Ben Bolstad
| Snapshot Date: 2025-08-20 13:45 -0400 (Wed, 20 Aug 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 2025-08-21 12:03 -0400 (Thu, 21 Aug 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" | 4819 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4597 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4539 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4536 |
| 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 251/2318 | 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: 2025-08-20 20:44:45 -0400 (Wed, 20 Aug 2025) |
| EndedAt: 2025-08-20 20:45:09 -0400 (Wed, 20 Aug 2025) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.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
0.277 0.144 0.285
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] "Wed Aug 20 20:45:00 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] "Wed Aug 20 20:45:00 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: 0x5687ea986c20>
>
>
>
> 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] "Wed Aug 20 20:45:00 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] "Wed Aug 20 20:45:00 2025"
>
> ColMode(tmp2)
<pointer: 0x5687ea986c20>
>
>
>
> ### 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,] 98.8917100 1.1229147 -0.0473928 0.6615786
[2,] 1.7801727 1.1476277 -0.5162766 0.6083335
[3,] 0.9402579 -0.1355675 -0.8059412 0.2250971
[4,] -0.2336726 0.8297869 -0.5180689 -1.1797234
> 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,] 98.8917100 1.1229147 0.0473928 0.6615786
[2,] 1.7801727 1.1476277 0.5162766 0.6083335
[3,] 0.9402579 0.1355675 0.8059412 0.2250971
[4,] 0.2336726 0.8297869 0.5180689 1.1797234
> 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,] 9.944431 1.0596767 0.2176989 0.8133748
[2,] 1.334231 1.0712739 0.7185239 0.7799574
[3,] 0.969669 0.3681949 0.8977423 0.4744440
[4,] 0.483397 0.9109264 0.7197701 1.0861507
>
> 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,] 223.33602 36.71968 27.22438 33.79533
[2,] 40.12248 36.86037 32.70152 33.40791
[3,] 35.63695 28.81752 34.78336 29.96954
[4,] 30.06764 34.93905 32.71577 37.04123
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5687ea7fb140>
> exp(tmp5)
<pointer: 0x5687ea7fb140>
> log(tmp5,2)
<pointer: 0x5687ea7fb140>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 464.8447
> Min(tmp5)
[1] 54.50696
> mean(tmp5)
[1] 73.56654
> Sum(tmp5)
[1] 14713.31
> Var(tmp5)
[1] 842.4164
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.91554 70.73914 69.94033 71.98394 70.70707 68.59803 70.16493 74.54828
[9] 71.91980 74.14840
> rowSums(tmp5)
[1] 1858.311 1414.783 1398.807 1439.679 1414.141 1371.961 1403.299 1490.966
[9] 1438.396 1482.968
> rowVars(tmp5)
[1] 7729.52606 74.13267 50.83982 52.85655 46.01618 103.23408
[7] 70.43827 59.09310 76.14059 90.94720
> rowSd(tmp5)
[1] 87.917723 8.610033 7.130205 7.270251 6.783523 10.160417 8.392751
[8] 7.687204 8.725857 9.536624
> rowMax(tmp5)
[1] 464.84467 84.83432 82.67798 84.01572 83.31170 91.16741 89.21851
[8] 89.46211 89.18269 97.87163
> rowMin(tmp5)
[1] 56.66398 56.19339 59.97988 60.06019 55.46154 54.50696 55.93560 57.86274
[9] 55.97430 56.73499
>
> colMeans(tmp5)
[1] 110.77433 71.54822 69.29168 74.39549 72.68308 72.80000 71.03391
[8] 67.84249 71.08579 70.26169 68.42197 70.74534 74.73082 71.76397
[15] 69.02089 70.22762 73.71809 73.40591 77.19349 70.38610
> colSums(tmp5)
[1] 1107.7433 715.4822 692.9168 743.9549 726.8308 728.0000 710.3391
[8] 678.4249 710.8579 702.6169 684.2197 707.4534 747.3082 717.6397
[15] 690.2089 702.2762 737.1809 734.0591 771.9349 703.8610
> colVars(tmp5)
[1] 15536.63470 73.58008 65.10567 79.39012 52.91972 55.15304
[7] 73.66185 32.04295 193.06846 90.83326 50.99261 63.99573
[13] 18.65806 107.39452 38.91342 69.88906 47.51156 126.86974
[19] 43.41543 74.24484
> colSd(tmp5)
[1] 124.646038 8.577883 8.068809 8.910113 7.274594 7.426509
[7] 8.582648 5.660649 13.894908 9.530648 7.140911 7.999733
[13] 4.319498 10.363133 6.238063 8.359967 6.892863 11.263647
[19] 6.589038 8.616544
> colMax(tmp5)
[1] 464.84467 80.96509 79.82065 87.12762 80.88288 83.72920 82.78455
[8] 79.72901 97.87163 83.31170 80.74053 80.33081 82.54693 83.42513
[15] 78.38700 84.83432 81.83857 89.46211 91.16741 84.01572
> colMin(tmp5)
[1] 56.16202 54.50696 54.68189 60.03847 61.02392 59.30608 55.93560 60.16131
[9] 56.19339 56.73499 56.88460 55.97430 69.96635 55.46154 59.25363 57.86274
[17] 63.31435 62.13307 69.16167 59.43337
>
>
> ### 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] 92.91554 70.73914 69.94033 71.98394 70.70707 68.59803 70.16493 74.54828
[9] NA 74.14840
> rowSums(tmp5)
[1] 1858.311 1414.783 1398.807 1439.679 1414.141 1371.961 1403.299 1490.966
[9] NA 1482.968
> rowVars(tmp5)
[1] 7729.52606 74.13267 50.83982 52.85655 46.01618 103.23408
[7] 70.43827 59.09310 76.80431 90.94720
> rowSd(tmp5)
[1] 87.917723 8.610033 7.130205 7.270251 6.783523 10.160417 8.392751
[8] 7.687204 8.763807 9.536624
> rowMax(tmp5)
[1] 464.84467 84.83432 82.67798 84.01572 83.31170 91.16741 89.21851
[8] 89.46211 NA 97.87163
> rowMin(tmp5)
[1] 56.66398 56.19339 59.97988 60.06019 55.46154 54.50696 55.93560 57.86274
[9] NA 56.73499
>
> colMeans(tmp5)
[1] 110.77433 71.54822 69.29168 74.39549 72.68308 72.80000 71.03391
