Ben Bolstad
| Snapshot Date: 2026-01-01 13:40 -0500 (Thu, 01 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 2026-01-03 11:34 -0500 (Sat, 03 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" | 4809 |
| 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: 2026-01-01 18:48:02 -0500 (Thu, 01 Jan 2026) |
| EndedAt: 2026-01-01 18:48:20 -0500 (Thu, 01 Jan 2026) |
| EllapsedTime: 18.2 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_1.75.0.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
0.123 0.051 0.171
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] "Thu Jan 1 18:48:12 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] "Thu Jan 1 18:48:12 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: 0x600001fdc000>
>
>
>
> 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] "Thu Jan 1 18:48:13 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] "Thu Jan 1 18:48:14 2026"
>
> ColMode(tmp2)
<pointer: 0x600001fdc000>
>
>
>
> ### 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,] 101.835577 -0.8826831 0.3864951 0.1558966
[2,] 1.569680 -1.0866472 0.7623891 -0.3749379
[3,] -2.673990 -1.3973090 0.4401611 1.2719375
[4,] -1.805132 0.8694079 1.3958872 1.5522770
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.835577 0.8826831 0.3864951 0.1558966
[2,] 1.569680 1.0866472 0.7623891 0.3749379
[3,] 2.673990 1.3973090 0.4401611 1.2719375
[4,] 1.805132 0.8694079 1.3958872 1.5522770
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.091361 0.9395122 0.6216873 0.3948374
[2,] 1.252869 1.0424237 0.8731489 0.6123218
[3,] 1.635234 1.1820783 0.6634464 1.1278021
[4,] 1.343552 0.9324204 1.1814767 1.2459041
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 227.74919 35.27780 31.60337 29.10427
[2,] 39.09837 36.51088 34.49388 31.49816
[3,] 44.02633 38.21809 32.07463 37.54996
[4,] 40.24065 35.19361 38.21065 39.01132
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001fd0000>
> exp(tmp5)
<pointer: 0x600001fd0000>
> log(tmp5,2)
<pointer: 0x600001fd0000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 474.0301
> Min(tmp5)
[1] 54.04742
> mean(tmp5)
[1] 73.42479
> Sum(tmp5)
[1] 14684.96
> Var(tmp5)
[1] 876.9467
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.08223 71.30145 75.26987 73.11846 71.25319 72.24536 69.20678 70.35663
[9] 71.58132 70.83264
> rowSums(tmp5)
[1] 1781.645 1426.029 1505.397 1462.369 1425.064 1444.907 1384.136 1407.133
[9] 1431.626 1416.653
> rowVars(tmp5)
[1] 8250.55734 55.57080 86.67310 40.95841 107.12194 54.89981
[7] 85.92603 30.15107 102.46490 58.33770
> rowSd(tmp5)
[1] 90.832579 7.454583 9.309839 6.399876 10.349973 7.409441 9.269630
[8] 5.490999 10.122495 7.637912
> rowMax(tmp5)
[1] 474.03010 84.34902 91.63503 83.75565 91.33054 83.50956 88.57809
[8] 81.04857 98.65106 85.04577
> rowMin(tmp5)
[1] 55.98168 57.38890 57.95005 61.64717 54.04742 55.59316 56.16773 61.92887
[9] 55.17250 56.17149
>
> colMeans(tmp5)
[1] 113.12066 74.09479 67.09090 70.94776 68.77168 74.21566 71.16047
[8] 72.22035 71.08807 73.50449 69.93593 72.26189 76.68747 69.62512
[15] 68.00839 69.05175 66.67569 71.93188 71.97379 76.12915
> colSums(tmp5)
[1] 1131.2066 740.9479 670.9090 709.4776 687.7168 742.1566 711.6047
[8] 722.2035 710.8807 735.0449 699.3593 722.6189 766.8747 696.2512
[15] 680.0839 690.5175 666.7569 719.3188 719.7379 761.2915
> colVars(tmp5)
[1] 16192.82616 38.74357 41.83067 71.92232 78.21654 84.43683
[7] 101.27466 48.33099 69.72983 120.96996 88.36827 61.31850
[13] 52.77967 41.74564 51.05245 40.75049 50.15336 52.44378
[19] 42.06755 60.13647
> colSd(tmp5)
[1] 127.251036 6.224433 6.467663 8.480703 8.844011 9.188952
[7] 10.063531 6.952049 8.350439 10.998635 9.400440 7.830613
[13] 7.264962 6.461087 7.145099 6.383611 7.081904 7.241808
[19] 6.485951 7.754771
> colMax(tmp5)
[1] 474.03010 83.12096 79.53047 83.50956 81.16733 91.33054 85.85435
[8] 85.04577 87.15204 98.65106 88.57809 80.80785 87.32157 78.13162
[15] 81.53822 78.01536 79.62973 85.68407 83.50858 89.51974
> colMin(tmp5)
[1] 54.04742 63.50208 55.59316 59.45391 55.98168 60.32973 55.17250 61.06308
[9] 60.55897 58.40067 56.41309 56.64997 66.87863 59.73604 56.17149 57.38890
[17] 56.16773 63.44559 63.23907 64.00464
>
>
> ### 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] 89.08223 71.30145 75.26987 73.11846 71.25319 72.24536 69.20678 70.35663
[9] 71.58132 NA
> rowSums(tmp5)
[1] 1781.645 1426.029 1505.397 1462.369 1425.064 1444.907 1384.136 1407.133
[9] 1431.626 NA
> rowVars(tmp5)
[1] 8250.55734 55.57080 86.67310 40.95841 107.12194 54.89981
[7] 85.92603 30.15107 102.46490 55.33272
> rowSd(tmp5)
[1] 90.832579 7.454583 9.309839 6.399876 10.349973 7.409441 9.269630
[8] 5.490999 10.122495 7.438597
> rowMax(tmp5)
[1] 474.03010 84.34902 91.63503 83.75565 91.33054 83.50956 88.57809
[8] 81.04857 98.65106 NA
> rowMin(tmp5)
[1] 55.98168 57.38890 57.95005 61.64717 54.04742 55.59316 56.16773 61.92887
[9] 55.17250 NA
>
> colMeans(tmp5)
[1] 113.12066 74.09479 67.09090 70.94776 NA 74.21566 71.16047
[8] 72.22035 71.08807 73.50449 69.93593 72.26189 76.68747 69.62512
[15] 68.00839 69.05175 66.67569 71.93188 71.97379 76.12915
> colSums(tmp5)
[1] 1131.2066 740.9479 670.9090 709.4776 NA 742.1566 711.6047
