Ben Bolstad
| Snapshot Date: 2025-10-23 14:17 -0400 (Thu, 23 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 2025-10-24 12:03 -0400 (Fri, 24 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" | 4898 |
| lconway | macOS 12.7.6 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4688 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4634 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4658 |
| 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 257/2359 | 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: 2025-10-23 21:41:43 -0400 (Thu, 23 Oct 2025) |
| EndedAt: 2025-10-23 21:42:12 -0400 (Thu, 23 Oct 2025) |
| EllapsedTime: 29.0 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
0.268 0.038 0.293
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] "Thu Oct 23 21:42:03 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] "Thu Oct 23 21:42:03 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: 0x55c6abb7dc80>
>
>
>
> 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] "Thu Oct 23 21:42:03 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] "Thu Oct 23 21:42:03 2025"
>
> ColMode(tmp2)
<pointer: 0x55c6abb7dc80>
>
>
>
> ### 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,] 101.1221009 2.358812 0.2526960 -0.57769841
[2,] 0.6307138 -1.058777 0.2007367 0.11905758
[3,] -0.6273403 -0.470344 0.1984199 -1.22011096
[4,] -1.9819305 1.831593 -0.3023560 -0.02940695
> 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,] 101.1221009 2.358812 0.2526960 0.57769841
[2,] 0.6307138 1.058777 0.2007367 0.11905758
[3,] 0.6273403 0.470344 0.1984199 1.22011096
[4,] 1.9819305 1.831593 0.3023560 0.02940695
> 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,] 10.0559485 1.5358423 0.5026888 0.7600647
[2,] 0.7941749 1.0289690 0.4480365 0.3450472
[3,] 0.7920482 0.6858163 0.4454435 1.1045863
[4,] 1.4078105 1.3533637 0.5498691 0.1714846
>
> 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,] 226.68159 42.71723 30.27958 33.17835
[2,] 33.57246 36.34847 29.68110 28.56953
[3,] 33.54782 32.32851 29.65285 37.26597
[4,] 41.06004 40.36523 30.80105 26.74425
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55c6add2d110>
> exp(tmp5)
<pointer: 0x55c6add2d110>
> log(tmp5,2)
<pointer: 0x55c6add2d110>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.808
> Min(tmp5)
[1] 53.28854
> mean(tmp5)
[1] 72.35074
> Sum(tmp5)
[1] 14470.15
> Var(tmp5)
[1] 889.6163
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.31610 67.06578 70.78707 70.37013 71.83041 71.18447 71.23448 71.35853
[9] 70.15321 69.20723
> rowSums(tmp5)
[1] 1806.322 1341.316 1415.741 1407.403 1436.608 1423.689 1424.690 1427.171
[9] 1403.064 1384.145
> rowVars(tmp5)
[1] 8147.75872 65.40864 73.54313 71.42913 101.67123 74.64485
[7] 79.10867 100.70010 77.35574 130.54501
> rowSd(tmp5)
[1] 90.264936 8.087561 8.575729 8.451576 10.083215 8.639725 8.894306
[8] 10.034944 8.795211 11.425630
> rowMax(tmp5)
[1] 471.80802 85.79294 91.91916 85.46109 87.51631 96.43867 84.42236
[8] 90.62280 85.69506 93.13591
> rowMin(tmp5)
[1] 55.54314 55.62585 58.93498 55.66466 54.11632 56.66890 56.25176 56.72399
[9] 54.04241 53.28854
>
> colMeans(tmp5)
[1] 110.03635 76.20914 67.95983 69.61597 70.01327 70.10051 71.76216
[8] 69.41568 68.94980 72.25433 64.68457 73.16022 71.83276 66.88280
[15] 63.81804 73.83638 70.73928 76.46860 67.91812 71.35701
> colSums(tmp5)
[1] 1100.3635 762.0914 679.5983 696.1597 700.1327 701.0051 717.6216
[8] 694.1568 689.4980 722.5433 646.8457 731.6022 718.3276 668.8280
[15] 638.1804 738.3638 707.3928 764.6860 679.1812 713.5701
> colVars(tmp5)
[1] 16271.04867 86.06417 80.06460 102.36560 67.12916 150.00134
[7] 83.08510 193.17804 51.49921 73.06170 82.82920 106.90517
[13] 76.20414 31.29609 38.28159 46.95614 46.96658 79.71243
[19] 68.44568 48.96444
> colSd(tmp5)
[1] 127.558021 9.277078 8.947882 10.117589 8.193239 12.247503
[7] 9.115103 13.898850 7.176295 8.547614 9.101055 10.339496
[13] 8.729498 5.594291 6.187212 6.852455 6.853217 8.928182
[19] 8.273191 6.997459
> colMax(tmp5)
[1] 471.80802 88.91033 82.58903 81.38267 84.42236 96.43867 83.56565
[8] 91.91916 82.71988 85.29657 82.95321 93.13591 85.69506 78.31803
[15] 72.82067 84.96703 81.22645 90.62280 81.20225 84.54018
> colMin(tmp5)
[1] 54.11632 64.07805 53.28854 55.66466 60.76110 54.04241 54.50901 55.07822
[9] 62.50049 57.16193 56.72399 63.49862 57.17455 59.35139 55.54314 63.58959
[17] 60.62178 58.96179 59.71370 61.34493
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.31610 67.06578 70.78707 70.37013 71.83041 71.18447 71.23448 NA
[9] 70.15321 69.20723
> rowSums(tmp5)
[1] 1806.322 1341.316 1415.741 1407.403 1436.608 1423.689 1424.690 NA
[9] 1403.064 1384.145
> rowVars(tmp5)
[1] 8147.75872 65.40864 73.54313 71.42913 101.67123 74.64485
[7] 79.10867 101.04585 77.35574 130.54501
> rowSd(tmp5)
[1] 90.264936 8.087561 8.575729 8.451576 10.083215 8.639725 8.894306
[8] 10.052157 8.795211 11.425630
> rowMax(tmp5)
[1] 471.80802 85.79294 91.91916 85.46109 87.51631 96.43867 84.42236
[8] NA 85.69506 93.13591
> rowMin(tmp5)
[1] 55.54314 55.62585 58.93498 55.66466 54.11632 56.66890 56.25176 NA
[9] 54.04241 53.28854
>
> colMeans(tmp5)
