Ben Bolstad
| Snapshot Date: 2025-10-03 13:45 -0400 (Fri, 03 Oct 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-10-04 12:03 -0400 (Sat, 04 Oct 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4853 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4640 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4585 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4576 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 255/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | 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: 1.73.0 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-10-03 21:45:28 -0400 (Fri, 03 Oct 2025) |
| EndedAt: 2025-10-03 21:46:03 -0400 (Fri, 03 Oct 2025) |
| EllapsedTime: 35.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-08-23 r88802)
* 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 ‘1.73.0’
* 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 ... NOTE
Note: information on .o files is not available
* 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: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** 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-3.22-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-3.22-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-3.22-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-3.22-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-3.22-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-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-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 version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
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
0.299 0.054 0.368
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
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-3.22-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 478419 25.6 1047111 56 639600 34.2
Vcells 885237 6.8 8388608 64 2081604 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 Oct 3 21:45:49 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 Oct 3 21:45:49 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: 0x5d5db5dccc80>
>
>
>
> 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 Oct 3 21:45:50 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 Oct 3 21:45:50 2025"
>
> ColMode(tmp2)
<pointer: 0x5d5db5dccc80>
>
>
>
> ### 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,] 101.3679747 -0.8087479 -0.06120112 -1.1737393
[2,] 0.6588794 -0.7768854 0.65514369 -0.7839195
[3,] 0.2854527 -1.4388185 1.56606708 0.5028167
[4,] 1.0682517 0.3390691 0.13146958 -1.4781108
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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,] 101.3679747 0.8087479 0.06120112 1.1737393
[2,] 0.6588794 0.7768854 0.65514369 0.7839195
[3,] 0.2854527 1.4388185 1.56606708 0.5028167
[4,] 1.0682517 0.3390691 0.13146958 1.4781108
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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,] 10.0681664 0.8993041 0.2473886 1.0833925
[2,] 0.8117139 0.8814110 0.8094095 0.8853923
[3,] 0.5342777 1.1995076 1.2514260 0.7090957
[4,] 1.0335626 0.5822964 0.3625873 1.2157758
>
> 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-3.22-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,] 227.04964 34.80179 27.53509 37.00766
[2,] 33.77602 34.59100 33.74924 34.63784
[3,] 30.62823 38.43389 39.08033 32.59377
[4,] 36.40388 31.16203 28.75734 38.63587
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5d5db660a260>
> exp(tmp5)
<pointer: 0x5d5db660a260>
> log(tmp5,2)
<pointer: 0x5d5db660a260>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.5741
> Min(tmp5)
[1] 52.60758
> mean(tmp5)
[1] 73.61719
> Sum(tmp5)
[1] 14723.44
> Var(tmp5)
[1] 873.984
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.53006 70.46664 69.68858 70.45119 72.16133 71.84110 71.10736 72.68631
[9] 75.23927 71.00002
> rowSums(tmp5)
[1] 1830.601 1409.333 1393.772 1409.024 1443.227 1436.822 1422.147 1453.726
[9] 1504.785 1420.000
> rowVars(tmp5)
[1] 8125.21157 73.34323 74.37600 63.06628 81.74177 59.66174
[7] 102.85865 89.09264 39.57760 46.82446
> rowSd(tmp5)
[1] 90.139955 8.564066 8.624152 7.941428 9.041116 7.724101 10.141926
[8] 9.438890 6.291073 6.842840
> rowMax(tmp5)
[1] 472.57408 90.94285 81.34058 87.85065 89.67801 86.38056 90.23052
[8] 90.28305 83.89547 81.82517
> rowMin(tmp5)
[1] 57.31068 54.81102 55.82268 57.31123 52.60758 58.51629 54.69120 56.74995
[9] 59.42843 58.48123
>
> colMeans(tmp5)
[1] 110.93397 74.18399 70.67889 74.13232 78.45001 70.98086 74.76862
[8] 71.40598 73.17989 72.35435 71.88615 69.85583 71.51624 65.03777
[15] 70.80018 72.70865 68.13784 71.79447 71.45581 68.08192
> colSums(tmp5)
[1] 1109.3397 741.8399 706.7889 741.3232 784.5001 709.8086 747.6862
[8] 714.0598 731.7989 723.5435 718.8615 698.5583 715.1624 650.3777
[15] 708.0018 727.0865 681.3784 717.9447 714.5581 680.8192
> colVars(tmp5)
[1] 16244.04917 69.08400 100.91419 38.38861 68.69036 63.15312
[7] 54.45574 28.46121 18.20819 69.90076 82.69957 67.26809
[13] 89.00018 48.32021 127.47955 94.51414 87.42480 90.64213
[19] 66.41746 23.85114
> colSd(tmp5)
[1] 127.452145 8.311679 10.045606 6.195855 8.287965 7.946894
[7] 7.379414 5.334905 4.267105 8.360667 9.093930 8.201712
[13] 9.433991 6.951274 11.290684 9.721838 9.350123 9.520616
[19] 8.149691 4.883763
> colMax(tmp5)
[1] 472.57408 89.67801 90.23052 83.89547 90.94285 81.82517 85.66789
