Ben Bolstad
| Snapshot Date: 2026-01-06 13:40 -0500 (Tue, 06 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 2026-01-07 11:35 -0500 (Wed, 07 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: 2026-01-06 18:47:18 -0500 (Tue, 06 Jan 2026) |
| EndedAt: 2026-01-06 18:47:38 -0500 (Tue, 06 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
0.126 0.048 0.180
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] "Tue Jan 6 18:47:28 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 Jan 6 18:47:29 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: 0x6000037283c0>
>
>
>
> 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 Jan 6 18:47:30 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 Jan 6 18:47:30 2026"
>
> ColMode(tmp2)
<pointer: 0x6000037283c0>
>
>
>
> ### 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,] 101.6401248 1.11051031 0.8862097 0.8362423
[2,] 0.2610693 -0.08020837 0.3552813 -0.6914642
[3,] 0.4787738 -0.41857280 -0.1504182 0.5615156
[4,] 0.9062313 -1.67983486 -0.6396683 -0.1630469
> 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,] 101.6401248 1.11051031 0.8862097 0.8362423
[2,] 0.2610693 0.08020837 0.3552813 0.6914642
[3,] 0.4787738 0.41857280 0.1504182 0.5615156
[4,] 0.9062313 1.67983486 0.6396683 0.1630469
> 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,] 10.0816727 1.0538075 0.9413871 0.9144629
[2,] 0.5109494 0.2832108 0.5960548 0.8315432
[3,] 0.6919348 0.6469720 0.3878379 0.7493434
[4,] 0.9519618 1.2960844 0.7997927 0.4037907
>
> 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,] 227.45685 36.64859 35.30008 34.98087
[2,] 30.37056 27.91232 31.31583 34.00690
[3,] 32.39812 31.88829 29.02880 33.05495
[4,] 35.42585 39.64068 33.63759 29.20095
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x60000371c000>
> exp(tmp5)
<pointer: 0x60000371c000>
> log(tmp5,2)
<pointer: 0x60000371c000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 473.4216
> Min(tmp5)
[1] 52.99437
> mean(tmp5)
[1] 73.07572
> Sum(tmp5)
[1] 14615.14
> Var(tmp5)
[1] 880.0031
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.29660 69.73929 71.45797 67.71158 71.42096 70.21117 69.42764 74.04298
[9] 71.97911 73.46989
> rowSums(tmp5)
[1] 1825.932 1394.786 1429.159 1354.232 1428.419 1404.223 1388.553 1480.860
[9] 1439.582 1469.398
> rowVars(tmp5)
[1] 8133.70531 59.45396 75.70030 71.94133 109.96830 89.67052
[7] 61.69582 73.55341 56.45086 62.55675
> rowSd(tmp5)
[1] 90.187057 7.710640 8.700592 8.481823 10.486577 9.469452 7.854669
[8] 8.576328 7.513379 7.909282
> rowMax(tmp5)
[1] 473.42164 83.03404 89.11241 82.50688 90.49238 85.66656 86.38078
[8] 96.41937 89.24703 83.73752
> rowMin(tmp5)
[1] 63.25616 55.37787 59.89964 52.99437 54.68931 54.14349 59.75087 64.14877
[9] 60.27036 56.27784
>
> colMeans(tmp5)
[1] 111.17507 72.47999 70.53205 67.48489 70.90403 69.93643 66.49925
[8] 69.76699 71.32047 67.88679 68.61057 76.02432 75.82455 71.86013
[15] 73.07950 73.39278 71.57919 72.14544 69.71364 71.29828
> colSums(tmp5)
[1] 1111.7507 724.7999 705.3205 674.8489 709.0403 699.3643 664.9925
[8] 697.6699 713.2047 678.8679 686.1057 760.2432 758.2455 718.6013
[15] 730.7950 733.9278 715.7919 721.4544 697.1364 712.9828
> colVars(tmp5)
[1] 16289.18328 104.73372 50.08656 16.26817 63.03888 178.07445
[7] 44.48952 57.79358 33.90082 75.86309 40.24565 64.82723
[13] 70.37190 65.19471 76.30007 36.23797 34.66107 84.19993
[19] 123.69113 122.29411
> colSd(tmp5)
[1] 127.629085 10.233950 7.077186 4.033382 7.939703 13.344454
[7] 6.670046 7.602209 5.822441 8.709942 6.343946 8.051536
[13] 8.388796 8.074324 8.734991 6.019798 5.887365 9.176052
[19] 11.121652 11.058667
> colMax(tmp5)
[1] 473.42164 87.26083 82.16693 72.80810 80.75930 96.41937 83.98050
[8] 80.22939 77.49205 79.09980 77.75652 88.00719 87.82634 84.83395
[15] 86.38078 83.03404 80.13045 87.57427 89.11241 85.36334
> colMin(tmp5)
[1] 56.27784 57.83805 60.41964 60.77796 54.86998 54.45567 60.27036 57.22622
[9] 61.21411 52.99437 60.76999 65.82800 63.51729 60.82819 64.62807 64.90887
[17] 63.51874 58.70598 54.68931 54.14349
>
>
> ### 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] 91.29660 69.73929 NA 67.71158 71.42096 70.21117 69.42764 74.04298
[9] 71.97911 73.46989
> rowSums(tmp5)
[1] 1825.932 1394.786 NA 1354.232 1428.419 1404.223 1388.553 1480.860
[9] 1439.582 1469.398
> rowVars(tmp5)
[1] 8133.70531 59.45396 79.23691 71.94133 109.96830 89.67052
[7] 61.69582 73.55341 56.45086 62.55675
> rowSd(tmp5)
[1] 90.187057 7.710640 8.901512 8.481823 10.486577 9.469452 7.854669
[8] 8.576328 7.513379 7.909282
> rowMax(tmp5)
[1] 473.42164 83.03404 NA 82.50688 90.49238 85.66656 86.38078
[8] 96.41937 89.24703 83.73752
> rowMin(tmp5)
[1] 63.25616 55.37787 NA 52.99437 54.68931 54.14349 59.75087 64.14877
[9] 60.27036 56.27784
>
> colMeans(tmp5)
[1] 111.17507 72.47999 70.53205 67.48489 70.90403 69.93643 66.49925
[8] 69.76699 71.32047 NA 68.61057 76.02432 75.82455 71.86013
[15] 73.07950 73.39278 71.57919 72.14544 69.71364 71.29828
> colSums(tmp5)
[1] 1111.7507 724.7999 705.3205 674.8489 709.0403 699.3643 664.9925
[8] 697.6699 713.2047 NA 686.1057 760.2432 758.2455 718.6013
[15] 730.7950 733.9278 715.7919 721.4544 697.1364 712.9828
