Ben Bolstad
| Snapshot Date: 2025-11-20 13:40 -0500 (Thu, 20 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 2025-11-21 11:37 -0500 (Fri, 21 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" | 4829 |
| lconway | macOS 12.7.6 Monterey | x86_64 | R Under development (unstable) (2025-10-21 r88958) -- "Unsuffered Consequences" | 4602 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4566 |
| 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 252/2327 | 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: 2025-11-20 21:40:14 -0500 (Thu, 20 Nov 2025) |
| EndedAt: 2025-11-20 21:40:39 -0500 (Thu, 20 Nov 2025) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz
###
##############################################################################
##############################################################################
* 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
0.232 0.057 0.277
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 20 21:40:29 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 20 21:40:29 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: 0x599159a515e0>
>
>
>
> 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 20 21:40:30 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 20 21:40:30 2025"
>
> ColMode(tmp2)
<pointer: 0x599159a515e0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.23999110 1.2340165 -1.52712084 -1.2933265
[2,] 0.51394380 -1.0831159 0.17535529 1.8396169
[3,] 0.02287432 0.8792101 -0.06782351 2.2234255
[4,] 1.10757395 -0.7922756 -1.88541540 -0.3428332
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.23999110 1.2340165 1.52712084 1.2933265
[2,] 0.51394380 1.0831159 0.17535529 1.8396169
[3,] 0.02287432 0.8792101 0.06782351 2.2234255
[4,] 1.10757395 0.7922756 1.88541540 0.3428332
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0119924 1.1108630 1.2357673 1.1372451
[2,] 0.7168987 1.0407285 0.4187545 1.3563248
[3,] 0.1512426 0.9376620 0.2604295 1.4911155
[4,] 1.0524134 0.8900987 1.3731043 0.5855196
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.35991 37.34265 38.88479 37.66578
[2,] 32.68293 36.49040 29.36290 40.40286
[3,] 26.53530 35.25583 27.67212 42.13458
[4,] 36.63171 34.69326 40.61646 31.19803
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5991595dc840>
> exp(tmp5)
<pointer: 0x5991595dc840>
> log(tmp5,2)
<pointer: 0x5991595dc840>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.0571
> Min(tmp5)
[1] 53.86754
> mean(tmp5)
[1] 72.13661
> Sum(tmp5)
[1] 14427.32
> Var(tmp5)
[1] 871.2326
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.78507 68.02547 66.29814 69.76263 71.79813 68.75579 72.86952 71.25860
[9] 68.91173 71.90097
> rowSums(tmp5)
[1] 1835.701 1360.509 1325.963 1395.253 1435.963 1375.116 1457.390 1425.172
[9] 1378.235 1438.019
> rowVars(tmp5)
[1] 7971.02138 69.69072 77.16964 73.55595 97.87052 75.81308
[7] 56.78844 57.72851 44.57493 110.28097
> rowSd(tmp5)
[1] 89.280577 8.348097 8.784625 8.576476 9.892953 8.707071 7.535810
[8] 7.597928 6.676446 10.501475
> rowMax(tmp5)
[1] 469.05714 86.59688 87.69761 84.76970 88.63663 87.62239 81.53746
[8] 91.62523 81.26263 93.97256
> rowMin(tmp5)
[1] 57.61720 57.21469 55.22975 53.86754 56.04151 55.64726 57.47302 62.47883
[9] 55.57103 56.29258
>
> colMeans(tmp5)
[1] 111.55177 71.15832 71.40002 73.56638 71.13166 69.04881 67.15770
[8] 65.85430 68.87090 72.26096 70.79031 68.69002 74.41185 67.69439
[15] 74.81986 66.64151 70.04525 68.97620 67.46032 71.20160
> colSums(tmp5)
[1] 1115.5177 711.5832 714.0002 735.6638 711.3166 690.4881 671.5770
[8] 658.5430 688.7090 722.6096 707.9031 686.9002 744.1185 676.9439
[15] 748.1986 666.4151 700.4525 689.7620 674.6032 712.0160
> colVars(tmp5)
[1] 15835.94701 31.94539 113.02378 104.65565 55.77029 48.32572
[7] 114.76631 72.46449 147.30383 115.97235 57.04840 61.01881
[13] 131.00140 57.29818 32.85623 64.24836 45.98783 102.20377
[19] 48.04150 73.28403
> colSd(tmp5)
[1] 125.840959 5.652025 10.631264 10.230134 7.467951 6.951671
[7] 10.712904 8.512608 12.136879 10.769046 7.553039 7.811454
[13] 11.445584 7.569556 5.732036 8.015507 6.781432 10.109588
[19] 6.931198 8.560609
> colMax(tmp5)
[1] 469.05714 77.72383 84.53784 87.69761 80.51386 77.77928 91.62523
[8] 80.31999 87.62239 91.67830 79.17865 81.78834 93.97256 81.41319
[15] 83.38496 80.54566 80.04166 86.59688 78.90349 86.94589
> colMin(tmp5)
[1] 55.22975 58.09026 57.59589 57.40413 60.75287 56.04151 56.29258 53.86754
[9] 58.03233 57.61720 57.21469 60.31553 62.81337 55.64726 66.21641 57.47302
[17] 59.86960 55.38728 57.44773 59.89843
>
>
> ### 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] 91.78507 68.02547 66.29814 69.76263 71.79813 NA 72.86952 71.25860
[9] 68.91173 71.90097
> rowSums(tmp5)
[1] 1835.701 1360.509 1325.963 1395.253 1435.963 NA 1457.390 1425.172
[9] 1378.235 1438.019
> rowVars(tmp5)
[1] 7971.02138 69.69072 77.16964 73.55595 97.87052 77.12896
[7] 56.78844 57.72851 44.57493 110.28097
> rowSd(tmp5)
[1] 89.280577 8.348097 8.784625 8.576476 9.892953 8.782309 7.535810
[8] 7.597928 6.676446 10.501475
> rowMax(tmp5)
[1] 469.05714 86.59688 87.69761 84.76970 88.63663 NA 81.53746
[8] 91.62523 81.26263 93.97256
> rowMin(tmp5)
[1] 57.61720 57.21469 55.22975 53.86754 56.04151 NA 57.47302 62.47883
[9] 55.57103 56.29258
>
> colMeans(tmp5)
[1] 111.55177 71.15832 71.40002 73.56638 71.13166 69.04881 67.15770
[8] NA 68.87090 72.26096 70.79031 68.69002 74.41185 67.69439
