Ben Bolstad
| Snapshot Date: 2026-05-18 13:45 -0400 (Mon, 18 May 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 2d99771 |
| git_last_commit_date: 2026-04-28 08:32:08 -0400 (Tue, 28 Apr 2026) |
| Back to Multiple platform build/check report for BioC 3.24: simplified long |
|
This page was generated on 2026-05-19 12:54 -0400 (Tue, 19 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4898 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There" | 4617 |
| 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 259/2377 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.77.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | | |||||||||
| 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: 1.77.0 |
| 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_1.77.0.tar.gz |
| StartedAt: 2026-05-18 20:36:51 -0400 (Mon, 18 May 2026) |
| EndedAt: 2026-05-18 20:37:14 -0400 (Mon, 18 May 2026) |
| EllapsedTime: 22.3 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_1.77.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 Patched (2026-05-01 r89994)
* 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: 2026-05-19 00:36:52 UTC
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.77.0’
* 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-3.24-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-3.24-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 ‘1.77.0’
** 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 Patched (2026-05-01 r89994) -- "Because it was There"
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
0.129 0.063 0.202
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There"
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-3.24-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 482663 25.8 1063038 56.8 NA 631997 33.8
Vcells 893071 6.9 8388608 64.0 196608 2112627 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 May 18 20:37:03 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 May 18 20:37:03 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: 0x104020520>
>
>
>
> 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 May 18 20:37:05 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 May 18 20:37:06 2026"
>
> ColMode(tmp2)
<pointer: 0x104020520>
>
>
>
> ### 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,] 101.36955767 -0.2641950 -0.52576199 -1.1278200
[2,] 1.17256624 0.9092827 -0.01260344 0.4246186
[3,] 0.03457339 0.2310199 -0.18010937 -0.5680618
[4,] 1.83615591 0.2932824 0.63991013 0.2518390
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.36955767 0.2641950 0.52576199 1.1278200
[2,] 1.17256624 0.9092827 0.01260344 0.4246186
[3,] 0.03457339 0.2310199 0.18010937 0.5680618
[4,] 1.83615591 0.2932824 0.63991013 0.2518390
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0682450 0.5139990 0.7250945 1.0619887
[2,] 1.0828510 0.9535632 0.1122650 0.6516277
[3,] 0.1859392 0.4806453 0.4243929 0.7536987
[4,] 1.3550483 0.5415555 0.7999438 0.5018356
>
> 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-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 227.05201 30.40419 32.77671 36.74771
[2,] 37.00108 35.44491 26.13525 31.94090
[3,] 26.89397 30.03747 29.42404 33.10505
[4,] 40.38664 30.70884 33.63935 30.27020
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x104020580>
> exp(tmp5)
<pointer: 0x104020580>
> log(tmp5,2)
<pointer: 0x104020580>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.579
> Min(tmp5)
[1] 54.39711
> mean(tmp5)
[1] 72.2129
> Sum(tmp5)
[1] 14442.58
> Var(tmp5)
[1] 880.3733
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.24758 67.91707 69.41665 70.01158 67.83594 69.56750 74.30065 70.22921
[9] 71.60216 71.00064
> rowSums(tmp5)
[1] 1804.952 1358.341 1388.333 1400.232 1356.719 1391.350 1486.013 1404.584
[9] 1432.043 1420.013
> rowVars(tmp5)
[1] 8177.43841 47.36570 86.69538 90.57826 38.66258 77.05289
[7] 82.69210 50.78631 60.65818 95.49533
> rowSd(tmp5)
[1] 90.429190 6.882274 9.311035 9.517261 6.217924 8.777977 9.093519
[8] 7.126452 7.788336 9.772171
> rowMax(tmp5)
[1] 472.57901 84.67107 91.10507 93.19726 77.49140 85.32485 97.64824
[8] 78.88459 84.03434 94.55084
> rowMin(tmp5)
[1] 57.45397 54.39711 55.97627 57.32334 58.58327 56.05957 59.32130 54.78983
[9] 56.09759 58.76062
>
> colMeans(tmp5)
[1] 110.75978 67.77317 66.79069 68.94663 65.72192 68.59993 68.65969
[8] 67.90895 69.07703 73.99076 67.85645 70.71044 71.61403 74.62136
[15] 70.80333 67.00965 75.10161 72.85345 70.92223 74.53689
> colSums(tmp5)
[1] 1107.5978 677.7317 667.9069 689.4663 657.2192 685.9993 686.5969
[8] 679.0895 690.7703 739.9076 678.5645 707.1044 716.1403 746.2136
[15] 708.0333 670.0965 751.0161 728.5345 709.2223 745.3689
> colVars(tmp5)
[1] 16233.05334 42.10396 60.24045 47.57041 68.70798 32.15588
[7] 75.76868 77.59820 60.17238 125.01062 85.65652 38.79575
[13] 64.01614 109.58287 64.11190 38.84194 186.72536 70.90433
[19] 61.80698 15.15398
> colSd(tmp5)
[1] 127.409000 6.488757 7.761472 6.897130 8.289028 5.670616
[7] 8.704521 8.808984 7.757086 11.180815 9.255081 6.228624
[13] 8.001008 10.468184 8.006991 6.232330 13.664749 8.420471
[19] 7.861741 3.892811
> colMax(tmp5)
[1] 472.57901 80.74954 79.17297 79.15139 78.44573 75.42704 82.43473
[8] 85.32485 79.72561 91.10507 84.46353 77.80013 84.67107 97.64824
