Ben Bolstad
| Snapshot Date: 2026-04-28 14:14 -0400 (Tue, 28 Apr 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_23 |
| git_last_commit: 9d72964 |
| git_last_commit_date: 2026-04-28 08:32:08 -0400 (Tue, 28 Apr 2026) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-04-29 10:15 -0400 (Wed, 29 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4988 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 Patched (2026-04-24 r89963) -- "Because it was There" | 4694 |
| 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 260/2415 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.76.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.76.0 |
| 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_1.76.0.tar.gz |
| StartedAt: 2026-04-28 20:22:28 -0400 (Tue, 28 Apr 2026) |
| EndedAt: 2026-04-28 20:22:47 -0400 (Tue, 28 Apr 2026) |
| EllapsedTime: 19.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.76.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 Patched (2026-04-24 r89963)
* using platform: aarch64-apple-darwin23
* R was compiled by
Apple clang version 17.0.0 (clang-1700.3.19.1)
GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-04-29 00:22:28 UTC
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.76.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 17.0.0 (clang-1700.6.4.2)’
* used SDK: ‘MacOSX26.2.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 1 NOTE
See
‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.76.0’
** 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 (2026-04-24 r89963) -- "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
0.123 0.051 0.169
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 Patched (2026-04-24 r89963) -- "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-3.23-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 482663 25.8 1063027 56.8 NA 632020 33.8
Vcells 893071 6.9 8388608 64.0 196608 2112201 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] "Tue Apr 28 20:22:39 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] "Tue Apr 28 20:22:39 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: 0x103f0c180>
>
>
>
> 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] "Tue Apr 28 20:22:40 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] "Tue Apr 28 20:22:41 2026"
>
> ColMode(tmp2)
<pointer: 0x103f0c180>
>
>
>
> ### 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,] 101.0432252 0.2630910 -0.03122765 1.1740261
[2,] -0.1274754 -0.2880763 -0.17762193 -0.4168962
[3,] -0.4686701 1.2389204 -1.77867769 1.5783924
[4,] 0.7217521 1.0731263 1.13838141 0.2529094
> 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,] 101.0432252 0.2630910 0.03122765 1.1740261
[2,] 0.1274754 0.2880763 0.17762193 0.4168962
[3,] 0.4686701 1.2389204 1.77867769 1.5783924
[4,] 0.7217521 1.0731263 1.13838141 0.2529094
> 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,] 10.0520259 0.5129240 0.1767135 1.0835248
[2,] 0.3570370 0.5367274 0.4214522 0.6456750
[3,] 0.6845948 1.1130680 1.3336708 1.2563409
[4,] 0.8495599 1.0359181 1.0669496 0.5029009
>
> 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,] 226.56348 30.39233 26.79836 37.00927
[2,] 28.69785 30.65535 29.39214 31.87365
[3,] 32.31462 37.36960 40.11539 39.14180
[4,] 34.21735 36.43231 36.80788 30.28192
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xc3a8a4000>
> exp(tmp5)
<pointer: 0xc3a8a4000>
> log(tmp5,2)
<pointer: 0xc3a8a4000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.5622
> Min(tmp5)
[1] 53.17134
> mean(tmp5)
[1] 72.4677
> Sum(tmp5)
[1] 14493.54
> Var(tmp5)
[1] 873.9926
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.09955 68.83005 71.48159 71.36355 71.75368 68.94363 69.30370 70.95530
[9] 72.06851 71.87747
> rowSums(tmp5)
[1] 1761.991 1376.601 1429.632 1427.271 1435.074 1378.873 1386.074 1419.106
[9] 1441.370 1437.549
> rowVars(tmp5)
[1] 8229.32529 56.96472 43.80937 38.98041 71.87080 72.50324
[7] 79.53965 94.12426 74.76594 91.49856
> rowSd(tmp5)
[1] 90.715629 7.547497 6.618865 6.243429 8.477665 8.514884 8.918500
[8] 9.701766 8.646730 9.565488
> rowMax(tmp5)
[1] 471.56221 83.46775 83.49492 81.61322 88.57259 84.09181 88.56469
[8] 90.73100 88.96780 88.11687
> rowMin(tmp5)
[1] 54.21998 59.73081 61.27671 57.61257 56.80355 54.66416 53.17134 56.05669
[9] 56.91396 55.70267
>
> colMeans(tmp5)
[1] 109.29862 72.83463 73.33763 70.73201 73.82157 73.89292 74.30891
[8] 69.76045 68.38879 73.40511 68.84644 70.12199 68.92570 68.70348
[15] 72.71557 65.61832 67.25721 69.26582 70.50698 67.61193
> colSums(tmp5)
[1] 1092.9862 728.3463 733.3763 707.3201 738.2157 738.9292 743.0891
[8] 697.6045 683.8879 734.0511 688.4644 701.2199 689.2570 687.0348
[15] 727.1557 656.1832 672.5721 692.6582 705.0698 676.1193
> colVars(tmp5)
[1] 16236.59301 105.55062 146.65681 111.38424 38.53376 57.21464
[7] 20.82696 53.83652 119.68230 69.48558 71.40733 51.68253
[13] 31.25280 63.42602 73.77314 38.23945 82.83123 97.28820
[19] 93.31947 40.12960
> colSd(tmp5)
[1] 127.422890 10.273783 12.110195 10.553873 6.207557 7.564036
[7] 4.563656 7.337337 10.939941 8.335801 8.450286 7.189056
[13] 5.590420 7.964046 8.589129 6.183806 9.101167 9.863478
[19] 9.660201 6.334792
> colMax(tmp5)
[1] 471.56221 88.56469 88.96780 88.11687 83.46775 81.59662 82.23253
