Ben Bolstad
| Snapshot Date: 2025-12-03 13:40 -0500 (Wed, 03 Dec 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2025-12-04 11:34 -0500 (Thu, 04 Dec 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4869 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4576 |
| 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 253/2331 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | 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: 1.75.0 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz |
| StartedAt: 2025-12-03 22:21:28 -0500 (Wed, 03 Dec 2025) |
| EndedAt: 2025-12-03 22:27:36 -0500 (Wed, 03 Dec 2025) |
| EllapsedTime: 367.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* 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 ‘1.75.0’
* checking package namespace information ... OK
* checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
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 ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ...* 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: 1 NOTE
See
‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** 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-3.23-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-3.23-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-3.23-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-3.23-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-3.23-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-3.23-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.23-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 Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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
0.218 0.059 0.266
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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-3.23-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 478818 25.6 1048392 56 639317 34.2
Vcells 885623 6.8 8388608 64 2082728 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] "Wed Dec 3 22:27:26 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] "Wed Dec 3 22:27:26 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: 0x5f2d695305e0>
>
>
>
> 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] "Wed Dec 3 22:27:27 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] "Wed Dec 3 22:27:27 2025"
>
> ColMode(tmp2)
<pointer: 0x5f2d695305e0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.406932 -1.946158881 -0.2578467 -0.2048731
[2,] 0.543905 0.007509849 1.4434362 2.3470484
[3,] 1.266334 1.698557283 0.5417278 -1.5157004
[4,] -1.707623 -0.154157300 -0.6050116 -0.5678576
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.406932 1.946158881 0.2578467 0.2048731
[2,] 0.543905 0.007509849 1.4434362 2.3470484
[3,] 1.266334 1.698557283 0.5417278 1.5157004
[4,] 1.707623 0.154157300 0.6050116 0.5678576
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-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,] 10.0203259 1.39504799 0.5077860 0.4526291
[2,] 0.7374992 0.08665938 1.2014309 1.5320080
[3,] 1.1253150 1.30328711 0.7360216 1.2311378
[4,] 1.3067606 0.39262870 0.7778249 0.7535633
>
> 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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.61019 40.89664 30.33571 29.73116
[2,] 32.91890 25.87410 38.45775 42.66713
[3,] 37.51948 39.73143 32.90194 38.82708
[4,] 39.77523 29.08044 33.38326 33.10349
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5f2d690bb840>
> exp(tmp5)
<pointer: 0x5f2d690bb840>
> log(tmp5,2)
<pointer: 0x5f2d690bb840>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.5781
> Min(tmp5)
[1] 53.85356
> mean(tmp5)
[1] 73.71942
> Sum(tmp5)
[1] 14743.88
> Var(tmp5)
[1] 865.0642
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.59740 71.97951 74.88866 70.98140 73.78312 75.98319 70.01681 69.43630
[9] 71.37935 69.14842
> rowSums(tmp5)
[1] 1791.948 1439.590 1497.773 1419.628 1475.662 1519.664 1400.336 1388.726
[9] 1427.587 1382.968
> rowVars(tmp5)
[1] 8084.31974 61.75325 68.39148 54.98308 70.35927 68.04489
[7] 111.95715 65.04523 58.64954 72.11132
> rowSd(tmp5)
[1] 89.912845 7.858324 8.269914 7.415058 8.388043 8.248933 10.580981
[8] 8.065062 7.658299 8.491839
> rowMax(tmp5)
[1] 469.57805 88.80604 86.60064 82.78693 86.20550 88.17851 96.87657
[8] 84.75686 87.86089 94.63311
> rowMin(tmp5)
[1] 55.45011 53.85356 61.36974 57.03832 56.74715 63.30960 54.07706 56.05921
[9] 59.71095 58.62509
>
> colMeans(tmp5)
[1] 112.31894 68.65121 71.61251 73.81668 70.09993 67.37568 75.10406
[8] 71.12574 71.94213 71.07838 75.80191 68.96716 74.09973 72.52764
[15] 69.23787 73.57367 71.31613 72.89321 70.77911 72.06658
> colSums(tmp5)
[1] 1123.1894 686.5121 716.1251 738.1668 700.9993 673.7568 751.0406
[8] 711.2574 719.4213 710.7838 758.0191 689.6716 740.9973 725.2764
[15] 692.3787 735.7367 713.1613 728.9321 707.7911 720.6658
> colVars(tmp5)
[1] 15851.77911 126.83678 57.69879 77.55467 117.67431 29.25362
[7] 43.33195 50.61154 84.52969 97.30919 37.85172 37.91076
[13] 136.96237 53.18776 76.43378 66.67704 121.16387 94.49067
[19] 66.03529 57.34038
> colSd(tmp5)
[1] 125.903849 11.262184 7.595972 8.806513 10.847779 5.408662
[7] 6.582701 7.114179 9.194003 9.864542 6.152375 6.157172
[13] 11.703092 7.292994 8.742641 8.165601 11.007446 9.720631
[19] 8.126210 7.572343
> colMax(tmp5)
[1] 469.57805 85.12100 88.17851 88.80604 86.60064 75.14030 85.32782
[8] 79.03358 85.39455 94.63311 84.40255 76.83163 91.90493 86.20550