[8] 722.2035 710.8807 735.0449 699.3593 722.6189 766.8747 696.2512
[15] 680.0839 690.5175 666.7569 719.3188 719.7379 761.2915
> colVars(tmp5)
[1] 16192.82616 38.74357 41.83067 71.92232 NA 84.43683
[7] 101.27466 48.33099 69.72983 120.96996 88.36827 61.31850
[13] 52.77967 41.74564 51.05245 40.75049 50.15336 52.44378
[19] 42.06755 60.13647
> colSd(tmp5)
[1] 127.251036 6.224433 6.467663 8.480703 NA 9.188952
[7] 10.063531 6.952049 8.350439 10.998635 9.400440 7.830613
[13] 7.264962 6.461087 7.145099 6.383611 7.081904 7.241808
[19] 6.485951 7.754771
> colMax(tmp5)
[1] 474.03010 83.12096 79.53047 83.50956 NA 91.33054 85.85435
[8] 85.04577 87.15204 98.65106 88.57809 80.80785 87.32157 78.13162
[15] 81.53822 78.01536 79.62973 85.68407 83.50858 89.51974
> colMin(tmp5)
[1] 54.04742 63.50208 55.59316 59.45391 NA 60.32973 55.17250 61.06308
[9] 60.55897 58.40067 56.41309 56.64997 66.87863 59.73604 56.17149 57.38890
[17] 56.16773 63.44559 63.23907 64.00464
>
> Max(tmp5,na.rm=TRUE)
[1] 474.0301
> Min(tmp5,na.rm=TRUE)
[1] 54.04742
> mean(tmp5,na.rm=TRUE)
[1] 73.38589
> Sum(tmp5,na.rm=TRUE)
[1] 14603.79
> Var(tmp5,na.rm=TRUE)
[1] 881.0715
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.08223 71.30145 75.26987 73.11846 71.25319 72.24536 69.20678 70.35663
[9] 71.58132 70.28870
> rowSums(tmp5,na.rm=TRUE)
[1] 1781.645 1426.029 1505.397 1462.369 1425.064 1444.907 1384.136 1407.133
[9] 1431.626 1335.485
> rowVars(tmp5,na.rm=TRUE)
[1] 8250.55734 55.57080 86.67310 40.95841 107.12194 54.89981
[7] 85.92603 30.15107 102.46490 55.33272
> rowSd(tmp5,na.rm=TRUE)
[1] 90.832579 7.454583 9.309839 6.399876 10.349973 7.409441 9.269630
[8] 5.490999 10.122495 7.438597
> rowMax(tmp5,na.rm=TRUE)
[1] 474.03010 84.34902 91.63503 83.75565 91.33054 83.50956 88.57809
[8] 81.04857 98.65106 85.04577
> rowMin(tmp5,na.rm=TRUE)
[1] 55.98168 57.38890 57.95005 61.64717 54.04742 55.59316 56.16773 61.92887
[9] 55.17250 56.17149
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.12066 74.09479 67.09090 70.94776 67.39439 74.21566 71.16047
[8] 72.22035 71.08807 73.50449 69.93593 72.26189 76.68747 69.62512
[15] 68.00839 69.05175 66.67569 71.93188 71.97379 76.12915
> colSums(tmp5,na.rm=TRUE)
[1] 1131.2066 740.9479 670.9090 709.4776 606.5495 742.1566 711.6047
[8] 722.2035 710.8807 735.0449 699.3593 722.6189 766.8747 696.2512
[15] 680.0839 690.5175 666.7569 719.3188 719.7379 761.2915
> colVars(tmp5,na.rm=TRUE)
[1] 16192.82616 38.74357 41.83067 71.92232 66.65303 84.43683
[7] 101.27466 48.33099 69.72983 120.96996 88.36827 61.31850
[13] 52.77967 41.74564 51.05245 40.75049 50.15336 52.44378
[19] 42.06755 60.13647
> colSd(tmp5,na.rm=TRUE)
[1] 127.251036 6.224433 6.467663 8.480703 8.164131 9.188952
[7] 10.063531 6.952049 8.350439 10.998635 9.400440 7.830613
[13] 7.264962 6.461087 7.145099 6.383611 7.081904 7.241808
[19] 6.485951 7.754771
> colMax(tmp5,na.rm=TRUE)
[1] 474.03010 83.12096 79.53047 83.50956 80.87915 91.33054 85.85435
[8] 85.04577 87.15204 98.65106 88.57809 80.80785 87.32157 78.13162
[15] 81.53822 78.01536 79.62973 85.68407 83.50858 89.51974
> colMin(tmp5,na.rm=TRUE)
[1] 54.04742 63.50208 55.59316 59.45391 55.98168 60.32973 55.17250 61.06308
[9] 60.55897 58.40067 56.41309 56.64997 66.87863 59.73604 56.17149 57.38890
[17] 56.16773 63.44559 63.23907 64.00464
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.08223 71.30145 75.26987 73.11846 71.25319 72.24536 69.20678 70.35663
[9] 71.58132 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1781.645 1426.029 1505.397 1462.369 1425.064 1444.907 1384.136 1407.133
[9] 1431.626 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8250.55734 55.57080 86.67310 40.95841 107.12194 54.89981
[7] 85.92603 30.15107 102.46490 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 90.832579 7.454583 9.309839 6.399876 10.349973 7.409441 9.269630
[8] 5.490999 10.122495 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 474.03010 84.34902 91.63503 83.75565 91.33054 83.50956 88.57809
[8] 81.04857 98.65106 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.98168 57.38890 57.95005 61.64717 54.04742 55.59316 56.16773 61.92887
[9] 55.17250 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.47834 73.48158 67.19120 71.74918 NaN 73.78344 72.17663
[8] 70.79531 71.20779 73.20914 70.85530 72.97146 76.81546 69.36193
[15] 69.32360 68.05579 66.09666 72.59513 72.94432 76.76958
> colSums(tmp5,na.rm=TRUE)
[1] 1057.3050 661.3342 604.7208 645.7426 0.0000 664.0509 649.5897
[8] 637.1578 640.8701 658.8823 637.6977 656.7431 691.3391 624.2574
[15] 623.9124 612.5021 594.8700 653.3562 656.4989 690.9262
> colVars(tmp5,na.rm=TRUE)
[1] 18003.29902 39.35625 46.94633 73.68690 NA 92.88977
[7] 102.31743 31.52634 78.28480 135.10988 89.90543 63.31901
[13] 59.19282 46.18460 37.97398 34.68509 52.65074 54.05041
[19] 36.72941 63.03940
> colSd(tmp5,na.rm=TRUE)
[1] 134.176373 6.273456 6.851739 8.584107 NA 9.637934
[7] 10.115208 5.614832 8.847870 11.623677 9.481848 7.957325
[13] 7.693687 6.795925 6.162303 5.889405 7.256083 7.351898
[19] 6.060479 7.939736
> colMax(tmp5,na.rm=TRUE)
[1] 474.03010 83.12096 79.53047 83.50956 -Inf 91.33054 85.85435
[8] 78.90863 87.15204 98.65106 88.57809 80.80785 87.32157 78.13162
