Ben Bolstad
| Snapshot Date: 2025-12-18 13:40 -0500 (Thu, 18 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 2025-12-19 11:34 -0500 (Fri, 19 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" | 4875 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4593 |
| 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 253/2332 | 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: 2025-12-18 21:29:33 -0500 (Thu, 18 Dec 2025) |
| EndedAt: 2025-12-18 21:29:58 -0500 (Thu, 18 Dec 2025) |
| EllapsedTime: 25.0 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
###
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##############################################################################
* 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 ... 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
0.253 0.041 0.283
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] "Thu Dec 18 21:29:48 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 Dec 18 21:29:48 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: 0x622a5b49e5e0>
>
>
>
> 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 Dec 18 21:29:49 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 Dec 18 21:29:49 2025"
>
> ColMode(tmp2)
<pointer: 0x622a5b49e5e0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.65072165 0.3652890 0.39678996 0.7583086
[2,] -0.08567224 -0.6752806 -0.04862778 0.1142983
[3,] 3.19259466 1.4379727 -1.88714768 -1.0365833
[4,] 0.23048639 0.4869015 0.62630238 0.3593289
> 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,] 99.65072165 0.3652890 0.39678996 0.7583086
[2,] 0.08567224 0.6752806 0.04862778 0.1142983
[3,] 3.19259466 1.4379727 1.88714768 1.0365833
[4,] 0.23048639 0.4869015 0.62630238 0.3593289
> 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,] 9.9825208 0.6043914 0.6299127 0.8708091
[2,] 0.2926982 0.8217546 0.2205171 0.3380803
[3,] 1.7867833 1.1991550 1.3737349 1.0181273
[4,] 0.4800900 0.6977833 0.7913927 0.5994405
>
> 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,] 224.47593 31.40920 31.69592 34.46640
[2,] 28.01265 33.89283 27.25380 28.49510
[3,] 46.06043 38.42952 40.62450 36.21786
[4,] 30.03139 32.46473 33.54023 31.35373
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x622a5b029840>
> exp(tmp5)
<pointer: 0x622a5b029840>
> log(tmp5,2)
<pointer: 0x622a5b029840>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.2172
> Min(tmp5)
[1] 53.23815
> mean(tmp5)
[1] 73.05885
> Sum(tmp5)
[1] 14611.77
> Var(tmp5)
[1] 850.2311
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.65901 67.90883 73.50269 73.98991 71.72612 72.61781 70.00741 68.89792
[9] 69.70839 72.57037
> rowSums(tmp5)
[1] 1793.180 1358.177 1470.054 1479.798 1434.522 1452.356 1400.148 1377.958
[9] 1394.168 1451.407
> rowVars(tmp5)
[1] 7944.48985 64.37099 70.20501 68.90584 44.47482 81.31548
[7] 85.60186 61.48824 101.17383 21.75133
> rowSd(tmp5)
[1] 89.131868 8.023154 8.378843 8.300954 6.668945 9.017510 9.252128
[8] 7.841443 10.058520 4.663833
> rowMax(tmp5)
[1] 467.21724 82.94760 95.86875 89.94879 84.73645 91.94968 86.93971
[8] 87.34585 90.81621 81.69138
> rowMin(tmp5)
[1] 59.14452 56.72521 59.28044 62.50640 61.85288 53.34568 54.51364 54.43725
[9] 53.23815 64.90885
>
> colMeans(tmp5)
[1] 111.80662 70.98276 68.88734 70.99768 70.88720 69.60996 74.21486
[8] 71.37798 72.74218 72.32214 73.59316 68.16312 70.88658 70.47042
[15] 70.95512 71.88115 72.36107 68.94083 68.77251 71.32427
> colSums(tmp5)
[1] 1118.0662 709.8276 688.8734 709.9768 708.8720 696.0996 742.1486
[8] 713.7798 727.4218 723.2214 735.9316 681.6312 708.8658 704.7042
[15] 709.5512 718.8115 723.6107 689.4083 687.7251 713.2427
> colVars(tmp5)
[1] 15746.14533 51.46231 57.36905 76.98065 44.98120 86.32601
[7] 52.08142 79.97333 30.97772 80.39548 53.16742 34.60446
[13] 101.11583 65.71363 36.70960 75.74622 71.51373 82.43419
[19] 92.29941 69.47283
> colSd(tmp5)
[1] 125.483646 7.173724 7.574236 8.773862 6.706803 9.291179
[7] 7.216746 8.942781 5.565763 8.966352 7.291599 5.882556
[13] 10.055637 8.106395 6.058845 8.703230 8.456579 9.079328
[19] 9.607258 8.335036
> colMax(tmp5)
[1] 467.21724 82.76700 84.55457 91.94968 78.86704 84.47317 82.94760
[8] 87.34585 80.55030 86.98241 87.28942 74.34379 90.81621 82.90435
[15] 81.49838 84.52048 89.81194 89.94879 86.93971 84.73645
> colMin(tmp5)
[1] 58.30467 61.04730 56.72521 59.30882 59.14452 53.34568 63.01773 54.51364
[9] 64.86406 57.05430 66.61574 56.49013 56.94441 54.43725 61.57318 58.29998
[17] 57.63407 59.28044 53.23815 54.43293
>
>
> ### 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] 89.65901 67.90883 NA 73.98991 71.72612 72.61781 70.00741 68.89792
[9] 69.70839 72.57037
> rowSums(tmp5)
[1] 1793.180 1358.177 NA 1479.798 1434.522 1452.356 1400.148 1377.958
[9] 1394.168 1451.407
> rowVars(tmp5)
[1] 7944.48985 64.37099 66.96237 68.90584 44.47482 81.31548
[7] 85.60186 61.48824 101.17383 21.75133
> rowSd(tmp5)
[1] 89.131868 8.023154 8.183054 8.300954 6.668945 9.017510 9.252128
[8] 7.841443 10.058520 4.663833
> rowMax(tmp5)
[1] 467.21724 82.94760 NA 89.94879 84.73645 91.94968 86.93971
[8] 87.34585 90.81621 81.69138
> rowMin(tmp5)
[1] 59.14452 56.72521 NA 62.50640 61.85288 53.34568 54.51364 54.43725