[8] 76.77260 88.25104 86.81827 81.61322 84.54240 79.56785 76.87365
[15] 81.45638 79.26845 81.31517 91.31250 90.73100 81.15241
> colMin(tmp5)
[1] 59.73081 56.05669 55.77728 54.66416 65.85567 61.27671 68.87995 54.21998
[9] 54.51101 60.29709 55.70267 63.54705 61.70106 57.36247 55.36884 56.34307
[17] 53.17134 56.91396 57.61257 58.65685
>
>
> ### 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] 88.09955 68.83005 71.48159 71.36355 NA 68.94363 69.30370 70.95530
[9] 72.06851 71.87747
> rowSums(tmp5)
[1] 1761.991 1376.601 1429.632 1427.271 NA 1378.873 1386.074 1419.106
[9] 1441.370 1437.549
> rowVars(tmp5)
[1] 8229.32529 56.96472 43.80937 38.98041 67.50214 72.50324
[7] 79.53965 94.12426 74.76594 91.49856
> rowSd(tmp5)
[1] 90.715629 7.547497 6.618865 6.243429 8.215969 8.514884 8.918500
[8] 9.701766 8.646730 9.565488
> rowMax(tmp5)
[1] 471.56221 83.46775 83.49492 81.61322 NA 84.09181 88.56469
[8] 90.73100 88.96780 88.11687
> rowMin(tmp5)
[1] 54.21998 59.73081 61.27671 57.61257 NA 54.66416 53.17134 56.05669
[9] 56.91396 55.70267
>
> colMeans(tmp5)
[1] 109.29862 72.83463 73.33763 NA 73.82157 73.89292 74.30891
[8] 69.76045 68.38879 73.40511 68.84644 70.12199 68.92570 68.70348
[15] 72.71557 65.61832 67.25721 69.26582 70.50698 67.61193
> colSums(tmp5)
[1] 1092.9862 728.3463 733.3763 NA 738.2157 738.9292 743.0891
[8] 697.6045 683.8879 734.0511 688.4644 701.2199 689.2570 687.0348
[15] 727.1557 656.1832 672.5721 692.6582 705.0698 676.1193
> colVars(tmp5)
[1] 16236.59301 105.55062 146.65681 NA 38.53376 57.21464
[7] 20.82696 53.83652 119.68230 69.48558 71.40733 51.68253
[13] 31.25280 63.42602 73.77314 38.23945 82.83123 97.28820
[19] 93.31947 40.12960
> colSd(tmp5)
[1] 127.422890 10.273783 12.110195 NA 6.207557 7.564036
[7] 4.563656 7.337337 10.939941 8.335801 8.450286 7.189056
[13] 5.590420 7.964046 8.589129 6.183806 9.101167 9.863478
[19] 9.660201 6.334792
> colMax(tmp5)
[1] 471.56221 88.56469 88.96780 NA 83.46775 81.59662 82.23253
[8] 76.77260 88.25104 86.81827 81.61322 84.54240 79.56785 76.87365
[15] 81.45638 79.26845 81.31517 91.31250 90.73100 81.15241
> colMin(tmp5)
[1] 59.73081 56.05669 55.77728 NA 65.85567 61.27671 68.87995 54.21998
[9] 54.51101 60.29709 55.70267 63.54705 61.70106 57.36247 55.36884 56.34307
[17] 53.17134 56.91396 57.61257 58.65685
>
> Max(tmp5,na.rm=TRUE)
[1] 471.5622
> Min(tmp5,na.rm=TRUE)
[1] 53.17134
> mean(tmp5,na.rm=TRUE)
[1] 72.53138
> Sum(tmp5,na.rm=TRUE)
[1] 14433.74
> Var(tmp5,na.rm=TRUE)
[1] 877.5917
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.09955 68.83005 71.48159 71.36355 72.38302 68.94363 69.30370 70.95530
[9] 72.06851 71.87747
> rowSums(tmp5,na.rm=TRUE)
[1] 1761.991 1376.601 1429.632 1427.271 1375.277 1378.873 1386.074 1419.106
[9] 1441.370 1437.549
> rowVars(tmp5,na.rm=TRUE)
[1] 8229.32529 56.96472 43.80937 38.98041 67.50214 72.50324
[7] 79.53965 94.12426 74.76594 91.49856
> rowSd(tmp5,na.rm=TRUE)
[1] 90.715629 7.547497 6.618865 6.243429 8.215969 8.514884 8.918500
[8] 9.701766 8.646730 9.565488
> rowMax(tmp5,na.rm=TRUE)
[1] 471.56221 83.46775 83.49492 81.61322 88.57259 84.09181 88.56469
[8] 90.73100 88.96780 88.11687
> rowMin(tmp5,na.rm=TRUE)
[1] 54.21998 59.73081 61.27671 57.61257 56.80355 54.66416 53.17134 56.05669
[9] 56.91396 55.70267
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.29862 72.83463 73.33763 71.94710 73.82157 73.89292 74.30891
[8] 69.76045 68.38879 73.40511 68.84644 70.12199 68.92570 68.70348
[15] 72.71557 65.61832 67.25721 69.26582 70.50698 67.61193
> colSums(tmp5,na.rm=TRUE)
[1] 1092.9862 728.3463 733.3763 647.5239 738.2157 738.9292 743.0891
[8] 697.6045 683.8879 734.0511 688.4644 701.2199 689.2570 687.0348
[15] 727.1557 656.1832 672.5721 692.6582 705.0698 676.1193
> colVars(tmp5,na.rm=TRUE)
[1] 16236.59301 105.55062 146.65681 108.69727 38.53376 57.21464
[7] 20.82696 53.83652 119.68230 69.48558 71.40733 51.68253
[13] 31.25280 63.42602 73.77314 38.23945 82.83123 97.28820
[19] 93.31947 40.12960
> colSd(tmp5,na.rm=TRUE)
[1] 127.422890 10.273783 12.110195 10.425798 6.207557 7.564036
[7] 4.563656 7.337337 10.939941 8.335801 8.450286 7.189056
[13] 5.590420 7.964046 8.589129 6.183806 9.101167 9.863478
[19] 9.660201 6.334792
> colMax(tmp5,na.rm=TRUE)
[1] 471.56221 88.56469 88.96780 88.11687 83.46775 81.59662 82.23253
[8] 76.77260 88.25104 86.81827 81.61322 84.54240 79.56785 76.87365
[15] 81.45638 79.26845 81.31517 91.31250 90.73100 81.15241
> colMin(tmp5,na.rm=TRUE)
[1] 59.73081 56.05669 55.77728 54.66416 65.85567 61.27671 68.87995 54.21998
[9] 54.51101 60.29709 55.70267 63.54705 61.70106 57.36247 55.36884 56.34307
[17] 53.17134 56.91396 57.61257 58.65685
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.09955 68.83005 71.48159 71.36355 NaN 68.94363 69.30370 70.95530
[9] 72.06851 71.87747
> rowSums(tmp5,na.rm=TRUE)
[1] 1761.991 1376.601 1429.632 1427.271 0.000 1378.873 1386.074 1419.106
[9] 1441.370 1437.549
> rowVars(tmp5,na.rm=TRUE)
[1] 8229.32529 56.96472 43.80937 38.98041 NA 72.50324
[7] 79.53965 94.12426 74.76594 91.49856
> rowSd(tmp5,na.rm=TRUE)
[1] 90.715629 7.547497 6.618865 6.243429 NA 8.514884 8.918500
[8] 9.701766 8.646730 9.565488
> rowMax(tmp5,na.rm=TRUE)
[1] 471.56221 83.46775 83.49492 81.61322 NA 84.09181 88.56469
[8] 90.73100 88.96780 88.11687
> rowMin(tmp5,na.rm=TRUE)
[1] 54.21998 59.73081 61.27671 57.61257 NA 54.66416 53.17134 56.05669