[15] 82.43728 85.00304 96.87657 87.93165 84.25811 81.65829
> colMin(tmp5)
[1] 57.05669 53.85356 63.13980 61.88152 54.07706 59.96333 63.62657 58.70743
[9] 57.61242 59.13704 66.18322 57.03832 58.17411 62.21324 59.56826 61.95905
[17] 58.62509 55.45011 62.41352 56.05921
>
>
> ### 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] 89.59740 NA 74.88866 70.98140 73.78312 75.98319 70.01681 69.43630
[9] 71.37935 69.14842
> rowSums(tmp5)
[1] 1791.948 NA 1497.773 1419.628 1475.662 1519.664 1400.336 1388.726
[9] 1427.587 1382.968
> rowVars(tmp5)
[1] 8084.31974 60.51265 68.39148 54.98308 70.35927 68.04489
[7] 111.95715 65.04523 58.64954 72.11132
> rowSd(tmp5)
[1] 89.912845 7.778988 8.269914 7.415058 8.388043 8.248933 10.580981
[8] 8.065062 7.658299 8.491839
> rowMax(tmp5)
[1] 469.57805 NA 86.60064 82.78693 86.20550 88.17851 96.87657
[8] 84.75686 87.86089 94.63311
> rowMin(tmp5)
[1] 55.45011 NA 61.36974 57.03832 56.74715 63.30960 54.07706 56.05921
[9] 59.71095 58.62509
>
> colMeans(tmp5)
[1] 112.31894 68.65121 71.61251 73.81668 70.09993 67.37568 75.10406
[8] 71.12574 71.94213 71.07838 75.80191 68.96716 NA 72.52764
[15] 69.23787 73.57367 71.31613 72.89321 70.77911 72.06658
> colSums(tmp5)
[1] 1123.1894 686.5121 716.1251 738.1668 700.9993 673.7568 751.0406
[8] 711.2574 719.4213 710.7838 758.0191 689.6716 NA 725.2764
[15] 692.3787 735.7367 713.1613 728.9321 707.7911 720.6658
> colVars(tmp5)
[1] 15851.77911 126.83678 57.69879 77.55467 117.67431 29.25362
[7] 43.33195 50.61154 84.52969 97.30919 37.85172 37.91076
[13] NA 53.18776 76.43378 66.67704 121.16387 94.49067
[19] 66.03529 57.34038
> colSd(tmp5)
[1] 125.903849 11.262184 7.595972 8.806513 10.847779 5.408662
[7] 6.582701 7.114179 9.194003 9.864542 6.152375 6.157172
[13] NA 7.292994 8.742641 8.165601 11.007446 9.720631
[19] 8.126210 7.572343
> colMax(tmp5)
[1] 469.57805 85.12100 88.17851 88.80604 86.60064 75.14030 85.32782
[8] 79.03358 85.39455 94.63311 84.40255 76.83163 NA 86.20550
[15] 82.43728 85.00304 96.87657 87.93165 84.25811 81.65829
> colMin(tmp5)
[1] 57.05669 53.85356 63.13980 61.88152 54.07706 59.96333 63.62657 58.70743
[9] 57.61242 59.13704 66.18322 57.03832 NA 62.21324 59.56826 61.95905
[17] 58.62509 55.45011 62.41352 56.05921
>
> Max(tmp5,na.rm=TRUE)
[1] 469.5781
> Min(tmp5,na.rm=TRUE)
[1] 53.85356
> mean(tmp5,na.rm=TRUE)
[1] 73.68325
> Sum(tmp5,na.rm=TRUE)
[1] 14662.97
> Var(tmp5,na.rm=TRUE)
[1] 869.1702
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.59740 71.50911 74.88866 70.98140 73.78312 75.98319 70.01681 69.43630
[9] 71.37935 69.14842
> rowSums(tmp5,na.rm=TRUE)
[1] 1791.948 1358.673 1497.773 1419.628 1475.662 1519.664 1400.336 1388.726
[9] 1427.587 1382.968
> rowVars(tmp5,na.rm=TRUE)
[1] 8084.31974 60.51265 68.39148 54.98308 70.35927 68.04489
[7] 111.95715 65.04523 58.64954 72.11132
> rowSd(tmp5,na.rm=TRUE)
[1] 89.912845 7.778988 8.269914 7.415058 8.388043 8.248933 10.580981
[8] 8.065062 7.658299 8.491839
> rowMax(tmp5,na.rm=TRUE)
[1] 469.57805 88.80604 86.60064 82.78693 86.20550 88.17851 96.87657
[8] 84.75686 87.86089 94.63311
> rowMin(tmp5,na.rm=TRUE)
[1] 55.45011 53.85356 61.36974 57.03832 56.74715 63.30960 54.07706 56.05921
[9] 59.71095 58.62509
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.31894 68.65121 71.61251 73.81668 70.09993 67.37568 75.10406
[8] 71.12574 71.94213 71.07838 75.80191 68.96716 73.34225 72.52764
[15] 69.23787 73.57367 71.31613 72.89321 70.77911 72.06658
> colSums(tmp5,na.rm=TRUE)
[1] 1123.1894 686.5121 716.1251 738.1668 700.9993 673.7568 751.0406
[8] 711.2574 719.4213 710.7838 758.0191 689.6716 660.0802 725.2764
[15] 692.3787 735.7367 713.1613 728.9321 707.7911 720.6658
> colVars(tmp5,na.rm=TRUE)
[1] 15851.77911 126.83678 57.69879 77.55467 117.67431 29.25362
[7] 43.33195 50.61154 84.52969 97.30919 37.85172 37.91076
[13] 147.62766 53.18776 76.43378 66.67704 121.16387 94.49067
[19] 66.03529 57.34038
> colSd(tmp5,na.rm=TRUE)
[1] 125.903849 11.262184 7.595972 8.806513 10.847779 5.408662
[7] 6.582701 7.114179 9.194003 9.864542 6.152375 6.157172
[13] 12.150212 7.292994 8.742641 8.165601 11.007446 9.720631
[19] 8.126210 7.572343
> colMax(tmp5,na.rm=TRUE)
[1] 469.57805 85.12100 88.17851 88.80604 86.60064 75.14030 85.32782
[8] 79.03358 85.39455 94.63311 84.40255 76.83163 91.90493 86.20550
[15] 82.43728 85.00304 96.87657 87.93165 84.25811 81.65829
> colMin(tmp5,na.rm=TRUE)
[1] 57.05669 53.85356 63.13980 61.88152 54.07706 59.96333 63.62657 58.70743
[9] 57.61242 59.13704 66.18322 57.03832 58.17411 62.21324 59.56826 61.95905
[17] 58.62509 55.45011 62.41352 56.05921
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.59740 NaN 74.88866 70.98140 73.78312 75.98319 70.01681 69.43630
[9] 71.37935 69.14842
> rowSums(tmp5,na.rm=TRUE)
[1] 1791.948 0.000 1497.773 1419.628 1475.662 1519.664 1400.336 1388.726
[9] 1427.587 1382.968
> rowVars(tmp5,na.rm=TRUE)
[1] 8084.31974 NA 68.39148 54.98308 70.35927 68.04489
[7] 111.95715 65.04523 58.64954 72.11132
> rowSd(tmp5,na.rm=TRUE)
[1] 89.912845 NA 8.269914 7.415058 8.388043 8.248933 10.580981
[8] 8.065062 7.658299 8.491839
> rowMax(tmp5,na.rm=TRUE)
[1] 469.57805 NA 86.60064 82.78693 86.20550 88.17851 96.87657
[8] 84.75686 87.86089 94.63311
> rowMin(tmp5,na.rm=TRUE)
[1] 55.45011 NA 61.36974 57.03832 56.74715 63.30960 54.07706 56.05921
[9] 59.71095 58.62509
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.18590 70.29540 70.67559 72.15120 69.67436 67.46726 75.35991
[8] 71.41181 70.68007 70.71916 75.67787 68.09333 NaN 72.79533
