Ben Bolstad
| Snapshot Date: 2025-11-27 13:40 -0500 (Thu, 27 Nov 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 2025-11-28 11:37 -0500 (Fri, 28 Nov 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" | 4866 |
| lconway | macOS 12.7.6 Monterey | x86_64 | R Under development (unstable) (2025-10-21 r88958) -- "Unsuffered Consequences" | 4614 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4571 |
| 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 252/2328 | 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 | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | 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: 2025-11-27 21:37:12 -0500 (Thu, 27 Nov 2025) |
| EndedAt: 2025-11-27 21:37:38 -0500 (Thu, 27 Nov 2025) |
| EllapsedTime: 26.1 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 ... 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
0.234 0.053 0.278
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 Nov 27 21:37:28 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 Nov 27 21:37:28 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: 0x62a642ba85e0>
>
>
>
> 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 Nov 27 21:37:29 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 Nov 27 21:37:29 2025"
>
> ColMode(tmp2)
<pointer: 0x62a642ba85e0>
>
>
>
> ### 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,] 99.8243894 -0.5863820 -1.131318 -0.6800489
[2,] -0.6271226 -0.5740558 -1.243773 0.5067654
[3,] 2.1797038 0.6493782 1.606845 -0.3552754
[4,] -0.9821561 -0.1853928 -0.377986 0.9651585
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8243894 0.5863820 1.131318 0.6800489
[2,] 0.6271226 0.5740558 1.243773 0.5067654
[3,] 2.1797038 0.6493782 1.606845 0.3552754
[4,] 0.9821561 0.1853928 0.377986 0.9651585
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9912156 0.7657558 1.0636341 0.8246508
[2,] 0.7919107 0.7576647 1.1152458 0.7118746
[3,] 1.4763820 0.8058401 1.2676138 0.5960498
[4,] 0.9910379 0.4305726 0.6148056 0.9824248
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.73655 33.24394 36.76766 33.92656
[2,] 33.54623 33.15070 37.39623 32.62551
[3,] 41.94352 33.70778 39.28298 31.31577
[4,] 35.89254 29.49112 31.52604 35.78941
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x62a642598350>
> exp(tmp5)
<pointer: 0x62a642598350>
> log(tmp5,2)
<pointer: 0x62a642598350>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.7597
> Min(tmp5)
[1] 53.65379
> mean(tmp5)
[1] 72.953
> Sum(tmp5)
[1] 14590.6
> Var(tmp5)
[1] 857.425
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.96605 69.84392 73.89592 71.46575 72.47024 71.93902 71.75609 69.59354
[9] 68.27349 69.32594
> rowSums(tmp5)
[1] 1819.321 1396.878 1477.918 1429.315 1449.405 1438.780 1435.122 1391.871
[9] 1365.470 1386.519
> rowVars(tmp5)
[1] 7908.10141 53.12986 65.44291 48.31523 93.63250 68.79208
[7] 113.03668 75.55151 69.41040 78.38552
> rowSd(tmp5)
[1] 88.927506 7.289023 8.089679 6.950916 9.676389 8.294099 10.631871
[8] 8.692037 8.331290 8.853560
> rowMax(tmp5)
[1] 467.75967 82.16509 90.47039 87.88295 89.92215 89.55437 87.10428
[8] 90.61447 86.98680 83.42906
> rowMin(tmp5)
[1] 58.43347 53.67305 62.58650 60.18889 53.65379 60.12927 54.78274 55.34893
[9] 53.72663 54.15804
>
> colMeans(tmp5)
[1] 111.96892 64.58540 69.42656 68.16474 72.31176 69.80738 71.79100
[8] 72.82428 69.29235 72.61869 71.46192 65.33287 70.43432 77.73299
[15] 73.36038 71.32893 71.45278 72.10232 71.34572 71.71662
> colSums(tmp5)
[1] 1119.6892 645.8540 694.2656 681.6474 723.1176 698.0738 717.9100
[8] 728.2428 692.9235 726.1869 714.6192 653.3287 704.3432 777.3299
[15] 733.6038 713.2893 714.5278 721.0232 713.4572 717.1662
> colVars(tmp5)
[1] 15707.38974 24.54820 68.13327 68.31634 66.40473 74.26026
[7] 143.33328 101.17208 99.84611 23.80057 73.20815 46.80730
[13] 34.72318 98.26268 64.49161 46.87985 104.84966 89.23895
[19] 29.90297 46.18514
> colSd(tmp5)
[1] 125.329126 4.954614 8.254288 8.265370 8.148910 8.617439
[7] 11.972188 10.058433 9.992302 4.878583 8.556176 6.841586
[13] 5.892638 9.912753 8.030667 6.846886 10.239612 9.446637
[19] 5.468361 6.795965
> colMax(tmp5)
[1] 467.75967 70.15833 81.76238 82.05671 84.88132 83.18077 90.47039
[8] 90.61447 83.25118 79.87233 84.47620 72.03802 78.20405 89.55437
[15] 85.33474 79.41332 85.53943 89.92215 80.78651 84.73825
> colMin(tmp5)
[1] 58.21543 54.78274 54.97482 53.72663 60.18889 57.52710 54.15804 58.06151
[9] 53.67305 64.17291 59.21628 54.41589 61.63993 59.81854 59.17414 57.95731
[17] 53.65379 60.47712 63.51626 63.72456
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.96605 69.84392 73.89592 NA 72.47024 71.93902 71.75609 69.59354
[9] 68.27349 69.32594
> rowSums(tmp5)
[1] 1819.321 1396.878 1477.918 NA 1449.405 1438.780 1435.122 1391.871
[9] 1365.470 1386.519
> rowVars(tmp5)
[1] 7908.10141 53.12986 65.44291 49.47808 93.63250 68.79208
[7] 113.03668 75.55151 69.41040 78.38552
> rowSd(tmp5)
[1] 88.927506 7.289023 8.089679 7.034065 9.676389 8.294099 10.631871
[8] 8.692037 8.331290 8.853560
> rowMax(tmp5)
[1] 467.75967 82.16509 90.47039 NA 89.92215 89.55437 87.10428
[8] 90.61447 86.98680 83.42906
> rowMin(tmp5)
[1] 58.43347 53.67305 62.58650 NA 53.65379 60.12927 54.78274 55.34893
[9] 53.72663 54.15804
>
> colMeans(tmp5)