[9] 53.23815 64.90885
>
> colMeans(tmp5)
[1] 111.80662 70.98276 NA 70.99768 70.88720 69.60996 74.21486
[8] 71.37798 72.74218 72.32214 73.59316 68.16312 70.88658 70.47042
[15] 70.95512 71.88115 72.36107 68.94083 68.77251 71.32427
> colSums(tmp5)
[1] 1118.0662 709.8276 NA 709.9768 708.8720 696.0996 742.1486
[8] 713.7798 727.4218 723.2214 735.9316 681.6312 708.8658 704.7042
[15] 709.5512 718.8115 723.6107 689.4083 687.7251 713.2427
> colVars(tmp5)
[1] 15746.14533 51.46231 NA 76.98065 44.98120 86.32601
[7] 52.08142 79.97333 30.97772 80.39548 53.16742 34.60446
[13] 101.11583 65.71363 36.70960 75.74622 71.51373 82.43419
[19] 92.29941 69.47283
> colSd(tmp5)
[1] 125.483646 7.173724 NA 8.773862 6.706803 9.291179
[7] 7.216746 8.942781 5.565763 8.966352 7.291599 5.882556
[13] 10.055637 8.106395 6.058845 8.703230 8.456579 9.079328
[19] 9.607258 8.335036
> colMax(tmp5)
[1] 467.21724 82.76700 NA 91.94968 78.86704 84.47317 82.94760
[8] 87.34585 80.55030 86.98241 87.28942 74.34379 90.81621 82.90435
[15] 81.49838 84.52048 89.81194 89.94879 86.93971 84.73645
> colMin(tmp5)
[1] 58.30467 61.04730 NA 59.30882 59.14452 53.34568 63.01773 54.51364
[9] 64.86406 57.05430 66.61574 56.49013 56.94441 54.43725 61.57318 58.29998
[17] 57.63407 59.28044 53.23815 54.43293
>
> Max(tmp5,na.rm=TRUE)
[1] 467.2172
> Min(tmp5,na.rm=TRUE)
[1] 53.23815
> mean(tmp5,na.rm=TRUE)
[1] 73.00108
> Sum(tmp5,na.rm=TRUE)
[1] 14527.21
> Var(tmp5,na.rm=TRUE)
[1] 853.8544
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.65901 67.90883 72.92101 73.98991 71.72612 72.61781 70.00741 68.89792
[9] 69.70839 72.57037
> rowSums(tmp5,na.rm=TRUE)
[1] 1793.180 1358.177 1385.499 1479.798 1434.522 1452.356 1400.148 1377.958
[9] 1394.168 1451.407
> rowVars(tmp5,na.rm=TRUE)
[1] 7944.48985 64.37099 66.96237 68.90584 44.47482 81.31548
[7] 85.60186 61.48824 101.17383 21.75133
> rowSd(tmp5,na.rm=TRUE)
[1] 89.131868 8.023154 8.183054 8.300954 6.668945 9.017510 9.252128
[8] 7.841443 10.058520 4.663833
> rowMax(tmp5,na.rm=TRUE)
[1] 467.21724 82.94760 95.86875 89.94879 84.73645 91.94968 86.93971
[8] 87.34585 90.81621 81.69138
> rowMin(tmp5,na.rm=TRUE)
[1] 59.14452 56.72521 59.28044 62.50640 61.85288 53.34568 54.51364 54.43725
[9] 53.23815 64.90885
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.80662 70.98276 67.14653 70.99768 70.88720 69.60996 74.21486
[8] 71.37798 72.74218 72.32214 73.59316 68.16312 70.88658 70.47042
[15] 70.95512 71.88115 72.36107 68.94083 68.77251 71.32427
> colSums(tmp5,na.rm=TRUE)
[1] 1118.0662 709.8276 604.3188 709.9768 708.8720 696.0996 742.1486
[8] 713.7798 727.4218 723.2214 735.9316 681.6312 708.8658 704.7042
[15] 709.5512 718.8115 723.6107 689.4083 687.7251 713.2427
> colVars(tmp5,na.rm=TRUE)
[1] 15746.14533 51.46231 30.44821 76.98065 44.98120 86.32601
[7] 52.08142 79.97333 30.97772 80.39548 53.16742 34.60446
[13] 101.11583 65.71363 36.70960 75.74622 71.51373 82.43419
[19] 92.29941 69.47283
> colSd(tmp5,na.rm=TRUE)
[1] 125.483646 7.173724 5.517990 8.773862 6.706803 9.291179
[7] 7.216746 8.942781 5.565763 8.966352 7.291599 5.882556
[13] 10.055637 8.106395 6.058845 8.703230 8.456579 9.079328
[19] 9.607258 8.335036
> colMax(tmp5,na.rm=TRUE)
[1] 467.21724 82.76700 76.20750 91.94968 78.86704 84.47317 82.94760
[8] 87.34585 80.55030 86.98241 87.28942 74.34379 90.81621 82.90435
[15] 81.49838 84.52048 89.81194 89.94879 86.93971 84.73645
> colMin(tmp5,na.rm=TRUE)
[1] 58.30467 61.04730 56.72521 59.30882 59.14452 53.34568 63.01773 54.51364
[9] 64.86406 57.05430 66.61574 56.49013 56.94441 54.43725 61.57318 58.29998
[17] 57.63407 59.28044 53.23815 54.43293
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.65901 67.90883 NaN 73.98991 71.72612 72.61781 70.00741 68.89792
[9] 69.70839 72.57037
> rowSums(tmp5,na.rm=TRUE)
[1] 1793.180 1358.177 0.000 1479.798 1434.522 1452.356 1400.148 1377.958
[9] 1394.168 1451.407
> rowVars(tmp5,na.rm=TRUE)
[1] 7944.48985 64.37099 NA 68.90584 44.47482 81.31548
[7] 85.60186 61.48824 101.17383 21.75133
> rowSd(tmp5,na.rm=TRUE)
[1] 89.131868 8.023154 NA 8.300954 6.668945 9.017510 9.252128
[8] 7.841443 10.058520 4.663833
> rowMax(tmp5,na.rm=TRUE)
[1] 467.21724 82.94760 NA 89.94879 84.73645 91.94968 86.93971
[8] 87.34585 90.81621 81.69138
> rowMin(tmp5,na.rm=TRUE)
[1] 59.14452 56.72521 NA 62.50640 61.85288 53.34568 54.51364 54.43725
[9] 53.23815 64.90885
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.57749 69.98240 NaN 70.51045 70.62744 68.72587 73.50504
[8] 71.97030 72.09745 71.50628 74.21884 67.94737 70.64828 70.62097
[15] 71.00397 72.36836 72.82996 70.01421 69.54599 71.34340
> colSums(tmp5,na.rm=TRUE)
[1] 1022.1974 629.8416 0.0000 634.5941 635.6470 618.5328 661.5454
[8] 647.7327 648.8770 643.5565 667.9696 611.5264 635.8345 635.5887
[15] 639.0357 651.3153 655.4696 630.1279 625.9139 642.0906
> colVars(tmp5,na.rm=TRUE)
[1] 17679.13354 46.63695 NA 83.93260 49.84478 88.32365
[7] 52.92336 86.02314 30.17360 82.95665 55.40919 38.40640
[13] 113.11646 73.67286 41.27146 82.54401 77.97961 79.77691
[19] 97.10621 78.15281
> colSd(tmp5,na.rm=TRUE)
[1] 132.962903 6.829125 NA 9.161473 7.060084 9.398066
[7] 7.274844 9.274866 5.493050 9.108054 7.443735 6.197290
[13] 10.635622 8.583290 6.424286 9.085373 8.830606 8.931792