[1] 110.03635 76.20914 67.95983 69.61597 70.01327 70.10051 71.76216
[8] 69.41568 68.94980 72.25433 64.68457 73.16022 71.83276 66.88280
[15] 63.81804 73.83638 70.73928 76.46860 NA 71.35701
> colSums(tmp5)
[1] 1100.3635 762.0914 679.5983 696.1597 700.1327 701.0051 717.6216
[8] 694.1568 689.4980 722.5433 646.8457 731.6022 718.3276 668.8280
[15] 638.1804 738.3638 707.3928 764.6860 NA 713.5701
> colVars(tmp5)
[1] 16271.04867 86.06417 80.06460 102.36560 67.12916 150.00134
[7] 83.08510 193.17804 51.49921 73.06170 82.82920 106.90517
[13] 76.20414 31.29609 38.28159 46.95614 46.96658 79.71243
[19] NA 48.96444
> colSd(tmp5)
[1] 127.558021 9.277078 8.947882 10.117589 8.193239 12.247503
[7] 9.115103 13.898850 7.176295 8.547614 9.101055 10.339496
[13] 8.729498 5.594291 6.187212 6.852455 6.853217 8.928182
[19] NA 6.997459
> colMax(tmp5)
[1] 471.80802 88.91033 82.58903 81.38267 84.42236 96.43867 83.56565
[8] 91.91916 82.71988 85.29657 82.95321 93.13591 85.69506 78.31803
[15] 72.82067 84.96703 81.22645 90.62280 NA 84.54018
> colMin(tmp5)
[1] 54.11632 64.07805 53.28854 55.66466 60.76110 54.04241 54.50901 55.07822
[9] 62.50049 57.16193 56.72399 63.49862 57.17455 59.35139 55.54314 63.58959
[17] 60.62178 58.96179 NA 61.34493
>
> Max(tmp5,na.rm=TRUE)
[1] 471.808
> Min(tmp5,na.rm=TRUE)
[1] 53.28854
> mean(tmp5,na.rm=TRUE)
[1] 72.40333
> Sum(tmp5,na.rm=TRUE)
[1] 14408.26
> Var(tmp5,na.rm=TRUE)
[1] 893.5533
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.31610 67.06578 70.78707 70.37013 71.83041 71.18447 71.23448 71.85715
[9] 70.15321 69.20723
> rowSums(tmp5,na.rm=TRUE)
[1] 1806.322 1341.316 1415.741 1407.403 1436.608 1423.689 1424.690 1365.286
[9] 1403.064 1384.145
> rowVars(tmp5,na.rm=TRUE)
[1] 8147.75872 65.40864 73.54313 71.42913 101.67123 74.64485
[7] 79.10867 101.04585 77.35574 130.54501
> rowSd(tmp5,na.rm=TRUE)
[1] 90.264936 8.087561 8.575729 8.451576 10.083215 8.639725 8.894306
[8] 10.052157 8.795211 11.425630
> rowMax(tmp5,na.rm=TRUE)
[1] 471.80802 85.79294 91.91916 85.46109 87.51631 96.43867 84.42236
[8] 90.62280 85.69506 93.13591
> rowMin(tmp5,na.rm=TRUE)
[1] 55.54314 55.62585 58.93498 55.66466 54.11632 56.66890 56.25176 56.72399
[9] 54.04241 53.28854
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.03635 76.20914 67.95983 69.61597 70.01327 70.10051 71.76216
[8] 69.41568 68.94980 72.25433 64.68457 73.16022 71.83276 66.88280
[15] 63.81804 73.83638 70.73928 76.46860 68.58850 71.35701
> colSums(tmp5,na.rm=TRUE)
[1] 1100.3635 762.0914 679.5983 696.1597 700.1327 701.0051 717.6216
[8] 694.1568 689.4980 722.5433 646.8457 731.6022 718.3276 668.8280
[15] 638.1804 738.3638 707.3928 764.6860 617.2965 713.5701
> colVars(tmp5,na.rm=TRUE)
[1] 16271.04867 86.06417 80.06460 102.36560 67.12916 150.00134
[7] 83.08510 193.17804 51.49921 73.06170 82.82920 106.90517
[13] 76.20414 31.29609 38.28159 46.95614 46.96658 79.71243
[19] 71.94560 48.96444
> colSd(tmp5,na.rm=TRUE)
[1] 127.558021 9.277078 8.947882 10.117589 8.193239 12.247503
[7] 9.115103 13.898850 7.176295 8.547614 9.101055 10.339496
[13] 8.729498 5.594291 6.187212 6.852455 6.853217 8.928182
[19] 8.482075 6.997459
> colMax(tmp5,na.rm=TRUE)
[1] 471.80802 88.91033 82.58903 81.38267 84.42236 96.43867 83.56565
[8] 91.91916 82.71988 85.29657 82.95321 93.13591 85.69506 78.31803
[15] 72.82067 84.96703 81.22645 90.62280 81.20225 84.54018
> colMin(tmp5,na.rm=TRUE)
[1] 54.11632 64.07805 53.28854 55.66466 60.76110 54.04241 54.50901 55.07822
[9] 62.50049 57.16193 56.72399 63.49862 57.17455 59.35139 55.54314 63.58959
[17] 60.62178 58.96179 59.71370 61.34493
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.31610 67.06578 70.78707 70.37013 71.83041 71.18447 71.23448 NaN
[9] 70.15321 69.20723
> rowSums(tmp5,na.rm=TRUE)
[1] 1806.322 1341.316 1415.741 1407.403 1436.608 1423.689 1424.690 0.000
[9] 1403.064 1384.145
> rowVars(tmp5,na.rm=TRUE)
[1] 8147.75872 65.40864 73.54313 71.42913 101.67123 74.64485
[7] 79.10867 NA 77.35574 130.54501
> rowSd(tmp5,na.rm=TRUE)
[1] 90.264936 8.087561 8.575729 8.451576 10.083215 8.639725 8.894306
[8] NA 8.795211 11.425630
> rowMax(tmp5,na.rm=TRUE)
[1] 471.80802 85.79294 91.91916 85.46109 87.51631 96.43867 84.42236
[8] NA 85.69506 93.13591
> rowMin(tmp5,na.rm=TRUE)
[1] 55.54314 55.62585 58.93498 55.66466 54.11632 56.66890 56.25176 NA
[9] 54.04241 53.28854
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.82914 77.25737 66.63638 68.49644 70.79130 69.79078 70.91116
[8] 67.91189 69.14574 72.56662 65.56908 73.33323 73.46145 66.55019
[15] 64.13951 74.89755 71.55528 74.89591 NaN 69.89222
> colSums(tmp5,na.rm=TRUE)
[1] 1015.4622 695.3163 599.7275 616.4679 637.1217 628.1171 638.2005
[8] 611.2070 622.3116 653.0995 590.1217 659.9991 661.1531 598.9517
[15] 577.2556 674.0780 643.9975 674.0632 0.0000 629.0299
> colVars(tmp5,na.rm=TRUE)
[1] 18217.18395 84.46086 70.36830 101.06110 68.71034 167.67230
[7] 85.32363 191.88491 57.50470 81.09728 84.38133 119.93155
[13] 55.88754 33.96352 41.90421 40.15715 45.34660 61.85128
[19] NA 30.94668
> colSd(tmp5,na.rm=TRUE)
[1] 134.971049 9.190259 8.388582 10.052915 8.289170 12.948834
[7] 9.237079 13.852253 7.583186 9.005403 9.185931 10.951327
[13] 7.475797 5.827823 6.473346 6.336967 6.733989 7.864559
[19] NA 5.562974
