Ben Bolstad
| Snapshot Date: 2025-11-10 13:45 -0500 (Mon, 10 Nov 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-11-11 12:02 -0500 (Tue, 11 Nov 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" | 4902 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4638 |
| 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 257/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.74.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.74.0 |
| 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_1.74.0.tar.gz |
| StartedAt: 2025-11-10 21:51:43 -0500 (Mon, 10 Nov 2025) |
| EndedAt: 2025-11-10 21:52:07 -0500 (Mon, 10 Nov 2025) |
| EllapsedTime: 24.0 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_1.74.0.tar.gz
###
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* 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 ‘1.74.0’
* 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
##############################################################################
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###
### 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 ‘1.74.0’
** 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
0.233 0.047 0.271
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] "Mon Nov 10 21:51:58 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] "Mon Nov 10 21:51:58 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: 0x5f123623eb10>
>
>
>
> 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] "Mon Nov 10 21:51:59 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] "Mon Nov 10 21:51:59 2025"
>
> ColMode(tmp2)
<pointer: 0x5f123623eb10>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.0959293 -0.6199386 -0.4718065 -0.6450846
[2,] 0.5901250 1.0940565 -1.5511675 1.6357769
[3,] 0.9950508 0.6063482 -1.8635682 1.3111989
[4,] 0.5219471 0.3280268 -0.8484518 0.6408452
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.0959293 0.6199386 0.4718065 0.6450846
[2,] 0.5901250 1.0940565 1.5511675 1.6357769
[3,] 0.9950508 0.6063482 1.8635682 1.3111989
[4,] 0.5219471 0.3280268 0.8484518 0.6408452
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9043389 0.7873618 0.6868818 0.8031716
[2,] 0.7681959 1.0459716 1.2454587 1.2789749
[3,] 0.9975223 0.7786837 1.3651257 1.1450759
[4,] 0.7224590 0.5727363 0.9211144 0.8005281
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 222.13932 33.49356 32.34062 33.67680
[2,] 33.27208 36.55377 39.00575 39.42553
[3,] 35.97027 33.39318 40.51483 37.76196
[4,] 32.74654 31.05539 35.05960 33.64613
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5f12350117c0>
> exp(tmp5)
<pointer: 0x5f12350117c0>
> log(tmp5,2)
<pointer: 0x5f12350117c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 462.3539
> Min(tmp5)
[1] 53.4056
> mean(tmp5)
[1] 72.65399
> Sum(tmp5)
[1] 14530.8
> Var(tmp5)
[1] 830.4122
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.17285 74.05704 74.36742 70.64898 69.41296 67.59313 69.86380 71.06255
[9] 67.36658 70.99453
> rowSums(tmp5)
[1] 1823.457 1481.141 1487.348 1412.980 1388.259 1351.863 1397.276 1421.251
[9] 1347.332 1419.891
> rowVars(tmp5)
[1] 7696.56955 55.50040 53.88793 52.70057 75.56790 51.59433
[7] 72.32337 60.67784 41.70492 85.35083
> rowSd(tmp5)
[1] 87.730095 7.449859 7.340840 7.259516 8.692980 7.182920 8.504315
[8] 7.789598 6.457935 9.238551
> rowMax(tmp5)
[1] 462.35389 84.00702 87.78787 94.90732 90.72204 80.03684 83.65318
[8] 91.74274 80.37407 93.24096
> rowMin(tmp5)
[1] 57.67840 60.44249 56.55092 62.24514 57.13371 53.40560 54.25652 61.13961
[9] 55.63916 57.91214
>
> colMeans(tmp5)
[1] 108.42737 67.97532 70.98172 71.60352 77.58346 72.87328 68.13503
[8] 70.05924 69.10838 70.20665 71.95843 72.08480 67.03194 69.71749
[15] 69.80645 68.51611 69.92384 70.20817 74.63507 72.24344
> colSums(tmp5)
[1] 1084.2737 679.7532 709.8172 716.0352 775.8346 728.7328 681.3503
[8] 700.5924 691.0838 702.0665 719.5843 720.8480 670.3194 697.1749
[15] 698.0645 685.1611 699.2384 702.0817 746.3507 722.4344
> colVars(tmp5)
[1] 15476.10609 31.35087 65.01745 114.54734 64.69593 129.48914
[7] 41.11328 74.24026 55.01659 54.40096 45.41596 36.36967
[13] 85.81180 82.62351 39.35140 42.18368 47.85344 67.21317
[19] 91.72160 95.27523
> colSd(tmp5)
[1] 124.402999 5.599184 8.063340 10.702679 8.043378 11.379330
[7] 6.411964 8.616279 7.417317 7.375700 6.739136 6.030727
[13] 9.263466 9.089748 6.273070 6.494896 6.917618 8.198364
[19] 9.577140 9.760903
> colMax(tmp5)
[1] 462.35389 76.08189 84.32630 93.24096 89.28346 89.78476 80.52645
[8] 84.00702 83.40491 80.02170 83.65318 80.72169 80.64376 90.72204
[15] 83.07957 75.31224 83.58241 83.48022 94.90732 91.74274
> colMin(tmp5)
[1] 61.87856 56.08215 61.07744 60.59524 66.09992 56.13594 59.78128 57.91214
[9] 59.82982 59.39948 62.62181 62.26296 53.40560 59.16485 62.86646 57.67840
[17] 62.18380 54.25652 61.84500 55.63916
>
>
> ### 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] 91.17285 74.05704 NA 70.64898 69.41296 67.59313 69.86380 71.06255
[9] 67.36658 70.99453
> rowSums(tmp5)
[1] 1823.457 1481.141 NA 1412.980 1388.259 1351.863 1397.276 1421.251
[9] 1347.332 1419.891
> rowVars(tmp5)
[1] 7696.56955 55.50040 56.85028 52.70057 75.56790 51.59433
[7] 72.32337 60.67784 41.70492 85.35083
> rowSd(tmp5)
[1] 87.730095 7.449859 7.539913 7.259516 8.692980 7.182920 8.504315
