Ben Bolstad
| Snapshot Date: 2026-04-20 13:40 -0400 (Mon, 20 Apr 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 2026-04-21 11:35 -0400 (Tue, 21 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4686 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 alpha (2026-04-08 r89818) | 4690 |
| 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 259/2404 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| 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: 2026-04-20 18:45:57 -0400 (Mon, 20 Apr 2026) |
| EndedAt: 2026-04-20 18:46:17 -0400 (Mon, 20 Apr 2026) |
| EllapsedTime: 20.3 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 version 4.6.0 alpha (2026-04-08 r89818)
* 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: 2026-04-20 22:45:57 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 -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 -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 -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 -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 -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 version 4.6.0 alpha (2026-04-08 r89818)
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
0.134 0.050 0.183
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 alpha (2026-04-08 r89818)
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 484141 25.9 1067251 57 NA 632017 33.8
Vcells 896965 6.9 8388608 64 196608 2112089 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] "Mon Apr 20 18:46:07 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] "Mon Apr 20 18:46:07 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: 0x101862c60>
>
>
>
> 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] "Mon Apr 20 18:46:09 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] "Mon Apr 20 18:46:09 2026"
>
> ColMode(tmp2)
<pointer: 0x101862c60>
>
>
>
> ### 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,] 99.40131670 -1.92806747 -1.38095217 1.2359784
[2,] -0.01851318 1.37879798 0.50214366 0.2132982
[3,] 0.71571227 0.95835380 -0.06153029 0.3307544
[4,] 0.75456999 -0.02680212 0.34844374 1.0581834
> 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,] 99.40131670 1.92806747 1.38095217 1.2359784
[2,] 0.01851318 1.37879798 0.50214366 0.2132982
[3,] 0.71571227 0.95835380 0.06153029 0.3307544
[4,] 0.75456999 0.02680212 0.34844374 1.0581834
> 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,] 9.9700209 1.3885487 1.1751392 1.1117457
[2,] 0.1360631 1.1742223 0.7086210 0.4618422
[3,] 0.8459978 0.9789555 0.2480530 0.5751125
[4,] 0.8686599 0.1637135 0.5902912 1.0286804
>
> 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,] 224.10153 40.81355 38.13234 37.35344
[2,] 26.37914 38.12102 32.58835 29.83172
[3,] 34.17569 35.74791 27.54206 31.08188
[4,] 34.44117 26.66394 31.25136 36.34499
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x101862cc0>
> exp(tmp5)
<pointer: 0x101862cc0>
> log(tmp5,2)
<pointer: 0x101862cc0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.438
> Min(tmp5)
[1] 52.94894
> mean(tmp5)
[1] 72.70376
> Sum(tmp5)
[1] 14540.75
> Var(tmp5)
[1] 868.3837
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 94.49966 68.69212 68.68378 71.13911 67.77146 72.05181 72.93544 70.65886
[9] 69.17238 71.43299
> rowSums(tmp5)
[1] 1889.993 1373.842 1373.676 1422.782 1355.429 1441.036 1458.709 1413.177
[9] 1383.448 1428.660
> rowVars(tmp5)
[1] 7766.34535 91.10387 50.05594 121.09720 78.13517 89.28027
[7] 70.19803 69.98307 90.65865 86.38591
> rowSd(tmp5)
[1] 88.126871 9.544835 7.075023 11.004417 8.839410 9.448824 8.378426
[8] 8.365589 9.521484 9.294402
> rowMax(tmp5)
[1] 466.43796 85.57735 78.94470 96.91418 81.75193 99.42858 93.76601
[8] 85.10277 88.46361 88.00903
> rowMin(tmp5)
[1] 58.18790 54.90473 57.32519 55.49749 52.94894 56.93091 59.45125 57.48909
[9] 55.19930 55.57791
>
> colMeans(tmp5)
[1] 113.27932 69.58121 67.50882 67.78076 73.06831 69.14700 76.25653
[8] 70.58782 76.70814 71.37198 68.15060 71.84526 71.94903 66.98503
[15] 69.04751 68.82933 66.91401 71.57719 71.71016 71.77723
> colSums(tmp5)
[1] 1132.7932 695.8121 675.0882 677.8076 730.6831 691.4700 762.5653
[8] 705.8782 767.0814 713.7198 681.5060 718.4526 719.4903 669.8503
[15] 690.4751 688.2933 669.1401 715.7719 717.1016 717.7723
> colVars(tmp5)
[1] 15566.52685 126.17505 95.06414 81.92061 86.10391 65.55925
[7] 29.26816 58.70800 136.85533 52.77234 55.28032 122.64072
[13] 48.85550 81.50684 78.63664 135.27329 45.64763 112.79604
[19] 76.87804 61.35066
> colSd(tmp5)
[1] 124.765888 11.232767 9.750084 9.051001 9.279219 8.096867
[7] 5.410005 7.662115 11.698518 7.264457 7.435073 11.074327
[13] 6.989671 9.028114 8.867730 11.630704 6.756303 10.620548
[19] 8.768012 7.832666
> colMax(tmp5)
[1] 466.43796 84.94807 79.48792 81.59960 86.23022 79.76943 83.26603
[8] 77.35706 93.76601 82.32240 80.56827 96.91418 85.10277 80.79183
[15] 88.39931 86.28522 79.48160 93.15564 88.00903 83.46948
> colMin(tmp5)
[1] 54.90473 55.49749 52.94894 55.93254 61.75463 56.66092 68.99743 58.91131
[9] 57.53999 62.41169 55.69223 57.72909 60.64887 56.31275 58.09127 55.19930
[17] 58.18790 58.15569 60.57634 58.47000
>
>
> ### 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] 94.49966 68.69212 68.68378 71.13911 NA 72.05181 72.93544 70.65886
