Ben Bolstad
| Snapshot Date: 2025-12-11 13:45 -0500 (Thu, 11 Dec 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 2025-12-15 12:08 -0500 (Mon, 15 Dec 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" | 4882 |
| merida1 | macOS 12.7.6 Monterey | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4673 |
| kjohnson1 | macOS 13.7.5 Ventura | arm64 | 4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble" | 4607 |
| 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 | | ||||||||
| 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: 2025-12-12 08:07:04 -0000 (Fri, 12 Dec 2025) |
| EndedAt: 2025-12-12 08:07:34 -0000 (Fri, 12 Dec 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
0.331 0.048 0.364
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 Dec 12 08:07:29 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 Dec 12 08:07:29 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: 0x1f3e5ff0>
>
>
>
> 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 Dec 12 08:07:29 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 Dec 12 08:07:29 2025"
>
> ColMode(tmp2)
<pointer: 0x1f3e5ff0>
>
>
>
> ### 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,] 100.0901482 1.4099052 0.2682947 -0.3149959
[2,] -0.6183250 -1.5640288 -0.8621976 -0.1861504
[3,] -0.3493194 -0.7287397 0.1940043 1.2633023
[4,] 1.7386625 -1.0515311 -0.2461267 0.8111920
> 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,] 100.0901482 1.4099052 0.2682947 0.3149959
[2,] 0.6183250 1.5640288 0.8621976 0.1861504
[3,] 0.3493194 0.7287397 0.1940043 1.2633023
[4,] 1.7386625 1.0515311 0.2461267 0.8111920
> 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,] 10.0045064 1.1873943 0.5179717 0.5612450
[2,] 0.7863365 1.2506114 0.9285460 0.4314515
[3,] 0.5910324 0.8536625 0.4404592 1.1239672
[4,] 1.3185835 1.0254419 0.4961116 0.9006620
>
> 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,] 225.13521 38.28385 30.44801 30.92745
[2,] 33.48169 39.07014 35.14766 29.50067
[3,] 31.25964 34.26536 29.59860 37.50297
[4,] 39.92450 36.30595 30.20724 34.81781
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x1e0c86c0>
> exp(tmp5)
<pointer: 0x1e0c86c0>
> log(tmp5,2)
<pointer: 0x1e0c86c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.5894
> Min(tmp5)
[1] 53.23968
> mean(tmp5)
[1] 73.70708
> Sum(tmp5)
[1] 14741.42
> Var(tmp5)
[1] 867.2256
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.67725 72.31262 69.39100 72.04048 70.68566 68.24811 73.55731 73.53994
[9] 74.42234 70.19611
> rowSums(tmp5)
[1] 1853.545 1446.252 1387.820 1440.810 1413.713 1364.962 1471.146 1470.799
[9] 1488.447 1403.922
> rowVars(tmp5)
[1] 7937.43927 58.76291 68.39822 84.40792 115.93302 43.22987
[7] 82.84463 72.87038 94.21956 67.00855
> rowSd(tmp5)
[1] 89.092308 7.665697 8.270322 9.187378 10.767219 6.574943 9.101903
[8] 8.536415 9.706676 8.185875
> rowMax(tmp5)
[1] 468.58945 83.70819 82.07327 89.54769 92.67584 83.90805 94.96690
[8] 88.01372 92.30599 87.76532
> rowMin(tmp5)
[1] 55.64139 54.38613 53.64059 57.02722 56.27555 54.49598 58.29203 57.41669
[9] 53.23968 55.81933
>
> colMeans(tmp5)
[1] 109.00192 77.26363 65.97851 68.43860 73.93230 73.45717 74.30468
[8] 73.29006 66.92427 67.48857 74.55336 75.90495 72.04732 72.64267
[15] 72.33624 75.02101 69.04505 71.55759 71.17740 69.77636
> colSums(tmp5)
[1] 1090.0192 772.6363 659.7851 684.3860 739.3230 734.5717 743.0468
[8] 732.9006 669.2427 674.8857 745.5336 759.0495 720.4732 726.4267
[15] 723.3624 750.2101 690.4505 715.5759 711.7740 697.7636
> colVars(tmp5)
[1] 16022.89932 66.55592 52.18105 29.53028 30.42951 90.97365
[7] 139.61790 38.66177 68.50622 107.71699 76.08981 28.60739
[13] 97.31907 101.77972 107.17536 131.73417 149.08514 56.86774
[19] 60.24838 61.08909
> colSd(tmp5)
[1] 126.581592 8.158181 7.223645 5.434177 5.516295 9.538011
[7] 11.816002 6.217859 8.276848 10.378679 8.722947 5.348587
[13] 9.865043 10.088594 10.352553 11.477551 12.210043 7.541070
[19] 7.761983 7.815951
> colMax(tmp5)
[1] 468.58945 92.67584 81.37778 78.05753 81.18809 83.70819 94.96690
[8] 80.48202 79.47163 85.35228 92.27293 82.38188 86.68399 87.15768
[15] 87.47771 89.54769 92.30599 87.76532 81.19182 79.33806
> colMin(tmp5)
[1] 58.35920 65.46648 57.02555 61.40177 65.02488 55.81933 59.29331 59.62811
[9] 53.23968 53.64059 61.19543 65.44207 57.41669 58.29203 55.64139 60.78477
[17] 54.38613 59.61844 58.35657 56.27555
>
>
> ### 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] 92.67725 72.31262 69.39100 72.04048 NA 68.24811 73.55731 73.53994
[9] 74.42234 70.19611
> rowSums(tmp5)
[1] 1853.545 1446.252 1387.820 1440.810 NA 1364.962 1471.146 1470.799
[9] 1488.447 1403.922
> rowVars(tmp5)
[1] 7937.43927 58.76291 68.39822 84.40792 121.07236 43.22987
[7] 82.84463 72.87038 94.21956 67.00855
> rowSd(tmp5)
[1] 89.092308 7.665697 8.270322 9.187378 11.003289 6.574943 9.101903
[8] 8.536415 9.706676 8.185875
> rowMax(tmp5)
[1] 468.58945 83.70819 82.07327 89.54769 NA 83.90805 94.96690
[8] 88.01372 92.30599 87.76532
> rowMin(tmp5)
[1] 55.64139 54.38613 53.64059 57.02722 NA 54.49598 58.29203 57.41669
[9] 53.23968 55.81933
>
> colMeans(tmp5)
[1] 109.00192 77.26363 65.97851 68.43860 73.93230 73.45717 74.30468
