Ben Bolstad
| Snapshot Date: 2025-12-01 13:45 -0500 (Mon, 01 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 2025-12-04 12:02 -0500 (Thu, 04 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" | 4878 |
| merida1 | macOS 12.7.6 Monterey | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4624 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4669 |
| 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 | | ||||||||
| 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: 2025-12-02 07:23:37 -0000 (Tue, 02 Dec 2025) |
| EndedAt: 2025-12-02 07:24:07 -0000 (Tue, 02 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
##############################################################################
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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
0.330 0.041 0.356
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 Dec 2 07:24:00 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] "Tue Dec 2 07:24:00 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: 0x115dbff0>
>
>
>
> 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 Dec 2 07:24:01 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] "Tue Dec 2 07:24:01 2025"
>
> ColMode(tmp2)
<pointer: 0x115dbff0>
>
>
>
> ### 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,] 99.3855420 0.19514730 -0.80470592 -0.4952830
[2,] 1.6374773 0.01693108 -1.49656406 -0.5616264
[3,] 0.3892901 0.70643824 -0.03745639 0.7936193
[4,] -0.1763116 0.18776534 -1.60313732 1.5245586
> 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,] 99.3855420 0.19514730 0.80470592 0.4952830
[2,] 1.6374773 0.01693108 1.49656406 0.5616264
[3,] 0.3892901 0.70643824 0.03745639 0.7936193
[4,] 0.1763116 0.18776534 1.60313732 1.5245586
> 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,] 9.9692298 0.4417548 0.8970540 0.7037634
[2,] 1.2796395 0.1301195 1.2233413 0.7494174
[3,] 0.6239311 0.8404988 0.1935365 0.8908532
[4,] 0.4198948 0.4333190 1.2661506 1.2347302
>
> 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,] 224.07784 29.61270 34.77525 32.53292
[2,] 39.43387 26.31813 38.72998 33.05580
[3,] 31.62860 34.11143 26.97282 34.70215
[4,] 29.37526 29.52096 39.26464 38.87186
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x102be6c0>
> exp(tmp5)
<pointer: 0x102be6c0>
> log(tmp5,2)
<pointer: 0x102be6c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.3887
> Min(tmp5)
[1] 52.5549
> mean(tmp5)
[1] 72.20931
> Sum(tmp5)
[1] 14441.86
> Var(tmp5)
[1] 865.0592
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.07758 69.50223 67.35642 70.33606 72.32476 71.45829 71.24537 69.36441
[9] 71.43889 68.98908
> rowSums(tmp5)
[1] 1801.552 1390.045 1347.128 1406.721 1446.495 1429.166 1424.907 1387.288
[9] 1428.778 1379.782
> rowVars(tmp5)
[1] 7927.91560 111.22579 87.45725 70.59714 76.41258 93.66779
[7] 77.85585 91.52386 68.56658 61.21171
> rowSd(tmp5)
[1] 89.038843 10.546364 9.351858 8.402210 8.741429 9.678212 8.823596
[8] 9.566810 8.280494 7.823792
> rowMax(tmp5)
[1] 466.38866 87.97250 89.72992 82.79178 91.54853 93.98813 85.87272
[8] 85.54554 88.99769 87.25766
> rowMin(tmp5)
[1] 58.28446 54.21402 56.14039 58.05968 52.55490 57.55273 55.80511 54.60350
[9] 57.74905 54.29994
>
> colMeans(tmp5)
[1] 109.03778 69.61175 71.79525 71.30094 69.22760 75.32285 74.80819
[8] 68.39846 73.70903 68.64955 71.10375 73.71203 71.95144 66.01508
[15] 67.65487 68.79808 67.13806 63.16622 71.30698 71.47828
> colSums(tmp5)
[1] 1090.3778 696.1175 717.9525 713.0094 692.2760 753.2285 748.0819
[8] 683.9846 737.0903 686.4955 711.0375 737.1203 719.5144 660.1508
[15] 676.5487 687.9808 671.3806 631.6622 713.0698 714.7828
> colVars(tmp5)
[1] 15840.70949 84.71050 91.56096 45.58786 81.04978 141.31281
[7] 25.76968 92.27987 151.72259 50.94313 74.15777 90.63613
[13] 71.05436 42.12477 50.45950 83.66325 88.39658 31.81290
[19] 109.32100 100.14505
> colSd(tmp5)
[1] 125.859880 9.203831 9.568749 6.751878 9.002765 11.887506
[7] 5.076385 9.606241 12.317572 7.137446 8.611491 9.520301
[13] 8.429375 6.490360 7.103485 9.146762 9.401945 5.640293
[19] 10.455668 10.007250
> colMax(tmp5)
[1] 466.38866 86.08906 85.87272 80.90668 82.62410 93.98813 83.54539
[8] 87.78987 94.57754 81.85952 82.09849 88.99769 83.51775 76.41717
[15] 81.64333 89.72992 80.13159 72.78655 91.54853 87.67982
> colMin(tmp5)
[1] 52.55490 54.77773 56.14039 60.36841 57.99486 58.27685 66.13645 56.27559
[9] 57.27951 57.74905 57.99908 58.72437 58.05968 57.59274 56.60213 56.57792
[17] 54.29994 54.21402 55.80511 58.16659
>
>
> ### 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] 90.07758 NA 67.35642 70.33606 72.32476 71.45829 71.24537 69.36441
[9] 71.43889 68.98908
> rowSums(tmp5)
[1] 1801.552 NA 1347.128 1406.721 1446.495 1429.166 1424.907 1387.288
[9] 1428.778 1379.782
> rowVars(tmp5)
[1] 7927.91560 110.18786 87.45725 70.59714 76.41258 93.66779
[7] 77.85585 91.52386 68.56658 61.21171
> rowSd(tmp5)
[1] 89.038843 10.497040 9.351858 8.402210 8.741429 9.678212 8.823596
[8] 9.566810 8.280494 7.823792
> rowMax(tmp5)
[1] 466.38866 NA 89.72992 82.79178 91.54853 93.98813 85.87272
[8] 85.54554 88.99769 87.25766