[15] 74.81986 66.64151 70.04525 68.97620 67.46032 71.20160
> colSums(tmp5)
[1] 1115.5177 711.5832 714.0002 735.6638 711.3166 690.4881 671.5770
[8] NA 688.7090 722.6096 707.9031 686.9002 744.1185 676.9439
[15] 748.1986 666.4151 700.4525 689.7620 674.6032 712.0160
> colVars(tmp5)
[1] 15835.94701 31.94539 113.02378 104.65565 55.77029 48.32572
[7] 114.76631 NA 147.30383 115.97235 57.04840 61.01881
[13] 131.00140 57.29818 32.85623 64.24836 45.98783 102.20377
[19] 48.04150 73.28403
> colSd(tmp5)
[1] 125.840959 5.652025 10.631264 10.230134 7.467951 6.951671
[7] 10.712904 NA 12.136879 10.769046 7.553039 7.811454
[13] 11.445584 7.569556 5.732036 8.015507 6.781432 10.109588
[19] 6.931198 8.560609
> colMax(tmp5)
[1] 469.05714 77.72383 84.53784 87.69761 80.51386 77.77928 91.62523
[8] NA 87.62239 91.67830 79.17865 81.78834 93.97256 81.41319
[15] 83.38496 80.54566 80.04166 86.59688 78.90349 86.94589
> colMin(tmp5)
[1] 55.22975 58.09026 57.59589 57.40413 60.75287 56.04151 56.29258 NA
[9] 58.03233 57.61720 57.21469 60.31553 62.81337 55.64726 66.21641 57.47302
[17] 59.86960 55.38728 57.44773 59.89843
>
> Max(tmp5,na.rm=TRUE)
[1] 469.0571
> Min(tmp5,na.rm=TRUE)
[1] 53.86754
> mean(tmp5,na.rm=TRUE)
[1] 72.18896
> Sum(tmp5,na.rm=TRUE)
[1] 14365.6
> Var(tmp5,na.rm=TRUE)
[1] 875.0819
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.78507 68.02547 66.29814 69.76263 71.79813 69.12617 72.86952 71.25860
[9] 68.91173 71.90097
> rowSums(tmp5,na.rm=TRUE)
[1] 1835.701 1360.509 1325.963 1395.253 1435.963 1313.397 1457.390 1425.172
[9] 1378.235 1438.019
> rowVars(tmp5,na.rm=TRUE)
[1] 7971.02138 69.69072 77.16964 73.55595 97.87052 77.12896
[7] 56.78844 57.72851 44.57493 110.28097
> rowSd(tmp5,na.rm=TRUE)
[1] 89.280577 8.348097 8.784625 8.576476 9.892953 8.782309 7.535810
[8] 7.597928 6.676446 10.501475
> rowMax(tmp5,na.rm=TRUE)
[1] 469.05714 86.59688 87.69761 84.76970 88.63663 87.62239 81.53746
[8] 91.62523 81.26263 93.97256
> rowMin(tmp5,na.rm=TRUE)
[1] 57.61720 57.21469 55.22975 53.86754 56.04151 55.64726 57.47302 62.47883
[9] 55.57103 56.29258
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.55177 71.15832 71.40002 73.56638 71.13166 69.04881 67.15770
[8] 66.31381 68.87090 72.26096 70.79031 68.69002 74.41185 67.69439
[15] 74.81986 66.64151 70.04525 68.97620 67.46032 71.20160
> colSums(tmp5,na.rm=TRUE)
[1] 1115.5177 711.5832 714.0002 735.6638 711.3166 690.4881 671.5770
[8] 596.8243 688.7090 722.6096 707.9031 686.9002 744.1185 676.9439
[15] 748.1986 666.4151 700.4525 689.7620 674.6032 712.0160
> colVars(tmp5,na.rm=TRUE)
[1] 15835.94701 31.94539 113.02378 104.65565 55.77029 48.32572
[7] 114.76631 79.14709 147.30383 115.97235 57.04840 61.01881
[13] 131.00140 57.29818 32.85623 64.24836 45.98783 102.20377
[19] 48.04150 73.28403
> colSd(tmp5,na.rm=TRUE)
[1] 125.840959 5.652025 10.631264 10.230134 7.467951 6.951671
[7] 10.712904 8.896465 12.136879 10.769046 7.553039 7.811454
[13] 11.445584 7.569556 5.732036 8.015507 6.781432 10.109588
[19] 6.931198 8.560609
> colMax(tmp5,na.rm=TRUE)
[1] 469.05714 77.72383 84.53784 87.69761 80.51386 77.77928 91.62523
[8] 80.31999 87.62239 91.67830 79.17865 81.78834 93.97256 81.41319
[15] 83.38496 80.54566 80.04166 86.59688 78.90349 86.94589
> colMin(tmp5,na.rm=TRUE)
[1] 55.22975 58.09026 57.59589 57.40413 60.75287 56.04151 56.29258 53.86754
[9] 58.03233 57.61720 57.21469 60.31553 62.81337 55.64726 66.21641 57.47302
[17] 59.86960 55.38728 57.44773 59.89843
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.78507 68.02547 66.29814 69.76263 71.79813 NaN 72.86952 71.25860
[9] 68.91173 71.90097
> rowSums(tmp5,na.rm=TRUE)
[1] 1835.701 1360.509 1325.963 1395.253 1435.963 0.000 1457.390 1425.172
[9] 1378.235 1438.019
> rowVars(tmp5,na.rm=TRUE)
[1] 7971.02138 69.69072 77.16964 73.55595 97.87052 NA
[7] 56.78844 57.72851 44.57493 110.28097
> rowSd(tmp5,na.rm=TRUE)
[1] 89.280577 8.348097 8.784625 8.576476 9.892953 NA 7.535810
[8] 7.597928 6.676446 10.501475
> rowMax(tmp5,na.rm=TRUE)
[1] 469.05714 86.59688 87.69761 84.76970 88.63663 NA 81.53746
[8] 91.62523 81.26263 93.97256
> rowMin(tmp5,na.rm=TRUE)
[1] 57.61720 57.21469 55.22975 53.86754 56.04151 NA 57.47302 62.47883
[9] 55.57103 56.29258
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.46274 71.30019 70.16998 75.36218 70.59752 69.50817 67.85063
[8] NaN 66.78740 71.84527 70.92842 69.25628 75.70057 69.03296
[15] 74.52934 65.87498 71.17588 69.91761 66.79213 70.83897
> colSums(tmp5,na.rm=TRUE)
[1] 1048.1647 641.7017 631.5299 678.2596 635.3777 625.5735 610.6557
[8] 0.0000 601.0866 646.6074 638.3558 623.3065 681.3051 621.2967
[15] 670.7641 592.8748 640.5829 629.2585 601.1292 637.5507
> colVars(tmp5,na.rm=TRUE)
[1] 17544.11699 35.71213 110.13075 81.45731 59.53188 51.99258
[7] 123.71032 NA 116.88089 128.52494 63.96485 65.03887
[13] 128.69258 44.30304 36.01379 65.66917 37.35521 105.00902
[19] 49.02381 80.96511
> colSd(tmp5,na.rm=TRUE)
[1] 132.454207 5.975963 10.494320 9.025370 7.715690 7.210588
[7] 11.122514 NA 10.811146 11.336884 7.997803 8.064668
[13] 11.344275 6.656053 6.001149 8.103652 6.111891 10.247391
[19] 7.001701 8.998061
> colMax(tmp5,na.rm=TRUE)
[1] 469.05714 77.72383 84.53784 87.69761 80.51386 77.77928 91.62523
[8] -Inf 87.23891 91.67830 79.17865 81.78834 93.97256 81.41319
[15] 83.38496 80.54566 80.04166 86.59688 78.90349 86.94589
> colMin(tmp5,na.rm=TRUE)
[1] 55.22975 58.09026 57.59589 64.70134 60.75287 56.04151 56.29258 Inf
