Ben Bolstad
| Snapshot Date: 2026-01-23 13:40 -0500 (Fri, 23 Jan 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-01-24 11:34 -0500 (Sat, 24 Jan 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences" | 4811 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences" | 4545 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 253/2345 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.75.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.75.0.tar.gz |
| StartedAt: 2026-01-23 18:54:15 -0500 (Fri, 23 Jan 2026) |
| EndedAt: 2026-01-23 18:54:37 -0500 (Fri, 23 Jan 2026) |
| EllapsedTime: 21.3 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.75.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 16.0.0 (clang-1600.0.26.6)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.75.0’
* 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 ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.1.sdk’
* 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 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 ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 1 NOTE
See
‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.1.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.6-arm64/Resources/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 Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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
0.124 0.050 0.182
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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] "/Users/biocbuild/bbs-3.23-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) limit (Mb) max used (Mb)
Ncells 481350 25.8 1058420 56.6 NA 633731 33.9
Vcells 891641 6.9 8388608 64.0 196608 2111489 16.2
>
>
>
>
> ##
> ## 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 Jan 23 18:54:27 2026"
> 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 Jan 23 18:54:27 2026"
>
>
> 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: 0x6000015802a0>
>
>
>
> 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 Jan 23 18:54:28 2026"
> 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 Jan 23 18:54:29 2026"
>
> ColMode(tmp2)
<pointer: 0x6000015802a0>
>
>
>
> ### 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,] 99.18986915 0.07165383 0.4148084 1.3390891
[2,] -0.81817307 -0.03107842 1.2893548 -0.2725216
[3,] -0.13101402 1.60930702 -1.4216107 -1.6570286
[4,] 0.04277688 -0.77783730 1.1579379 0.3743091
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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,] 99.18986915 0.07165383 0.4148084 1.3390891
[2,] 0.81817307 0.03107842 1.2893548 0.2725216
[3,] 0.13101402 1.60930702 1.4216107 1.6570286
[4,] 0.04277688 0.77783730 1.1579379 0.3743091
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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,] 9.9594111 0.2676823 0.6440562 1.157190
[2,] 0.9045292 0.1762907 1.1354976 0.522036
[3,] 0.3619586 1.2685847 1.1923132 1.287256
[4,] 0.2068257 0.8819509 1.0760753 0.611808
>
> 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: /Users/biocbuild/bbs-3.23-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,] 223.78398 27.74848 31.85537 37.91099
[2,] 34.86347 26.79399 37.64433 30.49288
[3,] 28.75060 39.29515 38.34474 39.52959
[4,] 27.11103 34.59735 36.91869 31.49239
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000015a41e0>
> exp(tmp5)
<pointer: 0x6000015a41e0>
> log(tmp5,2)
<pointer: 0x6000015a41e0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.777
> Min(tmp5)
[1] 52.80446
> mean(tmp5)
[1] 72.82444
> Sum(tmp5)
[1] 14564.89
> Var(tmp5)
[1] 849.0036
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.28918 71.80094 74.10248 68.58045 70.83245 69.63341 70.71997 71.67208
[9] 68.18491 71.42853
> rowSums(tmp5)
[1] 1825.784 1436.019 1482.050 1371.609 1416.649 1392.668 1414.399 1433.442
[9] 1363.698 1428.571
> rowVars(tmp5)
[1] 7870.23461 44.42475 63.22361 58.33879 90.30223 65.92333
[7] 46.69390 75.24901 64.37949 87.08864
> rowSd(tmp5)
[1] 88.714343 6.665189 7.951328 7.637983 9.502748 8.119318 6.833294
[8] 8.674619 8.023683 9.332129
> rowMax(tmp5)
[1] 465.77703 88.77158 87.15332 81.12959 84.88368 86.53306 80.01630
[8] 81.93854 85.44908 90.90722
> rowMin(tmp5)
[1] 54.80206 55.76817 59.84061 53.93629 55.09208 52.80446 54.65007 55.30745
[9] 53.88723 58.02083
>
> colMeans(tmp5)
[1] 107.49180 69.08217 71.72857 71.63890 66.71967 72.69810 75.88940
[8] 72.44048 67.32136 68.57173 71.78427 71.05263 72.49183 69.83624
[15] 67.28014 74.81904 70.39471 74.50383 70.17436 70.56958
> colSums(tmp5)
[1] 1074.9180 690.8217 717.2857 716.3890 667.1967 726.9810 758.8940
[8] 724.4048 673.2136 685.7173 717.8427 710.5263 724.9183 698.3624
[15] 672.8014 748.1904 703.9471 745.0383 701.7436 705.6958
> colVars(tmp5)
[1] 15909.48952 93.44960 46.33843 71.27025 51.31178 88.29846
[7] 41.40313 86.45232 91.08899 74.50785 97.53889 101.65771
[13] 14.35571 152.39479 27.57098 45.03836 60.23513 35.68565
[19] 62.34599 85.93251
> colSd(tmp5)
[1] 126.132825 9.666933 6.807234 8.442171 7.163224 9.396726
[7] 6.434527 9.297974 9.544055 8.631793 9.876178 10.082545
[13] 3.788893 12.344828 5.250808 6.711063 7.761130 5.973746
[19] 7.895948 9.269979
> colMax(tmp5)
[1] 465.77703 84.43771 79.80956 86.53306 80.17564 90.90722 85.02610
[8] 84.88368 82.24746 85.44908 84.68269 88.77158 81.38505 90.63246