[9] 56.91396 55.70267
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.24365 73.63552 71.64486 NaN 74.59855 73.18199 74.64241
[8] 69.25305 69.67604 71.91476 67.75564 70.65834 68.43034 68.48379
[15] 72.11976 65.67239 67.76133 69.70862 69.67137 66.94128
> colSums(tmp5,na.rm=TRUE)
[1] 1019.1928 662.7197 644.8037 0.0000 671.3869 658.6379 671.7817
[8] 623.2775 627.0843 647.2328 609.8008 635.9251 615.8731 616.3541
[15] 649.0779 591.0516 609.8520 627.3776 627.0424 602.4715
> colVars(tmp5,na.rm=TRUE)
[1] 18091.08012 111.52841 132.75227 NA 36.55884 58.68051
[7] 22.17907 57.66979 116.00122 53.18338 66.94752 54.90655
[13] 32.39884 70.81131 79.00119 42.98649 90.32613 107.24341
[19] 97.12919 40.08593
> colSd(tmp5,na.rm=TRUE)
[1] 134.503086 10.560701 11.521817 NA 6.046390 7.660320
[7] 4.709466 7.594063 10.770386 7.292694 8.182147 7.409895
[13] 5.691998 8.414946 8.888261 6.556408 9.504006 10.355840
[19] 9.855414 6.331345
> colMax(tmp5,na.rm=TRUE)
[1] 471.56221 88.56469 88.96780 -Inf 83.46775 81.59662 82.23253
[8] 76.77260 88.25104 85.35353 81.61322 84.54240 79.56785 76.87365
[15] 81.45638 79.26845 81.31517 91.31250 90.73100 81.15241
> colMin(tmp5,na.rm=TRUE)
[1] 59.73081 56.05669 55.77728 Inf 65.85567 61.27671 68.87995 54.21998
[9] 54.51101 60.29709 55.70267 63.54705 61.70106 57.36247 55.36884 56.34307
[17] 53.17134 56.91396 57.61257 58.65685
>
>
>
>
> 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] 208.3257 401.0397 262.9892 152.2723 445.9969 207.7122 252.5842 202.9147
[9] 423.6123 232.0862
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 208.3257 401.0397 262.9892 152.2723 445.9969 207.7122 252.5842 202.9147
[9] 423.6123 232.0862
>
>
>
> 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 2.842171e-14 4.973799e-14 0.000000e+00
[6] -1.136868e-13 1.705303e-13 5.684342e-14 -5.684342e-14 1.136868e-13
[11] 0.000000e+00 -4.263256e-14 -2.842171e-14 1.421085e-14 0.000000e+00
[16] -5.684342e-14 -1.136868e-13 -2.842171e-14 -8.526513e-14 1.705303e-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)
+ }
6 11
3 17
3 13
6 2
10 11
5 12
8 9
7 18
4 18
2 18
1 2
10 15
3 9
5 12
4 17
8 8
3 9
5 8
4 13
8 13
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] 2.507133
> Min(tmp)
[1] -2.444541
> mean(tmp)
[1] -0.03789935
> Sum(tmp)
[1] -3.789935
> Var(tmp)
[1] 0.8339199
>
> rowMeans(tmp)
[1] -0.03789935
> rowSums(tmp)
[1] -3.789935
> rowVars(tmp)
[1] 0.8339199
> rowSd(tmp)
[1] 0.9131921
> rowMax(tmp)
[1] 2.507133
> rowMin(tmp)
[1] -2.444541
>
> colMeans(tmp)
[1] 1.00424645 -0.34244125 -0.26746146 0.94699839 0.56644864 0.92955730
[7] 0.82613681 -0.69696474 -0.69932206 0.74280508 0.14058826 -1.73422062
[13] -2.44454075 0.97911307 1.27621733 0.44579213 1.44621968 -0.28614305
[19] 0.48653406 1.43178822 1.80336490 -0.63115125 -0.25872952 -1.42380056
[25] -0.35039736 -1.39094086 -0.37123333 0.32115301 0.53207199 -0.68298876
[31] -0.18933519 -0.50414288 0.20294031 0.30532495 -0.35619932 -1.26843863
[37] -0.02510502 0.55327161 -0.46339229 -1.35500474 -0.07001405 -0.48300727
[43] 1.52640130 0.36370803 -1.54488295 0.16349296 -0.82648854 0.56151719
[49] 2.50713278 0.54443839 -1.40840533 0.62987044 0.26137701 -0.32378516
[55] -0.97174784 -0.18005011 1.02191719 1.01065307 0.44932214 -0.53083687
[61] 0.08528582 0.52182858 -0.62559045 0.32534735 -0.32989788 -0.09439054
[67] -1.36139116 1.37327550 -0.63832746 -0.12003112 0.44646230 -0.87237436
[73] 1.49327753 -1.80936391 -0.34711964 -1.55590530 0.92620445 -0.03708012
[79] -0.39976444 0.64947214 -0.18276293 0.39804928 1.12924816 0.63094899
[85] -0.68981995 0.06521924 -0.01051859 -0.35771420 1.22678003 -0.81419948
[91] -0.67605594 0.22441713 -1.47839815 0.24062864 1.12137842 -1.45270842
[97] -1.38576293 -0.23591713 -0.35226284 -0.71963287
> colSums(tmp)
[1] 1.00424645 -0.34244125 -0.26746146 0.94699839 0.56644864 0.92955730
[7] 0.82613681 -0.69696474 -0.69932206 0.74280508 0.14058826 -1.73422062
[13] -2.44454075 0.97911307 1.27621733 0.44579213 1.44621968 -0.28614305
[19] 0.48653406 1.43178822 1.80336490 -0.63115125 -0.25872952 -1.42380056
[25] -0.35039736 -1.39094086 -0.37123333 0.32115301 0.53207199 -0.68298876
[31] -0.18933519 -0.50414288 0.20294031 0.30532495 -0.35619932 -1.26843863
[37] -0.02510502 0.55327161 -0.46339229 -1.35500474 -0.07001405 -0.48300727
[43] 1.52640130 0.36370803 -1.54488295 0.16349296 -0.82648854 0.56151719
[49] 2.50713278 0.54443839 -1.40840533 0.62987044 0.26137701 -0.32378516
[55] -0.97174784 -0.18005011 1.02191719 1.01065307 0.44932214 -0.53083687
[61] 0.08528582 0.52182858 -0.62559045 0.32534735 -0.32989788 -0.09439054
[67] -1.36139116 1.37327550 -0.63832746 -0.12003112 0.44646230 -0.87237436
[73] 1.49327753 -1.80936391 -0.34711964 -1.55590530 0.92620445 -0.03708012
[79] -0.39976444 0.64947214 -0.18276293 0.39804928 1.12924816 0.63094899
[85] -0.68981995 0.06521924 -0.01051859 -0.35771420 1.22678003 -0.81419948
[91] -0.67605594 0.22441713 -1.47839815 0.24062864 1.12137842 -1.45270842
[97] -1.38576293 -0.23591713 -0.35226284 -0.71963287
> 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] 1.00424645 -0.34244125 -0.26746146 0.94699839 0.56644864 0.92955730
[7] 0.82613681 -0.69696474 -0.69932206 0.74280508 0.14058826 -1.73422062
[13] -2.44454075 0.97911307 1.27621733 0.44579213 1.44621968 -0.28614305
