Ben Bolstad
| Snapshot Date: 2025-12-08 13:45 -0500 (Mon, 08 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 2025-12-11 12:07 -0500 (Thu, 11 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" | 4879 |
| merida1 | macOS 12.7.6 Monterey | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4670 |
| kjohnson1 | macOS 13.7.5 Ventura | arm64 | 4.5.2 Patched (2025-11-04 r88984) -- "[Not] Part in a Rumble" | 4604 |
| 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 | | ||||||||
| 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: 2025-12-09 08:25:40 -0000 (Tue, 09 Dec 2025) |
| EndedAt: 2025-12-09 08:26:10 -0000 (Tue, 09 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
0.317 0.040 0.344
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 9 08:26:04 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 9 08:26:04 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: 0x171bfff0>
>
>
>
> 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 9 08:26:05 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 9 08:26:05 2025"
>
> ColMode(tmp2)
<pointer: 0x171bfff0>
>
>
>
> ### 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,] 100.5673372 0.007835161 2.0003406 -1.76262790
[2,] -0.2086617 0.559818799 1.6828124 -0.02795953
[3,] -0.1638023 -0.920906534 0.5761935 1.47319708
[4,] -0.4687021 -0.233380414 -0.3202454 -1.70774358
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.5673372 0.007835161 2.0003406 1.76262790
[2,] 0.2086617 0.559818799 1.6828124 0.02795953
[3,] 0.1638023 0.920906534 0.5761935 1.47319708
[4,] 0.4687021 0.233380414 0.3202454 1.70774358
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0283267 0.08851644 1.4143340 1.327640
[2,] 0.4567951 0.74821040 1.2972326 0.167211
[3,] 0.4047250 0.95963875 0.7590741 1.213753
[4,] 0.6846182 0.48309462 0.5659023 1.306807
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.85060 25.89300 41.14368 40.03903
[2,] 29.77661 33.04192 39.65514 26.70007
[3,] 29.21105 35.51729 33.16693 38.61073
[4,] 32.31488 30.06433 30.97927 39.77581
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x15ea26c0>
> exp(tmp5)
<pointer: 0x15ea26c0>
> log(tmp5,2)
<pointer: 0x15ea26c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.0784
> Min(tmp5)
[1] 52.49175
> mean(tmp5)
[1] 72.04736
> Sum(tmp5)
[1] 14409.47
> Var(tmp5)
[1] 881.2579
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.00131 67.10483 69.39471 71.67669 70.68739 71.61272 67.29527 69.66583
[9] 67.86138 72.17351
> rowSums(tmp5)
[1] 1860.026 1342.097 1387.894 1433.534 1413.748 1432.254 1345.905 1393.317
[9] 1357.228 1443.470
> rowVars(tmp5)
[1] 7973.70588 84.97966 60.45265 65.67122 81.15027 51.33352
[7] 68.33091 95.13041 115.57664 87.89546
> rowSd(tmp5)
[1] 89.295610 9.218442 7.775130 8.103778 9.008344 7.164741 8.266251
[8] 9.753482 10.750658 9.375258
> rowMax(tmp5)
[1] 470.07844 82.53697 80.36318 84.38586 85.31078 84.90003 83.18981
[8] 93.73607 84.96264 93.69936
> rowMin(tmp5)
[1] 53.89289 53.64444 54.00593 56.42157 58.52720 60.01640 55.57809 58.12456
[9] 52.49175 55.83121
>
> colMeans(tmp5)
[1] 109.06221 65.04626 71.46056 72.33829 70.85801 71.41338 68.10078
[8] 70.11040 65.39421 72.60329 68.57863 77.75578 68.18260 64.48331
[15] 69.80795 65.81290 74.98186 68.84511 74.87772 71.23402
> colSums(tmp5)
[1] 1090.6221 650.4626 714.6056 723.3829 708.5801 714.1338 681.0078
[8] 701.1040 653.9421 726.0329 685.7863 777.5578 681.8260 644.8331
[15] 698.0795 658.1290 749.8186 688.4511 748.7772 712.3402
> colVars(tmp5)
[1] 16152.27165 53.09698 84.12040 117.90366 112.63475 71.42248
[7] 75.18067 42.02231 74.75638 51.16015 87.45507 57.73496
[13] 205.75235 53.74019 55.18961 68.08698 52.12929 42.48190
[19] 87.33647 81.72485
> colSd(tmp5)
[1] 127.091588 7.286767 9.171717 10.858345 10.612952 8.451182
[7] 8.670679 6.482462 8.646177 7.152632 9.351742 7.598352
[13] 14.344070 7.330770 7.428971 8.251484 7.220062 6.517814
[19] 9.345398 9.040180
> colMax(tmp5)
[1] 470.07844 76.75436 85.63518 83.33599 84.99070 84.02401 81.79432
[8] 77.26702 77.46549 82.64538 84.90003 86.90702 93.73607 77.69771
[15] 81.17744 78.48040 87.85235 80.74550 93.76177 85.31078
> colMin(tmp5)
[1] 60.79898 53.89289 61.27352 55.57270 54.00593 58.12456 53.64444 55.10286
[9] 53.92628 56.72447 55.25935 59.78232 55.57809 56.42157 58.07975 52.49175
[17] 67.35627 60.12767 62.17333 60.75003
>
>
> ### 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] 93.00131 67.10483 69.39471 71.67669 NA 71.61272 67.29527 69.66583
[9] 67.86138 72.17351
> rowSums(tmp5)
[1] 1860.026 1342.097 1387.894 1433.534 NA 1432.254 1345.905 1393.317
[9] 1357.228 1443.470
> rowVars(tmp5)
[1] 7973.70588 84.97966 60.45265 65.67122 78.44435 51.33352
[7] 68.33091 95.13041 115.57664 87.89546
> rowSd(tmp5)
[1] 89.295610 9.218442 7.775130 8.103778 8.856882 7.164741 8.266251
[8] 9.753482 10.750658 9.375258
> rowMax(tmp5)
[1] 470.07844 82.53697 80.36318 84.38586 NA 84.90003 83.18981
[8] 93.73607 84.96264 93.69936
> rowMin(tmp5)
[1] 53.89289 53.64444 54.00593 56.42157 NA 60.01640 55.57809 58.12456
[9] 52.49175 55.83121
>
> colMeans(tmp5)
[1] 109.06221 65.04626 71.46056 72.33829 70.85801 71.41338 NA
[8] 70.11040 65.39421 72.60329 68.57863 77.75578 68.18260 64.48331
[15] 69.80795 65.81290 74.98186 68.84511 74.87772 71.23402
> colSums(tmp5)
