.47295
[15] 83.75041 85.61931 81.95512 87.56782 77.73837 85.51143
> colMin(tmp5,na.rm=TRUE)
[1] 60.78545 57.24252 58.71257 58.39268 54.44836 62.13997 61.68769 54.90485
[9] 56.39541 67.29469 63.39156 60.19637 63.59994 60.40595 58.56829 67.32467
[17] 54.82474 61.55395 55.92743 58.79641
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.50524 NaN 71.90458 73.22752 70.06813 71.23188 74.36960 71.92451
[9] 70.32131 70.43218
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.105 0.000 1438.092 1464.550 1401.363 1424.638 1487.392 1438.490
[9] 1406.426 1408.644
> rowVars(tmp5,na.rm=TRUE)
[1] 8013.80571 NA 89.82853 62.12356 67.90027 70.52510
[7] 67.67233 89.95038 105.72122 57.62522
> rowSd(tmp5,na.rm=TRUE)
[1] 89.519862 NA 9.477792 7.881850 8.240162 8.397923 8.226319
[8] 9.484218 10.282082 7.591128
> rowMax(tmp5,na.rm=TRUE)
[1] 470.80288 NA 90.37187 86.14056 88.18244 86.80065 92.26113
[8] 87.17713 87.56782 80.49067
> rowMin(tmp5,na.rm=TRUE)
[1] 59.34874 NA 55.92743 62.51422 59.64107 54.44836 58.79641 54.90485
[9] 57.24252 57.17090
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.80475 76.14910 68.78347 73.59352 69.70868 73.07612 72.36740
[8] 65.89394 72.40622 74.21589 73.13505 71.05733 NaN 73.81843
[15] 73.87583 75.82658 67.88198 73.81576 66.53924 67.13107
> colSums(tmp5,na.rm=TRUE)
[1] 1024.2428 685.3419 619.0512 662.3417 627.3781 657.6851 651.3066
[8] 593.0455 651.6560 667.9430 658.2155 639.5160 0.0000 664.3659
[15] 664.8824 682.4392 610.9378 664.3418 598.8532 604.1797
> colVars(tmp5,na.rm=TRUE)
[1] 17940.33793 88.42163 98.97996 79.44083 129.16658 32.97725
[7] 28.10181 43.19520 154.49450 16.27570 91.37870 59.63475
[13] NA 88.32044 68.31772 32.73431 44.60684 66.08346
[19] 62.02323 85.43794
> colSd(tmp5,na.rm=TRUE)
[1] 133.941547 9.403278 9.948867 8.912959 11.365147 5.742582
[7] 5.301114 6.572306 12.429582 4.034316 9.559221 7.722354
[13] NA 9.397895 8.265453 5.721390 6.678835 8.129174
[19] 7.875483 9.243264
> colMax(tmp5,na.rm=TRUE)
[1] 470.80288 88.18244 86.14056 83.90444 87.32402 81.64410 79.24926
[8] 78.19785 92.26113 80.40037 87.17713 80.49067 -Inf 84.47295
[15] 83.75041 85.61931 81.95512 87.56782 77.73837 85.51143
> colMin(tmp5,na.rm=TRUE)
[1] 60.78545 57.24252 58.71257 58.39268 54.44836 62.13997 61.68769 54.90485
[9] 56.39541 67.29469 63.39156 60.19637 Inf 60.40595 58.56829 67.32467
[17] 58.16564 61.55395 55.92743 58.79641
>
>
>
>
> 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] 150.7370 136.8821 225.6740 228.5131 211.9329 196.0048 257.7979 364.1042
[9] 235.9471 170.7956
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 150.7370 136.8821 225.6740 228.5131 211.9329 196.0048 257.7979 364.1042
[9] 235.9471 170.7956
>
>
>
> 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] 5.684342e-14 2.842171e-14 8.526513e-14 2.273737e-13 8.526513e-14
[6] 1.705303e-13 -2.273737e-13 8.526513e-14 -2.842171e-14 2.842171e-14
[11] -1.421085e-14 1.705303e-13 0.000000e+00 5.684342e-14 2.842171e-14
[16] -1.989520e-13 1.705303e-13 -1.989520e-13 -5.684342e-14 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 12
10 20
10 18
2 6
8 20
7 9
1 13
1 2
5 15
9 3
4 1
1 9
6 13
7 5
5 15
9 11
5 17
2 12
9 17
3 18
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.113569
> Min(tmp)
[1] -3.181703
> mean(tmp)
[1] -0.1537554
> Sum(tmp)
[1] -15.37554
> Var(tmp)
[1] 1.230122
>
> rowMeans(tmp)
[1] -0.1537554
> rowSums(tmp)
[1] -15.37554
> rowVars(tmp)
[1] 1.230122
> rowSd(tmp)
[1] 1.109109
> rowMax(tmp)
[1] 2.113569
> rowMin(tmp)
[1] -3.181703
>
> colMeans(tmp)
[1] 2.01076743 -0.99037550 -0.74087193 0.69863652 -0.45365614 0.96367431
[7] -1.19402616 -0.01758947 -1.96123669 2.02373952 1.07077946 0.42189908
[13] -0.04788156 -0.06973509 0.72863937 -1.65819068 -0.55250731 0.92479713
[19] 0.86159150 -0.27349257 1.01701644 -1.37331530 -0.55295661 -1.35836485
[25] 1.10691872 -1.37850860 1.66156430 -1.11984106 -0.01509391 -0.70156935
[31] -1.65297396 -0.48172839 0.55955202 0.40111772 -0.28210183 -1.64972330
[37] 1.06624133 -2.82671245 1.97821321 -0.37252926 -1.31676502 -0.37324980