[9] 69.17238 71.43299
> rowSums(tmp5)
[1] 1889.993 1373.842 1373.676 1422.782 NA 1441.036 1458.709 1413.177
[9] 1383.448 1428.660
> rowVars(tmp5)
[1] 7766.34535 91.10387 50.05594 121.09720 76.13339 89.28027
[7] 70.19803 69.98307 90.65865 86.38591
> rowSd(tmp5)
[1] 88.126871 9.544835 7.075023 11.004417 8.725445 9.448824 8.378426
[8] 8.365589 9.521484 9.294402
> rowMax(tmp5)
[1] 466.43796 85.57735 78.94470 96.91418 NA 99.42858 93.76601
[8] 85.10277 88.46361 88.00903
> rowMin(tmp5)
[1] 58.18790 54.90473 57.32519 55.49749 NA 56.93091 59.45125 57.48909
[9] 55.19930 55.57791
>
> colMeans(tmp5)
[1] NA 69.58121 67.50882 67.78076 73.06831 69.14700 76.25653 70.58782
[9] 76.70814 71.37198 68.15060 71.84526 71.94903 66.98503 69.04751 68.82933
[17] 66.91401 71.57719 71.71016 71.77723
> colSums(tmp5)
[1] NA 695.8121 675.0882 677.8076 730.6831 691.4700 762.5653 705.8782
[9] 767.0814 713.7198 681.5060 718.4526 719.4903 669.8503 690.4751 688.2933
[17] 669.1401 715.7719 717.1016 717.7723
> colVars(tmp5)
[1] NA 126.17505 95.06414 81.92061 86.10391 65.55925 29.26816
[8] 58.70800 136.85533 52.77234 55.28032 122.64072 48.85550 81.50684
[15] 78.63664 135.27329 45.64763 112.79604 76.87804 61.35066
> colSd(tmp5)
[1] NA 11.232767 9.750084 9.051001 9.279219 8.096867 5.410005
[8] 7.662115 11.698518 7.264457 7.435073 11.074327 6.989671 9.028114
[15] 8.867730 11.630704 6.756303 10.620548 8.768012 7.832666
> colMax(tmp5)
[1] NA 84.94807 79.48792 81.59960 86.23022 79.76943 83.26603 77.35706
[9] 93.76601 82.32240 80.56827 96.91418 85.10277 80.79183 88.39931 86.28522
[17] 79.48160 93.15564 88.00903 83.46948
> colMin(tmp5)
[1] NA 55.49749 52.94894 55.93254 61.75463 56.66092 68.99743 58.91131
[9] 57.53999 62.41169 55.69223 57.72909 60.64887 56.31275 58.09127 55.19930
[17] 58.18790 58.15569 60.57634 58.47000
>
> Max(tmp5,na.rm=TRUE)
[1] 466.438
> Min(tmp5,na.rm=TRUE)
[1] 52.94894
> mean(tmp5,na.rm=TRUE)
[1] 72.78088
> Sum(tmp5,na.rm=TRUE)
[1] 14483.4
> Var(tmp5,na.rm=TRUE)
[1] 871.574
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 94.49966 68.69212 68.68378 71.13911 68.31958 72.05181 72.93544 70.65886
[9] 69.17238 71.43299
> rowSums(tmp5,na.rm=TRUE)
[1] 1889.993 1373.842 1373.676 1422.782 1298.072 1441.036 1458.709 1413.177
[9] 1383.448 1428.660
> rowVars(tmp5,na.rm=TRUE)
[1] 7766.34535 91.10387 50.05594 121.09720 76.13339 89.28027
[7] 70.19803 69.98307 90.65865 86.38591
> rowSd(tmp5,na.rm=TRUE)
[1] 88.126871 9.544835 7.075023 11.004417 8.725445 9.448824 8.378426
[8] 8.365589 9.521484 9.294402
> rowMax(tmp5,na.rm=TRUE)
[1] 466.43796 85.57735 78.94470 96.91418 81.75193 99.42858 93.76601
[8] 85.10277 88.46361 88.00903
> rowMin(tmp5,na.rm=TRUE)
[1] 58.18790 54.90473 57.32519 55.49749 52.94894 56.93091 59.45125 57.48909
[9] 55.19930 55.57791
>
> colMeans(tmp5,na.rm=TRUE)
[1] 119.49289 69.58121 67.50882 67.78076 73.06831 69.14700 76.25653
[8] 70.58782 76.70814 71.37198 68.15060 71.84526 71.94903 66.98503
[15] 69.04751 68.82933 66.91401 71.57719 71.71016 71.77723
> colSums(tmp5,na.rm=TRUE)
[1] 1075.4360 695.8121 675.0882 677.8076 730.6831 691.4700 762.5653
[8] 705.8782 767.0814 713.7198 681.5060 718.4526 719.4903 669.8503
[15] 690.4751 688.2933 669.1401 715.7719 717.1016 717.7723
> colVars(tmp5,na.rm=TRUE)
[1] 17077.99645 126.17505 95.06414 81.92061 86.10391 65.55925
[7] 29.26816 58.70800 136.85533 52.77234 55.28032 122.64072
[13] 48.85550 81.50684 78.63664 135.27329 45.64763 112.79604
[19] 76.87804 61.35066
> colSd(tmp5,na.rm=TRUE)
[1] 130.682809 11.232767 9.750084 9.051001 9.279219 8.096867
[7] 5.410005 7.662115 11.698518 7.264457 7.435073 11.074327
[13] 6.989671 9.028114 8.867730 11.630704 6.756303 10.620548
[19] 8.768012 7.832666
> colMax(tmp5,na.rm=TRUE)
[1] 466.43796 84.94807 79.48792 81.59960 86.23022 79.76943 83.26603
[8] 77.35706 93.76601 82.32240 80.56827 96.91418 85.10277 80.79183
[15] 88.39931 86.28522 79.48160 93.15564 88.00903 83.46948
> colMin(tmp5,na.rm=TRUE)
[1] 54.90473 55.49749 52.94894 55.93254 61.75463 56.66092 68.99743 58.91131
[9] 57.53999 62.41169 55.69223 57.72909 60.64887 56.31275 58.09127 55.19930
[17] 58.18790 58.15569 60.57634 58.47000
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 94.49966 68.69212 68.68378 71.13911 NaN 72.05181 72.93544 70.65886
[9] 69.17238 71.43299
> rowSums(tmp5,na.rm=TRUE)
[1] 1889.993 1373.842 1373.676 1422.782 0.000 1441.036 1458.709 1413.177
[9] 1383.448 1428.660
> rowVars(tmp5,na.rm=TRUE)
[1] 7766.34535 91.10387 50.05594 121.09720 NA 89.28027
[7] 70.19803 69.98307 90.65865 86.38591
> rowSd(tmp5,na.rm=TRUE)
[1] 88.126871 9.544835 7.075023 11.004417 NA 9.448824 8.378426
[8] 8.365589 9.521484 9.294402
> rowMax(tmp5,na.rm=TRUE)
[1] 466.43796 85.57735 78.94470 96.91418 NA 99.42858 93.76601
[8] 85.10277 88.46361 88.00903
> rowMin(tmp5,na.rm=TRUE)
[1] 58.18790 54.90473 57.32519 55.49749 NA 56.93091 59.45125 57.48909
[9] 55.19930 55.57791
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] NaN 70.06293 69.12659 66.24533 72.10347 68.09813 77.06310 71.88521
[9] 78.09085 71.16593 67.35530 73.41372 72.18506 68.17084 68.58091 68.74984
[17] 67.51934 71.55734 71.11519 73.05393
> colSums(tmp5,na.rm=TRUE)
[1] 0.0000 630.5664 622.1393 596.2080 648.9312 612.8832 693.5679 646.9669