[15] 84.03434 79.75607 94.55084 84.72434 83.38817 79.24199
> colMin(tmp5)
[1] 55.97627 58.94893 54.39711 58.58327 56.05957 58.32190 54.78983 57.32334
[9] 59.17885 58.61104 55.97792 61.29800 60.93641 56.90794 59.70269 59.65429
[17] 59.04781 58.76062 60.32079 65.66794
>
>
> ### 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] 90.24758 67.91707 69.41665 NA 67.83594 69.56750 74.30065 70.22921
[9] 71.60216 71.00064
> rowSums(tmp5)
[1] 1804.952 1358.341 1388.333 NA 1356.719 1391.350 1486.013 1404.584
[9] 1432.043 1420.013
> rowVars(tmp5)
[1] 8177.43841 47.36570 86.69538 64.17321 38.66258 77.05289
[7] 82.69210 50.78631 60.65818 95.49533
> rowSd(tmp5)
[1] 90.429190 6.882274 9.311035 8.010818 6.217924 8.777977 9.093519
[8] 7.126452 7.788336 9.772171
> rowMax(tmp5)
[1] 472.57901 84.67107 91.10507 NA 77.49140 85.32485 97.64824
[8] 78.88459 84.03434 94.55084
> rowMin(tmp5)
[1] 57.45397 54.39711 55.97627 NA 58.58327 56.05957 59.32130 54.78983
[9] 56.09759 58.76062
>
> colMeans(tmp5)
[1] 110.75978 67.77317 66.79069 68.94663 65.72192 68.59993 68.65969
[8] 67.90895 69.07703 73.99076 67.85645 70.71044 71.61403 74.62136
[15] 70.80333 67.00965 NA 72.85345 70.92223 74.53689
> colSums(tmp5)
[1] 1107.5978 677.7317 667.9069 689.4663 657.2192 685.9993 686.5969
[8] 679.0895 690.7703 739.9076 678.5645 707.1044 716.1403 746.2136
[15] 708.0333 670.0965 NA 728.5345 709.2223 745.3689
> colVars(tmp5)
[1] 16233.05334 42.10396 60.24045 47.57041 68.70798 32.15588
[7] 75.76868 77.59820 60.17238 125.01062 85.65652 38.79575
[13] 64.01614 109.58287 64.11190 38.84194 NA 70.90433
[19] 61.80698 15.15398
> colSd(tmp5)
[1] 127.409000 6.488757 7.761472 6.897130 8.289028 5.670616
[7] 8.704521 8.808984 7.757086 11.180815 9.255081 6.228624
[13] 8.001008 10.468184 8.006991 6.232330 NA 8.420471
[19] 7.861741 3.892811
> colMax(tmp5)
[1] 472.57901 80.74954 79.17297 79.15139 78.44573 75.42704 82.43473
[8] 85.32485 79.72561 91.10507 84.46353 77.80013 84.67107 97.64824
[15] 84.03434 79.75607 NA 84.72434 83.38817 79.24199
> colMin(tmp5)
[1] 55.97627 58.94893 54.39711 58.58327 56.05957 58.32190 54.78983 57.32334
[9] 59.17885 58.61104 55.97792 61.29800 60.93641 56.90794 59.70269 59.65429
[17] NA 58.76062 60.32079 65.66794
>
> Max(tmp5,na.rm=TRUE)
[1] 472.579
> Min(tmp5,na.rm=TRUE)
[1] 54.39711
> mean(tmp5,na.rm=TRUE)
[1] 72.10745
> Sum(tmp5,na.rm=TRUE)
[1] 14349.38
> Var(tmp5,na.rm=TRUE)
[1] 882.5845
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.24758 67.91707 69.41665 68.79129 67.83594 69.56750 74.30065 70.22921
[9] 71.60216 71.00064
> rowSums(tmp5,na.rm=TRUE)
[1] 1804.952 1358.341 1388.333 1307.034 1356.719 1391.350 1486.013 1404.584
[9] 1432.043 1420.013
> rowVars(tmp5,na.rm=TRUE)
[1] 8177.43841 47.36570 86.69538 64.17321 38.66258 77.05289
[7] 82.69210 50.78631 60.65818 95.49533
> rowSd(tmp5,na.rm=TRUE)
[1] 90.429190 6.882274 9.311035 8.010818 6.217924 8.777977 9.093519
[8] 7.126452 7.788336 9.772171
> rowMax(tmp5,na.rm=TRUE)
[1] 472.57901 84.67107 91.10507 84.05950 77.49140 85.32485 97.64824
[8] 78.88459 84.03434 94.55084
> rowMin(tmp5,na.rm=TRUE)
[1] 57.45397 54.39711 55.97627 57.32334 58.58327 56.05957 59.32130 54.78983
[9] 56.09759 58.76062
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.75978 67.77317 66.79069 68.94663 65.72192 68.59993 68.65969
[8] 67.90895 69.07703 73.99076 67.85645 70.71044 71.61403 74.62136
[15] 70.80333 67.00965 73.09099 72.85345 70.92223 74.53689
> colSums(tmp5,na.rm=TRUE)
[1] 1107.5978 677.7317 667.9069 689.4663 657.2192 685.9993 686.5969
[8] 679.0895 690.7703 739.9076 678.5645 707.1044 716.1403 746.2136
[15] 708.0333 670.0965 657.8189 728.5345 709.2223 745.3689
> colVars(tmp5,na.rm=TRUE)
[1] 16233.05334 42.10396 60.24045 47.57041 68.70798 32.15588
[7] 75.76868 77.59820 60.17238 125.01062 85.65652 38.79575
[13] 64.01614 109.58287 64.11190 38.84194 164.58651 70.90433
[19] 61.80698 15.15398
> colSd(tmp5,na.rm=TRUE)
[1] 127.409000 6.488757 7.761472 6.897130 8.289028 5.670616
[7] 8.704521 8.808984 7.757086 11.180815 9.255081 6.228624
[13] 8.001008 10.468184 8.006991 6.232330 12.829127 8.420471
[19] 7.861741 3.892811
> colMax(tmp5,na.rm=TRUE)
[1] 472.57901 80.74954 79.17297 79.15139 78.44573 75.42704 82.43473
[8] 85.32485 79.72561 91.10507 84.46353 77.80013 84.67107 97.64824
[15] 84.03434 79.75607 94.55084 84.72434 83.38817 79.24199
> colMin(tmp5,na.rm=TRUE)
[1] 55.97627 58.94893 54.39711 58.58327 56.05957 58.32190 54.78983 57.32334
[9] 59.17885 58.61104 55.97792 61.29800 60.93641 56.90794 59.70269 59.65429
[17] 59.04781 58.76062 60.32079 65.66794
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.24758 67.91707 69.41665 NaN 67.83594 69.56750 74.30065 70.22921
[9] 71.60216 71.00064
> rowSums(tmp5,na.rm=TRUE)
[1] 1804.952 1358.341 1388.333 0.000 1356.719 1391.350 1486.013 1404.584
[9] 1432.043 1420.013
> rowVars(tmp5,na.rm=TRUE)
[1] 8177.43841 47.36570 86.69538 NA 38.66258 77.05289
[7] 82.69210 50.78631 60.65818 95.49533
> rowSd(tmp5,na.rm=TRUE)
[1] 90.429190 6.882274 9.311035 NA 6.217924 8.777977 9.093519
[8] 7.126452 7.788336 9.772171
> rowMax(tmp5,na.rm=TRUE)
[1] 472.57901 84.67107 91.10507 NA 77.49140 85.32485 97.64824
[8] 78.88459 84.03434 94.55084
> rowMin(tmp5,na.rm=TRUE)
[1] 57.45397 54.39711 55.97627 NA 58.58327 56.05957 59.32130 54.78983
[9] 56.09759 58.76062