[8] 7.789598 6.457935 9.238551
> rowMax(tmp5)
[1] 462.35389 84.00702 NA 94.90732 90.72204 80.03684 83.65318
[8] 91.74274 80.37407 93.24096
> rowMin(tmp5)
[1] 57.67840 60.44249 NA 62.24514 57.13371 53.40560 54.25652 61.13961
[9] 55.63916 57.91214
>
> colMeans(tmp5)
[1] 108.42737 67.97532 70.98172 71.60352 77.58346 72.87328 68.13503
[8] 70.05924 69.10838 70.20665 71.95843 72.08480 67.03194 69.71749
[15] 69.80645 68.51611 69.92384 70.20817 74.63507 NA
> colSums(tmp5)
[1] 1084.2737 679.7532 709.8172 716.0352 775.8346 728.7328 681.3503
[8] 700.5924 691.0838 702.0665 719.5843 720.8480 670.3194 697.1749
[15] 698.0645 685.1611 699.2384 702.0817 746.3507 NA
> colVars(tmp5)
[1] 15476.10609 31.35087 65.01745 114.54734 64.69593 129.48914
[7] 41.11328 74.24026 55.01659 54.40096 45.41596 36.36967
[13] 85.81180 82.62351 39.35140 42.18368 47.85344 67.21317
[19] 91.72160 NA
> colSd(tmp5)
[1] 124.402999 5.599184 8.063340 10.702679 8.043378 11.379330
[7] 6.411964 8.616279 7.417317 7.375700 6.739136 6.030727
[13] 9.263466 9.089748 6.273070 6.494896 6.917618 8.198364
[19] 9.577140 NA
> colMax(tmp5)
[1] 462.35389 76.08189 84.32630 93.24096 89.28346 89.78476 80.52645
[8] 84.00702 83.40491 80.02170 83.65318 80.72169 80.64376 90.72204
[15] 83.07957 75.31224 83.58241 83.48022 94.90732 NA
> colMin(tmp5)
[1] 61.87856 56.08215 61.07744 60.59524 66.09992 56.13594 59.78128 57.91214
[9] 59.82982 59.39948 62.62181 62.26296 53.40560 59.16485 62.86646 57.67840
[17] 62.18380 54.25652 61.84500 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 462.3539
> Min(tmp5,na.rm=TRUE)
[1] 53.4056
> mean(tmp5,na.rm=TRUE)
[1] 72.64169
> Sum(tmp5,na.rm=TRUE)
[1] 14455.7
> Var(tmp5,na.rm=TRUE)
[1] 834.5758
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.17285 74.05704 74.32884 70.64898 69.41296 67.59313 69.86380 71.06255
[9] 67.36658 70.99453
> rowSums(tmp5,na.rm=TRUE)
[1] 1823.457 1481.141 1412.248 1412.980 1388.259 1351.863 1397.276 1421.251
[9] 1347.332 1419.891
> rowVars(tmp5,na.rm=TRUE)
[1] 7696.56955 55.50040 56.85028 52.70057 75.56790 51.59433
[7] 72.32337 60.67784 41.70492 85.35083
> rowSd(tmp5,na.rm=TRUE)
[1] 87.730095 7.449859 7.539913 7.259516 8.692980 7.182920 8.504315
[8] 7.789598 6.457935 9.238551
> rowMax(tmp5,na.rm=TRUE)
[1] 462.35389 84.00702 87.78787 94.90732 90.72204 80.03684 83.65318
[8] 91.74274 80.37407 93.24096
> rowMin(tmp5,na.rm=TRUE)
[1] 57.67840 60.44249 56.55092 62.24514 57.13371 53.40560 54.25652 61.13961
[9] 55.63916 57.91214
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.42737 67.97532 70.98172 71.60352 77.58346 72.87328 68.13503
[8] 70.05924 69.10838 70.20665 71.95843 72.08480 67.03194 69.71749
[15] 69.80645 68.51611 69.92384 70.20817 74.63507 71.92599
> colSums(tmp5,na.rm=TRUE)
[1] 1084.2737 679.7532 709.8172 716.0352 775.8346 728.7328 681.3503
[8] 700.5924 691.0838 702.0665 719.5843 720.8480 670.3194 697.1749
[15] 698.0645 685.1611 699.2384 702.0817 746.3507 647.3339
> colVars(tmp5,na.rm=TRUE)
[1] 15476.10609 31.35087 65.01745 114.54734 64.69593 129.48914
[7] 41.11328 74.24026 55.01659 54.40096 45.41596 36.36967
[13] 85.81180 82.62351 39.35140 42.18368 47.85344 67.21317
[19] 91.72160 106.05094
> colSd(tmp5,na.rm=TRUE)
[1] 124.402999 5.599184 8.063340 10.702679 8.043378 11.379330
[7] 6.411964 8.616279 7.417317 7.375700 6.739136 6.030727
[13] 9.263466 9.089748 6.273070 6.494896 6.917618 8.198364
[19] 9.577140 10.298104
> colMax(tmp5,na.rm=TRUE)
[1] 462.35389 76.08189 84.32630 93.24096 89.28346 89.78476 80.52645
[8] 84.00702 83.40491 80.02170 83.65318 80.72169 80.64376 90.72204
[15] 83.07957 75.31224 83.58241 83.48022 94.90732 91.74274
> colMin(tmp5,na.rm=TRUE)
[1] 61.87856 56.08215 61.07744 60.59524 66.09992 56.13594 59.78128 57.91214
[9] 59.82982 59.39948 62.62181 62.26296 53.40560 59.16485 62.86646 57.67840
[17] 62.18380 54.25652 61.84500 55.63916
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.17285 74.05704 NaN 70.64898 69.41296 67.59313 69.86380 71.06255
[9] 67.36658 70.99453
> rowSums(tmp5,na.rm=TRUE)
[1] 1823.457 1481.141 0.000 1412.980 1388.259 1351.863 1397.276 1421.251
[9] 1347.332 1419.891
> rowVars(tmp5,na.rm=TRUE)
[1] 7696.56955 55.50040 NA 52.70057 75.56790 51.59433
[7] 72.32337 60.67784 41.70492 85.35083
> rowSd(tmp5,na.rm=TRUE)
[1] 87.730095 7.449859 NA 7.259516 8.692980 7.182920 8.504315
[8] 7.789598 6.457935 9.238551
> rowMax(tmp5,na.rm=TRUE)
[1] 462.35389 84.00702 NA 94.90732 90.72204 80.03684 83.65318
[8] 91.74274 80.37407 93.24096
> rowMin(tmp5,na.rm=TRUE)
[1] 57.67840 60.44249 NA 62.24514 57.13371 53.40560 54.25652 61.13961
[9] 55.63916 57.91214
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.15625 67.80551 69.49899 70.82652 76.44964 71.31087 68.23667
[8] 69.19934 68.87746 69.43847 71.86818 71.38781 68.19650 68.78615
[15] 69.72418 68.61099 70.15891 69.77563 75.03800 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1009.4063 610.2496 625.4909 637.4386 688.0467 641.7979 614.1300
[8] 622.7941 619.8971 624.9462 646.8137 642.4903 613.7685 619.0753
[15] 627.5177 617.4989 631.4302 627.9807 675.3420 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17254.19287 34.94535 48.41161 122.07372 58.32043 118.21272
[7] 46.13621 75.20187 61.29375 54.56239 51.00134 35.45063
[13] 81.28108 83.19318 44.19420 47.35536 53.21345 73.51007
