Ben Bolstad
| Snapshot Date: 2025-09-19 13:45 -0400 (Fri, 19 Sep 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 2025-09-20 12:03 -0400 (Sat, 20 Sep 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" | 4814 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4603 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4547 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4553 |
| 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 253/2333 | 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: 2025-09-19 21:43:51 -0400 (Fri, 19 Sep 2025) |
| EndedAt: 2025-09-19 21:44:26 -0400 (Fri, 19 Sep 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
0.381 0.049 0.516
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 Sep 19 21:44:14 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 Sep 19 21:44:14 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: 0x5ab7b582dc80>
>
>
>
> 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 Sep 19 21:44:14 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 Sep 19 21:44:14 2025"
>
> ColMode(tmp2)
<pointer: 0x5ab7b582dc80>
>
>
>
> ### 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,] 98.7326315 1.1105519 -0.4721793 0.7611570
[2,] 0.5873730 0.9457347 -2.2454939 0.8199447
[3,] 0.3075487 -0.9163238 -2.0309370 0.6465458
[4,] -0.4364891 0.4239940 -1.0382069 0.4614980
> 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,] 98.7326315 1.1105519 0.4721793 0.7611570
[2,] 0.5873730 0.9457347 2.2454939 0.8199447
[3,] 0.3075487 0.9163238 2.0309370 0.6465458
[4,] 0.4364891 0.4239940 1.0382069 0.4614980
> 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,] 9.9364295 1.0538273 0.687153 0.8724431
[2,] 0.7664026 0.9724889 1.498497 0.9055080
[3,] 0.5545708 0.9572480 1.425109 0.8040807
[4,] 0.6606732 0.6511482 1.018924 0.6793364
>
> 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,] 223.09693 36.64882 32.34371 34.48559
[2,] 33.25140 35.67062 42.23047 34.87502
[3,] 30.85326 35.48880 41.28203 33.68735
[4,] 32.04322 31.93548 36.22745 32.25486
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5ab7b7a063a0>
> exp(tmp5)
<pointer: 0x5ab7b7a063a0>
> log(tmp5,2)
<pointer: 0x5ab7b7a063a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 464.347
> Min(tmp5)
[1] 54.05447
> mean(tmp5)
[1] 72.79453
> Sum(tmp5)
[1] 14558.91
> Var(tmp5)
[1] 841.0103
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.36539 70.13398 71.08437 71.07895 71.39432 70.39145 68.43489 70.11810
[9] 72.30568 71.63817
> rowSums(tmp5)
[1] 1827.308 1402.680 1421.687 1421.579 1427.886 1407.829 1368.698 1402.362
[9] 1446.114 1432.763
> rowVars(tmp5)
[1] 7768.82680 82.61319 104.81410 58.90668 68.07827 72.58365
[7] 57.93677 59.49015 75.91115 45.31091
> rowSd(tmp5)
[1] 88.140948 9.089180 10.237876 7.675069 8.250955 8.519604 7.611621
[8] 7.712986 8.712701 6.731338
> rowMax(tmp5)
[1] 464.34702 87.89718 88.75825 83.67524 90.87141 86.93286 81.30415
[8] 84.68732 86.69583 88.69827
> rowMin(tmp5)
[1] 54.79606 54.05447 55.89786 56.30328 58.12405 54.47849 55.96996 55.91503
[9] 60.49822 61.94852
>
> colMeans(tmp5)
[1] 110.24236 70.93357 72.36805 69.76689 67.87902 71.43429 72.13215
[8] 68.97265 69.49851 74.58319 69.92836 67.54115 71.08247 73.68958
[15] 71.97338 68.94915 68.26119 70.66470 73.48261 72.50733
> colSums(tmp5)
[1] 1102.4236 709.3357 723.6805 697.6689 678.7902 714.3429 721.3215
[8] 689.7265 694.9851 745.8319 699.2836 675.4115 710.8247 736.8958
[15] 719.7338 689.4915 682.6119 706.6470 734.8261 725.0733
> colVars(tmp5)
[1] 15507.40990 37.89299 87.83929 64.89381 56.38343 79.44920
[7] 65.70311 111.39910 91.04898 63.53503 84.36196 58.88267
[13] 125.53834 65.22367 117.24802 96.26133 35.56202 51.41245
[19] 46.69111 25.68837
> colSd(tmp5)
[1] 124.528751 6.155728 9.372261 8.055669 7.508890 8.913428
[7] 8.105745 10.554577 9.541959 7.970886 9.184877 7.673505
[13] 11.204389 8.076117 10.828112 9.811286 5.963390 7.170248
[19] 6.833089 5.068370
> colMax(tmp5)
[1] 464.34702 79.37061 87.89718 83.56636 78.70786 82.21385 86.93286
[8] 88.69827 84.68732 86.15303 88.75825 77.16229 90.87141 83.94293
[15] 86.69583 87.50287 78.96075 84.01942 81.39327 78.83089
> colMin(tmp5)
[1] 64.21701 60.26852 59.17136 55.91503 58.03564 54.05447 62.70877 56.02754
[9] 56.20140 57.93377 60.67902 54.47849 54.79606 57.18692 55.89786 55.96996
[17] 60.60588 60.12819 58.96501 64.58590
>
>
> ### 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] 91.36539 70.13398 71.08437 NA 71.39432 70.39145 68.43489 70.11810
[9] 72.30568 71.63817
> rowSums(tmp5)
[1] 1827.308 1402.680 1421.687 NA 1427.886 1407.829 1368.698 1402.362
[9] 1446.114 1432.763
> rowVars(tmp5)
[1] 7768.82680 82.61319 104.81410 61.08601 68.07827 72.58365
[7] 57.93677 59.49015 75.91115 45.31091
> rowSd(tmp5)
[1] 88.140948 9.089180 10.237876 7.815754 8.250955 8.519604 7.611621
[8] 7.712986 8.712701 6.731338
> rowMax(tmp5)
[1] 464.34702 87.89718 88.75825 NA 90.87141 86.93286 81.30415
[8] 84.68732 86.69583 88.69827
> rowMin(tmp5)
[1] 54.79606 54.05447 55.89786 NA 58.12405 54.47849 55.96996 55.91503
[9] 60.49822 61.94852
>
> colMeans(tmp5)