[9] 58.03233 57.61720 57.21469 60.31553 63.30662 59.81969 66.21641 57.47302
[17] 62.20839 55.38728 57.44773 59.89843
>
>
>
>
> 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] 339.1880 210.4340 162.4782 188.8520 210.2840 179.2893 169.1682 183.1299
[9] 270.9810 423.0213
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 339.1880 210.4340 162.4782 188.8520 210.2840 179.2893 169.1682 183.1299
[9] 270.9810 423.0213
>
>
>
> 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 5.684342e-14 -1.278977e-13 -2.842171e-14 0.000000e+00
[6] -5.684342e-14 0.000000e+00 -2.842171e-14 0.000000e+00 1.136868e-13
[11] -1.421085e-14 8.526513e-14 1.989520e-13 -2.842171e-14 -2.842171e-14
[16] -1.705303e-13 -2.842171e-14 7.105427e-14 1.136868e-13 -5.684342e-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)
+ }
9 7
2 14
7 18
7 18
5 16
9 3
1 13
10 16
5 6
1 3
4 12
2 12
10 8
5 15
2 3
6 15
10 11
2 18
1 3
6 16
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] 3.004327
> Min(tmp)
[1] -2.747788
> mean(tmp)
[1] -0.04017242
> Sum(tmp)
[1] -4.017242
> Var(tmp)
[1] 1.140271
>
> rowMeans(tmp)
[1] -0.04017242
> rowSums(tmp)
[1] -4.017242
> rowVars(tmp)
[1] 1.140271
> rowSd(tmp)
[1] 1.067835
> rowMax(tmp)
[1] 3.004327
> rowMin(tmp)
[1] -2.747788
>
> colMeans(tmp)
[1] 0.2080320619 -0.1831101674 1.1338262133 -1.6641497321 0.1374529907
[6] -0.1886308648 0.4718324140 -0.2016269222 0.7331452010 -0.3152626997
[11] -1.2823848567 0.3959159359 -1.8940463179 -1.4353167770 0.0760231296
[16] 1.0781519217 1.0406681674 -0.8415294995 -2.1068878113 -1.5738527397
[21] 0.9557305015 0.3325822343 1.4381155103 1.6071465419 -0.6037385547
[26] 0.3945756781 1.7653928045 -1.0905990882 -0.4886529390 -0.0193618217
[31] 2.5332567028 3.0043266199 -0.2409388814 -0.3050105928 -0.8719212331
[36] -0.4340824516 1.2996310237 -0.6595104954 -0.7301950782 0.4747275805
[41] 1.0811390956 0.4529926642 0.6553142831 -0.8781796757 0.1083463410
[46] 0.4447186580 -0.6139272654 0.5053742806 0.6086741719 0.4173722906
[51] 0.0819449328 -0.0005546239 1.3599700725 -0.7467131282 -1.5387796292
[56] 1.3519371471 -0.5811549006 -0.4969090906 -0.6935617937 -0.1563664970
[61] 0.1166738914 0.2436777689 1.4962049359 0.1467955140 0.0368208397
[66] -0.0558705928 -0.6700344057 2.2350976646 -1.2773421294 0.4692386731
[71] 1.9651854930 0.9702516556 -1.1336897232 0.1551675476 -1.1730410571
[76] 0.9128910993 -1.9735918110 0.4515807969 -2.7477880197 0.6656969068
[81] -1.8659980274 -0.9449212142 -0.7435498842 0.0093051206 -0.9091375298
[86] 1.0060042814 -0.3158523789 -0.2978918619 -1.8981981333 -0.1059745837
[91] -1.6018213952 -0.9980535045 0.4305093555 1.2275359161 -0.0882918809
[96] -0.8904052909 0.9850032171 -0.5660812901 -0.8764326173 0.2817232287
> colSums(tmp)
[1] 0.2080320619 -0.1831101674 1.1338262133 -1.6641497321 0.1374529907
[6] -0.1886308648 0.4718324140 -0.2016269222 0.7331452010 -0.3152626997
[11] -1.2823848567 0.3959159359 -1.8940463179 -1.4353167770 0.0760231296
[16] 1.0781519217 1.0406681674 -0.8415294995 -2.1068878113 -1.5738527397
[21] 0.9557305015 0.3325822343 1.4381155103 1.6071465419 -0.6037385547
[26] 0.3945756781 1.7653928045 -1.0905990882 -0.4886529390 -0.0193618217
[31] 2.5332567028 3.0043266199 -0.2409388814 -0.3050105928 -0.8719212331
[36] -0.4340824516 1.2996310237 -0.6595104954 -0.7301950782 0.4747275805
[41] 1.0811390956 0.4529926642 0.6553142831 -0.8781796757 0.1083463410
[46] 0.4447186580 -0.6139272654 0.5053742806 0.6086741719 0.4173722906
[51] 0.0819449328 -0.0005546239 1.3599700725 -0.7467131282 -1.5387796292
[56] 1.3519371471 -0.5811549006 -0.4969090906 -0.6935617937 -0.1563664970
[61] 0.1166738914 0.2436777689 1.4962049359 0.1467955140 0.0368208397
[66] -0.0558705928 -0.6700344057 2.2350976646 -1.2773421294 0.4692386731
[71] 1.9651854930 0.9702516556 -1.1336897232 0.1551675476 -1.1730410571
[76] 0.9128910993 -1.9735918110 0.4515807969 -2.7477880197 0.6656969068
[81] -1.8659980274 -0.9449212142 -0.7435498842 0.0093051206 -0.9091375298
[86] 1.0060042814 -0.3158523789 -0.2978918619 -1.8981981333 -0.1059745837
[91] -1.6018213952 -0.9980535045 0.4305093555 1.2275359161 -0.0882918809
[96] -0.8904052909 0.9850032171 -0.5660812901 -0.8764326173 0.2817232287
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.2080320619 -0.1831101674 1.1338262133 -1.6641497321 0.1374529907
[6] -0.1886308648 0.4718324140 -0.2016269222 0.7331452010 -0.3152626997
[11] -1.2823848567 0.3959159359 -1.8940463179 -1.4353167770 0.0760231296
[16] 1.0781519217 1.0406681674 -0.8415294995 -2.1068878113 -1.5738527397
[21] 0.9557305015 0.3325822343 1.4381155103 1.6071465419 -0.6037385547
[26] 0.3945756781 1.7653928045 -1.0905990882 -0.4886529390 -0.0193618217
[31] 2.5332567028 3.0043266199 -0.2409388814 -0.3050105928 -0.8719212331
[36] -0.4340824516 1.2996310237 -0.6595104954 -0.7301950782 0.4747275805
[41] 1.0811390956 0.4529926642 0.6553142831 -0.8781796757 0.1083463410
[46] 0.4447186580 -0.6139272654 0.5053742806 0.6086741719 0.4173722906
[51] 0.0819449328 -0.0005546239 1.3599700725 -0.7467131282 -1.5387796292
[56] 1.3519371471 -0.5811549006 -0.4969090906 -0.6935617937 -0.1563664970
[61] 0.1166738914 0.2436777689 1.4962049359 0.1467955140 0.0368208397
[66] -0.0558705928 -0.6700344057 2.2350976646 -1.2773421294 0.4692386731
[71] 1.9651854930 0.9702516556 -1.1336897232 0.1551675476 -1.1730410571
[76] 0.9128910993 -1.9735918110 0.4515807969 -2.7477880197 0.6656969068