[19] 101.36042 NA
> colSd(tmp5,na.rm=TRUE)
[1] 131.355216 5.911460 6.957845 11.048698 7.636781 10.872567
[7] 6.792364 8.671901 7.829033 7.386636 7.141522 5.954043
[13] 9.015602 9.121029 6.647872 6.881523 7.294755 8.573801
[19] 10.067791 NA
> colMax(tmp5,na.rm=TRUE)
[1] 462.35389 76.08189 81.18537 93.24096 89.28346 89.78476 80.52645
[8] 84.00702 83.40491 80.02170 83.65318 80.72169 80.64376 90.72204
[15] 83.07957 75.31224 83.58241 83.48022 94.90732 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 61.87856 56.08215 61.07744 60.59524 66.09992 56.13594 59.78128 57.91214
[9] 59.82982 59.39948 62.62181 62.26296 53.40560 59.16485 62.86646 57.67840
[17] 62.18380 54.25652 61.84500 Inf
>
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col <- 1
> cat(which.row," ",which.col,"\n")
3 1
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> rowVars(tmp5,na.rm=TRUE)
[1] 158.6600 256.8429 230.2013 134.2679 210.5844 205.3260 150.3841 362.2052
[9] 155.3500 295.5356
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 158.6600 256.8429 230.2013 134.2679 210.5844 205.3260 150.3841 362.2052
[9] 155.3500 295.5356
>
>
>
> 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] 1.705303e-13 -2.842171e-13 -1.421085e-14 -5.684342e-14 5.684342e-14
[6] 1.847411e-13 -2.842171e-14 1.705303e-13 5.684342e-14 1.136868e-13
[11] 1.989520e-13 5.684342e-14 2.557954e-13 1.421085e-14 1.705303e-13
[16] -2.842171e-14 0.000000e+00 4.263256e-14 5.684342e-14 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 8
7 12
3 10
10 5
5 11
5 11
2 6
5 3
2 15
9 6
1 11
2 19
3 11
2 18
5 1
1 10
3 5
3 13
1 14
1 3
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] 2.522164
> Min(tmp)
[1] -2.422548
> mean(tmp)
[1] 0.1110618
> Sum(tmp)
[1] 11.10618
> Var(tmp)
[1] 0.9264626
>
> rowMeans(tmp)
[1] 0.1110618
> rowSums(tmp)
[1] 11.10618
> rowVars(tmp)
[1] 0.9264626
> rowSd(tmp)
[1] 0.9625293
> rowMax(tmp)
[1] 2.522164
> rowMin(tmp)
[1] -2.422548
>
> colMeans(tmp)
[1] 0.210839772 -0.672671262 0.859277485 0.788648003 0.154110164
[6] 0.721931465 -0.068007657 0.808167790 -2.422548405 -0.383769626
[11] 0.415171848 -0.634350658 1.841378790 0.503373422 0.013805916
[16] -0.466435515 -0.206200524 0.283633259 0.117419131 1.875525079
[21] 1.479671422 -1.349627070 0.215575818 1.645349269 0.902476400
[26] -1.155361441 0.356480495 1.074357749 1.459783543 2.459156115
[31] -0.466511862 0.789908776 -1.503606925 -0.162615684 -0.361197332
[36] 0.862327081 -0.734595699 0.500971878 -0.673100714 0.554880540
[41] 0.890308012 0.308949544 -0.510280116 -0.093369988 -1.162876981
[46] 0.726502029 -1.699793149 1.340582202 0.736622239 -0.998219107
[51] 0.372071522 -0.558949160 0.225448417 -0.823284563 1.031290283
[56] -1.594454540 0.549410453 1.888406153 0.629042118 -0.834976252
[61] -1.583429841 -0.012751826 2.522164006 -0.807926078 0.145130449
[66] 1.128620472 -0.437897140 0.345267827 0.114796416 1.541293751
[71] -0.447521649 -0.155916628 -0.741884498 -0.002493551 0.733791737
[76] 1.460611840 -1.314409350 -0.737482595 0.040472256 -1.107632680
[81] 1.264687386 0.664366010 -0.348342245 0.215931974 0.047718229
[86] -0.037191867 1.626768668 0.013038906 -1.314664183 0.006675326
[91] 0.095832332 -0.109040274 -0.761557320 -0.513137187 -0.495213527
[96] 0.310730061 -1.474519435 -0.721869033 0.727150908 1.169963287
> colSums(tmp)
[1] 0.210839772 -0.672671262 0.859277485 0.788648003 0.154110164
[6] 0.721931465 -0.068007657 0.808167790 -2.422548405 -0.383769626
[11] 0.415171848 -0.634350658 1.841378790 0.503373422 0.013805916
[16] -0.466435515 -0.206200524 0.283633259 0.117419131 1.875525079
[21] 1.479671422 -1.349627070 0.215575818 1.645349269 0.902476400
[26] -1.155361441 0.356480495 1.074357749 1.459783543 2.459156115
[31] -0.466511862 0.789908776 -1.503606925 -0.162615684 -0.361197332
[36] 0.862327081 -0.734595699 0.500971878 -0.673100714 0.554880540
[41] 0.890308012 0.308949544 -0.510280116 -0.093369988 -1.162876981
[46] 0.726502029 -1.699793149 1.340582202 0.736622239 -0.998219107
[51] 0.372071522 -0.558949160 0.225448417 -0.823284563 1.031290283
[56] -1.594454540 0.549410453 1.888406153 0.629042118 -0.834976252
[61] -1.583429841 -0.012751826 2.522164006 -0.807926078 0.145130449
[66] 1.128620472 -0.437897140 0.345267827 0.114796416 1.541293751
[71] -0.447521649 -0.155916628 -0.741884498 -0.002493551 0.733791737
[76] 1.460611840 -1.314409350 -0.737482595 0.040472256 -1.107632680
[81] 1.264687386 0.664366010 -0.348342245 0.215931974 0.047718229
[86] -0.037191867 1.626768668 0.013038906 -1.314664183 0.006675326
[91] 0.095832332 -0.109040274 -0.761557320 -0.513137187 -0.495213527
[96] 0.310730061 -1.474519435 -0.721869033 0.727150908 1.169963287
> 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] 0.210839772 -0.672671262 0.859277485 0.788648003 0.154110164
[6] 0.721931465 -0.068007657 0.808167790 -2.422548405 -0.383769626
[11] 0.415171848 -0.634350658 1.841378790 0.503373422 0.013805916
[16] -0.466435515 -0.206200524 0.283633259 0.117419131 1.875525079
[21] 1.479671422 -1.349627070 0.215575818 1.645349269 0.902476400
[26] -1.155361441 0.356480495 1.074357749 1.459783543 2.459156115
[31] -0.466511862 0.789908776 -1.503606925 -0.162615684 -0.361197332
[36] 0.862327081 -0.734595699 0.500971878 -0.673100714 0.554880540