[9] 702.8177 640.4934 606.1977 660.7235 649.6656 613.5376 617.2282 618.7485
[17] 607.6740 644.0161 640.0367 657.4853
> colVars(tmp5,na.rm=TRUE)
[1] NA 139.33626 77.50409 65.63841 86.39395 61.37773 25.60800
[8] 47.11028 132.45334 58.89122 55.07479 110.29496 54.33570 75.87608
[15] 86.01693 152.11136 47.23133 126.89112 82.50547 50.68263
> colSd(tmp5,na.rm=TRUE)
[1] NA 11.804078 8.803641 8.101754 9.294835 7.834394 5.060434
[8] 6.863693 11.508837 7.674062 7.421239 10.502141 7.371276 8.710688
[15] 9.274531 12.333343 6.872505 11.264596 9.083252 7.119173
> colMax(tmp5,na.rm=TRUE)
[1] -Inf 84.94807 79.48792 77.74628 86.23022 79.76943 83.26603 77.35706
[9] 93.76601 82.32240 80.56827 96.91418 85.10277 80.79183 88.39931 86.28522
[17] 79.48160 93.15564 88.00903 83.46948
> colMin(tmp5,na.rm=TRUE)
[1] Inf 55.49749 57.32519 55.93254 61.75463 56.66092 69.78080 60.54049
[9] 57.53999 62.41169 55.69223 63.81828 60.64887 56.68909 58.09127 55.19930
[17] 58.18790 58.15569 60.57634 58.47000
>
>
>
>
> 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] 205.4318 170.0463 186.9685 168.5681 167.3732 173.6664 208.3987 170.6562
[9] 173.8518 241.1269
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 205.4318 170.0463 186.9685 168.5681 167.3732 173.6664 208.3987 170.6562
[9] 173.8518 241.1269
>
>
>
> 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] 0.000000e+00 -5.684342e-14 -2.273737e-13 0.000000e+00 -5.684342e-14
[6] 5.684342e-14 -2.273737e-13 -5.684342e-14 0.000000e+00 -1.705303e-13
[11] 2.557954e-13 -5.684342e-14 -4.263256e-14 5.684342e-14 0.000000e+00
[16] -1.421085e-13 0.000000e+00 1.705303e-13 -5.684342e-14 2.273737e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 9
6 15
1 3
7 4
1 7
8 18
6 4
1 12
4 19
4 4
1 3
10 19
2 6
3 5
7 9
2 14
1 10
6 18
9 5
5 4
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] 2.555424
> Min(tmp)
[1] -2.494584
> mean(tmp)
[1] -0.1120665
> Sum(tmp)
[1] -11.20665
> Var(tmp)
[1] 1.062901
>
> rowMeans(tmp)
[1] -0.1120665
> rowSums(tmp)
[1] -11.20665
> rowVars(tmp)
[1] 1.062901
> rowSd(tmp)
[1] 1.030971
> rowMax(tmp)
[1] 2.555424
> rowMin(tmp)
[1] -2.494584
>
> colMeans(tmp)
[1] -0.74307038 0.20496174 -0.30815850 0.03624862 0.98055621 -0.01192056
[7] 0.70549253 1.60652940 0.48773059 1.58775273 0.52317343 1.16210809
[13] 2.13229589 0.74466274 -0.89685292 -1.08838628 0.67916961 -1.93178250
[19] -1.30274982 2.55542411 -0.32640614 -0.37945764 -1.09783814 0.05292835
[25] 1.25657104 -1.03082171 0.92493032 -0.35515023 0.61160225 -1.10400322
[31] 1.43187901 -0.71421676 0.42269545 0.54964309 -1.31833415 -0.49822472
[37] -2.49458408 0.75589568 -1.00831448 -1.08039467 0.01898980 1.84113291
[43] -0.20184883 0.20193370 -0.76502221 -1.45095682 -1.79711928 0.16619227
[49] -0.57596374 1.49862867 -1.00327806 0.03660008 -2.16201648 -1.10679389
[55] -1.62023088 -1.61050007 -0.29322136 -1.16921931 -1.02198135 0.11360318
[61] 0.20354704 1.23749670 0.46942175 -0.31217496 0.10711183 1.20957532
[67] 0.15481515 0.75904890 0.45849915 0.31797478 0.79957502 -1.16701059
[73] -1.26096942 -1.97131246 -0.37414199 1.14434391 0.63001213 -1.05259257
[79] -1.27796781 -0.32158348 -0.32478878 -0.83368109 -1.00178013 1.42245408
[85] -0.39591236 0.81114446 0.90323971 0.15232298 0.16002725 0.40602060
[91] -0.85244068 -0.04584311 -1.33010892 0.25094402 0.61018414 -1.24997069
[97] 0.62697824 -1.81012372 0.40162661 0.31887628
> colSums(tmp)
[1] -0.74307038 0.20496174 -0.30815850 0.03624862 0.98055621 -0.01192056
[7] 0.70549253 1.60652940 0.48773059 1.58775273 0.52317343 1.16210809
[13] 2.13229589 0.74466274 -0.89685292 -1.08838628 0.67916961 -1.93178250
[19] -1.30274982 2.55542411 -0.32640614 -0.37945764 -1.09783814 0.05292835
[25] 1.25657104 -1.03082171 0.92493032 -0.35515023 0.61160225 -1.10400322
[31] 1.43187901 -0.71421676 0.42269545 0.54964309 -1.31833415 -0.49822472
[37] -2.49458408 0.75589568 -1.00831448 -1.08039467 0.01898980 1.84113291
[43] -0.20184883 0.20193370 -0.76502221 -1.45095682 -1.79711928 0.16619227
[49] -0.57596374 1.49862867 -1.00327806 0.03660008 -2.16201648 -1.10679389
[55] -1.62023088 -1.61050007 -0.29322136 -1.16921931 -1.02198135 0.11360318
[61] 0.20354704 1.23749670 0.46942175 -0.31217496 0.10711183 1.20957532
[67] 0.15481515 0.75904890 0.45849915 0.31797478 0.79957502 -1.16701059
[73] -1.26096942 -1.97131246 -0.37414199 1.14434391 0.63001213 -1.05259257
[79] -1.27796781 -0.32158348 -0.32478878 -0.83368109 -1.00178013 1.42245408
[85] -0.39591236 0.81114446 0.90323971 0.15232298 0.16002725 0.40602060
[91] -0.85244068 -0.04584311 -1.33010892 0.25094402 0.61018414 -1.24997069
[97] 0.62697824 -1.81012372 0.40162661 0.31887628
> 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] -0.74307038 0.20496174 -0.30815850 0.03624862 0.98055621 -0.01192056
[7] 0.70549253 1.60652940 0.48773059 1.58775273 0.52317343 1.16210809
[13] 2.13229589 0.74466274 -0.89685292 -1.08838628 0.67916961 -1.93178250
[19] -1.30274982 2.55542411 -0.32640614 -0.37945764 -1.09783814 0.05292835
[25] 1.25657104 -1.03082171 0.92493032 -0.35515023 0.61160225 -1.10400322
[31] 1.43187901 -0.71421676 0.42269545 0.54964309 -1.31833415 -0.49822472
[37] -2.49458408 0.75589568 -1.00831448 -1.08039467 0.01898980 1.84113291
[43] -0.20184883 0.20193370 -0.76502221 -1.45095682 -1.79711928 0.16619227
