Ben Bolstad
| Snapshot Date: 2025-11-20 15:01 -0500 (Thu, 20 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 2025-11-24 12:07 -0500 (Mon, 24 Nov 2025).
| 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" | 4873 |
| merida1 | macOS 12.7.6 Monterey | x86_64 | 4.5.2 Patched (2025-11-05 r88990) -- "[Not] Part in a Rumble" | 4654 |
| kjohnson1 | macOS 13.7.5 Ventura | arm64 | 4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble" | 4600 |
| 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 | | ||||||||
| merida1 | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.7.5 Ventura / arm64 | OK | OK | WARNINGS | 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: 2025-11-21 08:35:50 -0000 (Fri, 21 Nov 2025) |
| EndedAt: 2025-11-21 08:36:20 -0000 (Fri, 21 Nov 2025) |
| EllapsedTime: 30.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### 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
0.349 0.028 0.361
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 Nov 21 08:36:14 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 21 08:36:14 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: 0xd7cdff0>
>
>
>
> 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 21 08:36:14 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 21 08:36:15 2025"
>
> ColMode(tmp2)
<pointer: 0xd7cdff0>
>
>
>
> ### 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,] 100.1750337 -1.008974019 0.9289808 -0.1841220
[2,] -2.9968996 0.013643211 0.4843183 -0.3346746
[3,] -1.3830370 0.005329865 -1.6987045 -1.7593674
[4,] -0.8034185 -1.032506406 0.6607917 -0.3942604
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.1750337 1.008974019 0.9289808 0.1841220
[2,] 2.9968996 0.013643211 0.4843183 0.3346746
[3,] 1.3830370 0.005329865 1.6987045 1.7593674
[4,] 0.8034185 1.032506406 0.6607917 0.3942604
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0087479 1.00447699 0.9638365 0.4290944
[2,] 1.7311556 0.11680416 0.6959298 0.5785107
[3,] 1.1760260 0.07300592 1.3033436 1.3264115
[4,] 0.8963362 1.01612322 0.8128909 0.6279016
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.26251 36.05374 35.56735 29.47507
[2,] 45.30846 26.18168 32.44362 31.11978
[3,] 38.14330 25.73539 39.73214 40.02348
[4,] 34.76678 36.19374 33.78970 31.67328
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xc4b06c0>
> exp(tmp5)
<pointer: 0xc4b06c0>
> log(tmp5,2)
<pointer: 0xc4b06c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.8544
> Min(tmp5)
[1] 53.08342
> mean(tmp5)
[1] 73.18538
> Sum(tmp5)
[1] 14637.08
> Var(tmp5)
[1] 871.1552
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.75901 68.93979 74.15303 69.40497 73.35489 74.72791 71.70275 70.73926
[9] 68.56923 72.50295
> rowSums(tmp5)
[1] 1755.180 1378.796 1483.061 1388.099 1467.098 1494.558 1434.055 1414.785
[9] 1371.385 1450.059
> rowVars(tmp5)
[1] 8114.76019 89.38338 98.15275 95.51631 71.85153 39.48834
[7] 85.26438 82.19380 62.22458 92.72900
> rowSd(tmp5)
[1] 90.081964 9.454279 9.907207 9.773244 8.476528 6.283975 9.233872
[8] 9.066080 7.888256 9.629590
> rowMax(tmp5)
[1] 468.85441 94.30361 91.08182 91.59610 86.40257 83.22225 88.44179
[8] 90.94006 85.80218 85.24062
> rowMin(tmp5)
[1] 55.24439 54.49375 53.56484 53.08342 59.55102 59.79248 56.12187 57.71246
[9] 54.21713 55.11358
>
> colMeans(tmp5)
[1] 114.42320 66.85929 71.45220 64.18395 67.88289 68.49990 75.61662
[8] 67.60285 72.20062 68.75519 73.24436 69.01857 67.70291 71.76175
[15] 73.82800 74.30015 72.59225 75.54817 72.33199 75.90274
> colSums(tmp5)
[1] 1144.2320 668.5929 714.5220 641.8395 678.8289 684.9990 756.1662
[8] 676.0285 722.0062 687.5519 732.4436 690.1857 677.0291 717.6175
[15] 738.2800 743.0015 725.9225 755.4817 723.3199 759.0274
> colVars(tmp5)
[1] 15640.77156 87.57568 107.82693 67.91334 35.13309 53.09126
[7] 106.33870 53.09592 107.49713 109.87154 73.15348 48.53333
[13] 36.04990 72.24405 112.87602 69.29636 91.77323 28.06713
[19] 76.51974 65.13428
> colSd(tmp5)
[1] 125.063070 9.358188 10.383975 8.240955 5.927318 7.286375
[7] 10.312066 7.286694 10.368082 10.481963 8.552981 6.966586
[13] 6.004157 8.499650 10.624313 8.324444 9.579834 5.297842
[19] 8.747556 8.070581
> colMax(tmp5)
[1] 468.85441 76.16007 84.39329 83.30363 76.34685 81.55283 91.59610
[8] 81.21285 87.23580 84.74850 84.54152 77.38865 75.44386 86.40257
[15] 82.96045 85.80218 90.94006 84.94697 88.44179 91.08182
> colMin(tmp5)
[1] 56.12187 53.56484 55.59262 55.11358 58.02824 61.09104 59.75491 57.71638
[9] 55.24439 55.53931 60.28062 57.33169 59.60779 59.43119 55.41371 63.13525
[17] 53.08342 69.07493 63.36184 61.81983
>
>
> ### 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] 87.75901 68.93979 74.15303 NA 73.35489 74.72791 71.70275 70.73926
[9] 68.56923 72.50295
> rowSums(tmp5)
[1] 1755.180 1378.796 1483.061 NA 1467.098 1494.558 1434.055 1414.785
[9] 1371.385 1450.059
> rowVars(tmp5)
[1] 8114.76019 89.38338 98.15275 99.27420 71.85153 39.48834
[7] 85.26438 82.19380 62.22458 92.72900
> rowSd(tmp5)
[1] 90.081964 9.454279 9.907207 9.963644 8.476528 6.283975 9.233872
[8] 9.066080 7.888256 9.629590
> rowMax(tmp5)
[1] 468.85441 94.30361 91.08182 NA 86.40257 83.22225 88.44179
[8] 90.94006 85.80218 85.24062