[19] 9.854248 8.840408
> colMax(tmp5,na.rm=TRUE)
[1] 467.21724 82.76700 -Inf 91.94968 78.86704 84.47317 82.94760
[8] 87.34585 80.55030 86.98241 87.28942 74.34379 90.81621 82.90435
[15] 81.49838 84.52048 89.81194 89.94879 86.93971 84.73645
> colMin(tmp5,na.rm=TRUE)
[1] 58.30467 61.04730 Inf 59.30882 59.14452 53.34568 63.01773 54.51364
[9] 64.86406 57.05430 66.61574 56.49013 56.94441 54.43725 61.57318 58.29998
[17] 57.63407 61.65520 53.23815 54.43293
>
>
>
>
> 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] 271.0209 136.5900 163.6457 244.4746 182.7457 177.5426 145.3379 124.0244
[9] 313.3827 245.6494
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 271.0209 136.5900 163.6457 244.4746 182.7457 177.5426 145.3379 124.0244
[9] 313.3827 245.6494
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 2.842171e-14 -5.684342e-14 8.526513e-14 -2.842171e-14 -1.136868e-13
[6] -8.526513e-14 -1.421085e-13 2.273737e-13 2.842171e-14 5.684342e-14
[11] 5.684342e-14 5.684342e-14 1.136868e-13 0.000000e+00 -4.263256e-14
[16] 8.526513e-14 4.973799e-14 5.684342e-14 -2.273737e-13 1.847411e-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)
+ }
10 10
2 17
6 6
3 19
8 15
1 20
2 18
9 1
2 16
9 3
4 12
6 7
9 13
5 13
2 4
7 3
6 8
9 6
6 5
3 4
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.257079
> Min(tmp)
[1] -2.388025
> mean(tmp)
[1] 0.2740158
> Sum(tmp)
[1] 27.40158
> Var(tmp)
[1] 0.9063356
>
> rowMeans(tmp)
[1] 0.2740158
> rowSums(tmp)
[1] 27.40158
> rowVars(tmp)
[1] 0.9063356
> rowSd(tmp)
[1] 0.9520166
> rowMax(tmp)
[1] 2.257079
> rowMin(tmp)
[1] -2.388025
>
> colMeans(tmp)
[1] 0.310031092 -0.666951333 -0.619955656 -0.349968389 1.590758540
[6] -0.263884602 1.195025832 1.588469108 1.528196472 1.292413507
[11] -0.789446089 0.050577400 -0.042047407 0.837681210 0.759402455
[16] -1.075069084 1.299980473 1.604662643 -0.708724391 1.442982609
[21] 1.228018104 1.411646199 -0.329588445 0.075497343 0.353306490
[26] 0.302198760 -0.847559156 0.363935890 -0.130883528 -0.014667672
[31] 1.659144331 2.257078622 0.143019037 0.638479097 0.769373482
[36] 0.012739488 1.248828343 0.549185886 -0.063306441 0.882452525
[41] 1.347825039 0.198512749 0.184581268 1.716850431 -0.548376261
[46] -0.750170959 1.346090071 -0.092553315 -0.304460091 1.029488185
[51] 0.873209962 1.826177913 1.257961146 -0.520851964 -1.217276335
[56] 1.265451731 -0.794232162 0.996665816 0.124812895 0.096076225
[61] -0.212560985 -0.795843504 -0.230682144 1.139373693 -0.109543885
[66] -0.651390541 0.081583257 -0.506673869 0.805620818 0.553940616
[71] 0.188415449 -0.025571725 -0.596395723 1.329292262 -0.587450251
[76] -0.896562880 -0.105889586 -1.096938024 -0.251972306 -1.502468158
[81] -0.848783800 -0.379153331 -0.257362927 -1.223053305 0.703640996
[86] -0.703965670 2.046996649 -2.388024604 -0.856881839 1.797680666
[91] -0.617142159 -0.170057551 0.940518601 1.798022871 1.630236316
[96] 0.349212456 -0.003133453 -0.213488756 -0.449890389 2.189114896
> colSums(tmp)
[1] 0.310031092 -0.666951333 -0.619955656 -0.349968389 1.590758540
[6] -0.263884602 1.195025832 1.588469108 1.528196472 1.292413507
[11] -0.789446089 0.050577400 -0.042047407 0.837681210 0.759402455
[16] -1.075069084 1.299980473 1.604662643 -0.708724391 1.442982609
[21] 1.228018104 1.411646199 -0.329588445 0.075497343 0.353306490
[26] 0.302198760 -0.847559156 0.363935890 -0.130883528 -0.014667672
[31] 1.659144331 2.257078622 0.143019037 0.638479097 0.769373482
[36] 0.012739488 1.248828343 0.549185886 -0.063306441 0.882452525
[41] 1.347825039 0.198512749 0.184581268 1.716850431 -0.548376261
[46] -0.750170959 1.346090071 -0.092553315 -0.304460091 1.029488185
[51] 0.873209962 1.826177913 1.257961146 -0.520851964 -1.217276335
[56] 1.265451731 -0.794232162 0.996665816 0.124812895 0.096076225
[61] -0.212560985 -0.795843504 -0.230682144 1.139373693 -0.109543885
[66] -0.651390541 0.081583257 -0.506673869 0.805620818 0.553940616
[71] 0.188415449 -0.025571725 -0.596395723 1.329292262 -0.587450251
[76] -0.896562880 -0.105889586 -1.096938024 -0.251972306 -1.502468158
[81] -0.848783800 -0.379153331 -0.257362927 -1.223053305 0.703640996
[86] -0.703965670 2.046996649 -2.388024604 -0.856881839 1.797680666
[91] -0.617142159 -0.170057551 0.940518601 1.798022871 1.630236316
[96] 0.349212456 -0.003133453 -0.213488756 -0.449890389 2.189114896
> 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] 0.310031092 -0.666951333 -0.619955656 -0.349968389 1.590758540
[6] -0.263884602 1.195025832 1.588469108 1.528196472 1.292413507
[11] -0.789446089 0.050577400 -0.042047407 0.837681210 0.759402455
[16] -1.075069084 1.299980473 1.604662643 -0.708724391 1.442982609
[21] 1.228018104 1.411646199 -0.329588445 0.075497343 0.353306490
[26] 0.302198760 -0.847559156 0.363935890 -0.130883528 -0.014667672
[31] 1.659144331 2.257078622 0.143019037 0.638479097 0.769373482
[36] 0.012739488 1.248828343 0.549185886 -0.063306441 0.882452525
[41] 1.347825039 0.198512749 0.184581268 1.716850431 -0.548376261
[46] -0.750170959 1.346090071 -0.092553315 -0.304460091 1.029488185
[51] 0.873209962 1.826177913 1.257961146 -0.520851964 -1.217276335
[56] 1.265451731 -0.794232162 0.996665816 0.124812895 0.096076225
