Ben Bolstad
| Snapshot Date: 2025-11-14 13:40 -0500 (Fri, 14 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 2025-11-15 11:34 -0500 (Sat, 15 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" | 4826 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4561 |
| 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 251/2325 | 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: 2025-11-14 21:38:12 -0500 (Fri, 14 Nov 2025) |
| EndedAt: 2025-11-14 21:38:37 -0500 (Fri, 14 Nov 2025) |
| EllapsedTime: 25.1 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
###
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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
0.261 0.039 0.287
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] "Fri Nov 14 21:38:27 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Nov 14 21:38:27 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: 0x5d63183a15e0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Nov 14 21:38:28 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Nov 14 21:38:28 2025"
>
> ColMode(tmp2)
<pointer: 0x5d63183a15e0>
>
>
>
> ### 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,] 98.5485744 -0.9726366 -0.2439268 0.08704278
[2,] -0.7063267 -0.7144686 -1.7499327 0.30163689
[3,] -1.9184168 0.3992329 -2.0677351 -0.43741741
[4,] -0.3375121 -0.1965696 -0.4810779 0.17159904
> 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,] 98.5485744 0.9726366 0.2439268 0.08704278
[2,] 0.7063267 0.7144686 1.7499327 0.30163689
[3,] 1.9184168 0.3992329 2.0677351 0.43741741
[4,] 0.3375121 0.1965696 0.4810779 0.17159904
> 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,] 9.9271635 0.9862234 0.4938895 0.2950301
[2,] 0.8404325 0.8452625 1.3228502 0.5492148
[3,] 1.3850693 0.6318488 1.4379621 0.6613754
[4,] 0.5809579 0.4433617 0.6935978 0.4142451
>
> 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,] 222.82021 35.83487 30.18282 28.03734
[2,] 34.11065 34.16709 39.97843 30.79378
[3,] 40.76911 31.71772 41.44736 32.05117
[4,] 31.14709 29.63019 32.41706 29.31405
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5d6317f2c840>
> exp(tmp5)
<pointer: 0x5d6317f2c840>
> log(tmp5,2)
<pointer: 0x5d6317f2c840>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 463.7711
> Min(tmp5)
[1] 52.6729
> mean(tmp5)
[1] 72.25553
> Sum(tmp5)
[1] 14451.11
> Var(tmp5)
[1] 853.0128
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.25187 70.28855 69.00185 70.24760 66.90445 69.50691 70.58680 73.05784
[9] 72.57704 70.13239
> rowSums(tmp5)
[1] 1805.037 1405.771 1380.037 1404.952 1338.089 1390.138 1411.736 1461.157
[9] 1451.541 1402.648
> rowVars(tmp5)
[1] 7818.88470 71.21693 88.00799 87.67340 75.82041 81.22583
[7] 113.22715 100.75529 44.39415 46.05044
> rowSd(tmp5)
[1] 88.424458 8.439012 9.381258 9.363408 8.707492 9.012537 10.640825
[8] 10.037694 6.662893 6.786047
> rowMax(tmp5)
[1] 463.77107 83.57509 86.26724 91.99054 82.77532 84.83521 88.17133
[8] 92.39496 85.89280 83.32464
> rowMin(tmp5)
[1] 56.71078 54.98913 55.27711 54.20777 53.76308 53.78669 52.67290 53.52521
[9] 59.78744 58.47456
>
> colMeans(tmp5)
[1] 113.11884 70.60738 72.59543 63.00446 74.10792 68.51013 72.05748
[8] 67.84331 69.20512 64.00467 66.50232 71.14510 74.26993 72.66416
[15] 69.62407 76.71378 69.96143 64.58083 70.05573 74.53851
> colSums(tmp5)
[1] 1131.1884 706.0738 725.9543 630.0446 741.0792 685.1013 720.5748
[8] 678.4331 692.0512 640.0467 665.0232 711.4510 742.6993 726.6416
[15] 696.2407 767.1378 699.6143 645.8083 700.5573 745.3851
> colVars(tmp5)
[1] 15284.69153 51.81648 86.79879 22.43333 67.01492 67.05584
[7] 42.91471 75.46182 88.22127 58.47717 69.31872 53.56076
[13] 93.59292 80.90259 40.74296 61.13628 113.87334 63.82651
[19] 65.50036 138.00287
> colSd(tmp5)
[1] 123.631272 7.198366 9.316587 4.736384 8.186264 8.188763
[7] 6.550932 8.686876 9.392618 7.647037 8.325787 7.318522
[13] 9.674343 8.994586 6.383021 7.818970 10.671145 7.989150
[19] 8.093229 11.747462
> colMax(tmp5)
[1] 463.77107 79.46829 86.26724 71.60943 81.52665 81.86418 84.08376
[8] 81.64529 80.81628 76.88510 81.82256 78.18056 91.99054 85.59794
[15] 77.49900 86.03674 83.36802 78.66047 81.95847 90.52977
> colMin(tmp5)
[1] 58.94642 57.33078 56.19242 54.48697 56.71078 59.35420 62.56703 57.21673
[9] 56.07452 54.20777 52.67290 59.78744 63.65076 60.95634 56.35805 62.01990
[17] 53.78669 53.76308 57.53645 53.52521
>
>
> ### 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] 90.25187 70.28855 69.00185 70.24760 66.90445 69.50691 70.58680 NA
[9] 72.57704 70.13239
> rowSums(tmp5)
[1] 1805.037 1405.771 1380.037 1404.952 1338.089 1390.138 1411.736 NA
[9] 1451.541 1402.648
> rowVars(tmp5)
[1] 7818.88470 71.21693 88.00799 87.67340 75.82041 81.22583
[7] 113.22715 84.04150 44.39415 46.05044
> rowSd(tmp5)
[1] 88.424458 8.439012 9.381258 9.363408 8.707492 9.012537 10.640825
[8] 9.167415 6.662893 6.786047
> rowMax(tmp5)
[1] 463.77107 83.57509 86.26724 91.99054 82.77532 84.83521 88.17133
[8] NA 85.89280 83.32464
> rowMin(tmp5)
[1] 56.71078 54.98913 55.27711 54.20777 53.76308 53.78669 52.67290 NA
[9] 59.78744 58.47456
>
> colMeans(tmp5)
[1] 113.11884 70.60738 72.59543 63.00446 74.10792 68.51013 72.05748
[8] 67.84331 69.20512 64.00467 66.50232 71.14510 74.26993 72.66416