[1] 111.96892 64.58540 69.42656 68.16474 72.31176 69.80738 71.79100
[8] 72.82428 69.29235 72.61869 71.46192 65.33287 70.43432 77.73299
[15] 73.36038 71.32893 71.45278 72.10232 71.34572 NA
> colSums(tmp5)
[1] 1119.6892 645.8540 694.2656 681.6474 723.1176 698.0738 717.9100
[8] 728.2428 692.9235 726.1869 714.6192 653.3287 704.3432 777.3299
[15] 733.6038 713.2893 714.5278 721.0232 713.4572 NA
> colVars(tmp5)
[1] 15707.38974 24.54820 68.13327 68.31634 66.40473 74.26026
[7] 143.33328 101.17208 99.84611 23.80057 73.20815 46.80730
[13] 34.72318 98.26268 64.49161 46.87985 104.84966 89.23895
[19] 29.90297 NA
> colSd(tmp5)
[1] 125.329126 4.954614 8.254288 8.265370 8.148910 8.617439
[7] 11.972188 10.058433 9.992302 4.878583 8.556176 6.841586
[13] 5.892638 9.912753 8.030667 6.846886 10.239612 9.446637
[19] 5.468361 NA
> colMax(tmp5)
[1] 467.75967 70.15833 81.76238 82.05671 84.88132 83.18077 90.47039
[8] 90.61447 83.25118 79.87233 84.47620 72.03802 78.20405 89.55437
[15] 85.33474 79.41332 85.53943 89.92215 80.78651 NA
> colMin(tmp5)
[1] 58.21543 54.78274 54.97482 53.72663 60.18889 57.52710 54.15804 58.06151
[9] 53.67305 64.17291 59.21628 54.41589 61.63993 59.81854 59.17414 57.95731
[17] 53.65379 60.47712 63.51626 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 467.7597
> Min(tmp5,na.rm=TRUE)
[1] 53.65379
> mean(tmp5,na.rm=TRUE)
[1] 72.9861
> Sum(tmp5,na.rm=TRUE)
[1] 14524.23
> Var(tmp5,na.rm=TRUE)
[1] 861.5351
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.96605 69.84392 73.89592 71.73420 72.47024 71.93902 71.75609 69.59354
[9] 68.27349 69.32594
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.321 1396.878 1477.918 1362.950 1449.405 1438.780 1435.122 1391.871
[9] 1365.470 1386.519
> rowVars(tmp5,na.rm=TRUE)
[1] 7908.10141 53.12986 65.44291 49.47808 93.63250 68.79208
[7] 113.03668 75.55151 69.41040 78.38552
> rowSd(tmp5,na.rm=TRUE)
[1] 88.927506 7.289023 8.089679 7.034065 9.676389 8.294099 10.631871
[8] 8.692037 8.331290 8.853560
> rowMax(tmp5,na.rm=TRUE)
[1] 467.75967 82.16509 90.47039 87.88295 89.92215 89.55437 87.10428
[8] 90.61447 86.98680 83.42906
> rowMin(tmp5,na.rm=TRUE)
[1] 58.43347 53.67305 62.58650 60.18889 53.65379 60.12927 54.78274 55.34893
[9] 53.72663 54.15804
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.96892 64.58540 69.42656 68.16474 72.31176 69.80738 71.79100
[8] 72.82428 69.29235 72.61869 71.46192 65.33287 70.43432 77.73299
[15] 73.36038 71.32893 71.45278 72.10232 71.34572 72.31122
> colSums(tmp5,na.rm=TRUE)
[1] 1119.6892 645.8540 694.2656 681.6474 723.1176 698.0738 717.9100
[8] 728.2428 692.9235 726.1869 714.6192 653.3287 704.3432 777.3299
[15] 733.6038 713.2893 714.5278 721.0232 713.4572 650.8009
> colVars(tmp5,na.rm=TRUE)
[1] 15707.38974 24.54820 68.13327 68.31634 66.40473 74.26026
[7] 143.33328 101.17208 99.84611 23.80057 73.20815 46.80730
[13] 34.72318 98.26268 64.49161 46.87985 104.84966 89.23895
[19] 29.90297 47.98095
> colSd(tmp5,na.rm=TRUE)
[1] 125.329126 4.954614 8.254288 8.265370 8.148910 8.617439
[7] 11.972188 10.058433 9.992302 4.878583 8.556176 6.841586
[13] 5.892638 9.912753 8.030667 6.846886 10.239612 9.446637
[19] 5.468361 6.926829
> colMax(tmp5,na.rm=TRUE)
[1] 467.75967 70.15833 81.76238 82.05671 84.88132 83.18077 90.47039
[8] 90.61447 83.25118 79.87233 84.47620 72.03802 78.20405 89.55437
[15] 85.33474 79.41332 85.53943 89.92215 80.78651 84.73825
> colMin(tmp5,na.rm=TRUE)
[1] 58.21543 54.78274 54.97482 53.72663 60.18889 57.52710 54.15804 58.06151
[9] 53.67305 64.17291 59.21628 54.41589 61.63993 59.81854 59.17414 57.95731
[17] 53.65379 60.47712 63.51626 63.72456
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.96605 69.84392 73.89592 NaN 72.47024 71.93902 71.75609 69.59354
[9] 68.27349 69.32594
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.321 1396.878 1477.918 0.000 1449.405 1438.780 1435.122 1391.871
[9] 1365.470 1386.519
> rowVars(tmp5,na.rm=TRUE)
[1] 7908.10141 53.12986 65.44291 NA 93.63250 68.79208
[7] 113.03668 75.55151 69.41040 78.38552
> rowSd(tmp5,na.rm=TRUE)
[1] 88.927506 7.289023 8.089679 NA 9.676389 8.294099 10.631871
[8] 8.692037 8.331290 8.853560
> rowMax(tmp5,na.rm=TRUE)
[1] 467.75967 82.16509 90.47039 NA 89.92215 89.55437 87.10428
[8] 90.61447 86.98680 83.42906
> rowMin(tmp5,na.rm=TRUE)
[1] 58.43347 53.67305 62.58650 NA 53.65379 60.12927 54.78274 55.34893
[9] 53.72663 54.15804
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.10929 64.94134 69.84981 67.46183 73.65874 68.32145 71.75622
[8] 72.89974 69.24269 72.81283 71.94574 64.68393 71.07323 76.60522
[15] 72.35558 71.21200 71.30430 72.53814 71.28161 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1044.9836 584.4721 628.6483 607.1565 662.9287 614.8930 645.8060
[8] 656.0977 623.1842 655.3155 647.5117 582.1553 639.6591 689.4470
[15] 651.2002 640.9080 641.7387 652.8433 641.5345 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17477.95868 26.19139 74.63461 71.29740 54.29365 58.70284
[7] 161.23634 113.75452 112.29913 26.35164 79.72572 47.92051
[13] 34.47126 96.23696 61.19477 52.58602 117.70787 98.25695
[19] 33.59459 NA
> colSd(tmp5,na.rm=TRUE)
[1] 132.204231 5.117752 8.639133 8.443779 7.368423 7.661778
[7] 12.697887 10.665576 10.597128 5.133385 8.928926 6.922464
[13] 5.871223 9.810044 7.822709 7.251622 10.849326 9.912464