[8] 73.29006 66.92427 67.48857 74.55336 75.90495 NA 72.64267
[15] 72.33624 75.02101 69.04505 71.55759 71.17740 69.77636
> colSums(tmp5)
[1] 1090.0192 772.6363 659.7851 684.3860 739.3230 734.5717 743.0468
[8] 732.9006 669.2427 674.8857 745.5336 759.0495 NA 726.4267
[15] 723.3624 750.2101 690.4505 715.5759 711.7740 697.7636
> colVars(tmp5)
[1] 16022.89932 66.55592 52.18105 29.53028 30.42951 90.97365
[7] 139.61790 38.66177 68.50622 107.71699 76.08981 28.60739
[13] NA 101.77972 107.17536 131.73417 149.08514 56.86774
[19] 60.24838 61.08909
> colSd(tmp5)
[1] 126.581592 8.158181 7.223645 5.434177 5.516295 9.538011
[7] 11.816002 6.217859 8.276848 10.378679 8.722947 5.348587
[13] NA 10.088594 10.352553 11.477551 12.210043 7.541070
[19] 7.761983 7.815951
> colMax(tmp5)
[1] 468.58945 92.67584 81.37778 78.05753 81.18809 83.70819 94.96690
[8] 80.48202 79.47163 85.35228 92.27293 82.38188 NA 87.15768
[15] 87.47771 89.54769 92.30599 87.76532 81.19182 79.33806
> colMin(tmp5)
[1] 58.35920 65.46648 57.02555 61.40177 65.02488 55.81933 59.29331 59.62811
[9] 53.23968 53.64059 61.19543 65.44207 NA 58.29203 55.64139 60.78477
[17] 54.38613 59.61844 58.35657 56.27555
>
> Max(tmp5,na.rm=TRUE)
[1] 468.5894
> Min(tmp5,na.rm=TRUE)
[1] 53.23968
> mean(tmp5,na.rm=TRUE)
[1] 73.74597
> Sum(tmp5,na.rm=TRUE)
[1] 14675.45
> Var(tmp5,na.rm=TRUE)
[1] 871.3015
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.67725 72.31262 69.39100 72.04048 70.93395 68.24811 73.55731 73.53994
[9] 74.42234 70.19611
> rowSums(tmp5,na.rm=TRUE)
[1] 1853.545 1446.252 1387.820 1440.810 1347.745 1364.962 1471.146 1470.799
[9] 1488.447 1403.922
> rowVars(tmp5,na.rm=TRUE)
[1] 7937.43927 58.76291 68.39822 84.40792 121.07236 43.22987
[7] 82.84463 72.87038 94.21956 67.00855
> rowSd(tmp5,na.rm=TRUE)
[1] 89.092308 7.665697 8.270322 9.187378 11.003289 6.574943 9.101903
[8] 8.536415 9.706676 8.185875
> rowMax(tmp5,na.rm=TRUE)
[1] 468.58945 83.70819 82.07327 89.54769 92.67584 83.90805 94.96690
[8] 88.01372 92.30599 87.76532
> rowMin(tmp5,na.rm=TRUE)
[1] 55.64139 54.38613 53.64059 57.02722 56.27555 54.49598 58.29203 57.41669
[9] 53.23968 55.81933
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.00192 77.26363 65.97851 68.43860 73.93230 73.45717 74.30468
[8] 73.29006 66.92427 67.48857 74.55336 75.90495 72.72277 72.64267
[15] 72.33624 75.02101 69.04505 71.55759 71.17740 69.77636
> colSums(tmp5,na.rm=TRUE)
[1] 1090.0192 772.6363 659.7851 684.3860 739.3230 734.5717 743.0468
[8] 732.9006 669.2427 674.8857 745.5336 759.0495 654.5049 726.4267
[15] 723.3624 750.2101 690.4505 715.5759 711.7740 697.7636
> colVars(tmp5,na.rm=TRUE)
[1] 16022.89932 66.55592 52.18105 29.53028 30.42951 90.97365
[7] 139.61790 38.66177 68.50622 107.71699 76.08981 28.60739
[13] 104.35137 101.77972 107.17536 131.73417 149.08514 56.86774
[19] 60.24838 61.08909
> colSd(tmp5,na.rm=TRUE)
[1] 126.581592 8.158181 7.223645 5.434177 5.516295 9.538011
[7] 11.816002 6.217859 8.276848 10.378679 8.722947 5.348587
[13] 10.215252 10.088594 10.352553 11.477551 12.210043 7.541070
[19] 7.761983 7.815951
> colMax(tmp5,na.rm=TRUE)
[1] 468.58945 92.67584 81.37778 78.05753 81.18809 83.70819 94.96690
[8] 80.48202 79.47163 85.35228 92.27293 82.38188 86.68399 87.15768
[15] 87.47771 89.54769 92.30599 87.76532 81.19182 79.33806
> colMin(tmp5,na.rm=TRUE)
[1] 58.35920 65.46648 57.02555 61.40177 65.02488 55.81933 59.29331 59.62811
[9] 53.23968 53.64059 61.19543 65.44207 57.41669 58.29203 55.64139 60.78477
[17] 54.38613 59.61844 58.35657 56.27555
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.67725 72.31262 69.39100 72.04048 NaN 68.24811 73.55731 73.53994
[9] 74.42234 70.19611
> rowSums(tmp5,na.rm=TRUE)
[1] 1853.545 1446.252 1387.820 1440.810 0.000 1364.962 1471.146 1470.799
[9] 1488.447 1403.922
> rowVars(tmp5,na.rm=TRUE)
[1] 7937.43927 58.76291 68.39822 84.40792 NA 43.22987
[7] 82.84463 72.87038 94.21956 67.00855
> rowSd(tmp5,na.rm=TRUE)
[1] 89.092308 7.665697 8.270322 9.187378 NA 6.574943 9.101903
[8] 8.536415 9.706676 8.185875
> rowMax(tmp5,na.rm=TRUE)
[1] 468.58945 83.70819 82.07327 89.54769 NA 83.90805 94.96690
[8] 88.01372 92.30599 87.76532
> rowMin(tmp5,na.rm=TRUE)
[1] 55.64139 54.38613 53.64059 57.02722 NA 54.49598 58.29203 57.41669
[9] 53.23968 55.81933
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.28482 75.55116 66.97328 68.56072 73.52700 73.90534 75.31259
[8] 73.36411 67.24748 68.54934 74.29165 76.20763 NaN 71.02989
[15] 70.65385 76.60282 69.78679 70.94354 70.06469 71.27645
> colSums(tmp5,na.rm=TRUE)
[1] 1028.5633 679.9604 602.7596 617.0465 661.7430 665.1481 677.8133
[8] 660.2770 605.2273 616.9440 668.6248 685.8686 0.0000 639.2690
[15] 635.8847 689.4254 628.0811 638.4919 630.5822 641.4880
> colVars(tmp5,na.rm=TRUE)
[1] 17711.78531 41.88426 47.57096 33.05380 32.38515 100.08567
[7] 145.64141 43.43280 75.89427 108.52277 84.83049 31.15264
[13] NA 85.24028 88.73003 120.05225 161.53121 59.73437
[19] 53.85045 43.40970
> colSd(tmp5,na.rm=TRUE)
[1] 133.085632 6.471805 6.897171 5.749243 5.690795 10.004283
[7] 12.068198 6.590357 8.711732 10.417426 9.210347 5.581455
[13] NA 9.232566 9.419662 10.956836 12.709493 7.728801