[43] -1.33827309 1.06138115 1.58831322 1.36112012 -0.10063037 -0.40145897
[49] -0.94125397 2.09199133 1.07174070 -0.44842186 -0.83120775 -1.10133815
[55] -0.47930625 -1.33190365 -0.25012542 -1.20394388 -0.40667736 -0.12788444
[61] 0.66581373 -0.55065985 -1.14523834 -0.90837908 -1.13022867 0.30854182
[67] -0.03197912 -0.18033173 -0.94819641 -3.18170325 -0.19352877 0.14238481
[73] 0.15630432 0.79534020 -1.49630502 2.11356860 -0.83156701 1.63398479
[79] -0.50466255 0.42237010 -1.01807196 -1.36314747 0.44657450 -1.40101004
[85] 1.16458122 -0.68786524 -1.58455041 1.76770343 0.10355480 -0.96844654
[91] 0.80697554 -1.06357204 1.22920456 -1.14263757 -0.41101769 0.73134844
[97] 0.91781113 0.32300558 -0.98203275 0.32825544
> colSums(tmp)
[1] 2.01076743 -0.99037550 -0.74087193 0.69863652 -0.45365614 0.96367431
[7] -1.19402616 -0.01758947 -1.96123669 2.02373952 1.07077946 0.42189908
[13] -0.04788156 -0.06973509 0.72863937 -1.65819068 -0.55250731 0.92479713
[19] 0.86159150 -0.27349257 1.01701644 -1.37331530 -0.55295661 -1.35836485
[25] 1.10691872 -1.37850860 1.66156430 -1.11984106 -0.01509391 -0.70156935
[31] -1.65297396 -0.48172839 0.55955202 0.40111772 -0.28210183 -1.64972330
[37] 1.06624133 -2.82671245 1.97821321 -0.37252926 -1.31676502 -0.37324980
[43] -1.33827309 1.06138115 1.58831322 1.36112012 -0.10063037 -0.40145897
[49] -0.94125397 2.09199133 1.07174070 -0.44842186 -0.83120775 -1.10133815
[55] -0.47930625 -1.33190365 -0.25012542 -1.20394388 -0.40667736 -0.12788444
[61] 0.66581373 -0.55065985 -1.14523834 -0.90837908 -1.13022867 0.30854182
[67] -0.03197912 -0.18033173 -0.94819641 -3.18170325 -0.19352877 0.14238481
[73] 0.15630432 0.79534020 -1.49630502 2.11356860 -0.83156701 1.63398479
[79] -0.50466255 0.42237010 -1.01807196 -1.36314747 0.44657450 -1.40101004
[85] 1.16458122 -0.68786524 -1.58455041 1.76770343 0.10355480 -0.96844654
[91] 0.80697554 -1.06357204 1.22920456 -1.14263757 -0.41101769 0.73134844
[97] 0.91781113 0.32300558 -0.98203275 0.32825544
> 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] 2.01076743 -0.99037550 -0.74087193 0.69863652 -0.45365614 0.96367431
[7] -1.19402616 -0.01758947 -1.96123669 2.02373952 1.07077946 0.42189908
[13] -0.04788156 -0.06973509 0.72863937 -1.65819068 -0.55250731 0.92479713
[19] 0.86159150 -0.27349257 1.01701644 -1.37331530 -0.55295661 -1.35836485
[25] 1.10691872 -1.37850860 1.66156430 -1.11984106 -0.01509391 -0.70156935
[31] -1.65297396 -0.48172839 0.55955202 0.40111772 -0.28210183 -1.64972330
[37] 1.06624133 -2.82671245 1.97821321 -0.37252926 -1.31676502 -0.37324980
[43] -1.33827309 1.06138115 1.58831322 1.36112012 -0.10063037 -0.40145897
[49] -0.94125397 2.09199133 1.07174070 -0.44842186 -0.83120775 -1.10133815
[55] -0.47930625 -1.33190365 -0.25012542 -1.20394388 -0.40667736 -0.12788444
[61] 0.66581373 -0.55065985 -1.14523834 -0.90837908 -1.13022867 0.30854182
[67] -0.03197912 -0.18033173 -0.94819641 -3.18170325 -0.19352877 0.14238481
[73] 0.15630432 0.79534020 -1.49630502 2.11356860 -0.83156701 1.63398479
[79] -0.50466255 0.42237010 -1.01807196 -1.36314747 0.44657450 -1.40101004
[85] 1.16458122 -0.68786524 -1.58455041 1.76770343 0.10355480 -0.96844654
[91] 0.80697554 -1.06357204 1.22920456 -1.14263757 -0.41101769 0.73134844
[97] 0.91781113 0.32300558 -0.98203275 0.32825544
> colMin(tmp)
[1] 2.01076743 -0.99037550 -0.74087193 0.69863652 -0.45365614 0.96367431
[7] -1.19402616 -0.01758947 -1.96123669 2.02373952 1.07077946 0.42189908
[13] -0.04788156 -0.06973509 0.72863937 -1.65819068 -0.55250731 0.92479713
[19] 0.86159150 -0.27349257 1.01701644 -1.37331530 -0.55295661 -1.35836485
[25] 1.10691872 -1.37850860 1.66156430 -1.11984106 -0.01509391 -0.70156935
[31] -1.65297396 -0.48172839 0.55955202 0.40111772 -0.28210183 -1.64972330
[37] 1.06624133 -2.82671245 1.97821321 -0.37252926 -1.31676502 -0.37324980
[43] -1.33827309 1.06138115 1.58831322 1.36112012 -0.10063037 -0.40145897
[49] -0.94125397 2.09199133 1.07174070 -0.44842186 -0.83120775 -1.10133815
[55] -0.47930625 -1.33190365 -0.25012542 -1.20394388 -0.40667736 -0.12788444
[61] 0.66581373 -0.55065985 -1.14523834 -0.90837908 -1.13022867 0.30854182