> colMax(tmp5,na.rm=TRUE)
[1] 471.80802 88.91033 82.58903 81.38267 84.42236 96.43867 83.56565
[8] 91.91916 82.71988 85.29657 82.95321 93.13591 85.69506 78.31803
[15] 72.82067 84.96703 81.22645 85.76341 -Inf 78.00816
> colMin(tmp5,na.rm=TRUE)
[1] 54.11632 64.07805 53.28854 55.66466 60.76110 54.04241 54.50901 55.07822
[9] 62.50049 57.16193 56.98970 63.49862 62.43854 59.35139 55.54314 63.58959
[17] 60.62178 58.96179 Inf 61.34493
>
>
>
>
> 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] 272.3573 130.0416 254.2104 143.2334 262.7922 231.6626 222.8437 112.0531
[9] 155.0141 170.1303
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 272.3573 130.0416 254.2104 143.2334 262.7922 231.6626 222.8437 112.0531
[9] 155.0141 170.1303
>
>
>
> 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] 0.000000e+00 -1.136868e-13 1.278977e-13 0.000000e+00 0.000000e+00
[6] 0.000000e+00 0.000000e+00 -9.947598e-14 2.842171e-14 -2.842171e-14
[11] 5.684342e-14 8.526513e-14 1.705303e-13 0.000000e+00 -1.136868e-13
[16] -5.684342e-14 5.684342e-14 0.000000e+00 -2.842171e-13 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 8
6 5
3 10
6 14
6 3
8 2
7 16
9 12
1 2
8 8
8 9
5 6
6 16
6 12
6 4
2 4
10 8
2 12
1 7
3 13
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] 2.944778
> Min(tmp)
[1] -1.890815
> mean(tmp)
[1] 0.04295056
> Sum(tmp)
[1] 4.295056
> Var(tmp)
[1] 0.9785881
>
> rowMeans(tmp)
[1] 0.04295056
> rowSums(tmp)
[1] 4.295056
> rowVars(tmp)
[1] 0.9785881
> rowSd(tmp)
[1] 0.9892361
> rowMax(tmp)
[1] 2.944778
> rowMin(tmp)
[1] -1.890815
>
> colMeans(tmp)
[1] 0.08628802 0.64837764 -0.63504045 0.29598122 2.94477813 -0.11961286
[7] 0.92824318 -0.26330921 -0.78495039 1.52319416 0.37202706 -1.36920501
[13] -1.01161227 -1.39522983 -0.35974049 0.22663742 -0.47259538 1.32110713
[19] 0.21558824 0.85989177 -0.31490917 -0.34173186 -0.76510311 -0.12073627
[25] -0.12946642 -0.93733299 -0.69446377 0.34525599 0.41193453 -0.46977997
[31] 2.11962864 1.66742533 -1.54006261 0.93743465 0.58967620 1.19568216
[37] 0.10087781 -0.46222580 0.58577464 0.57316870 -0.54254236 0.87877159
[43] 0.43474435 -1.67241832 -1.07804633 1.68114263 0.34862720 -0.22638532
[49] 0.18741991 0.31574865 0.52892372 -0.78780496 1.59810453 -0.56664004
[55] -0.44414877 0.75768287 -1.09424197 -0.84954467 -1.27550480 -1.56488836
[61] 1.24349961 0.68796249 0.64622318 0.56177891 1.03178013 0.54279049
[67] 0.04134877 0.47625560 1.94723173 -0.98691357 -1.58935673 -1.33491130
[73] 0.65299090 -1.11482937 -0.69070909 -0.41430129 -1.04479912 1.01576694
[79] 1.36465871 -0.10697814 1.26717726 0.98403505 -0.37567896 -0.80237868
[85] -0.62079496 -1.89081453 1.05169583 -0.93488769 1.69010317 -0.51953022
[91] -0.52069566 1.55576952 -0.46166145 1.60313149 -0.07197346 -0.02609312
[97] -1.58816522 -0.48586304 -0.66734437 -0.21132859
> colSums(tmp)
[1] 0.08628802 0.64837764 -0.63504045 0.29598122 2.94477813 -0.11961286
[7] 0.92824318 -0.26330921 -0.78495039 1.52319416 0.37202706 -1.36920501
[13] -1.01161227 -1.39522983 -0.35974049 0.22663742 -0.47259538 1.32110713
[19] 0.21558824 0.85989177 -0.31490917 -0.34173186 -0.76510311 -0.12073627
[25] -0.12946642 -0.93733299 -0.69446377 0.34525599 0.41193453 -0.46977997
[31] 2.11962864 1.66742533 -1.54006261 0.93743465 0.58967620 1.19568216
[37] 0.10087781 -0.46222580 0.58577464 0.57316870 -0.54254236 0.87877159
[43] 0.43474435 -1.67241832 -1.07804633 1.68114263 0.34862720 -0.22638532
[49] 0.18741991 0.31574865 0.52892372 -0.78780496 1.59810453 -0.56664004
[55] -0.44414877 0.75768287 -1.09424197 -0.84954467 -1.27550480 -1.56488836
[61] 1.24349961 0.68796249 0.64622318 0.56177891 1.03178013 0.54279049
[67] 0.04134877 0.47625560 1.94723173 -0.98691357 -1.58935673 -1.33491130
[73] 0.65299090 -1.11482937 -0.69070909 -0.41430129 -1.04479912 1.01576694
[79] 1.36465871 -0.10697814 1.26717726 0.98403505 -0.37567896 -0.80237868
[85] -0.62079496 -1.89081453 1.05169583 -0.93488769 1.69010317 -0.51953022
[91] -0.52069566 1.55576952 -0.46166145 1.60313149 -0.07197346 -0.02609312
[97] -1.58816522 -0.48586304 -0.66734437 -0.21132859
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.08628802 0.64837764 -0.63504045 0.29598122 2.94477813 -0.11961286
[7] 0.92824318 -0.26330921 -0.78495039 1.52319416 0.37202706 -1.36920501
[13] -1.01161227 -1.39522983 -0.35974049 0.22663742 -0.47259538 1.32110713
[19] 0.21558824 0.85989177 -0.31490917 -0.34173186 -0.76510311 -0.12073627
[25] -0.12946642 -0.93733299 -0.69446377 0.34525599 0.41193453 -0.46977997
[31] 2.11962864 1.66742533 -1.54006261 0.93743465 0.58967620 1.19568216
[37] 0.10087781 -0.46222580 0.58577464 0.57316870 -0.54254236 0.87877159
[43] 0.43474435 -1.67241832 -1.07804633 1.68114263 0.34862720 -0.22638532
[49] 0.18741991 0.31574865 0.52892372 -0.78780496 1.59810453 -0.56664004
[55] -0.44414877 0.75768287 -1.09424197 -0.84954467 -1.27550480 -1.56488836
[61] 1.24349961 0.68796249 0.64622318 0.56177891 1.03178013 0.54279049
[67] 0.04134877 0.47625560 1.94723173 -0.98691357 -1.58935673 -1.33491130
[73] 0.65299090 -1.11482937 -0.69070909 -0.41430129 -1.04479912 1.01576694
[79] 1.36465871 -0.10697814 1.26717726 0.98403505 -0.37567896 -0.80237868