[15] 73.78547 87.15332 79.44893 81.90734 83.05951 81.08079
> colMin(tmp5)
[1] 56.42807 55.76817 62.40559 63.46694 58.02083 61.86694 66.11595 54.32319
[9] 54.65007 59.26807 57.18066 56.79712 68.76780 53.93629 57.65957 64.15944
[17] 54.80206 65.84195 52.80446 53.88723
>
>
> ### 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] NA 71.80094 74.10248 68.58045 70.83245 69.63341 70.71997 71.67208
[9] 68.18491 71.42853
> rowSums(tmp5)
[1] NA 1436.019 1482.050 1371.609 1416.649 1392.668 1414.399 1433.442
[9] 1363.698 1428.571
> rowVars(tmp5)
[1] 8272.53448 44.42475 63.22361 58.33879 90.30223 65.92333
[7] 46.69390 75.24901 64.37949 87.08864
> rowSd(tmp5)
[1] 90.953474 6.665189 7.951328 7.637983 9.502748 8.119318 6.833294
[8] 8.674619 8.023683 9.332129
> rowMax(tmp5)
[1] NA 88.77158 87.15332 81.12959 84.88368 86.53306 80.01630 81.93854
[9] 85.44908 90.90722
> rowMin(tmp5)
[1] NA 55.76817 59.84061 53.93629 55.09208 52.80446 54.65007 55.30745
[9] 53.88723 58.02083
>
> colMeans(tmp5)
[1] 107.49180 69.08217 71.72857 71.63890 NA 72.69810 75.88940
[8] 72.44048 67.32136 68.57173 71.78427 71.05263 72.49183 69.83624
[15] 67.28014 74.81904 70.39471 74.50383 70.17436 70.56958
> colSums(tmp5)
[1] 1074.9180 690.8217 717.2857 716.3890 NA 726.9810 758.8940
[8] 724.4048 673.2136 685.7173 717.8427 710.5263 724.9183 698.3624
[15] 672.8014 748.1904 703.9471 745.0383 701.7436 705.6958
> colVars(tmp5)
[1] 15909.48952 93.44960 46.33843 71.27025 NA 88.29846
[7] 41.40313 86.45232 91.08899 74.50785 97.53889 101.65771
[13] 14.35571 152.39479 27.57098 45.03836 60.23513 35.68565
[19] 62.34599 85.93251
> colSd(tmp5)
[1] 126.132825 9.666933 6.807234 8.442171 NA 9.396726
[7] 6.434527 9.297974 9.544055 8.631793 9.876178 10.082545
[13] 3.788893 12.344828 5.250808 6.711063 7.761130 5.973746
[19] 7.895948 9.269979
> colMax(tmp5)
[1] 465.77703 84.43771 79.80956 86.53306 NA 90.90722 85.02610
[8] 84.88368 82.24746 85.44908 84.68269 88.77158 81.38505 90.63246
[15] 73.78547 87.15332 79.44893 81.90734 83.05951 81.08079
> colMin(tmp5)
[1] 56.42807 55.76817 62.40559 63.46694 NA 61.86694 66.11595 54.32319
[9] 54.65007 59.26807 57.18066 56.79712 68.76780 53.93629 57.65957 64.15944
[17] 54.80206 65.84195 52.80446 53.88723
>
> Max(tmp5,na.rm=TRUE)
[1] 465.777
> Min(tmp5,na.rm=TRUE)
[1] 52.80446
> mean(tmp5,na.rm=TRUE)
[1] 72.85448
> Sum(tmp5,na.rm=TRUE)
[1] 14498.04
> Var(tmp5,na.rm=TRUE)
[1] 853.1101
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.57558 71.80094 74.10248 68.58045 70.83245 69.63341 70.71997 71.67208
[9] 68.18491 71.42853
> rowSums(tmp5,na.rm=TRUE)
[1] 1758.936 1436.019 1482.050 1371.609 1416.649 1392.668 1414.399 1433.442
[9] 1363.698 1428.571
> rowVars(tmp5,na.rm=TRUE)
[1] 8272.53448 44.42475 63.22361 58.33879 90.30223 65.92333
[7] 46.69390 75.24901 64.37949 87.08864
> rowSd(tmp5,na.rm=TRUE)
[1] 90.953474 6.665189 7.951328 7.637983 9.502748 8.119318 6.833294
[8] 8.674619 8.023683 9.332129
> rowMax(tmp5,na.rm=TRUE)
[1] 465.77703 88.77158 87.15332 81.12959 84.88368 86.53306 80.01630
[8] 81.93854 85.44908 90.90722
> rowMin(tmp5,na.rm=TRUE)
[1] 54.80206 55.76817 59.84061 53.93629 55.09208 52.80446 54.65007 55.30745
[9] 53.88723 58.02083
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.49180 69.08217 71.72857 71.63890 66.70547 72.69810 75.88940
[8] 72.44048 67.32136 68.57173 71.78427 71.05263 72.49183 69.83624
[15] 67.28014 74.81904 70.39471 74.50383 70.17436 70.56958
> colSums(tmp5,na.rm=TRUE)
[1] 1074.9180 690.8217 717.2857 716.3890 600.3492 726.9810 758.8940
[8] 724.4048 673.2136 685.7173 717.8427 710.5263 724.9183 698.3624
[15] 672.8014 748.1904 703.9471 745.0383 701.7436 705.6958
> colVars(tmp5,na.rm=TRUE)
[1] 15909.48952 93.44960 46.33843 71.27025 57.72348 88.29846
[7] 41.40313 86.45232 91.08899 74.50785 97.53889 101.65771
[13] 14.35571 152.39479 27.57098 45.03836 60.23513 35.68565
[19] 62.34599 85.93251
> colSd(tmp5,na.rm=TRUE)
[1] 126.132825 9.666933 6.807234 8.442171 7.597597 9.396726
[7] 6.434527 9.297974 9.544055 8.631793 9.876178 10.082545
[13] 3.788893 12.344828 5.250808 6.711063 7.761130 5.973746
[19] 7.895948 9.269979
> colMax(tmp5,na.rm=TRUE)
[1] 465.77703 84.43771 79.80956 86.53306 80.17564 90.90722 85.02610
[8] 84.88368 82.24746 85.44908 84.68269 88.77158 81.38505 90.63246
[15] 73.78547 87.15332 79.44893 81.90734 83.05951 81.08079
> colMin(tmp5,na.rm=TRUE)
[1] 56.42807 55.76817 62.40559 63.46694 58.02083 61.86694 66.11595 54.32319
[9] 54.65007 59.26807 57.18066 56.79712 68.76780 53.93629 57.65957 64.15944
[17] 54.80206 65.84195 52.80446 53.88723
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.80094 74.10248 68.58045 70.83245 69.63341 70.71997 71.67208
[9] 68.18491 71.42853
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1436.019 1482.050 1371.609 1416.649 1392.668 1414.399 1433.442
[9] 1363.698 1428.571
> rowVars(tmp5,na.rm=TRUE)
[1] NA 44.42475 63.22361 58.33879 90.30223 65.92333 46.69390 75.24901
[9] 64.37949 87.08864
> rowSd(tmp5,na.rm=TRUE)
[1] NA 6.665189 7.951328 7.637983 9.502748 8.119318 6.833294 8.674619
[9] 8.023683 9.332129
> rowMax(tmp5,na.rm=TRUE)
[1] NA 88.77158 87.15332 81.12959 84.88368 86.53306 80.01630 81.93854
[9] 85.44908 90.90722
> rowMin(tmp5,na.rm=TRUE)
[1] NA 55.76817 59.84061 53.93629 55.09208 52.80446 54.65007 55.30745
[9] 53.88723 58.02083
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 67.68233 70.34076 72.33144 70.83135 NaN 71.59909 75.53528 73.08883