[15] 81.53822 74.50753 79.62973 85.68407 83.50858 89.51974
> colMin(tmp5,na.rm=TRUE)
[1] 54.04742 63.50208 55.59316 59.45391 Inf 60.32973 55.17250 61.06308
[9] 60.55897 58.40067 56.41309 56.64997 66.87863 59.73604 58.36152 57.38890
[17] 56.16773 63.44559 63.70344 64.00464
>
>
>
>
> 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] 261.7238 296.6279 202.9181 277.7825 231.6192 176.5728 255.3227 162.5107
[9] 360.9472 195.3565
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 261.7238 296.6279 202.9181 277.7825 231.6192 176.5728 255.3227 162.5107
[9] 360.9472 195.3565
>
>
>
> 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 -8.526513e-14 -5.684342e-14 0.000000e+00
[6] -5.684342e-14 5.684342e-14 1.136868e-13 0.000000e+00 2.842171e-14
[11] 4.263256e-14 1.136868e-13 -2.842171e-14 -1.421085e-13 2.842171e-14
[16] -1.705303e-13 0.000000e+00 0.000000e+00 -2.842171e-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)
+ }
5 9
10 3
8 10
9 10
6 10
6 7
9 3
10 16
10 16
7 16
3 15
1 3
9 20
3 7
6 12
5 10
8 11
5 2
2 10
4 3
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] 2.205301
> Min(tmp)
[1] -2.387896
> mean(tmp)
[1] -0.01184262
> Sum(tmp)
[1] -1.184262
> Var(tmp)
[1] 1.065793
>
> rowMeans(tmp)
[1] -0.01184262
> rowSums(tmp)
[1] -1.184262
> rowVars(tmp)
[1] 1.065793
> rowSd(tmp)
[1] 1.032373
> rowMax(tmp)
[1] 2.205301
> rowMin(tmp)
[1] -2.387896
>
> colMeans(tmp)
[1] -0.44736061 -0.36202963 -1.93754526 0.51102083 -1.82730626 0.40423697
[7] 1.29978733 0.82874838 2.19988186 0.11439028 0.96244366 -0.26399943
[13] 2.05478207 -0.78707787 0.92260069 -0.60877437 0.92274853 0.16237436
[19] -0.90717172 0.34381501 -0.20237133 -1.46399220 0.66707086 0.30402147
[25] 0.42491190 -0.25384505 0.23894932 1.39182515 -0.51681974 -2.29135291
[31] -0.57259471 0.66147999 -0.67076856 -0.42597606 0.48612168 -1.31350719
[37] -1.16242414 2.20530138 -0.75786150 -0.41172061 0.30033577 -0.51158000
[43] -0.02407973 0.15386350 -0.65608290 1.71987621 1.57174219 -0.61831565
[49] -1.14101633 -0.69522641 -2.16394490 1.27032669 0.06949015 1.89268579
[55] -1.32420887 1.13929751 -2.38789606 0.16187243 0.38726280 -1.12398988
[61] -0.18470306 -0.99302959 0.35193908 -0.22303288 0.54106404 -0.19682053
[67] -1.26523178 0.97730428 1.99480691 -1.62561140 1.44152642 -0.05457235
[73] 0.22974014 0.49833248 1.26443879 0.74898803 -1.44248638 -0.82533933
[79] -0.30258738 -0.30438967 -0.24078749 -1.91900966 -1.69557705 0.01730988
[85] -0.57074040 -0.25188539 0.18537880 0.55137505 -0.04958416 -0.76308464
[91] 0.60704880 0.20772160 -0.34633991 0.09961279 1.54814205 1.54036165
[97] 0.38304988 -0.18747343 0.72082785 0.40663092
> colSums(tmp)
[1] -0.44736061 -0.36202963 -1.93754526 0.51102083 -1.82730626 0.40423697
[7] 1.29978733 0.82874838 2.19988186 0.11439028 0.96244366 -0.26399943
[13] 2.05478207 -0.78707787 0.92260069 -0.60877437 0.92274853 0.16237436
[19] -0.90717172 0.34381501 -0.20237133 -1.46399220 0.66707086 0.30402147
[25] 0.42491190 -0.25384505 0.23894932 1.39182515 -0.51681974 -2.29135291
[31] -0.57259471 0.66147999 -0.67076856 -0.42597606 0.48612168 -1.31350719
[37] -1.16242414 2.20530138 -0.75786150 -0.41172061 0.30033577 -0.51158000
[43] -0.02407973 0.15386350 -0.65608290 1.71987621 1.57174219 -0.61831565
[49] -1.14101633 -0.69522641 -2.16394490 1.27032669 0.06949015 1.89268579
[55] -1.32420887 1.13929751 -2.38789606 0.16187243 0.38726280 -1.12398988
[61] -0.18470306 -0.99302959 0.35193908 -0.22303288 0.54106404 -0.19682053
[67] -1.26523178 0.97730428 1.99480691 -1.62561140 1.44152642 -0.05457235
[73] 0.22974014 0.49833248 1.26443879 0.74898803 -1.44248638 -0.82533933
[79] -0.30258738 -0.30438967 -0.24078749 -1.91900966 -1.69557705 0.01730988
[85] -0.57074040 -0.25188539 0.18537880 0.55137505 -0.04958416 -0.76308464
[91] 0.60704880 0.20772160 -0.34633991 0.09961279 1.54814205 1.54036165
[97] 0.38304988 -0.18747343 0.72082785 0.40663092
> 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] -0.44736061 -0.36202963 -1.93754526 0.51102083 -1.82730626 0.40423697
[7] 1.29978733 0.82874838 2.19988186 0.11439028 0.96244366 -0.26399943
[13] 2.05478207 -0.78707787 0.92260069 -0.60877437 0.92274853 0.16237436
[19] -0.90717172 0.34381501 -0.20237133 -1.46399220 0.66707086 0.30402147
[25] 0.42491190 -0.25384505 0.23894932 1.39182515 -0.51681974 -2.29135291
[31] -0.57259471 0.66147999 -0.67076856 -0.42597606 0.48612168 -1.31350719
[37] -1.16242414 2.20530138 -0.75786150 -0.41172061 0.30033577 -0.51158000
[43] -0.02407973 0.15386350 -0.65608290 1.71987621 1.57174219 -0.61831565
[49] -1.14101633 -0.69522641 -2.16394490 1.27032669 0.06949015 1.89268579
[55] -1.32420887 1.13929751 -2.38789606 0.16187243 0.38726280 -1.12398988
[61] -0.18470306 -0.99302959 0.35193908 -0.22303288 0.54106404 -0.19682053
[67] -1.26523178 0.97730428 1.99480691 -1.62561140 1.44152642 -0.05457235
[73] 0.22974014 0.49833248 1.26443879 0.74898803 -1.44248638 -0.82533933
[79] -0.30258738 -0.30438967 -0.24078749 -1.91900966 -1.69557705 0.01730988
[85] -0.57074040 -0.25188539 0.18537880 0.55137505 -0.04958416 -0.76308464
[91] 0.60704880 0.20772160 -0.34633991 0.09961279 1.54814205 1.54036165
[97] 0.38304988 -0.18747343 0.72082785 0.40663092
