Ben Bolstad
| Snapshot Date: 2026-03-20 13:40 -0400 (Fri, 20 Mar 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 -0400 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-03-21 11:34 -0400 (Sat, 21 Mar 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences" | 4866 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-03-20 r89666) -- "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 257/2368 | 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 | ERROR | |||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
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: 2026-03-20 21:43:47 -0400 (Fri, 20 Mar 2026) |
| EndedAt: 2026-03-20 21:44:12 -0400 (Fri, 20 Mar 2026) |
| EllapsedTime: 25.2 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) (2026-03-20 r89666)
* using platform: aarch64-apple-darwin23
* R was compiled by
Apple clang version 17.0.0 (clang-1700.3.19.1)
GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-03-21 01:43:47 UTC
* 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 17.0.0 (clang-1700.6.4.2)’
* used SDK: ‘MacOSX26.2.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/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 17.0.0 (clang-1700.6.4.2)’
using SDK: ‘MacOSX26.2.sdk’
clang -arch arm64 -std=gnu23 -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=gnu23 -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]
1580 | if (!(Matrix->readonly) & setting){
| ^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
1580 | if (!(Matrix->readonly) & setting){
| ^
| ( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
1580 | if (!(Matrix->readonly) & setting){
| ^
| ( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
2 warnings generated.
clang -arch arm64 -std=gnu23 -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=gnu23 -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=gnu23 -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/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) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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
0.156 0.065 0.220
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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 484118 25.9 1067182 57 NA 632022 33.8
Vcells 896941 6.9 8388608 64 196608 2112082 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 Mar 20 21:44:00 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 Mar 20 21:44:00 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: 0x10169cd20>
>
>
>
> 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 Mar 20 21:44:02 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 Mar 20 21:44:03 2026"
>
> ColMode(tmp2)
<pointer: 0x10169cd20>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.7815787 -1.9689716 -0.2224074 -0.28661724
[2,] -0.1468801 0.6198358 0.0458471 -0.07027764
[3,] -1.1256542 0.8197941 0.2970724 -0.04316265
[4,] 0.5587228 -0.4275271 -1.8308993 0.03460941
> 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,] 98.7815787 1.9689716 0.2224074 0.28661724
[2,] 0.1468801 0.6198358 0.0458471 0.07027764
[3,] 1.1256542 0.8197941 0.2970724 0.04316265
[4,] 0.5587228 0.4275271 1.8308993 0.03460941
> 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,] 9.9388922 1.4032005 0.4716009 0.5353665
[2,] 0.3832494 0.7872965 0.2141194 0.2650993
[3,] 1.0609685 0.9054248 0.5450435 0.2077562
[4,] 0.7474777 0.6538556 1.3531073 0.1860360
>
> 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,] 223.17050 41.00098 29.93842 30.64028
[2,] 28.97937 33.49280 27.18704 27.72127
[3,] 36.73534 34.87404 30.74751 27.12072
[4,] 33.03350 31.96608 40.36197 26.89497
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x101670480>
> exp(tmp5)
<pointer: 0x101670480>
> log(tmp5,2)
<pointer: 0x101670480>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 464.5002
> Min(tmp5)
[1] 52.77438
> mean(tmp5)
[1] 72.80632
> Sum(tmp5)
[1] 14561.26
> Var(tmp5)
[1] 854.1978
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.01263 68.53555 71.51627 72.04155 73.20723 69.93867 70.38687 70.30705
[9] 70.56477 69.55262
> rowSums(tmp5)
[1] 1840.253 1370.711 1430.325 1440.831 1464.145 1398.773 1407.737 1406.141
[9] 1411.295 1391.052
> rowVars(tmp5)
[1] 7761.14571 63.35559 96.45714 100.97595 86.72382 47.94935
[7] 105.17702 66.60219 68.12288 102.22934
> rowSd(tmp5)
[1] 88.097365 7.959622 9.821259 10.048679 9.312562 6.924547 10.255585
[8] 8.161016 8.253659 10.110853
> rowMax(tmp5)
[1] 464.50016 83.27935 91.35839 93.56907 88.20222 83.52751 88.00280
[8] 85.19139 83.17596 86.76394
> rowMin(tmp5)
[1] 60.14256 56.58626 55.32589 55.97836 53.72779 58.88396 56.57397 54.74486
[9] 54.63508 52.77438
>
> colMeans(tmp5)
[1] 105.70759 73.37972 71.69138 66.14396 72.51615 70.53467 76.47844
[8] 73.39738 69.51107 70.26130 68.51159 72.44128 71.16179 72.13282
[15] 71.05447 69.28663 74.93984 61.54975 71.54234 73.88429
> colSums(tmp5)
[1] 1057.0759 733.7972 716.9138 661.4396 725.1615 705.3467 764.7844
[8] 733.9738 695.1107 702.6130 685.1159 724.4128 711.6179 721.3282
[15] 710.5447 692.8663 749.3984 615.4975 715.4234 738.8429
> colVars(tmp5)
[1] 15968.71955 35.71606 123.22122 85.43062 78.58752 55.44552
[7] 57.61457 46.26870 44.48774 64.58175 75.50370 47.39789
[13] 72.75188 91.86720 130.22514 67.40342 136.53707 40.91287
[19] 108.24023 71.81452
> colSd(tmp5)
[1] 126.367399 5.976291 11.100505 9.242869 8.864960 7.446175
[7] 7.590426 6.802110 6.669913 8.036277 8.689287 6.884612
[13] 8.529471 9.584738 11.411623 8.209959 11.684908 6.396317
