Ben Bolstad
| Snapshot Date: 2025-10-17 13:45 -0400 (Fri, 17 Oct 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-10-18 12:03 -0400 (Sat, 18 Oct 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4887 |
| lconway | macOS 12.7.6 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4677 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4622 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4632 |
| 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 256/2353 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 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. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-10-17 21:41:29 -0400 (Fri, 17 Oct 2025) |
| EndedAt: 2025-10-17 21:41:53 -0400 (Fri, 17 Oct 2025) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-08-23 r88802)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* 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: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* 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 re-building of vignette outputs ... OK
* 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/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/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){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.22-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-bioc/R/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 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
0.248 0.037 0.274
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 478419 25.6 1047111 56 639600 34.2
Vcells 885237 6.8 8388608 64 2081604 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Oct 17 21:41:43 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Oct 17 21:41:43 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: 0x5c7d7771ec80>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Oct 17 21:41:44 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Oct 17 21:41:44 2025"
>
> ColMode(tmp2)
<pointer: 0x5c7d7771ec80>
>
>
>
> ### 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,] 101.2852345 0.2394823 -2.5526702 -0.39843337
[2,] -1.5279200 -0.8513468 -0.1441321 -1.40173083
[3,] -2.3753347 0.5366954 0.2706726 0.94830338
[4,] -0.7387676 0.9052837 0.2711534 -0.01089531
> 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,] 101.2852345 0.2394823 2.5526702 0.39843337
[2,] 1.5279200 0.8513468 0.1441321 1.40173083
[3,] 2.3753347 0.5366954 0.2706726 0.94830338
[4,] 0.7387676 0.9052837 0.2711534 0.01089531
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0640566 0.4893692 1.5977078 0.6312158
[2,] 1.2360906 0.9226846 0.3796473 1.1839471
[3,] 1.5412121 0.7325950 0.5202621 0.9738087
[4,] 0.8595159 0.9514640 0.5207240 0.1043806
>
> 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,] 226.92580 30.13317 43.52975 31.71059
[2,] 38.88883 35.07819 28.94060 38.24120
[3,] 42.78746 32.86264 30.47329 35.68639
[4,] 34.33393 35.41992 30.47839 26.05470
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5c7d77f5c270>
> exp(tmp5)
<pointer: 0x5c7d77f5c270>
> log(tmp5,2)
<pointer: 0x5c7d77f5c270>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.3163
> Min(tmp5)
[1] 53.77898
> mean(tmp5)
[1] 72.64483
> Sum(tmp5)
[1] 14528.97
> Var(tmp5)
[1] 884.834
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.45906 74.21586 70.52210 69.15293 69.29293 71.55391 71.99441 68.48129
[9] 67.20873 70.56704
> rowSums(tmp5)
[1] 1869.181 1484.317 1410.442 1383.059 1385.859 1431.078 1439.888 1369.626
[9] 1344.175 1411.341
> rowVars(tmp5)
[1] 8042.59719 67.32223 110.57326 76.64627 62.14155 35.42052
[7] 83.81473 61.32543 66.36820 117.62962
> rowSd(tmp5)
[1] 89.680529 8.205013 10.515382 8.754786 7.882991 5.951514 9.155038
[8] 7.831055 8.146668 10.845719
> rowMax(tmp5)
[1] 472.31632 87.48083 92.86980 91.86667 81.92526 80.93622 87.60809
[8] 79.02094 84.18263 86.03367
> rowMin(tmp5)
[1] 59.68972 60.23608 53.77898 53.95763 55.78803 61.11684 56.08613 54.21298
[9] 54.98640 53.90667
>
> colMeans(tmp5)
[1] 113.33745 73.80346 70.22879 70.38254 75.31633 72.63573 71.01181
[8] 72.60368 69.00548 70.90448 69.44557 70.77258 69.23797 69.82040
[15] 70.68260 65.92430 69.89625 67.45510 70.38268 70.04935
> colSums(tmp5)
[1] 1133.3745 738.0346 702.2879 703.8254 753.1633 726.3573 710.1181
[8] 726.0368 690.0548 709.0448 694.4557 707.7258 692.3797 698.2040
[15] 706.8260 659.2430 698.9625 674.5510 703.8268 700.4935
> colVars(tmp5)
[1] 15971.01307 38.92441 92.27194 86.88025 107.87992 117.64681
[7] 96.06290 54.79796 79.74356 66.40622 72.12160 40.68334
[13] 110.92171 103.48120 88.21234 58.70043 70.69875 87.26903
[19] 114.83601 80.61312
> colSd(tmp5)
[1] 126.376474 6.238943 9.605829 9.320957 10.386526 10.846512
[7] 9.801168 7.402564 8.929925 8.149001 8.492444 6.378349
[13] 10.531938 10.172571 9.392142 7.661620 8.408255 9.341789
[19] 10.716156 8.978481
> colMax(tmp5)
[1] 472.31632 85.63202 90.60147 84.53937 91.86667 87.82468 92.86980
[8] 81.72706 80.05956 84.14776 84.18263 78.79831 84.79473 85.63842
[15] 87.48083 79.16144 80.93622 83.67004 86.03367 85.87884
> colMin(tmp5)
[1] 61.53656 62.71826 60.23608 54.22945 54.21298 55.78803 58.49458 61.30014
[9] 55.27868 53.95763 56.08613 61.75153 53.77898 54.40013 57.78410 54.98640
[17] 55.97519 54.33608 54.74036 58.29427
>
>
> ### 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] 93.45906 NA 70.52210 69.15293 69.29293 71.55391 71.99441 68.48129