[8] NA 71.08579 70.26169 68.42197 70.74534 74.73082 71.76397
[15] 69.02089 70.22762 73.71809 73.40591 77.19349 70.38610
> colSums(tmp5)
[1] 1107.7433 715.4822 692.9168 743.9549 726.8308 728.0000 710.3391
[8] NA 710.8579 702.6169 684.2197 707.4534 747.3082 717.6397
[15] 690.2089 702.2762 737.1809 734.0591 771.9349 703.8610
> colVars(tmp5)
[1] 15536.63470 73.58008 65.10567 79.39012 52.91972 55.15304
[7] 73.66185 NA 193.06846 90.83326 50.99261 63.99573
[13] 18.65806 107.39452 38.91342 69.88906 47.51156 126.86974
[19] 43.41543 74.24484
> colSd(tmp5)
[1] 124.646038 8.577883 8.068809 8.910113 7.274594 7.426509
[7] 8.582648 NA 13.894908 9.530648 7.140911 7.999733
[13] 4.319498 10.363133 6.238063 8.359967 6.892863 11.263647
[19] 6.589038 8.616544
> colMax(tmp5)
[1] 464.84467 80.96509 79.82065 87.12762 80.88288 83.72920 82.78455
[8] NA 97.87163 83.31170 80.74053 80.33081 82.54693 83.42513
[15] 78.38700 84.83432 81.83857 89.46211 91.16741 84.01572
> colMin(tmp5)
[1] 56.16202 54.50696 54.68189 60.03847 61.02392 59.30608 55.93560 NA
[9] 56.19339 56.73499 56.88460 55.97430 69.96635 55.46154 59.25363 57.86274
[17] 63.31435 62.13307 69.16167 59.43337
>
> Max(tmp5,na.rm=TRUE)
[1] 464.8447
> Min(tmp5,na.rm=TRUE)
[1] 54.50696
> mean(tmp5,na.rm=TRUE)
[1] 73.53558
> Sum(tmp5,na.rm=TRUE)
[1] 14633.58
> Var(tmp5,na.rm=TRUE)
[1] 846.4783
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.91554 70.73914 69.94033 71.98394 70.70707 68.59803 70.16493 74.54828
[9] 71.50878 74.14840
> rowSums(tmp5,na.rm=TRUE)
[1] 1858.311 1414.783 1398.807 1439.679 1414.141 1371.961 1403.299 1490.966
[9] 1358.667 1482.968
> rowVars(tmp5,na.rm=TRUE)
[1] 7729.52606 74.13267 50.83982 52.85655 46.01618 103.23408
[7] 70.43827 59.09310 76.80431 90.94720
> rowSd(tmp5,na.rm=TRUE)
[1] 87.917723 8.610033 7.130205 7.270251 6.783523 10.160417 8.392751
[8] 7.687204 8.763807 9.536624
> rowMax(tmp5,na.rm=TRUE)
[1] 464.84467 84.83432 82.67798 84.01572 83.31170 91.16741 89.21851
[8] 89.46211 89.18269 97.87163
> rowMin(tmp5,na.rm=TRUE)
[1] 56.66398 56.19339 59.97988 60.06019 55.46154 54.50696 55.93560 57.86274
[9] 55.97430 56.73499
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.77433 71.54822 69.29168 74.39549 72.68308 72.80000 71.03391
[8] 66.52177 71.08579 70.26169 68.42197 70.74534 74.73082 71.76397
[15] 69.02089 70.22762 73.71809 73.40591 77.19349 70.38610
> colSums(tmp5,na.rm=TRUE)
[1] 1107.7433 715.4822 692.9168 743.9549 726.8308 728.0000 710.3391
[8] 598.6959 710.8579 702.6169 684.2197 707.4534 747.3082 717.6397
[15] 690.2089 702.2762 737.1809 734.0591 771.9349 703.8610
> colVars(tmp5,na.rm=TRUE)
[1] 15536.63470 73.58008 65.10567 79.39012 52.91972 55.15304
[7] 73.66185 16.42478 193.06846 90.83326 50.99261 63.99573
[13] 18.65806 107.39452 38.91342 69.88906 47.51156 126.86974
[19] 43.41543 74.24484
> colSd(tmp5,na.rm=TRUE)
[1] 124.646038 8.577883 8.068809 8.910113 7.274594 7.426509
[7] 8.582648 4.052750 13.894908 9.530648 7.140911 7.999733
[13] 4.319498 10.363133 6.238063 8.359967 6.892863 11.263647
[19] 6.589038 8.616544
> colMax(tmp5,na.rm=TRUE)
[1] 464.84467 80.96509 79.82065 87.12762 80.88288 83.72920 82.78455
[8] 72.65138 97.87163 83.31170 80.74053 80.33081 82.54693 83.42513
[15] 78.38700 84.83432 81.83857 89.46211 91.16741 84.01572
> colMin(tmp5,na.rm=TRUE)
[1] 56.16202 54.50696 54.68189 60.03847 61.02392 59.30608 55.93560 60.16131
[9] 56.19339 56.73499 56.88460 55.97430 69.96635 55.46154 59.25363 57.86274
[17] 63.31435 62.13307 69.16167 59.43337
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.91554 70.73914 69.94033 71.98394 70.70707 68.59803 70.16493 74.54828
[9] NaN 74.14840
> rowSums(tmp5,na.rm=TRUE)
[1] 1858.311 1414.783 1398.807 1439.679 1414.141 1371.961 1403.299 1490.966
[9] 0.000 1482.968
> rowVars(tmp5,na.rm=TRUE)
[1] 7729.52606 74.13267 50.83982 52.85655 46.01618 103.23408
[7] 70.43827 59.09310 NA 90.94720
> rowSd(tmp5,na.rm=TRUE)
[1] 87.917723 8.610033 7.130205 7.270251 6.783523 10.160417 8.392751
[8] 7.687204 NA 9.536624
> rowMax(tmp5,na.rm=TRUE)
[1] 464.84467 84.83432 82.67798 84.01572 83.31170 91.16741 89.21851
[8] 89.46211 NA 97.87163
> rowMin(tmp5,na.rm=TRUE)
[1] 56.66398 56.19339 59.97988 60.06019 55.46154 54.50696 55.93560 57.86274
[9] NA 56.73499
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.24948 71.33771 69.07181 73.14015 73.89776 72.68353 70.73669
[8] NaN 70.66003 71.31768 69.04506 72.38656 74.99914 73.10575
[15] 69.01763 70.38438 72.81582 71.65294 77.40674 69.55971
> colSums(tmp5,na.rm=TRUE)
[1] 1037.2453 642.0394 621.6463 658.2613 665.0798 654.1518 636.6302
[8] 0.0000 635.9403 641.8592 621.4055 651.4791 674.9922 657.9518
[15] 621.1587 633.4594 655.3424 644.8764 696.6607 626.0374
> colVars(tmp5,na.rm=TRUE)
[1] 17253.41066 82.27904 72.70003 71.58515 42.93609 61.89457
[7] 81.87574 NA 215.16273 89.64241 52.99902 41.69192
[13] 20.18039 100.56448 43.77748 78.34873 44.29188 108.15807
[19] 48.33075 75.84269
> colSd(tmp5,na.rm=TRUE)
[1] 131.352239 9.070780 8.526431 8.460801 6.552563 7.867310
[7] 9.048521 NA 14.668426 9.467968 7.280043 6.456928
[13] 4.492258 10.028184 6.616455 8.851482 6.655215 10.399907
[19] 6.952032 8.708771
> colMax(tmp5,na.rm=TRUE)
[1] 464.84467 80.96509 79.82065 87.12762 80.88288 83.72920 82.78455
