Ben Bolstad
| Snapshot Date: 2025-10-31 13:45 -0400 (Fri, 31 Oct 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0400 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-11-01 12:02 -0400 (Sat, 01 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4901 |
| lconway | macOS 12.7.6 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4691 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4637 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 257/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.74.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.74.0 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2025-10-31 21:49:54 -0400 (Fri, 31 Oct 2025) |
| EndedAt: 2025-10-31 21:50:18 -0400 (Fri, 31 Oct 2025) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz
###
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##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-08-23 r88802)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.74.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.22-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.252 0.044 0.282
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 478419 25.6 1047111 56 639600 34.2
Vcells 885237 6.8 8388608 64 2081604 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Oct 31 21:50:09 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Oct 31 21:50:09 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: 0x630d80db3b10>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Oct 31 21:50:09 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Oct 31 21:50:09 2025"
>
> ColMode(tmp2)
<pointer: 0x630d80db3b10>
>
>
>
> ### 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,] 100.74310057 -0.8497526 -1.5038593 0.1416078
[2,] -2.08418945 -0.1900712 0.6469995 -0.8011778
[3,] -0.78683207 -1.5278491 -0.7054996 0.7816153
[4,] -0.09460032 1.2063311 -1.1201756 1.5176139
> 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,] 100.74310057 0.8497526 1.5038593 0.1416078
[2,] 2.08418945 0.1900712 0.6469995 0.8011778
[3,] 0.78683207 1.5278491 0.7054996 0.7816153
[4,] 0.09460032 1.2063311 1.1201756 1.5176139
> 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,] 10.0370863 0.9218203 1.2263194 0.3763081
[2,] 1.4436722 0.4359715 0.8043628 0.8950854
[3,] 0.8870356 1.2360619 0.8399402 0.8840901
[4,] 0.3075717 1.0983311 1.0583835 1.2319147
>
> 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,] 226.11396 35.06796 38.76705 28.90469
[2,] 41.52091 29.54979 33.69063 34.75203
[3,] 34.65719 38.88847 34.10490 34.62252
[4,] 28.17032 37.18964 36.70401 38.83676
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x630d807b15c0>
> exp(tmp5)
<pointer: 0x630d807b15c0>
> log(tmp5,2)
<pointer: 0x630d807b15c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.6266
> Min(tmp5)
[1] 54.30587
> mean(tmp5)
[1] 72.85288
> Sum(tmp5)
[1] 14570.58
> Var(tmp5)
[1] 870.8263
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.22473 71.93273 71.50205 69.54094 65.49663 72.65431 70.78390 74.07930
[9] 72.81540 68.49880
> rowSums(tmp5)
[1] 1824.495 1438.655 1430.041 1390.819 1309.933 1453.086 1415.678 1481.586
[9] 1456.308 1369.976
> rowVars(tmp5)
[1] 8029.76464 94.00890 59.22406 100.54858 37.13805 85.36932
[7] 63.41984 70.11720 54.51544 73.95583
> rowSd(tmp5)
[1] 89.608954 9.695819 7.695717 10.027391 6.094099 9.239552 7.963657
[8] 8.373601 7.383457 8.599757
> rowMax(tmp5)
[1] 470.62659 88.86277 86.59068 85.92980 79.15635 90.14150 85.11947
[8] 88.81209 84.58259 88.85629
> rowMin(tmp5)
[1] 57.55829 55.60785 57.99911 54.30587 56.06104 55.50657 59.65844 59.47940
[9] 58.61713 57.70697
>
> colMeans(tmp5)
[1] 111.48965 69.55902 75.15219 71.46981 71.07243 67.47447 71.80207
[8] 68.51171 75.95940 71.04696 70.80345 71.86032 73.16232 66.67848
[15] 68.68093 68.07464 66.97413 69.60170 73.22059 74.46332
> colSums(tmp5)
[1] 1114.8965 695.5902 751.5219 714.6981 710.7243 674.7447 718.0207
[8] 685.1171 759.5940 710.4696 708.0345 718.6032 731.6232 666.7848
[15] 686.8093 680.7464 669.7413 696.0170 732.2059 744.6332
> colVars(tmp5)
[1] 16030.38397 54.41414 54.50599 52.73572 63.45505 11.58590
[7] 50.41799 75.18939 125.43001 86.81646 48.20176 78.23727
[13] 96.22084 76.14149 81.66746 77.22754 72.64294 65.17671
[19] 105.28062 52.19829
> colSd(tmp5)
[1] 126.611153 7.376594 7.382817 7.261936 7.965868 3.403807
[7] 7.100563 8.671182 11.199554 9.317535 6.942749 8.845184
[13] 9.809222 8.725909 9.037005 8.787920 8.523083 8.073209
[19] 10.260635 7.224838
> colMax(tmp5)
[1] 470.62659 80.94125 85.08250 84.58259 82.28972 70.70673 81.41219
[8] 86.98291 88.86277 90.14150 82.01283 88.81209 88.44215 80.34499
[15] 86.51527 83.93596 82.36730 82.10527 86.59068 88.85629
> colMin(tmp5)
[1] 58.63282 61.50401 62.45430 60.16132 57.43930 59.34729 59.03704 56.06104
[9] 57.70697 58.38148 60.78507 62.75699 59.65844 56.35753 54.30587 58.61713
[17] 57.55958 55.50657 55.60785 62.64824
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 91.22473 71.93273 71.50205 NA 65.49663 72.65431 70.78390 74.07930
[9] 72.81540 68.49880
> rowSums(tmp5)
[1] 1824.495 1438.655 1430.041 NA 1309.933 1453.086 1415.678 1481.586
[9] 1456.308 1369.976
> rowVars(tmp5)
[1] 8029.76464 94.00890 59.22406 106.11990 37.13805 85.36932
[7] 63.41984 70.11720 54.51544 73.95583
> rowSd(tmp5)