[9] 67.20873 70.56704
> rowSums(tmp5)
[1] 1869.181 NA 1410.442 1383.059 1385.859 1431.078 1439.888 1369.626
[9] 1344.175 1411.341
> rowVars(tmp5)
[1] 8042.59719 70.98347 110.57326 76.64627 62.14155 35.42052
[7] 83.81473 61.32543 66.36820 117.62962
> rowSd(tmp5)
[1] 89.680529 8.425169 10.515382 8.754786 7.882991 5.951514 9.155038
[8] 7.831055 8.146668 10.845719
> rowMax(tmp5)
[1] 472.31632 NA 92.86980 91.86667 81.92526 80.93622 87.60809
[8] 79.02094 84.18263 86.03367
> rowMin(tmp5)
[1] 59.68972 NA 53.77898 53.95763 55.78803 61.11684 56.08613 54.21298
[9] 54.98640 53.90667
>
> colMeans(tmp5)
[1] 113.33745 73.80346 70.22879 70.38254 75.31633 72.63573 71.01181
[8] 72.60368 69.00548 70.90448 69.44557 70.77258 69.23797 NA
[15] 70.68260 65.92430 69.89625 67.45510 70.38268 70.04935
> colSums(tmp5)
[1] 1133.3745 738.0346 702.2879 703.8254 753.1633 726.3573 710.1181
[8] 726.0368 690.0548 709.0448 694.4557 707.7258 692.3797 NA
[15] 706.8260 659.2430 698.9625 674.5510 703.8268 700.4935
> colVars(tmp5)
[1] 15971.01307 38.92441 92.27194 86.88025 107.87992 117.64681
[7] 96.06290 54.79796 79.74356 66.40622 72.12160 40.68334
[13] 110.92171 NA 88.21234 58.70043 70.69875 87.26903
[19] 114.83601 80.61312
> colSd(tmp5)
[1] 126.376474 6.238943 9.605829 9.320957 10.386526 10.846512
[7] 9.801168 7.402564 8.929925 8.149001 8.492444 6.378349
[13] 10.531938 NA 9.392142 7.661620 8.408255 9.341789
[19] 10.716156 8.978481
> colMax(tmp5)
[1] 472.31632 85.63202 90.60147 84.53937 91.86667 87.82468 92.86980
[8] 81.72706 80.05956 84.14776 84.18263 78.79831 84.79473 NA
[15] 87.48083 79.16144 80.93622 83.67004 86.03367 85.87884
> colMin(tmp5)
[1] 61.53656 62.71826 60.23608 54.22945 54.21298 55.78803 58.49458 61.30014
[9] 55.27868 53.95763 56.08613 61.75153 53.77898 NA 57.78410 54.98640
[17] 55.97519 54.33608 54.74036 58.29427
>
> Max(tmp5,na.rm=TRUE)
[1] 472.3163
> Min(tmp5,na.rm=TRUE)
[1] 53.77898
> mean(tmp5,na.rm=TRUE)
[1] 72.64277
> Sum(tmp5,na.rm=TRUE)
[1] 14455.91
> Var(tmp5,na.rm=TRUE)
[1] 889.302
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.45906 74.27699 70.52210 69.15293 69.29293 71.55391 71.99441 68.48129
[9] 67.20873 70.56704
> rowSums(tmp5,na.rm=TRUE)
[1] 1869.181 1411.263 1410.442 1383.059 1385.859 1431.078 1439.888 1369.626
[9] 1344.175 1411.341
> rowVars(tmp5,na.rm=TRUE)
[1] 8042.59719 70.98347 110.57326 76.64627 62.14155 35.42052
[7] 83.81473 61.32543 66.36820 117.62962
> rowSd(tmp5,na.rm=TRUE)
[1] 89.680529 8.425169 10.515382 8.754786 7.882991 5.951514 9.155038
[8] 7.831055 8.146668 10.845719
> rowMax(tmp5,na.rm=TRUE)
[1] 472.31632 87.48083 92.86980 91.86667 81.92526 80.93622 87.60809
[8] 79.02094 84.18263 86.03367
> rowMin(tmp5,na.rm=TRUE)
[1] 59.68972 60.23608 53.77898 53.95763 55.78803 61.11684 56.08613 54.21298
[9] 54.98640 53.90667
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.33745 73.80346 70.22879 70.38254 75.31633 72.63573 71.01181
[8] 72.60368 69.00548 70.90448 69.44557 70.77258 69.23797 69.46106
[15] 70.68260 65.92430 69.89625 67.45510 70.38268 70.04935
> colSums(tmp5,na.rm=TRUE)
[1] 1133.3745 738.0346 702.2879 703.8254 753.1633 726.3573 710.1181
[8] 726.0368 690.0548 709.0448 694.4557 707.7258 692.3797 625.1495
[15] 706.8260 659.2430 698.9625 674.5510 703.8268 700.4935
> colVars(tmp5,na.rm=TRUE)
[1] 15971.01307 38.92441 92.27194 86.88025 107.87992 117.64681
[7] 96.06290 54.79796 79.74356 66.40622 72.12160 40.68334
[13] 110.92171 114.96371 88.21234 58.70043 70.69875 87.26903
[19] 114.83601 80.61312
> colSd(tmp5,na.rm=TRUE)
[1] 126.376474 6.238943 9.605829 9.320957 10.386526 10.846512
[7] 9.801168 7.402564 8.929925 8.149001 8.492444 6.378349
[13] 10.531938 10.722113 9.392142 7.661620 8.408255 9.341789
[19] 10.716156 8.978481
> colMax(tmp5,na.rm=TRUE)
[1] 472.31632 85.63202 90.60147 84.53937 91.86667 87.82468 92.86980
[8] 81.72706 80.05956 84.14776 84.18263 78.79831 84.79473 85.63842
[15] 87.48083 79.16144 80.93622 83.67004 86.03367 85.87884
> colMin(tmp5,na.rm=TRUE)
[1] 61.53656 62.71826 60.23608 54.22945 54.21298 55.78803 58.49458 61.30014
[9] 55.27868 53.95763 56.08613 61.75153 53.77898 54.40013 57.78410 54.98640
[17] 55.97519 54.33608 54.74036 58.29427
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.45906 NaN 70.52210 69.15293 69.29293 71.55391 71.99441 68.48129
[9] 67.20873 70.56704
> rowSums(tmp5,na.rm=TRUE)
[1] 1869.181 0.000 1410.442 1383.059 1385.859 1431.078 1439.888 1369.626
[9] 1344.175 1411.341
> rowVars(tmp5,na.rm=TRUE)
[1] 8042.59719 NA 110.57326 76.64627 62.14155 35.42052
[7] 83.81473 61.32543 66.36820 117.62962
> rowSd(tmp5,na.rm=TRUE)
[1] 89.680529 NA 10.515382 8.754786 7.882991 5.951514 9.155038
[8] 7.831055 8.146668 10.845719
> rowMax(tmp5,na.rm=TRUE)
[1] 472.31632 NA 92.86980 91.86667 81.92526 80.93622 87.60809
[8] 79.02094 84.18263 86.03367
> rowMin(tmp5,na.rm=TRUE)
[1] 59.68972 NA 53.77898 53.95763 55.78803 61.11684 56.08613 54.21298
[9] 54.98640 53.90667
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.93695 73.89155 71.33909 69.35903 74.39760 71.59677 71.16120
[8] 71.93378 69.95623 71.56467 68.68127 71.14169 67.50944 NaN
[15] 68.81612 65.95661 70.09842 66.67593 68.95355 69.97439
> colSums(tmp5,na.rm=TRUE)
[1] 1052.4325 665.0239 642.0518 624.2313 669.5784 644.3709 640.4508
[8] 647.4040 629.6060 644.0820 618.1315 640.2752 607.5850 0.0000