[8] -Inf 97.87163 83.31170 80.74053 80.33081 82.54693 83.42513
[15] 78.38700 84.83432 81.75864 89.46211 91.16741 84.01572
> colMin(tmp5,na.rm=TRUE)
[1] 56.16202 54.50696 54.68189 60.03847 61.02392 59.30608 55.93560 Inf
[9] 56.19339 56.73499 56.88460 61.00120 69.96635 55.46154 59.25363 57.86274
[17] 63.31435 62.13307 69.16167 59.43337
>
>
>
>
> 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] 225.1930 241.2474 174.6686 179.3102 243.4641 203.8344 142.1739 183.0842
[9] 364.6568 264.7850
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 225.1930 241.2474 174.6686 179.3102 243.4641 203.8344 142.1739 183.0842
[9] 364.6568 264.7850
>
>
>
> 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] -8.526513e-14 2.842171e-14 0.000000e+00 8.526513e-14 -2.842171e-13
[6] 3.979039e-13 0.000000e+00 8.526513e-14 1.136868e-13 -5.684342e-14
[11] -8.526513e-14 2.842171e-14 0.000000e+00 -1.421085e-14 -2.842171e-14
[16] 5.684342e-14 1.421085e-14 2.842171e-14 -8.526513e-14 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 7
8 15
9 2
7 3
3 7
7 19
7 6
5 16
2 10
7 20
5 8
7 15
10 15
10 9
3 16
3 6
3 3
2 18
10 3
4 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] 2.376646
> Min(tmp)
[1] -2.443367
> mean(tmp)
[1] 0.06908425
> Sum(tmp)
[1] 6.908425
> Var(tmp)
[1] 0.7428876
>
> rowMeans(tmp)
[1] 0.06908425
> rowSums(tmp)
[1] 6.908425
> rowVars(tmp)
[1] 0.7428876
> rowSd(tmp)
[1] 0.8619093
> rowMax(tmp)
[1] 2.376646
> rowMin(tmp)
[1] -2.443367
>
> colMeans(tmp)
[1] 0.250705354 -0.175937513 2.376645673 -0.115719909 0.517667500
[6] -0.561917166 -0.278666582 -0.939369950 -0.433596706 0.434113419
[11] -0.930994047 0.004558733 1.308752340 -0.428442679 -1.300625589
[16] -1.589148121 -0.297761688 -0.040962888 0.765015911 -0.056522682
[21] 1.461051571 -0.990929727 -0.591111589 0.476028354 1.455280207
[26] -0.805430038 0.441393844 0.386158366 -0.458302168 -0.599819090
[31] -0.428613466 0.821836677 0.746054755 -0.730468123 -0.247850027
[36] 0.913545301 0.856132694 -0.547003659 0.903876706 0.732684270
[41] 1.128716700 -2.443366843 -1.628133799 -0.607527682 0.718387400
[46] 1.660036039 -0.450368257 -0.687271002 -0.146463802 0.797864800
[51] -0.515291788 0.718682096 0.306104211 -0.072678220 -1.608980104
[56] 0.698215568 -0.120050461 0.188907672 -0.468382227 -0.387561795
[61] -0.429655215 0.611461556 0.530510352 1.087912522 -0.439944779
[66] 0.320015561 0.622359928 -0.138849581 1.262658679 -0.868456640
[71] -0.422100153 -1.320329968 0.243155170 0.554099213 0.003382200
[76] 0.016510981 -0.571606756 -0.585257030 -1.630712518 0.285135032
[81] 1.015657361 1.619762940 -0.129154165 0.784232122 0.665269622
[86] 1.329000023 -0.110711942 1.495615990 -0.194588856 0.416314601
[91] 1.291151358 -0.435950772 -1.241943470 0.156321915 0.106370772
[96] -1.220510102 0.483819158 1.018018267 0.609569785 0.736745225
> colSums(tmp)
[1] 0.250705354 -0.175937513 2.376645673 -0.115719909 0.517667500
[6] -0.561917166 -0.278666582 -0.939369950 -0.433596706 0.434113419
[11] -0.930994047 0.004558733 1.308752340 -0.428442679 -1.300625589
[16] -1.589148121 -0.297761688 -0.040962888 0.765015911 -0.056522682
[21] 1.461051571 -0.990929727 -0.591111589 0.476028354 1.455280207
[26] -0.805430038 0.441393844 0.386158366 -0.458302168 -0.599819090
[31] -0.428613466 0.821836677 0.746054755 -0.730468123 -0.247850027
[36] 0.913545301 0.856132694 -0.547003659 0.903876706 0.732684270
[41] 1.128716700 -2.443366843 -1.628133799 -0.607527682 0.718387400
[46] 1.660036039 -0.450368257 -0.687271002 -0.146463802 0.797864800
[51] -0.515291788 0.718682096 0.306104211 -0.072678220 -1.608980104
[56] 0.698215568 -0.120050461 0.188907672 -0.468382227 -0.387561795
[61] -0.429655215 0.611461556 0.530510352 1.087912522 -0.439944779
[66] 0.320015561 0.622359928 -0.138849581 1.262658679 -0.868456640
[71] -0.422100153 -1.320329968 0.243155170 0.554099213 0.003382200
[76] 0.016510981 -0.571606756 -0.585257030 -1.630712518 0.285135032
[81] 1.015657361 1.619762940 -0.129154165 0.784232122 0.665269622
[86] 1.329000023 -0.110711942 1.495615990 -0.194588856 0.416314601
[91] 1.291151358 -0.435950772 -1.241943470 0.156321915 0.106370772
[96] -1.220510102 0.483819158 1.018018267 0.609569785 0.736745225
> 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] 0.250705354 -0.175937513 2.376645673 -0.115719909 0.517667500
[6] -0.561917166 -0.278666582 -0.939369950 -0.433596706 0.434113419
[11] -0.930994047 0.004558733 1.308752340 -0.428442679 -1.300625589
[16] -1.589148121 -0.297761688 -0.040962888 0.765015911 -0.056522682
[21] 1.461051571 -0.990929727 -0.591111589 0.476028354 1.455280207
[26] -0.805430038 0.441393844 0.386158366 -0.458302168 -0.599819090
[31] -0.428613466 0.821836677 0.746054755 -0.730468123 -0.247850027
[36] 0.913545301 0.856132694 -0.547003659 0.903876706 0.732684270
[41] 1.128716700 -2.443366843 -1.628133799 -0.607527682 0.718387400
[46] 1.660036039 -0.450368257 -0.687271002 -0.146463802 0.797864800
[51] -0.515291788 0.718682096 0.306104211 -0.072678220 -1.608980104
[56] 0.698215568 -0.120050461 0.188907672 -0.468382227 -0.387561795
[61] -0.429655215 0.611461556 0.530510352 1.087912522 -0.439944779
[66] 0.320015561 0.622359928 -0.138849581 1.262658679 -0.868456640
[71] -0.422100153 -1.320329968 0.243155170 0.554099213 0.003382200