> colVars(tmp5)
[1] 16289.18328 104.73372 50.08656 16.26817 63.03888 178.07445
[7] 44.48952 57.79358 33.90082 NA 40.24565 64.82723
[13] 70.37190 65.19471 76.30007 36.23797 34.66107 84.19993
[19] 123.69113 122.29411
> colSd(tmp5)
[1] 127.629085 10.233950 7.077186 4.033382 7.939703 13.344454
[7] 6.670046 7.602209 5.822441 NA 6.343946 8.051536
[13] 8.388796 8.074324 8.734991 6.019798 5.887365 9.176052
[19] 11.121652 11.058667
> colMax(tmp5)
[1] 473.42164 87.26083 82.16693 72.80810 80.75930 96.41937 83.98050
[8] 80.22939 77.49205 NA 77.75652 88.00719 87.82634 84.83395
[15] 86.38078 83.03404 80.13045 87.57427 89.11241 85.36334
> colMin(tmp5)
[1] 56.27784 57.83805 60.41964 60.77796 54.86998 54.45567 60.27036 57.22622
[9] 61.21411 NA 60.76999 65.82800 63.51729 60.82819 64.62807 64.90887
[17] 63.51874 58.70598 54.68931 54.14349
>
> Max(tmp5,na.rm=TRUE)
[1] 473.4216
> Min(tmp5,na.rm=TRUE)
[1] 52.99437
> mean(tmp5,na.rm=TRUE)
[1] 73.06685
> Sum(tmp5,na.rm=TRUE)
[1] 14540.3
> Var(tmp5,na.rm=TRUE)
[1] 884.4318
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.29660 69.73929 71.27996 67.71158 71.42096 70.21117 69.42764 74.04298
[9] 71.97911 73.46989
> rowSums(tmp5,na.rm=TRUE)
[1] 1825.932 1394.786 1354.319 1354.232 1428.419 1404.223 1388.553 1480.860
[9] 1439.582 1469.398
> rowVars(tmp5,na.rm=TRUE)
[1] 8133.70531 59.45396 79.23691 71.94133 109.96830 89.67052
[7] 61.69582 73.55341 56.45086 62.55675
> rowSd(tmp5,na.rm=TRUE)
[1] 90.187057 7.710640 8.901512 8.481823 10.486577 9.469452 7.854669
[8] 8.576328 7.513379 7.909282
> rowMax(tmp5,na.rm=TRUE)
[1] 473.42164 83.03404 89.11241 82.50688 90.49238 85.66656 86.38078
[8] 96.41937 89.24703 83.73752
> rowMin(tmp5,na.rm=TRUE)
[1] 63.25616 55.37787 59.89964 52.99437 54.68931 54.14349 59.75087 64.14877
[9] 60.27036 56.27784
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.17507 72.47999 70.53205 67.48489 70.90403 69.93643 66.49925
[8] 69.76699 71.32047 67.11419 68.61057 76.02432 75.82455 71.86013
[15] 73.07950 73.39278 71.57919 72.14544 69.71364 71.29828
> colSums(tmp5,na.rm=TRUE)
[1] 1111.7507 724.7999 705.3205 674.8489 709.0403 699.3643 664.9925
[8] 697.6699 713.2047 604.0277 686.1057 760.2432 758.2455 718.6013
[15] 730.7950 733.9278 715.7919 721.4544 697.1364 712.9828
> colVars(tmp5,na.rm=TRUE)
[1] 16289.18328 104.73372 50.08656 16.26817 63.03888 178.07445
[7] 44.48952 57.79358 33.90082 78.63076 40.24565 64.82723
[13] 70.37190 65.19471 76.30007 36.23797 34.66107 84.19993
[19] 123.69113 122.29411
> colSd(tmp5,na.rm=TRUE)
[1] 127.629085 10.233950 7.077186 4.033382 7.939703 13.344454
[7] 6.670046 7.602209 5.822441 8.867399 6.343946 8.051536
[13] 8.388796 8.074324 8.734991 6.019798 5.887365 9.176052
[19] 11.121652 11.058667
> colMax(tmp5,na.rm=TRUE)
[1] 473.42164 87.26083 82.16693 72.80810 80.75930 96.41937 83.98050
[8] 80.22939 77.49205 79.09980 77.75652 88.00719 87.82634 84.83395
[15] 86.38078 83.03404 80.13045 87.57427 89.11241 85.36334
> colMin(tmp5,na.rm=TRUE)
[1] 56.27784 57.83805 60.41964 60.77796 54.86998 54.45567 60.27036 57.22622
[9] 61.21411 52.99437 60.76999 65.82800 63.51729 60.82819 64.62807 64.90887
[17] 63.51874 58.70598 54.68931 54.14349
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.29660 69.73929 NaN 67.71158 71.42096 70.21117 69.42764 74.04298
[9] 71.97911 73.46989
> rowSums(tmp5,na.rm=TRUE)
[1] 1825.932 1394.786 0.000 1354.232 1428.419 1404.223 1388.553 1480.860
[9] 1439.582 1469.398
> rowVars(tmp5,na.rm=TRUE)
[1] 8133.70531 59.45396 NA 71.94133 109.96830 89.67052
[7] 61.69582 73.55341 56.45086 62.55675
> rowSd(tmp5,na.rm=TRUE)
[1] 90.187057 7.710640 NA 8.481823 10.486577 9.469452 7.854669
[8] 8.576328 7.513379 7.909282
> rowMax(tmp5,na.rm=TRUE)
[1] 473.42164 83.03404 NA 82.50688 90.49238 85.66656 86.38078
[8] 96.41937 89.24703 83.73752
> rowMin(tmp5,na.rm=TRUE)
[1] 63.25616 55.37787 NA 52.99437 54.68931 54.14349 59.75087 64.14877
[9] 60.27036 56.27784
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.03536 73.15873 71.65565 67.33882 69.80900 71.05163 66.56634
[8] 70.33856 71.17874 NaN 69.26695 75.70770 75.76819 73.08590
[15] 73.43816 74.09844 71.25600 70.43113 67.55822 70.25166
> colSums(tmp5,na.rm=TRUE)
[1] 1044.3182 658.4286 644.9008 606.0494 628.2810 639.4647 599.0970
[8] 633.0470 640.6086 0.0000 623.4025 681.3693 681.9137 657.7731
[15] 660.9435 666.8859 641.3040 633.8801 608.0240 632.2650
> colVars(tmp5,na.rm=TRUE)
[1] 18059.57882 112.64265 42.14448 18.06165 57.42895 186.34247
[7] 50.00008 61.34259 37.91243 NA 40.42952 71.80280
[13] 79.13265 56.44078 84.39036 35.16578 37.81866 61.66258
[19] 86.88695 125.25761
> colSd(tmp5,na.rm=TRUE)
[1] 134.385932 10.613324 6.491878 4.249900 7.578189 13.650731
[7] 7.071073 7.832151 6.157307 NA 6.358421 8.473653
[13] 8.895653 7.512708 9.186423 5.930074 6.149688 7.852552
[19] 9.321317 11.191855
> colMax(tmp5,na.rm=TRUE)
[1] 473.42164 87.26083 82.16693 72.80810 78.37478 96.41937 83.98050
[8] 80.22939 77.49205 -Inf 77.75652 88.00719 87.82634 84.83395
[15] 86.38078 83.03404 80.13045 79.87305 81.90459 85.36334
> colMin(tmp5,na.rm=TRUE)
[1] 56.27784 57.83805 62.98027 60.77796 54.86998 54.45567 60.27036 57.22622