[1] 110.24236 70.93357 NA 69.76689 67.87902 71.43429 72.13215
[8] 68.97265 69.49851 74.58319 69.92836 67.54115 71.08247 73.68958
[15] 71.97338 68.94915 68.26119 70.66470 73.48261 72.50733
> colSums(tmp5)
[1] 1102.4236 709.3357 NA 697.6689 678.7902 714.3429 721.3215
[8] 689.7265 694.9851 745.8319 699.2836 675.4115 710.8247 736.8958
[15] 719.7338 689.4915 682.6119 706.6470 734.8261 725.0733
> colVars(tmp5)
[1] 15507.40990 37.89299 NA 64.89381 56.38343 79.44920
[7] 65.70311 111.39910 91.04898 63.53503 84.36196 58.88267
[13] 125.53834 65.22367 117.24802 96.26133 35.56202 51.41245
[19] 46.69111 25.68837
> colSd(tmp5)
[1] 124.528751 6.155728 NA 8.055669 7.508890 8.913428
[7] 8.105745 10.554577 9.541959 7.970886 9.184877 7.673505
[13] 11.204389 8.076117 10.828112 9.811286 5.963390 7.170248
[19] 6.833089 5.068370
> colMax(tmp5)
[1] 464.34702 79.37061 NA 83.56636 78.70786 82.21385 86.93286
[8] 88.69827 84.68732 86.15303 88.75825 77.16229 90.87141 83.94293
[15] 86.69583 87.50287 78.96075 84.01942 81.39327 78.83089
> colMin(tmp5)
[1] 64.21701 60.26852 NA 55.91503 58.03564 54.05447 62.70877 56.02754
[9] 56.20140 57.93377 60.67902 54.47849 54.79606 57.18692 55.89786 55.96996
[17] 60.60588 60.12819 58.96501 64.58590
>
> Max(tmp5,na.rm=TRUE)
[1] 464.347
> Min(tmp5,na.rm=TRUE)
[1] 54.05447
> mean(tmp5,na.rm=TRUE)
[1] 72.78142
> Sum(tmp5,na.rm=TRUE)
[1] 14483.5
> Var(tmp5,na.rm=TRUE)
[1] 845.2233
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.36539 70.13398 71.08437 70.85138 71.39432 70.39145 68.43489 70.11810
[9] 72.30568 71.63817
> rowSums(tmp5,na.rm=TRUE)
[1] 1827.308 1402.680 1421.687 1346.176 1427.886 1407.829 1368.698 1402.362
[9] 1446.114 1432.763
> rowVars(tmp5,na.rm=TRUE)
[1] 7768.82680 82.61319 104.81410 61.08601 68.07827 72.58365
[7] 57.93677 59.49015 75.91115 45.31091
> rowSd(tmp5,na.rm=TRUE)
[1] 88.140948 9.089180 10.237876 7.815754 8.250955 8.519604 7.611621
[8] 7.712986 8.712701 6.731338
> rowMax(tmp5,na.rm=TRUE)
[1] 464.34702 87.89718 88.75825 83.67524 90.87141 86.93286 81.30415
[8] 84.68732 86.69583 88.69827
> rowMin(tmp5,na.rm=TRUE)
[1] 54.79606 54.05447 55.89786 56.30328 58.12405 54.47849 55.96996 55.91503
[9] 60.49822 61.94852
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.24236 70.93357 72.03087 69.76689 67.87902 71.43429 72.13215
[8] 68.97265 69.49851 74.58319 69.92836 67.54115 71.08247 73.68958
[15] 71.97338 68.94915 68.26119 70.66470 73.48261 72.50733
> colSums(tmp5,na.rm=TRUE)
[1] 1102.4236 709.3357 648.2778 697.6689 678.7902 714.3429 721.3215
[8] 689.7265 694.9851 745.8319 699.2836 675.4115 710.8247 736.8958
[15] 719.7338 689.4915 682.6119 706.6470 734.8261 725.0733
> colVars(tmp5,na.rm=TRUE)
[1] 15507.40990 37.89299 97.54016 64.89381 56.38343 79.44920
[7] 65.70311 111.39910 91.04898 63.53503 84.36196 58.88267
[13] 125.53834 65.22367 117.24802 96.26133 35.56202 51.41245
[19] 46.69111 25.68837
> colSd(tmp5,na.rm=TRUE)
[1] 124.528751 6.155728 9.876242 8.055669 7.508890 8.913428
[7] 8.105745 10.554577 9.541959 7.970886 9.184877 7.673505
[13] 11.204389 8.076117 10.828112 9.811286 5.963390 7.170248
[19] 6.833089 5.068370
> colMax(tmp5,na.rm=TRUE)
[1] 464.34702 79.37061 87.89718 83.56636 78.70786 82.21385 86.93286
[8] 88.69827 84.68732 86.15303 88.75825 77.16229 90.87141 83.94293
[15] 86.69583 87.50287 78.96075 84.01942 81.39327 78.83089
> colMin(tmp5,na.rm=TRUE)
[1] 64.21701 60.26852 59.17136 55.91503 58.03564 54.05447 62.70877 56.02754
[9] 56.20140 57.93377 60.67902 54.47849 54.79606 57.18692 55.89786 55.96996
[17] 60.60588 60.12819 58.96501 64.58590
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.36539 70.13398 71.08437 NaN 71.39432 70.39145 68.43489 70.11810
[9] 72.30568 71.63817
> rowSums(tmp5,na.rm=TRUE)
[1] 1827.308 1402.680 1421.687 0.000 1427.886 1407.829 1368.698 1402.362
[9] 1446.114 1432.763
> rowVars(tmp5,na.rm=TRUE)
[1] 7768.82680 82.61319 104.81410 NA 68.07827 72.58365
[7] 57.93677 59.49015 75.91115 45.31091
> rowSd(tmp5,na.rm=TRUE)
[1] 88.140948 9.089180 10.237876 NA 8.250955 8.519604 7.611621
[8] 7.712986 8.712701 6.731338
> rowMax(tmp5,na.rm=TRUE)
[1] 464.34702 87.89718 88.75825 NA 90.87141 86.93286 81.30415
[8] 84.68732 86.69583 88.69827
> rowMin(tmp5,na.rm=TRUE)
[1] 54.79606 54.05447 55.89786 NA 58.12405 54.47849 55.96996 55.91503
[9] 60.49822 61.94852
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.08110 71.42957 NaN 70.05940 67.47244 71.32052 71.25884
[8] 67.54611 69.70410 74.43230 68.57029 68.02370 71.64869 72.58006
[15] 72.11915 70.35425 67.97674 71.83542 72.87194 73.38749
> colSums(tmp5,na.rm=TRUE)
[1] 1035.7299 642.8662 0.0000 630.5346 607.2520 641.8846 641.3296
[8] 607.9150 627.3369 669.8907 617.1326 612.2133 644.8382 653.2206
[15] 649.0724 633.1882 611.7907 646.5188 655.8475 660.4874
> colVars(tmp5,na.rm=TRUE)
[1] 17182.43611 39.86186 NA 72.04294 61.57170 89.23473
[7] 65.33596 102.43007 101.95460 71.22077 74.15828 63.62333
[13] 137.62377 59.52755 131.66496 86.08315 39.09702 42.41983
[19] 48.33223 20.18427
> colSd(tmp5,na.rm=TRUE)
[1] 131.081792 6.313625 NA 8.487811 7.846763 9.446414
[7] 8.083066 10.120774 10.097257 8.439240 8.611520 7.976424