[67] -0.03197912 -0.18033173 -0.94819641 -3.18170325 -0.19352877 0.14238481
[73] 0.15630432 0.79534020 -1.49630502 2.11356860 -0.83156701 1.63398479
[79] -0.50466255 0.42237010 -1.01807196 -1.36314747 0.44657450 -1.40101004
[85] 1.16458122 -0.68786524 -1.58455041 1.76770343 0.10355480 -0.96844654
[91] 0.80697554 -1.06357204 1.22920456 -1.14263757 -0.41101769 0.73134844
[97] 0.91781113 0.32300558 -0.98203275 0.32825544
> colMedians(tmp)
[1] 2.01076743 -0.99037550 -0.74087193 0.69863652 -0.45365614 0.96367431
[7] -1.19402616 -0.01758947 -1.96123669 2.02373952 1.07077946 0.42189908
[13] -0.04788156 -0.06973509 0.72863937 -1.65819068 -0.55250731 0.92479713
[19] 0.86159150 -0.27349257 1.01701644 -1.37331530 -0.55295661 -1.35836485
[25] 1.10691872 -1.37850860 1.66156430 -1.11984106 -0.01509391 -0.70156935
[31] -1.65297396 -0.48172839 0.55955202 0.40111772 -0.28210183 -1.64972330
[37] 1.06624133 -2.82671245 1.97821321 -0.37252926 -1.31676502 -0.37324980
[43] -1.33827309 1.06138115 1.58831322 1.36112012 -0.10063037 -0.40145897
[49] -0.94125397 2.09199133 1.07174070 -0.44842186 -0.83120775 -1.10133815
[55] -0.47930625 -1.33190365 -0.25012542 -1.20394388 -0.40667736 -0.12788444
[61] 0.66581373 -0.55065985 -1.14523834 -0.90837908 -1.13022867 0.30854182
[67] -0.03197912 -0.18033173 -0.94819641 -3.18170325 -0.19352877 0.14238481
[73] 0.15630432 0.79534020 -1.49630502 2.11356860 -0.83156701 1.63398479
[79] -0.50466255 0.42237010 -1.01807196 -1.36314747 0.44657450 -1.40101004
[85] 1.16458122 -0.68786524 -1.58455041 1.76770343 0.10355480 -0.96844654
[91] 0.80697554 -1.06357204 1.22920456 -1.14263757 -0.41101769 0.73134844
[97] 0.91781113 0.32300558 -0.98203275 0.32825544
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 2.010767 -0.9903755 -0.7408719 0.6986365 -0.4536561 0.9636743 -1.194026
[2,] 2.010767 -0.9903755 -0.7408719 0.6986365 -0.4536561 0.9636743 -1.194026
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.01758947 -1.961237 2.02374 1.070779 0.4218991 -0.04788156 -0.06973509
[2,] -0.01758947 -1.961237 2.02374 1.070779 0.4218991 -0.04788156 -0.06973509
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.7286394 -1.658191 -0.5525073 0.9247971 0.8615915 -0.2734926 1.017016
[2,] 0.7286394 -1.658191 -0.5525073 0.9247971 0.8615915 -0.2734926 1.017016
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.373315 -0.5529566 -1.358365 1.106919 -1.378509 1.661564 -1.119841
[2,] -1.373315 -0.5529566 -1.358365 1.106919 -1.378509 1.661564 -1.119841
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.01509391 -0.7015693 -1.652974 -0.4817284 0.559552 0.4011177 -0.2821018
[2,] -0.01509391 -0.7015693 -1.652974 -0.4817284 0.559552 0.4011177 -0.2821018
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.649723 1.066241 -2.826712 1.978213 -0.3725293 -1.316765 -0.3732498
[2,] -1.649723 1.066241 -2.826712 1.978213 -0.3725293 -1.316765 -0.3732498
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.338273 1.061381 1.588313 1.36112 -0.1006304 -0.401459 -0.941254
[2,] -1.338273 1.061381 1.588313 1.36112 -0.1006304 -0.401459 -0.941254
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 2.091991 1.071741 -0.4484219 -0.8312078 -1.101338 -0.4793063 -1.331904
[2,] 2.091991 1.071741 -0.4484219 -0.8312078 -1.101338 -0.4793063 -1.331904
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.2501254 -1.203944 -0.4066774 -0.1278844 0.6658137 -0.5506599 -1.145238
[2,] -0.2501254 -1.203944 -0.4066774 -0.1278844 0.6658137 -0.5506599 -1.145238
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.9083791 -1.130229 0.3085418 -0.03197912 -0.1803317 -0.9481964 -3.181703
[2,] -0.9083791 -1.130229 0.3085418 -0.03197912 -0.1803317 -0.9481964 -3.181703
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.1935288 0.1423848 0.1563043 0.7953402 -1.496305 2.113569 -0.831567
[2,] -0.1935288 0.1423848 0.1563043 0.7953402 -1.496305 2.113569 -0.831567
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.633985 -0.5046626 0.4223701 -1.018072 -1.363147 0.4465745 -1.40101