[19] 0.48653406 1.43178822 1.80336490 -0.63115125 -0.25872952 -1.42380056
[25] -0.35039736 -1.39094086 -0.37123333 0.32115301 0.53207199 -0.68298876
[31] -0.18933519 -0.50414288 0.20294031 0.30532495 -0.35619932 -1.26843863
[37] -0.02510502 0.55327161 -0.46339229 -1.35500474 -0.07001405 -0.48300727
[43] 1.52640130 0.36370803 -1.54488295 0.16349296 -0.82648854 0.56151719
[49] 2.50713278 0.54443839 -1.40840533 0.62987044 0.26137701 -0.32378516
[55] -0.97174784 -0.18005011 1.02191719 1.01065307 0.44932214 -0.53083687
[61] 0.08528582 0.52182858 -0.62559045 0.32534735 -0.32989788 -0.09439054
[67] -1.36139116 1.37327550 -0.63832746 -0.12003112 0.44646230 -0.87237436
[73] 1.49327753 -1.80936391 -0.34711964 -1.55590530 0.92620445 -0.03708012
[79] -0.39976444 0.64947214 -0.18276293 0.39804928 1.12924816 0.63094899
[85] -0.68981995 0.06521924 -0.01051859 -0.35771420 1.22678003 -0.81419948
[91] -0.67605594 0.22441713 -1.47839815 0.24062864 1.12137842 -1.45270842
[97] -1.38576293 -0.23591713 -0.35226284 -0.71963287
> colMin(tmp)
[1] 1.00424645 -0.34244125 -0.26746146 0.94699839 0.56644864 0.92955730
[7] 0.82613681 -0.69696474 -0.69932206 0.74280508 0.14058826 -1.73422062
[13] -2.44454075 0.97911307 1.27621733 0.44579213 1.44621968 -0.28614305
[19] 0.48653406 1.43178822 1.80336490 -0.63115125 -0.25872952 -1.42380056
[25] -0.35039736 -1.39094086 -0.37123333 0.32115301 0.53207199 -0.68298876
[31] -0.18933519 -0.50414288 0.20294031 0.30532495 -0.35619932 -1.26843863
[37] -0.02510502 0.55327161 -0.46339229 -1.35500474 -0.07001405 -0.48300727
[43] 1.52640130 0.36370803 -1.54488295 0.16349296 -0.82648854 0.56151719
[49] 2.50713278 0.54443839 -1.40840533 0.62987044 0.26137701 -0.32378516
[55] -0.97174784 -0.18005011 1.02191719 1.01065307 0.44932214 -0.53083687
[61] 0.08528582 0.52182858 -0.62559045 0.32534735 -0.32989788 -0.09439054
[67] -1.36139116 1.37327550 -0.63832746 -0.12003112 0.44646230 -0.87237436
[73] 1.49327753 -1.80936391 -0.34711964 -1.55590530 0.92620445 -0.03708012
[79] -0.39976444 0.64947214 -0.18276293 0.39804928 1.12924816 0.63094899
[85] -0.68981995 0.06521924 -0.01051859 -0.35771420 1.22678003 -0.81419948
[91] -0.67605594 0.22441713 -1.47839815 0.24062864 1.12137842 -1.45270842
[97] -1.38576293 -0.23591713 -0.35226284 -0.71963287
> colMedians(tmp)
[1] 1.00424645 -0.34244125 -0.26746146 0.94699839 0.56644864 0.92955730
[7] 0.82613681 -0.69696474 -0.69932206 0.74280508 0.14058826 -1.73422062
[13] -2.44454075 0.97911307 1.27621733 0.44579213 1.44621968 -0.28614305
[19] 0.48653406 1.43178822 1.80336490 -0.63115125 -0.25872952 -1.42380056
[25] -0.35039736 -1.39094086 -0.37123333 0.32115301 0.53207199 -0.68298876
[31] -0.18933519 -0.50414288 0.20294031 0.30532495 -0.35619932 -1.26843863
[37] -0.02510502 0.55327161 -0.46339229 -1.35500474 -0.07001405 -0.48300727
[43] 1.52640130 0.36370803 -1.54488295 0.16349296 -0.82648854 0.56151719
[49] 2.50713278 0.54443839 -1.40840533 0.62987044 0.26137701 -0.32378516
[55] -0.97174784 -0.18005011 1.02191719 1.01065307 0.44932214 -0.53083687
[61] 0.08528582 0.52182858 -0.62559045 0.32534735 -0.32989788 -0.09439054
[67] -1.36139116 1.37327550 -0.63832746 -0.12003112 0.44646230 -0.87237436
[73] 1.49327753 -1.80936391 -0.34711964 -1.55590530 0.92620445 -0.03708012
[79] -0.39976444 0.64947214 -0.18276293 0.39804928 1.12924816 0.63094899
[85] -0.68981995 0.06521924 -0.01051859 -0.35771420 1.22678003 -0.81419948
[91] -0.67605594 0.22441713 -1.47839815 0.24062864 1.12137842 -1.45270842
[97] -1.38576293 -0.23591713 -0.35226284 -0.71963287
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.004246 -0.3424413 -0.2674615 0.9469984 0.5664486 0.9295573 0.8261368
[2,] 1.004246 -0.3424413 -0.2674615 0.9469984 0.5664486 0.9295573 0.8261368
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.6969647 -0.6993221 0.7428051 0.1405883 -1.734221 -2.444541 0.9791131
[2,] -0.6969647 -0.6993221 0.7428051 0.1405883 -1.734221 -2.444541 0.9791131
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.276217 0.4457921 1.44622 -0.2861431 0.4865341 1.431788 1.803365
[2,] 1.276217 0.4457921 1.44622 -0.2861431 0.4865341 1.431788 1.803365
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.6311513 -0.2587295 -1.423801 -0.3503974 -1.390941 -0.3712333 0.321153
[2,] -0.6311513 -0.2587295 -1.423801 -0.3503974 -1.390941 -0.3712333 0.321153
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.532072 -0.6829888 -0.1893352 -0.5041429 0.2029403 0.305325 -0.3561993
[2,] 0.532072 -0.6829888 -0.1893352 -0.5041429 0.2029403 0.305325 -0.3561993
[,36] [,37] [,38] [,39] [,40] [,41]
[1,] -1.268439 -0.02510502 0.5532716 -0.4633923 -1.355005 -0.07001405
[2,] -1.268439 -0.02510502 0.5532716 -0.4633923 -1.355005 -0.07001405
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.4830073 1.526401 0.363708 -1.544883 0.163493 -0.8264885 0.5615172
[2,] -0.4830073 1.526401 0.363708 -1.544883 0.163493 -0.8264885 0.5615172
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 2.507133 0.5444384 -1.408405 0.6298704 0.261377 -0.3237852 -0.9717478
[2,] 2.507133 0.5444384 -1.408405 0.6298704 0.261377 -0.3237852 -0.9717478
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.1800501 1.021917 1.010653 0.4493221 -0.5308369 0.08528582 0.5218286
[2,] -0.1800501 1.021917 1.010653 0.4493221 -0.5308369 0.08528582 0.5218286
