Ben Bolstad
| Snapshot Date: 2026-01-05 13:45 -0500 (Mon, 05 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 2026-01-08 11:59 -0500 (Thu, 08 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: 2026-01-06 08:08:37 -0000 (Tue, 06 Jan 2026) |
| EndedAt: 2026-01-06 08:09:06 -0000 (Tue, 06 Jan 2026) |
| EllapsedTime: 29.0 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
###
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* 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
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###
### 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
0.309 0.056 0.351
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] "Tue Jan 6 08:09:00 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Jan 6 08:09:00 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: 0x2b33eff0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Jan 6 08:09:01 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Jan 6 08:09:01 2026"
>
> ColMode(tmp2)
<pointer: 0x2b33eff0>
>
>
>
> ### 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,] 100.6485484 2.94199857 -0.6407754 0.3071833
[2,] 0.2379997 -0.09178266 1.5312174 0.6894740
[3,] -0.4088913 -0.74180463 2.8658878 0.1313563
[4,] 0.4355668 1.33158524 1.9995724 0.5107651
> 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,] 100.6485484 2.94199857 0.6407754 0.3071833
[2,] 0.2379997 0.09178266 1.5312174 0.6894740
[3,] 0.4088913 0.74180463 2.8658878 0.1313563
[4,] 0.4355668 1.33158524 1.9995724 0.5107651
> 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,] 10.0323750 1.7152255 0.8004845 0.5542412
[2,] 0.4878521 0.3029565 1.2374237 0.8303457
[3,] 0.6394461 0.8612808 1.6928933 0.3624312
[4,] 0.6599748 1.1539433 1.4140624 0.7146783
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.97230 45.09425 33.64562 30.84960
[2,] 30.11652 28.12135 38.90545 33.99293
[3,] 31.80335 34.35461 44.79482 28.75567
[4,] 32.03532 37.87102 41.14020 32.65755
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x2a0216c0>
> exp(tmp5)
<pointer: 0x2a0216c0>
> log(tmp5,2)
<pointer: 0x2a0216c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.3317
> Min(tmp5)
[1] 54.34514
> mean(tmp5)
[1] 73.20185
> Sum(tmp5)
[1] 14640.37
> Var(tmp5)
[1] 874.046
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.70648 64.89897 74.31343 72.34120 74.36245 68.78674 69.74392 70.31538
[9] 74.88894 71.66101
> rowSums(tmp5)
[1] 1814.130 1297.979 1486.269 1446.824 1487.249 1375.735 1394.878 1406.308
[9] 1497.779 1433.220
> rowVars(tmp5)
[1] 8077.28899 39.97498 131.26810 87.99830 46.14378 91.31784
[7] 61.36525 41.68569 47.96834 83.49571
> rowSd(tmp5)
[1] 89.873739 6.322577 11.457229 9.380741 6.792921 9.556037 7.833598
[8] 6.456445 6.925918 9.137599
> rowMax(tmp5)
[1] 470.33173 80.97661 96.90558 93.51403 88.96736 86.19360 82.40398
[8] 83.79051 83.21649 90.20291
> rowMin(tmp5)
[1] 54.34514 57.56659 59.85116 56.75085 63.60360 55.68990 56.94905 56.35896
[9] 56.82609 55.12690
>
> colMeans(tmp5)
[1] 106.81869 72.74852 75.74922 66.79251 72.98754 69.99012 69.43154
[8] 69.95680 70.74274 72.00960 70.62169 69.58842 70.47207 68.87449
[15] 67.45574 72.60798 78.91706 71.34189 75.06321 71.86725
> colSums(tmp5)
[1] 1068.1869 727.4852 757.4922 667.9251 729.8754 699.9012 694.3154
[8] 699.5680 707.4274 720.0960 706.2169 695.8842 704.7207 688.7449
[15] 674.5574 726.0798 789.1706 713.4189 750.6321 718.6725
> colVars(tmp5)
[1] 16381.27533 115.84043 115.68320 32.05610 94.71856 57.23280
[7] 71.25012 84.46776 52.29158 106.12653 76.98632 94.80485
[13] 61.11463 60.66972 36.07068 100.66119 102.20051 97.52366
[19] 47.25436 47.81866
> colSd(tmp5)
[1] 127.989356 10.762919 10.755613 5.661811 9.732346 7.565236
[7] 8.440979 9.190634 7.231292 10.301773 8.774185 9.736778
[13] 7.817585 7.789077 6.005887 10.033005 10.109427 9.875407
[19] 6.874181 6.915104
> colMax(tmp5)
[1] 470.33173 93.85778 93.23455 74.64059 90.20291 81.76553 83.21649
[8] 89.45177 86.66739 88.96736 78.78051 86.43714 81.29764 85.59660
[15] 77.02330 93.51403 96.90558 84.13552 83.19286 83.37365
> colMin(tmp5)
[1] 56.35896 57.42771 57.07559 55.68990 60.43875 59.57495 59.92130 54.34514
[9] 59.92219 56.75085 56.94905 55.12690 59.07850 60.70188 57.05956 61.74244
[17] 63.60360 57.19676 63.90806 62.80895
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.70648 64.89897 74.31343 72.34120 74.36245 68.78674 69.74392 70.31538
[9] NA 71.66101
> rowSums(tmp5)
[1] 1814.130 1297.979 1486.269 1446.824 1487.249 1375.735 1394.878 1406.308
[9] NA 1433.220
> rowVars(tmp5)
[1] 8077.28899 39.97498 131.26810 87.99830 46.14378 91.31784
[7] 61.36525 41.68569 49.74762 83.49571
> rowSd(tmp5)
[1] 89.873739 6.322577 11.457229 9.380741 6.792921 9.556037 7.833598
[8] 6.456445 7.053199 9.137599
> rowMax(tmp5)
[1] 470.33173 80.97661 96.90558 93.51403 88.96736 86.19360 82.40398
[8] 83.79051 NA 90.20291
> rowMin(tmp5)
[1] 54.34514 57.56659 59.85116 56.75085 63.60360 55.68990 56.94905 56.35896
[9] NA 55.12690
>
> colMeans(tmp5)
[1] 106.81869 72.74852 75.74922 66.79251 72.98754 69.99012 69.43154
[8] 69.95680 70.74274 72.00960 NA 69.58842 70.47207 68.87449
