Ben Bolstad
| Snapshot Date: 2025-09-02 13:45 -0400 (Tue, 02 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 2025-09-03 12:03 -0400 (Wed, 03 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4826 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4616 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4563 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4541 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2321 | 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: 2025-09-02 21:40:28 -0400 (Tue, 02 Sep 2025) |
| EndedAt: 2025-09-02 21:41:02 -0400 (Tue, 02 Sep 2025) |
| EllapsedTime: 34.1 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 (2025-06-13)
* 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 (2025-06-13) -- "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
0.401 0.045 0.515
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 (2025-06-13) -- "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 478417 25.6 1047105 56 639600 34.2
Vcells 885231 6.8 8388608 64 2081598 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] "Tue Sep 2 21:40:49 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Sep 2 21:40:49 2025"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x5696a8bb2b80>
>
>
>
> 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] "Tue Sep 2 21:40:49 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] "Tue Sep 2 21:40:49 2025"
>
> ColMode(tmp2)
<pointer: 0x5696a8bb2b80>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.5413322 1.11703283 -0.4049080 -1.7977212
[2,] -0.7572626 0.42361977 -0.3905176 0.5384011
[3,] -0.2897292 0.50008914 -0.8384495 0.8364499
[4,] -0.2141103 0.01844951 0.9456234 -0.2552500
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.5413322 1.11703283 0.4049080 1.7977212
[2,] 0.7572626 0.42361977 0.3905176 0.5384011
[3,] 0.2897292 0.50008914 0.8384495 0.8364499
[4,] 0.2141103 0.01844951 0.9456234 0.2552500
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0270301 1.0568977 0.6363238 1.3407913
[2,] 0.8702084 0.6508608 0.6249140 0.7337582
[3,] 0.5382650 0.7071698 0.9156689 0.9145764
[4,] 0.4627206 0.1358290 0.9724317 0.5052228
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.81163 36.68601 31.76815 40.20563
[2,] 34.45935 31.93223 31.63966 32.87598
[3,] 30.67238 32.57179 34.99514 34.98221
[4,] 29.84132 26.37674 35.66994 30.30748
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5696a760b4b0>
> exp(tmp5)
<pointer: 0x5696a760b4b0>
> log(tmp5,2)
<pointer: 0x5696a760b4b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.9973
> Min(tmp5)
[1] 53.99029
> mean(tmp5)
[1] 73.0879
> Sum(tmp5)
[1] 14617.58
> Var(tmp5)
[1] 867.183
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 95.49674 68.89147 72.37184 71.38449 71.67770 68.91038 69.99783 68.59636
[9] 71.64596 71.90622
> rowSums(tmp5)
[1] 1909.935 1377.829 1447.437 1427.690 1433.554 1378.208 1399.957 1371.927
[9] 1432.919 1438.124
> rowVars(tmp5)
[1] 7811.78698 90.01149 54.32853 106.63219 67.77648 50.35252
[7] 60.80598 76.65785 76.99534 81.12832
> rowSd(tmp5)
[1] 88.384314 9.487439 7.370789 10.326286 8.232647 7.095951 7.797819
[8] 8.755447 8.774699 9.007126
> rowMax(tmp5)
[1] 469.99733 89.41157 85.73426 89.29824 84.94562 90.45498 83.87965
[8] 86.57050 84.75708 84.37160
> rowMin(tmp5)
[1] 63.24286 58.25728 59.15555 54.89973 56.39553 60.41354 53.99029 54.71133
[9] 54.43662 54.13668
>
> colMeans(tmp5)
[1] 108.54827 65.60247 70.97447 70.78358 67.72134 78.07849 76.43435
[8] 73.73314 72.16247 73.17568 72.05875 67.39312 67.13570 70.35064
[15] 73.77278 70.73160 67.40939 73.09981 73.24673 69.34523
> colSums(tmp5)
[1] 1085.4827 656.0247 709.7447 707.8358 677.2134 780.7849 764.3435
[8] 737.3314 721.6247 731.7568 720.5875 673.9312 671.3570 703.5064
[15] 737.7278 707.3160 674.0939 730.9981 732.4673 693.4523
> colVars(tmp5)
[1] 16174.68929 36.82545 21.08793 53.55711 64.46096 80.90193
[7] 74.24289 87.45164 45.02744 101.32369 88.06671 93.67204
[13] 70.37216 103.93277 72.58969 36.47627 51.23079 61.61883
[19] 131.69196 38.33613
> colSd(tmp5)
[1] 127.179752 6.068398 4.592160 7.318273 8.028758 8.994550
[7] 8.616431 9.351558 6.710249 10.065967 9.384386 9.678431
[13] 8.388811 10.194742 8.519958 6.039559 7.157569 7.849766
[19] 11.475712 6.191618
> colMax(tmp5)
[1] 469.99733 76.35712 77.94298 83.68276 83.87965 90.45498 84.37160
[8] 89.29824 83.94362 85.73426 86.57050 87.26800 83.42276 86.80069
[15] 84.94562 80.47682 77.48911 83.59104 89.41157 79.11268
> colMin(tmp5)
[1] 62.11079 54.89973 63.17914 61.71422 56.76984 59.85132 54.71133 58.25728
[9] 64.63637 55.72006 54.43662 53.99029 54.13668 59.52558 60.17225 63.01383
[17] 58.57167 59.91352 55.05136 60.20491
>
>
> ### 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] 95.49674 68.89147 72.37184 71.38449 NA 68.91038 69.99783 68.59636
[9] 71.64596 71.90622
> rowSums(tmp5)
[1] 1909.935 1377.829 1447.437 1427.690 NA 1378.208 1399.957 1371.927
[9] 1432.919 1438.124
> rowVars(tmp5)
[1] 7811.78698 90.01149 54.32853 106.63219 66.76621 50.35252
[7] 60.80598 76.65785 76.99534 81.12832
> rowSd(tmp5)
[1] 88.384314 9.487439 7.370789 10.326286 8.171059 7.095951 7.797819
[8] 8.755447 8.774699 9.007126
> rowMax(tmp5)
[1] 469.99733 89.41157 85.73426 89.29824 NA 90.45498 83.87965
[8] 86.57050 84.75708 84.37160
> rowMin(tmp5)