> rowMin(tmp5)
[1] 55.24439 54.49375 53.56484 NA 59.55102 59.79248 56.12187 57.71246
[9] 54.21713 55.11358
>
> colMeans(tmp5)
[1] 114.42320 66.85929 71.45220 64.18395 67.88289 68.49990 75.61662
[8] 67.60285 72.20062 68.75519 73.24436 69.01857 NA 71.76175
[15] 73.82800 74.30015 72.59225 75.54817 72.33199 75.90274
> colSums(tmp5)
[1] 1144.2320 668.5929 714.5220 641.8395 678.8289 684.9990 756.1662
[8] 676.0285 722.0062 687.5519 732.4436 690.1857 NA 717.6175
[15] 738.2800 743.0015 725.9225 755.4817 723.3199 759.0274
> colVars(tmp5)
[1] 15640.77156 87.57568 107.82693 67.91334 35.13309 53.09126
[7] 106.33870 53.09592 107.49713 109.87154 73.15348 48.53333
[13] NA 72.24405 112.87602 69.29636 91.77323 28.06713
[19] 76.51974 65.13428
> colSd(tmp5)
[1] 125.063070 9.358188 10.383975 8.240955 5.927318 7.286375
[7] 10.312066 7.286694 10.368082 10.481963 8.552981 6.966586
[13] NA 8.499650 10.624313 8.324444 9.579834 5.297842
[19] 8.747556 8.070581
> colMax(tmp5)
[1] 468.85441 76.16007 84.39329 83.30363 76.34685 81.55283 91.59610
[8] 81.21285 87.23580 84.74850 84.54152 77.38865 NA 86.40257
[15] 82.96045 85.80218 90.94006 84.94697 88.44179 91.08182
> colMin(tmp5)
[1] 56.12187 53.56484 55.59262 55.11358 58.02824 61.09104 59.75491 57.71638
[9] 55.24439 55.53931 60.28062 57.33169 NA 59.43119 55.41371 63.13525
[17] 53.08342 69.07493 63.36184 61.81983
>
> Max(tmp5,na.rm=TRUE)
[1] 468.8544
> Min(tmp5,na.rm=TRUE)
[1] 53.08342
> mean(tmp5,na.rm=TRUE)
[1] 73.23023
> Sum(tmp5,na.rm=TRUE)
[1] 14572.82
> Var(tmp5,na.rm=TRUE)
[1] 875.1505
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.75901 68.93979 74.15303 69.67581 73.35489 74.72791 71.70275 70.73926
[9] 68.56923 72.50295
> rowSums(tmp5,na.rm=TRUE)
[1] 1755.180 1378.796 1483.061 1323.840 1467.098 1494.558 1434.055 1414.785
[9] 1371.385 1450.059
> rowVars(tmp5,na.rm=TRUE)
[1] 8114.76019 89.38338 98.15275 99.27420 71.85153 39.48834
[7] 85.26438 82.19380 62.22458 92.72900
> rowSd(tmp5,na.rm=TRUE)
[1] 90.081964 9.454279 9.907207 9.963644 8.476528 6.283975 9.233872
[8] 9.066080 7.888256 9.629590
> rowMax(tmp5,na.rm=TRUE)
[1] 468.85441 94.30361 91.08182 91.59610 86.40257 83.22225 88.44179
[8] 90.94006 85.80218 85.24062
> rowMin(tmp5,na.rm=TRUE)
[1] 55.24439 54.49375 53.56484 53.08342 59.55102 59.79248 56.12187 57.71246
[9] 54.21713 55.11358
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.42320 66.85929 71.45220 64.18395 67.88289 68.49990 75.61662
[8] 67.60285 72.20062 68.75519 73.24436 69.01857 68.08557 71.76175
[15] 73.82800 74.30015 72.59225 75.54817 72.33199 75.90274
> colSums(tmp5,na.rm=TRUE)
[1] 1144.2320 668.5929 714.5220 641.8395 678.8289 684.9990 756.1662
[8] 676.0285 722.0062 687.5519 732.4436 690.1857 612.7701 717.6175
[15] 738.2800 743.0015 725.9225 755.4817 723.3199 759.0274
> colVars(tmp5,na.rm=TRUE)
[1] 15640.77156 87.57568 107.82693 67.91334 35.13309 53.09126
[7] 106.33870 53.09592 107.49713 109.87154 73.15348 48.53333
[13] 38.90889 72.24405 112.87602 69.29636 91.77323 28.06713
[19] 76.51974 65.13428
> colSd(tmp5,na.rm=TRUE)
[1] 125.063070 9.358188 10.383975 8.240955 5.927318 7.286375
[7] 10.312066 7.286694 10.368082 10.481963 8.552981 6.966586
[13] 6.237699 8.499650 10.624313 8.324444 9.579834 5.297842
[19] 8.747556 8.070581
> colMax(tmp5,na.rm=TRUE)
[1] 468.85441 76.16007 84.39329 83.30363 76.34685 81.55283 91.59610
[8] 81.21285 87.23580 84.74850 84.54152 77.38865 75.44386 86.40257
[15] 82.96045 85.80218 90.94006 84.94697 88.44179 91.08182
> colMin(tmp5,na.rm=TRUE)
[1] 56.12187 53.56484 55.59262 55.11358 58.02824 61.09104 59.75491 57.71638
[9] 55.24439 55.53931 60.28062 57.33169 59.60779 59.43119 55.41371 63.13525
[17] 53.08342 69.07493 63.36184 61.81983
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.75901 68.93979 74.15303 NaN 73.35489 74.72791 71.70275 70.73926
[9] 68.56923 72.50295
> rowSums(tmp5,na.rm=TRUE)
[1] 1755.180 1378.796 1483.061 0.000 1467.098 1494.558 1434.055 1414.785
[9] 1371.385 1450.059
> rowVars(tmp5,na.rm=TRUE)
[1] 8114.76019 89.38338 98.15275 NA 71.85153 39.48834
[7] 85.26438 82.19380 62.22458 92.72900
> rowSd(tmp5,na.rm=TRUE)
[1] 90.081964 9.454279 9.907207 NA 8.476528 6.283975 9.233872
[8] 9.066080 7.888256 9.629590
> rowMax(tmp5,na.rm=TRUE)
[1] 468.85441 94.30361 91.08182 NA 86.40257 83.22225 88.44179
[8] 90.94006 85.80218 85.24062
> rowMin(tmp5,na.rm=TRUE)
[1] 55.24439 54.49375 53.56484 NA 59.55102 59.79248 56.12187 57.71246
[9] 54.21713 55.11358
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 119.09661 65.91782 71.57702 63.99063 67.62622 69.32310 73.84112
[8] 67.16124 72.74255 70.22362 74.67062 69.53621 NaN 70.86911
[15] 72.81329 75.54069 74.75990 74.71656 72.14911 77.46750
> colSums(tmp5,na.rm=TRUE)
[1] 1071.8695 593.2603 644.1931 575.9157 608.6360 623.9079 664.5701
[8] 604.4511 654.6830 632.0126 672.0356 625.8259 0.0000 637.8220
[15] 655.3196 679.8662 672.8391 672.4490 649.3419 697.2075
> colVars(tmp5,na.rm=TRUE)
[1] 17350.15933 88.55100 121.13003 75.98210 38.78357 52.10389
[7] 84.16661 57.53895 117.63023 99.34724 59.41272 51.58544
[13] NA 72.31062 115.40198 60.64522 50.38452 23.79520
[19] 85.70845 45.73050
> colSd(tmp5,na.rm=TRUE)