[49] -0.57596374 1.49862867 -1.00327806 0.03660008 -2.16201648 -1.10679389
[55] -1.62023088 -1.61050007 -0.29322136 -1.16921931 -1.02198135 0.11360318
[61] 0.20354704 1.23749670 0.46942175 -0.31217496 0.10711183 1.20957532
[67] 0.15481515 0.75904890 0.45849915 0.31797478 0.79957502 -1.16701059
[73] -1.26096942 -1.97131246 -0.37414199 1.14434391 0.63001213 -1.05259257
[79] -1.27796781 -0.32158348 -0.32478878 -0.83368109 -1.00178013 1.42245408
[85] -0.39591236 0.81114446 0.90323971 0.15232298 0.16002725 0.40602060
[91] -0.85244068 -0.04584311 -1.33010892 0.25094402 0.61018414 -1.24997069
[97] 0.62697824 -1.81012372 0.40162661 0.31887628
> colMin(tmp)
[1] -0.74307038 0.20496174 -0.30815850 0.03624862 0.98055621 -0.01192056
[7] 0.70549253 1.60652940 0.48773059 1.58775273 0.52317343 1.16210809
[13] 2.13229589 0.74466274 -0.89685292 -1.08838628 0.67916961 -1.93178250
[19] -1.30274982 2.55542411 -0.32640614 -0.37945764 -1.09783814 0.05292835
[25] 1.25657104 -1.03082171 0.92493032 -0.35515023 0.61160225 -1.10400322
[31] 1.43187901 -0.71421676 0.42269545 0.54964309 -1.31833415 -0.49822472
[37] -2.49458408 0.75589568 -1.00831448 -1.08039467 0.01898980 1.84113291
[43] -0.20184883 0.20193370 -0.76502221 -1.45095682 -1.79711928 0.16619227
[49] -0.57596374 1.49862867 -1.00327806 0.03660008 -2.16201648 -1.10679389
[55] -1.62023088 -1.61050007 -0.29322136 -1.16921931 -1.02198135 0.11360318
[61] 0.20354704 1.23749670 0.46942175 -0.31217496 0.10711183 1.20957532
[67] 0.15481515 0.75904890 0.45849915 0.31797478 0.79957502 -1.16701059
[73] -1.26096942 -1.97131246 -0.37414199 1.14434391 0.63001213 -1.05259257
[79] -1.27796781 -0.32158348 -0.32478878 -0.83368109 -1.00178013 1.42245408
[85] -0.39591236 0.81114446 0.90323971 0.15232298 0.16002725 0.40602060
[91] -0.85244068 -0.04584311 -1.33010892 0.25094402 0.61018414 -1.24997069
[97] 0.62697824 -1.81012372 0.40162661 0.31887628
> colMedians(tmp)
[1] -0.74307038 0.20496174 -0.30815850 0.03624862 0.98055621 -0.01192056
[7] 0.70549253 1.60652940 0.48773059 1.58775273 0.52317343 1.16210809
[13] 2.13229589 0.74466274 -0.89685292 -1.08838628 0.67916961 -1.93178250
[19] -1.30274982 2.55542411 -0.32640614 -0.37945764 -1.09783814 0.05292835
[25] 1.25657104 -1.03082171 0.92493032 -0.35515023 0.61160225 -1.10400322
[31] 1.43187901 -0.71421676 0.42269545 0.54964309 -1.31833415 -0.49822472
[37] -2.49458408 0.75589568 -1.00831448 -1.08039467 0.01898980 1.84113291
[43] -0.20184883 0.20193370 -0.76502221 -1.45095682 -1.79711928 0.16619227
[49] -0.57596374 1.49862867 -1.00327806 0.03660008 -2.16201648 -1.10679389
[55] -1.62023088 -1.61050007 -0.29322136 -1.16921931 -1.02198135 0.11360318
[61] 0.20354704 1.23749670 0.46942175 -0.31217496 0.10711183 1.20957532
[67] 0.15481515 0.75904890 0.45849915 0.31797478 0.79957502 -1.16701059
[73] -1.26096942 -1.97131246 -0.37414199 1.14434391 0.63001213 -1.05259257
[79] -1.27796781 -0.32158348 -0.32478878 -0.83368109 -1.00178013 1.42245408
[85] -0.39591236 0.81114446 0.90323971 0.15232298 0.16002725 0.40602060
[91] -0.85244068 -0.04584311 -1.33010892 0.25094402 0.61018414 -1.24997069
[97] 0.62697824 -1.81012372 0.40162661 0.31887628
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.7430704 0.2049617 -0.3081585 0.03624862 0.9805562 -0.01192056 0.7054925
[2,] -0.7430704 0.2049617 -0.3081585 0.03624862 0.9805562 -0.01192056 0.7054925
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.606529 0.4877306 1.587753 0.5231734 1.162108 2.132296 0.7446627
[2,] 1.606529 0.4877306 1.587753 0.5231734 1.162108 2.132296 0.7446627
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.8968529 -1.088386 0.6791696 -1.931783 -1.30275 2.555424 -0.3264061
[2,] -0.8968529 -1.088386 0.6791696 -1.931783 -1.30275 2.555424 -0.3264061
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.3794576 -1.097838 0.05292835 1.256571 -1.030822 0.9249303 -0.3551502
[2,] -0.3794576 -1.097838 0.05292835 1.256571 -1.030822 0.9249303 -0.3551502
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.6116022 -1.104003 1.431879 -0.7142168 0.4226955 0.5496431 -1.318334
[2,] 0.6116022 -1.104003 1.431879 -0.7142168 0.4226955 0.5496431 -1.318334
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.4982247 -2.494584 0.7558957 -1.008314 -1.080395 0.0189898 1.841133
[2,] -0.4982247 -2.494584 0.7558957 -1.008314 -1.080395 0.0189898 1.841133
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2018488 0.2019337 -0.7650222 -1.450957 -1.797119 0.1661923 -0.5759637
[2,] -0.2018488 0.2019337 -0.7650222 -1.450957 -1.797119 0.1661923 -0.5759637
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.498629 -1.003278 0.03660008 -2.162016 -1.106794 -1.620231 -1.6105
[2,] 1.498629 -1.003278 0.03660008 -2.162016 -1.106794 -1.620231 -1.6105
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.2932214 -1.169219 -1.021981 0.1136032 0.203547 1.237497 0.4694218
[2,] -0.2932214 -1.169219 -1.021981 0.1136032 0.203547 1.237497 0.4694218
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.312175 0.1071118 1.209575 0.1548151 0.7590489 0.4584991 0.3179748
[2,] -0.312175 0.1071118 1.209575 0.1548151 0.7590489 0.4584991 0.3179748
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.799575 -1.167011 -1.260969 -1.971312 -0.374142 1.144344 0.6300121