> colMin(tmp)
[1] -0.44736061 -0.36202963 -1.93754526 0.51102083 -1.82730626 0.40423697
[7] 1.29978733 0.82874838 2.19988186 0.11439028 0.96244366 -0.26399943
[13] 2.05478207 -0.78707787 0.92260069 -0.60877437 0.92274853 0.16237436
[19] -0.90717172 0.34381501 -0.20237133 -1.46399220 0.66707086 0.30402147
[25] 0.42491190 -0.25384505 0.23894932 1.39182515 -0.51681974 -2.29135291
[31] -0.57259471 0.66147999 -0.67076856 -0.42597606 0.48612168 -1.31350719
[37] -1.16242414 2.20530138 -0.75786150 -0.41172061 0.30033577 -0.51158000
[43] -0.02407973 0.15386350 -0.65608290 1.71987621 1.57174219 -0.61831565
[49] -1.14101633 -0.69522641 -2.16394490 1.27032669 0.06949015 1.89268579
[55] -1.32420887 1.13929751 -2.38789606 0.16187243 0.38726280 -1.12398988
[61] -0.18470306 -0.99302959 0.35193908 -0.22303288 0.54106404 -0.19682053
[67] -1.26523178 0.97730428 1.99480691 -1.62561140 1.44152642 -0.05457235
[73] 0.22974014 0.49833248 1.26443879 0.74898803 -1.44248638 -0.82533933
[79] -0.30258738 -0.30438967 -0.24078749 -1.91900966 -1.69557705 0.01730988
[85] -0.57074040 -0.25188539 0.18537880 0.55137505 -0.04958416 -0.76308464
[91] 0.60704880 0.20772160 -0.34633991 0.09961279 1.54814205 1.54036165
[97] 0.38304988 -0.18747343 0.72082785 0.40663092
> colMedians(tmp)
[1] -0.44736061 -0.36202963 -1.93754526 0.51102083 -1.82730626 0.40423697
[7] 1.29978733 0.82874838 2.19988186 0.11439028 0.96244366 -0.26399943
[13] 2.05478207 -0.78707787 0.92260069 -0.60877437 0.92274853 0.16237436
[19] -0.90717172 0.34381501 -0.20237133 -1.46399220 0.66707086 0.30402147
[25] 0.42491190 -0.25384505 0.23894932 1.39182515 -0.51681974 -2.29135291
[31] -0.57259471 0.66147999 -0.67076856 -0.42597606 0.48612168 -1.31350719
[37] -1.16242414 2.20530138 -0.75786150 -0.41172061 0.30033577 -0.51158000
[43] -0.02407973 0.15386350 -0.65608290 1.71987621 1.57174219 -0.61831565
[49] -1.14101633 -0.69522641 -2.16394490 1.27032669 0.06949015 1.89268579
[55] -1.32420887 1.13929751 -2.38789606 0.16187243 0.38726280 -1.12398988
[61] -0.18470306 -0.99302959 0.35193908 -0.22303288 0.54106404 -0.19682053
[67] -1.26523178 0.97730428 1.99480691 -1.62561140 1.44152642 -0.05457235
[73] 0.22974014 0.49833248 1.26443879 0.74898803 -1.44248638 -0.82533933
[79] -0.30258738 -0.30438967 -0.24078749 -1.91900966 -1.69557705 0.01730988
[85] -0.57074040 -0.25188539 0.18537880 0.55137505 -0.04958416 -0.76308464
[91] 0.60704880 0.20772160 -0.34633991 0.09961279 1.54814205 1.54036165
[97] 0.38304988 -0.18747343 0.72082785 0.40663092
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.4473606 -0.3620296 -1.937545 0.5110208 -1.827306 0.404237 1.299787
[2,] -0.4473606 -0.3620296 -1.937545 0.5110208 -1.827306 0.404237 1.299787
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.8287484 2.199882 0.1143903 0.9624437 -0.2639994 2.054782 -0.7870779
[2,] 0.8287484 2.199882 0.1143903 0.9624437 -0.2639994 2.054782 -0.7870779
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.9226007 -0.6087744 0.9227485 0.1623744 -0.9071717 0.343815 -0.2023713
[2,] 0.9226007 -0.6087744 0.9227485 0.1623744 -0.9071717 0.343815 -0.2023713
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.463992 0.6670709 0.3040215 0.4249119 -0.2538451 0.2389493 1.391825
[2,] -1.463992 0.6670709 0.3040215 0.4249119 -0.2538451 0.2389493 1.391825
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5168197 -2.291353 -0.5725947 0.66148 -0.6707686 -0.4259761 0.4861217
[2,] -0.5168197 -2.291353 -0.5725947 0.66148 -0.6707686 -0.4259761 0.4861217
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.313507 -1.162424 2.205301 -0.7578615 -0.4117206 0.3003358 -0.51158
[2,] -1.313507 -1.162424 2.205301 -0.7578615 -0.4117206 0.3003358 -0.51158
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.02407973 0.1538635 -0.6560829 1.719876 1.571742 -0.6183156 -1.141016
[2,] -0.02407973 0.1538635 -0.6560829 1.719876 1.571742 -0.6183156 -1.141016
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.6952264 -2.163945 1.270327 0.06949015 1.892686 -1.324209 1.139298
[2,] -0.6952264 -2.163945 1.270327 0.06949015 1.892686 -1.324209 1.139298
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -2.387896 0.1618724 0.3872628 -1.12399 -0.1847031 -0.9930296 0.3519391
[2,] -2.387896 0.1618724 0.3872628 -1.12399 -0.1847031 -0.9930296 0.3519391
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.2230329 0.541064 -0.1968205 -1.265232 0.9773043 1.994807 -1.625611
[2,] -0.2230329 0.541064 -0.1968205 -1.265232 0.9773043 1.994807 -1.625611
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.441526 -0.05457235 0.2297401 0.4983325 1.264439 0.748988 -1.442486
[2,] 1.441526 -0.05457235 0.2297401 0.4983325 1.264439 0.748988 -1.442486
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.8253393 -0.3025874 -0.3043897 -0.2407875 -1.91901 -1.695577 0.01730988
[2,] -0.8253393 -0.3025874 -0.3043897 -0.2407875 -1.91901 -1.695577 0.01730988
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.5707404 -0.2518854 0.1853788 0.551375 -0.04958416 -0.7630846 0.6070488
[2,] -0.5707404 -0.2518854 0.1853788 0.551375 -0.04958416 -0.7630846 0.6070488