[8] 79.67979 78.07269 84.68501 86.53598 81.22020 80.86539 73.51008
[15] 87.85065 90.72916 80.74316 84.78933 80.60351 78.31531
> colMin(tmp5)
[1] 56.74995 61.80158 57.31068 66.64751 64.44071 58.86230 62.55767 63.00178
[9] 66.51810 61.52891 57.46732 60.27383 52.60758 54.81102 56.35382 61.16822
[17] 54.69120 59.46031 57.60903 61.40163
>
>
> ### 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] 91.53006 70.46664 69.68858 NA 72.16133 71.84110 71.10736 72.68631
[9] 75.23927 71.00002
> rowSums(tmp5)
[1] 1830.601 1409.333 1393.772 NA 1443.227 1436.822 1422.147 1453.726
[9] 1504.785 1420.000
> rowVars(tmp5)
[1] 8125.21157 73.34323 74.37600 48.86580 81.74177 59.66174
[7] 102.85865 89.09264 39.57760 46.82446
> rowSd(tmp5)
[1] 90.139955 8.564066 8.624152 6.990408 9.041116 7.724101 10.141926
[8] 9.438890 6.291073 6.842840
> rowMax(tmp5)
[1] 472.57408 90.94285 81.34058 NA 89.67801 86.38056 90.23052
[8] 90.28305 83.89547 81.82517
> rowMin(tmp5)
[1] 57.31068 54.81102 55.82268 NA 52.60758 58.51629 54.69120 56.74995
[9] 59.42843 58.48123
>
> colMeans(tmp5)
[1] 110.93397 74.18399 70.67889 74.13232 78.45001 70.98086 74.76862
[8] 71.40598 73.17989 72.35435 71.88615 69.85583 71.51624 65.03777
[15] NA 72.70865 68.13784 71.79447 71.45581 68.08192
> colSums(tmp5)
[1] 1109.3397 741.8399 706.7889 741.3232 784.5001 709.8086 747.6862
[8] 714.0598 731.7989 723.5435 718.8615 698.5583 715.1624 650.3777
[15] NA 727.0865 681.3784 717.9447 714.5581 680.8192
> colVars(tmp5)
[1] 16244.04917 69.08400 100.91419 38.38861 68.69036 63.15312
[7] 54.45574 28.46121 18.20819 69.90076 82.69957 67.26809
[13] 89.00018 48.32021 NA 94.51414 87.42480 90.64213
[19] 66.41746 23.85114
> colSd(tmp5)
[1] 127.452145 8.311679 10.045606 6.195855 8.287965 7.946894
[7] 7.379414 5.334905 4.267105 8.360667 9.093930 8.201712
[13] 9.433991 6.951274 NA 9.721838 9.350123 9.520616
[19] 8.149691 4.883763
> colMax(tmp5)
[1] 472.57408 89.67801 90.23052 83.89547 90.94285 81.82517 85.66789
[8] 79.67979 78.07269 84.68501 86.53598 81.22020 80.86539 73.51008
[15] NA 90.72916 80.74316 84.78933 80.60351 78.31531
> colMin(tmp5)
[1] 56.74995 61.80158 57.31068 66.64751 64.44071 58.86230 62.55767 63.00178
[9] 66.51810 61.52891 57.46732 60.27383 52.60758 54.81102 NA 61.16822
[17] 54.69120 59.46031 57.60903 61.40163
>
> Max(tmp5,na.rm=TRUE)
[1] 472.5741
> Min(tmp5,na.rm=TRUE)
[1] 52.60758
> mean(tmp5,na.rm=TRUE)
[1] 73.54566
> Sum(tmp5,na.rm=TRUE)
[1] 14635.59
> Var(tmp5,na.rm=TRUE)
[1] 877.3698
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.53006 70.46664 69.68858 69.53543 72.16133 71.84110 71.10736 72.68631
[9] 75.23927 71.00002
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.601 1409.333 1393.772 1321.173 1443.227 1436.822 1422.147 1453.726
[9] 1504.785 1420.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8125.21157 73.34323 74.37600 48.86580 81.74177 59.66174
[7] 102.85865 89.09264 39.57760 46.82446
> rowSd(tmp5,na.rm=TRUE)
[1] 90.139955 8.564066 8.624152 6.990408 9.041116 7.724101 10.141926
[8] 9.438890 6.291073 6.842840
> rowMax(tmp5,na.rm=TRUE)
[1] 472.57408 90.94285 81.34058 80.41550 89.67801 86.38056 90.23052
[8] 90.28305 83.89547 81.82517
> rowMin(tmp5,na.rm=TRUE)
[1] 57.31068 54.81102 55.82268 57.31123 52.60758 58.51629 54.69120 56.74995
[9] 59.42843 58.48123
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.93397 74.18399 70.67889 74.13232 78.45001 70.98086 74.76862
[8] 71.40598 73.17989 72.35435 71.88615 69.85583 71.51624 65.03777
[15] 68.90569 72.70865 68.13784 71.79447 71.45581 68.08192
> colSums(tmp5,na.rm=TRUE)
[1] 1109.3397 741.8399 706.7889 741.3232 784.5001 709.8086 747.6862
[8] 714.0598 731.7989 723.5435 718.8615 698.5583 715.1624 650.3777
[15] 620.1512 727.0865 681.3784 717.9447 714.5581 680.8192
> colVars(tmp5,na.rm=TRUE)
[1] 16244.04917 69.08400 100.91419 38.38861 68.69036 63.15312
[7] 54.45574 28.46121 18.20819 69.90076 82.69957 67.26809
[13] 89.00018 48.32021 103.03695 94.51414 87.42480 90.64213
[19] 66.41746 23.85114
> colSd(tmp5,na.rm=TRUE)
[1] 127.452145 8.311679 10.045606 6.195855 8.287965 7.946894
[7] 7.379414 5.334905 4.267105 8.360667 9.093930 8.201712
[13] 9.433991 6.951274 10.150712 9.721838 9.350123 9.520616
[19] 8.149691 4.883763
> colMax(tmp5,na.rm=TRUE)
[1] 472.57408 89.67801 90.23052 83.89547 90.94285 81.82517 85.66789
[8] 79.67979 78.07269 84.68501 86.53598 81.22020 80.86539 73.51008
[15] 81.88863 90.72916 80.74316 84.78933 80.60351 78.31531
> colMin(tmp5,na.rm=TRUE)
[1] 56.74995 61.80158 57.31068 66.64751 64.44071 58.86230 62.55767 63.00178
[9] 66.51810 61.52891 57.46732 60.27383 52.60758 54.81102 56.35382 61.16822
[17] 54.69120 59.46031 57.60903 61.40163
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.53006 70.46664 69.68858 NaN 72.16133 71.84110 71.10736 72.68631
[9] 75.23927 71.00002
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.601 1409.333 1393.772 0.000 1443.227 1436.822 1422.147 1453.726
[9] 1504.785 1420.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8125.21157 73.34323 74.37600 NA 81.74177 59.66174
[7] 102.85865 89.09264 39.57760 46.82446
> rowSd(tmp5,na.rm=TRUE)
[1] 90.139955 8.564066 8.624152 NA 9.041116 7.724101 10.141926
[8] 9.438890 6.291073 6.842840
> rowMax(tmp5,na.rm=TRUE)
[1] 472.57408 90.94285 81.34058 NA 89.67801 86.38056 90.23052
[8] 90.28305 83.89547 81.82517
> rowMin(tmp5,na.rm=TRUE)
[1] 57.31068 54.81102 55.82268 NA 52.60758 58.51629 54.69120 56.74995
[9] 59.42843 58.48123