[61] -0.212560985 -0.795843504 -0.230682144 1.139373693 -0.109543885
[66] -0.651390541 0.081583257 -0.506673869 0.805620818 0.553940616
[71] 0.188415449 -0.025571725 -0.596395723 1.329292262 -0.587450251
[76] -0.896562880 -0.105889586 -1.096938024 -0.251972306 -1.502468158
[81] -0.848783800 -0.379153331 -0.257362927 -1.223053305 0.703640996
[86] -0.703965670 2.046996649 -2.388024604 -0.856881839 1.797680666
[91] -0.617142159 -0.170057551 0.940518601 1.798022871 1.630236316
[96] 0.349212456 -0.003133453 -0.213488756 -0.449890389 2.189114896
> colMin(tmp)
[1] 0.310031092 -0.666951333 -0.619955656 -0.349968389 1.590758540
[6] -0.263884602 1.195025832 1.588469108 1.528196472 1.292413507
[11] -0.789446089 0.050577400 -0.042047407 0.837681210 0.759402455
[16] -1.075069084 1.299980473 1.604662643 -0.708724391 1.442982609
[21] 1.228018104 1.411646199 -0.329588445 0.075497343 0.353306490
[26] 0.302198760 -0.847559156 0.363935890 -0.130883528 -0.014667672
[31] 1.659144331 2.257078622 0.143019037 0.638479097 0.769373482
[36] 0.012739488 1.248828343 0.549185886 -0.063306441 0.882452525
[41] 1.347825039 0.198512749 0.184581268 1.716850431 -0.548376261
[46] -0.750170959 1.346090071 -0.092553315 -0.304460091 1.029488185
[51] 0.873209962 1.826177913 1.257961146 -0.520851964 -1.217276335
[56] 1.265451731 -0.794232162 0.996665816 0.124812895 0.096076225
[61] -0.212560985 -0.795843504 -0.230682144 1.139373693 -0.109543885
[66] -0.651390541 0.081583257 -0.506673869 0.805620818 0.553940616
[71] 0.188415449 -0.025571725 -0.596395723 1.329292262 -0.587450251
[76] -0.896562880 -0.105889586 -1.096938024 -0.251972306 -1.502468158
[81] -0.848783800 -0.379153331 -0.257362927 -1.223053305 0.703640996
[86] -0.703965670 2.046996649 -2.388024604 -0.856881839 1.797680666
[91] -0.617142159 -0.170057551 0.940518601 1.798022871 1.630236316
[96] 0.349212456 -0.003133453 -0.213488756 -0.449890389 2.189114896
> colMedians(tmp)
[1] 0.310031092 -0.666951333 -0.619955656 -0.349968389 1.590758540
[6] -0.263884602 1.195025832 1.588469108 1.528196472 1.292413507
[11] -0.789446089 0.050577400 -0.042047407 0.837681210 0.759402455
[16] -1.075069084 1.299980473 1.604662643 -0.708724391 1.442982609
[21] 1.228018104 1.411646199 -0.329588445 0.075497343 0.353306490
[26] 0.302198760 -0.847559156 0.363935890 -0.130883528 -0.014667672
[31] 1.659144331 2.257078622 0.143019037 0.638479097 0.769373482
[36] 0.012739488 1.248828343 0.549185886 -0.063306441 0.882452525
[41] 1.347825039 0.198512749 0.184581268 1.716850431 -0.548376261
[46] -0.750170959 1.346090071 -0.092553315 -0.304460091 1.029488185
[51] 0.873209962 1.826177913 1.257961146 -0.520851964 -1.217276335
[56] 1.265451731 -0.794232162 0.996665816 0.124812895 0.096076225
[61] -0.212560985 -0.795843504 -0.230682144 1.139373693 -0.109543885
[66] -0.651390541 0.081583257 -0.506673869 0.805620818 0.553940616
[71] 0.188415449 -0.025571725 -0.596395723 1.329292262 -0.587450251
[76] -0.896562880 -0.105889586 -1.096938024 -0.251972306 -1.502468158
[81] -0.848783800 -0.379153331 -0.257362927 -1.223053305 0.703640996
[86] -0.703965670 2.046996649 -2.388024604 -0.856881839 1.797680666
[91] -0.617142159 -0.170057551 0.940518601 1.798022871 1.630236316
[96] 0.349212456 -0.003133453 -0.213488756 -0.449890389 2.189114896
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3100311 -0.6669513 -0.6199557 -0.3499684 1.590759 -0.2638846 1.195026
[2,] 0.3100311 -0.6669513 -0.6199557 -0.3499684 1.590759 -0.2638846 1.195026
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.588469 1.528196 1.292414 -0.7894461 0.0505774 -0.04204741 0.8376812
[2,] 1.588469 1.528196 1.292414 -0.7894461 0.0505774 -0.04204741 0.8376812
[,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] 0.7594025 -1.075069 1.29998 1.604663 -0.7087244 1.442983 1.228018 1.411646
[2,] 0.7594025 -1.075069 1.29998 1.604663 -0.7087244 1.442983 1.228018 1.411646
[,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] -0.3295884 0.07549734 0.3533065 0.3021988 -0.8475592 0.3639359 -0.1308835
[2,] -0.3295884 0.07549734 0.3533065 0.3021988 -0.8475592 0.3639359 -0.1308835
[,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] -0.01466767 1.659144 2.257079 0.143019 0.6384791 0.7693735 0.01273949
[2,] -0.01466767 1.659144 2.257079 0.143019 0.6384791 0.7693735 0.01273949
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 1.248828 0.5491859 -0.06330644 0.8824525 1.347825 0.1985127 0.1845813
[2,] 1.248828 0.5491859 -0.06330644 0.8824525 1.347825 0.1985127 0.1845813
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] 1.71685 -0.5483763 -0.750171 1.34609 -0.09255331 -0.3044601 1.029488
[2,] 1.71685 -0.5483763 -0.750171 1.34609 -0.09255331 -0.3044601 1.029488
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] 0.87321 1.826178 1.257961 -0.520852 -1.217276 1.265452 -0.7942322
[2,] 0.87321 1.826178 1.257961 -0.520852 -1.217276 1.265452 -0.7942322
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] 0.9966658 0.1248129 0.09607623 -0.212561 -0.7958435 -0.2306821 1.139374
[2,] 0.9966658 0.1248129 0.09607623 -0.212561 -0.7958435 -0.2306821 1.139374
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] -0.1095439 -0.6513905 0.08158326 -0.5066739 0.8056208 0.5539406 0.1884154