[81] -1.8659980274 -0.9449212142 -0.7435498842 0.0093051206 -0.9091375298
[86] 1.0060042814 -0.3158523789 -0.2978918619 -1.8981981333 -0.1059745837
[91] -1.6018213952 -0.9980535045 0.4305093555 1.2275359161 -0.0882918809
[96] -0.8904052909 0.9850032171 -0.5660812901 -0.8764326173 0.2817232287
> colMin(tmp)
[1] 0.2080320619 -0.1831101674 1.1338262133 -1.6641497321 0.1374529907
[6] -0.1886308648 0.4718324140 -0.2016269222 0.7331452010 -0.3152626997
[11] -1.2823848567 0.3959159359 -1.8940463179 -1.4353167770 0.0760231296
[16] 1.0781519217 1.0406681674 -0.8415294995 -2.1068878113 -1.5738527397
[21] 0.9557305015 0.3325822343 1.4381155103 1.6071465419 -0.6037385547
[26] 0.3945756781 1.7653928045 -1.0905990882 -0.4886529390 -0.0193618217
[31] 2.5332567028 3.0043266199 -0.2409388814 -0.3050105928 -0.8719212331
[36] -0.4340824516 1.2996310237 -0.6595104954 -0.7301950782 0.4747275805
[41] 1.0811390956 0.4529926642 0.6553142831 -0.8781796757 0.1083463410
[46] 0.4447186580 -0.6139272654 0.5053742806 0.6086741719 0.4173722906
[51] 0.0819449328 -0.0005546239 1.3599700725 -0.7467131282 -1.5387796292
[56] 1.3519371471 -0.5811549006 -0.4969090906 -0.6935617937 -0.1563664970
[61] 0.1166738914 0.2436777689 1.4962049359 0.1467955140 0.0368208397
[66] -0.0558705928 -0.6700344057 2.2350976646 -1.2773421294 0.4692386731
[71] 1.9651854930 0.9702516556 -1.1336897232 0.1551675476 -1.1730410571
[76] 0.9128910993 -1.9735918110 0.4515807969 -2.7477880197 0.6656969068
[81] -1.8659980274 -0.9449212142 -0.7435498842 0.0093051206 -0.9091375298
[86] 1.0060042814 -0.3158523789 -0.2978918619 -1.8981981333 -0.1059745837
[91] -1.6018213952 -0.9980535045 0.4305093555 1.2275359161 -0.0882918809
[96] -0.8904052909 0.9850032171 -0.5660812901 -0.8764326173 0.2817232287
> colMedians(tmp)
[1] 0.2080320619 -0.1831101674 1.1338262133 -1.6641497321 0.1374529907
[6] -0.1886308648 0.4718324140 -0.2016269222 0.7331452010 -0.3152626997
[11] -1.2823848567 0.3959159359 -1.8940463179 -1.4353167770 0.0760231296
[16] 1.0781519217 1.0406681674 -0.8415294995 -2.1068878113 -1.5738527397
[21] 0.9557305015 0.3325822343 1.4381155103 1.6071465419 -0.6037385547
[26] 0.3945756781 1.7653928045 -1.0905990882 -0.4886529390 -0.0193618217
[31] 2.5332567028 3.0043266199 -0.2409388814 -0.3050105928 -0.8719212331
[36] -0.4340824516 1.2996310237 -0.6595104954 -0.7301950782 0.4747275805
[41] 1.0811390956 0.4529926642 0.6553142831 -0.8781796757 0.1083463410
[46] 0.4447186580 -0.6139272654 0.5053742806 0.6086741719 0.4173722906
[51] 0.0819449328 -0.0005546239 1.3599700725 -0.7467131282 -1.5387796292
[56] 1.3519371471 -0.5811549006 -0.4969090906 -0.6935617937 -0.1563664970
[61] 0.1166738914 0.2436777689 1.4962049359 0.1467955140 0.0368208397
[66] -0.0558705928 -0.6700344057 2.2350976646 -1.2773421294 0.4692386731
[71] 1.9651854930 0.9702516556 -1.1336897232 0.1551675476 -1.1730410571
[76] 0.9128910993 -1.9735918110 0.4515807969 -2.7477880197 0.6656969068
[81] -1.8659980274 -0.9449212142 -0.7435498842 0.0093051206 -0.9091375298
[86] 1.0060042814 -0.3158523789 -0.2978918619 -1.8981981333 -0.1059745837
[91] -1.6018213952 -0.9980535045 0.4305093555 1.2275359161 -0.0882918809
[96] -0.8904052909 0.9850032171 -0.5660812901 -0.8764326173 0.2817232287
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.2080321 -0.1831102 1.133826 -1.66415 0.137453 -0.1886309 0.4718324
[2,] 0.2080321 -0.1831102 1.133826 -1.66415 0.137453 -0.1886309 0.4718324
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.2016269 0.7331452 -0.3152627 -1.282385 0.3959159 -1.894046 -1.435317
[2,] -0.2016269 0.7331452 -0.3152627 -1.282385 0.3959159 -1.894046 -1.435317
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.07602313 1.078152 1.040668 -0.8415295 -2.106888 -1.573853 0.9557305
[2,] 0.07602313 1.078152 1.040668 -0.8415295 -2.106888 -1.573853 0.9557305
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.3325822 1.438116 1.607147 -0.6037386 0.3945757 1.765393 -1.090599
[2,] 0.3325822 1.438116 1.607147 -0.6037386 0.3945757 1.765393 -1.090599
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.4886529 -0.01936182 2.533257 3.004327 -0.2409389 -0.3050106 -0.8719212
[2,] -0.4886529 -0.01936182 2.533257 3.004327 -0.2409389 -0.3050106 -0.8719212
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.4340825 1.299631 -0.6595105 -0.7301951 0.4747276 1.081139 0.4529927
[2,] -0.4340825 1.299631 -0.6595105 -0.7301951 0.4747276 1.081139 0.4529927
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.6553143 -0.8781797 0.1083463 0.4447187 -0.6139273 0.5053743 0.6086742
[2,] 0.6553143 -0.8781797 0.1083463 0.4447187 -0.6139273 0.5053743 0.6086742
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.4173723 0.08194493 -0.0005546239 1.35997 -0.7467131 -1.53878 1.351937
[2,] 0.4173723 0.08194493 -0.0005546239 1.35997 -0.7467131 -1.53878 1.351937
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5811549 -0.4969091 -0.6935618 -0.1563665 0.1166739 0.2436778 1.496205
[2,] -0.5811549 -0.4969091 -0.6935618 -0.1563665 0.1166739 0.2436778 1.496205
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.1467955 0.03682084 -0.05587059 -0.6700344 2.235098 -1.277342 0.4692387
[2,] 0.1467955 0.03682084 -0.05587059 -0.6700344 2.235098 -1.277342 0.4692387
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.965185 0.9702517 -1.13369 0.1551675 -1.173041 0.9128911 -1.973592
[2,] 1.965185 0.9702517 -1.13369 0.1551675 -1.173041 0.9128911 -1.973592