[15] 619.3451 593.6095 630.8858 600.0833 620.5820 629.7695
> colVars(tmp5,na.rm=TRUE)
[1] 17821.63061 43.70266 89.93730 85.95527 111.86925 120.20896
[7] 107.81969 56.59908 79.54243 69.80377 74.56518 44.23601
[13] 91.17404 NA 60.04713 66.02623 79.07628 91.34764
[19] 106.21350 90.62654
> colSd(tmp5,na.rm=TRUE)
[1] 133.497680 6.610799 9.483528 9.271207 10.576826 10.963985
[7] 10.383626 7.523236 8.918656 8.354865 8.635113 6.651016
[13] 9.548510 NA 7.749008 8.125653 8.892484 9.557596
[19] 10.305993 9.519797
> colMax(tmp5,na.rm=TRUE)
[1] 472.31632 85.63202 90.60147 84.53937 91.86667 87.82468 92.86980
[8] 81.72706 80.05956 84.14776 84.18263 78.79831 80.54345 -Inf
[15] 80.50688 79.16144 80.93622 83.67004 86.03367 85.87884
> colMin(tmp5,na.rm=TRUE)
[1] 61.53656 62.71826 63.42617 54.22945 54.21298 55.78803 58.49458 61.30014
[9] 55.27868 53.95763 56.08613 61.75153 53.77898 Inf 57.78410 54.98640
[17] 55.97519 54.33608 54.74036 58.29427
>
>
>
>
> 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] 290.1352 198.5957 151.7057 152.7618 289.1754 117.9790 144.6249 250.7010
[9] 217.6719 315.6168
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 290.1352 198.5957 151.7057 152.7618 289.1754 117.9790 144.6249 250.7010
[9] 217.6719 315.6168
>
>
>
> 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] -2.842171e-14 0.000000e+00 -2.273737e-13 0.000000e+00 0.000000e+00
[6] 2.842171e-14 5.684342e-14 -2.842171e-14 2.842171e-14 -1.136868e-13
[11] -4.263256e-14 1.136868e-13 2.842171e-14 -5.684342e-14 0.000000e+00
[16] -1.136868e-13 5.684342e-14 1.136868e-13 2.842171e-14 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)
+ }
3 1
6 6
10 16
2 3
4 13
1 13
10 11
5 7
10 10
7 15
8 11
2 2
6 17
1 1
7 16
4 12
4 18
1 15
3 14
6 4
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] 2.635541
> Min(tmp)
[1] -3.061149
> mean(tmp)
[1] -0.05829537
> Sum(tmp)
[1] -5.829537
> Var(tmp)
[1] 1.326098
>
> rowMeans(tmp)
[1] -0.05829537
> rowSums(tmp)
[1] -5.829537
> rowVars(tmp)
[1] 1.326098
> rowSd(tmp)
[1] 1.151563
> rowMax(tmp)
[1] 2.635541
> rowMin(tmp)
[1] -3.061149
>
> colMeans(tmp)
[1] -3.061148640 -0.045069811 -0.325987286 -2.127459023 -0.881716055
[6] -0.761359578 0.610546183 0.418827343 1.667802837 1.301462937
[11] -0.524174815 -0.753712773 -0.371976355 0.191457735 -0.890839323
[16] -0.197710549 1.888471983 -1.954739659 1.402067329 1.711772198
[21] -0.268612144 -1.764622165 1.609181269 2.635540522 1.148502785
[26] -0.317068409 -2.698092933 -1.274288928 0.214477018 -1.186666173
[31] 1.310521183 -1.968744762 0.174950982 -0.617243687 0.304196463
[36] 0.510702530 -0.456121309 -1.182252344 -0.233297749 0.173696694
[41] -1.033578509 -0.002292824 -0.061674306 -0.152538721 1.916664478
[46] -0.018507771 2.508504873 0.276846569 1.131121817 -0.828074330
[51] -0.499111498 -0.795505049 -1.814744338 0.240014987 -0.651600918
[56] -1.584224344 0.421986458 -0.184542138 -0.531159769 -0.086286695
[61] 1.570382278 -1.097707731 0.092468891 -0.041649211 0.627510221
[66] -0.559527904 1.094738830 -0.337166651 -0.928364527 -0.902209293
[71] 0.649738651 1.119975312 1.209021161 1.941247248 -0.713184418
[76] -1.008556719 2.015703922 -1.189399477 -1.335329215 1.158498818
[81] 0.287445063 -0.680512685 1.227548220 -1.660758616 -0.169950951
[86] -0.884332199 -0.677711160 -1.103877821 -0.448541150 0.456983427
[91] -1.771322381 1.294089111 1.314788003 1.506261695 1.035623558
[96] 0.399998673 -0.615909415 -0.993120157 0.484967281 0.140032360
> colSums(tmp)
[1] -3.061148640 -0.045069811 -0.325987286 -2.127459023 -0.881716055
[6] -0.761359578 0.610546183 0.418827343 1.667802837 1.301462937
[11] -0.524174815 -0.753712773 -0.371976355 0.191457735 -0.890839323
[16] -0.197710549 1.888471983 -1.954739659 1.402067329 1.711772198
[21] -0.268612144 -1.764622165 1.609181269 2.635540522 1.148502785
[26] -0.317068409 -2.698092933 -1.274288928 0.214477018 -1.186666173
[31] 1.310521183 -1.968744762 0.174950982 -0.617243687 0.304196463
[36] 0.510702530 -0.456121309 -1.182252344 -0.233297749 0.173696694
[41] -1.033578509 -0.002292824 -0.061674306 -0.152538721 1.916664478
[46] -0.018507771 2.508504873 0.276846569 1.131121817 -0.828074330
[51] -0.499111498 -0.795505049 -1.814744338 0.240014987 -0.651600918
[56] -1.584224344 0.421986458 -0.184542138 -0.531159769 -0.086286695
[61] 1.570382278 -1.097707731 0.092468891 -0.041649211 0.627510221
[66] -0.559527904 1.094738830 -0.337166651 -0.928364527 -0.902209293
[71] 0.649738651 1.119975312 1.209021161 1.941247248 -0.713184418
[76] -1.008556719 2.015703922 -1.189399477 -1.335329215 1.158498818
[81] 0.287445063 -0.680512685 1.227548220 -1.660758616 -0.169950951
[86] -0.884332199 -0.677711160 -1.103877821 -0.448541150 0.456983427
[91] -1.771322381 1.294089111 1.314788003 1.506261695 1.035623558
[96] 0.399998673 -0.615909415 -0.993120157 0.484967281 0.140032360
> 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] -3.061148640 -0.045069811 -0.325987286 -2.127459023 -0.881716055
[6] -0.761359578 0.610546183 0.418827343 1.667802837 1.301462937
[11] -0.524174815 -0.753712773 -0.371976355 0.191457735 -0.890839323
[16] -0.197710549 1.888471983 -1.954739659 1.402067329 1.711772198
[21] -0.268612144 -1.764622165 1.609181269 2.635540522 1.148502785
[26] -0.317068409 -2.698092933 -1.274288928 0.214477018 -1.186666173
[31] 1.310521183 -1.968744762 0.174950982 -0.617243687 0.304196463