[15] 69.62407 76.71378 69.96143 64.58083 70.05573 NA
> colSums(tmp5)
[1] 1131.1884 706.0738 725.9543 630.0446 741.0792 685.1013 720.5748
[8] 678.4331 692.0512 640.0467 665.0232 711.4510 742.6993 726.6416
[15] 696.2407 767.1378 699.6143 645.8083 700.5573 NA
> colVars(tmp5)
[1] 15284.69153 51.81648 86.79879 22.43333 67.01492 67.05584
[7] 42.91471 75.46182 88.22127 58.47717 69.31872 53.56076
[13] 93.59292 80.90259 40.74296 61.13628 113.87334 63.82651
[19] 65.50036 NA
> colSd(tmp5)
[1] 123.631272 7.198366 9.316587 4.736384 8.186264 8.188763
[7] 6.550932 8.686876 9.392618 7.647037 8.325787 7.318522
[13] 9.674343 8.994586 6.383021 7.818970 10.671145 7.989150
[19] 8.093229 NA
> colMax(tmp5)
[1] 463.77107 79.46829 86.26724 71.60943 81.52665 81.86418 84.08376
[8] 81.64529 80.81628 76.88510 81.82256 78.18056 91.99054 85.59794
[15] 77.49900 86.03674 83.36802 78.66047 81.95847 NA
> colMin(tmp5)
[1] 58.94642 57.33078 56.19242 54.48697 56.71078 59.35420 62.56703 57.21673
[9] 56.07452 54.20777 52.67290 59.78744 63.65076 60.95634 56.35805 62.01990
[17] 53.78669 53.76308 57.53645 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 463.7711
> Min(tmp5,na.rm=TRUE)
[1] 52.6729
> mean(tmp5,na.rm=TRUE)
[1] 72.34965
> Sum(tmp5,na.rm=TRUE)
[1] 14397.58
> Var(tmp5,na.rm=TRUE)
[1] 855.5402
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.25187 70.28855 69.00185 70.24760 66.90445 69.50691 70.58680 74.08587
[9] 72.57704 70.13239
> rowSums(tmp5,na.rm=TRUE)
[1] 1805.037 1405.771 1380.037 1404.952 1338.089 1390.138 1411.736 1407.632
[9] 1451.541 1402.648
> rowVars(tmp5,na.rm=TRUE)
[1] 7818.88470 71.21693 88.00799 87.67340 75.82041 81.22583
[7] 113.22715 84.04150 44.39415 46.05044
> rowSd(tmp5,na.rm=TRUE)
[1] 88.424458 8.439012 9.381258 9.363408 8.707492 9.012537 10.640825
[8] 9.167415 6.662893 6.786047
> rowMax(tmp5,na.rm=TRUE)
[1] 463.77107 83.57509 86.26724 91.99054 82.77532 84.83521 88.17133
[8] 92.39496 85.89280 83.32464
> rowMin(tmp5,na.rm=TRUE)
[1] 56.71078 54.98913 55.27711 54.20777 53.76308 53.78669 52.67290 58.32819
[9] 59.78744 58.47456
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.11884 70.60738 72.59543 63.00446 74.10792 68.51013 72.05748
[8] 67.84331 69.20512 64.00467 66.50232 71.14510 74.26993 72.66416
[15] 69.62407 76.71378 69.96143 64.58083 70.05573 76.87333
> colSums(tmp5,na.rm=TRUE)
[1] 1131.1884 706.0738 725.9543 630.0446 741.0792 685.1013 720.5748
[8] 678.4331 692.0512 640.0467 665.0232 711.4510 742.6993 726.6416
[15] 696.2407 767.1378 699.6143 645.8083 700.5573 691.8599
> colVars(tmp5,na.rm=TRUE)
[1] 15284.69153 51.81648 86.79879 22.43333 67.01492 67.05584
[7] 42.91471 75.46182 88.22127 58.47717 69.31872 53.56076
[13] 93.59292 80.90259 40.74296 61.13628 113.87334 63.82651
[19] 65.50036 93.92562
> colSd(tmp5,na.rm=TRUE)
[1] 123.631272 7.198366 9.316587 4.736384 8.186264 8.188763
[7] 6.550932 8.686876 9.392618 7.647037 8.325787 7.318522
[13] 9.674343 8.994586 6.383021 7.818970 10.671145 7.989150
[19] 8.093229 9.691523
> colMax(tmp5,na.rm=TRUE)
[1] 463.77107 79.46829 86.26724 71.60943 81.52665 81.86418 84.08376
[8] 81.64529 80.81628 76.88510 81.82256 78.18056 91.99054 85.59794
[15] 77.49900 86.03674 83.36802 78.66047 81.95847 90.52977
> colMin(tmp5,na.rm=TRUE)
[1] 58.94642 57.33078 56.19242 54.48697 56.71078 59.35420 62.56703 57.21673
[9] 56.07452 54.20777 52.67290 59.78744 63.65076 60.95634 56.35805 62.01990
[17] 53.78669 53.76308 57.53645 63.11337
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.25187 70.28855 69.00185 70.24760 66.90445 69.50691 70.58680 NaN
[9] 72.57704 70.13239
> rowSums(tmp5,na.rm=TRUE)
[1] 1805.037 1405.771 1380.037 1404.952 1338.089 1390.138 1411.736 0.000
[9] 1451.541 1402.648
> rowVars(tmp5,na.rm=TRUE)
[1] 7818.88470 71.21693 88.00799 87.67340 75.82041 81.22583
[7] 113.22715 NA 44.39415 46.05044
> rowSd(tmp5,na.rm=TRUE)
[1] 88.424458 8.439012 9.381258 9.363408 8.707492 9.012537 10.640825
[8] NA 6.662893 6.786047
> rowMax(tmp5,na.rm=TRUE)
[1] 463.77107 83.57509 86.26724 91.99054 82.77532 84.83521 88.17133
[8] NA 85.89280 83.32464
> rowMin(tmp5,na.rm=TRUE)
[1] 56.71078 54.98913 55.27711 54.20777 53.76308 53.78669 52.67290 NA
[9] 59.78744 58.47456
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.42150 69.62284 71.83913 62.82492 73.39169 67.23737 71.16826
[8] 66.63412 70.38623 62.57351 65.89613 72.37367 74.47270 71.25805
[15] 69.49117 77.40295 71.25401 64.10196 69.10416 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1038.7935 626.6055 646.5522 565.4243 660.5252 605.1363 640.5143
[8] 599.7071 633.4761 563.1616 593.0652 651.3630 670.2543 641.3224
[15] 625.4205 696.6266 641.2861 576.9176 621.9374 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17135.62806 47.38857 91.21371 24.87487 69.62072 57.21374
[7] 39.38342 68.44546 83.55479 42.74437 73.84951 43.27515
[13] 104.82946 68.77232 45.63714 63.43502 109.31135 69.22502
[19] 63.50122 NA
> colSd(tmp5,na.rm=TRUE)
[1] 130.903125 6.883936 9.550587 4.987471 8.343903 7.563977
[7] 6.275621 8.273177 9.140831 6.537918 8.593574 6.578385
[13] 10.238626 8.292908 6.755526 7.964611 10.455207 8.320157
[19] 7.968765 NA
> colMax(tmp5,na.rm=TRUE)
[1] 463.77107 79.08952 86.26724 71.60943 81.52665 81.86418 84.08376
[8] 81.64529 80.81628 70.96030 81.82256 78.18056 91.99054 85.59794