[19] 10.403856 8.474345
> colMax(tmp5)
[1] 464.50016 85.33816 86.76394 83.62106 83.27935 79.72985 88.20222
[8] 84.82031 80.39466 83.02714 82.83826 82.23198 86.56947 85.58974
[15] 91.35839 79.20642 93.56907 72.95485 88.80291 84.20749
> colMin(tmp5)
[1] 55.62863 66.53321 56.58626 55.97836 53.72779 57.38995 60.84233 63.90733
[9] 56.99566 55.32589 57.04807 64.97888 60.14256 58.55731 52.77438 54.74486
[17] 59.24411 54.63508 56.32115 62.11799
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 92.01263 68.53555 71.51627 NA 73.20723 69.93867 70.38687 70.30705
[9] 70.56477 69.55262
> rowSums(tmp5)
[1] 1840.253 1370.711 1430.325 NA 1464.145 1398.773 1407.737 1406.141
[9] 1411.295 1391.052
> rowVars(tmp5)
[1] 7761.14571 63.35559 96.45714 98.06934 86.72382 47.94935
[7] 105.17702 66.60219 68.12288 102.22934
> rowSd(tmp5)
[1] 88.097365 7.959622 9.821259 9.902997 9.312562 6.924547 10.255585
[8] 8.161016 8.253659 10.110853
> rowMax(tmp5)
[1] 464.50016 83.27935 91.35839 NA 88.20222 83.52751 88.00280
[8] 85.19139 83.17596 86.76394
> rowMin(tmp5)
[1] 60.14256 56.58626 55.32589 NA 53.72779 58.88396 56.57397 54.74486
[9] 54.63508 52.77438
>
> colMeans(tmp5)
[1] 105.70759 73.37972 71.69138 66.14396 72.51615 70.53467 76.47844
[8] 73.39738 69.51107 70.26130 68.51159 72.44128 71.16179 72.13282
[15] 71.05447 NA 74.93984 61.54975 71.54234 73.88429
> colSums(tmp5)
[1] 1057.0759 733.7972 716.9138 661.4396 725.1615 705.3467 764.7844
[8] 733.9738 695.1107 702.6130 685.1159 724.4128 711.6179 721.3282
[15] 710.5447 NA 749.3984 615.4975 715.4234 738.8429
> colVars(tmp5)
[1] 15968.71955 35.71606 123.22122 85.43062 78.58752 55.44552
[7] 57.61457 46.26870 44.48774 64.58175 75.50370 47.39789
[13] 72.75188 91.86720 130.22514 NA 136.53707 40.91287
[19] 108.24023 71.81452
> colSd(tmp5)
[1] 126.367399 5.976291 11.100505 9.242869 8.864960 7.446175
[7] 7.590426 6.802110 6.669913 8.036277 8.689287 6.884612
[13] 8.529471 9.584738 11.411623 NA 11.684908 6.396317
[19] 10.403856 8.474345
> colMax(tmp5)
[1] 464.50016 85.33816 86.76394 83.62106 83.27935 79.72985 88.20222
[8] 84.82031 80.39466 83.02714 82.83826 82.23198 86.56947 85.58974
[15] 91.35839 NA 93.56907 72.95485 88.80291 84.20749
> colMin(tmp5)
[1] 55.62863 66.53321 56.58626 55.97836 53.72779 57.38995 60.84233 63.90733
[9] 56.99566 55.32589 57.04807 64.97888 60.14256 58.55731 52.77438 NA
[17] 59.24411 54.63508 56.32115 62.11799
>
> Max(tmp5,na.rm=TRUE)
[1] 464.5002
> Min(tmp5,na.rm=TRUE)
[1] 52.77438
> mean(tmp5,na.rm=TRUE)
[1] 72.87081
> Sum(tmp5,na.rm=TRUE)
[1] 14501.29
> Var(tmp5,na.rm=TRUE)
[1] 857.6761
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.01263 68.53555 71.51627 72.67670 73.20723 69.93867 70.38687 70.30705
[9] 70.56477 69.55262
> rowSums(tmp5,na.rm=TRUE)
[1] 1840.253 1370.711 1430.325 1380.857 1464.145 1398.773 1407.737 1406.141
[9] 1411.295 1391.052
> rowVars(tmp5,na.rm=TRUE)
[1] 7761.14571 63.35559 96.45714 98.06934 86.72382 47.94935
[7] 105.17702 66.60219 68.12288 102.22934
> rowSd(tmp5,na.rm=TRUE)
[1] 88.097365 7.959622 9.821259 9.902997 9.312562 6.924547 10.255585
[8] 8.161016 8.253659 10.110853
> rowMax(tmp5,na.rm=TRUE)
[1] 464.50016 83.27935 91.35839 93.56907 88.20222 83.52751 88.00280
[8] 85.19139 83.17596 86.76394
> rowMin(tmp5,na.rm=TRUE)
[1] 60.14256 56.58626 55.32589 55.97836 53.72779 58.88396 56.57397 54.74486
[9] 54.63508 52.77438
>
> colMeans(tmp5,na.rm=TRUE)
[1] 105.70759 73.37972 71.69138 66.14396 72.51615 70.53467 76.47844
[8] 73.39738 69.51107 70.26130 68.51159 72.44128 71.16179 72.13282
[15] 71.05447 70.32138 74.93984 61.54975 71.54234 73.88429
> colSums(tmp5,na.rm=TRUE)
[1] 1057.0759 733.7972 716.9138 661.4396 725.1615 705.3467 764.7844
[8] 733.9738 695.1107 702.6130 685.1159 724.4128 711.6179 721.3282
[15] 710.5447 632.8924 749.3984 615.4975 715.4234 738.8429
> colVars(tmp5,na.rm=TRUE)
[1] 15968.71955 35.71606 123.22122 85.43062 78.58752 55.44552
[7] 57.61457 46.26870 44.48774 64.58175 75.50370 47.39789
[13] 72.75188 91.86720 130.22514 63.78325 136.53707 40.91287
[19] 108.24023 71.81452
> colSd(tmp5,na.rm=TRUE)
[1] 126.367399 5.976291 11.100505 9.242869 8.864960 7.446175
[7] 7.590426 6.802110 6.669913 8.036277 8.689287 6.884612
[13] 8.529471 9.584738 11.411623 7.986442 11.684908 6.396317
[19] 10.403856 8.474345
> colMax(tmp5,na.rm=TRUE)
[1] 464.50016 85.33816 86.76394 83.62106 83.27935 79.72985 88.20222
[8] 84.82031 80.39466 83.02714 82.83826 82.23198 86.56947 85.58974
[15] 91.35839 79.20642 93.56907 72.95485 88.80291 84.20749
> colMin(tmp5,na.rm=TRUE)
[1] 55.62863 66.53321 56.58626 55.97836 53.72779 57.38995 60.84233 63.90733
[9] 56.99566 55.32589 57.04807 64.97888 60.14256 58.55731 52.77438 54.74486
[17] 59.24411 54.63508 56.32115 62.11799
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.01263 68.53555 71.51627 NaN 73.20723 69.93867 70.38687 70.30705
[9] 70.56477 69.55262
> rowSums(tmp5,na.rm=TRUE)
[1] 1840.253 1370.711 1430.325 0.000 1464.145 1398.773 1407.737 1406.141
[9] 1411.295 1391.052
> rowVars(tmp5,na.rm=TRUE)
[1] 7761.14571 63.35559 96.45714 NA 86.72382 47.94935
[7] 105.17702 66.60219 68.12288 102.22934
> rowSd(tmp5,na.rm=TRUE)
[1] 88.097365 7.959622 9.821259 NA 9.312562 6.924547 10.255585
[8] 8.161016 8.253659 10.110853
> rowMax(tmp5,na.rm=TRUE)
[1] 464.50016 83.27935 91.35839 NA 88.20222 83.52751 88.00280
[8] 85.19139 83.17596 86.76394
> rowMin(tmp5,na.rm=TRUE)
[1] 60.14256 56.58626 55.32589 NA 53.72779 58.88396 56.57397 54.74486
[9] 54.63508 52.77438
