Ben Bolstad
| Snapshot Date: 2026-01-07 13:40 -0500 (Wed, 07 Jan 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-01-08 11:35 -0500 (Thu, 08 Jan 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-12-22 r89219) -- "Unsuffered Consequences" | 4815 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4593 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 253/2332 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.75.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.75.0.tar.gz |
| StartedAt: 2026-01-07 18:49:04 -0500 (Wed, 07 Jan 2026) |
| EndedAt: 2026-01-07 18:49:24 -0500 (Wed, 07 Jan 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 Under development (unstable) (2025-11-04 r88984)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 16.0.0 (clang-1600.0.26.6)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.8
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.75.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.1.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 1 NOTE
See
‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.1.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.6-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.155 0.073 0.235
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 481248 25.8 1058085 56.6 NA 633817 33.9
Vcells 891449 6.9 8388608 64.0 196608 2110969 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] "Wed Jan 7 18:49:15 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] "Wed Jan 7 18:49:16 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: 0x600002e90000>
>
>
>
> 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] "Wed Jan 7 18:49:17 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] "Wed Jan 7 18:49:17 2026"
>
> ColMode(tmp2)
<pointer: 0x600002e90000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.3593436 -1.3761170 1.6679829 0.8816781
[2,] 0.9341515 0.7844463 -1.9126308 -0.2204385
[3,] -2.1718210 -1.0302596 -0.2365890 0.5310853
[4,] 1.2984276 -1.0960463 0.7508826 0.8153896
> 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,] 100.3593436 1.3761170 1.6679829 0.8816781
[2,] 0.9341515 0.7844463 1.9126308 0.2204385
[3,] 2.1718210 1.0302596 0.2365890 0.5310853
[4,] 1.2984276 1.0960463 0.7508826 0.8153896
> 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,] 10.0179511 1.1730801 1.2915041 0.9389772
[2,] 0.9665152 0.8856897 1.3829790 0.4695088
[3,] 1.4737100 1.0150171 0.4864041 0.7287560
[4,] 1.1394857 1.0469223 0.8665348 0.9029893
>
> 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,] 225.53885 38.10692 39.58302 35.27145
[2,] 35.59930 34.64134 40.74242 29.91553
[3,] 41.90892 36.18043 30.10063 32.81865
[4,] 37.69328 36.56527 34.41623 34.84528
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002e98000>
> exp(tmp5)
<pointer: 0x600002e98000>
> log(tmp5,2)
<pointer: 0x600002e98000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.4296
> Min(tmp5)
[1] 53.18326
> mean(tmp5)
[1] 72.6406
> Sum(tmp5)
[1] 14528.12
> Var(tmp5)
[1] 868.045
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.12860 70.94399 72.43183 73.95953 71.97815 69.08023 68.29405 71.34936
[9] 67.35081 68.88940
> rowSums(tmp5)
[1] 1842.572 1418.880 1448.637 1479.191 1439.563 1381.605 1365.881 1426.987
[9] 1347.016 1377.788
> rowVars(tmp5)
[1] 7957.49767 51.20142 78.60629 44.40479 76.06598 49.60818
[7] 45.39809 97.88944 100.26339 106.30245
> rowSd(tmp5)
[1] 89.204807 7.155517 8.866019 6.663692 8.721581 7.043308 6.737810
[8] 9.893909 10.013161 10.310308
> rowMax(tmp5)
[1] 469.42958 84.80001 87.22793 88.58359 91.48316 86.63791 78.32125
[8] 92.51996 85.18119 95.34513
> rowMin(tmp5)
[1] 53.41854 58.75639 55.07161 60.92050 56.87099 57.33839 53.30318 53.18326
[9] 53.89868 55.68043
>
> colMeans(tmp5)
[1] 112.76208 72.96456 68.32164 73.58344 71.71319 71.31940 68.97964
[8] 69.94723 68.10075 70.03725 71.03913 71.61814 69.60306 67.42588
[15] 70.68050 69.88781 74.65841 70.14784 67.35843 72.66353
> colSums(tmp5)
[1] 1127.6208 729.6456 683.2164 735.8344 717.1319 713.1940 689.7964
[8] 699.4723 681.0075 700.3725 710.3913 716.1814 696.0306 674.2588
[15] 706.8050 698.8781 746.5841 701.4784 673.5843 726.6353
> colVars(tmp5)
[1] 15755.45737 56.94739 90.60483 116.78218 61.27944 26.69262
[7] 38.53233 52.44981 34.83734 74.84358 33.98232 119.35900
[13] 26.51609 113.94986 84.30331 112.76135 88.83568 145.47022
[19] 103.25697 90.28035
> colSd(tmp5)
[1] 125.520745 7.546349 9.518657 10.806580 7.828119 5.166490
[7] 6.207442 7.242224 5.902316 8.651218 5.829436 10.925154
[13] 5.149377 10.674730 9.181683 10.618915 9.425268 12.061104
[19] 10.161544 9.501597
> colMax(tmp5)
[1] 469.42958 79.31456 84.80001 91.48316 83.41866 76.63487 81.90749
[8] 82.96260 75.22388 80.27809 77.73321 95.34513 76.20257 88.95884
[15] 85.18119 92.51996 88.58359 89.80828 87.05715 83.66315
> colMin(tmp5)
[1] 63.08520 53.89868 55.00895 55.68043 55.07161 61.34118 60.23085 60.42780
[9] 58.75639 54.03257 61.90725 57.33839 58.61968 55.09173 59.35333 53.41854
[17] 57.52260 55.86391 53.30318 53.18326
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 92.12860 70.94399 NA 73.95953 71.97815 69.08023 68.29405 71.34936
[9] 67.35081 68.88940
> rowSums(tmp5)
[1] 1842.572 1418.880 NA 1479.191 1439.563 1381.605 1365.881 1426.987