[1] 63.24286 58.25728 59.15555 54.89973 NA 60.41354 53.99029 54.71133
[9] 54.43662 54.13668
>
> colMeans(tmp5)
[1] 108.54827 65.60247 70.97447 70.78358 67.72134 78.07849 76.43435
[8] 73.73314 72.16247 73.17568 72.05875 NA 67.13570 70.35064
[15] 73.77278 70.73160 67.40939 73.09981 73.24673 69.34523
> colSums(tmp5)
[1] 1085.4827 656.0247 709.7447 707.8358 677.2134 780.7849 764.3435
[8] 737.3314 721.6247 731.7568 720.5875 NA 671.3570 703.5064
[15] 737.7278 707.3160 674.0939 730.9981 732.4673 693.4523
> colVars(tmp5)
[1] 16174.68929 36.82545 21.08793 53.55711 64.46096 80.90193
[7] 74.24289 87.45164 45.02744 101.32369 88.06671 NA
[13] 70.37216 103.93277 72.58969 36.47627 51.23079 61.61883
[19] 131.69196 38.33613
> colSd(tmp5)
[1] 127.179752 6.068398 4.592160 7.318273 8.028758 8.994550
[7] 8.616431 9.351558 6.710249 10.065967 9.384386 NA
[13] 8.388811 10.194742 8.519958 6.039559 7.157569 7.849766
[19] 11.475712 6.191618
> colMax(tmp5)
[1] 469.99733 76.35712 77.94298 83.68276 83.87965 90.45498 84.37160
[8] 89.29824 83.94362 85.73426 86.57050 NA 83.42276 86.80069
[15] 84.94562 80.47682 77.48911 83.59104 89.41157 79.11268
> colMin(tmp5)
[1] 62.11079 54.89973 63.17914 61.71422 56.76984 59.85132 54.71133 58.25728
[9] 64.63637 55.72006 54.43662 NA 54.13668 59.52558 60.17225 63.01383
[17] 58.57167 59.91352 55.05136 60.20491
>
> Max(tmp5,na.rm=TRUE)
[1] 469.9973
> Min(tmp5,na.rm=TRUE)
[1] 53.99029
> mean(tmp5,na.rm=TRUE)
[1] 73.1404
> Sum(tmp5,na.rm=TRUE)
[1] 14554.94
> Var(tmp5,na.rm=TRUE)
[1] 871.0087
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 95.49674 68.89147 72.37184 71.38449 72.15332 68.91038 69.99783 68.59636
[9] 71.64596 71.90622
> rowSums(tmp5,na.rm=TRUE)
[1] 1909.935 1377.829 1447.437 1427.690 1370.913 1378.208 1399.957 1371.927
[9] 1432.919 1438.124
> rowVars(tmp5,na.rm=TRUE)
[1] 7811.78698 90.01149 54.32853 106.63219 66.76621 50.35252
[7] 60.80598 76.65785 76.99534 81.12832
> rowSd(tmp5,na.rm=TRUE)
[1] 88.384314 9.487439 7.370789 10.326286 8.171059 7.095951 7.797819
[8] 8.755447 8.774699 9.007126
> rowMax(tmp5,na.rm=TRUE)
[1] 469.99733 89.41157 85.73426 89.29824 84.94562 90.45498 83.87965
[8] 86.57050 84.75708 84.37160
> rowMin(tmp5,na.rm=TRUE)
[1] 63.24286 58.25728 59.15555 54.89973 56.39553 60.41354 53.99029 54.71133
[9] 54.43662 54.13668
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.54827 65.60247 70.97447 70.78358 67.72134 78.07849 76.43435
[8] 73.73314 72.16247 73.17568 72.05875 67.92114 67.13570 70.35064
[15] 73.77278 70.73160 67.40939 73.09981 73.24673 69.34523
> colSums(tmp5,na.rm=TRUE)
[1] 1085.4827 656.0247 709.7447 707.8358 677.2134 780.7849 764.3435
[8] 737.3314 721.6247 731.7568 720.5875 611.2902 671.3570 703.5064
[15] 737.7278 707.3160 674.0939 730.9981 732.4673 693.4523
> colVars(tmp5,na.rm=TRUE)
[1] 16174.68929 36.82545 21.08793 53.55711 64.46096 80.90193
[7] 74.24289 87.45164 45.02744 101.32369 88.06671 102.24448
[13] 70.37216 103.93277 72.58969 36.47627 51.23079 61.61883
[19] 131.69196 38.33613
> colSd(tmp5,na.rm=TRUE)
[1] 127.179752 6.068398 4.592160 7.318273 8.028758 8.994550
[7] 8.616431 9.351558 6.710249 10.065967 9.384386 10.111601
[13] 8.388811 10.194742 8.519958 6.039559 7.157569 7.849766
[19] 11.475712 6.191618
> colMax(tmp5,na.rm=TRUE)
[1] 469.99733 76.35712 77.94298 83.68276 83.87965 90.45498 84.37160
[8] 89.29824 83.94362 85.73426 86.57050 87.26800 83.42276 86.80069
[15] 84.94562 80.47682 77.48911 83.59104 89.41157 79.11268
> colMin(tmp5,na.rm=TRUE)
[1] 62.11079 54.89973 63.17914 61.71422 56.76984 59.85132 54.71133 58.25728
[9] 64.63637 55.72006 54.43662 53.99029 54.13668 59.52558 60.17225 63.01383
[17] 58.57167 59.91352 55.05136 60.20491
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 95.49674 68.89147 72.37184 71.38449 NaN 68.91038 69.99783 68.59636
[9] 71.64596 71.90622
> rowSums(tmp5,na.rm=TRUE)
[1] 1909.935 1377.829 1447.437 1427.690 0.000 1378.208 1399.957 1371.927
[9] 1432.919 1438.124
> rowVars(tmp5,na.rm=TRUE)
[1] 7811.78698 90.01149 54.32853 106.63219 NA 50.35252
[7] 60.80598 76.65785 76.99534 81.12832
> rowSd(tmp5,na.rm=TRUE)
[1] 88.384314 9.487439 7.370789 10.326286 NA 7.095951 7.797819
[8] 8.755447 8.774699 9.007126
> rowMax(tmp5,na.rm=TRUE)
[1] 469.99733 89.41157 85.73426 89.29824 NA 90.45498 83.87965
[8] 86.57050 84.75708 84.37160
> rowMin(tmp5,na.rm=TRUE)
[1] 63.24286 58.25728 59.15555 54.89973 NA 60.41354 53.99029 54.71133
[9] 54.43662 54.13668
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.53349 65.14630 70.20019 70.59008 66.59161 80.10373 76.48458
[8] 74.91495 71.80852 72.27965 72.44870 NaN 68.32905 69.46703
[15] 72.53136 70.17905 66.47956 71.93412 74.19186 69.75680
> colSums(tmp5,na.rm=TRUE)
[1] 1021.8014 586.3167 631.8017 635.3107 599.3245 720.9336 688.3612
[8] 674.2345 646.2767 650.5169 652.0383 0.0000 614.9614 625.2033
[15] 652.7822 631.6115 598.3161 647.4071 667.7268 627.8112
> colVars(tmp5,na.rm=TRUE)
[1] 17916.93557 39.08753 16.97945 59.83056 58.16034 44.87165
[7] 83.49486 82.67045 49.24647 104.95696 97.36435 NA
[13] 63.14768 108.14065 64.32559 37.60111 47.90805 54.03426
[19] 138.10414 41.22249
> colSd(tmp5,na.rm=TRUE)
[1] 133.854158 6.252002 4.120613 7.735022 7.626293 6.698630
[7] 9.137552 9.092329 7.017583 10.244850 9.867338 NA
[13] 7.946551 10.399070 8.020324 6.131974 6.921564 7.350800
[19] 11.751772 6.420474
> colMax(tmp5,na.rm=TRUE)