[15] 69.34419 74.86418 71.85763 73.21940 71.16756 72.27237
> colSums(tmp5,na.rm=TRUE)
[1] 1054.6731 632.6586 636.0804 649.3608 627.0692 607.2054 678.2392
[8] 642.7063 636.1206 636.4724 681.1009 612.8400 0.0000 655.1580
[15] 624.0977 673.7777 646.7186 658.9746 640.5080 650.4513
> colVars(tmp5,na.rm=TRUE)
[1] 17566.77018 112.27879 55.03575 56.04335 130.34605 32.81597
[7] 48.01202 56.01732 77.17685 108.02112 42.41010 34.05935
[13] NA 59.03008 85.86084 56.27565 133.01063 105.10503
[19] 72.59221 64.03151
> colSd(tmp5,na.rm=TRUE)
[1] 132.539693 10.596169 7.418608 7.486211 11.416920 5.728522
[7] 6.929070 7.484472 8.785036 10.393321 6.512304 5.836039
[13] NA 7.683103 9.266113 7.501710 11.533023 10.252075
[19] 8.520106 8.001969
> colMax(tmp5,na.rm=TRUE)
[1] 469.57805 85.12100 88.17851 83.77858 86.60064 75.14030 85.32782
[8] 79.03358 85.39455 94.63311 84.40255 74.77328 -Inf 86.20550
[15] 82.43728 85.00304 96.87657 87.93165 84.25811 81.65829
> colMin(tmp5,na.rm=TRUE)
[1] 57.05669 56.74715 63.13980 61.88152 54.07706 59.96333 63.62657 58.70743
[9] 57.61242 59.13704 66.18322 57.03832 Inf 62.21324 59.56826 62.78800
[17] 58.62509 55.45011 62.41352 56.05921
>
>
>
>
> 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] 427.3141 189.8295 213.1093 222.7387 298.1655 448.6719 293.8157 289.4083
[9] 352.5315 180.5018
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 427.3141 189.8295 213.1093 222.7387 298.1655 448.6719 293.8157 289.4083
[9] 352.5315 180.5018
>
>
>
> 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 1.421085e-13 -5.684342e-14 0.000000e+00 0.000000e+00
[6] 5.684342e-14 -1.136868e-13 2.842171e-14 -2.842171e-14 -5.684342e-14
[11] 2.842171e-14 1.421085e-14 -5.684342e-14 -2.842171e-14 -5.684342e-14
[16] -8.526513e-14 -2.842171e-14 5.684342e-14 1.136868e-13 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
9 13
10 20
1 10
10 3
2 10
3 20
3 1
3 15
8 20
1 13
3 17
10 14
6 14
7 1
1 17
8 4
5 15
1 14
8 1
9 1
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] 2.295762
> Min(tmp)
[1] -1.94776
> mean(tmp)
[1] 0.0618912
> Sum(tmp)
[1] 6.18912
> Var(tmp)
[1] 0.9181538
>
> rowMeans(tmp)
[1] 0.0618912
> rowSums(tmp)
[1] 6.18912
> rowVars(tmp)
[1] 0.9181538
> rowSd(tmp)
[1] 0.9582034
> rowMax(tmp)
[1] 2.295762
> rowMin(tmp)
[1] -1.94776
>
> colMeans(tmp)
[1] 0.887563158 0.590753891 -1.601998770 -1.947760295 0.651947451
[6] 0.237578568 1.168884044 1.389150551 1.263743384 -0.186013175
[11] 0.121478856 0.250574298 0.616727085 1.195065792 -0.388301133
[16] 0.115457154 -1.894119578 0.522438245 1.344209757 -1.428272481
[21] 0.220404832 -0.858456660 -1.135395495 2.242944353 -0.314613454
[26] -0.236037614 0.942326109 0.713979026 -1.345150289 -1.757811936
[31] 0.589913292 0.344259167 -0.149858069 1.937928927 -0.042241567
[36] 0.376553915 0.510032778 0.247005146 0.736583820 0.565367480
[41] 1.504850169 1.018111123 -1.466291621 0.452105922 0.508723925
[46] 1.824071313 -1.249873221 -1.140636943 0.493912048 -1.088940895
[51] -0.177408133 0.067435664 0.385972059 1.144465947 -0.305042867
[56] -0.457822800 -0.009359083 -1.090114609 -1.633132176 -1.343828303
[61] 0.654852142 -0.216381317 0.283696189 0.064199668 0.447011895
[66] 0.875462650 -1.250031467 -0.075558614 0.665551291 0.117916397
[71] -1.016939530 -0.245733026 -1.075901695 -0.022733187 -0.056822105
[76] -0.154464996 -0.470756147 -0.670204803 1.648117525 -0.663077230
[81] 0.558267895 0.099073417 -0.196049112 -0.643261447 2.295761946
[86] 0.202959994 -0.357531554 -1.053074792 2.142133142 -0.273022777
[91] 0.965428893 -0.871578654 1.030135383 -0.525899525 -0.817421425
[96] 1.025423780 -0.814176329 -0.429475055 -0.040069697 1.119254155
> colSums(tmp)
[1] 0.887563158 0.590753891 -1.601998770 -1.947760295 0.651947451
[6] 0.237578568 1.168884044 1.389150551 1.263743384 -0.186013175
[11] 0.121478856 0.250574298 0.616727085 1.195065792 -0.388301133
[16] 0.115457154 -1.894119578 0.522438245 1.344209757 -1.428272481
[21] 0.220404832 -0.858456660 -1.135395495 2.242944353 -0.314613454
[26] -0.236037614 0.942326109 0.713979026 -1.345150289 -1.757811936
[31] 0.589913292 0.344259167 -0.149858069 1.937928927 -0.042241567
[36] 0.376553915 0.510032778 0.247005146 0.736583820 0.565367480
[41] 1.504850169 1.018111123 -1.466291621 0.452105922 0.508723925
[46] 1.824071313 -1.249873221 -1.140636943 0.493912048 -1.088940895
[51] -0.177408133 0.067435664 0.385972059 1.144465947 -0.305042867
[56] -0.457822800 -0.009359083 -1.090114609 -1.633132176 -1.343828303
[61] 0.654852142 -0.216381317 0.283696189 0.064199668 0.447011895
[66] 0.875462650 -1.250031467 -0.075558614 0.665551291 0.117916397
[71] -1.016939530 -0.245733026 -1.075901695 -0.022733187 -0.056822105
[76] -0.154464996 -0.470756147 -0.670204803 1.648117525 -0.663077230
[81] 0.558267895 0.099073417 -0.196049112 -0.643261447 2.295761946
[86] 0.202959994 -0.357531554 -1.053074792 2.142133142 -0.273022777
[91] 0.965428893 -0.871578654 1.030135383 -0.525899525 -0.817421425
[96] 1.025423780 -0.814176329 -0.429475055 -0.040069697 1.119254155
> 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] 0.887563158 0.590753891 -1.601998770 -1.947760295 0.651947451
[6] 0.237578568 1.168884044 1.389150551 1.263743384 -0.186013175
[11] 0.121478856 0.250574298 0.616727085 1.195065792 -0.388301133
[16] 0.115457154 -1.894119578 0.522438245 1.344209757 -1.428272481
[21] 0.220404832 -0.858456660 -1.135395495 2.242944353 -0.314613454