[9] 1347.016 1377.788
> rowVars(tmp5)
[1] 7957.49767 51.20142 77.42230 44.40479 76.06598 49.60818
[7] 45.39809 97.88944 100.26339 106.30245
> rowSd(tmp5)
[1] 89.204807 7.155517 8.798994 6.663692 8.721581 7.043308 6.737810
[8] 9.893909 10.013161 10.310308
> rowMax(tmp5)
[1] 469.42958 84.80001 NA 88.58359 91.48316 86.63791 78.32125
[8] 92.51996 85.18119 95.34513
> rowMin(tmp5)
[1] 53.41854 58.75639 NA 60.92050 56.87099 57.33839 53.30318 53.18326
[9] 53.89868 55.68043
>
> colMeans(tmp5)
[1] 112.76208 72.96456 68.32164 73.58344 71.71319 71.31940 68.97964
[8] 69.94723 68.10075 70.03725 71.03913 71.61814 69.60306 67.42588
[15] 70.68050 69.88781 74.65841 NA 67.35843 72.66353
> colSums(tmp5)
[1] 1127.6208 729.6456 683.2164 735.8344 717.1319 713.1940 689.7964
[8] 699.4723 681.0075 700.3725 710.3913 716.1814 696.0306 674.2588
[15] 706.8050 698.8781 746.5841 NA 673.5843 726.6353
> colVars(tmp5)
[1] 15755.45737 56.94739 90.60483 116.78218 61.27944 26.69262
[7] 38.53233 52.44981 34.83734 74.84358 33.98232 119.35900
[13] 26.51609 113.94986 84.30331 112.76135 88.83568 NA
[19] 103.25697 90.28035
> colSd(tmp5)
[1] 125.520745 7.546349 9.518657 10.806580 7.828119 5.166490
[7] 6.207442 7.242224 5.902316 8.651218 5.829436 10.925154
[13] 5.149377 10.674730 9.181683 10.618915 9.425268 NA
[19] 10.161544 9.501597
> colMax(tmp5)
[1] 469.42958 79.31456 84.80001 91.48316 83.41866 76.63487 81.90749
[8] 82.96260 75.22388 80.27809 77.73321 95.34513 76.20257 88.95884
[15] 85.18119 92.51996 88.58359 NA 87.05715 83.66315
> colMin(tmp5)
[1] 63.08520 53.89868 55.00895 55.68043 55.07161 61.34118 60.23085 60.42780
[9] 58.75639 54.03257 61.90725 57.33839 58.61968 55.09173 59.35333 53.41854
[17] 57.52260 NA 53.30318 53.18326
>
> Max(tmp5,na.rm=TRUE)
[1] 469.4296
> Min(tmp5,na.rm=TRUE)
[1] 53.18326
> mean(tmp5,na.rm=TRUE)
[1] 72.59269
> Sum(tmp5,na.rm=TRUE)
[1] 14445.94
> Var(tmp5,na.rm=TRUE)
[1] 871.9677
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.12860 70.94399 71.91906 73.95953 71.97815 69.08023 68.29405 71.34936
[9] 67.35081 68.88940
> rowSums(tmp5,na.rm=TRUE)
[1] 1842.572 1418.880 1366.462 1479.191 1439.563 1381.605 1365.881 1426.987
[9] 1347.016 1377.788
> rowVars(tmp5,na.rm=TRUE)
[1] 7957.49767 51.20142 77.42230 44.40479 76.06598 49.60818
[7] 45.39809 97.88944 100.26339 106.30245
> rowSd(tmp5,na.rm=TRUE)
[1] 89.204807 7.155517 8.798994 6.663692 8.721581 7.043308 6.737810
[8] 9.893909 10.013161 10.310308
> rowMax(tmp5,na.rm=TRUE)
[1] 469.42958 84.80001 87.22793 88.58359 91.48316 86.63791 78.32125
[8] 92.51996 85.18119 95.34513
> rowMin(tmp5,na.rm=TRUE)
[1] 53.41854 58.75639 55.07161 60.92050 56.87099 57.33839 53.30318 53.18326
[9] 53.89868 55.68043
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.76208 72.96456 68.32164 73.58344 71.71319 71.31940 68.97964
[8] 69.94723 68.10075 70.03725 71.03913 71.61814 69.60306 67.42588
[15] 70.68050 69.88781 74.65841 68.81152 67.35843 72.66353
> colSums(tmp5,na.rm=TRUE)
[1] 1127.6208 729.6456 683.2164 735.8344 717.1319 713.1940 689.7964
[8] 699.4723 681.0075 700.3725 710.3913 716.1814 696.0306 674.2588
[15] 706.8050 698.8781 746.5841 619.3037 673.5843 726.6353
> colVars(tmp5,na.rm=TRUE)
[1] 15755.45737 56.94739 90.60483 116.78218 61.27944 26.69262
[7] 38.53233 52.44981 34.83734 74.84358 33.98232 119.35900
[13] 26.51609 113.94986 84.30331 112.76135 88.83568 143.56455
[19] 103.25697 90.28035
> colSd(tmp5,na.rm=TRUE)
[1] 125.520745 7.546349 9.518657 10.806580 7.828119 5.166490
[7] 6.207442 7.242224 5.902316 8.651218 5.829436 10.925154
[13] 5.149377 10.674730 9.181683 10.618915 9.425268 11.981843
[19] 10.161544 9.501597
> colMax(tmp5,na.rm=TRUE)
[1] 469.42958 79.31456 84.80001 91.48316 83.41866 76.63487 81.90749
[8] 82.96260 75.22388 80.27809 77.73321 95.34513 76.20257 88.95884
[15] 85.18119 92.51996 88.58359 89.80828 87.05715 83.66315
> colMin(tmp5,na.rm=TRUE)
[1] 63.08520 53.89868 55.00895 55.68043 55.07161 61.34118 60.23085 60.42780
[9] 58.75639 54.03257 61.90725 57.33839 58.61968 55.09173 59.35333 53.41854
[17] 57.52260 55.86391 53.30318 53.18326
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.12860 70.94399 NaN 73.95953 71.97815 69.08023 68.29405 71.34936
[9] 67.35081 68.88940
> rowSums(tmp5,na.rm=TRUE)
[1] 1842.572 1418.880 0.000 1479.191 1439.563 1381.605 1365.881 1426.987
[9] 1347.016 1377.788
> rowVars(tmp5,na.rm=TRUE)
[1] 7957.49767 51.20142 NA 44.40479 76.06598 49.60818
[7] 45.39809 97.88944 100.26339 106.30245
> rowSd(tmp5,na.rm=TRUE)
[1] 89.204807 7.155517 NA 6.663692 8.721581 7.043308 6.737810
[8] 9.893909 10.013161 10.310308
> rowMax(tmp5,na.rm=TRUE)
[1] 469.42958 84.80001 NA 88.58359 91.48316 86.63791 78.32125
[8] 92.51996 85.18119 95.34513
> rowMin(tmp5,na.rm=TRUE)
[1] 53.41854 58.75639 NA 60.92050 56.87099 57.33839 53.30318 53.18326
[9] 53.89868 55.68043
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.59921 72.70453 68.95177 74.16963 73.56225 70.91473 68.87827
[8] 70.23546 67.91836 69.60010 71.05197 71.94012 70.82344 67.42942
[15] 70.24557 69.95589 73.28342 NaN 65.16969 72.03046
> colSums(tmp5,na.rm=TRUE)
[1] 1040.3929 654.3408 620.5659 667.5266 662.0603 638.2326 619.9045
[8] 632.1191 611.2653 626.4009 639.4677 647.4611 637.4109 606.8648