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.4515808 -2.747788 0.6656969 -1.865998 -0.9449212 -0.7435499 0.009305121
[2,] 0.4515808 -2.747788 0.6656969 -1.865998 -0.9449212 -0.7435499 0.009305121
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.9091375 1.006004 -0.3158524 -0.2978919 -1.898198 -0.1059746 -1.601821
[2,] -0.9091375 1.006004 -0.3158524 -0.2978919 -1.898198 -0.1059746 -1.601821
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.9980535 0.4305094 1.227536 -0.08829188 -0.8904053 0.9850032 -0.5660813
[2,] -0.9980535 0.4305094 1.227536 -0.08829188 -0.8904053 0.9850032 -0.5660813
[,99] [,100]
[1,] -0.8764326 0.2817232
[2,] -0.8764326 0.2817232
>
>
> Max(tmp2)
[1] 2.172104
> Min(tmp2)
[1] -2.008969
> mean(tmp2)
[1] 0.09742505
> Sum(tmp2)
[1] 9.742505
> Var(tmp2)
[1] 0.9209302
>
> rowMeans(tmp2)
[1] 0.9319008628 -0.6243616820 -0.7841273933 1.2135578954 -2.0089691975
[6] 1.3439922570 1.1926206357 0.2408637431 0.9877788873 -0.0071967536
[11] -0.9280216977 -0.5896874695 1.4874251911 0.6678224067 -0.5620801309
[16] -0.1034709512 0.5224326947 0.1205902347 0.4697239234 -0.1027141654
[21] 0.0121100209 0.8627866244 1.8458706010 -1.4227673332 -0.1105513271
[26] -1.8249260226 -0.7060946187 1.4557957775 -0.9175870143 0.8065569110
[31] 1.7063546256 -0.3591379612 -1.0735580425 0.3124339201 1.6615516657
[36] 0.5631701114 1.2733020284 -0.9736644948 -0.7038470089 -1.3755977138
[41] 0.3853653228 0.5644997152 -0.5825525725 0.5819385125 -0.4851016728
[46] 1.8495315914 0.1788882744 1.3291051366 0.7503365751 -1.2231903578
[51] 1.6472186778 -0.9171919407 -0.4738759176 -0.2240577447 1.1620277842
[56] -1.0892578393 -0.1861277447 0.2356140168 -1.3042883800 1.8534369509
[61] 0.0001593876 -0.6875723676 -0.0877904590 -0.4069577847 0.1732413260
[66] -0.3998525373 0.8099159685 -0.5017249268 -0.7872147140 -1.6335178169
[71] 0.0048415825 0.1545952139 1.0102723972 -0.0631730505 0.1122243781
[76] 0.2167048739 -0.8825951175 0.9270789384 -1.5584221294 -1.6173560929
[81] -1.2068796919 2.1721037093 1.6674254786 0.7203570748 -0.5786885806
[86] 0.5922850615 0.6757353792 0.3972937319 -0.9690287158 -0.0283812383
[91] -0.1558191641 0.3825004771 0.2843724403 1.1312260831 0.0212481425
[96] -0.1930897675 0.6514492147 1.0747472917 0.8448595839 -1.0766670699
> rowSums(tmp2)
[1] 0.9319008628 -0.6243616820 -0.7841273933 1.2135578954 -2.0089691975
[6] 1.3439922570 1.1926206357 0.2408637431 0.9877788873 -0.0071967536
[11] -0.9280216977 -0.5896874695 1.4874251911 0.6678224067 -0.5620801309
[16] -0.1034709512 0.5224326947 0.1205902347 0.4697239234 -0.1027141654
[21] 0.0121100209 0.8627866244 1.8458706010 -1.4227673332 -0.1105513271
[26] -1.8249260226 -0.7060946187 1.4557957775 -0.9175870143 0.8065569110
[31] 1.7063546256 -0.3591379612 -1.0735580425 0.3124339201 1.6615516657
[36] 0.5631701114 1.2733020284 -0.9736644948 -0.7038470089 -1.3755977138
[41] 0.3853653228 0.5644997152 -0.5825525725 0.5819385125 -0.4851016728
[46] 1.8495315914 0.1788882744 1.3291051366 0.7503365751 -1.2231903578
[51] 1.6472186778 -0.9171919407 -0.4738759176 -0.2240577447 1.1620277842
[56] -1.0892578393 -0.1861277447 0.2356140168 -1.3042883800 1.8534369509
[61] 0.0001593876 -0.6875723676 -0.0877904590 -0.4069577847 0.1732413260
[66] -0.3998525373 0.8099159685 -0.5017249268 -0.7872147140 -1.6335178169
[71] 0.0048415825 0.1545952139 1.0102723972 -0.0631730505 0.1122243781
[76] 0.2167048739 -0.8825951175 0.9270789384 -1.5584221294 -1.6173560929
[81] -1.2068796919 2.1721037093 1.6674254786 0.7203570748 -0.5786885806
[86] 0.5922850615 0.6757353792 0.3972937319 -0.9690287158 -0.0283812383
[91] -0.1558191641 0.3825004771 0.2843724403 1.1312260831 0.0212481425
[96] -0.1930897675 0.6514492147 1.0747472917 0.8448595839 -1.0766670699
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.9319008628 -0.6243616820 -0.7841273933 1.2135578954 -2.0089691975
[6] 1.3439922570 1.1926206357 0.2408637431 0.9877788873 -0.0071967536
[11] -0.9280216977 -0.5896874695 1.4874251911 0.6678224067 -0.5620801309
[16] -0.1034709512 0.5224326947 0.1205902347 0.4697239234 -0.1027141654
[21] 0.0121100209 0.8627866244 1.8458706010 -1.4227673332 -0.1105513271
[26] -1.8249260226 -0.7060946187 1.4557957775 -0.9175870143 0.8065569110
[31] 1.7063546256 -0.3591379612 -1.0735580425 0.3124339201 1.6615516657
[36] 0.5631701114 1.2733020284 -0.9736644948 -0.7038470089 -1.3755977138
[41] 0.3853653228 0.5644997152 -0.5825525725 0.5819385125 -0.4851016728
[46] 1.8495315914 0.1788882744 1.3291051366 0.7503365751 -1.2231903578
[51] 1.6472186778 -0.9171919407 -0.4738759176 -0.2240577447 1.1620277842
[56] -1.0892578393 -0.1861277447 0.2356140168 -1.3042883800 1.8534369509
[61] 0.0001593876 -0.6875723676 -0.0877904590 -0.4069577847 0.1732413260
[66] -0.3998525373 0.8099159685 -0.5017249268 -0.7872147140 -1.6335178169
[71] 0.0048415825 0.1545952139 1.0102723972 -0.0631730505 0.1122243781
[76] 0.2167048739 -0.8825951175 0.9270789384 -1.5584221294 -1.6173560929
[81] -1.2068796919 2.1721037093 1.6674254786 0.7203570748 -0.5786885806
[86] 0.5922850615 0.6757353792 0.3972937319 -0.9690287158 -0.0283812383
[91] -0.1558191641 0.3825004771 0.2843724403 1.1312260831 0.0212481425
[96] -0.1930897675 0.6514492147 1.0747472917 0.8448595839 -1.0766670699
> rowMin(tmp2)
[1] 0.9319008628 -0.6243616820 -0.7841273933 1.2135578954 -2.0089691975
[6] 1.3439922570 1.1926206357 0.2408637431 0.9877788873 -0.0071967536