[9] 61.21411 Inf 60.76999 65.82800 63.51729 61.70242 64.62807 64.90887
[17] 63.51874 58.70598 54.68931 54.14349
>
>
>
>
> 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] 137.9843 124.1777 273.0245 256.9099 190.1657 155.8861 290.0415 270.3526
[9] 255.2822 265.2940
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 137.9843 124.1777 273.0245 256.9099 190.1657 155.8861 290.0415 270.3526
[9] 255.2822 265.2940
>
>
>
> 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] 5.684342e-14 5.684342e-14 0.000000e+00 -2.842171e-14 1.705303e-13
[6] 3.410605e-13 1.136868e-13 0.000000e+00 0.000000e+00 -2.842171e-14
[11] -8.526513e-14 8.526513e-14 -1.421085e-14 1.136868e-13 -1.136868e-13
[16] 0.000000e+00 0.000000e+00 -2.842171e-14 -2.842171e-14 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
7 20
9 17
8 15
6 7
3 8
2 19
4 5
10 5
9 9
4 10
6 10
5 9
4 14
9 7
9 17
5 12
5 12
9 16
7 16
4 11
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] 1.653027
> Min(tmp)
[1] -2.544749
> mean(tmp)
[1] -0.1243604
> Sum(tmp)
[1] -12.43604
> Var(tmp)
[1] 0.6715065
>
> rowMeans(tmp)
[1] -0.1243604
> rowSums(tmp)
[1] -12.43604
> rowVars(tmp)
[1] 0.6715065
> rowSd(tmp)
[1] 0.819455
> rowMax(tmp)
[1] 1.653027
> rowMin(tmp)
[1] -2.544749
>
> colMeans(tmp)
[1] -0.06242986 -0.46785191 -0.71360384 0.83007225 -0.32119713 -0.17508756
[7] -1.33861348 -0.04528879 -0.65546204 -0.06705714 0.79548662 -0.48993213
[13] -0.35154523 -0.23915353 0.36569402 0.09345848 -0.06355175 0.13046402
[19] -1.48300537 -0.07925016 -0.02713740 1.29418685 0.68288627 -0.48633087
[25] -0.31788729 0.22551261 1.19335627 -0.50308165 -0.02357080 -0.56733744
[31] 1.53855292 0.03963452 0.12616335 1.49735200 0.51370319 0.36295193
[37] -0.21221272 -1.86955969 0.51486300 -0.42469607 -1.60572189 -0.05731052
[43] 0.61234759 -0.67940728 1.65302692 -1.70402273 0.22843427 -0.03149856
[49] -0.02280199 -1.05834155 1.21517978 0.92107909 -0.39883904 0.43505796
[55] 1.10328527 -0.99378923 1.15502229 -0.06115204 -0.35545111 -1.18177484
[61] -0.01287985 -0.80846518 0.20293448 -0.11824539 -1.01323333 -0.76676443
[67] 1.25858066 -0.72217848 0.82142771 -0.42196599 1.15164431 -0.61875154
[73] -1.53720329 -0.26358740 -0.65409076 -1.36821976 -0.23759201 -2.54474906
[79] -0.05609031 -0.17484422 -0.62540222 -0.38979336 0.47483938 -0.72486434
[85] 0.95823394 -1.25554849 0.26205787 -0.49108255 0.10927208 -0.90642765
[91] -0.12861178 1.08468525 -0.62503676 -1.39722826 0.94907280 0.38621355
[97] -0.38092710 0.75007245 -0.88808404 -0.10602484
> colSums(tmp)
[1] -0.06242986 -0.46785191 -0.71360384 0.83007225 -0.32119713 -0.17508756
[7] -1.33861348 -0.04528879 -0.65546204 -0.06705714 0.79548662 -0.48993213
[13] -0.35154523 -0.23915353 0.36569402 0.09345848 -0.06355175 0.13046402
[19] -1.48300537 -0.07925016 -0.02713740 1.29418685 0.68288627 -0.48633087
[25] -0.31788729 0.22551261 1.19335627 -0.50308165 -0.02357080 -0.56733744
[31] 1.53855292 0.03963452 0.12616335 1.49735200 0.51370319 0.36295193
[37] -0.21221272 -1.86955969 0.51486300 -0.42469607 -1.60572189 -0.05731052
[43] 0.61234759 -0.67940728 1.65302692 -1.70402273 0.22843427 -0.03149856
[49] -0.02280199 -1.05834155 1.21517978 0.92107909 -0.39883904 0.43505796
[55] 1.10328527 -0.99378923 1.15502229 -0.06115204 -0.35545111 -1.18177484
[61] -0.01287985 -0.80846518 0.20293448 -0.11824539 -1.01323333 -0.76676443
[67] 1.25858066 -0.72217848 0.82142771 -0.42196599 1.15164431 -0.61875154
[73] -1.53720329 -0.26358740 -0.65409076 -1.36821976 -0.23759201 -2.54474906
[79] -0.05609031 -0.17484422 -0.62540222 -0.38979336 0.47483938 -0.72486434
[85] 0.95823394 -1.25554849 0.26205787 -0.49108255 0.10927208 -0.90642765
[91] -0.12861178 1.08468525 -0.62503676 -1.39722826 0.94907280 0.38621355
[97] -0.38092710 0.75007245 -0.88808404 -0.10602484
> 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] -0.06242986 -0.46785191 -0.71360384 0.83007225 -0.32119713 -0.17508756
[7] -1.33861348 -0.04528879 -0.65546204 -0.06705714 0.79548662 -0.48993213
[13] -0.35154523 -0.23915353 0.36569402 0.09345848 -0.06355175 0.13046402
[19] -1.48300537 -0.07925016 -0.02713740 1.29418685 0.68288627 -0.48633087
[25] -0.31788729 0.22551261 1.19335627 -0.50308165 -0.02357080 -0.56733744
[31] 1.53855292 0.03963452 0.12616335 1.49735200 0.51370319 0.36295193
[37] -0.21221272 -1.86955969 0.51486300 -0.42469607 -1.60572189 -0.05731052
[43] 0.61234759 -0.67940728 1.65302692 -1.70402273 0.22843427 -0.03149856
[49] -0.02280199 -1.05834155 1.21517978 0.92107909 -0.39883904 0.43505796
[55] 1.10328527 -0.99378923 1.15502229 -0.06115204 -0.35545111 -1.18177484
[61] -0.01287985 -0.80846518 0.20293448 -0.11824539 -1.01323333 -0.76676443
[67] 1.25858066 -0.72217848 0.82142771 -0.42196599 1.15164431 -0.61875154
[73] -1.53720329 -0.26358740 -0.65409076 -1.36821976 -0.23759201 -2.54474906
[79] -0.05609031 -0.17484422 -0.62540222 -0.38979336 0.47483938 -0.72486434
[85] 0.95823394 -1.25554849 0.26205787 -0.49108255 0.10927208 -0.90642765
[91] -0.12861178 1.08468525 -0.62503676 -1.39722826 0.94907280 0.38621355
[97] -0.38092710 0.75007245 -0.88808404 -0.10602484
> colMin(tmp)
[1] -0.06242986 -0.46785191 -0.71360384 0.83007225 -0.32119713 -0.17508756