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.84109 75.22002 71.88158 73.43419 78.47802 71.20249 75.00996
[8] 71.50607 72.86303 72.68937 72.47022 69.01413 72.52317 65.89627
[15] NaN 73.75818 68.90068 72.27043 70.57626 67.93844
> colSums(tmp5,na.rm=TRUE)
[1] 1033.5698 676.9802 646.9342 660.9077 706.3022 640.8224 675.0896
[8] 643.5546 655.7673 654.2043 652.2320 621.1271 652.7085 593.0664
[15] 0.0000 663.8236 620.1061 650.4339 635.1863 611.4460
> colVars(tmp5,na.rm=TRUE)
[1] 18102.81760 65.64414 97.25565 37.70408 77.26783 70.49465
[7] 60.60746 31.90616 19.35477 77.37570 89.19928 67.70636
[13] 88.71886 46.06865 NA 93.93624 91.80618 99.42384
[19] 66.01657 26.60093
> colSd(tmp5,na.rm=TRUE)
[1] 134.546712 8.102107 9.861828 6.140365 8.790212 8.396109
[7] 7.785079 5.648554 4.399406 8.796346 9.444537 8.228387
[13] 9.419069 6.787389 NA 9.692071 9.581554 9.971150
[19] 8.125058 5.157609
> colMax(tmp5,na.rm=TRUE)
[1] 472.57408 89.67801 90.23052 83.89547 90.94285 81.82517 85.66789
[8] 79.67979 78.07269 84.68501 86.53598 81.22020 80.86539 73.51008
[15] -Inf 90.72916 80.74316 84.78933 80.60351 78.31531
> colMin(tmp5,na.rm=TRUE)
[1] 56.74995 61.80158 57.31068 66.64751 64.44071 58.86230 62.55767 63.00178
[9] 66.51810 61.52891 57.46732 60.27383 52.60758 54.81102 Inf 61.16822
[17] 54.69120 59.46031 57.60903 61.40163
>
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col <- 1
> cat(which.row," ",which.col,"\n")
3 1
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> rowVars(tmp5,na.rm=TRUE)
[1] 271.7477 197.9699 242.7245 214.5787 249.0283 181.7967 312.8679 108.9428
[9] 204.4198 244.3277
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 271.7477 197.9699 242.7245 214.5787 249.0283 181.7967 312.8679 108.9428
[9] 204.4198 244.3277
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -2.842171e-14 -5.684342e-14 -5.684342e-14 5.684342e-14 -1.705303e-13
[6] -5.684342e-14 -2.842171e-14 2.557954e-13 -8.526513e-14 5.684342e-14
[11] 2.842171e-14 -5.684342e-14 2.131628e-14 1.136868e-13 4.263256e-14
[16] 0.000000e+00 -5.684342e-14 5.684342e-14 1.705303e-13 -2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 18
9 14
3 20
5 8
8 20
6 3
5 13
1 13
2 16
6 2
7 18
5 1
2 5
4 17
10 6
6 7
1 18
10 6
4 11
4 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] 2.1174
> Min(tmp)
[1] -2.2616
> mean(tmp)
[1] 0.1858114
> Sum(tmp)
[1] 18.58114
> Var(tmp)
[1] 0.834346
>
> rowMeans(tmp)
[1] 0.1858114
> rowSums(tmp)
[1] 18.58114
> rowVars(tmp)
[1] 0.834346
> rowSd(tmp)
[1] 0.9134254
> rowMax(tmp)
[1] 2.1174
> rowMin(tmp)
[1] -2.2616
>
> colMeans(tmp)
[1] -0.143589588 0.997656411 -0.200851231 0.002048113 0.618425164
[6] 1.698128419 -0.059124870 -0.473361127 0.228685980 -2.261600019
[11] 1.760558320 1.292041881 0.322963266 -0.134487100 1.416750170
[16] -0.058379017 -1.176190254 0.083857521 1.080346177 1.362788467
[21] -0.793028497 0.396972653 -0.520966767 0.658555564 -1.033967995
[26] 0.178302252 0.174236736 1.055119326 1.916214135 0.129986997
[31] -0.003716046 0.940056948 -0.213414994 -0.252668849 1.277263360
[36] -1.030711959 0.616462088 0.329914717 1.033931681 -0.137304742
[41] 1.640741466 1.055847014 -0.090211799 -0.406084514 -0.905768780
[46] 1.713247644 1.356776694 0.071114336 -0.469840106 1.589840114
[51] -1.460808043 -0.202098562 1.181766386 -0.518080544 -1.295274835
[56] -0.761261436 0.076097273 0.630451863 1.026133178 -1.367322392
[61] 0.152774360 0.176712564 0.416323923 0.426166456 -0.485553974
[66] 0.209546303 0.453093918 0.591854284 -0.638959548 -1.053781056
[71] 0.722526260 0.191941499 1.898880221 -1.459947681 -0.171858768
[76] -0.051454798 0.866252927 -0.871322498 2.117400036 -0.397845982
[81] -0.499634034 -0.961364829 0.852763752 0.219199154 -1.113623916
[86] -0.864229906 -0.697321103 -1.074261354 0.797340615 0.578830928
[91] 0.720855732 0.658444823 -1.642903979 -0.088739540 0.298943221
[96] 1.319145111 1.280760050 0.687843536 1.088260047 -0.015087662
> colSums(tmp)
[1] -0.143589588 0.997656411 -0.200851231 0.002048113 0.618425164
[6] 1.698128419 -0.059124870 -0.473361127 0.228685980 -2.261600019
[11] 1.760558320 1.292041881 0.322963266 -0.134487100 1.416750170
[16] -0.058379017 -1.176190254 0.083857521 1.080346177 1.362788467
[21] -0.793028497 0.396972653 -0.520966767 0.658555564 -1.033967995
[26] 0.178302252 0.174236736 1.055119326 1.916214135 0.129986997
[31] -0.003716046 0.940056948 -0.213414994 -0.252668849 1.277263360
[36] -1.030711959 0.616462088 0.329914717 1.033931681 -0.137304742
[41] 1.640741466 1.055847014 -0.090211799 -0.406084514 -0.905768780
[46] 1.713247644 1.356776694 0.071114336 -0.469840106 1.589840114
[51] -1.460808043 -0.202098562 1.181766386 -0.518080544 -1.295274835
[56] -0.761261436 0.076097273 0.630451863 1.026133178 -1.367322392
[61] 0.152774360 0.176712564 0.416323923 0.426166456 -0.485553974
[66] 0.209546303 0.453093918 0.591854284 -0.638959548 -1.053781056
[71] 0.722526260 0.191941499 1.898880221 -1.459947681 -0.171858768
[76] -0.051454798 0.866252927 -0.871322498 2.117400036 -0.397845982
[81] -0.499634034 -0.961364829 0.852763752 0.219199154 -1.113623916
[86] -0.864229906 -0.697321103 -1.074261354 0.797340615 0.578830928
[91] 0.720855732 0.658444823 -1.642903979 -0.088739540 0.298943221
[96] 1.319145111 1.280760050 0.687843536 1.088260047 -0.015087662
> 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] -0.143589588 0.997656411 -0.200851231 0.002048113 0.618425164