[15] 67.45574 72.60798 78.91706 71.34189 75.06321 71.86725
> colSums(tmp5)
[1] 1068.1869 727.4852 757.4922 667.9251 729.8754 699.9012 694.3154
[8] 699.5680 707.4274 720.0960 NA 695.8842 704.7207 688.7449
[15] 674.5574 726.0798 789.1706 713.4189 750.6321 718.6725
> colVars(tmp5)
[1] 16381.27533 115.84043 115.68320 32.05610 94.71856 57.23280
[7] 71.25012 84.46776 52.29158 106.12653 NA 94.80485
[13] 61.11463 60.66972 36.07068 100.66119 102.20051 97.52366
[19] 47.25436 47.81866
> colSd(tmp5)
[1] 127.989356 10.762919 10.755613 5.661811 9.732346 7.565236
[7] 8.440979 9.190634 7.231292 10.301773 NA 9.736778
[13] 7.817585 7.789077 6.005887 10.033005 10.109427 9.875407
[19] 6.874181 6.915104
> colMax(tmp5)
[1] 470.33173 93.85778 93.23455 74.64059 90.20291 81.76553 83.21649
[8] 89.45177 86.66739 88.96736 NA 86.43714 81.29764 85.59660
[15] 77.02330 93.51403 96.90558 84.13552 83.19286 83.37365
> colMin(tmp5)
[1] 56.35896 57.42771 57.07559 55.68990 60.43875 59.57495 59.92130 54.34514
[9] 59.92219 56.75085 NA 55.12690 59.07850 60.70188 57.05956 61.74244
[17] 63.60360 57.19676 63.90806 62.80895
>
> Max(tmp5,na.rm=TRUE)
[1] 470.3317
> Min(tmp5,na.rm=TRUE)
[1] 54.34514
> mean(tmp5,na.rm=TRUE)
[1] 73.17382
> Sum(tmp5,na.rm=TRUE)
[1] 14561.59
> Var(tmp5,na.rm=TRUE)
[1] 878.3024
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.70648 64.89897 74.31343 72.34120 74.36245 68.78674 69.74392 70.31538
[9] 74.68412 71.66101
> rowSums(tmp5,na.rm=TRUE)
[1] 1814.130 1297.979 1486.269 1446.824 1487.249 1375.735 1394.878 1406.308
[9] 1418.998 1433.220
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.28899 39.97498 131.26810 87.99830 46.14378 91.31784
[7] 61.36525 41.68569 49.74762 83.49571
> rowSd(tmp5,na.rm=TRUE)
[1] 89.873739 6.322577 11.457229 9.380741 6.792921 9.556037 7.833598
[8] 6.456445 7.053199 9.137599
> rowMax(tmp5,na.rm=TRUE)
[1] 470.33173 80.97661 96.90558 93.51403 88.96736 86.19360 82.40398
[8] 83.79051 83.21649 90.20291
> rowMin(tmp5,na.rm=TRUE)
[1] 54.34514 57.56659 59.85116 56.75085 63.60360 55.68990 56.94905 56.35896
[9] 56.82609 55.12690
>
> colMeans(tmp5,na.rm=TRUE)
[1] 106.81869 72.74852 75.74922 66.79251 72.98754 69.99012 69.43154
[8] 69.95680 70.74274 72.00960 69.71516 69.58842 70.47207 68.87449
[15] 67.45574 72.60798 78.91706 71.34189 75.06321 71.86725
> colSums(tmp5,na.rm=TRUE)
[1] 1068.1869 727.4852 757.4922 667.9251 729.8754 699.9012 694.3154
[8] 699.5680 707.4274 720.0960 627.4364 695.8842 704.7207 688.7449
[15] 674.5574 726.0798 789.1706 713.4189 750.6321 718.6725
> colVars(tmp5,na.rm=TRUE)
[1] 16381.27533 115.84043 115.68320 32.05610 94.71856 57.23280
[7] 71.25012 84.46776 52.29158 106.12653 77.36428 94.80485
[13] 61.11463 60.66972 36.07068 100.66119 102.20051 97.52366
[19] 47.25436 47.81866
> colSd(tmp5,na.rm=TRUE)
[1] 127.989356 10.762919 10.755613 5.661811 9.732346 7.565236
[7] 8.440979 9.190634 7.231292 10.301773 8.795697 9.736778
[13] 7.817585 7.789077 6.005887 10.033005 10.109427 9.875407
[19] 6.874181 6.915104
> colMax(tmp5,na.rm=TRUE)
[1] 470.33173 93.85778 93.23455 74.64059 90.20291 81.76553 83.21649
[8] 89.45177 86.66739 88.96736 77.73248 86.43714 81.29764 85.59660
[15] 77.02330 93.51403 96.90558 84.13552 83.19286 83.37365
> colMin(tmp5,na.rm=TRUE)
[1] 56.35896 57.42771 57.07559 55.68990 60.43875 59.57495 59.92130 54.34514
[9] 59.92219 56.75085 56.94905 55.12690 59.07850 60.70188 57.05956 61.74244
[17] 63.60360 57.19676 63.90806 62.80895
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.70648 64.89897 74.31343 72.34120 74.36245 68.78674 69.74392 70.31538
[9] NaN 71.66101
> rowSums(tmp5,na.rm=TRUE)
[1] 1814.130 1297.979 1486.269 1446.824 1487.249 1375.735 1394.878 1406.308
[9] 0.000 1433.220
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.28899 39.97498 131.26810 87.99830 46.14378 91.31784
[7] 61.36525 41.68569 NA 83.49571
> rowSd(tmp5,na.rm=TRUE)
[1] 89.873739 6.322577 11.457229 9.380741 6.792921 9.556037 7.833598
[8] 6.456445 NA 9.137599
> rowMax(tmp5,na.rm=TRUE)
[1] 470.33173 80.97661 96.90558 93.51403 88.96736 86.19360 82.40398
[8] 83.79051 NA 90.20291
> rowMin(tmp5,na.rm=TRUE)
[1] 54.34514 57.56659 59.85116 56.75085 63.60360 55.68990 56.94905 56.35896
[9] NA 55.12690
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.37342 73.33981 74.95840 66.85680 72.11056 68.68174 67.89988
[8] 70.26027 70.77709 71.82061 NaN 68.85338 69.26923 68.32766
[15] 66.90398 72.10065 78.85174 70.14618 75.50190 71.53955
> colSums(tmp5,na.rm=TRUE)
[1] 1011.3608 660.0583 674.6256 601.7112 648.9950 618.1356 611.0989
[8] 632.3424 636.9938 646.3855 0.0000 619.6804 623.4231 614.9489
[15] 602.1358 648.9058 709.6656 631.3156 679.5171 643.8559
> colVars(tmp5,na.rm=TRUE)
[1] 18081.81529 126.38715 123.10782 36.01661 97.90600 45.12851
[7] 53.76404 93.99019 58.81476 118.99054 NA 100.57729
[13] 52.47717 64.88938 37.15448 110.34828 114.92756 93.62986
[19] 50.99612 52.58788
> colSd(tmp5,na.rm=TRUE)
[1] 134.468641 11.242204 11.095396 6.001384 9.894746 6.717776
[7] 7.332396 9.694854 7.669078 10.908279 NA 10.028823
[13] 7.244113 8.055395 6.095447 10.504679 10.720427 9.676252
[19] 7.141157 7.251750