[26] -0.236037614 0.942326109 0.713979026 -1.345150289 -1.757811936
[31] 0.589913292 0.344259167 -0.149858069 1.937928927 -0.042241567
[36] 0.376553915 0.510032778 0.247005146 0.736583820 0.565367480
[41] 1.504850169 1.018111123 -1.466291621 0.452105922 0.508723925
[46] 1.824071313 -1.249873221 -1.140636943 0.493912048 -1.088940895
[51] -0.177408133 0.067435664 0.385972059 1.144465947 -0.305042867
[56] -0.457822800 -0.009359083 -1.090114609 -1.633132176 -1.343828303
[61] 0.654852142 -0.216381317 0.283696189 0.064199668 0.447011895
[66] 0.875462650 -1.250031467 -0.075558614 0.665551291 0.117916397
[71] -1.016939530 -0.245733026 -1.075901695 -0.022733187 -0.056822105
[76] -0.154464996 -0.470756147 -0.670204803 1.648117525 -0.663077230
[81] 0.558267895 0.099073417 -0.196049112 -0.643261447 2.295761946
[86] 0.202959994 -0.357531554 -1.053074792 2.142133142 -0.273022777
[91] 0.965428893 -0.871578654 1.030135383 -0.525899525 -0.817421425
[96] 1.025423780 -0.814176329 -0.429475055 -0.040069697 1.119254155
> colMin(tmp)
[1] 0.887563158 0.590753891 -1.601998770 -1.947760295 0.651947451
[6] 0.237578568 1.168884044 1.389150551 1.263743384 -0.186013175
[11] 0.121478856 0.250574298 0.616727085 1.195065792 -0.388301133
[16] 0.115457154 -1.894119578 0.522438245 1.344209757 -1.428272481
[21] 0.220404832 -0.858456660 -1.135395495 2.242944353 -0.314613454
[26] -0.236037614 0.942326109 0.713979026 -1.345150289 -1.757811936
[31] 0.589913292 0.344259167 -0.149858069 1.937928927 -0.042241567
[36] 0.376553915 0.510032778 0.247005146 0.736583820 0.565367480
[41] 1.504850169 1.018111123 -1.466291621 0.452105922 0.508723925
[46] 1.824071313 -1.249873221 -1.140636943 0.493912048 -1.088940895
[51] -0.177408133 0.067435664 0.385972059 1.144465947 -0.305042867
[56] -0.457822800 -0.009359083 -1.090114609 -1.633132176 -1.343828303
[61] 0.654852142 -0.216381317 0.283696189 0.064199668 0.447011895
[66] 0.875462650 -1.250031467 -0.075558614 0.665551291 0.117916397
[71] -1.016939530 -0.245733026 -1.075901695 -0.022733187 -0.056822105
[76] -0.154464996 -0.470756147 -0.670204803 1.648117525 -0.663077230
[81] 0.558267895 0.099073417 -0.196049112 -0.643261447 2.295761946
[86] 0.202959994 -0.357531554 -1.053074792 2.142133142 -0.273022777
[91] 0.965428893 -0.871578654 1.030135383 -0.525899525 -0.817421425
[96] 1.025423780 -0.814176329 -0.429475055 -0.040069697 1.119254155
> colMedians(tmp)
[1] 0.887563158 0.590753891 -1.601998770 -1.947760295 0.651947451
[6] 0.237578568 1.168884044 1.389150551 1.263743384 -0.186013175
[11] 0.121478856 0.250574298 0.616727085 1.195065792 -0.388301133
[16] 0.115457154 -1.894119578 0.522438245 1.344209757 -1.428272481
[21] 0.220404832 -0.858456660 -1.135395495 2.242944353 -0.314613454
[26] -0.236037614 0.942326109 0.713979026 -1.345150289 -1.757811936
[31] 0.589913292 0.344259167 -0.149858069 1.937928927 -0.042241567
[36] 0.376553915 0.510032778 0.247005146 0.736583820 0.565367480
[41] 1.504850169 1.018111123 -1.466291621 0.452105922 0.508723925
[46] 1.824071313 -1.249873221 -1.140636943 0.493912048 -1.088940895
[51] -0.177408133 0.067435664 0.385972059 1.144465947 -0.305042867
[56] -0.457822800 -0.009359083 -1.090114609 -1.633132176 -1.343828303
[61] 0.654852142 -0.216381317 0.283696189 0.064199668 0.447011895
[66] 0.875462650 -1.250031467 -0.075558614 0.665551291 0.117916397
[71] -1.016939530 -0.245733026 -1.075901695 -0.022733187 -0.056822105
[76] -0.154464996 -0.470756147 -0.670204803 1.648117525 -0.663077230
[81] 0.558267895 0.099073417 -0.196049112 -0.643261447 2.295761946
[86] 0.202959994 -0.357531554 -1.053074792 2.142133142 -0.273022777
[91] 0.965428893 -0.871578654 1.030135383 -0.525899525 -0.817421425
[96] 1.025423780 -0.814176329 -0.429475055 -0.040069697 1.119254155
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.8875632 0.5907539 -1.601999 -1.94776 0.6519475 0.2375786 1.168884
[2,] 0.8875632 0.5907539 -1.601999 -1.94776 0.6519475 0.2375786 1.168884
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.389151 1.263743 -0.1860132 0.1214789 0.2505743 0.6167271 1.195066
[2,] 1.389151 1.263743 -0.1860132 0.1214789 0.2505743 0.6167271 1.195066
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.3883011 0.1154572 -1.89412 0.5224382 1.34421 -1.428272 0.2204048
[2,] -0.3883011 0.1154572 -1.89412 0.5224382 1.34421 -1.428272 0.2204048
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.8584567 -1.135395 2.242944 -0.3146135 -0.2360376 0.9423261 0.713979
[2,] -0.8584567 -1.135395 2.242944 -0.3146135 -0.2360376 0.9423261 0.713979
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.34515 -1.757812 0.5899133 0.3442592 -0.1498581 1.937929 -0.04224157
[2,] -1.34515 -1.757812 0.5899133 0.3442592 -0.1498581 1.937929 -0.04224157
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.3765539 0.5100328 0.2470051 0.7365838 0.5653675 1.50485 1.018111
[2,] 0.3765539 0.5100328 0.2470051 0.7365838 0.5653675 1.50485 1.018111
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.466292 0.4521059 0.5087239 1.824071 -1.249873 -1.140637 0.493912
[2,] -1.466292 0.4521059 0.5087239 1.824071 -1.249873 -1.140637 0.493912
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.088941 -0.1774081 0.06743566 0.3859721 1.144466 -0.3050429 -0.4578228
[2,] -1.088941 -0.1774081 0.06743566 0.3859721 1.144466 -0.3050429 -0.4578228
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.009359083 -1.090115 -1.633132 -1.343828 0.6548521 -0.2163813 0.2836962