[1] 1090.6221 650.4626 714.6056 723.3829 708.5801 714.1338 NA
[8] 701.1040 653.9421 726.0329 685.7863 777.5578 681.8260 644.8331
[15] 698.0795 658.1290 749.8186 688.4511 748.7772 712.3402
> colVars(tmp5)
[1] 16152.27165 53.09698 84.12040 117.90366 112.63475 71.42248
[7] NA 42.02231 74.75638 51.16015 87.45507 57.73496
[13] 205.75235 53.74019 55.18961 68.08698 52.12929 42.48190
[19] 87.33647 81.72485
> colSd(tmp5)
[1] 127.091588 7.286767 9.171717 10.858345 10.612952 8.451182
[7] NA 6.482462 8.646177 7.152632 9.351742 7.598352
[13] 14.344070 7.330770 7.428971 8.251484 7.220062 6.517814
[19] 9.345398 9.040180
> colMax(tmp5)
[1] 470.07844 76.75436 85.63518 83.33599 84.99070 84.02401 NA
[8] 77.26702 77.46549 82.64538 84.90003 86.90702 93.73607 77.69771
[15] 81.17744 78.48040 87.85235 80.74550 93.76177 85.31078
> colMin(tmp5)
[1] 60.79898 53.89289 61.27352 55.57270 54.00593 58.12456 NA 55.10286
[9] 53.92628 56.72447 55.25935 59.78232 55.57809 56.42157 58.07975 52.49175
[17] 67.35627 60.12767 62.17333 60.75003
>
> Max(tmp5,na.rm=TRUE)
[1] 470.0784
> Min(tmp5,na.rm=TRUE)
[1] 52.49175
> mean(tmp5,na.rm=TRUE)
[1] 71.99838
> Sum(tmp5,na.rm=TRUE)
[1] 14327.68
> Var(tmp5,na.rm=TRUE)
[1] 885.2265
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.00131 67.10483 69.39471 71.67669 70.10282 71.61272 67.29527 69.66583
[9] 67.86138 72.17351
> rowSums(tmp5,na.rm=TRUE)
[1] 1860.026 1342.097 1387.894 1433.534 1331.953 1432.254 1345.905 1393.317
[9] 1357.228 1443.470
> rowVars(tmp5,na.rm=TRUE)
[1] 7973.70588 84.97966 60.45265 65.67122 78.44435 51.33352
[7] 68.33091 95.13041 115.57664 87.89546
> rowSd(tmp5,na.rm=TRUE)
[1] 89.295610 9.218442 7.775130 8.103778 8.856882 7.164741 8.266251
[8] 9.753482 10.750658 9.375258
> rowMax(tmp5,na.rm=TRUE)
[1] 470.07844 82.53697 80.36318 84.38586 85.31078 84.90003 83.18981
[8] 93.73607 84.96264 93.69936
> rowMin(tmp5,na.rm=TRUE)
[1] 53.89289 53.64444 54.00593 56.42157 58.52720 60.01640 55.57809 58.12456
[9] 52.49175 55.83121
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.06221 65.04626 71.46056 72.33829 70.85801 71.41338 66.57927
[8] 70.11040 65.39421 72.60329 68.57863 77.75578 68.18260 64.48331
[15] 69.80795 65.81290 74.98186 68.84511 74.87772 71.23402
> colSums(tmp5,na.rm=TRUE)
[1] 1090.6221 650.4626 714.6056 723.3829 708.5801 714.1338 599.2135
[8] 701.1040 653.9421 726.0329 685.7863 777.5578 681.8260 644.8331
[15] 698.0795 658.1290 749.8186 688.4511 748.7772 712.3402
> colVars(tmp5,na.rm=TRUE)
[1] 16152.27165 53.09698 84.12040 117.90366 112.63475 71.42248
[7] 58.53477 42.02231 74.75638 51.16015 87.45507 57.73496
[13] 205.75235 53.74019 55.18961 68.08698 52.12929 42.48190
[19] 87.33647 81.72485
> colSd(tmp5,na.rm=TRUE)
[1] 127.091588 7.286767 9.171717 10.858345 10.612952 8.451182
[7] 7.650802 6.482462 8.646177 7.152632 9.351742 7.598352
[13] 14.344070 7.330770 7.428971 8.251484 7.220062 6.517814
[19] 9.345398 9.040180
> colMax(tmp5,na.rm=TRUE)
[1] 470.07844 76.75436 85.63518 83.33599 84.99070 84.02401 74.69865
[8] 77.26702 77.46549 82.64538 84.90003 86.90702 93.73607 77.69771
[15] 81.17744 78.48040 87.85235 80.74550 93.76177 85.31078
> colMin(tmp5,na.rm=TRUE)
[1] 60.79898 53.89289 61.27352 55.57270 54.00593 58.12456 53.64444 55.10286
[9] 53.92628 56.72447 55.25935 59.78232 55.57809 56.42157 58.07975 52.49175
[17] 67.35627 60.12767 62.17333 60.75003
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.00131 67.10483 69.39471 71.67669 NaN 71.61272 67.29527 69.66583
[9] 67.86138 72.17351
> rowSums(tmp5,na.rm=TRUE)
[1] 1860.026 1342.097 1387.894 1433.534 0.000 1432.254 1345.905 1393.317
[9] 1357.228 1443.470
> rowVars(tmp5,na.rm=TRUE)
[1] 7973.70588 84.97966 60.45265 65.67122 NA 51.33352
[7] 68.33091 95.13041 115.57664 87.89546
> rowSd(tmp5,na.rm=TRUE)
[1] 89.295610 9.218442 7.775130 8.103778 NA 7.164741 8.266251
[8] 9.753482 10.750658 9.375258
> rowMax(tmp5,na.rm=TRUE)
[1] 470.07844 82.53697 80.36318 84.38586 NA 84.90003 83.18981
[8] 93.73607 84.96264 93.69936
> rowMin(tmp5,na.rm=TRUE)
[1] 53.89289 53.64444 54.00593 56.42157 NA 60.01640 55.57809 58.12456
[9] 52.49175 55.83121
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.87034 64.92402 72.59245 71.89966 69.28771 72.57459 NaN
[8] 70.17417 65.79889 72.12613 69.69546 79.75283 68.03632 64.90762
[15] 69.84123 65.31640 74.64815 68.24923 76.02505 69.66993
> colSums(tmp5,na.rm=TRUE)
[1] 1006.8331 584.3161 653.3320 647.0970 623.5894 653.1714 0.0000
[8] 631.5675 592.1900 649.1352 627.2592 717.7754 612.3268 584.1686
[15] 628.5710 587.8476 671.8333 614.2430 684.2254 627.0294
> colVars(tmp5,na.rm=TRUE)
[1] 18082.59290 59.56597 80.22216 130.47717 98.97342 65.18051
[7] NA 47.22935 82.25852 54.99368 84.35482 20.08446
[13] 231.23066 58.43226 62.07585 73.82456 57.39262 43.79747
[19] 83.44461 64.41888
> colSd(tmp5,na.rm=TRUE)
[1] 134.471532 7.717900 8.956682 11.422660 9.948538 8.073445
[7] NA 6.872361 9.069648 7.415772 9.184488 4.481569
[13] 15.206271 7.644100 7.878823 8.592122 7.575792 6.617966
[19] 9.134802 8.026138
> colMax(tmp5,na.rm=TRUE)
[1] 470.07844 76.75436 85.63518 83.33599 80.45188 84.02401 -Inf
[8] 77.26702 77.46549 82.64538 84.90003 86.90702 93.73607 77.69771
[15] 81.17744 78.48040 87.85235 80.74550 93.76177 83.18981
> colMin(tmp5,na.rm=TRUE)
[1] 60.79898 53.89289 64.47929 55.57270 54.00593 58.12456 Inf 55.10286