[1] 131.720004 9.410154 11.005909 8.716771 6.227646 7.218302
[7] 9.174236 7.585444 10.845747 9.967309 7.707965 7.182301
[13] NA 8.503565 10.742531 7.787504 7.098205 4.878033
[19] 9.257886 6.762433
> colMax(tmp5,na.rm=TRUE)
[1] 468.85441 76.16007 84.39329 83.30363 76.34685 81.55283 85.31545
[8] 81.21285 87.23580 84.74850 84.54152 77.38865 -Inf 86.40257
[15] 82.81823 85.80218 90.94006 84.94697 88.44179 91.08182
> colMin(tmp5,na.rm=TRUE)
[1] 56.12187 53.56484 55.59262 55.11358 58.02824 61.60480 59.75491 57.71638
[9] 55.24439 56.40608 60.28062 57.33169 Inf 59.43119 55.41371 64.76310
[17] 65.71687 69.07493 63.36184 69.23142
>
>
>
>
> 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] 244.1710 236.9088 432.4877 154.0472 183.8117 333.8822 191.5401 319.5918
[9] 205.3234 240.7682
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 244.1710 236.9088 432.4877 154.0472 183.8117 333.8822 191.5401 319.5918
[9] 205.3234 240.7682
>
>
>
> 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 -5.684342e-14 -2.842171e-14 -2.842171e-14 -5.684342e-14
[6] 1.136868e-13 5.684342e-14 1.705303e-13 1.136868e-13 -1.136868e-13
[11] 1.421085e-13 -4.263256e-14 2.842171e-14 -1.136868e-13 -1.705303e-13
[16] 3.552714e-14 -2.842171e-14 5.684342e-14 5.684342e-14 -2.273737e-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)
+ }
7 11
3 12
1 19
8 18
3 8
6 10
7 7
7 14
3 19
9 8
8 13
3 15
4 8
3 3
1 20
7 6
4 19
1 12
6 15
5 16
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] 2.07757
> Min(tmp)
[1] -2.728525
> mean(tmp)
[1] 0.03056894
> Sum(tmp)
[1] 3.056894
> Var(tmp)
[1] 0.9987542
>
> rowMeans(tmp)
[1] 0.03056894
> rowSums(tmp)
[1] 3.056894
> rowVars(tmp)
[1] 0.9987542
> rowSd(tmp)
[1] 0.9993769
> rowMax(tmp)
[1] 2.07757
> rowMin(tmp)
[1] -2.728525
>
> colMeans(tmp)
[1] 0.66278774 -0.11206652 1.81005973 -1.14004932 1.77142691 -0.41817003
[7] -0.28317196 -0.92856003 0.11987223 0.44003135 -0.36175819 0.19522356
[13] -0.90053297 -1.19687853 1.59824006 0.89514189 0.37384430 1.13795427
[19] -0.11370543 0.25576582 -0.48528434 -0.11741654 -0.69708028 -2.72852520
[25] 1.22422430 -0.70215581 -1.04535673 0.97807210 -1.35381234 -0.42490285
[31] -1.44981409 -1.04814369 0.07277068 -0.94131016 0.07730654 -0.83355962
[37] -1.54688713 1.47490071 -0.90678650 1.97610199 0.21322313 -0.37421846
[43] 0.88111833 0.14736938 0.70104349 2.07757029 -0.23211322 1.70658313
[49] 0.79245983 0.67117327 -0.42909009 0.72369741 -0.13540601 0.99245201
[55] -1.02397005 1.21870583 1.82569674 0.80098826 -0.96159957 -1.35349460
[61] 0.09497387 -0.45644963 0.65529326 0.33543784 0.95578609 -0.04756671
[67] -0.55395641 0.82280242 1.23907901 -0.12852872 -1.08278027 1.17942978
[73] 0.22424394 -0.48834562 -0.84894557 0.65508868 -0.62834996 -0.54359239
[79] 0.49662465 -2.08723653 0.00482606 1.14641941 -1.10975281 -0.30577901
[85] 0.44791344 2.02383129 -1.13605073 -0.50454076 -0.74980940 0.23619035
[91] -1.81273221 -1.63787204 0.47909802 0.93034832 -0.53292416 1.30275963
[97] -0.65359380 0.51335607 0.81603658 0.23617679
> colSums(tmp)
[1] 0.66278774 -0.11206652 1.81005973 -1.14004932 1.77142691 -0.41817003
[7] -0.28317196 -0.92856003 0.11987223 0.44003135 -0.36175819 0.19522356
[13] -0.90053297 -1.19687853 1.59824006 0.89514189 0.37384430 1.13795427
[19] -0.11370543 0.25576582 -0.48528434 -0.11741654 -0.69708028 -2.72852520
[25] 1.22422430 -0.70215581 -1.04535673 0.97807210 -1.35381234 -0.42490285
[31] -1.44981409 -1.04814369 0.07277068 -0.94131016 0.07730654 -0.83355962
[37] -1.54688713 1.47490071 -0.90678650 1.97610199 0.21322313 -0.37421846
[43] 0.88111833 0.14736938 0.70104349 2.07757029 -0.23211322 1.70658313
[49] 0.79245983 0.67117327 -0.42909009 0.72369741 -0.13540601 0.99245201
[55] -1.02397005 1.21870583 1.82569674 0.80098826 -0.96159957 -1.35349460
[61] 0.09497387 -0.45644963 0.65529326 0.33543784 0.95578609 -0.04756671
[67] -0.55395641 0.82280242 1.23907901 -0.12852872 -1.08278027 1.17942978
[73] 0.22424394 -0.48834562 -0.84894557 0.65508868 -0.62834996 -0.54359239
[79] 0.49662465 -2.08723653 0.00482606 1.14641941 -1.10975281 -0.30577901
[85] 0.44791344 2.02383129 -1.13605073 -0.50454076 -0.74980940 0.23619035
[91] -1.81273221 -1.63787204 0.47909802 0.93034832 -0.53292416 1.30275963
[97] -0.65359380 0.51335607 0.81603658 0.23617679
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.66278774 -0.11206652 1.81005973 -1.14004932 1.77142691 -0.41817003
[7] -0.28317196 -0.92856003 0.11987223 0.44003135 -0.36175819 0.19522356
[13] -0.90053297 -1.19687853 1.59824006 0.89514189 0.37384430 1.13795427
[19] -0.11370543 0.25576582 -0.48528434 -0.11741654 -0.69708028 -2.72852520
[25] 1.22422430 -0.70215581 -1.04535673 0.97807210 -1.35381234 -0.42490285
[31] -1.44981409 -1.04814369 0.07277068 -0.94131016 0.07730654 -0.83355962
[37] -1.54688713 1.47490071 -0.90678650 1.97610199 0.21322313 -0.37421846
[43] 0.88111833 0.14736938 0.70104349 2.07757029 -0.23211322 1.70658313
[49] 0.79245983 0.67117327 -0.42909009 0.72369741 -0.13540601 0.99245201
[55] -1.02397005 1.21870583 1.82569674 0.80098826 -0.96159957 -1.35349460
[61] 0.09497387 -0.45644963 0.65529326 0.33543784 0.95578609 -0.04756671
[67] -0.55395641 0.82280242 1.23907901 -0.12852872 -1.08278027 1.17942978