[2,] 1.633985 -0.5046626 0.4223701 -1.018072 -1.363147 0.4465745 -1.40101
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.164581 -0.6878652 -1.58455 1.767703 0.1035548 -0.9684465 0.8069755
[2,] 1.164581 -0.6878652 -1.58455 1.767703 0.1035548 -0.9684465 0.8069755
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.063572 1.229205 -1.142638 -0.4110177 0.7313484 0.9178111 0.3230056
[2,] -1.063572 1.229205 -1.142638 -0.4110177 0.7313484 0.9178111 0.3230056
[,99] [,100]
[1,] -0.9820327 0.3282554
[2,] -0.9820327 0.3282554
>
>
> Max(tmp2)
[1] 2.137543
> Min(tmp2)
[1] -3.009053
> mean(tmp2)
[1] -0.06226064
> Sum(tmp2)
[1] -6.226064
> Var(tmp2)
[1] 1.016896
>
> rowMeans(tmp2)
[1] 0.32117884 -1.32974904 0.79312386 -0.96782936 -1.93655388 -0.58701279
[7] 0.46414868 -0.02830389 1.09887573 1.03557828 0.92579796 -0.36097434
[13] -0.18847454 -0.47516768 1.36840545 1.37806283 -0.31991131 -0.74405932
[19] 0.98563838 0.73197679 0.49996982 -1.75938644 -0.57902437 -0.21805873
[25] -0.24601350 -0.06660752 -1.08420896 1.06962659 -0.92820286 0.62784436
[31] 0.63840500 2.13754302 0.51554222 -0.79928276 -0.17603022 -0.25401437
[37] -1.48085458 -0.74372810 0.63526198 -0.33354428 -0.79899221 0.01822975
[43] 1.25329993 0.39068051 0.31605117 -0.38505034 -0.64766243 -3.00905317
[49] 0.31723803 1.49649644 -0.01278478 0.78806515 -1.47826430 0.90937698
[55] 0.06041783 1.61019657 -0.26747216 -0.24052526 1.04192087 -2.38984103
[61] 0.57883377 -0.58133734 -2.06992261 0.04681162 -0.90978580 -0.11556650
[67] 0.72565193 -2.05908241 -0.96075230 -0.13424793 -0.22885002 1.21576520
[73] 0.17268469 0.10885053 -0.75215015 -1.16247847 0.83680745 0.34240447
[79] -2.35627706 -0.67060686 0.63443091 1.09402392 -0.55198897 -0.26069103
[85] 1.18353385 -1.12601828 -1.28209652 0.97657724 0.18729779 1.88448672
[91] 0.38038792 0.12875235 -0.19264043 -1.95820005 1.25627801 1.11063387
[97] -0.31625386 0.04841835 0.16973067 -0.21179282
> rowSums(tmp2)
[1] 0.32117884 -1.32974904 0.79312386 -0.96782936 -1.93655388 -0.58701279
[7] 0.46414868 -0.02830389 1.09887573 1.03557828 0.92579796 -0.36097434
[13] -0.18847454 -0.47516768 1.36840545 1.37806283 -0.31991131 -0.74405932
[19] 0.98563838 0.73197679 0.49996982 -1.75938644 -0.57902437 -0.21805873
[25] -0.24601350 -0.06660752 -1.08420896 1.06962659 -0.92820286 0.62784436
[31] 0.63840500 2.13754302 0.51554222 -0.79928276 -0.17603022 -0.25401437
[37] -1.48085458 -0.74372810 0.63526198 -0.33354428 -0.79899221 0.01822975
[43] 1.25329993 0.39068051 0.31605117 -0.38505034 -0.64766243 -3.00905317
[49] 0.31723803 1.49649644 -0.01278478 0.78806515 -1.47826430 0.90937698
[55] 0.06041783 1.61019657 -0.26747216 -0.24052526 1.04192087 -2.38984103
[61] 0.57883377 -0.58133734 -2.06992261 0.04681162 -0.90978580 -0.11556650
[67] 0.72565193 -2.05908241 -0.96075230 -0.13424793 -0.22885002 1.21576520
[73] 0.17268469 0.10885053 -0.75215015 -1.16247847 0.83680745 0.34240447
[79] -2.35627706 -0.67060686 0.63443091 1.09402392 -0.55198897 -0.26069103
[85] 1.18353385 -1.12601828 -1.28209652 0.97657724 0.18729779 1.88448672
[91] 0.38038792 0.12875235 -0.19264043 -1.95820005 1.25627801 1.11063387
[97] -0.31625386 0.04841835 0.16973067 -0.21179282
> 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] 0.32117884 -1.32974904 0.79312386 -0.96782936 -1.93655388 -0.58701279
[7] 0.46414868 -0.02830389 1.09887573 1.03557828 0.92579796 -0.36097434
[13] -0.18847454 -0.47516768 1.36840545 1.37806283 -0.31991131 -0.74405932
[19] 0.98563838 0.73197679 0.49996982 -1.75938644 -0.57902437 -0.21805873
[25] -0.24601350 -0.06660752 -1.08420896 1.06962659 -0.92820286 0.62784436
[31] 0.63840500 2.13754302 0.51554222 -0.79928276 -0.17603022 -0.25401437
[37] -1.48085458 -0.74372810 0.63526198 -0.33354428 -0.79899221 0.01822975
[43] 1.25329993 0.39068051 0.31605117 -0.38505034 -0.64766243 -3.00905317
[49] 0.31723803 1.49649644 -0.01278478 0.78806515 -1.47826430 0.90937698
[55] 0.06041783 1.61019657 -0.26747216 -0.24052526 1.04192087 -2.38984103
[61] 0.57883377 -0.58133734 -2.06992261 0.04681162 -0.90978580 -0.11556650
[67] 0.72565193 -2.05908241 -0.96075230 -0.13424793 -0.22885002 1.21576520