[19] 5.796084 NA
> colMax(tmp5,na.rm=TRUE)
[1] 467.75967 70.15833 81.76238 82.05671 84.88132 78.76307 90.47039
[8] 90.61447 83.25118 79.87233 84.47620 72.03802 78.20405 89.55437
[15] 85.33474 79.41332 85.53943 89.92215 80.78651 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 58.21543 54.78274 54.97482 53.72663 60.28243 57.52710 54.15804 58.06151
[9] 53.67305 64.17291 59.21628 54.41589 61.63993 59.81854 59.17414 57.95731
[17] 53.65379 60.47712 63.51626 Inf
>
>
>
>
> 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] 341.3316 280.8435 190.1269 304.5005 215.9170 224.1879 305.2817 172.1005
[9] 326.8515 134.4684
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 341.3316 280.8435 190.1269 304.5005 215.9170 224.1879 305.2817 172.1005
[9] 326.8515 134.4684
>
>
>
> 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 -5.684342e-14 -1.705303e-13
[6] -1.705303e-13 1.136868e-13 1.705303e-13 1.705303e-13 -2.842171e-14
[11] -5.684342e-14 -5.684342e-14 5.684342e-14 0.000000e+00 -7.815970e-14
[16] 2.273737e-13 2.842171e-14 1.705303e-13 1.136868e-13 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 5
3 10
7 20
7 9
2 20
3 1
3 5
4 8
5 5
6 4
3 9
10 19
6 1
9 7
3 8
8 7
5 19
6 10
9 19
2 13
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 1.957701
> Min(tmp)
[1] -1.908905
> mean(tmp)
[1] 0.007822814
> Sum(tmp)
[1] 0.7822814
> Var(tmp)
[1] 0.8771336
>
> rowMeans(tmp)
[1] 0.007822814
> rowSums(tmp)
[1] 0.7822814
> rowVars(tmp)
[1] 0.8771336
> rowSd(tmp)
[1] 0.9365541
> rowMax(tmp)
[1] 1.957701
> rowMin(tmp)
[1] -1.908905
>
> colMeans(tmp)
[1] -1.384205753 -0.011244814 0.613420192 -0.932065507 1.439366742
[6] -0.205137626 -0.424286381 -1.192448879 0.987500953 0.214839012
[11] -1.249382335 -0.455229819 0.057268575 1.106406333 -1.128547914
[16] 0.424996656 0.234188824 -0.508923359 -0.395501347 -0.419411251
[21] -0.443725218 -1.256962936 -1.437286381 1.018688932 0.188764097
[26] -1.144094403 1.951799306 0.437292041 -1.832540962 -0.344707602
[31] -0.337044778 -0.737590070 -0.361202015 -0.980051392 -0.459781456
[36] 0.881583640 0.081677395 0.796266780 -0.009631682 0.944901811
[41] -0.011829940 -0.322797855 -0.148947933 -0.405154591 0.807167626
[46] 0.584827946 -1.734820903 0.716021144 -1.084074876 -0.343583371
[51] 1.391090513 1.168374931 -0.137766807 0.761266789 1.260597801
[56] -0.029266728 -0.845198940 -1.039464127 -0.135461077 0.931875414
[61] 0.137728542 0.812399537 1.585195155 0.039263066 1.554436429
[66] 0.328555933 1.624615302 0.276395516 -1.908904768 0.231159275
[71] 0.603614531 -0.630294085 -0.525299516 -1.602288295 0.954288128
[76] 0.533620096 1.957700961 -0.658486173 -0.088661289 -0.739597969
[81] 1.429032358 1.661679641 1.101539934 -0.840855768 -1.514713238
[86] -0.741003427 -0.404315139 -0.234145214 1.341713682 1.462098626
[91] 1.219774258 0.735640612 -0.537606618 -1.282100638 -0.303114083
[96] -0.262213156 -0.984129309 0.082019588 -0.986049441 0.242775957
> colSums(tmp)
[1] -1.384205753 -0.011244814 0.613420192 -0.932065507 1.439366742
[6] -0.205137626 -0.424286381 -1.192448879 0.987500953 0.214839012
[11] -1.249382335 -0.455229819 0.057268575 1.106406333 -1.128547914
[16] 0.424996656 0.234188824 -0.508923359 -0.395501347 -0.419411251
[21] -0.443725218 -1.256962936 -1.437286381 1.018688932 0.188764097
[26] -1.144094403 1.951799306 0.437292041 -1.832540962 -0.344707602
[31] -0.337044778 -0.737590070 -0.361202015 -0.980051392 -0.459781456
[36] 0.881583640 0.081677395 0.796266780 -0.009631682 0.944901811
[41] -0.011829940 -0.322797855 -0.148947933 -0.405154591 0.807167626
[46] 0.584827946 -1.734820903 0.716021144 -1.084074876 -0.343583371
[51] 1.391090513 1.168374931 -0.137766807 0.761266789 1.260597801
[56] -0.029266728 -0.845198940 -1.039464127 -0.135461077 0.931875414
[61] 0.137728542 0.812399537 1.585195155 0.039263066 1.554436429
[66] 0.328555933 1.624615302 0.276395516 -1.908904768 0.231159275
[71] 0.603614531 -0.630294085 -0.525299516 -1.602288295 0.954288128
[76] 0.533620096 1.957700961 -0.658486173 -0.088661289 -0.739597969
[81] 1.429032358 1.661679641 1.101539934 -0.840855768 -1.514713238
[86] -0.741003427 -0.404315139 -0.234145214 1.341713682 1.462098626
[91] 1.219774258 0.735640612 -0.537606618 -1.282100638 -0.303114083
[96] -0.262213156 -0.984129309 0.082019588 -0.986049441 0.242775957
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.384205753 -0.011244814 0.613420192 -0.932065507 1.439366742
[6] -0.205137626 -0.424286381 -1.192448879 0.987500953 0.214839012
[11] -1.249382335 -0.455229819 0.057268575 1.106406333 -1.128547914
[16] 0.424996656 0.234188824 -0.508923359 -0.395501347 -0.419411251
[21] -0.443725218 -1.256962936 -1.437286381 1.018688932 0.188764097
[26] -1.144094403 1.951799306 0.437292041 -1.832540962 -0.344707602
[31] -0.337044778 -0.737590070 -0.361202015 -0.980051392 -0.459781456
[36] 0.881583640 0.081677395 0.796266780 -0.009631682 0.944901811
[41] -0.011829940 -0.322797855 -0.148947933 -0.405154591 0.807167626
[46] 0.584827946 -1.734820903 0.716021144 -1.084074876 -0.343583371
[51] 1.391090513 1.168374931 -0.137766807 0.761266789 1.260597801
[56] -0.029266728 -0.845198940 -1.039464127 -0.135461077 0.931875414
[61] 0.137728542 0.812399537 1.585195155 0.039263066 1.554436429