> colMax(tmp5,na.rm=TRUE)
[1] 470.33173 93.85778 93.23455 74.64059 90.20291 77.44838 81.18191
[8] 89.45177 86.66739 88.96736 -Inf 86.43714 79.18657 85.59660
[15] 77.02330 93.51403 96.90558 84.13552 83.19286 83.37365
> colMin(tmp5,na.rm=TRUE)
[1] 56.35896 57.42771 57.07559 55.68990 60.43875 59.57495 59.92130 54.34514
[9] 59.92219 56.75085 Inf 55.12690 59.07850 60.70188 57.05956 61.74244
[17] 63.60360 57.19676 63.90806 62.80895
>
>
>
>
> 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] 211.3115 123.8002 171.9029 212.4946 264.8060 286.9156 256.8722 243.1728
[9] 248.4361 301.7943
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 211.3115 123.8002 171.9029 212.4946 264.8060 286.9156 256.8722 243.1728
[9] 248.4361 301.7943
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.136868e-13 -1.136868e-13 -8.526513e-14 5.684342e-14 -1.136868e-13
[6] -2.842171e-13 -2.842171e-14 -5.684342e-14 1.421085e-13 -5.684342e-14
[11] 0.000000e+00 -1.705303e-13 -2.842171e-13 7.105427e-14 0.000000e+00
[16] 1.136868e-13 1.421085e-13 -1.136868e-13 2.842171e-14 5.684342e-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)
+ }
7 10
9 18
8 19
1 6
4 17
8 9
2 10
5 5
5 6
3 20
4 6
8 16
2 1
5 13
10 7
4 7
6 11
10 9
10 14
2 5
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] 3.090809
> Min(tmp)
[1] -2.482586
> mean(tmp)
[1] 0.03843123
> Sum(tmp)
[1] 3.843123
> Var(tmp)
[1] 1.211688
>
> rowMeans(tmp)
[1] 0.03843123
> rowSums(tmp)
[1] 3.843123
> rowVars(tmp)
[1] 1.211688
> rowSd(tmp)
[1] 1.100767
> rowMax(tmp)
[1] 3.090809
> rowMin(tmp)
[1] -2.482586
>
> colMeans(tmp)
[1] -0.49412861 0.24748402 0.14093966 0.58150479 -0.14133062 -2.48258580
[7] 0.16832961 0.44438180 -0.31472055 1.07852597 2.21581825 -0.41587200
[13] 0.69130501 0.20796390 1.17712369 -1.07490664 -0.36828791 0.53595846
[19] -0.87424471 0.39137374 0.06738095 -0.25723597 -1.54960090 1.26603884
[25] -0.69686876 0.87704418 -1.45362098 1.91445906 -0.93232786 -0.79261253
[31] 2.15581078 -1.44156350 -0.50443321 0.54564496 1.83358521 -1.61927592
[37] 0.88558157 0.95278390 -0.50353949 -1.36836354 -0.86891834 0.60668381
[43] 0.51484877 0.42807406 2.11985856 0.68323666 0.29883978 -0.10428322
[49] 0.27943832 0.08708669 3.09080930 0.81236054 -0.53332627 0.07621748
[55] 1.68290212 0.24487406 -1.61625634 0.08545443 -1.43977886 0.76697196
[61] 0.40007073 1.41895271 -1.40520944 1.36690420 -0.66729950 -0.26058400
[67] -0.47460554 0.05345401 0.48493496 -0.60938687 1.23074683 -0.83418561
[73] 1.12162230 -2.30505337 0.14889137 -0.86521774 -1.54844224 0.54253910
[79] -0.68873821 -1.81285432 0.84625512 -0.47917007 -1.92886529 -0.81122002
[85] -0.73681151 0.15606235 0.40906336 3.05388527 -0.18067377 0.72625835
[91] 1.34738722 -0.71519102 0.47008241 0.59442385 -0.44641672 -0.49332505
[97] -0.59034417 -0.42210185 -1.67030782 1.10898107
> colSums(tmp)
[1] -0.49412861 0.24748402 0.14093966 0.58150479 -0.14133062 -2.48258580
[7] 0.16832961 0.44438180 -0.31472055 1.07852597 2.21581825 -0.41587200
[13] 0.69130501 0.20796390 1.17712369 -1.07490664 -0.36828791 0.53595846
[19] -0.87424471 0.39137374 0.06738095 -0.25723597 -1.54960090 1.26603884
[25] -0.69686876 0.87704418 -1.45362098 1.91445906 -0.93232786 -0.79261253
[31] 2.15581078 -1.44156350 -0.50443321 0.54564496 1.83358521 -1.61927592
[37] 0.88558157 0.95278390 -0.50353949 -1.36836354 -0.86891834 0.60668381
[43] 0.51484877 0.42807406 2.11985856 0.68323666 0.29883978 -0.10428322
[49] 0.27943832 0.08708669 3.09080930 0.81236054 -0.53332627 0.07621748
[55] 1.68290212 0.24487406 -1.61625634 0.08545443 -1.43977886 0.76697196
[61] 0.40007073 1.41895271 -1.40520944 1.36690420 -0.66729950 -0.26058400
[67] -0.47460554 0.05345401 0.48493496 -0.60938687 1.23074683 -0.83418561
[73] 1.12162230 -2.30505337 0.14889137 -0.86521774 -1.54844224 0.54253910
[79] -0.68873821 -1.81285432 0.84625512 -0.47917007 -1.92886529 -0.81122002
[85] -0.73681151 0.15606235 0.40906336 3.05388527 -0.18067377 0.72625835
[91] 1.34738722 -0.71519102 0.47008241 0.59442385 -0.44641672 -0.49332505
[97] -0.59034417 -0.42210185 -1.67030782 1.10898107
> 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] -0.49412861 0.24748402 0.14093966 0.58150479 -0.14133062 -2.48258580
[7] 0.16832961 0.44438180 -0.31472055 1.07852597 2.21581825 -0.41587200
[13] 0.69130501 0.20796390 1.17712369 -1.07490664 -0.36828791 0.53595846
[19] -0.87424471 0.39137374 0.06738095 -0.25723597 -1.54960090 1.26603884
[25] -0.69686876 0.87704418 -1.45362098 1.91445906 -0.93232786 -0.79261253
[31] 2.15581078 -1.44156350 -0.50443321 0.54564496 1.83358521 -1.61927592
[37] 0.88558157 0.95278390 -0.50353949 -1.36836354 -0.86891834 0.60668381
[43] 0.51484877 0.42807406 2.11985856 0.68323666 0.29883978 -0.10428322
[49] 0.27943832 0.08708669 3.09080930 0.81236054 -0.53332627 0.07621748
[55] 1.68290212 0.24487406 -1.61625634 0.08545443 -1.43977886 0.76697196
[61] 0.40007073 1.41895271 -1.40520944 1.36690420 -0.66729950 -0.26058400
[67] -0.47460554 0.05345401 0.48493496 -0.60938687 1.23074683 -0.83418561
[73] 1.12162230 -2.30505337 0.14889137 -0.86521774 -1.54844224 0.54253910
[79] -0.68873821 -1.81285432 0.84625512 -0.47917007 -1.92886529 -0.81122002