[9] 67.90219 67.73529 70.35111 72.63658 72.43718 67.52554 68.02290 74.76554
[17] 72.12723 74.70516 68.74268 70.39013
> colSums(tmp5,na.rm=TRUE)
[1] 609.1409 633.0669 650.9830 637.4822 0.0000 644.3918 679.8175 657.7994
[9] 611.1197 609.6177 633.1600 653.7292 651.9346 607.7299 612.2061 672.8898
[17] 649.1451 672.3465 618.6841 633.5112
> colVars(tmp5,na.rm=TRUE)
[1] 69.24347 87.31013 48.04195 72.84267 NA 85.74780 45.16770
[8] 92.52991 98.67976 75.95048 86.62440 86.14000 16.11657 111.37705
[15] 24.81084 50.63595 33.99634 39.69036 47.07992 96.31180
> colSd(tmp5,na.rm=TRUE)
[1] 8.321266 9.343989 6.931230 8.534791 NA 9.260011 6.720692
[8] 9.619247 9.933769 8.714957 9.307223 9.281164 4.014545 10.553532
[15] 4.981048 7.115894 5.830638 6.300028 6.861481 9.813857
> colMax(tmp5,na.rm=TRUE)
[1] 81.89340 84.43771 79.80956 86.53306 -Inf 90.90722 85.02610 84.88368
[9] 82.24746 85.44908 81.93854 88.77158 81.38505 81.10265 73.78547 87.15332
[17] 79.44893 81.90734 75.99483 81.08079
> colMin(tmp5,na.rm=TRUE)
[1] 56.42807 55.76817 62.40559 63.46694 Inf 61.86694 66.11595 54.32319
[9] 54.65007 59.26807 57.18066 58.85175 68.76780 53.93629 57.65957 64.15944
[17] 63.94823 65.84195 52.80446 53.88723
>
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col <- 1
> cat(which.row," ",which.col,"\n")
3 1
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> rowVars(tmp5,na.rm=TRUE)
[1] 162.5420 222.9462 318.9944 254.1672 435.9720 310.3276 334.3525 245.6426
[9] 188.4736 250.9443
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 162.5420 222.9462 318.9944 254.1672 435.9720 310.3276 334.3525 245.6426
[9] 188.4736 250.9443
>
>
>
> 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] 5.684342e-14 0.000000e+00 -1.421085e-14 8.526513e-14 0.000000e+00
[6] -2.557954e-13 -1.705303e-13 -2.842171e-14 0.000000e+00 -8.526513e-14
[11] -2.842171e-14 -1.136868e-13 0.000000e+00 0.000000e+00 5.684342e-14
[16] -2.842171e-14 0.000000e+00 -1.136868e-13 -2.557954e-13 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)
+ }
4 1
6 9
3 19
10 18
6 11
1 3
2 8
7 12
2 10
1 7
6 10
4 2
10 4
3 12
9 3
9 12
7 1
9 13
2 12
4 9
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] 2.143744
> Min(tmp)
[1] -2.962614
> mean(tmp)
[1] -0.1022598
> Sum(tmp)
[1] -10.22598
> Var(tmp)
[1] 0.8622036
>
> rowMeans(tmp)
[1] -0.1022598
> rowSums(tmp)
[1] -10.22598
> rowVars(tmp)
[1] 0.8622036
> rowSd(tmp)
[1] 0.9285492
> rowMax(tmp)
[1] 2.143744
> rowMin(tmp)
[1] -2.962614
>
> colMeans(tmp)
[1] 0.66584523 -0.94601505 -0.69667268 -0.20749052 -0.14648220 -1.26157804
[7] -0.46543307 0.62776965 1.94858229 0.28403485 0.09753046 0.46337517
[13] -0.72795768 -1.80211046 -0.01523196 0.71256063 0.64473979 0.06067949
[19] -1.29266611 0.51802726 -1.11850140 0.25691757 -0.14959069 -0.40608475
[25] -0.94536125 0.72460442 -1.80624049 -0.03057131 0.35356793 2.14374393
[31] 0.64693258 1.74610318 -0.48338743 0.66140855 0.45919408 -0.86954849
[37] 1.03480866 -0.90588245 -0.26879435 -0.36570110 -0.11578182 0.64117953
[43] 0.74129521 0.75627544 -0.94855610 -0.48985555 -0.16115035 -0.74909261
[49] -0.07304295 -0.78303033 -0.84569561 1.26133834 0.68664538 -0.03138112
[55] -1.06843229 -2.96261398 -1.05501925 -0.54711531 -0.20447893 0.18564470
[61] 0.48148651 -0.44334276 0.06140542 -0.98541607 0.09738496 -1.27928342
[67] 0.08792461 -0.55057460 0.62859505 -0.67667153 1.30387008 -1.41971085
[73] -0.66571439 1.09682790 1.14818592 -0.64767910 -0.47622133 0.49131549
[79] 0.43309728 1.38411293 0.75982491 0.19455970 0.40927843 -0.14003123
[85] -1.04934115 1.03249161 0.05433527 -0.61987044 1.55325206 -0.05036057
[91] 1.57865578 -0.61765968 -1.83103406 -0.40355478 -0.86258245 -0.82755077
[97] 0.70172902 -1.67705450 -2.12997509 0.25306135
> colSums(tmp)
[1] 0.66584523 -0.94601505 -0.69667268 -0.20749052 -0.14648220 -1.26157804
[7] -0.46543307 0.62776965 1.94858229 0.28403485 0.09753046 0.46337517
[13] -0.72795768 -1.80211046 -0.01523196 0.71256063 0.64473979 0.06067949
[19] -1.29266611 0.51802726 -1.11850140 0.25691757 -0.14959069 -0.40608475
[25] -0.94536125 0.72460442 -1.80624049 -0.03057131 0.35356793 2.14374393
[31] 0.64693258 1.74610318 -0.48338743 0.66140855 0.45919408 -0.86954849
[37] 1.03480866 -0.90588245 -0.26879435 -0.36570110 -0.11578182 0.64117953
[43] 0.74129521 0.75627544 -0.94855610 -0.48985555 -0.16115035 -0.74909261
[49] -0.07304295 -0.78303033 -0.84569561 1.26133834 0.68664538 -0.03138112
[55] -1.06843229 -2.96261398 -1.05501925 -0.54711531 -0.20447893 0.18564470
[61] 0.48148651 -0.44334276 0.06140542 -0.98541607 0.09738496 -1.27928342
[67] 0.08792461 -0.55057460 0.62859505 -0.67667153 1.30387008 -1.41971085
[73] -0.66571439 1.09682790 1.14818592 -0.64767910 -0.47622133 0.49131549
[79] 0.43309728 1.38411293 0.75982491 0.19455970 0.40927843 -0.14003123
[85] -1.04934115 1.03249161 0.05433527 -0.61987044 1.55325206 -0.05036057
[91] 1.57865578 -0.61765968 -1.83103406 -0.40355478 -0.86258245 -0.82755077
[97] 0.70172902 -1.67705450 -2.12997509 0.25306135
> 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] 0.66584523 -0.94601505 -0.69667268 -0.20749052 -0.14648220 -1.26157804
[7] -0.46543307 0.62776965 1.94858229 0.28403485 0.09753046 0.46337517
[13] -0.72795768 -1.80211046 -0.01523196 0.71256063 0.64473979 0.06067949
[19] -1.29266611 0.51802726 -1.11850140 0.25691757 -0.14959069 -0.40608475