[1] 89.608954 9.695819 7.695717 10.301452 6.094099 9.239552 7.963657
[8] 8.373601 7.383457 8.599757
> rowMax(tmp5)
[1] 470.62659 88.86277 86.59068 NA 79.15635 90.14150 85.11947
[8] 88.81209 84.58259 88.85629
> rowMin(tmp5)
[1] 57.55829 55.60785 57.99911 NA 56.06104 55.50657 59.65844 59.47940
[9] 58.61713 57.70697
>
> colMeans(tmp5)
[1] 111.48965 69.55902 75.15219 71.46981 71.07243 67.47447 71.80207
[8] NA 75.95940 71.04696 70.80345 71.86032 73.16232 66.67848
[15] 68.68093 68.07464 66.97413 69.60170 73.22059 74.46332
> colSums(tmp5)
[1] 1114.8965 695.5902 751.5219 714.6981 710.7243 674.7447 718.0207
[8] NA 759.5940 710.4696 708.0345 718.6032 731.6232 666.7848
[15] 686.8093 680.7464 669.7413 696.0170 732.2059 744.6332
> colVars(tmp5)
[1] 16030.38397 54.41414 54.50599 52.73572 63.45505 11.58590
[7] 50.41799 NA 125.43001 86.81646 48.20176 78.23727
[13] 96.22084 76.14149 81.66746 77.22754 72.64294 65.17671
[19] 105.28062 52.19829
> colSd(tmp5)
[1] 126.611153 7.376594 7.382817 7.261936 7.965868 3.403807
[7] 7.100563 NA 11.199554 9.317535 6.942749 8.845184
[13] 9.809222 8.725909 9.037005 8.787920 8.523083 8.073209
[19] 10.260635 7.224838
> colMax(tmp5)
[1] 470.62659 80.94125 85.08250 84.58259 82.28972 70.70673 81.41219
[8] NA 88.86277 90.14150 82.01283 88.81209 88.44215 80.34499
[15] 86.51527 83.93596 82.36730 82.10527 86.59068 88.85629
> colMin(tmp5)
[1] 58.63282 61.50401 62.45430 60.16132 57.43930 59.34729 59.03704 NA
[9] 57.70697 58.38148 60.78507 62.75699 59.65844 56.35753 54.30587 58.61713
[17] 57.55958 55.50657 55.60785 62.64824
>
> Max(tmp5,na.rm=TRUE)
[1] 470.6266
> Min(tmp5,na.rm=TRUE)
[1] 54.30587
> mean(tmp5,na.rm=TRUE)
[1] 72.867
> Sum(tmp5,na.rm=TRUE)
[1] 14500.53
> Var(tmp5,na.rm=TRUE)
[1] 875.1844
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.22473 71.93273 71.50205 69.51455 65.49663 72.65431 70.78390 74.07930
[9] 72.81540 68.49880
> rowSums(tmp5,na.rm=TRUE)
[1] 1824.495 1438.655 1430.041 1320.776 1309.933 1453.086 1415.678 1481.586
[9] 1456.308 1369.976
> rowVars(tmp5,na.rm=TRUE)
[1] 8029.76464 94.00890 59.22406 106.11990 37.13805 85.36932
[7] 63.41984 70.11720 54.51544 73.95583
> rowSd(tmp5,na.rm=TRUE)
[1] 89.608954 9.695819 7.695717 10.301452 6.094099 9.239552 7.963657
[8] 8.373601 7.383457 8.599757
> rowMax(tmp5,na.rm=TRUE)
[1] 470.62659 88.86277 86.59068 85.92980 79.15635 90.14150 85.11947
[8] 88.81209 84.58259 88.85629
> rowMin(tmp5,na.rm=TRUE)
[1] 57.55829 55.60785 57.99911 54.30587 56.06104 55.50657 59.65844 59.47940
[9] 58.61713 57.70697
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.48965 69.55902 75.15219 71.46981 71.07243 67.47447 71.80207
[8] 68.34163 75.95940 71.04696 70.80345 71.86032 73.16232 66.67848
[15] 68.68093 68.07464 66.97413 69.60170 73.22059 74.46332
> colSums(tmp5,na.rm=TRUE)
[1] 1114.8965 695.5902 751.5219 714.6981 710.7243 674.7447 718.0207
[8] 615.0747 759.5940 710.4696 708.0345 718.6032 731.6232 666.7848
[15] 686.8093 680.7464 669.7413 696.0170 732.2059 744.6332
> colVars(tmp5,na.rm=TRUE)
[1] 16030.38397 54.41414 54.50599 52.73572 63.45505 11.58590
[7] 50.41799 84.26264 125.43001 86.81646 48.20176 78.23727
[13] 96.22084 76.14149 81.66746 77.22754 72.64294 65.17671
[19] 105.28062 52.19829
> colSd(tmp5,na.rm=TRUE)
[1] 126.611153 7.376594 7.382817 7.261936 7.965868 3.403807
[7] 7.100563 9.179468 11.199554 9.317535 6.942749 8.845184
[13] 9.809222 8.725909 9.037005 8.787920 8.523083 8.073209
[19] 10.260635 7.224838
> colMax(tmp5,na.rm=TRUE)
[1] 470.62659 80.94125 85.08250 84.58259 82.28972 70.70673 81.41219
[8] 86.98291 88.86277 90.14150 82.01283 88.81209 88.44215 80.34499
[15] 86.51527 83.93596 82.36730 82.10527 86.59068 88.85629
> colMin(tmp5,na.rm=TRUE)
[1] 58.63282 61.50401 62.45430 60.16132 57.43930 59.34729 59.03704 56.06104
[9] 57.70697 58.38148 60.78507 62.75699 59.65844 56.35753 54.30587 58.61713
[17] 57.55958 55.50657 55.60785 62.64824
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.22473 71.93273 71.50205 NaN 65.49663 72.65431 70.78390 74.07930
[9] 72.81540 68.49880
> rowSums(tmp5,na.rm=TRUE)
[1] 1824.495 1438.655 1430.041 0.000 1309.933 1453.086 1415.678 1481.586
[9] 1456.308 1369.976
> rowVars(tmp5,na.rm=TRUE)
[1] 8029.76464 94.00890 59.22406 NA 37.13805 85.36932
[7] 63.41984 70.11720 54.51544 73.95583
> rowSd(tmp5,na.rm=TRUE)
[1] 89.608954 9.695819 7.695717 NA 6.094099 9.239552 7.963657
[8] 8.373601 7.383457 8.599757
> rowMax(tmp5,na.rm=TRUE)
[1] 470.62659 88.86277 86.59068 NA 79.15635 90.14150 85.11947
[8] 88.81209 84.58259 88.85629
> rowMin(tmp5,na.rm=TRUE)
[1] 57.55829 55.60785 57.99911 NA 56.06104 55.50657 59.65844 59.47940
[9] 58.61713 57.70697
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.36263 68.68720 75.01415 70.42938 69.82607 67.18833 71.99143
[8] NaN 76.50649 71.86443 71.91660 70.29704 71.96248 67.82525
[15] 70.27816 67.77619 68.02019 70.52938 74.67078 73.92962
> colSums(tmp5,na.rm=TRUE)
[1] 1056.2636 618.1848 675.1273 633.8645 628.4346 604.6950 647.9229
[8] 0.0000 688.5584 646.7799 647.2494 632.6734 647.6624 610.4273
[15] 632.5034 609.9857 612.1817 634.7645 672.0370 665.3666
> colVars(tmp5,na.rm=TRUE)
[1] 17646.14814 52.66519 61.10485 47.14974 53.91088 12.11305
[7] 56.31682 NA 137.74149 90.15064 40.28698 60.52383
[13] 92.05275 70.86445 63.17558 85.87892 69.41307 63.64208
[19] 94.78143 55.51866
> colSd(tmp5,na.rm=TRUE)