[41] 0.890308012 0.308949544 -0.510280116 -0.093369988 -1.162876981
[46] 0.726502029 -1.699793149 1.340582202 0.736622239 -0.998219107
[51] 0.372071522 -0.558949160 0.225448417 -0.823284563 1.031290283
[56] -1.594454540 0.549410453 1.888406153 0.629042118 -0.834976252
[61] -1.583429841 -0.012751826 2.522164006 -0.807926078 0.145130449
[66] 1.128620472 -0.437897140 0.345267827 0.114796416 1.541293751
[71] -0.447521649 -0.155916628 -0.741884498 -0.002493551 0.733791737
[76] 1.460611840 -1.314409350 -0.737482595 0.040472256 -1.107632680
[81] 1.264687386 0.664366010 -0.348342245 0.215931974 0.047718229
[86] -0.037191867 1.626768668 0.013038906 -1.314664183 0.006675326
[91] 0.095832332 -0.109040274 -0.761557320 -0.513137187 -0.495213527
[96] 0.310730061 -1.474519435 -0.721869033 0.727150908 1.169963287
> colMin(tmp)
[1] 0.210839772 -0.672671262 0.859277485 0.788648003 0.154110164
[6] 0.721931465 -0.068007657 0.808167790 -2.422548405 -0.383769626
[11] 0.415171848 -0.634350658 1.841378790 0.503373422 0.013805916
[16] -0.466435515 -0.206200524 0.283633259 0.117419131 1.875525079
[21] 1.479671422 -1.349627070 0.215575818 1.645349269 0.902476400
[26] -1.155361441 0.356480495 1.074357749 1.459783543 2.459156115
[31] -0.466511862 0.789908776 -1.503606925 -0.162615684 -0.361197332
[36] 0.862327081 -0.734595699 0.500971878 -0.673100714 0.554880540
[41] 0.890308012 0.308949544 -0.510280116 -0.093369988 -1.162876981
[46] 0.726502029 -1.699793149 1.340582202 0.736622239 -0.998219107
[51] 0.372071522 -0.558949160 0.225448417 -0.823284563 1.031290283
[56] -1.594454540 0.549410453 1.888406153 0.629042118 -0.834976252
[61] -1.583429841 -0.012751826 2.522164006 -0.807926078 0.145130449
[66] 1.128620472 -0.437897140 0.345267827 0.114796416 1.541293751
[71] -0.447521649 -0.155916628 -0.741884498 -0.002493551 0.733791737
[76] 1.460611840 -1.314409350 -0.737482595 0.040472256 -1.107632680
[81] 1.264687386 0.664366010 -0.348342245 0.215931974 0.047718229
[86] -0.037191867 1.626768668 0.013038906 -1.314664183 0.006675326
[91] 0.095832332 -0.109040274 -0.761557320 -0.513137187 -0.495213527
[96] 0.310730061 -1.474519435 -0.721869033 0.727150908 1.169963287
> colMedians(tmp)
[1] 0.210839772 -0.672671262 0.859277485 0.788648003 0.154110164
[6] 0.721931465 -0.068007657 0.808167790 -2.422548405 -0.383769626
[11] 0.415171848 -0.634350658 1.841378790 0.503373422 0.013805916
[16] -0.466435515 -0.206200524 0.283633259 0.117419131 1.875525079
[21] 1.479671422 -1.349627070 0.215575818 1.645349269 0.902476400
[26] -1.155361441 0.356480495 1.074357749 1.459783543 2.459156115
[31] -0.466511862 0.789908776 -1.503606925 -0.162615684 -0.361197332
[36] 0.862327081 -0.734595699 0.500971878 -0.673100714 0.554880540
[41] 0.890308012 0.308949544 -0.510280116 -0.093369988 -1.162876981
[46] 0.726502029 -1.699793149 1.340582202 0.736622239 -0.998219107
[51] 0.372071522 -0.558949160 0.225448417 -0.823284563 1.031290283
[56] -1.594454540 0.549410453 1.888406153 0.629042118 -0.834976252
[61] -1.583429841 -0.012751826 2.522164006 -0.807926078 0.145130449
[66] 1.128620472 -0.437897140 0.345267827 0.114796416 1.541293751
[71] -0.447521649 -0.155916628 -0.741884498 -0.002493551 0.733791737
[76] 1.460611840 -1.314409350 -0.737482595 0.040472256 -1.107632680
[81] 1.264687386 0.664366010 -0.348342245 0.215931974 0.047718229
[86] -0.037191867 1.626768668 0.013038906 -1.314664183 0.006675326
[91] 0.095832332 -0.109040274 -0.761557320 -0.513137187 -0.495213527
[96] 0.310730061 -1.474519435 -0.721869033 0.727150908 1.169963287
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.2108398 -0.6726713 0.8592775 0.788648 0.1541102 0.7219315 -0.06800766
[2,] 0.2108398 -0.6726713 0.8592775 0.788648 0.1541102 0.7219315 -0.06800766
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.8081678 -2.422548 -0.3837696 0.4151718 -0.6343507 1.841379 0.5033734
[2,] 0.8081678 -2.422548 -0.3837696 0.4151718 -0.6343507 1.841379 0.5033734
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.01380592 -0.4664355 -0.2062005 0.2836333 0.1174191 1.875525 1.479671
[2,] 0.01380592 -0.4664355 -0.2062005 0.2836333 0.1174191 1.875525 1.479671
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.349627 0.2155758 1.645349 0.9024764 -1.155361 0.3564805 1.074358
[2,] -1.349627 0.2155758 1.645349 0.9024764 -1.155361 0.3564805 1.074358
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.459784 2.459156 -0.4665119 0.7899088 -1.503607 -0.1626157 -0.3611973
[2,] 1.459784 2.459156 -0.4665119 0.7899088 -1.503607 -0.1626157 -0.3611973
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8623271 -0.7345957 0.5009719 -0.6731007 0.5548805 0.890308 0.3089495
[2,] 0.8623271 -0.7345957 0.5009719 -0.6731007 0.5548805 0.890308 0.3089495
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.5102801 -0.09336999 -1.162877 0.726502 -1.699793 1.340582 0.7366222
[2,] -0.5102801 -0.09336999 -1.162877 0.726502 -1.699793 1.340582 0.7366222
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.9982191 0.3720715 -0.5589492 0.2254484 -0.8232846 1.03129 -1.594455
[2,] -0.9982191 0.3720715 -0.5589492 0.2254484 -0.8232846 1.03129 -1.594455
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.5494105 1.888406 0.6290421 -0.8349763 -1.58343 -0.01275183 2.522164
[2,] 0.5494105 1.888406 0.6290421 -0.8349763 -1.58343 -0.01275183 2.522164