[85] -0.73681151 0.15606235 0.40906336 3.05388527 -0.18067377 0.72625835
[91] 1.34738722 -0.71519102 0.47008241 0.59442385 -0.44641672 -0.49332505
[97] -0.59034417 -0.42210185 -1.67030782 1.10898107
> colMin(tmp)
[1] -0.49412861 0.24748402 0.14093966 0.58150479 -0.14133062 -2.48258580
[7] 0.16832961 0.44438180 -0.31472055 1.07852597 2.21581825 -0.41587200
[13] 0.69130501 0.20796390 1.17712369 -1.07490664 -0.36828791 0.53595846
[19] -0.87424471 0.39137374 0.06738095 -0.25723597 -1.54960090 1.26603884
[25] -0.69686876 0.87704418 -1.45362098 1.91445906 -0.93232786 -0.79261253
[31] 2.15581078 -1.44156350 -0.50443321 0.54564496 1.83358521 -1.61927592
[37] 0.88558157 0.95278390 -0.50353949 -1.36836354 -0.86891834 0.60668381
[43] 0.51484877 0.42807406 2.11985856 0.68323666 0.29883978 -0.10428322
[49] 0.27943832 0.08708669 3.09080930 0.81236054 -0.53332627 0.07621748
[55] 1.68290212 0.24487406 -1.61625634 0.08545443 -1.43977886 0.76697196
[61] 0.40007073 1.41895271 -1.40520944 1.36690420 -0.66729950 -0.26058400
[67] -0.47460554 0.05345401 0.48493496 -0.60938687 1.23074683 -0.83418561
[73] 1.12162230 -2.30505337 0.14889137 -0.86521774 -1.54844224 0.54253910
[79] -0.68873821 -1.81285432 0.84625512 -0.47917007 -1.92886529 -0.81122002
[85] -0.73681151 0.15606235 0.40906336 3.05388527 -0.18067377 0.72625835
[91] 1.34738722 -0.71519102 0.47008241 0.59442385 -0.44641672 -0.49332505
[97] -0.59034417 -0.42210185 -1.67030782 1.10898107
> colMedians(tmp)
[1] -0.49412861 0.24748402 0.14093966 0.58150479 -0.14133062 -2.48258580
[7] 0.16832961 0.44438180 -0.31472055 1.07852597 2.21581825 -0.41587200
[13] 0.69130501 0.20796390 1.17712369 -1.07490664 -0.36828791 0.53595846
[19] -0.87424471 0.39137374 0.06738095 -0.25723597 -1.54960090 1.26603884
[25] -0.69686876 0.87704418 -1.45362098 1.91445906 -0.93232786 -0.79261253
[31] 2.15581078 -1.44156350 -0.50443321 0.54564496 1.83358521 -1.61927592
[37] 0.88558157 0.95278390 -0.50353949 -1.36836354 -0.86891834 0.60668381
[43] 0.51484877 0.42807406 2.11985856 0.68323666 0.29883978 -0.10428322
[49] 0.27943832 0.08708669 3.09080930 0.81236054 -0.53332627 0.07621748
[55] 1.68290212 0.24487406 -1.61625634 0.08545443 -1.43977886 0.76697196
[61] 0.40007073 1.41895271 -1.40520944 1.36690420 -0.66729950 -0.26058400
[67] -0.47460554 0.05345401 0.48493496 -0.60938687 1.23074683 -0.83418561
[73] 1.12162230 -2.30505337 0.14889137 -0.86521774 -1.54844224 0.54253910
[79] -0.68873821 -1.81285432 0.84625512 -0.47917007 -1.92886529 -0.81122002
[85] -0.73681151 0.15606235 0.40906336 3.05388527 -0.18067377 0.72625835
[91] 1.34738722 -0.71519102 0.47008241 0.59442385 -0.44641672 -0.49332505
[97] -0.59034417 -0.42210185 -1.67030782 1.10898107
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.4941286 0.247484 0.1409397 0.5815048 -0.1413306 -2.482586 0.1683296
[2,] -0.4941286 0.247484 0.1409397 0.5815048 -0.1413306 -2.482586 0.1683296
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.4443818 -0.3147206 1.078526 2.215818 -0.415872 0.691305 0.2079639
[2,] 0.4443818 -0.3147206 1.078526 2.215818 -0.415872 0.691305 0.2079639
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.177124 -1.074907 -0.3682879 0.5359585 -0.8742447 0.3913737 0.06738095
[2,] 1.177124 -1.074907 -0.3682879 0.5359585 -0.8742447 0.3913737 0.06738095
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.257236 -1.549601 1.266039 -0.6968688 0.8770442 -1.453621 1.914459
[2,] -0.257236 -1.549601 1.266039 -0.6968688 0.8770442 -1.453621 1.914459
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.9323279 -0.7926125 2.155811 -1.441563 -0.5044332 0.545645 1.833585
[2,] -0.9323279 -0.7926125 2.155811 -1.441563 -0.5044332 0.545645 1.833585
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.619276 0.8855816 0.9527839 -0.5035395 -1.368364 -0.8689183 0.6066838
[2,] -1.619276 0.8855816 0.9527839 -0.5035395 -1.368364 -0.8689183 0.6066838
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5148488 0.4280741 2.119859 0.6832367 0.2988398 -0.1042832 0.2794383
[2,] 0.5148488 0.4280741 2.119859 0.6832367 0.2988398 -0.1042832 0.2794383
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.08708669 3.090809 0.8123605 -0.5333263 0.07621748 1.682902 0.2448741
[2,] 0.08708669 3.090809 0.8123605 -0.5333263 0.07621748 1.682902 0.2448741
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.616256 0.08545443 -1.439779 0.766972 0.4000707 1.418953 -1.405209
[2,] -1.616256 0.08545443 -1.439779 0.766972 0.4000707 1.418953 -1.405209
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.366904 -0.6672995 -0.260584 -0.4746055 0.05345401 0.484935 -0.6093869
[2,] 1.366904 -0.6672995 -0.260584 -0.4746055 0.05345401 0.484935 -0.6093869
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.230747 -0.8341856 1.121622 -2.305053 0.1488914 -0.8652177 -1.548442
[2,] 1.230747 -0.8341856 1.121622 -2.305053 0.1488914 -0.8652177 -1.548442
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.5425391 -0.6887382 -1.812854 0.8462551 -0.4791701 -1.928865 -0.81122
[2,] 0.5425391 -0.6887382 -1.812854 0.8462551 -0.4791701 -1.928865 -0.81122