[19] 7.338286 6.588604
> colMax(tmp5,na.rm=TRUE)
[1] 468.58945 83.90805 81.37778 78.05753 81.18809 83.70819 94.96690
[8] 80.48202 79.47163 85.35228 92.27293 82.38188 -Inf 82.07327
[15] 81.08749 89.54769 92.30599 87.76532 80.27262 79.33806
> colMin(tmp5,na.rm=TRUE)
[1] 58.35920 65.46648 59.94901 61.40177 65.02488 55.81933 59.29331 59.62811
[9] 53.23968 53.64059 61.19543 65.44207 Inf 58.29203 55.64139 63.42850
[17] 54.38613 59.61844 58.35657 58.66348
>
>
>
>
> 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] 376.5379 336.0492 114.3221 143.2956 383.9037 175.6216 293.5692 238.2207
[9] 291.9050 332.3857
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 376.5379 336.0492 114.3221 143.2956 383.9037 175.6216 293.5692 238.2207
[9] 291.9050 332.3857
>
>
>
> 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] 7.105427e-14 5.684342e-14 5.684342e-14 5.684342e-14 0.000000e+00
[6] 0.000000e+00 -1.421085e-14 2.842171e-14 -8.526513e-14 -2.557954e-13
[11] -5.684342e-14 4.263256e-14 2.842171e-14 0.000000e+00 -8.526513e-14
[16] -1.421085e-13 -2.273737e-13 -1.136868e-13 0.000000e+00 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)
+ }
6 4
3 13
8 9
2 17
8 2
6 8
6 13
3 13
1 10
8 6
7 17
5 2
10 14
10 2
1 3
2 14
7 10
8 2
8 10
4 12
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] 2.251839
> Min(tmp)
[1] -2.203132
> mean(tmp)
[1] 0.08174571
> Sum(tmp)
[1] 8.174571
> Var(tmp)
[1] 0.8447366
>
> rowMeans(tmp)
[1] 0.08174571
> rowSums(tmp)
[1] 8.174571
> rowVars(tmp)
[1] 0.8447366
> rowSd(tmp)
[1] 0.9190955
> rowMax(tmp)
[1] 2.251839
> rowMin(tmp)
[1] -2.203132
>
> colMeans(tmp)
[1] 1.00763917 1.07669726 -0.34136250 0.40301283 -0.70989952 1.48341727
[7] -1.55470636 -0.06571761 -0.71800569 0.06683039 -0.53810538 -0.02079210
[13] 0.19624015 0.62847665 -1.22208929 -0.74878391 1.07360793 0.54265635
[19] -0.80593260 0.93842491 0.52411779 -1.21842526 -0.20617680 -1.55095322
[25] 0.18689051 -0.38382633 -0.15727626 -0.74461297 -0.72929942 -1.65905462
[31] 1.49332151 0.89685141 1.28268811 -0.54524809 0.61696234 2.25183910
[37] 1.40994182 1.39375413 0.09601487 -1.61487952 0.13866345 0.87411732
[43] -0.09901415 -2.20313226 -0.57256789 -0.04902186 -0.60666961 1.11230875
[49] -1.16612178 -1.33729130 -0.87377830 -0.34865716 -0.07942622 -0.30052219
[55] 1.44263328 -0.62942745 -0.23092436 0.05764731 1.11335377 0.36256049
[61] 0.14552659 0.76497313 0.67630707 1.50083232 0.79904315 0.70417110
[67] 0.05148723 -0.85181713 -0.22206479 1.31610297 0.09130591 0.13800069
[73] 0.46770150 0.36193546 0.97051074 0.61398138 -1.04307247 -0.98605070
[79] 1.21907337 1.89086531 -0.44347310 -0.73289734 -0.17605875 0.19819328
[85] 0.59045295 -0.20567335 -0.13131869 0.58356694 1.41190236 0.44295669
[91] 0.74475897 -1.78547088 0.78582048 -0.72826654 1.44667213 -1.08328743
[97] 0.26696450 -0.56170130 -0.71022971 1.01388047
> colSums(tmp)
[1] 1.00763917 1.07669726 -0.34136250 0.40301283 -0.70989952 1.48341727
[7] -1.55470636 -0.06571761 -0.71800569 0.06683039 -0.53810538 -0.02079210
[13] 0.19624015 0.62847665 -1.22208929 -0.74878391 1.07360793 0.54265635
[19] -0.80593260 0.93842491 0.52411779 -1.21842526 -0.20617680 -1.55095322
[25] 0.18689051 -0.38382633 -0.15727626 -0.74461297 -0.72929942 -1.65905462
[31] 1.49332151 0.89685141 1.28268811 -0.54524809 0.61696234 2.25183910
[37] 1.40994182 1.39375413 0.09601487 -1.61487952 0.13866345 0.87411732
[43] -0.09901415 -2.20313226 -0.57256789 -0.04902186 -0.60666961 1.11230875
[49] -1.16612178 -1.33729130 -0.87377830 -0.34865716 -0.07942622 -0.30052219
[55] 1.44263328 -0.62942745 -0.23092436 0.05764731 1.11335377 0.36256049
[61] 0.14552659 0.76497313 0.67630707 1.50083232 0.79904315 0.70417110
[67] 0.05148723 -0.85181713 -0.22206479 1.31610297 0.09130591 0.13800069
[73] 0.46770150 0.36193546 0.97051074 0.61398138 -1.04307247 -0.98605070
[79] 1.21907337 1.89086531 -0.44347310 -0.73289734 -0.17605875 0.19819328
[85] 0.59045295 -0.20567335 -0.13131869 0.58356694 1.41190236 0.44295669
[91] 0.74475897 -1.78547088 0.78582048 -0.72826654 1.44667213 -1.08328743
[97] 0.26696450 -0.56170130 -0.71022971 1.01388047
> 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] 1.00763917 1.07669726 -0.34136250 0.40301283 -0.70989952 1.48341727
[7] -1.55470636 -0.06571761 -0.71800569 0.06683039 -0.53810538 -0.02079210
[13] 0.19624015 0.62847665 -1.22208929 -0.74878391 1.07360793 0.54265635
[19] -0.80593260 0.93842491 0.52411779 -1.21842526 -0.20617680 -1.55095322
[25] 0.18689051 -0.38382633 -0.15727626 -0.74461297 -0.72929942 -1.65905462
[31] 1.49332151 0.89685141 1.28268811 -0.54524809 0.61696234 2.25183910
[37] 1.40994182 1.39375413 0.09601487 -1.61487952 0.13866345 0.87411732
[43] -0.09901415 -2.20313226 -0.57256789 -0.04902186 -0.60666961 1.11230875
[49] -1.16612178 -1.33729130 -0.87377830 -0.34865716 -0.07942622 -0.30052219
[55] 1.44263328 -0.62942745 -0.23092436 0.05764731 1.11335377 0.36256049
[61] 0.14552659 0.76497313 0.67630707 1.50083232 0.79904315 0.70417110
[67] 0.05148723 -0.85181713 -0.22206479 1.31610297 0.09130591 0.13800069
[73] 0.46770150 0.36193546 0.97051074 0.61398138 -1.04307247 -0.98605070
[79] 1.21907337 1.89086531 -0.44347310 -0.73289734 -0.17605875 0.19819328