[15] 77.49900 86.03674 83.36802 78.66047 81.95847 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 58.94642 57.33078 56.19242 54.48697 56.71078 59.35420 62.56703 57.21673
[9] 56.07452 54.20777 52.67290 59.78744 63.65076 60.95634 56.35805 62.01990
[17] 53.78669 53.76308 57.53645 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] 295.2126 136.4714 164.5787 333.8298 178.1137 139.6739 291.2643 200.2707
[9] 248.3855 189.5214
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 295.2126 136.4714 164.5787 333.8298 178.1137 139.6739 291.2643 200.2707
[9] 248.3855 189.5214
>
>
>
> 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-13 2.557954e-13 -5.684342e-14 5.684342e-14 1.136868e-13
[6] 2.842171e-14 0.000000e+00 -5.684342e-14 1.278977e-13 1.421085e-13
[11] 0.000000e+00 -2.273737e-13 5.684342e-14 2.842171e-14 0.000000e+00
[16] -5.684342e-14 2.842171e-14 8.526513e-14 0.000000e+00 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
6 14
7 12
1 14
5 15
2 17
1 8
9 17
1 10
7 2
3 5
4 19
3 1
5 1
7 17
6 2
10 3
2 19
4 18
7 18
10 13
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.164643
> Min(tmp)
[1] -2.32508
> mean(tmp)
[1] 0.1029274
> Sum(tmp)
[1] 10.29274
> Var(tmp)
[1] 0.94427
>
> rowMeans(tmp)
[1] 0.1029274
> rowSums(tmp)
[1] 10.29274
> rowVars(tmp)
[1] 0.94427
> rowSd(tmp)
[1] 0.9717356
> rowMax(tmp)
[1] 2.164643
> rowMin(tmp)
[1] -2.32508
>
> colMeans(tmp)
[1] 1.204899088 0.187213554 -1.441011509 -1.675717809 -0.335716152
[6] 0.611069390 -0.500848854 0.123416655 0.036372286 -0.767282143
[11] 0.859109063 0.433716080 0.299727766 -1.026829043 1.640113866
[16] 1.584357050 0.162209605 -0.292422124 0.748086143 -1.294290019
[21] -0.205681369 1.405153988 1.193455303 0.021570197 -0.399397726
[26] 0.593469391 0.890359163 -0.776024179 -0.035698811 -0.600965671
[31] -1.519077905 1.095839832 -0.500009973 -0.404127134 -0.463529129
[36] -0.615731124 0.365376945 0.651423741 1.429390610 -0.598661144
[41] -0.686286759 -1.530293305 0.571164116 -0.647601723 1.347637246
[46] 0.723545458 -1.170999695 1.221344820 0.610858336 0.054065868
[51] 0.924534577 0.189367259 1.357062881 -0.177920336 -0.264676782
[56] -0.335634532 -0.831118805 -1.438269599 -1.014635118 1.077997276
[61] 0.645590009 -0.918099459 1.566057821 -0.291618145 0.259895554
[66] 0.917526115 -0.006461096 1.744550269 0.212478997 0.221294484
[71] -0.069068285 0.448030912 -0.245571204 -1.136184575 -0.418759851
[76] 1.911706777 1.008770281 0.819390713 -0.974106314 -0.808384396
[81] -0.973376506 -1.295161871 1.553452073 1.084664361 -1.237312132
[86] 1.093759214 -0.128507878 -0.013245557 -0.634302117 0.657625564
[91] 1.194818576 2.164643018 0.820759414 0.231560485 1.773037944
[96] -0.665733640 -2.325079501 -0.260808560 -1.386846136 1.688306144
> colSums(tmp)
[1] 1.204899088 0.187213554 -1.441011509 -1.675717809 -0.335716152
[6] 0.611069390 -0.500848854 0.123416655 0.036372286 -0.767282143
[11] 0.859109063 0.433716080 0.299727766 -1.026829043 1.640113866
[16] 1.584357050 0.162209605 -0.292422124 0.748086143 -1.294290019
[21] -0.205681369 1.405153988 1.193455303 0.021570197 -0.399397726
[26] 0.593469391 0.890359163 -0.776024179 -0.035698811 -0.600965671
[31] -1.519077905 1.095839832 -0.500009973 -0.404127134 -0.463529129
[36] -0.615731124 0.365376945 0.651423741 1.429390610 -0.598661144
[41] -0.686286759 -1.530293305 0.571164116 -0.647601723 1.347637246
[46] 0.723545458 -1.170999695 1.221344820 0.610858336 0.054065868
[51] 0.924534577 0.189367259 1.357062881 -0.177920336 -0.264676782
[56] -0.335634532 -0.831118805 -1.438269599 -1.014635118 1.077997276
[61] 0.645590009 -0.918099459 1.566057821 -0.291618145 0.259895554
[66] 0.917526115 -0.006461096 1.744550269 0.212478997 0.221294484
[71] -0.069068285 0.448030912 -0.245571204 -1.136184575 -0.418759851
[76] 1.911706777 1.008770281 0.819390713 -0.974106314 -0.808384396
[81] -0.973376506 -1.295161871 1.553452073 1.084664361 -1.237312132
[86] 1.093759214 -0.128507878 -0.013245557 -0.634302117 0.657625564
[91] 1.194818576 2.164643018 0.820759414 0.231560485 1.773037944
[96] -0.665733640 -2.325079501 -0.260808560 -1.386846136 1.688306144
> 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] 1.204899088 0.187213554 -1.441011509 -1.675717809 -0.335716152
[6] 0.611069390 -0.500848854 0.123416655 0.036372286 -0.767282143
[11] 0.859109063 0.433716080 0.299727766 -1.026829043 1.640113866
[16] 1.584357050 0.162209605 -0.292422124 0.748086143 -1.294290019
[21] -0.205681369 1.405153988 1.193455303 0.021570197 -0.399397726
[26] 0.593469391 0.890359163 -0.776024179 -0.035698811 -0.600965671
[31] -1.519077905 1.095839832 -0.500009973 -0.404127134 -0.463529129
[36] -0.615731124 0.365376945 0.651423741 1.429390610 -0.598661144
[41] -0.686286759 -1.530293305 0.571164116 -0.647601723 1.347637246
[46] 0.723545458 -1.170999695 1.221344820 0.610858336 0.054065868
[51] 0.924534577 0.189367259 1.357062881 -0.177920336 -0.264676782
[56] -0.335634532 -0.831118805 -1.438269599 -1.014635118 1.077997276
[61] 0.645590009 -0.918099459 1.566057821 -0.291618145 0.259895554
[66] 0.917526115 -0.006461096 1.744550269 0.212478997 0.221294484
[71] -0.069068285 0.448030912 -0.245571204 -1.136184575 -0.418759851
[76] 1.911706777 1.008770281 0.819390713 -0.974106314 -0.808384396