[66] 0.328555933 1.624615302 0.276395516 -1.908904768 0.231159275
[71] 0.603614531 -0.630294085 -0.525299516 -1.602288295 0.954288128
[76] 0.533620096 1.957700961 -0.658486173 -0.088661289 -0.739597969
[81] 1.429032358 1.661679641 1.101539934 -0.840855768 -1.514713238
[86] -0.741003427 -0.404315139 -0.234145214 1.341713682 1.462098626
[91] 1.219774258 0.735640612 -0.537606618 -1.282100638 -0.303114083
[96] -0.262213156 -0.984129309 0.082019588 -0.986049441 0.242775957
> colMin(tmp)
[1] -1.384205753 -0.011244814 0.613420192 -0.932065507 1.439366742
[6] -0.205137626 -0.424286381 -1.192448879 0.987500953 0.214839012
[11] -1.249382335 -0.455229819 0.057268575 1.106406333 -1.128547914
[16] 0.424996656 0.234188824 -0.508923359 -0.395501347 -0.419411251
[21] -0.443725218 -1.256962936 -1.437286381 1.018688932 0.188764097
[26] -1.144094403 1.951799306 0.437292041 -1.832540962 -0.344707602
[31] -0.337044778 -0.737590070 -0.361202015 -0.980051392 -0.459781456
[36] 0.881583640 0.081677395 0.796266780 -0.009631682 0.944901811
[41] -0.011829940 -0.322797855 -0.148947933 -0.405154591 0.807167626
[46] 0.584827946 -1.734820903 0.716021144 -1.084074876 -0.343583371
[51] 1.391090513 1.168374931 -0.137766807 0.761266789 1.260597801
[56] -0.029266728 -0.845198940 -1.039464127 -0.135461077 0.931875414
[61] 0.137728542 0.812399537 1.585195155 0.039263066 1.554436429
[66] 0.328555933 1.624615302 0.276395516 -1.908904768 0.231159275
[71] 0.603614531 -0.630294085 -0.525299516 -1.602288295 0.954288128
[76] 0.533620096 1.957700961 -0.658486173 -0.088661289 -0.739597969
[81] 1.429032358 1.661679641 1.101539934 -0.840855768 -1.514713238
[86] -0.741003427 -0.404315139 -0.234145214 1.341713682 1.462098626
[91] 1.219774258 0.735640612 -0.537606618 -1.282100638 -0.303114083
[96] -0.262213156 -0.984129309 0.082019588 -0.986049441 0.242775957
> colMedians(tmp)
[1] -1.384205753 -0.011244814 0.613420192 -0.932065507 1.439366742
[6] -0.205137626 -0.424286381 -1.192448879 0.987500953 0.214839012
[11] -1.249382335 -0.455229819 0.057268575 1.106406333 -1.128547914
[16] 0.424996656 0.234188824 -0.508923359 -0.395501347 -0.419411251
[21] -0.443725218 -1.256962936 -1.437286381 1.018688932 0.188764097
[26] -1.144094403 1.951799306 0.437292041 -1.832540962 -0.344707602
[31] -0.337044778 -0.737590070 -0.361202015 -0.980051392 -0.459781456
[36] 0.881583640 0.081677395 0.796266780 -0.009631682 0.944901811
[41] -0.011829940 -0.322797855 -0.148947933 -0.405154591 0.807167626
[46] 0.584827946 -1.734820903 0.716021144 -1.084074876 -0.343583371
[51] 1.391090513 1.168374931 -0.137766807 0.761266789 1.260597801
[56] -0.029266728 -0.845198940 -1.039464127 -0.135461077 0.931875414
[61] 0.137728542 0.812399537 1.585195155 0.039263066 1.554436429
[66] 0.328555933 1.624615302 0.276395516 -1.908904768 0.231159275
[71] 0.603614531 -0.630294085 -0.525299516 -1.602288295 0.954288128
[76] 0.533620096 1.957700961 -0.658486173 -0.088661289 -0.739597969
[81] 1.429032358 1.661679641 1.101539934 -0.840855768 -1.514713238
[86] -0.741003427 -0.404315139 -0.234145214 1.341713682 1.462098626
[91] 1.219774258 0.735640612 -0.537606618 -1.282100638 -0.303114083
[96] -0.262213156 -0.984129309 0.082019588 -0.986049441 0.242775957
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.384206 -0.01124481 0.6134202 -0.9320655 1.439367 -0.2051376 -0.4242864
[2,] -1.384206 -0.01124481 0.6134202 -0.9320655 1.439367 -0.2051376 -0.4242864
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.192449 0.987501 0.214839 -1.249382 -0.4552298 0.05726858 1.106406
[2,] -1.192449 0.987501 0.214839 -1.249382 -0.4552298 0.05726858 1.106406
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.128548 0.4249967 0.2341888 -0.5089234 -0.3955013 -0.4194113 -0.4437252
[2,] -1.128548 0.4249967 0.2341888 -0.5089234 -0.3955013 -0.4194113 -0.4437252
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.256963 -1.437286 1.018689 0.1887641 -1.144094 1.951799 0.437292
[2,] -1.256963 -1.437286 1.018689 0.1887641 -1.144094 1.951799 0.437292
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.832541 -0.3447076 -0.3370448 -0.7375901 -0.361202 -0.9800514 -0.4597815
[2,] -1.832541 -0.3447076 -0.3370448 -0.7375901 -0.361202 -0.9800514 -0.4597815
[,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.8815836 0.0816774 0.7962668 -0.009631682 0.9449018 -0.01182994
[2,] 0.8815836 0.0816774 0.7962668 -0.009631682 0.9449018 -0.01182994
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.3227979 -0.1489479 -0.4051546 0.8071676 0.5848279 -1.734821 0.7160211
[2,] -0.3227979 -0.1489479 -0.4051546 0.8071676 0.5848279 -1.734821 0.7160211
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -1.084075 -0.3435834 1.391091 1.168375 -0.1377668 0.7612668 1.260598
[2,] -1.084075 -0.3435834 1.391091 1.168375 -0.1377668 0.7612668 1.260598
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.02926673 -0.8451989 -1.039464 -0.1354611 0.9318754 0.1377285 0.8123995
[2,] -0.02926673 -0.8451989 -1.039464 -0.1354611 0.9318754 0.1377285 0.8123995
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 1.585195 0.03926307 1.554436 0.3285559 1.624615 0.2763955 -1.908905
[2,] 1.585195 0.03926307 1.554436 0.3285559 1.624615 0.2763955 -1.908905
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.2311593 0.6036145 -0.6302941 -0.5252995 -1.602288 0.9542881 0.5336201