[13] 11.731316 7.715410 11.474535 9.278101 6.252761 6.513051
[19] 6.952139 4.492691
> colMax(tmp5,na.rm=TRUE)
[1] 464.34702 79.37061 -Inf 83.56636 78.70786 82.21385 86.93286
[8] 88.69827 84.68732 86.15303 88.75825 77.16229 90.87141 83.94293
[15] 86.69583 87.50287 78.96075 84.01942 81.39327 78.83089
> colMin(tmp5,na.rm=TRUE)
[1] 64.21701 60.26852 Inf 55.91503 58.03564 54.05447 62.70877 56.02754
[9] 56.20140 57.93377 60.67902 54.47849 54.79606 57.18692 55.89786 55.96996
[17] 60.60588 62.20560 58.96501 66.64893
>
>
>
>
> 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] 222.4127 166.2816 238.2791 257.3970 203.0452 244.5632 256.9660 280.7123
[9] 248.9325 247.5318
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 222.4127 166.2816 238.2791 257.3970 203.0452 244.5632 256.9660 280.7123
[9] 248.9325 247.5318
>
>
>
> 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 0.000000e+00 -4.263256e-14 1.421085e-13 1.136868e-13
[6] -1.421085e-13 5.684342e-14 -2.557954e-13 0.000000e+00 0.000000e+00
[11] 1.136868e-13 0.000000e+00 2.842171e-14 -5.684342e-14 2.842171e-14
[16] -5.684342e-14 8.526513e-14 3.410605e-13 2.842171e-14 -1.421085e-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)
+ }
6 7
7 10
9 8
7 17
3 9
10 11
9 16
4 20
1 18
9 19
4 10
1 18
9 10
5 11
6 2
3 16
3 4
8 10
10 10
9 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] 2.024729
> Min(tmp)
[1] -2.602445
> mean(tmp)
[1] -0.1051737
> Sum(tmp)
[1] -10.51737
> Var(tmp)
[1] 0.961802
>
> rowMeans(tmp)
[1] -0.1051737
> rowSums(tmp)
[1] -10.51737
> rowVars(tmp)
[1] 0.961802
> rowSd(tmp)
[1] 0.980715
> rowMax(tmp)
[1] 2.024729
> rowMin(tmp)
[1] -2.602445
>
> colMeans(tmp)
[1] -1.40633775 -1.79618079 -1.47718494 0.45192165 -1.66541611 -0.13885303
[7] 0.27557157 0.80426732 0.45991560 1.19065629 0.21806316 -0.91848619
[13] -0.59154579 0.46202926 -0.01756290 -0.31442762 -1.40495020 -2.60244505
[19] -0.70305064 0.41881810 -0.78791410 1.13622343 -0.29247071 -0.23194318
[25] 1.36142087 -0.02687450 -1.06404108 0.64888684 -0.80305052 -1.08885004
[31] -0.41590275 1.07182823 -0.36006377 -0.30757730 -0.71430010 0.09584704
[37] -0.07078363 0.10933690 0.75503061 1.32537420 0.78072696 -1.33306592
[43] -0.33909259 -0.66114830 -0.94691268 -1.00277085 0.75134776 -0.73540594
[49] 0.74770775 0.31254873 0.59304994 -1.68272326 0.46918808 -0.15343097
[55] -1.73769497 0.14210630 1.65433617 -1.69628074 0.48478740 -0.90510333
[61] 1.03753969 2.02472861 0.97811835 -0.76426644 -1.16606155 0.23815541
[67] -0.52690539 -0.09620834 0.30690339 -1.28307766 0.44218823 0.14480759
[73] -0.69135718 0.80597187 -0.74988102 -2.23232589 -0.62858970 0.18746369
[79] 0.09311717 -0.21636931 -0.35269183 0.21341975 1.90682229 0.03747795
[85] -0.47651755 1.10613276 -0.80901798 -0.30261732 1.50497586 1.69691912
[91] 1.12169485 1.61810767 0.04760222 1.49581101 -0.66265204 -0.71043579
[97] 0.97929286 -1.24580781 -1.69672749 -0.22025638
> colSums(tmp)
[1] -1.40633775 -1.79618079 -1.47718494 0.45192165 -1.66541611 -0.13885303
[7] 0.27557157 0.80426732 0.45991560 1.19065629 0.21806316 -0.91848619
[13] -0.59154579 0.46202926 -0.01756290 -0.31442762 -1.40495020 -2.60244505
[19] -0.70305064 0.41881810 -0.78791410 1.13622343 -0.29247071 -0.23194318
[25] 1.36142087 -0.02687450 -1.06404108 0.64888684 -0.80305052 -1.08885004
[31] -0.41590275 1.07182823 -0.36006377 -0.30757730 -0.71430010 0.09584704
[37] -0.07078363 0.10933690 0.75503061 1.32537420 0.78072696 -1.33306592
[43] -0.33909259 -0.66114830 -0.94691268 -1.00277085 0.75134776 -0.73540594
[49] 0.74770775 0.31254873 0.59304994 -1.68272326 0.46918808 -0.15343097
[55] -1.73769497 0.14210630 1.65433617 -1.69628074 0.48478740 -0.90510333
[61] 1.03753969 2.02472861 0.97811835 -0.76426644 -1.16606155 0.23815541
[67] -0.52690539 -0.09620834 0.30690339 -1.28307766 0.44218823 0.14480759
[73] -0.69135718 0.80597187 -0.74988102 -2.23232589 -0.62858970 0.18746369
[79] 0.09311717 -0.21636931 -0.35269183 0.21341975 1.90682229 0.03747795
[85] -0.47651755 1.10613276 -0.80901798 -0.30261732 1.50497586 1.69691912
[91] 1.12169485 1.61810767 0.04760222 1.49581101 -0.66265204 -0.71043579
[97] 0.97929286 -1.24580781 -1.69672749 -0.22025638
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.40633775 -1.79618079 -1.47718494 0.45192165 -1.66541611 -0.13885303
[7] 0.27557157 0.80426732 0.45991560 1.19065629 0.21806316 -0.91848619
[13] -0.59154579 0.46202926 -0.01756290 -0.31442762 -1.40495020 -2.60244505
[19] -0.70305064 0.41881810 -0.78791410 1.13622343 -0.29247071 -0.23194318
[25] 1.36142087 -0.02687450 -1.06404108 0.64888684 -0.80305052 -1.08885004
[31] -0.41590275 1.07182823 -0.36006377 -0.30757730 -0.71430010 0.09584704
[37] -0.07078363 0.10933690 0.75503061 1.32537420 0.78072696 -1.33306592
[43] -0.33909259 -0.66114830 -0.94691268 -1.00277085 0.75134776 -0.73540594
[49] 0.74770775 0.31254873 0.59304994 -1.68272326 0.46918808 -0.15343097
[55] -1.73769497 0.14210630 1.65433617 -1.69628074 0.48478740 -0.90510333
[61] 1.03753969 2.02472861 0.97811835 -0.76426644 -1.16606155 0.23815541
[67] -0.52690539 -0.09620834 0.30690339 -1.28307766 0.44218823 0.14480759