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.8079261 0.1451304 1.12862 -0.4378971 0.3452678 0.1147964 1.541294
[2,] -0.8079261 0.1451304 1.12862 -0.4378971 0.3452678 0.1147964 1.541294
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.4475216 -0.1559166 -0.7418845 -0.002493551 0.7337917 1.460612 -1.314409
[2,] -0.4475216 -0.1559166 -0.7418845 -0.002493551 0.7337917 1.460612 -1.314409
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.7374826 0.04047226 -1.107633 1.264687 0.664366 -0.3483422 0.215932
[2,] -0.7374826 0.04047226 -1.107633 1.264687 0.664366 -0.3483422 0.215932
[,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.04771823 -0.03719187 1.626769 0.01303891 -1.314664 0.006675326
[2,] 0.04771823 -0.03719187 1.626769 0.01303891 -1.314664 0.006675326
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.09583233 -0.1090403 -0.7615573 -0.5131372 -0.4952135 0.3107301 -1.474519
[2,] 0.09583233 -0.1090403 -0.7615573 -0.5131372 -0.4952135 0.3107301 -1.474519
[,98] [,99] [,100]
[1,] -0.721869 0.7271509 1.169963
[2,] -0.721869 0.7271509 1.169963
>
>
> Max(tmp2)
[1] 2.212622
> Min(tmp2)
[1] -2.63007
> mean(tmp2)
[1] -0.1218263
> Sum(tmp2)
[1] -12.18263
> Var(tmp2)
[1] 0.9302152
>
> rowMeans(tmp2)
[1] -0.03603396 0.50261004 -0.17689778 0.37670565 -0.36778548 -1.16170979
[7] -0.14126575 -1.22911054 0.74963784 -0.14079990 0.78917144 0.26726198
[13] 0.60192336 -1.32063630 -0.19219694 -1.38316881 1.59702696 -1.49741552
[19] 0.27336465 0.85320697 -0.27220185 -1.18771901 -0.07175656 0.24303190
[25] 0.63757484 -0.93559171 -0.49910238 0.07757610 -0.83524269 -2.20193828
[31] 1.00831751 0.08527804 -1.11805349 0.67866755 -1.37297053 -2.40409380
[37] 0.86556513 -1.71888895 0.47383053 0.95598833 -1.83659742 1.14655317
[43] -0.69468416 -0.15243530 -0.41563547 0.22970329 1.82728694 -1.60669708
[49] 0.69618164 0.22494821 1.20664271 0.50952570 0.38556499 -0.27553574
[55] -0.89302152 0.59714548 -0.01442441 -1.56561710 -0.52303501 0.80646087
[61] 1.11609192 1.05908539 -0.35115817 -0.97881452 0.49445186 -0.20756799
[67] 0.41942308 0.85554014 -0.74672212 2.21262191 -0.16649007 -0.25540854
[73] -2.63007037 -1.27411641 1.11242814 -0.42750377 -0.07724469 -0.59383032
[79] -0.64243954 0.02609808 -0.74646130 -1.62436494 -0.03660963 0.57541458
[85] 0.68397739 -0.16886393 -0.40350668 -1.80612577 -1.75611055 -0.07051674
[91] 1.42656491 0.43280508 -0.53019446 0.91732546 1.04388102 0.46676334
[97] -0.45766740 -0.40155111 0.66832069 0.23542511
> rowSums(tmp2)
[1] -0.03603396 0.50261004 -0.17689778 0.37670565 -0.36778548 -1.16170979
[7] -0.14126575 -1.22911054 0.74963784 -0.14079990 0.78917144 0.26726198
[13] 0.60192336 -1.32063630 -0.19219694 -1.38316881 1.59702696 -1.49741552
[19] 0.27336465 0.85320697 -0.27220185 -1.18771901 -0.07175656 0.24303190
[25] 0.63757484 -0.93559171 -0.49910238 0.07757610 -0.83524269 -2.20193828
[31] 1.00831751 0.08527804 -1.11805349 0.67866755 -1.37297053 -2.40409380
[37] 0.86556513 -1.71888895 0.47383053 0.95598833 -1.83659742 1.14655317
[43] -0.69468416 -0.15243530 -0.41563547 0.22970329 1.82728694 -1.60669708
[49] 0.69618164 0.22494821 1.20664271 0.50952570 0.38556499 -0.27553574
[55] -0.89302152 0.59714548 -0.01442441 -1.56561710 -0.52303501 0.80646087
[61] 1.11609192 1.05908539 -0.35115817 -0.97881452 0.49445186 -0.20756799
[67] 0.41942308 0.85554014 -0.74672212 2.21262191 -0.16649007 -0.25540854
[73] -2.63007037 -1.27411641 1.11242814 -0.42750377 -0.07724469 -0.59383032
[79] -0.64243954 0.02609808 -0.74646130 -1.62436494 -0.03660963 0.57541458
[85] 0.68397739 -0.16886393 -0.40350668 -1.80612577 -1.75611055 -0.07051674
[91] 1.42656491 0.43280508 -0.53019446 0.91732546 1.04388102 0.46676334
[97] -0.45766740 -0.40155111 0.66832069 0.23542511
> 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] -0.03603396 0.50261004 -0.17689778 0.37670565 -0.36778548 -1.16170979
[7] -0.14126575 -1.22911054 0.74963784 -0.14079990 0.78917144 0.26726198
[13] 0.60192336 -1.32063630 -0.19219694 -1.38316881 1.59702696 -1.49741552
[19] 0.27336465 0.85320697 -0.27220185 -1.18771901 -0.07175656 0.24303190
[25] 0.63757484 -0.93559171 -0.49910238 0.07757610 -0.83524269 -2.20193828
[31] 1.00831751 0.08527804 -1.11805349 0.67866755 -1.37297053 -2.40409380
[37] 0.86556513 -1.71888895 0.47383053 0.95598833 -1.83659742 1.14655317
[43] -0.69468416 -0.15243530 -0.41563547 0.22970329 1.82728694 -1.60669708
[49] 0.69618164 0.22494821 1.20664271 0.50952570 0.38556499 -0.27553574
[55] -0.89302152 0.59714548 -0.01442441 -1.56561710 -0.52303501 0.80646087
[61] 1.11609192 1.05908539 -0.35115817 -0.97881452 0.49445186 -0.20756799
[67] 0.41942308 0.85554014 -0.74672212 2.21262191 -0.16649007 -0.25540854
[73] -2.63007037 -1.27411641 1.11242814 -0.42750377 -0.07724469 -0.59383032
[79] -0.64243954 0.02609808 -0.74646130 -1.62436494 -0.03660963 0.57541458
[85] 0.68397739 -0.16886393 -0.40350668 -1.80612577 -1.75611055 -0.07051674
[91] 1.42656491 0.43280508 -0.53019446 0.91732546 1.04388102 0.46676334
[97] -0.45766740 -0.40155111 0.66832069 0.23542511
> rowMin(tmp2)
[1] -0.03603396 0.50261004 -0.17689778 0.37670565 -0.36778548 -1.16170979
[7] -0.14126575 -1.22911054 0.74963784 -0.14079990 0.78917144 0.26726198
[13] 0.60192336 -1.32063630 -0.19219694 -1.38316881 1.59702696 -1.49741552