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.6255905 0.3253473 -0.3298979 -0.09439054 -1.361391 1.373275 -0.6383275
[2,] -0.6255905 0.3253473 -0.3298979 -0.09439054 -1.361391 1.373275 -0.6383275
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.1200311 0.4464623 -0.8723744 1.493278 -1.809364 -0.3471196 -1.555905
[2,] -0.1200311 0.4464623 -0.8723744 1.493278 -1.809364 -0.3471196 -1.555905
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.9262044 -0.03708012 -0.3997644 0.6494721 -0.1827629 0.3980493 1.129248
[2,] 0.9262044 -0.03708012 -0.3997644 0.6494721 -0.1827629 0.3980493 1.129248
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.630949 -0.6898199 0.06521924 -0.01051859 -0.3577142 1.22678 -0.8141995
[2,] 0.630949 -0.6898199 0.06521924 -0.01051859 -0.3577142 1.22678 -0.8141995
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.6760559 0.2244171 -1.478398 0.2406286 1.121378 -1.452708 -1.385763
[2,] -0.6760559 0.2244171 -1.478398 0.2406286 1.121378 -1.452708 -1.385763
[,98] [,99] [,100]
[1,] -0.2359171 -0.3522628 -0.7196329
[2,] -0.2359171 -0.3522628 -0.7196329
>
>
> Max(tmp2)
[1] 2.143449
> Min(tmp2)
[1] -2.152066
> mean(tmp2)
[1] -0.003668957
> Sum(tmp2)
[1] -0.3668957
> Var(tmp2)
[1] 0.9511498
>
> rowMeans(tmp2)
[1] 0.46659052 0.03579624 -0.02035818 0.62728501 1.80996854 -0.27982800
[7] 0.04113934 1.24791557 0.15869901 -1.59683983 1.10481245 0.83444448
[13] -0.85446607 0.19973710 -2.15206622 -0.62818860 -1.74773835 0.61522615
[19] 0.55361306 2.09190557 1.34492651 1.51644233 -1.01513128 0.90946107
[25] -0.06231246 -0.36012340 -0.11239750 -0.55616981 0.61771011 0.93613558
[31] -0.75468321 -0.58585020 -0.65852740 0.80894631 -0.87747620 -1.11978884
[37] -1.50190154 -0.51481295 -0.44189040 -0.31660528 -0.56753041 0.37062217
[43] 0.08816834 0.17103642 -1.24493002 0.48014890 1.21641803 -0.64627466
[49] -0.43244328 -0.25755274 1.18032898 -1.01706122 0.74661814 -0.79473256
[55] 0.55793922 -0.44674142 1.20960716 -0.87856634 0.99454983 0.19611502
[61] 1.46383755 -0.36662077 1.10100492 -0.21234836 0.22724254 0.35627035
[67] -1.46518434 1.35943553 -0.77356310 -1.30259400 1.01905969 0.05346000
[73] 1.64598775 -1.42963119 -1.68220341 0.16040343 1.40156161 -1.09608500
[79] -0.78626217 1.15375512 -0.37606082 -1.06284159 1.01420388 -0.44162539
[85] 2.14344860 -0.77722584 0.49254146 0.97178817 0.58205960 -0.90497380
[91] 0.12872429 0.41984154 -1.04006551 0.57769720 -0.22603034 -1.69317339
[97] 0.51603488 -1.01626708 0.73743126 -1.92924770
> rowSums(tmp2)
[1] 0.46659052 0.03579624 -0.02035818 0.62728501 1.80996854 -0.27982800
[7] 0.04113934 1.24791557 0.15869901 -1.59683983 1.10481245 0.83444448
[13] -0.85446607 0.19973710 -2.15206622 -0.62818860 -1.74773835 0.61522615
[19] 0.55361306 2.09190557 1.34492651 1.51644233 -1.01513128 0.90946107
[25] -0.06231246 -0.36012340 -0.11239750 -0.55616981 0.61771011 0.93613558
[31] -0.75468321 -0.58585020 -0.65852740 0.80894631 -0.87747620 -1.11978884
[37] -1.50190154 -0.51481295 -0.44189040 -0.31660528 -0.56753041 0.37062217
[43] 0.08816834 0.17103642 -1.24493002 0.48014890 1.21641803 -0.64627466
[49] -0.43244328 -0.25755274 1.18032898 -1.01706122 0.74661814 -0.79473256
[55] 0.55793922 -0.44674142 1.20960716 -0.87856634 0.99454983 0.19611502
[61] 1.46383755 -0.36662077 1.10100492 -0.21234836 0.22724254 0.35627035
[67] -1.46518434 1.35943553 -0.77356310 -1.30259400 1.01905969 0.05346000
[73] 1.64598775 -1.42963119 -1.68220341 0.16040343 1.40156161 -1.09608500
[79] -0.78626217 1.15375512 -0.37606082 -1.06284159 1.01420388 -0.44162539
[85] 2.14344860 -0.77722584 0.49254146 0.97178817 0.58205960 -0.90497380
[91] 0.12872429 0.41984154 -1.04006551 0.57769720 -0.22603034 -1.69317339
[97] 0.51603488 -1.01626708 0.73743126 -1.92924770
> 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] 0.46659052 0.03579624 -0.02035818 0.62728501 1.80996854 -0.27982800
[7] 0.04113934 1.24791557 0.15869901 -1.59683983 1.10481245 0.83444448
[13] -0.85446607 0.19973710 -2.15206622 -0.62818860 -1.74773835 0.61522615
[19] 0.55361306 2.09190557 1.34492651 1.51644233 -1.01513128 0.90946107
[25] -0.06231246 -0.36012340 -0.11239750 -0.55616981 0.61771011 0.93613558
[31] -0.75468321 -0.58585020 -0.65852740 0.80894631 -0.87747620 -1.11978884
[37] -1.50190154 -0.51481295 -0.44189040 -0.31660528 -0.56753041 0.37062217
[43] 0.08816834 0.17103642 -1.24493002 0.48014890 1.21641803 -0.64627466
[49] -0.43244328 -0.25755274 1.18032898 -1.01706122 0.74661814 -0.79473256
[55] 0.55793922 -0.44674142 1.20960716 -0.87856634 0.99454983 0.19611502
[61] 1.46383755 -0.36662077 1.10100492 -0.21234836 0.22724254 0.35627035
[67] -1.46518434 1.35943553 -0.77356310 -1.30259400 1.01905969 0.05346000
[73] 1.64598775 -1.42963119 -1.68220341 0.16040343 1.40156161 -1.09608500
[79] -0.78626217 1.15375512 -0.37606082 -1.06284159 1.01420388 -0.44162539
[85] 2.14344860 -0.77722584 0.49254146 0.97178817 0.58205960 -0.90497380
[91] 0.12872429 0.41984154 -1.04006551 0.57769720 -0.22603034 -1.69317339
[97] 0.51603488 -1.01626708 0.73743126 -1.92924770
> rowMin(tmp2)
[1] 0.46659052 0.03579624 -0.02035818 0.62728501 1.80996854 -0.27982800
[7] 0.04113934 1.24791557 0.15869901 -1.59683983 1.10481245 0.83444448
[13] -0.85446607 0.19973710 -2.15206622 -0.62818860 -1.74773835 0.61522615
[19] 0.55361306 2.09190557 1.34492651 1.51644233 -1.01513128 0.90946107