> rowMin(tmp5)
[1] 58.28446 NA 56.14039 58.05968 52.55490 57.55273 55.80511 54.60350
[9] 57.74905 54.29994
>
> colMeans(tmp5)
[1] 109.03778 69.61175 NA 71.30094 69.22760 75.32285 74.80819
[8] 68.39846 73.70903 68.64955 71.10375 73.71203 71.95144 66.01508
[15] 67.65487 68.79808 67.13806 63.16622 71.30698 71.47828
> colSums(tmp5)
[1] 1090.3778 696.1175 NA 713.0094 692.2760 753.2285 748.0819
[8] 683.9846 737.0903 686.4955 711.0375 737.1203 719.5144 660.1508
[15] 676.5487 687.9808 671.3806 631.6622 713.0698 714.7828
> colVars(tmp5)
[1] 15840.70949 84.71050 NA 45.58786 81.04978 141.31281
[7] 25.76968 92.27987 151.72259 50.94313 74.15777 90.63613
[13] 71.05436 42.12477 50.45950 83.66325 88.39658 31.81290
[19] 109.32100 100.14505
> colSd(tmp5)
[1] 125.859880 9.203831 NA 6.751878 9.002765 11.887506
[7] 5.076385 9.606241 12.317572 7.137446 8.611491 9.520301
[13] 8.429375 6.490360 7.103485 9.146762 9.401945 5.640293
[19] 10.455668 10.007250
> colMax(tmp5)
[1] 466.38866 86.08906 NA 80.90668 82.62410 93.98813 83.54539
[8] 87.78987 94.57754 81.85952 82.09849 88.99769 83.51775 76.41717
[15] 81.64333 89.72992 80.13159 72.78655 91.54853 87.67982
> colMin(tmp5)
[1] 52.55490 54.77773 NA 60.36841 57.99486 58.27685 66.13645 56.27559
[9] 57.27951 57.74905 57.99908 58.72437 58.05968 57.59274 56.60213 56.57792
[17] 54.29994 54.21402 55.80511 58.16659
>
> Max(tmp5,na.rm=TRUE)
[1] 466.3887
> Min(tmp5,na.rm=TRUE)
[1] 52.5549
> mean(tmp5,na.rm=TRUE)
[1] 72.16709
> Sum(tmp5,na.rm=TRUE)
[1] 14361.25
> Var(tmp5,na.rm=TRUE)
[1] 869.0698
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.07758 68.91754 67.35642 70.33606 72.32476 71.45829 71.24537 69.36441
[9] 71.43889 68.98908
> rowSums(tmp5,na.rm=TRUE)
[1] 1801.552 1309.433 1347.128 1406.721 1446.495 1429.166 1424.907 1387.288
[9] 1428.778 1379.782
> rowVars(tmp5,na.rm=TRUE)
[1] 7927.91560 110.18786 87.45725 70.59714 76.41258 93.66779
[7] 77.85585 91.52386 68.56658 61.21171
> rowSd(tmp5,na.rm=TRUE)
[1] 89.038843 10.497040 9.351858 8.402210 8.741429 9.678212 8.823596
[8] 9.566810 8.280494 7.823792
> rowMax(tmp5,na.rm=TRUE)
[1] 466.38866 87.97250 89.72992 82.79178 91.54853 93.98813 85.87272
[8] 85.54554 88.99769 87.25766
> rowMin(tmp5,na.rm=TRUE)
[1] 58.28446 54.21402 56.14039 58.05968 52.55490 57.55273 55.80511 54.60350
[9] 57.74905 54.29994
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.03778 69.61175 70.81568 71.30094 69.22760 75.32285 74.80819
[8] 68.39846 73.70903 68.64955 71.10375 73.71203 71.95144 66.01508
[15] 67.65487 68.79808 67.13806 63.16622 71.30698 71.47828
> colSums(tmp5,na.rm=TRUE)
[1] 1090.3778 696.1175 637.3411 713.0094 692.2760 753.2285 748.0819
[8] 683.9846 737.0903 686.4955 711.0375 737.1203 719.5144 660.1508
[15] 676.5487 687.9808 671.3806 631.6622 713.0698 714.7828
> colVars(tmp5,na.rm=TRUE)
[1] 15840.70949 84.71050 92.21106 45.58786 81.04978 141.31281
[7] 25.76968 92.27987 151.72259 50.94313 74.15777 90.63613
[13] 71.05436 42.12477 50.45950 83.66325 88.39658 31.81290
[19] 109.32100 100.14505
> colSd(tmp5,na.rm=TRUE)
[1] 125.859880 9.203831 9.602659 6.751878 9.002765 11.887506
[7] 5.076385 9.606241 12.317572 7.137446 8.611491 9.520301
[13] 8.429375 6.490360 7.103485 9.146762 9.401945 5.640293
[19] 10.455668 10.007250
> colMax(tmp5,na.rm=TRUE)
[1] 466.38866 86.08906 85.87272 80.90668 82.62410 93.98813 83.54539
[8] 87.78987 94.57754 81.85952 82.09849 88.99769 83.51775 76.41717
[15] 81.64333 89.72992 80.13159 72.78655 91.54853 87.67982
> colMin(tmp5,na.rm=TRUE)
[1] 52.55490 54.77773 56.14039 60.36841 57.99486 58.27685 66.13645 56.27559
[9] 57.27951 57.74905 57.99908 58.72437 58.05968 57.59274 56.60213 56.57792
[17] 54.29994 54.21402 55.80511 58.16659
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.07758 NaN 67.35642 70.33606 72.32476 71.45829 71.24537 69.36441
[9] 71.43889 68.98908
> rowSums(tmp5,na.rm=TRUE)
[1] 1801.552 0.000 1347.128 1406.721 1446.495 1429.166 1424.907 1387.288
[9] 1428.778 1379.782
> rowVars(tmp5,na.rm=TRUE)
[1] 7927.91560 NA 87.45725 70.59714 76.41258 93.66779
[7] 77.85585 91.52386 68.56658 61.21171
> rowSd(tmp5,na.rm=TRUE)
[1] 89.038843 NA 9.351858 8.402210 8.741429 9.678212 8.823596
[8] 9.566810 8.280494 7.823792
> rowMax(tmp5,na.rm=TRUE)
[1] 466.38866 NA 89.72992 82.79178 91.54853 93.98813 85.87272
[8] 85.54554 88.99769 87.25766
> rowMin(tmp5,na.rm=TRUE)
[1] 58.28446 NA 56.14039 58.05968 52.55490 57.55273 55.80511 54.60350
[9] 57.74905 54.29994
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.03349 71.25997 NaN 71.57867 70.45388 77.21685 74.69763
[8] 68.52857 72.12420 67.18177 70.00874 74.35303 71.26491 65.87356
[15] 68.88295 70.15588 67.15820 64.16091 71.40545 71.04756
> colSums(tmp5,na.rm=TRUE)
[1] 1008.3014 641.3397 0.0000 644.2080 634.0849 694.9517 672.2787
[8] 616.7571 649.1178 604.6360 630.0786 669.1773 641.3842 592.8621
[15] 619.9466 631.4029 604.4238 577.4482 642.6491 639.4281
> colVars(tmp5,na.rm=TRUE)
[1] 17719.83789 64.73709 NA 50.41855 74.26350 118.62050
[7] 28.85339 103.62442 142.43144 33.07444 69.93807 97.34322
[13] 74.63384 47.16506 39.79984 73.38057 99.44158 24.65869
[19] 122.87705 110.57612