[9] 53.92628 56.72447 55.25935 73.53250 55.57809 56.42157 58.07975 52.49175
[17] 67.35627 60.12767 62.17333 60.75003
>
>
>
>
> 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] 254.2968 244.2712 154.8914 182.4508 179.1568 203.1208 202.7137 413.4386
[9] 160.4476 266.6040
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 254.2968 244.2712 154.8914 182.4508 179.1568 203.1208 202.7137 413.4386
[9] 160.4476 266.6040
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.989520e-13 -1.421085e-13 2.842171e-14 -1.705303e-13 5.684342e-14
[6] -1.421085e-14 4.263256e-14 2.273737e-13 -1.705303e-13 2.842171e-14
[11] 2.273737e-13 -5.684342e-14 5.684342e-14 2.842171e-14 -2.842171e-14
[16] -5.684342e-14 5.684342e-14 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)
+ }
4 17
2 16
1 5
5 1
8 19
7 9
8 18
2 14
9 4
7 1
6 7
7 15
3 1
10 7
2 4
10 17
10 19
9 1
5 8
9 15
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] 2.624644
> Min(tmp)
[1] -2.31551
> mean(tmp)
[1] -0.03076078
> Sum(tmp)
[1] -3.076078
> Var(tmp)
[1] 0.8974022
>
> rowMeans(tmp)
[1] -0.03076078
> rowSums(tmp)
[1] -3.076078
> rowVars(tmp)
[1] 0.8974022
> rowSd(tmp)
[1] 0.9473131
> rowMax(tmp)
[1] 2.624644
> rowMin(tmp)
[1] -2.31551
>
> colMeans(tmp)
[1] 1.637868370 -0.541626986 0.355490234 -1.708876458 0.049669783
[6] -0.260691812 0.902601757 0.632475782 -1.679695803 0.023996985
[11] -0.013890015 -0.323422202 -0.374723721 0.763204102 1.220762022
[16] -0.123260866 0.125396984 0.093871584 -0.407262728 -0.892912584
[21] -0.832200707 -0.048271889 -1.160189865 -0.765380842 0.095243072
[26] 1.143916802 1.022326240 -0.569499449 -0.395510891 -0.094985477
[31] 0.389777685 -0.792232123 2.624644282 -0.044098747 -0.222390977
[36] -0.651049933 -1.024211289 0.305551531 1.846266650 -0.948740324
[41] 0.264799185 0.423243981 1.624999526 0.729205833 -0.020282484
[46] -1.280083883 -0.275388988 -1.042862485 -0.763609139 2.122675158
[51] 0.348103670 -0.031555655 1.306242140 -0.613094089 -1.341402874
[56] -0.546076642 -0.077948199 1.500945303 -1.383198661 0.353390921
[61] 0.876872374 1.227085967 0.852458537 -0.817246559 -0.428955090
[66] -0.550385291 -1.703892944 0.866081952 0.636133282 -1.516776233
[71] 0.765013561 -0.900673990 -0.855421644 0.237023610 0.066525581
[76] -0.236496473 -0.337219167 0.541257585 1.046672888 0.463370671
[81] 0.749862603 1.776029508 -0.609104262 0.513180538 0.044065887
[86] 0.297150394 0.549553018 1.244857704 -0.364179171 0.007419048
[91] -2.315509537 -0.685405008 1.427555566 -1.002852287 -1.472024662
[96] -0.519003381 -0.832864446 -0.569045488 -1.750946051 -0.452287689
> colSums(tmp)
[1] 1.637868370 -0.541626986 0.355490234 -1.708876458 0.049669783
[6] -0.260691812 0.902601757 0.632475782 -1.679695803 0.023996985
[11] -0.013890015 -0.323422202 -0.374723721 0.763204102 1.220762022
[16] -0.123260866 0.125396984 0.093871584 -0.407262728 -0.892912584
[21] -0.832200707 -0.048271889 -1.160189865 -0.765380842 0.095243072
[26] 1.143916802 1.022326240 -0.569499449 -0.395510891 -0.094985477
[31] 0.389777685 -0.792232123 2.624644282 -0.044098747 -0.222390977
[36] -0.651049933 -1.024211289 0.305551531 1.846266650 -0.948740324
[41] 0.264799185 0.423243981 1.624999526 0.729205833 -0.020282484
[46] -1.280083883 -0.275388988 -1.042862485 -0.763609139 2.122675158
[51] 0.348103670 -0.031555655 1.306242140 -0.613094089 -1.341402874
[56] -0.546076642 -0.077948199 1.500945303 -1.383198661 0.353390921
[61] 0.876872374 1.227085967 0.852458537 -0.817246559 -0.428955090
[66] -0.550385291 -1.703892944 0.866081952 0.636133282 -1.516776233
[71] 0.765013561 -0.900673990 -0.855421644 0.237023610 0.066525581
[76] -0.236496473 -0.337219167 0.541257585 1.046672888 0.463370671
[81] 0.749862603 1.776029508 -0.609104262 0.513180538 0.044065887
[86] 0.297150394 0.549553018 1.244857704 -0.364179171 0.007419048
[91] -2.315509537 -0.685405008 1.427555566 -1.002852287 -1.472024662
[96] -0.519003381 -0.832864446 -0.569045488 -1.750946051 -0.452287689
> 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] 1.637868370 -0.541626986 0.355490234 -1.708876458 0.049669783
[6] -0.260691812 0.902601757 0.632475782 -1.679695803 0.023996985
[11] -0.013890015 -0.323422202 -0.374723721 0.763204102 1.220762022
[16] -0.123260866 0.125396984 0.093871584 -0.407262728 -0.892912584
[21] -0.832200707 -0.048271889 -1.160189865 -0.765380842 0.095243072
[26] 1.143916802 1.022326240 -0.569499449 -0.395510891 -0.094985477
[31] 0.389777685 -0.792232123 2.624644282 -0.044098747 -0.222390977
[36] -0.651049933 -1.024211289 0.305551531 1.846266650 -0.948740324
[41] 0.264799185 0.423243981 1.624999526 0.729205833 -0.020282484
[46] -1.280083883 -0.275388988 -1.042862485 -0.763609139 2.122675158
[51] 0.348103670 -0.031555655 1.306242140 -0.613094089 -1.341402874
[56] -0.546076642 -0.077948199 1.500945303 -1.383198661 0.353390921
[61] 0.876872374 1.227085967 0.852458537 -0.817246559 -0.428955090
[66] -0.550385291 -1.703892944 0.866081952 0.636133282 -1.516776233
[71] 0.765013561 -0.900673990 -0.855421644 0.237023610 0.066525581
[76] -0.236496473 -0.337219167 0.541257585 1.046672888 0.463370671
[81] 0.749862603 1.776029508 -0.609104262 0.513180538 0.044065887
[86] 0.297150394 0.549553018 1.244857704 -0.364179171 0.007419048
[91] -2.315509537 -0.685405008 1.427555566 -1.002852287 -1.472024662