[73] -0.69135718 0.80597187 -0.74988102 -2.23232589 -0.62858970 0.18746369
[79] 0.09311717 -0.21636931 -0.35269183 0.21341975 1.90682229 0.03747795
[85] -0.47651755 1.10613276 -0.80901798 -0.30261732 1.50497586 1.69691912
[91] 1.12169485 1.61810767 0.04760222 1.49581101 -0.66265204 -0.71043579
[97] 0.97929286 -1.24580781 -1.69672749 -0.22025638
> colMin(tmp)
[1] -1.40633775 -1.79618079 -1.47718494 0.45192165 -1.66541611 -0.13885303
[7] 0.27557157 0.80426732 0.45991560 1.19065629 0.21806316 -0.91848619
[13] -0.59154579 0.46202926 -0.01756290 -0.31442762 -1.40495020 -2.60244505
[19] -0.70305064 0.41881810 -0.78791410 1.13622343 -0.29247071 -0.23194318
[25] 1.36142087 -0.02687450 -1.06404108 0.64888684 -0.80305052 -1.08885004
[31] -0.41590275 1.07182823 -0.36006377 -0.30757730 -0.71430010 0.09584704
[37] -0.07078363 0.10933690 0.75503061 1.32537420 0.78072696 -1.33306592
[43] -0.33909259 -0.66114830 -0.94691268 -1.00277085 0.75134776 -0.73540594
[49] 0.74770775 0.31254873 0.59304994 -1.68272326 0.46918808 -0.15343097
[55] -1.73769497 0.14210630 1.65433617 -1.69628074 0.48478740 -0.90510333
[61] 1.03753969 2.02472861 0.97811835 -0.76426644 -1.16606155 0.23815541
[67] -0.52690539 -0.09620834 0.30690339 -1.28307766 0.44218823 0.14480759
[73] -0.69135718 0.80597187 -0.74988102 -2.23232589 -0.62858970 0.18746369
[79] 0.09311717 -0.21636931 -0.35269183 0.21341975 1.90682229 0.03747795
[85] -0.47651755 1.10613276 -0.80901798 -0.30261732 1.50497586 1.69691912
[91] 1.12169485 1.61810767 0.04760222 1.49581101 -0.66265204 -0.71043579
[97] 0.97929286 -1.24580781 -1.69672749 -0.22025638
> colMedians(tmp)
[1] -1.40633775 -1.79618079 -1.47718494 0.45192165 -1.66541611 -0.13885303
[7] 0.27557157 0.80426732 0.45991560 1.19065629 0.21806316 -0.91848619
[13] -0.59154579 0.46202926 -0.01756290 -0.31442762 -1.40495020 -2.60244505
[19] -0.70305064 0.41881810 -0.78791410 1.13622343 -0.29247071 -0.23194318
[25] 1.36142087 -0.02687450 -1.06404108 0.64888684 -0.80305052 -1.08885004
[31] -0.41590275 1.07182823 -0.36006377 -0.30757730 -0.71430010 0.09584704
[37] -0.07078363 0.10933690 0.75503061 1.32537420 0.78072696 -1.33306592
[43] -0.33909259 -0.66114830 -0.94691268 -1.00277085 0.75134776 -0.73540594
[49] 0.74770775 0.31254873 0.59304994 -1.68272326 0.46918808 -0.15343097
[55] -1.73769497 0.14210630 1.65433617 -1.69628074 0.48478740 -0.90510333
[61] 1.03753969 2.02472861 0.97811835 -0.76426644 -1.16606155 0.23815541
[67] -0.52690539 -0.09620834 0.30690339 -1.28307766 0.44218823 0.14480759
[73] -0.69135718 0.80597187 -0.74988102 -2.23232589 -0.62858970 0.18746369
[79] 0.09311717 -0.21636931 -0.35269183 0.21341975 1.90682229 0.03747795
[85] -0.47651755 1.10613276 -0.80901798 -0.30261732 1.50497586 1.69691912
[91] 1.12169485 1.61810767 0.04760222 1.49581101 -0.66265204 -0.71043579
[97] 0.97929286 -1.24580781 -1.69672749 -0.22025638
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.406338 -1.796181 -1.477185 0.4519216 -1.665416 -0.138853 0.2755716
[2,] -1.406338 -1.796181 -1.477185 0.4519216 -1.665416 -0.138853 0.2755716
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.8042673 0.4599156 1.190656 0.2180632 -0.9184862 -0.5915458 0.4620293
[2,] 0.8042673 0.4599156 1.190656 0.2180632 -0.9184862 -0.5915458 0.4620293
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.0175629 -0.3144276 -1.40495 -2.602445 -0.7030506 0.4188181 -0.7879141
[2,] -0.0175629 -0.3144276 -1.40495 -2.602445 -0.7030506 0.4188181 -0.7879141
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.136223 -0.2924707 -0.2319432 1.361421 -0.0268745 -1.064041 0.6488868
[2,] 1.136223 -0.2924707 -0.2319432 1.361421 -0.0268745 -1.064041 0.6488868
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.8030505 -1.08885 -0.4159028 1.071828 -0.3600638 -0.3075773 -0.7143001
[2,] -0.8030505 -1.08885 -0.4159028 1.071828 -0.3600638 -0.3075773 -0.7143001
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.09584704 -0.07078363 0.1093369 0.7550306 1.325374 0.780727 -1.333066
[2,] 0.09584704 -0.07078363 0.1093369 0.7550306 1.325374 0.780727 -1.333066
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.3390926 -0.6611483 -0.9469127 -1.002771 0.7513478 -0.7354059 0.7477078
[2,] -0.3390926 -0.6611483 -0.9469127 -1.002771 0.7513478 -0.7354059 0.7477078
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3125487 0.5930499 -1.682723 0.4691881 -0.153431 -1.737695 0.1421063
[2,] 0.3125487 0.5930499 -1.682723 0.4691881 -0.153431 -1.737695 0.1421063
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.654336 -1.696281 0.4847874 -0.9051033 1.03754 2.024729 0.9781183
[2,] 1.654336 -1.696281 0.4847874 -0.9051033 1.03754 2.024729 0.9781183
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.7642664 -1.166062 0.2381554 -0.5269054 -0.09620834 0.3069034 -1.283078
[2,] -0.7642664 -1.166062 0.2381554 -0.5269054 -0.09620834 0.3069034 -1.283078
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.4421882 0.1448076 -0.6913572 0.8059719 -0.749881 -2.232326 -0.6285897
[2,] 0.4421882 0.1448076 -0.6913572 0.8059719 -0.749881 -2.232326 -0.6285897