> colSd(tmp5,na.rm=TRUE)
[1] 133.115881 8.045936 NA 7.100602 8.617627 10.891304
[7] 5.371535 10.179608 11.934464 5.751038 8.362898 9.866267
[13] 8.639088 6.867682 6.308712 8.566246 9.972040 4.965752
[19] 11.084992 10.515518
> colMax(tmp5,na.rm=TRUE)
[1] 466.38866 86.08906 -Inf 80.90668 82.62410 93.98813 83.54539
[8] 87.78987 94.57754 74.68259 82.09849 88.99769 83.51775 76.41717
[15] 81.64333 89.72992 80.13159 72.78655 91.54853 87.67982
> colMin(tmp5,na.rm=TRUE)
[1] 52.55490 61.44400 Inf 60.36841 57.99486 60.72328 66.13645 56.27559
[9] 57.27951 57.74905 57.99908 58.72437 58.05968 57.59274 63.02472 60.42433
[17] 54.29994 57.74387 55.80511 58.16659
>
>
>
>
> 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] 206.2699 140.2004 288.4995 210.4448 284.6672 105.5613 170.1272 330.9731
[9] 178.8794 208.4200
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 206.2699 140.2004 288.4995 210.4448 284.6672 105.5613 170.1272 330.9731
[9] 178.8794 208.4200
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 -2.557954e-13 1.705303e-13 1.136868e-13 -2.842171e-14
[6] -5.684342e-14 -2.273737e-13 1.136868e-13 5.684342e-14 2.842171e-14
[11] 1.705303e-13 8.526513e-14 -5.684342e-14 -2.842171e-14 0.000000e+00
[16] -2.842171e-14 0.000000e+00 1.705303e-13 1.136868e-13 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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 7
4 12
6 5
8 9
5 3
8 1
1 18
5 1
8 2
2 14
8 15
3 13
2 7
3 13
8 8
5 6
4 6
4 6
7 5
5 10
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] 2.52264
> Min(tmp)
[1] -2.038791
> mean(tmp)
[1] -0.1780683
> Sum(tmp)
[1] -17.80683
> Var(tmp)
[1] 0.9019284
>
> rowMeans(tmp)
[1] -0.1780683
> rowSums(tmp)
[1] -17.80683
> rowVars(tmp)
[1] 0.9019284
> rowSd(tmp)
[1] 0.9496991
> rowMax(tmp)
[1] 2.52264
> rowMin(tmp)
[1] -2.038791
>
> colMeans(tmp)
[1] -0.32429485 -0.95491187 0.47838695 -0.40620077 -1.25774045 0.44508391
[7] -0.38152309 -0.27434816 0.61887871 1.11505561 -1.75856473 -1.67609804
[13] 0.67819976 0.81604784 -1.14993267 0.22327575 -0.07923951 -1.60680162
[19] -0.16903607 -0.48034077 -0.60155561 1.23845604 -0.43133773 -0.82216264
[25] -0.03230675 -0.93055561 -1.23357425 1.02315649 -0.87538827 -1.85293735
[31] -1.14757072 -1.38216611 1.74944680 -0.42160462 -0.95814384 0.42323184
[37] -0.57614428 1.96355026 0.31966361 -0.05892561 -0.02860717 -0.91921481
[43] 0.56779065 -0.17248608 -0.78965073 1.18972496 -0.54785008 0.16664171
[49] 1.28419787 -1.43970174 0.21909027 0.62224694 -0.73032337 1.45699806
[55] -0.97711222 -0.95940427 -1.67464551 -0.87807701 0.11097400 0.71002071
[61] 0.09532603 -0.14235449 -2.03879117 -1.64649878 0.74053854 -0.75028219
[67] 1.43495221 0.07371052 0.54607575 0.90607720 -0.37174989 0.63124552
[73] -1.25058196 2.52264045 0.16840768 0.03800531 0.57424185 -0.92476236
[79] -0.62194616 0.10866631 -1.85996375 0.44891434 -1.62010327 -0.26548433
[85] 0.09843831 0.11263790 -0.49903657 0.39579377 -1.59934688 1.88705004
[91] 0.07239028 -0.71731194 -0.37442088 -0.47471438 0.06116141 0.66020164
[97] -1.21729389 -0.36920449 0.27633391 0.62456898
> colSums(tmp)
[1] -0.32429485 -0.95491187 0.47838695 -0.40620077 -1.25774045 0.44508391
[7] -0.38152309 -0.27434816 0.61887871 1.11505561 -1.75856473 -1.67609804
[13] 0.67819976 0.81604784 -1.14993267 0.22327575 -0.07923951 -1.60680162
[19] -0.16903607 -0.48034077 -0.60155561 1.23845604 -0.43133773 -0.82216264
[25] -0.03230675 -0.93055561 -1.23357425 1.02315649 -0.87538827 -1.85293735
[31] -1.14757072 -1.38216611 1.74944680 -0.42160462 -0.95814384 0.42323184
[37] -0.57614428 1.96355026 0.31966361 -0.05892561 -0.02860717 -0.91921481
[43] 0.56779065 -0.17248608 -0.78965073 1.18972496 -0.54785008 0.16664171
[49] 1.28419787 -1.43970174 0.21909027 0.62224694 -0.73032337 1.45699806
[55] -0.97711222 -0.95940427 -1.67464551 -0.87807701 0.11097400 0.71002071
[61] 0.09532603 -0.14235449 -2.03879117 -1.64649878 0.74053854 -0.75028219
[67] 1.43495221 0.07371052 0.54607575 0.90607720 -0.37174989 0.63124552
[73] -1.25058196 2.52264045 0.16840768 0.03800531 0.57424185 -0.92476236
[79] -0.62194616 0.10866631 -1.85996375 0.44891434 -1.62010327 -0.26548433
[85] 0.09843831 0.11263790 -0.49903657 0.39579377 -1.59934688 1.88705004
[91] 0.07239028 -0.71731194 -0.37442088 -0.47471438 0.06116141 0.66020164
[97] -1.21729389 -0.36920449 0.27633391 0.62456898
> 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] -0.32429485 -0.95491187 0.47838695 -0.40620077 -1.25774045 0.44508391
[7] -0.38152309 -0.27434816 0.61887871 1.11505561 -1.75856473 -1.67609804
[13] 0.67819976 0.81604784 -1.14993267 0.22327575 -0.07923951 -1.60680162
[19] -0.16903607 -0.48034077 -0.60155561 1.23845604 -0.43133773 -0.82216264
[25] -0.03230675 -0.93055561 -1.23357425 1.02315649 -0.87538827 -1.85293735
[31] -1.14757072 -1.38216611 1.74944680 -0.42160462 -0.95814384 0.42323184
[37] -0.57614428 1.96355026 0.31966361 -0.05892561 -0.02860717 -0.91921481
[43] 0.56779065 -0.17248608 -0.78965073 1.18972496 -0.54785008 0.16664171
[49] 1.28419787 -1.43970174 0.21909027 0.62224694 -0.73032337 1.45699806
[55] -0.97711222 -0.95940427 -1.67464551 -0.87807701 0.11097400 0.71002071