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 109.81344 74.14044 70.32285 67.27347 72.46096 69.51298 76.06134
[8] 74.45183 69.03982 70.75128 69.63852 71.47834 70.14127 71.63584
[15] 70.58174 NaN 72.86993 61.71388 72.36654 73.25007
> colSums(tmp5,na.rm=TRUE)
[1] 988.3210 667.2639 632.9057 605.4612 652.1487 625.6168 684.5521 670.0665
[9] 621.3584 636.7615 626.7467 643.3050 631.2714 644.7226 635.2356 0.0000
[17] 655.8294 555.4249 651.2988 659.2506
> colVars(tmp5,na.rm=TRUE)
[1] 17775.15659 33.67020 117.55403 81.75676 88.37669 50.63295
[7] 62.85918 39.54381 47.55039 69.95351 70.65450 42.89103
[13] 70.12935 100.57201 143.98921 NA 105.40307 45.72391
[19] 114.12810 76.26617
> colSd(tmp5,na.rm=TRUE)
[1] 133.323504 5.802603 10.842234 9.041944 9.400888 7.115683
[7] 7.928378 6.288387 6.895679 8.363822 8.405623 6.549124
[13] 8.374327 10.028560 11.999550 NA 10.266600 6.761945
[19] 10.683075 8.733051
> colMax(tmp5,na.rm=TRUE)
[1] 464.50016 85.33816 86.76394 83.62106 83.27935 78.92590 88.20222
[8] 84.82031 80.39466 83.02714 82.83826 82.23198 86.56947 85.58974
[15] 91.35839 -Inf 88.00280 72.95485 88.80291 84.20749
> colMin(tmp5,na.rm=TRUE)
[1] 55.62863 68.01019 56.58626 56.44824 53.72779 57.38995 60.84233 68.12372
[9] 56.99566 55.32589 57.04807 64.97888 60.14256 58.55731 52.77438 Inf
[17] 59.24411 54.63508 56.32115 62.11799
>
>
>
>
> 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] 204.0530 146.8967 262.1582 225.0056 209.9955 156.0659 358.0598 297.8629
[9] 152.7614 395.3049
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 204.0530 146.8967 262.1582 225.0056 209.9955 156.0659 358.0598 297.8629
[9] 152.7614 395.3049
>
>
>
> 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] 4.263256e-14 -2.273737e-13 -1.136868e-13 -1.421085e-14 1.705303e-13
[6] 1.136868e-13 0.000000e+00 2.842171e-14 8.526513e-14 -8.526513e-14
[11] 2.842171e-14 -1.136868e-13 -5.684342e-14 5.684342e-14 -8.526513e-14
[16] 1.421085e-13 -2.557954e-13 -2.842171e-14 -1.136868e-13 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
8 7
4 11
3 1
1 1
6 19
6 4
5 15
7 7
8 11
5 2
8 4
9 3
2 9
3 5
2 19
5 5
2 17
6 17
9 4
8 20
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] 2.496014
> Min(tmp)
[1] -1.969359
> mean(tmp)
[1] 0.1582646
> Sum(tmp)
[1] 15.82646
> Var(tmp)
[1] 0.9813024
>
> rowMeans(tmp)
[1] 0.1582646
> rowSums(tmp)
[1] 15.82646
> rowVars(tmp)
[1] 0.9813024
> rowSd(tmp)
[1] 0.9906071
> rowMax(tmp)
[1] 2.496014
> rowMin(tmp)
[1] -1.969359
>
> colMeans(tmp)
[1] -1.2235271559 0.1840347562 -0.0408265067 0.5679005687 0.9736187958
[6] 0.6329429288 0.4365606314 0.6282009555 -1.8031539825 0.4041248093
[11] -1.0421193102 0.0685973418 0.8719423444 -0.6816238320 -0.0847694656
[16] 0.3894868420 -0.3069452597 -0.8338290559 0.6290635326 -1.2269657063
[21] 1.1720867990 0.2731675588 2.0688236833 1.0168596245 -0.7655847589
[26] 2.4320582770 0.7573005259 0.1874353054 0.9045455510 -0.6832983541
[31] 0.4573600060 0.8526532731 0.5326182287 0.4613495185 0.8799698127
[36] -0.3833642323 -0.2249755717 -1.5390843886 -1.6182105407 0.3223490040
[41] -0.7081215078 1.0962257510 0.9640931184 0.4800014497 0.0157834154
[46] -1.8474109788 0.0277767246 0.0991761202 -0.4462613807 -1.4849122019
[51] -1.4598444562 0.6023277579 1.5277574991 0.2183998915 1.9112678435
[56] -1.9693585557 0.4610206445 0.0647129049 -0.3462695873 -1.1790835305
[61] 0.1474502160 0.1696095604 -0.5379535138 0.7060594080 0.7010688752
[66] -0.9496551065 2.0858108564 1.7445996657 0.5362348122 -0.8797623387
[71] 0.5320797427 -0.9706321485 0.4125716387 0.1030339243 0.7470625977
[76] 1.8334399468 -0.1464194560 0.7108236627 -1.8406961166 0.2190527106
[81] -0.5915301624 -0.6067164941 -0.1539994085 -0.6933000927 0.9489700600
[86] -1.4187406890 -0.3925680879 0.8872850260 -0.3736734748 1.5678823031
[91] 1.8891521753 -0.0002708684 0.5520312570 1.2016576525 1.3990046088
[96] 0.1661129689 2.4960138842 -0.5620323215 0.5531946038 -0.0398410082
> colSums(tmp)
[1] -1.2235271559 0.1840347562 -0.0408265067 0.5679005687 0.9736187958
[6] 0.6329429288 0.4365606314 0.6282009555 -1.8031539825 0.4041248093
[11] -1.0421193102 0.0685973418 0.8719423444 -0.6816238320 -0.0847694656
[16] 0.3894868420 -0.3069452597 -0.8338290559 0.6290635326 -1.2269657063
[21] 1.1720867990 0.2731675588 2.0688236833 1.0168596245 -0.7655847589
[26] 2.4320582770 0.7573005259 0.1874353054 0.9045455510 -0.6832983541
[31] 0.4573600060 0.8526532731 0.5326182287 0.4613495185 0.8799698127
[36] -0.3833642323 -0.2249755717 -1.5390843886 -1.6182105407 0.3223490040
[41] -0.7081215078 1.0962257510 0.9640931184 0.4800014497 0.0157834154
[46] -1.8474109788 0.0277767246 0.0991761202 -0.4462613807 -1.4849122019
[51] -1.4598444562 0.6023277579 1.5277574991 0.2183998915 1.9112678435
[56] -1.9693585557 0.4610206445 0.0647129049 -0.3462695873 -1.1790835305
[61] 0.1474502160 0.1696095604 -0.5379535138 0.7060594080 0.7010688752
[66] -0.9496551065 2.0858108564 1.7445996657 0.5362348122 -0.8797623387
[71] 0.5320797427 -0.9706321485 0.4125716387 0.1030339243 0.7470625977
[76] 1.8334399468 -0.1464194560 0.7108236627 -1.8406961166 0.2190527106
[81] -0.5915301624 -0.6067164941 -0.1539994085 -0.6933000927 0.9489700600
[86] -1.4187406890 -0.3925680879 0.8872850260 -0.3736734748 1.5678823031
[91] 1.8891521753 -0.0002708684 0.5520312570 1.2016576525 1.3990046088
[96] 0.1661129689 2.4960138842 -0.5620323215 0.5531946038 -0.0398410082
> 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] -1.2235271559 0.1840347562 -0.0408265067 0.5679005687 0.9736187958