[25] -0.06231246 -0.36012340 -0.11239750 -0.55616981 0.61771011 0.93613558
[31] -0.75468321 -0.58585020 -0.65852740 0.80894631 -0.87747620 -1.11978884
[37] -1.50190154 -0.51481295 -0.44189040 -0.31660528 -0.56753041 0.37062217
[43] 0.08816834 0.17103642 -1.24493002 0.48014890 1.21641803 -0.64627466
[49] -0.43244328 -0.25755274 1.18032898 -1.01706122 0.74661814 -0.79473256
[55] 0.55793922 -0.44674142 1.20960716 -0.87856634 0.99454983 0.19611502
[61] 1.46383755 -0.36662077 1.10100492 -0.21234836 0.22724254 0.35627035
[67] -1.46518434 1.35943553 -0.77356310 -1.30259400 1.01905969 0.05346000
[73] 1.64598775 -1.42963119 -1.68220341 0.16040343 1.40156161 -1.09608500
[79] -0.78626217 1.15375512 -0.37606082 -1.06284159 1.01420388 -0.44162539
[85] 2.14344860 -0.77722584 0.49254146 0.97178817 0.58205960 -0.90497380
[91] 0.12872429 0.41984154 -1.04006551 0.57769720 -0.22603034 -1.69317339
[97] 0.51603488 -1.01626708 0.73743126 -1.92924770
>
> colMeans(tmp2)
[1] -0.003668957
> colSums(tmp2)
[1] -0.3668957
> colVars(tmp2)
[1] 0.9511498
> colSd(tmp2)
[1] 0.9752691
> colMax(tmp2)
[1] 2.143449
> colMin(tmp2)
[1] -2.152066
> colMedians(tmp2)
[1] 0.03846779
> colRanges(tmp2)
[,1]
[1,] -2.152066
[2,] 2.143449
>
> 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] 4.1461926 -4.0438702 -4.0630901 -0.9332066 -1.4749691 2.1227096
[7] -3.0216288 1.5336714 3.2880069 4.3709766
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.57371360
[2,] 0.05265362
[3,] 0.34398638
[4,] 0.80271720
[5,] 1.55938960
>
> rowApply(tmp,sum)
[1] -0.21572842 3.10369927 -3.76816652 1.20192552 -1.01569751 1.21359217
[7] 0.07731903 0.55362880 -1.26304971 2.03726973
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 10 8 6 8 3 7 3 5 10
[2,] 1 6 7 10 2 7 1 5 1 8
[3,] 4 4 4 3 4 2 3 4 7 2
[4,] 7 9 5 1 9 4 2 7 4 6
[5,] 5 7 3 9 1 8 8 2 3 5
[6,] 8 2 6 2 6 6 10 8 8 7
[7,] 10 1 9 8 3 1 4 1 2 4
[8,] 3 3 1 7 10 5 6 6 10 1
[9,] 2 5 10 4 7 9 5 10 9 9
[10,] 6 8 2 5 5 10 9 9 6 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.26665701 4.72283672 2.12663201 -2.60642905 -5.02778402 -1.37183402
[7] -3.45686919 -4.57254571 2.38045300 5.28498114 0.29072122 0.74460401
[13] 0.42474762 1.62426518 5.39683613 5.28609054 2.80039673 -0.08999964
[19] -0.13068052 1.19502137
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.2923275
[2,] 0.5780480
[3,] 0.7375443
[4,] 0.8226474
[5,] 0.8360898
>
> rowApply(tmp,sum)
[1] -0.3547961 -3.7517043 9.9926952 7.6094673 4.7924384
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 17 14 12 15
[2,] 19 20 19 7 11
[3,] 17 7 17 10 9
[4,] 8 5 7 9 2
[5,] 4 9 3 2 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5780480 1.75735067 1.04608223 -0.341913073 -0.9902125 0.33322083
[2,] 0.8226474 1.47158827 -0.54485179 -0.758395715 -0.4070385 -2.53151067
[3,] 0.8360898 1.78027679 1.53068219 0.014389461 -0.4153437 -0.01223587
[4,] 0.2923275 -0.34867276 0.17006672 -0.004219637 -1.4811483 0.28651139
[5,] 0.7375443 0.06229375 -0.07534734 -1.516290092 -1.7340410 0.55218031
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.6705383 -2.09497761 1.3896097 1.80453783 -0.4984071 0.4701042
[2,] -0.8069076 -0.27221338 -0.7726415 1.46482546 -0.6953245 -0.4906179
[3,] 0.4583036 -1.17644513 0.8126960 0.05453945 1.8776128 0.4940450
[4,] -1.5400103 -1.05532269 1.2335578 1.76591290 -0.2512534 0.7148324
[5,] 0.1022834 0.02641309 -0.2827689 0.19516550 -0.1419065 -0.4437597
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.14602913 0.1178516 -1.202314 -0.49681570 -0.3210972 0.68547486
[2,] -0.36423725 0.3415503 1.352294 0.04751787 -0.4009232 0.01666449
[3,] -0.06794781 -1.5209381 1.353262 0.94670957 1.7783046 0.61832258
[4,] 2.34661320 0.6419142 1.684942 2.54491589 -0.5504203 -0.38435602
[5,] -1.34365139 2.0438873 2.208651 2.24376291 2.2945329 -1.02610556
[,19] [,20]
[1,] 0.05164974 -0.8264213
[2,] -1.68212392 0.4579934
[3,] -0.05312180 0.6834938
[4,] 2.21505304 -0.6717767
[5,] -0.66213758 1.5517321
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 655 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6
row1 1.464476 -0.4162075 -0.6159223 -0.0009854296 0.5161501 0.9421965
col7 col8 col9 col10 col11 col12 col13
row1 0.01146593 -2.255521 -0.8320277 -1.041123 1.676663 -1.832962 -0.8906349
col14 col15 col16 col17 col18 col19 col20
row1 -0.6022085 0.06346648 0.3653362 -1.540508 1.248529 -0.08225078 -0.04901865
> tmp[,"col10"]
col10
row1 -1.04112307
row2 -1.50846141
row3 -0.21988107
row4 -0.03452441
row5 0.11797717
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.464476 -0.4162075 -0.6159223 -0.0009854296 0.5161501 0.9421965
row5 -1.604929 0.5410750 1.9640094 1.1223519265 1.8581456 -0.5821487
col7 col8 col9 col10 col11 col12
row1 0.01146593 -2.255521 -0.83202774 -1.0411231 1.6766626 -1.832962
row5 -0.26296154 1.255565 -0.07220066 0.1179772 0.1043476 1.669593
col13 col14 col15 col16 col17 col18
row1 -0.89063489 -0.6022085 0.06346648 0.3653362 -1.5405081 1.2485287
row5 0.08751874 -0.5055256 -1.64424761 -0.5313394 0.4859605 -0.1498959
col19 col20
row1 -0.08225078 -0.04901865
row5 0.48442963 0.55376140
> tmp[,c("col6","col20")]
col6 col20
row1 0.9421965 -0.04901865
row2 0.4186974 1.56250015
row3 -0.8746838 0.61030955
row4 -1.5433641 2.01429692
row5 -0.5821487 0.55376140