[6] 1.698128419 -0.059124870 -0.473361127 0.228685980 -2.261600019
[11] 1.760558320 1.292041881 0.322963266 -0.134487100 1.416750170
[16] -0.058379017 -1.176190254 0.083857521 1.080346177 1.362788467
[21] -0.793028497 0.396972653 -0.520966767 0.658555564 -1.033967995
[26] 0.178302252 0.174236736 1.055119326 1.916214135 0.129986997
[31] -0.003716046 0.940056948 -0.213414994 -0.252668849 1.277263360
[36] -1.030711959 0.616462088 0.329914717 1.033931681 -0.137304742
[41] 1.640741466 1.055847014 -0.090211799 -0.406084514 -0.905768780
[46] 1.713247644 1.356776694 0.071114336 -0.469840106 1.589840114
[51] -1.460808043 -0.202098562 1.181766386 -0.518080544 -1.295274835
[56] -0.761261436 0.076097273 0.630451863 1.026133178 -1.367322392
[61] 0.152774360 0.176712564 0.416323923 0.426166456 -0.485553974
[66] 0.209546303 0.453093918 0.591854284 -0.638959548 -1.053781056
[71] 0.722526260 0.191941499 1.898880221 -1.459947681 -0.171858768
[76] -0.051454798 0.866252927 -0.871322498 2.117400036 -0.397845982
[81] -0.499634034 -0.961364829 0.852763752 0.219199154 -1.113623916
[86] -0.864229906 -0.697321103 -1.074261354 0.797340615 0.578830928
[91] 0.720855732 0.658444823 -1.642903979 -0.088739540 0.298943221
[96] 1.319145111 1.280760050 0.687843536 1.088260047 -0.015087662
> colMin(tmp)
[1] -0.143589588 0.997656411 -0.200851231 0.002048113 0.618425164
[6] 1.698128419 -0.059124870 -0.473361127 0.228685980 -2.261600019
[11] 1.760558320 1.292041881 0.322963266 -0.134487100 1.416750170
[16] -0.058379017 -1.176190254 0.083857521 1.080346177 1.362788467
[21] -0.793028497 0.396972653 -0.520966767 0.658555564 -1.033967995
[26] 0.178302252 0.174236736 1.055119326 1.916214135 0.129986997
[31] -0.003716046 0.940056948 -0.213414994 -0.252668849 1.277263360
[36] -1.030711959 0.616462088 0.329914717 1.033931681 -0.137304742
[41] 1.640741466 1.055847014 -0.090211799 -0.406084514 -0.905768780
[46] 1.713247644 1.356776694 0.071114336 -0.469840106 1.589840114
[51] -1.460808043 -0.202098562 1.181766386 -0.518080544 -1.295274835
[56] -0.761261436 0.076097273 0.630451863 1.026133178 -1.367322392
[61] 0.152774360 0.176712564 0.416323923 0.426166456 -0.485553974
[66] 0.209546303 0.453093918 0.591854284 -0.638959548 -1.053781056
[71] 0.722526260 0.191941499 1.898880221 -1.459947681 -0.171858768
[76] -0.051454798 0.866252927 -0.871322498 2.117400036 -0.397845982
[81] -0.499634034 -0.961364829 0.852763752 0.219199154 -1.113623916
[86] -0.864229906 -0.697321103 -1.074261354 0.797340615 0.578830928
[91] 0.720855732 0.658444823 -1.642903979 -0.088739540 0.298943221
[96] 1.319145111 1.280760050 0.687843536 1.088260047 -0.015087662
> colMedians(tmp)
[1] -0.143589588 0.997656411 -0.200851231 0.002048113 0.618425164
[6] 1.698128419 -0.059124870 -0.473361127 0.228685980 -2.261600019
[11] 1.760558320 1.292041881 0.322963266 -0.134487100 1.416750170
[16] -0.058379017 -1.176190254 0.083857521 1.080346177 1.362788467
[21] -0.793028497 0.396972653 -0.520966767 0.658555564 -1.033967995
[26] 0.178302252 0.174236736 1.055119326 1.916214135 0.129986997
[31] -0.003716046 0.940056948 -0.213414994 -0.252668849 1.277263360
[36] -1.030711959 0.616462088 0.329914717 1.033931681 -0.137304742
[41] 1.640741466 1.055847014 -0.090211799 -0.406084514 -0.905768780
[46] 1.713247644 1.356776694 0.071114336 -0.469840106 1.589840114
[51] -1.460808043 -0.202098562 1.181766386 -0.518080544 -1.295274835
[56] -0.761261436 0.076097273 0.630451863 1.026133178 -1.367322392
[61] 0.152774360 0.176712564 0.416323923 0.426166456 -0.485553974
[66] 0.209546303 0.453093918 0.591854284 -0.638959548 -1.053781056
[71] 0.722526260 0.191941499 1.898880221 -1.459947681 -0.171858768
[76] -0.051454798 0.866252927 -0.871322498 2.117400036 -0.397845982
[81] -0.499634034 -0.961364829 0.852763752 0.219199154 -1.113623916
[86] -0.864229906 -0.697321103 -1.074261354 0.797340615 0.578830928
[91] 0.720855732 0.658444823 -1.642903979 -0.088739540 0.298943221
[96] 1.319145111 1.280760050 0.687843536 1.088260047 -0.015087662
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1435896 0.9976564 -0.2008512 0.002048113 0.6184252 1.698128 -0.05912487
[2,] -0.1435896 0.9976564 -0.2008512 0.002048113 0.6184252 1.698128 -0.05912487
[,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15]
[1,] -0.4733611 0.228686 -2.2616 1.760558 1.292042 0.3229633 -0.1344871 1.41675
[2,] -0.4733611 0.228686 -2.2616 1.760558 1.292042 0.3229633 -0.1344871 1.41675
[,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] -0.05837902 -1.17619 0.08385752 1.080346 1.362788 -0.7930285 0.3969727
[2,] -0.05837902 -1.17619 0.08385752 1.080346 1.362788 -0.7930285 0.3969727
[,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] -0.5209668 0.6585556 -1.033968 0.1783023 0.1742367 1.055119 1.916214
[2,] -0.5209668 0.6585556 -1.033968 0.1783023 0.1742367 1.055119 1.916214
[,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] 0.129987 -0.003716046 0.9400569 -0.213415 -0.2526688 1.277263 -1.030712
[2,] 0.129987 -0.003716046 0.9400569 -0.213415 -0.2526688 1.277263 -1.030712
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 0.6164621 0.3299147 1.033932 -0.1373047 1.640741 1.055847 -0.0902118
[2,] 0.6164621 0.3299147 1.033932 -0.1373047 1.640741 1.055847 -0.0902118
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] -0.4060845 -0.9057688 1.713248 1.356777 0.07111434 -0.4698401 1.58984
[2,] -0.4060845 -0.9057688 1.713248 1.356777 0.07111434 -0.4698401 1.58984