[2,] -0.009359083 -1.090115 -1.633132 -1.343828 0.6548521 -0.2163813 0.2836962
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.06419967 0.4470119 0.8754626 -1.250031 -0.07555861 0.6655513 0.1179164
[2,] 0.06419967 0.4470119 0.8754626 -1.250031 -0.07555861 0.6655513 0.1179164
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.01694 -0.245733 -1.075902 -0.02273319 -0.05682211 -0.154465 -0.4707561
[2,] -1.01694 -0.245733 -1.075902 -0.02273319 -0.05682211 -0.154465 -0.4707561
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.6702048 1.648118 -0.6630772 0.5582679 0.09907342 -0.1960491 -0.6432614
[2,] -0.6702048 1.648118 -0.6630772 0.5582679 0.09907342 -0.1960491 -0.6432614
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 2.295762 0.20296 -0.3575316 -1.053075 2.142133 -0.2730228 0.9654289
[2,] 2.295762 0.20296 -0.3575316 -1.053075 2.142133 -0.2730228 0.9654289
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.8715787 1.030135 -0.5258995 -0.8174214 1.025424 -0.8141763 -0.4294751
[2,] -0.8715787 1.030135 -0.5258995 -0.8174214 1.025424 -0.8141763 -0.4294751
[,99] [,100]
[1,] -0.0400697 1.119254
[2,] -0.0400697 1.119254
>
>
> Max(tmp2)
[1] 2.175428
> Min(tmp2)
[1] -3.283337
> mean(tmp2)
[1] -0.04574249
> Sum(tmp2)
[1] -4.574249
> Var(tmp2)
[1] 1.03764
>
> rowMeans(tmp2)
[1] -2.098985575 -1.068107304 -0.040522163 -0.962720102 -1.628424094
[6] 0.716731253 1.326324986 -1.795253560 0.160578888 1.316005701
[11] -0.004304676 -0.543550567 -0.970557002 -1.034224769 -1.866277942
[16] 1.691660585 -0.012626182 -0.424164655 -0.340940255 -1.076337492
[21] 1.358000122 0.688324172 0.785653217 1.201145503 -0.535169484
[26] 0.535194968 -0.206800620 0.761806010 0.862604354 0.178437187
[31] 0.269598676 -0.497648762 -0.958529040 0.530507141 2.175428274
[36] -0.920857444 -0.560680618 0.835773840 0.577857976 0.588463130
[41] -0.536340205 1.091406838 1.172851595 -3.283337040 -1.188851636
[46] 0.217540846 -0.173035297 -0.389401801 0.470931404 0.208099640
[51] 1.134903752 0.201947520 -1.081145861 -3.073561638 -0.534398377
[56] 0.799645213 0.385753817 1.349448062 0.512525285 -2.273944471
[61] 1.230148364 -0.007284796 0.655349121 -0.726892885 0.771667055
[66] 0.216932204 0.059530675 -0.010567961 0.681749737 -0.830844744
[71] 0.290014438 0.064788375 -1.524169759 -1.283630790 -0.764343399
[76] -0.266841767 0.709707352 -1.202076957 0.416825006 -0.106058619
[81] 0.751703545 0.064143531 0.671290693 0.430703153 -1.409894276
[86] -0.370744470 -1.566792338 -0.921478381 -0.872250379 1.271436194
[91] 1.499765725 -0.127540972 0.498983200 -0.551211864 0.427554774
[96] 0.813178272 0.271116244 0.952791820 0.606553993 0.587990713
> rowSums(tmp2)
[1] -2.098985575 -1.068107304 -0.040522163 -0.962720102 -1.628424094
[6] 0.716731253 1.326324986 -1.795253560 0.160578888 1.316005701
[11] -0.004304676 -0.543550567 -0.970557002 -1.034224769 -1.866277942
[16] 1.691660585 -0.012626182 -0.424164655 -0.340940255 -1.076337492
[21] 1.358000122 0.688324172 0.785653217 1.201145503 -0.535169484
[26] 0.535194968 -0.206800620 0.761806010 0.862604354 0.178437187
[31] 0.269598676 -0.497648762 -0.958529040 0.530507141 2.175428274
[36] -0.920857444 -0.560680618 0.835773840 0.577857976 0.588463130
[41] -0.536340205 1.091406838 1.172851595 -3.283337040 -1.188851636
[46] 0.217540846 -0.173035297 -0.389401801 0.470931404 0.208099640
[51] 1.134903752 0.201947520 -1.081145861 -3.073561638 -0.534398377
[56] 0.799645213 0.385753817 1.349448062 0.512525285 -2.273944471
[61] 1.230148364 -0.007284796 0.655349121 -0.726892885 0.771667055
[66] 0.216932204 0.059530675 -0.010567961 0.681749737 -0.830844744
[71] 0.290014438 0.064788375 -1.524169759 -1.283630790 -0.764343399
[76] -0.266841767 0.709707352 -1.202076957 0.416825006 -0.106058619
[81] 0.751703545 0.064143531 0.671290693 0.430703153 -1.409894276
[86] -0.370744470 -1.566792338 -0.921478381 -0.872250379 1.271436194
[91] 1.499765725 -0.127540972 0.498983200 -0.551211864 0.427554774
[96] 0.813178272 0.271116244 0.952791820 0.606553993 0.587990713
> 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] -2.098985575 -1.068107304 -0.040522163 -0.962720102 -1.628424094
[6] 0.716731253 1.326324986 -1.795253560 0.160578888 1.316005701
[11] -0.004304676 -0.543550567 -0.970557002 -1.034224769 -1.866277942
[16] 1.691660585 -0.012626182 -0.424164655 -0.340940255 -1.076337492
[21] 1.358000122 0.688324172 0.785653217 1.201145503 -0.535169484
[26] 0.535194968 -0.206800620 0.761806010 0.862604354 0.178437187
[31] 0.269598676 -0.497648762 -0.958529040 0.530507141 2.175428274
[36] -0.920857444 -0.560680618 0.835773840 0.577857976 0.588463130
[41] -0.536340205 1.091406838 1.172851595 -3.283337040 -1.188851636
[46] 0.217540846 -0.173035297 -0.389401801 0.470931404 0.208099640
[51] 1.134903752 0.201947520 -1.081145861 -3.073561638 -0.534398377
[56] 0.799645213 0.385753817 1.349448062 0.512525285 -2.273944471
[61] 1.230148364 -0.007284796 0.655349121 -0.726892885 0.771667055
[66] 0.216932204 0.059530675 -0.010567961 0.681749737 -0.830844744
[71] 0.290014438 0.064788375 -1.524169759 -1.283630790 -0.764343399
[76] -0.266841767 0.709707352 -1.202076957 0.416825006 -0.106058619
[81] 0.751703545 0.064143531 0.671290693 0.430703153 -1.409894276
[86] -0.370744470 -1.566792338 -0.921478381 -0.872250379 1.271436194
[91] 1.499765725 -0.127540972 0.498983200 -0.551211864 0.427554774
[96] 0.813178272 0.271116244 0.952791820 0.606553993 0.587990713
> rowMin(tmp2)