[11] -0.9280216977 -0.5896874695 1.4874251911 0.6678224067 -0.5620801309
[16] -0.1034709512 0.5224326947 0.1205902347 0.4697239234 -0.1027141654
[21] 0.0121100209 0.8627866244 1.8458706010 -1.4227673332 -0.1105513271
[26] -1.8249260226 -0.7060946187 1.4557957775 -0.9175870143 0.8065569110
[31] 1.7063546256 -0.3591379612 -1.0735580425 0.3124339201 1.6615516657
[36] 0.5631701114 1.2733020284 -0.9736644948 -0.7038470089 -1.3755977138
[41] 0.3853653228 0.5644997152 -0.5825525725 0.5819385125 -0.4851016728
[46] 1.8495315914 0.1788882744 1.3291051366 0.7503365751 -1.2231903578
[51] 1.6472186778 -0.9171919407 -0.4738759176 -0.2240577447 1.1620277842
[56] -1.0892578393 -0.1861277447 0.2356140168 -1.3042883800 1.8534369509
[61] 0.0001593876 -0.6875723676 -0.0877904590 -0.4069577847 0.1732413260
[66] -0.3998525373 0.8099159685 -0.5017249268 -0.7872147140 -1.6335178169
[71] 0.0048415825 0.1545952139 1.0102723972 -0.0631730505 0.1122243781
[76] 0.2167048739 -0.8825951175 0.9270789384 -1.5584221294 -1.6173560929
[81] -1.2068796919 2.1721037093 1.6674254786 0.7203570748 -0.5786885806
[86] 0.5922850615 0.6757353792 0.3972937319 -0.9690287158 -0.0283812383
[91] -0.1558191641 0.3825004771 0.2843724403 1.1312260831 0.0212481425
[96] -0.1930897675 0.6514492147 1.0747472917 0.8448595839 -1.0766670699
>
> colMeans(tmp2)
[1] 0.09742505
> colSums(tmp2)
[1] 9.742505
> colVars(tmp2)
[1] 0.9209302
> colSd(tmp2)
[1] 0.9596511
> colMax(tmp2)
[1] 2.172104
> colMin(tmp2)
[1] -2.008969
> colMedians(tmp2)
[1] 0.06673626
> colRanges(tmp2)
[,1]
[1,] -2.008969
[2,] 2.172104
>
> 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] 3.5693286 2.1985269 -1.4217311 7.8709158 2.6042230 -0.7743964
[7] -4.5041503 -6.1885200 -0.8911972 -6.2999671
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6658882
[2,] -0.2991839
[3,] 0.1876897
[4,] 0.9360707
[5,] 1.8159347
>
> rowApply(tmp,sum)
[1] 1.3699203 -2.9764374 -7.1080987 -6.4235720 -1.1974427 -1.6820539
[7] 6.3677435 3.9721043 -0.1125986 3.9534673
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 9 8 7 5 9 5 2 7 10
[2,] 6 3 7 9 9 5 7 3 10 4
[3,] 9 7 1 6 10 1 3 4 6 5
[4,] 7 10 10 10 4 8 10 1 9 6
[5,] 10 4 6 2 3 7 8 10 5 7
[6,] 2 8 9 8 6 4 1 6 3 9
[7,] 4 5 5 5 2 3 2 7 2 8
[8,] 1 2 4 3 8 2 4 5 8 2
[9,] 5 1 3 4 7 10 6 9 4 3
[10,] 8 6 2 1 1 6 9 8 1 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.0665794 1.1083662 0.4570445 4.3964713 1.4226053 1.2397331
[7] -2.7567706 -4.0006357 -3.1628241 1.5521451 -2.2001426 5.5043057
[13] 1.8884853 -3.3694494 -6.1699255 1.6904566 -1.3670334 -0.7350483
[19] 1.1715267 5.1420268
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8487959
[2,] -0.2572228
[3,] 1.0878434
[4,] 1.4699109
[5,] 1.6148438
>
> rowApply(tmp,sum)
[1] 2.755530 1.348999 6.088193 -2.340629 -2.974178
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 17 19 6 11
[2,] 7 14 17 13 7
[3,] 19 9 15 4 10
[4,] 9 20 10 16 16
[5,] 5 1 18 9 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.4699109 -0.1596962 1.3766093 0.02367066 -0.40995244 0.4057678
[2,] 1.0878434 0.6020593 -0.3328892 1.90953939 -1.81016745 -0.6623535
[3,] 1.6148438 1.2886249 0.9290381 0.53628498 1.49709581 1.6401285
[4,] -0.8487959 0.3821584 -1.2054808 0.84720420 0.07579931 0.2485509
[5,] -0.2572228 -1.0047802 -0.3102328 1.07977209 2.06983005 -0.3923606
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.40995868 -1.8038823 -0.27088763 0.9945497 0.5744735 1.2702236
[2,] -1.67248910 0.6595164 0.41717650 0.4739215 0.5581226 -0.1820537
[3,] -0.08625654 0.7380389 0.07356484 -1.3364248 -1.5205248 0.8515845
[4,] 0.73124158 -0.8637237 -2.32888666 1.2219217 -2.4219071 1.6819826
[5,] -1.31930786 -2.7305849 -1.05379118 0.1981771 0.6096932 1.8825687
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.4514525 -1.4657803 -0.1173989 -1.3702644 0.6403724 0.04096733
[2,] 0.9426536 -0.6564267 -1.2811911 -0.4727954 -0.4334372 -0.82771093
[3,] 0.5731283 -0.4285442 -0.9397032 1.2285905 -0.6839801 -0.33903290
[4,] -0.5297422 0.7040846 -2.0534395 0.8954622 0.2305458 0.10228131
[5,] 0.4509931 -1.5227828 -1.7781928 1.4094637 -1.1205343 0.28844684
[,19] [,20]
[1,] 0.9674714 0.5478822
[2,] 1.5550469 1.4746338
[3,] -0.3448457 0.7965825
[4,] -0.2585689 1.0486836
[5,] -0.7475772 1.2742447
>
>
> 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 : 564 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 0.04635844 0.9211439 0.1507203 0.971639 1.272519 1.325858 -0.01217403
col8 col9 col10 col11 col12 col13 col14
row1 0.7741107 0.2482615 -0.436887 1.428233 -0.1342993 -2.01146 0.3437051
col15 col16 col17 col18 col19 col20
row1 -0.03384407 0.7514635 0.5976375 -0.2257053 0.9909883 1.791101
> tmp[,"col10"]
col10
row1 -0.4368870
row2 -0.6178221
row3 -1.8015654
row4 0.2652921
row5 0.2452993
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.04635844 0.9211439 0.1507203 0.9716390 1.2725191 1.325858
row5 -1.12422162 0.4685080 -1.3516516 0.6304825 -0.3211637 -1.490040
col7 col8 col9 col10 col11 col12
row1 -0.01217403 0.7741107 0.2482615 -0.4368870 1.4282329 -0.1342993
row5 -1.35872170 1.2262672 0.9571435 0.2452993 -0.2143546 -0.4791937
col13 col14 col15 col16 col17 col18
row1 -2.0114599 0.3437051 -0.03384407 0.75146350 0.5976375 -0.2257053
row5 -0.2518521 0.3010992 0.71654310 -0.08309226 1.5627571 0.2182682
col19 col20
row1 0.9909883 1.7911015
row5 0.4065050 0.4486465
> tmp[,c("col6","col20")]
col6 col20