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.2077216 -0.3463399 0.09961279 1.548142 1.540362 0.3830499 -0.1874734
[2,] 0.2077216 -0.3463399 0.09961279 1.548142 1.540362 0.3830499 -0.1874734
[,99] [,100]
[1,] 0.7208278 0.4066309
[2,] 0.7208278 0.4066309
>
>
> Max(tmp2)
[1] 2.726676
> Min(tmp2)
[1] -2.29695
> mean(tmp2)
[1] 0.1335485
> Sum(tmp2)
[1] 13.35485
> Var(tmp2)
[1] 0.9610121
>
> rowMeans(tmp2)
[1] 0.868604369 -0.753526444 2.482805305 -0.570475854 1.681527627
[6] 1.101459011 -0.737222396 -0.850835531 -0.662755139 0.309096041
[11] 2.202230015 -0.305938991 -0.136551818 0.352054801 0.038045354
[16] -0.169576861 0.022442315 -0.225584472 0.639459975 -0.790396751
[21] 0.003271146 1.226091112 -1.802785801 -1.392667912 0.887460937
[26] -0.012114106 0.775850006 1.453780582 0.254402283 -0.117150686
[31] -0.619672187 0.303184927 0.058639017 -2.296950033 0.858627779
[36] 0.479363886 0.871235044 -1.808695869 0.116251749 -0.348769705
[41] 0.372578048 -1.007738091 0.852298114 -1.019501599 -0.520993777
[46] -0.726062449 0.175148818 0.566912338 -0.338438625 1.374459309
[51] 1.740107364 1.896227995 0.700792713 0.529894901 0.641970725
[56] -0.704998829 -0.436177274 -0.061901979 0.094135652 -0.270733405
[61] 0.242020338 -0.817836029 1.669283697 0.612127677 0.357241320
[66] 0.709050817 0.201159850 0.216553462 -1.034445461 -0.016233238
[71] -0.153544480 -0.202382250 0.199780769 -1.304734840 0.680680742
[76] 1.382425991 0.554746062 -0.882408863 1.581964836 -0.100028481
[81] -0.867477198 -1.371738158 -1.908312173 -0.441963901 -0.195989300
[86] 2.377533293 0.868226001 1.137377985 0.373628697 0.558360221
[91] 0.515941005 -0.060740789 -1.359712085 0.338273779 2.726676067
[96] -1.454172497 0.170758407 -0.094512916 -0.218828031 1.123906290
> rowSums(tmp2)
[1] 0.868604369 -0.753526444 2.482805305 -0.570475854 1.681527627
[6] 1.101459011 -0.737222396 -0.850835531 -0.662755139 0.309096041
[11] 2.202230015 -0.305938991 -0.136551818 0.352054801 0.038045354
[16] -0.169576861 0.022442315 -0.225584472 0.639459975 -0.790396751
[21] 0.003271146 1.226091112 -1.802785801 -1.392667912 0.887460937
[26] -0.012114106 0.775850006 1.453780582 0.254402283 -0.117150686
[31] -0.619672187 0.303184927 0.058639017 -2.296950033 0.858627779
[36] 0.479363886 0.871235044 -1.808695869 0.116251749 -0.348769705
[41] 0.372578048 -1.007738091 0.852298114 -1.019501599 -0.520993777
[46] -0.726062449 0.175148818 0.566912338 -0.338438625 1.374459309
[51] 1.740107364 1.896227995 0.700792713 0.529894901 0.641970725
[56] -0.704998829 -0.436177274 -0.061901979 0.094135652 -0.270733405
[61] 0.242020338 -0.817836029 1.669283697 0.612127677 0.357241320
[66] 0.709050817 0.201159850 0.216553462 -1.034445461 -0.016233238
[71] -0.153544480 -0.202382250 0.199780769 -1.304734840 0.680680742
[76] 1.382425991 0.554746062 -0.882408863 1.581964836 -0.100028481
[81] -0.867477198 -1.371738158 -1.908312173 -0.441963901 -0.195989300
[86] 2.377533293 0.868226001 1.137377985 0.373628697 0.558360221
[91] 0.515941005 -0.060740789 -1.359712085 0.338273779 2.726676067
[96] -1.454172497 0.170758407 -0.094512916 -0.218828031 1.123906290
> 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] 0.868604369 -0.753526444 2.482805305 -0.570475854 1.681527627
[6] 1.101459011 -0.737222396 -0.850835531 -0.662755139 0.309096041
[11] 2.202230015 -0.305938991 -0.136551818 0.352054801 0.038045354
[16] -0.169576861 0.022442315 -0.225584472 0.639459975 -0.790396751
[21] 0.003271146 1.226091112 -1.802785801 -1.392667912 0.887460937
[26] -0.012114106 0.775850006 1.453780582 0.254402283 -0.117150686
[31] -0.619672187 0.303184927 0.058639017 -2.296950033 0.858627779
[36] 0.479363886 0.871235044 -1.808695869 0.116251749 -0.348769705
[41] 0.372578048 -1.007738091 0.852298114 -1.019501599 -0.520993777
[46] -0.726062449 0.175148818 0.566912338 -0.338438625 1.374459309
[51] 1.740107364 1.896227995 0.700792713 0.529894901 0.641970725
[56] -0.704998829 -0.436177274 -0.061901979 0.094135652 -0.270733405
[61] 0.242020338 -0.817836029 1.669283697 0.612127677 0.357241320
[66] 0.709050817 0.201159850 0.216553462 -1.034445461 -0.016233238
[71] -0.153544480 -0.202382250 0.199780769 -1.304734840 0.680680742
[76] 1.382425991 0.554746062 -0.882408863 1.581964836 -0.100028481
[81] -0.867477198 -1.371738158 -1.908312173 -0.441963901 -0.195989300
[86] 2.377533293 0.868226001 1.137377985 0.373628697 0.558360221
[91] 0.515941005 -0.060740789 -1.359712085 0.338273779 2.726676067
[96] -1.454172497 0.170758407 -0.094512916 -0.218828031 1.123906290
> rowMin(tmp2)
[1] 0.868604369 -0.753526444 2.482805305 -0.570475854 1.681527627
[6] 1.101459011 -0.737222396 -0.850835531 -0.662755139 0.309096041
[11] 2.202230015 -0.305938991 -0.136551818 0.352054801 0.038045354
[16] -0.169576861 0.022442315 -0.225584472 0.639459975 -0.790396751
[21] 0.003271146 1.226091112 -1.802785801 -1.392667912 0.887460937
[26] -0.012114106 0.775850006 1.453780582 0.254402283 -0.117150686
[31] -0.619672187 0.303184927 0.058639017 -2.296950033 0.858627779
[36] 0.479363886 0.871235044 -1.808695869 0.116251749 -0.348769705
[41] 0.372578048 -1.007738091 0.852298114 -1.019501599 -0.520993777
[46] -0.726062449 0.175148818 0.566912338 -0.338438625 1.374459309