[1] 132.838805 7.257078 7.816959 6.866567 7.342403 3.480380
[7] 7.504453 NA 11.736332 9.494769 6.347202 7.779706
[13] 9.594413 8.418102 7.948307 9.267088 8.331451 7.977598
[19] 9.735575 7.451084
> colMax(tmp5,na.rm=TRUE)
[1] 470.62659 80.94125 85.08250 84.58259 78.72293 70.70673 81.41219
[8] -Inf 88.86277 90.14150 82.01283 88.81209 88.44215 80.34499
[15] 86.51527 83.93596 82.36730 82.10527 86.59068 88.85629
> colMin(tmp5,na.rm=TRUE)
[1] 61.02656 61.50401 62.45430 60.16132 57.43930 59.34729 59.03704 Inf
[9] 57.70697 58.38148 63.90352 62.75699 59.65844 57.55829 61.33375 58.61713
[17] 57.99911 55.50657 55.60785 62.64824
>
>
>
>
> 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] 351.8961 178.8338 167.2469 163.4728 221.8033 224.4196 156.8894 218.1613
[9] 233.4741 214.4055
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 351.8961 178.8338 167.2469 163.4728 221.8033 224.4196 156.8894 218.1613
[9] 233.4741 214.4055
>
>
>
> 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] 1.136868e-13 -1.421085e-14 2.273737e-13 -1.421085e-14 -5.684342e-14
[6] -2.842171e-14 -1.136868e-13 1.989520e-13 2.842171e-14 -5.684342e-14
[11] -5.684342e-14 5.684342e-14 -1.136868e-13 2.842171e-14 -1.136868e-13
[16] -5.684342e-14 5.684342e-14 -2.842171e-13 5.684342e-14 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 4
6 4
9 8
3 15
4 18
5 20
1 19
10 1
10 5
3 12
2 20
8 3
6 19
6 14
10 11
6 11
2 16
6 6
9 18
4 11
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] 3.736707
> Min(tmp)
[1] -2.482369
> mean(tmp)
[1] -0.100978
> Sum(tmp)
[1] -10.0978
> Var(tmp)
[1] 1.24965
>
> rowMeans(tmp)
[1] -0.100978
> rowSums(tmp)
[1] -10.0978
> rowVars(tmp)
[1] 1.24965
> rowSd(tmp)
[1] 1.117877
> rowMax(tmp)
[1] 3.736707
> rowMin(tmp)
[1] -2.482369
>
> colMeans(tmp)
[1] -1.44528212 0.34075419 0.02964093 -2.41512141 -0.73938460 2.00107534
[7] -0.38293988 -0.39350218 0.33236200 1.00973558 -0.46958416 -1.04382638
[13] -0.35794420 -1.24859494 1.31819706 -1.35528414 0.66751523 -0.54193201
[19] 0.68936589 -1.62893215 -0.70115299 -1.69874879 0.65807622 -2.09577140
[25] 0.16112733 -0.58581107 -0.69627022 -0.15523327 -0.72745689 1.48476197
[31] -1.88447668 0.53784109 -0.34326966 -0.03767823 -0.91762241 1.11038187
[37] 0.58368026 1.75194429 -0.45437897 -1.67353909 -0.35489191 0.63086910
[43] 0.15718594 1.29811059 0.52315063 -2.12849751 -0.18418799 -0.32662898
[49] -2.25060230 -1.83614604 0.29577321 -0.79629546 0.13206425 0.50252611
[55] -0.36500703 -0.35870227 -0.23739006 -0.05368058 1.11469288 0.03036580
[61] -1.40072512 -0.14036249 2.76422125 0.37600443 1.68038815 -1.09483933
[67] -0.02766311 -1.36474263 -0.58439161 0.85280957 1.33559945 0.31863024
[73] -0.01339578 -0.64517380 -1.81828763 -0.18828318 -0.74362291 1.00157322
[79] -0.36911444 -0.22453764 -0.40808301 -0.88495750 0.67362052 -0.08809726
[85] 0.86995707 -0.29903531 -2.48236933 -0.68104161 2.07274677 3.73670651
[91] 0.80258061 0.87387123 -0.38255377 0.62279728 1.71643068 0.29185235
[97] 0.81570791 -0.77633578 -0.21001196 -0.55110036
> colSums(tmp)
[1] -1.44528212 0.34075419 0.02964093 -2.41512141 -0.73938460 2.00107534
[7] -0.38293988 -0.39350218 0.33236200 1.00973558 -0.46958416 -1.04382638
[13] -0.35794420 -1.24859494 1.31819706 -1.35528414 0.66751523 -0.54193201
[19] 0.68936589 -1.62893215 -0.70115299 -1.69874879 0.65807622 -2.09577140
[25] 0.16112733 -0.58581107 -0.69627022 -0.15523327 -0.72745689 1.48476197
[31] -1.88447668 0.53784109 -0.34326966 -0.03767823 -0.91762241 1.11038187
[37] 0.58368026 1.75194429 -0.45437897 -1.67353909 -0.35489191 0.63086910
[43] 0.15718594 1.29811059 0.52315063 -2.12849751 -0.18418799 -0.32662898
[49] -2.25060230 -1.83614604 0.29577321 -0.79629546 0.13206425 0.50252611
[55] -0.36500703 -0.35870227 -0.23739006 -0.05368058 1.11469288 0.03036580
[61] -1.40072512 -0.14036249 2.76422125 0.37600443 1.68038815 -1.09483933
[67] -0.02766311 -1.36474263 -0.58439161 0.85280957 1.33559945 0.31863024
[73] -0.01339578 -0.64517380 -1.81828763 -0.18828318 -0.74362291 1.00157322
[79] -0.36911444 -0.22453764 -0.40808301 -0.88495750 0.67362052 -0.08809726
[85] 0.86995707 -0.29903531 -2.48236933 -0.68104161 2.07274677 3.73670651
[91] 0.80258061 0.87387123 -0.38255377 0.62279728 1.71643068 0.29185235
[97] 0.81570791 -0.77633578 -0.21001196 -0.55110036
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.44528212 0.34075419 0.02964093 -2.41512141 -0.73938460 2.00107534
[7] -0.38293988 -0.39350218 0.33236200 1.00973558 -0.46958416 -1.04382638
[13] -0.35794420 -1.24859494 1.31819706 -1.35528414 0.66751523 -0.54193201
[19] 0.68936589 -1.62893215 -0.70115299 -1.69874879 0.65807622 -2.09577140
[25] 0.16112733 -0.58581107 -0.69627022 -0.15523327 -0.72745689 1.48476197
[31] -1.88447668 0.53784109 -0.34326966 -0.03767823 -0.91762241 1.11038187
[37] 0.58368026 1.75194429 -0.45437897 -1.67353909 -0.35489191 0.63086910
[43] 0.15718594 1.29811059 0.52315063 -2.12849751 -0.18418799 -0.32662898
[49] -2.25060230 -1.83614604 0.29577321 -0.79629546 0.13206425 0.50252611
[55] -0.36500703 -0.35870227 -0.23739006 -0.05368058 1.11469288 0.03036580
[61] -1.40072512 -0.14036249 2.76422125 0.37600443 1.68038815 -1.09483933
[67] -0.02766311 -1.36474263 -0.58439161 0.85280957 1.33559945 0.31863024
[73] -0.01339578 -0.64517380 -1.81828763 -0.18828318 -0.74362291 1.00157322