[96] -0.519003381 -0.832864446 -0.569045488 -1.750946051 -0.452287689
> colMin(tmp)
[1] 1.637868370 -0.541626986 0.355490234 -1.708876458 0.049669783
[6] -0.260691812 0.902601757 0.632475782 -1.679695803 0.023996985
[11] -0.013890015 -0.323422202 -0.374723721 0.763204102 1.220762022
[16] -0.123260866 0.125396984 0.093871584 -0.407262728 -0.892912584
[21] -0.832200707 -0.048271889 -1.160189865 -0.765380842 0.095243072
[26] 1.143916802 1.022326240 -0.569499449 -0.395510891 -0.094985477
[31] 0.389777685 -0.792232123 2.624644282 -0.044098747 -0.222390977
[36] -0.651049933 -1.024211289 0.305551531 1.846266650 -0.948740324
[41] 0.264799185 0.423243981 1.624999526 0.729205833 -0.020282484
[46] -1.280083883 -0.275388988 -1.042862485 -0.763609139 2.122675158
[51] 0.348103670 -0.031555655 1.306242140 -0.613094089 -1.341402874
[56] -0.546076642 -0.077948199 1.500945303 -1.383198661 0.353390921
[61] 0.876872374 1.227085967 0.852458537 -0.817246559 -0.428955090
[66] -0.550385291 -1.703892944 0.866081952 0.636133282 -1.516776233
[71] 0.765013561 -0.900673990 -0.855421644 0.237023610 0.066525581
[76] -0.236496473 -0.337219167 0.541257585 1.046672888 0.463370671
[81] 0.749862603 1.776029508 -0.609104262 0.513180538 0.044065887
[86] 0.297150394 0.549553018 1.244857704 -0.364179171 0.007419048
[91] -2.315509537 -0.685405008 1.427555566 -1.002852287 -1.472024662
[96] -0.519003381 -0.832864446 -0.569045488 -1.750946051 -0.452287689
> colMedians(tmp)
[1] 1.637868370 -0.541626986 0.355490234 -1.708876458 0.049669783
[6] -0.260691812 0.902601757 0.632475782 -1.679695803 0.023996985
[11] -0.013890015 -0.323422202 -0.374723721 0.763204102 1.220762022
[16] -0.123260866 0.125396984 0.093871584 -0.407262728 -0.892912584
[21] -0.832200707 -0.048271889 -1.160189865 -0.765380842 0.095243072
[26] 1.143916802 1.022326240 -0.569499449 -0.395510891 -0.094985477
[31] 0.389777685 -0.792232123 2.624644282 -0.044098747 -0.222390977
[36] -0.651049933 -1.024211289 0.305551531 1.846266650 -0.948740324
[41] 0.264799185 0.423243981 1.624999526 0.729205833 -0.020282484
[46] -1.280083883 -0.275388988 -1.042862485 -0.763609139 2.122675158
[51] 0.348103670 -0.031555655 1.306242140 -0.613094089 -1.341402874
[56] -0.546076642 -0.077948199 1.500945303 -1.383198661 0.353390921
[61] 0.876872374 1.227085967 0.852458537 -0.817246559 -0.428955090
[66] -0.550385291 -1.703892944 0.866081952 0.636133282 -1.516776233
[71] 0.765013561 -0.900673990 -0.855421644 0.237023610 0.066525581
[76] -0.236496473 -0.337219167 0.541257585 1.046672888 0.463370671
[81] 0.749862603 1.776029508 -0.609104262 0.513180538 0.044065887
[86] 0.297150394 0.549553018 1.244857704 -0.364179171 0.007419048
[91] -2.315509537 -0.685405008 1.427555566 -1.002852287 -1.472024662
[96] -0.519003381 -0.832864446 -0.569045488 -1.750946051 -0.452287689
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.637868 -0.541627 0.3554902 -1.708876 0.04966978 -0.2606918 0.9026018
[2,] 1.637868 -0.541627 0.3554902 -1.708876 0.04966978 -0.2606918 0.9026018
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.6324758 -1.679696 0.02399698 -0.01389001 -0.3234222 -0.3747237 0.7632041
[2,] 0.6324758 -1.679696 0.02399698 -0.01389001 -0.3234222 -0.3747237 0.7632041
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.220762 -0.1232609 0.125397 0.09387158 -0.4072627 -0.8929126 -0.8322007
[2,] 1.220762 -0.1232609 0.125397 0.09387158 -0.4072627 -0.8929126 -0.8322007
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.04827189 -1.16019 -0.7653808 0.09524307 1.143917 1.022326 -0.5694994
[2,] -0.04827189 -1.16019 -0.7653808 0.09524307 1.143917 1.022326 -0.5694994
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.3955109 -0.09498548 0.3897777 -0.7922321 2.624644 -0.04409875 -0.222391
[2,] -0.3955109 -0.09498548 0.3897777 -0.7922321 2.624644 -0.04409875 -0.222391
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.6510499 -1.024211 0.3055515 1.846267 -0.9487403 0.2647992 0.423244
[2,] -0.6510499 -1.024211 0.3055515 1.846267 -0.9487403 0.2647992 0.423244
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.625 0.7292058 -0.02028248 -1.280084 -0.275389 -1.042862 -0.7636091
[2,] 1.625 0.7292058 -0.02028248 -1.280084 -0.275389 -1.042862 -0.7636091
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 2.122675 0.3481037 -0.03155565 1.306242 -0.6130941 -1.341403 -0.5460766
[2,] 2.122675 0.3481037 -0.03155565 1.306242 -0.6130941 -1.341403 -0.5460766
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.0779482 1.500945 -1.383199 0.3533909 0.8768724 1.227086 0.8524585
[2,] -0.0779482 1.500945 -1.383199 0.3533909 0.8768724 1.227086 0.8524585
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.8172466 -0.4289551 -0.5503853 -1.703893 0.866082 0.6361333 -1.516776
[2,] -0.8172466 -0.4289551 -0.5503853 -1.703893 0.866082 0.6361333 -1.516776
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.7650136 -0.900674 -0.8554216 0.2370236 0.06652558 -0.2364965 -0.3372192
[2,] 0.7650136 -0.900674 -0.8554216 0.2370236 0.06652558 -0.2364965 -0.3372192
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.5412576 1.046673 0.4633707 0.7498626 1.77603 -0.6091043 0.5131805
[2,] 0.5412576 1.046673 0.4633707 0.7498626 1.77603 -0.6091043 0.5131805