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.7368115 0.1560623 0.4090634 3.053885 -0.1806738 0.7262583 1.347387
[2,] -0.7368115 0.1560623 0.4090634 3.053885 -0.1806738 0.7262583 1.347387
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.715191 0.4700824 0.5944238 -0.4464167 -0.493325 -0.5903442 -0.4221019
[2,] -0.715191 0.4700824 0.5944238 -0.4464167 -0.493325 -0.5903442 -0.4221019
[,99] [,100]
[1,] -1.670308 1.108981
[2,] -1.670308 1.108981
>
>
> Max(tmp2)
[1] 2.181814
> Min(tmp2)
[1] -2.389006
> mean(tmp2)
[1] -0.01096015
> Sum(tmp2)
[1] -1.096015
> Var(tmp2)
[1] 0.7987797
>
> rowMeans(tmp2)
[1] 1.011842394 -0.166580299 -1.209642578 0.829452691 0.908195943
[6] -0.203066834 0.386737075 1.177306453 0.262346898 -1.010935923
[11] -0.719062086 0.255633801 1.043931048 1.036695437 -0.442503657
[16] 1.039784114 0.351187279 0.877674563 -0.671032133 -0.674538144
[21] 0.277149532 -1.441589750 -0.465346108 -0.881642022 -0.578278722
[26] 0.083060029 1.133884285 -0.125224156 -0.373792677 0.131456115
[31] -0.247740838 -1.329482547 0.072707865 1.886827430 1.276725828
[36] -0.284395216 -0.633543313 -0.686674327 1.082563906 -1.046171052
[41] -0.950912408 0.266643756 0.229480062 -1.221757425 -1.111158831
[46] 0.943510377 -0.899801530 0.209387499 1.988691028 1.187531618
[51] -2.389006287 -0.180126338 0.760025400 0.063715285 0.043828724
[56] 1.460213826 0.529116431 -0.219779656 0.195470092 0.183831233
[61] 0.716516690 -1.101979950 -0.474867761 -0.420562293 1.115571659
[66] -0.865505308 0.460654064 0.131481552 0.110821608 0.410148223
[71] -0.754584948 0.419157182 -1.106902355 0.375001990 0.068778172
[76] 0.034147553 0.337130794 0.085084575 0.530883510 -1.106928482
[81] -0.730536106 2.181814479 -1.797945783 -1.285155813 -0.238240846
[86] 0.934572359 0.137874328 -0.904100072 0.735283076 -0.015541200
[91] -1.601361796 0.007601725 1.046324146 0.787004143 0.537830325
[96] -0.613851139 -0.380481508 0.740120291 -2.264811500 -0.359283743
> rowSums(tmp2)
[1] 1.011842394 -0.166580299 -1.209642578 0.829452691 0.908195943
[6] -0.203066834 0.386737075 1.177306453 0.262346898 -1.010935923
[11] -0.719062086 0.255633801 1.043931048 1.036695437 -0.442503657
[16] 1.039784114 0.351187279 0.877674563 -0.671032133 -0.674538144
[21] 0.277149532 -1.441589750 -0.465346108 -0.881642022 -0.578278722
[26] 0.083060029 1.133884285 -0.125224156 -0.373792677 0.131456115
[31] -0.247740838 -1.329482547 0.072707865 1.886827430 1.276725828
[36] -0.284395216 -0.633543313 -0.686674327 1.082563906 -1.046171052
[41] -0.950912408 0.266643756 0.229480062 -1.221757425 -1.111158831
[46] 0.943510377 -0.899801530 0.209387499 1.988691028 1.187531618
[51] -2.389006287 -0.180126338 0.760025400 0.063715285 0.043828724
[56] 1.460213826 0.529116431 -0.219779656 0.195470092 0.183831233
[61] 0.716516690 -1.101979950 -0.474867761 -0.420562293 1.115571659
[66] -0.865505308 0.460654064 0.131481552 0.110821608 0.410148223
[71] -0.754584948 0.419157182 -1.106902355 0.375001990 0.068778172
[76] 0.034147553 0.337130794 0.085084575 0.530883510 -1.106928482
[81] -0.730536106 2.181814479 -1.797945783 -1.285155813 -0.238240846
[86] 0.934572359 0.137874328 -0.904100072 0.735283076 -0.015541200
[91] -1.601361796 0.007601725 1.046324146 0.787004143 0.537830325
[96] -0.613851139 -0.380481508 0.740120291 -2.264811500 -0.359283743
> 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] 1.011842394 -0.166580299 -1.209642578 0.829452691 0.908195943
[6] -0.203066834 0.386737075 1.177306453 0.262346898 -1.010935923
[11] -0.719062086 0.255633801 1.043931048 1.036695437 -0.442503657
[16] 1.039784114 0.351187279 0.877674563 -0.671032133 -0.674538144
[21] 0.277149532 -1.441589750 -0.465346108 -0.881642022 -0.578278722
[26] 0.083060029 1.133884285 -0.125224156 -0.373792677 0.131456115
[31] -0.247740838 -1.329482547 0.072707865 1.886827430 1.276725828
[36] -0.284395216 -0.633543313 -0.686674327 1.082563906 -1.046171052
[41] -0.950912408 0.266643756 0.229480062 -1.221757425 -1.111158831
[46] 0.943510377 -0.899801530 0.209387499 1.988691028 1.187531618
[51] -2.389006287 -0.180126338 0.760025400 0.063715285 0.043828724
[56] 1.460213826 0.529116431 -0.219779656 0.195470092 0.183831233
[61] 0.716516690 -1.101979950 -0.474867761 -0.420562293 1.115571659
[66] -0.865505308 0.460654064 0.131481552 0.110821608 0.410148223
[71] -0.754584948 0.419157182 -1.106902355 0.375001990 0.068778172
[76] 0.034147553 0.337130794 0.085084575 0.530883510 -1.106928482
[81] -0.730536106 2.181814479 -1.797945783 -1.285155813 -0.238240846
[86] 0.934572359 0.137874328 -0.904100072 0.735283076 -0.015541200
[91] -1.601361796 0.007601725 1.046324146 0.787004143 0.537830325
[96] -0.613851139 -0.380481508 0.740120291 -2.264811500 -0.359283743
> rowMin(tmp2)
[1] 1.011842394 -0.166580299 -1.209642578 0.829452691 0.908195943
[6] -0.203066834 0.386737075 1.177306453 0.262346898 -1.010935923
[11] -0.719062086 0.255633801 1.043931048 1.036695437 -0.442503657
[16] 1.039784114 0.351187279 0.877674563 -0.671032133 -0.674538144
[21] 0.277149532 -1.441589750 -0.465346108 -0.881642022 -0.578278722