[2,] 0.2311593 0.6036145 -0.6302941 -0.5252995 -1.602288 0.9542881 0.5336201
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 1.957701 -0.6584862 -0.08866129 -0.739598 1.429032 1.66168 1.10154
[2,] 1.957701 -0.6584862 -0.08866129 -0.739598 1.429032 1.66168 1.10154
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.8408558 -1.514713 -0.7410034 -0.4043151 -0.2341452 1.341714 1.462099
[2,] -0.8408558 -1.514713 -0.7410034 -0.4043151 -0.2341452 1.341714 1.462099
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.219774 0.7356406 -0.5376066 -1.282101 -0.3031141 -0.2622132 -0.9841293
[2,] 1.219774 0.7356406 -0.5376066 -1.282101 -0.3031141 -0.2622132 -0.9841293
[,98] [,99] [,100]
[1,] 0.08201959 -0.9860494 0.242776
[2,] 0.08201959 -0.9860494 0.242776
>
>
> Max(tmp2)
[1] 2.751706
> Min(tmp2)
[1] -3.305747
> mean(tmp2)
[1] 0.04698219
> Sum(tmp2)
[1] 4.698219
> Var(tmp2)
[1] 1.217642
>
> rowMeans(tmp2)
[1] -2.09692134 1.18075806 0.31254007 0.33095270 0.64744165 -0.56947383
[7] 1.45399396 0.58793021 0.78608552 2.34965992 -0.50048917 0.58806807
[13] -0.67737714 -1.41596328 -1.43569962 0.90117455 -0.31741701 1.36787632
[19] 0.09799746 1.44487330 0.17885501 -0.64322357 -1.07750275 0.50831482
[25] -0.13384638 0.44109525 -0.43200943 0.87947815 -0.83211743 -0.63121144
[31] 1.45141447 0.21286475 -0.26688084 1.34633407 -1.61200364 -0.80098200
[37] -0.33052662 -0.84483395 1.44843139 0.23160515 -1.19512352 1.42970727
[43] -0.27949598 1.19001357 -1.67236456 0.41025004 -0.63055577 -0.56092670
[49] 1.36000438 1.81890644 -0.85909699 -1.38690415 0.31241548 0.76128898
[55] 0.91593013 0.21279870 -3.30574695 0.59260429 -0.80160415 -1.49594447
[61] 2.23277619 -0.87898816 0.30226677 -0.65710068 0.85221966 -0.53495711
[67] -0.89824594 -0.60142204 -0.76208505 1.97815569 0.88804203 2.75170647
[73] -0.90696806 -0.46822696 -0.10675218 0.32967574 0.84682802 -1.46117306
[79] -1.74117695 -0.03811790 -2.42684040 0.66686645 -1.02902400 1.28045129
[85] -0.85375810 -0.25569130 1.67507118 0.65361772 -0.08606186 1.49304700
[91] 0.45232756 -0.56935219 1.01265047 -0.65157502 -0.57598360 -0.65678912
[97] 0.19906636 0.44494992 0.42504778 1.42832141
> rowSums(tmp2)
[1] -2.09692134 1.18075806 0.31254007 0.33095270 0.64744165 -0.56947383
[7] 1.45399396 0.58793021 0.78608552 2.34965992 -0.50048917 0.58806807
[13] -0.67737714 -1.41596328 -1.43569962 0.90117455 -0.31741701 1.36787632
[19] 0.09799746 1.44487330 0.17885501 -0.64322357 -1.07750275 0.50831482
[25] -0.13384638 0.44109525 -0.43200943 0.87947815 -0.83211743 -0.63121144
[31] 1.45141447 0.21286475 -0.26688084 1.34633407 -1.61200364 -0.80098200
[37] -0.33052662 -0.84483395 1.44843139 0.23160515 -1.19512352 1.42970727
[43] -0.27949598 1.19001357 -1.67236456 0.41025004 -0.63055577 -0.56092670
[49] 1.36000438 1.81890644 -0.85909699 -1.38690415 0.31241548 0.76128898
[55] 0.91593013 0.21279870 -3.30574695 0.59260429 -0.80160415 -1.49594447
[61] 2.23277619 -0.87898816 0.30226677 -0.65710068 0.85221966 -0.53495711
[67] -0.89824594 -0.60142204 -0.76208505 1.97815569 0.88804203 2.75170647
[73] -0.90696806 -0.46822696 -0.10675218 0.32967574 0.84682802 -1.46117306
[79] -1.74117695 -0.03811790 -2.42684040 0.66686645 -1.02902400 1.28045129
[85] -0.85375810 -0.25569130 1.67507118 0.65361772 -0.08606186 1.49304700
[91] 0.45232756 -0.56935219 1.01265047 -0.65157502 -0.57598360 -0.65678912
[97] 0.19906636 0.44494992 0.42504778 1.42832141
> 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] -2.09692134 1.18075806 0.31254007 0.33095270 0.64744165 -0.56947383
[7] 1.45399396 0.58793021 0.78608552 2.34965992 -0.50048917 0.58806807
[13] -0.67737714 -1.41596328 -1.43569962 0.90117455 -0.31741701 1.36787632
[19] 0.09799746 1.44487330 0.17885501 -0.64322357 -1.07750275 0.50831482
[25] -0.13384638 0.44109525 -0.43200943 0.87947815 -0.83211743 -0.63121144
[31] 1.45141447 0.21286475 -0.26688084 1.34633407 -1.61200364 -0.80098200
[37] -0.33052662 -0.84483395 1.44843139 0.23160515 -1.19512352 1.42970727
[43] -0.27949598 1.19001357 -1.67236456 0.41025004 -0.63055577 -0.56092670
[49] 1.36000438 1.81890644 -0.85909699 -1.38690415 0.31241548 0.76128898
[55] 0.91593013 0.21279870 -3.30574695 0.59260429 -0.80160415 -1.49594447
[61] 2.23277619 -0.87898816 0.30226677 -0.65710068 0.85221966 -0.53495711
[67] -0.89824594 -0.60142204 -0.76208505 1.97815569 0.88804203 2.75170647
[73] -0.90696806 -0.46822696 -0.10675218 0.32967574 0.84682802 -1.46117306
[79] -1.74117695 -0.03811790 -2.42684040 0.66686645 -1.02902400 1.28045129
[85] -0.85375810 -0.25569130 1.67507118 0.65361772 -0.08606186 1.49304700
[91] 0.45232756 -0.56935219 1.01265047 -0.65157502 -0.57598360 -0.65678912
[97] 0.19906636 0.44494992 0.42504778 1.42832141
> rowMin(tmp2)
[1] -2.09692134 1.18075806 0.31254007 0.33095270 0.64744165 -0.56947383
[7] 1.45399396 0.58793021 0.78608552 2.34965992 -0.50048917 0.58806807
[13] -0.67737714 -1.41596328 -1.43569962 0.90117455 -0.31741701 1.36787632
[19] 0.09799746 1.44487330 0.17885501 -0.64322357 -1.07750275 0.50831482
[25] -0.13384638 0.44109525 -0.43200943 0.87947815 -0.83211743 -0.63121144
[31] 1.45141447 0.21286475 -0.26688084 1.34633407 -1.61200364 -0.80098200
[37] -0.33052662 -0.84483395 1.44843139 0.23160515 -1.19512352 1.42970727