[85] -0.62079496 -1.89081453 1.05169583 -0.93488769 1.69010317 -0.51953022
[91] -0.52069566 1.55576952 -0.46166145 1.60313149 -0.07197346 -0.02609312
[97] -1.58816522 -0.48586304 -0.66734437 -0.21132859
> colMin(tmp)
[1] 0.08628802 0.64837764 -0.63504045 0.29598122 2.94477813 -0.11961286
[7] 0.92824318 -0.26330921 -0.78495039 1.52319416 0.37202706 -1.36920501
[13] -1.01161227 -1.39522983 -0.35974049 0.22663742 -0.47259538 1.32110713
[19] 0.21558824 0.85989177 -0.31490917 -0.34173186 -0.76510311 -0.12073627
[25] -0.12946642 -0.93733299 -0.69446377 0.34525599 0.41193453 -0.46977997
[31] 2.11962864 1.66742533 -1.54006261 0.93743465 0.58967620 1.19568216
[37] 0.10087781 -0.46222580 0.58577464 0.57316870 -0.54254236 0.87877159
[43] 0.43474435 -1.67241832 -1.07804633 1.68114263 0.34862720 -0.22638532
[49] 0.18741991 0.31574865 0.52892372 -0.78780496 1.59810453 -0.56664004
[55] -0.44414877 0.75768287 -1.09424197 -0.84954467 -1.27550480 -1.56488836
[61] 1.24349961 0.68796249 0.64622318 0.56177891 1.03178013 0.54279049
[67] 0.04134877 0.47625560 1.94723173 -0.98691357 -1.58935673 -1.33491130
[73] 0.65299090 -1.11482937 -0.69070909 -0.41430129 -1.04479912 1.01576694
[79] 1.36465871 -0.10697814 1.26717726 0.98403505 -0.37567896 -0.80237868
[85] -0.62079496 -1.89081453 1.05169583 -0.93488769 1.69010317 -0.51953022
[91] -0.52069566 1.55576952 -0.46166145 1.60313149 -0.07197346 -0.02609312
[97] -1.58816522 -0.48586304 -0.66734437 -0.21132859
> colMedians(tmp)
[1] 0.08628802 0.64837764 -0.63504045 0.29598122 2.94477813 -0.11961286
[7] 0.92824318 -0.26330921 -0.78495039 1.52319416 0.37202706 -1.36920501
[13] -1.01161227 -1.39522983 -0.35974049 0.22663742 -0.47259538 1.32110713
[19] 0.21558824 0.85989177 -0.31490917 -0.34173186 -0.76510311 -0.12073627
[25] -0.12946642 -0.93733299 -0.69446377 0.34525599 0.41193453 -0.46977997
[31] 2.11962864 1.66742533 -1.54006261 0.93743465 0.58967620 1.19568216
[37] 0.10087781 -0.46222580 0.58577464 0.57316870 -0.54254236 0.87877159
[43] 0.43474435 -1.67241832 -1.07804633 1.68114263 0.34862720 -0.22638532
[49] 0.18741991 0.31574865 0.52892372 -0.78780496 1.59810453 -0.56664004
[55] -0.44414877 0.75768287 -1.09424197 -0.84954467 -1.27550480 -1.56488836
[61] 1.24349961 0.68796249 0.64622318 0.56177891 1.03178013 0.54279049
[67] 0.04134877 0.47625560 1.94723173 -0.98691357 -1.58935673 -1.33491130
[73] 0.65299090 -1.11482937 -0.69070909 -0.41430129 -1.04479912 1.01576694
[79] 1.36465871 -0.10697814 1.26717726 0.98403505 -0.37567896 -0.80237868
[85] -0.62079496 -1.89081453 1.05169583 -0.93488769 1.69010317 -0.51953022
[91] -0.52069566 1.55576952 -0.46166145 1.60313149 -0.07197346 -0.02609312
[97] -1.58816522 -0.48586304 -0.66734437 -0.21132859
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.08628802 0.6483776 -0.6350405 0.2959812 2.944778 -0.1196129 0.9282432
[2,] 0.08628802 0.6483776 -0.6350405 0.2959812 2.944778 -0.1196129 0.9282432
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.2633092 -0.7849504 1.523194 0.3720271 -1.369205 -1.011612 -1.39523
[2,] -0.2633092 -0.7849504 1.523194 0.3720271 -1.369205 -1.011612 -1.39523
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.3597405 0.2266374 -0.4725954 1.321107 0.2155882 0.8598918 -0.3149092
[2,] -0.3597405 0.2266374 -0.4725954 1.321107 0.2155882 0.8598918 -0.3149092
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.3417319 -0.7651031 -0.1207363 -0.1294664 -0.937333 -0.6944638 0.345256
[2,] -0.3417319 -0.7651031 -0.1207363 -0.1294664 -0.937333 -0.6944638 0.345256
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.4119345 -0.46978 2.119629 1.667425 -1.540063 0.9374347 0.5896762
[2,] 0.4119345 -0.46978 2.119629 1.667425 -1.540063 0.9374347 0.5896762
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.195682 0.1008778 -0.4622258 0.5857746 0.5731687 -0.5425424 0.8787716
[2,] 1.195682 0.1008778 -0.4622258 0.5857746 0.5731687 -0.5425424 0.8787716
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.4347443 -1.672418 -1.078046 1.681143 0.3486272 -0.2263853 0.1874199
[2,] 0.4347443 -1.672418 -1.078046 1.681143 0.3486272 -0.2263853 0.1874199
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3157486 0.5289237 -0.787805 1.598105 -0.56664 -0.4441488 0.7576829
[2,] 0.3157486 0.5289237 -0.787805 1.598105 -0.56664 -0.4441488 0.7576829
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.094242 -0.8495447 -1.275505 -1.564888 1.2435 0.6879625 0.6462232
[2,] -1.094242 -0.8495447 -1.275505 -1.564888 1.2435 0.6879625 0.6462232
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.5617789 1.03178 0.5427905 0.04134877 0.4762556 1.947232 -0.9869136
[2,] 0.5617789 1.03178 0.5427905 0.04134877 0.4762556 1.947232 -0.9869136
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.589357 -1.334911 0.6529909 -1.114829 -0.6907091 -0.4143013 -1.044799
[2,] -1.589357 -1.334911 0.6529909 -1.114829 -0.6907091 -0.4143013 -1.044799
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.015767 1.364659 -0.1069781 1.267177 0.984035 -0.375679 -0.8023787
[2,] 1.015767 1.364659 -0.1069781 1.267177 0.984035 -0.375679 -0.8023787
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.620795 -1.890815 1.051696 -0.9348877 1.690103 -0.5195302 -0.5206957