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] -1.460808 -0.2020986 1.181766 -0.5180805 -1.295275 -0.7612614 0.07609727
[2,] -1.460808 -0.2020986 1.181766 -0.5180805 -1.295275 -0.7612614 0.07609727
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] 0.6304519 1.026133 -1.367322 0.1527744 0.1767126 0.4163239 0.4261665
[2,] 0.6304519 1.026133 -1.367322 0.1527744 0.1767126 0.4163239 0.4261665
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] -0.485554 0.2095463 0.4530939 0.5918543 -0.6389595 -1.053781 0.7225263
[2,] -0.485554 0.2095463 0.4530939 0.5918543 -0.6389595 -1.053781 0.7225263
[,72] [,73] [,74] [,75] [,76] [,77] [,78]
[1,] 0.1919415 1.89888 -1.459948 -0.1718588 -0.0514548 0.8662529 -0.8713225
[2,] 0.1919415 1.89888 -1.459948 -0.1718588 -0.0514548 0.8662529 -0.8713225
[,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] 2.1174 -0.397846 -0.499634 -0.9613648 0.8527638 0.2191992 -1.113624
[2,] 2.1174 -0.397846 -0.499634 -0.9613648 0.8527638 0.2191992 -1.113624
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] -0.8642299 -0.6973211 -1.074261 0.7973406 0.5788309 0.7208557 0.6584448
[2,] -0.8642299 -0.6973211 -1.074261 0.7973406 0.5788309 0.7208557 0.6584448
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] -1.642904 -0.08873954 0.2989432 1.319145 1.28076 0.6878435 1.08826
[2,] -1.642904 -0.08873954 0.2989432 1.319145 1.28076 0.6878435 1.08826
[,100]
[1,] -0.01508766
[2,] -0.01508766
>
>
> Max(tmp2)
[1] 2.296875
> Min(tmp2)
[1] -2.075226
> mean(tmp2)
[1] 0.02948859
> Sum(tmp2)
[1] 2.948859
> Var(tmp2)
[1] 0.9366405
>
> rowMeans(tmp2)
[1] -2.001735187 -1.158612588 -0.030365719 -1.371455794 0.998033104
[6] -0.094035588 1.008046840 1.107842401 -1.672936764 -0.062843172
[11] 0.137669622 -0.399281669 1.505865098 0.869779518 1.946471900
[16] -0.935024949 1.328659857 -0.309323143 0.227540898 -0.244940156
[21] 0.421805375 0.861411577 -0.640075254 -1.025132854 2.021979213
[26] 1.196349806 0.512667625 -0.524752791 -0.609756232 -1.503579206
[31] 0.214622602 -0.727775225 -0.612395334 -0.559520297 -0.356112561
[36] 0.831841648 0.172522188 -1.056364625 0.184865559 -2.075225802
[41] 1.144960829 -0.119409618 1.378136532 -0.702502788 0.013193183
[46] -0.037383934 -1.025383019 0.033608090 1.327151844 -0.198613754
[51] 0.642162664 0.152258262 -0.929557652 -0.594822010 -0.715394058
[56] -0.269524268 -0.117776354 -0.709012822 -0.375200149 -0.378931856
[61] -0.007523850 -1.732794224 1.157369137 0.869900345 -1.055908265
[66] 1.141798592 -0.176352317 -0.677995350 1.520940438 1.330346599
[71] -0.449124052 0.466676661 1.362733851 -0.145936563 0.575014765
[76] -0.092991005 0.993776761 -1.365134861 0.116267409 1.206538881
[81] 0.007528433 1.153785163 2.296875486 -0.603226767 1.609007496
[86] 0.174890737 -1.477981046 -1.608337948 -1.145896121 0.054980601
[91] 1.626306498 0.756073823 -0.279295426 -0.854030322 0.690456191
[96] 0.886202745 -0.327416072 0.383152739 -0.836122892 -0.690386479
> rowSums(tmp2)
[1] -2.001735187 -1.158612588 -0.030365719 -1.371455794 0.998033104
[6] -0.094035588 1.008046840 1.107842401 -1.672936764 -0.062843172
[11] 0.137669622 -0.399281669 1.505865098 0.869779518 1.946471900
[16] -0.935024949 1.328659857 -0.309323143 0.227540898 -0.244940156
[21] 0.421805375 0.861411577 -0.640075254 -1.025132854 2.021979213
[26] 1.196349806 0.512667625 -0.524752791 -0.609756232 -1.503579206
[31] 0.214622602 -0.727775225 -0.612395334 -0.559520297 -0.356112561
[36] 0.831841648 0.172522188 -1.056364625 0.184865559 -2.075225802
[41] 1.144960829 -0.119409618 1.378136532 -0.702502788 0.013193183
[46] -0.037383934 -1.025383019 0.033608090 1.327151844 -0.198613754
[51] 0.642162664 0.152258262 -0.929557652 -0.594822010 -0.715394058
[56] -0.269524268 -0.117776354 -0.709012822 -0.375200149 -0.378931856
[61] -0.007523850 -1.732794224 1.157369137 0.869900345 -1.055908265
[66] 1.141798592 -0.176352317 -0.677995350 1.520940438 1.330346599
[71] -0.449124052 0.466676661 1.362733851 -0.145936563 0.575014765
[76] -0.092991005 0.993776761 -1.365134861 0.116267409 1.206538881
[81] 0.007528433 1.153785163 2.296875486 -0.603226767 1.609007496
[86] 0.174890737 -1.477981046 -1.608337948 -1.145896121 0.054980601
[91] 1.626306498 0.756073823 -0.279295426 -0.854030322 0.690456191
[96] 0.886202745 -0.327416072 0.383152739 -0.836122892 -0.690386479
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -2.001735187 -1.158612588 -0.030365719 -1.371455794 0.998033104
[6] -0.094035588 1.008046840 1.107842401 -1.672936764 -0.062843172
[11] 0.137669622 -0.399281669 1.505865098 0.869779518 1.946471900
[16] -0.935024949 1.328659857 -0.309323143 0.227540898 -0.244940156
[21] 0.421805375 0.861411577 -0.640075254 -1.025132854 2.021979213
[26] 1.196349806 0.512667625 -0.524752791 -0.609756232 -1.503579206
[31] 0.214622602 -0.727775225 -0.612395334 -0.559520297 -0.356112561
[36] 0.831841648 0.172522188 -1.056364625 0.184865559 -2.075225802
[41] 1.144960829 -0.119409618 1.378136532 -0.702502788 0.013193183
[46] -0.037383934 -1.025383019 0.033608090 1.327151844 -0.198613754
[51] 0.642162664 0.152258262 -0.929557652 -0.594822010 -0.715394058
[56] -0.269524268 -0.117776354 -0.709012822 -0.375200149 -0.378931856
[61] -0.007523850 -1.732794224 1.157369137 0.869900345 -1.055908265
[66] 1.141798592 -0.176352317 -0.677995350 1.520940438 1.330346599
[71] -0.449124052 0.466676661 1.362733851 -0.145936563 0.575014765
[76] -0.092991005 0.993776761 -1.365134861 0.116267409 1.206538881