[43] -0.27949598 1.19001357 -1.67236456 0.41025004 -0.63055577 -0.56092670
[49] 1.36000438 1.81890644 -0.85909699 -1.38690415 0.31241548 0.76128898
[55] 0.91593013 0.21279870 -3.30574695 0.59260429 -0.80160415 -1.49594447
[61] 2.23277619 -0.87898816 0.30226677 -0.65710068 0.85221966 -0.53495711
[67] -0.89824594 -0.60142204 -0.76208505 1.97815569 0.88804203 2.75170647
[73] -0.90696806 -0.46822696 -0.10675218 0.32967574 0.84682802 -1.46117306
[79] -1.74117695 -0.03811790 -2.42684040 0.66686645 -1.02902400 1.28045129
[85] -0.85375810 -0.25569130 1.67507118 0.65361772 -0.08606186 1.49304700
[91] 0.45232756 -0.56935219 1.01265047 -0.65157502 -0.57598360 -0.65678912
[97] 0.19906636 0.44494992 0.42504778 1.42832141
>
> colMeans(tmp2)
[1] 0.04698219
> colSums(tmp2)
[1] 4.698219
> colVars(tmp2)
[1] 1.217642
> colSd(tmp2)
[1] 1.103468
> colMax(tmp2)
[1] 2.751706
> colMin(tmp2)
[1] -3.305747
> colMedians(tmp2)
[1] 0.1384262
> colRanges(tmp2)
[,1]
[1,] -3.305747
[2,] 2.751706
>
> 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] 2.589365 1.177261 -2.079146 -3.407426 2.099704 1.707971 4.067975
[8] 5.292908 -3.090154 3.849090
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6831273
[2,] -0.1913615
[3,] 0.1638642
[4,] 0.4847820
[5,] 1.4160462
>
> rowApply(tmp,sum)
[1] -0.8123731 0.8954269 4.0579414 4.7658135 1.4154907 2.8907582
[7] -2.1345944 -0.4534517 0.8944588 0.6880758
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 4 6 4 10 2 9 5 3 5
[2,] 4 5 2 6 5 1 3 7 8 10
[3,] 3 7 4 2 4 7 7 8 1 2
[4,] 1 3 3 7 6 3 4 1 2 4
[5,] 9 8 7 9 2 10 5 2 4 6
[6,] 5 9 5 1 9 8 1 9 7 8
[7,] 7 1 10 10 3 9 10 3 9 1
[8,] 10 2 9 8 7 6 6 4 10 9
[9,] 2 6 1 3 1 5 8 6 6 3
[10,] 6 10 8 5 8 4 2 10 5 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.7478032 5.9126694 -1.0589968 2.8695933 -0.2647552 0.6191008
[7] 3.3652608 2.9556138 -1.5237887 3.2950585 1.4355956 -0.6092462
[13] -0.7215868 -3.4155261 -2.7400659 1.2674963 2.3821508 -1.4231380
[19] 0.3632496 2.2392234
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6235913
[2,] -1.2899910
[3,] -0.5505553
[4,] 0.3137118
[5,] 0.4026226
>
> rowApply(tmp,sum)
[1] -1.183633 1.096790 4.389485 10.958621 -3.061157
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 3 13 5 3
[2,] 18 20 1 18 20
[3,] 11 6 17 4 6
[4,] 4 7 19 19 13
[5,] 8 5 14 17 5
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.3137118 0.7054055 0.1239140 -0.5418291 -0.2253520 0.30803146
[2,] -1.2899910 2.5274287 -0.5569964 -0.5288931 -0.6777458 -0.46626546
[3,] 0.4026226 -1.3348563 1.1584311 1.6359756 0.4640508 -0.10459559
[4,] -0.5505553 1.6598452 -0.5725434 1.9923131 1.4959232 0.82007588
[5,] -1.6235913 2.3548462 -1.2118021 0.3120269 -1.3216314 0.06185452
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3121593 -0.54179758 0.3051888 0.79462729 -0.5045597 -0.5091357
[2,] -1.0122198 1.12894800 0.4193605 0.06629616 1.6593098 0.7948253
[3,] 1.9985716 1.48309228 -0.4466344 -0.04921876 -0.2090707 -0.7418240
[4,] 0.9938784 0.87449501 -0.1206827 2.43235368 1.0992371 0.1378945
[5,] 1.0728713 0.01087612 -1.6810208 0.05100016 -0.6093209 -0.2910063
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.97447071 -1.7562485 -1.2788010 1.47642886 0.2455727 0.4780312
[2,] 0.04164494 0.5529886 -1.3098116 -0.08424022 0.5290479 -2.4577647
[3,] -0.12875533 -0.7160889 0.1773977 0.24597575 -0.3046728 -0.1968310
[4,] -0.69772436 -1.1672185 -0.9041039 1.05279191 0.9515065 0.2003414
[5,] 1.03771867 -0.3289589 0.5752529 -1.42345996 0.9606965 0.5530851
[,19] [,20]
[1,] -0.0187645 0.10425530
[2,] 1.1061264 0.65474142
[3,] 0.5293819 0.52653335
[4,] 1.3147517 -0.05395877
[5,] -2.5682459 1.00765208
>
>
> 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 : 648 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 : 558 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 1.368147 0.4274529 -1.290188 -0.2094719 -2.171863 -1.441734 -0.1669881
col8 col9 col10 col11 col12 col13 col14
row1 -0.3739391 -2.019239 1.61142 -2.10416 -1.132514 -0.6846218 0.02907682
col15 col16 col17 col18 col19 col20
row1 -0.4956361 0.4801764 0.9987775 -0.219671 -0.6583139 -0.8600042
> tmp[,"col10"]
col10
row1 1.61141953
row2 -0.16196037
row3 -0.08426657
row4 0.48022743
row5 0.61258249
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.3681469 0.4274529 -1.290188 -0.2094719 -2.1718633 -1.4417338 -0.1669881
row5 -0.6435073 0.2176435 -1.955900 -2.2477780 0.3148265 -0.6159629 1.1739831
col8 col9 col10 col11 col12 col13
row1 -0.3739391 -2.01923919 1.6114195 -2.1041596 -1.1325144 -0.6846218
row5 -0.9770155 -0.08575469 0.6125825 0.7298459 0.1119603 -1.4330111
col14 col15 col16 col17 col18 col19
row1 0.02907682 -0.4956361 0.4801764 0.9987775 -0.2196710 -0.6583139
row5 -0.15319547 0.1244018 1.1253937 -1.1587091 -0.4077262 -0.8037153
col20
row1 -0.8600042
row5 1.0363901
> tmp[,c("col6","col20")]
col6 col20
row1 -1.4417338 -0.8600042
row2 1.1061232 1.2201595
row3 1.3679185 -0.6280611
row4 0.4542816 -0.9623208
row5 -0.6159629 1.0363901
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.4417338 -0.8600042
row5 -0.6159629 1.0363901
>
>
>
>
> 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 49.79363 49.53915 51.06302 48.8758 49.02581 104.9305 49.94039 50.39849