[2,] 0.799575 -1.167011 -1.260969 -1.971312 -0.374142 1.144344 0.6300121
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.052593 -1.277968 -0.3215835 -0.3247888 -0.8336811 -1.00178 1.422454
[2,] -1.052593 -1.277968 -0.3215835 -0.3247888 -0.8336811 -1.00178 1.422454
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.3959124 0.8111445 0.9032397 0.152323 0.1600272 0.4060206 -0.8524407
[2,] -0.3959124 0.8111445 0.9032397 0.152323 0.1600272 0.4060206 -0.8524407
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.04584311 -1.330109 0.250944 0.6101841 -1.249971 0.6269782 -1.810124
[2,] -0.04584311 -1.330109 0.250944 0.6101841 -1.249971 0.6269782 -1.810124
[,99] [,100]
[1,] 0.4016266 0.3188763
[2,] 0.4016266 0.3188763
>
>
> Max(tmp2)
[1] 3.116495
> Min(tmp2)
[1] -1.955662
> mean(tmp2)
[1] 0.04951322
> Sum(tmp2)
[1] 4.951322
> Var(tmp2)
[1] 1.091588
>
> rowMeans(tmp2)
[1] 2.595579513 -0.136819516 -1.100719201 -1.596233533 -0.996848127
[6] 1.111979696 -0.799203448 -0.218706297 -0.936214873 2.211478050
[11] 0.795970951 1.071573131 1.221165350 0.802558837 -0.039935350
[16] 0.881070275 -0.699099560 -1.294307444 -0.377508628 -0.923003121
[21] 1.824261674 -0.684676305 -0.811375172 -0.672953079 0.826150522
[26] 0.480321771 -1.088798565 1.285903012 0.820702466 0.050115288
[31] 0.497791355 -0.301049941 0.851671211 1.227932865 -1.955661666
[36] 1.716572677 0.098042823 -0.007673055 0.358769356 0.821783188
[41] 2.211188603 -0.028876382 0.139391934 3.116494528 -0.412425637
[46] 0.357790816 -1.780586641 -0.200679939 -0.850001977 -0.045426277
[51] 0.036821613 0.469864560 -0.294758921 -1.071424506 -0.108464478
[56] -1.132771168 -0.138262986 0.626537379 -1.246093575 -0.730693101
[61] -0.667497431 1.697554154 -1.321906249 -1.241979713 0.735717285
[66] -1.072409080 -0.974084225 -0.892800176 -1.035014013 0.904514631
[71] 0.372138217 -0.732323588 -0.638203144 1.133889071 1.083212801
[76] 1.872649705 -0.273332112 0.958826596 0.967092169 -0.378188590
[81] -0.610848490 0.010049182 1.525331680 -1.434003391 0.395682461
[86] 0.661634696 -0.767043254 -0.946726634 -1.038645970 0.956960445
[91] -0.616001504 0.054982181 1.463995775 1.063945649 -0.483909440
[96] -1.081666032 0.632881909 -1.139104895 -0.720675507 0.698396222
> rowSums(tmp2)
[1] 2.595579513 -0.136819516 -1.100719201 -1.596233533 -0.996848127
[6] 1.111979696 -0.799203448 -0.218706297 -0.936214873 2.211478050
[11] 0.795970951 1.071573131 1.221165350 0.802558837 -0.039935350
[16] 0.881070275 -0.699099560 -1.294307444 -0.377508628 -0.923003121
[21] 1.824261674 -0.684676305 -0.811375172 -0.672953079 0.826150522
[26] 0.480321771 -1.088798565 1.285903012 0.820702466 0.050115288
[31] 0.497791355 -0.301049941 0.851671211 1.227932865 -1.955661666
[36] 1.716572677 0.098042823 -0.007673055 0.358769356 0.821783188
[41] 2.211188603 -0.028876382 0.139391934 3.116494528 -0.412425637
[46] 0.357790816 -1.780586641 -0.200679939 -0.850001977 -0.045426277
[51] 0.036821613 0.469864560 -0.294758921 -1.071424506 -0.108464478
[56] -1.132771168 -0.138262986 0.626537379 -1.246093575 -0.730693101
[61] -0.667497431 1.697554154 -1.321906249 -1.241979713 0.735717285
[66] -1.072409080 -0.974084225 -0.892800176 -1.035014013 0.904514631
[71] 0.372138217 -0.732323588 -0.638203144 1.133889071 1.083212801
[76] 1.872649705 -0.273332112 0.958826596 0.967092169 -0.378188590
[81] -0.610848490 0.010049182 1.525331680 -1.434003391 0.395682461
[86] 0.661634696 -0.767043254 -0.946726634 -1.038645970 0.956960445
[91] -0.616001504 0.054982181 1.463995775 1.063945649 -0.483909440
[96] -1.081666032 0.632881909 -1.139104895 -0.720675507 0.698396222
> 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] 2.595579513 -0.136819516 -1.100719201 -1.596233533 -0.996848127
[6] 1.111979696 -0.799203448 -0.218706297 -0.936214873 2.211478050
[11] 0.795970951 1.071573131 1.221165350 0.802558837 -0.039935350
[16] 0.881070275 -0.699099560 -1.294307444 -0.377508628 -0.923003121
[21] 1.824261674 -0.684676305 -0.811375172 -0.672953079 0.826150522
[26] 0.480321771 -1.088798565 1.285903012 0.820702466 0.050115288
[31] 0.497791355 -0.301049941 0.851671211 1.227932865 -1.955661666
[36] 1.716572677 0.098042823 -0.007673055 0.358769356 0.821783188
[41] 2.211188603 -0.028876382 0.139391934 3.116494528 -0.412425637
[46] 0.357790816 -1.780586641 -0.200679939 -0.850001977 -0.045426277
[51] 0.036821613 0.469864560 -0.294758921 -1.071424506 -0.108464478
[56] -1.132771168 -0.138262986 0.626537379 -1.246093575 -0.730693101
[61] -0.667497431 1.697554154 -1.321906249 -1.241979713 0.735717285
[66] -1.072409080 -0.974084225 -0.892800176 -1.035014013 0.904514631
[71] 0.372138217 -0.732323588 -0.638203144 1.133889071 1.083212801
[76] 1.872649705 -0.273332112 0.958826596 0.967092169 -0.378188590
[81] -0.610848490 0.010049182 1.525331680 -1.434003391 0.395682461
[86] 0.661634696 -0.767043254 -0.946726634 -1.038645970 0.956960445
[91] -0.616001504 0.054982181 1.463995775 1.063945649 -0.483909440
[96] -1.081666032 0.632881909 -1.139104895 -0.720675507 0.698396222
> rowMin(tmp2)
[1] 2.595579513 -0.136819516 -1.100719201 -1.596233533 -0.996848127
[6] 1.111979696 -0.799203448 -0.218706297 -0.936214873 2.211478050