[7] -1.33861348 -0.04528879 -0.65546204 -0.06705714 0.79548662 -0.48993213
[13] -0.35154523 -0.23915353 0.36569402 0.09345848 -0.06355175 0.13046402
[19] -1.48300537 -0.07925016 -0.02713740 1.29418685 0.68288627 -0.48633087
[25] -0.31788729 0.22551261 1.19335627 -0.50308165 -0.02357080 -0.56733744
[31] 1.53855292 0.03963452 0.12616335 1.49735200 0.51370319 0.36295193
[37] -0.21221272 -1.86955969 0.51486300 -0.42469607 -1.60572189 -0.05731052
[43] 0.61234759 -0.67940728 1.65302692 -1.70402273 0.22843427 -0.03149856
[49] -0.02280199 -1.05834155 1.21517978 0.92107909 -0.39883904 0.43505796
[55] 1.10328527 -0.99378923 1.15502229 -0.06115204 -0.35545111 -1.18177484
[61] -0.01287985 -0.80846518 0.20293448 -0.11824539 -1.01323333 -0.76676443
[67] 1.25858066 -0.72217848 0.82142771 -0.42196599 1.15164431 -0.61875154
[73] -1.53720329 -0.26358740 -0.65409076 -1.36821976 -0.23759201 -2.54474906
[79] -0.05609031 -0.17484422 -0.62540222 -0.38979336 0.47483938 -0.72486434
[85] 0.95823394 -1.25554849 0.26205787 -0.49108255 0.10927208 -0.90642765
[91] -0.12861178 1.08468525 -0.62503676 -1.39722826 0.94907280 0.38621355
[97] -0.38092710 0.75007245 -0.88808404 -0.10602484
> colMedians(tmp)
[1] -0.06242986 -0.46785191 -0.71360384 0.83007225 -0.32119713 -0.17508756
[7] -1.33861348 -0.04528879 -0.65546204 -0.06705714 0.79548662 -0.48993213
[13] -0.35154523 -0.23915353 0.36569402 0.09345848 -0.06355175 0.13046402
[19] -1.48300537 -0.07925016 -0.02713740 1.29418685 0.68288627 -0.48633087
[25] -0.31788729 0.22551261 1.19335627 -0.50308165 -0.02357080 -0.56733744
[31] 1.53855292 0.03963452 0.12616335 1.49735200 0.51370319 0.36295193
[37] -0.21221272 -1.86955969 0.51486300 -0.42469607 -1.60572189 -0.05731052
[43] 0.61234759 -0.67940728 1.65302692 -1.70402273 0.22843427 -0.03149856
[49] -0.02280199 -1.05834155 1.21517978 0.92107909 -0.39883904 0.43505796
[55] 1.10328527 -0.99378923 1.15502229 -0.06115204 -0.35545111 -1.18177484
[61] -0.01287985 -0.80846518 0.20293448 -0.11824539 -1.01323333 -0.76676443
[67] 1.25858066 -0.72217848 0.82142771 -0.42196599 1.15164431 -0.61875154
[73] -1.53720329 -0.26358740 -0.65409076 -1.36821976 -0.23759201 -2.54474906
[79] -0.05609031 -0.17484422 -0.62540222 -0.38979336 0.47483938 -0.72486434
[85] 0.95823394 -1.25554849 0.26205787 -0.49108255 0.10927208 -0.90642765
[91] -0.12861178 1.08468525 -0.62503676 -1.39722826 0.94907280 0.38621355
[97] -0.38092710 0.75007245 -0.88808404 -0.10602484
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.06242986 -0.4678519 -0.7136038 0.8300723 -0.3211971 -0.1750876
[2,] -0.06242986 -0.4678519 -0.7136038 0.8300723 -0.3211971 -0.1750876
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.338613 -0.04528879 -0.655462 -0.06705714 0.7954866 -0.4899321
[2,] -1.338613 -0.04528879 -0.655462 -0.06705714 0.7954866 -0.4899321
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
[1,] -0.3515452 -0.2391535 0.365694 0.09345848 -0.06355175 0.130464 -1.483005
[2,] -0.3515452 -0.2391535 0.365694 0.09345848 -0.06355175 0.130464 -1.483005
[,20] [,21] [,22] [,23] [,24] [,25] [,26]
[1,] -0.07925016 -0.0271374 1.294187 0.6828863 -0.4863309 -0.3178873 0.2255126
[2,] -0.07925016 -0.0271374 1.294187 0.6828863 -0.4863309 -0.3178873 0.2255126
[,27] [,28] [,29] [,30] [,31] [,32] [,33]
[1,] 1.193356 -0.5030816 -0.0235708 -0.5673374 1.538553 0.03963452 0.1261634
[2,] 1.193356 -0.5030816 -0.0235708 -0.5673374 1.538553 0.03963452 0.1261634
[,34] [,35] [,36] [,37] [,38] [,39] [,40]
[1,] 1.497352 0.5137032 0.3629519 -0.2122127 -1.86956 0.514863 -0.4246961
[2,] 1.497352 0.5137032 0.3629519 -0.2122127 -1.86956 0.514863 -0.4246961
[,41] [,42] [,43] [,44] [,45] [,46] [,47]
[1,] -1.605722 -0.05731052 0.6123476 -0.6794073 1.653027 -1.704023 0.2284343
[2,] -1.605722 -0.05731052 0.6123476 -0.6794073 1.653027 -1.704023 0.2284343
[,48] [,49] [,50] [,51] [,52] [,53] [,54]
[1,] -0.03149856 -0.02280199 -1.058342 1.21518 0.9210791 -0.398839 0.435058
[2,] -0.03149856 -0.02280199 -1.058342 1.21518 0.9210791 -0.398839 0.435058
[,55] [,56] [,57] [,58] [,59] [,60] [,61]
[1,] 1.103285 -0.9937892 1.155022 -0.06115204 -0.3554511 -1.181775 -0.01287985
[2,] 1.103285 -0.9937892 1.155022 -0.06115204 -0.3554511 -1.181775 -0.01287985
[,62] [,63] [,64] [,65] [,66] [,67] [,68]
[1,] -0.8084652 0.2029345 -0.1182454 -1.013233 -0.7667644 1.258581 -0.7221785
[2,] -0.8084652 0.2029345 -0.1182454 -1.013233 -0.7667644 1.258581 -0.7221785
[,69] [,70] [,71] [,72] [,73] [,74] [,75]
[1,] 0.8214277 -0.421966 1.151644 -0.6187515 -1.537203 -0.2635874 -0.6540908
[2,] 0.8214277 -0.421966 1.151644 -0.6187515 -1.537203 -0.2635874 -0.6540908
[,76] [,77] [,78] [,79] [,80] [,81] [,82]
[1,] -1.36822 -0.237592 -2.544749 -0.05609031 -0.1748442 -0.6254022 -0.3897934
[2,] -1.36822 -0.237592 -2.544749 -0.05609031 -0.1748442 -0.6254022 -0.3897934
[,83] [,84] [,85] [,86] [,87] [,88] [,89]
[1,] 0.4748394 -0.7248643 0.9582339 -1.255548 0.2620579 -0.4910825 0.1092721
[2,] 0.4748394 -0.7248643 0.9582339 -1.255548 0.2620579 -0.4910825 0.1092721
[,90] [,91] [,92] [,93] [,94] [,95] [,96]
[1,] -0.9064276 -0.1286118 1.084685 -0.6250368 -1.397228 0.9490728 0.3862135