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.74582 48.61262 50.60361 49.28493 50.63345 51.83882 48.35379 48.87465
col17 col18 col19 col20
row1 49.89727 50.34602 48.90247 103.4855
> tmp[,"col10"]
col10
row1 48.61262
row2 30.67152
row3 30.04920
row4 28.68754
row5 49.84151
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.79363 49.53915 51.06302 48.87580 49.02581 104.9305 49.94039 50.39849
row5 50.17074 50.67912 51.15996 50.10642 48.89283 105.3432 49.30374 50.39643
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.74582 48.61262 50.60361 49.28493 50.63345 51.83882 48.35379 48.87465
row5 47.63193 49.84151 49.59717 51.63142 48.68621 49.61299 51.40635 49.14314
col17 col18 col19 col20
row1 49.89727 50.34602 48.90247 103.4855
row5 49.43082 49.35990 50.48268 105.6757
> tmp[,c("col6","col20")]
col6 col20
row1 104.93046 103.48545
row2 76.25026 75.82596
row3 75.06639 74.27093
row4 74.05244 72.94239
row5 105.34321 105.67569
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9305 103.4855
row5 105.3432 105.6757
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9305 103.4855
row5 105.3432 105.6757
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.2138346
[2,] 0.1102298
[3,] -0.5201972
[4,] -2.0651864
[5,] 1.6098176
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.2924262 -0.47274158
[2,] 0.6230030 -0.39655386
[3,] 0.1407800 -0.06941163
[4,] -0.3717006 0.77116889
[5,] 0.1633500 0.18690625
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.0681953 1.0352102
[2,] 0.2311091 -0.1474706
[3,] 1.0157616 1.5392937
[4,] 0.5653229 -0.5643558
[5,] -1.0975094 -0.8073129
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.0681953
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.0681953
[2,] 0.2311091
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.7008391 -0.63869132 0.3372221 0.724817 0.07358821 -1.5424203 1.01103127
row1 0.9244135 0.09869404 0.5760997 -1.704383 0.67469886 -0.6231152 0.08046573
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.8393138 -0.9534396 0.4092961 -0.1895570 0.2267226 -0.0924030
row1 -0.3641860 -0.8776025 -0.8114884 0.2593623 -0.3172561 0.6475712
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.09407460 0.1283216 -1.394369 -1.2435046 1.3305050 -0.008655286
row1 0.01731608 1.6436962 1.563973 0.6079689 -0.6899551 -0.416361876
[,20]
row3 -1.4262116
row1 -0.7750302
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.6165682 -0.2891897 -0.1611278 -0.7445848 0.2788273 -1.525197 -1.878991
[,8] [,9] [,10]
row2 -0.106171 2.578118 -0.2990748
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1842333 -1.28049 -2.634969 -0.7344661 1.091665 -1.099337 2.079181
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -2.087827 0.1734879 0.8995168 0.8581583 -0.7594717 -0.07204376 2.848617
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.356683 0.4183017 1.060546 -0.2676056 -0.06425276 -0.5312104
>
>
> 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: 0x62a643d59ed0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711925f753671"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711925358ffd5"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711925049c822"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711925dd1e513"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711925df42153"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7119257a9daa0"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM71192679b810f"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711921299c6cb"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM71192620bb539"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM71192770717eb"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM7119259bf6e22"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711925070dacf"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM71192ab15d7"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM71192261050d2"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM711921552e702"
>
>
> ### 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: 0x62a643bb7160>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x62a643bb7160>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x62a643bb7160>
> rowMedians(tmp)
[1] -8.536229e-02 5.719187e-01 2.130017e-01 -1.298435e-01 5.476849e-01
[6] 5.070301e-01 -3.219338e-01 -2.157936e-01 5.597130e-01 -3.147424e-01
[11] -4.161167e-01 6.179295e-02 1.194449e-01 -2.767467e-02 -1.084793e-01
[16] 4.735564e-01 3.757240e-01 4.453205e-02 -2.189290e-01 3.365983e-02
[21] 3.431145e-01 -4.884451e-01 -2.692444e-01 1.589932e-01 1.448043e-01
[26] 1.035253e-01 -2.509076e-01 1.141923e-01 -3.574202e-01 2.440935e-01
[31] 4.182886e-01 6.005007e-02 -3.242517e-02 -5.311140e-01 -4.735820e-01
[36] 2.321775e-02 2.332478e-01 8.292038e-02 -2.972025e-02 1.365707e-01
[41] -4.627260e-02 1.133574e-01 -9.717057e-02 1.903561e-01 3.534786e-01
[46] -1.493823e-01 8.437602e-01 1.117006e-01 -1.007035e-01 -2.395907e-01
[51] -6.631581e-01 8.151919e-02 3.292608e-01 -4.948396e-01 2.506871e-04
[56] 5.520948e-01 -2.043967e-01 1.971124e-01 2.326624e-01 -2.610030e-01
[61] 1.223352e-01 -2.450870e-01 -1.355144e-01 1.302756e-01 3.402891e-01
[66] -5.948352e-01 -4.352639e-01 -2.951768e-01 4.950761e-01 2.556395e-01
[71] 3.906837e-01 5.214614e-01 -7.307249e-02 2.462485e-01 -1.519421e-01