[11] 0.795970951 1.071573131 1.221165350 0.802558837 -0.039935350
[16] 0.881070275 -0.699099560 -1.294307444 -0.377508628 -0.923003121
[21] 1.824261674 -0.684676305 -0.811375172 -0.672953079 0.826150522
[26] 0.480321771 -1.088798565 1.285903012 0.820702466 0.050115288
[31] 0.497791355 -0.301049941 0.851671211 1.227932865 -1.955661666
[36] 1.716572677 0.098042823 -0.007673055 0.358769356 0.821783188
[41] 2.211188603 -0.028876382 0.139391934 3.116494528 -0.412425637
[46] 0.357790816 -1.780586641 -0.200679939 -0.850001977 -0.045426277
[51] 0.036821613 0.469864560 -0.294758921 -1.071424506 -0.108464478
[56] -1.132771168 -0.138262986 0.626537379 -1.246093575 -0.730693101
[61] -0.667497431 1.697554154 -1.321906249 -1.241979713 0.735717285
[66] -1.072409080 -0.974084225 -0.892800176 -1.035014013 0.904514631
[71] 0.372138217 -0.732323588 -0.638203144 1.133889071 1.083212801
[76] 1.872649705 -0.273332112 0.958826596 0.967092169 -0.378188590
[81] -0.610848490 0.010049182 1.525331680 -1.434003391 0.395682461
[86] 0.661634696 -0.767043254 -0.946726634 -1.038645970 0.956960445
[91] -0.616001504 0.054982181 1.463995775 1.063945649 -0.483909440
[96] -1.081666032 0.632881909 -1.139104895 -0.720675507 0.698396222
>
> colMeans(tmp2)
[1] 0.04951322
> colSums(tmp2)
[1] 4.951322
> colVars(tmp2)
[1] 1.091588
> colSd(tmp2)
[1] 1.044791
> colMax(tmp2)
[1] 3.116495
> colMin(tmp2)
[1] -1.955662
> colMedians(tmp2)
[1] -0.04268081
> colRanges(tmp2)
[,1]
[1,] -1.955662
[2,] 3.116495
>
> 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] -3.0444203 -3.3452070 0.1190689 1.1489130 -2.5990780 -0.6415484
[7] 0.3501704 2.0487601 -1.2488613 -3.3831089
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.6156608
[2,] -0.6974414
[3,] -0.4036931
[4,] 0.4756792
[5,] 1.3542366
>
> rowApply(tmp,sum)
[1] -5.7436769 2.0934799 4.6176085 -0.3842025 -5.4392160 -4.7265390
[7] 2.0609318 -5.3251594 -0.2556120 2.5070742
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 6 2 4 6 3 7 2 10 6
[2,] 4 5 3 6 9 5 4 3 3 5
[3,] 5 10 7 3 8 6 10 1 7 3
[4,] 9 3 6 2 10 9 5 6 8 4
[5,] 2 2 5 9 5 4 6 9 2 2
[6,] 6 8 8 5 4 8 1 8 9 1
[7,] 1 9 10 7 7 7 3 5 4 9
[8,] 10 7 9 1 3 10 8 4 6 7
[9,] 3 4 1 10 2 2 9 7 5 8
[10,] 8 1 4 8 1 1 2 10 1 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.3870049 -0.5513443 0.1637764 -0.8328121 -2.4142242 0.2531075
[7] 2.3227530 0.2935445 1.9777749 -0.8564647 -3.4409914 0.6582679
[13] 0.2303560 -1.1282197 1.0158581 2.3873321 -0.9896383 2.9183128
[19] 1.6727307 -0.7733458
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1162020
[2,] -0.8722757
[3,] -0.5787432
[4,] -0.4865822
[5,] 0.6667981
>
> rowApply(tmp,sum)
[1] -2.9034583 -0.8819424 -3.0767307 2.3303249 5.0515748
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 4 4 6 5
[2,] 7 14 7 4 19
[3,] 15 11 5 10 14
[4,] 9 17 1 18 3
[5,] 13 9 10 5 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.6667981 -0.56026457 0.490457538 -0.4456084 -0.03761683 -1.7732490
[2,] -0.8722757 0.02241886 -0.108936890 0.3187076 -0.14131592 -0.3645082
[3,] -1.1162020 -0.62218825 -0.912777259 -1.4847654 -0.19213520 0.5471834
[4,] -0.5787432 -1.19178206 -0.003650041 1.6315290 -0.66884195 1.0645979
[5,] -0.4865822 1.80047170 0.698683017 -0.8526748 -1.37431434 0.7790834
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1262930 -0.4408327 0.7096124 -1.0881884 -2.0579396 0.20515525
[2,] -0.9848691 -0.1205413 -0.1928918 -0.2856630 -1.6584111 0.18547687
[3,] 0.8351908 -0.6697454 -1.1951092 0.2135129 0.3192128 0.54024671
[4,] 2.2309762 0.5526232 1.7962155 -1.6905257 1.1859887 -0.20722696
[5,] 0.3677481 0.9720406 0.8599480 1.9943995 -1.2298422 -0.06538401
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.7561475 -0.2165443 -0.67446914 1.13459464 2.5232385 -0.6137303
[2,] 0.3097387 -0.5593904 -0.08661191 1.06660790 -1.6874862 2.8333816
[3,] 0.8796437 -0.2193154 1.51629194 -0.14004648 0.5012383 -0.0954068
[4,] -1.2829799 -0.3489478 0.21807380 0.29038330 -1.6495424 0.2792850
[5,] -0.4321940 0.2159783 0.04257338 0.03579274 -0.6770865 0.5147833
[,19] [,20]
[1,] -0.8715546 -0.48317128
[2,] 1.5174811 -0.07285345
[3,] -1.2071465 -0.57441319
[4,] 0.9386383 -0.23574609
[5,] 1.2953125 0.59283818
>
>
> 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 : 655 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 1.246528 1.589246 0.644929 -0.05932197 0.7880438 -0.3325771 0.921383
col8 col9 col10 col11 col12 col13 col14
row1 -0.8818766 -0.7901499 -1.492318 -0.0727276 -0.8860874 -0.1376456 0.9793122
col15 col16 col17 col18 col19 col20
row1 -0.2773607 -0.5147213 0.3001742 2.427996 2.743452 -0.7646187
> tmp[,"col10"]
col10
row1 -1.49231753
row2 0.28394197
row3 -0.34884095
row4 -0.38108597
row5 -0.04967543
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.246528 1.5892464 0.644929 -0.05932197 0.7880438 -0.3325771 0.9213830
row5 -1.079710 -0.2063932 1.662528 1.04166528 -0.4023238 -0.4340406 0.8262168
col8 col9 col10 col11 col12 col13
row1 -0.8818766 -0.7901499 -1.49231753 -0.0727276 -0.8860874 -0.1376456
row5 0.3113106 -0.1999222 -0.04967543 -0.3544440 -0.8119170 -0.9537418
col14 col15 col16 col17 col18 col19
row1 0.9793122 -0.2773607 -0.5147213 0.3001742 2.4279956 2.743452
row5 -0.8459877 -1.1890976 0.8062589 -1.2932607 -0.8165128 -1.661149
col20