[1] -2.098985575 -1.068107304 -0.040522163 -0.962720102 -1.628424094
[6] 0.716731253 1.326324986 -1.795253560 0.160578888 1.316005701
[11] -0.004304676 -0.543550567 -0.970557002 -1.034224769 -1.866277942
[16] 1.691660585 -0.012626182 -0.424164655 -0.340940255 -1.076337492
[21] 1.358000122 0.688324172 0.785653217 1.201145503 -0.535169484
[26] 0.535194968 -0.206800620 0.761806010 0.862604354 0.178437187
[31] 0.269598676 -0.497648762 -0.958529040 0.530507141 2.175428274
[36] -0.920857444 -0.560680618 0.835773840 0.577857976 0.588463130
[41] -0.536340205 1.091406838 1.172851595 -3.283337040 -1.188851636
[46] 0.217540846 -0.173035297 -0.389401801 0.470931404 0.208099640
[51] 1.134903752 0.201947520 -1.081145861 -3.073561638 -0.534398377
[56] 0.799645213 0.385753817 1.349448062 0.512525285 -2.273944471
[61] 1.230148364 -0.007284796 0.655349121 -0.726892885 0.771667055
[66] 0.216932204 0.059530675 -0.010567961 0.681749737 -0.830844744
[71] 0.290014438 0.064788375 -1.524169759 -1.283630790 -0.764343399
[76] -0.266841767 0.709707352 -1.202076957 0.416825006 -0.106058619
[81] 0.751703545 0.064143531 0.671290693 0.430703153 -1.409894276
[86] -0.370744470 -1.566792338 -0.921478381 -0.872250379 1.271436194
[91] 1.499765725 -0.127540972 0.498983200 -0.551211864 0.427554774
[96] 0.813178272 0.271116244 0.952791820 0.606553993 0.587990713
>
> colMeans(tmp2)
[1] -0.04574249
> colSums(tmp2)
[1] -4.574249
> colVars(tmp2)
[1] 1.03764
> colSd(tmp2)
[1] 1.018646
> colMax(tmp2)
[1] 2.175428
> colMin(tmp2)
[1] -3.283337
> colMedians(tmp2)
[1] 0.1126836
> colRanges(tmp2)
[,1]
[1,] -3.283337
[2,] 2.175428
>
> 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] -0.7953404 -5.1595607 -1.9146883 3.8430364 2.0398629 0.9824971
[7] -2.0726937 3.6871695 3.2842597 2.0560357
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8374553
[2,] -0.5332860
[3,] -0.3746132
[4,] 0.4929790
[5,] 1.1630149
>
> rowApply(tmp,sum)
[1] -3.0581868 -0.2571650 5.0477836 6.7438995 1.5129046 0.8371021
[7] -0.7362609 -2.9497103 3.2103882 -4.4001772
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 9 2 2 10 3 3 3 4 5
[2,] 9 8 1 3 5 4 1 1 5 1
[3,] 7 4 10 9 4 1 4 2 1 2
[4,] 8 6 5 4 8 6 10 7 8 4
[5,] 1 5 6 8 6 7 2 6 7 10
[6,] 4 3 3 5 1 8 9 9 9 7
[7,] 3 1 7 10 3 2 6 5 2 6
[8,] 5 7 8 7 9 9 7 4 3 8
[9,] 6 2 9 6 2 5 5 10 6 9
[10,] 2 10 4 1 7 10 8 8 10 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.48180910 -4.81667847 -0.67223281 0.87077862 -2.70110542 -2.16686242
[7] 3.76310668 1.05920518 0.91179857 0.72325334 -3.19235247 -0.51989608
[13] -1.70000325 2.69166005 -0.39596661 -2.63808303 -0.04398501 -2.71517290
[19] 1.93972738 -1.62950982
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7353198
[2,] 0.8105097
[3,] 0.8253237
[4,] 1.1903927
[5,] 1.3909027
>
> rowApply(tmp,sum)
[1] -3.676263 -1.674311 -2.095886 2.571396 -2.875446
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 19 15 17 19 8
[2,] 7 1 8 4 5
[3,] 16 6 19 3 3
[4,] 15 13 3 16 16
[5,] 6 14 9 8 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.1903927 -0.5104073 0.5463734 0.1842218 -0.8509842 0.9787302
[2,] 0.8253237 -2.1954372 -0.5664957 0.0109391 0.6837936 -0.1379420
[3,] 0.8105097 -0.5423233 1.6177025 -1.2613590 -0.3858783 -1.1461605
[4,] 1.3909027 -0.4820712 -0.5849645 0.7827029 -0.2269004 -0.7741438
[5,] -0.7353198 -1.0864394 -1.6848484 1.1542739 -1.9211361 -1.0873464
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.2555423 -0.09241965 1.4572282 -0.06754947 -0.2074448 -1.6747644
[2,] 1.5120265 1.02701413 -1.8768260 -0.55159671 1.2754507 0.9885411
[3,] 0.3065631 -1.37598897 0.4700447 1.32912045 -3.1540692 -0.3648634
[4,] 0.8766600 0.17784509 -0.4457157 -0.09173967 -0.3159212 1.2469524
[5,] 1.3233994 1.32275458 1.3070674 0.10501874 -0.7903679 -0.7157618
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.27171339 -1.3383569 -0.06204199 -0.1028349 -0.9525541 -1.2380713
[2,] -0.03713625 -0.2532194 -0.31446121 -1.5476085 1.2074896 -0.2123281
[3,] -0.57975384 1.9454100 -0.85328226 0.7118804 -0.8852812 0.2343434
[4,] 0.11662742 0.6466613 0.68618427 -2.4362521 -0.3546082 0.3697789
[5,] -0.92802718 1.6911650 0.14763458 0.7367320 0.9409689 -1.8688958
[,19] [,20]
[1,] 0.6206510 -1.02917573
[2,] -0.6555828 -0.85625547
[3,] 0.6120992 0.41540073
[4,] 2.0703851 -0.08098724
[5,] -0.7078252 -0.07849211
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-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-3.23-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-3.23-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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.1414434 -0.03668644 -0.6631703 -0.8781371 -0.6575889 1.070348 0.8105667
col8 col9 col10 col11 col12 col13 col14
row1 -0.6451805 -0.1500786 -1.32966 1.228899 -1.097517 -0.1150073 -0.5982894
col15 col16 col17 col18 col19 col20
row1 -0.7779463 0.1505606 -0.36367 -0.0007735574 0.8594677 0.9384741
> tmp[,"col10"]
col10
row1 -1.3296603
row2 -0.9452777
row3 1.2941512
row4 1.5519328
row5 0.6537323
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.1414434 -0.03668644 -0.6631703 -0.8781371 -0.6575889 1.070348 0.8105667
row5 -0.2073135 1.62595358 -0.5078929 -0.8765890 1.3779714 1.630242 0.3438737
col8 col9 col10 col11 col12 col13
row1 -0.6451805 -0.1500786 -1.3296603 1.228899 -1.0975167 -0.11500728
row5 1.3820546 1.5340994 0.6537323 0.832618 0.3900217 0.04045676
col14 col15 col16 col17 col18 col19
row1 -0.5982894 -0.7779463 0.1505606 -0.3636700 -0.0007735574 0.8594677