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.1874637 0.09311717 -0.2163693 -0.3526918 0.2134197 1.906822 0.03747795
[2,] 0.1874637 0.09311717 -0.2163693 -0.3526918 0.2134197 1.906822 0.03747795
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.4765176 1.106133 -0.809018 -0.3026173 1.504976 1.696919 1.121695
[2,] -0.4765176 1.106133 -0.809018 -0.3026173 1.504976 1.696919 1.121695
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.618108 0.04760222 1.495811 -0.662652 -0.7104358 0.9792929 -1.245808
[2,] 1.618108 0.04760222 1.495811 -0.662652 -0.7104358 0.9792929 -1.245808
[,99] [,100]
[1,] -1.696727 -0.2202564
[2,] -1.696727 -0.2202564
>
>
> Max(tmp2)
[1] 2.472231
> Min(tmp2)
[1] -2.670875
> mean(tmp2)
[1] 0.1922155
> Sum(tmp2)
[1] 19.22155
> Var(tmp2)
[1] 1.144631
>
> rowMeans(tmp2)
[1] 0.47406072 1.28408483 1.39429751 -0.98144861 0.21816018 0.29849073
[7] 0.52234235 0.87362030 0.65775311 1.23642014 1.71235212 0.09072066
[13] 1.45429063 -0.31369735 1.18200975 0.58886745 0.28140140 1.08906274
[19] 1.57452667 -0.59998047 0.65462743 -0.80626606 0.08487879 -0.31339082
[25] 1.99699443 -1.81500829 0.53979431 0.47441007 1.29916745 1.30087656
[31] 0.54095369 -0.54019075 -0.73722672 -0.85631475 0.50010733 0.08012545
[37] -2.09700706 -1.05732053 -0.18571945 1.45756552 -0.59329238 1.99102666
[43] 0.68458684 -0.51691220 1.23698087 0.11641470 -0.92671221 0.80742888
[49] 0.10890566 2.12883832 0.73621120 1.77396423 -0.28132342 2.47223053
[55] 0.57668812 -1.15041238 -0.34554558 -0.38221576 -2.24410407 -1.73410256
[61] 1.25426796 -0.66551378 0.19476858 -1.85214934 -1.30927061 0.14065215
[67] 0.21331730 0.24565120 0.15420567 -0.61394188 0.22644856 0.52758330
[73] 0.83297433 0.48460577 1.87264273 -0.50024258 -1.56839260 0.58436755
[79] -0.49808384 -0.40418260 -2.67087465 0.23462947 -1.70495118 1.23491633
[85] 0.04531587 -0.41328510 0.83581467 0.61478686 -1.33647797 1.37885763
[91] 2.04035257 -0.76397490 -0.10173997 -0.58230138 0.54512546 0.54354007
[97] 0.61604836 -1.22338182 1.36903014 1.22336375
> rowSums(tmp2)
[1] 0.47406072 1.28408483 1.39429751 -0.98144861 0.21816018 0.29849073
[7] 0.52234235 0.87362030 0.65775311 1.23642014 1.71235212 0.09072066
[13] 1.45429063 -0.31369735 1.18200975 0.58886745 0.28140140 1.08906274
[19] 1.57452667 -0.59998047 0.65462743 -0.80626606 0.08487879 -0.31339082
[25] 1.99699443 -1.81500829 0.53979431 0.47441007 1.29916745 1.30087656
[31] 0.54095369 -0.54019075 -0.73722672 -0.85631475 0.50010733 0.08012545
[37] -2.09700706 -1.05732053 -0.18571945 1.45756552 -0.59329238 1.99102666
[43] 0.68458684 -0.51691220 1.23698087 0.11641470 -0.92671221 0.80742888
[49] 0.10890566 2.12883832 0.73621120 1.77396423 -0.28132342 2.47223053
[55] 0.57668812 -1.15041238 -0.34554558 -0.38221576 -2.24410407 -1.73410256
[61] 1.25426796 -0.66551378 0.19476858 -1.85214934 -1.30927061 0.14065215
[67] 0.21331730 0.24565120 0.15420567 -0.61394188 0.22644856 0.52758330
[73] 0.83297433 0.48460577 1.87264273 -0.50024258 -1.56839260 0.58436755
[79] -0.49808384 -0.40418260 -2.67087465 0.23462947 -1.70495118 1.23491633
[85] 0.04531587 -0.41328510 0.83581467 0.61478686 -1.33647797 1.37885763
[91] 2.04035257 -0.76397490 -0.10173997 -0.58230138 0.54512546 0.54354007
[97] 0.61604836 -1.22338182 1.36903014 1.22336375
> 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] 0.47406072 1.28408483 1.39429751 -0.98144861 0.21816018 0.29849073
[7] 0.52234235 0.87362030 0.65775311 1.23642014 1.71235212 0.09072066
[13] 1.45429063 -0.31369735 1.18200975 0.58886745 0.28140140 1.08906274
[19] 1.57452667 -0.59998047 0.65462743 -0.80626606 0.08487879 -0.31339082
[25] 1.99699443 -1.81500829 0.53979431 0.47441007 1.29916745 1.30087656
[31] 0.54095369 -0.54019075 -0.73722672 -0.85631475 0.50010733 0.08012545
[37] -2.09700706 -1.05732053 -0.18571945 1.45756552 -0.59329238 1.99102666
[43] 0.68458684 -0.51691220 1.23698087 0.11641470 -0.92671221 0.80742888
[49] 0.10890566 2.12883832 0.73621120 1.77396423 -0.28132342 2.47223053
[55] 0.57668812 -1.15041238 -0.34554558 -0.38221576 -2.24410407 -1.73410256
[61] 1.25426796 -0.66551378 0.19476858 -1.85214934 -1.30927061 0.14065215
[67] 0.21331730 0.24565120 0.15420567 -0.61394188 0.22644856 0.52758330
[73] 0.83297433 0.48460577 1.87264273 -0.50024258 -1.56839260 0.58436755
[79] -0.49808384 -0.40418260 -2.67087465 0.23462947 -1.70495118 1.23491633
[85] 0.04531587 -0.41328510 0.83581467 0.61478686 -1.33647797 1.37885763
[91] 2.04035257 -0.76397490 -0.10173997 -0.58230138 0.54512546 0.54354007
[97] 0.61604836 -1.22338182 1.36903014 1.22336375
> rowMin(tmp2)
[1] 0.47406072 1.28408483 1.39429751 -0.98144861 0.21816018 0.29849073
[7] 0.52234235 0.87362030 0.65775311 1.23642014 1.71235212 0.09072066
[13] 1.45429063 -0.31369735 1.18200975 0.58886745 0.28140140 1.08906274
[19] 1.57452667 -0.59998047 0.65462743 -0.80626606 0.08487879 -0.31339082
[25] 1.99699443 -1.81500829 0.53979431 0.47441007 1.29916745 1.30087656
[31] 0.54095369 -0.54019075 -0.73722672 -0.85631475 0.50010733 0.08012545
[37] -2.09700706 -1.05732053 -0.18571945 1.45756552 -0.59329238 1.99102666