[2,] -0.1095439 -0.6513905 0.08158326 -0.5066739 0.8056208 0.5539406 0.1884154
[,72] [,73] [,74] [,75] [,76] [,77] [,78]
[1,] -0.02557173 -0.5963957 1.329292 -0.5874503 -0.8965629 -0.1058896 -1.096938
[2,] -0.02557173 -0.5963957 1.329292 -0.5874503 -0.8965629 -0.1058896 -1.096938
[,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] -0.2519723 -1.502468 -0.8487838 -0.3791533 -0.2573629 -1.223053 0.703641
[2,] -0.2519723 -1.502468 -0.8487838 -0.3791533 -0.2573629 -1.223053 0.703641
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] -0.7039657 2.046997 -2.388025 -0.8568818 1.797681 -0.6171422 -0.1700576
[2,] -0.7039657 2.046997 -2.388025 -0.8568818 1.797681 -0.6171422 -0.1700576
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] 0.9405186 1.798023 1.630236 0.3492125 -0.003133453 -0.2134888 -0.4498904
[2,] 0.9405186 1.798023 1.630236 0.3492125 -0.003133453 -0.2134888 -0.4498904
[,100]
[1,] 2.189115
[2,] 2.189115
>
>
> Max(tmp2)
[1] 3.463903
> Min(tmp2)
[1] -2.09679
> mean(tmp2)
[1] -0.08867641
> Sum(tmp2)
[1] -8.867641
> Var(tmp2)
[1] 1.132553
>
> rowMeans(tmp2)
[1] 0.15284802 0.33751840 -0.12550555 0.09561372 -1.52507200 -0.09366461
[7] 0.98936416 -1.19274466 -1.09982224 -2.09679039 0.77302973 -0.88278359
[13] 0.11791004 -0.66376675 -0.74909904 -0.06941809 0.24013679 -2.02849765
[19] 0.05864279 2.36818542 0.68725252 -0.57689556 0.63529265 -1.35838024
[25] 0.35971339 3.15044032 -1.25776843 -0.47077291 -0.41232408 -0.18314751
[31] 0.52976516 -2.08894163 -0.68633490 -0.68700749 -0.79761373 -0.87682781
[37] -0.02936396 -0.41492807 -0.57199041 -0.43430468 1.99235097 -0.54915321
[43] 0.65937377 2.72281646 0.09688348 0.68409907 0.16309055 1.58658710
[49] -0.55676158 -0.20702700 1.05352701 1.11184819 -0.54357635 0.82327609
[55] -1.10540934 -0.88052153 0.31504283 -0.04631992 0.80032439 -0.36692231
[61] -0.96770357 -0.21931310 0.03678372 0.08204767 -0.22397044 1.16809039
[67] -0.92968927 0.04568202 -0.18112761 -0.56609534 -2.09297809 -0.60033653
[73] -0.55353497 -1.75542932 0.86329466 -0.98825182 0.52740351 0.30393785
[79] -0.79189150 3.46390284 -0.47857042 -1.51455319 -0.85154423 -0.43369120
[85] 0.96698819 0.51202693 1.83433184 0.96405591 0.16610332 -0.24094783
[91] -0.63460855 1.23693292 -0.95365899 -1.31554649 1.22911322 -1.46700589
[97] -0.13770975 -1.19986617 0.50476908 -0.55055698
> rowSums(tmp2)
[1] 0.15284802 0.33751840 -0.12550555 0.09561372 -1.52507200 -0.09366461
[7] 0.98936416 -1.19274466 -1.09982224 -2.09679039 0.77302973 -0.88278359
[13] 0.11791004 -0.66376675 -0.74909904 -0.06941809 0.24013679 -2.02849765
[19] 0.05864279 2.36818542 0.68725252 -0.57689556 0.63529265 -1.35838024
[25] 0.35971339 3.15044032 -1.25776843 -0.47077291 -0.41232408 -0.18314751
[31] 0.52976516 -2.08894163 -0.68633490 -0.68700749 -0.79761373 -0.87682781
[37] -0.02936396 -0.41492807 -0.57199041 -0.43430468 1.99235097 -0.54915321
[43] 0.65937377 2.72281646 0.09688348 0.68409907 0.16309055 1.58658710
[49] -0.55676158 -0.20702700 1.05352701 1.11184819 -0.54357635 0.82327609
[55] -1.10540934 -0.88052153 0.31504283 -0.04631992 0.80032439 -0.36692231
[61] -0.96770357 -0.21931310 0.03678372 0.08204767 -0.22397044 1.16809039
[67] -0.92968927 0.04568202 -0.18112761 -0.56609534 -2.09297809 -0.60033653
[73] -0.55353497 -1.75542932 0.86329466 -0.98825182 0.52740351 0.30393785
[79] -0.79189150 3.46390284 -0.47857042 -1.51455319 -0.85154423 -0.43369120
[85] 0.96698819 0.51202693 1.83433184 0.96405591 0.16610332 -0.24094783
[91] -0.63460855 1.23693292 -0.95365899 -1.31554649 1.22911322 -1.46700589
[97] -0.13770975 -1.19986617 0.50476908 -0.55055698
> 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] 0.15284802 0.33751840 -0.12550555 0.09561372 -1.52507200 -0.09366461
[7] 0.98936416 -1.19274466 -1.09982224 -2.09679039 0.77302973 -0.88278359
[13] 0.11791004 -0.66376675 -0.74909904 -0.06941809 0.24013679 -2.02849765
[19] 0.05864279 2.36818542 0.68725252 -0.57689556 0.63529265 -1.35838024
[25] 0.35971339 3.15044032 -1.25776843 -0.47077291 -0.41232408 -0.18314751
[31] 0.52976516 -2.08894163 -0.68633490 -0.68700749 -0.79761373 -0.87682781
[37] -0.02936396 -0.41492807 -0.57199041 -0.43430468 1.99235097 -0.54915321
[43] 0.65937377 2.72281646 0.09688348 0.68409907 0.16309055 1.58658710
[49] -0.55676158 -0.20702700 1.05352701 1.11184819 -0.54357635 0.82327609
[55] -1.10540934 -0.88052153 0.31504283 -0.04631992 0.80032439 -0.36692231
[61] -0.96770357 -0.21931310 0.03678372 0.08204767 -0.22397044 1.16809039
[67] -0.92968927 0.04568202 -0.18112761 -0.56609534 -2.09297809 -0.60033653
[73] -0.55353497 -1.75542932 0.86329466 -0.98825182 0.52740351 0.30393785
[79] -0.79189150 3.46390284 -0.47857042 -1.51455319 -0.85154423 -0.43369120
[85] 0.96698819 0.51202693 1.83433184 0.96405591 0.16610332 -0.24094783
[91] -0.63460855 1.23693292 -0.95365899 -1.31554649 1.22911322 -1.46700589
[97] -0.13770975 -1.19986617 0.50476908 -0.55055698
> rowMin(tmp2)
[1] 0.15284802 0.33751840 -0.12550555 0.09561372 -1.52507200 -0.09366461
[7] 0.98936416 -1.19274466 -1.09982224 -2.09679039 0.77302973 -0.88278359
[13] 0.11791004 -0.66376675 -0.74909904 -0.06941809 0.24013679 -2.02849765
[19] 0.05864279 2.36818542 0.68725252 -0.57689556 0.63529265 -1.35838024