row5 1.0755531 0.0531398 -1.3116895 -0.1299685 0.1907978585 -1.1011129
col20
row1 0.9384741
row5 -0.1135917
> tmp[,c("col6","col20")]
col6 col20
row1 1.07034816 0.9384741
row2 -0.06866435 0.1782038
row3 1.13921448 0.3432260
row4 1.16959100 0.1625075
row5 1.63024203 -0.1135917
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.070348 0.9384741
row5 1.630242 -0.1135917
>
>
>
>
> 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 49.29758 48.06853 48.50363 50.26184 50.92411 104.9512 49.85496 50.52278
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.70786 51.03686 50.02318 48.95533 50.01181 50.10347 49.10393 50.73805
col17 col18 col19 col20
row1 52.23 49.9755 51.02179 104.1276
> tmp[,"col10"]
col10
row1 51.03686
row2 29.74553
row3 31.02269
row4 31.70822
row5 48.76758
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.29758 48.06853 48.50363 50.26184 50.92411 104.9512 49.85496 50.52278
row5 50.89086 51.13716 51.45450 50.73452 51.87993 103.7962 50.84192 49.64186
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.70786 51.03686 50.02318 48.95533 50.01181 50.10347 49.10393 50.73805
row5 51.40102 48.76758 49.32890 50.77327 49.57804 48.90619 50.13634 52.51403
col17 col18 col19 col20
row1 52.23000 49.97550 51.02179 104.1276
row5 49.25244 51.02474 49.41243 104.7720
> tmp[,c("col6","col20")]
col6 col20
row1 104.95120 104.12757
row2 74.58745 74.27166
row3 75.20242 76.17598
row4 73.79944 74.20081
row5 103.79616 104.77196
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9512 104.1276
row5 103.7962 104.7720
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9512 104.1276
row5 103.7962 104.7720
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.9163918
[2,] 0.3848818
[3,] -1.2792379
[4,] 0.4524879
[5,] -0.7779449
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.2631312 1.3952134
[2,] 1.0067402 -2.5666436
[3,] -0.1582003 -0.7297603
[4,] 1.6085967 -0.3898785
[5,] 1.4893619 0.3801547
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.1570986 0.002000001
[2,] 1.0107450 -1.122776960
[3,] -0.2834279 0.371832069
[4,] 1.1354806 -0.030719992
[5,] -1.2719085 1.273516250
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.157099
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.157099
[2,] 1.010745
>
>
>
> 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 -1.03941671 0.9030265 -0.3623237 0.7539948 1.1889639 -1.280824
row1 0.07707688 -0.7702556 0.6072011 -1.5431675 -0.8860479 1.007116
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.8568665 1.5084715 2.6224416 -0.193282 1.4743980 -0.3308464 -1.256157
row1 1.6510066 -0.4891881 -0.4789777 -1.670861 -0.9589315 -1.3485827 1.269623
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -3.1145948 -0.9945917 2.0295458 0.7203296 -0.3369095 -1.786626 -0.5412388
row1 0.7332196 2.7341690 0.5470914 -0.3882503 0.5372170 1.283373 -0.7121104
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.6864069 1.488645 0.2402086 0.1922335 0.3807147 1.483593 -0.2665075
[,8] [,9] [,10]
row2 1.414848 -0.8679486 -0.9543874
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.227172 0.6388331 1.370648 -1.684071 -1.972477 0.8365402 -0.3445972
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.04641846 -0.7938052 -1.593783 0.5108824 1.104322 -0.3286751 -0.3926039
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.7845492 1.446251 -0.05561653 -1.14902 1.038386 -0.1327599
>
>
> 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: 0x5f2d68b72960>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405837d11ff8"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405832e08ece7"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM14058314c3cb68"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM14058335bf6b2"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405836072ca29"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM14058333aa3ba4"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405835d676988"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405833518b41b"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405833146b6eb"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM14058313c0131c"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405835a7072fc"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405831eca331d"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM14058336ba2711"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM14058350325ce5"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1405834da95616"
>
>
> ### 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: 0x5f2d6a0354d0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5f2d6a0354d0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5f2d6a0354d0>
> rowMedians(tmp)
[1] -0.066294746 -0.339110046 0.097846544 -0.337962019 0.406909901
[6] -0.275519130 -0.634058743 0.002752187 -0.405551174 -0.041875848
[11] -0.189680786 0.339977692 0.070516612 0.063505109 -0.089016834
[16] -0.324285922 -0.425221032 0.083708257 -0.377360196 -0.152423965
[21] -0.167527005 -0.016339482 0.118013227 0.293502039 -0.062147529
[26] -0.699503128 0.003156414 -0.364654389 0.280992667 0.124692101
[31] -0.045124622 -0.284639919 0.131719913 -0.060609553 -0.425396698
[36] 0.470796226 -0.419065474 0.760950624 -0.647759186 0.019079700
[41] -0.748654707 0.572019991 0.069483509 -0.741879896 -0.500350230
[46] 0.389926487 -0.235942151 0.326606206 -0.125738909 0.098469497