[85] 0.59045295 -0.20567335 -0.13131869 0.58356694 1.41190236 0.44295669
[91] 0.74475897 -1.78547088 0.78582048 -0.72826654 1.44667213 -1.08328743
[97] 0.26696450 -0.56170130 -0.71022971 1.01388047
> colMin(tmp)
[1] 1.00763917 1.07669726 -0.34136250 0.40301283 -0.70989952 1.48341727
[7] -1.55470636 -0.06571761 -0.71800569 0.06683039 -0.53810538 -0.02079210
[13] 0.19624015 0.62847665 -1.22208929 -0.74878391 1.07360793 0.54265635
[19] -0.80593260 0.93842491 0.52411779 -1.21842526 -0.20617680 -1.55095322
[25] 0.18689051 -0.38382633 -0.15727626 -0.74461297 -0.72929942 -1.65905462
[31] 1.49332151 0.89685141 1.28268811 -0.54524809 0.61696234 2.25183910
[37] 1.40994182 1.39375413 0.09601487 -1.61487952 0.13866345 0.87411732
[43] -0.09901415 -2.20313226 -0.57256789 -0.04902186 -0.60666961 1.11230875
[49] -1.16612178 -1.33729130 -0.87377830 -0.34865716 -0.07942622 -0.30052219
[55] 1.44263328 -0.62942745 -0.23092436 0.05764731 1.11335377 0.36256049
[61] 0.14552659 0.76497313 0.67630707 1.50083232 0.79904315 0.70417110
[67] 0.05148723 -0.85181713 -0.22206479 1.31610297 0.09130591 0.13800069
[73] 0.46770150 0.36193546 0.97051074 0.61398138 -1.04307247 -0.98605070
[79] 1.21907337 1.89086531 -0.44347310 -0.73289734 -0.17605875 0.19819328
[85] 0.59045295 -0.20567335 -0.13131869 0.58356694 1.41190236 0.44295669
[91] 0.74475897 -1.78547088 0.78582048 -0.72826654 1.44667213 -1.08328743
[97] 0.26696450 -0.56170130 -0.71022971 1.01388047
> colMedians(tmp)
[1] 1.00763917 1.07669726 -0.34136250 0.40301283 -0.70989952 1.48341727
[7] -1.55470636 -0.06571761 -0.71800569 0.06683039 -0.53810538 -0.02079210
[13] 0.19624015 0.62847665 -1.22208929 -0.74878391 1.07360793 0.54265635
[19] -0.80593260 0.93842491 0.52411779 -1.21842526 -0.20617680 -1.55095322
[25] 0.18689051 -0.38382633 -0.15727626 -0.74461297 -0.72929942 -1.65905462
[31] 1.49332151 0.89685141 1.28268811 -0.54524809 0.61696234 2.25183910
[37] 1.40994182 1.39375413 0.09601487 -1.61487952 0.13866345 0.87411732
[43] -0.09901415 -2.20313226 -0.57256789 -0.04902186 -0.60666961 1.11230875
[49] -1.16612178 -1.33729130 -0.87377830 -0.34865716 -0.07942622 -0.30052219
[55] 1.44263328 -0.62942745 -0.23092436 0.05764731 1.11335377 0.36256049
[61] 0.14552659 0.76497313 0.67630707 1.50083232 0.79904315 0.70417110
[67] 0.05148723 -0.85181713 -0.22206479 1.31610297 0.09130591 0.13800069
[73] 0.46770150 0.36193546 0.97051074 0.61398138 -1.04307247 -0.98605070
[79] 1.21907337 1.89086531 -0.44347310 -0.73289734 -0.17605875 0.19819328
[85] 0.59045295 -0.20567335 -0.13131869 0.58356694 1.41190236 0.44295669
[91] 0.74475897 -1.78547088 0.78582048 -0.72826654 1.44667213 -1.08328743
[97] 0.26696450 -0.56170130 -0.71022971 1.01388047
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.007639 1.076697 -0.3413625 0.4030128 -0.7098995 1.483417 -1.554706
[2,] 1.007639 1.076697 -0.3413625 0.4030128 -0.7098995 1.483417 -1.554706
[,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.06571761 -0.7180057 0.06683039 -0.5381054 -0.0207921 0.1962401
[2,] -0.06571761 -0.7180057 0.06683039 -0.5381054 -0.0207921 0.1962401
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0.6284766 -1.222089 -0.7487839 1.073608 0.5426564 -0.8059326 0.9384249
[2,] 0.6284766 -1.222089 -0.7487839 1.073608 0.5426564 -0.8059326 0.9384249
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] 0.5241178 -1.218425 -0.2061768 -1.550953 0.1868905 -0.3838263 -0.1572763
[2,] 0.5241178 -1.218425 -0.2061768 -1.550953 0.1868905 -0.3838263 -0.1572763
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] -0.744613 -0.7292994 -1.659055 1.493322 0.8968514 1.282688 -0.5452481
[2,] -0.744613 -0.7292994 -1.659055 1.493322 0.8968514 1.282688 -0.5452481
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.6169623 2.251839 1.409942 1.393754 0.09601487 -1.61488 0.1386634
[2,] 0.6169623 2.251839 1.409942 1.393754 0.09601487 -1.61488 0.1386634
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.8741173 -0.09901415 -2.203132 -0.5725679 -0.04902186 -0.6066696 1.112309
[2,] 0.8741173 -0.09901415 -2.203132 -0.5725679 -0.04902186 -0.6066696 1.112309
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -1.166122 -1.337291 -0.8737783 -0.3486572 -0.07942622 -0.3005222 1.442633
[2,] -1.166122 -1.337291 -0.8737783 -0.3486572 -0.07942622 -0.3005222 1.442633
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.6294274 -0.2309244 0.05764731 1.113354 0.3625605 0.1455266 0.7649731
[2,] -0.6294274 -0.2309244 0.05764731 1.113354 0.3625605 0.1455266 0.7649731
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.6763071 1.500832 0.7990431 0.7041711 0.05148723 -0.8518171 -0.2220648
[2,] 0.6763071 1.500832 0.7990431 0.7041711 0.05148723 -0.8518171 -0.2220648
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.316103 0.09130591 0.1380007 0.4677015 0.3619355 0.9705107 0.6139814
[2,] 1.316103 0.09130591 0.1380007 0.4677015 0.3619355 0.9705107 0.6139814
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -1.043072 -0.9860507 1.219073 1.890865 -0.4434731 -0.7328973 -0.1760588
[2,] -1.043072 -0.9860507 1.219073 1.890865 -0.4434731 -0.7328973 -0.1760588