[76] -6.083852e-01 5.815352e-02 -2.388547e-02 2.222455e-01 4.584011e-01
[81] -4.509316e-01 1.277341e-01 2.682732e-01 -5.255279e-01 1.195432e-01
[86] -3.021414e-01 -7.816961e-02 -2.644287e-01 1.977773e-01 1.771436e-01
[91] -7.576325e-01 -7.522321e-02 -2.118745e-01 5.416390e-02 -1.497485e-01
[96] -3.397963e-01 -1.064962e-01 -3.759803e-01 -4.423330e-01 1.209806e-01
[101] 8.100221e-02 -1.949540e-01 4.373642e-01 2.573229e-02 6.347085e-05
[106] 1.840923e-01 -1.332290e-01 1.371261e-01 -7.011291e-02 7.276051e-01
[111] 5.561472e-01 3.951713e-01 -1.624651e-01 -1.545746e-01 -5.938282e-01
[116] -1.379166e-01 -1.545435e-01 1.591482e-01 -9.066863e-02 1.865974e-02
[121] -3.819513e-01 -5.403971e-01 -6.242586e-01 -1.795450e-01 -3.818133e-01
[126] -2.726395e-01 -1.661529e-01 -5.205165e-01 2.532612e-01 -1.518088e-01
[131] -3.374466e-01 -1.882134e-01 -1.061260e-01 3.147967e-01 -1.821036e-03
[136] -6.074403e-01 -2.803370e-01 2.775210e-01 -2.072764e-01 -2.260172e-01
[141] -3.912274e-02 1.522495e-01 -2.059664e-01 -1.268342e-01 4.060508e-01
[146] 2.721948e-02 3.992888e-01 4.061522e-01 -3.003814e-01 1.803390e-01
[151] 2.278285e-01 3.634257e-01 7.208854e-02 2.406269e-01 -1.065671e-01
[156] 1.894604e-01 4.366201e-01 -1.339460e-01 -1.707561e-01 3.675662e-01
[161] 1.025604e-01 -2.105999e-01 2.270886e-01 3.320004e-01 -1.843895e-02
[166] -2.583334e-02 4.832538e-02 3.391407e-01 -3.358047e-01 1.480121e-01
[171] -3.391522e-01 -1.670081e-01 2.532369e-01 -5.431661e-01 -1.901223e-01
[176] 7.092772e-02 -4.444676e-01 6.118588e-02 9.309637e-02 -1.543660e-01
[181] -5.239536e-01 2.433905e-01 -4.248328e-02 -1.205648e-01 -9.183245e-02
[186] 1.369499e-01 -4.380309e-01 -3.051119e-02 -6.884789e-01 3.224863e-01
[191] 1.949888e-01 5.582832e-02 2.431606e-01 8.475750e-02 2.972312e-01
[196] 4.287488e-01 -1.014929e-01 -5.858316e-01 -1.380892e-01 4.241206e-01
[201] -8.109220e-02 5.547829e-01 -6.009157e-02 -7.709872e-01 6.039642e-02
[206] 1.447987e-01 -9.748838e-02 -1.817668e-01 4.038881e-01 -1.977975e-01
[211] -2.153711e-01 9.821308e-01 2.874622e-01 -2.558384e-01 -8.040409e-01
[216] 6.023815e-01 -2.637966e-01 2.813623e-02 5.842757e-01 -3.091980e-01
[221] 6.211654e-02 2.010951e-01 -3.543159e-01 -1.167418e-02 1.275946e-01
[226] -3.185407e-01 1.897543e-01 -2.435930e-01 -1.222804e-01 9.464479e-02
>
> proc.time()
user system elapsed
1.275 1.435 2.699
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: 0x5b204d2445e0>
> .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: 0x5b204d2445e0>
> .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: 0x5b204d2445e0>
> .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: 0x5b204d2445e0>
> 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: 0x5b204d21b410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204d21b410>
> .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: 0x5b204d21b410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204d21b410>
> .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: 0x5b204d21b410>
> 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: 0x5b204be20b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204be20b40>
> .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: 0x5b204be20b40>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5b204be20b40>
> .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: 0x5b204be20b40>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5b204be20b40>
> .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: 0x5b204be20b40>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5b204be20b40>
> .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: 0x5b204be20b40>
> 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: 0x5b204bac87a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5b204bac87a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204bac87a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204bac87a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile715b04369aa68" "BufferedMatrixFile715b072c63b15"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile715b04369aa68" "BufferedMatrixFile715b072c63b15"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204e57e050>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204e57e050>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5b204e57e050>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5b204e57e050>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5b204e57e050>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5b204e57e050>
> .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: 0x5b204cb9f0c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b204cb9f0c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5b204cb9f0c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5b204cb9f0c0>
> 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: 0x5b204dbb5a10>
> .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: 0x5b204dbb5a10>
> rm(P)
>
> proc.time()
user system elapsed
0.240 0.049 0.278
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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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
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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
0.232 0.055 0.276