[73] 0.22424394 -0.48834562 -0.84894557 0.65508868 -0.62834996 -0.54359239
[79] 0.49662465 -2.08723653 0.00482606 1.14641941 -1.10975281 -0.30577901
[85] 0.44791344 2.02383129 -1.13605073 -0.50454076 -0.74980940 0.23619035
[91] -1.81273221 -1.63787204 0.47909802 0.93034832 -0.53292416 1.30275963
[97] -0.65359380 0.51335607 0.81603658 0.23617679
> colMin(tmp)
[1] 0.66278774 -0.11206652 1.81005973 -1.14004932 1.77142691 -0.41817003
[7] -0.28317196 -0.92856003 0.11987223 0.44003135 -0.36175819 0.19522356
[13] -0.90053297 -1.19687853 1.59824006 0.89514189 0.37384430 1.13795427
[19] -0.11370543 0.25576582 -0.48528434 -0.11741654 -0.69708028 -2.72852520
[25] 1.22422430 -0.70215581 -1.04535673 0.97807210 -1.35381234 -0.42490285
[31] -1.44981409 -1.04814369 0.07277068 -0.94131016 0.07730654 -0.83355962
[37] -1.54688713 1.47490071 -0.90678650 1.97610199 0.21322313 -0.37421846
[43] 0.88111833 0.14736938 0.70104349 2.07757029 -0.23211322 1.70658313
[49] 0.79245983 0.67117327 -0.42909009 0.72369741 -0.13540601 0.99245201
[55] -1.02397005 1.21870583 1.82569674 0.80098826 -0.96159957 -1.35349460
[61] 0.09497387 -0.45644963 0.65529326 0.33543784 0.95578609 -0.04756671
[67] -0.55395641 0.82280242 1.23907901 -0.12852872 -1.08278027 1.17942978
[73] 0.22424394 -0.48834562 -0.84894557 0.65508868 -0.62834996 -0.54359239
[79] 0.49662465 -2.08723653 0.00482606 1.14641941 -1.10975281 -0.30577901
[85] 0.44791344 2.02383129 -1.13605073 -0.50454076 -0.74980940 0.23619035
[91] -1.81273221 -1.63787204 0.47909802 0.93034832 -0.53292416 1.30275963
[97] -0.65359380 0.51335607 0.81603658 0.23617679
> colMedians(tmp)
[1] 0.66278774 -0.11206652 1.81005973 -1.14004932 1.77142691 -0.41817003
[7] -0.28317196 -0.92856003 0.11987223 0.44003135 -0.36175819 0.19522356
[13] -0.90053297 -1.19687853 1.59824006 0.89514189 0.37384430 1.13795427
[19] -0.11370543 0.25576582 -0.48528434 -0.11741654 -0.69708028 -2.72852520
[25] 1.22422430 -0.70215581 -1.04535673 0.97807210 -1.35381234 -0.42490285
[31] -1.44981409 -1.04814369 0.07277068 -0.94131016 0.07730654 -0.83355962
[37] -1.54688713 1.47490071 -0.90678650 1.97610199 0.21322313 -0.37421846
[43] 0.88111833 0.14736938 0.70104349 2.07757029 -0.23211322 1.70658313
[49] 0.79245983 0.67117327 -0.42909009 0.72369741 -0.13540601 0.99245201
[55] -1.02397005 1.21870583 1.82569674 0.80098826 -0.96159957 -1.35349460
[61] 0.09497387 -0.45644963 0.65529326 0.33543784 0.95578609 -0.04756671
[67] -0.55395641 0.82280242 1.23907901 -0.12852872 -1.08278027 1.17942978
[73] 0.22424394 -0.48834562 -0.84894557 0.65508868 -0.62834996 -0.54359239
[79] 0.49662465 -2.08723653 0.00482606 1.14641941 -1.10975281 -0.30577901
[85] 0.44791344 2.02383129 -1.13605073 -0.50454076 -0.74980940 0.23619035
[91] -1.81273221 -1.63787204 0.47909802 0.93034832 -0.53292416 1.30275963
[97] -0.65359380 0.51335607 0.81603658 0.23617679
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.6627877 -0.1120665 1.81006 -1.140049 1.771427 -0.41817 -0.283172
[2,] 0.6627877 -0.1120665 1.81006 -1.140049 1.771427 -0.41817 -0.283172
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.92856 0.1198722 0.4400314 -0.3617582 0.1952236 -0.900533 -1.196879
[2,] -0.92856 0.1198722 0.4400314 -0.3617582 0.1952236 -0.900533 -1.196879
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.59824 0.8951419 0.3738443 1.137954 -0.1137054 0.2557658 -0.4852843
[2,] 1.59824 0.8951419 0.3738443 1.137954 -0.1137054 0.2557658 -0.4852843
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.1174165 -0.6970803 -2.728525 1.224224 -0.7021558 -1.045357 0.9780721
[2,] -0.1174165 -0.6970803 -2.728525 1.224224 -0.7021558 -1.045357 0.9780721
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.353812 -0.4249029 -1.449814 -1.048144 0.07277068 -0.9413102 0.07730654
[2,] -1.353812 -0.4249029 -1.449814 -1.048144 0.07277068 -0.9413102 0.07730654
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.8335596 -1.546887 1.474901 -0.9067865 1.976102 0.2132231 -0.3742185
[2,] -0.8335596 -1.546887 1.474901 -0.9067865 1.976102 0.2132231 -0.3742185
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.8811183 0.1473694 0.7010435 2.07757 -0.2321132 1.706583 0.7924598
[2,] 0.8811183 0.1473694 0.7010435 2.07757 -0.2321132 1.706583 0.7924598
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.6711733 -0.4290901 0.7236974 -0.135406 0.992452 -1.02397 1.218706
[2,] 0.6711733 -0.4290901 0.7236974 -0.135406 0.992452 -1.02397 1.218706
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.825697 0.8009883 -0.9615996 -1.353495 0.09497387 -0.4564496 0.6552933
[2,] 1.825697 0.8009883 -0.9615996 -1.353495 0.09497387 -0.4564496 0.6552933
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.3354378 0.9557861 -0.04756671 -0.5539564 0.8228024 1.239079 -0.1285287
[2,] 0.3354378 0.9557861 -0.04756671 -0.5539564 0.8228024 1.239079 -0.1285287
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.08278 1.17943 0.2242439 -0.4883456 -0.8489456 0.6550887 -0.62835
[2,] -1.08278 1.17943 0.2242439 -0.4883456 -0.8489456 0.6550887 -0.62835
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.5435924 0.4966247 -2.087237 0.00482606 1.146419 -1.109753 -0.305779