[81] -0.973376506 -1.295161871 1.553452073 1.084664361 -1.237312132
[86] 1.093759214 -0.128507878 -0.013245557 -0.634302117 0.657625564
[91] 1.194818576 2.164643018 0.820759414 0.231560485 1.773037944
[96] -0.665733640 -2.325079501 -0.260808560 -1.386846136 1.688306144
> colMin(tmp)
[1] 1.204899088 0.187213554 -1.441011509 -1.675717809 -0.335716152
[6] 0.611069390 -0.500848854 0.123416655 0.036372286 -0.767282143
[11] 0.859109063 0.433716080 0.299727766 -1.026829043 1.640113866
[16] 1.584357050 0.162209605 -0.292422124 0.748086143 -1.294290019
[21] -0.205681369 1.405153988 1.193455303 0.021570197 -0.399397726
[26] 0.593469391 0.890359163 -0.776024179 -0.035698811 -0.600965671
[31] -1.519077905 1.095839832 -0.500009973 -0.404127134 -0.463529129
[36] -0.615731124 0.365376945 0.651423741 1.429390610 -0.598661144
[41] -0.686286759 -1.530293305 0.571164116 -0.647601723 1.347637246
[46] 0.723545458 -1.170999695 1.221344820 0.610858336 0.054065868
[51] 0.924534577 0.189367259 1.357062881 -0.177920336 -0.264676782
[56] -0.335634532 -0.831118805 -1.438269599 -1.014635118 1.077997276
[61] 0.645590009 -0.918099459 1.566057821 -0.291618145 0.259895554
[66] 0.917526115 -0.006461096 1.744550269 0.212478997 0.221294484
[71] -0.069068285 0.448030912 -0.245571204 -1.136184575 -0.418759851
[76] 1.911706777 1.008770281 0.819390713 -0.974106314 -0.808384396
[81] -0.973376506 -1.295161871 1.553452073 1.084664361 -1.237312132
[86] 1.093759214 -0.128507878 -0.013245557 -0.634302117 0.657625564
[91] 1.194818576 2.164643018 0.820759414 0.231560485 1.773037944
[96] -0.665733640 -2.325079501 -0.260808560 -1.386846136 1.688306144
> colMedians(tmp)
[1] 1.204899088 0.187213554 -1.441011509 -1.675717809 -0.335716152
[6] 0.611069390 -0.500848854 0.123416655 0.036372286 -0.767282143
[11] 0.859109063 0.433716080 0.299727766 -1.026829043 1.640113866
[16] 1.584357050 0.162209605 -0.292422124 0.748086143 -1.294290019
[21] -0.205681369 1.405153988 1.193455303 0.021570197 -0.399397726
[26] 0.593469391 0.890359163 -0.776024179 -0.035698811 -0.600965671
[31] -1.519077905 1.095839832 -0.500009973 -0.404127134 -0.463529129
[36] -0.615731124 0.365376945 0.651423741 1.429390610 -0.598661144
[41] -0.686286759 -1.530293305 0.571164116 -0.647601723 1.347637246
[46] 0.723545458 -1.170999695 1.221344820 0.610858336 0.054065868
[51] 0.924534577 0.189367259 1.357062881 -0.177920336 -0.264676782
[56] -0.335634532 -0.831118805 -1.438269599 -1.014635118 1.077997276
[61] 0.645590009 -0.918099459 1.566057821 -0.291618145 0.259895554
[66] 0.917526115 -0.006461096 1.744550269 0.212478997 0.221294484
[71] -0.069068285 0.448030912 -0.245571204 -1.136184575 -0.418759851
[76] 1.911706777 1.008770281 0.819390713 -0.974106314 -0.808384396
[81] -0.973376506 -1.295161871 1.553452073 1.084664361 -1.237312132
[86] 1.093759214 -0.128507878 -0.013245557 -0.634302117 0.657625564
[91] 1.194818576 2.164643018 0.820759414 0.231560485 1.773037944
[96] -0.665733640 -2.325079501 -0.260808560 -1.386846136 1.688306144
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.204899 0.1872136 -1.441012 -1.675718 -0.3357162 0.6110694 -0.5008489
[2,] 1.204899 0.1872136 -1.441012 -1.675718 -0.3357162 0.6110694 -0.5008489
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1234167 0.03637229 -0.7672821 0.8591091 0.4337161 0.2997278 -1.026829
[2,] 0.1234167 0.03637229 -0.7672821 0.8591091 0.4337161 0.2997278 -1.026829
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.640114 1.584357 0.1622096 -0.2924221 0.7480861 -1.29429 -0.2056814
[2,] 1.640114 1.584357 0.1622096 -0.2924221 0.7480861 -1.29429 -0.2056814
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.405154 1.193455 0.0215702 -0.3993977 0.5934694 0.8903592 -0.7760242
[2,] 1.405154 1.193455 0.0215702 -0.3993977 0.5934694 0.8903592 -0.7760242
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.03569881 -0.6009657 -1.519078 1.09584 -0.50001 -0.4041271 -0.4635291
[2,] -0.03569881 -0.6009657 -1.519078 1.09584 -0.50001 -0.4041271 -0.4635291
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.6157311 0.3653769 0.6514237 1.429391 -0.5986611 -0.6862868 -1.530293
[2,] -0.6157311 0.3653769 0.6514237 1.429391 -0.5986611 -0.6862868 -1.530293
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5711641 -0.6476017 1.347637 0.7235455 -1.171 1.221345 0.6108583
[2,] 0.5711641 -0.6476017 1.347637 0.7235455 -1.171 1.221345 0.6108583
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.05406587 0.9245346 0.1893673 1.357063 -0.1779203 -0.2646768 -0.3356345
[2,] 0.05406587 0.9245346 0.1893673 1.357063 -0.1779203 -0.2646768 -0.3356345
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.8311188 -1.43827 -1.014635 1.077997 0.64559 -0.9180995 1.566058
[2,] -0.8311188 -1.43827 -1.014635 1.077997 0.64559 -0.9180995 1.566058
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.2916181 0.2598956 0.9175261 -0.006461096 1.74455 0.212479 0.2212945
[2,] -0.2916181 0.2598956 0.9175261 -0.006461096 1.74455 0.212479 0.2212945
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.06906829 0.4480309 -0.2455712 -1.136185 -0.4187599 1.911707 1.00877
[2,] -0.06906829 0.4480309 -0.2455712 -1.136185 -0.4187599 1.911707 1.00877