[76] 0.016510981 -0.571606756 -0.585257030 -1.630712518 0.285135032
[81] 1.015657361 1.619762940 -0.129154165 0.784232122 0.665269622
[86] 1.329000023 -0.110711942 1.495615990 -0.194588856 0.416314601
[91] 1.291151358 -0.435950772 -1.241943470 0.156321915 0.106370772
[96] -1.220510102 0.483819158 1.018018267 0.609569785 0.736745225
> colMin(tmp)
[1] 0.250705354 -0.175937513 2.376645673 -0.115719909 0.517667500
[6] -0.561917166 -0.278666582 -0.939369950 -0.433596706 0.434113419
[11] -0.930994047 0.004558733 1.308752340 -0.428442679 -1.300625589
[16] -1.589148121 -0.297761688 -0.040962888 0.765015911 -0.056522682
[21] 1.461051571 -0.990929727 -0.591111589 0.476028354 1.455280207
[26] -0.805430038 0.441393844 0.386158366 -0.458302168 -0.599819090
[31] -0.428613466 0.821836677 0.746054755 -0.730468123 -0.247850027
[36] 0.913545301 0.856132694 -0.547003659 0.903876706 0.732684270
[41] 1.128716700 -2.443366843 -1.628133799 -0.607527682 0.718387400
[46] 1.660036039 -0.450368257 -0.687271002 -0.146463802 0.797864800
[51] -0.515291788 0.718682096 0.306104211 -0.072678220 -1.608980104
[56] 0.698215568 -0.120050461 0.188907672 -0.468382227 -0.387561795
[61] -0.429655215 0.611461556 0.530510352 1.087912522 -0.439944779
[66] 0.320015561 0.622359928 -0.138849581 1.262658679 -0.868456640
[71] -0.422100153 -1.320329968 0.243155170 0.554099213 0.003382200
[76] 0.016510981 -0.571606756 -0.585257030 -1.630712518 0.285135032
[81] 1.015657361 1.619762940 -0.129154165 0.784232122 0.665269622
[86] 1.329000023 -0.110711942 1.495615990 -0.194588856 0.416314601
[91] 1.291151358 -0.435950772 -1.241943470 0.156321915 0.106370772
[96] -1.220510102 0.483819158 1.018018267 0.609569785 0.736745225
> colMedians(tmp)
[1] 0.250705354 -0.175937513 2.376645673 -0.115719909 0.517667500
[6] -0.561917166 -0.278666582 -0.939369950 -0.433596706 0.434113419
[11] -0.930994047 0.004558733 1.308752340 -0.428442679 -1.300625589
[16] -1.589148121 -0.297761688 -0.040962888 0.765015911 -0.056522682
[21] 1.461051571 -0.990929727 -0.591111589 0.476028354 1.455280207
[26] -0.805430038 0.441393844 0.386158366 -0.458302168 -0.599819090
[31] -0.428613466 0.821836677 0.746054755 -0.730468123 -0.247850027
[36] 0.913545301 0.856132694 -0.547003659 0.903876706 0.732684270
[41] 1.128716700 -2.443366843 -1.628133799 -0.607527682 0.718387400
[46] 1.660036039 -0.450368257 -0.687271002 -0.146463802 0.797864800
[51] -0.515291788 0.718682096 0.306104211 -0.072678220 -1.608980104
[56] 0.698215568 -0.120050461 0.188907672 -0.468382227 -0.387561795
[61] -0.429655215 0.611461556 0.530510352 1.087912522 -0.439944779
[66] 0.320015561 0.622359928 -0.138849581 1.262658679 -0.868456640
[71] -0.422100153 -1.320329968 0.243155170 0.554099213 0.003382200
[76] 0.016510981 -0.571606756 -0.585257030 -1.630712518 0.285135032
[81] 1.015657361 1.619762940 -0.129154165 0.784232122 0.665269622
[86] 1.329000023 -0.110711942 1.495615990 -0.194588856 0.416314601
[91] 1.291151358 -0.435950772 -1.241943470 0.156321915 0.106370772
[96] -1.220510102 0.483819158 1.018018267 0.609569785 0.736745225
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.2507054 -0.1759375 2.376646 -0.1157199 0.5176675 -0.5619172 -0.2786666
[2,] 0.2507054 -0.1759375 2.376646 -0.1157199 0.5176675 -0.5619172 -0.2786666
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.93937 -0.4335967 0.4341134 -0.930994 0.004558733 1.308752 -0.4284427
[2,] -0.93937 -0.4335967 0.4341134 -0.930994 0.004558733 1.308752 -0.4284427
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.300626 -1.589148 -0.2977617 -0.04096289 0.7650159 -0.05652268 1.461052
[2,] -1.300626 -1.589148 -0.2977617 -0.04096289 0.7650159 -0.05652268 1.461052
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.9909297 -0.5911116 0.4760284 1.45528 -0.80543 0.4413938 0.3861584
[2,] -0.9909297 -0.5911116 0.4760284 1.45528 -0.80543 0.4413938 0.3861584
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.4583022 -0.5998191 -0.4286135 0.8218367 0.7460548 -0.7304681 -0.24785
[2,] -0.4583022 -0.5998191 -0.4286135 0.8218367 0.7460548 -0.7304681 -0.24785
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.9135453 0.8561327 -0.5470037 0.9038767 0.7326843 1.128717 -2.443367
[2,] 0.9135453 0.8561327 -0.5470037 0.9038767 0.7326843 1.128717 -2.443367
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.628134 -0.6075277 0.7183874 1.660036 -0.4503683 -0.687271 -0.1464638
[2,] -1.628134 -0.6075277 0.7183874 1.660036 -0.4503683 -0.687271 -0.1464638
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.7978648 -0.5152918 0.7186821 0.3061042 -0.07267822 -1.60898 0.6982156
[2,] 0.7978648 -0.5152918 0.7186821 0.3061042 -0.07267822 -1.60898 0.6982156
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.1200505 0.1889077 -0.4683822 -0.3875618 -0.4296552 0.6114616 0.5305104
[2,] -0.1200505 0.1889077 -0.4683822 -0.3875618 -0.4296552 0.6114616 0.5305104
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.087913 -0.4399448 0.3200156 0.6223599 -0.1388496 1.262659 -0.8684566
[2,] 1.087913 -0.4399448 0.3200156 0.6223599 -0.1388496 1.262659 -0.8684566
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.4221002 -1.32033 0.2431552 0.5540992 0.0033822 0.01651098 -0.5716068