[2,] -0.5435924 0.4966247 -2.087237 0.00482606 1.146419 -1.109753 -0.305779
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.4479134 2.023831 -1.136051 -0.5045408 -0.7498094 0.2361903 -1.812732
[2,] 0.4479134 2.023831 -1.136051 -0.5045408 -0.7498094 0.2361903 -1.812732
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.637872 0.479098 0.9303483 -0.5329242 1.30276 -0.6535938 0.5133561
[2,] -1.637872 0.479098 0.9303483 -0.5329242 1.30276 -0.6535938 0.5133561
[,99] [,100]
[1,] 0.8160366 0.2361768
[2,] 0.8160366 0.2361768
>
>
> Max(tmp2)
[1] 3.396493
> Min(tmp2)
[1] -3.144042
> mean(tmp2)
[1] -0.1049338
> Sum(tmp2)
[1] -10.49338
> Var(tmp2)
[1] 1.341816
>
> rowMeans(tmp2)
[1] 0.12100057 -0.74602385 -0.86203832 -1.16438457 0.37781158 0.45173296
[7] 0.22709026 2.48689088 -0.50617778 0.37594334 0.15824957 1.48298488
[13] -1.16697353 -0.04347327 -0.76563738 -0.44506784 0.39025547 -1.81602120
[19] 1.40728234 -0.82873514 -0.15091148 -0.65282801 -0.33272947 -1.73202249
[25] -1.93954560 -2.39318505 0.58127309 -1.36333357 2.35008319 0.11943761
[31] 1.39126015 -1.37388462 -0.52363521 0.69011724 -0.64926790 -0.53780013
[37] -0.05134426 1.11085695 -2.37747680 1.38837839 0.83861277 3.39649250
[43] -1.07189241 0.68922043 -0.55571756 0.19918346 -0.74060616 0.01299441
[49] 0.26450364 -0.39738243 -0.81929195 1.08006713 0.94023717 0.31169654
[55] 0.43392009 -0.68675923 -0.97840906 0.15147803 -0.10491676 0.65780169
[61] 1.25214433 -2.57722230 -2.05438876 -0.15659415 0.77115314 2.23102703
[67] 1.82193611 0.73248040 0.14515032 1.27176795 1.12718008 1.63055346
[73] 0.21164924 -3.14404214 -0.35998914 0.49251640 1.04665127 -0.68515965
[79] -0.19638213 0.32290356 -0.24280858 -0.90520627 -1.00837985 -0.27949702
[85] -0.58400690 -1.54469654 -0.73805475 -0.38148916 -2.08691701 -0.86553313
[91] -1.80527923 -0.67871868 -0.65197904 0.60427230 -0.97277307 0.05292527
[97] 0.06036963 1.73446297 -0.70726875 0.31448198
> rowSums(tmp2)
[1] 0.12100057 -0.74602385 -0.86203832 -1.16438457 0.37781158 0.45173296
[7] 0.22709026 2.48689088 -0.50617778 0.37594334 0.15824957 1.48298488
[13] -1.16697353 -0.04347327 -0.76563738 -0.44506784 0.39025547 -1.81602120
[19] 1.40728234 -0.82873514 -0.15091148 -0.65282801 -0.33272947 -1.73202249
[25] -1.93954560 -2.39318505 0.58127309 -1.36333357 2.35008319 0.11943761
[31] 1.39126015 -1.37388462 -0.52363521 0.69011724 -0.64926790 -0.53780013
[37] -0.05134426 1.11085695 -2.37747680 1.38837839 0.83861277 3.39649250
[43] -1.07189241 0.68922043 -0.55571756 0.19918346 -0.74060616 0.01299441
[49] 0.26450364 -0.39738243 -0.81929195 1.08006713 0.94023717 0.31169654
[55] 0.43392009 -0.68675923 -0.97840906 0.15147803 -0.10491676 0.65780169
[61] 1.25214433 -2.57722230 -2.05438876 -0.15659415 0.77115314 2.23102703
[67] 1.82193611 0.73248040 0.14515032 1.27176795 1.12718008 1.63055346
[73] 0.21164924 -3.14404214 -0.35998914 0.49251640 1.04665127 -0.68515965
[79] -0.19638213 0.32290356 -0.24280858 -0.90520627 -1.00837985 -0.27949702
[85] -0.58400690 -1.54469654 -0.73805475 -0.38148916 -2.08691701 -0.86553313
[91] -1.80527923 -0.67871868 -0.65197904 0.60427230 -0.97277307 0.05292527
[97] 0.06036963 1.73446297 -0.70726875 0.31448198
> 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] 0.12100057 -0.74602385 -0.86203832 -1.16438457 0.37781158 0.45173296
[7] 0.22709026 2.48689088 -0.50617778 0.37594334 0.15824957 1.48298488
[13] -1.16697353 -0.04347327 -0.76563738 -0.44506784 0.39025547 -1.81602120
[19] 1.40728234 -0.82873514 -0.15091148 -0.65282801 -0.33272947 -1.73202249
[25] -1.93954560 -2.39318505 0.58127309 -1.36333357 2.35008319 0.11943761
[31] 1.39126015 -1.37388462 -0.52363521 0.69011724 -0.64926790 -0.53780013
[37] -0.05134426 1.11085695 -2.37747680 1.38837839 0.83861277 3.39649250
[43] -1.07189241 0.68922043 -0.55571756 0.19918346 -0.74060616 0.01299441
[49] 0.26450364 -0.39738243 -0.81929195 1.08006713 0.94023717 0.31169654
[55] 0.43392009 -0.68675923 -0.97840906 0.15147803 -0.10491676 0.65780169
[61] 1.25214433 -2.57722230 -2.05438876 -0.15659415 0.77115314 2.23102703
[67] 1.82193611 0.73248040 0.14515032 1.27176795 1.12718008 1.63055346
[73] 0.21164924 -3.14404214 -0.35998914 0.49251640 1.04665127 -0.68515965
[79] -0.19638213 0.32290356 -0.24280858 -0.90520627 -1.00837985 -0.27949702
[85] -0.58400690 -1.54469654 -0.73805475 -0.38148916 -2.08691701 -0.86553313
[91] -1.80527923 -0.67871868 -0.65197904 0.60427230 -0.97277307 0.05292527
[97] 0.06036963 1.73446297 -0.70726875 0.31448198
> rowMin(tmp2)
[1] 0.12100057 -0.74602385 -0.86203832 -1.16438457 0.37781158 0.45173296
[7] 0.22709026 2.48689088 -0.50617778 0.37594334 0.15824957 1.48298488
[13] -1.16697353 -0.04347327 -0.76563738 -0.44506784 0.39025547 -1.81602120
[19] 1.40728234 -0.82873514 -0.15091148 -0.65282801 -0.33272947 -1.73202249
[25] -1.93954560 -2.39318505 0.58127309 -1.36333357 2.35008319 0.11943761
[31] 1.39126015 -1.37388462 -0.52363521 0.69011724 -0.64926790 -0.53780013
[37] -0.05134426 1.11085695 -2.37747680 1.38837839 0.83861277 3.39649250
[43] -1.07189241 0.68922043 -0.55571756 0.19918346 -0.74060616 0.01299441
[49] 0.26450364 -0.39738243 -0.81929195 1.08006713 0.94023717 0.31169654