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.8193907 -0.9741063 -0.8083844 -0.9733765 -1.295162 1.553452 1.084664
[2,] 0.8193907 -0.9741063 -0.8083844 -0.9733765 -1.295162 1.553452 1.084664
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.237312 1.093759 -0.1285079 -0.01324556 -0.6343021 0.6576256 1.194819
[2,] -1.237312 1.093759 -0.1285079 -0.01324556 -0.6343021 0.6576256 1.194819
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 2.164643 0.8207594 0.2315605 1.773038 -0.6657336 -2.32508 -0.2608086
[2,] 2.164643 0.8207594 0.2315605 1.773038 -0.6657336 -2.32508 -0.2608086
[,99] [,100]
[1,] -1.386846 1.688306
[2,] -1.386846 1.688306
>
>
> Max(tmp2)
[1] 1.499012
> Min(tmp2)
[1] -2.174197
> mean(tmp2)
[1] -0.1506428
> Sum(tmp2)
[1] -15.06428
> Var(tmp2)
[1] 0.7075737
>
> rowMeans(tmp2)
[1] -1.532804777 0.755305355 -1.411890174 0.239015695 -1.375045780
[6] 0.506682569 1.146436647 -0.250834906 0.596658352 0.618276084
[11] -0.139631057 -0.171916250 -0.339079757 -0.574472931 -0.681591679
[16] 0.439459054 -0.385969759 0.194056024 0.991194156 -1.405111367
[21] 0.727740314 -0.327163575 0.465415737 0.372331567 -0.400682607
[26] -1.120942296 1.223014971 -0.003302725 -0.360256367 -1.349402956
[31] -1.712623826 -1.322719067 0.521124873 1.444062702 -0.009374256
[36] -0.526724241 -1.360089687 -0.229818702 -0.076928987 0.765668637
[41] 1.045373107 -1.031411602 -0.191313755 0.688696384 0.911875745
[46] -0.819684569 -0.756479973 0.632452866 0.235994244 -0.123197879
[51] 0.024994429 -0.600639657 1.386387277 1.436545508 -0.852029798
[56] 0.783306715 -2.174197299 0.872509136 -0.243774431 -0.128612590
[61] 0.194868670 -0.321580057 -0.628308048 -1.098350723 -0.951663280
[66] -1.103975669 0.078699409 -0.379626404 0.982268176 1.056193362
[71] -1.689289902 -0.058173272 -0.589121905 -0.174007480 -1.042292464
[76] -1.674498143 -0.183158421 0.361478493 0.636928398 -0.701831659
[81] -0.593986611 0.323398200 0.241901138 1.499011627 -0.523637050
[86] -0.928415658 -1.369311706 -0.475884878 0.515431075 -0.672333875
[91] -0.823294657 1.009261779 -0.114921849 0.018901432 -1.549462348
[96] 0.703280124 -0.401736401 0.270176871 0.666695043 -0.608771327
> rowSums(tmp2)
[1] -1.532804777 0.755305355 -1.411890174 0.239015695 -1.375045780
[6] 0.506682569 1.146436647 -0.250834906 0.596658352 0.618276084
[11] -0.139631057 -0.171916250 -0.339079757 -0.574472931 -0.681591679
[16] 0.439459054 -0.385969759 0.194056024 0.991194156 -1.405111367
[21] 0.727740314 -0.327163575 0.465415737 0.372331567 -0.400682607
[26] -1.120942296 1.223014971 -0.003302725 -0.360256367 -1.349402956
[31] -1.712623826 -1.322719067 0.521124873 1.444062702 -0.009374256
[36] -0.526724241 -1.360089687 -0.229818702 -0.076928987 0.765668637
[41] 1.045373107 -1.031411602 -0.191313755 0.688696384 0.911875745
[46] -0.819684569 -0.756479973 0.632452866 0.235994244 -0.123197879
[51] 0.024994429 -0.600639657 1.386387277 1.436545508 -0.852029798
[56] 0.783306715 -2.174197299 0.872509136 -0.243774431 -0.128612590
[61] 0.194868670 -0.321580057 -0.628308048 -1.098350723 -0.951663280
[66] -1.103975669 0.078699409 -0.379626404 0.982268176 1.056193362
[71] -1.689289902 -0.058173272 -0.589121905 -0.174007480 -1.042292464
[76] -1.674498143 -0.183158421 0.361478493 0.636928398 -0.701831659
[81] -0.593986611 0.323398200 0.241901138 1.499011627 -0.523637050
[86] -0.928415658 -1.369311706 -0.475884878 0.515431075 -0.672333875
[91] -0.823294657 1.009261779 -0.114921849 0.018901432 -1.549462348
[96] 0.703280124 -0.401736401 0.270176871 0.666695043 -0.608771327
> 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] -1.532804777 0.755305355 -1.411890174 0.239015695 -1.375045780
[6] 0.506682569 1.146436647 -0.250834906 0.596658352 0.618276084
[11] -0.139631057 -0.171916250 -0.339079757 -0.574472931 -0.681591679
[16] 0.439459054 -0.385969759 0.194056024 0.991194156 -1.405111367
[21] 0.727740314 -0.327163575 0.465415737 0.372331567 -0.400682607
[26] -1.120942296 1.223014971 -0.003302725 -0.360256367 -1.349402956
[31] -1.712623826 -1.322719067 0.521124873 1.444062702 -0.009374256
[36] -0.526724241 -1.360089687 -0.229818702 -0.076928987 0.765668637
[41] 1.045373107 -1.031411602 -0.191313755 0.688696384 0.911875745
[46] -0.819684569 -0.756479973 0.632452866 0.235994244 -0.123197879
[51] 0.024994429 -0.600639657 1.386387277 1.436545508 -0.852029798
[56] 0.783306715 -2.174197299 0.872509136 -0.243774431 -0.128612590
[61] 0.194868670 -0.321580057 -0.628308048 -1.098350723 -0.951663280
[66] -1.103975669 0.078699409 -0.379626404 0.982268176 1.056193362
[71] -1.689289902 -0.058173272 -0.589121905 -0.174007480 -1.042292464
[76] -1.674498143 -0.183158421 0.361478493 0.636928398 -0.701831659
[81] -0.593986611 0.323398200 0.241901138 1.499011627 -0.523637050
[86] -0.928415658 -1.369311706 -0.475884878 0.515431075 -0.672333875
[91] -0.823294657 1.009261779 -0.114921849 0.018901432 -1.549462348
[96] 0.703280124 -0.401736401 0.270176871 0.666695043 -0.608771327
> rowMin(tmp2)
[1] -1.532804777 0.755305355 -1.411890174 0.239015695 -1.375045780
[6] 0.506682569 1.146436647 -0.250834906 0.596658352 0.618276084
[11] -0.139631057 -0.171916250 -0.339079757 -0.574472931 -0.681591679
[16] 0.439459054 -0.385969759 0.194056024 0.991194156 -1.405111367
[21] 0.727740314 -0.327163575 0.465415737 0.372331567 -0.400682607