[26] 0.083060029 1.133884285 -0.125224156 -0.373792677 0.131456115
[31] -0.247740838 -1.329482547 0.072707865 1.886827430 1.276725828
[36] -0.284395216 -0.633543313 -0.686674327 1.082563906 -1.046171052
[41] -0.950912408 0.266643756 0.229480062 -1.221757425 -1.111158831
[46] 0.943510377 -0.899801530 0.209387499 1.988691028 1.187531618
[51] -2.389006287 -0.180126338 0.760025400 0.063715285 0.043828724
[56] 1.460213826 0.529116431 -0.219779656 0.195470092 0.183831233
[61] 0.716516690 -1.101979950 -0.474867761 -0.420562293 1.115571659
[66] -0.865505308 0.460654064 0.131481552 0.110821608 0.410148223
[71] -0.754584948 0.419157182 -1.106902355 0.375001990 0.068778172
[76] 0.034147553 0.337130794 0.085084575 0.530883510 -1.106928482
[81] -0.730536106 2.181814479 -1.797945783 -1.285155813 -0.238240846
[86] 0.934572359 0.137874328 -0.904100072 0.735283076 -0.015541200
[91] -1.601361796 0.007601725 1.046324146 0.787004143 0.537830325
[96] -0.613851139 -0.380481508 0.740120291 -2.264811500 -0.359283743
>
> colMeans(tmp2)
[1] -0.01096015
> colSums(tmp2)
[1] -1.096015
> colVars(tmp2)
[1] 0.7987797
> colSd(tmp2)
[1] 0.8937448
> colMax(tmp2)
[1] 2.181814
> colMin(tmp2)
[1] -2.389006
> colMedians(tmp2)
[1] 0.07074302
> colRanges(tmp2)
[,1]
[1,] -2.389006
[2,] 2.181814
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.61806852 -2.15992008 4.28271010 -3.20894664 -0.93853810 -0.09289747
[7] 1.72165999 -2.40189783 -0.59367581 -4.10815377
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5263277
[2,] -0.4225444
[3,] 0.1289817
[4,] 0.5106540
[5,] 1.7634262
>
> rowApply(tmp,sum)
[1] 1.0844374 1.6477053 -4.8339105 0.1830263 -0.3761082 -1.8174864
[7] -0.4087531 1.7740992 -1.6140341 -1.5205668
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 3 6 5 7 6 9 6 7 5
[2,] 10 6 2 9 3 7 2 3 3 3
[3,] 5 10 4 8 9 4 7 5 8 4
[4,] 3 4 3 2 4 8 6 1 6 8
[5,] 8 7 5 3 6 2 3 4 10 6
[6,] 1 8 10 10 5 3 4 7 5 1
[7,] 2 5 9 7 1 5 10 2 9 9
[8,] 4 9 8 4 8 1 1 9 2 10
[9,] 9 1 1 1 10 9 8 8 4 7
[10,] 6 2 7 6 2 10 5 10 1 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.4127884 -0.8928357 4.0961131 -4.4472879 -0.4928791 -1.4331696
[7] 0.4255963 0.2183235 0.2554718 1.9340113 -0.8939587 0.6504861
[13] -0.1737329 0.9872431 2.0548520 1.7072712 2.4829502 1.0464814
[19] -2.3940764 0.1259750
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3109004
[2,] -0.4937554
[3,] 0.6301298
[4,] 0.9503460
[5,] 1.6369685
>
> rowApply(tmp,sum)
[1] -0.5469078 2.1344661 2.2536975 2.1422820 0.6860855
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 19 20 4 16 1
[2,] 4 5 15 5 12
[3,] 20 8 12 18 19
[4,] 2 6 1 1 13
[5,] 9 16 8 10 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.9503460 -0.5761894 1.42121071 -1.2358855 -0.15601965 -0.5493655
[2,] 1.6369685 -0.5796094 -0.04431254 -0.5431384 0.76239887 0.3786448
[3,] -0.4937554 0.5083862 0.21236283 -1.0445171 -0.13273129 -0.2215050
[4,] 0.6301298 -0.4759102 1.26847046 -1.9600756 0.04088395 -0.3766158
[5,] -1.3109004 0.2304871 1.23838169 0.3363286 -1.00741099 -0.6643281
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.3851249 0.72158222 0.6047478 0.62999063 0.01822904 0.8166909
[2,] 0.1675703 -1.95172125 -0.4738548 1.48694062 0.38572213 -1.1509658
[3,] 0.5177857 -0.91840237 -0.0786752 0.01422775 -0.01702060 0.7888168
[4,] 0.3025434 0.02224565 -0.6162845 -0.74137398 -0.39650076 1.0040717
[5,] -0.1771782 2.34461929 0.8195384 0.54422631 -0.88438853 -0.8081275
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.50623451 -0.1199944 -0.2143004 0.1190664 -0.1680474 0.03237575
[2,] -0.61189691 1.5523943 1.0911735 0.3660736 0.1249065 0.10954552
[3,] 1.72620298 -0.2633423 0.4024103 1.4980781 0.7098482 0.42053510
[4,] 0.03158706 0.2654324 0.1816167 0.5214824 1.4650890 -0.70345211
[5,] 0.18660849 -0.4472469 0.5939519 -0.7974292 0.3511539 1.18747710
[,19] [,20]
[1,] -1.2281873 0.2782017
[2,] -0.7354838 0.1631104
[3,] -0.4887869 -0.8862203
[4,] 0.3333428 1.3455996
[5,] -0.2749611 -0.7747165
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.6969207 0.1834209 0.8168111 -2.545656 -0.8607023 0.7060815 -0.2744488
col8 col9 col10 col11 col12 col13
row1 -0.8041147 0.7623139 -0.02663097 0.7181733 -0.1138912 -0.4688809
col14 col15 col16 col17 col18 col19 col20
row1 0.05655163 -2.094748 -0.6317276 0.1927797 -1.062717 -0.3848136 0.9860062
> tmp[,"col10"]
col10
row1 -0.026630968
row2 1.448709621
row3 -1.496975015
row4 -0.008533216
row5 0.274619511
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.6969207 0.1834209 0.8168111 -2.5456563 -0.86070235 0.7060815
row5 0.4892857 -0.7584824 1.7651608 0.1233968 -0.05888677 -0.5448192
col7 col8 col9 col10 col11 col12
row1 -0.2744488 -0.8041147 0.7623139 -0.02663097 0.7181733 -0.1138912
row5 -0.1058808 -1.1566698 0.3319794 0.27461951 1.2977851 0.5492686
col13 col14 col15 col16 col17 col18
row1 -0.4688809 0.05655163 -2.094748 -0.6317276 0.19277966 -1.0627166
row5 -1.2271300 0.60424253 -0.293824 0.3951931 -0.04954332 -0.2028682
col19 col20
row1 -0.3848136 0.9860062
row5 0.9460678 0.2628344
> tmp[,c("col6","col20")]
col6 col20
row1 0.7060815 0.9860062
row2 -0.7614850 0.1924748
row3 0.8519445 0.7319534