[2,] -0.4221002 -1.32033 0.2431552 0.5540992 0.0033822 0.01651098 -0.5716068
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.585257 -1.630713 0.285135 1.015657 1.619763 -0.1291542 0.7842321
[2,] -0.585257 -1.630713 0.285135 1.015657 1.619763 -0.1291542 0.7842321
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.6652696 1.329 -0.1107119 1.495616 -0.1945889 0.4163146 1.291151
[2,] 0.6652696 1.329 -0.1107119 1.495616 -0.1945889 0.4163146 1.291151
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.4359508 -1.241943 0.1563219 0.1063708 -1.22051 0.4838192 1.018018
[2,] -0.4359508 -1.241943 0.1563219 0.1063708 -1.22051 0.4838192 1.018018
[,99] [,100]
[1,] 0.6095698 0.7367452
[2,] 0.6095698 0.7367452
>
>
> Max(tmp2)
[1] 2.105913
> Min(tmp2)
[1] -2.92497
> mean(tmp2)
[1] -0.06098094
> Sum(tmp2)
[1] -6.098094
> Var(tmp2)
[1] 1.049973
>
> rowMeans(tmp2)
[1] 0.493481654 -0.315347617 -0.881037281 0.263971340 0.671221645
[6] -0.112153989 -0.741063692 0.508692801 -0.890523887 1.141137984
[11] -0.481908952 0.096442349 -1.635154999 -1.417934207 -0.227244407
[16] 0.353917714 0.505454050 -0.925027061 1.222601180 0.281100911
[21] 0.065169366 0.074215265 0.292493668 -0.451177824 0.560771690
[26] 0.489671118 -0.680209878 0.892626673 -0.192588356 0.055926783
[31] 1.013825031 0.612085321 -0.841787748 0.755860508 -0.632496017
[36] -0.209488445 -1.787500327 0.818627662 0.606822057 1.032446108
[41] -0.027477483 0.235040438 -1.479294609 -0.149495546 -0.873720503
[46] 0.841638037 -0.519068905 -2.341137542 -1.269015366 -0.275945909
[51] 2.105912822 0.136137351 -0.337154733 -0.093161376 1.200500058
[56] 0.286901040 -0.311336618 -1.112643429 -0.606289826 1.576992162
[61] 1.134813183 -2.410300802 -2.164665300 -2.924969761 -1.606643936
[66] 1.032971505 -1.623589241 -2.330419340 0.147316988 1.062366952
[71] 0.647170290 0.294255302 0.157017469 1.074629934 -1.566548258
[76] 0.790843429 0.126495349 1.888427282 2.025509147 -1.406750151
[81] 0.182271488 -0.514665113 -0.129830026 -0.701963073 1.162558354
[86] 1.027619542 0.424475977 -0.310476661 -0.183742668 0.644178661
[91] -0.005864958 0.430044960 1.006022859 -1.788976437 -0.215337190
[96] -0.202561961 -0.731733302 1.694448278 -0.245458874 0.639667654
> rowSums(tmp2)
[1] 0.493481654 -0.315347617 -0.881037281 0.263971340 0.671221645
[6] -0.112153989 -0.741063692 0.508692801 -0.890523887 1.141137984
[11] -0.481908952 0.096442349 -1.635154999 -1.417934207 -0.227244407
[16] 0.353917714 0.505454050 -0.925027061 1.222601180 0.281100911
[21] 0.065169366 0.074215265 0.292493668 -0.451177824 0.560771690
[26] 0.489671118 -0.680209878 0.892626673 -0.192588356 0.055926783
[31] 1.013825031 0.612085321 -0.841787748 0.755860508 -0.632496017
[36] -0.209488445 -1.787500327 0.818627662 0.606822057 1.032446108
[41] -0.027477483 0.235040438 -1.479294609 -0.149495546 -0.873720503
[46] 0.841638037 -0.519068905 -2.341137542 -1.269015366 -0.275945909
[51] 2.105912822 0.136137351 -0.337154733 -0.093161376 1.200500058
[56] 0.286901040 -0.311336618 -1.112643429 -0.606289826 1.576992162
[61] 1.134813183 -2.410300802 -2.164665300 -2.924969761 -1.606643936
[66] 1.032971505 -1.623589241 -2.330419340 0.147316988 1.062366952
[71] 0.647170290 0.294255302 0.157017469 1.074629934 -1.566548258
[76] 0.790843429 0.126495349 1.888427282 2.025509147 -1.406750151
[81] 0.182271488 -0.514665113 -0.129830026 -0.701963073 1.162558354
[86] 1.027619542 0.424475977 -0.310476661 -0.183742668 0.644178661
[91] -0.005864958 0.430044960 1.006022859 -1.788976437 -0.215337190
[96] -0.202561961 -0.731733302 1.694448278 -0.245458874 0.639667654
> 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] 0.493481654 -0.315347617 -0.881037281 0.263971340 0.671221645
[6] -0.112153989 -0.741063692 0.508692801 -0.890523887 1.141137984
[11] -0.481908952 0.096442349 -1.635154999 -1.417934207 -0.227244407
[16] 0.353917714 0.505454050 -0.925027061 1.222601180 0.281100911
[21] 0.065169366 0.074215265 0.292493668 -0.451177824 0.560771690
[26] 0.489671118 -0.680209878 0.892626673 -0.192588356 0.055926783
[31] 1.013825031 0.612085321 -0.841787748 0.755860508 -0.632496017
[36] -0.209488445 -1.787500327 0.818627662 0.606822057 1.032446108
[41] -0.027477483 0.235040438 -1.479294609 -0.149495546 -0.873720503
[46] 0.841638037 -0.519068905 -2.341137542 -1.269015366 -0.275945909
[51] 2.105912822 0.136137351 -0.337154733 -0.093161376 1.200500058
[56] 0.286901040 -0.311336618 -1.112643429 -0.606289826 1.576992162
[61] 1.134813183 -2.410300802 -2.164665300 -2.924969761 -1.606643936
[66] 1.032971505 -1.623589241 -2.330419340 0.147316988 1.062366952
[71] 0.647170290 0.294255302 0.157017469 1.074629934 -1.566548258
[76] 0.790843429 0.126495349 1.888427282 2.025509147 -1.406750151
[81] 0.182271488 -0.514665113 -0.129830026 -0.701963073 1.162558354
[86] 1.027619542 0.424475977 -0.310476661 -0.183742668 0.644178661
[91] -0.005864958 0.430044960 1.006022859 -1.788976437 -0.215337190
[96] -0.202561961 -0.731733302 1.694448278 -0.245458874 0.639667654
> rowMin(tmp2)
[1] 0.493481654 -0.315347617 -0.881037281 0.263971340 0.671221645
[6] -0.112153989 -0.741063692 0.508692801 -0.890523887 1.141137984
[11] -0.481908952 0.096442349 -1.635154999 -1.417934207 -0.227244407