[43] 0.68458684 -0.51691220 1.23698087 0.11641470 -0.92671221 0.80742888
[49] 0.10890566 2.12883832 0.73621120 1.77396423 -0.28132342 2.47223053
[55] 0.57668812 -1.15041238 -0.34554558 -0.38221576 -2.24410407 -1.73410256
[61] 1.25426796 -0.66551378 0.19476858 -1.85214934 -1.30927061 0.14065215
[67] 0.21331730 0.24565120 0.15420567 -0.61394188 0.22644856 0.52758330
[73] 0.83297433 0.48460577 1.87264273 -0.50024258 -1.56839260 0.58436755
[79] -0.49808384 -0.40418260 -2.67087465 0.23462947 -1.70495118 1.23491633
[85] 0.04531587 -0.41328510 0.83581467 0.61478686 -1.33647797 1.37885763
[91] 2.04035257 -0.76397490 -0.10173997 -0.58230138 0.54512546 0.54354007
[97] 0.61604836 -1.22338182 1.36903014 1.22336375
>
> colMeans(tmp2)
[1] 0.1922155
> colSums(tmp2)
[1] 19.22155
> colVars(tmp2)
[1] 1.144631
> colSd(tmp2)
[1] 1.069874
> colMax(tmp2)
[1] 2.472231
> colMin(tmp2)
[1] -2.670875
> colMedians(tmp2)
[1] 0.2401403
> colRanges(tmp2)
[,1]
[1,] -2.670875
[2,] 2.472231
>
> 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] -6.75192370 0.03026594 -7.20401416 6.37108064 1.08642364 -4.72514380
[7] 1.33464348 0.68281391 -6.45846068 -0.01368186
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.4923919
[2,] -1.1858608
[3,] -0.6181443
[4,] 0.0317341
[5,] 0.7083005
>
> rowApply(tmp,sum)
[1] -3.2354596 -3.2655118 -0.5223882 4.2708233 4.0917096 -1.7777760
[7] -8.5760390 -2.7264982 -4.9954066 1.0885498
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 1 3 1 7 4 10 1 6 5
[2,] 4 6 9 5 2 3 9 5 9 9
[3,] 7 3 1 4 5 7 1 4 2 3
[4,] 10 4 8 10 10 10 6 8 10 7
[5,] 6 10 5 2 8 9 5 2 4 10
[6,] 1 2 2 7 4 6 8 6 3 2
[7,] 8 8 6 8 6 2 4 10 7 6
[8,] 9 9 10 3 3 8 3 9 8 4
[9,] 2 5 7 6 1 1 2 7 5 1
[10,] 5 7 4 9 9 5 7 3 1 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.09197394 -0.05475772 -2.47649902 1.59841666 4.60306911 -2.67219245
[7] 2.61680569 1.59540403 1.48708372 -1.69619632 -1.73209629 0.03001262
[13] 1.97838131 0.79919604 -0.65119728 -2.44100839 -2.72375653 0.31322155
[19] 2.69621590 0.64832648
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.09800547
[2,] 0.41324677
[3,] 0.49079579
[4,] 0.58830327
[5,] 0.69763358
>
> rowApply(tmp,sum)
[1] 0.3318162 7.4695267 3.0996745 -1.9704587 -2.9201556
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 12 11 14 10
[2,] 14 5 18 6 7
[3,] 10 11 15 1 4
[4,] 13 8 4 20 9
[5,] 20 20 3 16 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.69763358 0.5746540 -0.001445276 0.33508876 1.5851973 -1.7049184
[2,] 0.41324677 -0.1853369 0.352686434 0.03806635 3.5196823 -0.3902767
[3,] 0.49079579 0.8366290 0.796686871 -0.59547204 -1.4678955 -0.1183710
[4,] 0.58830327 -0.6369136 -2.375254904 2.05360220 0.7573989 -1.3211785
[5,] -0.09800547 -0.6437902 -1.249172140 -0.23286861 0.2086861 0.8625521
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.9366709 0.32642870 -0.2091510 -0.8053469 0.6187535 -0.3987931
[2,] 0.7684387 0.63464188 0.5196688 0.6085126 -0.9740676 -0.4103718
[3,] 0.7784222 -0.10157409 -0.4651086 0.8059543 -1.7154486 -0.0332970
[4,] -0.6184246 0.68350649 -0.3492041 -1.1609252 0.0854019 0.3366356
[5,] 0.7516985 0.05240104 1.9908786 -1.1443911 0.2532644 0.5358389
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.2062340 0.9335060 -1.2223262 -0.2577248 -1.23406133 -1.2915978
[2,] 0.8309751 0.8827462 -0.1398323 0.2044594 -0.33742725 -0.1838894
[3,] 2.2422880 0.8269863 0.7017116 -2.1073413 -0.08232518 1.2249720
[4,] 1.1843985 -1.4327243 1.1974601 -1.9182597 0.36136409 -0.3953324
[5,] -2.0730463 -0.4113182 -1.1882105 1.6378581 -1.43130686 0.9590691
[,19] [,20]
[1,] 1.3916971 0.26378489
[2,] 1.2743389 0.04326524
[3,] 0.6807716 0.40129016
[4,] 1.1789960 -0.18930823
[5,] -1.8295876 0.12929443
>
>
> 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 : 647 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 -0.7715115 1.669287 0.5651151 -0.798174 0.0349803 -1.135397 1.722266
col8 col9 col10 col11 col12 col13 col14
row1 1.121376 -0.1350712 1.388 0.5321473 0.9732843 0.1658046 -0.2265853
col15 col16 col17 col18 col19 col20
row1 -1.445063 1.350553 -1.341845 -0.9520076 -1.315603 -1.421306
> tmp[,"col10"]
col10
row1 1.388000
row2 -1.490695
row3 -1.089344
row4 2.030809
row5 1.511265
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7715115 1.6692866 0.5651151 -0.798174 0.0349803 -1.135397 1.722266
row5 0.6261261 -0.6211527 0.5791498 1.113978 -1.4964956 2.319727 1.548727
col8 col9 col10 col11 col12 col13 col14
row1 1.1213761 -0.1350712 1.388000 0.5321473 0.9732843 0.1658046 -0.2265853
row5 0.9873325 0.4041151 1.511265 0.6647937 -1.9314583 -1.5737382 1.1215627
col15 col16 col17 col18 col19 col20
row1 -1.445063 1.350553 -1.3418452 -0.9520076 -1.3156034 -1.421306
row5 1.114029 0.478467 0.2320235 -0.6135983 0.5145666 -1.860240
> tmp[,c("col6","col20")]
col6 col20
row1 -1.1353973 -1.42130583
row2 -0.6885455 0.06698267
row3 0.9745218 1.60872700
row4 0.7898053 -1.24006904
row5 2.3197273 -1.86024048
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.135397 -1.421306
row5 2.319727 -1.860240
>
>
>
>