[73] 0.17268469 0.10885053 -0.75215015 -1.16247847 0.83680745 0.34240447
[79] -2.35627706 -0.67060686 0.63443091 1.09402392 -0.55198897 -0.26069103
[85] 1.18353385 -1.12601828 -1.28209652 0.97657724 0.18729779 1.88448672
[91] 0.38038792 0.12875235 -0.19264043 -1.95820005 1.25627801 1.11063387
[97] -0.31625386 0.04841835 0.16973067 -0.21179282
> rowMin(tmp2)
[1] 0.32117884 -1.32974904 0.79312386 -0.96782936 -1.93655388 -0.58701279
[7] 0.46414868 -0.02830389 1.09887573 1.03557828 0.92579796 -0.36097434
[13] -0.18847454 -0.47516768 1.36840545 1.37806283 -0.31991131 -0.74405932
[19] 0.98563838 0.73197679 0.49996982 -1.75938644 -0.57902437 -0.21805873
[25] -0.24601350 -0.06660752 -1.08420896 1.06962659 -0.92820286 0.62784436
[31] 0.63840500 2.13754302 0.51554222 -0.79928276 -0.17603022 -0.25401437
[37] -1.48085458 -0.74372810 0.63526198 -0.33354428 -0.79899221 0.01822975
[43] 1.25329993 0.39068051 0.31605117 -0.38505034 -0.64766243 -3.00905317
[49] 0.31723803 1.49649644 -0.01278478 0.78806515 -1.47826430 0.90937698
[55] 0.06041783 1.61019657 -0.26747216 -0.24052526 1.04192087 -2.38984103
[61] 0.57883377 -0.58133734 -2.06992261 0.04681162 -0.90978580 -0.11556650
[67] 0.72565193 -2.05908241 -0.96075230 -0.13424793 -0.22885002 1.21576520
[73] 0.17268469 0.10885053 -0.75215015 -1.16247847 0.83680745 0.34240447
[79] -2.35627706 -0.67060686 0.63443091 1.09402392 -0.55198897 -0.26069103
[85] 1.18353385 -1.12601828 -1.28209652 0.97657724 0.18729779 1.88448672
[91] 0.38038792 0.12875235 -0.19264043 -1.95820005 1.25627801 1.11063387
[97] -0.31625386 0.04841835 0.16973067 -0.21179282
>
> colMeans(tmp2)
[1] -0.06226064
> colSums(tmp2)
[1] -6.226064
> colVars(tmp2)
[1] 1.016896
> colSd(tmp2)
[1] 1.008413
> colMax(tmp2)
[1] 2.137543
> colMin(tmp2)
[1] -3.009053
> colMedians(tmp2)
[1] -0.04745571
> colRanges(tmp2)
[,1]
[1,] -3.009053
[2,] 2.137543
>
> 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] -0.1012467 -2.8113269 -3.3636574 1.8967943 2.7009508 -4.3400508
[7] -0.6376558 -1.6932159 -0.2264719 -3.9016810
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8871516
[2,] -0.6133243
[3,] -0.2734723
[4,] 0.9834612
[5,] 1.3937705
>
> rowApply(tmp,sum)
[1] 0.8349821 1.4096417 -6.5512155 -3.4722596 -5.2788070 1.7407325
[7] -1.7961212 -3.0491305 0.3206192 3.3639968
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 3 7 1 4 7 8 5 8 10
[2,] 9 10 9 6 2 4 5 3 1 7
[3,] 8 5 2 2 9 6 2 6 4 3
[4,] 5 8 10 9 1 3 9 10 6 2
[5,] 10 6 5 8 10 10 1 9 5 4
[6,] 4 7 3 3 5 1 6 4 9 1
[7,] 1 9 6 5 3 8 4 7 10 6
[8,] 2 4 1 7 7 9 3 8 3 8
[9,] 7 1 4 10 8 2 10 2 7 9
[10,] 6 2 8 4 6 5 7 1 2 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.4409226 -3.4102080 -2.2343109 -2.6598543 -0.1069452 -2.3532181
[7] 1.5653269 -1.0440355 3.5465169 -6.0077273 1.2817692 -0.5842910
[13] 4.5234743 1.3480646 3.5112766 -1.3556230 -0.1583317 -2.3739855
[19] -2.3295166 3.5657844
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.7924701
[2,] -0.6304943
[3,] -0.2387576
[4,] -0.2038283
[5,] 0.4246276
>
> rowApply(tmp,sum)
[1] -2.3013599 -2.3017810 1.4625884 -6.2737060 0.6975018
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 1 3 10 8
[2,] 6 7 7 7 4
[3,] 2 9 5 17 5
[4,] 4 20 11 6 2
[5,] 14 16 16 8 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.4246276 -0.9828662 -1.4060708 -1.2012225 0.3946271 -1.51640326
[2,] -2.7924701 -0.2220070 -0.1935059 1.3003815 0.5591025 -0.49517440
[3,] -0.6304943 -0.2265098 -0.4281745 0.1523335 0.8817743 0.15936634
[4,] -0.2038283 -0.8316083 0.2381997 -0.8914767 -0.5850964 -0.08355835
[5,] -0.2387576 -1.1472168 -0.4447595 -2.0198701 -1.3573527 -0.41744843
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3053447 -0.6686798 0.74506299 0.7479314 1.7599209 -0.11880338
[2,] 0.5269256 -0.6057469 1.26752560 -0.4514642 -1.3350134 0.11791310
[3,] 0.2190549 1.0675674 1.04771859 -3.0304890 -1.1008516 -0.41358330
[4,] -1.2843823 -1.0955884 -0.01829792 -1.0219621 1.2260949 -0.18359428
[5,] 1.7983840 0.2584123 0.50450767 -2.2517434 0.7316184 0.01377689