[16] 0.353917714 0.505454050 -0.925027061 1.222601180 0.281100911
[21] 0.065169366 0.074215265 0.292493668 -0.451177824 0.560771690
[26] 0.489671118 -0.680209878 0.892626673 -0.192588356 0.055926783
[31] 1.013825031 0.612085321 -0.841787748 0.755860508 -0.632496017
[36] -0.209488445 -1.787500327 0.818627662 0.606822057 1.032446108
[41] -0.027477483 0.235040438 -1.479294609 -0.149495546 -0.873720503
[46] 0.841638037 -0.519068905 -2.341137542 -1.269015366 -0.275945909
[51] 2.105912822 0.136137351 -0.337154733 -0.093161376 1.200500058
[56] 0.286901040 -0.311336618 -1.112643429 -0.606289826 1.576992162
[61] 1.134813183 -2.410300802 -2.164665300 -2.924969761 -1.606643936
[66] 1.032971505 -1.623589241 -2.330419340 0.147316988 1.062366952
[71] 0.647170290 0.294255302 0.157017469 1.074629934 -1.566548258
[76] 0.790843429 0.126495349 1.888427282 2.025509147 -1.406750151
[81] 0.182271488 -0.514665113 -0.129830026 -0.701963073 1.162558354
[86] 1.027619542 0.424475977 -0.310476661 -0.183742668 0.644178661
[91] -0.005864958 0.430044960 1.006022859 -1.788976437 -0.215337190
[96] -0.202561961 -0.731733302 1.694448278 -0.245458874 0.639667654
>
> colMeans(tmp2)
[1] -0.06098094
> colSums(tmp2)
[1] -6.098094
> colVars(tmp2)
[1] 1.049973
> colSd(tmp2)
[1] 1.024682
> colMax(tmp2)
[1] 2.105913
> colMin(tmp2)
[1] -2.92497
> colMedians(tmp2)
[1] 0.06054807
> colRanges(tmp2)
[,1]
[1,] -2.924970
[2,] 2.105913
>
> 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] -1.8433734 0.9495175 0.1744588 2.1653910 1.0181354 7.9053214
[7] -1.1987436 -1.8572734 -7.6711688 1.6661633
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0154142
[2,] -0.7031244
[3,] -0.0669944
[4,] 0.1611697
[5,] 0.6148831
>
> rowApply(tmp,sum)
[1] -4.9682491 -0.1247714 -0.6019382 -1.6780549 0.7324054 -1.3228675
[7] 1.6764142 4.7364369 1.5063311 1.3527220
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 3 4 2 7 4 7 4 8 4
[2,] 9 4 8 9 1 2 6 7 9 2
[3,] 7 1 10 6 6 1 5 3 4 9
[4,] 3 8 7 7 9 10 4 6 5 7
[5,] 1 10 5 5 5 3 9 9 1 6
[6,] 10 9 9 3 10 9 1 8 10 10
[7,] 4 6 2 1 3 5 10 10 7 3
[8,] 5 7 1 10 2 7 8 2 2 5
[9,] 2 2 3 4 8 6 2 1 6 1
[10,] 6 5 6 8 4 8 3 5 3 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.2460725 1.5232529 -0.5198162 1.6324397 -0.1600375 2.2402276
[7] -0.1451117 0.2662816 1.4116585 -1.5330696 -0.7440861 0.9726216
[13] -3.0770522 0.8204649 -0.1440756 -0.2708017 0.1992389 -2.7806756
[19] 0.1986708 -1.0243825
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9644344
[2,] -0.6355363
[3,] -0.3663766
[4,] 0.2755795
[5,] 2.4446953
>
> rowApply(tmp,sum)
[1] -3.7089733 0.7594751 1.2323349 0.7854544 -0.4486159
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 20 5 1 14
[2,] 5 14 2 16 20
[3,] 13 11 15 4 3
[4,] 12 17 4 18 16
[5,] 6 4 16 12 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.3663766 -0.6420781 0.06428481 0.02566583 -0.3698509 0.2722031
[2,] 2.4446953 0.6632251 0.58467007 0.88332760 -1.1163184 0.8363968
[3,] -0.6355363 -0.9700544 0.73590327 -0.71773373 0.9294862 0.1928100
[4,] -1.9644344 0.6355532 -0.85142983 1.04640711 0.2492855 0.2741360
[5,] 0.2755795 1.8366071 -1.05324454 0.39477289 0.1473602 0.6646817
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.54121402 0.2117899 0.2927039 0.4873631 0.7130402 -0.08824722
[2,] 1.07601310 0.6418962 0.6955351 0.2076656 -0.3463667 0.11605623
[3,] -0.07341001 -0.1616078 -0.1299746 -0.1887159 -2.4765872 1.24705680
[4,] 0.37028857 -0.3119416 -0.8234534 -0.9594690 1.1215095 0.05856291
[5,] 0.02321062 -0.1138551 1.3768476 -1.0799134 0.2443182 -0.36080711
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.61063266 -0.09968643 0.1511567 -1.2281253 -0.1666057 -0.02811669
[2,] -1.74157674 -0.10879556 -2.5339579 -0.9737676 0.6561093 -1.23192464
[3,] -0.54473968 1.21896580 1.4821003 1.0347722 0.1908047 0.46445558
[4,] -1.34366058 0.14309582 0.1599480 1.2598993 0.2359464 0.09148156
[5,] -0.05770783 -0.33311474 0.5966772 -0.3635803 -0.7170159 -2.07657137
[,19] [,20]
[1,] -0.8290941 -1.1784182
[2,] 1.0187735 -1.0121814
[3,] -0.8277740 0.4621137
[4,] 0.5586237 0.8351057
[5,] 0.2781417 -0.1310023
>
>
> 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 : 652 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.9915942 -1.104467 -0.5216685 0.04806897 1.316813 -0.7039656 -1.399208
col8 col9 col10 col11 col12 col13 col14
row1 1.399338 -0.550503 -0.2031881 0.9174887 -0.2335711 -0.6528275 0.4924998
col15 col16 col17 col18 col19 col20
row1 -0.3817904 1.025972 -0.1492354 -1.115681 1.334333 1.097602
> tmp[,"col10"]
col10
row1 -0.2031881
row2 0.2102300
row3 0.6837780
row4 -0.8152872
row5 -0.6119932
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.9915942 -1.1044674 -0.5216685 0.04806897 1.3168133 -0.7039656 -1.3992080
row5 0.3845644 0.2601818 -1.5562972 3.07843960 0.7354053 -0.6160568 -0.4260069
col8 col9 col10 col11 col12 col13 col14
row1 1.3993384 -0.5505030 -0.2031881 0.9174887 -0.2335711 -0.6528275 0.4924998
row5 0.4071861 -0.6047704 -0.6119932 0.2491464 0.6543105 -0.5965215 0.3296427
col15 col16 col17 col18 col19 col20
row1 -0.3817904 1.025972 -0.1492354 -1.115681 1.334333 1.0976015
row5 -0.6385258 -1.016950 -0.5966030 2.658521 -1.704422 0.4431797
> tmp[,c("col6","col20")]
col6 col20
row1 -0.7039656 1.0976015