[25] 0.35971339 3.15044032 -1.25776843 -0.47077291 -0.41232408 -0.18314751
[31] 0.52976516 -2.08894163 -0.68633490 -0.68700749 -0.79761373 -0.87682781
[37] -0.02936396 -0.41492807 -0.57199041 -0.43430468 1.99235097 -0.54915321
[43] 0.65937377 2.72281646 0.09688348 0.68409907 0.16309055 1.58658710
[49] -0.55676158 -0.20702700 1.05352701 1.11184819 -0.54357635 0.82327609
[55] -1.10540934 -0.88052153 0.31504283 -0.04631992 0.80032439 -0.36692231
[61] -0.96770357 -0.21931310 0.03678372 0.08204767 -0.22397044 1.16809039
[67] -0.92968927 0.04568202 -0.18112761 -0.56609534 -2.09297809 -0.60033653
[73] -0.55353497 -1.75542932 0.86329466 -0.98825182 0.52740351 0.30393785
[79] -0.79189150 3.46390284 -0.47857042 -1.51455319 -0.85154423 -0.43369120
[85] 0.96698819 0.51202693 1.83433184 0.96405591 0.16610332 -0.24094783
[91] -0.63460855 1.23693292 -0.95365899 -1.31554649 1.22911322 -1.46700589
[97] -0.13770975 -1.19986617 0.50476908 -0.55055698
>
> colMeans(tmp2)
[1] -0.08867641
> colSums(tmp2)
[1] -8.867641
> colVars(tmp2)
[1] 1.132553
> colSd(tmp2)
[1] 1.064215
> colMax(tmp2)
[1] 3.463903
> colMin(tmp2)
[1] -2.09679
> colMedians(tmp2)
[1] -0.1950873
> colRanges(tmp2)
[,1]
[1,] -2.096790
[2,] 3.463903
>
> 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] 0.2214069 2.6954545 6.2642849 3.9479466 -0.8287750 -3.4399040
[7] -0.8552084 -1.0331956 -1.4321793 -4.0578517
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3327337
[2,] -0.5845336
[3,] 0.1004869
[4,] 0.6769875
[5,] 1.3782887
>
> rowApply(tmp,sum)
[1] -1.82113328 2.76598888 0.98365145 -0.52397657 1.08421630 -2.01610947
[7] 0.07411327 1.14391452 1.10445879 -1.31314486
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 8 6 3 8 7 9 1 8 5
[2,] 10 4 10 8 4 6 8 4 9 6
[3,] 6 10 7 10 7 2 7 3 3 9
[4,] 8 6 3 7 10 10 2 6 10 2
[5,] 4 7 1 4 9 9 1 5 7 7
[6,] 5 1 4 6 3 3 6 10 2 4
[7,] 9 5 2 1 5 1 5 7 6 10
[8,] 2 9 9 5 6 4 4 8 5 3
[9,] 3 2 5 9 2 8 10 9 1 1
[10,] 7 3 8 2 1 5 3 2 4 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.6489466 -1.4603399 -2.7730250 1.4752166 -2.5337610 1.1591447
[7] 0.6696855 0.7021324 -1.6446078 -0.0085474 0.3193015 0.6571275
[13] -0.1953682 2.3430406 0.5912405 2.8215018 -2.9906051 -0.6532125
[19] 3.4426740 -2.5341373
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.1738251
[2,] 0.1094063
[3,] 0.3325728
[4,] 0.9918320
[5,] 1.3889607
>
> rowApply(tmp,sum)
[1] 4.1437293 5.4252282 -1.5982926 -0.9967706 -4.9374867
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 8 16 11 14 20
[2,] 6 14 4 3 12
[3,] 14 2 12 1 4
[4,] 9 17 13 8 10
[5,] 1 11 7 12 6
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1738251 -0.3767754 0.7679343 -0.02811315 -1.5103982 0.9566959
[2,] 1.3889607 1.1137246 -1.4994592 1.40138443 0.3467380 1.5269132
[3,] 0.1094063 -1.0611519 0.2553999 0.36105405 -0.5780087 -0.8411176
[4,] 0.3325728 -1.2720379 -1.4178288 -0.28402880 -0.1275444 1.6023623
[5,] 0.9918320 0.1359008 -0.8790711 0.02492006 -0.6645477 -2.0857091
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.1612114 0.9812253 -1.07436958 0.2296351 -0.8990791 0.9290272
[2,] 1.8168806 0.5858289 -0.08705121 0.6425134 1.2306966 -0.3220679
[3,] 0.5460500 -0.5754412 -1.86009788 -0.9065625 -0.4118858 -1.5036787
[4,] -0.6317621 1.1386940 1.15219530 -0.9282844 0.9540368 1.3705985
[5,] 0.0997285 -1.4281746 0.22471555 0.9541509 -0.5544670 0.1832484
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.56331895 1.5546947 0.33104369 1.8333660 0.3979095 -0.3305886
[2,] -0.02980051 -0.2264378 0.04416805 -0.4977852 -2.9198080 -1.2987963
[3,] -0.01728097 -1.2587294 0.73532817 2.2741787 0.5023804 0.8301627
[4,] 0.03593808 1.3261002 -1.23035521 -0.2640108 -0.1948154 -0.2734250
[5,] 0.37909418 0.9474129 0.71105580 -0.5242469 -0.7762715 0.4194347
[,19] [,20]
[1,] 2.3012823 -0.02140518
[2,] 1.9626014 0.24602449
[3,] 1.2465323 0.55516967
[4,] -1.4117157 -0.87345991
[5,] -0.6560262 -2.44046632
>
>
> 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 : 653 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 -2.311659 -0.335495 0.09283585 -1.815897 -0.1931759 -0.8077127 -0.4606314
col8 col9 col10 col11 col12 col13 col14
row1 -2.171529 -0.2631767 0.02724195 -0.2837446 0.4769765 -0.615386 0.1376329
col15 col16 col17 col18 col19 col20
row1 -0.9133729 1.240194 0.8368631 -1.077174 -0.5734245 -0.2498644
> tmp[,"col10"]
col10
row1 0.02724195
row2 -0.08440750
row3 0.05950070
row4 0.22970198
row5 0.96294547
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -2.3116593 -0.335495 0.09283585 -1.815897 -0.1931759 -0.8077127
row5 -0.3450312 0.984365 -0.03681031 1.722528 0.9463209 -1.0810595
col7 col8 col9 col10 col11 col12
row1 -0.4606314 -2.1715290 -0.2631767 0.02724195 -0.2837446 0.4769765
row5 -0.3777690 0.6984258 -0.1277039 0.96294547 1.4189545 1.4885585
col13 col14 col15 col16 col17 col18 col19
row1 -0.6153860 0.1376329 -0.9133729 1.2401945 0.8368631 -1.077174 -0.5734245
row5 0.7116104 1.3518729 0.1796379 -0.1715397 -1.9842253 -1.092318 0.6786082
col20
row1 -0.2498644
row5 -0.2512467
> tmp[,c("col6","col20")]
col6 col20
row1 -0.8077127 -0.2498644
row2 0.5468776 -0.8417646
row3 0.7416699 2.2870489
row4 -0.9751919 1.2652637
row5 -1.0810595 -0.2512467