[79] -0.36911444 -0.22453764 -0.40808301 -0.88495750 0.67362052 -0.08809726
[85] 0.86995707 -0.29903531 -2.48236933 -0.68104161 2.07274677 3.73670651
[91] 0.80258061 0.87387123 -0.38255377 0.62279728 1.71643068 0.29185235
[97] 0.81570791 -0.77633578 -0.21001196 -0.55110036
> colMin(tmp)
[1] -1.44528212 0.34075419 0.02964093 -2.41512141 -0.73938460 2.00107534
[7] -0.38293988 -0.39350218 0.33236200 1.00973558 -0.46958416 -1.04382638
[13] -0.35794420 -1.24859494 1.31819706 -1.35528414 0.66751523 -0.54193201
[19] 0.68936589 -1.62893215 -0.70115299 -1.69874879 0.65807622 -2.09577140
[25] 0.16112733 -0.58581107 -0.69627022 -0.15523327 -0.72745689 1.48476197
[31] -1.88447668 0.53784109 -0.34326966 -0.03767823 -0.91762241 1.11038187
[37] 0.58368026 1.75194429 -0.45437897 -1.67353909 -0.35489191 0.63086910
[43] 0.15718594 1.29811059 0.52315063 -2.12849751 -0.18418799 -0.32662898
[49] -2.25060230 -1.83614604 0.29577321 -0.79629546 0.13206425 0.50252611
[55] -0.36500703 -0.35870227 -0.23739006 -0.05368058 1.11469288 0.03036580
[61] -1.40072512 -0.14036249 2.76422125 0.37600443 1.68038815 -1.09483933
[67] -0.02766311 -1.36474263 -0.58439161 0.85280957 1.33559945 0.31863024
[73] -0.01339578 -0.64517380 -1.81828763 -0.18828318 -0.74362291 1.00157322
[79] -0.36911444 -0.22453764 -0.40808301 -0.88495750 0.67362052 -0.08809726
[85] 0.86995707 -0.29903531 -2.48236933 -0.68104161 2.07274677 3.73670651
[91] 0.80258061 0.87387123 -0.38255377 0.62279728 1.71643068 0.29185235
[97] 0.81570791 -0.77633578 -0.21001196 -0.55110036
> colMedians(tmp)
[1] -1.44528212 0.34075419 0.02964093 -2.41512141 -0.73938460 2.00107534
[7] -0.38293988 -0.39350218 0.33236200 1.00973558 -0.46958416 -1.04382638
[13] -0.35794420 -1.24859494 1.31819706 -1.35528414 0.66751523 -0.54193201
[19] 0.68936589 -1.62893215 -0.70115299 -1.69874879 0.65807622 -2.09577140
[25] 0.16112733 -0.58581107 -0.69627022 -0.15523327 -0.72745689 1.48476197
[31] -1.88447668 0.53784109 -0.34326966 -0.03767823 -0.91762241 1.11038187
[37] 0.58368026 1.75194429 -0.45437897 -1.67353909 -0.35489191 0.63086910
[43] 0.15718594 1.29811059 0.52315063 -2.12849751 -0.18418799 -0.32662898
[49] -2.25060230 -1.83614604 0.29577321 -0.79629546 0.13206425 0.50252611
[55] -0.36500703 -0.35870227 -0.23739006 -0.05368058 1.11469288 0.03036580
[61] -1.40072512 -0.14036249 2.76422125 0.37600443 1.68038815 -1.09483933
[67] -0.02766311 -1.36474263 -0.58439161 0.85280957 1.33559945 0.31863024
[73] -0.01339578 -0.64517380 -1.81828763 -0.18828318 -0.74362291 1.00157322
[79] -0.36911444 -0.22453764 -0.40808301 -0.88495750 0.67362052 -0.08809726
[85] 0.86995707 -0.29903531 -2.48236933 -0.68104161 2.07274677 3.73670651
[91] 0.80258061 0.87387123 -0.38255377 0.62279728 1.71643068 0.29185235
[97] 0.81570791 -0.77633578 -0.21001196 -0.55110036
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.445282 0.3407542 0.02964093 -2.415121 -0.7393846 2.001075 -0.3829399
[2,] -1.445282 0.3407542 0.02964093 -2.415121 -0.7393846 2.001075 -0.3829399
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3935022 0.332362 1.009736 -0.4695842 -1.043826 -0.3579442 -1.248595
[2,] -0.3935022 0.332362 1.009736 -0.4695842 -1.043826 -0.3579442 -1.248595
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.318197 -1.355284 0.6675152 -0.541932 0.6893659 -1.628932 -0.701153
[2,] 1.318197 -1.355284 0.6675152 -0.541932 0.6893659 -1.628932 -0.701153
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.698749 0.6580762 -2.095771 0.1611273 -0.5858111 -0.6962702 -0.1552333
[2,] -1.698749 0.6580762 -2.095771 0.1611273 -0.5858111 -0.6962702 -0.1552333
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.7274569 1.484762 -1.884477 0.5378411 -0.3432697 -0.03767823 -0.9176224
[2,] -0.7274569 1.484762 -1.884477 0.5378411 -0.3432697 -0.03767823 -0.9176224
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.110382 0.5836803 1.751944 -0.454379 -1.673539 -0.3548919 0.6308691
[2,] 1.110382 0.5836803 1.751944 -0.454379 -1.673539 -0.3548919 0.6308691
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.1571859 1.298111 0.5231506 -2.128498 -0.184188 -0.326629 -2.250602
[2,] 0.1571859 1.298111 0.5231506 -2.128498 -0.184188 -0.326629 -2.250602
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.836146 0.2957732 -0.7962955 0.1320643 0.5025261 -0.365007 -0.3587023
[2,] -1.836146 0.2957732 -0.7962955 0.1320643 0.5025261 -0.365007 -0.3587023
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.2373901 -0.05368058 1.114693 0.0303658 -1.400725 -0.1403625 2.764221
[2,] -0.2373901 -0.05368058 1.114693 0.0303658 -1.400725 -0.1403625 2.764221
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.3760044 1.680388 -1.094839 -0.02766311 -1.364743 -0.5843916 0.8528096
[2,] 0.3760044 1.680388 -1.094839 -0.02766311 -1.364743 -0.5843916 0.8528096
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.335599 0.3186302 -0.01339578 -0.6451738 -1.818288 -0.1882832 -0.7436229
[2,] 1.335599 0.3186302 -0.01339578 -0.6451738 -1.818288 -0.1882832 -0.7436229
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.001573 -0.3691144 -0.2245376 -0.408083 -0.8849575 0.6736205 -0.08809726
[2,] 1.001573 -0.3691144 -0.2245376 -0.408083 -0.8849575 0.6736205 -0.08809726
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.8699571 -0.2990353 -2.482369 -0.6810416 2.072747 3.736707 0.8025806