[55] 0.43392009 -0.68675923 -0.97840906 0.15147803 -0.10491676 0.65780169
[61] 1.25214433 -2.57722230 -2.05438876 -0.15659415 0.77115314 2.23102703
[67] 1.82193611 0.73248040 0.14515032 1.27176795 1.12718008 1.63055346
[73] 0.21164924 -3.14404214 -0.35998914 0.49251640 1.04665127 -0.68515965
[79] -0.19638213 0.32290356 -0.24280858 -0.90520627 -1.00837985 -0.27949702
[85] -0.58400690 -1.54469654 -0.73805475 -0.38148916 -2.08691701 -0.86553313
[91] -1.80527923 -0.67871868 -0.65197904 0.60427230 -0.97277307 0.05292527
[97] 0.06036963 1.73446297 -0.70726875 0.31448198
>
> colMeans(tmp2)
[1] -0.1049338
> colSums(tmp2)
[1] -10.49338
> colVars(tmp2)
[1] 1.341816
> colSd(tmp2)
[1] 1.158368
> colMax(tmp2)
[1] 3.396493
> colMin(tmp2)
[1] -3.144042
> colMedians(tmp2)
[1] -0.1279141
> colRanges(tmp2)
[,1]
[1,] -3.144042
[2,] 3.396493
>
> 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] -0.54342873 -2.67350188 4.90440452 -0.07749249 -6.95187491 -0.83031597
[7] -1.18902313 6.89539885 -5.04302998 -1.47661549
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.29587939
[2,] -0.89560690
[3,] 0.05721793
[4,] 0.36148788
[5,] 1.59496484
>
> rowApply(tmp,sum)
[1] 4.53857670 -0.94944031 1.16803335 0.30553960 -1.90649679 -3.00440169
[7] -2.53462894 -2.17392583 -0.09538619 -2.33334912
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 9 10 1 9 6 8 8 5 3
[2,] 1 6 2 6 10 4 1 6 6 5
[3,] 10 4 7 9 4 10 9 5 3 7
[4,] 5 1 6 5 5 9 5 9 1 10
[5,] 6 2 1 2 6 7 4 3 2 1
[6,] 3 8 8 10 8 1 2 4 9 2
[7,] 4 7 3 7 1 5 7 2 10 8
[8,] 9 10 9 4 7 8 10 10 8 4
[9,] 8 3 4 3 3 2 6 1 4 9
[10,] 7 5 5 8 2 3 3 7 7 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.08057765 -0.27692565 0.38232127 0.18755969 1.03547544 -1.57707738
[7] -2.12250534 -6.10526163 2.19097572 2.39988475 1.12801597 0.54472684
[13] -0.19903564 -1.73939804 -0.55848396 1.45928693 3.43732607 -2.04487364
[19] -1.12363036 4.72852188
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.3323570
[2,] -0.4661104
[3,] 0.8002486
[4,] 0.8378384
[5,] 1.2409581
>
> rowApply(tmp,sum)
[1] 12.3016067 -0.6809372 -0.5189098 -8.0767510 -1.1975282
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 19 1 9 17
[2,] 6 15 19 6 7
[3,] 17 3 6 12 15
[4,] 1 12 16 10 11
[5,] 11 5 11 8 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.8002486 -0.2286242 1.1856049 -0.90184731 0.8123643 1.4874346
[2,] 1.2409581 0.3779095 -0.8005119 -0.02071356 -0.7615856 -0.5880538
[3,] -2.3323570 1.4435423 -0.8434418 1.05172687 0.1007945 -1.4489285
[4,] -0.4661104 -1.1592369 0.1094904 -0.18496157 -0.6439968 0.3188349
[5,] 0.8378384 -0.7105163 0.7311797 0.24335526 1.5278991 -1.3463645
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.61698742 -0.5116133 1.0177183 0.5586650 -0.1053562 0.9897727
[2,] 1.01368599 -0.3724983 1.3186898 -0.2204081 -0.6850382 -0.9676020
[3,] -1.00957695 -1.8434198 1.9910083 0.6578158 0.2235684 1.0842821
[4,] -2.71338632 -1.4352701 -1.1722368 0.8050965 0.9843834 -1.5742610
[5,] -0.03021549 -1.9424602 -0.9642039 0.5987155 0.7104586 1.0125350
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.1820843 -0.62121321 -0.3061333 1.13921463 0.8862336 1.952722
[2,] -0.7678234 -1.25753480 -0.1562384 0.17531059 0.7725710 1.146599
[3,] 1.3990005 0.05374285 0.9528914 -0.69277054 -0.2027227 -2.103426
[4,] 0.2695296 0.56819352 0.2193736 0.06565989 0.3689131 -1.936541
[5,] -2.2818267 -0.48258639 -1.2683773 0.77187237 1.6123311 -1.104229
[,19] [,20]
[1,] -0.230285791 2.577629224
[2,] -0.133180245 0.004526739
[3,] -0.003132153 1.002492763
[4,] -0.984273712 0.484048492
[5,] 0.227241543 0.659824659
>
>
> 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 : 648 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.8636811 -0.9000621 -0.2230556 0.4420854 -0.3314259 -1.618608 0.4482984
col8 col9 col10 col11 col12 col13 col14
row1 -0.731323 0.5460691 0.0489352 1.80762 1.991088 0.5345316 0.8865071
col15 col16 col17 col18 col19 col20
row1 1.663155 0.768409 -0.4253377 0.4081 0.2750772 -0.03205593
> tmp[,"col10"]
col10
row1 0.0489352
row2 0.7549446
row3 -0.2840833
row4 -1.0454167
row5 -0.1986600
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.8636811 -0.9000621 -0.2230556 0.4420854 -0.3314259 -1.6186081
row5 -0.9081685 -0.5306623 -2.6157454 -0.6207680 -1.0763967 0.7448151
col7 col8 col9 col10 col11 col12 col13
row1 0.4482984 -0.7313230 0.5460691 0.0489352 1.807620 1.99108788 0.5345316
row5 2.7674194 -0.2811138 1.9117327 -0.1986600 0.352879 0.09559771 1.1077036
col14 col15 col16 col17 col18 col19 col20
row1 0.8865071 1.663155 0.768409 -0.4253377 0.4081000 0.2750772 -0.03205593
row5 0.8139441 2.053868 -1.904962 1.0469882 -0.7914217 -1.8202546 -0.90641683
> tmp[,c("col6","col20")]
col6 col20
row1 -1.6186081 -0.03205593
row2 -0.4893970 -1.19891920
row3 1.2674271 -0.34047623
row4 0.7601881 0.32924462
row5 0.7448151 -0.90641683
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.6186081 -0.03205593
row5 0.7448151 -0.90641683
>
>
>
>
> 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 49.56498 49.37836 48.97452 51.36471 50.51658 103.9229 48.70112 51.1871
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.464 50.31386 50.56373 48.51855 48.96184 50.73885 48.75355 50.20879