[61] 0.09532603 -0.14235449 -2.03879117 -1.64649878 0.74053854 -0.75028219
[67] 1.43495221 0.07371052 0.54607575 0.90607720 -0.37174989 0.63124552
[73] -1.25058196 2.52264045 0.16840768 0.03800531 0.57424185 -0.92476236
[79] -0.62194616 0.10866631 -1.85996375 0.44891434 -1.62010327 -0.26548433
[85] 0.09843831 0.11263790 -0.49903657 0.39579377 -1.59934688 1.88705004
[91] 0.07239028 -0.71731194 -0.37442088 -0.47471438 0.06116141 0.66020164
[97] -1.21729389 -0.36920449 0.27633391 0.62456898
> colMin(tmp)
[1] -0.32429485 -0.95491187 0.47838695 -0.40620077 -1.25774045 0.44508391
[7] -0.38152309 -0.27434816 0.61887871 1.11505561 -1.75856473 -1.67609804
[13] 0.67819976 0.81604784 -1.14993267 0.22327575 -0.07923951 -1.60680162
[19] -0.16903607 -0.48034077 -0.60155561 1.23845604 -0.43133773 -0.82216264
[25] -0.03230675 -0.93055561 -1.23357425 1.02315649 -0.87538827 -1.85293735
[31] -1.14757072 -1.38216611 1.74944680 -0.42160462 -0.95814384 0.42323184
[37] -0.57614428 1.96355026 0.31966361 -0.05892561 -0.02860717 -0.91921481
[43] 0.56779065 -0.17248608 -0.78965073 1.18972496 -0.54785008 0.16664171
[49] 1.28419787 -1.43970174 0.21909027 0.62224694 -0.73032337 1.45699806
[55] -0.97711222 -0.95940427 -1.67464551 -0.87807701 0.11097400 0.71002071
[61] 0.09532603 -0.14235449 -2.03879117 -1.64649878 0.74053854 -0.75028219
[67] 1.43495221 0.07371052 0.54607575 0.90607720 -0.37174989 0.63124552
[73] -1.25058196 2.52264045 0.16840768 0.03800531 0.57424185 -0.92476236
[79] -0.62194616 0.10866631 -1.85996375 0.44891434 -1.62010327 -0.26548433
[85] 0.09843831 0.11263790 -0.49903657 0.39579377 -1.59934688 1.88705004
[91] 0.07239028 -0.71731194 -0.37442088 -0.47471438 0.06116141 0.66020164
[97] -1.21729389 -0.36920449 0.27633391 0.62456898
> colMedians(tmp)
[1] -0.32429485 -0.95491187 0.47838695 -0.40620077 -1.25774045 0.44508391
[7] -0.38152309 -0.27434816 0.61887871 1.11505561 -1.75856473 -1.67609804
[13] 0.67819976 0.81604784 -1.14993267 0.22327575 -0.07923951 -1.60680162
[19] -0.16903607 -0.48034077 -0.60155561 1.23845604 -0.43133773 -0.82216264
[25] -0.03230675 -0.93055561 -1.23357425 1.02315649 -0.87538827 -1.85293735
[31] -1.14757072 -1.38216611 1.74944680 -0.42160462 -0.95814384 0.42323184
[37] -0.57614428 1.96355026 0.31966361 -0.05892561 -0.02860717 -0.91921481
[43] 0.56779065 -0.17248608 -0.78965073 1.18972496 -0.54785008 0.16664171
[49] 1.28419787 -1.43970174 0.21909027 0.62224694 -0.73032337 1.45699806
[55] -0.97711222 -0.95940427 -1.67464551 -0.87807701 0.11097400 0.71002071
[61] 0.09532603 -0.14235449 -2.03879117 -1.64649878 0.74053854 -0.75028219
[67] 1.43495221 0.07371052 0.54607575 0.90607720 -0.37174989 0.63124552
[73] -1.25058196 2.52264045 0.16840768 0.03800531 0.57424185 -0.92476236
[79] -0.62194616 0.10866631 -1.85996375 0.44891434 -1.62010327 -0.26548433
[85] 0.09843831 0.11263790 -0.49903657 0.39579377 -1.59934688 1.88705004
[91] 0.07239028 -0.71731194 -0.37442088 -0.47471438 0.06116141 0.66020164
[97] -1.21729389 -0.36920449 0.27633391 0.62456898
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.3242948 -0.9549119 0.4783869 -0.4062008 -1.25774 0.4450839 -0.3815231
[2,] -0.3242948 -0.9549119 0.4783869 -0.4062008 -1.25774 0.4450839 -0.3815231
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.2743482 0.6188787 1.115056 -1.758565 -1.676098 0.6781998 0.8160478
[2,] -0.2743482 0.6188787 1.115056 -1.758565 -1.676098 0.6781998 0.8160478
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.149933 0.2232758 -0.07923951 -1.606802 -0.1690361 -0.4803408 -0.6015556
[2,] -1.149933 0.2232758 -0.07923951 -1.606802 -0.1690361 -0.4803408 -0.6015556
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.238456 -0.4313377 -0.8221626 -0.03230675 -0.9305556 -1.233574 1.023156
[2,] 1.238456 -0.4313377 -0.8221626 -0.03230675 -0.9305556 -1.233574 1.023156
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.8753883 -1.852937 -1.147571 -1.382166 1.749447 -0.4216046 -0.9581438
[2,] -0.8753883 -1.852937 -1.147571 -1.382166 1.749447 -0.4216046 -0.9581438
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.4232318 -0.5761443 1.96355 0.3196636 -0.05892561 -0.02860717 -0.9192148
[2,] 0.4232318 -0.5761443 1.96355 0.3196636 -0.05892561 -0.02860717 -0.9192148
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5677907 -0.1724861 -0.7896507 1.189725 -0.5478501 0.1666417 1.284198
[2,] 0.5677907 -0.1724861 -0.7896507 1.189725 -0.5478501 0.1666417 1.284198
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.439702 0.2190903 0.6222469 -0.7303234 1.456998 -0.9771122 -0.9594043
[2,] -1.439702 0.2190903 0.6222469 -0.7303234 1.456998 -0.9771122 -0.9594043
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.674646 -0.878077 0.110974 0.7100207 0.09532603 -0.1423545 -2.038791
[2,] -1.674646 -0.878077 0.110974 0.7100207 0.09532603 -0.1423545 -2.038791
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.646499 0.7405385 -0.7502822 1.434952 0.07371052 0.5460758 0.9060772
[2,] -1.646499 0.7405385 -0.7502822 1.434952 0.07371052 0.5460758 0.9060772