[2,] 0.8699571 -0.2990353 -2.482369 -0.6810416 2.072747 3.736707 0.8025806
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.8738712 -0.3825538 0.6227973 1.716431 0.2918524 0.8157079 -0.7763358
[2,] 0.8738712 -0.3825538 0.6227973 1.716431 0.2918524 0.8157079 -0.7763358
[,99] [,100]
[1,] -0.210012 -0.5511004
[2,] -0.210012 -0.5511004
>
>
> Max(tmp2)
[1] 2.71401
> Min(tmp2)
[1] -2.01015
> mean(tmp2)
[1] -0.01573637
> Sum(tmp2)
[1] -1.573637
> Var(tmp2)
[1] 0.9670055
>
> rowMeans(tmp2)
[1] 0.4304113467 0.4627828517 -0.7127876736 0.9269374126 -1.4906356985
[6] -0.9013794792 0.0545558207 -1.0817631118 -0.2623535531 0.4296382010
[11] -1.2654988506 -1.3463883842 -0.7031482017 0.6506925342 -0.8087946677
[16] 0.6621220276 -0.5926511065 -1.2370170077 -0.2261401614 -0.4904698614
[21] 0.2858211921 0.2322441641 -0.5197317611 -2.0101496852 0.6682542861
[26] -0.6411649884 -0.4257120326 -1.1538735721 -0.1124601026 1.8510240734
[31] -0.5050387585 -0.3552918565 0.3258940780 0.2049103677 -0.8774170998
[36] -0.8203880812 -0.3922618505 1.3551335186 1.2359825828 1.7970149491
[41] -0.0783554819 0.6105794223 0.7295408121 -0.0008489432 -0.4801207309
[46] -0.5432074537 0.0390880157 1.0435981220 1.0229338332 -0.8277589300
[51] -0.9743321181 -0.0743776446 0.6316944093 -1.0946958557 -0.1543088193
[56] -0.0107112333 -1.6485758740 -0.7062666378 1.0912835664 -1.3422624763
[61] 0.7213219060 -0.6891402450 1.0001726052 0.5025462771 2.4618337536
[66] 0.9196994345 2.7140097865 -0.6640643758 -0.2614643597 1.7623548007
[71] -1.4211871497 -0.0174370528 0.5142804073 -0.0745642086 0.2440251163
[76] -0.8188120086 -1.2887803849 -0.3210678345 0.8530249388 -0.8724767530
[81] -0.7636180036 1.0566768075 0.4272151599 -1.1948329094 1.2745108407
[86] -0.7225245619 0.5319363431 -1.6199967194 1.4399761928 0.7879472681
[91] -1.4140759361 0.8954084827 -0.2735408585 1.3798667853 -0.9641073671
[96] 1.8446930817 1.4878322943 0.0202012647 0.1431976798 -1.0484757363
> rowSums(tmp2)
[1] 0.4304113467 0.4627828517 -0.7127876736 0.9269374126 -1.4906356985
[6] -0.9013794792 0.0545558207 -1.0817631118 -0.2623535531 0.4296382010
[11] -1.2654988506 -1.3463883842 -0.7031482017 0.6506925342 -0.8087946677
[16] 0.6621220276 -0.5926511065 -1.2370170077 -0.2261401614 -0.4904698614
[21] 0.2858211921 0.2322441641 -0.5197317611 -2.0101496852 0.6682542861
[26] -0.6411649884 -0.4257120326 -1.1538735721 -0.1124601026 1.8510240734
[31] -0.5050387585 -0.3552918565 0.3258940780 0.2049103677 -0.8774170998
[36] -0.8203880812 -0.3922618505 1.3551335186 1.2359825828 1.7970149491
[41] -0.0783554819 0.6105794223 0.7295408121 -0.0008489432 -0.4801207309
[46] -0.5432074537 0.0390880157 1.0435981220 1.0229338332 -0.8277589300
[51] -0.9743321181 -0.0743776446 0.6316944093 -1.0946958557 -0.1543088193
[56] -0.0107112333 -1.6485758740 -0.7062666378 1.0912835664 -1.3422624763
[61] 0.7213219060 -0.6891402450 1.0001726052 0.5025462771 2.4618337536
[66] 0.9196994345 2.7140097865 -0.6640643758 -0.2614643597 1.7623548007
[71] -1.4211871497 -0.0174370528 0.5142804073 -0.0745642086 0.2440251163
[76] -0.8188120086 -1.2887803849 -0.3210678345 0.8530249388 -0.8724767530
[81] -0.7636180036 1.0566768075 0.4272151599 -1.1948329094 1.2745108407
[86] -0.7225245619 0.5319363431 -1.6199967194 1.4399761928 0.7879472681
[91] -1.4140759361 0.8954084827 -0.2735408585 1.3798667853 -0.9641073671
[96] 1.8446930817 1.4878322943 0.0202012647 0.1431976798 -1.0484757363
> 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] 0.4304113467 0.4627828517 -0.7127876736 0.9269374126 -1.4906356985
[6] -0.9013794792 0.0545558207 -1.0817631118 -0.2623535531 0.4296382010
[11] -1.2654988506 -1.3463883842 -0.7031482017 0.6506925342 -0.8087946677
[16] 0.6621220276 -0.5926511065 -1.2370170077 -0.2261401614 -0.4904698614
[21] 0.2858211921 0.2322441641 -0.5197317611 -2.0101496852 0.6682542861
[26] -0.6411649884 -0.4257120326 -1.1538735721 -0.1124601026 1.8510240734
[31] -0.5050387585 -0.3552918565 0.3258940780 0.2049103677 -0.8774170998
[36] -0.8203880812 -0.3922618505 1.3551335186 1.2359825828 1.7970149491
[41] -0.0783554819 0.6105794223 0.7295408121 -0.0008489432 -0.4801207309
[46] -0.5432074537 0.0390880157 1.0435981220 1.0229338332 -0.8277589300
[51] -0.9743321181 -0.0743776446 0.6316944093 -1.0946958557 -0.1543088193
[56] -0.0107112333 -1.6485758740 -0.7062666378 1.0912835664 -1.3422624763
[61] 0.7213219060 -0.6891402450 1.0001726052 0.5025462771 2.4618337536
[66] 0.9196994345 2.7140097865 -0.6640643758 -0.2614643597 1.7623548007
[71] -1.4211871497 -0.0174370528 0.5142804073 -0.0745642086 0.2440251163
[76] -0.8188120086 -1.2887803849 -0.3210678345 0.8530249388 -0.8724767530
[81] -0.7636180036 1.0566768075 0.4272151599 -1.1948329094 1.2745108407
[86] -0.7225245619 0.5319363431 -1.6199967194 1.4399761928 0.7879472681
[91] -1.4140759361 0.8954084827 -0.2735408585 1.3798667853 -0.9641073671
[96] 1.8446930817 1.4878322943 0.0202012647 0.1431976798 -1.0484757363
> rowMin(tmp2)
[1] 0.4304113467 0.4627828517 -0.7127876736 0.9269374126 -1.4906356985
[6] -0.9013794792 0.0545558207 -1.0817631118 -0.2623535531 0.4296382010
[11] -1.2654988506 -1.3463883842 -0.7031482017 0.6506925342 -0.8087946677
[16] 0.6621220276 -0.5926511065 -1.2370170077 -0.2261401614 -0.4904698614