[15] 632.2102 629.6030 659.5508 0.0000 586.5272 648.2742
> colVars(tmp5,na.rm=TRUE)
[1] 17634.33493 63.30514 97.46353 127.51422 30.47520 28.18692
[7] 43.23328 58.07141 38.81777 82.04913 38.22826 133.11253
[13] 13.07579 128.19346 92.71314 126.80437 78.67087 NA
[19] 62.26973 97.05661
> colSd(tmp5,na.rm=TRUE)
[1] 132.794333 7.956453 9.872362 11.292219 5.520435 5.309135
[7] 6.575202 7.620460 6.230391 9.058098 6.182900 11.537440
[13] 3.616046 11.322255 9.628766 11.260745 8.869660 NA
[19] 7.891117 9.851731
> colMax(tmp5,na.rm=TRUE)
[1] 469.42958 79.31456 84.80001 91.48316 83.41866 76.63487 81.90749
[8] 82.96260 75.22388 80.27809 77.73321 95.34513 76.20257 88.95884
[15] 85.18119 92.51996 88.58359 -Inf 76.90141 83.66315
> colMin(tmp5,na.rm=TRUE)
[1] 63.08520 53.89868 55.00895 55.68043 65.39517 61.34118 60.23085 60.42780
[9] 58.75639 54.03257 61.90725 57.33839 64.83953 55.09173 59.35333 53.41854
[17] 57.52260 Inf 53.30318 53.18326
>
>
>
>
> 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] 167.5743 196.1835 275.8086 154.8004 263.3794 222.9463 154.8173 161.5884
[9] 299.3482 272.3892
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 167.5743 196.1835 275.8086 154.8004 263.3794 222.9463 154.8173 161.5884
[9] 299.3482 272.3892
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.136868e-13 0.000000e+00 -1.705303e-13 8.526513e-14 -5.684342e-14
[6] 1.136868e-13 2.842171e-14 1.136868e-13 -1.136868e-13 -2.842171e-14
[11] -2.842171e-14 1.421085e-13 0.000000e+00 0.000000e+00 -1.705303e-13
[16] 8.526513e-14 -2.842171e-14 5.684342e-14 1.421085e-14 -1.421085e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 5
10 17
4 1
9 9
6 5
7 9
9 8
8 10
2 7
2 20
10 4
7 8
2 19
3 12
7 10
5 13
7 18
6 2
6 7
5 10
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 3.112716
> Min(tmp)
[1] -1.91809
> mean(tmp)
[1] 0.04746813
> Sum(tmp)
[1] 4.746813
> Var(tmp)
[1] 0.7712787
>
> rowMeans(tmp)
[1] 0.04746813
> rowSums(tmp)
[1] 4.746813
> rowVars(tmp)
[1] 0.7712787
> rowSd(tmp)
[1] 0.8782247
> rowMax(tmp)
[1] 3.112716
> rowMin(tmp)
[1] -1.91809
>
> colMeans(tmp)
[1] -0.419386608 -0.673077271 0.249066659 0.333312869 -0.236671717
[6] 0.929758694 -0.005377846 1.041439612 -0.232728632 -0.246976380
[11] 0.174494215 0.885951323 -0.235148846 -0.380608867 -0.694719101
[16] 0.892894710 -0.611099431 0.011681443 -0.213201925 0.773836987
[21] 0.093224735 0.060518390 0.146362765 -1.429575103 -0.308438762
[26] -0.081203652 0.527735778 0.312907248 0.607544368 3.112716494
[31] -1.557637198 1.485845163 -0.004712488 0.192264390 0.980770626
[36] 1.175374432 1.274002669 1.321066197 -0.105766628 -1.399845443
[41] -1.345682418 0.603232234 -0.191551892 -0.386702806 0.898762984
[46] -0.321321498 0.383799124 -0.412897997 -1.140774725 0.162930103
[51] -1.504766145 -0.764916805 -0.984198654 0.363767908 0.402661102
[56] 0.647497249 -0.915460582 -0.374321563 -0.090243542 0.042625280
[61] 1.584215063 -0.015079421 2.364924725 0.535322422 -1.360949422
[66] -1.366364551 1.009535357 -1.126224555 -1.918089528 0.107662833
[71] -0.563199151 -1.131207063 0.208170777 -0.153536958 0.529918288
[76] -0.887766152 1.099551816 -1.221053434 -0.629459776 -0.868018313
[81] 0.675562454 0.413552477 -0.629940112 0.590511140 -0.102192610
[86] 1.009837517 0.811231979 0.908716425 -0.476538015 0.719338503
[91] -0.111226737 -0.248554534 0.647218346 0.991752656 -0.718592927
[96] -0.603524104 0.321409469 1.479864413 -0.677741130 0.728744055
> colSums(tmp)
[1] -0.419386608 -0.673077271 0.249066659 0.333312869 -0.236671717
[6] 0.929758694 -0.005377846 1.041439612 -0.232728632 -0.246976380
[11] 0.174494215 0.885951323 -0.235148846 -0.380608867 -0.694719101
[16] 0.892894710 -0.611099431 0.011681443 -0.213201925 0.773836987
[21] 0.093224735 0.060518390 0.146362765 -1.429575103 -0.308438762
[26] -0.081203652 0.527735778 0.312907248 0.607544368 3.112716494
[31] -1.557637198 1.485845163 -0.004712488 0.192264390 0.980770626
[36] 1.175374432 1.274002669 1.321066197 -0.105766628 -1.399845443
[41] -1.345682418 0.603232234 -0.191551892 -0.386702806 0.898762984
[46] -0.321321498 0.383799124 -0.412897997 -1.140774725 0.162930103
[51] -1.504766145 -0.764916805 -0.984198654 0.363767908 0.402661102
[56] 0.647497249 -0.915460582 -0.374321563 -0.090243542 0.042625280
[61] 1.584215063 -0.015079421 2.364924725 0.535322422 -1.360949422
[66] -1.366364551 1.009535357 -1.126224555 -1.918089528 0.107662833
[71] -0.563199151 -1.131207063 0.208170777 -0.153536958 0.529918288
[76] -0.887766152 1.099551816 -1.221053434 -0.629459776 -0.868018313
[81] 0.675562454 0.413552477 -0.629940112 0.590511140 -0.102192610
[86] 1.009837517 0.811231979 0.908716425 -0.476538015 0.719338503
[91] -0.111226737 -0.248554534 0.647218346 0.991752656 -0.718592927
[96] -0.603524104 0.321409469 1.479864413 -0.677741130 0.728744055
> 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] -0.419386608 -0.673077271 0.249066659 0.333312869 -0.236671717
[6] 0.929758694 -0.005377846 1.041439612 -0.232728632 -0.246976380
[11] 0.174494215 0.885951323 -0.235148846 -0.380608867 -0.694719101
[16] 0.892894710 -0.611099431 0.011681443 -0.213201925 0.773836987
[21] 0.093224735 0.060518390 0.146362765 -1.429575103 -0.308438762
[26] -0.081203652 0.527735778 0.312907248 0.607544368 3.112716494