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.72647 68.20170 66.43234 69.60698 64.30816 69.45915 69.55096
[8] 69.08513 69.92215 74.81010 68.32519 69.92270 72.80043 74.20259
[15] 70.61824 67.56142 NaN 72.32138 70.55756 74.64617
> colSums(tmp5,na.rm=TRUE)
[1] 1023.5383 613.8153 597.8910 626.4628 578.7735 625.1324 625.9587
[8] 621.7662 629.2993 673.2909 614.9267 629.3043 655.2039 667.8233
[15] 635.5642 608.0528 0.0000 650.8924 635.0180 671.8156
> colVars(tmp5,na.rm=TRUE)
[1] 18163.17044 45.30105 66.32579 48.61095 54.81101 27.86993
[7] 76.30307 71.73477 59.65882 133.08465 93.89181 36.66415
[13] 56.18321 121.30783 71.74050 40.27208 NA 76.58246
[19] 68.03672 16.91388
> colSd(tmp5,na.rm=TRUE)
[1] 134.770807 6.730606 8.144065 6.972156 7.403446 5.279198
[7] 8.735163 8.469638 7.723912 11.536232 9.689779 6.055093
[13] 7.495546 11.013983 8.469976 6.346028 NA 8.751140
[19] 8.248438 4.112649
> colMax(tmp5,na.rm=TRUE)
[1] 472.57901 80.74954 79.17297 79.15139 77.02034 75.42704 82.43473
[8] 85.32485 79.72561 91.10507 84.46353 77.72369 84.67107 97.64824
[15] 84.03434 79.75607 -Inf 84.72434 83.38817 79.24199
> colMin(tmp5,na.rm=TRUE)
[1] 55.97627 58.94893 54.39711 58.58327 56.05957 58.32190 54.78983 57.45397
[9] 59.17885 58.61104 55.97792 61.29800 61.64435 56.90794 59.70269 59.65429
[17] Inf 58.76062 60.32079 65.66794
>
>
>
>
> 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] 259.6184 306.2412 223.3827 194.1081 393.1094 269.0389 247.9555 280.7552
[9] 173.8705 256.1694
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 259.6184 306.2412 223.3827 194.1081 393.1094 269.0389 247.9555 280.7552
[9] 173.8705 256.1694
>
>
>
> 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] -2.842171e-14 5.684342e-14 -1.136868e-13 4.263256e-14 -1.278977e-13
[6] 0.000000e+00 1.136868e-13 -1.136868e-13 -4.263256e-14 7.105427e-14
[11] 0.000000e+00 -1.136868e-13 -1.136868e-13 5.684342e-14 1.136868e-13
[16] -8.526513e-14 -1.705303e-13 1.989520e-13 -4.263256e-14 -4.263256e-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)
+ }
3 18
10 2
8 4
2 15
5 4
6 12
6 12
9 5
1 4
6 20
1 20
6 4
6 8
7 10
8 1
6 6
5 14
10 6
7 11
7 17
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] 2.017271
> Min(tmp)
[1] -2.51759
> mean(tmp)
[1] 0.02560579
> Sum(tmp)
[1] 2.560579
> Var(tmp)
[1] 0.8754805
>
> rowMeans(tmp)
[1] 0.02560579
> rowSums(tmp)
[1] 2.560579
> rowVars(tmp)
[1] 0.8754805
> rowSd(tmp)
[1] 0.9356712
> rowMax(tmp)
[1] 2.017271
> rowMin(tmp)
[1] -2.51759
>
> colMeans(tmp)
[1] -1.99069443 -0.85639710 0.77292734 -0.40396657 1.58439930 0.30188032
[7] 0.54837798 -0.38889969 0.24423243 0.99246735 0.29918591 -0.63043870
[13] 1.50599342 0.67319845 -0.86071849 -0.62379229 0.17979396 0.17457436
[19] 0.44428806 0.71106877 -1.21708690 0.96604064 1.13208355 0.40201156
[25] 1.05445541 -0.48121674 1.12816083 -0.56444698 0.55096629 -0.49898501
[31] 1.11139243 -0.21689423 0.39584853 0.64971767 0.05384694 0.81153245
[37] 0.93258173 1.90586516 -1.16759461 -0.04041542 0.73639467 -1.06016531
[43] 1.32559957 0.58626106 -1.08054559 -0.91105631 -2.51758966 0.63017761
[49] 0.40332044 -0.52482468 1.11799835 -0.93903289 -1.16804993 -0.13678857
[55] -0.28538345 -1.78469485 -0.39475291 0.36424592 -0.22546043 -0.87910366
[61] 0.02947778 -0.09909499 0.49633784 0.94544689 -0.57287074 1.03210802
[67] 0.84502807 -0.27103489 0.10405584 -0.66561298 -1.00603387 -1.85917019
[73] 0.04353870 -0.68877324 0.26310201 0.03144759 -1.33396815 1.67640635
[79] -1.25548060 2.01727128 -0.82537745 0.52296044 1.11363307 -0.36053962
[85] -0.56672843 -0.21982248 -1.27892746 -0.19488446 -0.10523089 0.43444475
[91] 0.23243233 1.89902962 -1.36560453 -0.20698951 0.56354205 0.10325965
[97] 0.80974016 -1.93874859 1.25924968 0.11106736
> colSums(tmp)
[1] -1.99069443 -0.85639710 0.77292734 -0.40396657 1.58439930 0.30188032
[7] 0.54837798 -0.38889969 0.24423243 0.99246735 0.29918591 -0.63043870
[13] 1.50599342 0.67319845 -0.86071849 -0.62379229 0.17979396 0.17457436
[19] 0.44428806 0.71106877 -1.21708690 0.96604064 1.13208355 0.40201156
[25] 1.05445541 -0.48121674 1.12816083 -0.56444698 0.55096629 -0.49898501
[31] 1.11139243 -0.21689423 0.39584853 0.64971767 0.05384694 0.81153245
[37] 0.93258173 1.90586516 -1.16759461 -0.04041542 0.73639467 -1.06016531
[43] 1.32559957 0.58626106 -1.08054559 -0.91105631 -2.51758966 0.63017761
[49] 0.40332044 -0.52482468 1.11799835 -0.93903289 -1.16804993 -0.13678857
[55] -0.28538345 -1.78469485 -0.39475291 0.36424592 -0.22546043 -0.87910366
[61] 0.02947778 -0.09909499 0.49633784 0.94544689 -0.57287074 1.03210802
[67] 0.84502807 -0.27103489 0.10405584 -0.66561298 -1.00603387 -1.85917019
[73] 0.04353870 -0.68877324 0.26310201 0.03144759 -1.33396815 1.67640635
[79] -1.25548060 2.01727128 -0.82537745 0.52296044 1.11363307 -0.36053962
[85] -0.56672843 -0.21982248 -1.27892746 -0.19488446 -0.10523089 0.43444475
[91] 0.23243233 1.89902962 -1.36560453 -0.20698951 0.56354205 0.10325965
[97] 0.80974016 -1.93874859 1.25924968 0.11106736
> 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] -1.99069443 -0.85639710 0.77292734 -0.40396657 1.58439930 0.30188032
[7] 0.54837798 -0.38889969 0.24423243 0.99246735 0.29918591 -0.63043870
[13] 1.50599342 0.67319845 -0.86071849 -0.62379229 0.17979396 0.17457436
[19] 0.44428806 0.71106877 -1.21708690 0.96604064 1.13208355 0.40201156