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.8077127 -0.2498644
row5 -1.0810595 -0.2512467
>
>
>
>
> 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 49.92333 51.00966 51.46569 47.98092 49.69801 104.9324 50.37772 49.67265
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.37122 50.59614 49.50986 51.65959 49.26073 50.82206 49.79906 51.47118
col17 col18 col19 col20
row1 51.26675 50.91692 47.54382 106.4785
> tmp[,"col10"]
col10
row1 50.59614
row2 27.42500
row3 29.95575
row4 29.42943
row5 50.03756
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.92333 51.00966 51.46569 47.98092 49.69801 104.9324 50.37772 49.67265
row5 48.76970 48.97835 50.76167 49.83723 50.58793 104.9918 48.96338 50.52598
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.37122 50.59614 49.50986 51.65959 49.26073 50.82206 49.79906 51.47118
row5 49.62943 50.03756 50.55988 51.11079 48.00829 49.77676 49.36306 48.90732
col17 col18 col19 col20
row1 51.26675 50.91692 47.54382 106.4785
row5 50.14668 52.38236 49.76001 105.1224
> tmp[,c("col6","col20")]
col6 col20
row1 104.93244 106.47851
row2 75.18925 74.31148
row3 73.52258 75.49868
row4 74.96397 74.91370
row5 104.99184 105.12241
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9324 106.4785
row5 104.9918 105.1224
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9324 106.4785
row5 104.9918 105.1224
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.61464625
[2,] 0.75908976
[3,] 0.49108124
[4,] -0.03074334
[5,] 1.17762862
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.09374732 -0.95579223
[2,] -0.81655083 1.38728820
[3,] -0.57970759 -1.05994333
[4,] 1.48147182 -0.05907501
[5,] 1.64657458 0.45731219
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.2857574 -2.6091026
[2,] 0.7258365 -0.8819032
[3,] 0.8332350 0.3907582
[4,] -0.7497180 -0.2252303
[5,] 0.3222156 -0.3621574
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2857574
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2857574
[2,] 0.7258365
>
>
>
> 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 -1.0228236 -1.9229633 -1.0029962 -1.8112315 -0.4598106 -0.4098779
row1 -0.3588993 -0.6237908 0.1092309 0.4154351 0.1468775 1.0557996
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.2823926 1.285204 1.3279299 0.0673348 0.1829306 0.1974493 0.6808382
row1 -0.4795901 -1.464311 -0.4895617 1.9289059 0.6282398 0.2582166 1.5622703
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 2.1148397 -0.1180293 -1.2830384 -0.02784826 1.811780 0.7100430 1.14933757
row1 0.5926047 -1.3879413 -0.2960245 -0.81892958 1.818839 0.9458595 0.09932169
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.371584 -0.7333335 0.07408451 -1.614412 1.517493 0.2251056 -0.6458895
[,8] [,9] [,10]
row2 -1.256709 -0.7629564 -0.8274805
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1449652 -0.1365755 -0.2888116 -0.9542493 1.608527 0.2308421 -0.4816925
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7690891 0.1070344 -3.853905 -0.3070939 1.521166 0.1191197 0.02682055
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.7674011 0.9959915 0.2209925 0.7705701 0.2413142 -1.070913
>
>
> 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: 0x622a5c120eb0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe45a962dcd"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe466812407"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe45d0bfef2"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe44eb66c61"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe46ab52fd6"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe46366af20"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe41dc8f8af"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe4264bf9dd"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe4471a537b"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe47c5caa8f"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe41de3d982"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe41b49f32c"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe432e1c2a"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe444d5da61"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM285fe4651ba74c"
>
>
> ### 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: 0x622a5c42d440>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x622a5c42d440>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x622a5c42d440>
> rowMedians(tmp)
[1] -0.336884296 0.111695037 -0.266761996 0.041634257 0.060004766
[6] -0.711079918 0.406977853 -0.415110283 0.186956274 0.243795631
[11] -0.087834789 0.582485387 0.413613416 0.325926084 0.468458603
[16] -0.412271863 -0.300399354 -0.115487667 -0.387501550 -0.041226562
[21] 0.166199720 0.396217546 0.342298553 -0.507300703 -0.038827007
[26] 0.101947031 0.012966283 0.559161828 0.284504265 0.445915595
[31] 0.065146743 -0.139397557 0.194111123 0.075278520 -0.120840760
[36] -0.158649384 0.208723084 0.032754249 0.112351355 -0.207243356
[41] 0.306450706 0.351654359 -0.157326577 0.157307890 0.035000560
[46] 0.011641895 0.241968328 0.243487868 0.111586671 0.495048794
[51] -0.130404257 0.340622442 0.068946309 0.296244779 -0.159655185
[56] 0.471480379 0.181261212 0.019594729 -0.222785184 0.059853926