[81] 0.007528433 1.153785163 2.296875486 -0.603226767 1.609007496
[86] 0.174890737 -1.477981046 -1.608337948 -1.145896121 0.054980601
[91] 1.626306498 0.756073823 -0.279295426 -0.854030322 0.690456191
[96] 0.886202745 -0.327416072 0.383152739 -0.836122892 -0.690386479
> rowMin(tmp2)
[1] -2.001735187 -1.158612588 -0.030365719 -1.371455794 0.998033104
[6] -0.094035588 1.008046840 1.107842401 -1.672936764 -0.062843172
[11] 0.137669622 -0.399281669 1.505865098 0.869779518 1.946471900
[16] -0.935024949 1.328659857 -0.309323143 0.227540898 -0.244940156
[21] 0.421805375 0.861411577 -0.640075254 -1.025132854 2.021979213
[26] 1.196349806 0.512667625 -0.524752791 -0.609756232 -1.503579206
[31] 0.214622602 -0.727775225 -0.612395334 -0.559520297 -0.356112561
[36] 0.831841648 0.172522188 -1.056364625 0.184865559 -2.075225802
[41] 1.144960829 -0.119409618 1.378136532 -0.702502788 0.013193183
[46] -0.037383934 -1.025383019 0.033608090 1.327151844 -0.198613754
[51] 0.642162664 0.152258262 -0.929557652 -0.594822010 -0.715394058
[56] -0.269524268 -0.117776354 -0.709012822 -0.375200149 -0.378931856
[61] -0.007523850 -1.732794224 1.157369137 0.869900345 -1.055908265
[66] 1.141798592 -0.176352317 -0.677995350 1.520940438 1.330346599
[71] -0.449124052 0.466676661 1.362733851 -0.145936563 0.575014765
[76] -0.092991005 0.993776761 -1.365134861 0.116267409 1.206538881
[81] 0.007528433 1.153785163 2.296875486 -0.603226767 1.609007496
[86] 0.174890737 -1.477981046 -1.608337948 -1.145896121 0.054980601
[91] 1.626306498 0.756073823 -0.279295426 -0.854030322 0.690456191
[96] 0.886202745 -0.327416072 0.383152739 -0.836122892 -0.690386479
>
> colMeans(tmp2)
[1] 0.02948859
> colSums(tmp2)
[1] 2.948859
> colVars(tmp2)
[1] 0.9366405
> colSd(tmp2)
[1] 0.9678019
> colMax(tmp2)
[1] 2.296875
> colMin(tmp2)
[1] -2.075226
> colMedians(tmp2)
[1] -0.05011355
> colRanges(tmp2)
[,1]
[1,] -2.075226
[2,] 2.296875
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.5107990 -1.7156512 4.9356306 1.7316416 4.5875968 2.3545413
[7] -2.0914408 0.9527705 3.8500020 -4.6468612
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2517171
[2,] -0.3060608
[3,] 0.1488528
[4,] 0.3767188
[5,] 0.9183454
>
> rowApply(tmp,sum)
[1] 2.2284101 3.2211187 6.2811393 1.6335028 -7.4020655 1.5665574
[7] 0.2528810 -1.5188412 0.8872339 3.3190920
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 9 2 5 5 3 7 6 1 8
[2,] 4 5 4 10 1 4 10 1 5 2
[3,] 6 6 8 4 7 9 5 10 2 5
[4,] 3 1 5 2 10 6 6 8 10 7
[5,] 8 8 9 7 3 8 9 4 8 3
[6,] 7 4 6 6 6 5 2 9 7 6
[7,] 2 2 1 8 8 10 3 2 3 1
[8,] 10 10 3 1 2 7 8 3 4 10
[9,] 9 7 10 9 9 1 4 5 6 9
[10,] 1 3 7 3 4 2 1 7 9 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.5185168 -0.2498611 2.9520805 -0.4513933 -1.3406709 -3.8381694
[7] -2.9924550 1.1951324 -2.5241399 1.5948793 5.0408953 -2.0540365
[13] 2.3464284 -2.2019289 -2.8280829 5.2904122 -0.1509287 -1.3558371
[19] 2.0024611 -3.1368758
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6848724
[2,] -1.6031747
[3,] -0.7434314
[4,] 0.2663049
[5,] 1.2466568
>
> rowApply(tmp,sum)
[1] -2.5923308 -0.5139247 4.6449907 3.0109686 -9.7703106
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 20 4 13 2
[2,] 18 1 13 11 17
[3,] 17 18 18 17 5
[4,] 5 19 9 5 12
[5,] 9 15 6 2 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.6848724 0.6034273 0.5585719 -0.78203025 -0.2668173 -0.9908332
[2,] 1.2466568 -1.7807155 1.1818354 1.22206921 0.7203888 -1.6272771
[3,] -0.7434314 0.3870239 1.4972534 -0.09738696 -0.5397166 -0.4951422
[4,] 0.2663049 0.1086398 1.1156966 -0.77557634 -1.3848547 -0.1172453
[5,] -1.6031747 0.4317635 -1.4012767 -0.01846892 0.1303289 -0.6076716
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.1851532 -0.3417684 0.7979251 0.49122183 -0.3734085 -0.8473933
[2,] -0.2540813 -0.4662446 -1.3662464 0.46883253 0.5880889 0.8687350
[3,] 0.2594702 1.3252722 -0.5948900 0.19916845 0.9774583 0.5585974
[4,] -0.3875562 0.1103850 0.4939088 -0.05785224 2.2447578 -1.0656857
[5,] -1.4251345 0.5674883 -1.8548375 0.49350874 1.6039987 -1.5682899
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 2.2127806 0.02420069 -0.2584464 0.01528359 0.20526287 -0.6460822
[2,] -0.4912081 0.03844227 0.7063968 1.12872026 -1.67648322 -1.1699834
[3,] 0.4940194 -0.41260135 -0.9720535 2.83172023 0.36784256 -1.1636172
[4,] -0.2793436 -0.87314052 -1.8073270 2.67864633 0.89448580 1.3655754
[5,] 0.4101801 -0.97882996 -0.4966527 -1.36395816 0.05796332 0.2582702
[,19] [,20]
[1,] 0.05604639 -0.18024575
[2,] 0.09181246 0.05633646
[3,] 2.21821889 -1.45221492
[4,] 0.78640661 -0.30525697
[5,] -1.15002325 -1.25549466
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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-3.22-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 0.5435535 -0.8463965 -0.9002233 -0.7034085 0.6014382 -0.3441515 1.37955
col8 col9 col10 col11 col12 col13 col14
row1 -1.505474 0.67303 0.1766452 0.1007671 -0.5113892 -0.003935918 1.387712
col15 col16 col17 col18 col19 col20
row1 -1.336635 -0.3892946 0.1609233 -0.9654991 0.423617 1.310215
> tmp[,"col10"]
col10
row1 0.1766452
row2 -1.8100459
row3 1.0776787
row4 0.5579014
row5 -0.9479868
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.5435535 -0.84639649 -0.9002233 -0.7034085 0.6014382 -0.34415145
row5 0.4146038 -0.08966475 -0.3928490 1.1787448 -1.2532973 0.06020976
col7 col8 col9 col10 col11 col12