[19] 0.27336465 0.85320697 -0.27220185 -1.18771901 -0.07175656 0.24303190
[25] 0.63757484 -0.93559171 -0.49910238 0.07757610 -0.83524269 -2.20193828
[31] 1.00831751 0.08527804 -1.11805349 0.67866755 -1.37297053 -2.40409380
[37] 0.86556513 -1.71888895 0.47383053 0.95598833 -1.83659742 1.14655317
[43] -0.69468416 -0.15243530 -0.41563547 0.22970329 1.82728694 -1.60669708
[49] 0.69618164 0.22494821 1.20664271 0.50952570 0.38556499 -0.27553574
[55] -0.89302152 0.59714548 -0.01442441 -1.56561710 -0.52303501 0.80646087
[61] 1.11609192 1.05908539 -0.35115817 -0.97881452 0.49445186 -0.20756799
[67] 0.41942308 0.85554014 -0.74672212 2.21262191 -0.16649007 -0.25540854
[73] -2.63007037 -1.27411641 1.11242814 -0.42750377 -0.07724469 -0.59383032
[79] -0.64243954 0.02609808 -0.74646130 -1.62436494 -0.03660963 0.57541458
[85] 0.68397739 -0.16886393 -0.40350668 -1.80612577 -1.75611055 -0.07051674
[91] 1.42656491 0.43280508 -0.53019446 0.91732546 1.04388102 0.46676334
[97] -0.45766740 -0.40155111 0.66832069 0.23542511
>
> colMeans(tmp2)
[1] -0.1218263
> colSums(tmp2)
[1] -12.18263
> colVars(tmp2)
[1] 0.9302152
> colSd(tmp2)
[1] 0.9644766
> colMax(tmp2)
[1] 2.212622
> colMin(tmp2)
[1] -2.63007
> colMedians(tmp2)
[1] -0.07450062
> colRanges(tmp2)
[,1]
[1,] -2.630070
[2,] 2.212622
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.7984989 -2.7039425 -0.6854377 1.5554335 1.9017553 -3.9357773
[7] -5.0263217 -5.4124724 -2.6709744 -0.3375313
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.89310400
[2,] -0.89912578
[3,] -0.02029182
[4,] 0.33956961
[5,] 1.21828332
>
> rowApply(tmp,sum)
[1] -2.847091 -1.869849 4.434711 -7.863586 -3.855640 3.211260 -1.748515
[8] -5.794349 4.568756 -8.349464
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 8 2 3 8 1 7 1 9 9
[2,] 1 9 1 6 6 9 10 5 4 5
[3,] 5 6 10 8 4 7 8 2 1 10
[4,] 7 5 7 1 10 10 6 9 6 1
[5,] 3 3 9 10 7 6 9 4 8 7
[6,] 4 7 4 5 1 8 3 7 10 3
[7,] 9 2 3 4 3 5 5 8 2 4
[8,] 2 4 6 7 9 3 1 3 5 2
[9,] 6 1 5 9 2 2 2 6 7 8
[10,] 10 10 8 2 5 4 4 10 3 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.17489637 -2.78909826 -0.70127887 1.40252346 -2.55076411 1.49547421
[7] -2.03796641 3.37960515 -2.70587639 3.20132506 2.48173735 1.27777395
[13] -1.05493727 -2.01144370 0.42001918 -1.50033154 -1.05225162 0.03523804
[19] 1.15138064 1.79876845
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1525922
[2,] -2.1202936
[3,] -0.9008326
[4,] 0.7352414
[5,] 1.2635807
>
> rowApply(tmp,sum)
[1] -3.4030497 5.5647302 -9.5004107 4.1639905 0.2397407
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 16 1 5 18
[2,] 8 8 2 2 17
[3,] 16 3 8 19 2
[4,] 13 10 7 18 10
[5,] 9 7 10 14 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -2.1525922 -0.605677687 0.6921131 0.3680889 -0.2965081 -0.9523951
[2,] 0.7352414 0.007758657 -0.8014924 0.2962976 -0.3631768 -0.3689020
[3,] -2.1202936 -1.822737746 -1.1552273 -1.2211206 -0.8003477 -0.6046856
[4,] -0.9008326 -1.529479084 2.0527630 1.8536004 0.6231990 1.0813253
[5,] 1.2635807 1.161037598 -1.4894353 0.1056572 -1.7139305 2.3401315
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3869015 1.2051877 -1.2365150 0.8094113 -0.2851536 0.9060001
[2,] -0.8383912 0.4915917 0.5841109 1.8197615 0.3717243 1.2284545
[3,] 0.7948051 1.6657600 -1.2467392 -0.2487757 -1.5642739 -1.5395996
[4,] -1.4040677 -0.4247276 0.1123542 0.3246888 2.5761571 0.5380976
[5,] -0.9772140 0.4417933 -0.9190873 0.4962392 1.3832834 0.1448214
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.8672473 -0.8447234 0.3347939 -0.1595179 -0.6633380 -1.5815568
[2,] 0.3541168 -1.2288654 0.4610680 0.1451036 -0.4867113 1.2752902
[3,] 0.1744272 1.3985142 -0.6771236 -1.3819672 0.8439292 0.0759807
[4,] -1.8143152 -1.4485158 0.3436850 0.9626018 -0.3716426 0.1431581
[5,] -0.6364134 0.1121466 -0.0424041 -1.0665519 -0.3744889 0.1223659
[,19] [,20]
[1,] -0.7051525 0.5103369
[2,] -0.5587149 2.4404652
[3,] 1.0687420 -1.1396774
[4,] 0.3249949 1.1209457
[5,] 1.0215112 -1.1333018
>
>
> 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 : 649 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 : 562 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 1.131596 -0.5537046 0.1349303 -0.02255654 -1.853758 1.994611 0.25836
col8 col9 col10 col11 col12 col13 col14
row1 1.598842 0.4917142 -0.654455 -0.1448858 -0.237381 -0.7115611 1.01357
col15 col16 col17 col18 col19 col20
row1 0.6515436 -1.274193 -1.827325 0.5101475 -0.208096 0.4933184
> tmp[,"col10"]
col10
row1 -0.6544550
row2 1.7798104
row3 -0.4687327
row4 -0.2021126
row5 -0.6828148
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.1315964 -0.55370458 0.1349303 -0.02255654 -1.8537576 1.9946109 0.258360
row5 0.3688326 0.03383433 -0.7323936 -0.84113038 -0.2333563 0.4058051 1.376437
col8 col9 col10 col11 col12 col13 col14
row1 1.5988419 0.4917142 -0.6544550 -0.1448858 -0.237381 -0.7115611 1.013570
row5 0.4780034 -1.4602165 -0.6828148 0.7210623 -1.123958 0.9446586 1.506353
col15 col16 col17 col18 col19 col20
row1 0.6515436 -1.2741926 -1.82732461 0.5101475 -0.20809601 0.4933184
row5 0.2242816 -0.1871638 0.08888565 -0.1330610 -0.03574556 0.4366490
> tmp[,c("col6","col20")]
col6 col20
row1 1.9946109 0.4933184
row2 1.0733569 0.7923291
row3 -1.5936549 2.1200042
row4 -1.5550798 1.4374421
row5 0.4058051 0.4366490