[1] 469.99733 76.35712 74.25281 83.68276 83.87965 90.45498 84.37160
[8] 89.29824 83.94362 85.73426 86.57050 -Inf 83.42276 86.80069
[15] 84.75708 80.47682 77.48911 79.56001 89.41157 79.11268
> colMin(tmp5,na.rm=TRUE)
[1] 62.11079 54.89973 63.17914 61.71422 56.76984 68.29139 54.71133 58.25728
[9] 64.63637 55.72006 54.43662 Inf 54.13668 59.52558 60.17225 63.01383
[17] 58.57167 59.91352 55.05136 60.20491
>
>
>
>
> 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] 162.55404 194.27847 210.58165 205.44510 257.02734 107.38321 349.43351
[8] 184.06920 195.50729 61.51109
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 162.55404 194.27847 210.58165 205.44510 257.02734 107.38321 349.43351
[8] 184.06920 195.50729 61.51109
>
>
>
> 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 -8.526513e-14 0.000000e+00 1.136868e-13 -2.842171e-14
[6] -1.421085e-13 0.000000e+00 1.136868e-13 5.684342e-14 -1.136868e-13
[11] 1.136868e-13 5.684342e-14 1.136868e-13 -8.526513e-14 -1.278977e-13
[16] -5.684342e-14 1.136868e-13 -2.842171e-14 -5.684342e-14 2.273737e-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)
+ }
3 6
4 12
9 13
8 13
2 17
5 6
4 8
3 20
1 10
8 7
2 2
2 10
8 12
5 5
7 6
2 2
7 5
5 19
7 4
7 6
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] 2.290371
> Min(tmp)
[1] -3.010377
> mean(tmp)
[1] -0.01887558
> Sum(tmp)
[1] -1.887558
> Var(tmp)
[1] 1.2547
>
> rowMeans(tmp)
[1] -0.01887558
> rowSums(tmp)
[1] -1.887558
> rowVars(tmp)
[1] 1.2547
> rowSd(tmp)
[1] 1.120134
> rowMax(tmp)
[1] 2.290371
> rowMin(tmp)
[1] -3.010377
>
> colMeans(tmp)
[1] -0.130980264 0.319123202 2.256063695 1.089010902 0.744813802
[6] -1.103679816 0.770106031 -1.028413665 0.630820210 0.962278457
[11] 1.308399113 -1.616694719 -1.709483788 -1.065360046 -0.938366455
[16] 2.242020753 -0.018307775 -1.345081347 0.141479521 0.754858574
[21] -1.446307544 -0.561185446 -0.101608341 -1.420935359 0.281815250
[26] 0.805155985 -1.397887576 -0.017408054 -0.002500402 -0.032525204
[31] 0.338820577 -0.782825053 0.866209086 1.163567053 1.221035463
[36] -1.857375615 -0.900603996 -0.017899598 -0.465777123 -0.752394341
[41] -0.544218662 1.762330732 -1.007268122 1.823440764 0.507396362
[46] -1.243539860 -1.181902768 -0.998775418 -2.594448373 1.555421792
[51] -0.744217109 0.920184069 2.290371138 0.425361881 -1.316454555
[56] 0.011840765 0.987056340 -0.051698596 0.569825783 0.190169859
[61] -0.272848426 -0.072640066 -0.234045290 0.685455484 -1.355477134
[66] 0.303071408 -1.417888055 -1.821458497 0.764694934 1.298752038
[71] 0.606535631 1.979529994 0.539753264 1.240840428 0.135752218
[76] 0.367994541 -0.799214869 1.136729485 -0.950331142 0.168510569
[81] -1.567806203 -0.274013405 -0.778825175 -3.010377471 1.596290505
[86] -0.638255584 0.490124785 -1.019929723 0.471274287 0.382333286
[91] 2.014310837 -0.349604323 -0.737104290 0.431865254 1.062386494
[96] -0.905761303 -2.010773082 0.647067085 0.241003507 1.221667875
> colSums(tmp)
[1] -0.130980264 0.319123202 2.256063695 1.089010902 0.744813802
[6] -1.103679816 0.770106031 -1.028413665 0.630820210 0.962278457
[11] 1.308399113 -1.616694719 -1.709483788 -1.065360046 -0.938366455
[16] 2.242020753 -0.018307775 -1.345081347 0.141479521 0.754858574
[21] -1.446307544 -0.561185446 -0.101608341 -1.420935359 0.281815250
[26] 0.805155985 -1.397887576 -0.017408054 -0.002500402 -0.032525204
[31] 0.338820577 -0.782825053 0.866209086 1.163567053 1.221035463
[36] -1.857375615 -0.900603996 -0.017899598 -0.465777123 -0.752394341
[41] -0.544218662 1.762330732 -1.007268122 1.823440764 0.507396362
[46] -1.243539860 -1.181902768 -0.998775418 -2.594448373 1.555421792
[51] -0.744217109 0.920184069 2.290371138 0.425361881 -1.316454555
[56] 0.011840765 0.987056340 -0.051698596 0.569825783 0.190169859
[61] -0.272848426 -0.072640066 -0.234045290 0.685455484 -1.355477134
[66] 0.303071408 -1.417888055 -1.821458497 0.764694934 1.298752038
[71] 0.606535631 1.979529994 0.539753264 1.240840428 0.135752218
[76] 0.367994541 -0.799214869 1.136729485 -0.950331142 0.168510569
[81] -1.567806203 -0.274013405 -0.778825175 -3.010377471 1.596290505
[86] -0.638255584 0.490124785 -1.019929723 0.471274287 0.382333286
[91] 2.014310837 -0.349604323 -0.737104290 0.431865254 1.062386494
[96] -0.905761303 -2.010773082 0.647067085 0.241003507 1.221667875
> 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] -0.130980264 0.319123202 2.256063695 1.089010902 0.744813802
[6] -1.103679816 0.770106031 -1.028413665 0.630820210 0.962278457
[11] 1.308399113 -1.616694719 -1.709483788 -1.065360046 -0.938366455
[16] 2.242020753 -0.018307775 -1.345081347 0.141479521 0.754858574
[21] -1.446307544 -0.561185446 -0.101608341 -1.420935359 0.281815250
[26] 0.805155985 -1.397887576 -0.017408054 -0.002500402 -0.032525204
[31] 0.338820577 -0.782825053 0.866209086 1.163567053 1.221035463
[36] -1.857375615 -0.900603996 -0.017899598 -0.465777123 -0.752394341
[41] -0.544218662 1.762330732 -1.007268122 1.823440764 0.507396362
[46] -1.243539860 -1.181902768 -0.998775418 -2.594448373 1.555421792
[51] -0.744217109 0.920184069 2.290371138 0.425361881 -1.316454555
[56] 0.011840765 0.987056340 -0.051698596 0.569825783 0.190169859
[61] -0.272848426 -0.072640066 -0.234045290 0.685455484 -1.355477134
[66] 0.303071408 -1.417888055 -1.821458497 0.764694934 1.298752038