[61] -0.317639181 0.355413373 -0.066495144 -0.587057281 0.116347054
[66] -0.033810883 0.157933073 -0.132553383 0.291942737 -0.302386420
[71] -0.362728866 0.373356407 0.368428307 0.378699479 0.061173300
[76] -0.264568661 -0.469411483 0.146365338 -0.121837048 -0.001277223
[81] 0.467038326 0.138888460 -0.466887419 -0.493182633 -0.253212159
[86] -0.308874950 -0.042154868 0.636181933 -0.035067265 0.123048697
[91] -0.479966130 0.370748111 -0.179912824 0.305801552 0.460930023
[96] 0.539008885 0.298735494 -0.219306648 -0.106854846 -0.028750272
[101] 0.238811127 -0.076360493 -0.090342635 -0.131034993 0.232443468
[106] 0.015366385 -0.387502761 0.240199193 -0.103792131 0.218292224
[111] 0.426146463 0.226217831 -0.162691669 0.807445013 -0.015480057
[116] -0.231792552 0.126178086 -0.353819223 0.075373183 0.197596583
[121] -0.266317764 0.395138217 0.357385026 0.766909322 -0.222548409
[126] 0.713927535 0.206271046 0.231694746 -0.076874009 -0.303590432
[131] 0.294931812 0.319595677 0.248732470 0.131201574 -0.386725094
[136] 0.388489455 0.450228552 -0.108236197 -0.618675504 0.064861255
[141] 0.011242528 0.022329896 -0.179449150 -0.135433442 0.208461316
[146] 0.178579976 -0.003701889 -0.337463722 0.283667699 -0.115698592
[151] 0.300096438 -0.327598189 0.185599310 -0.103935832 -0.042968963
[156] 0.229160938 -0.145569692 -0.102707631 -0.547005996 -0.431140325
[161] -0.592475471 -0.040785204 -0.480690572 -0.315475067 0.013372331
[166] -0.114473725 -0.716745053 0.445485453 -0.252700876 -0.722785198
[171] -0.045983735 0.425511901 -0.089606475 -0.373608904 -0.063050043
[176] -0.114964461 0.252313920 -0.050852830 -0.087043159 -0.133690832
[181] 0.461309770 0.299208470 -0.169698419 0.213433434 -0.331830436
[186] 0.078313479 -0.188880180 -0.078852069 0.272781906 -0.014848157
[191] -0.212074924 0.138425091 0.085958752 0.013941747 0.456383363
[196] 0.026136491 -0.498941149 0.235625332 0.190003972 0.341976851
[201] 0.617721830 0.176719702 0.123908733 -0.186678955 0.250855371
[206] -0.147491145 -0.128972089 0.332129625 -0.645376690 0.326860879
[211] 0.556729681 -0.410334210 -0.278642551 0.072442493 0.323578851
[216] -0.274953474 0.265276329 0.366432065 0.128217100 -0.535709444
[221] -0.532648892 -0.487719732 0.411571268 0.410815374 -0.266145545
[226] -0.109326152 0.627358111 0.085585582 -0.030660092 0.480374699
>
> proc.time()
user system elapsed
1.307 1.485 2.781
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: 0x632fcb9eab20>
> .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: 0x632fcb9eab20>
> .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: 0x632fcb9eab20>
> .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: 0x632fcb9eab20>
> 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: 0x632fcb9cb410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fcb9cb410>
> .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: 0x632fcb9cb410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fcb9cb410>
> .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: 0x632fcb9cb410>
> 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: 0x632fca2787a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fca2787a0>
> .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: 0x632fca2787a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x632fca2787a0>
> .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: 0x632fca2787a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x632fca2787a0>
> .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: 0x632fca2787a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x632fca2787a0>
> .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: 0x632fca2787a0>
> 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: 0x632fcb24a680>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x632fcb24a680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fcb24a680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fcb24a680>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2860c326b3bb5b" "BufferedMatrixFile2860c360d5da56"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2860c326b3bb5b" "BufferedMatrixFile2860c360d5da56"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fcafde490>
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fcafde490>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x632fcafde490>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x632fcafde490>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x632fcafde490>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x632fcafde490>
> .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: 0x632fcc63a110>
> .Call("R_bm_AddColumn",P)
<pointer: 0x632fcc63a110>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x632fcc63a110>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x632fcc63a110>
> 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: 0x632fcc6dd5e0>
> .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: 0x632fcc6dd5e0>
> rm(P)
>
> proc.time()
user system elapsed
0.252 0.052 0.291
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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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
0.240 0.043 0.272