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.9946109 0.4933184
row5 0.4058051 0.4366490
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.17605 49.44392 50.6757 49.68392 51.33344 104.3192 49.80682 49.70911
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.29227 50.71267 48.54222 48.79103 52.80934 49.08554 49.36122 49.19644
col17 col18 col19 col20
row1 47.22641 49.71431 50.06679 105.5452
> tmp[,"col10"]
col10
row1 50.71267
row2 31.11795
row3 30.14414
row4 29.85408
row5 48.68463
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.17605 49.44392 50.67570 49.68392 51.33344 104.3192 49.80682 49.70911
row5 52.68850 50.15675 49.86803 51.34728 47.90078 105.2470 50.16047 50.40985
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.29227 50.71267 48.54222 48.79103 52.80934 49.08554 49.36122 49.19644
row5 50.58918 48.68463 49.20730 49.17186 48.79378 49.54849 49.42862 51.40225
col17 col18 col19 col20
row1 47.22641 49.71431 50.06679 105.5452
row5 49.52948 51.45834 50.83830 103.4207
> tmp[,c("col6","col20")]
col6 col20
row1 104.31919 105.54521
row2 76.02427 76.74845
row3 74.68017 74.38454
row4 75.19575 76.19184
row5 105.24700 103.42074
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.3192 105.5452
row5 105.2470 103.4207
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.3192 105.5452
row5 105.2470 103.4207
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.27201000
[2,] 0.01313902
[3,] 1.77156748
[4,] -0.43715997
[5,] -0.15586994
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5959449 0.36375319
[2,] 0.5819852 -0.68007068
[3,] 0.7369181 0.07213719
[4,] -0.5367843 0.94421952
[5,] 1.0907262 0.82331474
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.5981262 0.08624581
[2,] 0.6909391 0.58602426
[3,] 0.3531835 -1.02100417
[4,] -0.5869623 -0.87367420
[5,] -0.9544288 0.80951101
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.5981262
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.5981262
[2,] 0.6909391
>
>
>
> 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 0.3449133 -0.4370775 0.6971822 -1.4848634 -1.181169 -1.3537737 -0.5239185
row1 0.4370526 1.2116711 0.6560827 0.2613064 2.335836 -0.2372879 0.6038468
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.85744495 -1.739098 0.3232582 -1.8700981 -1.052164 -0.3070757
row1 0.05949755 0.425930 -0.6334932 -0.5112948 1.370722 0.3935933
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.8152991 0.01284606 -0.2052764 -0.7266728 -0.08030652 -0.6168652
row1 -0.4393954 0.03002800 0.3493980 -1.5806449 -2.36079839 2.0892640
[,20]
row3 -0.1757645
row1 0.3539212
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.020156 0.6025785 0.9983962 0.2171144 0.562768 0.9095752 -1.087631
[,8] [,9] [,10]
row2 -1.455374 0.9709041 -0.6326356
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -2.295359 -0.5951434 0.3258719 0.1819182 -0.3154107 -0.4867074 0.06588035
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4569301 0.8271575 -0.6776861 1.230912 -0.4989101 0.9463323 2.617783
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.0712379 -0.04232675 -1.24596 -0.04411994 -0.7967016 -0.8279294
>
>
> 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: 0x5f123566ace0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM36670710467f3"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM36670138b2c32"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM366705f8c0703"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM366702c9b4dbc"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM366706bf746fc"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3667054fcba7d"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM366704275ed45"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3667036b2447d"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM366704d6e1a98"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM366705df9747f"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM366703910474a"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3667020a4ecb0"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3667078d8a08a"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM36670327d6eb"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3667073f0a91e"
>
>
> ### 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: 0x5f123569ec10>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5f123569ec10>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5f123569ec10>
> rowMedians(tmp)
[1] -0.215892387 0.314955671 -0.552076234 -0.126401341 -0.263568178
[6] 0.287470520 0.299363565 0.089924940 0.163543820 0.816589561
[11] -0.135862251 -0.198544826 0.025186676 -0.318261577 -0.067216523
[16] -0.115774320 0.660237530 0.042003935 0.039724101 0.166803601
[21] 0.627381934 0.306695889 0.010243185 0.242854310 0.128124897
[26] 0.113830097 -0.329068068 0.027191392 -0.233552907 0.076698198
[31] 0.172366376 -0.192803473 0.126365741 0.496049608 0.162147157
[36] 0.052173139 -0.226690772 -0.082367019 -0.333471991 -0.114755831
[41] 0.162973132 -0.384909260 -0.154064364 -0.306696604 -0.376285992
[46] 0.230421109 0.417242333 0.444141584 0.187190949 -0.521063629
[51] 0.096514630 0.278264028 -0.438329459 -0.117969802 -0.018672219
[56] -0.315760734 0.344042764 0.007185765 0.029239490 -0.126255456