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.1981933 0.590453 -0.2056734 -0.1313187 0.5835669 1.411902 0.4429567
[2,] 0.1981933 0.590453 -0.2056734 -0.1313187 0.5835669 1.411902 0.4429567
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.744759 -1.785471 0.7858205 -0.7282665 1.446672 -1.083287 0.2669645
[2,] 0.744759 -1.785471 0.7858205 -0.7282665 1.446672 -1.083287 0.2669645
[,98] [,99] [,100]
[1,] -0.5617013 -0.7102297 1.01388
[2,] -0.5617013 -0.7102297 1.01388
>
>
> Max(tmp2)
[1] 2.70061
> Min(tmp2)
[1] -1.999105
> mean(tmp2)
[1] -0.003165425
> Sum(tmp2)
[1] -0.3165425
> Var(tmp2)
[1] 0.9801988
>
> rowMeans(tmp2)
[1] 0.019660721 -1.925379655 -0.491476195 0.181533580 0.674120441
[6] -0.087523100 -0.907676805 1.874089013 0.753805793 1.145234709
[11] 0.463751086 1.264700177 -0.691085426 -0.625163075 0.566421617
[16] 0.428631654 -1.006596573 -0.357319302 1.512887038 0.002342968
[21] 0.356861985 0.596270355 -0.679671983 2.109319826 -0.402050528
[26] -0.943817642 1.312445755 0.606281576 -0.220610605 -0.287225968
[31] 0.118073034 0.392404409 0.793926624 0.933581430 0.766228906
[36] 0.616371161 1.968019423 0.060222461 -1.602122416 0.468064103
[41] 2.390125614 -1.999104793 -0.641732144 0.626656768 1.789176310
[46] -0.530633273 -0.372490266 0.811838347 2.700610468 -0.502531322
[51] -0.920094532 0.597986028 -0.137000073 -1.201178330 0.715993060
[56] -1.504572174 0.482601321 -0.335598888 1.045111021 -0.764719076
[61] -1.699255149 0.573328216 -1.231260353 0.404321264 0.841605364
[66] -0.071483529 0.870295160 -1.478173707 0.685726515 -0.062282770
[71] -0.025891006 -0.832126475 1.247890953 -1.253510316 -1.104333220
[76] -0.623911216 -0.066164782 0.348870138 0.240700956 -1.135729567
[81] -1.087092640 -0.255659556 0.004314724 -1.342181429 0.249127767
[86] -1.853678379 0.340922208 1.341634186 -0.256246582 -1.051523613
[91] -1.593891995 -0.088728386 -1.457343251 -0.168310443 -0.318300303
[96] 0.611951790 0.057730641 -0.848999859 -0.617773953 0.380915412
> rowSums(tmp2)
[1] 0.019660721 -1.925379655 -0.491476195 0.181533580 0.674120441
[6] -0.087523100 -0.907676805 1.874089013 0.753805793 1.145234709
[11] 0.463751086 1.264700177 -0.691085426 -0.625163075 0.566421617
[16] 0.428631654 -1.006596573 -0.357319302 1.512887038 0.002342968
[21] 0.356861985 0.596270355 -0.679671983 2.109319826 -0.402050528
[26] -0.943817642 1.312445755 0.606281576 -0.220610605 -0.287225968
[31] 0.118073034 0.392404409 0.793926624 0.933581430 0.766228906
[36] 0.616371161 1.968019423 0.060222461 -1.602122416 0.468064103
[41] 2.390125614 -1.999104793 -0.641732144 0.626656768 1.789176310
[46] -0.530633273 -0.372490266 0.811838347 2.700610468 -0.502531322
[51] -0.920094532 0.597986028 -0.137000073 -1.201178330 0.715993060
[56] -1.504572174 0.482601321 -0.335598888 1.045111021 -0.764719076
[61] -1.699255149 0.573328216 -1.231260353 0.404321264 0.841605364
[66] -0.071483529 0.870295160 -1.478173707 0.685726515 -0.062282770
[71] -0.025891006 -0.832126475 1.247890953 -1.253510316 -1.104333220
[76] -0.623911216 -0.066164782 0.348870138 0.240700956 -1.135729567
[81] -1.087092640 -0.255659556 0.004314724 -1.342181429 0.249127767
[86] -1.853678379 0.340922208 1.341634186 -0.256246582 -1.051523613
[91] -1.593891995 -0.088728386 -1.457343251 -0.168310443 -0.318300303
[96] 0.611951790 0.057730641 -0.848999859 -0.617773953 0.380915412
> 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] 0.019660721 -1.925379655 -0.491476195 0.181533580 0.674120441
[6] -0.087523100 -0.907676805 1.874089013 0.753805793 1.145234709
[11] 0.463751086 1.264700177 -0.691085426 -0.625163075 0.566421617
[16] 0.428631654 -1.006596573 -0.357319302 1.512887038 0.002342968
[21] 0.356861985 0.596270355 -0.679671983 2.109319826 -0.402050528
[26] -0.943817642 1.312445755 0.606281576 -0.220610605 -0.287225968
[31] 0.118073034 0.392404409 0.793926624 0.933581430 0.766228906
[36] 0.616371161 1.968019423 0.060222461 -1.602122416 0.468064103
[41] 2.390125614 -1.999104793 -0.641732144 0.626656768 1.789176310
[46] -0.530633273 -0.372490266 0.811838347 2.700610468 -0.502531322
[51] -0.920094532 0.597986028 -0.137000073 -1.201178330 0.715993060
[56] -1.504572174 0.482601321 -0.335598888 1.045111021 -0.764719076
[61] -1.699255149 0.573328216 -1.231260353 0.404321264 0.841605364
[66] -0.071483529 0.870295160 -1.478173707 0.685726515 -0.062282770
[71] -0.025891006 -0.832126475 1.247890953 -1.253510316 -1.104333220
[76] -0.623911216 -0.066164782 0.348870138 0.240700956 -1.135729567
[81] -1.087092640 -0.255659556 0.004314724 -1.342181429 0.249127767
[86] -1.853678379 0.340922208 1.341634186 -0.256246582 -1.051523613
[91] -1.593891995 -0.088728386 -1.457343251 -0.168310443 -0.318300303
[96] 0.611951790 0.057730641 -0.848999859 -0.617773953 0.380915412
> rowMin(tmp2)
[1] 0.019660721 -1.925379655 -0.491476195 0.181533580 0.674120441
[6] -0.087523100 -0.907676805 1.874089013 0.753805793 1.145234709
[11] 0.463751086 1.264700177 -0.691085426 -0.625163075 0.566421617
[16] 0.428631654 -1.006596573 -0.357319302 1.512887038 0.002342968
[21] 0.356861985 0.596270355 -0.679671983 2.109319826 -0.402050528