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.04406589 0.2971504 0.549553 1.244858 -0.3641792 0.007419048 -2.31551
[2,] 0.04406589 0.2971504 0.549553 1.244858 -0.3641792 0.007419048 -2.31551
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.685405 1.427556 -1.002852 -1.472025 -0.5190034 -0.8328644 -0.5690455
[2,] -0.685405 1.427556 -1.002852 -1.472025 -0.5190034 -0.8328644 -0.5690455
[,99] [,100]
[1,] -1.750946 -0.4522877
[2,] -1.750946 -0.4522877
>
>
> Max(tmp2)
[1] 1.966967
> Min(tmp2)
[1] -1.810455
> mean(tmp2)
[1] 0.08184211
> Sum(tmp2)
[1] 8.184211
> Var(tmp2)
[1] 0.7526563
>
> rowMeans(tmp2)
[1] -0.4784277899 0.6414072888 0.1440241944 -0.7846932783 -0.2886033948
[6] 0.5053085891 -1.0957740518 0.2743228411 1.1239676193 0.2680134501
[11] -1.4198920561 -0.6683562932 0.2420772159 -1.3230852521 -1.1997335551
[16] 0.0961478884 -0.8414840935 -0.0599134272 0.0077795395 1.5825996576
[21] 0.4397914793 -0.6851678927 -0.3066259955 1.1016501071 0.1188690499
[26] -0.0793855323 0.3015107098 0.7833375028 -1.1577066422 1.9669671551
[31] -1.5050626595 0.4368821093 0.1366886251 1.3878866836 0.6763329795
[36] -0.4818971552 1.2642450899 0.8608530351 1.2044770787 -0.0756424540
[41] 0.6426382258 -0.5800382695 -0.1958998131 -0.6806012631 0.3863614489
[46] 1.7651346802 -0.4662178548 0.5972653564 1.1616806239 1.4744264712
[51] -1.6151792015 -1.3418731525 -0.6030506293 -0.2304845826 1.1062752058
[56] 0.2816270174 -0.7203674792 1.2552418208 0.2705452152 0.1016747814
[61] -1.0634885483 1.5212473032 -0.0132103681 0.8552682766 -1.5512887400
[66] -0.0351287893 -1.0820198306 -0.0088388391 -0.1303649953 -0.0533891192
[71] 0.7583781060 0.1817561883 0.5503007001 0.2405575458 -1.0435900924
[76] 0.8850717323 0.3478224937 0.7647033146 1.7238382571 0.2277351349
[81] 1.0544306096 -0.0003597311 -0.8514267053 -1.0674225933 0.8830452903
[86] 0.9213129211 1.2255281424 -1.1438583803 -0.6981921510 -0.3018053037
[91] -0.9563280609 -1.8104549216 0.4862321557 0.0961041007 0.4161762192
[96] -0.0299114842 0.2347941714 1.0919871387 -0.2994407743 0.1355939440
> rowSums(tmp2)
[1] -0.4784277899 0.6414072888 0.1440241944 -0.7846932783 -0.2886033948
[6] 0.5053085891 -1.0957740518 0.2743228411 1.1239676193 0.2680134501
[11] -1.4198920561 -0.6683562932 0.2420772159 -1.3230852521 -1.1997335551
[16] 0.0961478884 -0.8414840935 -0.0599134272 0.0077795395 1.5825996576
[21] 0.4397914793 -0.6851678927 -0.3066259955 1.1016501071 0.1188690499
[26] -0.0793855323 0.3015107098 0.7833375028 -1.1577066422 1.9669671551
[31] -1.5050626595 0.4368821093 0.1366886251 1.3878866836 0.6763329795
[36] -0.4818971552 1.2642450899 0.8608530351 1.2044770787 -0.0756424540
[41] 0.6426382258 -0.5800382695 -0.1958998131 -0.6806012631 0.3863614489
[46] 1.7651346802 -0.4662178548 0.5972653564 1.1616806239 1.4744264712
[51] -1.6151792015 -1.3418731525 -0.6030506293 -0.2304845826 1.1062752058
[56] 0.2816270174 -0.7203674792 1.2552418208 0.2705452152 0.1016747814
[61] -1.0634885483 1.5212473032 -0.0132103681 0.8552682766 -1.5512887400
[66] -0.0351287893 -1.0820198306 -0.0088388391 -0.1303649953 -0.0533891192
[71] 0.7583781060 0.1817561883 0.5503007001 0.2405575458 -1.0435900924
[76] 0.8850717323 0.3478224937 0.7647033146 1.7238382571 0.2277351349
[81] 1.0544306096 -0.0003597311 -0.8514267053 -1.0674225933 0.8830452903
[86] 0.9213129211 1.2255281424 -1.1438583803 -0.6981921510 -0.3018053037
[91] -0.9563280609 -1.8104549216 0.4862321557 0.0961041007 0.4161762192
[96] -0.0299114842 0.2347941714 1.0919871387 -0.2994407743 0.1355939440
> 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] -0.4784277899 0.6414072888 0.1440241944 -0.7846932783 -0.2886033948
[6] 0.5053085891 -1.0957740518 0.2743228411 1.1239676193 0.2680134501
[11] -1.4198920561 -0.6683562932 0.2420772159 -1.3230852521 -1.1997335551
[16] 0.0961478884 -0.8414840935 -0.0599134272 0.0077795395 1.5825996576
[21] 0.4397914793 -0.6851678927 -0.3066259955 1.1016501071 0.1188690499
[26] -0.0793855323 0.3015107098 0.7833375028 -1.1577066422 1.9669671551
[31] -1.5050626595 0.4368821093 0.1366886251 1.3878866836 0.6763329795
[36] -0.4818971552 1.2642450899 0.8608530351 1.2044770787 -0.0756424540
[41] 0.6426382258 -0.5800382695 -0.1958998131 -0.6806012631 0.3863614489
[46] 1.7651346802 -0.4662178548 0.5972653564 1.1616806239 1.4744264712
[51] -1.6151792015 -1.3418731525 -0.6030506293 -0.2304845826 1.1062752058
[56] 0.2816270174 -0.7203674792 1.2552418208 0.2705452152 0.1016747814
[61] -1.0634885483 1.5212473032 -0.0132103681 0.8552682766 -1.5512887400
[66] -0.0351287893 -1.0820198306 -0.0088388391 -0.1303649953 -0.0533891192
[71] 0.7583781060 0.1817561883 0.5503007001 0.2405575458 -1.0435900924
[76] 0.8850717323 0.3478224937 0.7647033146 1.7238382571 0.2277351349
[81] 1.0544306096 -0.0003597311 -0.8514267053 -1.0674225933 0.8830452903
[86] 0.9213129211 1.2255281424 -1.1438583803 -0.6981921510 -0.3018053037
[91] -0.9563280609 -1.8104549216 0.4862321557 0.0961041007 0.4161762192
[96] -0.0299114842 0.2347941714 1.0919871387 -0.2994407743 0.1355939440
> rowMin(tmp2)
[1] -0.4784277899 0.6414072888 0.1440241944 -0.7846932783 -0.2886033948
[6] 0.5053085891 -1.0957740518 0.2743228411 1.1239676193 0.2680134501
[11] -1.4198920561 -0.6683562932 0.2420772159 -1.3230852521 -1.1997335551
[16] 0.0961478884 -0.8414840935 -0.0599134272 0.0077795395 1.5825996576