row1 1.3795498 -1.505474 0.673030 0.1766452 0.1007671 -0.5113892
row5 -0.2945637 1.139691 1.949968 -0.9479868 -0.3057076 1.5884797
col13 col14 col15 col16 col17 col18
row1 -0.003935918 1.3877115 -1.33663498 -0.3892946 0.1609233 -0.9654991
row5 -0.510591313 -0.6581885 -0.02195271 -0.2379535 0.7098194 -1.0663496
col19 col20
row1 0.423617 1.310215
row5 -2.145838 1.123145
> tmp[,c("col6","col20")]
col6 col20
row1 -0.344151455 1.3102153
row2 0.009060842 -0.3776812
row3 -1.531214688 0.5153933
row4 -0.082589181 1.2900460
row5 0.060209763 1.1231453
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.34415145 1.310215
row5 0.06020976 1.123145
>
>
>
>
> 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 53.15964 50.55782 49.89925 49.4268 49.81692 104.777 50.20261 49.66529
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.92457 51.12593 50.83843 50.04005 49.62492 50.9564 50.26107 49.49396
col17 col18 col19 col20
row1 50.30698 51.32884 49.34038 104.1778
> tmp[,"col10"]
col10
row1 51.12593
row2 28.77484
row3 29.24263
row4 29.84940
row5 49.43887
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 53.15964 50.55782 49.89925 49.42680 49.81692 104.7770 50.20261 49.66529
row5 51.45179 50.34226 50.62932 49.51221 51.55441 104.2072 49.13637 49.62040
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.92457 51.12593 50.83843 50.04005 49.62492 50.95640 50.26107 49.49396
row5 46.97583 49.43887 49.50334 48.77445 49.45030 50.95232 49.94314 49.71479
col17 col18 col19 col20
row1 50.30698 51.32884 49.34038 104.1778
row5 51.67753 47.23469 49.69255 104.7831
> tmp[,c("col6","col20")]
col6 col20
row1 104.77705 104.17784
row2 76.48596 73.22197
row3 73.52156 75.08714
row4 77.94673 75.31331
row5 104.20718 104.78308
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7770 104.1778
row5 104.2072 104.7831
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7770 104.1778
row5 104.2072 104.7831
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.6149523
[2,] -1.1326142
[3,] -1.1091163
[4,] 0.6286703
[5,] -1.0459577
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.0724286 -1.1647206
[2,] 2.0228266 -0.3151131
[3,] -1.3391979 -0.5703226
[4,] -0.9505233 -1.2562817
[5,] 1.1447380 -1.0864073
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.11668330 -0.94528963
[2,] 1.11987969 1.64984812
[3,] 0.71473371 -0.02404135
[4,] 0.02988593 -0.14059388
[5,] 0.61828931 0.06734483
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.1166833
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.1166833
[2,] 1.1198797
>
>
>
> 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 -0.6571456 0.1155856 0.1105827 -0.3559427 -1.227315 0.3396575 0.4551695
row1 0.9208132 -2.6552887 0.6654118 -0.2627671 -1.032098 -0.1810774 -2.1242913
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.88174996 -2.344373 0.7548949 2.1461812 0.0949916 -0.06529001 -1.077937
row1 0.08015278 1.375172 0.1164961 0.7050818 -0.7571472 1.18730651 -1.438636
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.565902 -0.06677062 -0.4570516 -0.5276291 1.496103 -0.2673115
row1 1.082389 0.65198250 0.8015855 -1.2241174 -1.610252 0.8921277
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.033062 -1.131215 0.26944 -0.9784595 0.5274086 -0.03312922 0.1274462
[,8] [,9] [,10]
row2 -0.1537088 0.97673 0.6580437
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5084831 2.260193 1.318332 -0.3757292 0.5382938 0.7229027 -0.4684596
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.278274 0.1601042 1.169655 0.986265 1.052808 -0.08205919 -0.2304276
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.298966 -1.821057 -0.7559656 -0.7784357 0.1349428 0.3144694
>
>
> 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: 0x5d5db65fd8c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a8f788dbd"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a8170f0ee5"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a8105484e9"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a84e589ff7"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a874559cc5"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a8ee84ce9"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a86a53d928"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a820b12d73"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a866759aa"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a872de8f7d"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a83b5014b9"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a8637ef232"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a858765e60"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a86a2e84ef"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ed2a8500f9384"
>
>
> ### 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: 0x5d5db7fb0990>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5d5db7fb0990>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5d5db7fb0990>
> rowMedians(tmp)
[1] -0.056113644 0.334055963 0.206128671 -0.219142824 -0.159420382
[6] 0.290133621 -0.209628486 0.512356675 0.064088133 -0.151877867
[11] -0.240052406 0.358300018 0.039714357 0.423288760 -0.118786095
[16] 0.375458853 -0.361131243 -0.378106224 0.401452870 0.321446139
[21] -0.479800734 0.052753327 -0.849476474 -0.443007777 -0.172374067
[26] -0.214448917 -0.037460462 0.160508264 -0.242885219 0.132478104
[31] -0.141012657 -0.305758237 -0.396331716 0.086081796 0.073128077
[36] 0.411602621 0.713809541 0.358684298 -0.030487780 -0.947809651