[25] 1.05445541 -0.48121674 1.12816083 -0.56444698 0.55096629 -0.49898501
[31] 1.11139243 -0.21689423 0.39584853 0.64971767 0.05384694 0.81153245
[37] 0.93258173 1.90586516 -1.16759461 -0.04041542 0.73639467 -1.06016531
[43] 1.32559957 0.58626106 -1.08054559 -0.91105631 -2.51758966 0.63017761
[49] 0.40332044 -0.52482468 1.11799835 -0.93903289 -1.16804993 -0.13678857
[55] -0.28538345 -1.78469485 -0.39475291 0.36424592 -0.22546043 -0.87910366
[61] 0.02947778 -0.09909499 0.49633784 0.94544689 -0.57287074 1.03210802
[67] 0.84502807 -0.27103489 0.10405584 -0.66561298 -1.00603387 -1.85917019
[73] 0.04353870 -0.68877324 0.26310201 0.03144759 -1.33396815 1.67640635
[79] -1.25548060 2.01727128 -0.82537745 0.52296044 1.11363307 -0.36053962
[85] -0.56672843 -0.21982248 -1.27892746 -0.19488446 -0.10523089 0.43444475
[91] 0.23243233 1.89902962 -1.36560453 -0.20698951 0.56354205 0.10325965
[97] 0.80974016 -1.93874859 1.25924968 0.11106736
> colMin(tmp)
[1] -1.99069443 -0.85639710 0.77292734 -0.40396657 1.58439930 0.30188032
[7] 0.54837798 -0.38889969 0.24423243 0.99246735 0.29918591 -0.63043870
[13] 1.50599342 0.67319845 -0.86071849 -0.62379229 0.17979396 0.17457436
[19] 0.44428806 0.71106877 -1.21708690 0.96604064 1.13208355 0.40201156
[25] 1.05445541 -0.48121674 1.12816083 -0.56444698 0.55096629 -0.49898501
[31] 1.11139243 -0.21689423 0.39584853 0.64971767 0.05384694 0.81153245
[37] 0.93258173 1.90586516 -1.16759461 -0.04041542 0.73639467 -1.06016531
[43] 1.32559957 0.58626106 -1.08054559 -0.91105631 -2.51758966 0.63017761
[49] 0.40332044 -0.52482468 1.11799835 -0.93903289 -1.16804993 -0.13678857
[55] -0.28538345 -1.78469485 -0.39475291 0.36424592 -0.22546043 -0.87910366
[61] 0.02947778 -0.09909499 0.49633784 0.94544689 -0.57287074 1.03210802
[67] 0.84502807 -0.27103489 0.10405584 -0.66561298 -1.00603387 -1.85917019
[73] 0.04353870 -0.68877324 0.26310201 0.03144759 -1.33396815 1.67640635
[79] -1.25548060 2.01727128 -0.82537745 0.52296044 1.11363307 -0.36053962
[85] -0.56672843 -0.21982248 -1.27892746 -0.19488446 -0.10523089 0.43444475
[91] 0.23243233 1.89902962 -1.36560453 -0.20698951 0.56354205 0.10325965
[97] 0.80974016 -1.93874859 1.25924968 0.11106736
> colMedians(tmp)
[1] -1.99069443 -0.85639710 0.77292734 -0.40396657 1.58439930 0.30188032
[7] 0.54837798 -0.38889969 0.24423243 0.99246735 0.29918591 -0.63043870
[13] 1.50599342 0.67319845 -0.86071849 -0.62379229 0.17979396 0.17457436
[19] 0.44428806 0.71106877 -1.21708690 0.96604064 1.13208355 0.40201156
[25] 1.05445541 -0.48121674 1.12816083 -0.56444698 0.55096629 -0.49898501
[31] 1.11139243 -0.21689423 0.39584853 0.64971767 0.05384694 0.81153245
[37] 0.93258173 1.90586516 -1.16759461 -0.04041542 0.73639467 -1.06016531
[43] 1.32559957 0.58626106 -1.08054559 -0.91105631 -2.51758966 0.63017761
[49] 0.40332044 -0.52482468 1.11799835 -0.93903289 -1.16804993 -0.13678857
[55] -0.28538345 -1.78469485 -0.39475291 0.36424592 -0.22546043 -0.87910366
[61] 0.02947778 -0.09909499 0.49633784 0.94544689 -0.57287074 1.03210802
[67] 0.84502807 -0.27103489 0.10405584 -0.66561298 -1.00603387 -1.85917019
[73] 0.04353870 -0.68877324 0.26310201 0.03144759 -1.33396815 1.67640635
[79] -1.25548060 2.01727128 -0.82537745 0.52296044 1.11363307 -0.36053962
[85] -0.56672843 -0.21982248 -1.27892746 -0.19488446 -0.10523089 0.43444475
[91] 0.23243233 1.89902962 -1.36560453 -0.20698951 0.56354205 0.10325965
[97] 0.80974016 -1.93874859 1.25924968 0.11106736
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.990694 -0.8563971 0.7729273 -0.4039666 1.584399 0.3018803 0.548378
[2,] -1.990694 -0.8563971 0.7729273 -0.4039666 1.584399 0.3018803 0.548378
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3888997 0.2442324 0.9924674 0.2991859 -0.6304387 1.505993 0.6731984
[2,] -0.3888997 0.2442324 0.9924674 0.2991859 -0.6304387 1.505993 0.6731984
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.8607185 -0.6237923 0.179794 0.1745744 0.4442881 0.7110688 -1.217087
[2,] -0.8607185 -0.6237923 0.179794 0.1745744 0.4442881 0.7110688 -1.217087
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.9660406 1.132084 0.4020116 1.054455 -0.4812167 1.128161 -0.564447
[2,] 0.9660406 1.132084 0.4020116 1.054455 -0.4812167 1.128161 -0.564447
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.5509663 -0.498985 1.111392 -0.2168942 0.3958485 0.6497177 0.05384694
[2,] 0.5509663 -0.498985 1.111392 -0.2168942 0.3958485 0.6497177 0.05384694
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8115324 0.9325817 1.905865 -1.167595 -0.04041542 0.7363947 -1.060165
[2,] 0.8115324 0.9325817 1.905865 -1.167595 -0.04041542 0.7363947 -1.060165
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.3256 0.5862611 -1.080546 -0.9110563 -2.51759 0.6301776 0.4033204
[2,] 1.3256 0.5862611 -1.080546 -0.9110563 -2.51759 0.6301776 0.4033204
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.5248247 1.117998 -0.9390329 -1.16805 -0.1367886 -0.2853835 -1.784695
[2,] -0.5248247 1.117998 -0.9390329 -1.16805 -0.1367886 -0.2853835 -1.784695
[,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.3947529 0.3642459 -0.2254604 -0.8791037 0.02947778 -0.09909499
[2,] -0.3947529 0.3642459 -0.2254604 -0.8791037 0.02947778 -0.09909499