[71] 0.606535631 1.979529994 0.539753264 1.240840428 0.135752218
[76] 0.367994541 -0.799214869 1.136729485 -0.950331142 0.168510569
[81] -1.567806203 -0.274013405 -0.778825175 -3.010377471 1.596290505
[86] -0.638255584 0.490124785 -1.019929723 0.471274287 0.382333286
[91] 2.014310837 -0.349604323 -0.737104290 0.431865254 1.062386494
[96] -0.905761303 -2.010773082 0.647067085 0.241003507 1.221667875
> colMin(tmp)
[1] -0.130980264 0.319123202 2.256063695 1.089010902 0.744813802
[6] -1.103679816 0.770106031 -1.028413665 0.630820210 0.962278457
[11] 1.308399113 -1.616694719 -1.709483788 -1.065360046 -0.938366455
[16] 2.242020753 -0.018307775 -1.345081347 0.141479521 0.754858574
[21] -1.446307544 -0.561185446 -0.101608341 -1.420935359 0.281815250
[26] 0.805155985 -1.397887576 -0.017408054 -0.002500402 -0.032525204
[31] 0.338820577 -0.782825053 0.866209086 1.163567053 1.221035463
[36] -1.857375615 -0.900603996 -0.017899598 -0.465777123 -0.752394341
[41] -0.544218662 1.762330732 -1.007268122 1.823440764 0.507396362
[46] -1.243539860 -1.181902768 -0.998775418 -2.594448373 1.555421792
[51] -0.744217109 0.920184069 2.290371138 0.425361881 -1.316454555
[56] 0.011840765 0.987056340 -0.051698596 0.569825783 0.190169859
[61] -0.272848426 -0.072640066 -0.234045290 0.685455484 -1.355477134
[66] 0.303071408 -1.417888055 -1.821458497 0.764694934 1.298752038
[71] 0.606535631 1.979529994 0.539753264 1.240840428 0.135752218
[76] 0.367994541 -0.799214869 1.136729485 -0.950331142 0.168510569
[81] -1.567806203 -0.274013405 -0.778825175 -3.010377471 1.596290505
[86] -0.638255584 0.490124785 -1.019929723 0.471274287 0.382333286
[91] 2.014310837 -0.349604323 -0.737104290 0.431865254 1.062386494
[96] -0.905761303 -2.010773082 0.647067085 0.241003507 1.221667875
> colMedians(tmp)
[1] -0.130980264 0.319123202 2.256063695 1.089010902 0.744813802
[6] -1.103679816 0.770106031 -1.028413665 0.630820210 0.962278457
[11] 1.308399113 -1.616694719 -1.709483788 -1.065360046 -0.938366455
[16] 2.242020753 -0.018307775 -1.345081347 0.141479521 0.754858574
[21] -1.446307544 -0.561185446 -0.101608341 -1.420935359 0.281815250
[26] 0.805155985 -1.397887576 -0.017408054 -0.002500402 -0.032525204
[31] 0.338820577 -0.782825053 0.866209086 1.163567053 1.221035463
[36] -1.857375615 -0.900603996 -0.017899598 -0.465777123 -0.752394341
[41] -0.544218662 1.762330732 -1.007268122 1.823440764 0.507396362
[46] -1.243539860 -1.181902768 -0.998775418 -2.594448373 1.555421792
[51] -0.744217109 0.920184069 2.290371138 0.425361881 -1.316454555
[56] 0.011840765 0.987056340 -0.051698596 0.569825783 0.190169859
[61] -0.272848426 -0.072640066 -0.234045290 0.685455484 -1.355477134
[66] 0.303071408 -1.417888055 -1.821458497 0.764694934 1.298752038
[71] 0.606535631 1.979529994 0.539753264 1.240840428 0.135752218
[76] 0.367994541 -0.799214869 1.136729485 -0.950331142 0.168510569
[81] -1.567806203 -0.274013405 -0.778825175 -3.010377471 1.596290505
[86] -0.638255584 0.490124785 -1.019929723 0.471274287 0.382333286
[91] 2.014310837 -0.349604323 -0.737104290 0.431865254 1.062386494
[96] -0.905761303 -2.010773082 0.647067085 0.241003507 1.221667875
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1309803 0.3191232 2.256064 1.089011 0.7448138 -1.10368 0.770106
[2,] -0.1309803 0.3191232 2.256064 1.089011 0.7448138 -1.10368 0.770106
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.028414 0.6308202 0.9622785 1.308399 -1.616695 -1.709484 -1.06536
[2,] -1.028414 0.6308202 0.9622785 1.308399 -1.616695 -1.709484 -1.06536
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.9383665 2.242021 -0.01830777 -1.345081 0.1414795 0.7548586 -1.446308
[2,] -0.9383665 2.242021 -0.01830777 -1.345081 0.1414795 0.7548586 -1.446308
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.5611854 -0.1016083 -1.420935 0.2818153 0.805156 -1.397888 -0.01740805
[2,] -0.5611854 -0.1016083 -1.420935 0.2818153 0.805156 -1.397888 -0.01740805
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.002500402 -0.0325252 0.3388206 -0.7828251 0.8662091 1.163567 1.221035
[2,] -0.002500402 -0.0325252 0.3388206 -0.7828251 0.8662091 1.163567 1.221035
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.857376 -0.900604 -0.0178996 -0.4657771 -0.7523943 -0.5442187 1.762331
[2,] -1.857376 -0.900604 -0.0178996 -0.4657771 -0.7523943 -0.5442187 1.762331
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.007268 1.823441 0.5073964 -1.24354 -1.181903 -0.9987754 -2.594448
[2,] -1.007268 1.823441 0.5073964 -1.24354 -1.181903 -0.9987754 -2.594448
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.555422 -0.7442171 0.9201841 2.290371 0.4253619 -1.316455 0.01184077
[2,] 1.555422 -0.7442171 0.9201841 2.290371 0.4253619 -1.316455 0.01184077
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.9870563 -0.0516986 0.5698258 0.1901699 -0.2728484 -0.07264007 -0.2340453
[2,] 0.9870563 -0.0516986 0.5698258 0.1901699 -0.2728484 -0.07264007 -0.2340453
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.6854555 -1.355477 0.3030714 -1.417888 -1.821458 0.7646949 1.298752
[2,] 0.6854555 -1.355477 0.3030714 -1.417888 -1.821458 0.7646949 1.298752
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.6065356 1.97953 0.5397533 1.24084 0.1357522 0.3679945 -0.7992149
[2,] 0.6065356 1.97953 0.5397533 1.24084 0.1357522 0.3679945 -0.7992149