row4 0.7471846 -0.4384606
row5 -0.5448192 0.2628344
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.7060815 0.9860062
row5 -0.5448192 0.2628344
>
>
>
>
> 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 51.42786 49.14767 49.87624 48.99464 49.67336 103.746 51.19965 48.33965
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.94162 48.96364 51.01245 50.09549 50.63913 51.40998 51.10866 50.79454
col17 col18 col19 col20
row1 49.63268 49.56348 50.13524 103.9906
> tmp[,"col10"]
col10
row1 48.96364
row2 30.98485
row3 29.87200
row4 31.74286
row5 51.26749
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.42786 49.14767 49.87624 48.99464 49.67336 103.7460 51.19965 48.33965
row5 49.15007 48.39580 49.73945 51.03383 48.75641 107.3702 50.06111 50.40000
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.94162 48.96364 51.01245 50.09549 50.63913 51.40998 51.10866 50.79454
row5 51.59192 51.26749 50.50043 50.40659 50.29593 47.66888 49.84790 48.19723
col17 col18 col19 col20
row1 49.63268 49.56348 50.13524 103.9906
row5 48.22826 48.60405 50.24226 106.3753
> tmp[,c("col6","col20")]
col6 col20
row1 103.74603 103.99060
row2 76.70236 74.86099
row3 75.99194 75.69198
row4 74.89374 75.30958
row5 107.37021 106.37528
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.7460 103.9906
row5 107.3702 106.3753
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.7460 103.9906
row5 107.3702 106.3753
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.6032554
[2,] 0.9850313
[3,] 0.4087550
[4,] -1.2158720
[5,] 0.6862927
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.4952497 -1.8635528
[2,] 1.2858811 0.9987329
[3,] 0.9410338 -0.8586085
[4,] -0.1484563 1.4114435
[5,] 0.5607907 1.1893616
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.735161129 -0.3574740
[2,] 0.638769629 -0.5615112
[3,] 0.001469545 -0.3935794
[4,] 0.250108506 1.0890504
[5,] 0.536552368 0.1593953
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.7351611
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.7351611
[2,] 0.6387696
>
>
>
> 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 -0.2642721 -1.5912748 1.6931867 1.395863 0.6670674 -1.103109 0.1758874
row1 -0.2662225 -0.8597355 -0.7817941 1.011905 -0.3997715 -1.059017 1.2944528
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.01515421 0.9957019 -0.1216228 -0.6641233 0.8885168 -0.9816116
row1 -0.69304153 -0.8268653 -0.7872625 0.1105319 0.9124232 0.9090630
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.6228874 -0.05111966 1.380188 -0.1386411 0.6085929 2.0007851 -1.4042637
row1 0.2958188 0.87165868 1.316041 -0.4473792 1.2253318 0.4420264 -0.4618204
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.9641401 -0.5597776 -0.4141481 -0.8469201 -1.121188 0.1441316 1.674229
[,8] [,9] [,10]
row2 0.216762 -0.4617245 -2.038301
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.2231146 1.68062 -0.5107243 -0.1428438 0.07932617 -0.2253256 -1.235242
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.8025582 -0.1233587 1.605043 -0.9478398 1.058464 1.221787 -1.110924
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2248137 0.1752184 0.1686501 0.1455692 -0.7182492 0.004616957
>
>
> 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: 0x2c4889e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b27663ce27b"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b2742c42aae"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b2793b551c"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b272b1682c1"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b2749c15b28"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b274ec2fccc"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b274de7bcf1"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b27786e8e9b"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b27717be2ca"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b2719d6f492"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b275be1fbf8"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b271aa7fdc5"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b2764763989"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b276922388b"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM320b27a5e87e"
>
>
> ### 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: 0x2a299930>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x2a299930>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x2a299930>
> rowMedians(tmp)
[1] -0.421673882 -0.118907951 -0.104974699 0.114277671 0.339295111
[6] -0.497108562 1.085850759 0.239396956 -0.355611795 0.264694180
[11] -0.098584419 0.059349600 -0.804036827 0.324893738 -0.009751276
[16] 0.125152916 -0.115436653 0.472211066 -0.415691609 -0.255260284
[21] 0.192205135 0.090514799 0.087428465 -0.223296866 -0.153691811
[26] -0.109130644 -0.178561629 -0.366151440 -0.783148898 0.136746267
[31] 0.283877127 0.328961044 0.265691983 -0.134411512 -0.100633951
[36] 0.215733487 0.090721742 -0.099207735 -0.249818058 -0.136386751
[41] 0.681412149 0.089031011 0.048392943 0.231001815 -0.155325375
[46] -0.251116787 0.069645432 0.353666184 0.281133280 0.360222581