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.4963378 0.9454469 -0.5728707 1.032108 0.8450281 -0.2710349 0.1040558
[2,] 0.4963378 0.9454469 -0.5728707 1.032108 0.8450281 -0.2710349 0.1040558
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.665613 -1.006034 -1.85917 0.0435387 -0.6887732 0.263102 0.03144759
[2,] -0.665613 -1.006034 -1.85917 0.0435387 -0.6887732 0.263102 0.03144759
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -1.333968 1.676406 -1.255481 2.017271 -0.8253774 0.5229604 1.113633
[2,] -1.333968 1.676406 -1.255481 2.017271 -0.8253774 0.5229604 1.113633
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.3605396 -0.5667284 -0.2198225 -1.278927 -0.1948845 -0.1052309 0.4344448
[2,] -0.3605396 -0.5667284 -0.2198225 -1.278927 -0.1948845 -0.1052309 0.4344448
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.2324323 1.89903 -1.365605 -0.2069895 0.5635421 0.1032596 0.8097402
[2,] 0.2324323 1.89903 -1.365605 -0.2069895 0.5635421 0.1032596 0.8097402
[,98] [,99] [,100]
[1,] -1.938749 1.25925 0.1110674
[2,] -1.938749 1.25925 0.1110674
>
>
> Max(tmp2)
[1] 2.069117
> Min(tmp2)
[1] -2.594384
> mean(tmp2)
[1] 0.04223258
> Sum(tmp2)
[1] 4.223258
> Var(tmp2)
[1] 1.261666
>
> rowMeans(tmp2)
[1] 0.38957002 -0.96373905 -0.42335914 0.32129371 0.57917750 0.75289734
[7] -0.79703508 0.78070834 1.09676058 -1.09107656 0.87436011 0.14498478
[13] -0.37146513 0.46212496 -2.23260782 -1.35990767 -2.04560193 0.26165312
[19] -0.45254021 -0.15343160 1.55515826 -0.44743565 1.26977069 -0.15477243
[25] 0.80791266 0.29540175 -1.35103067 0.65295922 -0.41625071 1.39381091
[31] 0.96186055 0.25430379 0.83210519 -1.59074060 -0.90575853 0.82177632
[37] 1.05506015 1.11492988 1.88428236 -1.51019666 -1.04568519 0.60859777
[43] -0.80304454 1.60363393 1.15537898 -0.06779979 -1.83051380 -0.91241986
[49] -0.82872419 2.06911748 -0.48391516 -1.44002570 0.40897287 1.08144160
[55] 0.05979990 1.57549465 1.84048924 0.23474382 -0.80697530 -0.66321682
[61] 0.02887832 1.08049225 0.88775428 0.48108595 -0.66289411 0.98917825
[67] -2.59438357 1.37486200 -0.23894966 1.72272269 -0.68546008 -0.32235302
[73] 0.56240946 1.29402661 -0.41586454 0.27343094 -1.92442985 0.15073378
[79] -1.41504721 -0.99211850 -1.44318883 -1.03874479 1.30035214 -0.12287880
[85] -0.41643218 -1.36540152 1.83699253 1.00577513 0.74010046 0.63815406
[91] -1.98911480 1.69687831 0.43711970 -1.21249475 0.48718131 1.92819848
[97] 0.76912009 -1.55260904 0.94404409 -2.06513062
> rowSums(tmp2)
[1] 0.38957002 -0.96373905 -0.42335914 0.32129371 0.57917750 0.75289734
[7] -0.79703508 0.78070834 1.09676058 -1.09107656 0.87436011 0.14498478
[13] -0.37146513 0.46212496 -2.23260782 -1.35990767 -2.04560193 0.26165312
[19] -0.45254021 -0.15343160 1.55515826 -0.44743565 1.26977069 -0.15477243
[25] 0.80791266 0.29540175 -1.35103067 0.65295922 -0.41625071 1.39381091
[31] 0.96186055 0.25430379 0.83210519 -1.59074060 -0.90575853 0.82177632
[37] 1.05506015 1.11492988 1.88428236 -1.51019666 -1.04568519 0.60859777
[43] -0.80304454 1.60363393 1.15537898 -0.06779979 -1.83051380 -0.91241986
[49] -0.82872419 2.06911748 -0.48391516 -1.44002570 0.40897287 1.08144160
[55] 0.05979990 1.57549465 1.84048924 0.23474382 -0.80697530 -0.66321682
[61] 0.02887832 1.08049225 0.88775428 0.48108595 -0.66289411 0.98917825
[67] -2.59438357 1.37486200 -0.23894966 1.72272269 -0.68546008 -0.32235302
[73] 0.56240946 1.29402661 -0.41586454 0.27343094 -1.92442985 0.15073378
[79] -1.41504721 -0.99211850 -1.44318883 -1.03874479 1.30035214 -0.12287880
[85] -0.41643218 -1.36540152 1.83699253 1.00577513 0.74010046 0.63815406
[91] -1.98911480 1.69687831 0.43711970 -1.21249475 0.48718131 1.92819848
[97] 0.76912009 -1.55260904 0.94404409 -2.06513062
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.38957002 -0.96373905 -0.42335914 0.32129371 0.57917750 0.75289734
[7] -0.79703508 0.78070834 1.09676058 -1.09107656 0.87436011 0.14498478
[13] -0.37146513 0.46212496 -2.23260782 -1.35990767 -2.04560193 0.26165312
[19] -0.45254021 -0.15343160 1.55515826 -0.44743565 1.26977069 -0.15477243
[25] 0.80791266 0.29540175 -1.35103067 0.65295922 -0.41625071 1.39381091
[31] 0.96186055 0.25430379 0.83210519 -1.59074060 -0.90575853 0.82177632
[37] 1.05506015 1.11492988 1.88428236 -1.51019666 -1.04568519 0.60859777
[43] -0.80304454 1.60363393 1.15537898 -0.06779979 -1.83051380 -0.91241986
[49] -0.82872419 2.06911748 -0.48391516 -1.44002570 0.40897287 1.08144160
[55] 0.05979990 1.57549465 1.84048924 0.23474382 -0.80697530 -0.66321682
[61] 0.02887832 1.08049225 0.88775428 0.48108595 -0.66289411 0.98917825
[67] -2.59438357 1.37486200 -0.23894966 1.72272269 -0.68546008 -0.32235302
[73] 0.56240946 1.29402661 -0.41586454 0.27343094 -1.92442985 0.15073378
[79] -1.41504721 -0.99211850 -1.44318883 -1.03874479 1.30035214 -0.12287880
[85] -0.41643218 -1.36540152 1.83699253 1.00577513 0.74010046 0.63815406
[91] -1.98911480 1.69687831 0.43711970 -1.21249475 0.48718131 1.92819848
[97] 0.76912009 -1.55260904 0.94404409 -2.06513062
> rowMin(tmp2)
[1] 0.38957002 -0.96373905 -0.42335914 0.32129371 0.57917750 0.75289734
[7] -0.79703508 0.78070834 1.09676058 -1.09107656 0.87436011 0.14498478
[13] -0.37146513 0.46212496 -2.23260782 -1.35990767 -2.04560193 0.26165312
[19] -0.45254021 -0.15343160 1.55515826 -0.44743565 1.26977069 -0.15477243