[21] 0.4397914793 -0.6851678927 -0.3066259955 1.1016501071 0.1188690499
[26] -0.0793855323 0.3015107098 0.7833375028 -1.1577066422 1.9669671551
[31] -1.5050626595 0.4368821093 0.1366886251 1.3878866836 0.6763329795
[36] -0.4818971552 1.2642450899 0.8608530351 1.2044770787 -0.0756424540
[41] 0.6426382258 -0.5800382695 -0.1958998131 -0.6806012631 0.3863614489
[46] 1.7651346802 -0.4662178548 0.5972653564 1.1616806239 1.4744264712
[51] -1.6151792015 -1.3418731525 -0.6030506293 -0.2304845826 1.1062752058
[56] 0.2816270174 -0.7203674792 1.2552418208 0.2705452152 0.1016747814
[61] -1.0634885483 1.5212473032 -0.0132103681 0.8552682766 -1.5512887400
[66] -0.0351287893 -1.0820198306 -0.0088388391 -0.1303649953 -0.0533891192
[71] 0.7583781060 0.1817561883 0.5503007001 0.2405575458 -1.0435900924
[76] 0.8850717323 0.3478224937 0.7647033146 1.7238382571 0.2277351349
[81] 1.0544306096 -0.0003597311 -0.8514267053 -1.0674225933 0.8830452903
[86] 0.9213129211 1.2255281424 -1.1438583803 -0.6981921510 -0.3018053037
[91] -0.9563280609 -1.8104549216 0.4862321557 0.0961041007 0.4161762192
[96] -0.0299114842 0.2347941714 1.0919871387 -0.2994407743 0.1355939440
>
> colMeans(tmp2)
[1] 0.08184211
> colSums(tmp2)
[1] 8.184211
> colVars(tmp2)
[1] 0.7526563
> colSd(tmp2)
[1] 0.8675577
> colMax(tmp2)
[1] 1.966967
> colMin(tmp2)
[1] -1.810455
> colMedians(tmp2)
[1] 0.1272315
> colRanges(tmp2)
[,1]
[1,] -1.810455
[2,] 1.966967
>
> 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] 4.029481 1.085038 3.531093 1.366920 2.782048 -2.263836 1.926218
[8] -2.132289 -1.286858 4.274917
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.68538519
[2,] 0.05551401
[3,] 0.50329037
[4,] 0.71398949
[5,] 1.41463377
>
> rowApply(tmp,sum)
[1] 0.139486 4.673917 -2.418531 -1.856966 4.879802 -1.445354 2.430085
[8] 2.371739 1.799465 2.739088
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 10 5 9 6 10 4 3 6 7
[2,] 2 8 8 2 3 5 3 8 9 2
[3,] 6 2 9 5 8 9 8 9 4 5
[4,] 5 3 2 4 7 8 7 5 3 10
[5,] 4 5 3 6 10 7 5 4 7 9
[6,] 1 7 7 8 1 1 1 6 1 8
[7,] 9 1 4 10 4 4 6 10 8 3
[8,] 7 6 6 7 5 3 2 1 2 1
[9,] 10 9 1 1 2 6 9 2 10 4
[10,] 3 4 10 3 9 2 10 7 5 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.22880706 0.55966571 4.44359935 0.79103569 -1.87165788 -1.79925200
[7] 5.15894661 0.77013555 2.13104504 -2.48044228 2.51218840 1.81853019
[13] -1.64601939 -1.24415002 -3.59707692 3.17471185 0.07402467 -3.08274233
[19] -1.84497932 -0.10849026
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.4352792
[2,] 0.1654373
[3,] 0.2077752
[4,] 0.8846856
[5,] 1.4061882
>
> rowApply(tmp,sum)
[1] 4.798935 -1.061823 5.822083 -4.958697 1.387381
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 17 16 7 9
[2,] 9 10 14 6 14
[3,] 1 19 17 19 20
[4,] 20 8 6 17 8
[5,] 4 3 9 8 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1654373 0.10862041 -0.9366047 1.46104327 -0.44892119 0.8901673
[2,] 1.4061882 -0.06673786 1.5063017 -0.71044235 -1.59801505 0.3409578
[3,] 0.8846856 0.64666555 0.9722804 -0.18261783 0.07551059 -0.2533713
[4,] -0.4352792 -0.75202294 1.6053204 0.30719143 -0.42730426 -1.9025167
[5,] 0.2077752 0.62314054 1.2963016 -0.08413883 0.52707203 -0.8744891
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.1892507 0.7770780 0.20923609 0.3038675 0.3459209 -0.2694756
[2,] 0.2610321 -0.9974445 1.03255706 -1.6099982 1.3244168 1.4669257
[3,] 1.3109756 0.5417130 0.18263497 -0.1799031 0.8617485 1.0148553
[4,] 1.6652031 -0.1275254 -0.02860509 -0.1155574 -0.9782942 -1.5555257
[5,] 0.7324851 0.5763145 0.73522202 -0.8788511 0.9583964 1.1617505
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.893691520 -0.26033217 -0.2627701 1.3453651 0.06359612 -0.7459916
[2,] -1.610899460 0.04549572 -1.2904469 -0.3484978 1.89746373 0.5342410
[3,] 0.008631458 -1.20959385 -0.3111543 0.4107368 0.27305437 -0.5090518
[4,] 0.186385942 -0.14143933 0.1087215 1.3483604 -1.34916839 -2.0491688
[5,] -1.123828852 0.32171961 -1.8414271 0.4187473 -0.81092116 -0.3127710
[,19] [,20]
[1,] -0.4817297 0.45148558
[2,] -1.4290638 -1.21585686
[3,] -0.6132884 1.89757173
[4,] -0.2292767 -0.08819519
[5,] 0.9083792 -1.15349553
>
>
> 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 : 649 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 : 560 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.030283 -0.33207 -0.6751216 -0.7100105 1.826782 -0.4412567 -0.9194669
col8 col9 col10 col11 col12 col13 col14
row1 0.5459671 0.6517422 -0.1951442 1.150219 0.2499366 0.3952631 1.207441
col15 col16 col17 col18 col19 col20
row1 2.758106 0.2827302 0.1905229 0.7856886 0.323126 -0.3253055
> tmp[,"col10"]
col10
row1 -0.1951442
row2 -0.6931673
row3 0.2304365
row4 -1.9441383
row5 -0.7683427
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.0302835 -0.332070 -0.6751216 -0.7100105 1.8267819 -0.4412567
row5 -0.8239855 -1.512074 -0.1028689 -0.8868086 0.5156394 1.0192968
col7 col8 col9 col10 col11 col12
row1 -0.91946694 0.5459671 0.6517422 -0.1951442 1.15021888 0.2499366
row5 -0.04828676 -0.6029756 -0.4509653 -0.7683427 0.09797459 0.6384614
col13 col14 col15 col16 col17 col18 col19
row1 0.3952631 1.2074409 2.758106 0.28273019 0.1905229 0.7856886 0.323126
row5 -1.2940650 -0.9255508 2.694999 0.02933813 1.1062745 1.0233727 -1.149833
col20
row1 -0.3253055
row5 0.1195127