[36] 0.510702530 -0.456121309 -1.182252344 -0.233297749 0.173696694
[41] -1.033578509 -0.002292824 -0.061674306 -0.152538721 1.916664478
[46] -0.018507771 2.508504873 0.276846569 1.131121817 -0.828074330
[51] -0.499111498 -0.795505049 -1.814744338 0.240014987 -0.651600918
[56] -1.584224344 0.421986458 -0.184542138 -0.531159769 -0.086286695
[61] 1.570382278 -1.097707731 0.092468891 -0.041649211 0.627510221
[66] -0.559527904 1.094738830 -0.337166651 -0.928364527 -0.902209293
[71] 0.649738651 1.119975312 1.209021161 1.941247248 -0.713184418
[76] -1.008556719 2.015703922 -1.189399477 -1.335329215 1.158498818
[81] 0.287445063 -0.680512685 1.227548220 -1.660758616 -0.169950951
[86] -0.884332199 -0.677711160 -1.103877821 -0.448541150 0.456983427
[91] -1.771322381 1.294089111 1.314788003 1.506261695 1.035623558
[96] 0.399998673 -0.615909415 -0.993120157 0.484967281 0.140032360
> colMin(tmp)
[1] -3.061148640 -0.045069811 -0.325987286 -2.127459023 -0.881716055
[6] -0.761359578 0.610546183 0.418827343 1.667802837 1.301462937
[11] -0.524174815 -0.753712773 -0.371976355 0.191457735 -0.890839323
[16] -0.197710549 1.888471983 -1.954739659 1.402067329 1.711772198
[21] -0.268612144 -1.764622165 1.609181269 2.635540522 1.148502785
[26] -0.317068409 -2.698092933 -1.274288928 0.214477018 -1.186666173
[31] 1.310521183 -1.968744762 0.174950982 -0.617243687 0.304196463
[36] 0.510702530 -0.456121309 -1.182252344 -0.233297749 0.173696694
[41] -1.033578509 -0.002292824 -0.061674306 -0.152538721 1.916664478
[46] -0.018507771 2.508504873 0.276846569 1.131121817 -0.828074330
[51] -0.499111498 -0.795505049 -1.814744338 0.240014987 -0.651600918
[56] -1.584224344 0.421986458 -0.184542138 -0.531159769 -0.086286695
[61] 1.570382278 -1.097707731 0.092468891 -0.041649211 0.627510221
[66] -0.559527904 1.094738830 -0.337166651 -0.928364527 -0.902209293
[71] 0.649738651 1.119975312 1.209021161 1.941247248 -0.713184418
[76] -1.008556719 2.015703922 -1.189399477 -1.335329215 1.158498818
[81] 0.287445063 -0.680512685 1.227548220 -1.660758616 -0.169950951
[86] -0.884332199 -0.677711160 -1.103877821 -0.448541150 0.456983427
[91] -1.771322381 1.294089111 1.314788003 1.506261695 1.035623558
[96] 0.399998673 -0.615909415 -0.993120157 0.484967281 0.140032360
> colMedians(tmp)
[1] -3.061148640 -0.045069811 -0.325987286 -2.127459023 -0.881716055
[6] -0.761359578 0.610546183 0.418827343 1.667802837 1.301462937
[11] -0.524174815 -0.753712773 -0.371976355 0.191457735 -0.890839323
[16] -0.197710549 1.888471983 -1.954739659 1.402067329 1.711772198
[21] -0.268612144 -1.764622165 1.609181269 2.635540522 1.148502785
[26] -0.317068409 -2.698092933 -1.274288928 0.214477018 -1.186666173
[31] 1.310521183 -1.968744762 0.174950982 -0.617243687 0.304196463
[36] 0.510702530 -0.456121309 -1.182252344 -0.233297749 0.173696694
[41] -1.033578509 -0.002292824 -0.061674306 -0.152538721 1.916664478
[46] -0.018507771 2.508504873 0.276846569 1.131121817 -0.828074330
[51] -0.499111498 -0.795505049 -1.814744338 0.240014987 -0.651600918
[56] -1.584224344 0.421986458 -0.184542138 -0.531159769 -0.086286695
[61] 1.570382278 -1.097707731 0.092468891 -0.041649211 0.627510221
[66] -0.559527904 1.094738830 -0.337166651 -0.928364527 -0.902209293
[71] 0.649738651 1.119975312 1.209021161 1.941247248 -0.713184418
[76] -1.008556719 2.015703922 -1.189399477 -1.335329215 1.158498818
[81] 0.287445063 -0.680512685 1.227548220 -1.660758616 -0.169950951
[86] -0.884332199 -0.677711160 -1.103877821 -0.448541150 0.456983427
[91] -1.771322381 1.294089111 1.314788003 1.506261695 1.035623558
[96] 0.399998673 -0.615909415 -0.993120157 0.484967281 0.140032360
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -3.061149 -0.04506981 -0.3259873 -2.127459 -0.8817161 -0.7613596 0.6105462
[2,] -3.061149 -0.04506981 -0.3259873 -2.127459 -0.8817161 -0.7613596 0.6105462
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.4188273 1.667803 1.301463 -0.5241748 -0.7537128 -0.3719764 0.1914577
[2,] 0.4188273 1.667803 1.301463 -0.5241748 -0.7537128 -0.3719764 0.1914577
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.8908393 -0.1977105 1.888472 -1.95474 1.402067 1.711772 -0.2686121
[2,] -0.8908393 -0.1977105 1.888472 -1.95474 1.402067 1.711772 -0.2686121
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.764622 1.609181 2.635541 1.148503 -0.3170684 -2.698093 -1.274289
[2,] -1.764622 1.609181 2.635541 1.148503 -0.3170684 -2.698093 -1.274289
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.214477 -1.186666 1.310521 -1.968745 0.174951 -0.6172437 0.3041965
[2,] 0.214477 -1.186666 1.310521 -1.968745 0.174951 -0.6172437 0.3041965
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.5107025 -0.4561213 -1.182252 -0.2332977 0.1736967 -1.033579 -0.002292824
[2,] 0.5107025 -0.4561213 -1.182252 -0.2332977 0.1736967 -1.033579 -0.002292824
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.06167431 -0.1525387 1.916664 -0.01850777 2.508505 0.2768466 1.131122
[2,] -0.06167431 -0.1525387 1.916664 -0.01850777 2.508505 0.2768466 1.131122
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.8280743 -0.4991115 -0.795505 -1.814744 0.240015 -0.6516009 -1.584224
[2,] -0.8280743 -0.4991115 -0.795505 -1.814744 0.240015 -0.6516009 -1.584224
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4219865 -0.1845421 -0.5311598 -0.0862867 1.570382 -1.097708 0.09246889