row2 0.8716996 -0.1875459
row3 -0.4740242 0.3952966
row4 1.0734751 -0.9801784
row5 -0.6160568 0.4431797
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.7039656 1.0976015
row5 -0.6160568 0.4431797
>
>
>
>
> 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 48.16263 52.79021 49.33961 49.01735 51.05817 106.1267 50.61687 49.8604
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.49566 51.08517 50.3601 50.16483 49.91913 48.94552 49.92465 51.07028
col17 col18 col19 col20
row1 49.56969 49.02954 50.12688 104.281
> tmp[,"col10"]
col10
row1 51.08517
row2 29.73894
row3 28.49867
row4 29.20883
row5 48.50433
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.16263 52.79021 49.33961 49.01735 51.05817 106.1267 50.61687 49.86040
row5 51.05025 51.32096 49.86683 50.26519 50.29575 103.2260 50.63496 48.75537
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.49566 51.08517 50.36010 50.16483 49.91913 48.94552 49.92465 51.07028
row5 50.24363 48.50433 51.34861 50.73142 52.70726 49.53592 50.13036 50.03322
col17 col18 col19 col20
row1 49.56969 49.02954 50.12688 104.2810
row5 49.61000 50.89352 49.47621 105.3619
> tmp[,c("col6","col20")]
col6 col20
row1 106.12671 104.28097
row2 75.04804 74.39226
row3 75.60846 75.34157
row4 73.00378 75.66806
row5 103.22597 105.36193
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.1267 104.2810
row5 103.2260 105.3619
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.1267 104.2810
row5 103.2260 105.3619
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.2219590
[2,] -0.9170426
[3,] 0.6122803
[4,] -1.5905186
[5,] -0.8597124
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.2066780 0.5948120
[2,] -0.3877150 -0.7086212
[3,] -0.7958512 -0.7916765
[4,] 0.1475964 -0.7403048
[5,] -0.1579246 1.3161870
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.92904490 -0.8616276
[2,] -0.94531208 -0.6970962
[3,] -0.45756429 1.6660925
[4,] -0.09246556 0.9010874
[5,] 0.29228411 0.3114403
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.9290449
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.9290449
[2,] -0.9453121
>
>
>
> 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 0.9231704 -1.3947386 -0.2016642 -1.490280 0.1318030 1.169182356
row1 -0.1731490 -0.2063028 0.4370127 1.342234 0.8995727 0.006268307
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -2.0031829 -0.4970903 -0.7601815 -2.8683042 -0.6820732 1.62826571
row1 -0.2084626 -0.8599899 -0.3804515 -0.5154253 1.6858803 0.03973353
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -1.451713 -0.5528809 0.4200463 -0.06275632 -2.0906933 0.2440216
row1 -1.218614 -1.4337433 -2.4947427 0.18682559 0.7286536 0.4329638
[,19] [,20]
row3 -0.5628226 0.007463734
row1 -0.3874550 0.328183161
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2374654 1.482456 0.3802404 -1.114026 -0.5916736 1.358725 1.828222
[,8] [,9] [,10]
row2 -1.186975 0.7542823 1.065006
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.050502 -1.17147 0.5500619 0.4491036 1.326986 -0.122938 0.8110991
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -2.14365 1.240295 0.7384387 -0.4207592 -0.4083205 1.530399 0.5135113
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.939279 -0.04858918 -0.374936 -0.1781138 -0.6454532 1.425446
>
>
> 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: 0x5687ec660c60>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25577391bd833"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557737a2c241f"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM255773362f6cc8"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557733e31aba5"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM255773273e6b73"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557734c07a493"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557736f50e9d2"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM255773163a8391"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557731ee5f125"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25577379abfb6b"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25577347e25f3c"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557731e25e6dd"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557737ca81012"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2557735545d5cd"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25577320cc933c"
>
>
> ### 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: 0x5687eceeca50>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5687eceeca50>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5687eceeca50>
> rowMedians(tmp)
[1] -0.307682127 0.258448583 -0.235205329 -0.012516549 -0.295975777
[6] 0.668073644 0.371051470 0.015219833 -0.120399928 -0.091107645
[11] -0.361728744 -0.058817905 -0.199770823 0.986700479 -0.148731943
[16] -0.167616378 -0.012273643 0.781179183 -0.103818207 0.695098509
[21] -0.303304346 0.125090172 0.583933694 -0.385092240 0.328951056
[26] 0.064616193 -0.191852862 -0.072523134 0.438103546 0.269529899
[31] 0.035430210 -0.442886494 -0.148819039 0.304739037 0.001002178
[36] -0.218692892 0.273098763 -0.356356331 -0.130539853 0.042995732
[41] -0.208233303 -0.106072312 0.103836726 0.235725941 0.125754337
[46] -0.180701645 0.027941411 0.036150795 -0.363406007 0.137926843