[6] 0.6329429288 0.4365606314 0.6282009555 -1.8031539825 0.4041248093
[11] -1.0421193102 0.0685973418 0.8719423444 -0.6816238320 -0.0847694656
[16] 0.3894868420 -0.3069452597 -0.8338290559 0.6290635326 -1.2269657063
[21] 1.1720867990 0.2731675588 2.0688236833 1.0168596245 -0.7655847589
[26] 2.4320582770 0.7573005259 0.1874353054 0.9045455510 -0.6832983541
[31] 0.4573600060 0.8526532731 0.5326182287 0.4613495185 0.8799698127
[36] -0.3833642323 -0.2249755717 -1.5390843886 -1.6182105407 0.3223490040
[41] -0.7081215078 1.0962257510 0.9640931184 0.4800014497 0.0157834154
[46] -1.8474109788 0.0277767246 0.0991761202 -0.4462613807 -1.4849122019
[51] -1.4598444562 0.6023277579 1.5277574991 0.2183998915 1.9112678435
[56] -1.9693585557 0.4610206445 0.0647129049 -0.3462695873 -1.1790835305
[61] 0.1474502160 0.1696095604 -0.5379535138 0.7060594080 0.7010688752
[66] -0.9496551065 2.0858108564 1.7445996657 0.5362348122 -0.8797623387
[71] 0.5320797427 -0.9706321485 0.4125716387 0.1030339243 0.7470625977
[76] 1.8334399468 -0.1464194560 0.7108236627 -1.8406961166 0.2190527106
[81] -0.5915301624 -0.6067164941 -0.1539994085 -0.6933000927 0.9489700600
[86] -1.4187406890 -0.3925680879 0.8872850260 -0.3736734748 1.5678823031
[91] 1.8891521753 -0.0002708684 0.5520312570 1.2016576525 1.3990046088
[96] 0.1661129689 2.4960138842 -0.5620323215 0.5531946038 -0.0398410082
> colMin(tmp)
[1] -1.2235271559 0.1840347562 -0.0408265067 0.5679005687 0.9736187958
[6] 0.6329429288 0.4365606314 0.6282009555 -1.8031539825 0.4041248093
[11] -1.0421193102 0.0685973418 0.8719423444 -0.6816238320 -0.0847694656
[16] 0.3894868420 -0.3069452597 -0.8338290559 0.6290635326 -1.2269657063
[21] 1.1720867990 0.2731675588 2.0688236833 1.0168596245 -0.7655847589
[26] 2.4320582770 0.7573005259 0.1874353054 0.9045455510 -0.6832983541
[31] 0.4573600060 0.8526532731 0.5326182287 0.4613495185 0.8799698127
[36] -0.3833642323 -0.2249755717 -1.5390843886 -1.6182105407 0.3223490040
[41] -0.7081215078 1.0962257510 0.9640931184 0.4800014497 0.0157834154
[46] -1.8474109788 0.0277767246 0.0991761202 -0.4462613807 -1.4849122019
[51] -1.4598444562 0.6023277579 1.5277574991 0.2183998915 1.9112678435
[56] -1.9693585557 0.4610206445 0.0647129049 -0.3462695873 -1.1790835305
[61] 0.1474502160 0.1696095604 -0.5379535138 0.7060594080 0.7010688752
[66] -0.9496551065 2.0858108564 1.7445996657 0.5362348122 -0.8797623387
[71] 0.5320797427 -0.9706321485 0.4125716387 0.1030339243 0.7470625977
[76] 1.8334399468 -0.1464194560 0.7108236627 -1.8406961166 0.2190527106
[81] -0.5915301624 -0.6067164941 -0.1539994085 -0.6933000927 0.9489700600
[86] -1.4187406890 -0.3925680879 0.8872850260 -0.3736734748 1.5678823031
[91] 1.8891521753 -0.0002708684 0.5520312570 1.2016576525 1.3990046088
[96] 0.1661129689 2.4960138842 -0.5620323215 0.5531946038 -0.0398410082
> colMedians(tmp)
[1] -1.2235271559 0.1840347562 -0.0408265067 0.5679005687 0.9736187958
[6] 0.6329429288 0.4365606314 0.6282009555 -1.8031539825 0.4041248093
[11] -1.0421193102 0.0685973418 0.8719423444 -0.6816238320 -0.0847694656
[16] 0.3894868420 -0.3069452597 -0.8338290559 0.6290635326 -1.2269657063
[21] 1.1720867990 0.2731675588 2.0688236833 1.0168596245 -0.7655847589
[26] 2.4320582770 0.7573005259 0.1874353054 0.9045455510 -0.6832983541
[31] 0.4573600060 0.8526532731 0.5326182287 0.4613495185 0.8799698127
[36] -0.3833642323 -0.2249755717 -1.5390843886 -1.6182105407 0.3223490040
[41] -0.7081215078 1.0962257510 0.9640931184 0.4800014497 0.0157834154
[46] -1.8474109788 0.0277767246 0.0991761202 -0.4462613807 -1.4849122019
[51] -1.4598444562 0.6023277579 1.5277574991 0.2183998915 1.9112678435
[56] -1.9693585557 0.4610206445 0.0647129049 -0.3462695873 -1.1790835305
[61] 0.1474502160 0.1696095604 -0.5379535138 0.7060594080 0.7010688752
[66] -0.9496551065 2.0858108564 1.7445996657 0.5362348122 -0.8797623387
[71] 0.5320797427 -0.9706321485 0.4125716387 0.1030339243 0.7470625977
[76] 1.8334399468 -0.1464194560 0.7108236627 -1.8406961166 0.2190527106
[81] -0.5915301624 -0.6067164941 -0.1539994085 -0.6933000927 0.9489700600
[86] -1.4187406890 -0.3925680879 0.8872850260 -0.3736734748 1.5678823031
[91] 1.8891521753 -0.0002708684 0.5520312570 1.2016576525 1.3990046088
[96] 0.1661129689 2.4960138842 -0.5620323215 0.5531946038 -0.0398410082
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.223527 0.1840348 -0.04082651 0.5679006 0.9736188 0.6329429 0.4365606
[2,] -1.223527 0.1840348 -0.04082651 0.5679006 0.9736188 0.6329429 0.4365606
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.628201 -1.803154 0.4041248 -1.042119 0.06859734 0.8719423 -0.6816238
[2,] 0.628201 -1.803154 0.4041248 -1.042119 0.06859734 0.8719423 -0.6816238
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.08476947 0.3894868 -0.3069453 -0.8338291 0.6290635 -1.226966 1.172087
[2,] -0.08476947 0.3894868 -0.3069453 -0.8338291 0.6290635 -1.226966 1.172087
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.2731676 2.068824 1.01686 -0.7655848 2.432058 0.7573005 0.1874353
[2,] 0.2731676 2.068824 1.01686 -0.7655848 2.432058 0.7573005 0.1874353
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.9045456 -0.6832984 0.45736 0.8526533 0.5326182 0.4613495 0.8799698
[2,] 0.9045456 -0.6832984 0.45736 0.8526533 0.5326182 0.4613495 0.8799698
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.3833642 -0.2249756 -1.539084 -1.618211 0.322349 -0.7081215 1.096226
[2,] -0.3833642 -0.2249756 -1.539084 -1.618211 0.322349 -0.7081215 1.096226