[51] 0.080261517 -0.444478884 0.545624972 -0.445442426 0.509752486
[56] 0.254812494 -0.195893499 -0.102348537 0.296559672 -0.041578799
[61] 0.042903348 -0.454821997 -0.159222601 -0.162798332 -0.264558066
[66] -0.046357712 -0.301844450 -0.437175452 0.422682798 0.025341186
[71] 0.340250956 -0.144886472 -0.196895554 -0.190480479 -0.357748209
[76] -0.054130762 0.142338516 0.068261546 -0.125661325 -0.106582105
[81] 0.329059044 0.381534526 -0.066793058 0.082559522 -0.025325155
[86] 0.211089661 0.043168114 -0.074288451 -0.159158481 -0.440467077
[91] 0.497923033 0.131087655 0.368317137 0.436881646 0.064453549
[96] 0.531167881 -0.305742509 0.004214069 0.920904294 -0.064572753
[101] -0.273853829 -0.332229592 0.319980272 0.341559492 -0.293513975
[106] 0.252725684 0.025823457 -0.032714400 0.774909396 0.058070081
[111] 0.249575871 -0.104287794 0.214846960 0.324143925 -0.274670337
[116] -0.216146275 0.283906691 -0.175736008 -0.152949784 0.092727633
[121] -0.452263014 -0.491519959 0.010940317 -0.192057993 -0.305296450
[126] -0.259039213 0.748530011 0.069526522 -0.200602675 0.218307196
[131] -0.340901458 -0.271358840 0.086247975 0.447790861 0.404405553
[136] -0.128979248 -0.092613809 0.159344758 0.317968190 -0.030324638
[141] -0.192250468 -0.422188132 0.158186323 0.426541960 0.268773551
[146] -0.515934721 -0.027278271 -0.410452695 -0.467066270 -0.410353607
[151] -0.125421728 -0.009219806 -0.365398294 -0.582690170 0.549120519
[156] 0.143475355 0.054351027 0.066174077 -0.313677027 0.223012713
[161] -0.470600169 0.288693188 0.548849945 0.095852425 -0.418278102
[166] -0.162873804 0.550045497 -0.031404226 0.512131720 -0.009379130
[171] -0.164806000 0.252466293 -0.740154677 0.403763361 0.315604974
[176] -0.371434190 -0.177197062 -0.005608752 -0.084616501 -0.271645229
[181] 0.273369360 0.119280556 -0.384259738 -0.028174320 0.210171394
[186] -0.317091883 0.305689820 0.142322921 -0.634059703 -0.094204466
[191] 0.338516331 -0.147596061 -0.120821052 0.093183731 0.436480466
[196] -0.005091529 0.634065129 0.126208612 0.315359743 -0.334283142
[201] -0.239428786 -0.362613535 0.253949537 0.156871420 -0.650366076
[206] -0.451077513 0.279555437 0.038162370 -0.167086361 -0.126227751
[211] 0.143955454 0.258062178 -0.221534410 0.496841074 -0.077888457
[216] 0.401988723 0.358217398 -0.044883412 -0.240355544 0.105950918
[221] -0.442729800 0.388780969 0.068958103 0.103168807 0.598603228
[226] 0.327650439 0.451615607 0.048202973 -0.243773323 -0.190833905
>
> proc.time()
user system elapsed
1.271 1.383 2.645
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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: 0x60d263f69b20>
> .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: 0x60d263f69b20>
> .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: 0x60d263f69b20>
> .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: 0x60d263f69b20>
> 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: 0x60d263f4a410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d263f4a410>
> .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: 0x60d263f4a410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d263f4a410>
> .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: 0x60d263f4a410>
> 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: 0x60d2627f77a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d2627f77a0>
> .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: 0x60d2627f77a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60d2627f77a0>
> .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: 0x60d2627f77a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60d2627f77a0>
> .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: 0x60d2627f77a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60d2627f77a0>
> .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: 0x60d2627f77a0>
> 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: 0x60d2637c9680>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x60d2637c9680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d2637c9680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d2637c9680>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1406de4f96f438" "BufferedMatrixFile1406def0692c5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1406de4f96f438" "BufferedMatrixFile1406def0692c5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d26355d490>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d26355d490>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60d26355d490>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60d26355d490>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60d26355d490>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60d26355d490>
> .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: 0x60d264bb9110>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60d264bb9110>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60d264bb9110>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x60d264bb9110>
> 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: 0x60d264c5c5e0>
> .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: 0x60d264c5c5e0>
> rm(P)
>
> proc.time()
user system elapsed
0.238 0.047 0.274
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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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.
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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
0.230 0.046 0.263