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.9421965 -0.04901865
row5 -0.5821487 0.55376140
>
>
>
>
> 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 50.63405 49.2242 49.80342 50.35559 51.06215 104.961 49.09661 50.01425
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.77451 49.46149 50.00048 49.42325 49.60407 50.15231 49.62854 49.95688
col17 col18 col19 col20
row1 49.08523 50.97413 50.54071 104.0702
> tmp[,"col10"]
col10
row1 49.46149
row2 30.84860
row3 29.29643
row4 31.79064
row5 50.08698
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.63405 49.22420 49.80342 50.35559 51.06215 104.9610 49.09661 50.01425
row5 48.84137 49.30373 51.13385 51.06949 51.47442 105.9151 50.62493 49.97140
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.77451 49.46149 50.00048 49.42325 49.60407 50.15231 49.62854 49.95688
row5 50.46392 50.08698 51.23595 49.83266 49.97659 49.74797 49.47881 48.03359
col17 col18 col19 col20
row1 49.08523 50.97413 50.54071 104.0702
row5 49.78477 52.77860 50.67992 104.8635
> tmp[,c("col6","col20")]
col6 col20
row1 104.96097 104.07017
row2 75.27939 75.79248
row3 74.04856 74.96270
row4 75.68012 76.29765
row5 105.91506 104.86352
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9610 104.0702
row5 105.9151 104.8635
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9610 104.0702
row5 105.9151 104.8635
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.120146767
[2,] 0.002534197
[3,] -0.283488361
[4,] 0.636193008
[5,] -0.479866281
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.03389305 -1.06123915
[2,] 1.58003386 0.07915311
[3,] 0.90899195 -0.08684736
[4,] 0.91223168 -0.82068557
[5,] -1.20094402 0.75037587
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.6212034 -0.2791979
[2,] -0.3861952 -0.7841023
[3,] -0.7785182 -1.7781503
[4,] 0.4808454 -0.5788089
[5,] -0.8061807 -0.1764903
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.6212034
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.6212034
[2,] -0.3861952
>
>
>
> 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 0.02960294 -0.4260202 -1.3188859 -1.2629416 -0.2951817 -1.3807460
row1 0.98611578 0.5295906 -0.2398447 -0.1156697 -0.9944924 0.8810895
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.3579712 -0.8294424 0.06158182 -0.04759233 0.9075944 -1.0756436
row1 0.5181782 -0.1172426 -0.35720248 -0.98710595 -0.6235198 -0.4040505
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.1988325 0.2232210 2.2939515 0.1167984 -0.7757048 0.2004949
row1 -0.8295481 -0.9058518 -0.6019168 -1.9487692 -0.1278201 -0.4515997
[,19] [,20]
row3 -0.5892050 0.8735230
row1 0.7270841 0.3873293
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5537247 -1.00834 -0.7534794 -0.6533441 -0.2396811 2.094452 -0.4056423
[,8] [,9] [,10]
row2 -0.4312668 -1.161698 -0.2280013
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2071241 -0.9349855 -0.2446685 0.1580837 -1.031556 1.213268 -1.422906
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7096309 0.1864087 -0.05876601 0.7214826 0.6877093 -0.7523094 -0.7227307
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.06109391 -1.004839 0.4768582 -1.05526 1.234534 0.4139635
>
>
> 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: 0xc3a8a4660>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c64c5fcf1"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c26165e7"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c486921e9"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c6e316d22"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c6ef40bb2"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c582c0c06"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c33c98b23"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c74cdc164"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c7053c824"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803cc78ed19"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c57160ab4"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c6818dc16"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c38195dbe"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c95981b8"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1803c53535bd3"
>
>
> ### 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: 0xc3a8a5200>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xc3a8a5200>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xc3a8a5200>
> rowMedians(tmp)
[1] 0.0360233738 -0.0138507765 -0.0250585784 0.3069571221 -0.2149392772
[6] 0.0908853156 0.1888003139 -0.2588251359 0.0697194257 -0.5600191364
[11] 0.0623985204 -0.0310876006 -0.0892162968 0.2606595894 0.0321320670
[16] -0.2137342445 0.0024566891 -0.1385688752 0.1595725622 0.2460160055
[21] 0.6654466686 -0.0612450635 0.3942170806 -0.3751422622 -0.3933458625
[26] 0.3457336867 -0.0201271222 0.2046138188 -0.1336382365 0.1232917690
[31] 0.1792085278 0.1730737035 -0.0656742528 0.0955526777 0.1439390340
[36] -0.1138504483 0.0522446077 0.5945477692 -0.1922465242 0.2370565609
[41] -0.0193946960 0.2379736396 0.6774757839 0.0526863954 -0.5617967739
[46] 0.5421561420 0.5942143032 0.2429333673 -0.7371124689 -0.0154897614
[51] 0.3015197408 0.1672803587 -0.0946270307 0.1605251573 -0.3992048710
[56] 0.1102764949 -0.2900064746 0.0071776766 -0.4994264153 0.2387398946