[2,] -0.620795 -1.890815 1.051696 -0.9348877 1.690103 -0.5195302 -0.5206957
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.55577 -0.4616614 1.603131 -0.07197346 -0.02609312 -1.588165 -0.485863
[2,] 1.55577 -0.4616614 1.603131 -0.07197346 -0.02609312 -1.588165 -0.485863
[,99] [,100]
[1,] -0.6673444 -0.2113286
[2,] -0.6673444 -0.2113286
>
>
> Max(tmp2)
[1] 2.595889
> Min(tmp2)
[1] -2.685207
> mean(tmp2)
[1] 0.1134857
> Sum(tmp2)
[1] 11.34857
> Var(tmp2)
[1] 1.123584
>
> rowMeans(tmp2)
[1] -0.813421555 0.838259953 -1.021347405 -0.443450529 -1.362397578
[6] -0.430845003 0.024470880 1.167095532 2.456617816 -1.659576845
[11] 0.608673680 0.203276965 1.033431696 -1.108058331 -0.682956807
[16] 0.704481704 -0.087045695 0.536540135 -1.460377389 0.991161035
[21] 0.506359184 0.599920679 -0.343960075 -0.769580997 0.256711658
[26] 0.700571183 -0.081629676 -0.509589141 -0.329667563 1.094261384
[31] -0.723157202 0.289479519 0.481599468 -0.600789426 0.339169976
[36] -0.684987606 0.029650214 0.104811934 -0.208299497 0.410351496
[41] 1.476100555 -2.576906500 0.210328501 -1.381688355 0.043014012
[46] -0.119873294 0.215496401 0.755274080 -1.488407951 1.156045308
[51] 0.170193317 1.383268176 2.396709142 -0.381795206 -0.098958156
[56] -0.162049551 -0.853770191 -0.869401589 2.067973356 -1.177563096
[61] 2.080626786 0.616064546 0.877278242 1.930658459 -0.249942865
[66] -1.158116261 -2.685206646 -0.140463334 -0.502000178 -0.216409351
[71] 0.327712235 -1.932912246 -0.488731165 -0.408200381 0.433686571
[76] -0.058857455 1.226408703 -0.363894823 0.991409782 2.441077856
[81] 0.172105864 -1.617705706 0.174845289 -0.056295451 -0.433890473
[86] 0.002085059 -0.052032132 -0.744080379 1.903864830 -0.149280417
[91] 0.842209773 0.054530304 1.249130022 2.595888605 0.868543688
[96] -0.954289326 1.575866622 0.572612570 1.867153090 -0.062627745
> rowSums(tmp2)
[1] -0.813421555 0.838259953 -1.021347405 -0.443450529 -1.362397578
[6] -0.430845003 0.024470880 1.167095532 2.456617816 -1.659576845
[11] 0.608673680 0.203276965 1.033431696 -1.108058331 -0.682956807
[16] 0.704481704 -0.087045695 0.536540135 -1.460377389 0.991161035
[21] 0.506359184 0.599920679 -0.343960075 -0.769580997 0.256711658
[26] 0.700571183 -0.081629676 -0.509589141 -0.329667563 1.094261384
[31] -0.723157202 0.289479519 0.481599468 -0.600789426 0.339169976
[36] -0.684987606 0.029650214 0.104811934 -0.208299497 0.410351496
[41] 1.476100555 -2.576906500 0.210328501 -1.381688355 0.043014012
[46] -0.119873294 0.215496401 0.755274080 -1.488407951 1.156045308
[51] 0.170193317 1.383268176 2.396709142 -0.381795206 -0.098958156
[56] -0.162049551 -0.853770191 -0.869401589 2.067973356 -1.177563096
[61] 2.080626786 0.616064546 0.877278242 1.930658459 -0.249942865
[66] -1.158116261 -2.685206646 -0.140463334 -0.502000178 -0.216409351
[71] 0.327712235 -1.932912246 -0.488731165 -0.408200381 0.433686571
[76] -0.058857455 1.226408703 -0.363894823 0.991409782 2.441077856
[81] 0.172105864 -1.617705706 0.174845289 -0.056295451 -0.433890473
[86] 0.002085059 -0.052032132 -0.744080379 1.903864830 -0.149280417
[91] 0.842209773 0.054530304 1.249130022 2.595888605 0.868543688
[96] -0.954289326 1.575866622 0.572612570 1.867153090 -0.062627745
> 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] -0.813421555 0.838259953 -1.021347405 -0.443450529 -1.362397578
[6] -0.430845003 0.024470880 1.167095532 2.456617816 -1.659576845
[11] 0.608673680 0.203276965 1.033431696 -1.108058331 -0.682956807
[16] 0.704481704 -0.087045695 0.536540135 -1.460377389 0.991161035
[21] 0.506359184 0.599920679 -0.343960075 -0.769580997 0.256711658
[26] 0.700571183 -0.081629676 -0.509589141 -0.329667563 1.094261384
[31] -0.723157202 0.289479519 0.481599468 -0.600789426 0.339169976
[36] -0.684987606 0.029650214 0.104811934 -0.208299497 0.410351496
[41] 1.476100555 -2.576906500 0.210328501 -1.381688355 0.043014012
[46] -0.119873294 0.215496401 0.755274080 -1.488407951 1.156045308
[51] 0.170193317 1.383268176 2.396709142 -0.381795206 -0.098958156
[56] -0.162049551 -0.853770191 -0.869401589 2.067973356 -1.177563096
[61] 2.080626786 0.616064546 0.877278242 1.930658459 -0.249942865
[66] -1.158116261 -2.685206646 -0.140463334 -0.502000178 -0.216409351
[71] 0.327712235 -1.932912246 -0.488731165 -0.408200381 0.433686571
[76] -0.058857455 1.226408703 -0.363894823 0.991409782 2.441077856
[81] 0.172105864 -1.617705706 0.174845289 -0.056295451 -0.433890473
[86] 0.002085059 -0.052032132 -0.744080379 1.903864830 -0.149280417
[91] 0.842209773 0.054530304 1.249130022 2.595888605 0.868543688
[96] -0.954289326 1.575866622 0.572612570 1.867153090 -0.062627745
> rowMin(tmp2)
[1] -0.813421555 0.838259953 -1.021347405 -0.443450529 -1.362397578
[6] -0.430845003 0.024470880 1.167095532 2.456617816 -1.659576845
[11] 0.608673680 0.203276965 1.033431696 -1.108058331 -0.682956807
[16] 0.704481704 -0.087045695 0.536540135 -1.460377389 0.991161035
[21] 0.506359184 0.599920679 -0.343960075 -0.769580997 0.256711658
[26] 0.700571183 -0.081629676 -0.509589141 -0.329667563 1.094261384
[31] -0.723157202 0.289479519 0.481599468 -0.600789426 0.339169976
[36] -0.684987606 0.029650214 0.104811934 -0.208299497 0.410351496