col17 col18 col19 col20
row1 50.62105 49.88314 49.1072 104.0384
> tmp[,"col10"]
col10
row1 50.31386
row2 30.01383
row3 29.74475
row4 30.35999
row5 49.63157
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.56498 49.37836 48.97452 51.36471 50.51658 103.9229 48.70112 51.18710
row5 49.59163 51.60090 49.10378 50.04401 50.06240 104.5968 48.05342 46.80653
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.46400 50.31386 50.56373 48.51855 48.96184 50.73885 48.75355 50.20879
row5 49.01154 49.63157 50.93406 51.54251 50.16673 48.06826 50.87222 53.01992
col17 col18 col19 col20
row1 50.62105 49.88314 49.10720 104.0384
row5 51.99179 48.80200 49.54929 104.1462
> tmp[,c("col6","col20")]
col6 col20
row1 103.92293 104.03843
row2 75.34140 75.38437
row3 75.57730 74.58662
row4 76.11712 74.10197
row5 104.59679 104.14622
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.9229 104.0384
row5 104.5968 104.1462
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.9229 104.0384
row5 104.5968 104.1462
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.2672283
[2,] 0.6663415
[3,] -0.1595256
[4,] 0.7140293
[5,] 1.5325229
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.48120406 2.0769115
[2,] 0.80969756 0.2345022
[3,] -0.05151165 0.8201354
[4,] -0.49544006 -0.2627488
[5,] -1.52985566 0.1826648
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.5131539 0.3109837
[2,] -0.5337298 0.7670394
[3,] 0.9439083 -0.4902458
[4,] -1.1291000 0.8914893
[5,] 1.1489351 1.0240942
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.5131539
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.5131539
[2,] -0.5337298
>
>
>
> 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 0.04356284 -1.3055206 -0.1681981 1.1071164 2.031438 -1.3054224 -1.835098
row1 0.29105330 0.3031082 1.4094640 0.9520826 -1.683326 0.3855974 -1.148977
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.958048 0.5715685 -1.3057819 0.1030066 -0.7472997 1.5179336 0.7492948
row1 1.045873 0.8664754 0.3802437 -0.7968336 1.0068108 -0.1575129 0.7367990
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.743295 -0.1864381 -1.361449 0.8847037 0.1689227 -0.7875718
row1 -0.504659 -0.2894676 -1.190285 1.3340436 -0.9517692 -1.7609964
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.7988424 -0.9979764 -0.4124402 -0.394838 0.7863279 1.327622 -0.8039327
[,8] [,9] [,10]
row2 -0.2682055 0.6960049 0.89224
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.446462 0.3741186 -0.2567689 -1.261112 -0.2616644 -1.791972 0.599493
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.007623609 0.1832795 0.189041 1.644269 0.4614274 0.4173819 -0.6433255
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.1879331 -0.2446448 0.1745828 0.2962472 0.7368814 0.2738123
>
>
> 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: 0xd6968f0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb9982374830a7"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99821851be77"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99822127d10d"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99821a86ff31"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb9982623ee1bb"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb9982701b5d42"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb998254b1c6f1"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb9982cd3afd3"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb998244eb5c4b"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99821b0a75d0"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99823663fba"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99823a0b0156"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99823175a09e"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb99825648dfbb"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMb9982210526c7"
>
>
> ### 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: 0xe37a680>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xe37a680>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xe37a680>
> rowMedians(tmp)
[1] -0.2769374572 0.6603115395 -0.2403229339 0.4231007845 -0.1751454321
[6] -0.1808021582 0.0005843797 0.0599061536 0.2055627988 -0.0015891446
[11] -0.4563217665 -0.4942963606 0.5928515969 0.0387737698 -0.2421713509
[16] 0.2322142193 0.4127503313 0.1232085448 -0.1576821181 -0.4369444180
[21] 0.2858474086 0.0062308669 -0.4191297669 0.1851954967 0.0262979855
[26] -0.5029820881 -0.1869377254 -0.7891869740 0.2895026100 -0.0448761245
[31] 0.0967741003 0.2689321060 -0.2961468579 0.0803446149 0.3353768132
[36] 0.1327984191 -0.0321985281 0.5148725124 0.3006036398 -0.4305401048
[41] -0.4585727943 -0.4018741044 0.4788523480 -0.1411407392 -0.1819811345
[46] 0.3842672874 0.0403468415 0.2263773709 -0.2492228133 -0.0937178766
[51] -0.2372633647 0.2808014865 -0.0212275171 -0.0597662530 0.1202773598
[56] 0.0417316998 0.1915060748 -0.0379894481 -0.8131387411 0.3963682548
[61] -0.2100567491 -0.1200758098 -0.5831179926 -0.0364139576 0.2060655212
[66] 0.1754190558 0.4857590177 -0.5270274247 0.0710235756 -0.0813702265
[71] -0.2041284818 0.4146400116 -0.4189832197 0.1959456946 -0.1221195399