[25] -0.94536125 0.72460442 -1.80624049 -0.03057131 0.35356793 2.14374393
[31] 0.64693258 1.74610318 -0.48338743 0.66140855 0.45919408 -0.86954849
[37] 1.03480866 -0.90588245 -0.26879435 -0.36570110 -0.11578182 0.64117953
[43] 0.74129521 0.75627544 -0.94855610 -0.48985555 -0.16115035 -0.74909261
[49] -0.07304295 -0.78303033 -0.84569561 1.26133834 0.68664538 -0.03138112
[55] -1.06843229 -2.96261398 -1.05501925 -0.54711531 -0.20447893 0.18564470
[61] 0.48148651 -0.44334276 0.06140542 -0.98541607 0.09738496 -1.27928342
[67] 0.08792461 -0.55057460 0.62859505 -0.67667153 1.30387008 -1.41971085
[73] -0.66571439 1.09682790 1.14818592 -0.64767910 -0.47622133 0.49131549
[79] 0.43309728 1.38411293 0.75982491 0.19455970 0.40927843 -0.14003123
[85] -1.04934115 1.03249161 0.05433527 -0.61987044 1.55325206 -0.05036057
[91] 1.57865578 -0.61765968 -1.83103406 -0.40355478 -0.86258245 -0.82755077
[97] 0.70172902 -1.67705450 -2.12997509 0.25306135
> colMin(tmp)
[1] 0.66584523 -0.94601505 -0.69667268 -0.20749052 -0.14648220 -1.26157804
[7] -0.46543307 0.62776965 1.94858229 0.28403485 0.09753046 0.46337517
[13] -0.72795768 -1.80211046 -0.01523196 0.71256063 0.64473979 0.06067949
[19] -1.29266611 0.51802726 -1.11850140 0.25691757 -0.14959069 -0.40608475
[25] -0.94536125 0.72460442 -1.80624049 -0.03057131 0.35356793 2.14374393
[31] 0.64693258 1.74610318 -0.48338743 0.66140855 0.45919408 -0.86954849
[37] 1.03480866 -0.90588245 -0.26879435 -0.36570110 -0.11578182 0.64117953
[43] 0.74129521 0.75627544 -0.94855610 -0.48985555 -0.16115035 -0.74909261
[49] -0.07304295 -0.78303033 -0.84569561 1.26133834 0.68664538 -0.03138112
[55] -1.06843229 -2.96261398 -1.05501925 -0.54711531 -0.20447893 0.18564470
[61] 0.48148651 -0.44334276 0.06140542 -0.98541607 0.09738496 -1.27928342
[67] 0.08792461 -0.55057460 0.62859505 -0.67667153 1.30387008 -1.41971085
[73] -0.66571439 1.09682790 1.14818592 -0.64767910 -0.47622133 0.49131549
[79] 0.43309728 1.38411293 0.75982491 0.19455970 0.40927843 -0.14003123
[85] -1.04934115 1.03249161 0.05433527 -0.61987044 1.55325206 -0.05036057
[91] 1.57865578 -0.61765968 -1.83103406 -0.40355478 -0.86258245 -0.82755077
[97] 0.70172902 -1.67705450 -2.12997509 0.25306135
> colMedians(tmp)
[1] 0.66584523 -0.94601505 -0.69667268 -0.20749052 -0.14648220 -1.26157804
[7] -0.46543307 0.62776965 1.94858229 0.28403485 0.09753046 0.46337517
[13] -0.72795768 -1.80211046 -0.01523196 0.71256063 0.64473979 0.06067949
[19] -1.29266611 0.51802726 -1.11850140 0.25691757 -0.14959069 -0.40608475
[25] -0.94536125 0.72460442 -1.80624049 -0.03057131 0.35356793 2.14374393
[31] 0.64693258 1.74610318 -0.48338743 0.66140855 0.45919408 -0.86954849
[37] 1.03480866 -0.90588245 -0.26879435 -0.36570110 -0.11578182 0.64117953
[43] 0.74129521 0.75627544 -0.94855610 -0.48985555 -0.16115035 -0.74909261
[49] -0.07304295 -0.78303033 -0.84569561 1.26133834 0.68664538 -0.03138112
[55] -1.06843229 -2.96261398 -1.05501925 -0.54711531 -0.20447893 0.18564470
[61] 0.48148651 -0.44334276 0.06140542 -0.98541607 0.09738496 -1.27928342
[67] 0.08792461 -0.55057460 0.62859505 -0.67667153 1.30387008 -1.41971085
[73] -0.66571439 1.09682790 1.14818592 -0.64767910 -0.47622133 0.49131549
[79] 0.43309728 1.38411293 0.75982491 0.19455970 0.40927843 -0.14003123
[85] -1.04934115 1.03249161 0.05433527 -0.61987044 1.55325206 -0.05036057
[91] 1.57865578 -0.61765968 -1.83103406 -0.40355478 -0.86258245 -0.82755077
[97] 0.70172902 -1.67705450 -2.12997509 0.25306135
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.6658452 -0.9460151 -0.6966727 -0.2074905 -0.1464822 -1.261578 -0.4654331
[2,] 0.6658452 -0.9460151 -0.6966727 -0.2074905 -0.1464822 -1.261578 -0.4654331
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.6277697 1.948582 0.2840348 0.09753046 0.4633752 -0.7279577 -1.80211
[2,] 0.6277697 1.948582 0.2840348 0.09753046 0.4633752 -0.7279577 -1.80211
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.01523196 0.7125606 0.6447398 0.06067949 -1.292666 0.5180273 -1.118501
[2,] -0.01523196 0.7125606 0.6447398 0.06067949 -1.292666 0.5180273 -1.118501
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.2569176 -0.1495907 -0.4060848 -0.9453612 0.7246044 -1.80624 -0.03057131
[2,] 0.2569176 -0.1495907 -0.4060848 -0.9453612 0.7246044 -1.80624 -0.03057131
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.3535679 2.143744 0.6469326 1.746103 -0.4833874 0.6614086 0.4591941
[2,] 0.3535679 2.143744 0.6469326 1.746103 -0.4833874 0.6614086 0.4591941
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.8695485 1.034809 -0.9058824 -0.2687944 -0.3657011 -0.1157818 0.6411795
[2,] -0.8695485 1.034809 -0.9058824 -0.2687944 -0.3657011 -0.1157818 0.6411795
[,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.7412952 0.7562754 -0.9485561 -0.4898555 -0.1611503 -0.7490926
[2,] 0.7412952 0.7562754 -0.9485561 -0.4898555 -0.1611503 -0.7490926
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.07304295 -0.7830303 -0.8456956 1.261338 0.6866454 -0.03138112 -1.068432
[2,] -0.07304295 -0.7830303 -0.8456956 1.261338 0.6866454 -0.03138112 -1.068432
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -2.962614 -1.055019 -0.5471153 -0.2044789 0.1856447 0.4814865 -0.4433428
[2,] -2.962614 -1.055019 -0.5471153 -0.2044789 0.1856447 0.4814865 -0.4433428
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.06140542 -0.9854161 0.09738496 -1.279283 0.08792461 -0.5505746 0.628595