[51] -0.074713808 0.115429669 0.158744281 0.052012579 0.041769607
[56] 0.090934479 0.355466317 0.434723591 0.218796154 -0.365800767
[61] 0.267363982 0.078608421 -0.532453724 -0.157760875 0.385012752
[66] -0.087759240 -0.215292551 -0.277974995 -0.007834309 -0.016894135
[71] 0.046525256 -0.278633964 0.245984799 -0.140560918 0.302534448
[76] 0.460864677 -0.312877926 0.334348166 -0.522164293 0.230362166
[81] 0.213560825 0.437657024 -0.070273277 0.534365478 0.670036628
[86] 0.313405822 -0.463321097 0.006298191 -0.100432235 0.047000500
[91] -0.619462217 -0.236824648 0.454946773 0.579835730 -0.164521890
[96] -0.017826560 0.357855698 0.436841884 -0.471372066 0.063223205
[101] -0.610562733 -0.150707346 -0.063628171 0.265357381 -0.350959366
[106] -0.293158596 -0.061877297 -0.159278128 -0.107295692 -0.366522456
[111] -0.006046953 0.170712042 -0.178970119 -0.022306700 0.196016920
[116] 0.404322854 0.387885319 0.233535488 -0.061926142 -0.183152845
[121] -0.268257923 -0.284075343 -0.081941665 0.095416134 0.289026589
[126] -0.003944511 -0.202659685 0.303865115 0.170241436 -0.288104477
[131] 0.181617653 -0.035812714 -0.459323289 -0.193302495 -0.086268425
[136] -0.595976569 -0.101074928 -0.070462922 0.295293464 -0.266925589
[141] 0.091550752 -0.310085182 -0.386128489 0.047611363 0.114754549
[146] 0.028368867 -0.410769838 0.381115895 0.215825588 0.429936522
[151] 0.064073517 0.567540798 -0.150312083 -0.061763628 -0.056120626
[156] 0.258350305 -0.047865202 0.047778610 0.040381476 0.008848636
[161] 0.296243576 -0.024170960 0.003067170 -0.270499262 -0.191686800
[166] -0.097755046 -0.247838923 -0.111820206 0.235701508 0.009272752
[171] 0.228870837 0.460054008 -0.106424836 0.016442224 0.072746592
[176] 0.210024024 -0.202559784 -0.045352357 0.664077277 0.068994251
[181] -0.276053062 -0.514642436 -0.658866293 0.023475837 -0.275829140
[186] -0.081317063 0.001392340 0.334028947 -0.299424527 -0.349306597
[191] -0.517022390 0.148602431 -0.235890277 -0.082097219 0.038015305
[196] 0.598877981 -0.360107475 0.063969670 -0.203303556 -0.157918509
[201] -0.258082640 -0.168677914 -0.309489208 0.066135911 0.216556239
[206] 0.387104742 0.081677377 0.106273457 0.746905878 -0.023810650
[211] 0.044522676 -0.361528322 0.358035848 -0.670478602 0.364890579
[216] 0.219585022 -0.248446399 -0.094250745 0.267287471 0.074390879
[221] -0.048270677 0.071602119 0.193633387 -0.751639574 0.046119242
[226] 0.314244594 -0.269294075 0.286793766 0.024254374 -0.234888276
>
> proc.time()
user system elapsed
1.306 0.787 1.960
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: 0x5cfbcf74ac20>
> .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: 0x5cfbcf74ac20>
> .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: 0x5cfbcf74ac20>
> .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: 0x5cfbcf74ac20>
> 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: 0x5cfbcf89c040>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbcf89c040>
> .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: 0x5cfbcf89c040>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbcf89c040>
> .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: 0x5cfbcf89c040>
> 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: 0x5cfbcf48b2e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbcf48b2e0>
> .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: 0x5cfbcf48b2e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5cfbcf48b2e0>
> .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: 0x5cfbcf48b2e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5cfbcf48b2e0>
> .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: 0x5cfbcf48b2e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5cfbcf48b2e0>
> .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: 0x5cfbcf48b2e0>
> 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: 0x5cfbd1a45150>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5cfbd1a45150>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbd1a45150>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbd1a45150>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2558c91eb86001" "BufferedMatrixFile2558c96bf9c9a9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2558c91eb86001" "BufferedMatrixFile2558c96bf9c9a9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbcf9fcf50>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbcf9fcf50>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5cfbcf9fcf50>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5cfbcf9fcf50>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5cfbcf9fcf50>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5cfbcf9fcf50>
> .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: 0x5cfbd04eea40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cfbd04eea40>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5cfbd04eea40>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5cfbd04eea40>
> 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: 0x5cfbcfeda560>
> .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: 0x5cfbcfeda560>
> rm(P)
>
> proc.time()
user system elapsed
0.278 0.149 0.294
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
0.300 0.135 0.301