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.9640931 0.4800014 0.01578342 -1.847411 0.02777672 0.09917612 -0.4462614
[2,] 0.9640931 0.4800014 0.01578342 -1.847411 0.02777672 0.09917612 -0.4462614
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.484912 -1.459844 0.6023278 1.527757 0.2183999 1.911268 -1.969359
[2,] -1.484912 -1.459844 0.6023278 1.527757 0.2183999 1.911268 -1.969359
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4610206 0.0647129 -0.3462696 -1.179084 0.1474502 0.1696096 -0.5379535
[2,] 0.4610206 0.0647129 -0.3462696 -1.179084 0.1474502 0.1696096 -0.5379535
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.7060594 0.7010689 -0.9496551 2.085811 1.7446 0.5362348 -0.8797623
[2,] 0.7060594 0.7010689 -0.9496551 2.085811 1.7446 0.5362348 -0.8797623
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.5320797 -0.9706321 0.4125716 0.1030339 0.7470626 1.83344 -0.1464195
[2,] 0.5320797 -0.9706321 0.4125716 0.1030339 0.7470626 1.83344 -0.1464195
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.7108237 -1.840696 0.2190527 -0.5915302 -0.6067165 -0.1539994 -0.6933001
[2,] 0.7108237 -1.840696 0.2190527 -0.5915302 -0.6067165 -0.1539994 -0.6933001
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.9489701 -1.418741 -0.3925681 0.887285 -0.3736735 1.567882 1.889152
[2,] 0.9489701 -1.418741 -0.3925681 0.887285 -0.3736735 1.567882 1.889152
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.0002708684 0.5520313 1.201658 1.399005 0.166113 2.496014 -0.5620323
[2,] -0.0002708684 0.5520313 1.201658 1.399005 0.166113 2.496014 -0.5620323
[,99] [,100]
[1,] 0.5531946 -0.03984101
[2,] 0.5531946 -0.03984101
>
>
> Max(tmp2)
[1] 2.723883
> Min(tmp2)
[1] -2.032887
> mean(tmp2)
[1] 0.125745
> Sum(tmp2)
[1] 12.5745
> Var(tmp2)
[1] 0.868007
>
> rowMeans(tmp2)
[1] 1.028818039 1.098821906 0.133050714 0.684136792 1.662776342
[6] 0.845085931 1.499782013 0.220619723 -0.520218777 1.219553264
[11] -0.643236981 0.024300329 -1.617164477 0.918279659 -1.435792144
[16] -1.254223252 -2.032887121 -0.633670474 -0.519860199 -0.626699861
[21] 0.263814940 -0.898169855 -0.942820436 -0.286791156 1.037217546
[26] 1.347370404 1.043055465 0.278607791 0.347208035 -0.911433365
[31] -0.638293152 0.253368138 1.033344724 0.115196858 -0.132351824
[36] -1.340707345 1.607256628 0.210669572 0.567776883 -0.771581857
[41] 1.538683636 -0.047829508 0.793644088 0.959199345 0.699982821
[46] 0.335228547 1.027877395 0.749953569 1.286849490 -1.272111112
[51] 1.602183258 -0.290053860 0.004236275 -0.022025253 0.547852868
[56] -1.994861060 0.002931559 1.018550996 0.916982701 0.240002364
[61] 0.213572592 -1.278141261 2.723882947 -0.622023277 0.356901493
[66] 1.698157035 -0.495980530 -0.811714993 -0.412169636 -0.130845731
[71] -0.662488993 0.174321169 0.112721347 0.319937914 -0.646577855
[76] 0.102605398 0.680561100 0.966418327 0.451676154 0.896663015
[81] 0.030513026 -1.885715412 -0.760334143 0.308609361 0.057336898
[86] 0.329420964 -0.028485239 -0.174121013 -0.375872957 -0.130422646
[91] 0.211419695 0.702861494 0.690101754 0.459527837 0.257569475
[96] -0.456564168 -0.621631936 -0.250236800 2.236710076 -1.995147347
> rowSums(tmp2)
[1] 1.028818039 1.098821906 0.133050714 0.684136792 1.662776342
[6] 0.845085931 1.499782013 0.220619723 -0.520218777 1.219553264
[11] -0.643236981 0.024300329 -1.617164477 0.918279659 -1.435792144
[16] -1.254223252 -2.032887121 -0.633670474 -0.519860199 -0.626699861
[21] 0.263814940 -0.898169855 -0.942820436 -0.286791156 1.037217546
[26] 1.347370404 1.043055465 0.278607791 0.347208035 -0.911433365
[31] -0.638293152 0.253368138 1.033344724 0.115196858 -0.132351824
[36] -1.340707345 1.607256628 0.210669572 0.567776883 -0.771581857
[41] 1.538683636 -0.047829508 0.793644088 0.959199345 0.699982821
[46] 0.335228547 1.027877395 0.749953569 1.286849490 -1.272111112
[51] 1.602183258 -0.290053860 0.004236275 -0.022025253 0.547852868
[56] -1.994861060 0.002931559 1.018550996 0.916982701 0.240002364
[61] 0.213572592 -1.278141261 2.723882947 -0.622023277 0.356901493
[66] 1.698157035 -0.495980530 -0.811714993 -0.412169636 -0.130845731
[71] -0.662488993 0.174321169 0.112721347 0.319937914 -0.646577855
[76] 0.102605398 0.680561100 0.966418327 0.451676154 0.896663015
[81] 0.030513026 -1.885715412 -0.760334143 0.308609361 0.057336898
[86] 0.329420964 -0.028485239 -0.174121013 -0.375872957 -0.130422646
[91] 0.211419695 0.702861494 0.690101754 0.459527837 0.257569475
[96] -0.456564168 -0.621631936 -0.250236800 2.236710076 -1.995147347
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.028818039 1.098821906 0.133050714 0.684136792 1.662776342
[6] 0.845085931 1.499782013 0.220619723 -0.520218777 1.219553264
[11] -0.643236981 0.024300329 -1.617164477 0.918279659 -1.435792144
[16] -1.254223252 -2.032887121 -0.633670474 -0.519860199 -0.626699861
[21] 0.263814940 -0.898169855 -0.942820436 -0.286791156 1.037217546
[26] 1.347370404 1.043055465 0.278607791 0.347208035 -0.911433365
[31] -0.638293152 0.253368138 1.033344724 0.115196858 -0.132351824
[36] -1.340707345 1.607256628 0.210669572 0.567776883 -0.771581857
[41] 1.538683636 -0.047829508 0.793644088 0.959199345 0.699982821
[46] 0.335228547 1.027877395 0.749953569 1.286849490 -1.272111112
[51] 1.602183258 -0.290053860 0.004236275 -0.022025253 0.547852868
[56] -1.994861060 0.002931559 1.018550996 0.916982701 0.240002364
[61] 0.213572592 -1.278141261 2.723882947 -0.622023277 0.356901493