[26] -0.943817642 1.312445755 0.606281576 -0.220610605 -0.287225968
[31] 0.118073034 0.392404409 0.793926624 0.933581430 0.766228906
[36] 0.616371161 1.968019423 0.060222461 -1.602122416 0.468064103
[41] 2.390125614 -1.999104793 -0.641732144 0.626656768 1.789176310
[46] -0.530633273 -0.372490266 0.811838347 2.700610468 -0.502531322
[51] -0.920094532 0.597986028 -0.137000073 -1.201178330 0.715993060
[56] -1.504572174 0.482601321 -0.335598888 1.045111021 -0.764719076
[61] -1.699255149 0.573328216 -1.231260353 0.404321264 0.841605364
[66] -0.071483529 0.870295160 -1.478173707 0.685726515 -0.062282770
[71] -0.025891006 -0.832126475 1.247890953 -1.253510316 -1.104333220
[76] -0.623911216 -0.066164782 0.348870138 0.240700956 -1.135729567
[81] -1.087092640 -0.255659556 0.004314724 -1.342181429 0.249127767
[86] -1.853678379 0.340922208 1.341634186 -0.256246582 -1.051523613
[91] -1.593891995 -0.088728386 -1.457343251 -0.168310443 -0.318300303
[96] 0.611951790 0.057730641 -0.848999859 -0.617773953 0.380915412
>
> colMeans(tmp2)
[1] -0.003165425
> colSums(tmp2)
[1] -0.3165425
> colVars(tmp2)
[1] 0.9801988
> colSd(tmp2)
[1] 0.9900499
> colMax(tmp2)
[1] 2.70061
> colMin(tmp2)
[1] -1.999105
> colMedians(tmp2)
[1] -0.01177402
> colRanges(tmp2)
[,1]
[1,] -1.999105
[2,] 2.700610
>
> 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] 6.2319760 -0.4999891 0.1654278 -3.8042033 3.3222517 -1.4816307
[7] 7.9532431 -3.0085265 1.5953430 -0.5263907
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5184876
[2,] 0.2816250
[3,] 0.8630321
[4,] 1.1832075
[5,] 1.7645755
>
> rowApply(tmp,sum)
[1] 2.4263974 -1.7873189 0.9147226 -1.8331531 1.1344630 4.3840639
[7] -1.3713852 -0.7627667 4.6545347 2.1879433
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 1 7 9 6 10 8 8 9 6
[2,] 3 2 4 6 8 3 4 9 6 2
[3,] 6 5 2 7 3 6 9 7 5 5
[4,] 1 4 3 5 5 4 2 6 3 7
[5,] 7 10 8 1 10 8 6 2 10 1
[6,] 5 7 9 2 1 2 5 4 7 3
[7,] 8 9 5 8 9 9 3 10 4 8
[8,] 2 8 1 4 7 1 10 3 2 9
[9,] 9 3 10 10 4 5 1 5 8 4
[10,] 4 6 6 3 2 7 7 1 1 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.5580459 -0.8103991 2.2633556 -1.4475412 -7.6385708 1.9263003
[7] -0.7367413 2.3384540 0.9271905 1.1013819 -0.3868619 1.0358031
[13] 1.4918358 -5.1312933 2.6362911 -1.8784513 3.8484797 0.3262992
[19] 0.4942619 0.3405733
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7138458
[2,] -0.2745954
[3,] 0.4351908
[4,] 0.7417607
[5,] 1.3695356
>
> rowApply(tmp,sum)
[1] 7.319745 -1.823083 1.665797 5.868394 -10.772440
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 14 19 2 11
[2,] 2 11 12 9 7
[3,] 16 13 2 19 12
[4,] 17 3 11 3 9
[5,] 1 1 3 4 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.7417607 -0.52304715 0.9162633 0.9533352 -1.9367354 0.1831880
[2,] 0.4351908 0.17636398 0.3748213 -1.2448017 -2.6736873 0.6063188
[3,] 1.3695356 0.54363844 -1.1825921 0.1213598 -0.9068081 0.6650629
[4,] -0.7138458 0.01279608 2.3885731 -0.5775407 -0.1597569 -0.1262189
[5,] -0.2745954 -1.02015048 -0.2337099 -0.6998938 -1.9615830 0.5979495
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.6532071 -0.24726268 0.5284063 0.7017268 1.74042233 1.36118297
[2,] 0.1123146 1.24958535 -0.4454856 0.5558552 -0.11492849 0.17140773
[3,] -0.7048241 0.80231777 2.0715980 1.1390266 -0.36328367 -0.41359943
[4,] -1.4785376 0.09639467 0.4906136 0.1429242 -0.07638281 0.01127545
[5,] 0.6810986 0.43741888 -1.7179417 -1.4381509 -1.57268925 -0.09446363
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.6900609 0.1747621 -0.2776929 0.3973195 0.2059789 1.35032255
[2,] 0.6846637 -2.3315773 0.7050218 -0.6637013 0.7324239 -0.21239239
[3,] -0.4409663 -2.3182850 0.5456558 0.5693394 -0.5146193 0.04163948
[4,] 0.5994806 0.1444465 0.6323462 -0.1509358 3.0846915 0.28409336
[5,] -0.0414031 -0.8006396 1.0309602 -2.0304731 0.3400046 -1.13736377
[,19] [,20]
[1,] -0.5054973 0.2120443
[2,] 0.3125461 -0.2530218
[3,] -0.1546200 0.7962215
[4,] 1.0227671 0.2412099
[5,] -0.1809340 -0.6558806
>
>
> 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 : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.515337 0.4308944 -1.260476 0.4327492 -0.9597087 -0.1856158 -1.43452
col8 col9 col10 col11 col12 col13 col14
row1 -0.8745552 0.6726356 0.3223861 0.2744434 1.100095 -0.5020043 1.56705
col15 col16 col17 col18 col19 col20
row1 -0.1458769 0.1061015 0.4228634 -2.725296 0.5645891 -1.171885
> tmp[,"col10"]
col10
row1 0.3223861
row2 2.0505975
row3 0.9800913
row4 -0.3484856
row5 -1.4166815
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.515337 0.4308944 -1.2604756 0.4327492 -0.9597087 -0.1856158 -1.4345202
row5 -1.338166 0.2386265 -0.6955553 -1.0175589 0.0073683 -1.9183800 0.9573566
col8 col9 col10 col11 col12 col13 col14
row1 -0.8745552 0.6726356 0.3223861 0.2744434 1.100095 -0.50200426 1.567050
row5 -0.8252902 1.2080754 -1.4166815 0.2204860 2.001163 -0.01982465 2.375588
col15 col16 col17 col18 col19 col20
row1 -0.1458769 0.1061015 0.4228634 -2.7252963 0.5645891 -1.1718847
row5 -1.5416791 1.1721191 0.0858171 -0.5790563 -0.5846066 -0.5464013
> tmp[,c("col6","col20")]
col6 col20
row1 -0.1856158 -1.17188469
row2 0.4746812 -0.23977923
row3 0.4631874 1.34208289
row4 -1.3651710 0.02085164