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.3717499 0.6312455 -1.250582 2.52264 0.1684077 0.03800531 0.5742418
[2,] -0.3717499 0.6312455 -1.250582 2.52264 0.1684077 0.03800531 0.5742418
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.9247624 -0.6219462 0.1086663 -1.859964 0.4489143 -1.620103 -0.2654843
[2,] -0.9247624 -0.6219462 0.1086663 -1.859964 0.4489143 -1.620103 -0.2654843
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.09843831 0.1126379 -0.4990366 0.3957938 -1.599347 1.88705 0.07239028
[2,] 0.09843831 0.1126379 -0.4990366 0.3957938 -1.599347 1.88705 0.07239028
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.7173119 -0.3744209 -0.4747144 0.06116141 0.6602016 -1.217294 -0.3692045
[2,] -0.7173119 -0.3744209 -0.4747144 0.06116141 0.6602016 -1.217294 -0.3692045
[,99] [,100]
[1,] 0.2763339 0.624569
[2,] 0.2763339 0.624569
>
>
> Max(tmp2)
[1] 1.839721
> Min(tmp2)
[1] -2.890083
> mean(tmp2)
[1] -0.003578952
> Sum(tmp2)
[1] -0.3578952
> Var(tmp2)
[1] 0.8431405
>
> rowMeans(tmp2)
[1] 0.13407878 -1.63340579 0.18500209 0.24719877 0.11844431 1.60023809
[7] -0.73348511 0.38491935 1.03854878 0.90139525 0.35607312 -1.32540974
[13] -1.49232741 1.64083996 -0.38836509 -2.89008329 0.72689554 1.51170767
[19] -0.07238075 0.92539336 1.28971017 -0.41562845 -1.09899894 0.43197121
[25] -0.26726888 1.00033702 0.99573347 -0.77720135 -0.01908315 -0.90517838
[31] 0.19765508 0.14793985 -0.74074600 0.83975753 -0.85682721 0.44037762
[37] -0.04621449 -0.31586029 0.73475008 1.06771631 0.19346608 -0.01160694
[43] 1.11600456 0.56198785 -0.42263663 -0.60578837 -0.48979209 1.05741620
[49] 0.46387549 0.25267166 1.03881690 -0.96632407 -1.03157483 1.44970072
[55] 0.93202260 0.61352227 -0.19041221 0.65532424 0.24360842 1.02383349
[61] 0.13493283 -0.86003589 -0.42362936 -0.33222406 -1.92037554 -0.62310963
[67] 0.47661365 1.65612367 -0.97136979 0.14177047 -0.61958847 -0.37975390
[73] 0.53607808 0.19130351 0.42790666 -0.21306249 -0.27041769 1.25985317
[79] -0.22449534 -0.60179710 0.35240806 1.83972086 -0.05356392 -1.04886620
[85] -0.42380071 0.21002699 -1.29540896 0.20788351 1.11834346 -0.71550725
[91] -0.66382221 -0.07658039 -1.10768672 -2.88884392 -0.74489893 0.29053513
[97] -0.29617959 -0.35497682 0.59586151 -1.50959625
> rowSums(tmp2)
[1] 0.13407878 -1.63340579 0.18500209 0.24719877 0.11844431 1.60023809
[7] -0.73348511 0.38491935 1.03854878 0.90139525 0.35607312 -1.32540974
[13] -1.49232741 1.64083996 -0.38836509 -2.89008329 0.72689554 1.51170767
[19] -0.07238075 0.92539336 1.28971017 -0.41562845 -1.09899894 0.43197121
[25] -0.26726888 1.00033702 0.99573347 -0.77720135 -0.01908315 -0.90517838
[31] 0.19765508 0.14793985 -0.74074600 0.83975753 -0.85682721 0.44037762
[37] -0.04621449 -0.31586029 0.73475008 1.06771631 0.19346608 -0.01160694
[43] 1.11600456 0.56198785 -0.42263663 -0.60578837 -0.48979209 1.05741620
[49] 0.46387549 0.25267166 1.03881690 -0.96632407 -1.03157483 1.44970072
[55] 0.93202260 0.61352227 -0.19041221 0.65532424 0.24360842 1.02383349
[61] 0.13493283 -0.86003589 -0.42362936 -0.33222406 -1.92037554 -0.62310963
[67] 0.47661365 1.65612367 -0.97136979 0.14177047 -0.61958847 -0.37975390
[73] 0.53607808 0.19130351 0.42790666 -0.21306249 -0.27041769 1.25985317
[79] -0.22449534 -0.60179710 0.35240806 1.83972086 -0.05356392 -1.04886620
[85] -0.42380071 0.21002699 -1.29540896 0.20788351 1.11834346 -0.71550725
[91] -0.66382221 -0.07658039 -1.10768672 -2.88884392 -0.74489893 0.29053513
[97] -0.29617959 -0.35497682 0.59586151 -1.50959625
> 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] 0.13407878 -1.63340579 0.18500209 0.24719877 0.11844431 1.60023809
[7] -0.73348511 0.38491935 1.03854878 0.90139525 0.35607312 -1.32540974
[13] -1.49232741 1.64083996 -0.38836509 -2.89008329 0.72689554 1.51170767
[19] -0.07238075 0.92539336 1.28971017 -0.41562845 -1.09899894 0.43197121
[25] -0.26726888 1.00033702 0.99573347 -0.77720135 -0.01908315 -0.90517838
[31] 0.19765508 0.14793985 -0.74074600 0.83975753 -0.85682721 0.44037762
[37] -0.04621449 -0.31586029 0.73475008 1.06771631 0.19346608 -0.01160694
[43] 1.11600456 0.56198785 -0.42263663 -0.60578837 -0.48979209 1.05741620
[49] 0.46387549 0.25267166 1.03881690 -0.96632407 -1.03157483 1.44970072
[55] 0.93202260 0.61352227 -0.19041221 0.65532424 0.24360842 1.02383349
[61] 0.13493283 -0.86003589 -0.42362936 -0.33222406 -1.92037554 -0.62310963
[67] 0.47661365 1.65612367 -0.97136979 0.14177047 -0.61958847 -0.37975390
[73] 0.53607808 0.19130351 0.42790666 -0.21306249 -0.27041769 1.25985317
[79] -0.22449534 -0.60179710 0.35240806 1.83972086 -0.05356392 -1.04886620
[85] -0.42380071 0.21002699 -1.29540896 0.20788351 1.11834346 -0.71550725
[91] -0.66382221 -0.07658039 -1.10768672 -2.88884392 -0.74489893 0.29053513
[97] -0.29617959 -0.35497682 0.59586151 -1.50959625
> rowMin(tmp2)
[1] 0.13407878 -1.63340579 0.18500209 0.24719877 0.11844431 1.60023809
[7] -0.73348511 0.38491935 1.03854878 0.90139525 0.35607312 -1.32540974
[13] -1.49232741 1.64083996 -0.38836509 -2.89008329 0.72689554 1.51170767
[19] -0.07238075 0.92539336 1.28971017 -0.41562845 -1.09899894 0.43197121
[25] -0.26726888 1.00033702 0.99573347 -0.77720135 -0.01908315 -0.90517838