[2,] 0.4219865 -0.1845421 -0.5311598 -0.0862867 1.570382 -1.097708 0.09246889
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.04164921 0.6275102 -0.5595279 1.094739 -0.3371667 -0.9283645 -0.9022093
[2,] -0.04164921 0.6275102 -0.5595279 1.094739 -0.3371667 -0.9283645 -0.9022093
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.6497387 1.119975 1.209021 1.941247 -0.7131844 -1.008557 2.015704
[2,] 0.6497387 1.119975 1.209021 1.941247 -0.7131844 -1.008557 2.015704
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.189399 -1.335329 1.158499 0.2874451 -0.6805127 1.227548 -1.660759
[2,] -1.189399 -1.335329 1.158499 0.2874451 -0.6805127 1.227548 -1.660759
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.169951 -0.8843322 -0.6777112 -1.103878 -0.4485412 0.4569834 -1.771322
[2,] -0.169951 -0.8843322 -0.6777112 -1.103878 -0.4485412 0.4569834 -1.771322
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.294089 1.314788 1.506262 1.035624 0.3999987 -0.6159094 -0.9931202
[2,] 1.294089 1.314788 1.506262 1.035624 0.3999987 -0.6159094 -0.9931202
[,99] [,100]
[1,] 0.4849673 0.1400324
[2,] 0.4849673 0.1400324
>
>
> Max(tmp2)
[1] 3.477848
> Min(tmp2)
[1] -2.690552
> mean(tmp2)
[1] 0.0399217
> Sum(tmp2)
[1] 3.99217
> Var(tmp2)
[1] 0.8315593
>
> rowMeans(tmp2)
[1] -0.396611588 0.496349397 0.871690029 1.055423417 0.647976937
[6] 0.787220149 -0.723983276 1.821474455 -1.820285061 0.523390862
[11] -0.891202334 -0.533701664 -0.396213708 -0.006522555 0.174211574
[16] 1.108193793 0.523569124 -0.868062880 1.357568145 0.358971063
[21] 0.828328588 0.041096740 -0.242582524 0.217438735 -0.485712309
[26] -2.690551969 0.432406883 -0.546670041 -0.570931627 0.720012887
[31] -1.020551350 1.111096357 -0.663580791 -0.303907533 0.395678374
[36] 0.537256882 0.892768907 -0.885382892 0.498916920 0.429327539
[41] -0.819594175 0.449420371 -1.278303270 1.087084613 0.923730264
[46] 0.503564753 -0.249381069 -0.491466715 1.200163619 0.250737074
[51] 3.477847719 0.889837810 -0.092849351 0.421210406 -0.291836128
[56] -1.476656167 -0.790340561 0.121891572 -0.681762466 0.593212243
[61] 0.898031489 -0.881792271 1.671360347 -0.368589913 0.086235325
[66] 0.000513479 -0.070416629 -0.354333880 -1.268758585 0.317627585
[71] -0.495280395 -0.733704677 0.657157108 0.170001207 -0.046513495
[76] -0.314830411 -0.123867712 -0.828540645 -0.152919328 -0.880050782
[81] -1.366704435 -1.541603930 -0.692326136 -0.152978728 1.817628463
[86] 1.028649084 -1.102620378 -0.660465021 -0.194077002 -0.689462643
[91] 0.866783151 0.317401059 -0.165836907 0.773121427 0.640951379
[96] 1.170180723 1.020396484 -0.004337657 0.742476527 -1.626757634
> rowSums(tmp2)
[1] -0.396611588 0.496349397 0.871690029 1.055423417 0.647976937
[6] 0.787220149 -0.723983276 1.821474455 -1.820285061 0.523390862
[11] -0.891202334 -0.533701664 -0.396213708 -0.006522555 0.174211574
[16] 1.108193793 0.523569124 -0.868062880 1.357568145 0.358971063
[21] 0.828328588 0.041096740 -0.242582524 0.217438735 -0.485712309
[26] -2.690551969 0.432406883 -0.546670041 -0.570931627 0.720012887
[31] -1.020551350 1.111096357 -0.663580791 -0.303907533 0.395678374
[36] 0.537256882 0.892768907 -0.885382892 0.498916920 0.429327539
[41] -0.819594175 0.449420371 -1.278303270 1.087084613 0.923730264
[46] 0.503564753 -0.249381069 -0.491466715 1.200163619 0.250737074
[51] 3.477847719 0.889837810 -0.092849351 0.421210406 -0.291836128
[56] -1.476656167 -0.790340561 0.121891572 -0.681762466 0.593212243
[61] 0.898031489 -0.881792271 1.671360347 -0.368589913 0.086235325
[66] 0.000513479 -0.070416629 -0.354333880 -1.268758585 0.317627585
[71] -0.495280395 -0.733704677 0.657157108 0.170001207 -0.046513495
[76] -0.314830411 -0.123867712 -0.828540645 -0.152919328 -0.880050782
[81] -1.366704435 -1.541603930 -0.692326136 -0.152978728 1.817628463
[86] 1.028649084 -1.102620378 -0.660465021 -0.194077002 -0.689462643
[91] 0.866783151 0.317401059 -0.165836907 0.773121427 0.640951379
[96] 1.170180723 1.020396484 -0.004337657 0.742476527 -1.626757634
> 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] -0.396611588 0.496349397 0.871690029 1.055423417 0.647976937
[6] 0.787220149 -0.723983276 1.821474455 -1.820285061 0.523390862
[11] -0.891202334 -0.533701664 -0.396213708 -0.006522555 0.174211574
[16] 1.108193793 0.523569124 -0.868062880 1.357568145 0.358971063
[21] 0.828328588 0.041096740 -0.242582524 0.217438735 -0.485712309
[26] -2.690551969 0.432406883 -0.546670041 -0.570931627 0.720012887
[31] -1.020551350 1.111096357 -0.663580791 -0.303907533 0.395678374
[36] 0.537256882 0.892768907 -0.885382892 0.498916920 0.429327539
[41] -0.819594175 0.449420371 -1.278303270 1.087084613 0.923730264
[46] 0.503564753 -0.249381069 -0.491466715 1.200163619 0.250737074
[51] 3.477847719 0.889837810 -0.092849351 0.421210406 -0.291836128
[56] -1.476656167 -0.790340561 0.121891572 -0.681762466 0.593212243
[61] 0.898031489 -0.881792271 1.671360347 -0.368589913 0.086235325
[66] 0.000513479 -0.070416629 -0.354333880 -1.268758585 0.317627585
[71] -0.495280395 -0.733704677 0.657157108 0.170001207 -0.046513495
[76] -0.314830411 -0.123867712 -0.828540645 -0.152919328 -0.880050782
[81] -1.366704435 -1.541603930 -0.692326136 -0.152978728 1.817628463
[86] 1.028649084 -1.102620378 -0.660465021 -0.194077002 -0.689462643
[91] 0.866783151 0.317401059 -0.165836907 0.773121427 0.640951379