[31] -1.557637198 1.485845163 -0.004712488 0.192264390 0.980770626
[36] 1.175374432 1.274002669 1.321066197 -0.105766628 -1.399845443
[41] -1.345682418 0.603232234 -0.191551892 -0.386702806 0.898762984
[46] -0.321321498 0.383799124 -0.412897997 -1.140774725 0.162930103
[51] -1.504766145 -0.764916805 -0.984198654 0.363767908 0.402661102
[56] 0.647497249 -0.915460582 -0.374321563 -0.090243542 0.042625280
[61] 1.584215063 -0.015079421 2.364924725 0.535322422 -1.360949422
[66] -1.366364551 1.009535357 -1.126224555 -1.918089528 0.107662833
[71] -0.563199151 -1.131207063 0.208170777 -0.153536958 0.529918288
[76] -0.887766152 1.099551816 -1.221053434 -0.629459776 -0.868018313
[81] 0.675562454 0.413552477 -0.629940112 0.590511140 -0.102192610
[86] 1.009837517 0.811231979 0.908716425 -0.476538015 0.719338503
[91] -0.111226737 -0.248554534 0.647218346 0.991752656 -0.718592927
[96] -0.603524104 0.321409469 1.479864413 -0.677741130 0.728744055
> colMin(tmp)
[1] -0.419386608 -0.673077271 0.249066659 0.333312869 -0.236671717
[6] 0.929758694 -0.005377846 1.041439612 -0.232728632 -0.246976380
[11] 0.174494215 0.885951323 -0.235148846 -0.380608867 -0.694719101
[16] 0.892894710 -0.611099431 0.011681443 -0.213201925 0.773836987
[21] 0.093224735 0.060518390 0.146362765 -1.429575103 -0.308438762
[26] -0.081203652 0.527735778 0.312907248 0.607544368 3.112716494
[31] -1.557637198 1.485845163 -0.004712488 0.192264390 0.980770626
[36] 1.175374432 1.274002669 1.321066197 -0.105766628 -1.399845443
[41] -1.345682418 0.603232234 -0.191551892 -0.386702806 0.898762984
[46] -0.321321498 0.383799124 -0.412897997 -1.140774725 0.162930103
[51] -1.504766145 -0.764916805 -0.984198654 0.363767908 0.402661102
[56] 0.647497249 -0.915460582 -0.374321563 -0.090243542 0.042625280
[61] 1.584215063 -0.015079421 2.364924725 0.535322422 -1.360949422
[66] -1.366364551 1.009535357 -1.126224555 -1.918089528 0.107662833
[71] -0.563199151 -1.131207063 0.208170777 -0.153536958 0.529918288
[76] -0.887766152 1.099551816 -1.221053434 -0.629459776 -0.868018313
[81] 0.675562454 0.413552477 -0.629940112 0.590511140 -0.102192610
[86] 1.009837517 0.811231979 0.908716425 -0.476538015 0.719338503
[91] -0.111226737 -0.248554534 0.647218346 0.991752656 -0.718592927
[96] -0.603524104 0.321409469 1.479864413 -0.677741130 0.728744055
> colMedians(tmp)
[1] -0.419386608 -0.673077271 0.249066659 0.333312869 -0.236671717
[6] 0.929758694 -0.005377846 1.041439612 -0.232728632 -0.246976380
[11] 0.174494215 0.885951323 -0.235148846 -0.380608867 -0.694719101
[16] 0.892894710 -0.611099431 0.011681443 -0.213201925 0.773836987
[21] 0.093224735 0.060518390 0.146362765 -1.429575103 -0.308438762
[26] -0.081203652 0.527735778 0.312907248 0.607544368 3.112716494
[31] -1.557637198 1.485845163 -0.004712488 0.192264390 0.980770626
[36] 1.175374432 1.274002669 1.321066197 -0.105766628 -1.399845443
[41] -1.345682418 0.603232234 -0.191551892 -0.386702806 0.898762984
[46] -0.321321498 0.383799124 -0.412897997 -1.140774725 0.162930103
[51] -1.504766145 -0.764916805 -0.984198654 0.363767908 0.402661102
[56] 0.647497249 -0.915460582 -0.374321563 -0.090243542 0.042625280
[61] 1.584215063 -0.015079421 2.364924725 0.535322422 -1.360949422
[66] -1.366364551 1.009535357 -1.126224555 -1.918089528 0.107662833
[71] -0.563199151 -1.131207063 0.208170777 -0.153536958 0.529918288
[76] -0.887766152 1.099551816 -1.221053434 -0.629459776 -0.868018313
[81] 0.675562454 0.413552477 -0.629940112 0.590511140 -0.102192610
[86] 1.009837517 0.811231979 0.908716425 -0.476538015 0.719338503
[91] -0.111226737 -0.248554534 0.647218346 0.991752656 -0.718592927
[96] -0.603524104 0.321409469 1.479864413 -0.677741130 0.728744055
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.4193866 -0.6730773 0.2490667 0.3333129 -0.2366717 0.9297587
[2,] -0.4193866 -0.6730773 0.2490667 0.3333129 -0.2366717 0.9297587
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.005377846 1.04144 -0.2327286 -0.2469764 0.1744942 0.8859513 -0.2351488
[2,] -0.005377846 1.04144 -0.2327286 -0.2469764 0.1744942 0.8859513 -0.2351488
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.3806089 -0.6947191 0.8928947 -0.6110994 0.01168144 -0.2132019 0.773837
[2,] -0.3806089 -0.6947191 0.8928947 -0.6110994 0.01168144 -0.2132019 0.773837
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] 0.09322473 0.06051839 0.1463628 -1.429575 -0.3084388 -0.08120365 0.5277358
[2,] 0.09322473 0.06051839 0.1463628 -1.429575 -0.3084388 -0.08120365 0.5277358
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.3129072 0.6075444 3.112716 -1.557637 1.485845 -0.004712488 0.1922644
[2,] 0.3129072 0.6075444 3.112716 -1.557637 1.485845 -0.004712488 0.1922644
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.9807706 1.175374 1.274003 1.321066 -0.1057666 -1.399845 -1.345682
[2,] 0.9807706 1.175374 1.274003 1.321066 -0.1057666 -1.399845 -1.345682
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.6032322 -0.1915519 -0.3867028 0.898763 -0.3213215 0.3837991 -0.412898
[2,] 0.6032322 -0.1915519 -0.3867028 0.898763 -0.3213215 0.3837991 -0.412898
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -1.140775 0.1629301 -1.504766 -0.7649168 -0.9841987 0.3637679 0.4026611