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.136729 -0.9503311 0.1685106 -1.567806 -0.2740134 -0.7788252 -3.010377
[2,] 1.136729 -0.9503311 0.1685106 -1.567806 -0.2740134 -0.7788252 -3.010377
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.596291 -0.6382556 0.4901248 -1.01993 0.4712743 0.3823333 2.014311
[2,] 1.596291 -0.6382556 0.4901248 -1.01993 0.4712743 0.3823333 2.014311
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.3496043 -0.7371043 0.4318653 1.062386 -0.9057613 -2.010773 0.6470671
[2,] -0.3496043 -0.7371043 0.4318653 1.062386 -0.9057613 -2.010773 0.6470671
[,99] [,100]
[1,] 0.2410035 1.221668
[2,] 0.2410035 1.221668
>
>
> Max(tmp2)
[1] 1.914682
> Min(tmp2)
[1] -3.469894
> mean(tmp2)
[1] -0.1554694
> Sum(tmp2)
[1] -15.54694
> Var(tmp2)
[1] 1.095108
>
> rowMeans(tmp2)
[1] -1.306545065 -1.146255232 -0.462668488 -0.636624603 0.710200146
[6] -0.848166478 1.354805345 0.944312023 0.603266649 -0.658957855
[11] -0.678764609 -1.195143854 -1.148681327 -1.589804451 -1.105447226
[16] 0.555907895 0.905558722 -1.025413540 -0.276438418 1.055131123
[21] 0.006046979 -0.481980366 -0.665998120 0.727278614 0.180093458
[26] 1.186537384 0.601834528 1.536143499 1.074195976 1.256082955
[31] -1.039206119 -0.330817496 1.664496996 -0.255887952 -0.405321871
[36] 1.450955287 0.495172318 0.885902213 0.238766448 -2.393480846
[41] -0.574814782 -1.699179193 -0.959669508 -0.539087764 1.029990267
[46] -0.909337642 0.364883762 1.485618762 -1.343360708 0.494175715
[51] -1.201798293 -0.837181295 -2.478794241 0.162011534 -0.532332434
[56] 0.270259214 1.914682160 0.434617783 0.077230898 0.482557937
[61] 1.322487420 -0.676412280 0.170519675 -1.356017363 -0.478646946
[66] -0.526991883 -1.662868363 -1.696207891 -0.338158753 -1.281717760
[71] 1.260323627 1.291970635 0.683421192 0.001707991 -0.163997519
[76] -0.911084896 0.896549415 -3.469893559 1.432906822 1.330736254
[81] -1.013354366 -0.939906760 -0.891819611 -1.590478335 -0.572330817
[86] 0.305606889 -0.787751918 -0.088027909 0.043097590 -1.492994794
[91] -0.782896085 1.305765336 0.430473473 0.576644954 0.888459965
[96] -0.299845238 -0.462417622 -0.882829141 -0.916385800 0.373867901
> rowSums(tmp2)
[1] -1.306545065 -1.146255232 -0.462668488 -0.636624603 0.710200146
[6] -0.848166478 1.354805345 0.944312023 0.603266649 -0.658957855
[11] -0.678764609 -1.195143854 -1.148681327 -1.589804451 -1.105447226
[16] 0.555907895 0.905558722 -1.025413540 -0.276438418 1.055131123
[21] 0.006046979 -0.481980366 -0.665998120 0.727278614 0.180093458
[26] 1.186537384 0.601834528 1.536143499 1.074195976 1.256082955
[31] -1.039206119 -0.330817496 1.664496996 -0.255887952 -0.405321871
[36] 1.450955287 0.495172318 0.885902213 0.238766448 -2.393480846
[41] -0.574814782 -1.699179193 -0.959669508 -0.539087764 1.029990267
[46] -0.909337642 0.364883762 1.485618762 -1.343360708 0.494175715
[51] -1.201798293 -0.837181295 -2.478794241 0.162011534 -0.532332434
[56] 0.270259214 1.914682160 0.434617783 0.077230898 0.482557937
[61] 1.322487420 -0.676412280 0.170519675 -1.356017363 -0.478646946
[66] -0.526991883 -1.662868363 -1.696207891 -0.338158753 -1.281717760
[71] 1.260323627 1.291970635 0.683421192 0.001707991 -0.163997519
[76] -0.911084896 0.896549415 -3.469893559 1.432906822 1.330736254
[81] -1.013354366 -0.939906760 -0.891819611 -1.590478335 -0.572330817
[86] 0.305606889 -0.787751918 -0.088027909 0.043097590 -1.492994794
[91] -0.782896085 1.305765336 0.430473473 0.576644954 0.888459965
[96] -0.299845238 -0.462417622 -0.882829141 -0.916385800 0.373867901
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -1.306545065 -1.146255232 -0.462668488 -0.636624603 0.710200146
[6] -0.848166478 1.354805345 0.944312023 0.603266649 -0.658957855
[11] -0.678764609 -1.195143854 -1.148681327 -1.589804451 -1.105447226
[16] 0.555907895 0.905558722 -1.025413540 -0.276438418 1.055131123
[21] 0.006046979 -0.481980366 -0.665998120 0.727278614 0.180093458
[26] 1.186537384 0.601834528 1.536143499 1.074195976 1.256082955
[31] -1.039206119 -0.330817496 1.664496996 -0.255887952 -0.405321871
[36] 1.450955287 0.495172318 0.885902213 0.238766448 -2.393480846
[41] -0.574814782 -1.699179193 -0.959669508 -0.539087764 1.029990267
[46] -0.909337642 0.364883762 1.485618762 -1.343360708 0.494175715
[51] -1.201798293 -0.837181295 -2.478794241 0.162011534 -0.532332434
[56] 0.270259214 1.914682160 0.434617783 0.077230898 0.482557937
[61] 1.322487420 -0.676412280 0.170519675 -1.356017363 -0.478646946
[66] -0.526991883 -1.662868363 -1.696207891 -0.338158753 -1.281717760
[71] 1.260323627 1.291970635 0.683421192 0.001707991 -0.163997519
[76] -0.911084896 0.896549415 -3.469893559 1.432906822 1.330736254
[81] -1.013354366 -0.939906760 -0.891819611 -1.590478335 -0.572330817
[86] 0.305606889 -0.787751918 -0.088027909 0.043097590 -1.492994794
[91] -0.782896085 1.305765336 0.430473473 0.576644954 0.888459965
[96] -0.299845238 -0.462417622 -0.882829141 -0.916385800 0.373867901
> rowMin(tmp2)
[1] -1.306545065 -1.146255232 -0.462668488 -0.636624603 0.710200146
[6] -0.848166478 1.354805345 0.944312023 0.603266649 -0.658957855
[11] -0.678764609 -1.195143854 -1.148681327 -1.589804451 -1.105447226
[16] 0.555907895 0.905558722 -1.025413540 -0.276438418 1.055131123
[21] 0.006046979 -0.481980366 -0.665998120 0.727278614 0.180093458