[25] 0.80791266 0.29540175 -1.35103067 0.65295922 -0.41625071 1.39381091
[31] 0.96186055 0.25430379 0.83210519 -1.59074060 -0.90575853 0.82177632
[37] 1.05506015 1.11492988 1.88428236 -1.51019666 -1.04568519 0.60859777
[43] -0.80304454 1.60363393 1.15537898 -0.06779979 -1.83051380 -0.91241986
[49] -0.82872419 2.06911748 -0.48391516 -1.44002570 0.40897287 1.08144160
[55] 0.05979990 1.57549465 1.84048924 0.23474382 -0.80697530 -0.66321682
[61] 0.02887832 1.08049225 0.88775428 0.48108595 -0.66289411 0.98917825
[67] -2.59438357 1.37486200 -0.23894966 1.72272269 -0.68546008 -0.32235302
[73] 0.56240946 1.29402661 -0.41586454 0.27343094 -1.92442985 0.15073378
[79] -1.41504721 -0.99211850 -1.44318883 -1.03874479 1.30035214 -0.12287880
[85] -0.41643218 -1.36540152 1.83699253 1.00577513 0.74010046 0.63815406
[91] -1.98911480 1.69687831 0.43711970 -1.21249475 0.48718131 1.92819848
[97] 0.76912009 -1.55260904 0.94404409 -2.06513062
>
> colMeans(tmp2)
[1] 0.04223258
> colSums(tmp2)
[1] 4.223258
> colVars(tmp2)
[1] 1.261666
> colSd(tmp2)
[1] 1.123239
> colMax(tmp2)
[1] 2.069117
> colMin(tmp2)
[1] -2.594384
> colMedians(tmp2)
[1] 0.2445238
> colRanges(tmp2)
[,1]
[1,] -2.594384
[2,] 2.069117
>
> 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] 5.0888402 -0.2475871 1.9379115 3.2797854 -1.4601792 3.2966602
[7] -0.3070988 -2.6500210 -0.2687558 -9.6373604
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2044996
[2,] -0.1747411
[3,] 0.3653905
[4,] 1.0693041
[5,] 2.3457904
>
> rowApply(tmp,sum)
[1] -2.2525940 -5.9683006 3.3122641 -2.9853932 0.7071448 6.4622365
[7] 0.7774826 -0.8617765 0.8951566 -1.0540256
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 6 8 6 6 10 3 5 10 2
[2,] 10 3 3 2 7 2 9 4 4 10
[3,] 2 9 7 8 4 1 10 8 9 4
[4,] 5 10 9 3 2 9 7 7 6 9
[5,] 8 4 6 4 8 5 1 3 3 8
[6,] 4 7 10 7 10 7 2 9 5 7
[7,] 6 2 5 9 3 3 6 2 8 6
[8,] 7 5 1 5 1 6 8 6 7 5
[9,] 1 1 4 10 5 8 5 10 2 3
[10,] 3 8 2 1 9 4 4 1 1 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.04036640 3.79715327 3.77619257 2.61628016 0.10323393 1.35286971
[7] -1.04220068 -0.14981453 1.07688306 -1.44077039 2.12546952 2.55365083
[13] -2.01264634 -0.06183172 -3.58407768 -0.16311993 -2.46817245 -3.62441894
[19] -0.82219416 4.44549640
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8668752
[2,] -0.1399322
[3,] 0.5120290
[4,] 0.5530554
[5,] 0.9013566
>
> rowApply(tmp,sum)
[1] 0.9979268 2.3851966 -0.2446800 2.8143617 0.4848112
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 10 10 1 18
[2,] 16 16 20 4 9
[3,] 17 13 11 17 20
[4,] 10 11 19 9 8
[5,] 8 20 3 7 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5530554 0.69520237 1.018982042 0.1549739 -0.3965941 -1.3254730823
[2,] 0.5120290 0.79955439 0.683136478 0.6335553 1.3696637 0.0026300372
[3,] -0.1399322 3.01940647 -0.008215538 2.2220085 -1.2639745 -0.0002133857
[4,] -1.8668752 -0.63439642 1.141464791 -0.1823741 -0.5174456 2.0625928879
[5,] 0.9013566 -0.08261354 0.940824798 -0.2118835 0.9115844 0.6133332566
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.39097013 -0.5089147 1.86764143 -0.7229657 1.6475507 0.2879028
[2,] -0.35621170 -1.3038264 -0.85567106 -1.8122756 0.6640753 1.3062640
[3,] 0.06675165 0.3063005 -0.26894085 1.1540238 -0.2519095 -0.1895448
[4,] -0.54710709 0.8405472 0.24010397 -0.3864693 -0.7480752 0.6607098
[5,] -0.59660367 0.5160788 0.09374957 0.3269163 0.8138282 0.4883190
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.5788468 -1.0280414 -1.37224293 0.56130484 -0.16510109 -1.0072705
[2,] 0.7232516 -0.5569968 1.12253797 -0.35782017 -1.59629054 -0.6452914
[3,] -1.7704833 -0.3411809 -1.92533621 0.19007982 0.04379165 -0.8723800
[4,] 1.5213984 1.7314072 -0.02802982 0.09329791 0.05260493 -0.6240048
[5,] -0.9079662 0.1329800 -1.38100669 -0.64998233 -0.80317741 -0.4754722
[,19] [,20]
[1,] 0.6342945 1.2914989
[2,] 0.7584170 1.2944655
[3,] -0.5469365 0.3320053
[4,] -0.9056872 0.9106992
[5,] -0.7622818 0.6168274
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.24-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-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.24-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 0.131013 -0.7089889 -1.011342 0.04179484 -0.4845706 0.02125273 -0.343251
col8 col9 col10 col11 col12 col13 col14
row1 0.7212458 -0.4202652 0.3323228 -1.043831 0.8409191 -0.4672757 -0.2694922
col15 col16 col17 col18 col19 col20
row1 0.2583312 -0.5701957 0.1452515 0.1318724 0.6971007 0.3418814
> tmp[,"col10"]
col10
row1 0.3323228
row2 0.3474417
row3 0.3343771
row4 -0.6086892
row5 0.5788286
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.1310130 -0.70898886 -1.011342 0.04179484 -0.4845706 0.02125273
row5 0.5286597 0.05179294 1.334367 -0.74127687 -0.6726164 0.30975289
col7 col8 col9 col10 col11 col12 col13
row1 -0.343251 0.7212458 -0.42026522 0.3323228 -1.0438313 0.8409191 -0.4672757
row5 -1.292842 -0.7694878 -0.05637617 0.5788286 0.8264759 0.4376534 1.1053714
col14 col15 col16 col17 col18 col19 col20
row1 -0.2694922 0.25833118 -0.5701957 0.1452515 0.1318724 0.6971007 0.3418814
row5 1.7138815 -0.05967385 -0.8564859 1.0972729 1.4202606 -0.1184148 0.5215724
> tmp[,c("col6","col20")]
col6 col20
row1 0.02125273 0.34188141
row2 1.37734006 0.02088081
row3 1.09280155 -2.30847878
row4 -1.59675571 0.52636146
row5 0.30975289 0.52157238