> tmp[,c("col6","col20")]
col6 col20
row1 -0.441256725 -0.3253055
row2 -0.257616810 -0.5066515
row3 -0.007609483 -0.5570180
row4 1.312163307 1.7812945
row5 1.019296816 0.1195127
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.4412567 -0.3253055
row5 1.0192968 0.1195127
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.14317 51.43191 50.4284 49.90725 49.93696 104.4215 50.3234 50.00229
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52277 50.83579 50.90054 49.54469 49.68644 49.46035 51.14918 49.64061
col17 col18 col19 col20
row1 51.55798 49.06477 49.87438 105.3783
> tmp[,"col10"]
col10
row1 50.83579
row2 31.17328
row3 30.37974
row4 29.77272
row5 51.30029
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.14317 51.43191 50.42840 49.90725 49.93696 104.4215 50.32340 50.00229
row5 49.13576 50.23764 50.03861 51.08389 49.50783 104.9473 48.31857 49.63454
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52277 50.83579 50.90054 49.54469 49.68644 49.46035 51.14918 49.64061
row5 49.06528 51.30029 50.06736 50.59562 50.23094 49.45387 50.98393 48.79806
col17 col18 col19 col20
row1 51.55798 49.06477 49.87438 105.3783
row5 51.35544 50.80431 49.86479 107.1838
> tmp[,c("col6","col20")]
col6 col20
row1 104.42146 105.37831
row2 73.69028 75.53163
row3 75.77804 73.99017
row4 73.81116 76.24740
row5 104.94731 107.18381
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.4215 105.3783
row5 104.9473 107.1838
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.4215 105.3783
row5 104.9473 107.1838
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.50553003
[2,] -1.35164071
[3,] 1.67343037
[4,] -1.24962680
[5,] -0.09751052
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.66733256 -0.32833707
[2,] -0.75587886 1.16877865
[3,] 0.98523846 -0.08804664
[4,] 0.09396199 1.25809034
[5,] 0.03144245 -1.21726311
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.930898014 -0.5280996
[2,] -0.006373652 1.4321781
[3,] 1.328756439 1.0745586
[4,] 0.283839737 -0.5768943
[5,] 1.146430942 0.1632364
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.930898
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.930898014
[2,] -0.006373652
>
>
>
> 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 -0.2812189 -1.1657596 0.3985245 0.5445602 1.04461351 -0.1522232
row1 -1.7744512 -0.2549487 1.4091925 -0.8497186 0.09947928 -1.3533168
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.7015788 0.4780601 -0.4815662 1.0558472 -0.3690466 -0.2448079
row1 0.2935191 -0.8072524 -0.3371549 -0.6124422 0.7641898 -0.4475296
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.6559485 -0.29664565 -0.3183640 -0.01189204 0.8341530 0.4069952
row1 1.9174702 -0.04071218 0.1192868 -0.46633155 0.4252082 0.4209761
[,19] [,20]
row3 -0.57213539 0.8512991
row1 0.01163503 -0.3092234
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.3464354 -1.241594 -0.7954184 -1.570864 -0.5427588 0.1139848 -1.150554
[,8] [,9] [,10]
row2 0.3513944 0.1464239 -1.380685
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.08913083 2.548265 0.2733536 1.964726 0.1149463 -0.3724222 0.1322833
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.32085 -0.2438191 -0.4924829 -0.1522848 -0.9401223 -0.00859365 0.0667426
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2130262 0.6777938 0.520516 -0.4281318 0.4227303 2.249048
>
>
> 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: 0x170b47b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a63784865a"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a63bd6599"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a66a0273e"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a651c2d9f"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a64749f24d"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a663b7455"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a66d765fff"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a615d28816"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a67efab7e0"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a6231038e"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a647a8f08a"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a665b18698"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a65ef08222"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a6610f5efc"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM339a63cca85a2"
>
>
> ### 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: 0x18575bd0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x18575bd0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x18575bd0>
> rowMedians(tmp)
[1] -0.4696922799 0.3068245928 0.3566081903 0.0452257381 0.2710947770
[6] -0.3314893469 -0.2886445930 0.1250693116 -0.1712941633 -0.3616031949
[11] 0.2339108415 -0.2788100623 -0.0546158708 -0.2759794515 0.3952436395
[16] -0.6763133918 0.2447096631 -0.3696392523 -0.1213908588 0.2166202680
[21] -0.2811662213 0.4584839808 -0.1408656859 0.3242359636 -0.1409604833
[26] -0.1973991916 0.2170313207 0.0883171296 0.1701938235 -0.1825849380
[31] 0.1728433341 -0.3213473460 -0.1014018372 0.3348654905 0.0662861088
[36] -0.0148229942 0.2338717343 0.7665599625 -0.0190754221 -0.6609005812
[41] -0.2214364656 0.4903197799 -0.1409538784 -0.0880730139 0.2839067881
[46] 0.2181795109 0.4493361528 -0.0628173454 -0.0220444016 0.8789097177