[26] 1.186537384 0.601834528 1.536143499 1.074195976 1.256082955
[31] -1.039206119 -0.330817496 1.664496996 -0.255887952 -0.405321871
[36] 1.450955287 0.495172318 0.885902213 0.238766448 -2.393480846
[41] -0.574814782 -1.699179193 -0.959669508 -0.539087764 1.029990267
[46] -0.909337642 0.364883762 1.485618762 -1.343360708 0.494175715
[51] -1.201798293 -0.837181295 -2.478794241 0.162011534 -0.532332434
[56] 0.270259214 1.914682160 0.434617783 0.077230898 0.482557937
[61] 1.322487420 -0.676412280 0.170519675 -1.356017363 -0.478646946
[66] -0.526991883 -1.662868363 -1.696207891 -0.338158753 -1.281717760
[71] 1.260323627 1.291970635 0.683421192 0.001707991 -0.163997519
[76] -0.911084896 0.896549415 -3.469893559 1.432906822 1.330736254
[81] -1.013354366 -0.939906760 -0.891819611 -1.590478335 -0.572330817
[86] 0.305606889 -0.787751918 -0.088027909 0.043097590 -1.492994794
[91] -0.782896085 1.305765336 0.430473473 0.576644954 0.888459965
[96] -0.299845238 -0.462417622 -0.882829141 -0.916385800 0.373867901
>
> colMeans(tmp2)
[1] -0.1554694
> colSums(tmp2)
[1] -15.54694
> colVars(tmp2)
[1] 1.095108
> colSd(tmp2)
[1] 1.046474
> colMax(tmp2)
[1] 1.914682
> colMin(tmp2)
[1] -3.469894
> colMedians(tmp2)
[1] -0.2881418
> colRanges(tmp2)
[,1]
[1,] -3.469894
[2,] 1.914682
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.3764154 4.7490618 -0.1264694 -0.7017192 -1.3457497 1.0217257
[7] -2.1329021 -8.4366895 4.2108168 3.4315332
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0934671
[2,] -0.6371323
[3,] 0.1680122
[4,] 0.4519944
[5,] 0.7582215
>
> rowApply(tmp,sum)
[1] -1.129307 -1.859523 1.565398 -1.172186 -2.293823 1.522945 -3.348802
[8] -1.729637 3.904578 4.833550
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 8 7 8 7 1 6 2 6 5
[2,] 3 10 3 9 9 3 10 7 10 7
[3,] 7 5 5 7 1 9 4 1 9 10
[4,] 6 3 10 5 6 7 9 3 1 2
[5,] 8 7 6 2 4 4 7 8 3 4
[6,] 10 2 1 3 3 5 3 9 8 9
[7,] 4 6 2 6 5 6 5 6 4 3
[8,] 9 1 4 1 2 8 2 5 2 1
[9,] 1 4 9 4 10 2 8 10 5 6
[10,] 5 9 8 10 8 10 1 4 7 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.3646250 1.5948799 1.6509557 0.7440615 -1.1343197 0.9259334
[7] -0.7605883 2.2204087 0.4335597 0.4025716 -0.8057329 -0.9494421
[13] -1.8501222 4.3857155 2.9275854 -0.8871826 1.7583426 0.9425335
[19] -2.5182540 1.4593301
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8643694
[2,] -0.2973369
[3,] -0.1240228
[4,] 1.0352244
[5,] 1.6151298
>
> rowApply(tmp,sum)
[1] 5.9746482 3.3595580 -2.7505879 5.6124672 -0.2912248
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 4 9 6 18
[2,] 18 1 18 18 5
[3,] 11 2 16 15 19
[4,] 12 15 4 13 9
[5,] 2 6 10 10 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.6151298 1.2441809 0.4582129 0.6241022 -0.90368661 0.96190903
[2,] -0.8643694 -1.5133274 -1.3300636 0.9332387 -0.60816874 1.05567278
[3,] -0.1240228 0.7250644 0.5976378 -1.0387362 0.01470091 0.09912621
[4,] -0.2973369 1.8289366 0.8319611 0.4161956 0.19347819 -0.51960036
[5,] 1.0352244 -0.6899747 1.0932075 -0.1907388 0.16935651 -0.67117428
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.2620339 -0.9614521 -0.58107931 -0.08576504 -0.08797567 1.2382968
[2,] -0.6854748 0.8866847 0.95362470 -0.04302226 1.62264266 0.4669697
[3,] 0.2338709 1.4112648 0.30121041 0.91269780 -1.24292531 -1.4728832
[4,] -1.8040163 -0.7521038 -0.04224899 0.18320226 -0.96286256 -0.2504675
[5,] 0.2329980 1.6360151 -0.19794714 -0.56454117 -0.13461197 -0.9313579
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.6422921 0.7313527 0.9300314 0.4119553 1.0441287 -0.239737802
[2,] 0.4643485 0.9822590 0.5230795 -0.9069375 1.2011936 0.767281657
[3,] -1.8598215 0.2551023 -0.3534098 0.3851409 -1.0291754 -0.745749420
[4,] -0.6572565 1.8450030 0.9564622 0.7201234 0.3657459 1.169535991
[5,] 0.8448993 0.5719986 0.8714221 -1.4974647 0.1764498 -0.008796902
[,19] [,20]
[1,] -0.8134325 -0.2312642
[2,] -0.3985006 -0.1475733
[3,] -0.4628829 0.6432022
[4,] 0.3810655 2.0066504
[5,] -1.2245035 -0.8116849
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.307575 2.172306 -0.5463695 2.223598 -0.4349324 -0.1128924 -0.2997118
col8 col9 col10 col11 col12 col13 col14
row1 -1.138724 3.018479 0.9006871 -0.08827923 0.8229395 -1.961319 -0.8108857
col15 col16 col17 col18 col19 col20
row1 -0.5048645 0.07136486 0.5010854 -0.4355201 -1.17186 0.2626378
> tmp[,"col10"]
col10
row1 0.9006871
row2 -1.2418291
row3 -0.5713588
row4 -0.7711222
row5 -0.7716309
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.3075748 2.1723063 -0.5463695 2.2235979 -0.4349324 -0.1128924
row5 -0.1175005 -0.2769772 0.1797852 -0.8935307 -0.3861850 -0.7596808
col7 col8 col9 col10 col11 col12
row1 -0.2997118 -1.138724 3.01847932 0.9006871 -0.08827923 0.8229395
row5 0.4442306 -1.273913 -0.09186977 -0.7716309 -0.89389770 2.0269907
col13 col14 col15 col16 col17 col18 col19
row1 -1.961319 -0.8108857 -0.5048645 0.07136486 0.5010854 -0.4355201 -1.171860
row5 -1.291921 -0.5554090 -0.5405091 -1.17102750 0.8268046 2.1942839 -1.226489
col20
row1 0.2626378
row5 1.4010193
> tmp[,c("col6","col20")]
col6 col20
row1 -0.1128923799 0.2626378
row2 2.1843896141 -0.9358101
row3 -0.0003007135 1.2006413
row4 0.4900579127 1.0184841
row5 -0.7596808438 1.4010193
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.1128924 0.2626378
row5 -0.7596808 1.4010193
>
>
>
>