[2,] 0.06140542 -0.9854161 0.09738496 -1.279283 0.08792461 -0.5505746 0.628595
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.6766715 1.30387 -1.419711 -0.6657144 1.096828 1.148186 -0.6476791
[2,] -0.6766715 1.30387 -1.419711 -0.6657144 1.096828 1.148186 -0.6476791
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.4762213 0.4913155 0.4330973 1.384113 0.7598249 0.1945597 0.4092784
[2,] -0.4762213 0.4913155 0.4330973 1.384113 0.7598249 0.1945597 0.4092784
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.1400312 -1.049341 1.032492 0.05433527 -0.6198704 1.553252 -0.05036057
[2,] -0.1400312 -1.049341 1.032492 0.05433527 -0.6198704 1.553252 -0.05036057
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.578656 -0.6176597 -1.831034 -0.4035548 -0.8625824 -0.8275508 0.701729
[2,] 1.578656 -0.6176597 -1.831034 -0.4035548 -0.8625824 -0.8275508 0.701729
[,98] [,99] [,100]
[1,] -1.677054 -2.129975 0.2530614
[2,] -1.677054 -2.129975 0.2530614
>
>
> Max(tmp2)
[1] 2.511511
> Min(tmp2)
[1] -2.392696
> mean(tmp2)
[1] -0.1775527
> Sum(tmp2)
[1] -17.75527
> Var(tmp2)
[1] 0.9871073
>
> rowMeans(tmp2)
[1] -0.308913709 -2.008939070 -0.311607520 0.626231995 -0.005384358
[6] -2.380918577 -1.840105819 0.118462312 0.907740418 0.702804108
[11] -2.000738912 1.208545150 -0.048360608 1.040514069 0.264624720
[16] 0.710506598 -2.126698017 0.487128897 1.115803161 -0.185038257
[21] -0.476678647 -0.367272355 -0.068982848 1.423326601 -0.316927307
[26] -0.420679947 1.728354944 -0.325703429 0.414214259 1.580091007
[31] -0.660194693 -0.144057680 -1.400785688 -0.954916174 -0.514016352
[36] -1.679950806 0.485060424 0.375622513 -0.920838988 0.734999786
[41] 1.121384661 2.511510623 0.846543051 -1.269390767 0.847804275
[46] -0.792676491 -0.856665971 0.709566642 -0.124099452 0.176793442
[51] -1.772700106 -1.364303999 -0.994238443 -0.385647610 1.356838483
[56] -1.248814223 -0.936564035 0.483010878 -0.539158180 0.121926804
[61] 0.198084094 -2.392695554 -0.497259869 -0.787314163 0.225095579
[66] -0.960085026 -0.124774061 -0.475844316 0.555785927 0.817467192
[71] 0.286206990 -0.375858731 -0.227248202 1.376037263 -1.426960817
[76] -0.911642361 -0.351559957 1.345044535 0.560544008 -0.765294327
[81] -2.366605751 -0.295740646 -0.505569510 0.105925541 -0.488572077
[86] 1.910468099 0.369171377 -1.270854178 -0.359569418 0.115207397
[91] -1.416321810 -0.524327806 -0.035509069 -0.818282755 0.380413153
[96] -0.718726116 0.511932016 -0.528346148 -0.125377424 -0.109757646
> rowSums(tmp2)
[1] -0.308913709 -2.008939070 -0.311607520 0.626231995 -0.005384358
[6] -2.380918577 -1.840105819 0.118462312 0.907740418 0.702804108
[11] -2.000738912 1.208545150 -0.048360608 1.040514069 0.264624720
[16] 0.710506598 -2.126698017 0.487128897 1.115803161 -0.185038257
[21] -0.476678647 -0.367272355 -0.068982848 1.423326601 -0.316927307
[26] -0.420679947 1.728354944 -0.325703429 0.414214259 1.580091007
[31] -0.660194693 -0.144057680 -1.400785688 -0.954916174 -0.514016352
[36] -1.679950806 0.485060424 0.375622513 -0.920838988 0.734999786
[41] 1.121384661 2.511510623 0.846543051 -1.269390767 0.847804275
[46] -0.792676491 -0.856665971 0.709566642 -0.124099452 0.176793442
[51] -1.772700106 -1.364303999 -0.994238443 -0.385647610 1.356838483
[56] -1.248814223 -0.936564035 0.483010878 -0.539158180 0.121926804
[61] 0.198084094 -2.392695554 -0.497259869 -0.787314163 0.225095579
[66] -0.960085026 -0.124774061 -0.475844316 0.555785927 0.817467192
[71] 0.286206990 -0.375858731 -0.227248202 1.376037263 -1.426960817
[76] -0.911642361 -0.351559957 1.345044535 0.560544008 -0.765294327
[81] -2.366605751 -0.295740646 -0.505569510 0.105925541 -0.488572077
[86] 1.910468099 0.369171377 -1.270854178 -0.359569418 0.115207397
[91] -1.416321810 -0.524327806 -0.035509069 -0.818282755 0.380413153
[96] -0.718726116 0.511932016 -0.528346148 -0.125377424 -0.109757646
> 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] -0.308913709 -2.008939070 -0.311607520 0.626231995 -0.005384358
[6] -2.380918577 -1.840105819 0.118462312 0.907740418 0.702804108
[11] -2.000738912 1.208545150 -0.048360608 1.040514069 0.264624720
[16] 0.710506598 -2.126698017 0.487128897 1.115803161 -0.185038257
[21] -0.476678647 -0.367272355 -0.068982848 1.423326601 -0.316927307
[26] -0.420679947 1.728354944 -0.325703429 0.414214259 1.580091007
[31] -0.660194693 -0.144057680 -1.400785688 -0.954916174 -0.514016352
[36] -1.679950806 0.485060424 0.375622513 -0.920838988 0.734999786
[41] 1.121384661 2.511510623 0.846543051 -1.269390767 0.847804275
[46] -0.792676491 -0.856665971 0.709566642 -0.124099452 0.176793442
[51] -1.772700106 -1.364303999 -0.994238443 -0.385647610 1.356838483
[56] -1.248814223 -0.936564035 0.483010878 -0.539158180 0.121926804
[61] 0.198084094 -2.392695554 -0.497259869 -0.787314163 0.225095579
[66] -0.960085026 -0.124774061 -0.475844316 0.555785927 0.817467192
[71] 0.286206990 -0.375858731 -0.227248202 1.376037263 -1.426960817
[76] -0.911642361 -0.351559957 1.345044535 0.560544008 -0.765294327
[81] -2.366605751 -0.295740646 -0.505569510 0.105925541 -0.488572077
[86] 1.910468099 0.369171377 -1.270854178 -0.359569418 0.115207397
[91] -1.416321810 -0.524327806 -0.035509069 -0.818282755 0.380413153
[96] -0.718726116 0.511932016 -0.528346148 -0.125377424 -0.109757646
> rowMin(tmp2)
[1] -0.308913709 -2.008939070 -0.311607520 0.626231995 -0.005384358