[41] 0.156430723 0.494211279 0.314144403 -0.075710203 -0.219741798
[46] 0.197230125 -0.017707489 -0.479894208 -0.088049871 -0.283370108
[51] -0.177632867 -0.004031748 -0.529076248 -0.569932493 -0.345545070
[56] -0.283032695 0.454368426 0.346371353 0.196472792 0.250084809
[61] -0.603661513 -0.229245610 -0.071276491 -0.254282510 0.445380119
[66] 0.320109142 0.570966918 0.001270877 0.172224361 -0.078222616
[71] -0.114136410 -0.135621324 -0.030035189 0.173141941 0.060924262
[76] 0.325873460 0.004041238 0.841586503 0.258095434 0.249399663
[81] -0.030770427 -0.219396927 -0.239487572 0.402252896 -0.318870663
[86] 0.392068721 0.024530541 -0.406665124 0.072778658 0.410688696
[91] 0.336675430 -0.113376780 -0.299172472 0.256749562 0.288573693
[96] 0.201580043 0.087891142 -0.221226989 -0.122553349 0.016405797
[101] 0.017249513 0.139870952 0.549723430 0.214039897 -0.341402535
[106] -0.017616597 0.314561614 -0.436606873 0.180427336 0.398362871
[111] -0.121587142 -0.401517305 -0.542040812 -0.116834422 0.244389607
[116] -0.136823039 -0.335728722 -0.126549748 0.004276360 -0.182521498
[121] -0.020599224 0.221783176 -0.367137266 -0.324676801 -0.090766167
[126] -0.126720799 -0.744353943 0.113917005 0.254902066 0.445163543
[131] 0.207069159 -0.079468645 0.126732028 0.106800509 -0.474619488
[136] -0.264527087 0.332941809 -0.026171473 0.254253586 -0.113399957
[141] 0.086006377 -0.547239192 0.259856340 -0.437937083 0.269474118
[146] -0.185838460 0.285321778 0.106387463 0.485713778 -0.355397311
[151] 0.102221049 0.753624391 -0.019519756 0.044004402 0.150475916
[156] -0.107474092 0.146288730 -0.320662622 -0.077316444 -0.573848335
[161] -0.012724274 -0.145774057 0.154233533 0.170852567 0.157195717
[166] -0.476811351 -0.432883148 0.272458214 0.231735662 -0.171958796
[171] 0.539635146 -0.246082228 0.263284184 0.105475615 0.102778624
[176] -0.027134837 0.022498716 -0.333026168 -0.227890324 0.300419911
[181] 0.014359397 -0.182976006 -0.090901096 0.465791453 -0.305784726
[186] 0.064085806 0.328113223 -0.329979714 0.028591206 -0.189807783
[191] -0.037144017 0.324963719 0.011003366 -0.271518339 0.228008983
[196] -0.267265426 0.185285285 -0.049574957 0.266772657 0.852550206
[201] -0.164140875 -0.341334799 -0.540945974 -0.094952835 0.632495211
[206] 0.521966499 0.165114412 0.397330750 0.363710236 -0.288427797
[211] 0.422812933 0.373793649 0.032405849 -0.457735368 -0.184454054
[216] 0.302912123 0.308643688 -0.119035252 -0.227045727 0.192590302
[221] -0.239326788 -0.071024737 -0.832038795 -0.545548227 -0.017988228
[226] 0.282089244 -0.175446957 -0.580459587 0.227028330 0.212298854
>
> proc.time()
user system elapsed
1.823 1.105 3.082
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
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: 0x607f592d3c80>
> .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: 0x607f592d3c80>
> .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: 0x607f592d3c80>
> .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: 0x607f592d3c80>
> 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: 0x607f58f6aa00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f58f6aa00>
> .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: 0x607f58f6aa00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f58f6aa00>
> .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: 0x607f58f6aa00>
> 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: 0x607f59035660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f59035660>
> .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: 0x607f59035660>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x607f59035660>
> .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: 0x607f59035660>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x607f59035660>
> .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: 0x607f59035660>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x607f59035660>
> .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: 0x607f59035660>
> 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: 0x607f595573d0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x607f595573d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f595573d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f595573d0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2ed4084507f8e8" "BufferedMatrixFile2ed4087ac35ece"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2ed4084507f8e8" "BufferedMatrixFile2ed4087ac35ece"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f5b6b4460>
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f5b6b4460>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x607f5b6b4460>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x607f5b6b4460>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x607f5b6b4460>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x607f5b6b4460>
> .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: 0x607f59b396d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x607f59b396d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x607f59b396d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x607f59b396d0>
> 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: 0x607f5af7c0c0>
> .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: 0x607f5af7c0c0>
> rm(P)
>
> proc.time()
user system elapsed
0.386 0.054 0.465
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.322 0.043 0.354