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.02125273 0.3418814
row5 0.30975289 0.5215724
>
>
>
>
> 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 50.69286 50.39058 48.66078 49.82706 50.58805 105.692 50.91655 50.62612
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52924 51.51546 49.10883 51.25713 51.36833 49.41596 49.11728 50.13842
col17 col18 col19 col20
row1 51.10479 51.73365 49.48057 105.0157
> tmp[,"col10"]
col10
row1 51.51546
row2 28.25951
row3 28.49705
row4 30.25759
row5 50.17493
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.69286 50.39058 48.66078 49.82706 50.58805 105.6920 50.91655 50.62612
row5 49.17890 49.94161 50.99684 49.16676 50.05325 105.7168 49.04573 49.71135
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52924 51.51546 49.10883 51.25713 51.36833 49.41596 49.11728 50.13842
row5 49.67320 50.17493 50.88132 49.55927 49.49397 51.65526 49.49791 49.27510
col17 col18 col19 col20
row1 51.10479 51.73365 49.48057 105.0157
row5 51.30389 50.95553 51.58355 105.5782
> tmp[,c("col6","col20")]
col6 col20
row1 105.69203 105.01567
row2 76.46158 75.70653
row3 75.89478 74.00193
row4 75.75237 74.36517
row5 105.71683 105.57820
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6920 105.0157
row5 105.7168 105.5782
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6920 105.0157
row5 105.7168 105.5782
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.6595423
[2,] -1.2818314
[3,] -0.2374679
[4,] 1.5325632
[5,] -1.3374565
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.03704157 -1.57549797
[2,] -0.35161307 -0.45520781
[3,] -0.64384374 -0.06179345
[4,] 0.81941354 -0.40556796
[5,] -1.03105114 -0.69025229
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.82659664 -0.4699062
[2,] 0.16992346 0.5560809
[3,] 0.04547354 -0.7805996
[4,] 1.64085018 -2.2434198
[5,] -0.97365348 -0.1341124
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.8265966
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.8265966
[2,] 0.1699235
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.9573757 -1.4112507 0.2199787 0.6342753 -0.1006501 0.62741298
row1 0.8673816 0.9980178 -0.8740795 -1.2332324 -0.2943374 -0.03056096
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.3285245 -0.4632638 0.7547826 -0.08044853 -1.86150667 -1.4833208
row1 0.2443481 -1.6117827 -1.2685470 -0.10083448 0.01061935 0.4681738
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.1652918 0.5387079 -0.8853212 -1.001073 1.314815 -0.737524 0.7274779
row1 -0.6054079 -0.8236419 0.5476194 -2.538618 2.217762 -1.601221 -1.1354748
[,20]
row3 0.4517088
row1 -2.1507035
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -2.206788 1.474358 -0.6165399 0.5281299 -0.4700424 -0.5483481 0.6701398
[,8] [,9] [,10]
row2 0.8677771 -0.1597464 1.213885
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.04082559 -1.290257 -0.3554383 1.345116 -0.2234076 -0.7752285 0.6919475
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.084365 -0.3925321 0.2089078 -1.056749 -1.358902 0.8336051 -0.2825883
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.663379 -1.129786 0.04569878 -0.2714041 -0.3528865 0.4218278
>
>
> 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: 0xc02a685a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a42b926802"
[2] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a418ea71a7"
[3] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a447cb97b8"
[4] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a4755d5db"
[5] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a4144b20a0"
[6] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a4504af2c8"
[7] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a4688951a6"
[8] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a4f4f9ee8"
[9] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a434499932"
[10] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a44be8bc6f"
[11] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a41cab4258"
[12] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a42f90ae1c"
[13] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a44396c8a9"
[14] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a4604ff1e9"
[15] "/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests/BM36a420932965"
>
>
> ### 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: 0xc02a691a0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xc02a691a0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.24-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xc02a691a0>
> rowMedians(tmp)
[1] 0.168827118 0.220056810 -0.051608542 -0.284055965 -0.008822409
[6] -0.537363080 -0.246740910 -0.442586039 0.110917729 -0.079035273
[11] 0.504107918 0.807447952 -0.258772980 0.115623162 0.416082981
[16] 0.007301472 0.204112974 -0.053631101 0.095601506 -0.089684304
[21] -0.115776406 0.253473205 0.020944023 0.269986057 0.413093131
[26] -0.137040872 0.394241395 0.116821406 -0.106837521 -0.317543805
[31] -0.113481535 -0.400432126 -0.247200734 0.111968851 0.513474028
[36] 0.047747929 0.493553726 -0.579610667 -0.200055401 0.221709215
[41] 0.029540972 -0.010747023 -0.395433421 0.094327100 -0.038031525
[46] -0.084492649 -0.213499434 -0.017643400 -0.718741770 -0.360685288
[51] 0.373262432 0.024945892 -0.019850550 0.149969821 0.141499050