[51] -0.4238266530 -0.6620890691 0.0411552648 -0.1405096530 0.6774758778
[56] -0.3516136716 0.1835502800 0.1710447847 -0.4633379828 -0.1939924239
[61] 0.0156304193 0.0293859526 -0.0473220437 0.9302692596 0.6944274156
[66] 0.3655751443 0.1008830253 -0.6649815526 0.7058346855 0.4857433021
[71] -0.5699689453 -0.2786843448 -0.2544130725 0.2741230297 -0.1333448814
[76] -0.1401801521 -0.1221405939 0.0214341337 0.0009141894 -0.3247965838
[81] 0.0122442228 0.4341576020 0.0248540366 -0.4763853688 -0.3379929887
[86] 0.4987210548 -0.2402619983 0.3103912411 0.0686056514 0.0357668963
[91] 0.1170256011 0.0551520443 0.2705969779 -0.1014410167 -0.0152160868
[96] -0.0779388460 0.7891251292 0.0750683517 0.2850928028 -0.3646989183
[101] 0.4306243632 -0.0335467862 -0.1309303074 -0.4009242735 -0.5119665967
[106] 0.3004642428 0.4569489490 0.2206454232 -0.1689836397 -0.2209597992
[111] -0.2332947113 0.6222182637 0.2185088157 0.1728943415 0.2104768303
[116] 0.2093164314 0.3940047820 0.5449212875 -0.1865846948 0.6103040434
[121] -0.2813552277 0.3317591163 0.2035457309 0.2897547030 0.6260241307
[126] -0.0464069369 -0.2024269629 0.2975110175 0.2207372676 -0.1106264216
[131] 0.2367989294 0.2414164115 0.1832689942 -0.1866467466 0.1093688470
[136] 0.1566595457 0.0977506933 0.2708666033 0.3083250609 -0.0436344390
[141] -0.3691716271 0.1715111793 -0.3426781034 0.0804303579 0.5905431043
[146] 0.5642630609 -0.2801431767 0.2860188710 -0.0010832924 0.0243739624
[151] 0.2470363200 0.0906303458 -0.3183403753 0.2519369978 -0.3689041688
[156] -0.1843816425 0.0289508518 0.4740589498 0.4064728753 0.1317639164
[161] 0.2552946661 0.0853205812 -0.5602869916 -0.3433664658 0.3387880564
[166] -0.1462162429 0.2467669893 -0.2108427213 -0.2088412812 0.6248990564
[171] -0.0657343085 -0.0456604208 -0.4705597695 0.2181629225 -0.4186381399
[176] -0.0382323829 -0.0988005202 0.1784215315 -0.0046613405 -0.2527055942
[181] -0.4671199341 -0.0190320415 0.3948387309 0.0992044766 -0.2883578157
[186] -0.0013642956 -0.0864082251 -0.4435586962 0.1378587160 -0.1061607159
[191] -0.7162200034 0.1234349505 0.5386174209 -0.1260075195 0.3307367170
[196] -0.4760887575 -0.6510250127 0.3936307804 0.5837434107 -0.0748182102
[201] 0.1231264544 0.4259159641 -0.0742624374 0.1619670489 -0.2915375886
[206] 0.3965788725 -0.0898976263 0.2645740625 -0.4133091672 0.4180566183
[211] 0.1505584267 0.2497669087 0.0219169896 -0.3408458192 -0.2893865899
[216] 0.0979572771 0.0187522248 0.1550952042 -0.0874765544 -0.5703847092
[221] -0.0656556364 -0.0588767241 -0.4932341780 -0.2995142865 0.4932804714
[226] -0.3119004305 -0.2423862392 -0.4660401245 -0.3538920020 0.1785590686
>
> proc.time()
user system elapsed
1.918 0.822 2.765
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: 0x24159ff0>
> .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: 0x24159ff0>
> .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: 0x24159ff0>
> .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: 0x24159ff0>
> 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: 0x2403f0e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2403f0e0>
> .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: 0x2403f0e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2403f0e0>
> .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: 0x2403f0e0>
> 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: 0x22fc6520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x22fc6520>
> .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: 0x22fc6520>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x22fc6520>
> .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: 0x22fc6520>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x22fc6520>
> .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: 0x22fc6520>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x22fc6520>
> .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: 0x22fc6520>
> 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: 0x229ca720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x229ca720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x229ca720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x229ca720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile33a125c6212e3" "BufferedMatrixFile33a12d378d18"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile33a125c6212e3" "BufferedMatrixFile33a12d378d18"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x238ba7d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x238ba7d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x238ba7d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x238ba7d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x238ba7d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x238ba7d0>
> .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: 0x239c1c90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x239c1c90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x239c1c90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x239c1c90>
> 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: 0x24c6a110>
> .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: 0x24c6a110>
> rm(P)
>
> proc.time()
user system elapsed
0.314 0.046 0.345
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.306 0.063 0.354