[6] -2.380918577 -1.840105819 0.118462312 0.907740418 0.702804108
[11] -2.000738912 1.208545150 -0.048360608 1.040514069 0.264624720
[16] 0.710506598 -2.126698017 0.487128897 1.115803161 -0.185038257
[21] -0.476678647 -0.367272355 -0.068982848 1.423326601 -0.316927307
[26] -0.420679947 1.728354944 -0.325703429 0.414214259 1.580091007
[31] -0.660194693 -0.144057680 -1.400785688 -0.954916174 -0.514016352
[36] -1.679950806 0.485060424 0.375622513 -0.920838988 0.734999786
[41] 1.121384661 2.511510623 0.846543051 -1.269390767 0.847804275
[46] -0.792676491 -0.856665971 0.709566642 -0.124099452 0.176793442
[51] -1.772700106 -1.364303999 -0.994238443 -0.385647610 1.356838483
[56] -1.248814223 -0.936564035 0.483010878 -0.539158180 0.121926804
[61] 0.198084094 -2.392695554 -0.497259869 -0.787314163 0.225095579
[66] -0.960085026 -0.124774061 -0.475844316 0.555785927 0.817467192
[71] 0.286206990 -0.375858731 -0.227248202 1.376037263 -1.426960817
[76] -0.911642361 -0.351559957 1.345044535 0.560544008 -0.765294327
[81] -2.366605751 -0.295740646 -0.505569510 0.105925541 -0.488572077
[86] 1.910468099 0.369171377 -1.270854178 -0.359569418 0.115207397
[91] -1.416321810 -0.524327806 -0.035509069 -0.818282755 0.380413153
[96] -0.718726116 0.511932016 -0.528346148 -0.125377424 -0.109757646
>
> colMeans(tmp2)
[1] -0.1775527
> colSums(tmp2)
[1] -17.75527
> colVars(tmp2)
[1] 0.9871073
> colSd(tmp2)
[1] 0.9935327
> colMax(tmp2)
[1] 2.511511
> colMin(tmp2)
[1] -2.392696
> colMedians(tmp2)
[1] -0.2061432
> colRanges(tmp2)
[,1]
[1,] -2.392696
[2,] 2.511511
>
> 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] -1.7685323 3.9742765 -3.7212220 0.5684073 1.9913288 -6.8898771
[7] -3.0748632 -0.7032812 -4.2726722 -2.8241086
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7168189
[2,] -1.1530324
[3,] -0.3581258
[4,] 0.5044696
[5,] 2.4140925
>
> rowApply(tmp,sum)
[1] 1.1960153 -0.5383748 -8.0448835 1.3973850 -4.7450032 -2.9688525
[7] -0.6118386 -0.7494822 -1.9540399 0.2985303
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 1 10 10 4 7 1 2 4 4
[2,] 10 7 5 4 9 10 7 9 9 7
[3,] 2 3 7 7 6 3 9 5 3 5
[4,] 4 9 6 5 5 4 6 10 5 8
[5,] 6 8 8 9 7 5 5 3 6 6
[6,] 9 5 4 1 3 1 4 7 7 3
[7,] 8 2 3 6 10 6 2 1 10 2
[8,] 1 6 2 3 8 8 10 8 2 9
[9,] 3 4 1 2 2 9 3 4 8 10
[10,] 5 10 9 8 1 2 8 6 1 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.8357525 2.8030606 -0.6736164 0.5526337 1.8440707 0.1792133
[7] -5.2115285 1.9291466 -0.4424001 -1.0008848 1.6391052 -5.3086638
[13] -3.5751826 0.6571413 -0.9085691 0.4724846 -0.4053935 -0.6738135
[19] 2.6754552 2.6049387
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8808147
[2,] -1.2553419
[3,] -0.7778581
[4,] -0.2622084
[5,] 0.3404707
>
> rowApply(tmp,sum)
[1] -4.8382032 0.4716685 1.2201271 -5.7750247 2.2428773
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 1 5 5 9
[2,] 17 14 17 17 10
[3,] 6 8 8 10 12
[4,] 12 18 18 8 3
[5,] 19 5 16 13 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.3404707 0.48811543 -0.62706711 0.01425442 0.9423236 -0.7368884
[2,] -1.8808147 0.63286178 -0.26750564 1.26623559 -1.0619304 1.3225794
[3,] -0.7778581 1.22272006 -0.28122696 1.24669122 1.1468107 -0.0440388
[4,] -1.2553419 0.52439578 0.01552698 -0.48796214 0.2360755 0.5214666
[5,] -0.2622084 -0.06503241 0.48665630 -1.48658539 0.5807913 -0.8839055
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.7471320 -0.1568954 0.4732022 -0.6212882 -0.1857201 -1.689361388
[2,] -0.3306955 0.9116869 0.1429608 -1.8197582 0.9453260 0.477347626
[3,] -1.7414270 -0.6597627 0.7073565 1.2694026 -0.5338910 -0.004973925
[4,] -0.8835071 -0.5756862 -1.8809400 1.1501125 0.3143870 -2.433476004
[5,] -0.5087670 2.4098041 0.1150204 -0.9793534 1.0990033 -1.658200061
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.09494311 0.8863980 -1.8572849 0.006271264 -2.18714689 0.1820053
[2,] -1.08103716 0.1100119 0.4802723 -0.205336397 1.04066976 -1.2602465
[3,] 0.46424293 -1.0701127 0.2176567 -1.095237725 0.21378172 0.6193069
[4,] -1.47509128 -0.0336710 -1.7736091 0.341923507 0.02070591 0.1672111
[5,] -1.57824020 0.7645151 2.0243959 1.424863920 0.50659595 -0.3820902
[,19] [,20]
[1,] -0.08409928 1.6266967
[2,] 1.49406223 -0.4450212
[3,] 1.46250079 -1.1418142
[4,] 1.05364644 0.6788089
[5,] -1.25065499 1.8862686
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.55133 -0.3046865 0.2142368 -0.9526348 -1.296746 2.172278 -0.8229643
col8 col9 col10 col11 col12 col13 col14
row1 0.6476886 -1.401863 0.2544009 0.4902808 0.2731106 -2.369085 -0.07693975
col15 col16 col17 col18 col19 col20
row1 0.3001555 -0.1281175 -0.948134 0.9309478 -0.4375983 1.94091
> tmp[,"col10"]
col10
row1 0.2544009
row2 -0.5184225
row3 -0.5146419
row4 1.2804975
row5 -2.5997305
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.551330 -0.3046865 0.2142368 -0.95263482 -1.2967463 2.17227773
row5 0.201725 -2.0189272 -0.6909989 0.07927501 -0.1361072 -0.04284206
col7 col8 col9 col10 col11 col12 col13
row1 -0.8229643 0.6476886 -1.401863 0.2544009 0.4902808 0.2731106 -2.3690853
row5 0.4812358 -2.5519994 1.678446 -2.5997305 0.7603623 -0.1464185 -0.2994794
col14 col15 col16 col17 col18 col19
row1 -0.07693975 0.3001555 -0.1281175 -0.948134 0.9309478 -0.4375983
row5 -1.41278024 -1.5202543 1.4914718 -1.110224 0.9828948 0.6924323
col20
row1 1.94090994
row5 0.08867787
> tmp[,c("col6","col20")]
col6 col20