[51] 0.495666280 -0.252513355 -0.117164090 -0.237124187 0.106204329
[56] 0.092575116 -0.204259517 -0.227095747 -0.102999553 -0.302487090
[61] -0.012331086 -0.311325925 -0.118177880 -0.085207398 0.141908180
[66] 0.455540971 -0.440410528 -0.411127423 0.156833350 0.084649427
[71] 0.020740335 0.217079450 -0.635704878 0.342570045 0.060883505
[76] -0.078824909 0.041852447 0.080567667 -0.091044168 -0.191016711
[81] -0.166975188 -0.135466814 0.022758301 0.201390551 -0.155694196
[86] -0.134663069 0.586894491 -0.101766619 -0.159721314 0.260444051
[91] -0.220993949 -0.238429637 -0.090571663 -0.172615651 -0.245263161
[96] 0.074294011 -0.028761330 -0.050055161 -0.407922614 0.034343544
[101] 0.060162914 -0.056878404 0.662640714 -0.462294939 0.078826975
[106] 0.695047370 0.057179473 -0.112058841 0.229329435 0.366666354
[111] -0.006413997 0.082151018 -0.134493760 -0.060811191 0.485138914
[116] -0.241875683 -0.141787654 0.362155462 0.546901647 0.056357329
[121] -0.271712403 -0.351660243 1.091761932 0.068941118 0.430736445
[126] 0.354860816 0.171629477 0.548858099 -0.457118358 -0.378078189
[131] -0.185382025 -0.346842695 0.170810655 -0.413315231 0.054558326
[136] -0.137733050 -0.315631619 -0.220597165 0.411964807 -0.057212805
[141] 0.143863033 0.137116428 0.497996879 0.192430106 -0.081293541
[146] 0.535598332 -0.292886864 -0.562212345 -0.357148210 0.085820773
[151] 0.080923593 -0.004740912 0.647582490 0.112347350 0.006171088
[156] 0.384039121 0.012493870 0.022372898 -0.019738295 -0.096036389
[161] 0.292719626 0.346743590 -0.300072125 -0.013374756 0.051690099
[166] 0.152133902 0.185501645 -0.112923960 -0.342310646 -0.114370681
[171] -0.211661021 0.544972409 0.187537565 -0.257745453 -0.326486501
[176] -0.061182184 0.140795180 0.315877812 -0.046935768 0.081157971
[181] -0.437762575 -0.230698615 0.217864816 -0.232422875 0.115960662
[186] 0.167482907 -0.120483193 -0.081156574 -0.351072144 -0.163374910
[191] -0.001066937 -0.162818571 0.410979047 -0.626104719 -0.215011302
[196] 0.297023026 -0.151859681 -0.774031597 -0.164740940 0.170858916
[201] -0.196199445 0.022983797 -0.276367138 -0.232941178 0.363477055
[206] -0.478473126 -0.180522747 0.033830041 0.098956307 -0.396087211
[211] -0.012371742 0.205024632 0.154165848 -0.203670837 -0.046687047
[216] 0.590673154 -0.058176967 0.386556013 0.220112450 0.075522895
[221] -0.725075651 -0.158411687 0.242997564 0.246559056 -0.081737922
[226] 0.829656945 -0.175319454 -0.278364800 0.496169869 0.233889868
>
> proc.time()
user system elapsed
1.754 0.887 2.667
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: 0x2a4c1ff0>
> .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: 0x2a4c1ff0>
> .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: 0x2a4c1ff0>
> .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: 0x2a4c1ff0>
> 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: 0x2a3a70e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2a3a70e0>
> .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: 0x2a3a70e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2a3a70e0>
> .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: 0x2a3a70e0>
> 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: 0x2932e520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2932e520>
> .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: 0x2932e520>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2932e520>
> .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: 0x2932e520>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x2932e520>
> .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: 0x2932e520>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x2932e520>
> .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: 0x2932e520>
> 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: 0x28d32720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x28d32720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x28d32720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x28d32720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile320b491024402c" "BufferedMatrixFile320b49d9f624b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile320b491024402c" "BufferedMatrixFile320b49d9f624b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x29c227d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x29c227d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x29c227d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x29c227d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x29c227d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x29c227d0>
> .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: 0x29d29c90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x29d29c90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x29d29c90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x29d29c90>
> 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: 0x2afd2110>
> .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: 0x2afd2110>
> rm(P)
>
> proc.time()
user system elapsed
0.332 0.034 0.351
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
0.346 0.041 0.371