[2,] -1.140775 0.1629301 -1.504766 -0.7649168 -0.9841987 0.3637679 0.4026611
[,56] [,57] [,58] [,59] [,60] [,61]
[1,] 0.6474972 -0.9154606 -0.3743216 -0.09024354 0.04262528 1.584215
[2,] 0.6474972 -0.9154606 -0.3743216 -0.09024354 0.04262528 1.584215
[,62] [,63] [,64] [,65] [,66] [,67] [,68]
[1,] -0.01507942 2.364925 0.5353224 -1.360949 -1.366365 1.009535 -1.126225
[2,] -0.01507942 2.364925 0.5353224 -1.360949 -1.366365 1.009535 -1.126225
[,69] [,70] [,71] [,72] [,73] [,74] [,75]
[1,] -1.91809 0.1076628 -0.5631992 -1.131207 0.2081708 -0.153537 0.5299183
[2,] -1.91809 0.1076628 -0.5631992 -1.131207 0.2081708 -0.153537 0.5299183
[,76] [,77] [,78] [,79] [,80] [,81] [,82]
[1,] -0.8877662 1.099552 -1.221053 -0.6294598 -0.8680183 0.6755625 0.4135525
[2,] -0.8877662 1.099552 -1.221053 -0.6294598 -0.8680183 0.6755625 0.4135525
[,83] [,84] [,85] [,86] [,87] [,88] [,89]
[1,] -0.6299401 0.5905111 -0.1021926 1.009838 0.811232 0.9087164 -0.476538
[2,] -0.6299401 0.5905111 -0.1021926 1.009838 0.811232 0.9087164 -0.476538
[,90] [,91] [,92] [,93] [,94] [,95] [,96]
[1,] 0.7193385 -0.1112267 -0.2485545 0.6472183 0.9917527 -0.7185929 -0.6035241
[2,] 0.7193385 -0.1112267 -0.2485545 0.6472183 0.9917527 -0.7185929 -0.6035241
[,97] [,98] [,99] [,100]
[1,] 0.3214095 1.479864 -0.6777411 0.7287441
[2,] 0.3214095 1.479864 -0.6777411 0.7287441
>
>
> Max(tmp2)
[1] 2.994206
> Min(tmp2)
[1] -2.44862
> mean(tmp2)
[1] -0.0157614
> Sum(tmp2)
[1] -1.57614
> Var(tmp2)
[1] 0.9611236
>
> rowMeans(tmp2)
[1] 0.46425824 -1.66960596 -0.90016659 0.51404099 -0.96040438 -0.06758088
[7] -0.73645913 -1.56345462 -1.12041552 0.84530892 -1.79415984 1.06991928
[13] -0.17264274 0.14837511 0.32689342 -2.05759932 0.20250197 0.25440707
[19] 0.57750467 -0.61013119 0.85954573 -0.81017656 -0.39221786 0.49794666
[25] 0.59639726 0.34517255 1.18624880 -0.39445771 0.09403164 -0.21423136
[31] -2.02512318 -0.50151569 -0.45212731 -0.94786713 1.77180261 -0.36211225
[37] -1.64481212 0.76370813 -2.44862023 -0.93361157 2.99420572 -0.11156121
[43] -0.51064344 -0.15287234 1.68261721 0.81971961 -0.19414420 -0.20708146
[49] 0.51633361 0.14561310 -0.28546809 -0.57416393 0.23037831 -0.27335338
[55] -0.61156600 0.98353194 -0.31260849 -0.19232393 0.51719125 0.90774236
[61] 0.53417188 0.64218951 -1.26972505 0.11623948 0.05605137 1.71997406
[67] -0.06850029 0.18430795 -0.40812000 1.45318022 0.34309321 1.42103829
[73] 0.09480086 0.89503588 1.06392224 -1.08242638 0.63047301 -1.63588268
[79] 1.58023520 -0.41535995 0.59705881 0.10356277 -0.75116651 0.14043657
[85] -0.93070923 -1.10121213 -1.32885870 -1.15561886 1.48370152 -0.78131734
[91] 0.08820226 1.24447473 0.07110830 -0.95082041 -0.93280023 0.97680641
[97] 0.10986784 -0.01936544 0.45350120 2.14219331
> rowSums(tmp2)
[1] 0.46425824 -1.66960596 -0.90016659 0.51404099 -0.96040438 -0.06758088
[7] -0.73645913 -1.56345462 -1.12041552 0.84530892 -1.79415984 1.06991928
[13] -0.17264274 0.14837511 0.32689342 -2.05759932 0.20250197 0.25440707
[19] 0.57750467 -0.61013119 0.85954573 -0.81017656 -0.39221786 0.49794666
[25] 0.59639726 0.34517255 1.18624880 -0.39445771 0.09403164 -0.21423136
[31] -2.02512318 -0.50151569 -0.45212731 -0.94786713 1.77180261 -0.36211225
[37] -1.64481212 0.76370813 -2.44862023 -0.93361157 2.99420572 -0.11156121
[43] -0.51064344 -0.15287234 1.68261721 0.81971961 -0.19414420 -0.20708146
[49] 0.51633361 0.14561310 -0.28546809 -0.57416393 0.23037831 -0.27335338
[55] -0.61156600 0.98353194 -0.31260849 -0.19232393 0.51719125 0.90774236
[61] 0.53417188 0.64218951 -1.26972505 0.11623948 0.05605137 1.71997406
[67] -0.06850029 0.18430795 -0.40812000 1.45318022 0.34309321 1.42103829
[73] 0.09480086 0.89503588 1.06392224 -1.08242638 0.63047301 -1.63588268
[79] 1.58023520 -0.41535995 0.59705881 0.10356277 -0.75116651 0.14043657
[85] -0.93070923 -1.10121213 -1.32885870 -1.15561886 1.48370152 -0.78131734
[91] 0.08820226 1.24447473 0.07110830 -0.95082041 -0.93280023 0.97680641
[97] 0.10986784 -0.01936544 0.45350120 2.14219331
> 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] 0.46425824 -1.66960596 -0.90016659 0.51404099 -0.96040438 -0.06758088
[7] -0.73645913 -1.56345462 -1.12041552 0.84530892 -1.79415984 1.06991928
[13] -0.17264274 0.14837511 0.32689342 -2.05759932 0.20250197 0.25440707
[19] 0.57750467 -0.61013119 0.85954573 -0.81017656 -0.39221786 0.49794666
[25] 0.59639726 0.34517255 1.18624880 -0.39445771 0.09403164 -0.21423136
[31] -2.02512318 -0.50151569 -0.45212731 -0.94786713 1.77180261 -0.36211225
[37] -1.64481212 0.76370813 -2.44862023 -0.93361157 2.99420572 -0.11156121
[43] -0.51064344 -0.15287234 1.68261721 0.81971961 -0.19414420 -0.20708146
[49] 0.51633361 0.14561310 -0.28546809 -0.57416393 0.23037831 -0.27335338
[55] -0.61156600 0.98353194 -0.31260849 -0.19232393 0.51719125 0.90774236
[61] 0.53417188 0.64218951 -1.26972505 0.11623948 0.05605137 1.71997406
[67] -0.06850029 0.18430795 -0.40812000 1.45318022 0.34309321 1.42103829
[73] 0.09480086 0.89503588 1.06392224 -1.08242638 0.63047301 -1.63588268
[79] 1.58023520 -0.41535995 0.59705881 0.10356277 -0.75116651 0.14043657
[85] -0.93070923 -1.10121213 -1.32885870 -1.15561886 1.48370152 -0.78131734
[91] 0.08820226 1.24447473 0.07110830 -0.95082041 -0.93280023 0.97680641