[26] -1.120942296 1.223014971 -0.003302725 -0.360256367 -1.349402956
[31] -1.712623826 -1.322719067 0.521124873 1.444062702 -0.009374256
[36] -0.526724241 -1.360089687 -0.229818702 -0.076928987 0.765668637
[41] 1.045373107 -1.031411602 -0.191313755 0.688696384 0.911875745
[46] -0.819684569 -0.756479973 0.632452866 0.235994244 -0.123197879
[51] 0.024994429 -0.600639657 1.386387277 1.436545508 -0.852029798
[56] 0.783306715 -2.174197299 0.872509136 -0.243774431 -0.128612590
[61] 0.194868670 -0.321580057 -0.628308048 -1.098350723 -0.951663280
[66] -1.103975669 0.078699409 -0.379626404 0.982268176 1.056193362
[71] -1.689289902 -0.058173272 -0.589121905 -0.174007480 -1.042292464
[76] -1.674498143 -0.183158421 0.361478493 0.636928398 -0.701831659
[81] -0.593986611 0.323398200 0.241901138 1.499011627 -0.523637050
[86] -0.928415658 -1.369311706 -0.475884878 0.515431075 -0.672333875
[91] -0.823294657 1.009261779 -0.114921849 0.018901432 -1.549462348
[96] 0.703280124 -0.401736401 0.270176871 0.666695043 -0.608771327
>
> colMeans(tmp2)
[1] -0.1506428
> colSums(tmp2)
[1] -15.06428
> colVars(tmp2)
[1] 0.7075737
> colSd(tmp2)
[1] 0.841174
> colMax(tmp2)
[1] 1.499012
> colMin(tmp2)
[1] -2.174197
> colMedians(tmp2)
[1] -0.1729619
> colRanges(tmp2)
[,1]
[1,] -2.174197
[2,] 1.499012
>
> 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] 1.6017551 -3.1504674 0.2713777 0.4596625 -3.7146181 5.0621287
[7] -6.8429537 -2.1944742 -3.5182267 -3.1818331
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.00015494
[2,] -0.09003388
[3,] 0.20145768
[4,] 0.46639903
[5,] 1.39266047
>
> rowApply(tmp,sum)
[1] -4.369545 -1.335145 -1.223746 -2.776441 -3.988478 -1.314796 1.231512
[8] -1.918013 -1.082510 1.569511
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 9 7 6 4 7 9 9 8 6
[2,] 8 6 1 4 2 3 10 7 4 3
[3,] 9 10 4 3 9 9 7 5 1 5
[4,] 5 2 10 5 6 8 1 10 7 8
[5,] 1 8 9 2 5 6 3 2 9 4
[6,] 6 4 6 8 7 10 8 4 10 10
[7,] 2 3 5 10 1 4 6 3 3 1
[8,] 3 5 3 9 10 1 4 6 6 2
[9,] 4 1 2 7 8 5 5 1 5 9
[10,] 10 7 8 1 3 2 2 8 2 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.31602075 -0.10218193 -0.33834274 -1.24716490 -4.56149701 -0.21172103
[7] -0.89661715 1.39514566 0.37454071 -0.58962471 0.04060276 -1.35396462
[13] -3.90034105 -2.09238487 -1.61121250 2.74841780 -3.72408881 2.72892936
[19] -4.01256452 2.09930180
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8048281
[2,] -0.5183303
[3,] -0.1667254
[4,] 0.5675167
[5,] 0.6063465
>
> rowApply(tmp,sum)
[1] -10.76791234 -1.08470812 0.87507984 -4.57255294 -0.02069495
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 16 6 9 13
[2,] 9 8 5 16 15
[3,] 7 14 14 6 16
[4,] 8 17 19 8 2
[5,] 2 11 2 7 10
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1667254 -0.5065475 -0.8412639 -0.7562563 -2.5866193 0.14770565
[2,] 0.6063465 -0.3614809 0.1474830 0.8681110 -0.1336759 -1.10587503
[3,] -0.5183303 -0.5840065 0.3289404 1.4477261 -1.0405094 -0.09038399
[4,] -0.8048281 0.6570741 -0.9390907 -0.8777316 -0.9347744 0.18482405
[5,] 0.5675167 0.6927788 0.9655884 -1.9290141 0.1340820 0.65200828
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.4850215 -0.1843438 0.001221155 0.111370520 -0.3452686 -1.5125287
[2,] -0.7228352 2.0319026 1.384112275 1.177784539 -0.2241718 -0.2043436
[3,] -1.2485245 -0.2276278 1.299033478 -0.901729760 -0.6455178 0.1414460
[4,] 1.7677364 1.0231701 -1.047098912 -0.003521164 -0.4138044 0.8772900
[5,] -0.2079722 -1.2479555 -1.262727283 -0.973528841 1.6693653 -0.6558284
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -2.0590027 -0.04129845 -1.20229984 0.7270562 -2.8450316 1.49166530
[2,] -1.7993122 -1.39783140 0.09026814 -0.3723350 -0.9781257 0.08794134
[3,] -0.2657666 -0.29840931 -0.39825816 1.6746877 -0.1181702 0.97276624
[4,] -0.2435112 -1.49530779 -1.35441272 0.4414495 -1.0441376 0.70799652
[5,] 0.4672516 1.14046208 1.25349008 0.2775594 1.2613763 -0.53144003
[,19] [,20]
[1,] -1.4761964 1.7614726
[2,] 0.2254271 -0.4040979
[3,] 0.4085407 0.9391736
[4,] -1.2086353 0.1347602
[5,] -1.9617006 -0.3320068
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7398656 0.7654879 1.963517 0.772078 1.044553 -0.5856934 0.1780359
col8 col9 col10 col11 col12 col13 col14 col15
row1 -0.600441 0.1238977 -0.384021 0.9725737 2.048986 -1.35337 -1.480991 1.4221
col16 col17 col18 col19 col20
row1 -0.3279237 -0.5815999 1.606738 -1.552467 1.027538
> tmp[,"col10"]
col10
row1 -0.3840210
row2 0.9263594
row3 -0.1908025
row4 -0.4074666
row5 -1.6480934
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7398656 0.7654879 1.9635170 0.7720780 1.0445530 -0.5856934 0.17803591
row5 -0.2813905 0.4914126 0.2732324 0.6925799 -0.4148018 0.1736405 -0.06856295
col8 col9 col10 col11 col12 col13
row1 -0.6004410 0.1238977 -0.384021 0.972573744 2.0489863 -1.3533696
row5 -0.5930223 -0.3466954 -1.648093 0.001711295 -0.2645906 -0.9892354
col14 col15 col16 col17 col18 col19 col20
row1 -1.4809915 1.422100 -0.3279237 -0.5815999 1.6067384 -1.5524669 1.027538
row5 -0.6480057 -2.493634 -1.9204460 -0.1546314 -0.4700981 0.3772878 1.681434
> tmp[,c("col6","col20")]
col6 col20
row1 -0.5856934 1.0275382
row2 -0.3010327 1.4078624
row3 -0.5986304 -0.9006316
row4 0.3688578 0.9747542
row5 0.1736405 1.6814345