[21] 0.2858211921 0.2322441641 -0.5197317611 -2.0101496852 0.6682542861
[26] -0.6411649884 -0.4257120326 -1.1538735721 -0.1124601026 1.8510240734
[31] -0.5050387585 -0.3552918565 0.3258940780 0.2049103677 -0.8774170998
[36] -0.8203880812 -0.3922618505 1.3551335186 1.2359825828 1.7970149491
[41] -0.0783554819 0.6105794223 0.7295408121 -0.0008489432 -0.4801207309
[46] -0.5432074537 0.0390880157 1.0435981220 1.0229338332 -0.8277589300
[51] -0.9743321181 -0.0743776446 0.6316944093 -1.0946958557 -0.1543088193
[56] -0.0107112333 -1.6485758740 -0.7062666378 1.0912835664 -1.3422624763
[61] 0.7213219060 -0.6891402450 1.0001726052 0.5025462771 2.4618337536
[66] 0.9196994345 2.7140097865 -0.6640643758 -0.2614643597 1.7623548007
[71] -1.4211871497 -0.0174370528 0.5142804073 -0.0745642086 0.2440251163
[76] -0.8188120086 -1.2887803849 -0.3210678345 0.8530249388 -0.8724767530
[81] -0.7636180036 1.0566768075 0.4272151599 -1.1948329094 1.2745108407
[86] -0.7225245619 0.5319363431 -1.6199967194 1.4399761928 0.7879472681
[91] -1.4140759361 0.8954084827 -0.2735408585 1.3798667853 -0.9641073671
[96] 1.8446930817 1.4878322943 0.0202012647 0.1431976798 -1.0484757363
>
> colMeans(tmp2)
[1] -0.01573637
> colSums(tmp2)
[1] -1.573637
> colVars(tmp2)
[1] 0.9670055
> colSd(tmp2)
[1] 0.9833644
> colMax(tmp2)
[1] 2.71401
> colMin(tmp2)
[1] -2.01015
> colMedians(tmp2)
[1] -0.07645985
> colRanges(tmp2)
[,1]
[1,] -2.01015
[2,] 2.71401
>
> 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] 0.76568674 2.04010523 0.09382193 -0.44943290 -1.05908920 0.20891514
[7] 5.70153925 3.07424785 -0.75639654 -3.08072978
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.58698343
[2,] -1.14073209
[3,] 0.03485381
[4,] 1.28284848
[5,] 2.17886458
>
> rowApply(tmp,sum)
[1] -1.9901323 0.2097603 1.9168627 4.0938332 4.9074285 -1.2887561
[7] -1.7498066 1.1353831 -3.6113634 2.9154583
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 1 10 4 6 2 2 10 10 6
[2,] 9 10 4 8 9 1 8 8 2 5
[3,] 10 2 9 2 3 7 9 2 4 8
[4,] 5 7 8 7 5 6 6 4 1 1
[5,] 4 3 7 3 10 4 3 3 7 7
[6,] 8 4 3 9 4 3 5 9 6 4
[7,] 6 9 6 6 8 9 10 6 8 10
[8,] 7 8 2 10 1 5 7 5 9 3
[9,] 2 6 1 5 2 10 1 7 3 9
[10,] 3 5 5 1 7 8 4 1 5 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -4.8901411 -2.2105061 0.8403785 2.3175886 1.0233033 -3.0943219
[7] 1.2838675 -1.4927690 4.5672476 1.0547194 -1.9194167 -4.0499122
[13] 3.4054686 -1.1849058 -0.6668632 -1.0229165 -1.7206544 1.3782268
[19] -1.7876861 -1.9816631
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7596493
[2,] -1.4804482
[3,] -1.1757936
[4,] -1.0295874
[5,] 0.5553373
>
> rowApply(tmp,sum)
[1] -8.562495 -3.811625 -5.135690 1.676636 5.682218
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 5 2 4 10
[2,] 13 3 1 19 7
[3,] 8 7 18 8 20
[4,] 15 14 10 14 18
[5,] 18 11 9 10 11
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.4804482 -0.2932645 -0.8986396 0.4934277 0.990897787 -0.6071839
[2,] -1.0295874 -1.6897868 -0.6462596 0.4195058 -0.063749862 -0.2789650
[3,] -1.7596493 -1.8226853 1.0283954 -0.3028198 -0.533325662 -1.3992166
[4,] -1.1757936 1.7717985 -0.2254194 0.3969136 -0.008258514 0.2971074
[5,] 0.5553373 -0.1765681 1.5823018 1.3105612 0.637739596 -1.1060638
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.5183584 -0.1207169 0.5041866 -1.6877167 -0.99298832 -1.9983143
[2,] 0.7503232 -2.0648145 0.4900626 1.5338788 0.03238967 -0.2984664
[3,] 0.2352466 0.3228187 -0.1981075 0.3106982 -0.27651564 -0.9734846
[4,] -0.1660832 -0.7882436 2.5824664 0.2552813 0.82181326 -0.3324707
[5,] 0.9827393 1.1581874 1.1886395 0.6425778 -1.50411565 -0.4471764
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.281317731 -1.8411224 -0.4329923 1.2981779 -1.1629061 0.6297931
[2,] -0.146199522 1.4901419 0.8703885 -1.9000253 0.6046792 -0.7724541
[3,] 1.153577412 -0.6970001 -0.5693434 0.7651514 -0.5656439 -1.1005959
[4,] 1.118277428 0.2240088 -0.2682408 -2.1535247 -1.2513728 1.3075748
[5,] -0.001504496 -0.3609340 -0.2666752 0.9673042 0.6545892 1.3139089
[,19] [,20]
[1,] -0.90868149 -0.8169622
[2,] -1.22774588 0.1150600
[3,] -0.18241895 1.4292286
[4,] 0.56144523 -1.2906434
[5,] -0.03028499 -1.4183462
>
>
> 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 : 565 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 0.2423656 0.4218294 -0.9897733 2.216972 -1.379331 1.728286 -0.09836178
col8 col9 col10 col11 col12 col13 col14
row1 1.066351 -0.9308493 -0.4490403 0.007359389 0.6478827 0.5884877 -0.6226272
col15 col16 col17 col18 col19 col20
row1 1.36543 -1.687435 -0.2625077 -1.318051 1.131943 -0.8648045
> tmp[,"col10"]
col10
row1 -0.4490403
row2 1.3892455
row3 -0.9539420
row4 -0.2906837
row5 2.1400812
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.2423656 0.4218294 -0.9897733 2.216972 -1.379331 1.72828593 -0.09836178
row5 0.5759471 2.3397200 0.2297529 1.493702 -0.377072 -0.05513715 0.02852752
col8 col9 col10 col11 col12 col13
row1 1.066351 -0.93084927 -0.4490403 0.007359389 0.6478827 0.5884877
row5 -2.050021 -0.09397217 2.1400812 0.580233202 -1.1986155 -1.4010011
col14 col15 col16 col17 col18 col19 col20
row1 -0.6226272 1.3654301 -1.68743498 -0.2625077 -1.318051 1.131943 -0.8648045
row5 2.0194861 0.5001898 -0.08453184 0.8667058 -1.711265 1.099390 -0.9328809
> tmp[,c("col6","col20")]
col6 col20
row1 1.72828593 -0.8648045
row2 0.35608923 -0.7934847