[41] 1.476100555 -2.576906500 0.210328501 -1.381688355 0.043014012
[46] -0.119873294 0.215496401 0.755274080 -1.488407951 1.156045308
[51] 0.170193317 1.383268176 2.396709142 -0.381795206 -0.098958156
[56] -0.162049551 -0.853770191 -0.869401589 2.067973356 -1.177563096
[61] 2.080626786 0.616064546 0.877278242 1.930658459 -0.249942865
[66] -1.158116261 -2.685206646 -0.140463334 -0.502000178 -0.216409351
[71] 0.327712235 -1.932912246 -0.488731165 -0.408200381 0.433686571
[76] -0.058857455 1.226408703 -0.363894823 0.991409782 2.441077856
[81] 0.172105864 -1.617705706 0.174845289 -0.056295451 -0.433890473
[86] 0.002085059 -0.052032132 -0.744080379 1.903864830 -0.149280417
[91] 0.842209773 0.054530304 1.249130022 2.595888605 0.868543688
[96] -0.954289326 1.575866622 0.572612570 1.867153090 -0.062627745
>
> colMeans(tmp2)
[1] 0.1134857
> colSums(tmp2)
[1] 11.34857
> colVars(tmp2)
[1] 1.123584
> colSd(tmp2)
[1] 1.059993
> colMax(tmp2)
[1] 2.595889
> colMin(tmp2)
[1] -2.685207
> colMedians(tmp2)
[1] 0.02706055
> colRanges(tmp2)
[,1]
[1,] -2.685207
[2,] 2.595889
>
> 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] 0.4913482 -1.4698415 -2.7377427 2.4220601 -12.3585984 6.6784622
[7] 3.4570694 -2.4640244 2.4798986 1.4640574
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.28682027
[2,] -0.71529143
[3,] 0.06180226
[4,] 0.84193720
[5,] 1.36281738
>
> rowApply(tmp,sum)
[1] -4.7457049 1.7532730 -3.2809688 3.1989413 0.1560528 -2.7642414
[7] 0.3168462 -0.1599515 3.0364643 0.4519780
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 4 2 3 9 6 8 2 8 9
[2,] 10 8 7 5 6 1 3 3 7 5
[3,] 7 9 8 6 3 3 5 8 3 1
[4,] 5 3 3 8 7 9 9 10 4 7
[5,] 1 2 5 1 1 2 1 1 2 2
[6,] 6 6 9 2 10 10 10 5 10 3
[7,] 8 10 10 7 4 8 2 4 1 8
[8,] 4 1 1 9 8 4 4 7 5 6
[9,] 9 5 6 4 5 5 6 6 6 10
[10,] 3 7 4 10 2 7 7 9 9 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.06756155 -0.07421376 1.56710291 -2.41300637 -3.17048545 -1.57690576
[7] 3.47259815 1.27635017 -1.15935616 2.19270953 2.04428764 1.70503461
[13] 0.76786453 -4.30784362 3.04817083 2.42391057 -1.53265329 0.22910630
[19] -0.66340118 -2.34897007
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.08822401
[2,] 0.61008417
[3,] 0.70645155
[4,] 0.82955350
[5,] 1.00969634
>
> rowApply(tmp,sum)
[1] -3.368285 2.057223 2.495873 -4.906377 8.269427
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 16 14 13 15
[2,] 6 13 12 2 16
[3,] 7 17 20 14 4
[4,] 9 2 8 9 6
[5,] 14 10 4 4 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.82955350 -0.9923723 -0.80704219 -0.56912451 0.4836720 1.2024397
[2,] 0.61008417 0.2863383 1.36808300 -1.09996668 -0.1598199 -0.4563225
[3,] 0.70645155 0.5255795 1.50456668 -0.09776082 -1.0925945 -0.3148227
[4,] -0.08822401 -1.2861160 -0.07653371 -0.70461170 -1.0653444 -0.8067424
[5,] 1.00969634 1.3923567 -0.42197087 0.05845734 -1.3363987 -1.2014578
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8400592 -0.4962824 -0.06092158 -1.0451089 1.9785089 0.70800510
[2,] -0.1969915 -0.2000849 -0.99488344 2.2725192 0.4807162 0.40351072
[3,] 0.7305616 0.9802755 0.55212453 0.5186595 -1.4566312 0.03751851
[4,] 1.2984368 -0.9552606 -0.71779165 -1.5347153 0.7276775 -1.07183202
[5,] 0.8005321 1.9477026 0.06211599 1.9813551 0.3140163 1.62783230
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.5959752 -1.0774892 0.17517269 0.5401856 -0.0001440827 -1.7433747
[2,] 1.4522575 -0.9590348 0.03654623 0.2749971 -1.5800992878 1.7970981
[3,] -1.2176636 -1.1393073 0.98334768 1.3218344 -0.7660422435 0.3997560
[4,] 1.8692190 -0.8465905 0.36122955 -0.3833733 0.5487977628 0.6133545
[5,] 0.2600269 -0.2854218 1.49187467 0.6702668 0.2648345570 -0.8377276
[,19] [,20]
[1,] -0.5731775 -1.1648687
[2,] -0.9076928 -0.3700318
[3,] 1.0199388 -0.6999193
[4,] -0.3784121 -0.4095443
[5,] 0.1759425 0.2953939
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.058617 0.7275768 0.3761002 -0.9957164 -0.4714619 0.8655653 0.3035653
col8 col9 col10 col11 col12 col13 col14
row1 0.9348342 -1.086666 0.6004404 2.112731 0.3908623 0.4132967 -0.05828123
col15 col16 col17 col18 col19 col20
row1 -2.131587 -1.219439 0.5057424 -1.501786 -0.6400395 0.2609799
> tmp[,"col10"]
col10
row1 0.6004404
row2 1.0686013
row3 -1.3035094
row4 1.7359146
row5 0.8162296
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.058617 0.7275768 0.3761002 -0.9957164 -0.4714619 0.8655653 0.3035653
row5 -1.033278 1.7415880 1.2474566 0.1634423 0.7475715 0.4823577 -0.6034414
col8 col9 col10 col11 col12 col13
row1 0.93483416 -1.0866656 0.6004404 2.11273085 0.3908623 0.4132967
row5 -0.05935928 -0.1605401 0.8162296 0.05013442 0.7527790 -0.7515154
col14 col15 col16 col17 col18 col19
row1 -0.05828123 -2.1315873 -1.219439 0.5057424 -1.5017860 -0.6400395
row5 0.02090437 0.8980438 -1.269179 0.7967832 0.5459483 -0.8050957
col20
row1 0.260979909
row5 -0.002291156
> tmp[,c("col6","col20")]
col6 col20
row1 0.8655653 0.260979909
row2 -1.2432024 -0.468079658
row3 1.0358561 0.467144746
row4 -0.9036828 -0.261538510
row5 0.4823577 -0.002291156
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.8655653 0.260979909
row5 0.4823577 -0.002291156
>
>
>
>
> 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 50.56199 50.05632 51.32235 50.34584 49.86689 104.1903 51.10642 50.91536