[2,] -0.9064276 -0.1286118 1.084685 -0.6250368 -1.397228 0.9490728 0.3862135
[,97] [,98] [,99] [,100]
[1,] -0.3809271 0.7500724 -0.888084 -0.1060248
[2,] -0.3809271 0.7500724 -0.888084 -0.1060248
>
>
> Max(tmp2)
[1] 2.110378
> Min(tmp2)
[1] -2.182348
> mean(tmp2)
[1] -0.04659317
> Sum(tmp2)
[1] -4.659317
> Var(tmp2)
[1] 0.9925512
>
> rowMeans(tmp2)
[1] 0.1884819857 -2.0238324811 0.2059937019 -1.2509458117 -1.2632085030
[6] -1.7877718875 -1.0806332896 0.8217931700 1.5965387991 1.1724398905
[11] -0.1263971314 0.6321419346 -0.4717186400 -0.1590052525 1.0858979422
[16] -0.8915978764 0.2090836448 0.4345853572 0.7294609840 -0.2523531636
[21] -0.0216608460 -1.8347442308 1.2016221549 0.7359828762 1.5837507782
[26] 1.0803008957 -0.8875845129 -2.1823476100 -1.5008174430 -0.6044143045
[31] -0.1265805589 1.4757728140 0.1321994309 0.3886021143 0.1503259865
[36] 0.1232451057 -0.4409758771 -0.6341906651 2.1103775231 1.1465132884
[41] 0.6430418858 -0.2857641316 -0.9391320375 1.3028305042 -0.6388895360
[46] -1.3053044077 -1.7164919271 0.0366097737 0.0436718044 -0.9491200412
[51] 0.0005231818 0.2763005306 1.3701791518 -2.0623420301 -1.6054839657
[56] 1.4349919470 -0.9569220241 0.7894081627 0.7754109545 0.2237994981
[61] 0.2848456257 -0.3794089988 0.8445195075 -0.3570036058 -0.6016057802
[66] -0.1933139018 0.2624405753 0.9063776227 -0.4049932586 -0.0064611036
[71] -0.6846770684 -0.5079665567 -0.7458854414 0.8007270236 0.0545955613
[76] -1.8248877515 1.1632143773 1.0548606544 -2.0223630839 -0.1273134630
[81] 0.4995346261 -0.5093539304 0.4731411170 -0.5423098602 -1.0928850388
[86] -0.1477981250 1.5638856597 0.0623925398 0.1032706059 1.3486780858
[91] -0.1081709378 1.7888077935 -0.8371460057 0.2870339261 -1.0829425162
[96] -0.0243655306 1.0291549098 0.8827279575 -1.6431224105 -0.3271979104
> rowSums(tmp2)
[1] 0.1884819857 -2.0238324811 0.2059937019 -1.2509458117 -1.2632085030
[6] -1.7877718875 -1.0806332896 0.8217931700 1.5965387991 1.1724398905
[11] -0.1263971314 0.6321419346 -0.4717186400 -0.1590052525 1.0858979422
[16] -0.8915978764 0.2090836448 0.4345853572 0.7294609840 -0.2523531636
[21] -0.0216608460 -1.8347442308 1.2016221549 0.7359828762 1.5837507782
[26] 1.0803008957 -0.8875845129 -2.1823476100 -1.5008174430 -0.6044143045
[31] -0.1265805589 1.4757728140 0.1321994309 0.3886021143 0.1503259865
[36] 0.1232451057 -0.4409758771 -0.6341906651 2.1103775231 1.1465132884
[41] 0.6430418858 -0.2857641316 -0.9391320375 1.3028305042 -0.6388895360
[46] -1.3053044077 -1.7164919271 0.0366097737 0.0436718044 -0.9491200412
[51] 0.0005231818 0.2763005306 1.3701791518 -2.0623420301 -1.6054839657
[56] 1.4349919470 -0.9569220241 0.7894081627 0.7754109545 0.2237994981
[61] 0.2848456257 -0.3794089988 0.8445195075 -0.3570036058 -0.6016057802
[66] -0.1933139018 0.2624405753 0.9063776227 -0.4049932586 -0.0064611036
[71] -0.6846770684 -0.5079665567 -0.7458854414 0.8007270236 0.0545955613
[76] -1.8248877515 1.1632143773 1.0548606544 -2.0223630839 -0.1273134630
[81] 0.4995346261 -0.5093539304 0.4731411170 -0.5423098602 -1.0928850388
[86] -0.1477981250 1.5638856597 0.0623925398 0.1032706059 1.3486780858
[91] -0.1081709378 1.7888077935 -0.8371460057 0.2870339261 -1.0829425162
[96] -0.0243655306 1.0291549098 0.8827279575 -1.6431224105 -0.3271979104
> 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] 0.1884819857 -2.0238324811 0.2059937019 -1.2509458117 -1.2632085030
[6] -1.7877718875 -1.0806332896 0.8217931700 1.5965387991 1.1724398905
[11] -0.1263971314 0.6321419346 -0.4717186400 -0.1590052525 1.0858979422
[16] -0.8915978764 0.2090836448 0.4345853572 0.7294609840 -0.2523531636
[21] -0.0216608460 -1.8347442308 1.2016221549 0.7359828762 1.5837507782
[26] 1.0803008957 -0.8875845129 -2.1823476100 -1.5008174430 -0.6044143045
[31] -0.1265805589 1.4757728140 0.1321994309 0.3886021143 0.1503259865
[36] 0.1232451057 -0.4409758771 -0.6341906651 2.1103775231 1.1465132884
[41] 0.6430418858 -0.2857641316 -0.9391320375 1.3028305042 -0.6388895360
[46] -1.3053044077 -1.7164919271 0.0366097737 0.0436718044 -0.9491200412
[51] 0.0005231818 0.2763005306 1.3701791518 -2.0623420301 -1.6054839657
[56] 1.4349919470 -0.9569220241 0.7894081627 0.7754109545 0.2237994981
[61] 0.2848456257 -0.3794089988 0.8445195075 -0.3570036058 -0.6016057802
[66] -0.1933139018 0.2624405753 0.9063776227 -0.4049932586 -0.0064611036
[71] -0.6846770684 -0.5079665567 -0.7458854414 0.8007270236 0.0545955613
[76] -1.8248877515 1.1632143773 1.0548606544 -2.0223630839 -0.1273134630
[81] 0.4995346261 -0.5093539304 0.4731411170 -0.5423098602 -1.0928850388
[86] -0.1477981250 1.5638856597 0.0623925398 0.1032706059 1.3486780858
[91] -0.1081709378 1.7888077935 -0.8371460057 0.2870339261 -1.0829425162
[96] -0.0243655306 1.0291549098 0.8827279575 -1.6431224105 -0.3271979104
> rowMin(tmp2)
[1] 0.1884819857 -2.0238324811 0.2059937019 -1.2509458117 -1.2632085030
[6] -1.7877718875 -1.0806332896 0.8217931700 1.5965387991 1.1724398905
[11] -0.1263971314 0.6321419346 -0.4717186400 -0.1590052525 1.0858979422
[16] -0.8915978764 0.2090836448 0.4345853572 0.7294609840 -0.2523531636
[21] -0.0216608460 -1.8347442308 1.2016221549 0.7359828762 1.5837507782