[51] 1.740107364 1.896227995 0.700792713 0.529894901 0.641970725
[56] -0.704998829 -0.436177274 -0.061901979 0.094135652 -0.270733405
[61] 0.242020338 -0.817836029 1.669283697 0.612127677 0.357241320
[66] 0.709050817 0.201159850 0.216553462 -1.034445461 -0.016233238
[71] -0.153544480 -0.202382250 0.199780769 -1.304734840 0.680680742
[76] 1.382425991 0.554746062 -0.882408863 1.581964836 -0.100028481
[81] -0.867477198 -1.371738158 -1.908312173 -0.441963901 -0.195989300
[86] 2.377533293 0.868226001 1.137377985 0.373628697 0.558360221
[91] 0.515941005 -0.060740789 -1.359712085 0.338273779 2.726676067
[96] -1.454172497 0.170758407 -0.094512916 -0.218828031 1.123906290
>
> colMeans(tmp2)
[1] 0.1335485
> colSums(tmp2)
[1] 13.35485
> colVars(tmp2)
[1] 0.9610121
> colSd(tmp2)
[1] 0.9803123
> colMax(tmp2)
[1] 2.726676
> colMin(tmp2)
[1] -2.29695
> colMedians(tmp2)
[1] 0.1051937
> colRanges(tmp2)
[,1]
[1,] -2.296950
[2,] 2.726676
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.130615 -1.847405 -6.710656 1.459619 -3.409355 2.879315 1.622081
[8] 2.891193 -1.607729 1.758229
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3683224
[2,] -1.1231687
[3,] -0.8558608
[4,] 0.7566624
[5,] 0.9850261
>
> rowApply(tmp,sum)
[1] -0.49344762 -0.52112991 -2.97223465 0.95937046 -3.25552823 0.15975751
[7] 3.41256060 -1.63904860 -1.67578802 -0.06983517
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 8 3 1 2 8 8 3 9 2
[2,] 6 7 6 2 9 7 2 1 10 4
[3,] 8 4 1 7 6 2 6 5 5 1
[4,] 7 1 9 6 10 4 9 2 3 8
[5,] 4 2 8 3 5 1 5 7 7 6
[6,] 3 3 2 9 3 10 10 10 4 9
[7,] 10 6 10 5 8 6 4 4 1 5
[8,] 5 10 5 10 1 5 7 8 2 10
[9,] 2 5 4 8 4 9 3 6 6 3
[10,] 9 9 7 4 7 3 1 9 8 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.1518536 -4.2309076 0.6360507 1.9117646 1.7697713 -0.7060464
[7] -2.1692721 1.9524471 -2.8762303 2.2099675 -6.7561248 -1.7901737
[13] -0.4207637 -2.1577624 -1.6179735 0.2363188 -0.2457271 -0.5324217
[19] -2.1511153 2.5463592
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.60286330
[2,] -0.36339938
[3,] -0.22222728
[4,] 0.04267923
[5,] 0.99395709
>
> rowApply(tmp,sum)
[1] -4.680376 -1.232550 3.711272 -6.644726 -6.697313
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 10 16 12 10
[2,] 9 3 12 3 3
[3,] 7 20 9 19 5
[4,] 8 17 3 18 19
[5,] 18 16 14 1 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.60286330 -0.2986688 -0.9031075 -0.5478387 1.1738014 0.7926279
[2,] -0.36339938 -0.9632387 1.9478948 0.8014165 0.7383185 -0.7146107
[3,] 0.99395709 0.3443546 -0.2987687 -0.7365998 0.6322105 0.5788073
[4,] 0.04267923 -1.6212478 0.9704413 0.8748247 -2.3670741 -1.1707690
[5,] -0.22222728 -1.6921069 -1.0804092 1.5199619 1.5925149 -0.1921019
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.7548654 1.5472360 0.2059083 1.02071540 -2.4194695 -1.42442572
[2,] -0.8517484 -0.2720182 -1.9278782 0.27996259 -0.6053869 -0.41849859
[3,] 1.3302694 1.1253323 1.1675652 0.69553664 -0.7166227 -0.73464799
[4,] -0.1599902 -1.5310632 0.3550050 0.04303697 -1.0789967 0.75743767
[5,] -0.7329375 1.0829603 -2.6768307 0.17071586 -1.9356489 0.02996089
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.29652171 -0.1692721 0.62752680 -1.7405442 -0.1032296 -0.21554035
[2,] 0.14294503 0.2798048 -1.25224858 0.1938744 -0.7464631 -0.44273824
[3,] -0.01391168 -0.6110754 -0.83630316 2.1579013 -0.8324689 -0.38059007
[4,] -0.94441790 -2.0179811 -0.19380601 -0.1048678 1.0138324 0.47823200
[5,] -0.90190087 0.3607614 0.03685744 -0.2700448 0.4226020 0.02821497
[,19] [,20]
[1,] -1.0422282 0.8773396
[2,] 1.0453402 1.8961220
[3,] -0.3564250 0.2027513
[4,] -0.4578656 0.4678642
[5,] -1.3399367 -0.8977178
>
>
> 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 : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 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 -0.5006415 -1.275314 -1.178707 -0.898434 -0.7668486 0.4213044 0.1759897
col8 col9 col10 col11 col12 col13 col14
row1 0.1959649 0.7236232 -1.869558 0.920384 -0.3534674 0.07011874 0.2588955
col15 col16 col17 col18 col19 col20
row1 -0.3839377 -0.07855878 0.0485534 2.452264 -0.5588484 -0.3492191
> tmp[,"col10"]
col10
row1 -1.8695584
row2 -0.4396453
row3 0.3264511
row4 -1.2353666
row5 -1.0219870
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.5006415 -1.2753139 -1.1787068 -0.8984340 -0.76684855 0.4213044
row5 -1.8372409 0.1944009 -0.4079322 0.9397762 0.09203771 0.1172950
col7 col8 col9 col10 col11 col12 col13
row1 0.1759897 0.1959649 0.7236232 -1.869558 0.920384 -0.3534674 0.07011874
row5 -0.4737267 0.6776865 -0.4374124 -1.021987 -1.436359 -0.2217890 0.02761409
col14 col15 col16 col17 col18 col19
row1 0.2588955 -0.3839377 -0.07855878 0.0485534 2.4522637 -0.55884836
row5 0.7373769 -0.6037326 0.57134655 0.5618586 0.4093374 -0.02968521
col20
row1 -0.3492191
row5 0.9681849
> tmp[,c("col6","col20")]
col6 col20
row1 0.421304356 -0.3492191
row2 0.678535705 -1.3456891
row3 0.008846388 -1.0147014
row4 1.398468624 0.7648067
row5 0.117294960 0.9681849
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.4213044 -0.3492191
row5 0.1172950 0.9681849
>
>
>
>
> 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 50.02199 48.66039 49.73687 49.46489 50.08045 104.5451 51.60957 50.89988