[66] 1.698157035 -0.495980530 -0.811714993 -0.412169636 -0.130845731
[71] -0.662488993 0.174321169 0.112721347 0.319937914 -0.646577855
[76] 0.102605398 0.680561100 0.966418327 0.451676154 0.896663015
[81] 0.030513026 -1.885715412 -0.760334143 0.308609361 0.057336898
[86] 0.329420964 -0.028485239 -0.174121013 -0.375872957 -0.130422646
[91] 0.211419695 0.702861494 0.690101754 0.459527837 0.257569475
[96] -0.456564168 -0.621631936 -0.250236800 2.236710076 -1.995147347
> rowMin(tmp2)
[1] 1.028818039 1.098821906 0.133050714 0.684136792 1.662776342
[6] 0.845085931 1.499782013 0.220619723 -0.520218777 1.219553264
[11] -0.643236981 0.024300329 -1.617164477 0.918279659 -1.435792144
[16] -1.254223252 -2.032887121 -0.633670474 -0.519860199 -0.626699861
[21] 0.263814940 -0.898169855 -0.942820436 -0.286791156 1.037217546
[26] 1.347370404 1.043055465 0.278607791 0.347208035 -0.911433365
[31] -0.638293152 0.253368138 1.033344724 0.115196858 -0.132351824
[36] -1.340707345 1.607256628 0.210669572 0.567776883 -0.771581857
[41] 1.538683636 -0.047829508 0.793644088 0.959199345 0.699982821
[46] 0.335228547 1.027877395 0.749953569 1.286849490 -1.272111112
[51] 1.602183258 -0.290053860 0.004236275 -0.022025253 0.547852868
[56] -1.994861060 0.002931559 1.018550996 0.916982701 0.240002364
[61] 0.213572592 -1.278141261 2.723882947 -0.622023277 0.356901493
[66] 1.698157035 -0.495980530 -0.811714993 -0.412169636 -0.130845731
[71] -0.662488993 0.174321169 0.112721347 0.319937914 -0.646577855
[76] 0.102605398 0.680561100 0.966418327 0.451676154 0.896663015
[81] 0.030513026 -1.885715412 -0.760334143 0.308609361 0.057336898
[86] 0.329420964 -0.028485239 -0.174121013 -0.375872957 -0.130422646
[91] 0.211419695 0.702861494 0.690101754 0.459527837 0.257569475
[96] -0.456564168 -0.621631936 -0.250236800 2.236710076 -1.995147347
>
> colMeans(tmp2)
[1] 0.125745
> colSums(tmp2)
[1] 12.5745
> colVars(tmp2)
[1] 0.868007
> colSd(tmp2)
[1] 0.931669
> colMax(tmp2)
[1] 2.723883
> colMin(tmp2)
[1] -2.032887
> colMedians(tmp2)
[1] 0.1924954
> colRanges(tmp2)
[,1]
[1,] -2.032887
[2,] 2.723883
>
> 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] 1.9976583 -2.0649201 3.6226772 -0.7835942 0.4988169 -3.0457062
[7] 3.3277761 -6.1986035 6.6887293 0.1102616
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9840111
[2,] -0.4248604
[3,] 0.2062301
[4,] 0.4996839
[5,] 2.5967095
>
> rowApply(tmp,sum)
[1] 0.2050835 4.3125039 5.2036500 -2.8832399 -2.4019519 -2.5163972
[7] 1.4055449 -0.9797853 0.2348399 1.5728474
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 5 5 9 4 9 2 2 4 10
[2,] 5 9 7 3 7 4 1 5 3 3
[3,] 10 7 6 2 6 6 7 4 5 9
[4,] 2 2 9 4 3 1 5 6 9 5
[5,] 3 3 3 10 9 7 6 10 8 1
[6,] 7 4 1 1 2 10 8 7 7 2
[7,] 8 10 4 6 8 3 10 9 6 6
[8,] 6 1 2 7 1 5 4 1 2 4
[9,] 4 6 10 8 5 8 9 8 10 7
[10,] 1 8 8 5 10 2 3 3 1 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.50232764 -3.98072306 0.03070952 -1.93870011 -1.97727004 -2.84950320
[7] -4.59337775 -3.80554573 -2.44188680 0.55860818 2.92877090 -0.44973257
[13] 0.80157140 0.19647551 1.39083608 4.98771522 -3.98902087 -1.05381915
[19] 3.69299838 0.50590040
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0085114
[2,] -0.4685797
[3,] 0.2093563
[4,] 0.8200730
[5,] 0.9453342
>
> rowApply(tmp,sum)
[1] -3.7013769 -2.5762970 0.7886886 -3.3887824 -3.6105536
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 2 10 18 17
[2,] 3 9 4 15 2
[3,] 16 6 16 8 13
[4,] 4 5 7 5 18
[5,] 5 16 9 16 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.4685797 -0.93496583 0.2286246 -0.8924160 -0.5882227 0.007647161
[2,] -2.0085114 -0.48721873 -0.9831951 -1.2008690 0.7349110 -1.893764644
[3,] 0.2093563 -0.64822929 0.8174706 -0.1661062 0.1389109 0.687492807
[4,] 0.9453342 0.08981894 -0.3959103 -0.9874025 0.1804839 -1.263551043
[5,] 0.8200730 -2.00012816 0.3637198 1.3080935 -2.4433532 -0.387327483
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.3660621 -0.2062664 0.075183339 0.5586003 -0.5051731 0.9240883
[2,] -1.5299850 -0.1257936 -2.260064148 -0.5745565 0.5245574 0.7306563
[3,] -0.5548725 -0.7756513 0.695822268 0.4143279 1.4021649 -3.3054450
[4,] -1.1976112 -1.4229052 0.002668431 -0.2976316 0.9754477 0.7050332
[5,] -0.9448469 -1.2749293 -0.955496686 0.4578681 0.5317741 0.4959346
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.31035231 0.09122236 -0.2891246 1.51195194 -1.318555603 -1.7819083
[2,] 1.26119919 -0.01150828 0.4185955 -0.66145462 0.399435771 2.3123388
[3,] 0.36090038 0.99723749 0.3775120 2.52809533 -2.688020940 -0.5990914
[4,] -0.06628953 -0.51486881 -1.0979515 -0.03149813 -0.005905413 -0.5529955
[5,] -0.44388633 -0.36560725 1.9818047 1.64062070 -0.375974683 -0.4321627
[,19] [,20]
[1,] -0.2751892 0.83812081
[2,] 1.8670723 0.91185784
[3,] 0.9617584 -0.06494401
[4,] 1.8980017 -0.35104963
[5,] -0.7586448 -0.82808462
>
>
> 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 -0.3066639 -1.472365 -0.328831 -0.4165188 -0.1876343 -1.013224 -0.3799731
col8 col9 col10 col11 col12 col13 col14
row1 0.2609373 0.5144986 -1.198868 -0.3122723 0.5189627 -2.158149 1.243316
col15 col16 col17 col18 col19 col20
row1 0.315191 -0.9329024 0.2235619 0.03329353 -0.3984635 1.321218
> tmp[,"col10"]
col10
row1 -1.1988681
row2 -0.7025109
row3 -0.3460729
row4 0.9614668
row5 0.8054791
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.3066639 -1.4723653 -0.328831 -0.4165188 -0.1876343 -1.0132239
row5 0.8250649 -0.6319806 -1.716008 -0.8576641 0.2523525 0.3619683
col7 col8 col9 col10 col11 col12 col13