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.5856934 1.027538
row5 0.1736405 1.681434
>
>
>
>
> 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 49.18476 50.34458 50.84465 50.71622 50.05551 105.5156 50.69878 49.92838
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.49628 48.51089 49.50664 49.97635 49.25411 50.02754 51.10944 50.21854
col17 col18 col19 col20
row1 50.06075 50.40931 47.62072 104.8493
> tmp[,"col10"]
col10
row1 48.51089
row2 31.60250
row3 29.53089
row4 29.37842
row5 49.18924
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.18476 50.34458 50.84465 50.71622 50.05551 105.5156 50.69878 49.92838
row5 50.25760 50.93457 50.66228 48.96042 50.10826 105.8906 50.27854 50.73976
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.49628 48.51089 49.50664 49.97635 49.25411 50.02754 51.10944 50.21854
row5 49.01513 49.18924 51.04160 49.87496 52.06480 49.99056 49.25731 48.81149
col17 col18 col19 col20
row1 50.06075 50.40931 47.62072 104.8493
row5 50.29471 50.12110 52.59967 104.0370
> tmp[,c("col6","col20")]
col6 col20
row1 105.51559 104.84935
row2 75.49711 75.57323
row3 74.36191 75.18758
row4 75.63107 73.78615
row5 105.89059 104.03703
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.5156 104.8493
row5 105.8906 104.0370
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.5156 104.8493
row5 105.8906 104.0370
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8197768
[2,] -0.1612456
[3,] 0.4629231
[4,] 0.6032684
[5,] -0.4461606
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.1573924 1.08120502
[2,] -0.6181036 0.08718765
[3,] 1.4471911 0.04409273
[4,] -0.4665503 1.46332975
[5,] -2.0824030 1.28317545
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.8333298 2.23635799
[2,] 1.1774434 -0.09952232
[3,] -0.1859869 -0.73186608
[4,] 0.5753311 0.21675646
[5,] 0.7570335 -0.08169479
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.8333298
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.8333298
[2,] 1.1774434
>
>
>
> 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 0.3174311 -0.6476394 -0.1705399 -0.5583441 -0.1173769 1.25415806 0.2980339
row1 1.7625446 0.2504984 0.5778301 1.1836811 -0.4549098 0.04621704 0.2565094
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.8185140 0.7634782 1.310485 0.6677870 -1.7850860 1.9467121 -0.5662762
row1 0.3044849 0.9807236 1.083051 0.6493871 -0.3721455 -0.6213742 1.4650389
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.5367402 -0.05024006 -0.08194205 0.5862334 -1.2863768 -0.3871559
row1 -1.5835439 0.10519887 -0.56739286 1.0576313 -0.5237004 0.1026002
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.8728303 0.1108796 1.183679 -0.5291344 -0.703692 -1.170109 -0.1685034
[,8] [,9] [,10]
row2 -0.6506615 0.3582688 -0.4436657
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.81804 0.1632118 0.7371106 1.011774 1.491002 -0.9843111 -0.8349718
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.7094888 1.041275 2.529229 -1.091338 0.3264525 0.4175182 0.4457303
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.724222 0.07086711 0.3435669 -0.1244846 1.106503 1.081491
>
>
> 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: 0x5d6317cf15b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a9cf8cde9"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a9de2769a"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a93a44d38b"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a93ff16f70"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a918a92a84"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a9793ebd4e"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a9572caed"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a9120d8970"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a966935bac"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a94a2d069f"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a92ed01601"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a9696a8719"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a94e8591f1"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a9667c37cc"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a56a944421731"
>
>
> ### 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: 0x5d6317b94db0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5d6317b94db0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5d6317b94db0>
> rowMedians(tmp)
[1] -0.2619576217 0.6069478046 -0.0226468320 0.0453240382 0.4390034411
[6] -0.1047335610 0.2479553562 -0.7690133281 -0.1268271508 -0.1744845622
[11] 0.3227162343 0.0791200271 0.0411427455 -0.1856971980 -0.0478562058
[16] -0.2093833129 0.4608150944 0.4278214791 0.3657850680 -0.3928790265
[21] -0.0715773890 0.1793802825 0.5927130669 0.1178135870 -0.0009171177
[26] 0.3872562051 -0.0507904743 -0.6928488147 0.1234980489 -0.2857417364
[31] -0.0572305057 -0.1014098343 0.0890669370 0.3362453090 -0.6811494974
[36] -0.7356461235 -0.1133673567 0.4872049885 0.6524960645 0.3293351447
[41] -0.4446550660 -0.1929603581 -0.0475563260 -0.2062600467 -0.2211354513
[46] -0.2201577027 0.5933595401 0.0019853104 0.2364876132 -0.5558156171
[51] -0.0218541252 -0.1902155127 0.0350686829 0.4631848100 -0.2671817358
[56] 0.1935397118 0.0599212976 0.1675262117 -0.0925180138 -0.1544544521