row5 -1.9183800 -0.54640129
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.1856158 -1.1718847
row5 -1.9183800 -0.5464013
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.11032 49.81959 50.39714 49.41383 49.09148 105.062 48.87968 51.13927
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.93375 49.02323 50.13294 51.73588 50.98682 50.6298 49.78562 50.8913
col17 col18 col19 col20
row1 47.14314 49.40915 49.72588 104.0082
> tmp[,"col10"]
col10
row1 49.02323
row2 30.13802
row3 29.63174
row4 30.56264
row5 49.58704
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.11032 49.81959 50.39714 49.41383 49.09148 105.062 48.87968 51.13927
row5 49.70216 48.12937 49.00691 49.01576 51.30193 104.686 49.13516 48.58876
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.93375 49.02323 50.13294 51.73588 50.98682 50.62980 49.78562 50.89130
row5 49.64276 49.58704 51.33756 48.75291 50.54674 50.77079 49.12088 50.17833
col17 col18 col19 col20
row1 47.14314 49.40915 49.72588 104.0082
row5 48.28756 51.03124 47.75705 105.2943
> tmp[,c("col6","col20")]
col6 col20
row1 105.06201 104.00822
row2 76.71812 76.34389
row3 75.55975 76.35494
row4 75.27075 75.56461
row5 104.68597 105.29429
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.062 104.0082
row5 104.686 105.2943
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.062 104.0082
row5 104.686 105.2943
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.1349223
[2,] -0.8107646
[3,] 0.6437932
[4,] -0.4958232
[5,] -0.5824259
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.4849589 0.9836654
[2,] -0.7349212 0.7279797
[3,] 1.2907767 -0.3134259
[4,] -0.2321583 0.4463826
[5,] -0.5139621 2.0948105
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.488146427 -1.1054226
[2,] -0.908071194 0.4090370
[3,] -0.536336227 0.2871904
[4,] -1.098042928 -0.5552872
[5,] 0.004296472 0.5898886
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.488146
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.4881464
[2,] -0.9080712
>
>
>
> 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 1.2220194 0.3860191 -0.3115554 -2.1015732 0.2048140 -0.8097535 0.2467580
row1 0.1113325 1.3146068 -0.2285350 0.5808862 0.1013944 0.1838219 0.2648839
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.477577 0.2031745 -1.0280088 0.7406032 0.2912364 1.2544422 1.7658114
row1 1.962282 0.8222981 -0.7479693 -0.5955601 -0.6900305 0.3909673 0.9264651
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.4378920 0.2723632 1.799403 -0.9514113 1.803935 0.6755281
row1 0.4017267 0.4718070 -1.054350 -1.1443232 -1.305778 0.3845092
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.915918 -1.482271 0.7964087 0.201773 -0.8655792 1.49004 -0.637129
[,8] [,9] [,10]
row2 -0.5399102 -0.1523816 -0.6762255
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.9325803 0.01261116 0.8769483 -1.808967 -0.5890804 -0.2253545 0.4769261
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.602294 -0.1070988 -0.08347941 -0.7945733 -1.257866 -1.406751 0.4731167
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4798662 -0.734975 1.602066 1.271247 0.004738099 0.9053369
>
>
> 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: 0x1f107ae0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a17615d58c"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a1226c2a50"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a163bb2a0b"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a110744169"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a12fb2497b"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a12106d673"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a17e8e9b3d"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a127e8eb4f"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a12f458030"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a139c1b85"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a15ac88cf9"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a115544de4"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a14fc5b16c"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a175d41b65"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1ac0a11110d932"
>
>
> ### 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: 0x1e3412a0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x1e3412a0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x1e3412a0>
> rowMedians(tmp)
[1] 0.664000857 -0.013448657 0.088069999 -0.085538967 0.112468884
[6] -0.393295698 -0.089832111 0.162674318 -0.099221250 0.606644187
[11] -0.435270914 0.638639020 -0.088857535 -0.172276605 0.491215904
[16] 0.062922608 0.035728403 -0.257415346 0.302997259 -0.136098856
[21] 0.249787481 0.182739478 -0.182392258 0.026859611 -0.042285784
[26] 0.200765156 0.169103504 -0.235827055 0.401861319 -0.124961305
[31] -0.497203418 -0.086631022 0.226766326 -0.506968784 0.326317465
[36] 0.209053123 -0.061862766 0.212555736 0.178078561 -0.353998386
[41] -0.443713840 -0.692418657 -0.733453060 -0.123693251 -0.071020446
[46] -0.085008485 -0.123729205 0.125618928 0.502904991 0.056967598
[51] -0.513327697 -0.209273759 -0.453931882 0.351742424 0.517354586