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.2332236 1.1057568 0.67537187 -1.13678018 -1.24769779 -0.45813155
[2,] 1.0323957 -0.1510011 -0.21408347 -0.02100901 0.80071482 0.37871436
[3,] 1.5818727 0.3428255 1.64229597 -0.12800661 -0.05003586 0.02446633
[4,] 0.9200334 -1.3051845 -0.05865669 -0.09088661 -0.37054776 -2.11167810
[5,] 0.7559489 1.3556678 1.46634891 0.02105938 0.70923493 -0.20735652
[,19] [,20]
[1,] 0.2034563 -0.1600278
[2,] -1.9299103 0.1259316
[3,] -0.4518710 0.8033288
[4,] 0.1043946 1.3739181
[5,] -0.2555861 1.4226337
>
>
> 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 : 652 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 : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.016586 1.101539 1.44765 0.0228922 0.1272716 1.809765 0.01610853
col8 col9 col10 col11 col12 col13 col14
row1 -0.3521795 -0.7910494 0.3974301 0.5147357 -1.173797 0.3740616 -1.579122
col15 col16 col17 col18 col19 col20
row1 1.035831 -0.9630571 0.1440584 -0.9143906 1.167858 -0.2721451
> tmp[,"col10"]
col10
row1 0.3974301
row2 -1.2246475
row3 1.2501578
row4 1.1076697
row5 0.3880257
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.016586 1.101539 1.44764961 0.0228922 0.1272716 1.809765 0.01610853
row5 1.055959 -1.144489 0.04356359 1.9398654 -1.6752522 1.478601 -1.99257176
col8 col9 col10 col11 col12 col13 col14
row1 -0.3521795 -0.7910494 0.3974301 0.5147357 -1.1737968 0.3740616 -1.5791218
row5 0.1205820 -0.1644459 0.3880257 -0.2025430 0.7070806 0.3352173 0.2837674
col15 col16 col17 col18 col19 col20
row1 1.0358312 -0.9630571 0.1440584 -0.9143906 1.1678584 -0.2721451
row5 0.7433654 -1.0637318 -0.7189535 -0.6610357 0.8109396 0.3112873
> tmp[,c("col6","col20")]
col6 col20
row1 1.8097647 -0.2721451
row2 0.1305559 0.6749152
row3 0.6199892 0.6520486
row4 0.2138633 -0.6575120
row5 1.4786011 0.3112873
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.809765 -0.2721451
row5 1.478601 0.3112873
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.61275 50.72128 50.0943 49.53707 50.18986 105.7129 50.64352 50.28995
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.33275 51.39193 49.08237 49.09616 49.92584 49.60756 51.39729 48.98978
col17 col18 col19 col20
row1 50.98428 49.16285 48.97629 103.7379
> tmp[,"col10"]
col10
row1 51.39193
row2 29.51596
row3 30.18601
row4 30.64443
row5 49.82895
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.61275 50.72128 50.09430 49.53707 50.18986 105.7129 50.64352 50.28995
row5 49.32831 49.68409 49.27776 50.09250 49.27394 107.2038 51.83031 50.19555
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.33275 51.39193 49.08237 49.09616 49.92584 49.60756 51.39729 48.98978
row5 49.19308 49.82895 50.62512 50.22839 49.59923 49.57542 50.17368 49.66874
col17 col18 col19 col20
row1 50.98428 49.16285 48.97629 103.7379
row5 50.91977 47.60489 50.79458 103.3198
> tmp[,c("col6","col20")]
col6 col20
row1 105.71289 103.73787
row2 74.21785 74.66203
row3 77.45710 76.01015
row4 74.46076 76.84967
row5 107.20385 103.31981
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7129 103.7379
row5 107.2038 103.3198
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7129 103.7379
row5 107.2038 103.3198
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.5079570
[2,] 0.4765293
[3,] -1.0740947
[4,] 0.9645413
[5,] -0.1411010
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.09275220 2.561878907
[2,] 0.44018481 0.001552076
[3,] -0.98160739 -0.267766825
[4,] -0.11046618 -0.960084249
[5,] 0.08641224 1.144495049
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.0574365 0.7356632
[2,] -0.9072751 0.5289106
[3,] 0.8741734 2.7249135
[4,] 0.7885327 -1.2553849
[5,] -0.9531069 0.8169506
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.0574365
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.0574365
[2,] -0.9072751
>
>
>
> 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 -0.2839706 -0.8349535 0.6320334 -1.961220 0.6073529 -0.5364506 0.5138990
row1 -0.5819867 1.2832663 -0.3479783 1.282305 0.2857541 -1.0646614 -0.1937374
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.7305341 0.4024405 2.60392 -2.086410 0.6514859 -1.609030 -0.3414338