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.58034 50.13325 50.01785 51.31288 49.4037 49.4559 48.97814 49.80881
col17 col18 col19 col20
row1 50.18428 50.14079 49.84659 105.041
> tmp[,"col10"]
col10
row1 50.13325
row2 29.55652
row3 30.98471
row4 29.18944
row5 50.73883
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.56199 50.05632 51.32235 50.34584 49.86689 104.1903 51.10642 50.91536
row5 50.66171 48.88585 48.57687 50.52144 50.88994 107.4018 50.36075 48.30975
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.58034 50.13325 50.01785 51.31288 49.40370 49.45590 48.97814 49.80881
row5 49.77725 50.73883 52.30637 49.39459 52.71919 50.23248 50.07573 48.44396
col17 col18 col19 col20
row1 50.18428 50.14079 49.84659 105.0410
row5 49.23759 48.44348 50.54483 104.7034
> tmp[,c("col6","col20")]
col6 col20
row1 104.19025 105.04100
row2 74.91262 75.31413
row3 75.03698 76.48514
row4 74.47158 75.25506
row5 107.40175 104.70344
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.1903 105.0410
row5 107.4018 104.7034
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.1903 105.0410
row5 107.4018 104.7034
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.6598559
[2,] -0.5369046
[3,] -1.4023878
[4,] -0.6990913
[5,] 0.4314872
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.1295456 0.1716333
[2,] -0.8459656 1.4673192
[3,] 1.2613046 0.1771521
[4,] -2.0211836 1.4745877
[5,] 0.8420003 0.3926735
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.2018886 1.5056891
[2,] 0.8678184 2.2098291
[3,] -0.1537909 -1.7131363
[4,] -0.1881285 1.1039759
[5,] 1.9971712 0.4285854
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2018886
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2018886
[2,] 0.8678184
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.8841694 -0.2826472 1.406646 0.5036295 -0.7235711 0.4526535 0.3933321
row1 -0.1490366 -0.6057338 -1.110624 1.1370357 -1.3927345 2.2522559 -1.4368951
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.5525417 1.127065 -0.7814624 0.3139212 0.4187916 1.312038 0.41200925
row1 0.5203310 -1.693283 0.1045571 -0.6244488 -0.2011535 1.643001 0.04384396
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.1456499 0.2102871 0.9322907 0.6004272 -1.405781 0.03730026
row1 -0.5630512 0.1730335 -0.7569858 1.5485969 1.371478 1.76091688
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5760159 0.8184207 -1.822119 -0.2388882 -1.417414 -0.7903891 1.166276
[,8] [,9] [,10]
row2 -2.513579 0.3273065 0.00520096
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.0878745 -0.5036451 0.5955266 0.3528237 -1.392615 0.1035865 -0.9620667
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.932774 -0.1092645 0.3486007 1.37172 -0.4514147 1.120378 -1.114395
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.7723398 -0.8916988 0.8438471 0.1921465 1.598866 -0.5434823
>
>
> 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: 0x55c6ac4130a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce621f02a7"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce2ccc2f37"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce40ec66e2"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce75a2195f"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce46302e21"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce2c1dca74"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce97392cc"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce198e2f6f"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce5f32a50a"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce51bafb4"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce70c82e91"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce1e9c2dc2"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fceb69f4fd"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce54df3f3e"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM309fce7b118831"
>
>
> ### 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: 0x55c6adc34790>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55c6adc34790>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55c6adc34790>
> rowMedians(tmp)
[1] 0.0009896165 -0.1310123955 0.2990885123 -0.2077356856 0.3729282357
[6] 0.1225855656 0.5885023994 0.3631555392 0.3741739517 -0.0738658522
[11] -0.0379991130 0.1337725808 -0.1946947611 0.0359563831 -0.6548403677
[16] -0.3036989647 -0.5186487961 0.3828438100 -0.1590470455 -0.3290361433
[21] 0.2060004153 0.0956926242 -0.0538015882 0.3544277775 0.6544642614
[26] 0.3906098236 -0.2300516966 0.3364032038 0.1400240084 0.4048199380
[31] 0.1465356862 -0.2929042935 0.1614648964 0.2557450786 0.2266340405
[36] -0.0992910839 -0.1866767582 0.1136346365 0.0373966998 -0.0083558714
[41] 0.2233740865 -0.4319017116 -0.1378128800 -0.1546138019 0.2458030898
[46] -0.0722425784 0.1376087277 0.3408433917 0.3893312065 0.2795503893
[51] -0.5481336491 0.5188219920 -0.1655477921 -0.0819579351 -0.1074950152
[56] 0.0040926658 0.1226552755 0.0066539661 -0.1789764960 -0.4687919151
[61] -0.0663860612 -0.0647264625 0.4008769640 0.4528243499 0.4571435167
[66] 0.2029437187 0.3887207932 0.8602828119 -0.2273964498 0.5222940172