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.41184 47.68691 50.82498 49.11788 47.74285 49.10281 49.29091 50.01814
col17 col18 col19 col20
row1 49.13877 50.08346 50.43115 104.168
> tmp[,"col10"]
col10
row1 47.68691
row2 30.35016
row3 28.57417
row4 31.41664
row5 49.43567
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.02199 48.66039 49.73687 49.46489 50.08045 104.5451 51.60957 50.89988
row5 49.52015 49.97049 49.30930 51.08936 49.09871 105.5811 48.05501 50.68337
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.41184 47.68691 50.82498 49.11788 47.74285 49.10281 49.29091 50.01814
row5 49.55311 49.43567 50.94180 50.32211 51.30427 50.83116 47.98230 51.26302
col17 col18 col19 col20
row1 49.13877 50.08346 50.43115 104.1680
row5 49.99855 49.89466 48.55313 105.1342
> tmp[,c("col6","col20")]
col6 col20
row1 104.54512 104.16796
row2 74.20432 74.22783
row3 75.59919 75.28516
row4 75.02725 76.47661
row5 105.58109 105.13418
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5451 104.1680
row5 105.5811 105.1342
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5451 104.1680
row5 105.5811 105.1342
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.56831247
[2,] 0.09073074
[3,] -1.25709927
[4,] -2.06611892
[5,] -0.45739953
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.7717898 -0.55168759
[2,] 0.8817111 0.58572029
[3,] 0.4613036 0.04918616
[4,] -0.1408815 -0.32550829
[5,] -1.7306157 -0.26275512
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.2464130 -0.53711526
[2,] -1.0717511 1.37524005
[3,] 0.6102406 -1.62753577
[4,] 0.2261491 -0.55057131
[5,] 1.8525613 -0.06431903
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.246413
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.246413
[2,] -1.071751
>
>
>
> 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 1.243594 -1.798022 0.6061621 1.2237087 0.2329499 0.3453166 0.3286417
row1 1.256976 -1.754331 -0.7542523 0.3786418 0.3611317 0.1696037 -0.1985172
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.8554968 -0.6433227 -0.4310445 -1.122713 -0.6775739 -0.0275747 0.1083794
row1 -0.5047265 -1.5521875 1.2649564 -0.897316 0.5545534 -0.9662883 2.1986920
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.6042183 -0.3051486 0.1156994 0.6796290 0.5822818 -1.05535
row1 -0.4414307 0.4439090 -1.1226183 0.5665985 1.3771416 1.06158
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 2.750136 0.797649 -0.6274046 -0.1540158 -0.7590882 -1.564243 -2.044089
[,8] [,9] [,10]
row2 0.639817 -1.188298 -0.08776396
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.387697 -0.07537439 1.247905 0.6153041 0.01870162 0.3175158 0.4378458
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6420423 -0.3495439 0.2004805 -0.7337613 0.02977619 -0.3907524 -0.8752077
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.3358156 -0.6831476 2.258439 -0.879683 0.2820366 -0.5608678
>
>
> 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: 0x600001fdc0c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa58363452e9c"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa58352f736ae"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5836427040f"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5833d7ba827"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa58315cb7fa"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5836e327ec8"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5833521b4fd"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa58337f1694b"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5834a37d79e"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa583182cec23"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5832d42fa3b"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa58383a4eb4"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5832c050fa4"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa58345ee90"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMa5836f313013"
>
>
> ### 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: 0x600001fd8360>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001fd8360>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001fd8360>
> rowMedians(tmp)
[1] -0.480188497 0.111956397 0.127732996 0.374909385 -0.104387786
[6] -0.079387061 -0.261263847 0.558946179 -0.017055713 -0.279368642
[11] -0.153452682 -0.227280111 0.139569713 -0.128138802 -0.463337525
[16] 0.101849421 -0.135326794 0.030507461 -0.254861564 0.056841730
[21] -0.080290256 0.289200662 -0.163980693 0.284804646 -0.297811422
[26] 0.198817046 0.320621957 0.106999476 0.102692891 -0.369664187
[31] -0.377945331 -0.005380030 0.072664511 0.063880356 0.463947364
[36] -0.405388551 0.072639633 0.027733837 0.071024411 -0.103032016
[41] 0.154466952 0.037167120 0.436436751 -0.584161426 0.073490663
[46] 0.097418507 0.498026064 -0.169274119 0.157681571 0.343666622
[51] 0.333869926 -0.320398864 -0.056223237 0.095130040 0.349071450
[56] -0.021674241 0.099826417 0.070806202 0.066814889 0.041680279
[61] -0.186901294 -0.021837563 0.551020907 0.495956684 0.092287753
[66] 0.031180467 -0.122866671 0.588131998 -0.627995845 0.327207805
[71] 0.134774250 -0.601302579 0.097172783 -0.411696642 -0.245553859