[61] -0.5069250709 -0.3535602899 0.1107874555 -0.1524519928 -0.3621889227
[66] -0.3405633649 0.0265902962 0.2298102699 0.6463561030 -0.1617700724
[71] 0.0495537103 0.1629519480 0.0686673274 -0.5458616351 0.2065334996
[76] -0.2050550638 0.1118893930 -0.2876128625 -0.0879444606 0.2620016026
[81] 0.2908501485 0.0462777444 -0.4549262249 -0.4996909468 0.1483094817
[86] 0.1457247171 0.0817613565 -0.0612240326 -0.0422229690 -0.2092438693
[91] 0.1933092421 -0.3313987962 -0.0344689841 0.4401815795 -0.2809806263
[96] 0.1001455551 -0.2764819977 -0.0615214278 -0.1563872140 -0.1373950887
[101] 0.5413428273 -0.0761865514 -0.2062142271 -0.5995656564 0.2667059483
[106] -0.0996615585 0.5148114212 0.0408146946 0.0782103952 -0.0360057257
[111] 0.1252079992 0.3298152511 0.2376777528 0.1302866802 -0.1734997574
[116] -0.1533118296 0.2397706515 -0.3905999755 0.6703490348 -0.1000641803
[121] -0.3290447336 -0.3496836519 0.1794853889 -0.7102179207 -0.0946200343
[126] -0.3294848013 0.0688130622 0.2247687250 0.3210174346 0.2205696057
[131] 0.3214176006 0.2059250851 0.3389577529 -0.0525500296 -0.0208311357
[136] -0.0397431230 -0.4858748940 0.1652236727 -0.1506779183 0.0241716366
[141] -0.5617545691 -0.2531169993 -0.1009172240 -0.2893879029 -0.2290899070
[146] -0.1370036499 -0.0479330659 0.1490937545 -0.0869270292 -0.1368246327
[151] -0.1713952884 -0.0376909920 -0.1664035487 0.6167978427 0.1781477600
[156] 0.1678062871 -0.5021830935 0.0558022295 -0.3067562460 0.2578551059
[161] -0.4922147830 0.2208831554 -0.1138508809 0.2263930156 0.3741046278
[166] -0.0491799974 0.2570477882 0.1109761516 0.1161900719 -0.1531541992
[171] -0.1150408227 -0.0625169482 -0.2719509984 0.3602663716 -0.0421124660
[176] -0.0160633311 -0.1719880805 -0.3857488217 0.4147502651 0.0679778560
[181] 0.2044138416 -0.3343789584 -0.6059452023 -0.1277233872 -0.5385390843
[186] -0.2912239948 0.2790846947 0.1738515036 -0.0479569247 -0.5357351190
[191] 0.1020473134 -0.1401639139 -0.1321869534 0.0168472950 -0.3078363626
[196] 0.1940060268 -0.4791874127 -0.0793698636 0.7791187078 0.4407573971
[201] -0.4412177184 0.2257501813 -0.3646177276 -0.3243357242 0.2564653147
[206] 0.5801994989 -0.7272568107 -0.8268606574 -0.0596186491 0.0810961749
[211] 0.0362441444 -0.1037012567 -0.3293730051 -0.0552951298 0.3428610618
[216] 0.3418437890 0.4917465607 -0.0334434549 0.6944481589 -0.0771939272
[221] 0.5538798959 0.6137163099 -0.1285879740 0.0078887381 0.2010030401
[226] 0.2797650297 -0.1142357912 -0.7384487482 -0.7789681950 0.1223071877
>
> proc.time()
user system elapsed
1.427 1.435 2.850
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: 0x56efc5397b20>
> .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: 0x56efc5397b20>
> .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: 0x56efc5397b20>
> .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: 0x56efc5397b20>
> 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: 0x56efc5378410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc5378410>
> .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: 0x56efc5378410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc5378410>
> .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: 0x56efc5378410>
> 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: 0x56efc3c257a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc3c257a0>
> .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: 0x56efc3c257a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x56efc3c257a0>
> .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: 0x56efc3c257a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x56efc3c257a0>
> .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: 0x56efc3c257a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x56efc3c257a0>
> .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: 0x56efc3c257a0>
> 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: 0x56efc4bf7680>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x56efc4bf7680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc4bf7680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc4bf7680>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1a583b667fa194" "BufferedMatrixFile1a583b73ffe5af"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1a583b667fa194" "BufferedMatrixFile1a583b73ffe5af"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc498b490>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc498b490>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56efc498b490>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56efc498b490>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x56efc498b490>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x56efc498b490>
> .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: 0x56efc5fe7110>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56efc5fe7110>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x56efc5fe7110>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x56efc5fe7110>
> 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: 0x56efc608a5e0>
> .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: 0x56efc608a5e0>
> rm(P)
>
> proc.time()
user system elapsed
0.248 0.064 0.299
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
0.237 0.045 0.271