[71] -0.4338465393 0.2354327754 0.2993584136 -0.2767720653 -0.1670935074
[76] -0.2967933138 -0.5642960298 -0.5763962110 0.2800996586 0.2499699241
[81] 0.2882381262 0.7404926904 -0.0258285929 -0.1832755570 -0.2654596112
[86] 0.5207690825 -0.3910387930 -0.4233038058 -0.4707538234 -0.2308322220
[91] -0.0144803977 0.3702617105 -0.0693404345 0.0300533496 -0.0585624442
[96] -0.3037226807 -0.2041467185 -0.0004313450 0.5173827841 0.1912251627
[101] -0.2838855360 0.2398480580 0.5667363770 -0.2041493243 -0.3599516075
[106] 0.3691720343 -0.0044829049 0.2034006611 0.5369144456 0.0440123173
[111] -0.6050556824 -0.0899552058 0.1460283902 0.1869126801 -0.4308687852
[116] 0.1851570775 -0.0698849240 0.2249237697 -0.1897067896 0.7171001751
[121] -0.2390650329 0.0678155415 0.0086529631 -0.3553300785 -0.2779238364
[126] 0.0741684076 -0.1342863884 -0.2687055680 -0.2006090378 0.1676474482
[131] -0.0562860246 0.1836186666 -0.1087687487 0.6017229757 0.0520522592
[136] -0.1895237331 0.4462811386 -0.4541462243 0.2635355224 -0.4889461503
[141] 0.2039352253 0.1808429708 0.5613517278 0.1966925239 0.0325848041
[146] -0.6185401876 -0.3182492875 -0.3655208182 0.1817971754 -0.1050542976
[151] -0.4495874188 0.2327505933 -0.3333740594 0.0555430383 0.1593870238
[156] -0.2549907406 0.1262163786 -0.1318748561 -0.5397571449 -0.2109145016
[161] -0.0305008446 -0.1522475282 0.2077427735 -0.2398782787 0.8084367928
[166] -0.4850351957 -0.5853183376 0.2490566105 -0.1831621220 0.4563860791
[171] -0.3915996582 0.0911011624 -0.0102036561 -0.0281431142 -0.0617107768
[176] -0.3655141467 0.2986786724 -0.4112186858 -0.0726991466 -0.1026732038
[181] -0.0631942788 -0.2517798508 -0.0911741770 -0.3892285784 0.3909611424
[186] -0.1963076778 -0.1630368521 0.0156193016 -0.1582355418 0.0295945615
[191] -0.3687641173 0.0626772329 0.0999504899 0.2912492976 -0.3922268538
[196] -0.1580168890 0.0259944258 -0.4611423949 0.3893192857 -0.0575305236
[201] -0.4607052390 -0.2027789523 0.6540187599 0.0647990157 -0.2082664540
[206] -0.7208705296 -0.4120882870 -0.4137323160 -0.0927618366 0.4682807508
[211] -0.0663017546 -0.0269235970 0.0565894408 -0.0077977521 -0.2690327284
[216] -0.2215555476 0.0991941690 0.3932354964 -0.1789462647 -0.1760385525
[221] -0.0609682670 -0.3241371429 0.1342987367 0.3193063511 -0.1682053258
[226] 0.3654626773 0.3505154663 -0.0541178917 0.3602243329 0.4814188982
>
> proc.time()
user system elapsed
1.302 0.637 1.923
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: 0x5a08ff747c80>
> .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: 0x5a08ff747c80>
> .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: 0x5a08ff747c80>
> .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: 0x5a08ff747c80>
> 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: 0x5a08ff3dea00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a08ff3dea00>
> .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: 0x5a08ff3dea00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a08ff3dea00>
> .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: 0x5a08ff3dea00>
> 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: 0x5a08ff4a9660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a08ff4a9660>
> .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: 0x5a08ff4a9660>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5a08ff4a9660>
> .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: 0x5a08ff4a9660>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5a08ff4a9660>
> .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: 0x5a08ff4a9660>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5a08ff4a9660>
> .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: 0x5a08ff4a9660>
> 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: 0x5a08ff9cb3e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5a08ff9cb3e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a08ff9cb3e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a08ff9cb3e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile30a03c2faa594d" "BufferedMatrixFile30a03c6cd07412"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile30a03c2faa594d" "BufferedMatrixFile30a03c6cd07412"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a0901b28470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a0901b28470>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5a0901b28470>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5a0901b28470>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5a0901b28470>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5a0901b28470>
> .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: 0x5a08fffad6e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a08fffad6e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5a08fffad6e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5a08fffad6e0>
> 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: 0x5a09013f00d0>
> .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: 0x5a09013f00d0>
> rm(P)
>
> proc.time()
user system elapsed
0.231 0.060 0.279
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
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.250 0.046 0.284