[56] -0.850359912 0.050767862 -0.499256219 -0.089697067 0.296776044
[61] 0.125115318 -0.246445236 -0.223455643 0.418775342 -0.339902061
[66] -0.482925417 0.327156492 0.014534986 0.101885473 -0.332119384
[71] -0.218006233 0.067374665 -0.092379096 -0.413109602 0.017154636
[76] 0.597639354 -0.121742860 0.154594875 0.519361535 0.501710366
[81] 0.260947378 0.502237665 0.479446376 0.068972822 0.276407468
[86] 0.052920905 0.060840595 -0.019187898 0.588081562 0.185963368
[91] -0.177460566 0.282340442 0.149427151 -0.141479516 -0.189123210
[96] 0.188098136 -0.125394453 -0.398540953 -0.196734783 0.124613310
[101] 0.212413939 0.005183642 0.147315615 -0.011033885 -0.432802756
[106] 0.340237524 0.120663161 -0.812879533 -0.149111664 0.342697187
[111] -0.109443313 0.391712755 -0.356731957 0.468333468 -0.136438078
[116] -0.052092691 -0.321961709 -0.548921049 0.460970844 -0.003988234
[121] 0.347323506 0.186803178 0.406238827 -0.188668515 -0.327034751
[126] -0.114020710 -0.501698646 0.381633528 -0.120909006 0.359565167
[131] 0.018707082 -0.135837063 -0.560033933 -0.600404697 -0.373428073
[136] 0.096676102 0.499126648 0.186047192 0.091916354 0.048445446
[141] 0.308656931 -0.021552429 0.006472402 -0.037316620 0.324468829
[146] -0.125627915 -0.107550478 -0.888794951 0.051398171 -0.445486189
[151] -0.209863495 -0.093398762 -0.197377888 0.147149090 0.064082808
[156] -0.391627475 0.232835740 -0.592443956 0.779148049 -0.581302245
[161] -0.068029083 -0.231256061 -0.112615299 0.514256222 -0.478199027
[166] -0.107844045 -0.047434282 0.011355040 -0.571582938 -0.311701532
[171] -0.162947869 -0.078669567 0.477900210 -0.071458995 0.233739075
[176] 0.265902134 0.461737543 -0.072496287 -0.126253104 0.082406648
[181] -0.065834976 0.374227323 -0.016241026 0.461749285 -0.155650480
[186] 0.213878898 -0.181563711 0.416568185 -0.318311479 0.147243709
[191] -0.142216138 -0.328393634 -0.258312397 -0.238760331 -0.241930379
[196] 0.223228980 -0.132057141 0.253838064 -0.281331516 -0.293886030
[201] -0.380437570 -0.105356314 0.335579914 0.084053057 -0.287125041
[206] -0.149394482 -0.275104362 0.074835622 0.112232441 -0.126860688
[211] -0.136870146 -0.354276820 -0.459104415 0.163596627 -0.262082684
[216] 0.052254379 0.334951004 -0.043713131 0.261562237 -0.300762791
[221] -0.353695392 -0.190651736 0.289776657 0.213847311 0.339153130
[226] -0.187163901 0.235868312 0.339973675 -0.093105759 -0.267799278
>
> proc.time()
user system elapsed
0.807 6.462 7.904
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There"
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: 0x105548da0>
> .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: 0x105548da0>
> .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: 0x105548da0>
> .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: 0x105548da0>
> 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: 0xa733b0060>
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b0060>
> .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: 0xa733b0060>
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b0060>
> .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: 0xa733b0060>
> 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: 0xa733b0360>
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b0360>
> .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: 0xa733b0360>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xa733b0360>
> .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: 0xa733b0360>
>
> .Call("R_bm_RowMode",P)
<pointer: 0xa733b0360>
> .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: 0xa733b0360>
>
> .Call("R_bm_ColMode",P)
<pointer: 0xa733b0360>
> .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: 0xa733b0360>
> 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: 0xa733b0480>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xa733b0480>
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b0480>
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b0480>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3b7b10ef9c97" "BufferedMatrixFile3b7b63118630"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3b7b10ef9c97" "BufferedMatrixFile3b7b63118630"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b05a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b05a0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xa733b05a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xa733b05a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xa733b05a0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xa733b05a0>
> .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: 0xa733b0720>
> .Call("R_bm_AddColumn",P)
<pointer: 0xa733b0720>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xa733b0720>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xa733b0720>
> 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: 0xa733b0840>
> .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: 0xa733b0840>
> rm(P)
>
> proc.time()
user system elapsed
0.118 0.047 0.160
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 Patched (2026-05-01 r89994) -- "Because it was There"
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.
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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
0.131 0.038 0.169