> 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 49.55629 49.03612 50.0484 49.85045 49.28273 104.1701 50.4487 50.5056
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.08018 49.6719 50.53812 49.21682 49.91523 48.95563 48.37275 50.43
col17 col18 col19 col20
row1 49.75494 51.34112 48.91925 103.5461
> tmp[,"col10"]
col10
row1 49.67190
row2 31.56973
row3 31.03224
row4 29.66957
row5 51.17359
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.55629 49.03612 50.04840 49.85045 49.28273 104.1701 50.44870 50.50560
row5 49.71209 48.94428 50.66186 50.22090 49.24891 104.8248 51.02467 51.99533
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.08018 49.67190 50.53812 49.21682 49.91523 48.95563 48.37275 50.43000
row5 48.70251 51.17359 50.69786 49.58872 51.04239 50.63428 50.42423 50.71594
col17 col18 col19 col20
row1 49.75494 51.34112 48.91925 103.5461
row5 48.95636 50.46641 48.75725 103.6997
> tmp[,c("col6","col20")]
col6 col20
row1 104.17013 103.54610
row2 75.88496 74.85598
row3 73.94671 75.92957
row4 75.35337 74.53352
row5 104.82484 103.69971
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.1701 103.5461
row5 104.8248 103.6997
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.1701 103.5461
row5 104.8248 103.6997
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.28636609
[2,] 0.37025187
[3,] 0.29390442
[4,] -1.03547947
[5,] -0.02978856
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.2652819 -0.5203128
[2,] -0.3794144 -0.8936351
[3,] -1.0930119 0.8928944
[4,] 0.9496011 1.2690628
[5,] -0.6707118 1.2189083
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.0630882 -0.06585759
[2,] 1.6066140 -1.62377758
[3,] -1.6295335 -0.06211983
[4,] -0.9595835 -0.32866014
[5,] -1.5944507 -0.44193579
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.063088
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.063088
[2,] 1.606614
>
>
>
> 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 0.2285566 0.01047013 -0.1255284 0.3350447 -1.07421495 0.1290865
row1 -0.2763788 -0.11781580 0.6313691 2.1323687 -0.01833656 1.2572412
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.0420440 0.7263095 1.0101097 1.7335203 1.4460723 -1.3841662 -0.8021139
row1 0.4395279 -2.3128000 -0.6885116 0.6022395 0.6673008 -0.4730604 0.5640776
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.4055960 0.5222606 0.40433569 -1.6183448 0.3998942 0.3899684 -1.721774
row1 -0.7196061 0.2133221 -0.02175707 -0.3558266 0.3683161 -1.2734791 0.459697
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.1388131 -0.4579872 -0.3671965 0.8525977 -1.080375 0.2506885 0.2272195
[,8] [,9] [,10]
row2 0.8098278 -0.8058894 0.891761
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.05638807 0.2922904 -1.553228 -0.1307265 -1.154651 -0.8304866 1.803647
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.2779476 -0.3839036 -0.2670982 0.7370659 -0.5272238 0.8552956 2.644658
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2287779 0.2768074 0.5281545 -0.4001867 -0.02869542 -0.4891056
>
>
> 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: 0x5696a88f27a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd1213112ee"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd168729913"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd15eee3d45"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd1441564c0"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd17c00c76a"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd173dfd63a"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd13b2a3843"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd13c24452c"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd13b5110d6"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd1224540e0"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd13c40c4d9"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd177e9749d"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd172e2ac57"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd1590511e9"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM311dd1424b6d14"
>
>
> ### 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: 0x5696aa0416c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5696aa0416c0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5696aa0416c0>
> rowMedians(tmp)
[1] 0.6732919011 0.3717963117 0.3996232682 0.3531916902 -0.2150596425
[6] -0.1213177520 0.3868889616 0.0638267053 -0.0708981667 0.1930386540
[11] -0.2134890763 -0.1998576871 -0.3767199783 0.3202052988 0.3807899423
[16] -0.3937214118 -0.0427315300 0.0284769261 0.1258981408 0.1796887349
[21] -0.1338973100 -0.7358259561 0.5761117248 -0.0709648243 -0.2984879346
[26] 0.2619926456 -0.0592076380 -0.6606923334 0.1013922008 0.1009865427
[31] 0.2953791549 -0.1636588021 0.3092144869 0.1671190070 0.4418797868
[36] -0.0286887450 0.4340440221 0.2251660449 -0.4095930597 -0.5674436732
[41] -0.2540754102 -0.6113842483 -0.2674599144 0.1917721180 0.3240223556
[46] 0.0427344516 0.1036046895 0.5375222637 -0.8699952546 0.2169859762
[51] -0.0394838817 0.0657786956 0.0027698840 -0.2017412797 0.5764361197
[56] 0.2769888916 0.4131258421 0.5438713081 -0.6774597033 0.0987236424
[61] -0.1705342760 -0.1642382089 0.0207712221 0.3392566811 -0.2321343956
[66] 0.3884196671 -0.1202710311 0.2170810817 -0.0764425193 -0.1185619744
[71] -0.2435718726 0.2174046008 0.1707914823 0.2752823465 -0.0356552842