row1 1.3258581 1.7911015
row2 0.8875751 0.0837295
row3 -0.2573443 -0.6740436
row4 -0.7909520 0.6319635
row5 -1.4900404 0.4486465
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.325858 1.7911015
row5 -1.490040 0.4486465
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.78277 49.79309 50.34234 49.82009 49.81964 104.7685 50.13025 50.30325
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.19739 49.49096 50.75365 48.52219 49.20391 51.34016 49.90559 50.98469
col17 col18 col19 col20
row1 50.32932 51.22424 48.85576 105.6471
> tmp[,"col10"]
col10
row1 49.49096
row2 31.11712
row3 30.02618
row4 30.11595
row5 51.48957
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.78277 49.79309 50.34234 49.82009 49.81964 104.7685 50.13025 50.30325
row5 49.52369 49.78847 51.55546 50.54993 50.42067 106.3872 48.52312 49.75322
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.19739 49.49096 50.75365 48.52219 49.20391 51.34016 49.90559 50.98469
row5 49.22986 51.48957 50.78943 50.47966 48.31737 51.16967 50.47718 49.73176
col17 col18 col19 col20
row1 50.32932 51.22424 48.85576 105.6471
row5 50.47461 49.94621 51.31893 105.7358
> tmp[,c("col6","col20")]
col6 col20
row1 104.76849 105.64708
row2 75.25241 75.12043
row3 75.44306 75.89440
row4 75.55251 73.74296
row5 106.38721 105.73580
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7685 105.6471
row5 106.3872 105.7358
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7685 105.6471
row5 106.3872 105.7358
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.47018294
[2,] -0.14281034
[3,] 0.03276367
[4,] -0.37933639
[5,] 0.87384512
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.7776133 -0.4978255
[2,] 1.7206634 -1.3412664
[3,] 0.1806389 0.6663395
[4,] 0.4393359 -1.3862627
[5,] -0.8105987 -0.4064324
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.03701419 -0.8453906
[2,] 0.11953063 0.1888754
[3,] 0.91297585 -1.1173039
[4,] 0.70517237 0.1942760
[5,] -2.09006480 1.4346290
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.03701419
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.03701419
[2,] 0.11953063
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.01105876 0.5176412 -0.1935403 1.7115806 -0.2893903 0.1161573
row1 -0.35407828 -1.2134358 1.4308317 0.2879384 -0.2536043 0.4938062
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.07388462 -1.9354605 -0.1823774 0.6323583 -0.7921391 0.4427684
row1 0.69647704 -0.7117875 -1.1235706 -2.1615766 1.0675965 0.2919045
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 0.9127617 -1.7301969 0.8528148 1.484076 0.5701457 -0.7606902 0.7713376
row1 0.6494052 -0.1435654 1.9314651 -1.146422 -1.6812143 -0.3949269 0.7325565
[,20]
row3 0.1244776
row1 -1.1608818
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.163452 0.6238069 -0.8536012 0.3897821 -0.921946 1.558872 -0.06916391
[,8] [,9] [,10]
row2 -1.337707 -0.274779 -0.7948842
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5408968 0.3968691 -0.2774978 -0.4261826 0.06359153 1.264685 -0.3504535
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.9817073 0.2959404 0.6348791 1.090681 -1.072431 1.465311 0.7040676
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8035997 2.110514 1.9265 0.7354778 1.839096 -0.2351251
>
>
> 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: 0x59915a3834e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c15b22ee5"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c4816cd31"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c1f86e2eb"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c360c9b7"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c247cbe51"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c299e91ab"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c9d2f0c4"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c4d961c96"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c53a224a9"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c7051cad3"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c70f8edc2"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c3cf354a1"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c7384da3"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c5cb121fd"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM34441c60f237"
>
>
> ### 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: 0x59915a551af0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x59915a551af0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x59915a551af0>
> rowMedians(tmp)
[1] -0.1450019803 -0.3352712006 -0.2019802731 0.0024781706 -0.4085824637
[6] 0.1885058774 0.4102411630 0.4419288093 0.4125678322 -0.3320068525
[11] 0.5886021698 0.4093364735 0.2663281704 -0.4355203968 0.6866758980
[16] 0.3609247876 0.7245652116 0.4146356406 -0.1616239246 -0.3069080847
[21] -0.4279363794 -0.0286506797 0.3279980935 -0.2084335145 0.1754266907
[26] 0.1215654150 0.2082985600 -0.0179127034 -0.1230010962 0.0422881228
[31] 0.4358882282 -0.4876340751 -0.6028449300 -0.3348335633 0.4328962571
[36] 0.0795908750 0.0179902795 0.1330657431 -0.2542332635 0.1879184876
[41] -0.0495906488 -0.4396125471 -0.1129645735 -0.5159595750 0.1469249362
[46] 0.2682269176 -0.0703758581 -0.3552251411 -0.2326567601 -0.1144737285
[51] 0.0503607860 0.4824681219 0.1302832253 -0.2930331920 -0.1395253507
[56] -0.0722153067 0.2466653449 0.1720380137 0.2307637454 0.4757980199
[61] 0.3943582821 -0.1611243282 0.2987512386 0.0041433584 0.3783328708