row1 2.17227773 1.94090994
row2 -1.17361924 0.71361206
row3 -0.21675994 1.52997793
row4 -1.22068027 1.20739836
row5 -0.04284206 0.08867787
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 2.17227773 1.94090994
row5 -0.04284206 0.08867787
>
>
>
>
> 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 50.46881 50.44709 49.50372 49.55876 49.22206 105.788 51.57818 50.58228
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.13828 49.18507 47.84735 50.63095 51.2707 49.57708 49.37711 51.36179
col17 col18 col19 col20
row1 48.83208 51.45001 51.15619 106.3003
> tmp[,"col10"]
col10
row1 49.18507
row2 29.87335
row3 30.74594
row4 29.84177
row5 49.87402
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.46881 50.44709 49.50372 49.55876 49.22206 105.7880 51.57818 50.58228
row5 50.95635 49.53661 49.46481 50.85281 51.87600 104.6918 49.55758 48.36267
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.13828 49.18507 47.84735 50.63095 51.27070 49.57708 49.37711 51.36179
row5 51.29683 49.87402 49.92014 49.40872 51.30316 49.20590 49.55232 49.43025
col17 col18 col19 col20
row1 48.83208 51.45001 51.15619 106.3003
row5 51.23970 50.35469 49.25212 105.7976
> tmp[,c("col6","col20")]
col6 col20
row1 105.78800 106.30027
row2 72.71303 75.61964
row3 74.27554 74.12199
row4 75.35557 74.79884
row5 104.69179 105.79756
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7880 106.3003
row5 104.6918 105.7976
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7880 106.3003
row5 104.6918 105.7976
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.6203639
[2,] 0.8924508
[3,] 1.2262299
[4,] -0.8995325
[5,] 0.2989763
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.0460477 -0.23677293
[2,] 1.9241757 0.55552050
[3,] 0.1791586 -0.03421778
[4,] 0.3207591 0.12250055
[5,] 0.8309257 0.08062135
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.1940763 -0.02960511
[2,] 0.7255180 -0.18677629
[3,] 0.8139138 -0.76827826
[4,] 0.3878847 1.84028091
[5,] -1.6638019 -0.40550331
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.1940763
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.1940763
[2,] 0.7255180
>
>
>
> 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 -1.5665949 -0.6637607 -0.4233296 0.9713759 0.7654716 -1.0518467
row1 0.5739986 -0.2466429 -0.2303086 -1.4816219 1.3468102 0.5073288
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.8806227 -0.929184 -0.04980872 -1.1199947 0.9172674 1.2514271 0.9597534
row1 0.3422368 -1.231667 0.46183833 -0.5353728 0.2738093 -0.1783682 1.5116576
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3998565 -0.6601507 -0.4411645 -0.1116209 0.08021549 -0.01414651
row1 1.2606620 -0.2603714 0.4677482 0.1956748 -0.66938468 -0.77731599
[,20]
row3 -0.7738022
row1 0.7624961
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.03001176 -0.4581286 1.075371 -0.7598892 -0.4962925 0.8598029 0.8825966
[,8] [,9] [,10]
row2 -1.285702 0.3335744 0.1981785
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.8848965 1.985102 0.1662979 -1.081907 0.5203003 -0.1518244 1.775093
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.932102 -0.05755584 0.1680719 1.720764 -0.5249212 -1.182119 -0.4389371
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4495051 -0.8716232 -0.7262508 -1.767968 0.8117567 0.1569854
>
>
> 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: 0x600001580300>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855cda64511"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c1f006617"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c532e7fe7"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c11cf415b"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c3dcbc67f"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855cd54db8b"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c3e198983"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c7e93174e"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c6adf42cd"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c679ad78b"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c66bd1bd0"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c96d2962"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c5db7e5c3"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c544d9546"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1855c318351e7"
>
>
> ### 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: 0x600001580480>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001580480>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001580480>
> rowMedians(tmp)
[1] -0.238756778 0.039861320 0.133394234 1.012833438 -0.242433139
[6] 0.224411236 -0.223248110 0.300356104 0.709469642 0.083497708
[11] -0.303582314 -0.135968032 0.015812045 0.023599560 0.471101157
[16] -0.774263924 0.722342554 0.679784829 0.297403079 -0.211966263
[21] -0.193351439 0.257919369 0.071670528 -0.124318478 0.132084748
[26] -0.209521402 0.431332972 0.702763940 0.330941720 -0.148406476
[31] -0.081280825 0.107576982 -0.414638778 0.169391685 -0.483684445
[36] -0.281022083 -0.301516618 -0.604093405 0.610312343 0.086228877
[41] 0.300863136 -0.269026881 -0.165404825 0.168981549 0.147035539
[46] 0.342480928 0.095875598 0.575699067 -0.159133020 0.448320699
[51] 0.046019828 0.353634010 0.309090633 -0.034671385 -0.441953979
[56] 0.171602773 0.146192893 0.179956532 0.164062045 -0.067324539