row1 0.3381243 0.8158346 1.23161 1.323312 -2.8509503 -1.441998 1.1474235
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.4966891 0.1243019 1.0196623 1.9227335 -0.06060688 0.2345431
row1 -0.6593735 -1.9698845 0.9730717 -0.8892687 -0.76244317 0.3498569
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.657089 1.400101 2.118565 0.05525471 -0.6562842 0.1200401 -0.7727732
[,8] [,9] [,10]
row2 -0.6455745 -0.5773287 1.199512
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.09069901 0.996842 -0.1327068 1.246262 1.791146 2.795608 -2.651795
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.8211542 0.6668418 0.2191855 0.9639455 -0.1107349 0.9855662 2.672945
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.03199358 0.4817515 1.311897 -1.280799 -0.598829 -0.1520593
>
>
> 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: 0x15d749a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe6d3f76d8"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe6786c3b31"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe6f2e08aa"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe61bc64bb9"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe647d275c5"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe6583c4d15"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe64cd6cb81"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe62efc7839"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe635d3f732"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe631cb1b4f"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe6498e7628"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe64ac599c5"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe639f1ae5a"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe678759ec5"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a5fe660fcf475"
>
>
> ### 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: 0x170a98e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x170a98e0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x170a98e0>
> rowMedians(tmp)
[1] -0.3809444565 -0.0648410098 -0.0604371650 -0.2920883011 -0.1681281990
[6] -0.3378240820 0.3754118356 -0.0125402564 -0.2202576644 -0.1904908355
[11] 0.1330096402 0.4001097775 -0.5972328407 0.3290559897 -0.1656191366
[16] 0.0700855727 0.4840369901 0.7508844808 -0.1483315008 0.2384267507
[21] 0.2027097048 -1.1219681494 0.0580131641 0.5252242300 0.8046386575
[26] 0.3824856676 0.0923486451 -0.1816408940 0.8656772672 0.0508520084
[31] 0.5724190633 0.1505102396 0.1554614550 -0.1894201651 -0.2428428958
[36] 0.3448822398 0.3038217003 -0.1285646894 -0.1310467559 0.1015421314
[41] -0.0688071123 0.1192836768 0.0403957916 -0.3407663271 0.4008164488
[46] -0.2472841029 0.0634053631 0.5105826026 -0.2130255032 -0.4381788750
[51] -0.3499492173 0.2030701541 -0.0423151501 -0.2086911888 0.1244928311
[56] 0.3902108578 0.3811963517 -0.2831001142 -0.2219570438 0.3804578888
[61] 0.1705070015 0.3228655015 -0.0637414279 0.0606913412 -0.1130597447
[66] -0.0170639994 -0.0254830761 -0.1445562047 0.2924015623 -0.0636448138
[71] 0.0187640168 -0.1816869297 0.2584724835 -0.0291515527 -0.2133956871
[76] -0.3621783402 0.3031936339 0.1773469985 -0.2902925637 0.5102232996
[81] -1.0585676877 -0.5760330170 0.5967823347 0.2443779133 -0.3879887986
[86] 0.2680145607 -0.5434658069 -0.0156464185 0.1735889210 0.0581327141
[91] -0.5070418239 0.2075976511 -0.1420123502 0.7000878257 0.0015366154
[96] 0.1181536655 0.3725921727 -0.0076426598 -0.0603171610 -0.1448167448
[101] 0.1304371203 -0.2564032130 -0.0050383713 0.3586317248 0.0087123947
[106] 0.1094986009 -0.5035999004 -0.6028383863 0.0323478693 0.6903044291
[111] -0.5719657998 -0.4170510096 0.0588981657 0.0132978872 -0.2247267840
[116] -0.0859425254 0.0616490725 0.1254253562 0.5124148409 0.4333912401
[121] 0.3830638690 0.1309883463 -0.3831870445 -0.3248705214 -0.0376830665
[126] 0.1170977224 0.3528686660 0.0459378811 0.1796504909 0.2236108716
[131] -0.0655488999 -0.2328907234 0.2175320515 -0.1746369457 -0.4417212127