[97] 0.10986784 -0.01936544 0.45350120 2.14219331
> rowMin(tmp2)
[1] 0.46425824 -1.66960596 -0.90016659 0.51404099 -0.96040438 -0.06758088
[7] -0.73645913 -1.56345462 -1.12041552 0.84530892 -1.79415984 1.06991928
[13] -0.17264274 0.14837511 0.32689342 -2.05759932 0.20250197 0.25440707
[19] 0.57750467 -0.61013119 0.85954573 -0.81017656 -0.39221786 0.49794666
[25] 0.59639726 0.34517255 1.18624880 -0.39445771 0.09403164 -0.21423136
[31] -2.02512318 -0.50151569 -0.45212731 -0.94786713 1.77180261 -0.36211225
[37] -1.64481212 0.76370813 -2.44862023 -0.93361157 2.99420572 -0.11156121
[43] -0.51064344 -0.15287234 1.68261721 0.81971961 -0.19414420 -0.20708146
[49] 0.51633361 0.14561310 -0.28546809 -0.57416393 0.23037831 -0.27335338
[55] -0.61156600 0.98353194 -0.31260849 -0.19232393 0.51719125 0.90774236
[61] 0.53417188 0.64218951 -1.26972505 0.11623948 0.05605137 1.71997406
[67] -0.06850029 0.18430795 -0.40812000 1.45318022 0.34309321 1.42103829
[73] 0.09480086 0.89503588 1.06392224 -1.08242638 0.63047301 -1.63588268
[79] 1.58023520 -0.41535995 0.59705881 0.10356277 -0.75116651 0.14043657
[85] -0.93070923 -1.10121213 -1.32885870 -1.15561886 1.48370152 -0.78131734
[91] 0.08820226 1.24447473 0.07110830 -0.95082041 -0.93280023 0.97680641
[97] 0.10986784 -0.01936544 0.45350120 2.14219331
>
> colMeans(tmp2)
[1] -0.0157614
> colSums(tmp2)
[1] -1.57614
> colVars(tmp2)
[1] 0.9611236
> colSd(tmp2)
[1] 0.9803691
> colMax(tmp2)
[1] 2.994206
> colMin(tmp2)
[1] -2.44862
> colMedians(tmp2)
[1] 0.06357984
> colRanges(tmp2)
[,1]
[1,] -2.448620
[2,] 2.994206
>
> 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] 4.0525536 4.2581505 -2.8467122 -2.4315310 -0.9516816 -4.9201508
[7] 3.9797209 0.1615821 -1.0658998 4.1166717
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9351995
[2,] -0.5115128
[3,] -0.0885505
[4,] 1.5988033
[5,] 2.3006302
>
> rowApply(tmp,sum)
[1] 2.3751439 -1.5035584 -2.9928514 2.8868807 -1.2586238 3.7847802
[7] -0.4025844 1.6657651 -4.0664974 3.8642490
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 3 5 9 2 10 8 5 6 1
[2,] 8 1 8 10 6 7 6 8 8 6
[3,] 4 2 9 3 4 1 2 7 9 8
[4,] 3 5 4 5 8 3 10 1 5 3
[5,] 5 8 1 6 9 8 5 6 2 4
[6,] 2 9 6 7 1 4 1 2 3 10
[7,] 9 10 2 2 7 6 4 4 10 7
[8,] 1 4 3 8 5 5 9 9 7 2
[9,] 6 6 10 1 3 9 3 3 4 5
[10,] 7 7 7 4 10 2 7 10 1 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.5863079 -0.8862900 -0.4245005 4.1339320 -0.2296726 -0.3814093
[7] 0.9898341 -3.4504543 -5.1693488 -2.4846095 0.2143880 3.3234594
[13] -0.6395301 -4.3621632 4.3125419 -2.4709315 -6.5040437 0.9232659
[19] -5.3967289 -0.9175147
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.3141004
[2,] -0.7681949
[3,] -0.3182695
[4,] 0.8815573
[5,] 0.9326997
>
> rowApply(tmp,sum)
[1] -4.067143 -4.345059 -4.926806 -1.836974 -5.830102
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 10 1 20 10
[2,] 12 17 8 13 1
[3,] 8 15 15 1 18
[4,] 14 8 20 7 20
[5,] 9 16 7 9 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.8815573 0.4909023 -0.2024160 0.6032864 0.003609861 0.50108078
[2,] -0.3182695 0.4047023 0.1082110 -0.3777574 0.282918379 -0.87380702
[3,] -2.3141004 -0.5796874 0.2352002 2.5113004 -0.889564127 0.97064421
[4,] 0.9326997 0.1668005 -1.6737740 -0.2591709 -0.115344385 0.09653279
[5,] -0.7681949 -1.3690076 1.1082782 1.6562735 0.488707720 -1.07586008
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.7624942 -1.4260667 -1.3210800 -2.13615132 0.2514364 0.19983541
[2,] -0.8317021 0.1028765 -1.6343794 -0.02280782 -0.4108005 0.87821950
[3,] 0.9097216 -0.1855413 -1.6160105 -1.84193069 0.8180441 1.93027803
[4,] 0.8396572 -0.9384438 -1.1742616 0.47187410 0.1311498 0.33226616
[5,] -0.6903368 -1.0032790 0.5763826 1.04440619 -0.5754418 -0.01713969
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.7507552 -2.40530005 1.0010216 -1.1290397 -1.8259786 0.616317822
[2,] -0.3366012 -0.02385648 1.4132825 0.5174713 -1.6479367 -0.091895200
[3,] -0.3646775 -0.18396446 0.1090364 -0.1380275 -1.5688358 -0.006333373
[4,] 0.1024776 -0.86098693 0.5647283 -0.5012891 -0.1758532 0.444589563
[5,] -0.7914842 -0.88805532 1.2244731 -1.2200465 -1.2854394 -0.039412910
[,19] [,20]
[1,] -1.4473510 1.7639433
[2,] -0.8852049 -0.5977227
[3,] -1.3043040 -1.4180538
[4,] -0.5059370 0.2853111
[5,] -1.2539320 -0.9509926
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.167041 -0.6902885 -0.5301962 -1.921051 0.3492929 -2.268728 0.3121827
col8 col9 col10 col11 col12 col13 col14
row1 -1.070202 0.274961 -0.8322822 -0.8939847 0.1277054 0.8247562 -1.112059
col15 col16 col17 col18 col19 col20
row1 0.7208868 0.559267 -0.4231276 1.298376 0.5780171 -0.8252026
> tmp[,"col10"]
col10
row1 -0.8322822
row2 -0.5893980
row3 -0.2411947
row4 1.8466811
row5 -1.2184154
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.1670413 -0.6902885 -0.5301962 -1.921051 0.3492929 -2.268728 0.3121827
row5 -0.5336596 0.3940868 -0.2801690 -1.018746 1.1587412 1.795933 0.2628709
col8 col9 col10 col11 col12 col13 col14
row1 -1.070202 0.274961 -0.8322822 -0.8939847 0.1277054 0.8247562 -1.1120591
row5 -1.187629 1.900578 -1.2184154 0.3445745 -1.4972366 -1.2274944 0.8335311
col15 col16 col17 col18 col19 col20
row1 0.7208868 0.5592670 -0.4231276 1.2983759 0.5780171 -0.82520260
row5 -1.0350192 0.9387159 0.2991769 0.1458926 1.7445135 0.02744608