row1 -0.3799731 0.2609373 0.5144986 -1.1988681 -0.3122723 0.5189627 -2.1581492
row5 0.8209246 -2.7074329 2.0589661 0.8054791 -2.2348074 0.1107619 -0.3795032
col14 col15 col16 col17 col18 col19 col20
row1 1.2433159 0.315191 -0.9329024 0.22356185 0.03329353 -0.3984635 1.321218
row5 0.7094737 1.307258 -0.4725389 -0.04918551 0.05507027 -1.7616458 1.092809
> tmp[,c("col6","col20")]
col6 col20
row1 -1.0132239 1.3212183
row2 -0.1645369 1.7282369
row3 0.4009895 0.1968302
row4 0.2320979 -0.9260703
row5 0.3619683 1.0928094
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.0132239 1.321218
row5 0.3619683 1.092809
>
>
>
>
> 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 50.63471 50.95146 51.25497 49.9518 50.08571 105.4309 50.69448 50.39955
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.02087 50.49244 50.94804 49.86684 49.59668 49.40519 51.81559 48.39241
col17 col18 col19 col20
row1 49.92588 50.73196 49.95823 105.5369
> tmp[,"col10"]
col10
row1 50.49244
row2 30.28615
row3 30.86465
row4 30.39842
row5 50.29824
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.63471 50.95146 51.25497 49.95180 50.08571 105.4309 50.69448 50.39955
row5 51.54344 49.29206 50.39810 48.51629 50.33270 103.5300 48.98334 50.75813
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.02087 50.49244 50.94804 49.86684 49.59668 49.40519 51.81559 48.39241
row5 49.66606 50.29824 49.66376 50.85280 51.52084 49.97341 49.90383 48.95130
col17 col18 col19 col20
row1 49.92588 50.73196 49.95823 105.5369
row5 49.59968 47.86073 49.35197 104.9297
> tmp[,c("col6","col20")]
col6 col20
row1 105.43092 105.53693
row2 74.39281 74.99298
row3 74.14378 74.74087
row4 77.26323 74.87690
row5 103.52998 104.92975
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4309 105.5369
row5 103.5300 104.9297
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4309 105.5369
row5 103.5300 104.9297
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.2134026
[2,] -0.2767316
[3,] 0.4621740
[4,] -0.7876843
[5,] 1.9685092
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.7121069 0.3407665
[2,] 0.7201116 -0.2366736
[3,] -1.1565746 -0.8756531
[4,] 0.6014651 0.5056430
[5,] 0.2965709 -1.8627254
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.08042241 -0.6892878
[2,] -0.70540226 -0.6465584
[3,] 0.70669993 0.7000978
[4,] 0.37638691 1.5635554
[5,] 1.08031906 1.3160375
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.08042241
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.08042241
[2,] -0.70540226
>
>
>
> 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] [,7]
row3 1.0786718 0.004527884 -2.431295 -1.296193 0.7790243 1.0464723 -1.2205106
row1 0.8332432 -0.252535558 -1.583227 1.818510 0.1471019 -0.2824649 0.4997939
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.1777297 -0.1674276 1.196971 0.1504796 -1.870275 -0.77863954 -1.5177411
row1 0.6975419 0.5794835 1.999174 0.2517455 1.694209 -0.07616376 -0.6041596
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.2042592 1.5892539 0.6524285 0.3194238 -1.2151171 -0.7004575
row1 0.2091561 0.2836949 2.0862655 0.2735559 -0.1646005 0.1998413
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.084209 -0.6033612 1.433009 0.3478572 0.5645529 -0.890859 -0.6647396
[,8] [,9] [,10]
row2 2.174955 -0.3325328 0.2899142
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.7880587 -2.833414 -1.012225 -0.4023703 1.678317 -0.3445986 1.740654
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.8221965 -1.070976 -1.783063 0.8981607 0.1515422 -0.6013736 -0.8881334
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.729409 -0.2557797 1.150498 -1.106636 0.333456 -1.87613
>
>
> 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: 0x79b174540>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1293446cf1754"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM129344604b01d"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM129345dc663d4"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12934bc42365"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1293479efc1eb"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM129346ba469d7"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM129347720d976"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12934da50f14"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM129344f80f10b"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM129341a5131f4"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1293448a697ab"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12934312f80d0"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1293425b1f0ea"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12934453fa5fb"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1293455aa2541"
>
>
> ### 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: 0x79b175020>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x79b175020>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x79b175020>
> rowMedians(tmp)
[1] -0.017457836 0.465869477 0.042770677 0.104312972 0.552448875
[6] 0.234830049 -0.294062153 -0.572698306 -0.184973621 0.290639032
[11] -0.522964916 -0.498166067 0.333371273 0.684094503 0.326802814
[16] -0.335969128 0.185626803 0.300522360 0.298267909 -0.081472894
[21] 0.664301509 -0.047652812 0.421875396 0.230083696 0.314448415
[26] -0.097792252 -0.383432020 0.020167833 0.037892072 -0.217646592
[31] -0.498011363 0.410478231 0.267934632 0.020746045 -0.206467731
[36] 0.303228859 0.136688244 -0.223953742 0.387798599 -0.323225547