[76] -0.7789000015 -0.2107318219 0.4290370880 -0.0758021219 -0.1113687551
[81] 0.9447128021 -0.6024116180 -0.1074062035 -0.4196188507 0.5095847922
[86] -0.5055485624 0.3169314769 -0.0829595161 0.1914000967 0.0242732883
[91] 0.0132876430 -0.2060110709 0.0269208607 -0.0140334971 -0.4847640175
[96] 0.1233443513 -0.4303711919 0.1376496215 -0.3432418870 0.4065014914
[101] 0.2859501400 0.3110170448 0.3350726596 0.2670623245 -0.0902005518
[106] -0.0824719950 0.1879935371 -0.1586236439 0.0073004959 -0.2935365353
[111] 0.3178709448 -0.4380921191 -0.4779251363 0.0050961791 0.2788154944
[116] -0.3263851993 0.3750128277 -0.1666953326 0.1375716593 0.2578815509
[121] 0.2356414618 0.3488976850 0.0662762911 0.5191742567 0.2906503436
[126] -0.0066239518 0.3554815753 0.3220408964 0.3204559270 0.1109791558
[131] -0.4230163392 0.1310631833 -0.0142773950 -0.1388906598 -0.1965214947
[136] -0.5454469450 0.3151605992 -0.0812140134 -0.0490390308 -0.1318942905
[141] -0.1587128264 -0.3275341574 -0.0849286442 -0.0753161420 0.4033169239
[146] 0.2936568053 0.4268767496 -0.1025929296 0.0458401864 -0.6813193370
[151] 0.1581195671 -0.2833665974 -0.2309199250 0.0138642378 0.2536890146
[156] -0.2995350071 -0.4036821286 -0.3062697916 0.0031682546 -0.0625180175
[161] -0.4377836298 -0.2523910810 -0.3707034852 0.0277230144 -0.8193122999
[166] -0.0594575233 0.0074314384 0.2489022268 0.2976961666 -0.0840499295
[171] -0.1590570689 -0.0651803101 0.1616248382 -0.5813411733 0.3288065468
[176] 0.3565676679 -0.1310441715 -0.5837078738 -0.0909259884 -0.2022664395
[181] -0.6407585570 0.1193427311 -0.0063505616 -0.0792250682 0.4072988512
[186] 0.0897823250 -0.0123651327 -0.1851560193 -0.2571697241 -0.5769454540
[191] -0.1341229618 0.5367658839 -0.6297671731 0.2006320603 -0.0300984866
[196] 0.3838162864 -0.0555982797 0.2451186101 0.4188127513 -0.1679462830
[201] 0.5168229962 0.7736724208 -0.5502847907 -0.4010591329 0.1955019760
[206] -0.0958446962 0.4822908860 -0.2064299926 -0.8080995241 0.0308370647
[211] -0.6650681834 0.1348032668 -0.3032779930 -0.2889165080 -0.6996603228
[216] 0.2367270970 -0.0218850045 0.3883715026 -0.1466796386 -0.4283954920
[221] -0.0996175348 0.3873780381 0.4363235929 0.3590842802 0.0997636979
[226] -0.2946356793 0.1760389844 -0.3851820536 0.2162135379 0.2827187564
>
> proc.time()
user system elapsed
1.976 0.781 2.787
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: 0x31512ff0>
> .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: 0x31512ff0>
> .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: 0x31512ff0>
> .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: 0x31512ff0>
> 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: 0x313f80e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x313f80e0>
> .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: 0x313f80e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x313f80e0>
> .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: 0x313f80e0>
> 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: 0x3037f520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3037f520>
> .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: 0x3037f520>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x3037f520>
> .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: 0x3037f520>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x3037f520>
> .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: 0x3037f520>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x3037f520>
> .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: 0x3037f520>
> 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: 0x2fd83720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x2fd83720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2fd83720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2fd83720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb99d13833de34" "BufferedMatrixFileb99d175d27779"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb99d13833de34" "BufferedMatrixFileb99d175d27779"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x30c737d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x30c737d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x30c737d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x30c737d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x30c737d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x30c737d0>
> .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: 0x30d7ac90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x30d7ac90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x30d7ac90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x30d7ac90>
> 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: 0x32023110>
> .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: 0x32023110>
> rm(P)
>
> proc.time()
user system elapsed
0.332 0.054 0.370
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
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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
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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
0.331 0.038 0.354