row3 -1.12016017 -2.2360315
row4 1.45763870 0.5585283
row5 -0.05513715 -0.9328809
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.72828593 -0.8648045
row5 -0.05513715 -0.9328809
>
>
>
>
> 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 50.73595 51.38793 49.56129 48.04373 49.83412 106.2894 49.29796 48.88975
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.97677 49.99268 51.29953 47.52398 49.06257 50.73616 49.19344 50.07716
col17 col18 col19 col20
row1 50.72559 49.85895 51.08974 104.4406
> tmp[,"col10"]
col10
row1 49.99268
row2 30.29956
row3 29.57976
row4 32.19628
row5 49.47480
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.73595 51.38793 49.56129 48.04373 49.83412 106.2894 49.29796 48.88975
row5 50.11972 48.57047 50.19075 49.54027 51.17595 105.3088 49.67357 49.60150
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.97677 49.99268 51.29953 47.52398 49.06257 50.73616 49.19344 50.07716
row5 49.46403 49.47480 50.04877 48.62686 49.99113 50.97479 50.93999 49.88866
col17 col18 col19 col20
row1 50.72559 49.85895 51.08974 104.4406
row5 50.30030 49.82410 52.04579 103.3329
> tmp[,c("col6","col20")]
col6 col20
row1 106.28936 104.44064
row2 75.18628 73.28222
row3 74.80523 74.82588
row4 75.53966 74.82447
row5 105.30876 103.33293
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.2894 104.4406
row5 105.3088 103.3329
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.2894 104.4406
row5 105.3088 103.3329
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4434871
[2,] -2.2313621
[3,] 0.5408854
[4,] 0.4448908
[5,] 1.1173686
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.17465130 -0.85939009
[2,] -0.01217128 -0.85831775
[3,] 0.36944679 0.19373890
[4,] -1.15840401 0.15843363
[5,] 0.07366053 -0.06774885
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.56601009 0.5461982
[2,] -0.31037259 1.4711460
[3,] 1.84876702 -0.4617958
[4,] 1.70035118 -0.8671748
[5,] -0.00416979 -0.3685538
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.56601
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.5660101
[2,] -0.3103726
>
>
>
> 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 0.6164747 0.1913840 -0.5877428 -0.6271821 0.2784962 -0.07581653
row1 2.1327578 0.8859629 0.2105315 -1.0319095 -0.9502273 0.89786724
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.06362796 -1.444914 -0.1704647 -0.2538876 -0.5257637 -0.3286465 2.4859046
row1 2.01622346 1.025245 1.6932991 -1.1240826 -1.8003768 -0.5998996 0.9470819
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.6232886 -0.8309601 1.29108293 0.4127739 -0.5403662 1.035853 -0.6714945
row1 0.4823387 0.3359187 0.05161646 1.2962428 -0.4788455 1.997561 0.3187558
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.2576579 -1.044953 1.000317 -0.3806148 0.5635515 -1.905486 0.3954682
[,8] [,9] [,10]
row2 -1.870779 0.07511262 -1.292234
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.7606081 -0.8052066 -0.04897064 -0.16666 -0.9627396 0.2917553 -0.4773175
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.1943693 -0.5536392 0.1448004 -0.1558408 0.5003795 -0.04126028 0.2728743
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8385443 -0.9527392 0.1806809 -0.6247546 -0.80107 0.5204037
>
>
> 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: 0x630d808cdb10>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e55d02d121"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e5417d5be3"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e514388442"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e542d48a1c"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e54660d811"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e55f840852"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e5631f4d07"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e57cdf2513"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e5235fb7ad"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e555982bb"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e52aab503c"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e55ca4a014"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e576370301"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e57dc07b81"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM2fb4e52b1f3c69"
>
>
> ### 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: 0x630d8066b6b0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x630d8066b6b0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x630d8066b6b0>
> rowMedians(tmp)
[1] 2.955210e-01 -3.409084e-01 4.541856e-02 1.776150e-01 -3.940038e-01
[6] 2.964825e-01 4.628530e-02 2.314505e-01 2.998753e-01 3.159223e-01
[11] -3.279448e-01 -2.273505e-01 -1.304535e-01 1.299439e-01 -1.308397e-01
[16] -5.866754e-01 -1.678450e-01 4.241304e-01 -3.921755e-01 1.011466e+00
[21] -6.475128e-01 -1.047576e-01 -6.450643e-02 2.741901e-01 -1.396677e-02
[26] -7.920127e-01 3.705926e-01 1.899573e-01 -3.745919e-01 2.645977e-01
[31] 2.038302e-01 -5.251943e-01 5.173721e-01 -4.843440e-01 -8.843544e-02
[36] -2.960899e-01 1.068492e+00 5.878034e-02 -2.292641e-01 2.577400e-01
[41] 4.868022e-01 -4.994307e-01 -4.937407e-01 -7.310358e-02 -4.844067e-01
[46] 2.851850e-01 -2.274390e-02 -8.960833e-02 -5.111940e-01 -1.620013e-01
[51] -9.101411e-02 -4.067701e-01 4.540009e-02 5.921553e-01 -2.080624e-01