> tmp[,c("col6","col20")]
col6 col20
row1 -2.2687276 -0.82520260
row2 0.6534005 0.04628892
row3 -0.5014031 1.37330823
row4 0.3369121 -0.51793213
row5 1.7959326 0.02744608
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -2.268728 -0.82520260
row5 1.795933 0.02744608
>
>
>
>
> 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 50.4366 51.71228 49.37892 49.18033 50.23693 105.7913 49.4104 49.17685
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.6196 51.04778 49.74 50.78993 48.37822 50.08359 50.39369 50.36799
col17 col18 col19 col20
row1 49.8007 49.0753 52.03367 105.2471
> tmp[,"col10"]
col10
row1 51.04778
row2 29.62348
row3 30.03107
row4 29.10928
row5 49.28656
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.43660 51.71228 49.37892 49.18033 50.23693 105.7913 49.41040 49.17685
row5 49.12829 49.67230 49.38323 50.95609 50.57866 105.0451 51.22984 49.98228
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.61960 51.04778 49.74000 50.78993 48.37822 50.08359 50.39369 50.36799
row5 49.23161 49.28656 50.79214 51.18707 50.30468 50.22755 50.33887 50.55131
col17 col18 col19 col20
row1 49.80070 49.0753 52.03367 105.2471
row5 52.07221 51.1470 51.24019 104.4702
> tmp[,c("col6","col20")]
col6 col20
row1 105.79127 105.24710
row2 74.45500 75.57991
row3 76.82587 76.00777
row4 76.33889 75.78345
row5 105.04511 104.47023
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7913 105.2471
row5 105.0451 104.4702
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7913 105.2471
row5 105.0451 104.4702
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.6571361
[2,] -0.2652843
[3,] 0.3112512
[4,] -1.4101300
[5,] -0.8659312
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.3714568 0.2243535
[2,] -0.3979001 0.6888414
[3,] 1.4235185 -2.4606734
[4,] 0.5535477 2.2824876
[5,] -1.5339804 0.2378449
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.4154025 -0.9206147
[2,] 0.7351691 -1.0730721
[3,] 1.9976208 -1.8060380
[4,] -0.3780141 1.1825117
[5,] -0.5700163 1.0554241
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.415403
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.4154025
[2,] 0.7351691
>
>
>
> 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 -0.9499588 -0.3605967 0.6779035 0.5390297 1.001572 -1.1941613 -1.9493179
row1 0.6875322 0.3720899 0.4371947 0.8363792 -1.366613 0.8233288 -0.8215828
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -2.6130065 0.7235864 -0.168389 -1.3096811 1.1909609 -0.01668242
row1 -0.1936438 -0.6203154 -1.404558 0.1977175 -0.8150897 -1.53784479
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.2622215 -1.4225804 1.639833 0.7053548 1.2016325 -1.36006771
row1 -2.1519439 -0.7853145 -2.165494 -0.8364827 -0.8302545 -0.07098871
[,20]
row3 0.3984234
row1 2.4258705
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.111408 -1.906762 0.3677831 -0.3588373 -1.04512 0.1382464 -0.1775001
[,8] [,9] [,10]
row2 -1.414601 1.881511 -2.700613
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.053546 -0.6462496 -0.5835719 1.08803 -0.2268484 0.2940271 1.665907
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.200005 -1.682119 -1.559946 0.6985309 -0.5521284 -1.01735 -0.4722719
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -2.132203 -0.5916064 0.325255 -1.142109 -0.2891038 0.9575643
>
>
> 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: 0x600002e981e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f406e850770"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f405fab82bf"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f407514faaa"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f403454eaf3"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f40330d125c"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f401f307033"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f4025163444"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f4054c16f61"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f40677774bf"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f405391dcaa"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f40d2e47c3"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f40596959f7"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f40139194fd"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f403acc7814"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM16f4045df8734"
>
>
> ### 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: 0x600002ef84e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002ef84e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002ef84e0>
> rowMedians(tmp)
[1] 0.105875432 -0.318199641 -0.481378684 0.348205749 0.232304011
[6] -0.478772128 0.070589506 0.037842770 -0.455442172 0.368666604
[11] -0.161061525 -0.374048053 0.239238796 -0.189565380 0.333964909
[16] -0.113344040 0.352036750 0.055112943 0.430758133 -0.114410858
[21] -0.353977265 -0.351022798 -0.163767597 -0.133902362 0.060310649
[26] 0.054523853 0.150823456 -0.476384875 0.056366924 0.240182782
[31] -0.053084809 -0.045402422 -0.265992316 -0.120096889 -0.225016100
[36] -0.220567814 -0.258382419 0.412634385 0.289960366 0.170846762
[41] 0.013996302 -0.143118230 -0.228650037 -0.112090715 0.119015641