row1 -0.7646187
row5 -0.5697126
> tmp[,c("col6","col20")]
col6 col20
row1 -0.3325771 -0.7646187
row2 0.6236514 -2.1385361
row3 0.4105213 0.3616592
row4 0.7150634 0.4888259
row5 -0.4340406 -0.5697126
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.3325771 -0.7646187
row5 -0.4340406 -0.5697126
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.4213 50.36051 50.3106 49.86711 50.56391 104.3768 50.40334 49.34205
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.59386 49.49687 49.60239 48.64357 49.9053 50.05109 48.63011 49.97261
col17 col18 col19 col20
row1 50.22485 48.70699 49.16512 105.0388
> tmp[,"col10"]
col10
row1 49.49687
row2 28.41505
row3 29.98760
row4 30.92118
row5 50.02483
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.42130 50.36051 50.3106 49.86711 50.56391 104.3768 50.40334 49.34205
row5 50.96182 50.22540 48.3745 49.51391 48.43333 106.3719 48.03597 48.24404
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.59386 49.49687 49.60239 48.64357 49.90530 50.05109 48.63011 49.97261
row5 51.32434 50.02483 48.79322 47.30171 51.01168 51.17324 50.40301 50.60285
col17 col18 col19 col20
row1 50.22485 48.70699 49.16512 105.0388
row5 51.30849 49.31478 48.94643 105.9103
> tmp[,c("col6","col20")]
col6 col20
row1 104.37678 105.03882
row2 75.07641 74.52765
row3 76.23788 74.55033
row4 75.74324 74.47599
row5 106.37193 105.91034
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.3768 105.0388
row5 106.3719 105.9103
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.3768 105.0388
row5 106.3719 105.9103
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.0383761
[2,] -0.8064887
[3,] 0.5725268
[4,] 0.2230642
[5,] 1.4916914
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.3947253 2.1550098
[2,] 2.0624790 -0.8965063
[3,] -0.5982829 0.2428536
[4,] 1.7813194 -0.7539631
[5,] -2.2975517 0.1089557
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.2342350 -0.6778276
[2,] 1.3962516 -1.1487771
[3,] 1.5110880 0.8114376
[4,] 0.2590166 -1.5065423
[5,] -0.2540796 0.2477536
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.234235
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.234235
[2,] 1.396252
>
>
>
> 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 -0.3580978 -0.1712076 1.8763556 0.2149551 0.08007602 1.4713027 -0.07616135
row1 -0.4068569 -0.2298056 0.0466987 0.8887529 0.91460233 0.2542729 0.25489359
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.2660669 0.3318739 -0.6576149 0.5795978 -1.7104152 -1.460764 0.3589321
row1 1.2354657 0.4928198 0.4725075 -0.4591702 0.9375717 2.065785 1.2008903
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.6341549 -0.4915142 0.4818042 -1.2992694 1.297660 0.8615721
row1 1.9171849 0.6732515 0.6669606 -0.9307235 1.566531 -0.7780966
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5894685 -0.6968299 -0.3889978 -0.4383045 0.4929494 0.2088211 1.186082
[,8] [,9] [,10]
row2 -0.2363437 -0.1773043 -0.7180774
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1546254 -1.203516 0.06200352 1.371527 1.760281 1.037852 0.4546145
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.396068 1.051834 1.018318 -0.4583035 1.873709 -0.4957113 0.266486
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5647273 -0.8048168 -1.111108 -0.4769384 0.6918472 -1.107916
>
>
> 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: 0x927874600>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa5762e20ca"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa54e6aea63"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa54d4231cd"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa534d3b15b"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa53620e875"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa52a7d7516"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa512920d25"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa5329d01a9"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa561d81834"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa5321d301b"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa51a415651"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa53789ed4e"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa5403ab85e"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa54f1e4443"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM12aa54c13b349"
>
>
> ### 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: 0x9278750e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x9278750e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x9278750e0>
> rowMedians(tmp)
[1] 0.090701154 -0.226862512 0.612893572 0.504612341 0.174806059
[6] -0.426960969 0.158073938 -0.122392367 0.454485669 0.308228001
[11] 0.347153123 -0.135136728 0.081990193 0.453506521 -0.208915200
[16] -0.201150646 -0.468255168 0.088319506 0.151436902 -0.018579044
[21] 0.336108483 0.549284049 0.215307136 0.015907100 0.310797626
[26] 0.282894969 0.006368186 0.235240275 0.040630482 0.588975034
[31] 0.030507154 0.010231358 0.291808377 0.439123854 0.236010193
[36] 0.058879702 -0.034273759 0.140396157 0.145590919 -0.412607955
[41] 0.125414113 -0.029440507 -0.481924286 -0.174504443 0.399722553
[46] 0.404271818 -0.160807098 -0.023754779 -0.280518253 -0.116035994