[136] 0.2454038941 0.1729470400 -0.3015689676 0.1374962107 -0.1586607687
[141] -0.2160684062 0.5570281343 0.1851834707 0.2097129251 -0.1015998389
[146] -0.2328925944 -0.5042310025 0.3103905574 -0.4100101570 0.1748324382
[151] -0.0360579928 0.2195103053 0.4371271057 -0.3957848591 -0.0636019155
[156] 0.3854247390 -0.3054037038 0.4083414034 -0.1427966007 0.2686246000
[161] -0.3708577917 0.1352618618 -0.0879163029 -0.6847894127 0.1707493483
[166] -0.0429751505 0.7018223606 0.4282066950 -0.2112052315 -0.0997784591
[171] 0.2347732293 0.4796572016 -0.0015132694 -0.1323661457 -0.4955456299
[176] 0.3101667464 -0.4600860568 -0.3682753716 -0.1363501469 -0.0379609073
[181] 0.3372849679 -0.2604483350 0.2686312718 -0.3952503514 -0.2365094572
[186] 0.4523698407 0.0473324393 0.3324449237 0.0916160576 0.0390185606
[191] 0.0617586626 -0.4201008485 -0.3808138597 -0.2814748946 0.3926467657
[196] -0.1705088870 0.4890862707 0.3972904270 0.3538639253 -0.2974016782
[201] -0.3124123174 0.0792773075 -0.0102454998 0.1041068505 -0.1091171679
[206] -0.2465930746 -0.0874572922 0.7463414317 -0.0338141216 -0.1858617167
[211] 0.4654513664 -0.1464001697 -0.2422738684 0.1884393050 -0.0278557844
[216] 0.3925116164 -0.0114319780 0.1703794923 -0.0048059756 -0.5609712297
[221] -0.1823939209 0.0072055698 -0.4404196601 0.3138169960 0.0953149892
[226] -0.0006781436 -0.3465691581 -0.1951793588 -0.0004839753 0.0889905332
>
> proc.time()
user system elapsed
1.811 0.964 2.801
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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: 0x2f38fff0>
> .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: 0x2f38fff0>
> .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: 0x2f38fff0>
> .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: 0x2f38fff0>
> 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: 0x2f2750e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2f2750e0>
> .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: 0x2f2750e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2f2750e0>
> .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: 0x2f2750e0>
> 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: 0x2e1fc520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2e1fc520>
> .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: 0x2e1fc520>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2e1fc520>
> .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: 0x2e1fc520>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x2e1fc520>
> .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: 0x2e1fc520>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x2e1fc520>
> .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: 0x2e1fc520>
> 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: 0x2dc00720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x2dc00720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2dc00720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2dc00720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1a61336370fb3e" "BufferedMatrixFile1a61337ccdd5f0"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1a61336370fb3e" "BufferedMatrixFile1a61337ccdd5f0"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x2eaf07d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2eaf07d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2eaf07d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2eaf07d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x2eaf07d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x2eaf07d0>
> .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: 0x2ebf7c90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2ebf7c90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2ebf7c90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x2ebf7c90>
> 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: 0x2fea0110>
> .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: 0x2fea0110>
> rm(P)
>
> proc.time()
user system elapsed
0.339 0.053 0.377
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.320 0.052 0.358