[31] 0.19765508 0.14793985 -0.74074600 0.83975753 -0.85682721 0.44037762
[37] -0.04621449 -0.31586029 0.73475008 1.06771631 0.19346608 -0.01160694
[43] 1.11600456 0.56198785 -0.42263663 -0.60578837 -0.48979209 1.05741620
[49] 0.46387549 0.25267166 1.03881690 -0.96632407 -1.03157483 1.44970072
[55] 0.93202260 0.61352227 -0.19041221 0.65532424 0.24360842 1.02383349
[61] 0.13493283 -0.86003589 -0.42362936 -0.33222406 -1.92037554 -0.62310963
[67] 0.47661365 1.65612367 -0.97136979 0.14177047 -0.61958847 -0.37975390
[73] 0.53607808 0.19130351 0.42790666 -0.21306249 -0.27041769 1.25985317
[79] -0.22449534 -0.60179710 0.35240806 1.83972086 -0.05356392 -1.04886620
[85] -0.42380071 0.21002699 -1.29540896 0.20788351 1.11834346 -0.71550725
[91] -0.66382221 -0.07658039 -1.10768672 -2.88884392 -0.74489893 0.29053513
[97] -0.29617959 -0.35497682 0.59586151 -1.50959625
>
> colMeans(tmp2)
[1] -0.003578952
> colSums(tmp2)
[1] -0.3578952
> colVars(tmp2)
[1] 0.8431405
> colSd(tmp2)
[1] 0.9182268
> colMax(tmp2)
[1] 1.839721
> colMin(tmp2)
[1] -2.890083
> colMedians(tmp2)
[1] 0.1262615
> colRanges(tmp2)
[,1]
[1,] -2.890083
[2,] 1.839721
>
> 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] -1.07753800 1.37582462 5.28580863 1.78602444 -6.76235138 3.73151371
[7] -5.16895326 -4.68063399 3.26923339 0.06282262
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4377604
[2,] -0.9742708
[3,] -0.2514991
[4,] 0.6549459
[5,] 1.2914326
>
> rowApply(tmp,sum)
[1] -4.3330672 -0.7110282 0.2941481 0.6984979 -1.4217761 0.5941073
[7] -2.3257876 4.0140160 -0.4464867 1.4591273
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 10 5 2 9 3 2 2 10 6
[2,] 10 2 3 9 6 9 4 3 6 4
[3,] 9 4 4 8 7 7 7 9 9 8
[4,] 7 1 1 7 10 2 9 8 8 5
[5,] 1 8 9 1 3 4 5 1 1 10
[6,] 8 6 10 4 5 6 6 7 7 9
[7,] 2 9 2 3 8 5 3 6 3 2
[8,] 4 3 6 5 2 8 8 4 2 1
[9,] 3 5 8 6 4 10 10 5 5 7
[10,] 6 7 7 10 1 1 1 10 4 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.1646068 3.1119263 -0.7228249 1.0817543 -1.6536616 -3.9289635
[7] -2.2089803 -0.4868782 2.1824257 -0.3934438 -0.4257626 -0.1715226
[13] -3.5571304 -1.3910647 0.1888129 -0.1109644 1.4514014 -0.1626225
[19] 1.6546127 -1.0577588
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.041513008
[2,] -0.002228265
[3,] 0.184678679
[4,] 0.683584960
[5,] 1.340084407
>
> rowApply(tmp,sum)
[1] 5.019897 2.018172 -1.340486 -4.537723 -5.595898
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 12 14 18 12
[2,] 14 9 13 17 20
[3,] 2 11 20 5 11
[4,] 16 13 9 13 14
[5,] 4 8 17 4 10
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.683584960 0.74464884 -1.1271990 1.0280016 -0.7580598 0.08918339
[2,] 0.184678679 -0.16623871 0.1313278 0.3368567 -0.1843009 -0.47498523
[3,] -0.002228265 -0.03146862 1.3898275 -0.2102428 0.5423555 -1.24073364
[4,] 1.340084407 0.62277573 -1.0025091 -0.3686420 -1.0443790 -0.86869181
[5,] -0.041513008 1.94220909 -0.1142721 0.2957807 -0.2092775 -1.43373620
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 2.1056060 1.2540556 -0.4218769 0.66287163 1.9554978 -0.7332342
[2,] -1.3025606 -0.6443711 1.0712860 -0.01419154 0.4667179 0.7582312
[3,] -0.3019193 -0.1212194 -0.1895275 -0.90570826 0.8091221 1.1574839
[4,] -0.6050782 -0.4994860 1.4193529 -0.49205336 -1.3096935 -0.3783798
[5,] -2.1050282 -0.4758572 0.3031912 0.35563776 -2.3474069 -0.9756238
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.4464767 -0.8545657 -0.6876825 0.78301629 0.21003075 1.49134937
[2,] 0.4472752 -0.2033659 -1.2810560 0.66284833 1.38973248 -0.68907949
[3,] -0.2586737 0.1250438 -0.3333222 -1.07892366 0.26363583 -0.04314013
[4,] -0.8625528 -1.1889406 2.0464140 -0.08554009 -0.07420344 -0.40827818
[5,] -1.4367024 0.7307637 0.4444596 -0.39236527 -0.33779419 -0.51347403
[,19] [,20]
[1,] 0.3411150 -0.29996978
[2,] 2.1567161 -0.62734889
[3,] -0.2720566 -0.63879093
[4,] -1.2448865 0.46696447
[5,] 0.6737248 0.04138636
>
>
> 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 0.9043392 -0.335819 1.586257 -0.1391031 -0.5995836 -2.254901 0.6588424
col8 col9 col10 col11 col12 col13 col14
row1 -0.07166607 2.108504 -1.555365 -1.566584 -0.2529169 0.7337492 0.883597
col15 col16 col17 col18 col19 col20
row1 -1.116151 -0.7029467 -1.180383 1.959815 0.0435054 0.185266
> tmp[,"col10"]
col10
row1 -1.5553650
row2 -2.1154921
row3 -0.7916441
row4 -1.1261500
row5 0.6597264
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.9043392 -0.335819 1.586257 -0.1391031 -0.5995836 -2.2549014 0.6588424
row5 0.9736894 -1.060038 1.001424 -0.8536967 -0.6599109 0.8079819 -0.1834639
col8 col9 col10 col11 col12 col13
row1 -0.07166607 2.1085041 -1.5553650 -1.5665840 -0.2529169 0.7337492
row5 0.06344531 -0.1319879 0.6597264 0.5510807 0.9856153 -1.5745344
col14 col15 col16 col17 col18 col19
row1 0.8835970 -1.11615055 -0.7029467 -1.1803826 1.9598152 0.0435054
row5 -0.1031277 0.03438402 2.2831048 0.3395472 0.4668811 -0.6830420
col20
row1 0.1852660
row5 -0.1042206
> tmp[,c("col6","col20")]
col6 col20
row1 -2.2549014 0.18526599
row2 -0.5394201 -1.22094535
row3 0.3280862 0.12875641
row4 0.5280261 0.06270366
row5 0.8079819 -0.10422062