[61] 0.707720940 -0.598848187 0.089107725 0.372910197 0.022549979
[66] 0.190486083 -0.645614647 0.024911354 0.106601177 -0.319554699
[71] 0.062809482 0.166201133 -0.044790850 -0.310336688 -0.029074174
[76] -0.081697877 -0.028934432 -0.181804810 -0.345877370 0.027996619
[81] -0.040305197 0.385654205 0.432125980 -0.225033089 -0.395850339
[86] -0.091534506 -0.114649444 0.032413206 -0.499323960 0.189333653
[91] 0.220971735 -0.373324737 0.617354629 0.567612595 0.221899268
[96] 0.046401453 -0.619135870 -0.420684576 0.129032961 -0.779004540
[101] 0.129006624 0.683164627 0.625164767 -0.077914037 -0.172951961
[106] 0.551614314 -0.332233036 -0.104904885 -0.107169528 -0.428665143
[111] -0.377849573 0.111178862 -0.147412764 -0.141604985 0.140100233
[116] 0.016125124 -0.335136057 0.173993486 -0.238266250 -0.206845547
[121] -0.037280465 0.446562351 -0.236173116 -0.744122525 0.120178073
[126] 0.146687354 0.180558329 0.418994058 0.349611251 0.134506389
[131] 0.164615907 0.254682223 0.153945860 0.295985387 0.394756794
[136] -0.403135922 0.109572262 -0.124681905 -0.084301434 0.426611006
[141] 0.027472650 0.061120578 0.241978164 0.368353227 -0.423163611
[146] 0.246385466 -0.015432105 -0.343326614 -0.359292185 -0.626730131
[151] -0.137697523 0.625605557 -0.269227162 -0.848868334 -0.288462518
[156] -0.032135941 0.335328700 -0.211152203 -0.166210694 -0.244388311
[161] -0.804356441 -0.044190418 -0.442719453 -0.156585415 -0.158474307
[166] 0.395051736 -0.302297359 -0.421446747 -0.052145504 0.042895385
[171] -0.333089349 -0.037954873 0.329578094 0.262766522 -0.065542492
[176] -0.329574798 -0.250600193 -0.333312737 -0.409070566 -0.293933920
[181] 0.156408323 0.586398460 0.176174082 0.196560760 -0.285170101
[186] 0.056618940 -0.137804403 0.422138406 -0.123123347 0.165579377
[191] -0.022061029 0.241964778 -0.306438239 -0.112080684 -0.495182281
[196] -0.412098175 -0.445797942 -0.124357025 -0.312359923 0.773213547
[201] -0.208367395 0.096833315 0.111823714 0.636582915 0.367692392
[206] -0.014244218 -0.488655630 0.575816777 -0.355355312 0.129403842
[211] 0.192583886 0.000358048 -0.044392177 0.333121532 0.089954830
[216] 0.029378778 -0.048365610 -0.022445734 -0.202868390 -0.457599338
[221] -0.491183731 0.112504680 -0.146313186 0.557781243 -0.145605551
[226] 0.264329975 -0.322571719 -0.098193204 -0.357774372 -0.025018771
>
> proc.time()
user system elapsed
0.718 3.642 5.193
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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: 0x600001888000>
> .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: 0x600001888000>
> .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: 0x600001888000>
> .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: 0x600001888000>
> 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: 0x600001894660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001894660>
> .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: 0x600001894660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001894660>
> .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: 0x600001894660>
> 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: 0x600001894840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001894840>
> .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: 0x600001894840>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001894840>
> .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: 0x600001894840>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001894840>
> .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: 0x600001894840>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001894840>
> .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: 0x600001894840>
> 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: 0x600001894a20>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600001894a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001894a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001894a20>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4e5163d300e" "BufferedMatrixFile4e575d1a360"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4e5163d300e" "BufferedMatrixFile4e575d1a360"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018841e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018841e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000018841e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000018841e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000018841e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000018841e0>
> .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: 0x6000018843c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018843c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000018843c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000018843c0>
> 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: 0x6000018845a0>
> .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: 0x6000018845a0>
> rm(P)
>
> proc.time()
user system elapsed
0.141 0.060 0.197
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
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Platform: aarch64-apple-darwin20
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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
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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
0.124 0.033 0.154