[26] 1.0803008957 -0.8875845129 -2.1823476100 -1.5008174430 -0.6044143045
[31] -0.1265805589 1.4757728140 0.1321994309 0.3886021143 0.1503259865
[36] 0.1232451057 -0.4409758771 -0.6341906651 2.1103775231 1.1465132884
[41] 0.6430418858 -0.2857641316 -0.9391320375 1.3028305042 -0.6388895360
[46] -1.3053044077 -1.7164919271 0.0366097737 0.0436718044 -0.9491200412
[51] 0.0005231818 0.2763005306 1.3701791518 -2.0623420301 -1.6054839657
[56] 1.4349919470 -0.9569220241 0.7894081627 0.7754109545 0.2237994981
[61] 0.2848456257 -0.3794089988 0.8445195075 -0.3570036058 -0.6016057802
[66] -0.1933139018 0.2624405753 0.9063776227 -0.4049932586 -0.0064611036
[71] -0.6846770684 -0.5079665567 -0.7458854414 0.8007270236 0.0545955613
[76] -1.8248877515 1.1632143773 1.0548606544 -2.0223630839 -0.1273134630
[81] 0.4995346261 -0.5093539304 0.4731411170 -0.5423098602 -1.0928850388
[86] -0.1477981250 1.5638856597 0.0623925398 0.1032706059 1.3486780858
[91] -0.1081709378 1.7888077935 -0.8371460057 0.2870339261 -1.0829425162
[96] -0.0243655306 1.0291549098 0.8827279575 -1.6431224105 -0.3271979104
>
> colMeans(tmp2)
[1] -0.04659317
> colSums(tmp2)
[1] -4.659317
> colVars(tmp2)
[1] 0.9925512
> colSd(tmp2)
[1] 0.9962686
> colMax(tmp2)
[1] 2.110378
> colMin(tmp2)
[1] -2.182348
> colMedians(tmp2)
[1] -0.002968961
> colRanges(tmp2)
[,1]
[1,] -2.182348
[2,] 2.110378
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.9608133 0.3556962 -3.0815883 -0.1104896 4.4161871 -1.0761093
[7] 1.5271690 2.7071727 -1.7555600 -4.4188696
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8559152
[2,] -0.3723538
[3,] 0.1318498
[4,] 0.6909107
[5,] 1.8428191
>
> rowApply(tmp,sum)
[1] 3.6628523 4.7280271 -1.5779774 1.8750563 -2.1729998 -1.9591357
[7] -6.4480952 -0.9057743 4.8881224 -1.5656541
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 1 9 8 8 2 8 8 10 1
[2,] 6 5 10 9 9 1 2 4 5 4
[3,] 8 6 3 1 6 7 1 2 9 6
[4,] 5 2 7 7 2 9 3 5 6 7
[5,] 10 10 1 6 10 4 5 9 8 2
[6,] 7 3 4 5 3 5 4 10 2 5
[7,] 4 9 8 3 4 3 10 7 7 10
[8,] 9 4 6 10 5 8 7 3 4 8
[9,] 2 7 5 2 7 10 9 1 1 9
[10,] 1 8 2 4 1 6 6 6 3 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.76193918 1.26408801 -0.28731263 1.48175216 -2.23498345 1.02212076
[7] 2.69673992 2.39414243 -0.18084734 -3.87071144 0.24483728 -1.48887728
[13] 1.10480107 -1.21137249 0.59905853 0.70929528 0.07680996 -0.51596222
[19] -0.69625948 -2.93916149
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2056599
[2,] -0.5253358
[3,] -0.5085974
[4,] -0.1151895
[5,] 1.5928435
>
> rowApply(tmp,sum)
[1] 0.9805033 0.5192458 -6.6032061 2.8211994 -0.3115240
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 8 9 1 19
[2,] 19 10 1 18 13
[3,] 10 20 13 4 5
[4,] 12 17 5 19 9
[5,] 20 1 3 15 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.5085974 1.7222159 -0.2546710 0.1536751 1.779930 0.6664393
[2,] -0.1151895 0.0519424 1.6445601 0.9100297 -1.887369 1.1141120
[3,] -0.5253358 -2.3629706 0.2062114 -1.0839435 -1.936894 -0.7621825
[4,] -1.2056599 1.5360148 -1.0193859 1.6198042 1.202858 -0.4657180
[5,] 1.5928435 0.3168856 -0.8640273 -0.1178133 -1.393508 0.4694699
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.8167158 0.7087603 0.9046224 -1.5428208 1.1196579 -1.0241508
[2,] 0.7379002 0.7998678 0.4743644 -0.6175858 0.1573786 -1.6639464
[3,] 0.7881806 0.8552026 0.2288645 0.2655288 -0.7457944 -1.6849859
[4,] 1.3844386 -0.7414830 -1.1011265 -1.0880567 0.3394526 0.1932554
[5,] 0.6029363 0.7717947 -0.6875722 -0.8877770 -0.6258574 2.6909504
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.54433113 1.58576155 -0.8796010 -0.7430841 0.02600244 -0.77599610
[2,] 1.14935194 -0.66065480 -0.4589414 0.4695080 -0.03989897 -0.18891624
[3,] 0.03345958 -2.01864345 1.3559547 1.2302582 0.06558412 0.33938917
[4,] -0.14493958 -0.09792226 -0.1075731 1.6822112 0.03821079 -0.08375525
[5,] -0.47740199 -0.01991353 0.6892193 -1.9295979 -0.01308842 0.19331619
[,19] [,20]
[1,] -0.839131210 -0.8461244
[2,] -1.874922191 0.5176550
[3,] -0.001473976 -0.8496152
[4,] 1.218499915 -0.3379256
[5,] 0.800767978 -1.4231512
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.2625331 1.989236 0.01459735 -0.1696654 0.6068986 0.716908 0.03192492
col8 col9 col10 col11 col12 col13 col14
row1 0.9491953 -0.8035173 -1.217618 0.9243995 -0.6683356 0.3722245 -1.608555
col15 col16 col17 col18 col19 col20
row1 -2.31231 -0.6733268 -0.001302747 0.4133285 -0.4530977 0.2300348
> tmp[,"col10"]
col10
row1 -1.217617714
row2 -0.637269138
row3 -0.077622398
row4 0.006542681
row5 -0.970674148
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.2625331 1.9892362 0.01459735 -0.1696654 0.6068986 0.716908
row5 -1.2651523 -0.4798563 0.78353505 0.3105083 -0.5945232 -1.578233
col7 col8 col9 col10 col11 col12
row1 0.03192492 0.9491953 -0.8035173 -1.2176177 0.9243995 -0.6683356
row5 -0.44556268 -1.0966370 -1.0738005 -0.9706741 0.3991599 -0.4665659
col13 col14 col15 col16 col17 col18
row1 0.3722245 -1.608555 -2.3123105 -0.6733268 -0.001302747 0.4133285
row5 0.1098282 -1.351052 -0.6198727 1.0588102 -1.779432116 0.3644066
col19 col20
row1 -0.4530977 0.2300348
row5 -0.8657148 1.8501688
> tmp[,c("col6","col20")]
col6 col20
row1 0.7169080 0.2300348