[76] -0.225612180 -0.395417851 -0.090277078 0.472756957 0.089968290
[81] 0.035172610 -0.006452774 -0.145591899 -0.249115866 0.051119756
[86] -0.414648911 -0.324757018 -0.032408294 0.349002993 0.181964660
[91] -0.139100479 -0.106102662 0.593122121 -0.030506960 -0.142817830
[96] -0.202878661 -0.242014619 -0.449917924 -1.011481328 -0.286970632
[101] -0.247484645 -0.157031960 -0.089931314 -0.038887130 -0.169074667
[106] 0.708304883 -0.523130866 -0.079209799 -0.069375186 -0.009771806
[111] 0.073307043 0.169209983 0.138871765 0.215464422 -0.076560059
[116] -0.498367134 0.345364279 -0.242817249 0.090653327 -0.302769614
[121] 0.159406713 -0.264677305 -0.101871896 -0.118703638 0.105899205
[126] -0.059423849 -0.873243166 0.279301235 0.392173884 0.693593027
[131] -0.442643114 0.175682504 0.328279497 0.551410657 0.774245800
[136] 0.326024283 0.180333266 0.194225078 0.074997579 -0.327665787
[141] 0.338078319 -0.107550486 0.461095469 -0.497822478 -0.291336033
[146] 0.353759212 -0.423151485 -0.187830814 0.070136105 0.732914301
[151] 0.001671790 -0.141408059 0.064398566 0.199851635 0.405761566
[156] 0.377901044 -0.308381781 0.105674500 0.114253208 -0.031521267
[161] -0.312945808 -0.316768674 0.824955457 -0.209202616 0.296772405
[166] 0.284730809 -0.057156760 -0.173867253 0.260928837 0.281718345
[171] 0.286171097 -0.042366267 0.184636968 0.165795210 0.212121428
[176] 0.106329280 0.355768274 -0.632806837 0.273831321 0.474843186
[181] 0.204860354 -0.071879233 -0.592962738 0.129821800 -0.088071018
[186] -0.195892133 -0.087080780 0.006088232 -0.015334389 0.018964156
[191] 0.251938043 -0.217583598 0.745432877 -0.109472472 -0.467178182
[196] 0.080312529 -0.535084743 0.105426400 0.222837216 0.222551013
[201] -0.136177008 -0.521773979 -0.354043042 -0.324150726 -0.320818602
[206] 0.078640675 -0.132120389 -0.365932709 -0.611762861 -0.497434448
[211] -0.016371251 -0.538453861 -0.059111844 0.202742513 0.436056866
[216] -0.363299759 0.008653082 -0.389560977 0.040513940 0.337573840
[221] -0.166997305 -0.359026221 -0.382050273 0.228066578 0.347658654
[226] 0.217271189 0.458930319 -0.433910596 -0.261890455 0.343940925
>
> proc.time()
user system elapsed
0.687 3.514 4.509
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: 0x600003854060>
> .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: 0x600003854060>
> .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: 0x600003854060>
> .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: 0x600003854060>
> 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: 0x600003878000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003878000>
> .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: 0x600003878000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003878000>
> .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: 0x600003878000>
> 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: 0x600003854420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003854420>
> .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: 0x600003854420>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003854420>
> .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: 0x600003854420>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003854420>
> .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: 0x600003854420>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003854420>
> .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: 0x600003854420>
> 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: 0x600003874000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003874000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003874000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003874000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileab403c81f057" "BufferedMatrixFileab4076c9fec9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileab403c81f057" "BufferedMatrixFileab4076c9fec9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003874240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003874240>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003874240>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003874240>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003874240>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003874240>
> .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: 0x600003870000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003870000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003870000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003870000>
> 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: 0x600003870180>
> .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: 0x600003870180>
> rm(P)
>
> proc.time()
user system elapsed
0.131 0.068 0.200
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
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Platform: aarch64-apple-darwin20
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Type 'license()' or 'licence()' for distribution details.
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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
0.125 0.033 0.160