[56] -0.241662582 -0.141913959 0.047630328 0.100686367 -0.457982173
[61] 0.162073372 -0.632526773 0.185978328 -0.232188132 -0.245749688
[66] 0.317652231 -0.365137817 -0.423407401 0.785666952 0.107618863
[71] 0.098260109 0.371848013 0.006919408 0.565463956 -0.062938184
[76] 0.089346593 -0.123482027 0.029539724 -0.101461482 -0.285372119
[81] -0.268883393 -0.343390125 -0.502474402 -0.161006729 -0.082109152
[86] 0.321321003 0.052318160 0.404413297 -0.256355954 0.022945010
[91] 0.309858407 -0.716414862 -0.092061093 -0.123388756 0.118514627
[96] 0.396143472 0.183224199 0.209188872 -0.493062768 -0.321647702
[101] 0.190449928 -0.548097032 -0.712972397 0.238400063 0.049650147
[106] -0.439841794 -0.006936147 0.169290383 0.388624505 -0.037091765
[111] -0.422921417 0.063255261 0.358112993 0.298671677 -0.086148802
[116] 0.162157929 -0.035054040 0.004440633 -0.426990151 0.183805582
[121] 0.231874341 0.396152336 -0.015443164 -0.518537494 0.495994820
[126] 0.032742061 -0.099212627 -0.241091072 0.355664839 0.302931146
[131] 0.129403776 -0.091273455 -0.003534595 -0.390540333 0.229739532
[136] -0.071429360 -0.129837874 -0.204393355 -0.146872904 -0.130381407
[141] 0.169297969 -0.548685719 -0.075237048 -0.023216517 -0.178683185
[146] -0.031596301 -0.539725382 -0.331403978 0.115809028 0.013705437
[151] -0.063971365 0.008485338 -0.119845187 -0.074882578 0.528534078
[156] 0.138893475 0.002354914 0.772670658 0.207212345 0.005838561
[161] -0.009600682 0.495805479 -0.268301735 0.061567547 -0.104395439
[166] 0.175877692 -0.421369641 0.169150041 0.140440892 -0.257257869
[171] 0.190694386 -0.042567558 0.402754654 0.151571205 0.258559514
[176] -0.100977741 0.137354671 -0.235193991 -0.086102979 0.102891046
[181] -0.327258067 -0.068929467 0.016261409 -0.318757790 -0.579474644
[186] -0.040114075 -0.260023856 -0.112788717 0.302518741 0.359842005
[191] 0.407510865 0.218500426 0.089025680 0.078433087 0.284648272
[196] 0.164229409 0.240781749 0.320838917 -0.602680620 -0.108101164
[201] 0.612429228 0.671443344 -0.198649781 0.374780015 0.887744820
[206] 0.222204981 0.192402148 0.686134703 -0.806733577 0.217948180
[211] 0.113227458 0.520218104 -0.097534090 -0.309812739 0.354567042
[216] 0.437572305 -0.068435179 0.243794601 0.036966227 0.060559775
[221] 0.583220937 -0.522165366 -0.164662010 -0.074388400 0.543810134
[226] -0.013157327 0.117768037 0.361617579 0.559897708 0.276476732
>
> proc.time()
user system elapsed
1.854 0.871 2.751
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: 0x3b8f0ff0>
> .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: 0x3b8f0ff0>
> .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: 0x3b8f0ff0>
> .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: 0x3b8f0ff0>
> 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: 0x3b7d60e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3b7d60e0>
> .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: 0x3b7d60e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3b7d60e0>
> .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: 0x3b7d60e0>
> 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: 0x3a75d520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3a75d520>
> .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: 0x3a75d520>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x3a75d520>
> .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: 0x3a75d520>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x3a75d520>
> .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: 0x3a75d520>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x3a75d520>
> .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: 0x3a75d520>
> 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: 0x3a161720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x3a161720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3a161720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3a161720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1ac0bd35e6b8f1" "BufferedMatrixFile1ac0bd4878086e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1ac0bd35e6b8f1" "BufferedMatrixFile1ac0bd4878086e"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x3b0517d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3b0517d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x3b0517d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x3b0517d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x3b0517d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x3b0517d0>
> .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: 0x3b158c90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3b158c90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x3b158c90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x3b158c90>
> 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: 0x3c401110>
> .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: 0x3c401110>
> rm(P)
>
> proc.time()
user system elapsed
0.349 0.019 0.354
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.
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
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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
0.329 0.048 0.362