[61] -0.2427637146 -0.0058070201 -0.4387501347 -0.0221814924 -0.3241736378
[66] -0.3500104801 -0.5254400374 0.1280877984 0.0910751429 0.2572550245
[71] 0.3423437858 -0.1156780768 -0.5928009386 -0.1118601203 0.3681720465
[76] -0.2148385381 -0.2566041003 -0.3242811826 -0.2941622113 0.5566543227
[81] 0.4449511422 -0.4865261910 -0.4957979561 0.1481049828 0.1178755577
[86] 0.1516612289 -0.1067790790 0.6787840128 0.1136201325 0.8584010962
[91] -0.4116617588 0.0812073773 -0.1949442361 -0.3606277024 -0.0908444214
[96] -0.8095473221 -0.2610162519 -0.1021630435 -0.1611581487 -0.3706553966
[101] -0.2370225841 -0.2323656860 -0.3376613844 -0.0238970309 -0.4201386623
[106] 0.6576248241 -0.1662059335 -0.0339531827 0.0009008526 0.4765418496
[111] -0.3701949998 -0.1017198959 -0.4389720072 -0.7050894393 -0.2853566012
[116] 0.1455362347 0.0134282556 -0.0275176064 0.0576394238 -0.2829722870
[121] 0.3252057429 0.1777938619 0.2836984400 0.6899415283 -0.0647310839
[126] 0.0814510272 -0.3590272972 0.0323481820 -0.3577991924 -0.2386916767
[131] 0.3644339465 0.2501535773 -0.1749567989 -0.2394663486 -0.1089546012
[136] 0.5426069164 -0.1243375444 0.0340535188 0.2820588300 -0.6451553272
[141] -0.4846834127 -0.1572082068 0.4347859587 -0.4568594613 0.0391832856
[146] 0.7403613278 0.2395158917 -0.1819373463 0.5014965330 -0.3560010598
[151] 0.1139295555 -0.0236312031 -0.2823496160 -0.1479048269 -0.3673176213
[156] -0.1607650797 -0.1015062596 -0.3004520714 -0.4778804863 0.0488947547
[161] 0.2143133301 0.1062977902 0.3237689288 0.2896136031 -0.3829582865
[166] -0.4464242482 0.0834024819 -0.3015655053 -0.1497610197 -0.1862127819
[171] -0.1483799200 -0.3808156394 0.6824967930 -0.0698829613 0.4366595225
[176] -0.0443865761 0.2744561217 0.0444605267 0.1659684368 0.1204355433
[181] -0.2218513524 0.1940496831 -0.0136680566 0.0294430832 -0.2849960499
[186] 0.5967577981 0.0369112232 0.1386160815 -0.3948430324 -0.8719957240
[191] 0.0298114451 -0.0651654766 0.6349926235 0.1769913994 -0.1952799665
[196] -0.1916828882 0.0137347811 0.3163749035 -0.2474729677 0.1007833665
[201] -0.1037999639 -0.0035838061 -0.0065074141 0.1186212995 0.4482921491
[206] 0.4212155991 -0.2599921252 -0.1295136967 0.4070882077 0.0788720757
[211] -0.3434498873 0.0516416969 0.3950229444 -0.5648091865 -0.3424317515
[216] -0.0675960717 -0.1406629754 -0.0342868450 0.3809386068 0.1158318684
[221] 0.4508230301 0.3188216629 -0.3694353778 0.2824130074 -0.1043836025
[226] 0.4481538850 0.4003989499 -0.1340280103 -0.2522665502 0.4769100054
>
> proc.time()
user system elapsed
0.726 4.819 5.641
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 Patched (2026-04-24 r89963) -- "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: 0x80f000000>
> .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: 0x80f000000>
> .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: 0x80f000000>
> .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: 0x80f000000>
> 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: 0x80f000060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f000060>
> .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: 0x80f000060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f000060>
> .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: 0x80f000060>
> 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: 0x80f000480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f000480>
> .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: 0x80f000480>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x80f000480>
> .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: 0x80f000480>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x80f000480>
> .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: 0x80f000480>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x80f000480>
> .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: 0x80f000480>
> 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: 0x80f0005a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x80f0005a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f0005a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f0005a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile183722c0452b6" "BufferedMatrixFile18372f20b3ec"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile183722c0452b6" "BufferedMatrixFile18372f20b3ec"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f0006c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f0006c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x80f0006c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x80f0006c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x80f0006c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x80f0006c0>
> .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: 0x80f000840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x80f000840>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x80f000840>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x80f000840>
> 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: 0x80f000960>
> .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: 0x80f000960>
> rm(P)
>
> proc.time()
user system elapsed
0.119 0.050 0.163
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 Patched (2026-04-24 r89963) -- "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
0.120 0.033 0.146