[41] 0.236429337 0.198455910 -0.072905645 0.168081065 0.376697642
[46] 0.441064473 0.493117421 -0.235090508 0.052718469 0.168698019
[51] -0.119367698 -0.092274791 0.088286713 -0.543777302 0.109772863
[56] 0.641980280 0.259734273 -0.086084361 -0.833935300 0.019311660
[61] -0.241840395 -0.295656021 0.472304404 -0.078816525 -0.144705857
[66] 0.247350469 0.216282702 0.191688251 0.010345372 -0.221173485
[71] 0.144306152 0.075478900 -0.169954225 0.640271670 -0.250015435
[76] 0.067707950 -0.034083993 -0.330393646 0.070239819 -0.192454854
[81] -0.133338367 0.173633888 -0.089660291 -0.269547031 0.247776770
[86] 0.532093396 -0.222814642 0.556598285 -0.678790775 0.135048302
[91] 0.308292067 -0.248919301 -0.251662766 -0.419240709 -0.013540721
[96] 0.562957056 -0.152660257 -0.128172616 0.035011444 -0.146976807
[101] -0.312099305 0.374646322 -0.299967508 -0.113295709 -0.033509983
[106] 0.192180562 -0.128611341 0.413816312 -0.292205059 0.229830297
[111] -0.424455391 0.147839460 -0.077158500 -0.294311120 0.555722504
[116] 0.279486466 0.061125696 0.366416759 -0.127296151 -0.175833722
[121] -0.389225136 -0.017620688 -0.366815431 -0.001882831 0.453327537
[126] -0.435614060 -0.203151738 -0.310769248 -0.248718310 0.075389527
[131] -0.062721092 0.444582617 0.680124193 0.398935261 -0.116455070
[136] 0.136681155 -0.190193340 -0.469856795 -0.273645979 -0.205497253
[141] 0.281335523 -0.413981178 0.424146955 -0.501200708 -0.377227992
[146] 0.116670583 0.886401573 -0.286606296 0.013468242 -0.566863738
[151] -0.082999715 0.422405373 0.092848789 0.316441764 -0.146673365
[156] 0.111943703 0.209780032 -0.565241676 0.137265233 0.232118234
[161] -0.186750142 -0.294346918 0.121895733 -0.564452361 0.110062821
[166] -0.464894009 0.341110353 -0.346590641 0.399048936 -0.522185224
[171] -0.278999637 0.240495956 0.286917855 0.435640587 0.243403581
[176] -0.199945951 0.236982854 -0.223275161 -0.008744716 0.075892374
[181] 0.203628857 -0.541838142 0.541428837 -0.088806445 -0.016134839
[186] -0.079414839 0.085322926 -0.032150518 0.458053743 0.168421986
[191] -0.025243055 -0.274375092 -0.172859479 0.361367988 -0.248494955
[196] -0.302074707 -0.068144751 0.171946334 0.069963154 0.097893493
[201] -0.438460712 -0.444859712 -0.202208162 0.522243068 -0.308387472
[206] -0.117158100 -0.009248964 -0.563634982 -0.240787486 -0.107541742
[211] -0.093095043 0.025282224 -0.323684350 0.120516919 0.008490229
[216] -0.135533840 -0.114840981 -0.004374175 0.484277332 -0.121100215
[221] 0.234489925 -0.068588915 -0.203747321 -0.201881682 0.094007999
[226] 0.183172099 -0.329548146 -0.268545000 -0.378334950 -0.568737230
>
> proc.time()
user system elapsed
0.973 6.467 7.697
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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: 0x747800240>
> .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: 0x747800240>
> .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: 0x747800240>
> .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: 0x747800240>
> 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: 0x7478002a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7478002a0>
> .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: 0x7478002a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7478002a0>
> .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: 0x7478002a0>
> 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: 0x7478006c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7478006c0>
> .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: 0x7478006c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7478006c0>
> .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: 0x7478006c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7478006c0>
> .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: 0x7478006c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7478006c0>
> .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: 0x7478006c0>
> 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: 0x7478007e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7478007e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7478007e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7478007e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12b032c01ecf3" "BufferedMatrixFile12b03326b5c17"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12b032c01ecf3" "BufferedMatrixFile12b03326b5c17"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x747800900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x747800900>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x747800900>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x747800900>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x747800900>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x747800900>
> .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: 0x747800a80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x747800a80>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x747800a80>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x747800a80>
> 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: 0x747800ba0>
> .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: 0x747800ba0>
> rm(P)
>
> proc.time()
user system elapsed
0.148 0.067 0.215
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2026-03-20 r89666) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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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
0.161 0.044 0.207