[96] 1.170180723 1.020396484 -0.004337657 0.742476527 -1.626757634
> rowMin(tmp2)
[1] -0.396611588 0.496349397 0.871690029 1.055423417 0.647976937
[6] 0.787220149 -0.723983276 1.821474455 -1.820285061 0.523390862
[11] -0.891202334 -0.533701664 -0.396213708 -0.006522555 0.174211574
[16] 1.108193793 0.523569124 -0.868062880 1.357568145 0.358971063
[21] 0.828328588 0.041096740 -0.242582524 0.217438735 -0.485712309
[26] -2.690551969 0.432406883 -0.546670041 -0.570931627 0.720012887
[31] -1.020551350 1.111096357 -0.663580791 -0.303907533 0.395678374
[36] 0.537256882 0.892768907 -0.885382892 0.498916920 0.429327539
[41] -0.819594175 0.449420371 -1.278303270 1.087084613 0.923730264
[46] 0.503564753 -0.249381069 -0.491466715 1.200163619 0.250737074
[51] 3.477847719 0.889837810 -0.092849351 0.421210406 -0.291836128
[56] -1.476656167 -0.790340561 0.121891572 -0.681762466 0.593212243
[61] 0.898031489 -0.881792271 1.671360347 -0.368589913 0.086235325
[66] 0.000513479 -0.070416629 -0.354333880 -1.268758585 0.317627585
[71] -0.495280395 -0.733704677 0.657157108 0.170001207 -0.046513495
[76] -0.314830411 -0.123867712 -0.828540645 -0.152919328 -0.880050782
[81] -1.366704435 -1.541603930 -0.692326136 -0.152978728 1.817628463
[86] 1.028649084 -1.102620378 -0.660465021 -0.194077002 -0.689462643
[91] 0.866783151 0.317401059 -0.165836907 0.773121427 0.640951379
[96] 1.170180723 1.020396484 -0.004337657 0.742476527 -1.626757634
>
> colMeans(tmp2)
[1] 0.0399217
> colSums(tmp2)
[1] 3.99217
> colVars(tmp2)
[1] 0.8315593
> colSd(tmp2)
[1] 0.9118987
> colMax(tmp2)
[1] 3.477848
> colMin(tmp2)
[1] -2.690552
> colMedians(tmp2)
[1] -0.001912089
> colRanges(tmp2)
[,1]
[1,] -2.690552
[2,] 3.477848
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.2297089 4.4957957 -5.2959312 -4.0486569 4.7181680 0.4261550
[7] 3.8925397 -0.3168417 -1.7200415 1.3644510
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0295817
[2,] -0.5335203
[3,] -0.0135721
[4,] 0.6894404
[5,] 1.0214581
>
> rowApply(tmp,sum)
[1] -2.8990938 2.5677543 -0.8242693 -0.1845929 2.3171922 2.6490458
[7] 1.5443060 -3.6860985 0.3370263 1.9240770
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 8 8 10 2 5 7 6 3 2
[2,] 6 9 5 3 1 7 10 8 6 9
[3,] 4 3 1 5 4 6 3 3 4 6
[4,] 2 7 2 1 10 2 8 2 1 8
[5,] 10 4 3 4 6 3 9 10 10 7
[6,] 3 10 10 9 9 4 4 1 2 4
[7,] 7 5 7 6 7 10 6 4 8 5
[8,] 1 6 6 7 5 9 2 5 5 10
[9,] 9 2 4 2 8 1 1 9 9 3
[10,] 8 1 9 8 3 8 5 7 7 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.99424616 -1.04784342 -0.11872751 -1.64061224 0.24829726 0.38800272
[7] 0.05169226 2.53349629 -3.96722259 -1.28312871 -2.73375792 -1.42494697
[13] 2.92368422 -1.58728904 1.25724525 -0.58099664 -0.16097522 0.34942839
[19] -1.07741862 -1.96213158
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.50009522
[2,] -0.38303314
[3,] 0.05735111
[4,] 2.02375263
[5,] 2.79627079
>
> rowApply(tmp,sum)
[1] -8.674139 -3.414306 3.007420 3.325731 -1.083664
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 12 19 20 8
[2,] 15 9 3 11 3
[3,] 7 13 11 17 11
[4,] 5 6 9 9 16
[5,] 12 15 2 18 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.50009522 0.2576017 -0.96269214 -1.45473599 -0.03695729 -0.75280605
[2,] 0.05735111 -0.2423884 0.06433022 -0.42222062 0.40235171 0.61837093
[3,] 2.02375263 -0.6372851 -0.07420701 -0.11977113 -0.89945010 -0.09955165
[4,] 2.79627079 0.2829614 0.92434802 -0.09467996 1.18326194 0.52117917
[5,] -0.38303314 -0.7087332 -0.07050659 0.45079547 -0.40090900 0.10081032
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.4812769 0.9693132 -1.100477468 -0.5347404 -1.4979359 0.1063310
[2,] -0.3341666 2.4238306 -1.415827406 -0.3999469 -1.2146230 0.5689044
[3,] -1.0482754 0.3337353 -0.007501753 -0.6052170 -0.1879516 -0.5474546
[4,] 0.5919154 -0.6283598 0.295254437 0.6743972 -0.2014661 0.5640202
[5,] 0.3609420 -0.5650230 -1.738670402 -0.4176216 0.3682188 -2.1167480
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.04302981 -0.8910696 1.51747279 0.907814865 -2.0119464 0.5178965
[2,] 0.52174979 -0.9575411 -0.05136176 -0.001124057 0.4443915 -2.1533261
[3,] 1.30115782 0.8363866 0.18359652 -0.565222820 0.2714142 2.9480659
[4,] 1.36146090 -1.0493344 -1.52091539 -1.121501318 -0.4198944 -0.2597102
[5,] -0.30371411 0.4742696 1.12845309 0.199036690 1.5550599 -0.7034977
[,19] [,20]
[1,] -0.3447004 -2.38671929
[2,] -1.4785909 0.15553111
[3,] -0.5390640 0.44026341
[4,] -0.6243988 0.05092228
[5,] 1.9093355 -0.22212909
>
>
> 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 : 652 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 1.06666 0.7149584 -0.8506583 2.189222 -0.212602 0.2627502 -0.4904441
col8 col9 col10 col11 col12 col13 col14
row1 -0.8243474 0.9917886 1.570048 -0.7000406 0.3015967 0.8129381 0.3532265
col15 col16 col17 col18 col19 col20
row1 -0.4114309 0.9345696 -0.4026822 1.59778 -0.2554523 0.6032643
> tmp[,"col10"]
col10
row1 1.5700483
row2 -1.0828905
row3 0.1446753
row4 2.5882487
row5 -0.2958703
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.0666601 0.7149584 -0.8506583 2.189222 -0.2126020 0.26275021
row5 -0.8265537 -0.2986877 1.1001740 -1.998939 -0.7911962 0.01574733
col7 col8 col9 col10 col11 col12
row1 -0.4904441 -0.8243474 0.9917886 1.5700483 -0.7000406 0.3015967
row5 1.8299710 1.2357326 -1.2607992 -0.2958703 -0.2273298 -0.5078103
col13 col14 col15 col16 col17 col18 col19