> 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 49.0519 48.74949 50.17423 50.65055 51.09061 107.7114 49.29619 50.30143
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.10457 49.05571 49.48041 50.3047 50.48796 48.65101 50.68521 49.72498
col17 col18 col19 col20
row1 49.83942 48.73128 49.88405 105.409
> tmp[,"col10"]
col10
row1 49.05571
row2 29.97428
row3 29.40192
row4 29.53653
row5 51.82472
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.05190 48.74949 50.17423 50.65055 51.09061 107.7114 49.29619 50.30143
row5 49.05858 50.04769 49.16953 51.29648 50.53660 103.5036 51.07088 50.05064
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.10457 49.05571 49.48041 50.30470 50.48796 48.65101 50.68521 49.72498
row5 51.41326 51.82472 48.98456 51.36834 49.52620 50.49160 49.38788 50.57754
col17 col18 col19 col20
row1 49.83942 48.73128 49.88405 105.4090
row5 50.70464 50.58682 50.32698 104.1375
> tmp[,c("col6","col20")]
col6 col20
row1 107.71143 105.40901
row2 74.83986 74.84341
row3 74.64801 74.41162
row4 74.47796 73.68611
row5 103.50362 104.13746
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 107.7114 105.4090
row5 103.5036 104.1375
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 107.7114 105.4090
row5 103.5036 104.1375
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.67593680
[2,] -0.93773635
[3,] -0.63037567
[4,] -0.02096003
[5,] 0.84843758
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.5991699 -0.8230713
[2,] 0.5158882 -0.2181775
[3,] -0.6158974 0.9556658
[4,] 1.2138040 -0.4194313
[5,] 0.5250039 0.9797896
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.1691564 0.6176878
[2,] 0.5188631 0.3701412
[3,] -0.8769830 0.2420057
[4,] -0.2381864 -0.2271686
[5,] 0.1698660 -1.4890934
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.1691564
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.1691564
[2,] 0.5188631
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.06117638 0.6676516 -0.7546703 0.7056849 0.6673846 0.1260304
row1 -2.29910656 -0.2564338 0.3008958 -0.4415884 -0.3150843 -0.1704006
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.17403818 0.3374420 -0.02765668 -1.1358506 0.3639555 0.02331039
row1 0.04196064 -0.4042785 0.77325993 -0.7805882 -0.7340029 -0.17908542
[,13] [,14] [,15] [,16] [,17] [,18]
row3 2.29092828 1.957022 -0.9375861 0.04952109 0.1181468 -0.00124192
row1 0.09295515 1.559257 0.1964337 -0.27922267 0.5741046 2.24866450
[,19] [,20]
row3 -0.7601432 -0.7688055
row1 1.8611541 -0.2314087
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.7433022 -1.217416 1.082874 0.7569066 0.9263237 -0.2160425 2.350721
[,8] [,9] [,10]
row2 -0.1962454 0.1550087 1.579814
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.638058 -0.6150722 2.184573 -0.9231792 1.023516 0.9259346 0.2150156
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5130103 -0.5917486 -1.60036 0.3461744 0.2556701 1.615914 1.95817
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.221799 0.9031706 -0.6308619 0.09333727 -2.060194 0.9363055
>
>
> 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: 0x5ab7b5d0ff60>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5651151678e"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5653f838888"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e565303edcee"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5654d83c7b0"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e56575804867"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5652c18577"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e56514bf5a6f"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5652cfa2562"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5655a5d4be7"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e56553dcab49"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5657d2e26f9"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e5652134a20"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e56544699959"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e56556184b53"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM6e56526261dd2"
>
>
> ### 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: 0x5ab7b534d670>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5ab7b534d670>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5ab7b534d670>
> rowMedians(tmp)
[1] 0.152470538 0.300980999 -0.808773781 0.506597971 0.044445308
[6] -0.152953532 -0.142753140 0.143128649 0.100992147 -0.219065546
[11] -0.351750049 0.230661966 0.468683136 -0.177970724 -0.184951378
[16] -0.164476901 0.190720301 0.483313110 0.023402923 -0.188937577
[21] -0.379655183 0.234743466 -0.645271182 -0.122282780 -0.339590327
[26] -0.022699426 0.054312999 0.180324155 0.204980314 0.208884830
[31] -0.431401264 0.547875988 0.647937593 0.175114226 0.223844410
[36] -0.397187897 0.065501361 -0.842547975 -0.108061496 0.107731936
[41] -0.627003847 -0.427892556 0.911858987 -0.558011946 0.505618219
[46] 0.302296937 0.276862184 -0.690386337 0.156295843 0.297889086
[51] -0.128261978 -0.279719045 -0.332942358 -0.801721622 -0.141101177
[56] -0.197372359 0.626015417 0.320326048 0.271048200 0.253569359