[46] -0.113803174 -0.197717988 -0.115647201 -0.274337113 0.177314468
[51] 0.315694981 0.289422108 -0.386329705 -0.511750696 0.020281372
[56] -0.099390402 -0.518290672 -0.010861461 -0.349078790 0.133293034
[61] -0.189080461 -0.259896373 -0.175888130 0.048512001 -0.103667762
[66] 0.026443181 -0.220758986 0.069709875 -0.599503892 -0.188855609
[71] 0.275034323 0.115786984 -0.013449196 0.388870760 -0.097559026
[76] -0.021418708 0.133244276 0.023454843 0.666794759 -0.238232442
[81] -0.585188939 0.145801327 0.192442375 -0.211357572 -0.088253213
[86] -0.146591225 -0.005551663 -0.408651586 0.147479483 0.111477734
[91] -0.245929785 -0.284092540 -0.150961684 -0.275055244 -0.674998631
[96] -0.087612406 -0.244096182 0.006377889 0.405533857 -0.324258880
[101] -0.547847421 -0.134581396 -0.041198041 0.019613289 0.356748477
[106] 0.200235221 0.583214741 -0.145033322 -0.167933175 -0.118888774
[111] -0.531962163 0.334685211 0.034725394 0.145195965 0.051243917
[116] 0.570004032 -0.148589389 0.414361419 -0.018819636 -0.372946692
[121] 0.132604546 0.007841102 0.010934833 0.226186128 -0.012635486
[126] 0.410872738 0.058002140 0.266337336 0.798676483 -0.186003324
[131] -0.707742996 0.457381928 0.433724654 0.133155647 -0.503693981
[136] 0.325139089 -0.386674437 0.068068123 -0.097805421 0.177957436
[141] 0.454419490 0.032763546 0.334960511 0.095754050 0.299717149
[146] -0.430892470 -0.763444327 -0.267786368 0.467318224 0.393560817
[151] -0.163009211 -0.655363907 -0.131353970 -0.377744755 0.339830963
[156] -0.040151514 0.203921413 -0.294254724 0.012240575 0.124621474
[161] -0.613311571 0.574001510 0.064248764 0.025382190 0.078959270
[166] 0.324802573 0.123727023 -0.263773669 -0.224102523 -0.808686348
[171] -0.284501793 -0.183628163 -0.042199740 0.280818858 0.022842174
[176] 0.034279238 -0.104658520 -0.571230169 0.174629009 0.223477509
[181] -0.043192932 0.139227800 0.020449920 0.085545157 -0.246220755
[186] 0.246123094 -0.423895547 -0.621378313 0.098994563 0.280124439
[191] 0.410813241 -0.248209296 0.486538701 -0.029408887 -0.349555334
[196] 0.476193320 -0.100890718 0.039972030 -0.006742509 -0.327397520
[201] 0.111905467 -0.022093845 -0.338233636 -0.323119116 0.019114092
[206] 0.351729708 0.178458998 -0.054840704 -0.294742691 0.268850733
[211] -0.040638853 0.255725780 -0.488337353 0.065945811 -0.323515009
[216] 0.083698092 0.148865956 0.263998431 -0.629475068 -0.471478315
[221] -0.231385659 0.228049987 0.210685580 0.089347294 -0.068108936
[226] -0.166971145 -0.526173408 -0.321752477 -0.361061298 -0.275548301
>
> proc.time()
user system elapsed
0.742 3.634 4.907
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x600000fa82a0>
> .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: 0x600000fa82a0>
> .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: 0x600000fa82a0>
> .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: 0x600000fa82a0>
> 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: 0x600000fac540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000fac540>
> .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: 0x600000fac540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000fac540>
> .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: 0x600000fac540>
> 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: 0x600000fac720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000fac720>
> .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: 0x600000fac720>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000fac720>
> .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: 0x600000fac720>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600000fac720>
> .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: 0x600000fac720>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600000fac720>
> .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: 0x600000fac720>
> 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: 0x600000fac900>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600000fac900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000fac900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000fac900>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile174f21cf2d52d" "BufferedMatrixFile174f2a898c34"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile174f21cf2d52d" "BufferedMatrixFile174f2a898c34"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000facba0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000facba0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000facba0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000facba0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600000facba0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600000facba0>
> .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: 0x600000facd80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000facd80>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000facd80>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600000facd80>
> 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: 0x600000facf60>
> .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: 0x600000facf60>
> rm(P)
>
> proc.time()
user system elapsed
0.125 0.048 0.186
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.153 0.044 0.189