[51] -0.120795448 -0.218378067 -0.571231664 0.285498266 0.470446493
[56] -0.411492364 -0.220189625 -0.210743537 0.304732831 0.185340182
[61] -0.079388572 0.459693667 -0.259458730 0.080481077 0.218224358
[66] 0.153684959 0.069373357 -0.273703762 -0.378041484 -0.489977333
[71] 0.152129493 0.500133335 0.220107207 -0.651495666 0.168038282
[76] 0.197707474 0.096601523 -0.020151034 -0.326183810 0.233725739
[81] 0.100338894 0.008912317 -0.708147915 0.493093612 0.034795008
[86] 0.443792567 -0.198604316 0.582969537 0.111481740 -0.463544413
[91] 0.069399343 0.008893357 0.216606435 -0.092295366 -0.588680269
[96] 0.170983078 0.275060968 -0.192067427 0.019530900 0.175711012
[101] -0.365009449 -0.516708094 0.032298605 0.269675623 -0.476050374
[106] -0.292380577 0.130704141 0.101643816 0.408293916 0.261255879
[111] 0.669735072 -0.321920942 0.257577246 0.310384817 0.204873111
[116] -0.201671638 -0.633035129 0.280874914 -0.422189420 0.470526349
[121] -0.538683243 -0.085865559 0.019157973 0.235530218 -0.294291051
[126] 0.116400885 -0.247469736 0.650760910 -0.204739763 -0.182971827
[131] -0.607260065 -0.253418666 0.010068544 0.576081646 -0.444119113
[136] 0.155216227 0.183212606 -0.502681796 -0.293923266 0.005750588
[141] -0.242258638 -0.579935598 0.112462073 -0.184560917 -0.458349543
[146] 0.180266558 -0.252385436 -0.348407302 0.049605730 0.474671831
[151] 0.219366437 -0.300656268 0.058739197 0.095981117 -0.617210714
[156] 0.322408546 -0.260188715 -0.586538489 -0.408556448 -0.601324227
[161] -0.499822034 0.400353651 0.778632326 -0.626177207 0.333946195
[166] -0.247179659 -0.369353210 -0.031042444 -0.067796971 0.098260309
[171] 0.163167599 -0.148131818 0.409503390 0.263342847 0.018817518
[176] -0.274262353 0.277595409 0.060769860 -0.112092117 -0.511699888
[181] 0.404132243 -0.014669173 -0.139443944 -0.515840695 -0.029434495
[186] -0.562703644 0.451283300 0.019364787 -0.166493423 -0.264258138
[191] 0.705560633 0.149450596 -0.469791503 -0.085246598 0.296173793
[196] -0.288919012 0.106818645 -0.247881975 -0.215780368 0.433069095
[201] 0.110753742 0.258691358 -0.121347479 0.088910338 0.252580957
[206] 0.138428767 0.108309720 -0.218864748 -0.311480357 -0.258101847
[211] 0.026303494 0.037177515 -0.125791756 0.170679363 -0.251425088
[216] 0.435610687 -0.146463738 -0.035373080 -0.009198881 -0.244649317
[221] -0.155006644 -0.182819480 -0.038519763 -0.003342167 -0.191022619
[226] 0.387821879 -0.096445327 0.339738978 -0.193391553 0.517668282
>
> proc.time()
user system elapsed
0.801 5.136 6.392
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 alpha (2026-04-08 r89818)
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: 0x101bf72d0>
> .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: 0x101bf72d0>
> .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: 0x101bf72d0>
> .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: 0x101bf72d0>
> 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: 0x8dadf03c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf03c0>
> .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: 0x8dadf03c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf03c0>
> .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: 0x8dadf03c0>
> 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: 0x8dadf05a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf05a0>
> .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: 0x8dadf05a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x8dadf05a0>
> .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: 0x8dadf05a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x8dadf05a0>
> .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: 0x8dadf05a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x8dadf05a0>
> .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: 0x8dadf05a0>
> 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: 0x8dadf0780>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x8dadf0780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf0780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf0780>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12dbf1e95077a" "BufferedMatrixFile12dbf58605d6a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12dbf1e95077a" "BufferedMatrixFile12dbf58605d6a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf0a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf0a20>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x8dadf0a20>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x8dadf0a20>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x8dadf0a20>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x8dadf0a20>
> .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: 0x8dadf0c00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x8dadf0c00>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x8dadf0c00>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x8dadf0c00>
> 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: 0x8dadf0de0>
> .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: 0x8dadf0de0>
> rm(P)
>
> proc.time()
user system elapsed
0.131 0.056 0.186
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 alpha (2026-04-08 r89818)
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
0.120 0.029 0.143