row1 0.8129381 0.3532265 -0.4114309 0.9345696 -0.4026822 1.5977797 -0.2554523
row5 1.2349164 0.8925257 0.4078532 0.6743079 0.3527943 -0.3875686 1.0196153
col20
row1 0.60326433
row5 0.01595783
> tmp[,c("col6","col20")]
col6 col20
row1 0.26275021 0.60326433
row2 0.26843535 -0.17123823
row3 -1.03248236 1.94968040
row4 -2.24525527 0.43129972
row5 0.01574733 0.01595783
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.26275021 0.60326433
row5 0.01574733 0.01595783
>
>
>
>
> 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 50.14382 50.14246 50.38855 51.16483 49.69399 104.4873 51.03235 47.189
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.39284 49.50986 48.9503 50.72523 50.38039 52.54743 50.24978 50.52607
col17 col18 col19 col20
row1 52.16742 49.71101 49.37118 107.3125
> tmp[,"col10"]
col10
row1 49.50986
row2 29.68663
row3 29.35011
row4 30.89243
row5 50.39457
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.14382 50.14246 50.38855 51.16483 49.69399 104.4873 51.03235 47.1890
row5 49.77165 50.21669 50.42936 49.83308 49.56968 104.9311 48.70116 48.7558
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.39284 49.50986 48.95030 50.72523 50.38039 52.54743 50.24978 50.52607
row5 50.12743 50.39457 51.04506 50.03188 49.43058 49.82292 50.66954 51.22270
col17 col18 col19 col20
row1 52.16742 49.71101 49.37118 107.3125
row5 51.36901 50.96252 50.73362 106.2774
> tmp[,c("col6","col20")]
col6 col20
row1 104.48730 107.31249
row2 74.47140 74.71980
row3 76.56463 76.82907
row4 73.44946 75.47802
row5 104.93107 106.27744
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.4873 107.3125
row5 104.9311 106.2774
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.4873 107.3125
row5 104.9311 106.2774
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.7750832
[2,] 1.1003481
[3,] 0.8792148
[4,] -0.9275811
[5,] 2.0315161
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.8156990 0.5580084
[2,] -0.7156764 0.5250161
[3,] -0.8922031 0.8418725
[4,] -0.7174707 0.7612131
[5,] 0.4007071 -1.0910714
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.7697281 1.467778505
[2,] 0.7006070 0.005972221
[3,] 0.3002305 -2.111769710
[4,] -0.2572332 0.416466966
[5,] -1.5632228 0.512086923
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.769728
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.769728
[2,] 0.700607
>
>
>
> 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 -0.4167193 0.5916507 -1.05755004 -1.17469514 -0.05225103 -1.423174
row1 1.4663268 -1.4340591 0.06273022 -0.07388136 -0.74203571 0.896469
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.1108349 0.9134098 -0.1594018 0.8566923 -2.288197 0.3147048
row1 -0.4344789 -3.0722898 -0.2687796 -0.2588710 -0.120490 -1.0468371
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.6372479 0.3288583 0.1447904 0.03349277 1.6530790 -0.2222845
row1 -1.6201096 -0.1444160 -1.8780463 -0.75758417 -0.3805777 -0.9957158
[,19] [,20]
row3 1.464307669 0.1441442
row1 0.005549478 -0.0986902
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.958739 0.4912779 -1.777837 1.144222 -0.2981816 0.963193 0.1926963
[,8] [,9] [,10]
row2 0.1074773 -1.151161 -2.261939
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.97973 0.1876496 0.3702799 -0.4653538 1.362355 1.239741 -2.16381
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.322526 -0.07737758 2.034315 -0.8269522 1.455406 0.2969516 0.7155275
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.233639 0.08237906 1.055382 0.8488892 1.965155 -1.580945
>
>
> 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: 0x5c7d79375d70>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a3091a398"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a3b100751"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a69450f63"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a3fa37f8a"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a15b368b3"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a2d883430"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a5d71794f"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a3a0cfe05"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a27b7f2bf"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a76362861"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a6045adac"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a339b422c"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a510b981b"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a3fe1a0ad"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b699a2b845e83"
>
>
> ### 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: 0x5c7d77466610>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5c7d77466610>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5c7d77466610>
> rowMedians(tmp)
[1] 0.242722185 -0.068867160 0.506530196 0.393195190 -0.162743832
[6] 0.013527305 -0.628244094 -0.109701993 -0.618555288 -0.208749199
[11] -0.005941049 0.199115412 -0.363368586 -0.106270172 0.215396403
[16] 0.407455703 -0.354123362 0.005414443 0.102167068 -0.119354438
[21] 0.008489038 -0.193127129 -0.656518303 0.078718405 0.143569877
[26] -0.692351616 0.730858284 0.061499809 -0.141605722 0.168528676
[31] -0.014895009 -0.389294403 -0.258311009 0.171374313 0.337822769
[36] 0.194859754 0.111958592 0.545784993 0.020678551 0.489186209