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -2.2549014 0.1852660
row5 0.8079819 -0.1042206
>
>
>
>
> 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 50.10004 50.07821 49.95662 51.53046 50.11325 106.0219 48.71259 51.35455
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.17469 51.33642 48.45314 51.26106 48.88783 52.58422 49.43412 49.53441
col17 col18 col19 col20
row1 48.28359 49.11105 50.67755 106.1019
> tmp[,"col10"]
col10
row1 51.33642
row2 30.63427
row3 29.67958
row4 29.24886
row5 51.21220
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.10004 50.07821 49.95662 51.53046 50.11325 106.0219 48.71259 51.35455
row5 48.49759 49.70692 52.03650 51.50127 49.74759 105.0311 47.90797 51.09762
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.17469 51.33642 48.45314 51.26106 48.88783 52.58422 49.43412 49.53441
row5 50.34994 51.21220 49.89954 50.27140 48.94273 49.10816 49.75903 49.95022
col17 col18 col19 col20
row1 48.28359 49.11105 50.67755 106.1019
row5 49.76231 50.65489 50.65736 106.1701
> tmp[,c("col6","col20")]
col6 col20
row1 106.02190 106.10185
row2 75.59238 75.98669
row3 74.74070 75.76130
row4 75.00486 74.45395
row5 105.03110 106.17008
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.0219 106.1019
row5 105.0311 106.1701
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.0219 106.1019
row5 105.0311 106.1701
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.1039425
[2,] -1.4882482
[3,] 0.3996271
[4,] 0.4439336
[5,] 0.9942750
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7683192 1.30592342
[2,] -0.1665449 -0.41958644
[3,] 0.9250239 -0.01728879
[4,] 0.4338614 -1.09231112
[5,] 0.3704553 -0.03648840
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.11369403 -0.7805742
[2,] -2.00266803 -0.1440794
[3,] 0.08483975 0.7698697
[4,] -0.70799702 1.1261526
[5,] -1.84211610 0.4895647
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.113694
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.113694
[2,] -2.002668
>
>
>
> 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]
row3 0.6619502 -0.95220876 0.5250994 -0.6738060 0.4718010 -0.1407812
row1 -1.7857704 0.08946434 -1.3698169 -0.1136101 0.2261133 0.7035521
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.1288473 0.003423928 -1.1589818 0.1016415 -0.02928974 0.8992558
row1 -0.8547055 -1.255812334 -0.1750878 -0.3028425 -1.86017203 0.4390015
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.7172565 0.6857300 0.7823358 0.06135716 0.6715177 0.4111712
row1 -0.6115598 -0.8195883 -0.8131157 -0.84151462 -0.5642758 0.3900310
[,19] [,20]
row3 2.3005933 0.7544677
row1 0.5915858 0.2484858
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.03207266 -0.7140302 0.7773838 0.6501562 -0.357039 -0.161651 0.8209378
[,8] [,9] [,10]
row2 0.9238456 -0.3731973 0.4378045
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.795855 -1.144509 1.368733 -0.1287581 0.02267637 -0.390523 -0.8689233
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.852335 -0.2190655 0.2378329 -2.280444 -1.912372 0.708385 0.4525212
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.6390926 -0.3160238 0.7067784 -0.04064519 -0.770128 -0.2888313
>
>
> 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: 0xfd5f180>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef345e450ab"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef3fa9bc2d"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef331a38fbd"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef33aae1dbc"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef350d7053"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef34f836b13"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef336c91273"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef3674a88f3"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef31b17d10f"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef37e7c642"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef35d838a94"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef33c86fbc8"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef36bc4ed88"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef323b413a"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM139ef3432a634a"
>
>
> ### 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: 0x1007ae50>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x1007ae50>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x1007ae50>
> rowMedians(tmp)
[1] -0.049628690 0.004445360 -0.311950145 0.275175042 0.152673547
[6] 0.170871488 0.088396193 -0.450603319 0.047318207 -0.059749149
[11] 0.176998942 -0.595423305 -0.105338866 0.575447128 0.047055431
[16] -0.122811010 0.936626370 0.136585066 -0.071778971 -0.381917766
[21] -0.312402203 -0.183923126 0.301540168 -0.480257631 -0.500562180
[26] 0.257513211 -0.148162464 0.284284641 0.219429050 0.261351701
[31] -0.227134870 -0.545542593 -0.553345564 0.007412609 -0.461685703
[36] -0.570958427 0.085150997 0.208415199 0.375897129 -0.124719382
[41] -0.020442081 -0.458904375 -0.103956597 -0.005909395 0.248609712
[46] 0.006331935 -0.185554019 -0.087775656 0.448019604 -0.212511533