[56] -9.131207e-01 8.589052e-02 -4.227535e-02 -1.028709e-01 1.713507e-01
[61] -6.489859e-02 -2.519257e-01 -4.823410e-01 6.908593e-05 -5.502758e-01
[66] 3.841535e-01 3.633957e-01 3.219662e-02 5.502504e-01 2.920528e-01
[71] 4.379539e-01 3.717241e-01 4.035700e-02 -4.135421e-01 3.823105e-01
[76] -3.805122e-01 -1.853221e-01 -5.961848e-01 -3.312990e-01 1.873179e-02
[81] 4.062579e-02 1.453667e-01 -5.582375e-01 -1.302407e-01 1.911139e-01
[86] 3.702649e-01 1.076054e-02 -6.012046e-01 3.724482e-01 -1.316933e-01
[91] -6.906606e-03 -6.694672e-01 1.279976e-01 2.920822e-01 1.950672e-01
[96] 2.608394e-01 3.250338e-01 -1.365312e-01 -1.939599e-01 -4.366058e-01
[101] -7.832781e-02 -5.638017e-02 1.142877e-01 5.702752e-02 1.200732e-01
[106] 1.752690e-01 1.553080e-01 8.664853e-02 -1.064393e-01 7.178889e-01
[111] -2.947996e-01 5.310131e-01 1.137142e-01 3.349509e-01 -4.088932e-02
[116] -3.666803e-01 -1.355791e-01 -8.014808e-03 -1.086114e-01 -6.308080e-01
[121] -3.625433e-02 1.235877e+00 1.163938e-01 -3.319275e-02 7.004486e-02
[126] 2.577293e-01 1.487019e-01 1.974642e-01 6.311015e-01 -1.481496e-01
[131] 3.245516e-01 -2.560041e-01 -1.975467e-01 5.757181e-02 1.180261e-02
[136] 9.523291e-02 -7.152613e-01 -3.255581e-01 -1.270169e-01 -4.540205e-01
[141] -2.196282e-01 5.177925e-01 1.192456e-01 4.132358e-02 -7.332705e-02
[146] -1.821217e-01 -3.404355e-01 -1.227325e-01 -1.184626e-01 1.065500e-01
[151] 4.910442e-01 2.419017e-01 -2.842016e-01 -2.215415e-01 3.912010e-01
[156] 4.704546e-01 -8.352873e-01 1.025615e-01 3.868359e-01 3.595442e-02
[161] 4.048562e-01 7.236742e-03 2.250780e-01 1.656002e-01 -7.913526e-02
[166] -2.244170e-01 -2.388673e-01 -7.193546e-02 3.989740e-01 3.539941e-01
[171] 1.591250e-01 -7.869487e-02 6.673646e-01 -1.511273e-01 3.047904e-02
[176] -4.592404e-01 -2.392599e-01 5.319713e-01 5.899034e-02 3.109924e-01
[181] -3.963405e-03 2.419162e-01 -1.218519e-01 9.728096e-01 -1.691014e-01
[186] -7.202706e-02 1.651629e-01 -6.332738e-03 5.498970e-01 -4.162703e-01
[191] 4.497517e-03 -5.368780e-01 -4.645813e-02 -3.948572e-01 1.163043e-01
[196] 2.360589e-01 4.687844e-01 -2.085678e-01 -7.845175e-02 -3.844460e-01
[201] -1.847884e-01 5.745319e-01 -3.466194e-01 -3.411413e-01 3.588557e-01
[206] 3.297430e-01 -3.390899e-01 -2.215905e-01 4.504213e-01 3.633277e-01
[211] -5.064035e-01 -5.692418e-01 -1.406378e-01 5.885845e-01 2.404657e-01
[216] 7.326232e-01 -3.078852e-01 -1.856675e-01 -1.044142e-01 1.878248e-01
[221] -1.308387e-01 5.336414e-01 -2.018689e-01 -9.191331e-02 1.678682e-01
[226] -3.420018e-01 -4.249064e-02 -2.021061e-01 -1.383472e-01 -2.470594e-01
>
> proc.time()
user system elapsed
1.226 0.665 1.879
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x59b59b47fb10>
> .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: 0x59b59b47fb10>
> .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: 0x59b59b47fb10>
> .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: 0x59b59b47fb10>
> 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: 0x59b59a131660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b59a131660>
> .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: 0x59b59a131660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b59a131660>
> .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: 0x59b59a131660>
> 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: 0x59b599d12c40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b599d12c40>
> .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: 0x59b599d12c40>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x59b599d12c40>
> .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: 0x59b599d12c40>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x59b599d12c40>
> .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: 0x59b599d12c40>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x59b599d12c40>
> .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: 0x59b599d12c40>
> 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: 0x59b59c7fe4f0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x59b59c7fe4f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b59c7fe4f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b59c7fe4f0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2fb596541f9102" "BufferedMatrixFile2fb5967afec967"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2fb596541f9102" "BufferedMatrixFile2fb5967afec967"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b59c13ca80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b59c13ca80>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x59b59c13ca80>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x59b59c13ca80>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x59b59c13ca80>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x59b59c13ca80>
> .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: 0x59b59c019750>
> .Call("R_bm_AddColumn",P)
<pointer: 0x59b59c019750>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x59b59c019750>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x59b59c019750>
> 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: 0x59b59a089fc0>
> .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: 0x59b59a089fc0>
> rm(P)
>
> proc.time()
user system elapsed
0.254 0.044 0.287
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.245 0.045 0.279