[41] 0.037528163 0.436861054 0.350450109 -0.064760391 -0.357859468
[46] 0.316961739 -0.251159744 -0.124733257 0.057986920 0.022070642
[51] 1.047199604 0.431863922 -0.379177866 0.622082593 0.113726915
[56] 0.011607946 0.479073335 -0.085013349 0.066700060 -0.208167938
[61] 0.001752251 0.240532633 0.415586435 0.313471275 -0.129592564
[66] 0.277188179 0.171938070 -0.662113932 0.464378326 0.325223289
[71] 0.156894039 -0.437784847 0.725591186 -0.073706248 0.623476454
[76] 0.247127611 -0.040882410 0.069745890 -0.387022565 0.330128516
[81] 0.191868408 0.208669098 0.428065129 0.084359683 0.329142595
[86] -0.285729351 0.340578462 -0.218910912 0.106411551 -0.031485851
[91] 0.395028905 0.168193669 -0.016431389 0.562366358 0.311636101
[96] -0.194042134 -0.019173386 -0.493987897 -0.105765519 -0.189532648
[101] 0.283054475 -0.177469140 -0.128566410 0.279804329 0.009229229
[106] -0.114415681 0.309486699 0.094040995 -0.200123313 0.763350868
[111] -0.595549554 -0.278216626 0.247133720 0.031538260 0.146412921
[116] 0.248325692 -0.225414558 0.499985181 -0.723711563 -0.340000459
[121] -0.224377673 -0.019180630 0.239349481 -0.599404100 0.039177185
[126] 0.317112237 0.104519584 0.127273014 0.295118615 0.338216211
[131] -0.022853950 -0.602784930 -0.101839116 -0.128050394 0.024247676
[136] 0.864253638 -0.628268970 0.034028191 0.280238610 -0.076060486
[141] -0.080592367 -0.308279039 0.397941198 0.308903008 0.038973816
[146] 0.358507695 -0.714424638 0.385683932 0.374559731 -0.390551994
[151] 0.128310716 0.260398099 0.065249406 -0.264048342 0.474396834
[156] -0.383260738 -0.040831759 0.355281717 -0.015297395 0.328038929
[161] -0.111289930 -0.083467566 0.077199599 -0.574004857 0.070125051
[166] 0.259380972 0.788749587 0.311912117 -0.129861789 0.098733059
[171] -0.053367117 -0.265383909 0.433195323 -0.020206229 0.179230820
[176] 0.028167945 -0.358058558 0.325506049 -0.013965066 -0.120499066
[181] -0.066834639 -0.022100538 0.182022086 0.148782921 -0.544176546
[186] 0.068738449 -0.020314146 0.030754780 -0.364154040 -0.167405830
[191] -0.249007692 0.093414743 0.140771748 0.497410568 0.521242008
[196] 0.024318610 0.483159559 -0.253608745 -0.300263311 0.450019140
[201] -0.167613752 0.045119958 0.663060761 -0.257144523 0.188274254
[206] -0.225503854 0.202093583 -0.281936485 -0.157671081 0.377619600
[211] 0.310670809 0.114591570 0.470204763 0.344157544 0.016751798
[216] -0.399196774 0.584549590 0.374687283 -0.529487892 -0.213816478
[221] -0.304537134 -0.012680325 0.157066953 -0.207470637 -0.460523372
[226] 0.132099393 0.216339848 0.145984651 0.798798887 0.512286877
>
> proc.time()
user system elapsed
1.212 0.669 1.870
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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: 0x62fe89c8fc80>
> .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: 0x62fe89c8fc80>
> .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: 0x62fe89c8fc80>
> .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: 0x62fe89c8fc80>
> 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: 0x62fe89926a00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe89926a00>
> .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: 0x62fe89926a00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe89926a00>
> .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: 0x62fe89926a00>
> 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: 0x62fe899f1660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe899f1660>
> .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: 0x62fe899f1660>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x62fe899f1660>
> .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: 0x62fe899f1660>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x62fe899f1660>
> .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: 0x62fe899f1660>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x62fe899f1660>
> .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: 0x62fe899f1660>
> 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: 0x62fe89f133e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x62fe89f133e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe89f133e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe89f133e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b69e54cb33ddb" "BufferedMatrixFile1b69e56e3321a3"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b69e54cb33ddb" "BufferedMatrixFile1b69e56e3321a3"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe8c070470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe8c070470>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x62fe8c070470>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x62fe8c070470>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x62fe8c070470>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x62fe8c070470>
> .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: 0x62fe8a4f56e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62fe8a4f56e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x62fe8a4f56e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x62fe8a4f56e0>
> 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: 0x62fe8b9380d0>
> .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: 0x62fe8b9380d0>
> rm(P)
>
> proc.time()
user system elapsed
0.245 0.054 0.285
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
0.244 0.040 0.271