[51] -0.338378222 0.255361913 0.381555781 0.234006184 -0.148102068
[56] 0.349028734 -0.334887936 -0.054135579 0.276437727 -0.053523020
[61] 0.355536058 -0.237570604 -0.121610248 0.078015677 0.088418151
[66] 0.431592011 -0.049333730 -0.634886625 -0.505139187 -0.282803759
[71] 0.285469947 0.128692825 -0.068120470 0.012853079 0.209543719
[76] -0.180200971 -0.054310301 0.079766138 0.090976839 0.099734629
[81] 0.198491111 0.365899059 -0.092486456 -0.486435533 -0.381768813
[86] 0.103835188 0.094247608 0.157484908 -0.100518080 0.222171087
[91] 0.039750630 -0.146491664 -0.026998084 0.055208361 -0.069645332
[96] 0.358051524 -0.302857141 -0.346879831 -0.018755007 0.172824458
[101] -0.051444432 -0.350320430 0.516000659 0.078246391 -0.227442496
[106] -0.284257930 0.760531560 -0.520329892 -0.364440742 -0.231227655
[111] 0.158993270 0.114409584 -0.186548379 0.097594335 0.612500447
[116] -0.442243217 0.309673314 -0.035941531 -0.248808010 0.103583413
[121] 0.110202895 0.041436532 -0.014844670 -0.277254499 0.473891226
[126] -0.363920002 -0.017917229 -0.181619230 -0.555767168 -0.366361639
[131] -0.211109065 0.151444478 0.691699506 -0.107225244 0.080434601
[136] 0.031001439 0.349384270 -0.087045198 -0.314389099 0.187962335
[141] -0.006769434 0.102995366 0.584253547 -0.230159499 -0.615640722
[146] 0.096843377 -0.063536626 -0.310660238 -0.007949599 -0.049958901
[151] 0.322279223 -0.269026652 0.040928948 0.192060216 0.102049602
[156] 0.362211824 0.104612023 0.229431059 0.073595389 -0.167828301
[161] -0.429878885 -0.100999146 0.400075574 -0.348875046 0.096546048
[166] 0.024978740 -0.104509010 -0.469133641 0.610886467 0.358230699
[171] -0.147187225 0.353465864 -0.127513805 -0.048873597 0.207673603
[176] -0.284720582 0.613980783 0.064575299 0.118827589 0.266335560
[181] -0.037801024 0.120512025 -0.156638623 -0.167558873 -0.181063001
[186] 0.565837577 -0.529624047 0.180334283 -0.391379651 0.130153661
[191] 0.326641159 0.350433367 0.284873637 0.473581600 -0.029491609
[196] 0.421685743 0.082847662 -0.332866431 -0.016755084 -0.246072077
[201] 0.032572496 -0.321819232 0.316263046 0.096299716 -0.370099537
[206] 0.052626194 0.165691763 -0.277476451 -0.394186183 0.054268454
[211] -0.082299174 0.323051135 0.233918287 0.376227318 -0.952030383
[216] -0.141787157 0.265149928 0.278712289 0.075986700 0.177323743
[221] -0.113465920 0.579314509 -0.203510095 0.224112684 -0.341075769
[226] -0.027566270 0.403652621 0.109858778 -0.183106710 -0.750610881
>
> proc.time()
user system elapsed
1.925 0.893 2.849
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: 0x1e9aaff0>
> .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: 0x1e9aaff0>
> .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: 0x1e9aaff0>
> .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: 0x1e9aaff0>
> 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: 0x1e8900e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e8900e0>
> .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: 0x1e8900e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e8900e0>
> .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: 0x1e8900e0>
> 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: 0x1d817520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1d817520>
> .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: 0x1d817520>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1d817520>
> .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: 0x1d817520>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x1d817520>
> .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: 0x1d817520>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x1d817520>
> .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: 0x1d817520>
> 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: 0x1d21b720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x1d21b720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1d21b720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1d21b720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile139f3b15a390b6" "BufferedMatrixFile139f3b596fc792"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile139f3b15a390b6" "BufferedMatrixFile139f3b596fc792"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e10b7d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e10b7d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1e10b7d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1e10b7d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x1e10b7d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x1e10b7d0>
> .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: 0x1e212c90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e212c90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1e212c90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x1e212c90>
> 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: 0x1f4bb110>
> .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: 0x1f4bb110>
> rm(P)
>
> proc.time()
user system elapsed
0.341 0.035 0.362
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
0.332 0.027 0.345