row2 1.7789559 -0.7889470
row3 0.7264527 1.7169211
row4 -0.8643649 -0.2305928
row5 -1.5782331 1.8501688
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.716908 0.2300348
row5 -1.578233 1.8501688
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.47314 49.58314 49.08541 50.90371 50.60568 105.4279 50.21408 48.51694
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.03953 49.70704 49.99203 49.98069 50.07316 49.22723 49.56678 50.03449
col17 col18 col19 col20
row1 52.16392 49.68395 49.75134 105.2086
> tmp[,"col10"]
col10
row1 49.70704
row2 29.61177
row3 30.46811
row4 28.55963
row5 49.76955
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.47314 49.58314 49.08541 50.90371 50.60568 105.4279 50.21408 48.51694
row5 49.27077 50.08817 49.12152 48.67600 50.16528 105.3680 50.57839 48.58296
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.03953 49.70704 49.99203 49.98069 50.07316 49.22723 49.56678 50.03449
row5 48.46794 49.76955 50.37052 50.52775 50.09869 49.06422 49.81522 50.94169
col17 col18 col19 col20
row1 52.16392 49.68395 49.75134 105.2086
row5 50.43754 51.94619 52.31377 108.1595
> tmp[,c("col6","col20")]
col6 col20
row1 105.42795 105.20857
row2 75.85983 74.32833
row3 74.68431 75.51782
row4 76.17226 73.88610
row5 105.36804 108.15953
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4279 105.2086
row5 105.3680 108.1595
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4279 105.2086
row5 105.3680 108.1595
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.5488095
[2,] 1.1296674
[3,] 0.3561535
[4,] 0.5710878
[5,] 0.2178033
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.28781045 0.1060485
[2,] -2.11214445 -1.4939853
[3,] -1.82495263 -1.1309675
[4,] -0.73165646 0.2152684
[5,] -0.03034649 -0.3968134
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.3097948 -0.35521859
[2,] -1.5133933 -0.53796162
[3,] -0.3724413 1.08268775
[4,] 0.5957743 0.04689399
[5,] -0.7230811 -0.61479898
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3097948
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.3097948
[2,] -1.5133933
>
>
>
> 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 -0.3161594 1.226107 -0.6230269 1.4540240 1.1372459 1.12878367 -0.9586018
row1 0.2616145 1.207619 0.8349193 -0.6256123 -0.3339788 0.03875953 0.2117384
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.8760357 -0.6605616 -0.08562607 0.24165278 -0.853065 0.14400488
row1 -0.1398511 0.9539498 -1.11838094 0.07056922 -1.253088 -0.08218513
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.4832978 -0.1683984 0.3787778 0.3757082 -0.8956919 -0.6799405 0.2319965
row1 -0.6075305 0.8275501 0.8860962 0.1969926 1.2124719 0.7800022 -1.2659199
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.271744 -0.005470524 -0.9584194 1.835068 1.216838 -0.2036383 -0.6038341
[,8] [,9] [,10]
row2 -1.437569 1.168921 0.8574734
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.3106494 1.502376 -0.2267114 0.8844743 -1.06703 0.3685386 -1.229597
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.6150378 1.888135 0.4505707 -0.6535922 -0.9934476 0.01980878 -0.3839686
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4352086 1.287046 0.9892296 0.2712931 -1.425109 1.048488
>
>
> 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: 0x6000037285a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f7553863617"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f7510494ad8"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f753bd0b342"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f752a8d0bc"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f75191fe801"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f757db8a689"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f7565bdacda"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f7579f5065"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f756c571acb"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f754aa03cfe"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f755e046df8"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f7574cfe500"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f757cc39ee9"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f75ef612fd"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f753d58a7b7"
>
>
> ### 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: 0x60000372c240>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60000372c240>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60000372c240>
> rowMedians(tmp)
[1] -0.478848692 -0.234772328 0.170051888 0.120910072 0.116565762
[6] 0.277415578 -0.171810855 0.243189883 0.477655581 -0.324914216
[11] -0.137860460 0.370938254 0.767793547 -0.294490732 0.696480269
[16] 0.137119952 -0.092337376 0.123032487 -0.305144386 0.385624191
[21] -0.171762336 -0.397153770 0.347505004 0.634587448 0.189190472
[26] 0.211325688 -0.137256364 0.024880030 0.272072491 0.062074212
[31] 0.431631206 -0.593462635 -0.030429629 0.443703509 -0.158038605
[36] 0.189186871 -0.270835427 0.341973362 0.001268235 -0.357322509
[41] -0.519333763 0.151026858 -0.169820496 -0.313717487 0.432954755
[46] -0.562991789 0.008680617 -0.015220355 -0.596519785 0.199522945