[66] -0.0553125895 0.1732573354 0.3086071604 -0.0609122884 -0.5925550728
[71] 0.5312016616 -0.1034613510 0.0180001177 0.1568326983 1.0092190842
[76] -0.4006645120 0.1534557308 0.2879550262 0.1461962685 0.0654129112
[81] -0.1514944471 -0.3005208494 0.1838447742 0.2858534458 -0.3182218788
[86] -0.4568047727 0.5568879638 -0.1764848988 -0.4739954484 -0.3093126651
[91] 0.3880232180 -0.7162756891 0.3385540733 -0.0151887590 -0.3896139595
[96] -0.0009428818 -0.0775769584 0.1866274624 -0.2685535628 -0.2269024122
[101] 0.3315369207 0.0289901006 0.1492347861 0.0732344977 -0.4420552691
[106] -0.1000047079 -0.1300867212 0.3837468218 0.2922372323 -0.1219928598
[111] -0.1275837632 -0.2118724868 -0.1472383352 -0.2108388547 0.0258282999
[116] 0.3053790678 -0.2328567485 0.0682847250 0.3215729652 -0.2015036076
[121] -0.1193913271 0.1204657480 0.0674225434 0.0169406212 -0.6420585497
[126] -0.1367826798 0.0956982686 -0.9819967209 -0.2506180007 0.3878289950
[131] 0.3337516630 0.2384329052 0.3300260772 -0.2517673640 -0.1061615829
[136] -0.4244225722 0.1459340127 0.6030141958 -0.0645273425 0.2493488194
[141] 0.0179999858 -0.0174473723 0.0192071977 -0.0303498393 -0.0923464560
[146] 0.0788973662 0.0159960265 0.1293007890 0.3973652793 -0.0279392879
[151] 0.0052354140 0.0776420174 0.6339985082 0.2241716964 -0.3708223539
[156] 0.0706915891 -0.2678736113 -0.2798844412 -0.2033827658 -0.1775808475
[161] -0.5124452408 -0.7258537916 -0.2471841752 -0.2421472986 -0.1683512589
[166] 0.1896075339 0.3640715753 -0.4617032001 0.1000033192 0.1539423986
[171] 0.5113363745 -0.2413102752 -0.0171664196 -0.2550401316 0.3280701088
[176] -0.3580711883 0.7761766432 -0.0406578871 -0.0746010248 -0.1691514297
[181] 0.3184936458 0.1013562123 0.2874342244 0.1536829549 -0.0548544486
[186] 0.1951013921 -0.4974097679 0.1450538303 0.1708044241 0.1228419724
[191] -0.2561902954 0.2053494383 0.1065789007 -0.0555548781 0.4401417045
[196] 0.0014156262 0.0616249310 0.8782958133 -0.0545065048 -0.0476629244
[201] 0.2476675618 -0.0425533412 0.0365465074 -0.2218210973 0.6505591977
[206] -0.3887072716 0.1566631344 0.0585940472 -0.1173048137 -0.3714884106
[211] 0.4746922037 0.0422092461 -0.0148264648 -0.5703004815 -0.2849586102
[216] -0.4338083409 0.0213168878 -0.4877407621 0.5789421237 -0.4159821278
[221] -0.2102986543 -0.2416544382 0.0789357771 0.7279216473 -0.0206160663
[226] 0.1036262451 -0.6475350291 0.2106659382 0.2297755521 -0.1147715177
>
> proc.time()
user system elapsed
1.326 1.426 2.742
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: 0x603f6be7ab20>
> .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: 0x603f6be7ab20>
> .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: 0x603f6be7ab20>
> .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: 0x603f6be7ab20>
> 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: 0x603f6be5b410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6be5b410>
> .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: 0x603f6be5b410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6be5b410>
> .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: 0x603f6be5b410>
> 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: 0x603f6a7087a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6a7087a0>
> .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: 0x603f6a7087a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x603f6a7087a0>
> .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: 0x603f6a7087a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x603f6a7087a0>
> .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: 0x603f6a7087a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x603f6a7087a0>
> .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: 0x603f6a7087a0>
> 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: 0x603f6b6da680>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x603f6b6da680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6b6da680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6b6da680>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3444d3428b25a3" "BufferedMatrixFile3444d3784357f7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3444d3428b25a3" "BufferedMatrixFile3444d3784357f7"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6b46e490>
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6b46e490>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x603f6b46e490>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x603f6b46e490>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x603f6b46e490>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x603f6b46e490>
> .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: 0x603f6caca110>
> .Call("R_bm_AddColumn",P)
<pointer: 0x603f6caca110>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x603f6caca110>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x603f6caca110>
> 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: 0x603f6cb6d5e0>
> .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: 0x603f6cb6d5e0>
> rm(P)
>
> proc.time()
user system elapsed
0.241 0.054 0.284
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
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.
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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
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.236 0.050 0.272