[76] 0.0203518867 -0.2249689860 -0.4150204677 -0.4900550436 -0.0134188169
[81] -0.2291663746 0.5244190142 0.3920689428 0.1095324212 -0.4334292964
[86] 0.2783718475 0.2885983884 -0.1613178308 0.0008562942 -0.0143552201
[91] 0.1500660363 0.2585745247 0.0887023574 0.4095780909 -0.1500985438
[96] -0.9127613383 0.2103334983 0.6479683771 -0.2515155316 -0.2926034387
[101] -0.4207395212 -0.2879184792 0.0406490782 -0.1859306402 -0.1243171437
[106] 0.0256194614 0.1637646326 0.3317879664 -0.0381361175 0.1121904439
[111] -0.2717894473 -0.4657929467 0.1520941214 0.5513617066 0.0330462158
[116] 0.0702686632 -0.2164182530 -0.3611420504 -0.2959405553 -0.1198511592
[121] -0.3105969872 0.7014089791 -0.0870373524 -0.0036801248 -0.1873222470
[126] -0.0427148422 -0.1699634013 0.1168843276 -0.3188221918 0.2749707378
[131] 0.1882119925 -0.6982799276 -0.3610815375 -0.4322353479 -0.2346971670
[136] -0.1971639518 0.0592825594 0.3027296364 -0.0784923542 0.0069077511
[141] -0.0987252985 0.1390516877 -0.5161212055 0.3111839088 -0.2696976964
[146] 0.4977906443 -0.0809889200 0.0416918532 0.1292679074 -0.6510656742
[151] 0.4399859925 0.5034752128 0.0358841876 -0.4083213752 0.1297187112
[156] 0.7742948996 -0.0682245623 -0.2088001123 -0.2173222306 -0.2077185333
[161] -0.2962274523 0.5901829433 -0.2413524622 -0.2535857089 -0.0641822671
[166] -0.3278054806 0.2416332769 0.1347123149 -0.3322946718 -0.0634664677
[171] -0.2999015383 -0.3149493012 -0.2440197937 0.1778021682 0.5082159306
[176] 0.2187654064 0.3257135648 0.1176869787 0.2759765245 0.1967376145
[181] -0.3172158780 0.1618374128 0.1267965211 0.1730915910 0.3296252650
[186] 0.3369138317 -0.3896653289 0.0296245074 -0.2874002658 -0.0824892976
[191] 0.3918474429 -0.0753397431 0.1572144215 0.0252966150 0.1367082827
[196] -0.7600141893 -0.1210073639 -0.2378623032 0.2847913981 -0.1907896760
[201] 0.4167853810 0.0546199376 0.0146065355 0.1528513108 -0.2082035851
[206] 0.0695594562 0.0125477430 -0.2122799203 0.3231868247 0.5516960495
[211] -0.0433667701 -0.0605692555 0.4203165619 0.2270450735 0.7326039392
[216] -0.0966033835 -0.1153082551 -0.1442631166 0.2459747988 -0.3352778208
[221] -0.1927022359 -0.4799663353 -0.1218346426 0.2290754129 -0.0707535178
[226] 0.1087911544 -0.1668362843 -0.2178753856 0.7998866676 0.2052767718
>
> proc.time()
user system elapsed
1.654 0.908 2.614
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 (2025-06-13) -- "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: 0x56b49516ab80>
> .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: 0x56b49516ab80>
> .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: 0x56b49516ab80>
> .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: 0x56b49516ab80>
> 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: 0x56b49514d390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b49514d390>
> .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: 0x56b49514d390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b49514d390>
> .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: 0x56b49514d390>
> 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: 0x56b4951351e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b4951351e0>
> .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: 0x56b4951351e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x56b4951351e0>
> .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: 0x56b4951351e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x56b4951351e0>
> .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: 0x56b4951351e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x56b4951351e0>
> .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: 0x56b4951351e0>
> 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: 0x56b4949ba2a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x56b4949ba2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b4949ba2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b4949ba2a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile311f8c25172f47" "BufferedMatrixFile311f8c60ea1bd1"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile311f8c25172f47" "BufferedMatrixFile311f8c60ea1bd1"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b495bbdda0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b495bbdda0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56b495bbdda0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56b495bbdda0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x56b495bbdda0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x56b495bbdda0>
> .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: 0x56b495e52470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56b495e52470>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x56b495e52470>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x56b495e52470>
> 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: 0x56b495033410>
> .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: 0x56b495033410>
> rm(P)
>
> proc.time()
user system elapsed
0.334 0.044 0.423
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 (2025-06-13) -- "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.
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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
0.298 0.062 0.381