[61] -0.427268326 0.284952816 -0.014159988 -0.348757713 0.017616022
[66] -0.210362169 0.013919963 -0.220046384 -0.012972321 0.380393753
[71] 0.243128406 0.203709461 0.139135183 -0.089069773 -0.676616045
[76] -0.267453358 0.039288557 0.082676100 0.530237051 -0.105381846
[81] 0.520203629 0.067283669 0.244831298 0.451983359 0.214773667
[86] -0.345291829 0.166481391 -0.286243063 0.028762128 -0.101112351
[91] 0.221453919 -0.174639576 -0.295564247 -0.196851101 -0.125777358
[96] 0.451130098 -0.006822843 -0.078088799 0.105386336 -0.343740653
[101] -0.736373912 -0.164517444 0.037085072 -0.077115669 0.193501856
[106] 0.502974321 0.061219347 -0.336764557 0.026766790 -0.451515889
[111] -0.775035133 0.006169752 0.084735361 0.240924420 0.501456825
[116] 0.047145967 -0.380255788 -0.228520481 0.240422476 -0.041081700
[121] 0.142546900 -0.383187435 -0.303853187 -0.100348982 -0.952892869
[126] -0.236153501 -0.240057437 0.043618698 -0.228063569 0.392495612
[131] 0.186919836 -0.450500308 -0.522992155 -0.497074171 0.037737099
[136] 0.442835623 -0.278704783 0.057755279 0.365242489 -0.155674392
[141] 0.036241552 0.291319266 0.448892565 0.259333148 0.336579737
[146] 0.031771467 -0.269133601 0.065453996 0.258338572 0.272058826
[151] -0.036447171 -0.256214514 0.575503494 -0.013128763 -0.010215126
[156] -0.166375193 -0.159358798 -0.235395762 0.533133601 0.476000059
[161] 0.178293723 0.537406279 -0.039812948 0.292824839 -0.186904199
[166] -0.186264554 -0.266802150 -0.684497555 0.668599201 -0.328799912
[171] 0.033128282 -0.372070757 -0.616667199 -0.135429747 -0.032755788
[176] 0.189750386 -0.324847819 -0.532821645 -0.096310301 0.016366451
[181] 0.314275878 -0.583580673 0.228234836 -0.380054489 -0.427659345
[186] -0.271206093 0.068882765 -0.197173104 -0.469211775 -0.163312672
[191] 0.047890914 -0.063036976 -0.210761888 0.050014040 0.211031490
[196] 1.149679384 -0.075172684 -0.047842772 -0.013617556 -0.106108633
[201] -0.448540568 0.362996167 0.304656929 -0.150797163 -0.269640964
[206] -0.029035078 0.434169107 -0.405359614 -0.522364794 -0.012220371
[211] -0.243892543 -0.074557663 -0.630470375 -0.183626720 0.079398989
[216] -0.442763676 -0.098569693 -0.422611080 0.061258100 -0.074014732
[221] 0.235679668 -0.005416462 0.080758161 -0.374659676 0.113644816
[226] 0.055359714 -0.180131691 0.201550759 -0.190170709 0.007018281
>
> proc.time()
user system elapsed
1.247 0.655 1.892
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: 0x5f4725f77b10>
> .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: 0x5f4725f77b10>
> .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: 0x5f4725f77b10>
> .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: 0x5f4725f77b10>
> 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: 0x5f4724b5ea00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4724b5ea00>
> .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: 0x5f4724b5ea00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4724b5ea00>
> .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: 0x5f4724b5ea00>
> 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: 0x5f4725184fd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4725184fd0>
> .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: 0x5f4725184fd0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5f4725184fd0>
> .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: 0x5f4725184fd0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5f4725184fd0>
> .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: 0x5f4725184fd0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5f4725184fd0>
> .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: 0x5f4725184fd0>
> 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: 0x5f47272a83b0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5f47272a83b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f47272a83b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f47272a83b0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile36804318525b1" "BufferedMatrixFile368047cc21049"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile36804318525b1" "BufferedMatrixFile368047cc21049"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f47257a2fe0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f47257a2fe0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5f47257a2fe0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5f47257a2fe0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5f47257a2fe0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5f47257a2fe0>
> .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: 0x5f47259d8060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f47259d8060>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5f47259d8060>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5f47259d8060>
> 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: 0x5f4724c29660>
> .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: 0x5f4724c29660>
> rm(P)
>
> proc.time()
user system elapsed
0.243 0.046 0.278
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
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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.
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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
0.235 0.045 0.269