[61] -0.556674220 0.135403710 -0.038854820 0.107423661 -0.216792539
[66] -0.050948261 0.048566073 0.069494405 -0.693432320 -0.356178207
[71] 0.371134774 0.062410955 0.501604196 0.354068436 -0.151755688
[76] -0.125143177 0.585716665 -0.406448071 0.226889414 -0.112761337
[81] -0.179277145 -0.271705694 0.304516327 0.107221027 -0.028490736
[86] 0.362266256 -0.173872553 0.167436218 0.019672714 -0.245326047
[91] -0.085979596 -0.220119077 -0.395134369 0.223899430 -0.003550031
[96] -0.323679106 0.108871691 -0.683000347 0.216808369 -0.145485386
[101] -0.522059380 -0.693023073 0.254393365 0.335640641 -0.353721524
[106] 0.194577799 -0.477446125 0.349783811 0.094021252 -0.193443187
[111] 0.012974975 -0.025894666 -0.188820705 0.224183205 0.454471180
[116] -0.275462915 -0.344779513 -0.270523512 -0.034510223 -0.169467353
[121] 0.263914094 -0.006617753 -0.259763263 -0.253258702 -0.068030660
[126] 0.304899031 0.136272064 0.447523043 -0.025211204 -0.300804445
[131] -0.008360286 0.563868291 0.016148799 -0.410819274 0.377763438
[136] -0.112308430 0.163487180 0.708354521 0.092797800 0.438021302
[141] -0.109835000 0.870750839 -0.046610210 0.082294169 -0.318508180
[146] 0.281918492 0.030822381 0.170885062 0.569905206 0.026630566
[151] 0.087907264 -0.033506627 0.812809531 0.247820334 -0.035377242
[156] 0.489907662 0.080208590 -0.341620538 -0.071587285 -0.306718110
[161] -0.486057950 -0.233458346 -0.092880094 -0.396456663 -0.020128276
[166] 0.504581912 0.119776375 -0.045310423 -0.467227064 0.407873186
[171] -0.224316939 0.393913186 -0.145378203 -0.587364552 0.314051094
[176] -0.098438864 0.214396173 0.094188345 -0.270095121 -0.056436883
[181] 0.262850151 -0.114724164 0.015086523 0.131637364 -0.123768704
[186] 0.250512940 -0.281267633 -0.051062911 0.199138392 -0.400996605
[191] -0.386493291 0.286476617 -0.241181428 0.067843002 -0.167469985
[196] -0.098824570 -0.503791759 -0.295958157 0.306746277 -0.999500839
[201] -0.613670174 0.355668387 -0.239561478 -0.214247429 -0.245087005
[206] 0.036438065 -0.272654760 0.074092965 0.327093747 -0.230232788
[211] -0.108251458 -0.337512550 0.294863961 0.165888449 -0.188076803
[216] 0.413961302 -0.504609153 0.076534434 -0.469164101 -0.438295954
[221] -0.097975798 0.334767536 -0.398487927 0.236571679 -0.018033059
[226] 0.183518228 0.301015195 -0.064694705 0.037071351 0.323454206
>
> proc.time()
user system elapsed
1.820 0.882 2.737
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: 0x580ac8801c80>
> .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: 0x580ac8801c80>
> .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: 0x580ac8801c80>
> .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: 0x580ac8801c80>
> 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: 0x580ac8498a00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x580ac8498a00>
> .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: 0x580ac8498a00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x580ac8498a00>
> .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: 0x580ac8498a00>
> 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: 0x580ac8563660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x580ac8563660>
> .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: 0x580ac8563660>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x580ac8563660>
> .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: 0x580ac8563660>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x580ac8563660>
> .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: 0x580ac8563660>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x580ac8563660>
> .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: 0x580ac8563660>
> 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: 0x580ac8a853d0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x580ac8a853d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x580ac8a853d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x580ac8a853d0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6e7c0333958ef" "BufferedMatrixFile6e7c05d580e8e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6e7c0333958ef" "BufferedMatrixFile6e7c05d580e8e"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x580acabe2460>
> .Call("R_bm_AddColumn",P)
<pointer: 0x580acabe2460>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x580acabe2460>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x580acabe2460>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x580acabe2460>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x580acabe2460>
> .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: 0x580aca219e60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x580aca219e60>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x580aca219e60>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x580aca219e60>
> 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: 0x580ac908c710>
> .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: 0x580ac908c710>
> rm(P)
>
> proc.time()
user system elapsed
0.313 0.048 0.352
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
0.411 0.051 0.463