[51] -0.045993169 0.137985927 0.125967230 0.095354319 0.413606717
[56] 0.374633114 -0.852001332 -0.559453963 -0.017912628 -0.154507538
[61] -0.094865734 0.143452109 -0.059297101 0.276743136 0.638302771
[66] 0.201802234 -0.180669716 -0.512180309 -0.249151817 0.342142232
[71] 0.079187889 -0.172528977 0.078498877 0.068792106 0.123823967
[76] 0.177775193 -0.233322910 -0.421607553 -0.208932973 -0.443590917
[81] 0.225803707 0.015496522 0.303476079 -0.064731779 0.071538770
[86] -0.096115433 0.005846497 -0.055714489 0.119687377 -0.137754950
[91] -0.034837190 0.225229577 0.018993828 -0.034083724 -0.154719294
[96] 0.207422758 0.183426113 0.034849034 0.179085215 0.184445859
[101] -0.112249769 0.651190427 0.183728940 -0.068866386 0.641053620
[106] 0.418798981 0.285837025 -0.322849479 0.465462177 -0.056482142
[111] -0.171583384 0.692394659 -0.051534732 -0.263147157 0.393203600
[116] 0.056366447 -0.490130843 0.167683732 0.214639328 -0.383993892
[121] 0.367620246 0.430400395 -0.745579977 -0.621014481 0.327065259
[126] -0.059664746 0.470845122 -0.260866328 0.047571192 0.071659867
[131] -0.035817427 0.109731453 -0.530592621 0.231692760 -0.419429565
[136] 0.563333850 0.307380877 -0.177203679 0.120845422 -0.465634927
[141] -0.067967136 0.425565881 0.182739537 0.384645101 0.001430534
[146] -0.057919788 -0.246958247 0.334938947 -0.274769532 0.188006169
[151] -0.304842687 0.559031247 -0.212207337 -0.046328554 -0.209864942
[156] -0.005196363 -0.078176661 0.240463817 -0.177308227 -0.039535441
[161] 0.476292059 -0.012803482 0.185423896 0.227908428 -0.008271598
[166] 0.120049597 -0.309530397 0.284666075 0.026276424 0.267915790
[171] -0.468285434 0.509119927 0.287842860 0.325402672 0.861665579
[176] -0.115916629 0.004439505 -0.319271329 0.052336129 -0.166580467
[181] -0.689310803 -0.190675566 0.705935590 -0.098984616 0.072917485
[186] -0.016308160 0.260504322 0.061189070 -0.202098497 0.158201509
[191] 0.034918519 -0.206994834 0.112368154 0.675493891 -0.003273225
[196] -0.097952066 0.198424710 0.064574876 0.310107952 -0.071286087
[201] 0.142995116 0.248392548 0.116348204 0.236422289 -0.550979229
[206] 0.247533414 -0.176888066 -0.382534166 -0.121886582 0.037069855
[211] 0.483054316 0.017564089 -0.231837363 0.218012436 -0.105038011
[216] -0.285351321 -0.320010991 0.083010782 -0.403134634 -0.695027146
[221] -0.177897433 0.145345437 0.106171798 0.244274452 -0.200114124
[226] -0.094848406 -0.473933308 -0.204141321 -0.019279800 -0.210977468
>
> proc.time()
user system elapsed
0.709 3.665 4.767
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: 0x600002eec000>
> .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: 0x600002eec000>
> .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: 0x600002eec000>
> .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: 0x600002eec000>
> 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: 0x600002ed80c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ed80c0>
> .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: 0x600002ed80c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ed80c0>
> .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: 0x600002ed80c0>
> 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: 0x600002ee8120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ee8120>
> .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: 0x600002ee8120>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002ee8120>
> .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: 0x600002ee8120>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600002ee8120>
> .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: 0x600002ee8120>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600002ee8120>
> .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: 0x600002ee8120>
> 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: 0x600002ec8000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002ec8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ec8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ec8000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile113b4128fb67c" "BufferedMatrixFile113b421bd4b22"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile113b4128fb67c" "BufferedMatrixFile113b421bd4b22"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ef0120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ef0120>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002ef0120>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002ef0120>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002ef0120>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002ef0120>
> .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: 0x600002ef8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002ef8000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002ef8000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002ef8000>
> 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: 0x600002ef8180>
> .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: 0x600002ef8180>
> rm(P)
>
> proc.time()
user system elapsed
0.158 0.069 0.222
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
0.130 0.033 0.159